ZOOM LINK: https://msu.zoom.us/j/96839345688

Meeting ID: 968 3934 5688

Passcode: beacon

Moderator: Danielle Whittaker

Introduction: Louise Mead

As scientists, we often identify a problem, research its background, and develop solutions to better understand it or solve it. While this approach may work well in the lab, when we apply this strategy to societal issues that impact our communities, we are not as effective because we leave out a critical step—the development of community-driven solutions. Dr. Jeanine Abrams McLean (Vice President at Fair Count and a former Phylogenetics Unit Lead at the Centers for Disease Control and Prevention) will discuss how scientists can combine research strategies, data, and community engagement to create community-driven solutions that can positively impact underrepresented and marginalized communities that are impacted by social inequities. She will specifically discuss her work with Fair Count’s Science for Social Equity program, which focuses on science-related issues such as mental health, climate change, and health literacy. Dr. Abrams McLean will also discuss the Pandemic to Prosperity: South program, which is a data, policy, and organizing effort comparing the South’s pandemic recovery to the nation’s and highlighting overlooked populations, ultimately working to inspire groundbreaking solutions to entrenched problems that can lead the way for the nation as a whole.

LINK TO RECORDING: https://youtu.be/p-pYP8UfwVU

LINK TO CHAT FILE: https://mediaspace.msu.edu/media/BEACON+Congress+Keynote+1+-+Jeanine+Abrams+McLean/1_a3swezy9 (click on "Attachments" under the video and download the .txt file)

ZOOM LINK: https://msu.zoom.us/j/95612124297

Meeting ID: 956 1212 4297

Passcode: beacon

Led by Jory Schossau

Learning is often an integral part of higher order organismal evolution. However, learning may not exist across all taxa because it is a consequence of particular evolutionary history. Learning influences natural selection, and natural selection creates dispositions related to learning. This sandbox is a roundtable discussion and brainstorming session about the interplay between learning, predisposition to learning, this bidirectional effect, and measuring this effect. Ideally, participants will learn new methods for their own research and form new collaborations.

Note: This session will *not* be recorded.

ZOOM LINK: https://msu.zoom.us/j/95202291120

Meeting ID: 952 0229 1120

Passcode: beacon

Technical Assistant: Mike Wiser

Moderator: Adriana Briscoe

• 1:30 Adriana Briscoe, Mahul Chakraborty, Angelica Lara, Dylan Rainbow, Yan Tao, Edwin Solares, Iskander Said, Russ Corbett-Detig, Lawrence Gilbert, and J.J. Emerson: A W-linked gene duplication underlies sexually dimorphic UV color vision in Heliconius butterflies. In animals, color vision requires photoreceptor cells that are sensitive to different wavelengths of light. Unlike mammals, butterflies possess photoreceptor cells that are sensitive to the ultraviolet part of the spectrum due to the gene ultraviolet-sensitive rhodopsin (UVRh). This gene has been duplicated in Heliconius butterflies. In individuals expressing both copies of UVRh, behavioral and electrophysiological studies demonstrate that these copies confer sensitivity between distinct wavelengths within the UV portion of the spectrum, enabling them to discriminate between those wavelengths. Interestingly, this phenotype is found only among females within a subset of Heliconius butterflies. However, the genetic mechanism behind this important sexually dimorphic phenotype remains a mystery. In order to determine the genetic basis of this trait, we used long reads and Hi-C scaffolding to build a reference-grade genome assembly of one of the butterflies with sexually dimorphic UV color vision, H. charithonia. We assemble each chromosome, including both sex chromosomes, into individual scaffolds, with most chromosomes spanning only one or a few contigs. We discovered that one copy of UVRh, UVRh1, is on the W chromosome, making it obligately female-specific. We use PCR assays to show that in species that exhibit sexually dimorphic UVRh1 expression, UVRh1 DNA is female-specific, whereas in species lacking dimorphism, UVRh1 DNA is found in both sexes, suggesting that UVRh1 attained W-linkage in one part of the clade, but maintained autosomal linkage elsewhere. We propose two evolutionary models explaining the acquisition of sexual dimorphism of UVRh1 in Heliconius and discuss how to distinguish in future work.

• 1:45 A. M. Raicu, D. Kadiyala, M. Niblock, Y. Yang, A. Jain, K. Bird, A. Seenivasan, K. Bertholf and D. N. Arnosti: The cynosure of CtBP: evolution of a bilatarian transcriptional corepressor. Molecular studies over the past 40 years have revealed the building blocks for the bilaterian body plan, including transcription factors encoded by HOX genes that are key for segmental and tissue identify. Alterations in the structure and expression of sequence-specific transcription factors are key aspects of lineage-specific innovations, but less well understood is how similar modifications to the central transcriptional apparatus may contribute to evolutionary transformations. The C-terminal Binding Protein is an NAD(H)-binding transcriptional corepressor derived from an ancestral lineage of alpha hydroxyacid dehydrogenases; CtBP is found in mammals and invertebrates, and features a core NAD-binding domain as well as a long unstructured C-terminus of unknown function. This factor can act on promoters and enhancers to repress transcription through chromatin-linked mechanisms. Our comparative phylogenetic study shows that CtBP is a bilaterian innovation, whose unstructured C-terminus of over 100 residues is present in all orthologs. Interestingly, while both deuterostome and protostome lineages have one or more copy of this gene, the structure of the C-terminus has undergone radical transformation independently in certain lineages, including in cephalochordates, flatworms, nematodes, and tardigrades. Some of these phyla have been documented to have experienced dramatic losses of core bilaterian genes in the development of their unique body plans. Within the better-conserved arthopod CtBP C-terminal regions, dynamic changes in the spacing of conserved blocks of residues are observed to evolve over short timespans. Also contributing to CtBP C-terminal diversity is the production of myriad alternative RNA splicing products that impact C-terminal structure, including the production of “short” tailless forms of CtBP in Drosophila; these different isoforms may have specific temporal and/or tissue-specific activity. Again, the molecular mechanisms that generate such short forms appear to be independently derived in many lineages. Vertebrates, in contrast to invertebrates, add diversity to their CtBP portfolios through gene duplications; the CtBP C-terminal sequences have diverged between CtBP1 and CtBP2, and the differential genetic activity of these paralogs points to possible changes in their actions as transcriptional corepressors. Interestingly, few lineages outside of ray-finned fish feature any modifications to the unstructured C-termini, raising the possibility that gene regulatory constraints of building the vertebrate body from these enhancer-rich genomes may place specific constraints on the putative C-terminal regulatory domain of CtBP.

• 2:00 Geoffrey Severin, Brian Y. Hsueh, Clinton A. Elg, John A. Dover, Christopher R. Rhoades, Alex J. Wessel, Benjamin J. Ridenhour, Eva M. Top, Janani Ravi, Kristin N. Parent, and Christopher M. Waters: Discovery of a novel phage defense system in Vibrio cholerae. The El Tor biotype of Vibrio cholerae is responsible for perpetuating the longest cholera pandemic in recorded history (1961-current). The genomic islands VSP-1 and -2 are understudied genetic features that distinguish El Tor from previous pandemic V. cholerae. To understand their utility, we calculated the co-occurrence of VSP genes across bacterial genomes. This analysis predicted the previously uncharacterized gene vc0175, herein renamed deoxycytidylate deaminase Vibrio (dcdV), is in a gene network with dncV, a cyclic GMP-AMP synthase involved in phage defense. DcdV consists of two domains; a P-loop kinase and a deoxycytidylate deaminase. Both domains are required for the deamination of dCTP and dCMP and this activity inhibits phage predation by starving replicating virions of dC substrates. DcdV activity is post-translationally inhibited, in a manner analogous to Type III toxin-antitoxin systems, by a unique noncoding RNA. Homologs of dcdV are broadly conserved in bacteria, with distant members found in archaea and eukaryotes. Our results demonstrate that bacteria, like eukaryotes, protect against viral infection by depleting the availability of deoxynucleotide substrates.

• 2:15 Alexander Bricco, Iliya Miralavykomsari, Shaowei Bo, Christian Farrar, Michael T. McMahon, Wolfgang Banzhaf and Assaf A. Gilad​: A Protein Optimizing Evolving Tool (POET) based on Genetic Programming. The development of further techniques in synthetic biology is dependent on reporter genes to generate a quantifiable response on whether the base circuit is set up correctly. Reporter genes for Magnetic Resonance Imaging (MRI) would allow genes to be measured in a non-invasive and safe manner, paving the way for translational use in human subjects. One of the best mechanisms for generating such a reporter gene is Chemical Exchange Saturation Transfer (CEST), which generates contrast without addition of outside metals and allows for the contrast mechanism to be controlled. Previous CEST reporter genes can be further optimized via protein evolution but have proven difficult to improve using typical protein optimization engineering methods. We developed the Protein Optimization Evolving Tool (POET). POET uses genetic programing to identify motifs within peptides that allows them to produce MRI contrast. This method is not only a new way of designing peptides, but due to the nature of the program, a far wider search space of peptides is analyzed, leading to the exploration of novel mechanisms to optimize the production of CEST contrast.

• 2:30 Harvey Lee, Connor Grady, Assaf Gilad: Biosynthesis of an Activatable Fluorescent MRI Contrast Agent. Studies involving the binding of proteins and rare earth elements (REE) are attractive to many researchers due to the versatility of proteins and unique attributes of rare earths. Among REEs, gadolinium is the most commonly used element for molecular imaging in the clinic with more than 30 million injections a year. Several protein-based MRI contrast agents have been reported with attributes such as enhanced relaxivity, stability, and targeting capabilities. Synthesis of these contrast agents can be simply achieved via bioreactors, allowing mass production at an affordable price while eliminating several steps and byproducts from chemical reactions. It is ideal to assess the presence of free ions left in the solution after initiating a binding to avoid reaction with other molecules in-vivo, and an excess amount of protein/chelate may be added to ensure safety. The answer to the question of how much more should be added above the theoretical ratio could differ with unique binding kinetics and adding too much would decrease performance. A current method of evaluating the existence of free rare earths involves the use of Arsenazo III, which is a calcium sensing dye that reacts with REEs as well as uranium, thorium, and zirconium. Here, we sought out to create a biosynthetically producible recombinant protein that directly indicates binding with high specificity for REEs, which can be utilized downstream as an MRI and optical imaging agent upon binding gadolinium. We have developed such a probe and have termed this new construct GLamouR

LINK TO RECORDING: https://youtu.be/Rp08TGSpM94

ZOOM LINK: https://msu.zoom.us/j/91944760863

Meeting ID: 919 4476 0863

Passcode: beacon

Technical Assistant: Louise Mead

Moderator: Maitreya Dunham

• 3:30 Maitreya Dunham: yEvo: a yeast experimental evolution and genomics teaching lab. Watching evolution in action is a compelling way to learn about evolution. We have developed a yeast experimental evolution lab to work well in high school classrooms, while also generating data relevant for our research program. This "win-win" model for teaching labs is infinitely adaptable to individual classroom and scientist needs. I'll discuss our first complete case study on azole resistance, as well as some of the variations that are in progress. I'll also advertise our "franchise" system for any other researchers who might like to join the yEvo team.

