WATCH ON CROWDCAST: https://www.crowdcast.io/e/beacon-congress-august

Using digital evolution, our lab is trying to understand the many affects of coevolution on the dynamics of adaptation. I’ll talk about some old and some exciting new work on evolvability, but I’m also interested in understanding what position digital evolution and artificial life have within the boundaries of evolutionary biology. Are these biological, computational, or computational biology experiments?

ZOOM LINK: https://msu.zoom.us/j/99199493856

Meeting ID: 991 9949 3856

Moderator: Louise Mead

Led by Alita Burmeister and Mike Wiser

In 1998, Jane Maienshein observed that “…deploring our lack of scientific literacy has become quite popular recently.” (Science 281, 5379, p 917)

A generation later, the SARS-CoV-2 pandemic highlights our continuing need for a scientifically literate public. In this sandbox session, we will discuss ways to improve scientific literacy while leveraging student interest in (and misconceptions generated by) the COVID-19 pandemic. We’ll brainstorm new learning objectives, assessments, and activities relevant to all fields of STEM. A goal of this session is to generate a list of objectives and approaches that could be ‘dropped’ into existing courses, as well as to discuss longer-term educational solutions for scientific literacy."

ZOOM LINK: https://msu.zoom.us/j/95872257099

Webinar ID: 958 7225 7099

Moderator: Danielle Whittaker

• 1:30 Padmini Rajagopalan: Evolution of Complex Coordinated Behavior. Cooperative tasks such as herding and hunting are common among higher animals in nature. A particularly complex example is that of mobbing by spotted hyenas. Through careful coordination, a large number of spotted hyenas can attack a group of lions and successfully steal a kill from them, even though lions are much bigger and stronger. This behavior is more complex than others that hyenas exhibit, and it appears to be heritable. How such behavioral advance can emerge in evolution is a fascinating question; it is difficult to study in nature, but computational simulations can provide insight. In simulation, hyenas initially evolved different levels of boldness, corresponding to simple behaviors such as solo attack, delayed attack, and delayed approach. These behaviors can be seen as stepping stones in constructing the more complex mobbing behavior in later generations. These results suggest a general stepping-stone-based mechanism through which complex coordinated behaviors can arise in humans and animals. This insight should prove useful in building cognitive architectures and team strategies for artificial agents in the future.

• 1:45 Julie Jarvey: The effect of social rank on the evolution of cooperative hunting. The evolution of cooperative hunting has been a central topic in evolutionary biology. The greater per capita reward is often thought to promote cooperative hunting. However, many animal societies have linear dominance hierarchies where resource access is determined by social rank. One example is the spotted hyena (Crocuta crocuta), where rank is maternally “inherited,” and rewards from cooperative hunting are shared unequally. Despite this inequality, animals in these societies cooperate. Here, we use digital evolution to test how rank influences the evolution of cooperative hunting in an agent-based digital evolution experiment. We created a world using the Modular Agent Based Evolver to reflect the social and hunting dynamics of spotted hyena societies. We found that overall cooperation decreased as the rewards from cooperative hunting became less fair (i.e., increasingly skewed by rank). Among individual agents, the probability of cooperating decreased with relative rank. These results support predictions made from game theoretical models, and provide insight into the mechanisms that may promote cooperation in animal societies structured by dominance hierarchies.

• 2:00 Chris Adami: Know your opponent: the trade-off between cost and information in the evolution of cooperation. The evolution of cooperative behavior in biology is still being treated as somewhat of a mystery. Several "rules" for understanding the evolution of cooperation are known: these rules relate the cost-to-benefit ratio of the behavior to certain other parameters of the theory. Here we suggest that cooperation evolves as long as the participating organism has a minimal amount of information that will allow it to channel costly behaviors towards those individuals that are likely to reciprocate. Such a theory of cooperation would unify the existing theoretical approaches known as kin selection, reciprocal altruism, indirect reciprocity, network reciprocity, as well as group selection. We find empirically that the minimum amount of information necessary to engage in cooperation increases linearly with the cost-to-benefit ratio in the iterated Prisoner's Dilemma, which corroborates an information-theoretic law of cooperation that supersedes the equivalent law derived from the Price equation.

• 2:15 Sarah Albani: Associative Learning across Computational Substrates. Animal behavior suggests that associative learning is a vital evolutionary learning process, as the brain associates new responses with particular stimuli to allow for complex environmental responses. Understanding the evolution of associative learning can therefore allow us to better understand neuroevolution broadly. To study neuroevolution in digital systems, we can draw analogies between biological brains and computational structures: both receive inputs, project outputs, and are able to adapt over time. In fact, the evolution of associative learning has already been demonstrated in at least one digital system. However, gathering more information on how associative learning evolves across multiple digital systems could help us better understand the evolution of artificial intelligence. Here we investigate which specific components within computational structures have a prominent effect on the rate of associative learning. We use the Modular Agent Based Evolver (MABE) framework to investigate how different computational structures (brains) adapt to the same task. Over generations, we analyze the learning curves of each brain and compare them to one another. Our results will then allow us to further investigate the different structural designs of each brain. Each brain’s assets or flaws will give us a deeper look into how to understand the learning of an artificial brain.

• 2:30 Zachary Huang: Honey bee swimming: panicking or adaptive behavior. Honey bees have recently been shown to have a unique swimming behavior (PNAS, https://doi.org/10.1073) upon dropped onto a water surface. What is not known is whether this swimming behavior is simply a "panic response" or is it adaptive behavior. It is possible that bees were simply "panicking" and swimming randomly in different directions. If this is true we would expect bees arrive in all possible directions. We tested this hypothesis and show that bee swimming is adaptive. We dropped honey bee workers to the center of a water bowl (diameter: 21.6 cm) and let the bees swim toward the edge. One piece of paper with a black area was presented to one direction of the bowl. This black area was 72 degrees wide in the 360 degree circle. The black area was moved in all 4 different directions to remove any potential directional preference. We then took digital photographs of each bee when she arrived at the edge of the glass bowl. Degrees were measured by ImageJ software. We found a much higher percentage of bees swam toward the black area than expected if they swam randomly (P<0.01). We therefore conclude that honey bees, when dropped to a water surface, are behaving in an adaptive fashion: that they swim to a darker area, which presumably represents the closest bank of a small pool of water. Because honey bee workers only forage for water at a small percentage, it is possible that this adaptive behavior was selected before queen and worker diverged in evolutionary history. We thus predict that the same behavior should be found in solitary bees, and also present (perhaps stronger) in honey bee queens.

• 2:45 Darren Incorvaia: Colony Size and the Evolution of Spatial Recruitment in Social Insects. Eusocial insects such as ants, bees, and wasps, are some of the most ecologically dominant and economically important organisms on the planet. Living as a colony comes with intense energetic demands, and many social insect species have evolved collective foraging strategies to enable efficient and flexible exploitation of resources in the environment. Some of the best understood of these strategies, such as the dance language of honeybees and the pheromone trails of some ants, involve spatial communication that allows recruits to be led to specific resource locations. This feature, which intuitively seems advantageous, is not ubiquitous across social insects. Here, we use an agent-based model and a phylogenetic comparison to test the hypothesis that colony size is important for the evolution of spatial recruitment in collective foraging strategies, such that it is advantageous only when the colony is large enough. Our results support this hypothesis, with the opportunity cost of recruitment not being effectively counteracted by recruitment in small colonies. This study provides insights into the evolution of communication and foraging strategies in this important animal group.

ZOOM LINK: https://msu.zoom.us/j/99051739212

Webinar ID: 990 5173 9212

Moderator: Emily Dolson

• 1:30 Samuel Chen: A Computational Molecular Evolutionary Approach to Characterize Bacterial Proteins. Molecular evolution and phylogeny can provide key insights into pathogenic protein families. Studying how these proteins evolve across bacteria, can help identify lineage-specific and pathogen-specific signatures and variants, and consequently, their functions. We are building a streamlined computational approach for the molecular evolution and phylogeny of target proteins, widely applicable across protein and pathogen families. We applied this approach to examine the phage shock protein (Psp) system and its evolution across all three domains of life (~6500 genomes within bacteria, archaea, and eukaryota). We are also testing our workflow for Mycobacteria, Staphylococci, and Bacillus anthracis among other pathogens. Our process currently starts with one or more proteins and identifying their homologs from thousands of species, along with their detailed functional characterization including domain architectures, genomic neighborhoods, phyletic spreads, and phylogenetic analyses. Towards this end, we are developing a molecular evolution and phylogeny web-application (for biologists) and R package (for computational biologists). These workflows will automate and streamline the key steps in molecular evolution and phylogeny resulting in more efficient and accurate analyses.

