posted May 8, 2011 11:08 PM by UCmerced CompBioJournalClub
[
updated May 9, 2011 12:37 AM
]
Howard Hughes Medical Institute, Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine,
Baltimore, Maryland 21205, USA
Published in Advance
March 17, 2011,
doi:
10.1261/rna.2623711
RNA
2011.
17:
925-932
Abstract
Numerous mechanisms have evolved to
control the accuracy of translation, including a recently discovered
retrospective quality
control mechanism in bacteria. This quality control
mechanism is sensitive to perturbations in the codon:anticodon
interaction
in the P site of the ribosome that trigger a
dramatic loss of fidelity in subsequent tRNA and release factor
selection events
in the A site. These events ultimately lead to
premature termination of translation in response to an initial miscoding
error.
In this work, we extend our investigations of this
mechanism to an in vitro reconstituted Saccharomyces cerevisiae translation system. We report that yeast ribosomes do not respond to mismatches in the P site by loss of fidelity in subsequent
substrate recognition events. We conclude that retrospective editing, as initially characterized in Escherichia coli, does not occur in S. cerevisiae. These results highlight potential mechanistic differences in the functional core of highly conserved ribosomes.
 
The EMBO Journal 30, 1497 - 1507 (4 March 2011) | doi:10.1038/emboj.2011.58 Xabier Agirrezabala,
Eduard Schreiner,
Leonardo G Trabuco,
Jianlin Lei,
Rodrigo F Ortiz-Meoz,
Klaus Schulten,
Rachel Green and Joachim Frank
AbstractThe
structural basis of the tRNA selection process is investigated by
cryo-electron microscopy of ribosomes programmed with UGA codons and
incubated with ternary complex (TC) containing the near-cognate Trp-tRNATrp in the presence of kirromycin. Going through more than 350 000 images and employing image classification procedures, we find ~8%
in which the TC is bound to the ribosome. The reconstructed 3D map
provides a means to characterize the arrangement of the near-cognate
aa-tRNA with respect to elongation factor Tu (EF-Tu) and the ribosome,
as well as the domain movements of the ribosome. One of the interesting
findings is that near-cognate tRNA's acceptor stem region is flexible
and CCA end becomes disordered. The data bring direct structural
insights into the induced-fit mechanism of decoding by the ribosome, as
the analysis of the interactions between small and large ribosomal
subunit, aa-tRNA and EF-Tu and comparison with the cognate case (UGG
codon) offers clues on how the conformational signals conveyed to the
GTPase differ in the two cases.
| Volume 472 Number 7343 | | | | nature alert | | The science that matters. Every week. |
| | | | | |
http://www.nature.com/news/specials/phdfuture/index.html?WT.mc_id=TWT_NatureNewshttp://www.nature.com/news/specials/phdfuture/index.html?WT.mc_id=TWT_NatureNews
Published online 20 April 2011 |
Nature
472,
280-282
(2011)
| doi:10.1038/472280a
News Feature
Alison McCook Fix it, overhaul it or skip it completely —
institutions and individuals are taking innovative approaches to
postgraduate science training.
Published online 20 April 2011 |
Nature
472,
276-279
(2011)
| doi:10.1038/472276a
News Feature
David Cyranoski
,
Natasha Gilbert
,
Heidi Ledford
,
Anjali Nayar
&
Mohammed Yahia
The world is producing more PhDs than ever before. Is it time to stop? Reform the PhD system or close it down Published online 20 April 2011 |
Nature
472,
261
(2011)
| doi:10.1038/472261a
There are too many doctoral programmes, producing too many PhDs for the
job market. Shut some and change the rest, says Mark C. Taylor.
Fix the PhD Nature 472, 259–260 (21 April 2011) doi:10.1038/472259b
No longer a guaranteed ticket to an academic career, the PhD system needs a serious rethink.  The EMBO Journal 30, 1497 - 1507 (4 March 2011) | doi:10.1038/emboj.2011.58 Xabier Agirrezabala,
Eduard Schreiner,
Leonardo G Trabuco,
Jianlin Lei,
Rodrigo F Ortiz-Meoz,
Klaus Schulten,
Rachel Green and Joachim Frank The structural basis of the tRNA selection process is investigated by
cryo-electron microscopy of ribosomes programmed with UGA codons and
incubated with ternary complex (TC) containing the near-cognate Trp-tRNATrp in the presence of kirromycin. Going through more than 350 000 images and employing image classification procedures, we find ~8%
in which the TC is bound to the ribosome. The reconstructed 3D map
provides a means to characterize the arrangement of the near-cognate
aa-tRNA with respect to elongation factor Tu (EF-Tu) and the ribosome,
as well as the domain movements of the ribosome. One of the interesting
findings is that near-cognate tRNA's acceptor stem region is flexible
and CCA end becomes disordered. The data bring direct structural
insights into the induced-fit mechanism of decoding by the ribosome, as
the analysis of the interactions between small and large ribosomal
subunit, aa-tRNA and EF-Tu and comparison with the cognate case (UGG
codon) offers clues on how the conformational signals conveyed to the
GTPase differ in the two cases.
Thomas E. Jonesa, Rebecca W. Alexanderb, and Tao Pana,1 aDepartment of Biochemistry and Molecular Biology and Institute of Biophysical Dynamics, University of Chicago, Chicago, IL
60637; and bDepartment of Chemistry, Wake Forest University, Winston-Salem, NC 27109
Edited by Paul Schimmel, The Skaggs Institute for Chemical Biology, La Jolla, CA, and approved March 10, 2011 (received for
review December 20, 2010) Published online before print
April 11, 2011,
doi:
10.1073/pnas.1019033108
PNAS
April 26, 2011
vol. 108
no. 17
6933-6938
Abstract
Aminoacyl-tRNA synthetases perform a
critical step in translation by aminoacylating tRNAs with their cognate
amino acids.
Although high fidelity of aminoacyl-tRNA
synthetases is often thought to be essential for cell biology, recent
studies indicate
that cells tolerate and may even benefit from tRNA
misacylation under certain conditions. For example, mammalian cells
selectively
induce mismethionylation of nonmethionyl tRNAs, and
this type of misacylation contributes to a cell’s response to oxidative
stress. However, the enzyme responsible for tRNA
mismethionylation and the mechanism by which specific tRNAs are
mismethionylated
have not been elucidated. Here we show by tRNA
microarrays and filter retention that the methionyl-tRNA synthetase
enzyme
from Escherichia coli (EcMRS) is sufficient to mismethionylate two tRNA species, and ,
indicating that tRNA mismethionylation is also present in the bacterial
domain of life. We demonstrate that the anticodon
nucleotides of these misacylated tRNAs play a
critical role in conferring mismethionylation identity. We also show
that a
certain low level of mismethionylation is
maintained for these tRNAs, suggesting that mismethionylation levels may
have evolved
to confer benefits to the cell while still
preserving sufficient translational fidelity to ensure cell viability.
EcMRS mutants
show distinct effects on mismethionylation,
indicating that many regions in this synthetase enzyme influence
mismethionylation.
Our results show that tRNA mismethionylation can be
carried out by a single protein enzyme, mismethionylation also requires
identity elements in the tRNA, and EcMRS has a
defined structure-function relationship for tRNA mismethionylation.
aCenter for Bioinformatics and Computational Genomics,
bSchool of Biology, and
gSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332;
cDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI 48109; dResearch School of Biology, The Australian National University, Canberra, ACT 0200, Australia; eThe Broad Institute, Cambridge, MA 02142; and fCenter for Microbial Ecology, Michigan State University, East Lansing, MI 48824 Edited by W. Ford Doolittle, Dalhousie University, Halifax, Canada, and approved March 18, 2011 (received for review October
18, 2010) Published online before print
April 11, 2011,
doi:
10.1073/pnas.1015622108
PNAS
April 26, 2011
vol. 108
no. 17
7200-7205
Abstract
Defining bacterial species remains a challenging problem even for the model bacterium Escherichia coli and has major practical consequences for reliable diagnosis of infectious disease agents and regulations for transport and
possession of organisms of economic importance. E. coli
traditionally is thought to live within the gastrointestinal tract of
humans and other warm-blooded animals and not to survive
for extended periods outside its host; this
understanding is the basis for its widespread use as a fecal
contamination indicator.
Here, we report the genome sequences of nine
environmentally adapted strains that are phenotypically and
taxonomically indistinguishable
from typical E. coli (commensal or
pathogenic). We find, however, that the commensal genomes encode for
more functions that are important for
fitness in the human gut, do not exchange genetic
material with their environmental counterparts, and hence do not evolve
according to the recently proposed fragmented
speciation model. These findings are consistent with a more stringent
and ecologic
definition for bacterial species than the current
definition and provide means to start replacing traditional approaches
of
defining distinctive phenotypes for new species
with omics-based procedures. They also have important implications for
reliable
diagnosis and regulation of pathogenic E. coli and for the coliform cell-counting test.
aDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel; and
bDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158 Edited by Susan Lindquist, Whitehead Institute for Biomedical Research, Cambridge, MA, and approved March 17, 2011 (received
for review January 3, 2011)
Published online before print
April 12, 2011,
doi:
10.1073/pnas.1019754108
PNAS
April 26, 2011
vol. 108
no. 17
7271-7276
Abstract
Survival in natural habitats selects for
microorganisms that are well-adapted to a wide range of conditions.
Recent studies
revealed that cells evolved innovative response
strategies that extend beyond merely sensing a given stimulus and
responding
to it on encounter. A diversity of microorganisms,
including Escherichia coli, Vibrio cholerae, and
several yeast species, were shown to use a predictive regulation
strategy that uses the appearance of one stimulus as
a cue for the likely arrival of a subsequent one. A
better understanding of such a predictive strategy requires elucidating
the interplay between key biological and
environmental forces. Here, we describe a mathematical framework to
address this
challenge. We base this framework on experimental
systems featuring early preparation to either a stress or an exposure to
improvement in the growth medium. Our model
calculates the fitness advantage originating under each regulation
strategy in
a given habitat. We conclude that, although a
predictive response strategy might by advantageous under some ecologies,
its
costs might exceed the benefit in others. The
combined theoretical–experimental treatment presented here helps assess
the
potential of natural ecologies to support a
predictive behavior.
  |  |
Nature Genetics 43 , 476–481 (2011) doi:10.1038/ng.807
- Received 13 September 2010
- Accepted 18 March 2011
- Published online 10 April 2011
-
Tina T Hu, Pedro Pattyn, Erica G Bakker, Jun Cao, Jan-Fang Cheng, Richard M Clark, Noah Fahlgren, Jeffrey A Fawcett, Jane Grimwood, Heidrun Gundlach, Georg Haberer, Jesse D Hollister, Stephan Ossowski, Robert P Ottilar, Asaf A Salamov, Korbinian Schneeberger, Manuel Spannagl, Xi Wang, Liang Yang, Mikhail E Nasrallah, Joy Bergelson, James C Carrington, Brandon S Gaut, Jeremy Schmutz, Klaus F X Mayer,Yves Van de Peer,
-
Igor V Grigoriev,
-
Magnus Nordborg,
-
Detlef Weigel
-
& Ya-Long Guo
We report the 207-Mb genome sequence of the North American Arabidopsis lyrata
strain MN47 based on 8.3× dideoxy sequence coverage. We predict 32,670
genes in this outcrossing species compared to the 27,025 genes in the
selfing species Arabidopsis thaliana. The much smaller 125-Mb genome of A. thaliana, which diverged from A. lyrata
10 million years ago, likely constitutes the derived state for the
family. We found evidence for DNA loss from large-scale rearrangements,
but most of the difference in genome size can be attributed to hundreds
of thousands of small deletions, mostly in noncoding DNA and
transposons. Analysis of deletions and insertions still segregating in A. thaliana
indicates that the process of DNA loss is ongoing, suggesting pervasive
selection for a smaller genome. The high-quality reference genome
sequence for A. lyrata will be an important resource for functional, evolutionary and ecological studies in the genus Arabidopsis.
- Nature Genetics 43, 389 (2011) doi:10.1038/ng.827
- Published online
- 27 April 2011
More data than we can handle is no excuse to
give up our efforts to promote data access, but it may make us think
about new ways to make it sustainable.
Nicolas Mirouze1, Peter Prepiak1, David Dubnau1,2* 1 Public Health Research Center, New Jersey Medical School, Newark, New Jersey, United States of America, 2 Department of Microbiology and Molecular Genetics, New Jersey Medical School, Newark, New Jersey, United States of America Citation: Mirouze N, Prepiak P, Dubnau D (2011) Fluctuations in spo0A Transcription Control Rare Developmental Transitions in Bacillus subtilis. PLoS Genet 7(4):
e1002048.
doi:10.1371/journal.pgen.1002048 Abstract TopPhosphorylated Spo0A is a master regulator of stationary phase development in the model bacterium Bacillus subtilis,
controlling the formation of spores, biofilms, and cells competent for
transformation. We have monitored the rate of transcription of the spo0A
gene during growth in sporulation medium using promoter fusions to
firefly luciferase. This rate increases sharply during transient
diauxie-like pauses in growth rate and then declines as growth resumes.
In contrast, the rate of transcription of an rRNA gene decreases and
increases in parallel with the growth rate, as expected for stable RNA
synthesis. The growth pause-dependent bursts of spo0A transcription, which reflect the activity of the spo0A vegetative promoter, are largely independent of all known regulators of spo0A transcription. Evidence is offered in support of a “passive regulation” model in which RNA polymerase stops transcribing rRNA genes during growth pauses, thus becoming available for the transcription of spo0A.
We show that the bursts are followed by the production of
phosphorylated Spo0A, and we propose that they represent initial
responses to stress that bring the average cell closer to the thresholds
for transition to bimodally expressed developmental responses.
Measurement of the numbers of cells expressing a competence marker
before and after the bursts supports this hypothesis. In the absence of
ppGpp, the increase in spo0A transcription that accompanies the
entrance to stationary phase is delayed and sporulation is markedly
diminished. In spite of this, our data contradicts the hypothesis that
sporulation is initiated when a ppGpp-induced depression of the GTP pool
relieves repression by CodY. We suggest that, while the programmed
induction of sporulation that occurs in stationary phase is apparently
provoked by increased flux through the phosphorelay, bet-hedging
stochastic transitions to at least competence are induced by bursts in
transcription. |
posted Apr 15, 2011 1:53 PM by UCmerced CompBioJournalClub
[
updated Apr 22, 2011 8:41 PM
]
 | 5 April 2011; Vol. 108, No. 14
|
Statistical image analysis reveals features affecting fates of Myxococcus xanthus developmental aggregates
- Chunyan Xiea,
- Haiyang Zhanga,
- Lawrence J. Shimketsb, and
- Oleg A. Igoshina,1
aDepartment of Bioengineering, Rice University, Houston, TX 77005; and
bDepartment of Microbiology, University of Georgia, Athens, GA 30602
Edited * by Armin Dale Kaiser, Stanford University School of Medicine, Stanford, CA, and approved February 23, 2011 (received for
review December 8, 2010)
Published online before print
March 21, 2011,
doi:
10.1073/pnas.1018383108
PNAS
April 5, 2011
vol. 108
no. 14
5915-5920 http://www.pnas.org/content/108/14/5915.full
Abstract
Starving Myxococcus xanthus
bacteria use their motility systems to self-organize into multicellular
fruiting bodies, large mounds in which cells differentiate into
metabolically inert spores. Despite the identification of the genetic
pathways required for aggregation and the use of microcinematography to
observe aggregation dynamics in WT and mutant strains, a mechanistic
understanding of aggregation is still incomplete. For example, it is
not clear why some of the initial aggregates mature into fruiting
bodies, whereas others disperse, merge, or split into two. Here, we
develop high-throughput image quantification and statistical analysis
methods to gain insight into M. xanthus
developmental aggregation dynamics. A quantitative metric of features
characterizing each aggregate is used to deduce the properties of the
aggregates that are correlated with each fate. The analysis shows that
small aggregate size but not neighbor-related parameters correlate with
aggregate dispersal. Furthermore, close proximity is necessary but not
sufficient for aggregate merging. Finally, splitting occurs for those
aggregates that are unusually large and elongated. These observations
place severe constraints on the underlying aggregation mechanisms and
present strong evidence against the role of long-range morphogenic
gradients or biased cell exchange in the dispersal, merging, or
splitting of transient aggregates. This approach can be expanded and
adapted to study self-organization in other cellular systems.

Published April 07, 2011Genome-Wide Meta-Analysis Identifies Regions on 7p21 (AHR) and 15q24 (CYP1A2) As Determinants of Habitual Caffeine Consumption
Marilyn C. Cornelis1#, Keri L. Monda2#, Kai Yu3#, Nina Paynter4#, Elizabeth M. Azzato3, Siiri N. Bennett5, Sonja I. Berndt3, Eric Boerwinkle6, Stephen Chanock3, Nilanjan Chatterjee3, David Couper7, Gary Curhan8, Gerardo Heiss2, Frank B. Hu1, David J. Hunter1, Kevin Jacobs3, Majken K. Jensen1, Peter Kraft9, Maria Teresa Landi3, Jennifer A. Nettleton6, Mark P. Purdue3, Preetha Rajaraman3, Eric B. Rimm1, Lynda M. Rose4, Nathaniel Rothman3, Debra Silverman3, Rachael Stolzenberg-Solomon3, Amy Subar3, Meredith Yeager3, Daniel I. Chasman4¶*, Rob M. van Dam10¶*, Neil E. Caporaso3¶* 1 Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America, 2
Department of Epidemiology, The University of North Carolina at Chapel
Hill, Chapel Hill, North Carolina, United States of America, 3
Division of Cancer Epidemiology and Genetics, National Cancer
Institute, National Institutes of Health, Bethesda, Maryland, United
States of America, 4 Brigham and Women's Hospital, Boston, Massachusetts, United States of America, 5 Collaborative Health Studies Coordinating Center, University of Washington, Seattle, Washington, United States of America, 6
Division of Epidemiology, Human Genetics, and Environmental Sciences,
The University of Texas Health Science Center at Houston, Houston,
Texas, United States of America, 7
Department of Biostatistics, Collaborative Studies Coordinating Center,
The University of North Carolina at Chapel Hill, Chapel Hill, North
Carolina, United States of America, 8 Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 9
Program in Molecular and Genetic Epidemiology, Harvard School of Public
Health, Boston, Massachusetts, United States of America, 10
Department of Epidemiology and Public Health and Department of
Medicine, Yong Loo Lin School of Medicine, National University of
Singapore, Singapore, Singapore Editor: Greg Gibson, Georgia Institute of Technology, United States of America
Received: November 17, 2010; Accepted: February 6, 2011; Published: April 7, 2011
AbstractWe
report the first genome-wide association study of habitual caffeine
intake. We included 47,341 individuals of European descent based on
five population-based studies within the United States. In a
meta-analysis adjusted for age, sex, smoking, and eigenvectors of
population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4×10−19), near AHR, and 15q24 (P = 5.2×10−14), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.
Author Summary
Caffeine
is the most widely consumed psychoactive substance in the world.
Although demographic and social factors have been linked to habitual
caffeine consumption, twin studies report a large heritable component.
Through a comprehensive search of the human genome involving over
40,000 participants, we discovered two loci associated with habitual
caffeine consumption: the first near AHR and the second between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates, as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.
Caffeine intake has been associated with manifold physiologic effects
and both detrimental and beneficial health outcomes. Knowledge of the
genetic determinants of caffeine intake may provide insight into
underlying mechanisms and may provide ways to study the potential
health effects of caffeine more comprehensively.
Incorporating Biological Pathways via a Markov Random Field Model in Genome-Wide Association StudiesMin Chen1, Judy Cho2, Hongyu Zhao3* 1
Division of Biostatistics, Department of Clinical Sciences, University
of Texas Southwestern Medical Center, Dallas, Texas, United States of
America, 2 Internal Medicine, Yale University, New Haven, Connecticut, United States of America, 3
Center for Statistical Genomics and Proteomics, Department of
Epidemiology and Public Health, Yale University, New Haven,
Connecticut, United States of America Editor: David B. Allison, University of Alabama at Birmingham, United States of America Received: June 17, 2010; Accepted: February 24, 2011; Published: April 7, 2011 http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1001353
AbstractGenome-wide
association studies (GWAS) examine a large number of markers across the
genome to identify associations between genetic variants and disease.
Most published studies examine only single markers, which may be less
informative than considering multiple markers and multiple genes
jointly because genes may interact with each other to affect disease
risk. Much knowledge has been accumulated in the literature on
biological pathways and interactions. It is conceivable that
appropriate incorporation of such prior knowledge may improve the
likelihood of making genuine discoveries. Although a number of methods
have been developed recently to prioritize genes using prior biological
knowledge, such as pathways, most methods treat genes in a specific
pathway as an exchangeable set without considering the topological
structure of a pathway. However, how genes are related with each other
in a pathway may be very informative to identify association signals.
To make use of the connectivity information among genes in a pathway in
GWAS analysis, we propose a Markov Random Field (MRF) model to
incorporate pathway topology for association analysis. We show that the
conditional distribution of our MRF model takes on a simple logistic
regression form, and we propose an iterated conditional modes algorithm
as well as a decision theoretic approach for statistical inference of
each gene's association with disease. Simulation studies show that our
proposed framework is more effective to identify genes associated with
disease than a single gene–based method. We also illustrate the
usefulness of our approach through its applications to a real data
example.
Author Summary
Statistical
methods used in most GWAS are based on the analysis of single markers.
Prior biological information about markers, genes, and pathways is not
commonly incorporated in the detection of associated disease loci.
Recently a number of methods have been developed to incorporate such
information, and it has been shown that they may make use of prior
biological knowledge in association analysis. However, most of these
methods ignore the regulatory relationships and functional interactions
among genes. In this article, we propose a statistical method that can
explicitly model the interactions of genes in a neighborhood defined by
the topology of a pathway. Simulation studies and a real data example
show that the proposed method can improve the power of identifying
associated genes when they are in the neighborhood of other genes whose
association has been firmly established in previous studies.
  Published April 07, 2011
Modification of Gene Duplicability during the Evolution of Protein Interaction Network
Matteo D'Antonio, Francesca D. Ciccarelli* Department of Experimental Oncology, European Institute of Oncology, Milan, Italy Editor: Christos A. Ouzounis, The Centre for Research and Technology, Hellas, Greece Received: September 29, 2010; Accepted: February 24, 2011; Published: April 7, 2011 http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002029
AbstractDuplications
of genes encoding highly connected and essential proteins are selected
against in several species but not in human, where duplicated genes
encode highly connected proteins. To understand when and how gene
duplicability changed in evolution, we compare gene and network
properties in four species (Escherichia coli, yeast, fly, and
human) that are representative of the increase in evolutionary
complexity, defined as progressive growth in the number of genes,
cells, and cell types. We find that the origin and conservation of a
gene significantly correlates with the properties of the encoded
protein in the protein-protein interaction network. All four species
preserve a core of singleton and central hubs that originated early in
evolution, are highly conserved, and accomplish basic biological
functions. Another group of hubs appeared in metazoans and duplicated
in vertebrates, mostly through vertebrate-specific whole genome
duplication. Such recent and duplicated hubs are frequently targets of
microRNAs and show tissue-selective expression, suggesting that these
are alternative mechanisms to control their dosage. Our study shows how
networks modified during evolution and contributes to explaining the
occurrence of somatic genetic diseases, such as cancer, in terms of
network perturbations.