• 3:45 Alexa Warwick, Bryce Taylor, Ryan Skophammer, Josephine M. Boyer, Kristin Gunkelman, Margaux Walson, Paul A. Rowley, and Maitreya J. Dunham: Evaluating yEvo: an experimental evolution research experience for high school students. As the resources needed to conduct research in microbial experimental evolution and whole-genome sequencing become more accessible, these experiments can be a powerful tool for teaching evolution. We have developed a series of connected and standards-aligned yeast evolution laboratory modules, called “yEvo”, for high school biology students. In this presentation, we describe our process of designing, testing, and iteratively improving the five yEvo modules as implemented over three years with students from three focal schools. Pre- and post-surveys from 72 students and one-on-one interviews with students and teachers were used to assess our program goals and improve these modules. We measured changes in student conceptions of mutation and evolution, confidence in scientific practices, and interest in STEM and biology careers. Students who participated in module one could better explain the importance of variation in evolution and the random nature of mutation. They also reported increased confidence in their ability to design a valid biology experiment. We used the survey results to identify places where specific curricular interventions could improve student learning. We hope that this collaborative endeavor can serve as a model for other university researchers and K-16 classrooms interested in engaging in open-ended research questions using yeast as a model system.

• 4:00 Benjamin Person, Samantha Johns, Diane Blackwood, Robert T. Pennock: Learning Evolution through Play: Games as an Educational Tool. Video games are increasingly being explored as an avenue to teach science to students of various ages. In this talk, we will highlight some of the keys to using games as an educational tool and discuss how games may best be wielded as a tool in the belt of learning (ranging from guided lesson plans to open student exploration) using the MSU Beacon Salmon Run project as a framework.

LINK TO RECORDING: https://youtu.be/qXX6UG1o_9g

ZOOM LINK: https://msu.zoom.us/j/98695382667

Meeting ID: 986 9538 2667

Passcode: beacon

Technical Assistant: Devin Lake

Moderator: Emily Dolson

• 3:30 Chris Adami and Nitash C G: Information-theoretic characterization of the complete genotype-phenotype map of a complex pre-biotic world. How information is encoded in bio-molecular sequences is difficult to quantify since such an analysis usually requires sampling an exponentially large genetic space. Here we show how information theory reveals both robust and compressed information encoding in the largest complete genotype-phenotype map (over 5 trillion sequences) obtained to date: the space of self-replicators in the digital life system Avida. We also provide evidence that in this "fitness landscape before evolution", the highest fitness genotypes are also the most robust to mutations.

• 3:45 Emily Dolson: What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms? Maintaining a sufficiently diverse population to successfully solve challenging problems is a central challenge in all branches of evolutionary computation. If the population's diversity collapses, the algorithm can prematurely converge on a sub-optimal solution from which is unable to escape. While many techniques have been designed to combat this challenge, we currently lack a clear understanding of what factors contribute to their success or failure in any given situation. One possible source of deeper insight is phylogenetic metrics. Here, I investigate the relationship between these metrics and other diversity metrics across a variety of selection methods and computational problems. I find that phylogenetic metrics provide different information about a population than diversity metrics, and explore the extent to which they are informative about outcomes in evolutionary computation.

• 4:00 Arend Hintze: Evolvability of Developmental Encodings. Artificial neural networks can be defined as a sequence of weight matrices. Typically, when optimizing them using a genetic algorithm, mutations affect single weights, making the optimization process slow and cumbersome. Indirect encodings, on the other hand, use a string of symbols or numbers to describe the network. These symbols get algorithmically translated into the weights of the networks. Now mutations can affect many or all weights allowing for a more effective exploration of the fitness landscape. Developmental encodings are also indirect encodings, but they translate the genome over various steps into the final phenotype. The question is if this more extreme form of encoding provides advantages to evolutionary optimization? Comparing different forms of encodings and their corresponding mutational effect size distribution reveal an exciting relation between both.

• 4:15 Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf, and Cedric Gondro: Evolving Hierarchical Memory-Prediction Machines in Multi-Task Reinforcement Learning. A fundamental aspect of behaviour is the ability to encode salient features of experience in memory and use these memories, in combination with current sensory information, to predict the best action for each situation such that long-term objectives are maximized. The world is highly dynamic, and behavioural agents must generalize across a variety of environments and objectives over time. This scenario can be modeled as a partially-observable multi-task reinforcement learning problem. We use genetic programming to evolve highly-generalized agents capable of operating in six unique environments from the control literature, including OpenAI’s entire Classic Control suite. This requires the agent to support discrete and continuous actions simultaneously. No task-identification sensor inputs are provided, thus agents must identify tasks from the dynamics of state variables alone and define control policies for each task. We show that emergent hierarchical structure in the evolving programs leads to multi-task agents that succeed by performing a temporal decomposition and encoding of the problem environments in memory. The resulting agents are competitive with task-specific agents in all six environments. Furthermore, the hierarchical structure of programs allows for dynamic run-time complexity, which results in relatively efficient operation.

• 4:30 Risto Miikkulainen, Cem Tutum, and Suhaib Abdulquddos: Generalization of Agent Behavior through Explicit Representation of Context. In order to deploy autonomous agents in digital interactive environments, they must be able to act robustly in unseen situations. The standard machine learning approach is to include as much variation as possible into training these agents. The agents can then interpolate within their training, but they cannot extrapolate much beyond it. In this talk we propose a principled approach where a context module is coevolved with a skill module in the game. The context module recognizes the temporal variation in the game and modulates the outputs of the skill module so that the action decisions can be made robustly even in previously unseen situations. The approach is evaluated in the Flappy Bird and LunarLander video games, as well as in the CARLA autonomous driving simulation. The Context+Skill approach leads to significantly more robust behavior in environments that require extrapolation beyond training. Such a principled generalization ability is essential in deploying autonomous agents in real-world tasks, and can serve as a foundation for continual adaptation as well.

• 4:45 Katherine Skocelas, Austin Ferguson, Clifford Bohm, Katherine Perry, Rosemary Adaji, and Charles Ofria: The Evolution of Cellular Restraint in Multicellular Organisms. The major evolutionary transition to multicellularity shifted the unit of selection from individual cells to multicellular organisms. Post-transition, unregulated cell growth is usually maladaptive and called "cancer". Cancer most often arises during cellular replication when mutations disrupt proper regulation. In 1977, British epidemiologist Richard Peto recognized that physically larger species do not exhibit proportionally increased rates of cancer, despite undergoing more cell divisions. Research into this phenomenon (termed "Peto's paradox") has revealed that different species use varied cancer-suppression techniques, involving genetic robustness, error correction, and cellular policing. Evolutionary pressures to produce cellular restraint are hypothesized, but neither they nor their interactions are fully understood. We built a simulation to study this paradox under a range of evolutionary conditions. Specifically, we tested the hypothesis that larger organisms should have a stronger selective pressure to evolve genetic robustness against cancer-causing mutations. We focused on early multicellular organisms (with only one cell type) where cellular restraint prevents cells from overwriting each other. As such, unrestrained cells will outcompete restrained cells within an organism, but restrained cells alone will result in faster reproduction and thus more fit organisms. Many factors contributed to evolved levels of restraint, including genome length (which could limit capacity for restraint), rate of mutations (which erode restraint), and the differential fitness benefit of additional restraint (which could be lost in noise or overwhelmed by mutational decay). Ultimately, when we controlled for these factors we demonstrated a clear selective pressure for greater restraint in larger multicellular organisms.

LINK TO RECORDING: https://youtu.be/IT4O9oSAkUU

ZOOM LINK: https://msu.zoom.us/j/97123824573

Meeting ID: 971 2382 4573

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Technical Assistant: Devin Lake

Led by Tanush Jagdish and Jeffrey Barrick

In 1988, Richard Lenski started an evolution experiment with 12 replicate E. coli populations to study, in real time, broad evolutionary dynamics and patterns such as fitness gains and parallelism. After 33 years and 75,000 generations of evolution, the Long-Term Evolution Experiment (LTEE) continues today. The questions we can pose with this unique system have burgeoned as new technologies have been developed for characterizing and manipulating microbial genetics and physiology. Moreover, surprising evolutionary changes in the LTEE have led to new research directions that weren’t anticipated, such as the repeated emergence of coexistence and the evolution of novel phenotypes that opened previously inaccessible niches.

With a growing number of researchers from around the world using the LTEE as a study system, there is a need for more effective communication and organization. This workshop is a first step in building such a community. It will focus on five aims: a) developing and sharing tools for LTEE-based experiments; b) identifying new and existing LTEE datasets; c) discussing open questions in the field that the LTEE is well poised to answer; d) creating avenues for collaboration and data-sharing between groups pursuing similar ideas; and e) providing a platform for scientists working on specific questions with the LTEE to network with scientists who have different backgrounds and expertise to discuss and troubleshoot common problems, and to learn from the community as a whole.

Our hope is that, moving forward, we can build this workshop into a regular meeting that brings together LTEE researchers from around the world to pursue these aims. The overarching goal of this effort is to allow research using the LTEE as a model system or tool to progress as efficiently as possible by leveraging the expertise, advice, and feedback of the entire community and its collective experience.

LINK TO RECORDING: https://youtu.be/2HPP2d2NSUo

ZOOM LINK: https://msu.zoom.us/j/94614680261

Meeting ID: 946 1468 0261

Passcode: beacon

Moderator: Danielle Whittaker

Introduction: Rich Lenski

A generic characteristic of life is that it is tuned to the conditions found on our planet that enable its existence. What is tuned, specifically, is the chemistry that occurs within cells, and enzymes are what makes chemistry within cells possible by catalyzing reactions. In this talk, I will specifically discuss how we use ancient enzymes as (paleo)sensors of geologic conditions in deep time by highlighting our latest work on biogeochemically essential systems. Leveraging the informatic characteristics of enzyme composition, and the tight coupling between internal (cellular) and external (environmental) conditions that are enabled by enzymatic function, can enable the exploration of early life circumstances.

LINK TO RECORDING: https://youtu.be/6OKGIm1WO50

ZOOM LINK: https://msu.zoom.us/j/96488038206

Meeting ID: 964 8803 8206

Passcode: beacon

Led by Alexander Lalejini

In this tutorial, I'll show you how I compose citable (with a legit DOI) and web-enabled supplemental material for publications. By adding a DOI to your supplemental materials (e.g., using Zenodo or OSF), you can add it to a paper's references and cite the supplement where appropriate throughout the paper. This approach to supplemental material can sidestep the journal's or conference's file format requirements on your supplemental material, which allows you to present your supplemental code/data/information in the most appropriate format. Never paste supplemental source code into a pdf again! Using GitHub + GitHub pages, you can trivially publish your supplemental material as a website. Bring your own tips and tricks to the tutorial for discussion. After the tutorial, we'll discuss things folks have done for supplemental material, things folks have seen that they liked, and things folks have seen that they don't like.