• 1:40 Tanvi Ingle: A Pipeline for Bacterial WGCN Construction and Visualization. For decades, scientists have studied bacterial genomes to identify gene functions through a variety of sequencing and wet lab techniques. Given that this process is often time and resource-intensive, the functions of many genes are not well understood. Weighted Gene Co-expression Networks (WGCNs) offer an alternative method to elucidate possible gene functions by clustering unannotated genes that share expression patterns with well annotated genes. However, constructing these networks can be a complicated and tedious process. To streamline this analysis, we present a pipeline that leverages RNAseq data to construct and annotate WGCNs for a dozen clinically and academically relevant bacteria. In addition, we created a graph visualization Shiny App featuring these WGCNs that allows researchers to visualize subnetworks, gene expression patterns, and intra- and inter-bacterial relationships. This pipeline can be easily adapted to any bacteria, thus supporting the creation of novel, data-driven hypotheses concerning many microbial genes of interest.

• 1: 50 Karn Jongnarangsin: A Pangenome and Comparative Genomics Workflow for Bacteria. Whole-genome comparisons can be performed through the use of pangenomes: a master gene set derived from genomes of numerous related species. Pangenomes identify which genes are conserved across all genomes (core), present in multiple but not necessarily all genomes (accessory), and unique to single species/strains. The presence/absence of genes across genomes can, therefore, be used to study species evolution and diversity, and functional annotation of various bacterial groups. One use case for pangenomes is investigating Mycobacterial species as they have a wide range of associated pathologies in human and animal hosts, e.g., members of the Mycobacterium tuberculosis (MTB) complex are causative agents of tuberculosis, non-tuberculous Mycobacteria (NTM) may cause pulmonary and chronic pathologies in animals and humans. Another use case is investigating Staphylococci, which are notorious for their various antibiotics resistances, horizontal gene transfer capabilities, and enterotoxins similarity, e.g., S. aureus and its resistant strains (MRSA, VRSA, etc.), S. epidermidis and its pathogenicity islands. The process of constructing a pangenome from a large number of complete genomes involves multiple, computationally intensive, intermediary steps, including the annotation of constituent genomes and gene grouping based on feature/function. We are incorporating all these steps in a streamlined pangenome construction workflow to compare Mycobacterial/Staphylococcal pathogenic and nonpathogenic species. The comparative pathogenomics and pangenome workflows that we develop can be easily repurposed to address several critical pathogenesis and host-specificity related questions in any bacterial species of interest.

• 2:00 Kevin Liu: Non-parametric and semi-parametric support estimation using SEquential RESampling random walks on biomolecular sequences. Non-parametric and semi-parametric resampling procedures are widely used to perform support estimation in computational biology and bioinformatics. Among the most widely used methods in this class is the standard bootstrap method, which consists of random sampling with replacement. While not requiring assumptions about any particular parametric model for resampling purposes, the bootstrap and related techniques assume that sites are independent and identically distributed (i.i.d.). The i.i.d. assumption can be an over-simplification for many problems in computational biology and bioinformatics. In particular, sequential dependence within biomolecular sequences is often an essential biological feature due to biochemical function, evolutionary processes such as recombination, and other factors. To relax the simplifying i.i.d. assumption, we propose a new non-parametric/semi-parametric sequential resampling technique that generalizes “Heads-or-Tails” mirrored inputs, a simple but clever technique due to Landan and Graur. The generalized procedure takes the form of random walks along either aligned or unaligned biomolecular sequences. We refer to our new method as the SERES (or “SEquential RESampling”) method. To demonstrate the performance of the new technique, we apply SERES to estimate support for the multiple sequence alignment problem. Using simulated and empirical data, we show that SERES-based support estimation yields comparable or typically better performance compared to state-of-the-art methods.

• 2:10 Lauren Gillespie: Species Prediction Using Phylogenetically-Informed Convolutional Neural Network From High-Resolution Satellite Imagery Data. Predicting species distributions using presence-only data is an open problem in landscape ecology, with most state-of-the-art species distribution models (SDM) relying on automatically-generated negative samples that can be quite brittle to hyperparameter choices. Here instead we propose learning a species representation from high-resolution satellite imagery data using a convolutional neural network. To aid in training the network to predict across over thousands of different species classes, we introduce a novel phylogenetically-informed loss, where both species, genus, and family are classified for each training example.

• 2:20 Clifford Bohm: Introducing Soft-Wired Neuron Brains. Soft-wired neuron (SWN) brains are a new form of digital cognitive architecture that combine features of Markov Brains and ANNs. SWNs are collections of highly capable neuron-like logic units with interconnectivity determined using a tag based system which allows connections to slowly migrate over evolutionary timescales. This talk will introduce SWNs in addition to exploring possible future directions.

• 2:30 Addison Wood: How to build a brain: using developmental processes to construct neural networks. Behavior emerges from brain activity, and brains are constructed by emergent processes and sculpted over the life of an organism. Although it is now common practice in evolutionary studies of behavior to allow genes to prescribe specific traits, it is not clear whether this imitates how natural selection works on biological organisms which develop and learn. We are developing a way of evolving simulated brains made of spiking neuron-like components in simulated simple bodies. Three stages of emergent processes construct the wiring, as in developmental biology, but we are using evolutionary processes to select the parameters of these processes of wiring the brain, which we believe is more likely to capture biological evolutionary dynamics than selecting for specific traits. We simulate animats moving in a 2-D world, in which they need to locate by smell and chase down prey. We evolve the genes that specify the emergent processes of neurons find their targets and how synapses change in response to experience. No specific behaviors are selected directly. After fitness has stabilized, we find that the ranges of half the gene parameters are tightly constrained and a small range of architectures dominate in the population. We find that among those parameters not tightly constrained there are only very weak relations between genes and fitness, as expected, but also between genes and any measured behavior, which is not. We propose that our results better reflect the unexpected findings of behavioral genetics, due to the emergent indirect relation of genes to measurable behavior.

• 2:40 Jory Schossau: Evolution of Instinctual Curiosity. Instinctual curiosity is clearly a beneficial behavior for organisms living in a somewhat predictable world, such as ours. However, the origins of this are not known, but are thought to bootstrap learning. We propose an evolutionary computational reinforcement learning framework built on the MABE platform and investigate several hypotheses around the evolutionary origins of instinctual curiosity, especially focusing on the degree of environmental predictability.

ZOOM LINK: https://msu.zoom.us/j/99978912124

Meeting ID: 999 7891 2124

Moderator: Connie James

Led by Clifford Bohm

MABE is an agent based digital evolution research tool designed to study evolving populations. MABE uses a modular approach to allow researches to combine existing and new components to assemble experiments with the goals of minimizing time spent and maximizing reuse of existing infrastructure. In this tutorial we will quickly introduce MABE, including a live demo showing its operation and discuses new features and planed future improvements.

