BEACON Researchers at Work: Can’t we all get along? Overcoming evolutionary conflict

This week’s BEACON Researchers at Work blog post is by University of Washington postdoc Sylvie Estrela.

SylvieEstrela_photoConflict is widespread in nature and that is no exception in the microbial world. Examples of competitive interactions between microbes include competition for shared limiting nutrients, competition for space, and the production of compounds such as toxins and antibiotics that inhibit or kill competitors. In the face of such conflict, how can we explain the occurrence of mutually beneficial associations between unrelated organisms, known as mutualisms?

Microbes are intrinsically leaky, that is, they produce a broad range of metabolites into their environment as a result of their metabolism. When these waste products of metabolism are used as nutrients for growth, this is called cross-feeding. Thus, a cross-feeder reaps some benefit from the association with a producer. If the waste product is toxic to the producer, then waste removal by the cross-feeder is beneficial to the producer. This can be seen as trading a service (detoxification) for a resource (food). At a first glance, it seems that both partners would benefit from the association, setting out the ground for mutualism to occur. To gain a better insight into the dynamics of this interaction, I started by developing a simple mathematical model. The model revealed that this simple cross-feeding interaction can generate a variety of possible ecological outcomes, spanning mutualism, exploitation, and competition. Furthermore, it highlighted the importance of the metabolic constraints of individual species and the features of their shared environment, such as toxicity level and decay rate of the waste product, in determining the conditions for mutualism [1].

This was the beginning of my academic journey into exploring how mutualism may arise at the first place and be maintained, and which ended up being the main focus of my PhD research supervised by Dr. Sam Brown at the University of Edinburgh. At this point, the model described two species growing in a well-mixed (planktonic-like) environment. But in natural environments, most microbes live in surface-attached, spatially-structured communities such as biofilms. An interesting feature of growth in a structured environment is the stronger potential for demographic feedbacks between interacting partners. This is mostly due to the fact that an individual cell has a stronger effect (either positive or negative) on its neighbouring cells than on the cells that are further apart, which in turn feeds back on its own growth. So how do metabolic interactions and demographic feedbacks combine to shape the spatial organisation and functioning of polymicrobial communities?

Figure 1. Simulation of a two species community where species are engaged in a food for detoxification metabolic interaction. While strong metabolic interdependence drives species mixing, weak metabolic interdependence drives species segregation.

Figure 1. Simulation of a two species community where species are engaged in a food for detoxification metabolic interaction. While strong metabolic interdependence drives species mixing, weak metabolic interdependence drives species segregation.

To address this question, I used a spatially-explicit model that simulates the growth of the two-species community on a surface. I found that strong metabolic interdependence generates mutualism and species mixing, and community behaviour is less sensitive to variation in initial conditions (initial species frequency and spatial distribution). In contrast, weak metabolic interdependence generates competition and species segregation, and community behaviour is highly contingent on initial conditions (fig. 1, [2]). Hence, these findings suggest that demographic feedbacks between species are central to the community development, shaping whether and how potential metabolic interactions come to be strengthened or attenuated between expanding species [3].

Now as a postdoc in Prof. Ben Kerr’s lab (UW), I’m interested in exploring further some of these questions by specifically focusing on the evolution of mutualisms and interdependencies when traits are costly to perform rather than just a waste product of metabolism. Because of the lack of relatedness between partners, evolutionary conflicts of interest will be strong. But despite conflict, interspecific mutualism can prevail when the conditions are such that partners’ interests are aligned and potential conflicts are kept in check. A critical question is how this can be achieved. In collaboration with Prof. Ben Kerr and Prof. Eric Klavins (UW), I’m using the ‘gro’ simulation platform to address this question (fig. 2).

Figure 2. Snapshot of a ‘gro’ simulation showing the emergent spatial pattern of two species exchanging costly essential functions.

Figure 2. Snapshot of a ‘gro’ simulation showing the emergent spatial pattern of two species exchanging costly essential functions.


Key references

[1] Estrela, S. et al. (2012) From Metabolism to Ecology: Cross-Feeding Interactions Shape the Balance between Polymicrobial Conflict and Mutualism. Am. Nat. 180, 566–576

[2] Estrela, S. and Brown, S.P. (2013) Metabolic and demographic feedbacks shape the emergent spatial structure and function of microbial communities. PLoS Comput. Biol. 9, e1003398

[3] Estrela S, Whiteley M, and Brown SP (in press) The demographic determinants of human microbiome health. Trends in Microbiology

For more information about Sylvie’s work, you can contact her at sestrela at uw dot edu.