Author Summary
Gene
copy number is often tightly controlled because it directly affects the
gene dosage. In several species, including yeast, worm, and fly, genes
that have a single gene copy (singleton genes) encode proteins with
several connections in the protein interaction network (hubs) as well
as essential proteins. Surprisingly, in mouse and human essential
proteins and hubs are encoded by genes with more than one copy in the
genome (duplicated genes). Here we show that these two distinct groups
of hubs were acquired at different times during the evolution of
protein interaction network and contribute in different ways to the
cell life. Singleton hubs are ancestral genes that are conserved from
prokaryotes to vertebrates and accomplish basic functions that deal
with the cell survival. Duplicated hubs were acquired mostly within
metazoans and duplicated through vertebrate-specific whole genome
duplication. These genes are involved in processes that are crucial for
the organization of multicellularity. Although duplicated, also recent
hubs are subject to gene dosage control through microRNAs and
tissue-selective expression. The clarification of how the protein
interaction network evolves enables us to understand the adaptation to
the progressive increase in complexity and to better characterize the
genes involved in diseases such as cancer.
  Multi-Scaled Explorations of Binding-Induced Folding of Intrinsically Disordered Protein Inhibitor IA3 to its Target Enzyme
Jin Wang1,2,3*, Yong Wang1, Xiakun Chu2, Stephen J. Hagen4, Wei Han2, Erkang Wang1* 1
State Key Laboratory of Electroanalytical Chemistry, Changchun
Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun,
Jilin, People's Republic of China, 2 College of Physics, Jilin University, Changchun, Jilin, People's Republic of China, 3
Department of Chemistry, Physics and Applied Mathematics, State
University of New York at Stony Brook, Stony Brook, New York, United
States of America, 4 Department of Physics, University of Florida, Gainesville, Florida, United States of America Editor: Gerhard Hummer, National Institute of
Diabetes and Digestive and Kidney Diseases, National Institutes of
Health, United States of America Received: August 17, 2010; Accepted: March 7, 2011; Published: April 7, 2011 http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1001118
AbstractBiomolecular
function is realized by recognition, and increasing evidence shows that
recognition is determined not only by structure but also by flexibility
and dynamics. We explored a biomolecular recognition process that
involves a major conformational change – protein folding. In
particular, we explore the binding-induced folding of IA3, an
intrinsically disordered protein that blocks the active site cleft of
the yeast aspartic proteinase saccharopepsin (YPrA) by folding its own
N-terminal residues into an amphipathic alpha helix. We developed a
multi-scaled approach that explores the underlying mechanism by
combining structure-based molecular dynamics simulations at the residue
level with a stochastic path method at the atomic level. Both the free
energy profile and the associated kinetic paths reveal a common scheme
whereby IA3 binds to its target enzyme prior to folding itself into a
helix. This theoretical result is consistent with recent time-resolved
experiments. Furthermore, exploration of the detailed trajectories
reveals the important roles of non-native interactions in the initial
binding that occurs prior to IA3 folding. In contrast to the common
view that non-native interactions contribute only to the roughness of
landscapes and impede binding, the non-native interactions here
facilitate binding by reducing significantly the entropic search space
in the landscape. The information gained from multi-scaled simulations
of the folding of this intrinsically disordered protein in the presence
of its binding target may prove useful in the design of novel
inhibitors of aspartic proteinases.
Author Summary
The
intrinsically disordered peptide IA3 is the endogenous inhibitor for
the enzyme named yeast aspartic proteinase saccharopepsin (YPrA). In
the presence of YPrA, IA3 folds itself into an amphipathic helix that
blocks the active site cleft of the enzyme. We developed a multi-scaled
approach to explore the underlying mechanism of this binding-induced
ordering transition. Our approach combines a structure-based molecular
dynamics model at the residue level with a stochastic path method at
the atomic level. Our simulations suggest that IA3 inhibits YPrA
through an induced-fit mechanism where the enzyme (YPrA) induces
conformational change of its inhibitor (IA3). This expands the
definition of an induced-fit model from its original meaning that the
binding of substrate (IA3) drives conformational change in the protein
(YPrA). Our result is consistent with recent kinetic experiments and
provides a microscopic explanation for the underlying mechanism. We
also discuss the important roles of non-native interactions and
backtracking. These results enrich our understanding of the
enzyme-inhibition mechanism and may have value in the design of drugs.
Nucl. Acids Res. Table of Contents for Vol. 39, No. 7 Integrative analysis of genomic, functional and protein interaction data predicts long-range enhancer-target gene interactions
- Christian Rödelsperger1,2,3,
- Gao Guo3,
- Mateusz Kolanczyk2,
- Angelika Pletschacher3,
- Sebastian Köhler1,3,
- Sebastian Bauer3,
- Marcel H. Schulz2,4 and
- Peter N. Robinson1,2,3,*
+ Author Affiliations
1Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 2Max Planck Institute for Molecular Genetics, 3Institute for Medical Genetics, Charité-Universitätsmedizin, Berlin and 4International Max Planck Research School for Computational Biology and Scientific Computing, Berlin, Germany
↵*To whom correspondence should be addressed. Tel: +49 30 450566042; Fax: +49 30 450569915; Email: peter.robinson@charite.de
- Received June 25, 2010.
- Revision received October 14, 2010.
- Accepted October 14, 2010.
Nucl. Acids Res.
(2011)
39
(7):
2492-2502.
doi:
10.1093/nar/gkq1081
First published online:
November 24, 2010http://nar.oxfordjournals.org/content/39/7/2492.abstract?etoc
Abstract
Multicellular
organismal development is controlled by a complex network of
transcription factors, promoters and enhancers. Although reliable
computational and experimental methods exist for enhancer detection,
prediction of their target genes remains a major challenge. On the
basis of available literature and ChIP-seq and ChIP-chip data for
enhanceosome factor p300 and the transcriptional regulator Gli3, we
found that genomic proximity and conserved synteny predict target genes
with a relatively low recall of 12–27% within 2 Mb intervals centered
at the enhancers. Here, we show that functional similarities between
enhancer binding proteins and their transcriptional targets and
proximity in the protein–protein interactome improve prediction of
target genes. We used all four features to train random forest
classifiers that predict target genes with a recall of 58% in 2 Mb
intervals that may contain dozens of genes, representing a better than
two-fold improvement over the performance of prediction based on single
features alone. Genome-wide ChIP data is still relatively poorly
understood, and it remains difficult to assign biological significance
to binding events. Our study represents a first step in integrating
various genomic features in order to elucidate the genomic network of
long-range regulatory interactions.
Bioinformatics Table of Contents for 15 April 2011; Vol. 27, No. 8 MemLoci: predicting subcellular localization of membrane proteins in eukaryotes
- Andrea Pierleoni1,2,
- Pier Luigi Martelli1 and
- Rita Casadio1,*
+ Author Affiliations
1Biocomputing Group, Computational Biology Network, via San Giacomo 9/2, 40126 Bologna and 2Externautics s.p.a., Via Fiorentina 1, 53100 Siena, Italy
↵*To whom correspondence should be addressed.
- Received December 4, 2010.
- Revision received February 22, 2011.
- Accepted February 23, 2011.
Bioinformatics
(2011)
27
(9):
1224-1230.
doi:
10.1093/bioinformatics/btr108
First published online:
March 2, 2011http://bioinformatics.oxfordjournals.org/content/27/9/1224.full?etoc
Abstract
Motivation:
Subcellular localization is a key feature in the process of functional
annotation of both globular and membrane proteins. In the absence of
experimental data, protein localization is inferred on the basis of
annotation transfer upon sequence similarity search. However,
predictive tools are necessary when the localization of homologs is not
known. This is so particularly for membrane proteins. Furthermore, most
of the available predictors of subcellular localization are
specifically trained on globular proteins and poorly perform on
membrane proteins.
Results:
Here we develop MemLoci, a new support vector machine-based tool that
discriminates three membrane protein localizations: plasma, internal
and organelle membrane. When tested on an independent set, MemLoci
outperforms existing methods, reaching an overall accuracy of 70% on
predicting the location in the three membrane types, with a generalized
correlation coefficient as high as 0.50.
Availability: The MemLoci server is freely available on the web at: http://mu2py.biocomp.unibo.it/memloci. Datasets described in the article can be downloaded at the same site.
Contact: casadio@biocomp.unibo.it
Supplementary information: Supplementary data are available at Bioinformatics online.
Identifying discriminative classification-based motifs in biological sequences
- Celine Vens1,2,*,
- Marie-Noëlle Rosso2 and
- Etienne G. J. Danchin2
+ Author Affiliations
1Katholieke Universiteit Leuven, Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium and 2Institut
National de la Recherche Agronomique, U.M.R. - I.B.S.V. INRA-UNSA-CNRS,
400 route des Chappes, BP 167, 06903 Sophia-Antipolis Cedex, France
↵*To whom correspondence should be addressed.
- Received September 8, 2010.
- Revision received January 25, 2011.
- Accepted February 24, 2011.
Bioinformatics
(2011)
27
(9):
1231-1238.
doi:
10.1093/bioinformatics/btr110
First published online:
March 3, 2011http://bioinformatics.oxfordjournals.org/content/27/9/1231.full?etoc
Abstract
Motivation:
Identification of conserved motifs in biological sequences is crucial
to unveil common shared functions. Many tools exist for motif
identification, including some that allow degenerate positions with
multiple possible nucleotides or amino acids. Most efficient methods
available today search conserved motifs in a set of sequences, but do
not check for their specificity regarding to a set of negative
sequences.
Results:
We present a tool to identify degenerate motifs, based on a given
classification of amino acids according to their physico-chemical
properties. It returns the top K motifs
that are most frequent in a positive set of sequences involved in a
biological process of interest, and absent from a negative set. Thus,
our method discovers discriminative motifs in biological sequences that
may be used to identify new sequences involved in the same process. We
used this tool to identify candidate effector proteins secreted into
plant tissues by the root knot nematode Meloidogyne incognita. Our tool identified a series of motifs specifically present in a positive set of known effectors while totally absent from
a negative set of evolutionarily conserved housekeeping proteins. Scanning the proteome of M.incognita, we detected 2579 proteins that contain these specific motifs and can be considered as new putative effectors.
Availability and Implementation: The motif discovery tool and the proteins used in the experiments are available at http://dtai.cs.kuleuven.be/ml/systems/merci.
Contact: celine.vens@cs.kuleuven.be
Supplementary Information: Supplementary data are available at Bioinformatics online.
 Prediction of microRNA targets in Caenorhabditis elegans using a self-organizing map
- Liisa Heikkinen1,2,
- Mikko Kolehmainen3 and
- Garry Wong1,2,*
+ Author Affiliations
1Department of Biosciences, 2Department of Neurobiology, A.I.Virtanen Institute for Molecular Sciences, Biocenter Finland and 3Department of Environmental Science, University of Eastern Finland, Kuopio, Finland
↵*To whom correspondence should be addressed.
- Received November 25, 2010.
- Revision received February 20, 2011.
- Accepted March 12, 2011.
Bioinformatics
(2011)
27
(9):
1247-1254.
doi:
10.1093/bioinformatics/btr144
First published online:
March 21, 2011Abstract
Motivation:
MicroRNAs (miRNAs) are small non-coding RNAs that regulate
transcriptional processes via binding to the target gene mRNA. In
animals, this binding is imperfect, which makes the computational
prediction of animal miRNA targets a challenging task. The accuracy of
miRNA target prediction can be improved with the use of machine
learning methods. Previous work has described methods using supervised
learning, but they suffer from the lack of adequate training examples,
a common problem in miRNA target identification, which often leads to
deficient generalization ability.
Results: In this work, we introduce mirSOM, a miRNA target prediction tool based on clustering of short 3′-untranslated region (3′-UTR) substrings with self-organizing map (SOM). As our method uses unsupervised learning and a large set of verified Caenorhabditis elegans 3′-UTRs,
we did not need to resort to training using a known set of targets. Our
method outperforms seven other methods in predicting the experimentally
verified C.elegans true and false miRNA targets.
Availability: mirSOM miRNA target predictions are available at http://kokki.uku.fi/bioinformatics/mirsom.
Contact: liisa.heikkinen@uef.fi
Supplementary information: Supplementary data are available at Bioinformatics online.
 Comparative visualization of genetic and physical maps with Strudel
- Micha Bayer1,*,
- Iain Milne1,
- Gordon Stephen1,
- Paul Shaw1,
- Linda Cardle1,
- Frank Wright2 and
- David Marshall1
+ Author Affiliations
1Genetics Programme, Scottish Crop Research Institute and 2Biomathematics and Statistics Scotland, Invergowrie, Dundee, DD2 5DA, UK
↵*To whom correspondence should be addressed.
- Received December 21, 2010.
- Revision received February 11, 2011.
- Accepted February 24, 2011.
Abstract Summary:
Data visualization can play a key role in comparative genomics, for
example, underpinning the investigation of conserved synteny patterns.
Strudel is a desktop application that allows users to easily compare
both genetic and physical maps interactively and efficiently. It can
handle large datasets from several genomes simultaneously, and allows
all-by-all comparisons between these.
Availability and implementation: Installers for Strudel are available for Windows, Linux, Solaris and Mac OS X at http://bioinf.scri.ac.uk/strudel/.
Contact: strudel@scri.ac.uk; micha.bayer@scri.ac.uk
INTRODUCTION
Crop
genetics is still dominated by species for which fully sequenced and
well-annotated genomes are unavailable. Comparative genomics is an
important means of annotating unfinished genomes, and requires powerful
visualization tools that elucidate the relationships with already
annotated genomes.
There are a number of tools in this area, which range from web-based applications with database back-ends to standalone desktop
applications (Fang et al., 2003; Lewis et al., 2002; Meyer et al., 2009; Mueller et al., 2008; Pan et al., 2005; Sawkins et al., 2004). The challenges faced by any comparative visualization application are the increasing volume of data, fast delivery of these
to users, efficient on-screen rendering of a large amount of information and layout constraints.
Here,
we present Strudel, a standalone Java desktop application that aims to
combine ease of installation with ease of use, and allows the
simultaneous multi-way comparison of several genomes. Usability has
been a major design criterion for Strudel, and in early acceptance
testing users were able to start generating insights into their data
within minutes of downloading the application, without having to first
consult the manual. Strudel's graphical interface has been designed to
reduce visual clutter as much as possible, and a critical condition for
this is that homologies between two chromosomes are never drawn across
other genomes.
GeCo++: a C++ library for genomic features computation and annotation in the presence of variants
- Matteo Cereda1,2,
- Manuela Sironi1,
- Matteo Cavalleri3 and
- Uberto Pozzoli1,*
+ Author Affiliations
1Bioinformatics Lab, Scientific Institute I.R.C.C.S. ‘E. Medea’, Via Don L. Monza, 23852 Bosisio Parini (LC), Italy, 2Department of Theoretical Physics, University of Turin, Via P. Giuria 1 -10125, Torino and 3Bioingineering Lab, Scientific Institute I.R.C.C.S. ‘E. Medea’, Via Don L. Monza, 23852 Bosisio Parini (LC), Italy
- *To whom correspondence should be addressed.
- Received December 15, 2010.
- Revision received February 15, 2011.
- Accepted March 1, 2011.
Bioinformatics
(2011)
27
(9):
1313-1315.
doi:
10.1093/bioinformatics/btr123
First published online:
March 12, 2011
http://bioinformatics.oxfordjournals.org/content/27/9/1313.full?etocAbstract
Summary:
We propose a C++ class library developed to the purpose of making the
implementation of sequence analysis algorithms easier and faster when
genomic annotations and variations need to be considered. The library
provides a class hierarchy to seamlessly bind together annotations of
genomic elements to sequences and to algorithm results; it allows to
evaluate the effect of mutations/variations in terms of both element
position shifts and of algorithm results, limiting recalculation to the
minimum. Particular care has been posed to keep memory and time
overhead into acceptable limits.
Availability and Implementation: A complete tutorial as well as a detailed doxygen generated documentation and source code is freely available at http://bioinformatics.emedea.it/geco, under the GPL license. The library was written in standard ISO C++, and does not depend on external libraries.
Contact: uberto.pozzoli@bp.lnf.it
 Rapid membrane protein topology prediction
- Aron Hennerdal and
- Arne Elofsson*
+ Author Affiliations
Department of Biochemistry and Biophysics, Stockholm Bioinformatics Center, Center for Biomembrane Research, Swedish e-science
Research Center, Stockholm University, 106 91 Stockholm, Sweden
↵*To whom correspondence should be addressed.
- Received December 2, 2010.
- Revision received February 16, 2011.
- Accepted February 28, 2011.
Bioinformatics
(2011)
27
(9):
1322-1323.
doi:
10.1093/bioinformatics/btr119
Abstract
Summary:
State-of-the-art methods for topology of α-helical membrane proteins
are based on the use of time-consuming multiple sequence alignments
obtained from PSI-BLAST or other sources. Here, we examine if it is
possible to use the consensus of topology prediction methods that are
based on single sequences to obtain a similar accuracy as the more
accurate multiple sequence-based methods. Here, we show that
TOPCONS-single performs better than any of the other topology
prediction methods tested here, but ∼6% worse than the best method that
is utilizing multiple sequence alignments.
Availability and Implementation: TOPCONS-single is available as a web server from http://single.topcons.net/
and is also included for local installation from the web site. In
addition, consensus-based topology predictions for the entire
international protein index (IPI) is available from the web server and
will be updated at regular intervals.
Contact: arne@bioinfo.se
Supplementary information: Supplementary data are avaliable at Bioinformatics online.
 ogaraK: a population genetics simulator for malaria
- Tiago Antao* and
- Ian M. Hastings
+ Author Affiliations
Department of Molecular and Biochemical Parasitology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3
5QA, UK
↵*To whom correspondence should be addressed.
- Received December 19, 2010.
- Revision received February 18, 2011.
- Accepted March 9, 2011.
Abstract
Motivation: The evolution of resistance in Plasmodium falciparum
malaria against most available treatments is a major global health
threat. Population genetics approaches are commonly used to model the
spread of drug resistance. Due to uncommon features in malaria biology,
existing forward-time population genetics simulators cannot suitably
model Plasmodium falciparum malaria.
Results:
Here we present ogaraK, a population genetics simulator for modelling
the spread of drug-resistant malaria. OgaraK is designed to make
malaria simulation computationally tractable as it models infections,
not individual parasites. OgaraK is also able to model the life cycle
of the parasite which includes both haploid and diploid phases and
sexual and asexual reproduction. We also allow for the simulation of
different inbreeding levels, an important difference between high and
low transmission areas and a fundamental factor influencing the outcome
of strategies to control or eliminate malaria.
Availability: OgaraK is available as free software (GPL) from the address http://popgen.eu/soft/ogaraK.
Contact: tra@popgen.eu
Supplementary information: Supplementary data is available at Bioinformatics online.
Science
15 April 2011:
Vol. 332
no. 6027
pp.
342-346
DOI:
10.1126/science.1202998
DNA Origami with Complex Curvatures in Three-Dimensional Space
- Dongran Han1,2,*,
- Suchetan Pal1,2,
- Jeanette Nangreave1,2,
- Zhengtao Deng1,2,
- Yan Liu1,2,*, and
- Hao Yan1,2,*
+ Author Affiliations
1The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
2Department of Chemistry and Biochemistry, Arizona State University, Tempe, AZ 85287, USA.
*↵To whom correspondence should be addressed. E-mail: hao.yan@asu.edu (H.Y.); dongran.han@asu.edu (D.H.); yan_liu@asu.edu (Y.L.)
http://www.sciencemag.org/content/332/6027/342.abstract?sa_campaign=Email%2Ftoc%2F15-April-2011%2F10.1126%2Fscience.1202998
Abstract
We
present a strategy to design and construct self-assembling DNA
nanostructures that define intricate curved surfaces in
three-dimensional (3D) space using the DNA origami folding technique.
Double-helical DNA is bent to follow the rounded contours of the target
object, and potential strand crossovers are subsequently identified.
Concentric rings of DNA are used to generate in-plane curvature,
constrained to 2D by rationally designed geometries and crossover
networks. Out-of-plane curvature is introduced by adjusting the
particular position and pattern of crossovers between adjacent DNA
double helices, whose conformation often deviates from the natural,
B-form twist density. A series of DNA nanostructures with high
curvature—such as 2D arrangements of concentric rings and 3D spherical
shells, ellipsoidal shells, and a nanoflask—were assembled.
- Received for publication 18 January 2011.
- Accepted for publication 4 March 2011.
|
posted Apr 10, 2011 4:31 PM by UCmerced CompBioJournalClub
Article Subject Categories: Bioinformatics | Functional genomics Molecular Systems Biology 7 Article number: 473 doi:10.1038/msb.2011.6 Published online: 15 March 2011 Citation: Molecular Systems Biology 7:473 Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic dataJeroen Raes1,2, Ivica Letunic1, Takuji Yamada1, Lars Juhl Jensen1,3 & Peer Bork1,4 - Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Molecular and Cellular Interactions Department, VIB – Vrije Universiteit Brussel, Brussels, Belgium
- NNF Center for Protein Research, Copenhagen, Denmark
- Max Delbrück Center for Molecular Medicine, Berlin-Buch, Germany
Correspondence to: Peer Bork1,4 Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg 69117, Germany. Tel.: +49 6 221 387 8526; Fax: +49 6 221 387 8517; Email: bork@embl.de Received 4 May 2010; Accepted 25 January 2011; Published online 15 March 2011 This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission. Topof pageAbstractUsing metagenomic ‘parts lists’ to infer global patterns on microbial ecology remains a significant challenge. To deduce important ecological indicators such as environmental adaptation, molecular trait dispersal, diversity variation and primary production from the gene pool of an ecosystem, we integrated 25 ocean metagenomes with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the biomolecular repertoire of each sample and the main limiting factor on functional trait dispersal (absence of biogeographic provincialism). Molecular functional richness and diversity show a distinct latitudinal gradient peaking at 20°N and correlate with primary production. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes is an important quantitative readout for molecular trait-based biogeography and ecology.
RNAcode: Robust discrimination of coding and noncoding regions in comparative sequence data- Stefan Washietl1,2,8,
- Sven Findeiß3,
- Stephan A. Müller4,
- Stefan Kalkhof4,
- Martin von Bergen4,
- Ivo L. Hofacker2,
- Peter F. Stadler2,3,5,6,7 and
- Nick Goldman1
-Author Affiliations - 1EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
- 2Institute for Theoretical Chemistry, University of Vienna, A-1090 Wien, Austria
- 3Bioinformatics Group, Department of Computer Science; and Interdisciplinary Center for Bioinformatics, University of Leipzig, D-04107 Leipzig, Germany
- 4Department of Proteomics, Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany
- 5Max Planck Institute for Mathematics in the Sciences, D-04103 Leipzig, Germany
- 6RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, 04103 Leipzig, Germany
- 7Santa Fe Institute, Santa Fe, New Mexico 87501, USA
+ AbstractWith the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied “out of the box,” without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as “noncoding.” RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.
Nucleic Acids Research Table of Contents Alert A new issue of Nucleic Acids Research is available online:Vol. 39, No. 5The below Table of Contents is available online at: http://nar.oxfordjournals.org/content/vol39/issue5/index.dtlThe pseudogenes of Mycobacterium lepraereveal the functional relevance of gene order within operons- Enrique M. Muro1,*,
- Nancy Mah1,
- Gabriel Moreno-Hagelsieb2 and
- Miguel A. Andrade-Navarro1
+Author Affiliations - 1Computational Biology and Data Mining Group, Max Delbrück Center for Molecular Medicine, Robert-Rössle Strasse 10, 13125, Berlin, Germany and 2Department of Biology, Wilfrid Laurier University. Waterloo, Ontario, Canada
- *To whom correspondence should be addressed. Tel: (+49) 30 9406 4227; Fax: (+49) 30 9406 4240; Email: enrique.muro@mdc-berlin.de
- Received March 26, 2010.
- Revision received October 13, 2010.
- Accepted October 14, 2010.
