BEACON researchers are working on a wide range of multidisciplinary research projects focusing on evolution in action. The list below provides descriptions of current and past projects that have received BEACON support.
A biocomputational study of cooperation in pathogenic bacteria
Philip McKinley, Chris Waters
This project integrates in silico evolution of digital organisms with in vitro experiments using model bacterial systems to better understand collective behaviors in bacteria, namely quorum sensing and biofilm formation, and help to predict the responses of bacteria to ‘antiinfective’ treatments targeting these processes. We have made significant progress in a key area of this research, namely, characterizing the effect of resource availability on biofilm formation. Specifically, we have conducted experiments in biofilm formation using cooperating and non-cooperating Vibrio cholerae strains that confirm a novel finding first revealed through our experiments with digital organisms (Connelly 2010). In short, these experiments demonstrate that the relationship between resource availability and biofilm formation is non-linear: as resource supply increases, cooperation gradually increases until a critical threshold is reached, at which a rapid transition occurs between non-cooperative and cooperative states. These findings diverge from previous work by Brockhurst et al. (2007) which suggested that cooperation increases linearly with resource availability. Rather, our results indicate that cooperation, at least in terms of biofilm formation in V. cholerae, is a bimodal state with the bacteria exhibiting either minimal cooperation or complete BEACON 2010 Annual Report II. Research Page 29 cooperation. Importantly, this finding was inspired by initial experiments using Avida and confirmed with wet lab experiments. This result has practical implications in the development of new strategies to treat biofilms. Specifically, these results would suggest that interventions that can modulate the cooperative behavior of bacterial populations, such as inhibitors of QS, might be able to strongly inhibit biofilm formation in a non-linear manner.
Adaptation in changing environments
Benjamin Kerr, Charles Ofria
The fitness landscape is a map from genotype to fitness for a given environment, where elevation gauges fitness. Populations take ‘steps’ through mutation and are driven up slopes by selection. The operation of mutation and selection generates an evolutionary ‘path’ on the fitness landscape. The topography of the fitness landscape depends on the environment. When the environment changes, the relative fitness of genotypes may change, altering the landscape. The change in environment can lead the population to a higher peak (‘selective bridge’) or a lower peak (‘selective trap’). Here we explore adaptation in changing environments using AVIDA and bacteria. We propagate our populations under a tripartite scheme: exposure to environment (i) A, (ii) B, and then (iii) A again. The control treatment involves exposure to environment A only. In AVIDA, different environments are defined by different sets of rewarded logical tasks. In bacterial microcosms, different environments involve different added antibiotics. Isolates are assessed for fitness in environment A. The precise paths followed and the role of changing environments is assessed. We have executed several runs in AVIDA and found a positive effect of changing environment (on tasks performed and final fitness). We propagated 176 populations of E. coli for 170 generations under combinations of four blactam antibiotics: ceftazidime, ceftriaxone, cefotaxime, and piperacillin/sulbactam. Here, we found mixed results. Sometimes environmental change had positive effects on final growth rate and sometimes it had negative effects. We are currently sequencing isolates at different candidate loci to understand the precise paths of adaptation.
Automatic identification technology
Paul M. Stanfield
This project seeks to develop evolutionary models for life cycle management of durable goods equipped with sensorintegrated automatic identification technology. Such AIT technology enables the product to behave as a biological organism with genetic core; having memory, processing, and communication capabilities; with the ability to network with similar products for life cycle improvement. The potential application of such techniques to organizations like the Department of Defense is significant. We have product life cycle taxonomy with associated biological analogs. The result is a nested evolutionary approach that has parametric/operational improvement with a design improvement cycle. The model includes gene coding, intelligence developed within the individual, and intelligence developed within the community. We have also looked at other biological phenomena that may be useful — schooling and collaborative breeding. We have identified an application basis (particular form of healthcare infusion pump) and begun to collect needed life cycle data. We have created an initial system architecture called ‘ASK’ — agents seeking knowledge. The architecture is very preliminary and will be modified significantly as our related research advances.
We are developing an innovative computational learning system for mobile platforms that is capable of learning diverse functionalities and scientific knowledge required to perform specific mission tasks. The learning system is based on a novel model of biofunctional learning [Iran-Nejad 1989; Iran-Nejad & Homaifar 1991] and can be interactively trained by humans. It will be capable of improving or adapting a robot’s behaviors over mission lifetime in response to environment or system changes. The biofunctional theory of learning and remembering represents ideas and concepts that may explain mechanisms of human learning. This theory has not yet been realized as a computational model and has never before been used as a basis for developing artificially intelligent systems. Human beings maneuver and manipulate objects in any known environment based on knowledge of the place and/or an educated search, which is based on the most probable location of target items and actions. This aspect of this project envisions a house setting that is designed to enable the robot to interact meaningfully with the environment and residents through its sensors. The robot is required to improve the quality of life of a cognitively impaired person living in the house. It does this by learning to perform some daily activities such as searching for items (e.g. gadgets, drugs, food items, literature), giving indoor directions, etc. The robot only needs to have partial knowledge of targets and their location. This raises the question of learning and decision making which will be the integral part of this project. The other interesting aspects include robotic localization, navigation, obstacle detection, obstacle avoidance and path planning modules. The next phase envisions the robot’s ability to live in an unknown home using the knowledge learnt from a known home environment.
Cattle genome evolution and the origin of New World cattle breeds
In this project we are assessing the genetic history and evolution of New World cattle (Bos taurus) and assessing the genomic patterns of introgression in the Longhorn genome. We are using data from 54,000 genome-wide single nucleotide polymorphisms (SNPs). We have used the program STRUCTURE to genetically cluster individuals from ten predefined breeds, including: Texas Longhorn [32 individuals], Angus , Hereford , Jersey , Shorthorn , Limousin , Romosinuano , Corriente , Ankole Watusi , and Brahman (B. t. indicus) . To assess STRUCTURE’s ability to identify admixed individuals we included five additional Longhorn individuals with known mixed breed ancestry. Our preliminary data analysis shows clear differentiation between most cattle breeds. Breeds derived from the two subspecies Bos taurus taurus and Bos taurus indicus show the strongest distinction. These results also suggest that the group now described as ‘Texas Longhorn’ are descended from Spanish cattle, as distinct from western European breeds such as Angus, but are not genetically distinct from other Iberian-derived North American cattle breeds such as Corriente. Although this Longhorn-like group consists mainly of B. t. taurus cattle, most individuals show 5-10% B. t. indicus introgression. Additionally, most Longhorn cattle sampled here show some degree of admixture with other European breeds. Future work will focus on mapping the genomic regions of introgression. We are also using principal component analysis (PCA) to determine the SNPs most strongly associated with population differentiation.
Comparative and functional genomics of invasive pathogens
Emerging infectious diseases present a great challenge for both biological diversity and human health. This BEACON project focuses on developing a mechanistic understanding of emerging diseases by studying a recently discovered fungal pathogen and its vertebrate hosts. Initial proposed goals focused exclusively on whole-genome studies of the chytrid Batrachochytrium dendrobatidis (Bd), a fungal pathogen responsible for frog population declines and species extinctions around the world. However, we have revised these goals to focus on an essential and complementary objective: understanding host response to Bd. Even closely related hosts exhibit varying levels of susceptibility to Bd; therefore we are investigating the genetic determinants of disease susceptibility in frog species pairs. We have completed a pilot experiment comparing disease outcome in two species pairs: Bufo boreas (susceptible) vs Bufo marinus (resistant) and Rana muscosa (susceptible) vs Rana catesbeiana (resistant). We are now optimizing genomic and immunological assays to determine the functional differences between species pairs.
Computational and empirical approaches to understanding rapid evolution and the possible loss of biodiversity in damselflies in response to global change
Thomas Getty, Chris Klausmeier, Idelle Cooper
The goals of this project are to understanding how contemporary evolution in action will mitigate or exacerbate the impacts of global change on biodiversity. The evolutionary consequences of depleted stratospheric ozone and elevated solar radiation are poorly understood, but we propose to study the direct selection on organisms via survival and result in changes in species ranges. We will combine computational and empirical approaches to understand the impacts of global change on the evolution and biodiversity of Hawaiian damselflies. Our previous research in one species, Megalagrion calliphya, indicates that red pigmentation in both sexes is prevalent under high solar radiation and may function as an antioxidant that protects damselflies from UV damage. The empirical stages of this project include field studies of temperature and UV effects on M. calliphya survival, collection of specimens throughout their range to measure habitat structure, and characterization of habitat requirements and ranges of other Megalagrion species. Information from these field studies will allow us to measure evolution in action by quantifying selection on pigmentation relative to environmental variables affected by global climate change.
Development of a three-dimensional digital evolution testbed
Charles Ofria, Robert T. Pennock, Fred Dyer, Philip McKinley
We are designing and implementing a distributed virtual world where 3D digital organisms compete, self-replicate, and evolve in an open-ended fashion. We will use this system as a platform for research and education. Early experiments have demonstrated that the evolution of 3D morphologies and behavior is more engaging to a human observer than abstract digital organisms, and the evolved traits are more intuitive to understand, making it ideal for research into the early evolution of intelligence. In order to achieve openended evolution, we are developing software that can sustain a few hundred co-existing organisms that can survive and reproduce in their environment. We recently evolved a single organism that can forage for food sources placed at arbitrary positions. This organism was obtained after running evolutionary experiments on 80 CPU cores for several days. At the same time, we have successfully tested an experimental environment where we simulated a population of 200 organisms and as many food sources, which totals over a thousand primitives. On a fast desktop computer, it takes us approximately an hour of computation to simulate twenty seconds in the virtual environment.
Development of mathematical and simulation models that predict aspects of microbial adaptation
We are studying how different regions of genes evolve at different rates in microbes (yeast, E. coli). For example, sites in a gene that correspond to buried regions in the expressed protein tend to be more conserved than sites that correspond to exposed regions. Likewise, sites that interact with other proteins tend to be more conserved than sites that don’t interact but have otherwise similar properties. Thus, it is important to calculate local, context-specific evolutionary rates and to find biologically meaningful interpretations for them. At present, we have two aims: (1) We develop novel algorithms to infer context-specific evolutionary rates. (2) We develop mathematical models that can predict the biological and biophysical parameters that determine these context-specific rates. We have completed a first manuscript on Aim 2, and are currently working on a manuscript covering Aim 1.
Evolution of antibiotic resistance in biofilms
The goals of the project are to model the evolution of antibiotic resistance in bacterial biofilms, and compare data from the lab to simulations. We have implemented a forward-time simulation algorithm to produce model biofilms, and are working on making this faster and more efficient by simulating backwards in time. We are also sequencing whole genomes from bacterial biofilms grown in the lab.
Evolution of novel toxins
Nearly every lineage of bacteria produces antimicrobials called bacteriocins. The colicins of Escherichia coli are the best studied. The colicin operon contains a colicin gene (col) that encodes the colicin (Col) and an immunity gene (imm) that encodes a protein (Imm) providing high-affinity, colicin-specific immunity. Single mutations can have lethal consequences, interfering with binding. Nonetheless, colicins are surprisingly diverse and there is strong evidence of common ancestry. How do new pairs originate? In this project we test the positive selection hypothesis, comprised of two steps. First, mutations in imm confer a conformational change in Imm, which broadens immunity (Imm can still bind its own colicin as well as other colicins). Second, complimentary changes occur in the colicin, leading to a novel Col-Imm protein complex. We test this hypothesis with a combination of genetic engineering and experimental evolution. Using the colicin E3 system, we introduce unbiased mutations (~1 per gene) into imm via gene replacement with error-prone PCR products. Following transformation into competent cells, we screen mutants for the ability to grow on both their native colicin (E3) and on another functionally distinct E-series colicin. We propagate the broadened immunity BEACON 2010 Annual Report II. Research Page 28 mutants in soft agar in the presence of their ancestor. Novel colicin producers leave a ‘kill’ clearing in the ancestral lawn. To date we have inserted the E3 operon on the pBR322 vector, introduced restriction sites around the imm gene (via site-directed mutagenesis), and troubleshot the random mutagenesis protocol. We are currently working on inserting mutant imm genes into the operon.
Evolution of plasmid host range
Plasmid-mediated gene transfer is an important mechanism of rapid bacterial adaptation to changing environments. However, little is known about the range of hosts in which plasmids can stably replicate, and whether this range evolves over time. A better understanding of plasmid host-range evolution is critical to our ability to either promote or limit the spread of pollutant degradation or drug resistance genes in microbial communities. The goal of our project is to determine the evolutionary mechanisms of changes in plasmid host-range, with an emphasis on the role of plasmid-host coevolution. To achieve this we use a combination of experimental evolution studies, genetic and biochemical analyses, and comparative genomics. Our previous work suggests that the stability of a broad-host-range plasmid in a novel Pseudomonas koreensis host was BEACON 2010 Annual Report II. Research Page 30 drastically improved over 1,000 generations through coevolution. We have begun to unravel the dynamics and genetic basis of this coevolutionary process. We found that coevolution occurred gradually over time and not in a single step (1). Preliminary analysis of chromosome and plasmid pyrosequence data indicates two types of genetic changes, concurrent with the coevolution postulate: acquisition by the plasmid of a transposon from a resident plasmid, and multiple SNPs in the evolved chromosome. We will confirm and characterize these genetic changes and determine which ones are directly involved in plasmid stability. Next, the effects of host specialization on the plasmid’s host-range will be examined. We have also recently published a genomics approach to assess the putative evolutionary host range of naturally occurring plasmids (2).
Evolutionary algorithms inspired by social and linguistic behavior
We are developing new evolutionary algorithms inspired by social and linguistic behavior with emphasis placed on generating new computational algorithms, as well as on understanding deep analogies between engineering and scientific problems. For instance, we are exploring the application of graph and network theories to understand spatial-temporal distributions of biological populations, social groups, and virtual crowds and how they interact in the light of Darwinian-like fitness pressures. Equations describing infection patterns are a generalization of the heat equation. This epidemiology/thermal analogy leads us to hypothesize that these equations have the elements of the Lorentz chaotic system, which first arose as a very simple model of the atmosphere; i.e. as a fluid-thermal system. We are investigating this analogy with the following goals: (a) to discretize the equations into grids, triangulations, or even nonplanar networks that can include additional effects; (b) to study variations on the these networks and to simulate using COMSOL; (c) to compare the results with computationalbiology software like Avida; (d) to use physical analogy to hypothesize epidemiological patterns and to test them.
Thomas Schmidt, Barry L Williams, C. Titus Brown
The goal of this project is to apply evolutionary principles to the interpretation of metagenomes — DNA sequences recovered directly from complex microbial communities. Specifically, we will determine the rate of non-synonymous to synonymous (dN/dS) substitutions in metagenomes to determine the selective pressure under which genes have been evolving. We have begun this project with two genes involved in the exchange of atmospheric greenhouse gases with microbial communities in soil – nitrate reductase (nirK) and a subunit of methane monooxygenase (pmoA). Our working hypothesis is that nirK has been under increased positive selection in agricultural lands due to the continuous fertilization with ammonium nitrate, and contributes to the increased production of nitrous oxide from agricultural soils — the major source of nitrous oxide in Earth’s atmosphere. We are also testing the hypothesis that pmoA is under increased selective pressure in native forested lands, where increased competition amongst the methane-oxidizing bacteria results in an increased consumption of atmospheric methane as compared to agricultural lands. We have created separate alignments of approximately 1,000 nirK and pmoA nucleotide sequences and constructed phylogenetic trees for both. To accommodate the computational demands of analyzing 1,000 member trees, the software used to estimate dN/dS is being modified to run on the High Performance Computer Cluster at MSU. Information about the evolution of microbes responsible for the production and consumption of greenhouse gases has the potential to inform land management decisions. The general strategy to analyze metagenomes will be applicable to any environment.