LINK TO RECORDING: https://youtu.be/tFdxALbivnc

ZOOM LINK: https://msu.zoom.us/j/94084598364

Meeting ID: 940 8459 8364

Passcode: beacon

Technical Assistant: Devin Lake

Moderator: Mike Blazanin

• 2:00 Michael Blazanin and Paul Turner: Community context matters in experimental bacteria-phage ecology and evolution. Bacteria-phage symbioses are ubiquitous in nature and serve as valuable biological models. Historically, the ecology and evolution of bacteria-phage systems have been studied in either very simple or very complex communities. Although both approaches provide insight, their shortcomings limit our understanding of bacteria and phages in multispecies contexts. To address this gap, here we synthesize the emerging body of bacteria-phage experiments in medium-complexity communities, specifically those that manipulate bacterial community presence. Generally, community presence suppresses both focal bacterial (phage host) and phage densities, while sometimes altering bacteria-phage ecological interactions in diverse ways. Simultaneously, community presence can have an array of evolutionary effects. Sometimes community presence has no effect on the coevolutionary dynamics of bacteria and their associated phages, whereas other times the presence of additional bacterial species constrains bacteria-phage coevolution. At the same time, community context can alter mechanisms of adaptation and interact with the pleiotropic consequences of (co)evolution. Ultimately, these experiments show that community context can have important ecological and evolutionary effects on bacteria-phage systems, but many questions still remain unanswered and ripe for additional investigation.

• 2:15 Sylvie Estrela: Functional attractors in microbial community assembly. Predicting the composition and function of microbial communities in a given habitat is a major aspiration in microbiome biology. To realize this goal, it is critical to identify which features of microbial communities are reproducible and predictable, which are not, and why. We have addressed this question by studying the assembly of hundreds of communities in simple replicate habitats and connecting the experiments with modeling. We have found that microbial community assembly is generally reproducible and convergent at higher levels of taxonomic community organization and reflects an emergent metabolic self-organization between different functional groups whose ratios can be quantitatively explained with simple models.

• 2:30 Shakeal Hodge, Zhen Ren, Anya Vostinar, and Emily Dolson: More symbionts, more problems: evolutionary stability of host-endosymbiont mutualism is reduced by multi-infection. Endosymbioses (in which a symbiont lives inside a host) exist in many contexts in nature. Interactions between the host and endosymbiont exist along a spectrum from parasitism to mutualism. In mutualistic interactions, both partners benefit. In parasitic interactions, however, the endosymbiont harms the host (often by stealing resources) for its own benefit. Hosts may or may not invest resources in defending themselves from parasites. Previous research in a digital model system called Symbulation has shown that the evolutionary stability of mutualisms between hosts and endosymbionts depends on the rate of vertical transmission (symbiont offspring ending up inside host offspring), with even fairly low rates of vertical transmission being sufficient to maintain mutualism. However, this work was conducted in a scenario where only one symbiont could infect a given host at a time. Here, we investigate the impact of larger symbiont populations within a host on the relationship between vertical transmission rate and mutualism. We show that larger symbiont populations increase the vertical transmission rate needed to maintain mutualism. We hypothesize that this effect is caused by a breakdown in cooperation between the set of symbionts within the host. Investigations into whether this effect can be mitigated by adding extra incentives for cooperation among symbionts is ongoing.

• 2:45 Eric Libby, Rebecka Andersson, Chris Kempes, and Jordan Okie: A null model for predicting the likelihood of prokaryotic endosymbioses. The endosymbiosis that gave rise to mitochondria and eukaryotes is a pivotal event in the evolution of life on earth— unparalleled in terms of its rarity and significance. It is thought to have occurred only once and account for the evolution of all large, complex life. Although it is regarded as a major transition in evolution, it is unlike other major transitions such as multicellularity in that we lack a theoretical framework to predict its likelihood or identify conditions promoting its evolution. To address this knowledge gap we develop a theoretical framework to predict the likelihood that two prokaryotes can form a viable host-endosymbiont pair. Since there are many examples of endosymbioses evolving between larger, eukaryotic organisms, we focus on cell size as a limiting factor. Using allometric scaling laws that describe physiological requirements and ecological abundances as a function of cell size, we construct a null model that predicts the likelihood that two prokaryotes of certain sizes can form a host-endosymbiosis pair.

• 3:00 Tinyiko Maswanganye: Determining evolutionary mechanisms of SARS-CoV-2: Water waste surveillance. Viruses are present in every aspect of the ecosystem and found a way to maintain reproduction in the human body. SARS-CoV-2 of zoonotic origin has adapted to the human body and multiple at increasing rates and spread, making this virus the deadliest in this century. Since the beginning of the pandemic, life hasn’t been quiet, leaving many individuals out of work or school due to public health concerns. Therefore, it is imperative to better the quality of life by monitoring outbreaks in specials populations such as schools, nursing homes, and prisons using Wastewater-based epidemiology (WBE). Wastewater-based epidemiology (WBE) is an effective monitoring method that can help in community-based screening and prevention of emerging or re-emerging viruses. Using wastewater-based epidemiology will help us track the spread of the virus across the campus of North Carolina Agricultural and Technical State University, which would allow an effective contact tracing procedure. In such significant populations, the infections rate tends to be high, which essentially allows the virus to mutate. Therefore, our project aims to evaluate whether evolutionary changes of SARS-CoV-2 will impact the virus proofreading mechanism. Using WBE determine high risk areas by surveillance of water-waste from selected dormitories and monitor emerging variants/mutation. To test will collect water-waste from manhole designated to dormitories across campus, and extract total nucleic acid followed by molecular detection of SARS-CoV- 2 using Reverse Transcriptase real time PCR (RT-qPCR). Following PCR will perform genetic sequencing to determine mutations.

• 3:15 Rachel Richards: TNF Signaling Promotes Effective Restriction of Legionella Infection in Human Macrophages. Legionella pneumophila infection results in a severe acute form of pneumonia known as Legionnaires’ Disease. While this bacteria can typically be cleared by innate immune defenses, the rate of clinical incidence among immunocompromised individuals is rising in the U.S. Legionella infects alveolar macrophages in the lungs and blocks cytokine production to promote pathogenesis and bacterial replication. Previous studies have shown that the loss of TNF activity in alveolar macrophages leads to increased bacterial replication and persistence in vivo, suggesting a critical role of TNF in restricting Legionella infection. However, the role of TNF signaling during Legionella infection has yet to be fully elucidated. Preliminary data demonstrates that TNF signaling is required for Legionella restriction in murine bone marrow-derived macrophages (BMDMs). Thus, I hypothesize that TNF signaling is crucial to restrict Legionella infection in human macrophages. We infected two types of human monocyte-derived macrophages with L. pneumophila strains 16-24 hours following TNF stimulation and used cell death and cytokine production as read-outs. Results show that TNF signaling induces increased cytokine production and possible cell death during infection in vitro to significantly restrict bacterial replication. However, it is not clear if this is downstream of inflammasome-mediated restriction or is through an inflammasome-independent pathway. My research begins to elucidate the essential role of TNF signaling during Legionella infection in human macrophages to deepen our understanding of innate immune responses to intracellular pathogens and the molecular mechanisms behind bacterial replication restriction.

• 3:30 Wei Wang, Ahmad Hejasebazzi, Julia Zheng, and Kevin J. Liu: Build a Better Bootstrap and the RAWR Shall Beat a Random Path to Your Door: Phylogenetic Support Estimation Revisited. The standard bootstrap method is used throughout science and engineering to perform general-purpose non-parametric resampling and re-estimation. Among the most widely cited and widely used such applications is the phylogenetic bootstrap method, which Felsenstein proposed in 1985 as a means to place statistical confidence intervals on an estimated phylogeny (or estimate “phylogenetic support”). A key simplifying assumption of the bootstrap method is that input data are independent and identically distributed (i.i.d.). However, the i.i.d. assumption is an over-simplification for biomolecular sequence analysis, as Felsenstein noted. In this study, we introduce a new sequence-aware non-parametric resampling technique, which we refer to as RAWR (“RAndom Walk Resampling”). RAWR consists of random walks that synthesize and extend the standard bootstrap method and the “mirrored inputs” idea of Landan and Graur. We apply RAWR to the task of phylogenetic support estimation. RAWR’s performance is compared to the state of the art using synthetic and empirical data that span a range of dataset sizes and evolutionary divergence. We show that RAWR support estimates offer comparable or typically superior type I and type II error compared to phylogenetic bootstrap support. We also conduct a re-analysis of large-scale genomic sequence data from a recent study of Darwin’s finches. Our findings clarify phylogenetic uncertainty in a charismatic clade that serves as an important model for complex adaptive evolution.

LINK TO RECORDING: https://youtu.be/VH51GyzGksw

ZOOM LINK: https://msu.zoom.us/j/96288087457

Meeting ID: 962 8808 7457

Passcode: beacon

Led by Acacia Ackles

This sandbox session is an invitation for collaboration on a review of genetic complexity through an anti-oppressive and justice-oriented lens. A pitch for such a paper has been drafted with primarily graduate students across biology disciplines, and we are seeking additional collaborators across all fields and career stages with an interest in untangling the complex history of genetics as a means for oppression. We particularly invite social scientists to contribute their expertise.

The session will consist of (1) a brief background presentation on the foundations of genetic complexity and its use in eugenics and other forms of oppression; (2) a review of the current state-of-the-project; (3) a brainstorming session with participants to identify possible additional directions for the project; and (4) a brief "cite-a-thon" gathering resources for a shared folder for those interested in contributing to the project. Those not interested in joining but interested in the topic broadly are welcome to contribute.

Participants interested in joining the project and contributing as authors will leave with access to all materials from the sandbox session and will be added to a small Slack group to facilitate collaboration on the project. We aim to submit the review with all interested authors included by the end of the 2021-2022 academic year.