ZOOM LINK: https://msu.zoom.us/j/92093419002

Webinar ID: 920 9341 9002

Moderator: Mike Wiser

• 3:30 Salvador Castaneda Barba: Sensitivity of Hi-C for detecting plasmid-host associations in soil. Plasmids play a significant role in the spread of antibiotic resistance genes (ARG) in the environment and have been shown to emerge from farm or feedlot settings. From farms, these plasmids and their ARG can spread further through agricultural application of manure as fertilizer. The limitations of current methods have prevented us from gaining further insight into the fate of antibiotic resistance plasmids in manure enriched soil. To address this knowledge gap, we are using the Hi-C method to determine the fate of plasmids in soil. Hi-C is a culture-independent approach that uses proximity ligation to physically link DNA molecules that are present in the same cell, such as plasmids and the chromosome of their host, within microbial communities. Our first objective was to test the limits of Hi-C to detect plasmid-host associations in soil. Agricultural soil was mixed with mock communities of a plasmid donor, a Pseudomonas putida recipient, and decreasing densities of P. putida carrying plasmid pB10, hereafter referred to as transconjugants. The Hi-C method was applied to each of these soil communities and the resulting Hi-C libraries were sequenced. We were able to detect transconjugant fractions when present as low as 10-4 of the total bacterial community. Our results show that the Hi-C method is capable of detecting links between plasmids and their hosts in soil. As a culture-independent approach, the Hi-C method has the potential to significantly improve our understanding of the range and rate of spread of antibiotic resistance genes that are introduced into soil.

• 3:45 Emily Dolson: An introduction to using counterdiabatic driving to eliminate genetic lag in changing environments. Many approaches to harnessing evolution rely on switching between different environments to force a population into a desirable region of a fitness landscape. This approach is, for example, the idea behind mitigating antibiotic resistance by cycling behind collaterally-sensitive drugs. However, a serious obstacle to this plan is that it requires precise control of the timing with which the population traverses the fitness landscape. It isn’t safe to apply the next drug in the sequence until we can be sure that the population has reached the desired region of the landscape. Here, we present a solution to this problem. By borrowing a new technique called counterdiabatic driving from quantum mechanics, we can derive a sequence of environments to subject the population to that will quickly and predictably lead the population to a region of the fitness landscape. Counterdiabatic driving requires four pieces of information: 1) mutation rate, 2) population size, 3) perfect knowledge of the relevant regions of a sequence of fitness landscapes that exist along some environmental change axis, and 4) a way to apply these fitness landscapes in sequence that would bring the population to the target genotype distribution given infinite time. This talk will describe the high-level intuition behind counterdiabatic driving and present proof-of-concept data from an agent-based model evolving on an empirically-derived fitness landscape from malaria drug resistance genes.

• 4:00 Connie Rojas: Host evolutionary history and ecology drives gut microbiota structure in African herbivores. The gut microbiota, defined as the collection of microbes inhabiting the gastrointestinal tract of animals, is critical for their hosts’ functioning. In mammals, resident gut microbes prime the development of their host’s immune system, detoxify plant secondary compounds, synthesize essential vitamins, and contribute to their host’s digestive efficiency. Prior studies conducted across a wide range of mammalian taxa reveal that host phylogenetic relatedness and host diet are strong drivers of gut microbiota structure; however, depending on the host taxa surveyed and the type of habitats and diets represented, one factor may be more influential than the other. Here, we use 16S rRNA gene sequencing surveys to disentangle the effects of host phylogeny and host dietary guild on the gut microbiota of 11 species of herbivores living sympatrically in the Masai Mara National Reserve, Kenya. The study species represented three orders and 5 families (Bovidae, Equidae, Giraffidae, Suidae, Elephantidae), and were classified as either grazers, browsers, or mixed-feeders. Our results demonstrate that the gut microbiota was highly species-specific and host family was a stronger predictor than host dietary guild. However, while gut microbiota similarity increased with host phylogenetic relatedness, this relationship was not apparent among closely related host clades. Overall, these findings suggest that host phylogeny may structure the gut microbiota at broad taxonomic scales, but ecology may be more influential in driving the gut microbiota among more closely related species.

• 4:15 Anya Vostinar and Sarah Doore: Factors Influencing Bacteriophage Multiplicity Over Time. Multiplicity of infection (MOI), the ratio of bacteriophage to bacterial cells, clearly affects the ecological and evolutionary outcomes of the system. In phage therapy applications, current dogma states that a higher MOI of lytic phage is more likely to decrease the bacterial population, with a general guideline of 10 phage per cell viewed as “optimal” to kill all bacteria within one to a few lysis cycles. MOI has often been discussed as a value only determined at the start of infection, implying it is static. However, we show it is not stable over time, even when we assume 100% adsorption. In this preliminary work, we use a combination of in vivo data and an agent-based model to show that the relationship between starting MOI and peak MOI varies depending on how long viral particles are able to persist in the environment and the starting MOI. We also show that phage interference causes a decrease in MOI regardless of starting MOI or persistence of particles. While virus interference has been described at high starting MOI in vivo, the dynamics between interference and later MOI have not been investigated over long periods of time or over the course of several infection cycles. These results call into question the standard MOI of 10 for application of phages and emphasize the importance of further investigating phage-phage interactions during infection.

ZOOM LINK: https://msu.zoom.us/j/95981505799

Meeting ID: 959 8150 5799

Moderator: Danielle Whittaker

Hosted by Ian Dworkin

George passed away February 6th, 2020. George was not only one of our strongest advocates for BEACON at the NSF, but a great Drosophila evolutionary geneticist. We will meet to reminisce, share stories and discuss his contributions, and for those who wish to, toast George with the best Scotch Whisky in your house (he was a great lover of Scotch).

We can also discuss this paper of his (given the title, it seemed most appropriate): A TIME SERIES OF EVOLUTION IN ACTION: A latitudinal cline in wing size in South American Drosophila subobscura

https://onlinelibrary.wiley.com/doi/abs/10.1111/j.0014-3820.2004.tb00410.x

WATCH ON CROWDCAST: https://www.crowdcast.io/e/beacon-congress-august/2

Now, perhaps more than ever, it is essential to convey data clearly. From COVID-19 to Climate Change, iconic graphs are used to make the case for action. But how well do visuals both capture and display knowledge, not just for the ‘public’, but among developing scientists? This talk will share tools effective in quickly analyzing college student knowledge and skills via visual media. We will look first at how graphs can reveal what students know (or don’t) as visualizations of experimental data. We’ll then turn to software approaches to analyze changes in student content knowledge and structure via concept maps. While example cases will be rooted in biology, the potential applications will be presented in intentionally broadly-applicable ways; the main goals are to use visuals to increase learning, promote equity, and save instructors time, particularly in remote instruction.

ZOOM LINK: https://msu.zoom.us/j/97144889382

Meeting ID: 971 4488 9382

Moderator: Josh Campbell

Led by Rob Pennock

What are the scientific character virtues and how do they relate to responsible conduct of research? These workshop/discussions can be used to help fulfill NSF's and MSU’s annual RCR requirement. First timers will discuss curiosity and the goals of science. Those who attended previously will do a new module on collaborativeness and collegiality.

ZOOM LINK: https://msu.zoom.us/j/94074968122

Webinar ID: 940 7496 8122

Moderator: Louise Mead

• 1:30 John Phillips: Engaging Ecuadorian Students and Teachers in Evolutionary Emblematic Ecosystems. As scientists, we frequently conduct research in field locations but too often we collect our data and leave without significant engagement with local communities to emphasize the broader scientific impacts of our work and why their specific ecosystem is important to our work. To address this deficiency, we have begun working with Ecuadorian students in the Galápagos Islands where our research group conducts evolutionary studies on the adaptive radiation of land snails. Thus far, our outreach has centered on scientific inquiry and empirical tests of the scientific method while emphasizing the importance of biodiversity of the archipelago. Herein, we outline our efforts to integrate our scientific work into the classroom and work with teachers to design lesson plans centered on evolution and speciation. We believe that building a foundation of evolution-based engagement will increase the scientific-based understanding of this historic evolutionary playground in local students as we foster this relationship for years to come.

• 1:45 Terence Soule: Evolvy Bugs? Pew Pew! Evolving Behaviors in a Mobile Space Shooter. It is widely assumed that incorporating evolution has great potential to make video games much more challenging and compelling because the enemy population will adapt to the players' decisions and strategies. However, some game genres are better suited to incorporating evolutionary mechanics than others. In particular because evolution typically requires large population sizes and many generations it is difficult to incorporate in a casual, mobile game. First, because gameplay in a casual game usually only lasts for a few minutes’ evolution may not be able to rely on long time-scales. Second, because in a mobile game space (both memory and screen space) is limited evolution may not be able to rely on large populations. In this research we present our strategies for overcoming these limitations while developing the evolutionary, casual, mobile space shooter: “Evolvy Bugs? Pew Pew!”.