Evolutionary optimizing of strategies to improve emergency response planning using agentbased models to model human behavior
Erik David Goodman
This project aims to study optimal responses to a particular disaster situation, but also to serve as a learning tool for helping emergency response planners understand how simulation and optimization tools can be used in planning for disaster mitigation. Initial work on this model has yielded a working simulation, but the optimization used to date has not produced globally optimal results. Currently, greater realism in agent behaviors is being introduced while more effective optimization strategies are being explored.
Evolving artificial neural networks for control of ambulatory prosthetics
Users of sensing devices could benefit greatly from devices that can sense the user’s informational needs and adjust the parameters of their sensors to optimally meet these needs in an autonomous fashion. The interaction between the system and human must be carefully addressed to make the autonomy and reliability truly possible. This task involves the development of a cooperative set of biological interfaces between the human operator and the robotic assistants that enable a smooth and transparent symbiotic relation to exist, where the human operator’s informational needs are sensed and internal system parameters and sensor inputs are adjusted to meet these needs optimally in an autonomous fashion. Basic research addressed by the team includes: (i) experimental work undertaken to acquire new knowledge of the underlying phenomena of thought (the desire to move) and body movements along with changes in the electroencephalography measurements (head) and surface electromyography (moving appendage); (ii) large-scale clustering applications that will transform the measured data into conscious commands to an appendage from the operator; and (iii) the development of a framework for distributed human-machine voice-interface applications. Progress has been made on research into cognitive workloads and further collection of EEG signals has been performed. We are beginning our mapping of EEG data to the workload performance curve. A given subject was connected to a hardware device such as a MindSet 24 10-20 standard data acquisition system. The subject was then instructed BEACON 2010 Annual Report II. Research Page 24 to maintain control of several unmanned aerial vehicles (UAVs) while being bombarded with vast amounts information over approximately 60-minute intervals. Information being relayed to the controller for each UAV includes: position, payload, targets, new target coordinates, damage to vehicle, fuel levels, weapons remaining, etc. The controller is updated with this information for at least 5 aerial vehicles on a random time interval. The hypothesis for this research was that the controller should maintain control of the UAVs throughout the sixty minute duration or until the controller became fatigued. The controller is believed to be in control of the vehicles if they are answering questions pertaining to the information being provided correctly and having targets hit accuracy above 50 percent. Once the controller’s accuracy fell below 60 percent a warning appeared, ‘Fatigue Warning.’ The EEG activity across the brain of the controller was then monitor and mapped to a performance curve. Once the performance fell below 50 percent a computer was then prompted to aid in the control of the aircraft until the controller is able to successfully control all the aircraft.
Evolving robotic fish – autonomous schools
Xiaobo Tan, Philip McKinley, Jenny Boughman
By exploring evolution in action in robotic systems, the ultimate goal of this research is to (1) enable adaptive, autonomous robotic networks for demanding engineering applications, and (2) potentially provide an experimental platform for examining questions in biological evolution. In particular, we propose to exploit advances in biological and computational evolution to realize robotic fish schools with a high degree of autonomy. Specific goals of this project include (1) building a multidisciplinary team with expertise spanning robotics, evolutionary computing, and biology, and (2) jump-starting the exploration of a framework for synthesizing adaptive, autonomous behaviors for robotic fish schools by integrating biological insight, computational evolution, simulation, and hardware experimentation. Progress made to date has included: We have started a regular meeting for the three PIs (Tan, McKinley, Boughman) and their students involved in this project, with the meeting place alternating between the Engineering Building and the Giltner Hall (Zoology). We have begun the exploration of software for simulating the dynamics and control of robotic fish. We have started the design of robotic fish that will be used in experimental validation of evolved coordination strategies.
James Arthur Foster, Mitch D Day
Our objective is to develop a model microbial community with which to perform controlled experiments to elucidate the genetic components of adaptation in obligate commensal communities. We have altered our community from the proposed aquatic pond community to the “ginger beer plant,” which is a consortium of yeast and bacteria that form particles whose size is a phenotypic trait available for selection. To date, we have established the protocols for passaging these communities, and have performed three serial passages of a high/low/random line. We have observed a rapid response to selection in that particle sizes in the high/low lines are significantly different from that in the random line.
Foundations of intelligence: evolving memory utilization and behavioral flexibility
Robert T. Pennock, Fred Dyer, Benjamin Kerr
The goal of the project is to use Avida to study the early evolution of intelligent decision-making in an environment that is complex enough to create situations in which the decision-making agent is subject to ambiguity about its position in the environment and the consequences of possible decisions. The work will build upon previous work by Laura Grabowski (MSU PhD graduate) documenting the evolution of simple memory as a part of a solution to this problem. To build upon this work we intend to explore how the evolution of memory use is influenced by characteristics of the genetic architecture of the avidians and the structure of the environment in which they live. Post-doc Frank Bartlett has been learning Avida and refining ideas about the design of experiments to manipulate the genetics and environmental constraints on the evolutionary process. We are adapting an extension of Avida developed by Pennock’s undergraduate Professorial Assistant (Jacob Walker) that will enable the exploration of behavioral evolution given different resource landscapes — this will speed work toward the original goals of this project and lay the groundwork for further studies of spatial behavior by individuals and groups. In weekly lab meetings, we have also begun to explore connections between spatial decision-making as a problem in itself and the evolution of group-level strategies of resource sharing and territorial defense — this has led to a collaboration with another internal project involving Ofria, Dyer, and Heckendorn.
Gene introgression and hybridization
This project uses comparative genomic data to test a divergence-with-gene-flow model of speciation in the radiation of western chipmunks. The complete mitochondrial genome of the yellow-pine chipmunk Tamias amoenus (species selected at random from the genus) is sought through PCR amplification and Sanger sequencing. Primers were designed using a consensus sequence from the mitochondrial genomes of Sciurus (Rodentia: Sciuridae, the same family as Tamias) and Glis (Rodentia: Gliridae, sister to Sciuridae). Primers were designed using Primer3Plus such that they flanked a single gene of interest or spanned multiple gene regions. The set of possible primer pairs was constrained to include those that ended in a G-C clamp, lacked ambiguous nucleotides, and had similar melting temperatures (Tm ). Varying numbers of primers were ordered for a given gene region (typically around four to five forward and reverse). As part of an initial analysis, several individuals were selected to have their mitochondrial genomes sequenced. These included an introgressed and non-introgressed T. ruficaudus simulans, a non-introgressed T. ruficaudus ruficaudus, an introgressed T. amoenus luteiventris, a T. amoenus canicaudus, and a representative T. amoenus from Washington. Nine proteincoding regions were sequenced and subjected to a molecular evolutionary analysis using the program YN00 in the package PAML (Yang 2007) to determine if there was a selective difference between pairs of sequences that had non-equivalent amino acid substitutions. Preliminary analyses suggested that there were two gene regions (ND5 and ATP8) where the ratio of the rate of nonsynonymous substitutions to the rate of synonymous substitutions (_) was greater than the low background values, indicating these as regions of interest. Additional sequencing will provide further insight into these regions of interest.
Genetic & Evolutionary Biometrics (GEB)
The goal of the project is to develop a number of Genetic & Evolutionary Based Feature Extraction, Selection, and Weighting Systems for Face, Periocular, Iris, and Multibiometric Recognition Systems. A second goal is to work with Marshall and Johnson Space Flight Center in the development of a revised version of X-TOOLSS. X-TOOLSS is a system developed at NCA&T for NASA, which incorporates 11 Genetic & Evolutionary Computations. Currently, these students have been working with the PI in an effort to develop three manuscripts to be submitted to the IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM). X-TOOLSS was used to develop GEFE (Genetic & Evolutionary Feature Extraction), GEFeS (Genetic & Evolutionary Feature Selection), and GEFeW (Genetic & Evolutionary Feature Weighting). These GEC-based systems have been shown to reduce the number of features needed for biometric recognition as well as to increase the recognition rate.
Genetic investigation of norms
For our investigation of the genesis and stability of social norms using GA techniques, we are converging from the two extremes in software agents: agents with very simple behaviors as used in agent-based simulation, and agents as supported by APIs for complex behaviors, agent communication languages, system support, and many other features. Regarding the simple agents, we are becoming familiar with the use of the GA wrapper for the Java Genetic Algorithms Package (JGAP) provided by the Repast Simphony agent simulation toolkit. We are also experimenting with encoding Repast agent behaviors to represent communicating state machines of the kind required for this research. We use Repast Simphony in the web engineering course that we taught in spring 2008 and will teach again in spring 2011, and this research thread fits nicely with what is taught. For problem-solving agents, we have used the JADE (Java Agent DEvelopment) framework for years. We are experimenting with the framework-provided state-machine behavior in conjunction with JGAP. A major challenge is to minimize agent resource demands to allow populations of meaningful size.
Genetic variation, cooperation and motility in Myxococcus xanthus
Patricia Hartzell, Allan Caplan
The goals are to identify regulatory factors that regulate phase variation in Myxococcus BEACON 2010 Annual Report II. Research Page 27 xanthus. M. xanthus cells can vary their form or ‘phase’ to produce colonies that contain predominantly yellow (pigmented) or predominantly tan (non-pigmented) cells that differ greatly in their abilities to swarm, survive, and develop. Comparison of the phenotypes of wild-type yellow, wild-type tan, a DKXanthene pigment mutant and a putative XreHTH mutant shows that the pathway for pigment production is distinct from the swarming/aggregation pathway in yellow variants. In contrast, tan variants appeared to have enhanced survival. To identify genes that might define separate pathways, we used microarray and RT-PCR to probe yellow and tan phase populations. Genes involved in production of the yellow pigment, DKXanthene, showed increased expression in yellow cells compared with tan cells. In contrast, tan cells showed increased expression in genes such as pkn14, which encodes a serine-threonine kinase that regulates the MrpC-MazF toxinantitoxin system. Several new sets of genes found to be differentially upregulated only in yellow variants provide valuable insights to the mechanism by which phase variation affects production of polyketides, swarming and aggregation.
Improving globality of evolutionary search on a classical design problem
Erik David Goodman, John Oliva
To date, Oliva and Goodman have performed preliminary runs that illustrate the non-globality of the current search method. The next goal will be to create a search method that can reliably find a globally optimal solution to a problem with such a known solution; after that, methods will be sought to render that process more efficient in terms of the number of objective function evaluations required to achieve reliably the global optimal solution.
Modeling species interactions
We will use 454 sequencing to explore the effects of spatial structure on genetic diversity in virus populations that are adapting to a change in temperature. The evolution experiments have already been carried out by the lab as part of another project and Sanger sequencing was used to detect SNPs at the population level for various locations in the spatial habitat (agar plate). This coarse sequencing detects variants that are present at about 25% frequency in a given region. Using 454 sequencing to explore variation at a much deeper level, we will test the hypothesis that spatial structure leads to a significant increase in genomic novelty that can seed many more evolutionary trajectories than are possible in a ‘mixed’ environment.
Pin the tail on the Ascidian: exploring loss and gain of chordate features in Molgula
C. Titus Brown, Billie J. Swalla
This pilot project uses high-throughput expression analysis of mRNA sequence from early developmental stages of the two separate species and hybrid embryos to detect allele-specific expression differences between M. occulta and M. oculata. Specifically, we will do quantitative sequencing of mRNA with 454 and/or Illumina sequencing at cleavage, mid-gastrula, and early neural stages; and analyze the expression levels of mRNAs to determine which coding variations display allele-specific expression variation. We found both species and prepared RNA of the embryos of both stages and the hybrids. Unfortunately, the RNA was thawed due to an error of shipping and the RNA is somewhat degraded. We are looking for alternative ways to continue the sequencing project with RNA collected by the Swalla lab in previous years.
Plastic plasticity: the regulation and evolution of phenotypic plasticity in silico and in vivo
Alexander Shingleton, Herbert Sauro
Plasticity pathways transduce environmental information to developmental processes resulting in phenotypic variation. Nevertheless, we have very little understanding of how the structure of such pathways amplifies or attenuates environmental signals to regulate developmental processes. Our specific goal is to model the function and evolution of plasticity pathways in silico and subsequently test these models in vivo. We are using the well elucidated insulin/IGFsignaling (IIS) pathway to achieve this goal. The IIS pathway regulates body and organ size with respect to nutrition in all animals and the pathway has evolved so that, within a species, some morphological traits are more nutritionally plastic than others. The proximate changes underlying this evolution are, however, unknown. Our specific aim is to generate a mathematical model of the IIS pathway, evolve this model in silico using different levels of plasticity as an objective function, and predict which components of the pathway are likely targets for selection on plasticity. These predictions will be tested using experimental data from existing wild-type and artificially-selected Drosophila lines that show evolved variation in nutritional plasticity. We have already constructed a mathematical model of the IIS pathway, which includes 19 state variables. Preliminary simulations have been performed and have identified key components of the pathway that regulate plasticity. The next stage in the project is to develop an ‘evolvable’ form of the model
Pressures, patterns, and processes in the early evolution of sociality
Charles Ofria, Fred Dyer, Robert Heckendorn
The goal of this project is to use digital evolution to identify conditions that allow organisms to form groups, facilitate the stability of those groups, remove specific constraints on the range of allowed social strategies, encourage cooperation, and promote the evolution of sociality itself. Our initial experiments have progressed on two fronts:
- We have developed abstract grouping mechanisms that allow digital organisms to join groups by simply stating which group that they choose to be a part of. This setup allows us to investigate questions about scenarios where grouping is tolerated without adding the complications associated with navigation. Initial results indicate that the organisms do divide up among the different groups available in proportion to the amount of resource available to each of them. We are not experimenting with giving the organisms the ability to expend some of their resource to prevent others from joining a group or force current group members out.
- We have given the digital organisms the ability to travel around a 2-dimensional lattice that contains spatially heterogeneous resources that the organisms must obtain and consume in order to successfully replicate. Organisms can control their facing, their movement, and can sense resource concentrations where they are and where they face. Initial results indicate the organisms can easily make use of these abilities to patrol small areas BEACON 2010 Annual Report II. Research Page 25 wherein they collect the available resources, but do not yet engage in more complex strategies.
Selective advantages of cooperation in dynamic environments
Robert Heckendorn, Terence Soule
We have written a model of the ‘hyena problem’ – how hyenas can learn to cooperate to drive lions from a kill without being injured. This model will be used to study the role of incremental fitness and group communication in the evolution of cooperation. We have begun applying heritability theory to the problem of noisy/non-reproducible fitness functions. In most multi-agent problems variations in the environment, starting conditions, etc., mean that fitness measurements are ‘noisy’: they only approximate an individual or teams’ true, or genotypic, fitness. Selection ends up selecting lucky rather than fit individuals. This has direct parallels in heritability theory, which we are leveraging to determine when evolution has become stuck. We are exploring COTS robot platforms and are developing the support layer libraries for the robots. Living things do not have wheel rotation counters and precise directions to desired locations and yet perform just fine. Therefore, the key to this work is to use fuzzy logic that will allow the use of approximate location and direction derived from simple casually assembled robots to better simulate the approximate world that real creatures live in and reason about. We have replicated the speciation model in Gavrilets and Vose ‘Dynamic Patterns of Adaptive Radiation’ and are collecting preliminary data on speciation in dynamic environments.