LINK TO RECORDING: https://youtu.be/EuOrVnGs0GE

ZOOM LINK: https://msu.zoom.us/j/91634697124

Meeting ID: 916 3469 7124

Passcode: beacon

Technical Assistant: Connie James

Moderator: Alita Burmeister

• 4:00 Alita Burmeister, Carli Roush, Roxy Barahman, and Paul Turner: TolC-specific phage selection results in both evolutionary trade-offs and trade-ups with antibiotic resistance across antibiotic classes. Evolutionary trade-offs are thought to be a fundamental force constraining adaptation in natural populations. Trade-offs and have also been exploited in the treatment of bacterial infections through selection by phage at the expense of antibiotic resistance. However, it is currently unknown how widespread and reliable such trade-offs may be. We recently discovered the potential for trade-offs between phage resistance and antibiotic resistance mediated by the lytic Escherichia coli phage U136B. Phage U136B adsorbs to TolC, which is an outer membrane protein component of a multidrug efflux pump. Loss or modification of the tolC gene is a common evolutionary response to selection by phage U136B, whereby some phage resistant mutants have reduced antibiotic resistance. However, this trade-off strongly depended on the antibiotic, type of selection experiment, and the specific host resistance mutation. In many cases, we even observed trade-ups between phage- and antibiotic resistance, such that evolution of phage resistance also increased resistance to tetracycline or colistin. Here, we investigate the potential for trade-offs and trade-ups between phage U136B resistance and six additional antibiotics from different classes: clindamycin, oxacillin, erythromycin, trimethoprim-sulfamethoxazole, ciprofloxacin, and gentamycin. We compare phage-resistant mutants selected from either traditional fluctuation assays (a sample of all possible phage resistance mutations) or from a period of experimental evolution (a sample of competitively fit phage resistance mutations). For mutants from fluctuation assays, only clindamycin had reliably reduced antibiotic MICs, consistent with an evolutionary trade-off. For all other antibiotics, MICs varied among the mutants, including some with increased, decreased, or no change in MIC, suggesting a strong effect of the specific phage resistance mutation on whether trade-offs or trade-ups evolve. For mutants from experimental evolution, MICs for all antibiotics were often reduced relative to their common ancestor, consistent with a generalized evolutionary trade-off. However, in some cases bacteria evaded the trade-off and had phage resistance with no change in MICs. For oxacillin and erythromycin, both the ancestor and some mutants had MICs above the detection limit, so neither trade-offs nor trade-ups could be ruled out. Overall, our results suggest that phage resistance may sometimes, but not always, be an evolutionary force that maintains antibiotic sensitivity in bacterial populations.

• 4:15 Kyle Card, Jeff Maltas, and Jacob G. Scott: The Multifaceted Nature of Antibiotic Resistance Evolution. The evolution of antibiotic resistance is a serious and growing problem. The ability to predict a pathogen’s capacity to evolve resistance is therefore a critical public-health goal. In previous work, we found that differences between genetic backgrounds can sometimes lead to unpredictable responses in phenotypic resistance and influence its genetic basis by channeling evolution down particular mutational paths. However, it is still not clear how background integrates with demographic and other factors to influence resistance evolution. For example, rare pathways leading to high-level resistance may become more accessible with larger population sizes and increased mutation rates, but can this increase in evolutionary potential outweigh, or be outweighed by, any potentiating or constraining effects of changes in genetic background? We are addressing these questions using a computational approach. We first evolve populations of varying sizes and mutation rates from different genotypes under the influence of genetic drift. We then transfer these evolved populations into a simulated “drug” environment to measure resistance potential. We found that, on balance, large populations with high mutation rates are more evolvable in these drug environments, as expected. However, the maximum effect due to background is more pronounced when the populations are small, and the number of possible initial genotypes is large. In future work, we will examine whether resistance potential is conserved among drug environments that are more similar (i.e., within-class drugs) relative to environments that are less similar (i.e., between-class drugs). We will further examine a time-series of E. coli strains isolated from one population that evolved increases in both population size and mutation rate during the Long-Term Evolution Experiment (LTEE). Above all, our work underscores the need to consider the multifactorial nature of resistance evolution when predicting and treating this phenotype.

• 4:30 Mizpha Fernander, Paris Parsons, Billal Khaled, Amina Bradley, Joseph L. Graves, Jr., and Misty Thomas: Evaluating the Genotypic and Phenotypic Changes in Streptococcus mutans Adaptations to Microgravity Using Experimental Evolution. Background: Maintaining life on extended missions in space is becoming a priority for NASA. It is also becoming evident that space travelers’ immune system undergoes severe dysregulation, and increases in susceptibility to opportunistic infections. Decreased saliva flow and low bone density could make them susceptible to infections by dental caries and plaque causing Streptococcus microorganism pathogenesis. S. mutans is well studied on earth, but its evolution is not studied on extended space exploration. Project Goal: This research study aims to examine the evolutionary adaptation of S. mutans under simulated microgravity (MG) and normal gravity (NG). The study will test whether extended (100-day) exposure could lead to a strain that is more virulent and capable of increased infection. Methodology: For this study populations of S. mutans were propagated (x4) populations under (MG); and (NG) using High Aspect Ratio Vessels (HARVs’) to simulate MG. Virulence was assessed using MIC assays to evaluate antibiotic resistance profiles, acid stress tests, and adherence/biofilm assays. Genetic and cellular changes of S. mutans were evaluated using both DNA and RNA sequencing. Results: DNA sequencing determined that mutations (ptsH, SMU_399, rpoC) occur more readily during adaptation to MG. All microgravity populations showed independent signatures for adaptation. Genomic analysis showed mutations in adhesion, and acid tolerance virulence factors. In sucrose-dependent adhesion (SDA) we saw no mutations in the genes that activate adhesion. However, NG showed mutations in the vikK gene that enhance SDA. NG3 did not restore SDA with mutations in (I407F, 0.37), (V8IF, 0.6) due to vikK mutations in 100% of the population. In sucrose-independent adhesion (SIA) both populations have an SMU_399 mutation that activates the com system gene in SIA showing frequencies in NG4 (0.2)/MG3 (0.6). This also show that SMU_399 has not gone to fixation; with S721I mutations in spaP (0.204/0.19) that activates SIA. Results showed adhesion mechanisms to MG was not altered. In acid tolerance NG reduced in CFU’s after 30 minutes similar to the ancestral. MG reduced in CFU’s after 20 minutes indicating a reduction in acid tolerance. MG1 acquired a mutation in the pnpA gene regulating acid stress. MG3 acquired a mutation in lytR gene that decreases acid tolerance. Results showed no change in antibiotic susceptibility. Discussion/Conclusion: Overall the data indicates that S. mutans decrease in virulence as a result of adaptation to MG. Future Directions: Will examine the co-adaptation of S. mutans to MG and silver. NASA aims to switch to silver in the Potable Water Dispenser (PWD) on the US portion of the International Space Stations (ISS). This data studied adaptation of planktonic populations to MG. Therefore, it will be necessary to examine biofilm phenotypes in the HARVs using hydroxyapatite discs. This will provide better insight into the pathogenic state of the organism.

• 4:45 Olusola Jeje, Liesl Jeffers-Francis, Joseph Graves, Jr., and Akamu Ewunkem: Experimental evolution of Escherichia coli in iron (III) and bacteriophage T7: Pleiotropy and correlated responses. At times a selective advantage of one trait proves detrimental to another. Such negative correlations between traits are called evolutionary trade-offs. Goethe's Law of Compensation reinforced the observation that biological adaptations have some secondary effects on fitness. It was recognized that ‘to spend on one side, nature is forced to economize on the other side’. This perception suggests that cellular resources allocated to one characteristic can lead to reduced fitness in another. With the knowledge of evolutionary trade-offs, we created variants of Escherichia coli K-12 MG1655 that were selected for iron (III) sulphate only, T7 bacteriophage only and for a combination of both iron (III) sulphate plus T7 bacteriophage. We investigated phenotypic and genomic changes of all variants, the control and ancestral populations when exposed to increasing concentrations of antimicrobials such as metals (iron (II), Iron (III), gallium, silver), antibiotics (ampicillin, a β-lactam antibiotic, tetracycline, chloramphenicol, rifampicin) and bacteriophage (T7). We used an experimental evolution approach of daily transfer of E. coli in 1.75 mg/ml iron (III) sulphate for 21 days for the iron-selected variant. The bacteriophage-selected variant was infected with 100 µL of 1:100 dilution of 3.4 × 106 pfu T7 bacteriophage. We showed that iron (III)/phage- selected variants demonstrated superior 24-hour growth in excess iron (III) relative to iron (III) only and bacteriophage only selected variants. Iron (III)/phage variants showed superior growth in excess ampicillin and tetracycline compared to iron-only variant. There was no difference in cell density between iron (III)/phage-selected and iron (III)-selected populations in excess chloramphenicol, sulfonamide, and silver nitrate. However, differences in response of iron (III)/Phage and iron (III) populations to concentrations of chloramphenicol, sulfonamide and silver nitrate were significant. Selective sweeps that might have been responsible for phage attack resistance in the phage-selected group includes hfq and waaC which are active genes against envelope stress. General stress response sweeps that belong to the σS or rpoS regulon were also found. We concluded that E. coli K-12 MG1655 selected for both iron (III) plus T7 phage yielded variants with better resistance to metallic, antibiotic and bacteriophage antimicrobial agents. Single selective sweep might be controlling multiple phenotypic traits, a phenomenon also referred to as pleiotropy. This implies that resistance to certain metals could lead to resistance to bacteriophage and subsequently confer selective advantage to antibiotics on certain bacteria.

• 5:00 Carli Roush, Paul Turner, and Alita Burmeister: Investigating relationships between phage resistance and antibiotic sensitivity in uropathogenic and laboratory strains of Escherichia coli. Fatal multi-drug resistant bacterial infections are a serious and growing problem. This resistance usually occurs in patients with persistent infections, such as cystic fibrosis or recurring urinary tract infections (UTIs). One potential alternative to antibiotic treatment is phage therapy, which uses bacteriophage to kill bacterial cells. Bacteriophage U136B’s receptor is TolC, a component of Escherichia coli’s main antibiotic efflux pump, so mutations which make the bacteria phage resistant can also impact its ability to efflux antibiotics. We previously showed that resistance to phage U136B can lead to both trade-offs and trade-ups in antibiotic sensitivity in E. coli K-12 laboratory strain BW25113. Here, we investigated the potential for such trade-ups or trade-offs in E. coli B strain REL606 and uropathogenic E. coli (UPEC) for six antibiotics. Among 10 phage-resistant mutants of REL606, we found that the relationship between phage resistance and antibiotic sensitivity varies depending on the antibiotic. These mutants have higher sensitivity to three of the six antibiotics, while maintaining or increasing resistance to the other three antibiotics. Among 8 phage-resistant mutants of UPEC, the resulting antibiotic sensitivity varies based on whether phage resistance is partial or complete. UPEC mutants which have complete resistance show higher sensitivity to antibiotics, while strains with partial phage resistance generally have unchanged or decreased antibiotic sensitivity. This preliminary trade-off between complete phage resistance and antibiotic sensitivity in UPEC makes phage U136B a potential candidate for phage therapy that restores antibiotic sensitivity.