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BEACON Researchers at Work: Teaching a Robot to Learn

This week’s BEACON Researchers at Work blog post is by University of Idaho graduate student Travis DeVault.

TravisI imagine it would be difficult to find someone working in the field of computer science that did not start with a love of working with a computer. Likewise, I doubt many people choose to work with robots unless they love robots and the future that robots hold for us. We live in a world where personal, mobile computers are more limited by fashion trends than by hardware requirements, but it was only a few decades ago that personal computers were just starting to enter the average home. And so, it is the same for robots today as it was for computers decades ago.

The promise that robots offer us for tomorrow is that of cheap, reliable machines that can perform any number of complex or simple tasks that are currently performed by people. We have robots working on other planets, robots that explore our oceans, robots that perform surgery, and robots that build cars; in the near future though, robots will be common in every home and business. Robot surgeons and explorers will need less human supervision, and the cars will be robots. I’m personally most looking forward to a robot maid that can do a good job cleaning dishes.

Training trackBut for now, I think we’ve got to admit robots are pretty stupid. All the cool robots are either teleoperated by people, or at least heavily monitored and given instructions. Sure, I’ve got a robot vacuum that can do a better job than I can, but according to my wife, I’ve always found a way to make the house more of a mess when I try to clean. The robot vacuum never learns a better way to clean, it misses spots, it never knows where the dirty areas are, it scares my dog, and it still can’t figure out how to empty its own dirt bin. It’s really just an RC car with a vacuum and some infrared sensors to make sure it doesn’t bump into walls (I still bump into walls when I vacuum).

The research I do at the University of Idaho Laboratory for Artificial Intelligence and Robotics (LAIR) uses the principles of evolution in many different ways to enhance robotic learning. Our goal is to make robots that can learn over time, either through observing people or by receiving instruction from a human trainer or from other robots. One aspect that is very unique about the LAIR is that we use real robots for all of our work. Most groups doing robotics research will do most of the work in simulation, and then maybe transfer a finished control structure to a physical robot in order to create a youtube video. At the LAIR, the entire experiment is conducted on the robot.

Because the work is done with a physical robot, one of the challenges of the work is creating a robot that is able to sense its environment. Although many sensors have been created for robots such as infrared and ultrasonic eyes, we’ve chosen to rely more on the built-in cameras of a smartphone. Image processing is a slow job even on a beefy PC, on a smartphone it because a very slow process. One of the ways that we use evolution is in an evolved vision algorithm; the evolution uses a genetic algorithm to decide what parts of an image it should process in order to make decisions.

Our goal is to create robots capable of learning in a large variety of environments, which includes taking the robots outside as part of our experiments. We create robotic brains which can evolve different behaviors based on the situations presented to the robots by a human trainer. Our robots have used an evolved brain to travel on indoor and outdoor paths. The learning is done at run time when the robot is driven on the road by the trainer. Using this type of evolved learning, the robots have achieved a 95% success rate at navigating roads which the robot had never been trained on.

Continuing on this work, we have decided to focus on distributing the evolutionary learning over a network of several robots. Some of the questions we’ve asked leading into the work are: Does distribution increase the learning rate? Does a robot perform better with distribution? Do multiple trainers matter? Can we make the robots train other robots to perform better on a more difficult problem? Currently, the roads following results are so good without distribution that we are creating a more difficult experiment for the robot, so that we can effectively test all of these questions.

trvis robotFuture plans for the LAIR include working with the agriculture department at the University of Idaho to make evolve robots capable of weeding potato and wheat fields. We intend to try to use an evolved vision algorithm to identify invasive species and plant illnesses using smartphone cameras and sensors. The smartphones could then create a GPS map of areas that farmer would need to investigate. We will eventually have robots with sophisticated enough behaviors that we can rely on them to kill the unwanted plants.

For more information about Travis’ work, you can contact him at zerill at gmail dot com.