Sexual signaling evolutionary dynamics
Jenny Boughman, Robin Tinghitella, Thomas Getty, Chris Klausmeier
Our group is collaborating on a set of projects investigating rapid evolutionary change in sexual signaling systems both empirically and via adaptive dynamics modeling. We are highlighting the loss of mating signals, and hypothesize that the dynamics of trait loss and elaboration contribute to the vast extant variation in sexual signaling systems. We hypothesize further that opposing natural and sexual selection pressures are important for the loss of sexual signals and that variation in female preferences might aid or resist such rapid changes. We’ve initiated research using a model system for rapid ecological speciation, limnetic-benthic threespine stickleback species pairs. In one lake, a well-established species pair collapsed rapidly (< 20 generations) into a hybrid swarm. Hybrid sticklebacks are marked by a loss of female preferences and a loss of distinct male mating characteristics (e.g. nuptial coloration). Our initial empirical goal is to determine why females accept males who lack the sexual signal. We will begin by asking: 1) Are female preferences phenotypically plastic? 2) If so, do mating decisions vary with female age, or with female experience with hybrid males (who are at high frequency now), or with habitat (the mating environment differs compared to before the species pair collapsed)? Further investigations will follow in a second model system -- field crickets from the island of Kauai where the sexual signal (song) was lost in <20 generations.
That mystery of mysteries: speciation in action
Richard Lenski, Jenny Boughman, Barry L Williams
The Boughman, Lenski & Williams labs are united in their BEACON work by a focus on the genetics of speciation in action. Boughman is examining how sexual and natural selection act together to create premating isolation in stickleback fish. Her group will determine the genetic basis of premating isolation by combining genetic mapping studies with field measures of sexual selection and premating isolation as they occur in nature. Blount and Lenski will use gene-transfer processes to move alleles between the two E. coli lineages that have diverged in resource use, and to ask whether these lineages diverged to the extent that their hybrids are maladapted. Williams and Anderson have shown in digital organisms that genetic compensation for deleterious mutation favors compensatory evolution to maintain fitness at the phenotypic level and that this leads to rapid diversification at the genetic level. They have an Avida project started since August that tests whether the rate of genetic incompatibilities between evolving populations of digital organisms “snowballs” through time, testing a key model in speciation genetics. They find some support for this, but exceptions suggest that certain alleles are incompatible regardless of how they are paired.
The limits of stigmergic coordination within multi-agent systems
Kay E. Holekamp, Risto Miikkulainen, Benjamin Kerr
Stigmergy, which is cooperation without direct communication, commonly coordinates group activities among social insects and other animals. Stigmergy can support efficient collaboration among simple agents, including those lacking memory, intelligence or even awareness of one another. However, gregarious animals do communicate directly to solve many problems, raising the question of when stigmergic communication is adequate to accomplish animal goals, and when it is inadequate. The initial goal of our research is to identify those conditions under which stigmergic coordination breaks down. We have two full-time grad students in the field in Kenya who are charged with the task of videotaping several different multi-agent cooperative behaviors among free-living spotted hyenas, while undergrads at MSU are charged with extracting data on communication signals and outcomes of cooperative interactions from videotapes recorded in the field. Meanwhile a grad student in the Miikkulainen lab is using multi-agent ESP architecture to evaluate how relationships (antagonistic or mutualistic) between agents and the stimuli in their environments interact with the coordination mechanism mediating group behaviors to feed back and shape neural network complexity and other aspects of cognitive evolution. The computational simulations aim to study conditions under which the hyenas choose to hunt alone vs. in coordinated packs, and whether the coordination might take place through stigmergic rather than direct communication. The work proceeds through a sequence of incrementally more complex tasks, leading up to a simulation where populations of hyenas, mice and zebras are all in the field simultaneously, and are all evolving. The goal is to determine under what conditions the hyenas evolve to hunt alone or in packs or both. The sequence will be done first without any direct communication between the hyenas (i.e. they do not see each other), and then repeated with direct communication. The goal will be to see whether communication affects the behaviors that develop. In our preliminary results for the first four steps in the sequence (without communication), collaboration/cooperation, as opposed to competition, emerges under all of the conditions tested so far, which include variations on the number of predators, prey, and the rewards for the predators. All these experiments will be repeated with direct communication (by broadcasting the locations of predators) to evaluate how hunting based on stigmergy may be different from hunting based on direct communication.
Transseasonal dynamics of influenza
We are using a network-based mathematical model to look at the interaction between antigenic evolution of flu and host population structure on the long-term transmission dynamics of flu. We have completed the first stage of the analysis and are drafting a manuscript describing the model and results.
Using experimental evolution in digital and biological systems to examine the role of sexual selection and standing genetic variation on compensatory evolution
The primary goals of this project are:
- to quantify the relative contributions of standing genetic BEACON 2010 Annual Report II. Research Page 18 variation and new mutations in compensating for deleterious mutations, and
- to understand how sexual selection influences rates and patterns of compensatory evolution.
This project utilizes experimental evolution in a pair of complementary model systems to address different aspects of these questions: digital organisms in AVIDA; and Drosophila melanogaster, focusing on mutations affecting the male sex comb, an important trait for copulation success. To date, we have
- obtained several Drosophila strains carrying mutations causing sex comb defects;
- begun quantifying the morphological effects of these mutations; and
- begun developing protocols to measure the mutations’ effects on male copulation success. In the AVIDA system, we have
- performed some initial test runs with the base AVIDA software package to determine the optimal computing environment [we are exploring both commercial cloud computing services with Amazon as well as Michigan State University's High Performance Computing Center]; and
- started learning how to work with the AVIDA source code to implement custom modifications to the digital evolution environment
A Bio-Computational Study of Cooperation in Bacteria
Philip McKinley, Eva Top, Chris Waters
Understanding and predicting the evolution of cooperation in bacteria, and how it can be disrupted, has widespread implications for ecology, agriculture and human health. A critical challenge in addressing this problem is to characterize complex collective behaviors, such as biofilm formation and quorum sensing, that are integral to many bacterial functions. While recent studies have yielded advances in understanding the molecular mechanisms controlling these processes, the evolution of these behaviors remains obscure. This project couples in silico evolution experiments using self-replicating digital organisms with in vitro studies of specific bacteria (Pseudomonas aeruginosa, Vibrio cholerae, and Vibrio harveyi). These two distinct but related approaches will inform and direct each other in a reciprocal nature, accelerating any progress that either approach could make independently. Digital evolution experiments are conducted using Avida, a well-established platform previously used to investigate fundamental aspects of the evolutionary process. Wet bench techniques include molecular genetics, flow cytometry, and confocal microscopy. The project focuses on the following two interrelated topics: 1. Biofilm formation. We will identify selective forces and environmental conditions that drive the formation of biofilms. Biofilms are the dominant form of bacterial growth in natural environments, but their shielding properties make them a serious problem in human health, agriculture, and the operation of mechanical systems. An NIH report estimates that 80% of all infections involve biofilms, as the biofilm matrix helps to protect the bacteria against antibiotics and the host’s immune system. 2. Quorum sensing (QS). QS is a collective signaling behavior whereby actions of individuals depend on the density of the surrounding population. The widespread evolution and maintenance of QS in the natural world is thought to be problematic, as QS is proposed to be a mechanism for coordination of cooperative behaviors. Whereas our previous work successfully evolved QS in Avida by using group level selection, we are now studying the ability of Avidians to evolve a QS response at the level of individual selection. Observation of this evolution in Avida would have fundamental implications in understanding the evolution of QS and will drive experiments on the bench.
A Planning Grant for The Relevancy of Evolution to Our Daily Lives: A Museum Exhibit
Christina Cid, Edward C Theriot
Funds are requested for a planning grant to develop a modular museum exhibit about the relevancy of evolution to our daily lives that can be edited by and/or directly used by other BEACON partner museums. This approach allows for the possibility of providing this resource as a traveling exhibition for loans to museums across the country. The goals of the exhibit are to: convey the relevance of evolution to our daily lives, make the work of BEACON scientists accessible to the general public, and teach fundamental concepts in evolutionary biology in action based upon current research in the learning sciences on people’s understanding of evolution and the nature of science. The final exhibit will consist of: a panel about BEACON and a minimum of 5 interactive modules highlighting 5 different scientist’s work regarding the importance of evolution to our daily lives. The goals of the planning grant are to hire a graduate research assistant, working under the supervision of the Director of Education at the Texas Natural Science Center, who will:
- Work with BEACON scientists, starting at UT-Austin and then expanding the conversation to include all BEACON partner universities, to develop up to 10 narratives that can be used on the interactive modules;
- Collaborate with BEACON partner museums on the development of the exhibit and identify representative and diverse research occurring at the other institutions; and
- Create the exhibit design including developing the narratives, graphics, and interactive elements, as well as develop a final production cost budget.
An Integrated Approach to Testing Divergence with Gene Flow Model of Speciation; Empirical Genomics: Simulation, and In Silico Evolution
Jack Sullivan, James Arthur Foster, David Hillis
Determining the frequency and genetic impact of hybridization during animal speciation remains a central and unresolved issue in evolutionary biology. Recurrent hybridization among animal species has traditionally been viewed a rare and homogenizing force (Dobzhansky, 1951; Mayr, 1963). Alternatively, genetic factors underlying speciation, either via differential adaptation or sexual selection, may continue to accumulate between divergent populations despite on-going gene flow, eventually leading to lineage differentiation (i.e., speciation) (e.g., Porter and Johnson, 2002). This second model, divergence-withgene- flow (DwGF), predicts that closely-related taxa may retain differentiation despite high levels of hybridization and introgression (Machado et al. 2002; Besansky et al. 2003; Grant et al., 2005; Turner et al., 2005). If DwGF is common, hybridization may be an important transient phase in speciation and introgression should be heterogeneous across the genome (e.g., Reisberg et al. 1999, Wu 2001). This project will build collaboration between the PIs labs and test predictions of DwGF in empirical (in vivo and in silico) and in simulated systems. The in vivo system will focus on the chipmunk radiation, a promising model for DwGF, and fund an RA for student Brice Sarver at UofI (Sullivan lab). The in silico empirical system will focus on spread of non-recombining (i.e., non-introgressing) regions of the genome (a postdoc of Foster at UofI, funded independently), and the simulations will be conducted by an RA at UT, Emily McTavish (Hillis lab). This three-pronged approach will be synergistic and will provide preliminary data for an NSF proposal, to be submitted in 2012.
Avida-ED Infrastructure Maintenance and Development
Robert T. Pennock, Charles Ofria, James Arthur Foster, Joseph L Graves, James Smith, Billie J. Swalla, Claus Wilke
Avida-ED is the education version of the Avida digital evolution platform
BEACON Day at NC A & T
BEACON@A&T will host a BEACON wide day in celebration of the accomplishments of the NSF BEACON Science and Technology Center. It will help introduce and/or educate NCAT Administration about BEACON, provide a forum for discussion of BEACON research across the Center, provide an opportunity for faculty across the Center to come to NCAT and discuss possible collaborations and provide a show case for NCAT students to get excited about research at BEACON Institutions or other universities.
BEACON High School Summer Residential Program
Drew Kim, Thomas Getty, Andy Anderson
BEACON High School Summer Residential Program will pursue three main goals:
- Increasing participation in science and engineering. We will broaden participation in STEM disciplines by introducing teachers and students from underrepresented groups to the new research opportunities afforded by BEACON’s applied evolutionary tools and research programs.
- Disseminating materials generated by BEACON. Our team includes experts in science education and outreach who will work with all BEACON researchers to adapt BEACON research for use in science classes in schools in ways that address national science standards and goals.
- Demonstrate the fundamental power and importance of evolution. BEACON will contribute to the pressing national need to bolster U.S. competitiveness and pre- eminence in science and technology (NAS Committee on Prospering in the Global Economy of the 21st Century 2007) by educating people about the importance of understanding, managing and harnessing biological and computational evolutionary processes.
BEACON REU Field Experience
Billie J. Swalla, Katherine Gross, Sarah L. Simmons, Joseph L Graves
The BEACON Research Experience for Undergraduates (REU) provides funding for seven undergraduates with previous research experience at a partner institution to travel to a field station and pursue a crossdisciplinary research experience. Students will engage in summer research either at Kellogg Biological Station (KBS) in Michigan or Friday Harbor Laboratories (FHL) in Washington, which both have strong field components and active integrated summer REU programs. Students with varied science backgrounds will be pursuing empirical evolutionary research with a strong field component. Priority will be given to undergraduate students from BEACON partner schools and students underrepresented in the sciences. Students at both sites will participate in professional development workshops, receive training in statistical methods, and visit BEACON laboratories on the affiliated main campus. Videoconferences will link the REU students at KBS and FHL and students will be encouraged to present their results at various national conferences and the BEACON Congress. This REU program will bridge campuses and disciplines, strengthen relationships among partners, and generate new collaborations, enhancing the capacity of BEACON to integrate undergraduate education with research.
Computational and empirical approaches to understanding rapid evolution of damselflies in response to anthropogenic change
Thomas Getty, Idelle Cooper, Chris Klausmeier
Understanding how contemporary evolution in action will mitigate or exacerbate the impacts of anthropogenic change on biodiversity is a critical research need that requires investigation at many levels within nature, from the cellular and biochemical level within individuals to dynamics within populations and to interactions between species. This project will combine empirical research at all these levels with computational modeling to understand and anticipate the potential impacts of global change on the evolution and biodiversity of Hawaiian damselflies. The anthropogenic depletion of stratospheric ozone and resulting rise in ultraviolet radiation exposure are well documented but the evolutionary consequences are poorly understood. Such change can alter direct selection on organisms via survival, and the resulting changes in species ranges can lead to indirect selection through changing species interactions. Both of these processes will be addressed in this project: direct effects will be studied in Hawaiian Megalagrion damselflies and species interactions will be examined in local Calopteryx damselflies.
Contemporary evolution of cyanobacteria and viruses: implications for marine nutrient cycling
Jay Lennon, Jeffrey E Barrick, Eva Top, Chris Klausmeier
Increasingly, ecologists are finding that ‘rapid’ evolutionary change can have important consequences for population, community, and ecosystem dynamics. Strong evidence for these ecoevolutionary interactions has been generated in model systems involving bacteria and viruses (phage)1. Microorganisms are ideal for studying evolution in action because they have rapid growth rates, achieve high population densities, and are amenable to genetic manipulation. In addition, the ecology and evolution of microbes are important because these taxa play a critical role in the functioning and stability of natural and managed ecosystems. In this proposal, we focus on an abundant and cosmopolitan group of marine cyanobacteria (Synechococcus) and the viruses that infect them. Our prior work has demonstrated that virus predation can have strong impacts on Synechococcus, resulting in altered nutrient cycling (e.g., nitrogen, and phosphorus). However, these ecological effects are buffered by the rapid evolution of host resistance to virus infection2. To better understand the feedbacks between ecological and evolutionary processes, we will use a combination of adaptive dynamics modeling and whole-genome sequencing of Synechococcus isolates from a recently conducted chemostat experiment. Results from this study will help us understand the mechanisms of bacterial and virus evolution and its consequences for marine ecosystem functioning. Ultimately, our multi-institutional project will establish new collaborations that will develop and test eco-evolutionary theory, while providing financial support and hands-on training opportunities for a BEACON Ph.D. student.
Continuation for Podcast and Teacher Ed course
This proposal is for a continuation of previous work on two education projects from the original BEACON proposal, namely 1) an online course in evolution pedagogy for teachers and 2) a podcast on evolutionary science for the general public. During the first four months of active BEACON funding at NCATSU, significant progress towards these two deliverables has been made.