• 5:15 Kelyah Spurgeon and Misty Thomas: Assessing the Evolution of Streptococcus mutans Biofilms in Microgravity. There is limited knowledge on the microbial response to long-term space flight conditions. The ability to provide a supply of potable water on the ISS has been a challenge due contamination risk and limited space. Current studies have demonstrated that low-shear stress and microgravity can lead to enhanced growth, biofilm formation, extracellular polysaccharide production, and increase in virulence for many microbial species. Streptococcus mutans is a gram-positive facultative anaerobe commonly found in the oral cavity and is associated with tooth decay in humans. Previous studies have indicated that astronauts display a decrease in salivary lysozyme production and bone resorption making them more susceptible dental disease while in space. Recent reports indicate a switch to silver as the primary biocide instead of the usual Iodine for NASA’s future long-term space travel due to thyroid issues associated with the use of iodine and poor water palatability. Here, we aim to assess changes in Streptococcus biofilm composition due to adaptation to microgravity. Our hypothesis includes two parts parts: 1.Both planktonic and biofilm Streptococcal communities will evolve to display increased resistance to acid, antibiotics and oxidative stress when exposed to long-term microgravity. 2. Resistant communities will harbor mutations that will enhance S. mutans adhesion and increase biofilm formation. For growth in simulated microgravity we use high aspect ratio vessels (HARVs). Our previous assessment of planktonic S. mutans phenotypes and genotypes with colloidal silver treatment showed that there were changes which may be associated directly with microgravity compared to normal gravity. While the planktonic form of S. mutans displayed no specific changes in antibiotic resistance, acid tolerance and adhesion due to microgravity, our findings suggest that these factors for S. mutans virulence is dependent upon the formation of biofilms.

LINK TO RECORDING: https://youtu.be/N41hFo1bSz0

ZOOM LINK: https://msu.zoom.us/j/93183476987

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Moderator: Danielle Whittaker

Introduction: Emily Dolson

Predictive Coding, the idea that brains predict the world around them, has become dominant in cognitive science, neuroscience, and Artificial Intelligence. As an Artificial Life researcher, I am attracted to the bizarre and the unusual, which brought me to study the concept of failure in prediction. In this talk, I will present my work on visual illusions (sometimes considered as perceptual failures), their predictive roots, and the artificial neural networks that can reproduce and discover new illusions. I will also explain how "failure to predict" can be used as a biosignature to detect life on Earth, and possibly on other planets.

LINK TO RECORDING (includes the chat): https://mediaspace.msu.edu/media/BEACON+Congress+Keynote+3+-+Lana+Sinapayen/1_wf0eoo11

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EXPERIMENTAL EVOLUTION

1. Isaac Gifford and Jeffrey E. Barrick: Watching Transposon-driven Bacterial Genome Evolution in Action. Transposons are traditionally considered to be “parasitic DNA,” however they have also been shown to improve the evolvability of their hosts by increasing mutation rates. Additionally, colonization of genomes by transposons, their subsequent proliferation, and the genome rearrangements they catalyze are thought to be important for the evolution of bacterial symbionts and pathogens. Much of our understanding of the role of transposons in genome evolution is based on comparative studies of genomes that have already gone through colonization and genome reduction. To improve our understanding of the early events in genome colonization as well as the timing and course of proliferation and genome rearrangements, we are performing a combination of laboratory and in silico evolution studies. The model bacterium Acinetobacter baylyi colonized with a hyperactive mariner transposon will be cultured over a period of up to two years to observe the proliferation of new transposons and rearrangements caused by recombination between them. These experiments will also examine the effect of selection on these processes by comparing strains in adaptive evolution experiments with those from mutation accumulation experiments. In parallel, we are developing a simulation program for modeling the long-term effects of a new transposon on the evolution of a bacterial genome. Rates for transposition, recombination, and mutation determined from the experimental studies of A. baylyi will be incorporated into these simulations. This combination of computational and laboratory approaches will allow us to visualize these processes and study how these evolutionary parameters interact to determine the initial success and long-term fate of a newly acquired transposon and the genome it colonizes.

2. Ivan Mangal, Carli Roush, Eddy Tzintzun-Tapia, Paul E. Turner, and Alita R. Burmeister: Experimental Evolution of Plaque Size in Phage U136B. The rate at which phage adsorb to their hosts is a key indicator of a phage’s fitness in environmental and therapeutic settings. Previous studies with phage lambda have reported reduced plaque size in phages with faster rates of adsorption. Here, we investigated how phage U136B evolves in response to host resistance by comparing the plaque sizes of experimentally evolved phages to their ancestor. In particular, we predicted that evolved phages under selection for faster adsorption would produce smaller plaques. To test this prediction, we determined plaque sizes of evolved phage U136B isolates from Days 5 and 10 of a 10-day coevolution experiment. Plaques were photographed and analyzed using ImageJ software, with an average of 781 plaques analyzed per phage isolate. Contrary to our hypothesis, we saw a variety of results, with plaque size increasing in some populations and decreasing in others. In fact, the phage isolate with the smallest plaque size was separately shown to have the slowest adsorption rate relative to the ancestor. We also observed differences in plaque sizes between Days 5 and Days 10, suggesting within-population variation, continued evolution, or both. Future work will involve identifying mutations in evolved U136B mutants and how these mutations impact adsorption rate and plaque size.

3. Brittany Sanders, Sydney Townsend, Maria Ford, Misty Thomas, and Joseph Graves: In the Light of Evolution: Evaluating the Effects of Evolutionary Adaptations in Two-Component Response Systems. Bacteria continuously interact with their surroundings and are regularly exposed to stressful environmental conditions. As a result, microorganisms have evolved various biological response mechanisms to help regulate cellular homeostasis and their survival under certain stressful environmental conditions. These biological response mechanisms act as the cells “sensory organs” that receive physical stimuli from the environment, inducing a cascade of intracellular signals to form an external cellular response. Bacteria must be able to sense, respond and acclimate to these stressful conditions by: (1) Acclimation- short term responses via the upregulation or downregulation of gene expression or (2) Adaptation- permanent change due to the acquisition of simple mutations in the genome. Two-component response systems (TCRS) are among the best studied genetic elements for environmental acclimation in bacteria but very little is known about their role in adaptation. TCRS are efficient for short term acclimation and survival, however, long term exposure to adverse environmental conditions tend to select for differential reproduction leading to the survival of adapted clones and therefore their role in adaptation is less well known. Our project goal is to understand the role TCRS play in environmental adaptation and the fitness costs associated with this adaption. We hypothesize that, mutations in the TCRS CusS/R leading to adaptation to high levels of silver (a well-studied stressor) will decrease the overall fitness of the bacteria characterized by a decreased growth rate, and quick reversion when the stressor is removed. To investigate evolutionary adaptations within TCRS we use In vivo recombineering technology to insert chromosomal mutations in the cusS gene known to be associated with silver resistance into Escherichia coli K12 MG1655. We then tested for bacterial fitness with comparative growth curves, competition assays and reverse selection experiments. As a result of recombineering four silver resistant mutant CusS strains (R15L, T14P, T17P and N279H), growth assays showed that despite an increase in resistance to silver their overall growth rate in absence of the stressor was decreased. Based on these findings, we believe our competition assays will show that the WT will outcompete the adapted mutants. In conclusion this research aims to show that the acquisition of mutations in TCRS have biological consequences on both fitness and function of the organism. Activation of the CusS/R system leads to expression of a silver efflux pump. We believe that the decrease in fitness is due to constitutive expression of this efflux pump which would require significant energy input from the cell, thereby decreasing other essential processes. Although, in presence of silver this evolutionary tradeoff would be worth the cost of survival. Future Directions: Given the essential role TCRS play in various bacterial processes and their absence from mammals, synthetic engineering of TCRS has been proposed for many applications ranging from bioremediation to antimicrobial drug design. Therefore, better understanding adaptation in these systems will better help researchers design systems of potential medical/industrial use.

4. Eddy Tzintzun-Tapia, Carli Roush, Ivan Mangal, Paul E. Turner, and Alita Burmeister: Evolution of Bacteriophage Adsorption Rates to the Antibiotic Efflux Pump TolC. Bacteriophages (phages) are ubiquitous in nature and have garnered recent attention for their therapeutic potential in combating multi-drug resistant bacterial infections. For example, some bacteriophages can be utilized to exert selection pressures on their hosts, steering host populations to be phage resistant while also becoming more antibiotic sensitive. However, less is known about how phages evolutionarily respond to this type of resistance. In our previous work, we conducted a 10-day evolution experiment with 10 populations containing Escherichia coli and phage U136B, which uses the TolC antibiotic efflux pump as a receptor. In that experiment, we found that five phage populations went extinct by Day 5, while five phage populations persisted through Day 10. In this study, we compared the adsorption rate of evolved phage isolates to their ancestor phage, predicting that the Day-10 phage isolates would have faster adsorption rates than the ancestor. We found that three of the five evolved Day-10 phage isolates had faster adsorption rates than the ancestor phage, while the other two had either the same or slower adsorption rates. We also compared phage isolates from all 10 populations at Day 5 (before any extinctions) to determine whether adsorption rate differs between phage populations that eventually went extinct and those that persisted. We predicted that Day-5 phage isolates from populations that persisted through Day 10 would have faster adsorption rates than phage isolates from populations that later went extinct. We found that two of the five phage isolates from populations that persisted through Day 10 had faster adsorption rates than the ancestor phage, while all five of the phage isolates from populations that later went extinct had similar adsorption rates to the ancestor. These results give us insight into the causes of extinction in phage-host systems and how phages may evolve with their hosts to avoid extinction.

GENETICS & GENOMICS

5. Daniel Ananey-Obiri and Kristen Rhinehardt: Natural Language Processing Techniques for Antibiotic Resistance Prediction. Antibiotic resistance increasingly has become a threat to global health as it hampers the efficacy of current antibiotics and development of new antibiotic drugs. Also, more than $55 billion is spent on antibiotic resistance (AMR) and 23,000 die from it annually. Appropriate identification of AMR is fundamental to the administration of the right antibiotics and also for epidemiological purposes. However, the mechanisms for identifying sequences with AMR genes such as minimum inhibitory concentration are tedious and time consuming and using sequence similarity-based models have also not performed to satisfaction due to the highly diverse and complexity of such sequences. To explore AMR among genomic sequences we applied word vectors to bacterial sequences using Global vectors (GloVe), skip-gram (SG), and continuous bag of words (CBOW) neural embeddings and used them as embedding layers in bidirectional recurrent neural networks (BiRNNs) to classify antibacterial resistant protein sequences. The combination of the bidirectional RNN with GloVe, SG, and CBOW were compared the Blast, resistance genes identifier (RGI), and One-hot encoding model. BiRNNGloVe outperformed both BiRNNSG and BiRNNCBOW on all metrics, with 99%, 98.85%, recall, and precision, respectfully. The second most-performed model, BiRNNSG was about 1 percent less than BiRNNGloVe on all metrics. All RNNs with embedding layers immensely outperformed the baseline models. By these, we will be able to accurately identify patients who suffer from antibiotic resistance in a timely manner, and subsequently help health providers to take appropriate decisions to save the life of patients.