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BEACON Researchers at Work: What Every Scientist Needs to Know

This week’s BEACON Researchers at Work blog post is by University of Texas graduate student Amir Shahmoradi.

asmSummary: In a world in which science and technological breakthroughs dominate all aspects of almost every individual human life, scientists and researchers are under an ever increasing pressure to cross and expand the borders of human knowledge. As new discoveries require higher levels of precision and reproducibility, excess workload and hyper-competitive work environments have made researchers more prone to human cognitive biases. A solution to this emerging problem is to introduce all graduate students in STEM fields with the limitations of human mind and scientific instruments and their potential role in false positive discoveries and misconduct of scientific research. I suggest that a full-semester course that covers relevant topics including those mandated by NSF as Responsible Conduct of Research should be developed and tailored for each individual STEM field of research and be offered as an integral core course of every graduate program across the world.

Growing up in a traditional and highly religious society, I was drawn from an early age to the romantic mystique of ancient religious and philosophical writings. I joined study sessions and participated in lively discussions with religious scholars. But living in an academic household, I gradually developed a sense of scientific skepticism that led me to question the basic tenets of this knowledge. By contrast, science and mathematics seemed so captivating to me as a teenager for a very simple reason: Science is based on observation, evidence, and mathematics. It is universal, independent of people, society, religion and ideologies.

My passion for science, in particular Astronomy, Physics and Biology kept growing, until I stumbled on a post dubbed “The Same Color Illusion” in Astronomy Picture of the Day (APOD), which profoundly changed the way I view and perceive the world around me ever since. This APOD post showcased a simple example of human cognitive bias and how it can affect our perception of similar and different colors, with a simple clear message: “What human senses perceive of the world, does not necessarily reflect the reality.”


The psychological literature is full of studies that demonstrate how human’s limited senses can result in cognitive flaws and biases in our understanding of the universe. In fact, psychologists have pinpointed many types of biases that affect not only the way we see but how we think about and react to the world around us. Confirmation bias, for example, is the tendency to notice, accept, and remember data that confirms what we already believe, and to ignore, forget, or explain away data that is contradictory to our beliefs. To make things worse, add the (unknown) limitations of instruments by which human probes the universe. The combined effects of human and instrument biases can result in erroneous conclusions and predictions.

Fortunately, many of such biases are now well understood by scientists, in particular, by experimental physicists, biologists and observational astronomers. A worked-out example is the well-known Malmquist bias in observational astronomy. Nevertheless, as our circle of knowledge expands, so does the circumference of darkness surrounding it, bringing new types of instrumental and human cognitive biases with it, that might affect human’s understanding of natural phenomena.

Today, we live in a world that relies heavily on science and technology. As a result, the number of scientists has also grown exponentially rapidly over the past century. With limited funds and resources now available to the community of scientists, the competition and work stress has also increased steadily among researchers.

In such a hyper-competitive atmosphere, scientists are more prone to perception and cognitive biases due to excess workload and stress. There already exist websites, such as Retraction Watch, that regularly report new examples of wrong scientific papers, and papers that contain fake or irreproducible results, forgeries and plagiarism.

The two major funding resources of science in the United States, the National Science Foundation and the National Institute of Health have already stepped in to mitigate the increasing trend that is seen in irreproducibility of scientific discoveries and retractions of scientific articles, before scientists lose the public’s trust in their work. Examples of actions taken include new rules for validating scientific discoveries and mandatory Responsible Conduct of Research (RCR) for all students and postdocs supported by NIH and NSF funds.

Personally, I cannot believe that any scientist in the world would intentionally want to fake results or commit plagiarism or be involved in any other unethical action. Over the past decade, I have witnessed how human cognitive biases can affect the minds and scientific results of numerous scientists. I have seen scientists who insist on the accuracy of their wrong discoveries, and in many cases, I have become convinced that there is no personal intention involved in their stance. I have been very fortunate to work on some specific research projects that opened my mind to many of the limitations that we humans and our scientific instruments face in probing and understanding the universe.

I personally believe the RCR trainings mandated by NIH and NSF can become even more efficient, if they were instead offered as a mandatory comprehensive full-semester course, for all graduate students in all STEM fields, a course that would also cover the myriad of human cognitive biases and instrumental limitations that would meddle with reasoning of every scientist and their understanding of natural phenomena. Regardless of where these students end up, whether academia or industry, whether they are funded by NSF/NIH or not, every student in science programs must learn about the limitations of human mind and its potential adverse effects in scientific reasoning and discoveries.

For more information about Amir’s work, you can contact him at a dot shahmoradi at gmail dot com.

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BEACON Researchers at Work: Engineering life

This week’s blog post is by University of Washington graduate student Leandra Brettner.