AbstractAlmost 50 years following the discovery of the prokaryotic operon, the functional relevance of gene order within operons remains unclear. In this work, we take advantage of the eroded genome of Mycobacterium leprae to add evidence supporting the notion that functionally less important genes have a tendency to be located at the end of its operons. M. leprae’s genome includes 1133 pseudogenes and 1614 protein-coding genes and can be compared with the close genome of M. tuberculosis. Assuming M. leprae’s pseudogenes to represent dispensable genes, we have studied the position of these pseudogenes in the operons of M. leprae and of their orthologs in M. tuberculosis. We observed that both tend to be located in the 3′ (downstream) half of the operon (P-values of 0.03 and 0.18, respectively). Analysis of pseudogenes in all available prokaryotic genomes confirms this trend (P-value of 7.1 × 10−7). In a complementary analysis, we found a significant tendency for essential genes to be located at the 5′ (upstream) half of the operon (P-value of 0.006). Our work provides an indication that, in prokarya, functionally less important genes have a tendency to be located at the end of operons, while more relevant genes tend to be located toward operon starts.
tRNA 5′-end repair activities of tRNAHisguanylyltransferase (Thg1)-like proteins from Bacteria and Archaea- Bhalchandra S. Rao1,2,
- Emily L. Maris1 and
- Jane E. Jackman1,2,*
+Author Affiliations - 1Department of Biochemistry and Center for RNA Biology and 2Molecular, Cellular and Developmental Biology Graduate Program, The Ohio State University, Columbus, OH 43210, USA
- *To whom correspondence should be addressed. Tel: +1 614 247 8097; Fax: +1 614 292 6773; Email: jackman.14@osu.edu
- Received August 5, 2010.
- Revision received September 30, 2010.
- Accepted October 1, 2010.
AbstractThe tRNAHis guanylyltransferase (Thg1) family comprises a set of unique 3′–5′ nucleotide addition enzymes found ubiquitously in Eukaryotes, where they function in the critical G−1 addition reaction required for tRNAHis maturation. However, in most Bacteria and Archaea, G−1 is genomically encoded; thus post-transcriptional addition of G−1 to tRNAHis is not necessarily required. The presence of highly conserved Thg1-like proteins (TLPs) in more than 40 bacteria and archaea therefore suggests unappreciated roles for TLP-catalyzed 3′–5′ nucleotide addition. Here, we report that TLPs from Bacillus thuringiensis(BtTLP) and Methanosarcina acetivorans (MaTLP) display biochemical properties consistent with a prominent role in tRNA 5′-end repair. Unlike yeast Thg1, BtTLP strongly prefers addition of missing N+1 nucleotides to 5′-truncated tRNAs over analogous additions to full-length tRNA (kcat/KM enhanced 5–160-fold). Moreover, unlike for −1 addition, BtTLP-catalyzed additions to truncated tRNAs are not biased toward addition of G, and occur with tRNAs other than tRNAHis. Based on these distinct biochemical properties, we propose that rather than functioning solely in tRNAHis maturation, bacterial and archaeal TLPs are well-suited to participate in tRNA quality control pathways. These data support more widespread roles for 3′–5′ nucleotide addition reactions in biology than previously expected.

Nature Reviews Molecular Cell Biology 12, 206 (April 2011) | doi:10.1038/nrm3095 Gene expression: Misreading the codeJoanna E. Huddleston Ribosomes read the genetic code by matching the base-pairing of the mRNA codon to the correct tRNA anticodon. The discovery of tRNAs with mutations in the body of the tRNA (as opposed to in the anticodon) that result in aberrant decoding showed that tRNAs are not just scaffolds for amino acids and anticodons; the structure of the tRNA itself has a role in reading the code. Now, Schmeing et al. show how these mutant tRNAs lead to miscoding. Using X-ray crystallography, they find that the mutations aid the distortion of the tRNA that is necessary for it to interact simultaneously with the codon and with elongation factor-Tu (EF-Tu) to allow catalysis of protein synthesis.
Science 25 March 2011: Vol. 331 no. 6024 p. 1513 DOI: 10.1126/science.331.6024.1513 MICROBIOLOGYGoing Viral: Exploring the Role Of Viruses in Our BodiesIn the past decade, scientists have learned that the vast bacterial world inside the human body plays a role in regulating the energy we take in from food, primes the immune system, and performs a variety of other functions that help maintain our health. Now, researchers are gaining similar respect for the viruses we carry around. For a start, the variety and sheer number of viruses that inhabit us put our bacterial companions to shame. Many of the viruses prey on the bacteria in our bodies, altering their numbers and diversity and shuffling genes—including genes for antibiotic resistance—from one bacterium to another. At the International Human Microbiome Congress earlier this month, one provocative, albeit preliminary, finding emerged: Infants with unexplained fevers harbor many more viruses than healthy infants.
USINESS OFFICE FEATURE LIFE SCIENCE TECHNOLOGIES: Synthetic Genomics - Building a Better BacteriumThe May 20, 2010, online edition of Science magazine contained pieces on Brownian motion and gravitational waves, small RNAs and drug delivery--items of interest to narrow slices of the research community. One article, though, generated instant worldwide attention. Entitled "Creation of a bacterial cell controlled by a chemically synthesized genome," the report detailed the world's first "synthetic cell," and it was at once praised and panned. Watchdog groups weighed in, as did U.S. President Barack Obama. Powered by advances in DNA synthesis and genome manipulation, the study was merely a proof-of-principle: Mycoplasma mycoides JCVI-syn1.0 has no practical scientific or commercial value. Yet its cobalt blue colonies represent the living embodiment of an entirely new, and previously unimaginable, branch of biology. Welcome to the age of synthetic genomics.
 
On the Origin of DNA Genomes: Evolution of the Division of Labor between Template and Catalyst in Model Replicator SystemsNobuto Takeuchi1*, Paulien Hogeweg2, Eugene V. Koonin1 1 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America, 2 Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands
bstract TopThe division of labor between template and catalyst is a fundamental property of all living systems: DNA stores genetic information whereas proteins function as catalysts. The RNA world hypothesis, however, posits that, at the earlier stages of evolution, RNA acted as both template and catalyst. Why would such division of labor evolve in the RNA world? We investigated the evolution of DNA-like molecules, i.e. molecules that can function only as template, in minimal computational models of RNA replicator systems. In the models, RNA can function as both template-directed polymerase and template, whereas DNA can function only as template. Two classes of models were explored. In the surface models, replicators are attached to surfaces with finite diffusion. In the compartment models, replicators are compartmentalized by vesicle-like boundaries. Both models displayed the evolution of DNA and the ensuing division of labor between templates and catalysts. In the surface model, DNA provides the advantage of greater resistance against parasitic templates. However, this advantage is at least partially offset by the disadvantage of slower multiplication due to the increased complexity of the replication cycle. In the compartment model, DNA can significantly delay the intra-compartment evolution of RNA towards catalytic deterioration. These results are explained in terms of the trade-off between template and catalyst that is inherent in RNA-only replication cycles: DNA releases RNA from this trade-off by making it unnecessary for RNA to serve as template and so rendering the system more resistant against evolving parasitism. Our analysis of these simple models suggests that the lack of catalytic activity in DNA by itself can generate a sufficient selective advantage for RNA replicator systems to produce DNA. Given the widespread notion that DNA evolved owing to its superior chemical properties as a template, this study offers a novel insight into the evolutionary origin of DNA.
ReviewHorizontal gene transfer between bacteria and animals
Julie C. Dunning Hotoppa,  a Institute for Genome Science, Department of Microbiology & Immunology, University of Maryland School of Medicine, Baltimore, USA, MD 21201 Available online 18 February 2011.
Horizontal gene transfer is increasingly described between bacteria and animals. Such transfers that are vertically inherited have the potential to influence the evolution of animals. One classic example is the transfer of DNA from mitochondria and chloroplasts to the nucleus after the acquisition of these organelles by eukaryotes. Even today, many of the described instances of bacteria-to-animal transfer occur as part of intimate relationships such as those of endosymbionts and their invertebrate hosts, particularly insects and nematodes, while numerous transfers are also found in asexual animals. Both of these observations are consistent with modern evolutionary theory, in particular the serial endosymbiotic theory and Muller's ratchet. Although it is tempting to suggest that these particular lifestyles promote horizontal gene transfer, it is difficult to ascertain given the nonrandom sampling of animal genome sequencing projects and the lack of a systematic analysis of animal genomes for such transfers.
Resolving Difficult Phylogenetic Questions: Why More Sequences Are Not EnoughHervé Philippe1*, Henner Brinkmann1, Dennis V. Lavrov2, D. Timothy J. Littlewood3, Michael Manuel4, Gert Wörheide5,6, Denis Baurain7 1 Département de Biochimie, Centre Robert-Cedergren, Université de Montréal, Montréal, Québec, Canada, 2 Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa, United States of America, 3 Department of Zoology, The Natural History Museum, London, United Kingdom, 4 Université Paris 6, UMR 7138 "Systématique, Adaptation, Evolution" UPMC CNRS IRD MHNH, Paris, France, 5 Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München, München, Germany, 6 GeoBio-Center, Ludwig-Maximilians-Universität München, München, Germany, 7 Unit of Animal Genomics, GIGA-R and Faculty of Veterinary Medicine, University of Liège, Liège, Belgium Citation: Philippe H, Brinkmann H, Lavrov DV, Littlewood DTJ, Manuel M, et al. (2011) Resolving Difficult Phylogenetic Questions: Why More Sequences Are Not Enough. PLoS Biol 9(3): e1000602. doi:10.1371/journal.pbio.1000602 Academic Editor: David Penny, Massey University, New Zealand Published: March 15, 2011 Copyright: © 2011 Philippe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The work was funded by NSERC (www.nserc-crsng.gc.ca), CRC (www.chairs-chaires.gc.ca), Agence Nationale de la Recherche (http://www.agence-nationale-recherche.fr/), ARC Biomod (www.cfwb.be), and DFG (http://www.dfg.de/en/index.jsp). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Abbreviations: BS, bootstrap support; EST, expressed sequence tag; LBA, long branch attraction * E-mail: herve.philippe@umontreal.ca In the quest to reconstruct the Tree of Life, researchers have increasingly turned to phylogenomics, the inference of phylogenetic relationships using genome-scale data (Box 1). Mesmerized by the sustained increase in sequencing throughput, many phylogeneticists entertained the hope that the incongruence frequently observed in studies using single or a few genes [1] would come to an end with the generation of large multigene datasets. Yet, as so often happens, reality has turned out to be far more complex, as three recent large-scale analyses, one published in PLoS Biology [2]–[4], make clear. The studies, which deal with the early diversification of animals, produced highly incongruent (Box 2) findings despite the use of considerable sequence data (see Figure 1). Clearly, merely adding more sequences is not enough to resolve the inconsistencies.

Methodology articleA next-generation sequencing method for overcoming the multiple gene copy problem in polyploid phylogenetics, applied to Poa grassesPhilippa C Griffin , Charles Robin and Ary A Hoffmann  BMC Biology 2011, 9:19doi:10.1186/1741-7007-9-19 Abstract (provisional)BackgroundPolyploidy is important from a phylogenetic perspective because of its immense past impact on evolution and its potential future impact on diversification, survival and adaptation, especially in plants. Molecular population genetics studies of polyploid organisms have been difficult because of problems in sequencing multiple-copy nuclear genes using Sanger sequencing. This paper describes a method for sequencing a barcoded mixture of targeted gene regions using next-generation sequencing methods to overcome these problems. Science 1 April 2011: Vol. 332 no. 6025 pp. 43-44 DOI: 10.1126/science.1200486 IMMUNOLOGYDanger, Microbes, and HomeostasisThe immune system is conventionally viewed as a means to fight infection. It has become clear, however, that what is considered the “immune” system has also evolved to maintain homeostasis and regulate commensal microbes that normally inhabit the body. Such varied functions demand nuanced and context-appropriate control of immune responses. The thoughts on how immunity becomes activated include two views: by recognition of “nonself” molecules of infectious agents (1) or by recognition of “danger” signals—host molecules released by damaged host cells (2). Empirical evidence supports both models, but also reveals their limits. Insights from recent studies on insect immune systems, which are generalizable to vertebrates, suggest that the two models may be compatible. That is, a host determines the balance of nonself elicitors and danger signals to decide when to activate the immune system against pathogenic infection while also maintaining healthy relationships with commensals. |
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Beyond Predictions: Biodiversity Conservation in a Changing Climate- Terence P. Dawson1,
- Stephen T. Jackson2,
- Joanna I. House3,
- Iain Colin Prentice3,4,5, and
- Georgina M. Mace4,6,*
+Author Affiliations - 1School of the Environment, University of Dundee, Dundee DD1 4HN, Scotland, UK.
- 2Department of Botany, Program in Ecology, and Berry Biodiversity Conservation Center, University of Wyoming, Laramie, WY 82071, USA.
- 3QUEST, Department of Earth Sciences, University of Bristol, Bristol BS8 1RJ, UK.
- 4Grantham Institute for Climate Change and Division of Biology, Imperial College London, London SW7 2AZ, UK.
- 5Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia.
- 6Centre for Population Biology, Imperial College London, Ascot SL5 7PY, UK.
- *↵To whom correspondence should be addressed. E-mail: g.mace@imperial.ac.uk
ABSTRACTClimate change is predicted to become a major threat to biodiversity in the 21st century, but accurate predictions and effective solutions have proved difficult to formulate. Alarming predictions have come from a rather narrow methodological base, but a new, integrated science of climate-change biodiversity assessment is emerging, based on multiple sources and approaches. Drawing on evidence from paleoecological observations, recent phenological and microevolutionary responses, experiments, and computational models, we review the insights that different approaches bring to anticipating and managing the biodiversity consequences of climate change, including the extent of species’ natural resilience. We introduce a framework that uses information from different sources to identify vulnerability and to support the design of conservation responses. Although much of the information reviewed is on species, our framework and conclusions are also applicable to ecosystems, habitats, ecological communities, and genetic diversity, whether terrestrial, marine, or fresh water. Bacteria-Phage Antagonistic Coevolution in Soil- Pedro Gómez1,2,* and
- Angus Buckling1,3
+Author Affiliations - 1Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.
- 2Centro de Edafología y Biología Aplicada del Segura, Consejo Superior de Investigaciones Científicas (CEBAS-CSIC), Murcia (Espinardo) 30100, Spain.
- 3Biosciences, University of Exeter, Penryn TR10 9EZ, UK.
- *↵To whom correspondence should be addressed. E-mail: pedro.gomezlopez@zoo.ox.ac.uk
ABSTRACTBacteria and their viruses (phages) undergo rapid coevolution in test tubes, but the relevance to natural environments is unclear. By using a “mark-recapture” approach, we showed rapid coevolution of bacteria and phages in a soil community. Unlike coevolution in vitro, which is characterized by increases in infectivity and resistance through time (arms race dynamics), coevolution in soil resulted in hosts more resistant to their contemporary than past and future parasites (fluctuating selection dynamics). Fluctuating selection dynamics, which can potentially continue indefinitely, can be explained by fitness costs constraining the evolution of high levels of resistance in soil. These results suggest that rapid coevolution between bacteria and phage is likely to play a key role in structuring natural microbial communities.
Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems AnalysisMatthew A. Oberhardt1#, Jacek Puchałka2#, Vítor A. P. Martins dos Santos1,2¶*, Jason A. Papin1¶* 1 Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America, 2 Helmholtz Center for Infection Research (HZI), Braunschweig, Germany Abstract TopIn the past decade, over 50 genome-scale metabolic reconstructions have been built for a variety of single- and multi- cellular organisms. These reconstructions have enabled a host of computational methods to be leveraged for systems-analysis of metabolism, leading to greater understanding of observed phenotypes. These methods have been sparsely applied to comparisons between multiple organisms, however, due mainly to the existence of differences between reconstructions that are inherited from the respective reconstruction processes of the organisms to be compared. To circumvent this obstacle, we developed a novel process, termed metabolic network reconciliation, whereby non-biological differences are removed from genome-scale reconstructions while keeping the reconstructions as true as possible to the underlying biological data on which they are based. This process was applied to two organisms of great importance to disease and biotechnological applications, Pseudomonas aeruginosa andPseudomonas putida, respectively. The result is a pair of revised genome-scale reconstructions for these organisms that can be analyzed at a systems level with confidence that differences are indicative of true biological differences (to the degree that is currently known), rather than artifacts of the reconstruction process. The reconstructions were re-validated with various experimental data after reconciliation. With the reconciled and validated reconstructions, we performed a genome-wide comparison of metabolic flexibility between P. aeruginosa and P. putida that generated significant new insight into the underlying biology of these important organisms. Through this work, we provide a novel methodology for reconciling models, present new genome-scale reconstructions of P. aeruginosa and P. putida that can be directly compared at a network level, and perform a network-wide comparison of the two species. These reconstructions provide fresh insights into the metabolic similarities and differences between these important Pseudomonads, and pave the way towards full comparative analysis of genome-scale metabolic reconstructions of multiple species.
Noise Contributions in an Inducible Genetic Switch: A Whole-Cell Simulation Study
Elijah Roberts1,2, Andrew Magis3, Julio O. Ortiz4,Wolfgang Baumeister4, Zaida Luthey-Schulten1,2,3* 1 Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 2 Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 3 Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 4 Department of Molecular Structural Biology, Max Planck Institute of Biochemistry, Martinsreid, Germany Abstract TopStochastic expression of genes produces heterogeneity in clonal populations of bacteria under identical conditions. We analyze and compare the behavior of the inducible lac genetic switch using well-stirred and spatially resolved simulations for Escherichia coli cells modeled under fast and slow-growth conditions. Our new kinetic model describing the switching of the lac operon from one phenotype to the other incorporates parameters obtained from recently published in vivosingle-molecule fluorescence experiments along with in vitro rate constants. For the well-stirred system, investigation of the intrinsic noise in the circuit as a function of the inducer concentration and in the presence/absence of the feedback mechanism reveals that the noise peaks near the switching threshold. Applying maximum likelihood estimation, we show that the analytic two-state model of gene expression can be used to extract stochastic rates from the simulation data. The simulations also provide mRNA–protein probability landscapes, which demonstrate that switching is the result of crossing both mRNA and protein thresholds. Using cryoelectron tomography of an E. coli cell and data from proteomics studies, we construct spatial in vivo models of cells and quantify the noise contributions and effects on repressor rebinding due to cell structure and crowding in the cytoplasm. Compared to systems without spatial heterogeneity, the model for the fast-growth cells predicts a slight decrease in the overall noise and an increase in the repressors rebinding rate due to anomalous subdiffusion. The tomograms for E. coli grown under slow-growth conditions identify the positions of the ribosomes and the condensed nucleoid. The smaller slow-growth cells have increased mRNA localization and a larger internal inducer concentration, leading to a significant decrease in the lifetime of the repressor–operator complex and an increase in the frequency of transcriptional bursts.
Directed networks reveal genomic barriers and DNA repair bypasses to lateral gene transfer among prokaryotes- Ovidiu Popa1,
- Einat Hazkani-Covo2,
- Giddy Landan3,
- William Martin1 and
- Tal Dagan1,4
+Author Affiliations - 1 Institute of Botany III, Heinrich-Heine University Düsseldorf, Düsseldorf 40225, Germany;
- 2 Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina 27705, USA;
- 3 Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204-5001, USA
AbstractLateral gene transfer (LGT) plays a major role in prokaryote evolution with only a few genes that are resistant to it; yet the nature and magnitude of barriers to lateral transfer are still debated. Here, we implement directed networks to investigate donor–recipient events of recent lateral gene transfer among 657 sequenced prokaryote genomes. For 2,129,548 genes investigated, we detected 446,854 recent lateral gene transfer events through nucleotide pattern analysis. Among these, donor–recipient relationships could be specified through phylogenetic reconstruction for 7% of the pairs, yielding 32,028 polarized recent gene acquisition events, which constitute the edges of our directed networks. We find that the frequency of recent LGT is linearly correlated both with genome sequence similarity and with proteome similarity of donor–recipient pairs. Genome sequence similarity accounts for 25% of the variation in gene-transfer frequency, with proteome similarity adding only 1% to the variability explained. The range of donor–recipient GC content similarity within the network is extremely narrow, with 86% of the LGTs occurring between donor–recipient pairs having ≤5% difference in GC content. Hence, genome sequence similarity and GC content similarity are strong barriers to LGT in prokaryotes. But they are not insurmountable, as we detected 1530 recent transfers between distantly related genomes. The directed network revealed that recipient genomes of distant transfers encode proteins of nonhomologous end-joining (NHEJ; a DNA repair mechanism) far more frequently than the recipient lacking that mechanism. This implicates NHEJ in genes spread across distantly related prokaryotes through bypassing the donor–recipient sequence similarity barrier. |
NATURE STRUCTURAL & MOLECULAR BIOLOGY | ARTICLE
How mutations in tRNA distant from the anticodon affect the fidelity of decoding- Nature Structural & Molecular Biology
- 18,
- 432–436
- (2011)
- doi:10.1038/nsmb.2003
- Received
- 19 October 2010
- Accepted
- 08 December 2010
- Published online
- 06 March 2011
AbstractThe ribosome converts genetic information into protein by selecting aminoacyl tRNAs whose anticodons base-pair to an mRNA codon. Mutations in the tRNA body can perturb this process and affect fidelity. The Hirsh suppressor is a well-studied tRNATrp harboring a G24A mutation that allows readthrough of UGA stop codons. Here we present crystal structures of the 70S ribosome complexed with EF-Tu and aminoacyl tRNA (native tRNATrp, G24A tRNATrp or the miscoding A9C tRNATrp) bound to cognate UGG or near-cognate UGA codons, determined at 3.2-Å resolution. The A9C and G24A mutations lead to miscoding by facilitating the distortion of tRNA required for decoding. A9C accomplishes this by increasing tRNA flexibility, whereas G24A allows the formation of an additional hydrogen bond that stabilizes the distortion. Our results also suggest that each native tRNA will adopt a unique conformation when delivered to the ribosome that allows accurate decoding.
NATURE STRUCTURAL & MOLECULAR BIOLOGY | ARTICLE
mRNA translocation occurs during the second step of ribosomal intersubunit rotation- Nature Structural & Molecular Biology
- 18,
- 457–462
- (2011)
- doi:10.1038/nsmb.2011
- Received
- 09 June 2010
- Accepted
- 15 December 2010
- Published online
- 13 March 2011
AbstractDuring protein synthesis, mRNA and tRNA undergo coupled translocation through the ribosome in a process that is catalyzed by elongation factor G(EF-G). On the basis of cryo-EM reconstructions, counterclockwise and clockwise rotational movements between the large and small ribosomal subunits have been implicated in a proposed ratcheting mechanism to drive the unidirectional movement of translocation. We used a combination of two fluorescence-based approaches to study the timing of these events, intersubunit fluorescence resonance energy transfer measurements to observe relative rotational movement of the subunits, and a fluorescence quenching assay to monitor translocation of mRNA. Binding of EF-G–GTP first induces rapid counterclockwise intersubunit rotation, followed by a slower, clockwise reversal of the rotational movement. We compared the rates of these movements and found that mRNA translocation occurs during the second, clockwise rotation event, corresponding to the transition from the hybrid state to the classical state. |
posted Mar 28, 2011 11:42 AM by UCmerced CompBioJournalClub
 A Boolean-based systems biology approach to predict novel genes associated with cancer: Application to colorectal cancerShivashankar H Nagaraj and Antonio Reverter  Computational and Systems Biology, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Division of Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, Brisbane, Queensland 4067, Australia author email corresponding author email
BMC Systems Biology 2011, 5:35doi:10.1186/1752-0509-5-35 | | Published: | 26 February 2011 |
AbstractBackgroundCancer has remarkable complexity at the molecular level, with multiple genes, proteins, pathways and regulatory interconnections being affected. We introduce a systems biology approach to study cancer that formally integrates the available genetic, transcriptomic, epigenetic and molecular knowledge on cancer biology and, as a proof of concept, we apply it to colorectal cancer. ResultsWe first classified all the genes in the human genome into cancer-associated and non-cancer-associated genes based on extensive literature mining. We then selected a set of functional attributes proven to be highly relevant to cancer biology that includes protein kinases, secreted proteins, transcription factors, post-translational modifications of proteins, DNA methylation and tissue specificity. These cancer-associated genes were used to extract 'common cancer fingerprints' through these molecular attributes, and a Boolean logic was implemented in such a way that both the expression data and functional attributes could be rationally integrated, allowing for the generation of a guilt-by-association algorithm to identify novel cancer-associated genes. Finally, these candidate genes are interlaced with the known cancer-related genes in a network analysis aimed at identifying highly conserved gene interactions that impact cancer outcome. We demonstrate the effectiveness of this approach using colorectal cancer as a test case and identify several novel candidate genes that are classified according to their functional attributes. These genes include the following: 1) secreted proteins as potential biomarkers for the early detection of colorectal cancer (FXYD1, GUCA2B, REG3A); 2) kinases as potential drug candidates to prevent tumor growth (CDC42BPB, EPHB3, TRPM6); and 3) potential oncogenic transcription factors (CDK8, MEF2C, ZIC2). ConclusionWe argue that this is a holistic approach that faithfully mimics cancer characteristics, efficiently predicts novel cancer-associated genes and has universal applicability to the study and advancement of cancer research. 