6. S. W. Davenport and S. H. Harrison: Analysis of Oceanic Fungal Gene Structure and Alignment via Generative Adversarial Networks. Our project investigates conserved genetic regions found for fungal metagenomic sequences in the ocean as concerns an overall objective to computationally study how genes vary with respect to diverse environments. For conducting this study, we analyzed genomic data across yeast lineages by identifying orthologous associations across these genomes, specifically for the examination of well-conserved kinases. We specifically utilized annotative and experimental information from laboratory-based studies of Saccharomyces cerevisiae, and aligned these kinases to fungal transcriptomic data coming from 68 different environmental locations as recorded by the Tara Oceans project. A generative adversarial network (GAN) was then used to evaluate and simulate fungal alignment data in conjunction with a classifier for differentiating environmental parameters for the fungal metagenomic data. Our approach overall demonstrates how computationally guided evaluations of genetic variation across environments can be effectively achieved with GAN-based analysis.

7. Elliot Majlessi, Vignesh Srihard, Joe Burke, Neal Hammer, and Janani Ravi: Evolution of Staphylococcal Antibiotic Resistance Systems. Bacteria continuously evolve and adapt to their environment — when pathogens encounter antibiotics administered to the host, they evolve further, giving rise to antibiotic resistance. Resistance can be innate or acquired. But these resistance mechanisms are believed to have evolved from resistant genes, which can often spread from one pathogen to another via mechanisms such as horizontal gene transfer. Yet, we still lack detailed characterization of antimicrobial-resistant genes, proteins, and genomes, especially in the context of their evolution and origins. Here, we apply our computational approach to characterize the Staphylococcal antibiotic-resistant proteins across bacteria. This approach is based on a novel computational framework we recently developed for characterizing bacterial genomes and operons using comparative genomics, molecular evolution, and phylogeny. Specifically, we are studying the conservation and modularity of Staphylococcal genes and proteins involved in antibiotic resistance by mapping the constituent domains in terms of their phyletic spreads. Our work will establish the nature and evolution of Staphylococcal antibiotic resistance systems including Methicillin- and Vancomycin-resistant Staphylococcus aureus species (MRSA, VRSA).

8. Vignesh Sridhar, Joe Burke, Elliot Majlessi, Karn Jongnarangsin, Arjun Krishnan, and Janani Ravi: Developing a machine learning approach to determine gene/protein features to classify bacterial groups. A bacterial pathogen begins its evolutionary course as an environmental organism, branching out into commensals, symbiotic intracellular bacteria, en route to becoming opportunistic pathogens. Further, these pathogens encounter antibiotics administered to the host and continue to evolve ultimately giving rise to antibiotic resistance. Therefore, it is critical to compare and contrast bacterial groups to better understand the conservation and modularity in pathogen antibiotic resistance. Comparative genomics and pangenomics enable researchers to identify genomic features across different bacterial groups, such as pathogens/nonpathogens, or host-specific pathogens. Such analyses are particularly helpful in identifying genes that are conserved and unique to different subsets of organisms. While characterizing these genes further will provide valuable molecular insights for the original questions of interest, currently, there is a dearth of tools that provide automatic identification of such genome-/protein-level features. We are, therefore, developing a computational approach that takes the results of typical comparative genomic and pangenomic workflows to identify and characterize gene/protein-level functions for specific functional phenotypes. Our approach works by integrating multiple scales of data (i.e., from protein motifs/domains to genome organization) across the tree of life. These data become input features for a supervised machine learning model designed to classify bacterial groups or phenotypic attributes of interest. Examining the importance of all the features in the trained model will help us identify and characterize genes/proteins of interest in an unbiased and comprehensive manner. Here, we apply this approach to identify novel genomic features that contribute to antibiotic resistance. This computational framework will be especially valuable to tackle emerging and understudied zoonotic pathogens and infectious diseases. We will also integrate this ML framework with our MolEvolvR approach to characterize the prioritized proteins.

SYNTHETIC BIOLOGY

9. Victor Li and Jeffrey E. Barrick: Exploring Evolutionary Stability and Fitness Effects of Transgenes in T7 Phage Using Golden Gate Assembly and RB-TnSeq. Viruses with transgene insertions could be useful tools in the fight against disease. Transgene insertions could provide additional functions for phage therapy applications, as well as attenuate viruses for live attenuated vaccines. We plan on using several methods to modify the genome of T7 phage with transgenes in order to study their effects on fitness and their evolutionary stability. Using a strain of T7 phage with the native BsmBI restriction sites removed, we plan on assembling a T7 phage genome with transgene inserts using an 11 part Golden Gate assembly reaction. We also plan to use an RB-TnSeq based system to randomly insert barcoded sequences into the T7 genome. These sequences will contain the trxA gene flanked by BsmBI recognition sites. The trxA gene will then be selected for on a ΔtrxA Escherichia coli host, and the BsmBI recognition sites can then be used to replace the trxA gene insert with a transgene insert of our choosing. We plan to use this method to explore which areas on the T7 genome can be used to express transgenes as well as insert transgenes into suitable regions. We plan to use both methods to explore the potential fitness effects and evolutionary stability of our transgene insertions through experimental evolution.

10. Cameron T. Roots and Jeffrey E. Barrick: Approaches for Engineering Virus-Based Biotechnologies that are Safe from Evolution. New approaches to phage therapy and the development of live attenuated vaccines could help combat multidrug-resistant bacteria and the ever-present spread of communicable diseases. We are beginning to test virus engineering strategies using bacteriophage T7 as a model system. In our first aim, we will engineer T7 to display azide groups on its surface. We hypothesize that attaching enzymes and other molecules to these azide groups using click chemistry can flexibly expand phage function in ways that may be untenable through fusion proteins encoded on the phage genome. Azide groups will be incorporated by expressing T7 capsid proteins from a plasmid in specialized host cells that also have an orthogonal translation system that recodes the amber stop codon to 4-azido-phenylalanine. Wild-type phages infecting these cells will produce chemically modified but genetically wild-type progeny. Thus, improved phage function does not come with a risk of spreading recombinant DNA. In our second aim, we will engineer T7 genomes with deoptimized gene expression architectures by inserting additional promoters and terminators that modularize T7 gene expression and by altering codon usage in key genes. We hypothesize that these types of modification will attenuate phages in ways that are not easy for evolution to recover. Redesigned T7 genomes will be simulated in silico to estimate how the modifications affect fitness. Promising genomes will then be assembled and evolved to evaluate whether they achieve stable attenuation, such as what one would like to engineer in a live vaccine, or how they mutate to restore wild-type fitness. These aims will contribute to the development of design principles for virus-derived technologies in medicine and agriculture as well as advance our understanding of microbial evolution control.

COMMUNITIES & COLLECTIVE DYNAMICS

11. Eliot Haddad: Bacteroides is associated with archetypal constituents of the Western diet and decreased urinary glycocholate in pregnant women. The human organism is better classified as a holobiont due to its mutualistic associations with vast populations of microorganisms. Specifically, the gut microbiota is associated with numerous health outcomes and metabolic functions. Diet is a major influence on the gut microbiota, which in turn can produce microbially-derived metabolites that have downstream effects on host physiology. However, many of these interactions have yet to be sufficiently characterized for future mechanistic exploration. As such, our aim was to identify associations between urinary metabolites, dietary intake information, and fecal microbial samples to elucidate potential biomarkers and metabolic interactions in a sample of pregnant women. Of n=27 women enrolled in the Pregnancy Eating and Postpartum Diapers study, n=23 provided fecal samples, n=26 provided urine samples, and n=18 completed 24-hour dietary recalls at 36 weeks gestation. A resulting pool of 342 taxa, 100 dietary constituents, and 277 urinary metabolites were statistically analyzed in R. Bacteroides was negatively correlated with urinary glycocholate, a bile salt used to facilitate the absorption of fats. Bacteroides also explained most of the variation in beta diversity between participants and was therefore deemed a taxon of interest. Participants exhibiting Bacteroides dominance consumed more total fats, sodium, and protein, which are archetypal constituents of the Western pattern diet. These results suggest that Bacteroides may be associated with unhealthy dietary choices and decreased urinary excretion of glycocholate, which has implications for future studies examining links between the gut microbiota, diet, and overall health.

12. Mia Van Allen, Azam Sher, Lixin Zhang, and Linda Mansfield: Plasmid-Mediated Transfer of Antibiotic Resistance Genes (ARGs) to Commensal and Multi-Drug Resistant Bacteria. Antibiotic resistant (AR) pathogens have become a major health problem: the CDC announced we are now existing in a post antibiotic era. Plasmids are the carriers of antibiotic resistance genes, and they spread between bacteria in the microbiome via a horizontal gene transfer mechanism called conjugation. During each conjugation event, plasmids enter a host cell and can express their antibiotic resistance genes, resulting in newly acquired antibiotic resistance for that cell. This process of unrestrained AR plasmid spread cultivates an evolving reservoir of antibiotic resistant pathogens and commensal bacteria in the human gut microbiome.  This study aimed to replicate and observe the rate and patterns of transconjugant frequency of fluoro-tagged plasmids in combinations of commensal, pathogenic, and lab strain bacteria in vitro. Conjugation protocols that allowed for quantitating transconjugation events using both introduction and absence of antibiotic pressure for selection were created and employed. The transconjugant colonies were confirmed using colony PCR with primers selecting for presence of green fluorescent protein that exists within the plasmid. Fluorescent microscopy was used to observe the transconjugants plasmid directly. Using the transconjugant frequencies obtained, predictions of plasmid spread could be made that model those in the human gut microbiome. Additionally, the individual combinations of donor and recipient bacteria could give insight into strain-specific features that affect transconjugant frequency and plasmid spread effect. Understanding plasmid spread between gut microbiota is crucial to gain insight on how potential treatments can be developed to combat the spread of antibiotic resistance genes.  

DIGITAL EVOLUTION

13. Mitchell Johnson and Jamie Schmidt: Developing MABE2. We will be giving a brief explanation of our work on MABE2, and how someone with little experience with MABE2 is still able to setup and run a digital evolution experiment. We will also be giving a thorough explanation of the underlying structure of MABE2.