• 2:00 Bryce Taylor: A University-High School collaborative evolution experiment implicates new adaptive routes to azole resistance in S. cerevisiae. Microbial experimental evolution paired with whole-genome sequencing provides a powerful opportunity to see evolution in action over relatively short time scales. The tools required to carry out such investigations have become more accessible, making it possible to expand these studies beyond the purview of the research lab and into the classroom. We developed lab modules (called yEvo) in which high school students use experimental evolution to study azole antifungal resistance in a non-pathogenic lab strain of S. cerevisiae. Clones from student experiments possessed mutations previously shown to impact azole resistance, demonstrating the efficacy of our protocols. We find recurrent mutations in an mRNA degradation pathway and in an uncharacterized mitochondrial protein (CSF1) that have plausible mechanistic connections to azole resistance. We additionally identified patterns of co-occurring mutations, suggesting a higher-order genetic interaction that connects mitochondrial ATP and heme synthesis with ergosterol production. This information may inform new treatments for genetically-related pathogenic species of yeast. This summer we are testing home evolution kits that we hope will fill a need for our partners this fall if quarantine continues. We are testing a variety of new evolution conditions, including caffeine (a TOR signaling inhibitor), tea tree oil (a TCA cycle inhibitor), and wood hydrolysate (a biofuel feedstock). Each of these offers an opportunity to frame the activity in new ways and to investigate new aspects of yeast biology. We hope that this collaboration can serve as a model for involving members of the broader science-interested public in the scientific process.

ZOOM LINK: https://msu.zoom.us/j/98460244531

Webinar ID: 984 6024 4531

Moderator: Rosemary Adaji

• 1:30 Matthew Andres Moreno: Spatial constraints and kin recognition can produce major evolutionary transitions in individuality. Evolutionary transitions occur when previously-independent replicating entities unite to form more complex individuals have profoundly shaped natural evolutionary history. If the original, lower-level entities are kin, then such a transition in individuality is termed "fraternal" (e.g., transitions to multicellularity or to eusocial colonies). The necessary conditions and evolutionary mechanisms for fraternal transitions to arise continue to be fruitful targets of scientific interest. We examine a range of fraternal transitions in populations of open-ended self-replicating computer programs. These digital cells were allowed to form kin groups by selectively adjoining or expelling daughter cells. The capability to recognize kin group membership enabled preferential communication and cooperation between cells. We observe group-level traits characteristic of fraternal transitions in individuality: reproductive division of labor, resource sharing (including endowment of seed resources to offspring groups), asymmetrical behaviors mediated by messaging, morphological patterning, and adaptive apoptosis. We report case studies on 8 distinct replicates where transitions occurred (all under identical environmental conditions), and explore the diverse range of adaptive strategies that made those transitions successful.

• 1:40 Andrew Dang: Color vision in nymphalid butterfly, Adelpha fessonia. Mimicry is an effective survival strategy that helps prey avoid predation by resembling unprofitable species. However, most studies of the visual ecology of mimicry focus on the visual capabilities of their predators as opposed to the visual systems of the prey themselves. In this study, we characterized the photoreceptors of Adelpha fessonia, a butterfly belonging to a diverse genus comprising of over 200 butterfly species with multiple mimicry complexes. RNA-Seq revealed the presence of three visual opsin mRNAs encoding for long-, blue-, and ultraviolet-sensitive opsins and for three other opsin-like proteins. Epi-microphotospectrometry and optophysiology were used to determine the peak sensitivities of A. fessonia’s long wave and ultraviolet sensitive eye photopigments at 530 nm and 355 nm, respectively. We inferred the peak sensitivity of the blue-sensitive eye opsin at 431 nm using UV-visible spectroscopy data from other Adelpha species and comparative sequence analysis. Immunohistochemistry is currently ongoing to confirm the presence and abundance of the three visual opsins while a transcripts per million assay is being used to determine all six opsin mRNA expression levels. Our results reveal A. fessonia eyes are similar to other nymphalid species like the painted lady butterfly, Vanessa cardui, which lacks heterogeneously expressed filtering pigments in the eye but different from other nymphalids like the monarch, Danaus plexippus and the postman, Heliconius erato. As Adelpha possesses vast mimicry complexes within Nymphalidae, examining visual systems of individual Adelpha species is integral to understanding how mimetic species discriminate one from another to maintain mimicry while avoiding hybridization.

• 1:50 Angelica Guadalupe Lara: Ommochrome and Melanin Pigmentation Genes in the Butterfly Heliconius charithonia. Angelica G. Lara, Dylan Rainbow and Adriana D. Briscoe. Pigmentation genes play various roles throughout the insects including photoprotection, thermoregulation, crypsis and communication. To further understand the evolution of pigmentation genes, we studied and annotated the genome of a lepidopteran, specifically the butterfly Heliconius charithonia. After using a basic local alignment search tool (Blastn) with the coding sequence (CDS) of 52 known ommochrome and melanin pigmentation gene transcripts in H. charitonia as query sequences against the reference genome of H. charithonia, data was compiled and analyzed. The E-values, score bits, number of exons, and completeness of the gene in question were recorded. Notably, gene duplication was found in three genes: Ruby, ATP-binding cassette subfamily member 4, and ATP-binding cassette subfamily member 4-2. All three genes were completely duplicated in the same scaffold, with identical intron/exon structure. They were unique, however, in the direction of their duplicates. Ruby had opposing duplicates, whereas ATP-binding cassette subfamily member 4, and ATP-binding cassette subfamily member 4-2 had both duplicates in ascending and descending order, respectively. Amongst duplicated genes, there was also evidence of pseudogenes, alternative haplotypes, and partially or completely missing exons. These findings, validated by comparing the H. charitonia scaffolds with those in LepBase, indicate that the pigmentation gene transcripts of H. charitonia are predominately complete. While the expression and function of the duplicate pigmentation genes remain to be elucidated, our findings underscore the role that detailed genome annotation can play in furthering our understanding of the structural evolution of genes involved in pigmentation.

• 2:00 Eben Gering: Behavioral and demographic covariates of coccidean infection in free-living spotted hyenas. Coccidian parasites can influence hosts’ hormones, nervous systems, behavior, and fitness - but these relationships are understudied in nature. Here, we analyze covariation between a) fitness-related host traits, including behavioral boldness and social rank, and b) naturally occurring infections of spotted hyenas. These analyses utilize behavioral and demographic data from the Mara Hyena Project, along with ELISA and IFA diagnostics targeting two globally distributed, highly generalist coccidia: Toxoplasma gondii and Neospora canium. Both parasites were found to be prevalent in Mara hyenas during the project’s early (pre-2000) and more recent (post-2008) sampling periods. As predicted by the host-manipulation hypothesis, T. gondii infections were associated with costly behavioral boldness toward lions, which are a definitive T. gondii host. We are now contrasting this result to the environmental, social, and behavioral covariates of N. canium infections. These analyses will illuminate connections between parasitic infections and host behavior in a highly social model species, and drivers of transmission for two protists impacting conservation, agriculture, and public health worldwide.

• 2:10 Minako Izutsu: Effect of population bottleneck on rate of adaptation in experimental evolution with Escherichia coli. Population bottlenecks are common in nature and impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation in evolving populations. On the other hand, in a resource-limited environment a small founding population can undergo more generations and produce more descendants than a large one, which allows surviving beneficial mutations to spread more quickly. We investigate the impact of bottlenecks on the dynamics of adaptation in experimental populations of Escherichia coli. We propagated 48 populations under 4 dilution regimes (2-, 8-, 100-, and 1000-fold), all reaching the same final population size, for 150 days. A theoretical model predicts that fitness gains should be maximized with 8-fold dilutions. However, we observed earlier and greater fitness gains in the populations subjected to 100- and 1000-fold dilutions than in those that evolved in the 8-fold regime. We sequenced the whole genomes of 48 evolved clones and found that the clones evolved under 100-fold dilution have less mutations than those evolved under 1000-fold regime although 100-fold clones showed higher mean fitness than 1000-fold clones. This suggests mutations accumulated under 100-fold dilution tend to have larger effects than those under 1000-fold regime. We also found high parallelism at the gene level within and between treatments. We show the overall results of the genome sequencing, address the potential explanation for the failure of the theoretical model, and discuss the effect of population bottlenecks.