Design and Implementation of Assistive Robotic Residence Home (DIARRH)
We are designing an RFID fully augmented home (rooms are tagged and most of the items in the house are tagged with RFIDs) setting with assistive robot which interacts meaningfully with that environment and residents through its sensors and RFID antennae. The robot is required to improve the quality of life of the cognitively impaired living in the house by running errands. It does this by learning to decide on and execute some daily activities such as searching for items e.g. gadgets, drugs, food items, literature, etc.; giving indoor directions, etc. The knowledge acquired from the RFID fully augmented environment will then be diploid in a RFID partially augmented home (Only house compartments are tagged to aid navigation). The robot has full or partial knowledge of targets and partial knowledge of target location. Thus, learning and decision making are the integral parts of this project. We are investigating evolutionary learning algorithm and developing a hybrid evolutionary learning algorithm capable of robust learning of common household items features and decision making routines. Consequently, the assistive robot should be equipped with a vision system to aid maneuverability and recognition. Thus, we are developing a hybrid hierarchical blend of low level and high level object segmentation and recognition techniques capable of robust and near real-time recognition of some selected household items and actions.
Ehancing Diversity Through Evolution in Action at the Molecular Level
Barry L Williams
Underrepresented minorities (UM) are nearly absent from the field of evolutionary biology. The reasons behind this paucity of enrollment are not clear, but a central goal of BEACON is to educate and train undergraduate and graduate UM who might then go on to careers in the field of evolutionary biology; thereby generating the necessary inspiration for future biologists to increase representation for minorities in evolution. I propose to develop and implement a nine week course for UM in my lab at MSU. The recruiting processes for identification of UM interested in summer research within the sciences are already in place at the partner institutions. I will provide students with an introduction to evolutionary biology through discussion groups and integration into actual research projects from my lab, providing them with first hand exposure to the process of science and cutting edge approaches. The research is composed of topics that are at the interface of molecular biology, biomedical research and evolution in action, which will facilitate the engagement of students that might not otherwise be interested in evolution. The projects incorporate a variety of approaches, so students will be trained in disciplines like microbial pathogenicity, genetic mapping, genome sequencing, and protein biochemistry. The medically relevant topics include the origin and maintenance of clinical pathogenicity in fungi, and the maintenance of congenital defects in natural populations. Students will build upon previous research in the lab to generate their own hypotheses, test them, and present their results to BEACON to finish each term.
Engaging Educators with Evolution in Action
Randall Hayes, Thomas Getty
The ‘two cultures’ problem proposed by Snow has become almost a self_fulfilling prophecy (1). Science is considered boring by many students, largely because of the way it is communicated (2_3), and the arts often ignore the progress made by evolutionary science into areas of human experience such as emotion. We will use experts in communication, namely professional writers and teachers, to bridge the gap between professional researchers and the classroom. This will consist of 3 sub_projects. First, we will include cuttingedge BEACON research in classroom modules for a Science, Technology, & Society class at the undergraduate level. Second, we will develop online curriculum guides for science fiction short stories dealing with evolution, targeted towards grades 9_16, to encourage the reading skills necessary for success in graduate or medical school (4). Our lessons will unpack the science behind the stories to deepen the experience of reading them, and allow students to discuss the stories online with their authors (hopefully), with one another, and with BEACON scientists, particularly including graduate students and postdocs from all five partners. Finally, we will reach into the elementary schools with simple, fun, scientifically responsible computational models of evolution, to counteract the misuses of the word in popular TV shows like Pokemon, which confuse evolution and development/metamorphosis, and which emphasize a linear progression in size and power. We will use these programs to target specific common misunderstandings of evolutionary science on the part of teachers and students, rather than attempting to teach an entire course about evolution.
Evolution of Cooperation Among Competing Predators
Risto Miikkulainen, Kay E. Holekamp, Benjamin Kerr
The goal of our interdisciplinary research is to develop a computational theory of how cooperative behavior evolves among competing predators. Building on our prior work on stigmergy and the evolution of communication among predators, the proposed simulations focus on a specific cooperative behavior observed in hyenas: collaboration to steal food from lions and competition among hyenas over the food when they succeed. By analysis of videotaped events from nature, we will characterize the roles played by hyenas of all social ranks present in building coalitions and participating in collective attacks, and we will also document how rewards are distributed among the cooperating hyenas. In computational simulations, the evolutionary origins of these behaviors will be explored, determining the conditions under which each behavior is effective. The result will be a computational theory of how and why competing predators cooperate, as well as computational methods for evolving complex cooperation among intelligent agents in virtual environments.
Evolution of Synthetic Genomes
Holly Wichman, Andrew D Ellington
Recent innovations in synthetic biology have allowed de novo synthesis of genes and their expression in distantly related organisms. Indeed, entire genomes have now been synthesized1. To date, genome synthesis has been predominately done from an engineering perspective, focusing primarily on the logistics of large scale DNA synthesis and assembly. The goal of this project is to introduce an evolutionary perspective to synthetic biology, and in particular to genome engineering. Toward this end we will design, synthesize and evolve phage genomes to have either high or low fitness. We will also develop a mismatch repair procedure to aid in construction of synthetic genomes.
Evolution of the Rules Microbes Use to Play Games
Benjamin Kerr, Chris Adami, Arend Hintze
Evolutionary Game Theory (EGT)  attempts to understand how behavior that benefits others at a cost to self evolves by natural selection. One of the paradigmatic systems in this endeavor is a microbial system in which ‘suicidal’ behavior (by releasing a bacteriocin) can benefit others that carry resistance to the toxin. This system has been well studied theoretically  and experimentally , but this work has only focused on shortterm adaptation, which determines the evolutionary stable strategy (ESS) given the parameters (the ‘rules’) of the game. However, if the mutation rate is not too low, we cannot expect that the parameters that determine toxin_efficiency, resistance, cost of resistance, and cost of toxin, stay constant as a population adapts to its environment. Instead, we expect these rules of the game to evolve as well. It is known that the threeplayer dynamics between sensitive, resistant, and producer strains can involve nontransitive dynamics reminiscent of the Rock_Paper_Scissors game [3,4]. However, the space of strategies includes several other games such as Snowdrift and Prisoner’s Dilemma game  that could all be reached if the rules can evolve. We here propose to study not only the fixed points of the spatial version of the game, using theory and computational simulations as in [5,6] and in experiments as in , but also study how the predicted fixed points move as the rules evolve in response to different environments, in the manner described in . We thus study the interplay between short_ and long_time scales in EGT.
Evolutionary Design of Bio-inspired Fish-type Flying Robot Actuated by Artificial Muscles
Erik David Goodman, Xiaobo Tan, John Oliva, Philip McKinley
Biomimetic features are important in design and control of robotic systems. Researchers have also utilized experimental results from robotic systems, especially in the case of biomimetic designs, to increase our understanding of the behaviors of biological creatures. However, most actuators used in these biologically inspired robotic systems are still traditional electric motors, which utilize a strikingly different drive mechanism from the muscles used in biological creatures, strongly limiting the transfer of information between the two domains. The proposed work attempts to bridge this gap by using artificial muscles to actuate the biologically inspired robotic systems. Prototype work by Fan and others has shown the feasibility of creating a robot that is neutrally buoyant in air, then powering it with EAP- (electroactive polymer)-based artificial muscles. However, such a vehicle will require an adaptive control system controlling actuators that are very different from traditional motors, and the team proposes to evolve such a controller on the basis of the CPG (center pattern generator) methodology. The robot prototype, CPG controller and actuator configuration will be co-evolved to achieve the desired classes of behaviors.
Evolutionary dynamics of traits that mediate predator-prey/host-parasite interactions.
Ian Dworkin, Gerry Dozier, Richard Lenski, Charles Ofria, Benjamin Kerr
The language of evolution often uses terms such as ‘target’ of selection, that imply a unidirectionality to natural selection. Yet in most systems, complexity arises through interactions, whether intra-specific (competition and mate choice) or inter-specific such as between host-parasite or predator-prey. Hence, there is increasing interest in novel theoretical and empirical work that examines co-evolutionary dynamics and outcomes. However, the details of such interactions can vary substantially based on the nature of the interactions, as well as the relative evolutionary rates of the ‘partners’. For instance, in microbial systems, a viral parasite and its bacterial host may both evolve rapidly; while a viral pathogen and a human host will evolve on dramatically different time scales. These observations lead to diverse questions about the dynamics of such interactions at varying time scales, and in particular the evolution of traits that mediate such interactions. We propose to investigate the dynamics of such traits in diverse biological and computational systems, with the long-term goal of determining what features are universal across these interactions, and which features reflect scales of time and complexity that are particular to certain systems.
Stephen Thomas, Steven Thomas, Louise Souther Mead
Funds are being requested to develop two Flash-based digital games that will increase the public’s familiarity with evolutionary processes, help translate BEACON research to lay audiences, and increase interactivity and impact of museum natural history displays. The games will be simple in playability, yet focus on specific challenges and misconceptions pertaining to understanding evolution. The context for each game will be drawn from BEACON projects, with the introduction and conclusion of each game connecting evolution to specific BEACON research. These games will be delivered on touchscreens and placed in front of related museum exhibits to augment exhibit messages; games will also be usable on mobile devices and the internet. This project therefore addresses three specific goals of BEACON: 1) to communicate BEACON research to the public, 2) to teach fundamental concepts of evolution in action, and 3) to increase the level of viewer engagement with museum exhibits.
Evolutionary Games for K-6th
Despite, or perhaps because of, its singular importance, evolution and evolutionary theory suffer from a significant lack of acceptance, particularly in the United States. Additionally, among both those who accept evolution and those who reject it there are numerous fundamental misconceptions regarding the action of evolution. In many cases these two problems are mutually reinforcing, individuals reject evolution because they misunderstand fundamental tenants or misunderstand fundamental tenants because they refuse to consider them with an open mind. Education can be used to increase both understanding and acceptance of evolution and thus is one of BEACON’s fundamental missions. Many efforts have been made to design educational tools and materials to clearly and convincingly illustrate evolution and evolutionary theory. Although often successful, these efforts have had three limitations: they primary focus on high school or undergraduate education; often involved formal educational experiences; and they are more observational than participatory — individuals observe (in silico) evolution rather than participating in it. Thus, they are less likely to involve and excite very young students whose views regarding evolution are less established and to involve people less invested in formal education. To address these limitations we will develop evolutionary games that 1) are designed for a much younger audience, i.e. K-6th grade and 2) represent a good medium for introducing and exploring the concepts of evolution without requiring an extensive educational curriculum. In addition, this research will examine the problems involved in effectively incorporating evolution into games and will develop general techniques for overcoming these problems.
Thomas Schmidt, Barry L Williams, Bjørn Østman, C. Titus Brown, Larry Forney
For 3 billion years, life on Earth was strictly microbial. A dramatic diversity of microbes evolved during that time, and they now house the majority of the genetic diversity on the planet. Access to these microbial genes is now possible through metagenomics — the sequencing of DNA extracted directly from complex microbial communities. While the capacity to obtain DNA sequences is growing rapidly, our ability to interpret sequences is limited both computationally and conceptually. The goal of this project is to expand upon our initial efforts to apply evolutionary principles to the interpretation of metagenomes. In the first 4 months of this project, we measured selection pressures by estimating evolutionary rates of non-synonymous and synonymous substitutions in metagenomes of the gene nirK, which is involved in the production of nitrous oxide, a potent greenhouse gas. We found strong evidence for purifying selection at nirK in agricultural treatments and relaxed selection in forested soils. While standard ecological analysis revealed different populations of nirK-containing bacteria in agricultural and forested soils, this evolutionary based approach provided the first evidence from metagenomes for selection acting on a specific gene. We propose to expand the analysis to other genes and other complex microbial communities as a precursor to initiating a larger effort in the nascent field of evolutionary metagenomics.
Evolutionary Optimizing of Strategies to Improve Emergency Response Planning using Agent-Based Models to Model Human Behavior
Erik David Goodman
Critical Incident Analysis is an emerging field of study that encompasses modeling of natural disasters and man-caused incidents, responses to minimize their adverse impacts, and understanding of the short- and long-term effects these incidents and the responses to them have on society, particularly on people’s trust in government and willingness to follow emergency directives. Goodman was one of the founding members of the Academy for Critical Incident Analysis (ACIA), started two years ago at John Jay College, City University of New York, to study CIA. JJC educates much of the leadership of the emergency responders of New York City and other large cities, and created this new Academy under sponsorship of the Dart Foundation. This project concerns application of evolutionary computation to the realm of planning for responses to critical incidents. Robert Till, a mechanical engineer, is an Associate Professor at JJC in the department of Protection Management, and works on, among other things, emergency management in evacuation scenarios (train stations, subways, urban traffic, etc.). Goodman has served as the ‘mathematical modeling and optimization’ guru for the Academy. Goodman began the project working with MSU Professorial Assistant (undergrad) Matthew Durak and with Till on development of an agent-based model for urban evacuation in response to a hazardous chemical leak from a train wreck, modeling behavior of individual drivers and effects of toxic chemical exposure on their fates and behaviors. Evolutionary computation (in the form of HEEDS, developed by Goodman) is used to optimize the control of (non-sensor-equipped) traffic signals to speed traffic from the city. Early results indicate that signal optimization can reduce fatalities from such incidents by about half. This initial model is serving as the illustration of such an ABM/ optimization approach for a chapter in the forthcoming Handbook of Critical Incident Analysis authored by ACIA participants, which will be used, among other places, in courses in Critical Incident Analysis being taught at JJC.
Exploiting Robot-Fish Interactions and Evolutionary Computing to Understand and Synthesize Complex Collective Behavior
Xiaobo Tan, Philip McKinley, Jenny Boughman
We propose to create realistic two-way interactions between real and robotic fish and build an evolutionary computing (EC)-based framework, to 1) understand sophisticated communication and group behavior in fish, and 2) synthesize control and learning strategies for autonomous robotic systems operating in noisy and unstructured environments. Specifically, we will focus on the study of a particularly interesting behavior found in fish, predator inspection, which provides a rich context for fish-robot interactions and is highly relevant to autonomous robotic systems. An autonomous robotic fish with realistic morphological and movement features will be used as a responsive predator to interact with a group of sticklebacks (prey), so that we can study the communication, cooperation, and learning behavior of the latter. EC methods based on digital evolution and neuro-evolution will be used to model the observed behavior and understand its evolutionary origin, and to further design complex autonomous behavior for robotic fish operating in uncertain environments with computational, communication, and energy constraints. The project is expected to yield critical initial results on the new paradigm of using two-way animal-robot interactions to advance the knowledge base in both biology and engineering. Such results will be crucial for landing multi-investigator grants from agencies such as NSF and ONR (which already indicated interest). The project exploits evolutionary computing to bridge evolutionary biology and evolutionary robotics, and is aligned fully with BEACON’s mission. Direct robot-fish interactions will also provide intriguing materials for education and outreach, including museum exhibits and hands-on demos for K-12 students.
Foundations of Intelligence: Behavioral Flexibility in a Spatial Context
Charles Ofria, Robert T. Pennock, Fred Dyer, Robert Heckendorn, Benjamin Kerr, Frank Norman Bartlett, Aaron Wagner, Arend Hintze, Luis Zaman, Jacob Walker
A major challenge in biology is to understand how evolution can build intelligent systems that integrate sensory information, learn, make inferences, and choose a course of action appropriate for the environment. To answer such evolutionary questions, biologists typically draw upon comparisons of extant species. However, this approach is limited to questions about recent stages in evolution, and is not amenable to experimental manipulation of genetic, environmental, or phenotypic constraints on evolution. We can overcome these limitations using digital evolution. Building on preliminary work funded by BEACON, we will use Avida and Arend Hintze’s Emgine software to explore the early evolution of intelligent behavior in tasks similar to those studied by team members in bees or hyenas. We will develop populations of digital organisms that evolve the ability to move about a grid, sense resources or other organisms, and reactively change orientation, and then examine the process by which the intelligent control of these movements evolves. We will focus on two problems: (1) navigation toward energy sources or refuges in the presence of local or long-distance sensory information; (2) formation of stable groups associated with resource locations. In one case organisms are trying to find specific locations; in the other they are trying to coexist around them. The coordinated study of these spatial control strategies will illuminate how basic information-processing mechanisms can be integrated through evolution to produce rudiments of spatial intelligence.