LeandraAll living organisms share a universal programming language—DNA. Long strings of unit molecules A’s, T’s, C’s and G’s dictate the unique traits of each individual, but the code is read ubiquitously across each species. This means that a gene that encodes a protein in one organism would encode the same protein if transplanted to another creature. Synthetic biologists use this property to engineer life by doing just that, rearranging genes from different species to program new behaviors into organisms. I am a synthetic biology graduate student in the lab of Professor Eric Klavins, and I work with genetically programmed bacteria, specifically Escherichia coli.

Microbes such as viruses, bacteria and yeast, are cheap and easy to grow, making them excellent platforms for synthesizing traditionally expensive organic chemicals such as fuels, pharmacologicals, and commodities like plastics. By performing the chemistry to create these products in microorganisms, we can potentially both decrease cost and increase sustainability and performance. Researchers like Jay Keasling at UCSF and Angela Belcher at MIT are demonstrating the amazing utility of living chemistry by manufacturing drugs such as artemisinic acid in yeast and building record breaking batteries out of viruses.

However, when we introduce foreign behaviors into cells, we are competing with millions if not billions of years of evolutionary history. Microbes, like all organisms, work hard to maintain the energy balance that supports life. Synthetic programs mess with that equilibrium, limiting the engineering complexity we have currently been able to achieve.

I work on developing ways to increase the complexity of engineered behaviors in microbes by isolating them into working groups—kind of like how factories use assembly lines, everyone has a specific task that contributes to the whole. These division of labor schemes are seen through every hierarchy of biology, from symbiotic bacteria to eusocial insects.

Our system’s goal is to digest complex carbohydrates like those in plant waste and turn it into usable biomass that can go towards producing carbon-based products like the biofuels and therapeutics mentioned, further reducing the cost and making production carbon neutral.

schematic of systemThe population of engineered bacteria start out in a consumer state where their only job is to grow and reproduce. Then, every so often, a cell will switch to an altruistic state where it produces an enzyme that breaks down cellulose and lyses to deliver the goods to the extracellular environment. The digested sugars can then be used as food for the consumer cells.

This cooperative architecture has allowed us to build in the complex behavior of novel nutrient use that can be coupled with chemical production in the future.  

However, this system suffers from an interesting form of community evolutionary instability called “the tragedy of the commons.” In well mixed culture, any variants that arise that cease to perform the cooperative behavior (cheaters) can still reap the public good provided by the altruists. Because they fail to lyse, the cheaters have an increased fitness advantage and can sweep the population—but to their ultimate demise. Without the altruists, cellulose digestion comes to a halt and the population crashes. Previous work has shown that if, however, there is some spatial organization to the environment, the communal benefit applies only to nearby, closely related cells who are likely fellow altruists. The cheaters are left stranded with limited or no access to the resource. This phenomena, dubbed kin selection, propagates the cooperative behavior through many generations. Members of Professor Ben Kerr’s lab are currently working with my system to investigate if they can evolve strains that exhibit increased cooperation by propagating cell lines in structured environments.

I look forward to continuing to collaborate with the Kerr lab, and potentially extending their research to the design and tuning of new synthetic organisms.

For more information about Leandra’s work, you can contact her at leandra dot brettner at gmail dot com.

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Meet the 2014 BEACON Distinguished Postdocs, Chandra Jack and Will Soto

This year, BEACON was fortunate to be able to appoint TWO new Distinguished Postdoctoral Fellows. Meet Chandra Jack and Will Soto!

Chandra Jack

ChandraChandra started working in the Strassmann-Queller lab at Rice University as an undergraduate in the summer after her sophomore year to earn money while volunteering as a member of the Rice EMS. That summer she began research looking at kin discrimination between different genotypes of Dictyostelium purpureum. Originally planning to go to medical school, Joan got her hooked on all things dicty, so she spent a year after graduating as a technician before beginning graduate work in the same lab. She received her PhD in evolutionary biology where her thesis work explored how the population structure of D. discoideum is affected by interactions with related species and with other members of the same species.

Now at MSU, Chandra joined the Friesen’s lab in the plant biology department in August. She was really interested in Maren’s research exploring the mutualism between plants and rhizobia, as well as the many methods being used in the lab. However, she isn’t sure if Maren would have accepted her if she knew her plant reputation included losing one cactus and killing another.

(Currently all of her plants are alive and accounted for.)