14. Stella Li, Ken Reid, Hannah Peeler, Yuan Yuan, Andrew Sloss, and Wolfgang Banzhaf: Benchmarking of the Shackleton Genetic Programming Framework for LLVM Compiler Optimization. LLVM IR (low-level virtual machine intermediate representation) is an intermediate step in the compilation of computer code. LLVM compilers allow optimization by using a sequence of steps (passes) to improve run-time or other criteria. Genetic Programming (GP) is an algorithm that is inspired by the natural selection process and can automatically generate computer programs with better performance throughout generations. The Shackleton Framework employs Elitist Linear Genetic Programming to automatically search for close-to-optimal sequences of LLVM optimization passes. In preliminary testing, Shackleton is able to evolve a pass sequence that resulted in up to 20% improvement in execution speed over base pass sequences when applied to LLVM IR. The goal of this research is to improve the Shackleton Framework, to find close-to-optimal hyperparameter settings, and to systematically evaluate its performance on various benchmarks by comparing it to the default LLVM optimization levels and a hand-written baseline optimization sequence. The Taguchi Method - a cost-effective way to tune the performance of each parameter - is used to implement the benchmarking experiments. The benchmarking process is done primarily on the Backtracker Algorithm of the Subset Sum Problem, which is to be extended to additional benchmarks in the next stage. Finally, runtime analysis is performed using the standard Taguchi analysis method to determine the efficacy of the optimization framework.

15. Arnav Narula, and Ryan McGee: Evolution of Information Compression in Biological Networks. Organisms that integrate more sensory information about environmental conditions are better able to match their morphology and behavior to the demands of the environment and are more likely to be favored by natural selection. Hence, an organism’s phenotype, and thus fitness, can be traced in part to the information capacity of its sensory networks (e.g., biochemical signaling networks, transcriptional regulatory networks, neural circuits). Environmental signals are noisy, and much of the variation may be uninformative about the selection pressures that dictate which phenotype should be adopted. In theory, an ideal sensory network should follow the information bottleneck principle, where the network achieves a compression of the input signals that encodes as much as it can about the meaningful environmental features, but as little of the irrelevant noise as possible. However, the conditions in which natural selection produces networks that adhere to the information bottleneck principle is an open question. In machine learning, some artificial neural networks, which share properties with many feed-forward biological networks, exhibit this kind of information compression after training. These findings offer interesting connections and methodologies for studying the evolution of information compression when networks are “trained” by natural selection. We analyze the evolution of information processing in biological networks by synthesizing insights from machine learning with information theory and evolutionary mechanisms. We implement methods for measuring information in computational network models and use these tools to analyze information properties of networks generated by natural selection. Our results offer insight into how information flow in evolved biological networks deviates from the precise information processing observed in trained artificial neural networks.

16. Samuel Chen, Lauren Sosinski, Joseph Burke, John Johnston, and Janani Ravi: MolEvolvR: A modern web framework for characterizing novel and understudied proteins using molecular evolution and phylogeny. With the emergence of new zoonotic and antimicrobial resistant pathogens, the need for fast classification of protein function and homology is a key step in understanding these organisms. Studying how bacterial pathogenic proteins evolve can help identify lineage-specific and pathogen-specific signatures and variants, and consequently, their functions. We have developed a streamlined computational approach for characterizing the molecular evolution and phylogeny of target proteins, widely applicable across proteins and species of interest. Our approach starts with query protein(s) of interest, identifying their homologs, and characterizing each protein by its domain architecture and phyletic spread. We have developed the MolEvolvR webapp to enable biologists to run our entire workflow on their data by simply uploading a list of their proteins of interest. The webapp accepts inputs in multiple formats: protein/domain sequences, multi-protein operons/homologous proteins, or motif/domain scans. Depending on the input, MolEvolvR returns the complete set of homologs/phylogenetic tree, domain architectures, and common partner domains. Users can obtain graphical summaries that include MSA and phylogenetic trees, domain architectures, domain proximity networks, phyletic spreads, co-occurrence patterns, and relative occurrences across lineages. This tool has direct applications in the fields of pangenomics and metagenomics, where proteins of interest are identified but not always easily classified. With MolEvolvR, users wield a powerful and easy to use workflow for a wide range of protein characterization analyses, including data summarization and dynamic visualization. The webapp can be accessed here: http://jravilab.org/molevolvr.

EDUCATION

17. Eric Berling, Chet McLeskey, Michael O'Rourke, and Robert T. Pennock: Virtues-based Responsible Conduct of Research Education: BEACON and Beyond. In 2013, as part of BEACON’s commitment to integrity and excellence, the Scientific Virtues Project and the Toolbox Dialogue Initiative collaborated to craft and pilot virtues-based Responsible Conduct of Research (RCR) training workshops with the BEACON center. Our approach, which aims to foster a culture of excellence and integrity in university and research settings, supplements and infuses traditional RCR education with an appreciation and understanding of the scientific virtues. Through discussion-based RCR training workshops, our approach helps researchers think about the ethical dimensions of scientific practice through the lens of scientific excellence. Our BEACON participants helped shape and develop this approach, and participant feedback was enthusiastic and encouraging. In the past few years, we have been able to expand our virtue-based approach to RCR education beyond BEACON, bringing our approach to RCR education to other units across the Michigan State University (MSU) campus, including those outside of STEM fields. This virtues-based approach is now the foundation of the VERITIES Initiative, which is an NSF-supported institutional transformation initiative at MSU, which will allow us to continue to augment RCR education throughout the university with our virtues-based approach that was piloted and developed here at BEACON.

18. Louise Mead: Using backwards design to generate assessment items for evolution understanding. Good pedagogy promotes using backward design in the development of college courses and classroom activities. Over the past few years instructors and faculty from BEACON, MSU, and the Society for the Study of Evolution have collaborated on a set of learning objectives for an undergraduate upper-level evolution course. These learning objectives are ready for community feedback before they are shared posted on CourseSource and used to aligned assessment items for CODON Learning, a new software platform designed to create and teach inclusive, high-structure classes.

19. Diane J. Blackwood, Matthew Rupp, Charles Ofria, and Robert T. Pennock: Avida-ED 4: Adding More Resource Options. In past versions of Avida-ED, either present and unlimited or absent. Avida-ED 4 introducees limited resources with some options for spatial distribution. The amounts and pattern of distribution is set for each of the 9 resources individually. This permits student discovery of ecological concepts using a familiar, award-winning software platform.

20. Yemi Shin: Avida-ED 4 Gets a Makeover. Avida-ED 4 is upgraded with more usability features including dragbars to resize the screens, and a new drag and drop backend that is more extensible and easy to use. Come join me for a session demonstrating the updates and how Avida-ED 4 might be of use in your next evolutionary biology classroom.

ZOOM LINK: https://msu.zoom.us/j/93023816667

Meeting ID: 930 2381 6667

Passcode: beacon

Technical Assistant: Louise Mead

Led by Ryan Skophammer and Bryce Taylor

Experimental evolution can be a powerful demonstration of the process of natural selection in a classroom setting. These long-term projects help students develop basic lab techniques and lead to a better understanding of diverse biological concepts. However, it can be tricky for educators to get started without assistance from experienced experimental evolution researchers. On the flip side, experimental evolution researchers may not be aware of how best to utilize the topic in a classroom setting. In this sandbox, we will share our experiences in teaching experimental evolution at the high school level. We will then introduce several experimental evolution lab exercises that can provide a good jumping off point for educators new to the field. We will end with a group discussion on participants' experiences, ideas, and questions related to the topic. We hope that all participants come away with new ideas and a larger network of educators interested in teaching experimental evolution.

Note: This session will *not* be recorded.

ZOOM LINK: https://msu.zoom.us/j/94486530127

Meeting ID: 944 8653 0127

Passcode: beacon

Technical Assistant: Mike Wiser

Moderator: Matthew Andres Moreno

• 2:00 Matthew Andres Moreno: Lessons Learned Administering a Summer Workshop. The Workshop for Avida-ED Software Development (WAVES) is a ten-week, full-time software development experience that matches early-career participants with mentors working on software for digital evolution and public-facing science outreach. The workshop came together abruptly in 2020 in response to the sudden need for fully-virtual research experiences. In addition to outlining the objectives and format of the WAVES workshop, in this talk, I’ll be sharing lessons I learned as the lead workshop coordinator, touching on topics such as

  • soliciting and reviewing applications,

  • organizing workshop materials,

  • devising team-building and social activities,

  • running virtual group meetings, and

  • showcasing participant achievements.

As a first-time coordinator now rounding out my second year in the role, there have been a lot of lessons learned!

• 2:15 Charles Ofria, Emily Dolson, and Matthew Andres Moreno: Empirical: A Scientific Software Library for Research, Education, and Public Engagement. The objective of the Empirical C++ Library is to facilitate efficient, reliable, and broadly accessible scientific software. The ubiquitous availability of internet-connected mobile and desktop computing creates incredible potential for low-barrier, hands-on scientific outreach across broad educational and general audiences. The Emscripten compiler, which enables source code originally written for research computing to run in web browsers, provides an exciting opportunity to realize the potential of research software for public outreach via installation-free access and rich graphical user interfaces. The Empirical C++ library leverages Emscripten to provide a streamlined framework for attaching a mobile-friendly, web-based user interface to existing software that requires no domain knowledge in HTML, CSS, and JavaScript. This talk will provide a hands-on introduction to Empirical’s web tools. In service of our other objectives --- efficiency and reliability --- Empirical also includes more general-purpose debugging, metaprogramming, and data management tools, as well as utilities specially relevant to digital evolution such as phylogenetic trackers and the MABE2 framework. Our presentation will touch on these topics as well.

• 2:30 Emily Dolson and Abigail Wilson: A randomization-based approach to normalizing phylogenetic metrics? Phylogenetic tree analysis is a crucial tool for understanding evolutionary history. When measuring phylogenies of different sizes and shapes, it is important to have viable metrics that can be used for comparison. However, many phylogeny measurements are very sensitive to tree size. For example, phylogenetic diversity gets inflated as phylogenies get larger, making it difficult to meaningfully compare over time or between different populations. This problem is exacerbated in the context of digital evolution, where many assumptions about reconstructed phylogenies from nature are violated and it is unclear whether traditional approaches to normalizing phylogeny metrics are valid. This presentation will discuss approaches to normalizing phylogeny metrics in computational models. Specifically, we will be examining a randomization based approach in which thousands of hypothetical trees are generated and metrics for those trees are recorded and stored for normalization, providing a wide spectrum of possible tree shapes and sizes. The optimal end result of this project is to provide more insightful metrics to a user by producing both a numerical value for their measurement as well as its corresponding percentile mark.

• 2:45 Santiago Rodriguez Papa, Matthew Andres Moreno, and Charles Ofria: SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications. Event-driven genetic programming representations have been shown to outperform traditional imperative representations on interaction-intensive problems. These representations organize genome content into modules that are triggered in response to environmental signals, simplifying simulation design and implementation. Existing work developing event-driven genetic programming methodology has largely used the SignalGP library, which caters to traditional program synthesis applications. The SignalGP-Lite library enables larger-scale artificial life experiments with streamlined agents by reducing control flow overhead and trading run-time flexibility for better performance due to compile-time configuration. Here, we report benchmarking experiments that show an 8x to 30x speedup. We also report solution quality equivalent to SignalGP on two benchmark problems originally developed to test the ability of evolved programs to respond to a large number of signals and to modulate signal response based on context.