Gene Network Activation During Hemichordate Development and Regeneration
Billie J. Swalla
Spinal cord injuries in the human population are common and frequently result in paralysis, greatly changing the quality of life for the person. It is estimated that about 450,000 people in the USA live with spinal cord injuries, with about 10,000 new injuries each year. These injuries primarily result from motor vehicle accidents, violence, or falls, but there is no cure. Great strides have been made in understanding the genetic and cellular basis of nerve cord injury, but there is currently no model system in which adult animals can completely regenerate their central nervous system. We can induce regeneration of the head, neck and central nervous system in a hemichordate, Ptychodera flava. Hemichordates are invertebrate deuterostomes, related to vertebrates, and share many of their developmental genes and gene networks with humans. Hemichordates are closely related to echinoderms, which are remarkable for their powers of regeneration. Some hemichordate worms show immediate, dramatic regeneration of their anterior head region after being cut in half. They quickly regenerate their central nervous system, heart, kidney and pharyngeal slits. Hemichordates have a central nervous system that rolls up from ectoderm during the process of regeneration, very similar to the way that the central nervous system is formed during normal development in hemichordates and vertebrates. Adult body regeneration in hemichordates may therefore show similar molecular patterning to chordate regeneration. We are asking for funds to quickly establish molecular tools to study regeneration in Ptychodera
Genetic & Evolutionary Biometrics and Security
GENERTIA-II: A Proactive Vulnerability Analysis, Design & Redesign NCA&T has been partnering with Secure Designs, Inc. to develop a system for vulnerability analysis of intrusion detection systems (and firewalls). The name of this proactive and selfhealing system is GENERTIA-II (GENEtic inteRactive Teams for Information Assurance). GENERTIA-II is an extension of GENERTIA-I. GENERTIA-II will perform multi-packet vulnerability analysis, design, and redesign. Genetic & Evolutionary Biometrics (GEB) NCA&T has been developing a number of Genetic & Evolutionary Feature Extractors (GEFEs) and Genetic & Evolutionary Feature Selection (GEFeS) methods. The GEFEs have been used to evolve novel feature extractors for Face & Periocular Recognition. GEFEs have been used to reduce the size of feature sets while increasing accuracy for Face, Periocular, and Iris Recognition.
Genomic mechanisms underlying increased virulence in Campylobacter jejuni
C. Titus Brown, Jeffrey E Barrick
The enteric pathogen Campylobacter jejuni adapts quickly to its host environment, rapidly gaining virulence in serial transfers through a mouse model of campylobacteriosis (Jerome et aI., 2011). This gain of virulence appears to be caused entirely by mutations in contingency loci, homo polymeric tracts that experience frequent base insertion and deletions that alter gene sequence and expression. Previously, we used population-level resequencing to show that these were the only genomic differences between a pre- and post-passage population (Jerome et aI., 2011), supporting the hypothesis that contingency loci generate genomic diversity that enables C. jejuni to rapidly evolve to exploit new host environments. We propose to extend this work by sequencing other replicate C. jejuni lineages, already passaged through mice as part of the same experiment, to determine whether or not the same contingency loci changes are responsible for adaptation in these populations. As part of this effort, we will improve how the breseq software tool predicts mutations in population-level bacterial resequencing data, analyze contingency loci evolution in laboratory-evolved C. jejuni lineages with relaxed selection, and initiate an effort to quantitatively analyze the evolution of contingency loci in C. jejuni using a quasispecies model (in collaboration with a course taught by Dr. Wilke and Dr. Covert at UT Austin; see their proposal).
Hyenas Rule! – Distance Learning Products
Gary Morgan, Julie A Avery, Barbara Lundrigan
The goal of this project is to take IVC (Interactive Videoconferencing) distance learning and modular exhibit products developed for the ‘Hyenas Rule’ exhibit and make them available to schools nationally. Funds will be used to refine the products for use by grades 9-12, using the research of zoology graduate students as a lens to deepen understanding of science methods, evolution and expose students to science as a career choice. Support and auxiliary materials will include an online exhibit, downloadable materials for teachers and students as well as pre/post program evaluation. Additional funds will be used to subsidize the costs of providing IVC programs to increase participation of underserved students.
Increase BEACON-UW Diversity
The University of Washington has many programs that actively reach out to and recruit students from underrepresented ethnic background and students with disability. I propose to initiate recruiting efforts in conjunction with and parallel to the many existing programs in UW so that underrepresented students will be encouraged to participate in BEACON’s education and research activities.
Individual versus Group Selection in Cooperative Communities
Wenying Shou, Benjamin Kerr
Cooperation is wide-spread yet paradoxical: why cooperate if cheating is an option? Underpinning the conundrum of cooperation is the conflict between individual and group interest: a cooperator pays a cost to generate, for its partner, a benefit greater than the cost. A ‘cheater’ consumes the benefit without paying the cost of cooperation. Thus, in a mixed community of cooperators and cheaters, cheaters have a fitness advantage and should therefore out-compete cooperators, resulting in a group of pure cheaters. However, a group of cheaters is less fit than a group of cooperators, since only in the latter do individuals derive a net benefit from reciprocal cooperation. The conflict between individual and group interest predicts that selection at the individual and the group level will yield dramatically different outcomes, selecting for cheating and cooperation, respectively. To test this prediction, we will use CoSMO, an engineered yeast cooperative system that consists of two metabolically complementary strains, each overproducing and subsequently releasing a metabolite essential for its partner strain. Since metabolite overproduction incurs a fitness cost, cheaters would be cells that consume but not supply metabolites. We propose to perform a comparative evolution experiment on CoSMO to test the difference between individual and group selections. In individual selection, all CoSMO cocultures will be propagated, effectively selecting for fastest-growing individuals. In group selection, only the top tier of fastest growing cocultures will be selected, each expanded to multiple progeny cocultures. We will test whether group but not individual selection results in stable cooperation.
Long-term consequences of evolution in action examined over a phylogeny
Luke Harmon, Joe Felsenstein
In this project we will develop new statistical comparative methods to connect longterm patterns of evolutionary change with short-term studies of evolutionary processes. Recent studies of evolution in action have shown that selection can often be very strong and that traits can evolve very quickly. However, rates of long-term evolution (‘macroevolution’) are much slower than what one might expect given how quickly traits change over short time scales (‘microevolution’). Despite the critical importance of linking micro- and macroevolution, the two areas of study remain mostly separate. Our work will address this important discrepancy by developing and applying new statistical tools for analyzing comparative data — that is, phenotypic and genetic data from living species along with information about their evolutionary relationships. Our project has two specific aims. First, we will develop methods that fit quantitative genetic models to comparative data. Current methods for analyzing comparative data are limited to heuristic models that are disconnected from biological processes. We will develop methods to fit models that include measurable biological parameters, such as population size, mutation rates, and the mode and strength of selection. Second, we will use these new methods to test evolutionary hypotheses in five large datasets across the tree of life, from plants to lizards and mammals. Our project will make much-needed connections between ‘evolution in real time’ and ‘evolution in deep time.’ The goals of the project are: 1. To develop new methodological approaches for analyzing comparative data. 2. To evaluate the performance of these methods using simulations. 3. To use these new methods to test evolutionary hypotheses using data from the tree of life.
Mystery of Mysteries
Barry L Williams, Jenny Boughman, Richard Lenski, Luke Harmon
Borrowing a phrase from the philosopher-scientist John Herschel, Charles Darwin called the origin of species ‘that mystery of mysteries’. The fundamental process of speciation is the inception of all biological diversification, yet we know little about the mechanisms that cause species to become reproductively isolated over time. This lack of knowledge is because the process of speciation is typically too slow to observe over the course of a lifetime. We can examine genetic differences between existing species, but the causal differences behind reproductive isolation are buried among the myriad other changes that have accrued over time. We will address these limitations by studying systems that allow us to observe rapid speciation as it occurs in nature, in the lab, and in computational realms. The Boughman lab will focus on incipient species pairs of sticklebacks to determine the genetic underpinnings of how natural and sexual selection have repeatedly resulted in premating isolation. The Lenski lab will examine whether an experimental E. coli population that evolved the novel ability to utilize citrate for energy is a case of speciation observed in the lab, by moving adaptive mutations between citrate positive and negative strains to determine if hybrid genotypes are maladapted. The Williams and Harmon labs will use a combination of digital and yeast populations to determine the relative roles of adaptation to deleterious mutations, adaptation to novel environments, migration, and random chance in the evolution of postmating isolation.
Plastic Plasticity: The Regulation and Evolution of Plasticity Pathways
Alexander Shingleton, Herbert Sauro
The last few decades have seen phenotypic plasticity move from being considered a nuisance in evolutionary biology to playing a central role in the origin of diversity. Plasticity is recognized as facilitating the evolution of novelties, through genetic accommodation/assimilation, and speciation, by allowing organisms to occupy novel niches 1. Nevertheless, a deeper understanding of the role plasticity plays in evolution is hindered by a fundamental lack of understanding of how plastic responses are regulated at a molecular genetic level 2. Our long term goal is to elucidate the molecular genetic mechanisms that regulate plasticity, and use in vivo and in silico approaches to explore how plasticity both evolves and how it facilitates/hinders phenotypic evolution. Our specific goal is to model the function and evolution of ‘plasticity pathways’ in silico and subsequently test these models in vivo. Plasticity pathways transduce environmental information to developmental processes generating phenotypic variation. We have developed a mathematical model of a key plasticity pathway, the insulin/IGF-signaling (IIS) pathway, which regulates organ size with respect to nutrition in all animals. We propose to evolve this model in silico and identify which components of the pathway are targets for selection on plasticity. We will then test these predictions using experimental data from existing wild-type and artificially-selected Drosophila lines that show evolved variation in nutritional plasticity. Our results will bring our understanding of how plasticity is regulated and how it evolves to a new and more profound level, an essential pre-requisite for understanding how phenotypic plasticity can facilitate and bias evolution.
Rapid evolutionary responses of marine phytoplankton to rising temperatures
Elena Litchman, Eva Top, Chris Klausmeier
Marine phytoplankton are globally important primary producers contributing ca. half of Earth’s carbon fixation. Diatoms are the dominant players in marine phytoplankton, generating approximately 20% of global primary production and forming the base of marine food webs. Due to their large size and weight, they contribute a disproportionately high amount to carbon sequestration in the oceans. Global climate models predict a rise in mean ocean temperatures of up to 3°C this century under a business-as-usual scenario. Diatoms experience drastic fitness changes over small temperature ranges, and this rise in temperature could have negative effects on their populations and global carbon sequestration. It is likely, however, that diatoms will be able to adapt to rising temperatures. Such adaptation is likely to involve complex trade-offs in cellular investment and eco-physiological strategies, requiring interdisciplinary research approaches. We will, therefore, take a three-pronged approach to unraveling the mechanisms of evolutionary responses of marine phytoplankton to rising temperatures.
- We will characterize thermal niches of several strains of diatoms and run laboratory evolution experiments with individual clones of ecologically important diatom species and clone mixtures to determine the nature of adaptation (either through increased temperature optima, growth rate at higher temperatures, change in niche width, etc.).
- We will investigate the genetic basis of such adaptation by comparing the genomes of ancestral and evolved populations and identify candidate genes responsible for thermal adaptation in phytoplankton.
- We will use adaptive dynamics models to predict the most plausible routes of evolution under different environmental scenarios.
Studying genomic mechanisms underlying the loss of tails in the Molgulids
C. Titus Brown, Billie J. Swalla
The MolguJid clade of ascidians contains multiple species that have at least three times independently lost tails during their larval stage. While the vast majority of the 3,000+ described species of ascidians develop swimming tails, replete with muscles and notochord, fifteen of the one hundred and fifty Molgulid species have lost a larval tail, suggesting that there is some genomic preadaptation for tail loss. Extensive prior investigation of two Molgula, M. occulta (tailless) and M. oculata (tailed), and their hybrids, has demonstrated that the loss of the tail in M. occulta is most likely due to loss of function mutations. Morever, this loss of function may have been potentiated at the base of the Molgulid clade by genome rearrangements. Therefore, we can study the Molgula to gain insight into the mechanisms by which significant changes to gene networks occur; how downstream components of gene networks change with upstream changes; and how genomic changes lead to changes in evolvability. We propose to continue our existing collaboration. In particular, we will extend our project to gather more embryos and sequencing data, cross-train our graduate students in computational and experimental analysis, and present our early results at an international conference.
Teaching evolution through action: the AVIDA challenge
James Arthur Foster, Mitch D Day, Gerry Dozier, Charles Ofria
The AVIDA Challenge uses a winner-take-all contest structure to encourage exploration of the AVIDA artificial life system and teach essential concepts of evolutionary theory and artificial life to undergraduate and high school students. The contest strategically introduces AVIDA to new institutions, trains future research assistants and addresses the lack of sufficient documentation for the AVIDA platform. We see this as a low-risk, low-cost way to quickly develop a broad base of competent AviDieties (Avida programmers) within the BEACON affiliate institutions and provide a model that can be replicated in any educational setting. Field-tested AviDieties will then be ready to assist with AVIDA-based research projects at their home institutions and increase demand for tools produced through BEACON activities. We will pose well-defined challenge problems, which students will meet using Avida. This will allow un-ambiguous determination of a winner. No other stipulations are given, so wildly creative and unorthodox solutions are allowed. A contestant could even attempt to rationally design a winning Avidian. We will not re-invent the wheel with the AVIDA Challenge. The creators of AVIDA have run similar competitions within the lead institution and have agreed to share materials and experience. Our effort will be primarily focused on documentation and promotion of AVIDA in affiliate institutions and to under-represented groups.
Teaching evolution to computer scientists, and vice versa
C. Titus Brown, Alexander Shingleton
In Year 1, we taught two introductory graduate courses (evolution for computer scientists, and computational science for biologists) across mUltiple institutions (MSU, UT Austin, and UW Seattle). We request funds to support this teaching in Y2, including a T A, some travel funds, some computational development funds, and additional technology improvement.
Brian D. Baer, Brian D. Baer, Renee M Starkey
The Genetic Architecture of Multidimensional Adaptation & Speciation
Bree Rosenblum, Jenny Boughman, Luke Harmon
We have developed a new collaboration to study the evolution and genetics of multidimensional adaptation. Our work integrates field, lab and computational approaches and focuses on two rapidly evolving groups, stickleback fish and white sands lizards. In both taxa we are studying a suite of traits, which are under correlated selection (i.e., body color, body shape, habitat use, mate preference, and locomotor performance). The current proposal focuses on the genomics of these adaptive traits in an effort to understand how and why they evolve together. We will employ computationally intensive analyses to link phenotype, genotype, and fitness, and reveal the nature of evolutionary change at the genetic level. Our proposal also includes plans for a cross-institutional graduate seminar on multidimensional adaptation and outreach efforts to increase public understanding of evolution.
The role of environmental change in evolutionary adaptation
Earth is a dynamic place; environments are changing constantly, and sometimes rapidly. The long-term survival of organisms is dependent on their ability to adapt genetically (i.e. evolve) to accommodate environmental transformations. The evolutionary consequences of shifts in environmental form have received some attention. However, the effects of the rate at which environmental changes occur remain largely elusive. Here, a microbial model system is used to address this issue. Previously in our laboratories, Escherichia coli populations were evolved under increasing concentrations of the antibiotic rifampicin. Three treatment groups were exposed to an identical final concentration of rifampicin, but arrived at this endpoint by differing rates. The probability of survival, final growth rate, and the identity of the mutations conferring drug resistance depended on the rate at which the environment changed. Using this system, we propose a combination of experimental evolution, molecular genetics and phenotypic assays to elucidate and compare the evolutionary trajectories accessible over increasing rates of environmental change. Together, the results obtained will provide insight into how the rate of environmental change affects adaptation. This research has significant practical applications, which include improving predictions of the effects of climate change and developing more successful antibiotic treatments.