• 2:20 Lance Fredericks: Exploring the Overwhelming Susceptibility to Killer Toxins in the Pathogenic Yeast, Candida glabrata. Combatting the spread of drug-resistant microbes requires new antifungal compounds with novel mechanisms of inhibition. We investigate natural, proteinaceous toxins that are encoded by double stranded RNA satellites found within Saccharomyces cerevisiae. Commonly known as killer yeasts, toxin-producing strains of S. cerevisiae have been found to inhibit the growth of many fungal pathogens. By testing over 9,000 interactions between killer yeasts and pathogens we determined that Candida glabrata is broadly susceptible to killer toxins, while other Candida species showed little to no susceptibility. Of the 90 killer strains of S. cerevisiae tested against over 130 C. glabrata, several were capable of inhibiting all isolates, including clinical samples from the CDC/FDA and the Wayne State University Clinic. Then, to proactively investigate the inevitable resistance to these toxins that would arise in a clinical setting we went on to generate toxin resistant mutants of C. glabrata in order to study natural toxin resistance mechanisms. We phenotypically characterized these mutants based on virulence in a wax moth model, susceptibility to traditional drugs, and cross resistance to other killer toxins. In addition to the phenotypic investigation, we sequenced each mutant to identify target genes for resistance. The sequencing confirmed known targets for killer toxins while also indicating new pathways involved in toxin resistance. From the sequencing and phenotypic characterization, we have developed a picture of killer toxin susceptibility and resistance in C. glabrata.

• 2:30 John Lee: The role of c-di-GMP in the control of phenotypic diversity in two pandemic strains of Vibrio cholerae. There are two biotype strains of Vibrio cholerae that are responsible for seven cholera pandemics since 1817. The earlier six pandemics have been attributed to the Classical strain, which has been replaced by El Tor strain during the current seventh pandemic. The underlying evolutionary process that leads to the dominance of El Tor strain remains largely unknown. In this study, we show that two pandemic strains of V. cholerae maintain different levels of the secondary messenger molecule, cyclic-di-GMP. C-di-GMP integrates many environmental signals to regulate the transition between motility and biofilm formation. This phenotypic switching is an output response of signal integration with stochastic molecular fluctuations that gives rise to single-cell heterogeneity. Using a single-cell tracking method, we demonstrate that a clonal batch culture of V. cholerae are phenotypically diverse at a single-cell level and the distribution of motility phenotypes differs between the Classical and El Tor strains. The c-di-GMP concentration in El Tor strain allowed a higher degree of phenotypic heterogeneity, which may be used as a bet-hedging or division-of-labor strategy during environmental fluctuations as V. cholerae transitions between the human host and aquatic environment. The conclusion of this study sheds light on the role of c-di-GMP in the control of phenotypic diversity that can serve as a selectable trait, favoring phenotypic distributions of one biotype strain over the other.

• 2:40 Melissa Steele-Ogus: Evolutionary Divergent Actin Interactors in the Parasite Giardia Lamblia. The evolution of an organism’s morphology is shaped by the boundaries of its environment. Giardia lamblia is a deep-branching intestinal parasite that diverged from the other eukaryotes over a billion years ago; thus, many of Giardia’s systems are simplified than and divergent from those of the model eukaryotes. For instance, the actin cytoskeleton, required for membrane trafficking, maintenance of cell polarity, and cell division in eukaryotes, retains these conserved functions in Giardia, despite its divergent sequence identity and the fact that it lacks the conserved actin regulators found in later-emerging eukaryotes. These canonical actin regulators function to control the temporal and spatial assembly of actin into filaments to serve various functions in the cell. Such proteins constrict actin evolution, as the amino acids required for binding must be retained. The lack of conserved actin interactors makes Giardia unique, as it completely lacks this evolutionary pressure that has constrained actin form and function in the model eukaryotes. Here we use liquid chromatography tandem mass spectrometry (LC MSMS) to identify a number of novel filamentous-actin interactors in Giardia, most of which lack homologues in other organisms. We then describe the localization of a subgroup of these interactors which fall into the following categories: marginal groove, flagella, ventral disc, nucleus, membrane, and nonspecific. As Giardia and human cellular systems are extremely different, novel proteins identified in this study could be potential drug targets for treatment of giardiasis.

ZOOM LINK: https://msu.zoom.us/j/97373990635

Meeting ID: 973 7399 0635

Moderator: Danielle Whittaker

Led by Acacia Ackles

This workshop will provide participants with tools and resources to edit and improve their scientific writing. We will incorporate advice from "The Science of Scientific Writing" (Gopen & Swan, 1990) and other resources to look for common pitfalls and areas for improvement in our academic papers. Participants at all levels of scientific writing experience are welcome. Participants will leave the workshop with a marked-up version of their own writing to go forth and improve upon!

ZOOM LINK: https://msu.zoom.us/j/96306868290

Webinar ID: 963 0686 8290

Moderator: Connie James

• 3:30 Brian Hsueh: Combining bioinformatics and wet-lab experiments to explore horizontally transferred genes in Vibrio cholerae. The El Tor biotype of the Gram-negative bacterial pathogen Vibrio cholerae is the causative agent of the 7th cholera pandemic, which started in 1961. The El Tor biotype has acquired two genomic islands—VSP 1 & 2—that are not present in the previous six pandemic strains of the classical biotype. Several groups have demonstrated that a four gene operon in VSP 1 (capV-dncV-vc0180-vc0181) comprises an anti-phage system termed CBASS (cyclic oligonucleotide-based anti-phage signaling system). This system involves the synthesis of cyclic-GMP-AMP (cGAMP) by the DncV enzyme and the activation of the phospholipase CapV to achieve abortive infection as a phage defense mechanism. Despite this finding, the function of the other approximately 36 ORFs encoded on these two genomic islands remains uncharacterized. We developed a bioinformatic pipeline to predict other gene networks within the VSP islands by exploring the co-occurrence of island gene products across bacterial genomes. In addition to the CBASS system, our analysis predicted that dncV was involved in a gene network with the putative deoxycytidylate deaminase vc0175, renamed here-in as deoxycytidylate deaminase Vibrio (dcdV). DcdV consists of two domains—a putative nucleoside/nucleotide kinase (NK) domain and a conserved deoxycytidylate deaminase (DCD) domain. We hypothesized the function of DcdV could include depleting dCTP/dCMP while elevating dUTP/dUMP levels, leading to the perturbation of the host nucleotide pools to prevent bacteriophage replication. Ectopic expression of DcdV in V. cholerae lacking VSP-1, but not the wild type strain, results in filamentous cell phenotype, leading us to identify a region of 174 nt 5’ of dcdV that encodes an inhibitor of DcdV we named DifV. Both domains of DcdV are required to induce cell filamentation. Through controlled in vitro and in vivo assays, we demonstrated that DcdV utilizes dCTP/dCMP as substrates for deamination to uracils and increases uracil incorporation in the genomes, respectively. Orthologs of dcdV are widely encoded in Gram-negative bacteria, although no function has ever been attributed to these genes. Our results suggest a model whereby DcdV/DifV encode a previously undescribed phage defense element that contributes to the emergence and spread of the current V. cholerae pandemic.