Her research will address the role of PMI (Plant-Microbe-Insect) interactions in driving rapid evolution using Medicago polymorpha. She will compare the response of different genotypes of M. polymorpha from its native habitat in Europe to those of invasive genotypes found in North America when they interact with local (N. American) herbivores and rhizobacteria from both environments to look for evidence of genetic variation and to see if genetic variation between the two genotypes results in changes in gene expression. She will also create models that investigate the role of PMI interactions on the relationship between gene expression and plant fitness. Chandra’s work will determine the importance of multitrophic level interactions on rapid evolution and the success of invasive species as they enter new territories.

For more information about Chandra’s work, you can contact her at chandra dot jack at gmail dot com.

Will Soto

Will Soto

Will received his B.S. in biology from California State University, Fresno. Will developed an enthusiasm in microbiology in high school biology classes but became fascinated with evolution as a subject while at CSU, Fresno. Learning about the geological history of the fossil record and the rich biological diversity that evolved through adaptive radiations was exciting to Will. Evolution’s great stories like the “Age of Fishes,” “hopeful monsters,” the Cambrian Explosion, and mass extinctions were intriguing to Will. Additionally, learning about evolution made Will wonder why there were no freshwater echinoderms or freshwater cephalopods, given the tremendous biodiversity of these taxonomic groups. “Evolution has a great folklore and causes one to wonder about the rest of the natural world,” says Will. Will’s interests in microbiology and evolution merged into one. Will was especially interested in prokaryotes due to their colossal genetic and metabolic diversity.

After graduation from CSU, Fresno, Will spent two years in Fred Cohan’s lab at Wesleyan University, where he studied bacterial evolution. “It was in Fred Cohan’s lab that I learned about microbial experimental evolution and developed an interest for the work of Rich Lenski, Al Bennett, and Mike Travisano,” says Will. “When I read the Nature paper by Rainey and Travisano (1998) about adaptive radiation with Pseudomonas fluorescens, I was completely thrilled,” states Will. “Wrinkly spreaders and fuzzy spreaders; here’s another cool story,” he adds. After leaving Wesleyan University, Will entered a PhD program at New Mexico State University in Las Cruces in Michele Nishiguchi’s lab, where he studied the sepiolid squid-Vibrio mutualism. Will pursued a microbial experimental evolution project, where he serially passaged Vibrio fischeri through a novel squid host. “I took a V. fischeri strain indigenous to the Hawaiian bobtail squid (Euprymna scolopes) and serially transferred it through the Australian dumpling squid (Euprymna tasmanica),” claims Will. “I had a great PhD advisor who allowed me complete freedom. I also had a fantastic graduate committee,” says Will. Kathy Hanley, Geof Smith, John Gustafson, and Michele Nishiguchi were all on Will’s dissertation committee. Kathy Hanley is a superb evolutionary biologist, while Geof Smith and John Gustafson (now at Oklahoma State University in Stillwater) are spectacular microbiologists. Michele Nishiguchi provided the expertise on host-microbe interactions, along with the sepiolid squids and bioluminescent V. fischeri.

In 2012, Will became a postdoctoral teaching fellow funded through a grant from the Howard Hughes Medical Institute. He had two excellent postdoc advisors, Mike Travisano and Robin Wright. “I was delighted to be in Mike Travisano’s lab, as he was one of my grad school heroes!” says Will. In Mike’s lab, Will learned the tricks of the trade to microbial experimental evolution. Robin Wright mentored Will in the value of active learning, science education, and how to incorporate research into undergraduate education. “At the University of Minnesota-Twin Cities, I got to teach in an active learning classroom for the first time alongside Robin Wright. The experience was invaluable!” claims Will. 

Here at Michigan State University, as BEACON postdoc fellow, Will is working with Chris Waters on developing host infection models between disease-causing marine bacteria (e.g., Vibrio harveyi) and invertebrate hosts (e.g., shrimp) for microbial experimental evolution projects. “Chris and I are trying to take microbial experimental evolution with vibrios to aquaculture,” states Will. Will concludes, “I don’t understand why more microbial experimental evolution work hasn’t been done with the Vibrionaceae. This bacterial family has much to offer in studying evolutionary biology.”

For more information about Will’s work, you can contact him at wsoto at msu dot edu.

Previous recipients of the BEACON Postdoctoral Fellowship are Annat Haber (2013) and Joshua Nahum (2012).

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