Adaptive seeds tame genomic sequence comparison- Szymon M. Kiełbasa1,
- Raymond Wan2,
- Kengo Sato3,
- Paul Horton2 and
- Martin C. Frith2,4
+Author Affiliations - 1 Department of Computational Biology, Max Planck Institute for Molecular Genetics, Berlin D-14195, Germany;
- 2 Computational Biology Research Center, Tokyo 135-0064, Japan;
- 3 Graduate School of Frontier Sciences, University of Tokyo, Chiba 277-8561, Japan
AbstractThe main way of analyzing biological sequences is by comparing and aligning them to each other. It remains difficult, however, to compare modern multi-billionbase DNA data sets. The difficulty is caused by the nonuniform (oligo)nucleotide composition of these sequences, rather than their size per se. To solve this problem, we modified the standard seed-and-extend approach (e.g., BLAST) to use adaptive seeds. Adaptive seeds are matches that are chosen based on their rareness, instead of using fixed-length matches. This method guarantees that the number of matches, and thus the running time, increases linearly, instead of quadratically, with sequence length. LAST, our open source implementation of adaptive seeds, enables fast and sensitive comparison of large sequences with arbitrarily nonuniform composition. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons- Brian J. Haas1,9,
- Dirk Gevers1,
- Ashlee M. Earl1,
- Mike Feldgarden1,
- Doyle V. Ward1,
- Georgia Giannoukos1,
- Dawn Ciulla1,
- Diana Tabbaa1,
- Sarah K. Highlander2,3,
- Erica Sodergren4,
- Barbara Methé5,
- Todd Z. DeSantis6,
- The Human Microbiome Consortium,
- Joseph F. Petrosino2,3,
- Rob Knight7,8 and
- Bruce W. Birren1
+Author Affiliations - 1 Genome Sequencing and Analysis Program, The Broad Institute, Cambridge, Massachusetts 02142, USA;
- 2 Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA;
- 3 Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas 77030, USA;
- 4 The Genome Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA;
- 5 Human Genomic Medicine, J. Craig Venter Institute, Rockville, Maryland 20850, USA;
- 6 Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA;
- 7 Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado 80309, USA;
- 8 Howard Hughes Medical Institute, University of Colorado, Boulder, Colorado 80309, USA
AbstractBacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys. 
BIO::Phylo-phyloinformatic analysis using perlRutger A Vos1 , Jason Caravas2 , Klaas Hartmann3 , Mark A Jensen4 and Chase Miller5  1 School of Biological Sciences, University of Reading, UK 2 Department of Biological Sciences, Wayne State University, Detroit, MI, USA 3 Tasmanian Aquaculture and Fisheries Institute, University of Tasmania, Australia 4 Fortinbras Research, Rockville, MD, USA 5 Center for Infection and Immunity, Columbia University, New York, NY, USA author email corresponding author email
BMC Bioinformatics 2011, 12:63doi:10.1186/1471-2105-12-63 | | Published: | 27 February 2011 |
AbstractBackgroundPhyloinformatic analyses involve large amounts of data and metadata of complex structure. Collecting, processing, analyzing, visualizing and summarizing these data and metadata should be done in steps that can be automated and reproduced. This requires flexible, modular toolkits that can represent, manipulate and persist phylogenetic data and metadata as objects with programmable interfaces. ResultsThis paper presents Bio::Phylo, a Perl5 toolkit for phyloinformatic analysis. It implements classes and methods that are compatible with the well-known BioPerl toolkit, but is independent from it (making it easy to install) and features a richer API and a data model that is better able to manage the complex relationships between different fundamental data and metadata objects in phylogenetics. It supports commonly used file formats for phylogenetic data including the novel NeXML standard, which allows rich annotations of phylogenetic data to be stored and shared. Bio::Phylo can interact with BioPerl, thereby giving access to the file formats that BioPerl supports. Many methods for data simulation, transformation and manipulation, the analysis of tree shape, and tree visualization are provided. ConclusionsBio::Phylo is composed of 59 richly documented Perl5 modules. It has been deployed successfully on a variety of computer architectures (including various Linux distributions, Mac OS X versions, Windows, Cygwin and UNIX-like systems). It is available as open source (GPL) software fromhttp://search.cpan.org/dist/Bio-Phylo webcite compomics-utilities: an open-source Java library for computational proteomicsHarald Barsnes1,2 , Marc Vaudel3 , Niklaas Colaert4,5 , Kenny Helsens4,5 , Albert Sickmann3 , Frode S Berven1 and Lennart Martens4,5  1 Proteomics Unit, Department of Biomedicine, University of Bergen, Norway 2 Computational Biology Unit, UniComputing, Bergen, Norway 3 Leibniz - Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany 4 Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium 5 Department of Biochemistry, Ghent University, B-9000 Ghent, Belgium author email corresponding author email
BMC Bioinformatics 2011, 12:70doi:10.1186/1471-2105-12-70 AbstractBackgroundThe growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. ResultsIn order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. ConclusionsAs a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics. Science 4 March 2011: Vol. 331 no. 6021 pp. 1185-1188 DOI: 10.1126/science.1199707Pseudomonas sax Genes Overcome Aliphatic Isothiocyanate–Mediated Non-Host Resistance in Arabidopsis- Jun Fan1,*†,
- Casey Crooks1,2,†,
- Gary Creissen1,
- Lionel Hill1,
- Shirley Fairhurst1,
- Peter Doerner3,4,*, and
- Chris Lamb1,‡
+Author Affiliations - 1John Innes Centre, Norwich NR4 7UH, UK.
- 2USDA Forest Products Laboratory, 1 Gifford Pinchot Drive, Madison, WI 53726, USA.
- 3Institute of Molecular Plant Sciences, University of Edinburgh, Mayfield Road, Edinburgh EH9 3JH, UK.
- 4Laboratoire de Physiologie Cellulaire Végétale, CNRS, CEA, INRA, and Université Joseph Fourier, F-38000 Grenoble, France
+Author Notes - *To whom correspondence should be addressed. E-mail: jun.fan@bbsrc.ac.uk (J.F.); peter.doerner@ed.ac.uk(P.D.)
↵† These authors contributed equally to this work.
ABSTRACTMost plant-microbe interactions do not result in disease; natural products restrict non-host pathogens. We found that sulforaphane (4-methylsulfinylbutyl isothiocyanate), a natural product derived from aliphatic glucosinolates, inhibits growth in Arabidopsis of non-host Pseudomonasbacteria in planta. Multiple sax genes (saxCAB/F/D/G) were identified in Pseudomonas species virulent on Arabidopsis. These sax genes are required to overwhelm isothiocyanate-based defenses and facilitate a disease outcome, especially in the young leaves critical for plant survival. Introduction of saxCAB genes into non-host strains enabled them to overcome these Arabidopsisdefenses. Our study shows that aliphatic isothiocyanates, previously shown to limit damage by herbivores, are also crucial, robust, and developmentally regulated defenses that underpin non-host resistance in the Arabidopsis-Pseudomonas pathosystem. - Received for publication 28 October 2010.
- Accepted for publication 24 January 2011.
Science 18 March 2011: Vol. 331 no. 6023 pp. 1383-1384 DOI: 10.1126/science.331.6023.1383 CONSERVATION ECOLOGYEmbracing InvasivesMuch of the fauna and flora of the Galápagos islands is unique, but introduced species are taking over. Conservationists have spent the past 50 years attempting to remove introduced species and restore the islands' flora and fauna to prehuman days. There have been some successes: Goats have been eliminated from several islands. But the effort to eradicate blackberry, guava, and 34 other invasive plant species has cost more than $1 million and succeeded in eliminating just four. The most invasive and problematic of these aliens—blackberry and guava—have developed into forests where nothing else grows, birds cannot nest, and even insects are rare. The main reason for this failure is that invasive plants are far more competitive than native plants. Seeds of invasive species, such as blackberries, are long-lived and accumulate in high numbers in the soil, and restoration activities can have the paradoxical effect of stimulating them to germinate. Now, a group of maverick ecologists is promoting the idea that the addition of nonnative species to natives in a region leads to "novel" or "hybrid" ecosystems that have ecological value and may be worthy of conservation.

The population dynamics of bacteria in physically structured habitats and the adaptive virtue of random motility- Yan Weia,b,
- Xiaolin Wangc,
- Jingfang Liuc,
- Ilya Nememand,e,
- Amoolya H. Singha,e,
- Howie Weissc, and
- Bruce R. Levina,1
+Author Affiliations - aDepartment of Biology,
- bGraduate Program in Population Biology, Ecology, and Evolution,
- dDepartments of Physics and Biology, and
- eComputational and Life Sciences Strategic Initiative, Emory University, Atlanta, GA 30322; and
- cDepartment of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332
Edited* by Robert May, University of Oxford, Oxford, United Kingdom, and approved January 12, 2011 (received for review September 9, 2010)
AbstractWhy is motility so common in bacteria? An obvious answer to this ecological and evolutionary question is that in almost all habitats, bacteria need to go someplace and particularly in the direction of food. Although the machinery required for motility and chemotaxis (acquiring and processing the information needed to direct movement toward nutrients) are functionally coupled in contemporary bacteria, they are coded for by different sets of genes. Moreover, information that resources are more abundant elsewhere in a habitat would be of no value to a bacterium unless it already had the means to get there. Thus, motility must have evolved before chemotaxis, and bacteria with flagella and other machinery for propulsion in random directions must have an advantage over bacteria relegated to moving at the whim of external forces alone. However, what are the selection pressures responsible for the evolution and maintenance of undirected motility in bacteria? Here we use a combination of mathematical modeling and experiments with Escherichia coli to generate and test a parsimonious and ecologically general hypothesis for the existence of undirected motility in bacteria: it enables bacteria to move away from each other and thereby obtain greater individual shares of resources in physically structured environments. The results of our experiments not only support this hypothesis, but are quantitatively and qualitatively consistent with the predictions of our model. Clustering to identify RNA conformations constrained by secondary structure- Adelene Y. L. Sima and
- Michael Levittb,1
+Author Affiliations - aDepartment of Applied Physics, Stanford University, Stanford, CA 94305; and
- bDepartment of Structural Biology, Stanford University School of Medicine, D100 Fairchild Building, Stanford, CA 94305
Contributed by Michael Levitt, December 21, 2010 (sent for review October 24, 2010)
AbstractRNA often folds hierarchically, so that its sequence defines its secondary structure (helical base-paired regions connected by single-stranded junctions), which subsequently defines its tertiary fold. To preserve base-pairing and chain connectivity, the three-dimensional conformations that RNA can explore are strongly confined compared to when secondary structure constraints are not enforced. Using three examples, we studied how secondary structure confines and dictates an RNA’s preferred conformations. We made use of Macromolecular Conformations by SYMbolic programming (MC-Sym) fragment assembly to generate RNA conformations constrained by secondary structure. Then, to understand the correlations between different helix placements and orientations, we robustly clustered all RNA conformations by employing unique methods to remove outliers and estimate the best number of conformational clusters. We observed that the preferred conformation (as judged by largest cluster size) for each type of RNA junction molecule tested is consistent with its biological function. Further, the improved quality of models in our pruned datasets facilitates subsequent discrimination using scoring functions based either on statistical analysis (knowledge based) or experimental data.
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample- J. Gregory Caporasoa,
- Christian L. Lauberb,
- William A. Waltersc,
- Donna Berg-Lyonsb,
- Catherine A. Lozuponea,
- Peter J. Turnbaughd,
- Noah Fiererb,e, and
- Rob Knighta,f,1
+Author Affiliations - aDepartment of Chemistry and Biochemistry,
- bCooperative Institute for Research in Environmental Sciences,
- cDepartment of Molecular, Cellular, and Developmental Biology, and
- eDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309;
- dHarvard FAS Center for Systems Biology, Cambridge, MA 02138; and
- fHoward Hughes Medical Institute, Boulder, CO 80309
Edited by Jeffrey I. Gordon, Washington University School of Medicine, St. Louis, MO, and approved April 30, 2010 (received for review February 27, 2010)
AbstractThe ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known “mock communities” at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
Journal of Computational Biology naiveBayesCall: An Efficient Model-Based Base-Calling Algorithm for High-Throughput Sequencing
To cite this article: Wei-Chun Kao, Yun S. Song. Journal of Computational Biology. March 2011, 18(3): 365-377. doi:10.1089/cmb.2010.0247. Published in Volume: 18 Issue 3: March 8, 2011
Wei-Chun Kao1 and Yun S. Song1,2 1Department of EECS, University of California, Berkeley, California. 2Department of Statistics, University of California, Berkeley, California. Address correspondence to: Dr. Yun S. Song Departments of EECS and Statistics University of CaliforniaBerkeley, CA 94720, USA E-mail: yss@eecs.berkeley.eduAbstract Immense amounts of raw instrument data (i.e., images of fluorescence) are currently being generated using ultra high-throughput sequencing platforms. An important computational challenge associated with this rapid advancement is to develop efficient algorithms that can extract accurate sequence information from raw data. To address this challenge, we recently introduced a novel model-based base-calling algorithm that is fully parametric and has several advantages over previously proposed methods. Our original algorithm, called BayesCall, significantly reduced the error rate, particularly in the later cycles of a sequencing run, and also produced useful base-specific quality scores with a high discrimination ability. Unfortunately, however, BayesCall is too computationally expensive to be of broad practical use. In this article, we build on our previous model-based approach to devise an efficient base-calling algorithm that is orders of magnitude faster than BayesCall, while still maintaining a comparably high level of accuracy. Our new algorithm is called naiveBayesCall, and it utilizes approximation and optimization methods to achieve scalability. We describe the performance of naiveBayesCall and demonstrate how improved base-calling accuracy may facilitate de novo assembly and SNP detection when the sequence coverage depth is low to moderate. Molecular Systems Biology |
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SynopsisSubject Categories: Bioinformatics | Functional genomics Molecular Systems Biology 7 Article number: 473 doi:10.1038/msb.2011.6 Published online: 15 March 2011 Citation: Molecular Systems Biology 7:473 Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic dataJeroen Raes1,2, Ivica Letunic1, Takuji Yamada1, Lars Juhl Jensen1,3 & Peer Bork1,4 - Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Molecular and Cellular Interactions Department, VIB – Vrije Universiteit Brussel, Brussels, Belgium
- NNF Center for Protein Research, Copenhagen, Denmark
- Max Delbrück Center for Molecular Medicine, Berlin-Buch, Germany
Correspondence to: Peer Bork1,4 Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg 69117, Germany. Tel.: +49 6 221 387 8526; Fax: +49 6 221 387 8517; Email: bork@embl.de Received 4 May 2010; Accepted 25 January 2011; Published online 15 March 2011 Topof pageArticle highlights- Climatic factors drive functional and phylogenetic composition of ocean microbial communities.
- Function dispersal is controlled by environmental conditions.
- Functional richness has a clear latitudinal gradient and correlates with primary production.
- Metagenomic data can be used as a predictor for ecosystem processes.
- To understand the relationship between community composition and environment, functional readouts are the most direct. Metagenomic data enable such trait-based ecology at the molecular level.
Topof pageSynopsisMetagenomics (shotgun sequencing of pooled DNA of complete microbial communities) is widely used to investigate ecosystem functioning of environmental and clinical samples. However, the nature of this data (usually a gigantic collection of gene fragments of 1000s of organisms) makes it very hard to infer global patterns on microbial ecology of the environment at hand. To address important ecological questions such as ‘How do microbial communities adapt to the environmental conditions?’, ‘What drives the functional variation across the globe and to what extent do genes disperse?’ and ‘What drives variation of CO2 uptake across different locations and communities?’, we integrated 25 ocean metagenomes from the Global Ocean Sampling project with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the functional and phylogenetic composition of an environment and the main limiting factor on whether functions dispersal across the planet. We find a distinct latitudinal gradient in the size and diversity of the functional repertoire of ocean microbial communities, peaking at 20°N, and which correlates with oceanic CO2 uptake. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes can be used as quantitative predictor for molecular trait-based biogeography and ecology.
Dynamic Phenotypic Clustering in Noisy EcosystemsMorten Ernebjerg1, Roy Kishony1,2* 1 Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America, 2 School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America Abstract TopIn natural ecosystems, hundreds of species typically share the same environment and are connected by a dense network of interactions such as predation or competition for resources. Much is known about how fixed ecological niches can determine species abundances in such systems, but far less attention has been paid to patterns of abundances in randomly varying environments. Here, we study this question in a simple model of competition between many species in a patchy ecosystem with randomly fluctuating environmental conditions. Paradoxically, we find that introducing noise can actually induce ordered patterns of abundance-fluctuations, leading to a distinct periodic variation in the correlations between species as a function of the phenotypic distance between them; here, difference in growth rate. This is further accompanied by the formation of discrete, dynamic clusters of abundant species along this otherwise continuous phenotypic axis. These ordered patterns depend on the collective behavior of many species; they disappear when only individual or pairs of species are considered in isolation. We show that they arise from a balance between the tendency of shared environmental noise to synchronize species abundances and the tendency for competition among species to make them fluctuate out of step. Our results demonstrate that in highly interconnected ecosystems, noise can act as an ordering force, dynamically generating ecological patterns even in environments lacking explicit niches. Author Summary TopIn natural ecosystems, hundreds of species with different characteristics typically live side by side, some competing for the same foods and some preying on others. A central question in ecology is how the abundance of a given species in such an ecosystem depends on its particular characteristics (its phenotype). Clearly, fixed environments can favor certain phenotypes (thick fur in a cold climate), but what happens when environmental conditions fluctuate randomly as e.g. the weather does? We investigated this question using a simple mathematical model of an ecosystem with many competing species. We found that, paradoxically, randomness in the environment can lead to the appearance of ordered clusters of abundant species with similar phenotypes, with the species adopting intermediate phenotypes being much less abundant (a mountains-and-valleys pattern). The clusters move around so that different phenotypes are favored at different times. We found that these effects arise from the tension between the tendency of noise to level out difference in abundances and the tendency of competition to create larger abundance differences.
 A protein fold classifier formed by fusing different modes of pseudo amino acid composition via PSSM Kaveh Kavousia, Behzad Moshiria, Mehdi Sadeghib, d, , , , Babak N. Araabia and Ali Akbar Moosavi-Movahedic a Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran b National Institute of Genetic Engineering and Biotechnology, Tehran, Iran c Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran d School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran Received 18 July 2010; revised 13 November 2010; accepted 13 December 2010. Available online 17 December 2010. AbstractProtein function is related to its chemical reaction to the surrounding environment including other proteins. On the other hand, this depends on the spatial shape and tertiary structure of protein and folding of its constituent components in space. The correct identification of protein domain fold solely using extracted information from protein sequence is a complicated and controversial task in the current computational biology. In this article a combined classifier based on the information content of extracted features from the primary structure of protein has been introduced to face this challenging problem. In the first stage of our proposed two-tier architecture, there are several classifiers each of which is trained with a different sequence based feature vector. Apart from the application of the predicted secondary structure, hydrophobicity, van der Waals volume, polarity, polarizability, and different dimensions of pseudo-amino acid composition vectors in similar studies, the position specific scoring matrix (PSSM) has also been used to improve the correct classification rate (CCR) in this study. Using K-fold cross validation on training dataset related to 27 famous folds of SCOP, the 28 dimensional probability output vector from each evidence theoretic K-NN classifier is used to determine the information content or expertness of corresponding feature for discrimination in each fold class. In the second stage, the outputs of classifiers for test dataset are fused using Sugeno fuzzy integral operator to make better decision for target fold class. The expertness factor of each classifier in each fold class has been used to calculate the fuzzy integral operator weights. Results make it possible to provide deeper interpretation about the effectiveness of each feature for discrimination in target classes for query proteins. Graphical abstract. Research highlights In this study we use combined classifier for identification of protein domain fold. Information content of extracted features of protein has been introduced to face this problem. We show that position specific scoring matrix improves the correct classification rate. Results provide deeper interpretation about the effectiveness of each feature for discrimination.
Keywords: Sequence based feature; Position specific scoring matrix; Information content; Protein fold classification; Combined classifier
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Feb 14 through Feb 27 by Joshua Phillips
posted Mar 14, 2011 9:33 AM by UCmerced CompBioJournalClub
[
updated Mar 28, 2011 10:48 AM
]

A quality metric for homology modeling: the H-factor
Eric di Luccio1,2 and Patrice Koehl1 
1
Computer
Science Department, Room 4337, Genome Center, GBSF University of
California Davis 451 East Health Sciences Drive Davis, CA 95616, USA
2
School
of Applied Biosciences, Kyungpook National University (KNU), 1370
Sangyeok-dong, Buk-gu, Daegu, 702-701, Republic of Korea
BMC Bioinformatics 2011,
12:48
http://dx.doi.org/10.1186/1471-2105-12-48
|
| Published: |
4 February 2011 |
Abstract
Background
The analysis of protein structures provides fundamental insight into
most biochemical functions and consequently into the cause and possible
treatment of diseases. As the structures of most known proteins cannot
be solved experimentally for technical or sometimes simply for time
constraints, in silico protein structure prediction is
expected to step in and generate a more complete picture of the protein
structure universe. Molecular modeling of protein structures is a fast
growing field and tremendous works have been done since the publication
of the very first model. The growth of modeling techniques and more
specifically of those that rely on the existing experimental knowledge
of protein structures is intimately linked to the developments of high
resolution, experimental techniques such as NMR, X-ray crystallography
and electron microscopy. This strong connection between experimental
and in silico methods is however not devoid of criticisms and concerns among modelers as well as among experimentalists.
Results
In this paper, we focus on homology-modeling and more specifically,
we review how it is perceived by the structural biology community and
what can be done to impress on the experimentalists that it can be a
valuable resource to them. We review the common practices and provide a
set of guidelines for building better models. For that purpose, we
introduce the H-factor, a new indicator for assessing the quality of
homology models, mimicking the R-factor in X-ray crystallography. The
methods for computing the H-factor is fully described and validated on
a series of test cases.
Conclusions
We have developed a web service for computing the H-factor for
models of a protein structure. This service is freely accessible at http://koehllab.genomecenter.ucdavis.edu/toolkit/h-factor webcite. A novel approach to the clustering of microarray data via nonparametric density estimationRiccardo De Bin and Davide Risso  Department of Statistical Sciences, University of Padova, Padova, Italy BMC Bioinformatics 2011,
12:49 http://dx.doi.org/10.1186/1471-2105-12-49 Abstract
Background
Cluster analysis is a crucial tool in several biological and medical
studies dealing with microarray data. Such studies pose challenging
statistical problems due to dimensionality issues, since the number of
variables can be much higher than the number of observations.