• 3:45 Olusola Jeje: Experimental Evolution of Escherichia coli K-12 MG1655 in Iron (III) Sulphate and T7 Bacteriophage Yielded Phenotypes that were Better Fitted in Conventional Antimicrobial Agents. Iron is very essential to growth and cell division in bacteria, iron deficiency interferes with cytokinesis, the last stage of cell division. With this knowledge of iron importance, we developed experimentally, phenotypes of Escherichia coli K-12 MG1655 that were selected for iron (III) sulphate, another phenotype that was selected for both iron (III) sulphate plus T7 bacteriophage. We investigated the interactions of all phenotypes with excess iron (III), iron (II), gallium and silver. We further studied the interactions of the phenotypes with ampicillin, a β-lactam antibiotic, tetracycline, chloramphenicol, and rifampicin. Our methods include culturing the iron (III)-selected group in 1.75 mg/ml of iron (III) sulphate solution in a daily transfer and incubating the iron (III) plus phage-selected group in 100 µL of 1:100 dilution of 3.4 × 106 pfu T7 bacteriophage. Phenotypes were tested in Minimum Inhibitory Concentration, MIC assays. Our findings show that experimental selection for both iron (III) plus phage in same E. coli populations yielded phenotypes that demonstrated superior growth in excess iron (III), gallium and silver. In a gallium MIC, E. coli selected for iron (III) plus phage demonstrated superior growth in excess gallium. At 1.00 mg/ml, 1.75 mg/ml, and 2.50 mg/ml of gallium concentrations, cell growth was 0.24, 0.18 and 0.15 respectively for iron (III) plus phage-selected phenotypes, in comparison to 0.18, 0.14 and 0.01 of the iron (III)-selected group. Experimental selection for both iron (III) plus phage in same E. coli populations also yielded phenotypes that demonstrated superior growth in excess ampicillin, tetracycline, chloramphenicol, and rifampicin. Iron (III)-selected plus phage-selected phenotypes were better fitted in ampicillin, a β-lactam antibiotic. At 0.006 mg/ml, 0.012 mg/ml, 0.025 mg/ml, 0.050 mg ml, 0.075 mg/ml, 0.10 mg/ml, 0.175 mg/ml, 0.25 mg/ml, and 0.50 mg/ml concentrations of the antibiotic, iron (III)-selected plus phage selected phenotype demonstrated a superior growth of 0.27, 0.35, 0.37, 0.38, 0.39, 0.35, 0.35, 0.25 and 0.05 respectively in comparison to 0.00 for iron (III)-selected and control at all concentrations. Selected bacteria are thus resistant to iron (III) and phage We concluded that E. coli K-12 MG1655 selected for both iron (III) plus T7 phage yielded populations with better resistance to metals and antimicrobial agents. The implications of this is that resistance to certain metals might facilitate resistance to bacteriophage and subsequently confer selective advantage to antimicrobial resistance on certain bacteria.

• 4:00 Janani Ravi: An integrative computational evolutionary approach to characterize bacterial proteins and genomes. Studying bacterial physiology, adaptation, and pathogenicity through the lens of evolution requires delineating the phylogenetic history of bacterial proteins and genomes. Mapping these histories in turn requires integrating a variety of data types (genome/protein sequence, protein motifs, domains, secondary structure predictions). However, each type of data – and the tools developed to analyze them – reside in disconnected web-resources that are not interoperable. To address this challenge, we have developed a computational framework for comprehensive evolutionary analysis that systematically integrates multiple data sources for gleaning sequence-structure-function relationships and performing comparative pathogenomics under one umbrella. Our framework goes beyond simple sequence comparisons by delving into constituent domains, domain architectures, genomic neighborhoods, and pangenomes. These analyses can pinpoint molecular/genomic features that are unique to bacterial groups of interest (e.g., specific pathogens), which can then help prioritize candidate molecular targets, even in poorly characterized bacterial genomes. To demonstrate the versatility of this framework, we are currently applying it to Nontuberculous Mycobacteria (NTM), Staphylococcus aureus, and Bacillus anthracis that are zoonotic pathogens causing severe and chronic pathologies in humans and animals. We are also implementing these approaches as open-source software (R package) and web-based applications that will enable us, and the scientific community, to prioritize candidate genetic factors in their application of interest for experimental validation.

• 4:15 Melissa Steele-Ogus: An Evolutionarily Unique Actin and its Role in Maintaining Infection in Giardia Lamblia. Giardia lamblia is the most prevalent intestinal parasite, both in the United States and worldwide. While treatment options do exist, they have a high incidence of side effects, and up to 20% of cases are treatment resistant. Giardia is a single-celled eukaryote that lives in two extremely different environments, and thus has two extremely different stages in its life cycle. The metabolically quiescent cyst lives in freshwater, while the active trophozoite colonizes the lumen of the intestine. These two environments provide their own selective pressures, which have shaped Giardia’s evolutionary path and morphology. In the intestine, Giardia must resist the flow of peristalsis in order to maintain infection. Giardia has adapted to this environment by attachment to microvilli, which is mediated by its ventral disc, a unique microtubule-based organelle. Giardia actin (glActin) is the most evolutionarily divergent actin described in the literature, with a 58% identity to the average actin, and lacks any conserved interactors. We recently identified a number of novel glActin interactors that localize to the ventral disc, indicating a role for actin in ventral disc function.One such protein, Disc Associated and Actin-Related Protein (DAARP), was noteworthy because it appears highly enriched in the two regions of the disc important for fluid flow during attachment. DAARP has no homologues or conserved identifiable protein domains. In this study, we investigate the role of both glActin and DAARP in attachment, gaining insight into an evolutionarily divergent organism and a promising area for new therapeutics against a harmful parasite.

• 4:30 Misty Thomas: Can I eat sugar in outer space? Assessing the adaptive response of Streptococcus mutans to microgravity. Microbes are not only ubiquitous on earth, but also in outer space. The crew’s normal flora harbor large quantities of microbes, making them an important source of bacterial contamination. This combined with severe immune dysregulation during space flight, make infections resulting from their flora a primary concern. Approximately 20% of oral bacteria are streptococci, which are responsible for both establishment of healthy dental plaque and dental decay. The phenotypes of these organisms as they exist on earth are well studied and treatment strategies are more predictable, but these may not hold true during space travel. To evaluate this, we conducted a 100-day experimental evolution study using High Aspect Rotating Vessels (HARVs) to simulate microgravity and compare it against a normal gravity controls and to the ancestral strain. Here we assessed genomic and transcriptomic changes through whole genome resequencing and RNAseq to correlate to the observed phenotypic changes. Here we found that as a result of adaptation to microgravity some populations exhibited a decrease in two of its virulence phenotypes adhesion and acid tolerance both supported by genomic and transcriptomic changes in correlated genes. Interestingly, not all 4 populations followed the same evolutionary trajectory. In addition, we saw small changes in susceptibility to a number of antibiotics most notably in two populations to antibiotics that target the ribosome. These two populations also showed a number of genomic changes in genes involved in ribosome biogenesis and they also displayed transcriptional changes in a number of ribosomal proteins. Overall, we are trying to understand if microgravity could render astronauts more susceptible to dental decay caused by the human oral resident Streptococcus mutans. Together the data shows that when grown in conditions allowing for planktonic growth that two of the major indicators of pathogenesis, adhesion and acid tolerance decrease after 100-days of adaptation. Moving forward we will now assess the co-evolution in both microgravity and in colloidal silver as silver is proposed to be used as the primary filtration agent used by NASA on long-term space missions in addition to performing similar studies using bacterial biofilms.

ZOOM LINK: https://msu.zoom.us/j/98053101652

Meeting ID: 980 5310 1652

Hosted by Emily Dolson and Austin Ferguson

We will have a range of virtually-playable games available (Code Names, Werewolf, Jackbox, etc.). We will meet on Zoom to decide what to play, possibly breaking into multiple groups if people are interested in different games. Most games lend themselves to large groups, so there will be a fair amount of flexibility. Feel free to drop in when you can and leave when you must!

WATCH ON CROWDCAST: https://www.crowdcast.io/e/beacon-congress-august/3

Humanity demonstrated our mastery of the principles of flight through engineering flying machines with capabilities far beyond natural example, through means highly divergent from natural example. By this standard, we have yet to demonstrate our mastery of the principles of biological evolution: An open challenge in the study of evolution is to isolate the engineering principles of unceasing open-ended inventiveness. This talk will describe a series of algorithms that explore different abstractions of open-ended creativity, highlighting deep open questions that may be gating further progress.