Using directed evolution to optimize mutational robustness of genetic circuits
Sean Sleight, Herbert Sauro
Synthetic biology involves the engineering of cells with genetic circuits to perform a function that does not exist in nature. One problem with genetic circuits is their stability over evolutionary time in the absence of a selective pressure. We recently published work describing the evolutionary stability dynamics of genetic circuits and the mutations leading to their loss-of-function. In this work, we rationally re-engineered the genetic circuits based on loss-of-function mutations and found we were able to make the circuits more robust over evolutionary time. We propose to extend this work by using part shuffling and mutation randomization to engineer the circuits and then use a directed evolution approach to identify circuit designs that are the most robust. Part shuffling involves developing a novel PCR-based assembly method to shuffle the biological parts (e.g. promoters) in genetic circuits. Mutation randomization involves randomizing parts via mutagenic PCR in order to change parts at the sequence level. New engineered circuits will be transformed into E. coli and evolved via serial transfer. Using directed evolution, circuits that are the most robust over evolutionary time will be selected and the part shuffling and randomization methods will be re-applied to these circuits for at least 5 cycles. We expect that this evolutionary approach will allow us to re-engineer circuits that are more robust than we can design rationally, give insight into the evolutionary dynamics of genetic circuit stability, and allow us to develop improved design principles for engineering mutationally robust genetic circuits.
A Graduate Course in Computation for Evolutionary Biologists
Arthur W Covert, C. Titus Brown
We request Year 3 funding to support the continued active evolution
and development of a graduate course in computation, to be taught
across all four BEACON graduate institutions. The goals of this
course are to train current and future BEACON graduate researchers
in computational thinking and methodologies that are increasingly
important for research in evolutionary biology.
Aggregation and Co-evolution of Instructional Units in Digital Organisms to Model Metabolic Gene Clustering in Bacteria
Gowon Patterson, Julius Hamilton Jackson, Erik David Goodman
Genes for physiologically related metabolic functions tend to organize in non-random clusters in some well-studied bacterial chromosomes. This gene organization implies existence of a selection pressure that rewards the organism for gathering genes with related metabolic function. The goal of this project is to develop a digital model for study of the evolution of metabolic pathways and the tendency for related genes to co-locate on the chromosome. The first attempt at the model is being developed within the Avida platform. A focal point of research is the gene clustering phenomenon that occurs in bacteria. When an organism establishes a metabolic pathway, do selection pressures drive gene co-location? Is gene co-location accidental and coincidental? While the molecular mechanisms that rearrange genes in bacterial chromosomes are well-studied and understood, the selection pressure and selective advantage are not. The initial objectives are to 1) establish a community of digital organisms containing multiple, digital genes (d-genes) for a single, digital metabolic (d-metab) pathway; 2) evolve digital organisms (d-orgs) that gather the d-metab d-genes onto the same chromosome; and 3) devise a reward scheme for d-gene co-locations that conserve resources. An analogous, digital model may provide insight to evolutionary advantages and enable observation in more depth of the relationship between certain biological concepts and digital evolution. Successful development of a metabolic model in Avida would increase the breadth of research conducted using the Avida toolset.
An experimental evolution model for genomic islands of speciation
Barry L Williams, Paul Hohenlohe
With advances in DNA sequencing technology, the field of speciation genomics has emerged as a critical discipline in evolutionary biology. A central concept in speciation genomics is the genomic island — a chromosomal region of elevated differentiation between populations, caused by divergent selection, that can facilitate the evolution of reproductive isolation and speciation. This idea has received some support from modeling and comparative genomic work, but we still do not well understand the evolutionary processes that can lead to the formation of genomic islands and their dynamic behavior over time. A novel and extremely powerful tool to address these issues would be an experimental evolution system for genomic islands. In this project we will evaluate two possible experimental evolution systems: yeast and AVIDA. We will establish replicate divergent population pairs and use whole-genome data at multiple time points to observe the dynamics of genomic islands in an experimental setting. If successful, this project will provide a powerful new tool for speciation genomics, spawning many avenues for future research. This project is an equal collaboration between two labs at MSU and UI and will train graduate students in a range of techniques for modern evolutionary biology. By observing evolution in action, both in vivo and in silico, and by contributing a new approach to studying evolutionary processes, this project is central to BEACON’s mission.
An integrated approach to testing divergence with gene flow model of speciation; empirical genomics: simulation, and in silico evolution
David Hillis, Jack Sullivan, Emily Jane McTavish, Brice Andrew James Sarver
Determining the frequency and genetic impact of hybridization during animal speciation remains a central and unresolved issue in evolutionary biology. Recurrent hybridization among animal species has traditionally been viewed a rare and homogenizing force (Dobzhansky, 1951; Mayr, 1963). Alternatively, genetic factors underlying speciation, either via differential adaptation or sexual selection, may continue to accumulate between divergent populations despite on-going gene flow, eventually leading to lineage differentiation (i.e., speciation; e.g., Porter and Johnson, 2002). This second model, divergence-with-gene-flow (DwGF), predicts that closely-related taxa may continue to differentiate despite high levels of hybridization and introgression (Machado et al., 2002; Besansky et al., 2003; Grant et al., 2005; Turner et al., 2005). If DwGF is common (Nosil, 2008; Pinho & Hey, 2010), hybridization may be an important transient phase in speciation and introgression it also should be heterogeneous across the genome (e.g., Reisberg et al. 1999, Wu 2001). This project will build collaboration between the PIs labs and test predictions of DwGF in empirical (in vivo and in silico) and in simulated systems. The in vivo system will focus on the chipmunk radiation, a promising model for DwGF, and continue funding an RA for student Brice Sarver at UofI. and the simulations will be conducted by a continuing RA at UT, Emily Jane McTavish. This three-pronged approach will be synergistic and will provide preliminary data for a larger NSF proposal, to be submitted in 2013.
Avida-ED Curriculum Development and Assessment Pilot Study
Robert T. Pennock, James Arthur Foster, Joseph L Graves, Randall Hayes, Benjamin Kerr, Louise Souther Mead, James Smith, Claus Wilke, Neem Serra, Amy Lark
Avida-ED is the education version of the Avida digital evolution platform
BEACON Day NCA&T 2012
Gerry Dozier, Judi Brown Clarke, Yolanda Baker
BEACON Day at North Carolina A&T State University (NCA&T) is an event where ‘Evolution in Action’ is showcased to the entire faculty and student body at NCA&T. An additional goals of BEACON Day is to develop collaborations between researchers at NCA&T and researchers at the BEACON partner schools as well as develop student pipelines to other BEACON partner institutions.
BEACON Field Research Experiences for Undergraduates — Summer 2012
Joseph L Graves, Katherine Gross, Billie J. Swalla, Sarah L. Simmons, Rachel Prunier
The BEACON Field Research Experience will fund undergraduates to pursue cross-disciplinary research at the Kellogg Biological Station (KBS) and Friday Harbor Laboratories (FHL). Both sites have strong summer undergraduate research programs involving BEACON faculty. The program will support both advanced undergraduates (as REUs) and early career students (as Undergraduate Research Apprentices, URA). The URA program addresses the lack of preparedness that can limit the participation of students from under-represented groups in research experiences or pursuing STEM careers. All students will pursue empirical evolutionary research with a strong field component and be introduced to the analytical and computational tools needed for multidisciplinary research. Both REUs and URAs will participate in weekly seminars and mentoring activities at each site and will visit BEACON laboratories on the affiliated main campus. Videoconferences over the summer will provide a forum for students at the two field stations to share their research experiences and attend weekly BEACON seminars. The proposed program enhances the capacity of BEACON to integrate undergraduate education with multidisciplinary research activities and foster greater collaboration among partner institutions. It supports the educational goals of BEACON by increasing the diversity of students participating in research, better preparing them for careers in the scientific workforce, and increasing their understanding of evolution and the nature of science.
BEACON High School Summer Institute Programs
Thomas Getty, Drew Kim
The BEACON High School Residential Program got off to a great start in its first session in the summer of 2011, hosting 28 students (57% under-represented minorities; 61% female) for a week-long session of learning about evolution in action. Two graduate students were supported to develop and lead inquiry activities relating to natural selection in flowers, sexual selection in damselflies, and the dynamics of microevolution using Avida-Ed and BoxCar2D. Many people contributed to the program, including faculty from engineering, computer science and biology. Evaluations were quite positive. Understanding of evolution increased significantly and 26 of 28 participants said they would recommend the program to others. The program was highlighted for NSF officers at the Summer Congress, to our External Advisory Committee and to the NSF Site Visit Team in December. Important “areas for growth” have been identified and will be addressed in this continuation. We know that we need to recruit more broadly and will do so. We have learned how to improve the inquiry activities and are working to do that. Perhaps most importantly, the NSF Site Visitors encouraged us to broaden our impacts by disseminating our curriculum innovations nationally. We told them that we would, and we are working with Louise Mead to do it.
BEACON@A&T Administration/Infrastructure Request
Gerry Dozier, Joseph L Graves, Yolanda Baker
This budget request is for funds that will allow BEACON@A&T researchers and students to travel to BEACON related events, summer support for two faculty members, as well as a salary for the BEACON@A&T university program manager.
Biologically and Socially Inspired Computational Evolution for Product Life Cycle Management
Patrick Wanko, Paul M. Stanfield
Increasingly, the design of durable products, such as automobiles and aircraft, has expanded from traditional mechanical design to include more biologically inspired capabilities – learn, morph, communicate and sustain. This same transition is making its way to high value assemblies and parts on such products. The transition is enabled by Sensor-Integrated Automatic Identification Technology (SIAIT) which can provide data collection, storage, processing, and communication capabilities with minimal power requirements. Intelligent use of these enhanced capabilities depends primarily on the development of integrating processes. Processes are needed to use the collected data to improve part/product design and operating parameters in order to minimize costs, extend life cycles, and enhance sustainability. The federal government alone spends 100s of billions of dollars each year on these issues. Due to the biological nature of the parts, bio/eco systems are expected to be the primary sources of process innovation.
The project proposes the continued research in the use of two adaptions of evolutionary computing specifically catered to solve this problem. One adaption is inspired by the dynamics of fish schooling and the other by social networks. Though justifiable based on the significance of product life cycle management, the algorithms are likely to be expanded to other complex service systems and might serve as examples of ways to use evolutionary computation to model biological/social phenomenon not typically considered evolution-based.
Biologically Inspired Control of Electric Energy Storage Systems
Gary Lebby, Morlue Eesiah, Kenneth Jones, Wen Fang, Charles Winley
Within the energy systems community there is a heightened interest in using alternative energy sources as a secondary and in some cases a primary power generation source for a stand-alone energy system. The power generated from these sources is dynamic in nature and can be highly dependent on the surrounding environment; therefore the energy system requires some type of energy storage element to adjust to the dynamics presented by the generation sources. Proper control of the embedded energy storage elements is a key factor for maintaining system reliability and sustaining optimal performance.
This project aims to develop a biologically inspired control mechanism for charging and discharging energy storage units within stand-alone energy systems; maintaining optimal performance by minimizing energy losses and reducing unnecessary switching between working states for the energy storage unit, extending their lifetime.
Can Communication Stabilize Cooperation?
Brian Connelly, Eric Bruger, Nerva Espinosa, Philip McKinley, Chris Waters, Benjamin Kerr
The evolution of cooperation is puzzling from an orthodox evolutionary perspective because a cooperative population is vulnerable to displacement by cheaters (individuals that benefit from cooperation without reciprocating). Thus, cooperation should inevitably dwindle into extinction. In stark contrast to expectation, cooperative behavior is widespread in Nature. Here, we consider the role of simple communication in resolving the cooperation paradox. We focus on bacterial communication in the form of “quorum-sensing” (QS), where gene expression depends on the concentration of signal molecules in the milieu. These bacteria-produced signals increase in concentration with cell density, such that a population can simultaneously “turn on” target genes at specific cell densities. Many QS target genes code for costly public goods (e.g., exoenzymes) and, not surprisingly, these systems are susceptible to cheaters. Nonetheless, our agent-based simulations predict that, in a spatially structured habitat, QS cooperators can invade a population of cheaters, whereas unconditional cooperators cannot. We will test these predictions about the emergence of cooperation with three different QS bacterial systems. We then explore the maintenance of cooperation in the face of de novo cheaters. Here we use an experimental evolution approach with two QS bacterial systems and the digital evolution platform, Avida (where digital organisms can send/receive signals and act cooperatively). Collectively, these experiments will reveal when and how simple communication stabilizes cooperation.
Coevolution in Genome Sections in Gram-negative Bacteria
Scott H. Harrison, Julius Hamilton Jackson, Justin Zhan
Recombinational change is associated with how bacterial populations succeed in switching between non-host to host environments. To investigate the impact on physiologic function and association with microbial habitat, we examine the arrangement of genes associated with the biosynthesis of the cytoplasmic membrane, cell wall and outer membrane in all fully sequenced Gram-negative bacteria. We construct a generative model for simulating the rearrangement of these genes based on site-specific and homologous recombination events. As a case scenario, lambda and lambdoid phages have been identified as a primary cause of recombinational change in some emergent disease-causing enteric bacteria. We seek to specifically address the likelihood by which lambda and lambdoid phage types distinctively mediate rearrangement.
Continuation for Podcast and Teacher Ed Course 2012-13
Podcast. VSI: Variation Selection Inheritance is a downloadable radio program composed of interviews and commentary that examines how evolution works, broadly, at the levels of biology, culture, and technology. A secondary focus is the process of science and how that process affects scientific culture. It is aimed at the general public but should be useful in the classroom as well.
Online Teacher Course BIOL 670. One school of thought in teaching politically sensitive topics like evolution is to simply ignore the controversy. The thesis of this course (and a future research project for an education specialist), borrowed from the physics education literature, is that students already have unconscious intuitions about how natural systems work, based more on their life experiences than on classroom study. These intuitions must be made conscious and demonstrated by the student to be inadequate before they can be updated to more accurate, more complete models. Simply presenting scientific models does not integrate them into the student’s existing epistemology. Students often have very explicit models of evolution, but the assumptions and implications of those models have never been examined. This course will consist of expanded versions of the following two modules, originally developed by PBS and WGBH Boston. The first module, Teaching Evolution, contains both information about how evolution works and pedagogical ideas about how to teach it in an inquiry-based way. The second, Teaching Evolution in the 21st Century, looks more specifically at intelligent design.
Cross-fertilization of Techniques for Epistasis from Evolutionary Computation and Biology
Robert Heckendorn, Sudarshan R Chari, Richard Lenski
Epistasis, or the phenotypic consequences of non-additive interactions between genes is a fundamental property of genetic systems. While theory predicts that epistasis can have profound consequences on the trajectory and dynamics of evolving systems, there remains several numerous unanswered questions that are primarily the result of a lack of a general set of tools that can be used both estimate the degree of epistasis in a system, as well as its contribution (relative to additive effects) to the observed phenotype. In particular the tools to investigate problems beyond second order interactions, or for complex multi-variate traits are generally lacking. These issues also are of concern in the field of evolutionary computation, which uses natural selection as an algorithm to aid in optimization problems. Despite these common problems, there has been little effort to integrate and synthesize approaches across fields. We propose to both integrate some of the current approaches used to study epistasis across evolutionary computation and biology. Furthermore we will be extending approaches under current development by the investigators to allow the examination of interactions of arbitrary dimensionality, as well as multi-variate “traits” that allow for the consideration of pleiotropy. We will develop software to implement these methods that will aid and extend the tools for the investigation of epistasis.