Results
Here, we present a general framework to deal with the clustering of
microarray data, based on a three-step procedure: (i) gene filtering;
(ii) dimensionality reduction; (iii) clustering of observations in the
reduced space. Via a nonparametric model-based clustering approach we
obtain promising results both in simulated and real data.
Conclusions
The proposed algorithm is a simple and effective tool for the clustering of microarray data, in an unsupervised setting.

Intercellular Nanotubes Mediate Bacterial Communication
Authors
Cell, Volume 144, Issue 4, 590-600, 18 February 2011
http://dx.doi.org/10.1016/j.cell.2011.01.015
Summary
Bacteria
are known to communicate primarily via secreted extracellular factors.
Here we identify a previously uncharacterized type of bacterial
communication mediated by nanotubes that bridge neighboring cells.
Using Bacillus subtilis as a model organism, we visualized
transfer of cytoplasmic fluorescent molecules between adjacent cells.
Additionally, by coculturing strains harboring different antibiotic
resistance genes, we demonstrated that molecular exchange enables cells
to transiently acquire nonhereditary resistance. Furthermore,
nonconjugative plasmids could be transferred from one cell to another,
thereby conferring hereditary features to recipient cells. Electron
microscopy revealed the existence of variously sized tubular extensions
bridging neighboring cells, serving as a route for exchange of
intracellular molecules. These nanotubes also formed in an interspecies
manner, between B. subtilis and Staphylococcus aureus, and even between B. subtilis and the evolutionary distant bacterium Escherichia coli.
We propose that nanotubes represent a major form of bacterial
communication in nature, providing a network for exchange of cellular
molecules within and between species. Site down at time of composition (links via NCBI-PubMed): Massive genomic rearrangement acquired in a single catastrophic event during cancer development.Stephens PJ, Greenman CD, Fu B, Yang F, Bignell GR, Mudie LJ, Pleasance ED, Lau KW, Beare D, Stebbings LA, McLaren S, Lin ML, McBride DJ, Varela I, Nik-Zainal S, Leroy C, Jia M, Menzies A, Butler AP, Teague JW, Quail MA, Burton J, Swerdlow H, Carter NP, Morsberger LA, Iacobuzio-Donahue C, Follows GA, Green AR, Flanagan AM, Stratton MR, Futreal PA, Campbell PJ. Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. Cell. 2011 Jan 7;144(1):27-40 http://www.ncbi.nlm.nih.gov/sites/entrez/21215367?dopt=Abstract&holding=f1000%2Cf1000mAbstractCancer is driven by
somatically acquired point mutations and chromosomal rearrangements,
conventionally thought to accumulate gradually over time. Using
next-generation sequencing, we characterize a phenomenon, which we term
chromothripsis, whereby tens to hundreds of genomic rearrangements
occur in a one-off cellular crisis. Rearrangements involving one or a
few chromosomes crisscross back and forth across involved regions,
generating frequent oscillations between two copy number states. These
genomic hallmarks are highly improbable if rearrangements accumulate
over time and instead imply that nearly all occur during a single
cellular catastrophe. The stamp of chromothripsis can be seen in at
least 2%-3% of all cancers, across many subtypes, and is present in
∼25% of bone cancers. We find that one, or indeed more than one,
cancer-causing lesion can emerge out of the genomic crisis. This
phenomenon has important implications for the origins of genomic
remodeling and temporal emergence of cancer.
Modeling aqueous solvation with semi-explicit assembly
- Christopher J. Fennella,
- Charles W. Kehoeb, and
- Ken A. Dilla,1
- Author Affiliations
-
aDepartment of Pharmaceutical Chemistry, and
-
bGraduate Group in Bioinformatics, University of California, San Francisco, CA 94143
-
Contributed by Ken A. Dill, December 1, 2010 (sent for review October 1, 2010)
PNAS
February 22, 2011
vol. 108
no. 8
3234-3239
http://dx.doi.org/10.1073/pnas.1017130
Abstract
We
describe a computational solvation model called semi-explicit assembly
(SEA). SEA water captures much of the physics of explicit-solvent
models but with computational speeds approaching those of
implicit-solvent models. We use an explicit-water model to precompute
properties of water solvation shells around simple spheres, then
assemble a solute’s solvation shell by combining the shells of these
spheres. SEA improves upon implicit-solvent models of solvation free
energies by accounting for local solute curvature, accounting for
near-neighbor nonadditivities, and treating water’s dipole as being
asymmetrical with respect to positive or negative solute charges. SEA
does not involve parameter fitting, because parameters come from the
given underlying explicit-solvation model. SEA is about as accurate as
explicit simulations as shown by comparisons against four different
homologous alkyl series, a set of 504 varied solutes, solutes taken
retrospectively from two solvation-prediction events, and a
hypothetical polar-solute series, and SEA is about 100-fold faster than
Poisson–Boltzmann calculations.
Experimental support for the evolution of symmetric protein architecture from a simple peptide motif
- Jihun Lee and
- Michael Blaber1
- Author Affiliations
- Department of Biomedical Sciences, Florida State University, Tallahassee FL 32306-4300
-
Edited* by Brian W. Matthews, University of Oregon, Eugene, OR, and approved November 10, 2010 (received for review October
6, 2010)
Abstract
The
majority of protein architectures exhibit elements of structural
symmetry, and “gene duplication and fusion” is the evolutionary
mechanism generally hypothesized to be responsible for their emergence
from simple peptide motifs. Despite the central importance of the gene
duplication and fusion hypothesis, experimental support for a plausible
evolutionary pathway for a specific protein architecture has yet to be
effectively demonstrated. To address this question, a unique “top-down
symmetric deconstruction” strategy was utilized to successfully
identify a simple peptide motif capable of recapitulating, via gene
duplication and fusion processes, a symmetric protein architecture (the
threefold symmetric β-trefoil fold). The folding properties of
intermediary forms in this deconstruction agree precisely with a
previously proposed “conserved architecture” model for symmetric
protein evolution. Furthermore, a route through foldable sequence-space
between the simple peptide motif and extant protein fold is
demonstrated. These results provide compelling experimental support for
a plausible evolutionary pathway of symmetric protein architecture via
gene duplication and fusion processes.
News lead: Leading the dog of selection by its mutational nose
There
are two simple caricatures of evolutionary dynamics: the phenotypic
caricature focuses on continuous and predictable selection on
variability of quantitative traits, whereas the genotypic caricature
focuses on discrete, stochastic mutations. Although the apparent
contradictions between these pictures were reconciled long ago, our
quantitative understanding of the interplay between them is still
surprisingly primitive. Indeed, even the simplest models of the
dynamics of large asexual populations in which many alleles and many
new mutations contribute to the evolving fitness have resisted
solution. The PNAS paper by Hallatschek
(
1)
is a substantial advance in the development of the mathematical methods needed to analyze these and more complex models.
Referenced article from above article: The noisy edge of traveling waves
- Oskar Hallatschek1
- Author Affiliations
- Biophysics and Evolutionary Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
-
Edited by* Pierre C. Hohenberg, New York University, New York, NY, and approved November 30, 2010 (received for review September
12, 2010)
PNAS
February 1, 2011
vol. 108
no. 5
1783-1787
http://dx.doi.org/10.1073/pnas.1013529108
Abstract
Traveling
waves are ubiquitous in nature and control the speed of many important
dynamical processes, including chemical reactions, epidemic outbreaks,
and biological evolution. Despite their fundamental role in complex
systems, traveling waves remain elusive because they are often
dominated by rare fluctuations in the wave tip, which have defied any
rigorous analysis so far. Here, we show that by adjusting nonlinear
model details, noisy traveling waves can be solved exactly. The moment
equations of these tuned models are closed and have a simple analytical
structure resembling the deterministic approximation supplemented by a
nonlocal cutoff term. The peculiar form of the cutoff shapes the noisy
edge of traveling waves and is critical for the correct prediction of
the wave speed and its fluctuations. Our approach is illustrated and
benchmarked using the example of fitness waves arising in simple models
of microbial evolution, which are highly sensitive to number
fluctuations. We demonstrate explicitly how these models can be tuned
to account for finite population sizes and determine how quickly
populations adapt as a function of population size and mutation rates.
More generally, our method is shown to apply to a broad class of
models, in which number fluctuations are generated by branching
processes. Because of this versatility, the method of model tuning may
serve as a promising route toward unraveling universal properties of
complex discrete particle systems.
Aphid genome expression reveals host–symbiont cooperation in the production of amino acids
- Allison K. Hansen1 and
- Nancy A. Moran
- Author Affiliations
- Department of Ecology and Evolutionary Biology, Yale University, West Haven, CT 06516-7388
-
Edited by Trudy F. C. Mackay, North Carolina State University, Raleigh, NC, and approved January 3, 2011 (received for review
September 8, 2010)
PNAS
February 15, 2011
vol. 108
no. 7
2849-2854
http://dx.doi.org/10.1073/pnas.1013465108
Abstract
The
evolution of intimate symbiosis requires the coordination of gene
expression and content between the distinct partner genomes; this
coordination allows the fusion of capabilities of each organism into a
single integrated metabolism. In aphids, the 10 essential amino acids
are scarce in the phloem sap diet and are supplied by the obligate
bacterial endosymbiont (Buchnera), which lives inside specialized cells called bacteriocytes. Although Buchnera’s
genome encodes most genes for essential amino acid biosynthesis,
several genes in essential amino acid pathways are missing, as are most
genes for production of nonessential amino acids. Additionally, it is
unresolved whether the supply of nitrogen for amino acid biosynthesis
is supplemented by recycling of waste ammonia. We compared pea aphid
gene expression between bacteriocytes and other body tissues using RNA
sequencing and pathway analysis and exploiting the genome sequences
available for both partners. We found that 26 genes underlying amino
acid biosynthesis were up-regulated in bacteriocytes. Seven of these
up-regulated genes fill the gaps of Buchnera’s essential amino acid pathways. In addition, genes underlying five nonessential amino acid pathways lost from Buchnera
are up-regulated in bacteriocytes. Finally, our results reveal that two
genes, glutamine synthetase and glutamate synthase, which potentially
work together in the incorporation of ammonium nitrogen into glutamate
(GOGAT) cycle to assimilate ammonia into glutamate, are up-regulated in
bacteriocytes. Thus, host gene expression and symbiont capabilities are
closely integrated within bacteriocytes, which function as specialized
organs of amino acid production. Furthermore, the GOGAT cycle may be a
key source of nitrogen fueling the integrated amino acid metabolism of
the aphid–Buchnera partnership.
Exercise training increases size of hippocampus and improves memory
- Kirk I. Ericksona,
- Michelle W. Vossb,c,
- Ruchika Shaurya Prakashd,
- Chandramallika Basake,
- Amanda Szabof,
- Laura Chaddockb,c,
- Jennifer S. Kimb,
- Susie Heob,c,
- Heloisa Alvesb,c,
- Siobhan M. Whitef,
- Thomas R. Wojcickif,
- Emily Maileyf,
- Victoria J. Vieiraf,
- Stephen A. Martinf,
- Brandt D. Pencef,
- Jeffrey A. Woodsf,
- Edward McAuleyb,f, and
- Arthur F. Kramerb,c,1
- Author Affiliations
- aDepartment of Psychology, University of Pittsburgh, Pittsburgh, PA 15260;
- bBeckman Institute for Advanced Science and Technology, and
- fDepartment of Kinesiology and Community Health, University of Illinois, Champaign-Urbana, IL 61801;
- cDepartment of Psychology, University of Illinois, Champaign-Urbana, IL 61820;
- dDepartment of Psychology, Ohio State University, Columbus, OH 43210; and
- eDepartment of Psychology, Rice University, Houston, TX 77251
-
Edited* by Fred Gage, Salk Institute, San Diego, CA, and approved December 30, 2010 (received for review October 23, 2010)
PNAS
February 15, 2011
vol. 108
no. 7
3017-3022
http://dx.doi.org/10.1073/pnas.1015950108
Abstract
The
hippocampus shrinks in late adulthood, leading to impaired memory and
increased risk for dementia. Hippocampal and medial temporal lobe
volumes are larger in higher-fit adults, and physical activity training
increases hippocampal perfusion, but the extent to which aerobic
exercise training can modify hippocampal volume in late adulthood
remains unknown. Here we show, in a randomized controlled trial with
120 older adults, that aerobic exercise training increases the size of
the anterior hippocampus, leading to improvements in spatial memory.
Exercise training increased hippocampal volume by 2%, effectively
reversing age-related loss in volume by 1 to 2 y. We also demonstrate
that increased hippocampal volume is associated with greater serum
levels of BDNF, a mediator of neurogenesis in the dentate gyrus.
Hippocampal volume declined in the control group, but higher
preintervention fitness partially attenuated the decline, suggesting
that fitness protects against volume loss. Caudate nucleus and thalamus
volumes were unaffected by the intervention. These theoretically
important findings indicate that aerobic exercise training is effective
at reversing hippocampal volume loss in late adulthood, which is
accompanied by improved memory function.
Opportunity and Means: Horizontal Gene Transfer from the Human Host to a Bacterial Pathogen
The
acquisition and incorporation of genetic material between nonmating
species, or horizontal gene transfer (HGT), has been frequently
described for phylogenetically related organisms, but far less evidence
exists for HGT between highly divergent organisms. Here we report the
identification and characterization of a horizontally transferred
fragment of the human long interspersed nuclear element L1 to the
genome of the strictly human pathogen Neisseria gonorrhoeae. A 685-bp sequence exhibiting 98 to 100% identity to copies of the human L1 element was identified adjacent to the irg4 gene in some N. gonorrhoeae genomes. The L1 fragment was observed in ~11% of the N. gonorrhoeae population sampled but was not detected in Neisseria meningitidis or commensal Neisseria isolates. In addition, N. gonorrhoeae
transcripts containing the L1 sequence were detected by reverse
transcription-PCR, indicating that an L1-derived gene product may be
produced. The high degree of identity between human and gonococcal L1
sequences, together with the absence of L1 sequences from related Neisseria species, indicates that this HGT event occurred relatively recently in evolutionary history. The identification of L1 sequences
in N. gonorrhoeae demonstrates that HGT can occur between a mammalian host and a resident bacterium, which has important implications for the
coevolution of both humans and their associated microorganisms.
Editorial: Devil in the details
- Journal name:
- Nature
- Volume:
-
470,
- Pages:
- 305–306
- Date published:
- (17 February 2011)
- DOI:
- http://dx.doi.org/10.1038/470305b
- Published online
- 16 February 2011
To ensure their results are reproducible, analysts should show their workings.
 Towards the prediction of protein interaction partners using physical dockingMark Nicholas Wass1,2,
Gloria Fuentes1,a,
Carles Pons3,4,
Florencio Pazos5
&
Alfonso Valencia1
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Structural Bioinformatics Group, Centre for Bioinformatics, Imperial College London, London, UK
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
- Computational Bioinformatics, National Institute of Bioinformatics (INB), Barcelona, Spain
- Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain
Molecular Systems Biology 7
Article number: 469 http://dx.doi.org/10.1038/msb.2011.3AbstractDeciphering the whole network of
protein interactions for a given proteome (‘interactome’) is the goal
of many experimental and computational efforts in Systems Biology.
Separately the prediction of the structure of protein complexes by
docking methods is a well-established scientific area. To date, docking
programs have not been used to predict interaction partners. We provide
a proof of principle for such an approach. Using a set of protein
complexes representing known interactors in their unbound form, we show
that a standard docking program can distinguish the true interactors
from a background of 922 non-redundant potential interactors. We
additionally show that true interactions can be distinguished from
non-likely interacting proteins within the same structural family. Our
approach may be put in the context of the proposed ‘funnel-energy
model’; the docking algorithm may not find the native complex, but it
distinguishes binding partners because of the higher probability of
favourable models compared with a collection of non-binders. The
potential exists to develop this proof of principle into new approaches
for predicting interaction partners and reconstructing biological
networks.
GeneticsThe Evolution of Host Specialization in the Vertebrate Gut Symbiont Lactobacillus reuteriSteven A. Frese1, Andrew K. Benson1, Gerald W. Tannock2, Diane M. Loach2, Jaehyoung Kim1, Min Zhang1, Phaik Lyn Oh1, Nicholas C. K. Heng3, Prabhu B. Patil1,4, Nathalie Juge5, Donald A. MacKenzie5, Bruce M. Pearson5, Alla Lapidus6, Eileen Dalin6, Hope Tice6, Eugene Goltsman6, Miriam Land7, Loren Hauser7, Natalia Ivanova6, Nikos C. Kyrpides6, Jens Walter1* 1 Department of Food Science and Technology, University of Nebraska, Lincoln, Nebraska, United States of America, 2 Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand, 3 Sir John Walsh Research Institute (Faculty of Dentistry), University of Otago, Dunedin, New Zealand, 4 Institute of Microbial Technology (IMTECH), Chandigarh, India, 5 Institute of Food Research, Norwich Research Park, Norwich, United Kingdom, 6 Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America, 7 Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1001314
Abstract TopRecent
research has provided mechanistic insight into the important
contributions of the gut microbiota to vertebrate biology, but
questions remain about the evolutionary processes that have shaped this
symbiosis. In the present study, we showed in experiments with
gnotobiotic mice that the evolution of Lactobacillus reuteri
with rodents resulted in the emergence of host specialization. To
identify genomic events marking adaptations to the murine host, we
compared the genome of the rodent isolate L. reuteri 100-23 with that of the human isolate L. reuteri
F275, and we identified hundreds of genes that were specific to each
strain. In order to differentiate true host-specific genome content
from strain-level differences, comparative genome hybridizations were
performed to query 57 L. reuteri strains originating from six
different vertebrate hosts in combination with genome sequence
comparisons of nine strains encompassing five phylogenetic lineages of
the species. This approach revealed that rodent strains, although
showing a high degree of genomic plasticity, possessed a specific
genome inventory that was rare or absent in strains from other
vertebrate hosts. The distinct genome content of L. reuteri
lineages reflected the niche characteristics in the gastrointestinal
tracts of their respective hosts, and inactivation of seven out of
eight representative rodent-specific genes in L. reuteri
100-23 resulted in impaired ecological performance in the gut of mice.
The comparative genomic analyses suggested fundamentally different
trends of genome evolution in rodent and human L. reuteri
populations, with the former possessing a large and adaptable
pan-genome while the latter being subjected to a process of reductive
evolution. In conclusion, this study provided experimental evidence and
a molecular basis for the evolution of host specificity in a vertebrate
gut symbiont, and it identified genomic events that have shaped this
process. Correlated Evolution of Nearby Residues in Drosophilid ProteinsBenjamin Callahan1*, Richard A. Neher2¤, Doris Bachtrog3, Peter Andolfatto4, Boris I. Shraiman2,5 1 Department of Applied Physics, Stanford University, Stanford, California, United States of America, 2
Kavli Institute for Theoretical Physics, University of California Santa
Barbara, Santa Barbara, California, United States of America, 3
Department of Integrative Biology and Center for Theoretical
Evolutionary Genomics, University of California Berkeley, Berkeley,
California, United States of America, 4
Department of Ecology and Evolutionary Biology and the Lewis-Sigler
Institute for Integrative Genomics, Princeton University, Princeton,
New Jersey, United States of America, 5 Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1001315Abstract TopHere
we investigate the correlations between coding sequence substitutions
as a function of their separation along the protein sequence. We
consider both substitutions between the reference genomes of several
Drosophilids as well as polymorphisms in a population sample of
Zimbabwean Drosophila melanogaster. We find that amino acid
substitutions are “clustered” along the protein sequence, that is, the
frequency of additional substitutions is strongly enhanced within ≈10
residues of a first such substitution. No such clustering is observed
for synonymous substitutions, supporting a “correlation length”
associated with selection on proteins as the causative mechanism.
Clustering is stronger between substitutions that arose in the same
lineage than it is between substitutions that arose in different
lineages. We consider several possible origins of clustering,
concluding that epistasis (interactions between amino acids within a
protein that affect function) and positional heterogeneity in the
strength of purifying selection are primarily responsible. The role of
epistasis is directly supported by the tendency of nearby substitutions
that arose on the same lineage to preserve the total charge of the
residues within the correlation length and by the preferential
cosegregation of neighboring derived alleles in our population sample.
We interpret the observed length scale of clustering as a statistical
reflection of the functional locality (or modularity) of proteins:
amino acids that are near each other on the protein backbone are more
likely to contribute to, and collaborate toward, a common subfunction. Computational Biology
Molecular Dynamics Simulations of Forced Unbending of Integrin αVβ3Wei Chen1¤a, Jizhong Lou2¤b, Jen Hsin3, Klaus Schulten3, Stephen C. Harvey2,4, Cheng Zhu1,2,5* 1 Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, 2 Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, United States of America, 3
Department of Physics and Beckman Institute, University of Illinois at
Urbana-Champaign, Urbana, Illinois, United States of America, 4 School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America, 5 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1001086Abstract TopIntegrins
may undergo large conformational changes during activation, but the
dynamic processes and pathways remain poorly understood. We used
molecular dynamics to simulate forced unbending of a complete integrin αVβ3
ectodomain in both unliganded and liganded forms. Pulling the head of
the integrin readily induced changes in the integrin from a bent to an
extended conformation. Pulling at a cyclic RGD ligand bound to the
integrin head also extended the integrin, suggesting that force can
activate integrins. Interactions at the interfaces between the hybrid
and β tail domains and between the hybrid and epidermal growth factor 4
domains formed the major energy barrier along the unbending pathway,
which could be overcome spontaneously in ~1 µs to yield a
partially-extended conformation that tended to rebend. By comparison, a
fully-extended conformation was stable. A newly-formed coordination
between the αV Asp457 and the α-genu metal ion might
contribute to the stability of the fully-extended conformation. These
results reveal the dynamic processes and pathways of integrin
conformational changes with atomic details and provide new insights
into the structural mechanisms of integrin activation. Biology Self-Organization and Regulation of Intrinsically Disordered Proteins with Folded N-TerminiPhilip C. Simister1, Fred Schaper2, Nicola O'Reilly3, Simon McGowan4, Stephan M. Feller1* 1
Cell Signalling Group, Weatherall Institute of Molecular Medicine, John
Radcliffe Hospital, University of Oxford, Oxford, United Kingdom, 2 Department of Systems Biology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany, 3 Peptide Synthesis Laboratory, Cancer Research UK London Research Institute, London, United Kingdom, 4
Computational Biology Research Group, Weatherall Institute of Molecular
Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United
Kingdom http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000591 Summary TopHere
we hypothesize that some proteins use their structured N-terminal
domains (SNTDs) to organize the remaining protein chain by means of
intramolecular interactions, so generating partially condensed
proteins. This model has several attractive features: as the nascent
protein chain emerges from the ribosome, the SNTD folds spontaneously
and then serves as a nucleation point for the yet unstructured amino
acid chain, creating more compact shapes. This reduces the risk of
protein degradation or aggregation. Moreover, an interspersed pattern
of SNTD-docked regions and free loops can coordinate assembly of
sub-complexes in defined loop-sections and enables novel regulatory
mechanisms, for example through posttranslational modifications of
docked regions.
On origin of genetic code and tRNA before translationAndrei S Rodin1,2 , Eörs Szathmáry2,3,4 and Sergei N Rodin2,5  1
Human Genetics Center, School of Public Health, University of Texas, Houston, TX 77225, USA 2
Collegium Budapest (Institute for Advanced Study), Szentháromság u. 2, H-1014 Budapest, Hungary 3
Parmenides Center for the Study of Thinking, Kirchplatz 1, D-82049 Munich/Pullach, Germany 4
Institute of Biology, Eötvös University, 1c Pázmány Péter sétány, H-1117 Budapest, Hungary 5
Department of Molecular and Cellular Biology, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA Biology Direct 2011,
6:14 http://dx.doi.org/10.1186/1745-6150-6-14AbstractBackground
Synthesis of proteins is based on the genetic code - a nearly
universal assignment of codons to amino acids (aas). A major challenge
to the understanding of the origins of this assignment is the
archetypal "key-lock vs. frozen accident" dilemma. Here we re-examine
this dilemma in light of 1) the fundamental veto on "foresight
evolution", 2) modular structures of tRNAs and aminoacyl-tRNA
synthetases, and 3) the updated library of aa-binding sites in RNA
aptamers successfully selected in vitro for eight amino acids.