ZOOM LINK: https://msu.zoom.us/j/96913935940

Meeting ID: 969 1393 5940

Moderator: Danielle Whittaker

Led by Anya Vostinar and Sarah Doore

Symbiosis, a close and long-term interaction between two or more organisms from different species, is a ubiquitous phenomenon, found at all levels of life and nearly every context that we have looked for it. Microbiomes, which exemplify symbiosis at multiple levels, play a crucial role in the functioning of most higher-level organisms, in addition to the many better-known examples of symbiosis from pollinators to parasites. Studying symbiosis in model systems presents many challenges and there are many questions left to answer about the evolutionary dynamics of symbiosis. This sandbox session aims to provide space to discuss the major questions regarding symbiotic evolutionary dynamics and to identify cross-disciplinary collaborations that could seek to answer these questions.

ZOOM LINK: https://msu.zoom.us/j/97876044873

Webinar ID: 978 7604 4873

Moderator: Rosemary Adaji

• 1:30 Cory DuPai: A systematic analysis of beta hairpin motifs in the PDB. Beta hairpins, composed of two antiparallel beta strands joined by a short loop, represent one of the simplest possible protein structural motifs. Perhaps because of this simplicity, beta hairpins are also one of the most common structural motifs, with examples found in eukaryotic transmembrane proteins, small antimicrobial peptides, and even synthetically designed bio-active molecules. Using all solved protein structures in the Protein Data Bank (PDB) we were able to probe for proteins containing this motif and identify common properties of beta hairpins across some thirty thousand diverse molecules. Key findings include periodicity of side chains corresponding to polar and non-polar faces, positional biases in amino acid composition, and a propensity for specific residue pairings across beta strands.

• 1:45 Joshua Franklin: Binomial Inheritance as an Explanation for Peritrichous Flagellation in Salmonella. Bacteria possess a wide diversity of flagellar configurations, but despite the importance of flagellar motility, there is no overarching theory explaining observed flagellation patterns. For example, the benefit of peritrichous flagellation, in which multiple flagella are distributed along the cell body, is unclear, as many bacteria swim just as well using only a single flagellum. We also know that flagella are relatively expensive structures, which we demonstrate using a Salmonella enterica flagella-inducible system in combination with a multilevel growth curve model. Using single-cell tracking we provide evidence that possessing more than one flagellum provides little-to-no swimming benefit at water-like viscosities. So why do some bacteria make multiple flagella? Here we propose that peritrichous flagellation can serve as a Pareto-optimal mechanism for ensuring offspring receive at least one flagellum. Following from our observation that flagella number is approximately negative-binomially distributed, we derive a model predicting the optimal number of flagella as a function of the cost and reward for possessing at least one flagellum. Our model is supported by the results of a computational evolutionary experiment using agent-based simulations of flagellated bacteria. The optimal number of flagella is a logarithmic function of the fitness reward, which explains why peritrichously flagellated cells living in low viscosity environments have relatively few flagella. However, the large number of flagella found in bacteria such as Bacillus subtilis or Proteus vulgaris are unlikely to be explained by our model, suggesting that highly flagellated cells are subject to a different evolutionary tradeoff.

• 2:00 Connor Grady: Magnetobiomaniupulation: A Novel Synthetic Biology Approach to Control Enzymes. Background: The creation of a novel synthetic circuit based on a “switch” controlled in a non-invasive manner will become a valuable tool for the field of synthetic biology. Many circuit designs rely on external light or chemicals to stimulate the circuit. The “switch” for our design is based on the Electromagnetic Perceptive Gene (EPG; GenBank: MH590650.1) which was discovered in Kryptopterus bicirrhis (glass catfish). When EPG is expressed in mammalian cells, electromagnetic fields (EMF) can elicit a measurable response in the cell (1). Methods: EPG was cloned between NanoLuc and mVenus on the N and C terminals respectively and expressed in HeLa cells. EPG was cloned between split Nanoluc and into BL21 cells. Results were measured using the VICTOR Nivo and IVIS (PerkinElmer) with EMF induction with static magnetic field (~10 mTesla) and electromagnet (~35 mTesla). Results: Utilizing Förester Resonance Energy Transfer (FRET) we observed a 2-10% change in ΔF/F following stimulation with magnetic field in contrast to controls without stimulation. When EPG was fused to a split NanoLuc we observed a 50% increase in photon flux with cell lysates and 70% increase with whole cell. Discussion: We were able to demonstrate the potential to control enzymes by using EPG as a “biological hinge” that allows bringing together two proteins or two parts of a split protein by remote EMF induction. This is the first step toward engineering a new platform technology for remote control of enzyme activity with EMF. 1. Krishnan, V. et al. Sci Rep8, 8764, (2018).

• 2:15 Adam Hockenberry: Selection for rapid translation of bacteriophage mRNAs is lifestyle dependent. In many bacterial species, highly translated mRNAs are characterized by the presence of a Shine-Dalgarno sequence motif upstream of the start codon and weak secondary structure within this initiation region. These features facilitate binding of the small ribosomal subunit and stabilize the assembly of the initiation complex, resulting in rapid translation rates. Bacteriophages rely on host-cell translational machinery and their mRNAs must, at least initially, compete with host mRNAs for ribosomes. Despite the ecological importance of phages and the distinct evolutionary pressures that they face, the general constraints and principles underlying the translation of phage mRNAs are largely unknown. Here, we show that the translation initiation regions of phage genomes are strongly enriched in Shine-Dalgarno sequences relative to host genomes. We find that in general, the initiation region of phage mRNAs have relatively stronger secondary structures when compared to host mRNAs. However, a subset of mostly virulent phages have relatively weaker mRNA secondary structure in initiation regions--likely resulting in rapid ribosomal recruitment and high translation rates. Our findings are consistent across a range of different host/phage pairs and are independent of several factors including overall expression levels and gene essentiality constraints. Further study of phage translational regulation---with a particular emphasis on lytic phages---may provide new strategies for engineering phage genomes and recombinant expression systems more generally.

• 2:30 Alexander Lalejini and Lauren Gillespie: Changing environments promote the evolution of physical modularity through gene segregation. Genetic architectures are heavily shaped by evolutionary pressures. What environmental characteristics shift selection to favor more modular genetic architectures where genes are non-overlapping versus more compact alternatives? Intuitively, there is an evolutionary trade-off in how genetic information is organized: gene overlap allows for more compact information storage and enables tight physical coupling between genes, whereas more diffuse genetic architectures allow genes to be modified independently. We use computational models to verify predictions for how environmental change and mutation rate shape the evolution of gene segregation. Specifically, we demonstrate that changing environments promote gene segregation, and we confirm that segregated genes are better able to adapt to novel environments. Furthermore, we find that high mutation rate is sufficient to drive the evolution of increased gene overlap to reduce the mutational load on coding regions.

• 2:45 Andrew Thompson: The genome of the bi-annual Rio Pearlfish (Nematolebias whitei) informs the genetic regulation of diapause and environmentally-cued hatching. Thompson, A. W., Wojtas, H., Davoll, M., and Braasch, I. Annual or seasonal killifishes are emerging Eco-Evo-Devo models due to their unique embryonic dormant stages and are being used to study development, metabolism, cell proliferation, and stress tolerance in vertebrates. They inhabit seasonal pools that desiccate, resulting in the death of the adult population. Unique adaptations including specialized egg structures, desiccation resistance, and up to three ontogenetic diapause stages slowing developmental and metabolic rates enable the embryonic population to survive annual dry seasons. When the habitat floods, annual killifish terminate their third and final diapause (DIII), hatch, and begin a new lifecycle. We sequence the genome of the bi-annual Rio Pearlfish, Nematolebias whitei. Rio Pearlfish are native to seasonal pools in the coastal plains near Rio de Janeiro, Brazil, where they complete two life cycles per year. During DIII, Pearlfish have fully developed and functioning organ systems when making changes to metabolism and cell cycle during developmental arrest. Our model species represents an independent origin of annualism in fishes different from other killifish species. Tight linkage of DIII and hatching with the expression of a complex family of hatching enzymes leads us to analyze gene regulatory mechanisms associated with environmentally-cued hatching in comparison to other aquatic vertebrates. Our analysis of the HE family including those of Rio Pearlfish reveals a complex evolutionary history of hatching enzymes in killifishes. Using Pearlfish, we analyze the developmental gene networks by which resilient vertebrates control hatching, and uncover how evolutionary changes in these networks contribute to adaptations to extreme environments. Additionally, we use the Pearlfish and other annual killifishes to create Killi-Kits, an educational outreach tool. Killi-Kits include dormant killifish embryos, a small tank, food, a clip-on, smartphone microscope for photo/video recording, various other accessories, and instructional online resources. A-FISH-ionados of all ages can easily observe the different killifish developmental stages with the smartphone microscope. Overall, we establish the Rio Pearlfish as a research organism and educational toolkit for Eco-Evo-Devo and evolution in action.