• 3:00 Lanea Rohan and Aria Killebrew Bruehl: Planning for the future of MABE2: A summer of documentation and testing. The second Modular Agent-Based Evolver framework (MABE2) is an open-source research platform that provides accessible tools for conducting evolutionary computation and digital evolution research. MABE2 reduces the time between constructing a hypothesis and generating results by providing a library of modules that connect to form a variety of experiments. To promote use among interdisciplinary researchers, modules are connected and adjusted via a simple text interface (i.e., the user does not need to add or edit any code). However, if the user requires modules beyond the existing library, MABE2 provides a set of practical tools for developing additional modules. With the understanding that MABE2 is a large piece of software, this summer we created a documentation guide and testing framework as part of the 2021 Workshop for Avida-ED Software Development (WAVES). In this talk, we will highlight the role of the documentation and testing framework in the MABE2 user experience through a demonstration of constructing and running a custom experiment. By creating the documentation and testing framework, we hope to make MABE2 more approachable to new users and more useful to the interdisciplinary research community.

• 3:15 Tait Weicht, Matthew Andres Moreno, and Charles Ofria: Moving scientific computation into the browser. Providing the means to replicate an experiment is a powerful tool for scientific engagement with both the general public and one’s professional peers. Modern web browsers are now powerful enough to run complex simulations with dynamic graphical user interfaces inside of a web application, shareable with anyone by just copying a link. However, a steep learning curve in modern web design and cross-compiling to target web browsers can prevent researchers from taking advantage of this platform. Empirical, a C++ library, aims to streamline the browser-based deployment of scientific software. We give an overview of some of the prefabricated Bootstrap-based web components provided by Empirical that can quickly turn a command-line tool into a browser-based one. We also discuss some approaches to responsive web development to support mobile devices in the context of scientific web applications.

LINK TO RECORDING: https://youtu.be/9w1aj8E4x10

ZOOM LINK: https://msu.zoom.us/j/99295306971

Webinar ID: 992 9530 6971

Passcode: beacon

Technical Assistant: Mike Wiser

Moderator: Alexander Lalejini

• 4:00 G. Ozan Bozdag, Seyed Alireza Zamani-Dahaj, Penelope C. Kahn. Thomas C. Day, Peter J. Yunker, and William C. Ratcliff: De novo evolution of macroscopic multicellularity. The evolution of large size is fundamentally important for multicellularity, creating new ecological niches and opportunities for the evolution of increased organismal complexity. Yet little is known about how readily large size evolves, particularly in nascent multicellular organisms that lack genetically-regulated multicellular development. Here we examine the interplay between biological, biophysical, and environmental drivers of macroscopic multicellularity using long-term experimental evolution. Over 600 daily transfers (~3,000 generations), multicellular snowflake yeast evolved macroscopic size, becoming >19,000 times larger while still remaining clonal. They accomplished this substantial increase in size through sustained biophysical adaptation, evolving increasingly elongate cells that initially reduced the strain of cellular packing, then facilitated branch entanglement so that groups of cells stay together even after many cellular bonds fracture. As a result, individual multicellular yeast became more than 10,000 times more biophysically tough. 4/5 replicate populations show evidence of predominantly adaptive evolution, with mutations becoming significantly enriched in genes affecting the cell cycle, filamentous growth, and budding processes. Macroscopic size only evolved in a treatment incapable of aerobic metabolism, demonstrating how low oxygen availability constrains the evolution of larger size. Taken together, this work shows how selection acting on the emergent properties of simple multicellular groups can drive sustained biophysical adaptation, an early step in the evolution of increasingly complex multicellular organisms.

• 4:15 John S. Favate, Shun Liang, Srujana S. Yadavalli, and Premal Shah: The landscape of transcriptional and translational changes over 22 years of bacterial adaptation. Organisms can adapt to an environment by taking multiple mutational paths. This redundancy at the genetic level, where many mutations have similar phenotypic and fitness effects, can make untangling the molecular mechanisms of complex adaptations difficult. Here we use the E. coli long-term evolution experiment (LTEE) as a model to address this challenge. To bridge the gap between disparate genomic changes and parallel fitness gains, we characterize the landscape of transcriptional and translational changes across 11 replicate populations evolving in parallel for 50,000 generations. By quantifying absolute changes in mRNA abundances, we show that not only do all evolved lines have more mRNAs but that this increase in mRNA abundance scales with cell size. We also find that despite few shared mutations at the genetic level, clones from replicate populations in the LTEE are remarkably similar to each other in their gene expression patterns at both the transcriptional and translational levels. Furthermore, we show that the bulk of the expression changes are due to changes at the transcriptional level with very few translational changes. Finally, we show how mutations in transcriptional regulators lead to consistent and parallel changes in the expression levels of downstream genes, thereby linking genomic changes to parallel fitness gains in the LTEE. These results deepen our understanding of the molecular mechanisms underlying complex adaptations and provide insights into the repeatability of evolution.

• 4:30 Noah Gettle and Michael Travisano: The mechanistic basis for adaptation and divergence in evolving populations of multicellular Saccharomyces cerevisiae. Complex traits are foundational to biological systems. Elucidating the causal mechanisms in the evolution of complex traits is essential for understanding their origins. Associations between ecological factors and phenotype have long been used to gain insights into the causes of selection, such as the repeated origins of streamlined body shapes in aquatic organisms. For some traits, parallel changes in phenotype have even been mapped to parallel genetic changes. Evolutionary predictions are made possible by these and similar explications of evolutionary outcomes. However, the complexities of genotype to phenotype mapping, including pervasive genetic interactions underlying most traits, make identification of causal mechanisms beyond the superficial especially challenging. These challenges can be overcome by studying the origins and evolution of these complex genotype-phenotype relationships. Studying the evolution of complexity from its onset reduces the number of pre-existing genetic interactions to disentangle, thereby enabling the identification of causal mechanisms. In order to investigate the mechanistic basis for the evolution of complex traits, we quantitatively evaluated parallel transitions to multicellularity in experimentally evolved populations of brewers’ yeast, Saccharomyces cerevisiae. In a previous study, we demonstrated the rapid appearance and sweep of multicellular phenotypes in ten populations of yeast seeded with the same unicellular clonal strain by evolving populations under selection for increased settling rates in liquid media. While convergent in terms of state (i.e. multicellularity), replicate populations differed considerably in terms of other phenotypic characteristics associated with the transition from uni- to multicellularity.

• 4:45 Alexander Lalejini, Austin J. Ferguson, Nkrumah A. Grant, and Charles Ofria: Adaptive phenotypic plasticity stabilizes evolution in fluctuating environments. Fluctuating environmental conditions are ubiquitous in natural systems, and populations have evolved various strategies to cope with such fluctuations. The particular mechanisms that evolve profoundly influence subsequent evolutionary dynamics. One such mechanism is phenotypic plasticity, which is the ability of a single genotype to produce alternate phenotypes in an environmentally dependent context. Here, we use digital organisms (self-replicating computer programs) to investigate how adaptive phenotypic plasticity alters evolutionary dynamics and influences evolutionary outcomes in cyclically changing environments. Specifically, we examined the evolutionary histories of both plastic populations and non-plastic populations to ask: (1) Does adaptive plasticity promote or constrain evolutionary change? (2) Are plastic populations better able to evolve and then maintain novel traits? And (3), how does adaptive plasticity affect the potential for maladaptive alleles to accumulate in evolving genomes? We find that populations with adaptive phenotypic plasticity undergo less evolutionary change than non-plastic populations, which must rely on genetic variation from de novo mutations to continuously readapt to environmental fluctuations. Indeed, the non-plastic populations undergo more frequent selective sweeps and accumulate many more genetic changes. We find that the repeated selective sweeps in non-plastic populations drive the loss of beneficial traits and accumulation of maladaptive alleles via deleterious hitchhiking, whereas phenotypic plasticity can stabilize populations against environmental fluctuations. This stabilization allows plastic populations to more easily retain novel adaptive traits than their non-plastic counterparts. In general, the evolution of adaptive phenotypic plasticity shifted evolutionary dynamics to be more similar to that of populations evolving in a static environment than to non-plastic populations evolving in an identical fluctuating environment. All natural environments subject populations to some form of change; our findings suggest that the stabilizing effect of phenotypic plasticity plays an important role in subsequent adaptive evolution.

• 5:00 Rohan Maddamsetti and Nkrumah Grant: Purifying selection in the long-term evolution experiment with Escherichia coli. Purifying selection maintains organismal structure and function over evolutionary time. Despite its importance for understanding the evolutionary dynamics of natural microbial communities, purifying selection has been little studied in microbial evolution experiments. In a series of recent papers, we report that simple methods, applied to genomic and metagenomic time series of Lenski’s long-term evolution experiment with Escherichia coli (LTEE), are able to discover several interesting patterns of purifying selection, which in some cases, are universal across the tree of life. First, abundant proteins evolve slowly in mutator populations of the LTEE. Specifically, the density of all observed mutations per gene, significantly anti-correlates with mRNA abundance, protein abundance, and degree of protein-protein interaction. The same pattern holds for nonsynonymous mutation density. However, synonymous mutation density, measured across the LTEE mutator populations, positively correlates with protein abundance. Second, we find evidence of purifying selection on the E. coli protein-protein interaction (PPI) network, such that evolved PPI networks are more resilient than expected by chance. Third, we developed a simple test to infer mode of selection (STIMS) which is able to recover a signal of purifying selection on essential genes. Many of these essential genes show evidence of both positive and purifying selection under LTEE conditions. Finally, we used STIMS to test for purifying selection on central and superessential metabolic enzymes, and find that patterns of purifying selection on metabolic enzymes in the LTEE are largely idiosyncratic and population-specific.

• 5:15 Matthew Andres Moreno, Santiago Rodriguez Papa, and Charles Ofria: Case Study of Novelty, Complexity, and Adaptation in a Multicellular System. Continuing generation of novelty, complexity, and adaptation are well-established as core aspects of open-ended evolution. However, the manner in which these phenomena relate remains an area of great theoretical interest.It is yet to be firmly established to what extent these phenomena are coupled and by what means they interact.In this work, we track the co-evolution of novelty, complexity, and adaptation in a case study from a simulation system designed to study the evolution of digital multicellularity.In this case study, we describe ten qualitatively distinct multicellular morphologies, several of which exhibit asymmetrical growth and distinct life stages. We contextualize the evolutionary history of these morphologies with measurements of complexity and adaptation.Our case study suggests a loose, sometimes divergent, relationship can exist among novelty, complexity, and adaptation.

LINK TO RECORDING: https://youtu.be/dl_wcqsIWuM