Results
The aa-binding sites of arginine, isoleucine and tyrosine contain
both their cognate triplets, anticodons and codons. We have noticed
that these cases might be associated with palindrome-dinucleotides. For
example, one-base shift to the left brings arginine codons CGN, with CG
at 1-2 positions, to the respective anticodons NCG, with CG at 2-3
positions. Formally, the concomitant presence of codons and anticodons
is also expected in the reverse situation, with codons containing
palindrome-dinucleotides at their 2-3 positions, and anticodons
exhibiting them at 1-2 positions. A closer analysis reveals that,
surprisingly, RNA binding sites for Arg, Ile and Tyr "prefer" (exactly
as in the actual genetic code) the anticodon(2-3)/codon(1-2) tetramers
to their anticodon(1-2)/codon(2-3) counterparts, despite the seemingly
perfect symmetry of the latter. However, since in vitro selection
of aa-specific RNA aptamers apparently had nothing to do with
translation, this striking preference provides a new strong support to
the notion of the genetic code emerging before translation, in response
to catalytic (and possibly other) needs of ancient RNA life.
Consistently with the pre-translation origin of the code, we propose
here a new model of tRNA origin by the gradual, Fibonacci process-like,
elongation of a tRNA molecule from a primordial coding triplet and
5'DCCA3' quadruplet (D is a base-determinator) to the eventual 76
base-long cloverleaf-shaped molecule.
Conclusion
Taken together, our findings necessarily imply that primordial
tRNAs, tRNA aminoacylating ribozymes, and (later) the translation
machinery in general have been co-evolving to ''fit'' the (likely
already defined) genetic code, rather than the opposite way around.
Coding triplets in this primal pre-translational code were likely
similar to the anticodons, with second and third nucleotides being more
important than the less specific first one. Later, when the code was
expanding in co-evolution with the translation apparatus, the
importance of 2-3 nucleotides of coding triplets "transferred" to the
1-2 nucleotides of their complements, thus distinguishing anticodons
from codons. This evolutionary primacy of anticodons in genetic coding
makes the hypothesis of primal stereo-chemical affinity between amino
acids and cognate triplets, the hypothesis of coding coenzyme handles
for amino acids, the hypothesis of tRNA-like genomic 3' tags suggesting
that tRNAs originated in replication, and the hypothesis of ancient
ribozymes-mediated operational code of tRNA aminoacylation not mutually
contradicting but rather co-existing in harmony.
 High Spontaneous Rate of Gene Duplication in Caenorhabditis elegansAuthors- Hint: Rollover Authors and Affiliations
-
Current Biology, Volume 21, Issue 4, 306-310, 03 February 2011 http://dx.doi.org/10.1016/j.cub.2011.01.026SummaryGene and genome duplications are the primary source
of new genes and novel functions and have played a pivotal role in the
evolution of genomic and organismal complexity [ 1, 2].
The spontaneous rate of gene duplication is a critical parameter for
understanding the evolutionary dynamics of gene duplicates; yet few
direct empirical estimates exist and differ widely. The presence of a
large population of recently derived gene duplicates in sequenced
genomes suggests a high rate of spontaneous origin, also evidenced by
population genomic studies reporting rampant copy-number polymorphism
at the intraspecific level [ 3, 4, 5, 6]. An analysis of long-term mutation accumulation lines of Caenorhabditis elegans
for gene copy-number changes with array comparative genomic
hybridization yields the first direct estimate of the genome-wide rate
of gene duplication in a multicellular eukaryote. The gene duplication
rate in C. elegans is quite high, on the order of 10 −7
duplications/gene/generation. This rate is two orders of magnitude
greater than the spontaneous rate of point mutation per nucleotide site
in this species and also greatly exceeds an earlier estimate derived
from the frequency distribution of extant gene duplicates in the
sequenced C. elegans genome. |
Jan 31 through Feb 13 by David H. Ardell
posted Feb 25, 2011 4:23 PM by UCmerced CompBioJournalClub
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updated Feb 28, 2011 10:55 AM
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Before senescence: the evolutionary demography of ontogenesisAbstractThe age-specific mortality curve for many species, including humans, is U-shaped: mortality declines with age in the developing cohort (ontogenescence) before increasing with age (senescence). The field of evolutionary demography has long focused on understanding the evolution of senescence while largely failing to address the evolution of ontogenescence. The current review is the first to gather the few available hypotheses addressing the evolution of ontogenescence, examine the basis and assumptions of each and ask what the phylogenetic extent of ontogenescence may be. Ontogenescence is among the most widespread of life-history traits, occurring in every population for which I have found sufficiently detailed data, in major groups throughout the eukaryotes, across many causes of death and many life-history types. Hypotheses seeking to explain ontogenescence include those based on kin selection, the acquisition of robustness, heterogeneous frailties and life-history optimization. I propose a further hypothesis, arguing that mortality drops with age because most transitions that could trigger the risks caused by genetic and developmental malfunctions are concentrated in early life. Of these hypotheses, only those that frame ontogenescence as an evolutionary by-product rather than an adaptation can explai
Science 11 February 2011: Vol. 331 no. 6018 pp. 728-729 DOI: 10.1126/science.1197891 On the Future of Genomic Data- Scott D. Kahn
+Author Affiliations - Illumina, 9885 Towne Centre Drive, San Diego, CA 92121, USA.
ABSTRACTMany of the challenges in genomics derive from the informatics needed to store and analyze the raw sequencing data that is available from highly multiplexed sequencing technologies. Because single week-long sequencing runs today can produce as much data as did entire genome centers a few years ago, the need to process terabytes of information has become de rigueur for many labs engaged in genomic research. The availability of deep (and large) genomic data sets raises concerns over information access, data security, and subject/patient privacy that must be addressed for the field to continue its rapid advances.
Changing the Equation on Scientific Data VisualizationABSTRACTAn essential facet of the data deluge is the need for different types of users to apply visualizations to understand how data analyses and queries relate to each other. Unfortunately, visualization too often becomes an end product of scientific analysis, rather than an exploration tool that scientists can use throughout the research life cycle. However, new database technologies, coupled with emerging Web-based technologies, may hold the key to lowering the cost of visualization generation and allow it to become a more integral part of the scientific process. Science 11 February 2011: Vol. 331 no. 6018 pp. 694-695 DOI: 10.1126/science.331.6018.694 NEWSRescue of Old Data Offers Lesson for Particle PhysicistsAccustomed to working in large collaborations and moving swiftly on to bigger, better machines, particle physicists have no standard format for sharing or storing information after an experiment shuts down. Old data can end up scattered across the globe, stored haphazardly on old tapes, or lost entirely. This tendency has prompted some in the field to call for better care to be taken of data after an experiment has finished. For a very small fraction of the experiment's budget, they argue, data could be preserved in a form usable by later generations of physicists. To promote this strategy, researchers from a half-dozen major labs around the world, including CERN, formed a working group in 2009 called Data Preservation in High Energy Physics. One of the group's aims is to create the new post of "data archivist," someone within each experimental team who will ensure that information is properly managed.
Genome Sequence of Leuconostoc inhae KCTC 3774, Isolated from Kimchi  Dae-Soo Kim,1, Sang-Haeng Choi,1, Dong-Wook Kim,1 Ryong Nam Kim,1Seong-Hyeuk Nam,1 Aram Kang,1,2 Aeri Kim,1,2 and Hong-Seog Park1,2*Genome Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 111 Gwahangno, Yuseong-gu, Daejeon 305-806, Republic of Korea,1 University of Science and Technology (UST), 113 Gwahangno, Yuseong-gu, Daejeon 305-806, Republic of Korea2 Received 1 December 2010/ Accepted 13 December 2010 ABSTRACT Leuconostoc inhae strain KCTC 3774 is a Gram-positive, non-spore-forming,heterofermentative, spherical or lenticular lactic acid bacterium. Here we announce the draft genome sequence of Leuconostoc inhae KCTC 3774, isolated from traditional Korean kimchi, and describe major findings from its annotation. Journal of Bacteriology, March 2011, p. 1183-1190, Vol. 193, No. 5 0021-9193/11/$12.00+0 doi:10.1128/JB.00925-10 Copyright © 2011, American Society for Microbiology. All Rights Reserved.
Complete Genome Sequence of the Metabolically Versatile Plant Growth-Promoting EndophyteVariovorax paradoxus S110 , Jong-In Han,1, * Hong-Kyu Choi,2, Seung-Won Lee,11,3 Paul M. Orwin,4Jina Kim,1 Sarah L. LaRoe,5 Tae-gyu Kim,1 Jennifer O'Neil,5 Jared R. Leadbetter,6 Sang Yup Lee,7 Cheol-Goo Hur,3 Jim C. Spain,8 Galina Ovchinnikova,9 Lynne Goodwin,10 and Cliff Han10Department of Civil and Environmental Engineering, KAIST, Daejeon, Republic of Korea,1 Department of Genetic Engineering, Dong-A University, Busan, Republic of Korea,2 Bioinformatics Research Center, KRIBB, Daejeon, Republic of Korea,3 California State University at San Bernardino, Department of Biology, San Bernardino, California,4 Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 8th St., Troy, New York,5Divisions of Biology and Environmental Science and Engineering, California Institute of Technology, Pasadena, California,6 Department of Chemical and Biomolecular Engineering, KAIST, Daejeon, Republic of Korea,7 School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia,8 DOE Joint Genome Institute, Walnut Creek, California,9 Los Alamos National Laboratory, Los Alamos, New Mexico,10 Department of Agricultural Bio-Resources, Genomics Division, National Academy of Agricultural Science, Suwon, Republic of Korea,11 Received 7 August 2010/ Accepted 11 November 2010 Variovorax paradoxus is a microorganism of special interest due to its diverse metabolic capabilities, including the biodegradation of both biogenic compounds and anthropogenic contaminants. V. paradoxus also engages in mutually beneficial interactions with both bacteria and plants. The complete genome sequence of V. paradoxus S110 is composed of 6,754,997 bp with 6,279 predicted protein-coding sequences within two circular chromosomes. Genomicanalysis has revealed multiple metabolic features for autotrophic and heterotrophic lifestyles. These metabolic diversities enable independent survival, as well as a symbiotic lifestyle. Consequently, S110 appears to have evolved into a superbly adaptable microorganism that is able to survive in ever-changing environmental conditions. Based on our findings, we suggest V. paradoxus S110 as a potential candidate for agrobiotechnological applications, such as biofertilizer and biopesticide. Because it has many associations with other biota, it is also suited to serve as an additional model system for studies of microbe-plant and microbe-microbe interactions.
The latest articles from Biology Direct, published between 27-Jan-2011 and 09-Feb-2011Discovery notesEvolutionary patterns of phosphorylated serinesYerbol Z Kurmangaliyev1,2 , Alexander Goland1 and Mikhail S Gelfand1,3  1 Institute for Information Transmission Problems (the Kharkevich Institute) RAS, Bolshoi Karetny pereulok 19, Moscow, 127994, Russia 2 National Center for Biotechnology of the Republic of Kazakhstan, Valikhanov str., 13/1, Astana, 010000, Republic of Kazakhstan 3 Faculty of Bioengineering and Bioinformatics, Moscow State University, Vorobievy Gory 1-73, Moscow, 119991, Russia author email corresponding author email
Biology Direct 2011, 6:8doi:10.1186/1745-6150-6-8 | | Published: | 9 February 2011 |
AbstractPosttranslationally modified amino acids are chemically distinct types of amino acids and in terms of evolution they might behave differently from their non-modified counterparts. In order to check this possibility, we reconstructed the evolutionary history of phosphorylated serines in several groups of organisms. Comparisons of substitution vectors have revealed some significant differences in the evolution of modified and corresponding non-modified amino acids. In particular, phosphoserines are more frequently substituted to aspartate and glutamate, compared to non-phosphorylated serines. Abstract (provisional)BackgroundGenome degradation is an ongoing process in all members of the Rickettsiales order, which makes these bacterial species an excellent model for studying reductive evolution through interspecies variation in genome size and gene content. In this study, we evaluated the degree to which gene loss shaped the content of some Rickettsiales genomes. We shed light on the role played by horizontal gene transfers in the genome evolution of Rickettsiales. ResultsOur phylogenomic tree, based on whole-genome content, presented a topology distinct from that of the whole core gene concatenated phylogenetic tree, suggesting that the gene repertoires involved have different evolutionary histories. Indeed, we present evidence for 3 possible horizontal gene transfer events from various organisms to Orientia and 6 to Rickettsia spp., while we also identified 3 possible horizontal gene transfer events from Rickettsia and Orientia to other bacteria. We found 17 putative genes in Rickettsia spp. that are probably the result of de novo gene creation; 2 of these genes appear to be functional. On the basis of these results, we were able to reconstruct the gene repertoires of "proto-Rickettsiales" and "proto-Rickettsiaceae", which correspond to the ancestors of Rickettsiales and Rickettsiaceae, respectively. Finally, we found that 2,135 genes were lost during the evolution of the Rickettsiaceae to an intracellular lifestyle. ConclusionsOur phylogenetic analysis allowed us to track the gene gain and loss events occurring in bacterial genomes during their evolution from a free-living to an intracellular lifestyle. We have shown that the primary mechanism of evolution and specialization in strictly intracellular bacteria is gene loss. Despite the intracellular habitat, we found several horizontal gene transfers between Rickettsiales species and various prokaryotic, viral and eukaryotic species. Open peer review: Reviewed by Arcady Mushegian, Eugene V. Koonin and Patrick Forterre. For the full reviews please go to the Reviewers' comments section.
OpinionThe Multiple Personalities of Watson and Crick StrandsReed A Cartwright and Dan Graur  Biology Direct 2011, 6:7doi:10.1186/1745-6150-6-7 | | Published: | 8 February 2011 |
Abstract (provisional)BackgroundIn genetics it is customary to refer to double-stranded DNA as containing a 'Watson strand' and a 'Crick strand.' However, there seems to be no consensus in the literature on the exact meaning of these two terms, and the many usages contradict one another as well as the original definition. Here, we review the history of the terminology and suggest retaining a single sense that is currently the most useful and consistent. Proposal: The Saccharomyces Genome Database defines the Watson strand as the strand which has its 5'-end at the short-arm telomere and the Crick strand as its complement. The Watson strand is always used as the reference strand in their database. Using this as the basis of our standard, we recommend that Watson and Crick strand terminology only be used in the context of genomics. When possible, the centromere or other genomic feature should be used as a reference point, dividing the chromosome into two arms of unequal lengths. Under our proposal, the Watson strand is standardized as the strand whose 5'-end is on the short arm of the chromosome, and the Crick strand as the one whose 5'-end is on the long arm. Furthermore, the Watson strand should be retained as the reference (plus) strand in a genomic database. This usage not only makes the determination of Watson and Crick unambiguous but also allows unambiguous selection of reference stands for genomics. Reviewers: This article was reviewed by John M. Logsdon, Igor B. Rogozin (nominated by Andrey Rzhetsky), and William Martin. Mechanism for the Alteration of the Substrate Specificities of Template-Independent RNA Polymerases To view the full text, please login as a subscribed user or purchase a subscription. Click here to view the full text on ScienceDirect. Structure, Volume 19, Issue 2, 232-243, 9 February 2011 Copyright © 2011 Elsevier Ltd All rights reserved. 10.1016/j.str.2010.12.006 Authors- Highlights
- Crystal structure of eubacterial polyA polymerase and its complex with ATP
- The size and shape of the nucleobase interacting pocket are suitable for only ATP
- The RNA-binding and catalytic domains together dictate the substrate specificity of polyA polymerase
- The mechanism of ATP selection by polyA polymerase is distinct from that by the CCA-adding enzyme
SummaryPolyA polymerase (PAP) adds a polyA tail onto the 3′-end of RNAs without a nucleic acid template, using adenosine-5′-triphosphate (ATP) as a substrate. The mechanism for the substrate selection by eubacterial PAP remains obscure. Structural and biochemical studies of Escherichia coli PAP (EcPAP) revealed that the shape and size of the nucleobase-interacting pocket of EcPAP are maintained by an intra-molecular hydrogen-network, making it suitable for the accommodation of only ATP, using a single amino acid, Arg197. The pocket structure is sustained by interactions between the catalytic domain and the RNA-binding domain. EcPAP has a flexible basic C-terminal region that contributes to optimal RNA translocation for processive adenosine 5′-monophosphate (AMP) incorporations onto the 3′-end of RNAs. A comparison of the EcPAP structure with those of other template-independent RNA polymerases suggests that structural changes of domain(s) outside the conserved catalytic core domain altered the substrate specificities of the template-independent RNA polymerases.
Genome and transcriptome analyses of the mountain pine beetle-fungal symbiontGrosmannia clavigera, a lodgepole pine pathogen- Scott DiGuistinia,
- Ye Wanga,
- Nancy Y. Liaob,
- Greg Taylorb,
- Philippe Tanguayc,
- Nicolas Feaud,
- Bernard Henrissate,
- Simon K. Chanb,
- Uljana Hesse-Orcea,
- Sepideh Massoumi Alamoutia,
- Clement K. M. Tsuif,
- Roderick T. Dockingb,
- Anthony Levasseurg,
- Sajeet Haridasa,
- Gordon Robertsonb,
- Inanc Birolb,
- Robert A. Holtb,
- Marco A. Marrab,
- Richard C. Hamelinc,
- Martin Hirstb,
- Steven J. M. Jonesb,
- Jörg Bohlmannf,h,1, and
- Colette Breuila,1
+Author Affiliations - aDepartment of Wood Science,
- fDepartment of Forest Science, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
- bBritish Columbia Cancer Agency Genome Sciences Centre, Vancouver, BC, Canada V5Z 4E6;
- cNatural Resources Canada, Ste-Foy, QC, Canada G1V 4C7;
- dUnité Mixte de Recherche 1202, Institut National de la Recherche Agronomique-Université Bordeaux I, Biodiversité, Gènes et Communautés, Institut National de la Recherche Agronomique Bordeaux-Aquitaine, 33612 Cestas Cedex, France;
- eArchitecture et Fonction des Macromolécules Biologiques, Unité Mixte de Recherche-6098, Centre National de la Recherche Scientifique, Universités Aix-Marseille I & II, 13288 Marseille cedex 9, France;
- gBiotechnologie des Champignons Filamenteux, Unité Mixte de Recherche-1161, Institut National de la Recherche, Universités de Provence et de la Méditerranée, 13288 Marseille cedex 09, France; and
- hMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada V6T 1Z3
Edited by Rodney B. Croteau, Washington State University, Pullman, WA, and approved December 27, 2010 (received for review August 2, 2010)
AbstractIn western North America, the current outbreak of the mountain pine beetle (MPB) and its microbial associates has destroyed wide areas of lodgepole pine forest, including more than 16 million hectares in British Columbia. Grosmannia clavigera (Gc), a critical component of the outbreak, is a symbiont of the MPB and a pathogen of pine trees. To better understand the interactions between Gc, MPB, and lodgepole pine hosts, we sequenced the ∼30-Mb Gc genome and assembled it into 18 supercontigs. We predict 8,314 protein-coding genes, and support the gene models with proteome, expressed sequence tag, and RNA-seq data. We establish that Gc is heterothallic, and report evidence for repeat-induced point mutation. We report insights, from genome and transcriptome analyses, into how Gc tolerates conifer-defense chemicals, including oleoresin terpenoids, as they colonize a host tree. RNA-seq data indicate that terpenoids induce a substantial antimicrobial stress in Gc, and suggest that the fungus may detoxify these chemicals by using them as a carbon source. Terpenoid treatment strongly activated a ∼100-kb region of the Gc genome that contains a set of genes that may be important for detoxification of these host-defense chemicals. This work is a major step toward understanding the biological interactions between the tripartite MPB/fungus/forest system.
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 **************************Announcement**************************
NAR Synthetic Biology Open Access Special Issue
A new open access special issue of NAR on Synthetic Biology is now available to read
online: here. Edited by James J. Collins, Drew Endy, Clyde A. Hutchison III,
and Richard J. Roberts, it details the many advances made in this dynamic area -
including those at the intersections of chemistry, physics, biology and engineering.
**************************Announcement**************************
Nucleic Acids Research Table of Contents Alert - A new issue of Nucleic Acids Research is available online:
- Vol. 39, No. 3
- The below Table of Contents is available online at: http://nar.oxfordjournals.org/content/vol39/issue3/index.dtl
Investigating the predictability of essential genes across distantly related organisms using an integrative approach- Jingyuan Deng1,2,
- Lei Deng1,3,
- Shengchang Su4,
- Minlu Zhang5,
- Xiaodong Lin6,
- Lan Wei7,
- Ali A. Minai3,
- Daniel J. Hassett4 and
- Long J. Lu1,2,5,8,*
+Author Affiliations - 1Division of Biomedical Informatics, Cincinnati Children’s Hospital Research Foundation, Cincinnati, OH 45229, 2Department of Biomedical Engineering, 3Department of Electrical and Computer Engineering, 4Department of Molecular Genetics, Biochemistry and Microbiology, 5Department of Computer Science, University of Cincinnati, Cincinnati, OH 45229, 6Department of Management Science and Information Systems, Rutgers University, Piscataway, NJ 08854, 7School of Medicine, Yale University, New Haven, CT 06511 and 8Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45229, USA
- *To whom correspondence should be addressed. Tel: +1 513 636 8720; Fax: +1 513 636 2056; Email: long.lu@cchmc.org
- Received May 28, 2010.
- Revision received August 15, 2010.
- Accepted August 18, 2010.
AbstractRapid and accurate identification of new essential genes in under-studied microorganisms will significantly improve our understanding of how a cell works and the ability to re-engineer microorganisms. However, predicting essential genes across distantly related organisms remains a challenge. Here, we present a machine learning-based integrative approach that reliably transfers essential gene annotations between distantly related bacteria. We focused on four bacterial species that have well-characterized essential genes, and tested the transferability between three pairs among them. For each pair, we trained our classifier to learn traits associated with essential genes in one organism, and applied it to make predictions in the other. The predictions were then evaluated by examining the agreements with the known essential genes in the target organism. Ten-fold cross-validation in the same organism yielded AUC scores between 0.86 and 0.93. Cross-organism predictions yielded AUC scores between 0.69 and 0.89. The transferability is likely affected by growth conditions, quality of the training data set and the evolutionary distance. We are thus the first to report that gene essentiality can be reliably predicted using features trained and tested in a distantly related organism. Our approach proves more robust and portable than existing approaches, significantly extending our ability to predict essential genes beyond orthologs.
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C-terminal domain of archaeal O-phosphoseryl-tRNA kinase displays large-scale motion to bind the 7-bp D-stem of archaeal tRNASec- R. Lynn Sherrer1,
- Yuhei Araiso2,3,
- Caroline Aldag1,
- Ryuichiro Ishitani2,
- Joanne M. L. Ho1,
- Dieter Söll1,4,* and
- Osamu Nureki2,3,*
+Author Affiliations - 1Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520-8114, USA, 2Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, 3Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawa 226-8501, Japan and 4Department of Chemistry, Yale University, New Haven, Connecticut 06520-8114, USA
- *To whom correspondence should be addressed. Tel: +81 3 5841 4392; Fax: +81 3 5841 8057; Email: nureki@ims.u-tokyo.ac.jp
- Correspondence may also be addressed to Dieter Söll. Tel: +1 203 432 6200; Fax: +1 203 432 6202; Email: dieter.Soll@yale.edu
- Received August 17, 2010.