ZOOM LINK: https://msu.zoom.us/j/95263105623

Meeting ID: 952 6310 5623

Moderator: Melissa Williams

Led by Emily Dolson

Open science is a philosophy of doing research that encompasses many different components. In general, the principles of open science are related to making your research readily available to others. This approach oversees general awareness of your work and makes it easier for others to build on and understand (there are also ethical arguments in favor of it). However, the open science ecosystem is a large place and it can be hard to figure out where to begin! This tutorial will be a broad overview of tools that are helpful to doing open science, with an emphasis on computational science. Audience input and participation will be encouraged!

ZOOM LINK: https://msu.zoom.us/j/98936109691

Webinar ID: 989 3610 9691

Moderator: Jory Schossau

• 3:30 Garrett Bingham: Evolutionary Optimization of Deep Learning Activation Functions. The choice of activation function can have a large effect on the performance of a neural network. While there have been some attempts to hand-engineer novel activation functions, the Rectified Linear Unit (ReLU) remains the most commonly-used in practice. This paper shows that evolutionary algorithms can discover novel activation functions that outperform ReLU. A tree-based search space of candidate activation functions is defined and explored with mutation, crossover, and exhaustive search. Experiments on training wide residual networks on the CIFAR-10 and CIFAR-100 image datasets show that this approach is effective. Replacing ReLU with evolved activation functions results in statistically significant increases in network accuracy. Optimal performance is achieved when evolution is allowed to customize activation functions to a particular task; however, these novel activation functions are shown to generalize, achieving high performance across tasks. Evolutionary optimization of activation functions is therefore a promising new dimension of metalearning in neural networks.

• 3:45 Risto Miikkulainen: From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic. Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with non-pharmaceutical interventions (NPIs) such as social distancing restrictions and school and business closures. This paper demonstrates how Evolutionary AI could be used to facilitate the next step, i.e., determining most effective intervention strategies automatically. Through evolutionary surrogate-assisted prescription (ESP), it is possible to generate a large number of candidate strategies and evaluate them with predictive models. Strategies can be customized for different countries and locales, and balance the need to contain the pandemic and the need to minimize their economic impact. As more data becomes available, the approach can be increasingly useful in dealing with COVID-19 as well as possible future pandemics.

• 4:00 Santiago Gonzalez: Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization. Metalearning of deep neural network (DNN) architectures and hyperparameters has become an increasingly important area of research. Loss functions are a type of metaknowledge that is crucial to effective training of DNNs, however, their potential role in metalearning has not yet been fully explored. Whereas early work focused on genetic programming (GP) on tree representations, this paper proposes continuous CMA-ES optimization of multivariate Taylor polynomial parameterizations. This approach, TaylorGLO, makes it possible to represent and search useful loss functions more effectively. In MNIST and CIFAR-10 benchmark tasks, TaylorGLO finds new loss functions that outperform functions previously discovered through GP, as well as the standard cross-entropy loss, in fewer generations. These functions serve to regularize the learning task by discouraging overfitting to the labels, which is particularly useful in tasks where limited training data is available. The results thus demonstrate that loss function optimization is a productive new avenue for metalearning.

• 4:15 Christopher Large: Genomic stability and adaptation of beer brewing yeasts during serial repitching in the brewery. Ale brewing yeast are the result of admixture between diverse strains of Saccharomyces cerevisiae, resulting in a heterozygous tetraploid that has since undergone numerous genomic rearrangements. As a result, comparisons between the genomes of modern related ale brewing strains show both extensive aneuploidy and mitotic recombination that has resulted in a loss of intragenomic diversity. Similar patterns of intraspecific admixture and subsequent selection for one haplotype have been seen in many domesticated crops, potentially reflecting a general pattern of domestication syndrome between these systems. We set out to explore the evolution of the ale brewing yeast, to understand both polyploid evolution and the process of domestication in the ecologically relevant environment of the brewery. Utilizing a common brewery practice known as ‘repitching’, in which yeasts are reused over multiple beer fermentations, we generated population time courses from multiple breweries utilizing similar strains of ale yeast. Applying whole-genome sequencing to the time courses, we have found that the same structural variations in the form of aneuploidy and mitotic recombination of particular chromosomes reproducibly rise to detectable frequency during adaptation to brewing conditions across multiple related strains in different breweries. Our results demonstrate that domestication of ale strains is an ongoing process and will likely continue to occur as modern brewing practices develop.

• 4:30 Matt McGuffie: Unintentional evolution has altered the copy number of many engineered plasmids. Engineered plasmids are ubiquitous molecular tools in the biological sciences and are useful vectors for engineering many organisms. Critical components of plasmid backbones, such as origins of replication and antibiotic resistance genes, are often assumed to be completely immutable, and these components are rarely re-sequenced for verification. Therefore, it is unclear how often these components unintentionally mutate and to what degree this unplanned evolution affects plasmid function. We analyzed the sequences of over 30,000 engineered plasmids to detect signatures of evolution in the ColE1 origin of replication, a component which is used in >95% of the plasmids in this dataset. We identified many previously uncharacterized variants of the ColE1 origin, some of which appear to have arisen independently multiple times in plasmids created by different researchers. This signature of parallel evolution suggests selection for a modified function. We hypothesized that most of these mutations reduce plasmid copy number because cells that evolve to lessen the burden of a costly engineered plasmid insert can gain a fitness advantage. We reconstructed and tested the effects of these mutations on the copy number of the pUC19 cloning vector, a common plasmid containing the ColE1 origin. We found that most of these mutations reduce plasmid copy number, in agreement with our hypothesis. Interestingly, a few constructs actually show increased plasmid copy number, which could be due to artificial selection from researchers. Overall, our study highlights how plasmids can evolve outside of human oversight in ways that affect the predictability and reliability of genetic engineering.

• 4:45 Genevieve Mortensen: Burden of hundreds of genetic parts and devices defines an evolutionary limit on constructability in synthetic biology. Synthetic biologists seek to engineer cells with new and useful functions by combining standardized genetic parts. However, little is known about the reliability of these parts during long-term, continuous use. Programming a cell to perform a novel function can significantly reduce its replication rate if the added construct appropriates limiting cellular resources. Often, this fitness burden can be alleviated by a single loss-of-function mutation within the engineered DNA sequence. Cells with these mutations can rapidly evolve and sweep a population so only an ever-decreasing fraction of cells continue to perform the desired function. We quantitatively characterized the fitness burdens of 328 BioBrick plasmids from the iGEM parts kit to understand which are most susceptible to evolutionary failure by measuring how each plasmid affected the growth rate of E. coli. We also utilized a translational capacity monitor, a GFP cassette placed in the chromosome of the E. coli host cells, to understand how much of this burden was due to ribosomes being allocated to the genetic construct and away from native functions. We found that roughly 1/4 of the iGEM plasmids significantly reduced E. coli growth rates, but none did so by more than ~40%. Burden from some constructs was wholly due to ribosome appropriation but other highly burdensome plasmids did not reduce GFP expression. Finally, we created a stochastic population genetic simulation which predicts plasmids that exceed 40% fitness burden would likely mutate before they could be constructed. Thus, understanding evolution in action explains important constraints on synthetic biology.