Darwin vs. DARPA: Evolution of a 256-node neural controller
Chris Adami, Arend Hintze, Dave Knoester, Sam Chapman, Risto Miikkulainen
The highly publicized DARPA project “SyNAPSE” aims at developing neuromorphic machine technology that would ultimately support artificial intelligence, for a project cost to date of $42 million. The design is based on fairly standard neural network technology rendered in hardware, and appears to be difficult to program, with only limited learning capacity. Rather than demonstrate the scalability of a neuromorphic computation paradigm, many expect that this project will instead demonstrate that human design of controllers for complex tasks is impossible. We propose instead to evolve a comtroller with similar specifications as DARPA’s neuromorphic chip, but using a novel computational framework (stochastic Markov networks) where the connectivity of computational nodes and learning behavior of each gate is evolved with a Genetic Algorithm. We intend to match the performance of DARAPs chip (recognition of single numerals and playing the computer game “Pong”) within the first 6 months of the project, then move on to successfully evolve a controller for a scaled-down version of the game “Tetris”, using Markov brains where each gate is run on a single core of a GPU. Achieving this project has ramifications that may be felt across the entire AI community, as it would show that evolution beats design, even when the design is based on modern biological principles, and has substantial institutional (DARPA and IBM) as well as financial support behind it. Furthermore, evolution beats design for a fraction of the cost.
Design and Implementation of Assistive Robotic Residence Home (DIARRH)
Abrham Workineh, Daniel Opoku, Abdollah Homaifar, Albert Esterline
We are designing an RFID fully augmented home (rooms are tagged and most of the items in the house are tagged with RFIDs) setting with assistive robot which interacts meaningfully with that environment and residents through its sensors and RFID antennae. The robot is required to improve the quality of life of the cognitively impaired living in the house by running errands. It does this by learning to decide on and execute some daily activities such as searching for items e.g. gadgets, drugs, food items, literature, etc.; giving indoor directions, etc. The knowledge acquired from the RFID fully augmented environment will then be diploid in a RFID partially augmented home.The robot has full or partial knowledge of targets and their location. Thus, learning and decision making are the integral parts of this project. We are investigating evolutionary learning algorithm and developing a hybrid evolutionary learning algorithm capable of robust learning of common household items features and decision making routines, with particular focus on hierarchy formation in LCS. Building a hierarchical set of rules, where accurate and more specific rules respond to a subset of the situations covered by more general but less accurate default rules will be vital to achieve a compact rule set size, especially when dealing with an environment that has huge numbers of states. Thus, we are developing a hybrid hierarchical blend of low level and high level object segmentation and recognition techniques capable of robust and near real-time recognition of some selected household items and actions.
Developing a Virtue-based Approach to RCR Training
Robert T. Pennock, Michael O’Rourke
NSF requires RCR training for all BEACON student participants, and BEACON’s major ethics goal, stated in its strategic plan is”“to practice and promote ethical and responsible research by implementing cross-disciplinary and multi-institutional ethics programs that will inform and guide all participants of the Center.”” This project aims to pilot a new approach to RCR training based on intrinsic “scientific virtues” (such as curiosity, objectivity, skepticism, integrity, etc.) as an alternative to the traditional “legalistic” approach. We will develop presentations, workshops and Toolbox-style modules that embody this virtue-based approach. We will pilot test these in BEACON weekly meetings and annual Congress, which will also help grad students and post-docs fulfill their RCR requirements.
Enhancing Diversity Through a Summer Workshop on Evolution in Action at the Molecular Level
Barry L Williams
The goal of this project is to continue a summer research experience for underrepresented minority undergraduates. Students will develop cutting edge research skills, learn the process of science and concepts in evolution, and will be exposed to scientific undergraduate and graduate student culture. The course will incorporate research from the Williams’ lab that includes molecular evolution, genetics, molecular biology, and microbiology. The multi-disciplinary approaches are used to address question in each of three research projects that are central to the mission of BEACON. The first is experimental evolution to examine the adaptive processes that influence evolution of pathogenicity in yeast. The second is determination of the mutational fitness landscapes for yeast proteins. The third is to identify segregating mutations that contribute to population specific yeast adaptations to pathogenicity in human hosts. Because the nature of this work is both bio-medical and evolution in action, I have been quite fortunate thus far in recruiting students that might not otherwise be interested in evolutionary biology.
Enrich Research Experience for Undergraduate Students from Underrepresented Ethnic Background and/or Living with Disability
Faculty members at the UW are very interested in hosting research projects by students from underrepresented ethnic groups and students with disabilities. We strongly believe that exposing students to the wonders of scientific research at an early stage will facilitate their scientific development. We request summer research funding for three current UW undergraduates and one incoming freshmen to the UW, all from underrepresented ethnic groups or living with disabilities. Collaboration with the UW GenOM (Genomics Outreach for Minorities) program is proposed.
Evolution Curriculum for Elementary Classrooms: Implementation and Assessment of LadyBug and Supporting Activities
Melissa Kjelvik, Terence Soule, Thomas Getty
“Nothing in biology makes sense except in the light of evolution””, and yet, many K-12 teachers across the country are still trying to teach biology without teaching evolution. This is particularly acute at the elementary level. There are many reasons for this, including a lack of understanding and acceptance of evolution among adults, including teachers2. Our goal is to capitalize on BEACON personnel, research and resources to develop effective new inquiry activities that will entice and empower elementary students to “discover” how evolution works. Computer games can do this effectively3-5, but only if they are integrated into the elementary curriculum in ways that captivate students and serve teachers’ curriculum needs. The LadyBug online software developed by Terry Soule6 has great potential to capture elementary students’ attention while they discover the basics of evolution, but to realize its full potential in elementary classrooms, it needs to be developed into an effective curriculum module that teachers will adopt because it serves their needs. We can do this by working with KBS K-12 Partnership teachers, using their classrooms as a research and development test bed for adapting LadyBug and supporting materials into effective learning progressions that teachers across the country will use in the classroom to meet their goals and the kids use to discover how evolution works. This is a new project that has emerged from two different earlier projects7-8. As part of this project, Melissa Kjelvik will also work with Louise Mead on other education initiatives.
Evolution of cognition, communication, and social coordination
Robert Heckendorn, Chris Adami, Fred Dyer, Robert T. Pennock, Charles Ofria, Frank Norman Bartlett, Peter Stone, Arend Hintze
A major challenge in biology and computer science is to understand how intelligent behavior emerges in systems (animals, robots) that are made up of simple components (cells, transistors). Biologists study how evolution shapes the organization of bodies and brains to enable animals to integrate information and choose actions appropriately; this is challenging because of the complexity of brains and their evolutionary histories. In computer science, a common approach is to design artificial systems that can deal with problems similar to those faced by organisms; in spite of some successes, the behavior of artificial systems is still a poor match for the fluidity, flexibility, and richness of behavior even in small-brained organisms such as insects. We seek to advance both fields by studying the evolution of digital systems where the environments can be specified, evolutionary history can be recorded, and evolved strategies can be decoded. Building on prior work by our group, we are focusing on the evolution of basic navigational skills in individuals, and their integration via communication into coordinated behavior of the sort observed in honey bee colonies. Specifically, we will use digital evolution in multiple platforms to ask: (1) what are the ecological and genetic prerequisites favoring the evolution of basic navigational abilities? (2) how could navigational information be transmitted from one individual to another? (3) how could algorithms that evolve for these problems be used to guide the search for more flexible algorithms for robotic control in AI?
Evolution of Evolvability
Rosangela Canino-Koning, Joshua Richard Nahum, Eamon O’Dea, Charles Ofria, Richard Lenski, Lauren Meyers, Benjamin Kerr, Eric Klavins
In an ever-changing world, organisms must continually adapt to survive. Under such fluctuating conditions, it can be advantageous to be evolvable. One way to achieve greater evolvability is to increase the rate of mutation. However, raising the mutation rate uniformly across the genome is problematic as the majority of mutations are not beneficial. By concentrating mutations in genomic regions more likely to yield adaptation (contingency loci), a lineage lifts its evolvability while minimizing an increase in mutation load. In natural systems, short sequence tandem repeats (loci that experience a high frequency of indels as a result of polymerase slippage) may act as contingency loci. Here we engineer a contingency locus of tandem repeats in the ribosome binding site of a fluorescence gene, where repeat number affects gene expression level. We compete a bacterial strain with the contingency locus against a “non-contingency” strain under conditions expected to favor (oscillating selection) or disfavor (constant selection) evolvability. We also use experimental evolution to explore the origin of contingency loci in this bacterial system as well as the digital system Avida. In the latter case, we introduce a new instruction that alters the mutation rate of nearby instructions. All microbial and digital experiments will be informed by mathematical models of evolution in changing environments. Collectively, this research will provide insight into the evolution of genomic motifs that elevate local mutation rate and selective conditions that favor the evolution of evolvability.
Evolutionary dynamics of traits that mediate predator-prey/host-parasite interactions
Justin Meyer, Jenna Gallie, Benjamin Kerr, Charles Ofria, Richard Lenski, Gerry Dozier, Luis Zaman, Michael DeNieu, Alita Burmeister, Ian Dworkin
The language of evolution often uses terms such as “target” of selection, that imply a unidirectionality to natural selection. Yet in most systems, complexity arises through interactions, whether intra-specific (competition and mate choice) or inter-specific such as between host-parasite or predator-prey. Hence, there is increasing interest in novel theoretical and empirical work that examines co-evolutionary dynamics and outcomes. However, the details of such interactions can vary substantially based on the nature of the interactions, as well as the relative evolutionary rates of the “partners”. For instance, in microbial systems, a viral parasite and its bacterial host may both evolve rapidly; while a viral pathogen and a human host will evolve on dramatically different time scales. These observations lead to diverse questions about the dynamics of such interactions at varying time scales, and the shape of the co-evolutionary fitness landscape. We propose to investigate and estimate these landscapes in diverse biological and computational systems, with the long-term goal of determining what features are universal across these interactions, and which features reflect scales of time and complexity that are particular to certain systems.
Fly Wing Biometrics
Gerry Dozier, Ian Dworkin
This budget request seek seed funding for the development of a research program devoted towards the development of genetic & evolutionary based feature extraction and feature selection for biometric recognition of fly wings. This proposal budget request is a collaboration between one faculty and one student in the Computer Science department at North Carolina A&T State University and one faculty member in the Department of Zoology at Michigan State University.
Idaho Administrative Budget
James Arthur Foster
We are requesting operating funds for Year 3, which which to accomplish the following goals:
Increase IBEST/BEACON effectiveness
Optimize IBEST/BEACON interactions
Recruit new, diverse students and postdocs
Support BEACON staffing
Respond to unexpected opportunities
Funds will be distributed at the discretion of the PI (Foster) with advise from the IBEST Research Oversight Team (Forney, Wichman, Joyce, Foster).
Making the Avida Software more accessible to researchers.
Charles Ofria, David Michael Bryson
We will produce a version of the Avida software with a graphical interface that is simple to install and use on both Windows and Apple operating systems. Our goal is to make the software highly accessible to all members of BEACON (and the scientific community beyond) so that a new research can easily start an Avida project without requiring additional help from an existing user. The current state of the software relies on text files for configuration, a text-based user interface, and documentation that can be arcane at times. Our goal is to update the look and feel of the software, building off recent advances made in Avida-ED (its educational counterpart) so that it has a much broad set of tools for configuration, interaction, and analysis. Additionally, we plan to develop a built-in and intuitive help system, as well as screen-cast tutorials to easily guide new users through setting up an experiment, running it, and understanding the results.
Pinpointing the genetic origins and functional co-option of a peptide pheromone
Barry L Williams, Heather Eisthen
Pheromones are molecules that evoke discrete behavioral and/or physiological responses from conspecifics. Amphibian pheromones tend to be peptides, affording the unique opportunity to study the evolution of genes coding for communication signals. The first peptide pheromone to be discovered was sodefrin, a female-attracting pheromone produced by newts (Cynops pyrrhogaster); similar genes coding for sodefrin-like peptides have been found in other genera of newts, and even another family of salamanders. We recently discovered a homologous gene for the sodefrin-like peptide in the genome of axolotls (Ambystoma mexicanum), which belong to a third family of salamanders, as well in the genome of the frog Xenopus tropicalis. Surprisingly, the homologs are also present but without annotated function in humans, mice, and zebrafish, suggesting that the origin of this gene family is ancient. The evolutionary history of this gene family has not been explored and the function of the gene products is unknown outside of two families of salamanders. We propose here a set of pilot experiments combining bioinformatics, neurophysiology, and behavior, designed to elucidate the history and function of this gene family, to train and recruit a female minority graduate student, and to provide preliminary data for a grant proposal to either NSF or NIH. We expect that the results of this work will either reveal the existence of the first widespread peptide pheromone family, or will help us understand how molecules are evolutionarily co-opted for use as pheromones.
Rapid evolution of damselflies in response to anthropogenic change and range shifts
Thomas Getty, Eben Gering, Idelle Cooper, Molly Cummings, Muraleedharan G Nair
Understanding how contemporary evolution in action will mitigate or exacerbate the impacts of climate change on biodiversity is a critical research need that requires the integration of evolutionary theory, biochemical and physical mechanisms, and ecology. Our primary research question is: How does anthropogenic environmental change affect biodiversity through microevolutionary and macroevolutionary processes? We investigate this question at multiple levels in nature: (1) species distributions along ecological gradients, (2) species interactions within communities, and (3) biochemical and physical mechanisms within individuals. Our previous research in Megalagrion and Calopteryx damselflies reveals several links between biodiversity and environmental conditions that point to a major role for color variation in adaptation and speciation. By examining Megalagrion pigmentation that is under ecological selection and Calopteryx pigmentation that is under sexual selection, our continuing research will help elucidate the general mechanisms that enable rapid evolution during climate change.
Reforming a Large Undergraduate Nonmajors Biology Course (Part 1 of Infusing Evolution Through an Entire College Biology Curriculum)
Chad Rohrbacher, Randall Hayes
4e. Abstract: The “two cultures” problem proposed by Snow has become almost a self-fulfilling prophecy (1). Science is considered boring by many students, largely because of the way it is communicated (2-3), and evolution is treated as simply one more fact-set to be memorized, rather than as biology’s unique organizing principle. African-Americans such as the students at NCATSU are particularly likely to reject evolution based on previous cultural training (4). We will train adjuncts and graduate teaching assistants to use the latest active learning techniques as we research more effective ways to teach evolution, particularly to skeptical audiences. We will begin by collecting journal responses through an automated writing tutor (5), simultaneously collecting data on student’’ mental models of evolution and improving their writing skills (a vital secondary goal is improving our master’s students’ chances of entering a Ph.D. program). This pilot program is the first step in a larger program to create a “citizen’s biology,” focusing on major concepts necessary for personal health and harmony with the natural world over narrow professional training. We will begin by reforming a specific course: BIOL 100, the introductory nonmajors course. This will be a high-impact project because of the large number of students served (hundreds/semester), and because it will serve as a model for similar programs targeted towards those who teach preprofessional majors courses.