- Revision received September 6, 2010.
- Accepted September 8, 2010.
AbstractO-Phosphoseryl-tRNA kinase (PSTK) is the key enzyme in recruiting selenocysteine (Sec) to the genetic code of archaea and eukaryotes. The enzyme phosphorylates Ser-tRNASec to produceO-phosphoseryl-tRNASec (Sep-tRNASec) that is then converted to Sec-tRNASec by Sep-tRNA:Sec-tRNA synthase. Earlier we reported the structure of the Methanocaldococcus jannaschii PSTK (MjPSTK) complexed with AMPPNP. This study presents the crystal structure (at 2.4-Å resolution) of MjPSTK complexed with an anticodon-stem/loop truncated tRNASec(Mj*tRNASec), a good enzyme substrate. Mj*tRNASec is bound between the enzyme’s C-terminal domain (CTD) and N-terminal kinase domain (NTD) that are connected by a flexible 11 amino acid linker. Upon Mj*tRNASec recognition the CTD undergoes a 62-Å movement to allow proper binding of the 7-bp D-stem. This large reorganization of the PSTK quaternary structure likely provides a means by which the unique tRNASec species can be accurately recognized with high affinity by the translation machinery. However, while the NTD recognizes the tRNA acceptor helix, shortened versions of MjPSTK (representing only 60% of the original size, in which the entire CTD, linker loop and an adjacent NTD helix are missing) are still activein vivo and in vitro, albeit with reduced activity compared to the full-length enzyme.
 RNA Table of Contents Alert A new issue of RNA is available online:1 March 2011; Vol. 17, No. 3
The below Table of Contents is available online at: http://rnajournal.cshlp.org/content/vol17/issue3/?etoc
Proofreading and spellchecking: A two-tier strategy for pre-mRNA splicing quality control- Defne E. Egecioglu1,2 and
- Guillaume Chanfreau1,2
+Author Affiliations - 1Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, California 90095-1569, USA
- 2Molecular Biology Institute, University of California Los Angeles, Los Angeles, California 90095-1569, USA
AbstractMulti-tier strategies exist in many biochemical processes to ensure a maximal fidelity of the reactions. In this review, we focus on the two-tier quality control strategy that ensures the quality of the products of the pre-mRNA splicing reactions catalyzed by the spliceosome. The first step in the quality control process relies on kinetic proofreading mechanisms that are internal to the spliceosome and that are performed by ATP-dependent RNA helicases. The second quality control step, spellchecking, involves recognition of unspliced pre-mRNAs or aberrantly spliced mRNAs that have escaped the first proofreading mechanisms, and subsequent degradation of these molecules by degradative enzymes in the nucleus or in the cytoplasm. This two-tier quality control strategy highlights a need for high fidelity and a requirement for degradative activities that eliminate defective molecules. The presence of multiple quality control activities during splicing underscores the importance of this process in the expression of genetic information. Identification of compounds that decrease the fidelity of start codon recognition by the eukaryotic translational machinery- Julie E. Takacs1,
- Timothy B. Neary1,
- Nicholas T. Ingolia2,3,4,
- Adesh K. Saini5,
- Pilar Martin-Marcos5,
- Jerry Pelletier6,
- Alan G. Hinnebusch5 and
- Jon R. Lorsch1
+Author Affiliations - 1Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
- 2Department of Cellular and Molecular Pharmacology and Howard Hughes Medical Institute, University of California, San Francisco, California 94158, USA
- 3California Institute for Quantitative Biosciences, San Francisco, California 94158, USA
- 4Department of Embryology, Carnegie Institution, Baltimore, Maryland 21218, USA
- 5Laboratory of Gene Regulation and Development, Eunice Kennedy Shriver Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892, USA
- 6Department of Biochemistry and McGill Cancer Center, McGill University, Montreal, Quebec H3G 1Y6, Canada
AbstractTranslation initiation in eukaryotes involves more than a dozen protein factors. Alterations in six factors have been found to reduce the fidelity of start codon recognition by the ribosomal preinitiation complex in yeast, a phenotype referred to as Sui−. No small molecules are known that affect the fidelity of start codon recognition. Such compounds would be useful tools for probing the molecular mechanics of translation initiation and its regulation. To find compounds with this effect, we set up a high-throughput screen using a dual luciferase assay in S. cerevisiae. Screening of over 55,000 compounds revealed two structurally related molecules that decrease the fidelity of start codon selection by approximately twofold in the dual luciferase assay. This effect was confirmed using additional in vivo assays that monitor translation from non-AUG start codons. Both compounds increase translation of a natural upstream open reading frame previously shown to initiate translation at a UUG. The compounds were also found to exacerbate increased use of UUG as a start codon (Sui− phenotype) conferred by haploinsufficiency of wild-type eukaryotic initiation factor (eIF) 1, or by mutation in eIF1. Furthermore, the effects of the compounds are suppressed by overexpressing eIF1, which is known to restore the fidelity of start codon selection in strains harboring Sui− mutations in various other initiation factors. Together, these data strongly suggest that the compounds affect the translational machinery itself to reduce the accuracy of selecting AUG as the start codon. Distinct regulatory programs establish widespread sex-specific alternative splicing in Drosophila melanogaster- Britta Hartmann1,2,3,
- Robert Castelo2,4,
- Belén Miñana1,2,
- Erin Peden5,
- Marco Blanchette6,8,
- Donald C. Rio6,
- Ravinder Singh5 and
- Juan Valcárcel7
+Author Affiliations - 1Centre de Regulació Genòmica, Dr. Aiguader 88, 08003 Barcelona, Spain
- 2Universitat Pompeu Fabra, Dr. Aiguader 88, 08003 Barcelona, Spain
- 3Centre for Biological Signalling Studies (BIOSS), Albert-Ludwigs-Universitaät, Habsburgerstrasse 49, 79104 Freiburg, Germany
- 4Institut Municipal d'Investigació Mèdica, Dr. Aiguader 88, 08003 Barcelona, Spain
- 5Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, Colorado 80309, USA
- 6Department of Molecular and Cell Biology, University of California at Berkeley, California 94720-3204, USA
- 7Institució Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain
AbstractIn Drosophila melanogaster, female-specific expression of Sex-lethal (SXL) and Transformer (TRA) proteins controls sex-specific alternative splicing and/or translation of a handful of regulatory genes responsible for sexual differentiation and behavior. Recent findings in 2009 by Telonis-Scott et al. document widespread sex-biased alternative splicing in fruitflies, including instances of tissue-restricted sex-specific splicing. Here we report results arguing that some of these novel sex-specific splicing events are regulated by mechanisms distinct from those established by female-specific expression of SXL and TRA. Bioinformatic analysis of SXL/TRA binding sites, experimental analysis of sex-specific splicing in S2 and Kc cells lines and of the effects of SXL knockdown in Kc cells indicate that SXL-dependent and SXL-independent regulatory mechanisms coexist within the same cell. Additional determinants of sex-specific splicing can be provided by sex-specific differences in the expression of RNA binding proteins, including Hrp40/Squid. We report that sex-specific alternative splicing of the gene hrp40/squid leads to sex-specific differences in the levels of this hnRNP protein. The significant overlap between sex-regulated alternative splicing changes and those induced by knockdown of hrp40/squidand the presence of related sequence motifs enriched near subsets of Hrp40/Squid-regulated and sex-regulated splice sites indicate that this protein contributes to sex-specific splicing regulation. A significant fraction of sex-specific splicing differences are absent in germline-less tudor mutant flies. Intriguingly, these include alternative splicing events that are differentially spliced in tissues distant from the germline. Collectively, our results reveal that distinct genetic programs control widespread sex-specific splicing in Drosophila melanogaster.
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Proc Natl Acad Sci U S A. 2010 Nov 16;107(46):19820-5. Epub 2010 Nov 1. Stochastic reaction-diffusion kinetics in the microscopic limit.Fange D, Berg OG, Sjöberg P, Elf J. Department of Cell and Molecular Biology, Uppsala University, 75124 Uppsala, Sweden. AbstractQuantitative analysis of biochemical networks often requires consideration of both spatial and stochastic aspects of chemical processes. Despite significant progress in the field, it is still computationally prohibitive to simulate systems involving many reactants or complex geometries using a microscopic framework that includes the finest length and time scales of diffusion-limited molecular interactions. For this reason, spatially or temporally discretized simulations schemes are commonly used when modeling intracellular reaction networks. The challenge in defining such coarse-grained models is to calculate the correct probabilities of reaction given the microscopic parameters and the uncertainty in the molecular positions introduced by the spatial or temporal discretization. In this paper we have solved this problem for the spatially discretized Reaction-Diffusion Master Equation; this enables a seamless and physically consistent transition from the microscopic to the macroscopic frameworks of reaction-diffusion kinetics. We exemplify the use of the methods by showing that a phosphorylation-dephosphorylation mot f, commonly observed in eukaryotic signaling pathways, is predicted to display fluctuations that depend on the geometry of the system.
Proc Natl Acad Sci U S A. 2010 Apr 13;107(15):6946-51. Epub 2010 Mar 24. Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate.Silverman SJ, Petti AA, Slavov N, Parsons L, Briehof R, Thiberge SY, Zenklusen D, Gandhi SJ, Larson DR, Singer RH, Botstein D. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA. AbstractOscillations in patterns of expression of a large fraction of yeast genes are associated with the "metabolic cycle," usually seen only in prestarved, continuous cultures of yeast. We used FISH of mRNA in individual cells to test the hypothesis that these oscillations happen in single cells drawn from unsynchronized cultures growing exponentially in chemostats. Gene-expression data from synchronized cultures were used to predict coincident appearance of mRNAs from pairs of genes in the unsynchronized cells. Quantitative analysis of the FISH results shows that individual unsynchronized cells growing slowly because of glucose limitation or phosphate limitation show the predicted oscillations. We conclude that the yeast metabolic cycle is an intrinsic property of yeast metabolism and does not depend on either synchronization or external limitation of growth by the carbon source.
Proc Natl Acad Sci U S A. 2008 Dec 30;105(52):20705-10. Epub 2008 Dec 19. Determination of cell fate selection during phage lambda infection.St-Pierre F, Endy D. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. AbstractBacteriophage lambda infection of Escherichia coli can result in distinct cell fate outcomes. For example, some cells lyse whereas others survive as lysogens. A quantitative biophysical model of lambda infection supports the hypothesis that spontaneous differences in the timing of individual molecular events during lambda infection leads to variation in the selection of cell fates. Building from this analysis, the lambda lysis-lysogeny decision now serves as a paradigm for how intrinsic molecular noise can influence cellular behavior, drive developmental processes, and produce population heterogeneity. Here, we report experimental evidence that warrants reconsidering this framework. By using cell fractioning, plating, and single-cell fluorescent microscopy, we find that physical differences among cells present before infection bias lambda developmental outcomes. Specifically, variation in cell volume at the time of infection can be used to help predict cell fate: a approximately 2-fold increase in cell volume results in a 4- to 5-fold decrease in the probability of lysogeny. Other cell fate decisions now thought to be stochastic might also be determined by pre-existing variation.
OpinionAre low temperature habitats hot spots of microbial evolution driven by viruses? Alexandre M. Anesioa, and Christopher M. Bellasa a Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK Available online 3 December 2010.
There is an increasing body of evidence to show that viruses are important drivers of microbial evolution and that they can store a great deal of the Earth's microbial diversity in their genomes. Examination of microbial diversity in polar regions has revealed a higher than expected diversity of viruses, bacteria and eukaryotic microbes. Further, the few available studies in polar regions reveal that viral control of microbial mortality is important in these habitats. In this opinion article, we argue that strong relationships between viruses and their hosts in a range of polar habitats could be key in explaining why polar regions are in fact hot spots of microbial diversity and evolution. Further, we argue that periodic glaciations, and particularly the Neoproterozoic low-latitude glaciation, known as ‘snowball Earth’, could have been periods of intense diversification in aquatic refuges.
OpinionTime to recognise that mitochondria are bacteria? Mark J. Pallena,  a Centre for Systems Biology, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK Available online 1 December 2010.
The scientific community is comfortable with recognising mitochondria as organelles that happen to be descendants of bacteria. Here, I playfully explore the arguments for and against a phylogenetic fundamentalism that states that mitochondria are bacteria and should be given their own taxonomic family, the Mitochondriaceae. I also explore the consequences of recognizing mitochondria as bacteria for our understanding of the systemic response to trauma and for the prospects of creating transgenic mitochondria.
 Volume 41, Issue 3, 4 February 2011, Pages 247-248
ArticleNascent Peptide in the Ribosome Exit Tunnel Affects Functional Properties of the A-Site of the Peptidyl Transferase Center Haripriya Ramu1, Nora Vázquez-Laslop1, Dorota Klepacki1, Qing Dai2, Joseph Piccirilli3, Ronald Micura4 andAlexander S. Mankin1, ,  1 Center for Pharmaceutical Biotechnology, University of Illinois, Chicago, IL 60607, USA 2 Department of Molecular Genetics and Cell Biology, University of Illinois, Chicago, IL 60607, USA 3 Department of Biochemistry and Molecular Biology and Department of Chemistry, University of Chicago, Chicago, IL 60637, USA 4 Institute of Organic Chemistry and Center for Molecular Biosciences, University of Innsbruck, Innsbruck, Austria Received 4 October 2010; revised 30 October 2010; accepted 11 November 2010. Published: February 3, 2011. Available online 3 February 2011.
SummaryThe ability to monitor the nascent peptide structure and to respond functionally to specific nascent peptide sequences is a fundamental property of the ribosome. An extreme manifestation of such response is nascent peptide-dependent ribosome stalling, involved in the regulation of gene expression. The molecular mechanisms of programmed translation arrest are unclear. By analyzing ribosome stalling at the regulatory cistron of the antibiotic resistance gene ermA, we uncovered a carefully orchestrated cooperation between the ribosomal exit tunnel and the A-site of the peptidyl transferase center (PTC) in halting translation. The presence of an inducing antibiotic and a specific nascent peptide in the exit tunnel abrogate the ability of the PTC to catalyze peptide bond formation with a particular subset of amino acids. The extent of the conferred A-site selectivity is modulated by the C-terminal segment of the nascent peptide, where the third-from-last residue plays a critical role. Graphical AbstractHighlights► In the presence of erythromycin, the ribosome stalls at the 8th codon of ermAL1 ► Stalled ribosome is unable to catalyze peptide bond formation with the 9th amino acid ► The nature of the A-site codon is critical for stalling ► Nascent peptide sequence renders the A-site selective to the nature of aminoacyl-tRNA
ArticleThe Base-Pairing RNA Spot 42 Participates in a Multioutput Feedforward Loop to Help Enact Catabolite Repression inEscherichia coli Chase L. Beisel1, , and Gisela Storz1, ,  1 Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20892-5430, USA Received 13 August 2010; revised 29 October 2010; accepted 1 December 2010. Published: February 3, 2011. Available online 3 February 2011.
SummaryBacteria selectively consume some carbon sources over others through a regulatory mechanism termed catabolite repression. Here, we show that the base-pairing RNA Spot 42 plays a broad role in catabolite repression in Escherichia coli by directly repressing genes involved in central and secondary metabolism, redox balancing, and the consumption of diverse nonpreferred carbon sources. Many of the genes repressed by Spot 42 are transcriptionally activated by the global regulator CRP. Since CRP represses Spot 42, these regulators participate in a specific regulatory circuit called a multioutput feedforward loop. We found that this loop can reduce leaky expression of target genes in the presence of glucose and can maintain repression of target genes under changing nutrient conditions. Our results suggest that base-pairing RNAs in feedforward loops can help shape the steady-state levels and dynamics of gene expression. Graphical AbstractHighlights► Spot 42 regulates the consumption of numerous nonpreferred carbon sources ► Spot 42 participates with CRP in a multioutput coherent feedforward loop ► The loop can reduce the leaky expression of glucose-repressed genes ► The loop can help maintain glucose repression under changing nutrient conditions
PreviewPeptides in the Ribosomal Tunnel Talk Back Daniel N. Wilson1, ,  1 Gene Center and Department for Biochemistry, Center for Protein Science-Munich (CiPS-M), University of Munich, Feodor-Lynen-Strasse 25, D-81377 Munich, Germany Available online 3 February 2011.
| Refers to: |  | Nascent Peptide in the Ribosome Exit Tunnel Affects Functional Properties of the A-Site of the Peptidyl Transferase Center Molecular Cell, Volume 41, Issue 3, 4 February 2011, Pages 321-330, Haripriya Ramu, Nora Vázquez-Laslop, Dorota Klepacki, Qing Dai, Joseph Piccirilli, Ronald Micura, Alexander S. Mankin
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In this issue of Molecular Cell, Ramu et al. demonstrate that nascent peptides located within the ribosomal tunnel can talk back to the peptidyl transferase center to induce translational stalling by restricting the species of aminoacyl-tRNAs that can bind there.
Nascent Peptide in the Ribosome Exit Tunnel Affects Functional Properties of the A-Site of the Peptidyl Transferase Center Original Research Article
Pages 321-330 Haripriya Ramu, Nora Vázquez-Laslop, Dorota Klepacki, Qing Dai, Joseph Piccirilli, Ronald Micura, Alexander S. Mankin
Graphical Abstract
Highlights► In the presence of erythromycin, the ribosome stalls at the 8th codon of ermAL1 ► Stalled ribosome is unable to catalyze peptide bond formation with the 9th amino acid ► The nature of the A-site codon is critical for stalling ► Nascent peptide sequence renders the A-site selective to the nature of aminoacyl-tRNA
| TABLE OF CONTENTS
| February 2011 Volume 18, Issue 2 |
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RNA secondary structure in mutually exclusive splicing pp159 - 168 Yun Yang, Leilei Zhan, Wenjing Zhang, Feng Sun, Wenfeng Wang, Nan Tian, Jingpei Bi, Haitao Wang, Dike Shi, Yajian Jiang, Yaozhou Zhang and Yongfeng Jin doi:10.1038/nsmb.1959 Alternative splicing plays a major role in the generation of functional diversity but the underlying mechanisms remain poorly understood. In a comparative genome analysis of 73 arthropod species, spanning around 420 million years of evolution, Yongfeng and coworkers find built-in intronic elements that lead to mutual exclusive splicing. These elements are species- or clade-specific, but evolutionarily conserved at the secondary structure level. Abstract | Full Text | PDF
|  |  |  | Alternate rRNA secondary structures as regulators of translation pp169 - 176 Shu Feng, Heng Li, Jing Zhao, Konstantin Pervushin, Ky Lowenhaupt, Thomas U Schwartz and Peter Dröge doi:10.1038/nsmb.1962 Understanding the structural dynamics of ribosomal components is key to understanding translation. The Z-DNA– and Z-RNA–binding domain from the human RNA editing enzyme ADAR1-L is now shown to bind to specific regions of ribosomal RNAs affecting translation, suggesting that these regions might at least transiently form Z-RNA structure not observed in crystal structures. Abstract | Full Text | PDF |
NATURE STRUCTURAL & MOLECULAR BIOLOGY | ARTICLE
Dynamic local unfolding in the serpin α-1 antitrypsin provides a mechanism for loop insertion and polymerization- Nature Structural & Molecular Biology
- 18,
- 222–226
- (2011)
- doi:10.1038/nsmb.1976
- Received
- 30 April 2010
- Accepted
- 12 November 2010
- Published online
- 23 January 2011
AbstractThe conformational plasticity of serine protease inhibitors (serpins) underlies both their activities as protease inhibitors and their susceptibility to pathogenic misfolding and aggregation. Here, we structurally characterize a sheet-opened state of the serpin α-1 antitrypsin (α1AT) and show how local unfolding allows functionally essential strand insertion. Mutations in α1AT that cause polymerization-induced serpinopathies map to the labile region, suggesting that the evolution of serpin function required sampling of high risk conformations on a dynamic energy landscape.
Transcriptome-wide sequencing reveals numerous APOBEC1 mRNA-editing targets in transcript 3′ UTRs- Nature Structural & Molecular Biology
- 18,
- 230–236
- (2011)
- doi:10.1038/nsmb.1975
- Received
- 31 August 2010
- Accepted
- 10 November 2010
- Published online
- 23 January 2011
AbstractApolipoprotein B–editing enzyme, catalytic polypeptide-1 (APOBEC1) is a cytidine deaminase initially identified by its activity in converting a specific cytidine (C) to uridine (U) in apolipoprotein B (apoB) mRNA transcripts in the small intestine. Editing results in the translation of a truncated apoB isoform with distinct functions in lipid transport. To address the possibility that APOBEC1 edits additional mRNAs, we developed a transcriptome-wide comparative RNA sequencing (RNA-Seq) screen. We identified and validated 32 previously undescribed mRNA targets of APOBEC1 editing, all of which are located in AU-rich segments of transcript 3′ untranslated regions (3′ UTRs). Further analysis established several characteristic sequence features of editing targets, which were predictive for the identification of additional APOBEC1 substrates. The transcriptomics approach to RNA editing presented here dramatically expands the list of APOBEC1 mRNA editing targets and reveals a novel cellular mechanism for the modification of transcript 3′ UTRs.
Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics- Nature Protocols
- 6,
- 147–157
- (2011)
- doi:10.1038/nprot.2010.192
AbstractMass spectrometry (MS)-based proteomics is increasingly applied in a quantitative format, often based on labeling of samples with stable isotopes that are introduced chemically or metabolically. In the stable isotope labeling by amino acids in cell culture (SILAC) method, two cell populations are cultured in the presence of heavy or light amino acids (typically lysine and/or arginine), one of them is subjected to a perturbation, and then both are combined and processed together. In this study, we describe a different approach—the use of SILAC as an internal or 'spike-in' standard—wherein SILAC is only used to produce heavy labeled reference proteins or proteomes. These are added to the proteomes under investigation after cell lysis and before protein digestion. The actual experiment is therefore completely decoupled from the labeling procedure. Spike-in SILAC is very economical, robust and in principle applicable to all cell- or tissue-based proteomic analyses. Applications range from absolute quantification of single proteins to the quantification of whole proteomes. Spike-in SILAC is especially advantageous when analyzing the proteomes of whole tissues or organisms. The protocol describes the quantitative analysis of a tissue sample relative to super-SILAC spike-in, a mixture of five SILAC-labeled cell lines that accurately represents the tissue. It includes the selection and preparation of the spike-in SILAC standard, the sample preparation procedure, and analysis and evaluation of the results.
 | Article alert |
The latest articles from BMC Genomics, published between 18-Jan-2011 and 31-Jan-2011GC content around splice sites affects splicing through pre-mRNA secondary structuresJing Zhang1 , CC Jay Kuo1 and Liang Chen2  1 Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA 2 Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, California 90089, USA author email corresponding author email
BMC Genomics 2011, 12:90doi:10.1186/1471-2164-12-90 | | Published: | 31 January 2011 |
AbstractBackgroundAlternative splicing increases protein diversity by generating multiple transcript isoforms from a single gene through different combinations of exons or through different selections of splice sites. It has been reported that RNA secondary structures are involved in alternative splicing. Here we perform a genomic study of RNA secondary structures around splice sites in humans (Homo sapiens), mice (Mus musculus), fruit flies (Drosophila melanogaster), and nematodes (Caenorhabditis elegans) to further investigate this phenomenon. ResultsWe observe that GC content around splice sites is closely associated with the splice site usage in multiple species. RNA secondary structure is the possible explanation, because the structural stability difference among alternative splice sites, constitutive splice sites, and skipped splice sites can be explained by the GC content difference. Alternative splice sites tend to be GC-enriched and exhibit more stable RNA secondary structures in all of the considered species. In humans and mice, splice sites of first exons and long exons tend to be GC-enriched and hence form more stable structures, indicating the special role of RNA secondary structures in promoter proximal splicing events and the splicing of long exons. In addition, GC-enriched exon-intron junctions tend to be overrepresented in tissue-specific alternative splice sites, indicating the functional consequence of the GC effect. Compared with regions far from splice sites and decoy splice sites, real splice sites are GC-enriched. We also found that the GC-content effect is much stronger than the nucleotide-order effect to form stable secondary structures. ConclusionAll of these results indicate that GC content is related to splice site usage and it may mediate the splicing process through RNA secondary structures. Population transcriptomics of Drosophila melanogasterfemalesLena Müller1 , Stephan Hutter1 , Rayna Stamboliyska1 , Sarah S Saminadin-Peter1,2 , Wolfgang Stephan1 and John Parsch1  1 Department of Biology II, University of Munich (LMU), 82152 Planegg-Martinsried, Germany 2 Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA author email corresponding author email
BMC Genomics 2011, 12:81doi:10.1186/1471-2164-12-81 | | Published: | 28 January 2011 |
AbstractBackgroundVariation at the level of gene expression is abundant in natural populations and is thought to contribute to the adaptive divergence of populations and species. Gene expression also differs considerably between males and females. Here we report a microarray analysis of gene expression variation among females of 16 Drosophilamelanogaster strains derived from natural populations, including eight strains from the putative ancestral range in sub-Saharan Africa and eight strains from Europe. Gene expression variation among males of the same strains was reported previously. ResultsWe detected relatively low levels of expression polymorphism within populations, but much higher expression divergence between populations. A total of 569 genes showed a significant expression difference between the African and European populations at a false discovery rate of 5%. Genes with significant over-expression in Europe included the insecticide resistance gene Cyp6g1, as well as genes involved in proteolysis and olfaction. Genes with functions in carbohydrate metabolism and vision were significantly over-expressed in the African population. There was little overlap between genes expressed differently between populations in females and males. ConclusionsOur results suggest that adaptive changes in gene expression have accompanied the out-of-Africa migration of D. melanogaster. Comparison of female and male expression data indicates that the vast majority of genes differing in expression between populations do so in only one sex and suggests that most regulatory adaptation has been sex-specific. Conserved generation of short products at piRNA lociPhilipp Berninger1,2 , Lukasz Jaskiewicz1 , Mohsen Khorshid1 and Mihaela Zavolan1  1 Biozentrum, Universität Basel and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland 2 EMBL Grenoble, 6 rue Jules Horowitz, 38042 Grenoble, France author email corresponding author email
BMC Genomics 2011, 12:46doi:10.1186/1471-2164-12-46 | | Published: | 19 January 2011 |
AbstractBackgroundThe piRNA pathway operates in animal germ lines to ensure genome integrity through retrotransposon silencing. The Piwi protein-associated small RNAs (piRNAs) guide Piwi proteins to retrotransposon transcripts, which are degraded and thereby post-transcriptionally silenced through a ping-pong amplification process. Cleavage of the retrotransposon transcript defines at the same time the 5' end of a secondary piRNA that will in turn guide a Piwi protein to a primary piRNA precursor, thereby amplifying primary piRNAs. Although several studies provided evidence that this mechanism is conserved among metazoa, how the process is initiated and what enzymatic activities are responsible for generating the primary and secondary piRNAs are not entirely clear. ResultsHere we analyzed small RNAs from three mammalian species, seeking to gain further insight into the mechanisms responsible for the piRNA amplification loop. We found that in all these species piRNA-directed targeting is accompanied by the generation of short sequences that have a very precisely defined length, 19 nucleotides, and a specific spatial relationship with the guide piRNAs. ConclusionsThis suggests that the processing of the 5' product of piRNA-guided cleavage occurs while the piRNA target is engaged by the Piwi protein. Although they are not stabilized through methylation of their 3' ends, the 19-mers are abundant not only in testes lysates but also in immunoprecipitates of Miwi and Mili proteins. They will enable more accurate identification of piRNA loci in deep sequencing data sets.  | Article alert |
Noise regulation by quorum sensing in low mRNA copy number systemsMarc Weber and Javier Buceta  Computer Simulation and Modelling (Co.S.Mo.) Lab, Parc Científic de Barcelona, C/Baldiri Reixac 10-12, Barcelona 08028, Spain author email corresponding author email
BMC Systems Biology 2011, 5:11doi:10.1186/1752-0509-5-11 | | Published: | 20 January 2011 |
AbstractBackgroundCells must face the ubiquitous presence of noise at the level of signaling molecules. The latter constitutes a major challenge for the regulation of cellular functions including communication processes. In the context of prokaryotic communication, the so-called quorum sensing (QS) mechanism relies on small diffusive molecules that are produced and detected by cells. This poses the intriguing question of how bacteria cope with the fluctuations for setting up a reliable information exchange. ResultsWe present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold. Within that framework we study, both numerically and analytically, the role that diffusion plays in the regulation of the dynamics and the fluctuations of signaling molecules. In addition, we unveil the contribution of different sources of noise, intrinsic and transcriptional, in the QS mechanism. ConclusionsThe interplay between noisy sources and the communication process produces a repertoire of dynamics that depends on the diffusion rate. Importantly, the total noise shows a non-monotonic behavior as a function of the diffusion rate. QS systems seems to avoid values of the diffusion that maximize the total noise. These results point towards the direction that bacteria have adapted their communication mechanisms in order to improve the signal-to-noise ratio.
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New Articles in PLoS Genetics | Published February 10, 2011 |
Correlated Evolution of Nearby Residues in Drosophilid ProteinsBenjamin Callahan1*, Richard A. Neher2¤, Doris Bachtrog3,Peter Andolfatto4, Boris I. Shraiman2,5 1 Department of Applied Physics, Stanford University, Stanford, California, United States of America, 2 Kavli Institute for Theoretical Physics, University of California Santa Barbara, Santa Barbara, California, United States of America, 3 Department of Integrative Biology and Center for Theoretical Evolutionary Genomics, University of California Berkeley, Berkeley, California, United States of America, 4 Department of Ecology and Evolutionary Biology and the Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, 5Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America Abstract TopHere we investigate the correlations between coding sequence substitutions as a function of their separation along the protein sequence. We consider both substitutions between the reference genomes of several Drosophilids as well as polymorphisms in a population sample of Zimbabwean Drosophila melanogaster. We find that amino acid substitutions are “clustered” along the protein sequence, that is, the frequency of additional substitutions is strongly enhanced within ≈10 residues of a first such substitution. No such clustering is observed for synonymous substitutions, supporting a “correlation length” associated with selection on proteins as the causative mechanism. Clustering is stronger between substitutions that arose in the same lineage than it is between substitutions that arose in different lineages. We consider several possible origins of clustering, concluding that epistasis (interactions between amino acids within a protein that affect function) and positional heterogeneity in the strength of purifying selection are primarily responsible. The role of epistasis is directly supported by the tendency of nearby substitutions that arose on the same lineage to preserve the total charge of the residues within the correlation length and by the preferential cosegregation of neighboring derived alleles in our population sample. We interpret the observed length scale of clustering as a statistical reflection of the functional locality (or modularity) of proteins: amino acids that are near each other on the protein backbone are more likely to contribute to, and collaborate toward, a common subfunction.
Epistatic Interaction Maps Relative to Multiple Metabolic PhenotypesEvan S. Snitkin1,2, Daniel Segrè1,3* 1 Program in Bioinformatics, Boston University, Boston, Massachusetts, United States of America, 2 Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America, 3 Department of Biology and Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America Abstract TopAn epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for 1Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.
Pervasive Adaptive Protein Evolution Apparent in Diversity Patterns around Amino Acid Substitutions in Drosophila simulansShmuel Sattath1, Eyal Elyashiv1, Oren Kolodny1, Yosef Rinott2, Guy Sella1* 1 Department of Ecology, Evolution, and Behavior, Hebrew University of Jerusalem, Jerusalem, Israel, 2 Department of Statistics, Hebrew University of Jerusalem, Jerusalem, Israel In Drosophila, multiple lines of evidence converge in suggesting that beneficial substitutions to the genome may be common. All suffer from confounding factors, however, such that the interpretation of the evidence—in particular, conclusions about the rate and strength of beneficial substitutions—remains tentative. Here, we use genome-wide polymorphism data in D. simulans and sequenced genomes of its close relatives to construct a readily interpretable characterization of the effects of positive selection: the shape of average neutral diversity around amino acid substitutions. As expected under recurrent selective sweeps, we find a trough in diversity levels around amino acid but not around synonymous substitutions, a distinctive pattern that is not expected under alternative models. This characterization is richer than previous approaches, which relied on limited summaries of the data (e.g., the slope of a scatter plot), and relates to underlying selection parameters in a straightforward way, allowing us to make more reliable inferences about the prevalence and strength of adaptation. Specifically, we develop a coalescent-based model for the shape of the entire curve and use it to infer adaptive parameters by maximum likelihood. Our inference suggests that ~13% of amino acid substitutions cause selective sweeps. Interestingly, it reveals two classes of beneficial fixations: a minority (approximately 3%) that appears to have had large selective effects and accounts for most of the reduction in diversity, and the remaining 10%, which seem to have had very weak selective effects. These estimates therefore help to reconcile the apparent conflict among previously published estimates of the strength of selection. More generally, our findings provide unequivocal evidence for strongly beneficial substitutions in Drosophila and illustrate how the rapidly accumulating genome-wide data can be leveraged to address enduring questions about the genetic basis of adaptation
Parallel Evolution of a Type IV Secretion System in Radiating Lineages of the Host-Restricted Bacterial Pathogen Bartonella
Philipp Engel1, Walter Salzburger2, Marius Liesch1, Chao-Chin Chang3, Soichi Maruyama4, Christa Lanz5, Alexandra Calteau6, Aurélie Lajus6, Claudine Médigue6, Stephan C. Schuster7, Christoph Dehio1* 1 Focal Area Infection Biology, Biozentrum, University of Basel, Basel, Switzerland,2 Zoological Institute, University of Basel, Basel, Switzerland, 3 College of Veterinary Medicine, National Chung Hsing University, Taichung, Taiwan, 4 Nihon University, Fujisawa, Kanagawa, Japan, 5 Max Planck Institute for Developmental Biology, Tübingen, Germany, 6 Commissariat à l'Energie Atomique (CEA), Direction des Sciences du Vivant, Institut de Génomique, Genoscope and CNRS-UMR 8030, Laboratoire d'Analyse Bioinformatique en Génomique et Métabolisme, Evry, France,7 Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, Pennsylvania, United States of America Adaptive radiation is the rapid origination of multiple species from a single ancestor as the result of concurrent adaptation to disparate environments. This fundamental evolutionary process is considered to be responsible for the genesis of a great portion of the diversity of life. Bacteria have evolved enormous biological diversity by exploiting an exceptional range of environments, yet diversification of bacteria via adaptive radiation has been documented in a few cases only and the underlying molecular mechanisms are largely unknown. Here we show a compelling example of adaptive radiation in pathogenic bacteria and reveal their genetic basis. Our evolutionary genomic analyses of the α-proteobacterial genus Bartonella uncover two parallel adaptive radiations within these host-restricted mammalian pathogens. We identify a horizontally-acquired protein secretion system, which has evolved to target specific bacterial effector proteins into host cells as the evolutionary key innovation triggering these parallel adaptive radiations. We show that the functional versatility and adaptive potential of the VirB type IV secretion system (T4SS), and thereby translocated Bartonella effector proteins (Beps), evolved in parallel in the two lineages prior to their radiations. Independent chromosomal fixation of thevirB operon and consecutive rounds of lineage-specific bep gene duplications followed by their functional diversification characterize these parallel evolutionary trajectories. Whereas most Beps maintained their ancestral domain constitution, strikingly, a novel type of effector protein emerged convergently in both lineages. This resulted in similar arrays of host cell-targeted effector proteins in the two lineages ofBartonella as the basis of their independent radiation. The parallel molecular evolution of the VirB/Bep system displays a striking example of a key innovation involved in independent adaptive processes and the emergence of bacterial pathogens. Furthermore, our study highlights the remarkable evolvability of T4SSs and their effector proteins, explaining their broad application in bacterial interactions with the environment.
The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study
Alexandra C. Nica1,2, Leopold Parts1, Daniel Glass3, James Nisbet1, Amy Barrett4, Magdalena Sekowska1, Mary Travers4, Simon Potter1, Elin Grundberg1,3, Kerrin Small1,3,Åsa K. Hedman4, Veronique Bataille3, Jordana Tzenova Bell3,4, Gabriela Surdulescu3, Antigone S. Dimas2,4,Catherine Ingle1, Frank O. Nestle5, Paola di Meglio5, Josine L. Min4, Alicja Wilk1, Christopher J. Hammond3, Neelam Hassanali4, Tsun-Po Yang1, Stephen B. Montgomery2,Steve O'Rahilly6, Cecilia M. Lindgren4, Krina T. Zondervan4,Nicole Soranzo1,3, Inês Barroso1,6, Richard Durbin1,Kourosh Ahmadi3, Panos Deloukas1*, Mark I. McCarthy4,7,8*, Emmanouil T. Dermitzakis2*, Timothy D. Spector3*, The MuTHER Consortium 1 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom, 2 Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland, 3 Department of Twin Research, King's College London, London, United Kingdom, 4 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom, 5 St. John's Institute of Dermatology, King's College London, London, United Kingdom, 6 University of Cambridge Metabolic Research Labs, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom, 7 Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital, Oxford, United Kingdom, 8 Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role ofcis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis—MCTA) permits immediate replication of eQTLs using co-twins (93%–98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%–20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.
Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during EarlyDrosophila Development
Tommy Kaplan1, Xiao-Yong Li2, Peter J. Sabo3, Sean Thomas3, John A. Stamatoyannopoulos3, Mark D. Biggin4*,Michael B. Eisen1,2,4* 1 Department of Molecular and Cell Biology, California Institute of Quantitative Biosciences, University of California Berkeley, Berkeley, California, United States of America, 2 Howard Hughes Medical Institute, University of California Berkeley, Berkeley, California, United States of America, 3 Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America, 4Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America Abstract TopTranscription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ~0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision.
A Mathematical Framework for Protein Structure ComparisonWei Liu, Anuj Srivastava*, Jinfeng Zhang* Department of Statistics, Florida State University, Tallahassee, Florida, United States of America Abstract TopComparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set.
Accurate Quantification of Functional Analogy among Close HomologsMaria D. Chikina1, Olga G. Troyanskaya2,3* 1 Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America, 2 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, 3 Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America Abstract TopCorrectly evaluating functional similarities among homologous proteins is necessary for accurate transfer of experimental knowledge from one organism to another, and is of particular importance for the development of animal models of human disease. While the fact that sequence similarity implies functional similarity is a fundamental paradigm of molecular biology, sequence comparison does not directly assess the extent to which two proteins participate in the same biological processes, and has limited utility for analyzing families with several parologous members. Nevertheless, we show that it is possible to provide a cross-organism functional similarity measure in an unbiased way through the exclusive use of high-throughput gene-expression data. Our methodology is based on probabilistic cross-species mapping of functionally analogous proteins based on Bayesian integrative analysis of gene expression compendia. We demonstrate that even among closely related genes, our method is able to predict functionally analogous homolog pairs better than relying on sequence comparison alone. We also demonstrate that the landscape of functional similarity is often complex and that definitive “functional orthologs” do not always exist. Even in these cases, our method and the online interface we provide are designed to allow detailed exploration of sources of inferred functional similarity that can be evaluated by the user. New Articles in PLoS Computational BiologyGene Expression Noise in Spatial Patterning: hunchbackPromoter Structure Affects Noise Amplitude and Distribution in Drosophila SegmentationDavid M. Holloway1,2*, Francisco J. P. Lopes3, Luciano da Fontoura Costa4, Bruno A. N. Travençolo4,5, Nina Golyandina6, Konstantin Usevich6, Alexander V. Spirov7 1 Mathematics Department, British Columbia Institute of Technology, Burnaby, British Columbia, Canada, 2 Biology Department, University of Victoria, Victoria, British Columbia, Canada, 3 Instituto de Biofisica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil, 4 Instituto de Fisica de Sao Carlos, Universidade de Sao Paulo, Sao Carlos, Sao Paulo, Brazil, 5 Faculty of Computing, Federal University of Uberlândia, Uberlândia, Brazil, 6 Mathematics and Mechanics Faculty, St. Petersburg State University, St. Petersburg, Russia, 7 Computer Science and Center of Excellence in Wireless and Information Technology, Stony Brook University, Stony Brook, New York, United States of America Abstract Top1Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb14F, and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hbpromoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e.g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.
Structural Properties of the Caenorhabditis elegans Neuronal NetworkLav R. Varshney1, Beth L. Chen2, Eric Paniagua3, David H. Hall4, Dmitri B. Chklovskii5* 1 Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, 2 Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America, 3 California Institute of Technology, Pasadena, California, United States of America, 4 Albert Einstein College of Medicine, Bronx, New York, United States of America, 5 Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, United States of America Abstract TopDespite recent interest in reconstructing neuronal networks, complete wiring diagrams on the level of individual synapses remain scarce and the insights into function they can provide remain unclear. Even forCaenorhabditis elegans, whose neuronal network is relatively small and stereotypical from animal to animal, published wiring diagrams are neither accurate nor complete and self-consistent. Using materials from White et al. and new electron micrographs we assemble whole, self-consistent gap junction and chemical synapse networks of hermaphrodite C. elegans. We propose a method to visualize the wiring diagram, which reflects network signal flow. We calculate statistical and topological properties of the network, such as degree distributions, synaptic multiplicities, and small-world properties, that help in understanding network signal propagation. We identify neurons that may play central roles in information processing, and network motifs that could serve as functional modules of the network. We explore propagation of neuronal activity in response to sensory or artificial stimulation using linear systems theory and find several activity patterns that could serve as substrates of previously described behaviors. Finally, we analyze the interaction between the gap junction and the chemical synapse networks. Since several statistical properties of the C. elegans network, such as multiplicity and motif distributions are similar to those found in mammalian neocortex, they likely point to general principles of neuronal networks. The wiring diagram reported here can help in understanding the mechanistic basis of behavior by generating predictions about future experiments involving genetic perturbations, laser ablations, or monitoring propagation of neuronal activity in response to stimulation.
Stochastic Theory of Early Viral Infection: Continuous versus Burst Production of VirionsJohn E. Pearson1, Paul Krapivsky2, Alan S. Perelson1* 1 Theoretical Biology & Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America, 2 Department of Physics, Boston University, Boston, Massachusetts, United States of America Abstract TopViral production from infected cells can occur continuously or in a burst that generally kills the cell. For HIV infection, both modes of production have been suggested. Standard viral dynamic models formulated as sets of ordinary differential equations can not distinguish between these two modes of viral production, as the predicted dynamics is identical as long as infected cells produce the same total number of virions over their lifespan. Here we show that in stochastic models of viral infection the two modes of viral production yield different early term dynamics. Further, we analytically determine the probability that infections initiated with any number of virions and infected cells reach extinction, the state when both the population of virions and infected cells vanish, and show this too has different solutions for continuous and burst production. We also compute the distributions of times to establish infection as well as the distribution of times to extinction starting from both a single virion as well as from a single infected cell for both modes of virion production.
| Science 4 February 2011: Vol. 331 no. 6017 p. 511 DOI: 10.1126/science.1203356Lessons from GenomicsIn February 2001, Nature and Science provided the first detailed look at the human genome: a string of some 3 billion nucleotides whose unique sequence forms the genetic blueprint for each individual. This momentous occasion made headlines around the world. Now that a decade has elapsed, where has this achievement led us and where are we going with other such ambitious endeavors? Throughout this month in Science, the News and Commentary sections will present viewpoints and analyses of the effects of the genomics revolution on science and society (seehttp://scim.ag/genome10). Many lessons can be derived from the Human Genome Project that should be helpful in guiding other large science projects through their inevitable challenges.* The editors suggest the following Related Resources on Science sitesIn Science MagazineHUMAN GENOME 10TH ANNIVERSARYWaiting for the RevolutionScience 4 February 2011: 526-529. GENOME-SEQUENCING ANNIVERSARYA Celebration of the Genome, Part I- Barbara R. Jasny and
- Laura M. Zahn
Science 4 February 2011: 546.
CELL BIOLOGYA Translational Pause to LocalizeThe unconventional splicing of a messenger RNA (mRNA) is key to a mechanism that controls the cellular response to unfolded proteins that accumulate in the endoplasmic reticulum (ER). Mammalian cells attempt to counterbalance this state of stress by expressing specific genes through the transcription factor XBP1 (1). The synthesis of this transcription factor requires splicing to generate its encoding mRNA, a process that occurs at the cytoplasmic face of the ER membrane. On page 586 of this issue (2), Yanagitani et al. reveal how translational pausing of the mRNA to be spliced contributes to this localization. The finding reveals surprising similarities in mechanisms regulating translation in eukaryotes and prokaryotes. The editors suggest the following Related Resources on Science sitesIn Science MagazineTranslational Pausing Ensures Membrane Targeting and Cytoplasmic Splicing of XBP1u mRNA- Kota Yanagitani,
- Yukio Kimata,
- Hiroshi Kadokura,
- and Kenji Kohno
Science 4 February 2011: 586-589.Published online 13 January 2011
Science 4 February 2011: Vol. 331 no. 6017 pp. 586-589 DOI: 10.1126/science.1197142 Translational Pausing Ensures Membrane Targeting and Cytoplasmic Splicing of XBP1u mRNA- Kota Yanagitani,
- Yukio Kimata,
- Hiroshi Kadokura, and
- Kenji Kohno*
+Author Affiliations - Laboratory of Molecular and Cell Genetics, Graduate School of Biological Sciences, Nara Institute of Science and Technology, 8916-5, Takayama, Ikoma, Nara 630-0192, Japan.
- *To whom correspondence should be addressed. E-mail: kkouno@bs.naist.jp
ABSTRACTUpon endoplasmic reticulum (ER) stress, an endoribonuclease, inositol-requiring enzyme-1α, splices the precursor unspliced form of X-box–binding protein 1 messenger RNA (XBP1u mRNA) on the ER membrane to yield an active transcription factor (XBP1s), leading to the alleviation of the stress. The nascent peptide encoded by XBP1u mRNA drags the mRNA–ribosome–nascent chain (R-RNC) complex to the membrane for efficient cytoplasmic splicing. We found that translation of the XBP1u mRNA was briefly paused to stabilize the R-RNC complex. Mutational analysis of XBP1u revealed an evolutionarily conserved peptide module at the carboxyl terminus that was responsible for the translational pausing and was required for the efficient targeting and splicing of the XBP1u mRNA. Thus, translational pausing may be used for unexpectedly diverse cellular processes in mammalian cells.
 | Article alert |
The latest articles from BMC Bioinformatics, published between 20-Jan-2011 and 02-Feb-2011 |
Research articleInvestigating the effect of paralogs on microarray gene-set analysisAndre J Faure1,2 , Cathal Seoighe1,3 and Nicola J Mulder1  1 Computational Biology Group, Department of Clinical Laboratory Sciences, University of Cape Town, Cape Town, South Africa 2 EMBL-European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK 3 School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Ireland author email corresponding author email
BMC Bioinformatics 2011, 12:29doi:10.1186/1471-2105-12-29 | | Published: | 24 January 2011 |
AbstractBackgroundIn order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. ResultsWe show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http://www.cbio.uct.ac.za/indygene webcite, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. ConclusionsThe Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.
nocoRNAc: Characterization of non-coding RNAs in prokaryotesAlexander Herbig and Kay Nieselt  Center for Bioinformatics Tübingen, University of Tübingen, Sand 14, 72076 Tübingen, Germany author email corresponding author email
BMC Bioinformatics 2011, 12:40doi:10.1186/1471-2105-12-40 | | Published: | 31 January 2011 |
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