Robust evolutionary multi-objective optimization of practical rural land-use strategies, taking into account environmental impacts
Kalyanmoy Deb, Erik David Goodman
Robust Multi-objective Evolutionary Optimization to Allow Greenhouse Production/Energy Use Tradeoffs
Erik David Goodman, Kalyanmoy Deb, Jose Rafael Llera, Prakarn Unachak
As part of China’s Twelfth Five-Year Plan, a new generation of energy-efficient greenhouses is to be designed, under direction of Prof. Lihong Xu, of Tongji University, a regular visitor to BEACON. An experimental greenhouse, with extensive instrumentation, is under construction on the campus of Tongji University. Profs. Xu, Deb and Goodman are developing an evolutionary control strategy, called Multi-Objective Compatible Control, which will allow explicit identification of Pareto-optimal tradeoffs between the rate of production of the crop and the amounts of energy and materials used to support the growth. It is difficult to develop a controller to maintain not a fixed environment, but a time-varying tradeoff, based on weather and plant conditions, that stays in a Pareto-optimal range of input costs and resulting crop growth. A key to improving the model used for control is to include a more realistic model of plant growth, and for this purpose, Hannah Professor David Kramer (MSU BCM & Molecular Biology) and Profs. Jeremy Harbinson and Ep Heuvelink (Wageningen U, NL) are joining the team. The project is heavily funded in China, including sending of Tongji graduate students to MSU, and BEACON student participant Jose Llera has non-BEACON fellowship funding to cover his participation for next year, so BEACON is asked to support a student from Dr. Kramer;s lab and a postdoc at MSU to coordinate the team. Proposals to NSF’s International Division and to USDA are expected to yield support for the longer term.
Scent marking mammals, their microbial symbionts, and the hologenome theory of evolution
Tracy Teal, Benjamin Kerr, Charles Ofria, Thomas Schmidt, Kay E. Holekamp, Kevin R Theis, Luis Zaman
No animal has evolved independently of symbiotic microbes. Instead, each has coevolved with suites of microbes whose genomes have profoundly affected its biology. As a paradigm-shifting consequence, animals are beginning to be viewed as holobionts — consortia of hosts and all their symbiotic microbes — rather than isolated entities. The hologenome theory of evolution—heralded as the new frontier of animal biology — holds that 1) interactions between hosts and microbionts affect the fitness of the holobiont, 2) genetic variation among holobionts can be enhanced by the incorporation of new microbionts, and 3) microbionts can be transmitted across generations of animal hosts with fidelity. The theory’s summary principle is that the holobiont is a primary unit of selection. Our objective is to begin testing predictions of the theory 1) by designing and implementing novel ecological network analyses to link molecularly surveyed microbionts to their ecologically relevant functional genes, 2) by investigating natural variation in microbiotic community structure within and among African mammals, and 3) by creating and studying artificial holobiont populations in digital fitness arenas using Avida. The natural investigations will afford a broad and extrapolatory view of mammal-multisymbiont mutualisms, while the digital experiments will enable us to tease apart holobiotic selective pressures by revealing the genotypic and phenotypic qualities of entire populations. In concert, these inquiries will afford a robust foundation for further evaluations of the hologenome theory of evolution.
Slow and Steady Wins the Race? Adaptation in Structured Worlds
Charles Ofria, Arthur W Covert, Claus Wilke, Aaron Wagner, Joshua Richard Nahum, Benjamin Kerr, Robert T. Pennock, Luis Zaman, Eva Top, Larry Forney, Heather Goldsby, Brittany Harding
One of the central aims of evolutionary biology involves understanding how populations adapt over time. This information is contained in the mapping from genotypes to fitness, metaphorically called the “adaptive landscape.” Given the vast number of possible genotypes for any organism, any adaptive landscape is unknowable in full detail. Nonetheless, by studying multiple replicate evolving populations, we can infer some topographical features. In particular, we can infer whether a landscape is smooth (mutations act independently) or rugged (epistasis is present). Here, we use a combination of computer models and microbial/digital experimental evolution to explore landscape topography. By using spatial structure as an experimental variable, fitness trajectories in evolving populations can distinguish between smooth and rugged landscapes. We have found evidence for rugged topography in evolving E. coli and Avidian metapopulations. Here we extend this experimental approach to elucidate the landscape topography of a bacterial plasmid. We then use all three systems (Avida, plasmid and bacteria) to test additional predictions from our models about the effects of spatial structure on genome evolution. Finally, we will build (1) a “spatial topology manager” enabling full versatility in defining population structure in Avida and (2) a touch-screen educational application allowing for students to “finger-paint” adaptive landscapes and watch structured populations evolve in real time. Altogether, this research will lead to a deeper understanding of adaptation in structured worlds.
Social Evolution and Learning in Computational and Biological Agents
Eliana Feasley, Kay E. Holekamp, Risto Miikkulainen, Wesley Tansey, Andrew Booms
While evolutionary computation has been used successfully to develop complex behaviors in intelligent agents, in natural populations the individuals also learn some of these behaviors during their lifetime. Interaction of learning and evolution has been studied in limited computational settings to date, either through immediate rewards, or through individuals designated as teachers. In this project, social learning is proposed as a biologically motivated form of machine learning: Each individual can learn from any individual in the population deemed successful. Social learning will be implemented in neuroevolution simulations, and its power compared to other approaches to evolve intelligent behavior (i.e. evolution only, student/teacher model, and reinforcement learning). Existing and proposed observations of learning in hyena societies will be used both as motivation and as a test case for this new approach.
Studying genomic mechanisms underlying the loss of tails in the Molgulids
C. Titus Brown, Elijah Kariem Lowe, Max Maliska, Billie J. Swalla, Lauren Elizabeth Vandepas, Charlotte Konikoff
The mechanisms by which evolutionary novelty evolves in animal development are incredibly complex and extremely interesting. Our model makes use of two closely related ascidian species that have dramatically different larval body plans. Molgula oculata eggs develop into free-swimming chordate tadpole larvae, whereas a closely related sister species, Molgula occulta, develops into an anural, or tailless ascidian. Fertilization and cleavage in M. occulta are remarkably similar in timing and pattern to its sister species, M. oculata. However, the anural M. occulta embryo fails to differentiate several chordate features, including an otolith (gravity sensing vesicle), notochord and tail muscle cells, which are characteristic of ascidian tailed tadpole larvae. These chordate features have been shown to be controlled by genomic changes affecting zygotic development: when an egg from the anural species is fertilized by sperm from the urodele species, the hybrid possesses many chordate features, including the brain sensory organ, notochord, muscle, and tail. We have been investigating the cellular and molecular basis of these tailless ascidians by comparing the transcriptome of the hybrid and the two species embryos at several different developmental stages. Surprisingly, the notochord specification gene network is expressed, in spite of the embryo lacking a notochord. However, metamorphosis genes are also expressed early, much earlier than has ever been seen in other ascidian species. We have submitted an NSF preproposal to continue our exciting and productive collaboration.
The Evolution of Canalization Mechanisms
Jeffrey E Barrick, Alexander Shingleton, Carlos Anderson
It is easy to be struck by the range in diversity of organisms that inhabit nature. What is equally impressive, however, is the constancy of form within any particular species. The process by which development generates a reliable phenotype in spite of environmental and genetic perturbations is called canalization, and is an area of great interest to both developmental and evolutionary biologists. Despite years of research on the topic, however, there are very few biological examples of canalization mechanisms, severely constraining our understanding of how canalization evolves. These mechanisms ostensibly act by imposing external control on the developmental pathways they canalize, rather like training wheels on child’s bike. However, our research has revealed a new class of canalization mechanisms that lie within the developmental pathway that they canalize. Here we propose to elucidate the nature of this class of canalization mechanisms, using the fruit fly Drosophila melanogaster as a model organism, and explore the extent to which such mechanisms are likely to evolve, using Avida artificial life software.
The Genetic Architecture of Multidimensional Adaptation and Speciation
Paul Hohenlohe, Bree Rosenblum, Luke Harmon, Jenny Boughman, Jason Keagy, Tyler Hether
Our continuing collaboration focuses on the evolution and genetics of multidimensional adaptation and speciation. These questions demand a multidisciplinary approach, and our team integrates field, lab, and computational approaches focused on two rapidly evolving groups, stickleback fish and white sands lizards. We study suites of traits in both taxa that are under correlated selection (body color, body shape, habitat use, mate preference, and locomotion). We study the genomics of these adaptive traits in an effort to understand how and why they evolve together. We employ computationally intensive analyses to link phenotype, genotype, and fitness, and reveal the nature of evolutionary change at the genetic level in the animals’ natural environment. The first year of our project included a cross-institutional graduate seminar on multidimensional adaptation. We also had outreach efforts to increase public understanding of evolution. Our collaboration has expanded to incorporate a new faculty member at U Idaho, Paul Hohenlohe. The value of adding Paul to our team is exceptional; he furthers our multidisciplinary goals by bringing in a modeling approach to our questions about the effects of dimensionality on the genetic architecture of speciation. One outcome of our graduate seminar was to realize both the promise of our approach, and that so little is known that we lack even basic predictions of what genetic architecture results from multifarious selection. Theory can generate those predictions; an important contribution to evolutionary biology and to our empirical work.
The genetic basis of weediness: rapid evolution of flowering time in wild radish
James Arthur Foster, Gregory Goins, David C. Tank, Jeffrey Conner, Ian Dworkin
Evolution can be very rapid, especially when there are major changes in the environment. One such change caused by humans was agriculture, and many species of animals, plants, and microbes rapidly evolved to be come pests in farmer’s fields. Wild radish is one of the world’s worst weeds, and has spread to every continent but Antarctica, but the weedy form of this species differs markedly from their native ancestors from the Mediterranean region. The principal difference is in flowering time — the weeds flower within a month after sprouting to ensure seed production before the field is harvested, while the native wild radish delays flowering until after their first winter. We propose to sequence a number of genes known to be involved in flowering time to determine which of these genes evolved rapidly as wild radish adapted to agriculture. The sequence data will also be used to ask other key questions about weed evolution, such as when the weeds first evolved, when did they spread across the globe, which genes evolved first, and whether wild radish adapted to agriculture once or multiple times. If there were multiple evolutionary origins of weedy radish, we will determine whether the same flowering time genes were responsible for rapid adaptation in each case, in other words, was evolution repeatable at the DNA level, and whether the weeds evolved from the same or different native populations. These results will improve our understanding of the mechanisms of evolution in action, and may be helpful in managing the weeds as well as breeding better crop radishes.
The University of Texas Infrastructure Request
Laurie Alvarez, Risto Miikkulainen
Request for UT infrastructure
Undergraduate Research Education in Computational Biology
Arthur W Covert, Claus Wilke, Benjamin Kerr, Barry L Williams
We request funding for a Freshman-Research-Initiative (FRI) stream at the University of Texas at Austin (UT), to further the education goals of BEACON. An FRI stream is a year-long course designed to give freshman and sophomore students actual research experience. 20 to 30 students spend one semester in an inquiry-based course learning computational research methods, taught by a Research Educator (a post-doctoral-level instructor), followed by a semester conducting actual research in various labs, at UT and other BEACON institutions. In the first semester, students learn standard research techniques in computational biology, including the basics of programming, running software-aided statistical analysis on large data sets, running Avida, and basic scientific reasoning. In the second semester, students participate in a variety of hands-on research projects organized by the Research Educator. For the 2012 stream, several UT students will spend the summer at collaborator labs at other BEACON institutions to initiate their research projects. They will complete their projects during the fall semester at UT. Funding for this proposal will enable undergraduate students to perform research on evolution in action. Through their computational experiments, they will experience evolution rather than simply learning about it in a classroom. Past students in the FRI program have made contributions to projects which will be submitted to the Alife XIII conference (and future journal publications) as co-authors.
Understanding and Synthesizing Collective Behavior with Mixed Robotic and Live Fish Schools
Xiaobo Tan, Philip McKinley, Jenny Boughman, Liliana Lettieri, Jason Keagy, Jianxun Wang, Sanaz Bazaz Behbahani, Tony Joseph Clark, Lihong Xu, Daniel Joel Couvertier
Exploiting synergy between robotics, evolutionary computing, and fish biology, this project aims to create mixed robotic and live fish schools to (1) understand sophisticated group behavior of live fish, and (2) guide the synthesis of complex autonomous behavior for robotic fish schools. Using bluegill sunfish as a model system, we will develop robotic fish with high maneuverability, energy-efficiency, and realistic swimming behavior, by taking inspiration from biology and drawing upon advances in 3D multi-material printing and computational evolution. The robots will be actuated by both caudal fin and pectoral fins, and controlled by a central pattern generator (CPG). Coevolution will be applied to jointly optimize the morphology, actuation mechanisms, and the CPG controller. Multiple robotic sunfish will then be used to engage live sunfish and elicit their subtle, complex behavior in sustained interactions. In particular, we will investigate how live fish join a robotic fish school under a range of hydrodynamic and lighting conditions, and use the gained insight to design robust schooling strategies for robotic fish. The project is expected to yield critical initial results on the new paradigm of applying sophisticated animal-robot interactions, facilitated by evolutionary computation, to advance both biology and engineering. Such results will be crucial for obtaining multi-investigator grants from agencies such as NSF and ONR. The project will also provide intriguing materials for education and outreach, including museum exhibits and hands-on demos for K-12 students.
Unleash your inner scientist: employing and enjoying inquiry in the classroom and lab. A BEACON/BioQUEST summer workshop for the new AP Biology Framework.
Louise Souther Mead, James Smith
The new AP Biology Framework is an exciting opportunity to shift to a more concept-focused inquiry-based course. BEACON and BioQUEST are collaborating to offer a five-day, residential workshop at the Kellogg Biological Station for AP Biology teachers to prepare for the upcoming course changes. The workshop will emphasize incorporating an inquiry approach in the classroom and lab and teachers will receive information on the logistics and special administrative aspects of offering a College Board sanctioned AP Biology course. The workshop provides time to select and adapt labs that connect to the four Big Ideas in the AP Bio framework (the process of evolution, energy flow, information transfer, and the complexity of biological systems). BEACON staff and researchers will offer specific examples and connections to evolution in action. We envision summer 2012 as an opportunity to pilot the program, and establish the collaboration between BEACON and BioQUEST, and anticipate similar workshops can be offered in 2013 across our consortium institutions, particularly with the support from and collaboration with BioQUEST.
This is a first-time infrastructure/administration request from UW. Funds are requested for three items, including (1) partial salary of an administrator to handle all financial, organizational, and administrative duties for UW BEACON, (2) the ONIX Microfluidic Perfusion Platform allowing for long-term live cell imaging of bacteria, yeast and animal cells and (3) fees for equipment use (e.g., robots, scopes, sequencers, servers, etc.) at the Comparative Genomics Center and the Imaging Facility at UW. All equipment (including the purchased ONIX system) would be available to any UW and visiting BEACON faculty member or student. All items included in this request are meant to benefit the UW BEACON community (as opposed to a single lab). Matching funds have been allocated to further enrich the UW BEACON community (through purchase of furniture and computers for shared space, food for all-hands Friday BEACON meetings, and additional equipment usage fees).
Why hop? Understanding morphology, mechanics, and natural selection in the evolution of bipedal hopping.
Anne K. Gutmann, Craig McGowan, Philip McKinley
Our goal is to understand why animals as diverse as kangaroos, wallabies, kangaroo rats, and jerboas all hop. These animals span a surprisingly wide range of body sizes and habitats, but all have the same basic leg design and use a two-legged hop to move from place to place. One hypothesis is that hopping evolved as a means of producing the high accelerations needed to escape predators. However, differences in muscle-tendon architecture suggest that some hopping animals have evolved for energy efficiency rather than high acceleration. We propose using an interdisciplinary approach that integrates biomechanics, computation, and physics-based simulation to understand how selective pressures shape the evolution of leg design and gait in these animals. To achieve this, we will use an established evolutionary environment and physics-based simulator to determine which selective pressures produce bipedal hopping. Simultaneously, we will develop a detailed musculoskeletal model of a kangaroo rat to determine the effects of muscle-tendon architecture on hopping dynamics. Finally, we will adjust the leg design of this model to match the designs that emerge in the physics-based simulator and compare the effect of different limb designs on muscle-tendon dynamics. This integrated approach will provide novel insight into why and how the musculoskeletal system evolved for hopping. Results from this study can be readily applied to improve biologically-inspired robots and prosthetic devices.