BEACON Researchers at Work: A Developing Science Teacher – Research, Theory, and Application

Posted on February 16, 2015 by Danielle Whittaker

This week’s BEACON Researchers at Work blog post is by MSU undergraduate Lazarius Miller.

LazariusTeaching has been a dream of mine since I was a small child. I am a native of Detroit Michigan as well as a proud alumnus of Detroit Public Schools. I am interested in teaching science in urban school systems, which has a very diverse student population as well as resemble the education system that I came from. My hope is to develop curriculum that is focused on evolutionary science, so that diverse learners have the opportunity to understand more about themselves and the world in which they live, like I have been able to do.

When I was younger, my mom jokingly told me that I had been a monkey previously. She pointed to my tailbone and told me that I use to have a tail and that it fell off one day. I figured my mom was just joking, but it did pique an interest in how could I have been a monkey. When in middle and high school, I was told that evolution was not true and that I should not believe in something like that. I never thought much of evolution in high school, because we did not get a chance to talk about it in my biology class. My interest was piqued again during my freshman year at Michigan State University. The summer after my freshman year was completed, I worked with Dr. Louise Mead in the BEACON Center for the Study of Evolution in Action on a project entitled “Does Religion and Education Background affect Student Perceptions of Evolution.” This project had opened my eyes to teaching and learning that I did not truly understand. The project looked at how religion affected student perceptions of evolution using education background as another measuring factor, influenced a student’s desire to pursue a science career. As an aspiring middle/high school science teacher, this topic was important because the ages 13-17 seem to be very influential ages where individuality and independence start to develop. This age also seems like a time in which students begin to show rebellious behavior towards their guardians, but the beliefs that have been instilled in them have not had a chance to modify completely.

The original sample of students surveyed was invitees of a summer enrichment camp for high school achievers. The group of 29 students was from different grades, hometowns, school locations and types, as well as had taken a difference in science course difficulty. Racial background was not included in the study, but I did read a whitepaper by Dr. Joseph Graves, Dr. Louise Mead, and Dr. Judi Brown Clarke on African Americans in Evolutionary Science. The paper talked about how many people of color, primarily African Americans, are extremely religious, possibly due to the reliance of “God” during slavery, and any deviation from religion would not be received well. 

My original hypothesis was that the students would have a high religiosity and their attitude towards evolution would be negative. That was not the result. The students generally had a more positive attitude toward religion and studying science. I tried to figure out why the results turned out the way they did and then I remembered that these students were invited for their academic performance in science and math in high school, so they were probably more accepting of scientific phenomenon than non-science students. I wanted to test another group of students and compare results, but I also started to get interested in curriculum and if all students were getting equal access to proper scientific instruction and materials. 

The next summer, Summer 2014, I studied and researched at the Kellogg Biological Station in Hickory Corners, MI. There I took an ecology lecture and lab course that was more practical and applied. One of our assignments was to write a blog post about an ecological or biological concept that we found interesting. I immediately thought about my research project the previous summer and decided that I would talk about that. The initial article did not work out because it was focused too much on the social side of the study, but I wanted to find a way to explain evolution to someone who had professed disbelief. I instantly recalled a conversation with my aunt who happens to be a minister in a Baptist church. I used the concept of sin to explain to her how evolution works. I explained that sin would continue to grow and develop until an outside stimulus threatens the survival of sin. Our conversation was a bit longer, but she told me that she understood evolution better than she did before. I decided to write about something that many people would relate to and I chose to talk about the evolution of iPhones. In this article, I created an iPhone phylogeny that detailed some of the major changes in appearance (phenotype) and operating systems (genotype). At the time the newest iPhones out were the iPhone 5c and 5s. I also stated in the article that based on the phylogeny, we would have an iPhone 6c and 6s.

In December 2014, I got the opportunity to go back to my high school to speak with the AP Biology students about evolution, mainly trying to interest them in science. These students in this class were freshmen when I was a senior in high school; so some of them were familiar with me, which probably made the reception a bit easier to see familiar faces. My initial thoughts about this visit was that it was going to be tough because my school is primarily students of color and their ties to their religious beliefs would be strong and some may not entertain the thought of the evolution. As the day got closer to my presentation, I decided to develop a website that the students could access on their phones to take 3 short surveys, as well as a short presentation on evolution. I also provided my blog post on the evolution if iPhones for them to read over, hopefully to open their minds to the process of evolution before I stated talking about dichotomies and relatedness of unfamiliar organism.

As the hour started, I was excited to share my experiences and hope to spark an interest in other future scientists. Before I was introduced, I heard two students talking about me. One young man suggested I was a former student; another disagreed with him. Another girl waived to me and said that she remembered me. I introduced myself and started the presentation. Everything was going well, I had the students take the pre-survey then I explained a couple of results from my research project, and finally I distributed the articles. I had the students read them before the phylogeny presentation. Some students had questions during the presentation that seemed to be thought out and not just disagreement. I observed the students faces across the classroom. Some were engaged, others were disengaged, and I could not tell about the others. The dialogue at the end of the presentation consisted of students expressing that they were conflicted, some were interested, and others were silent.

In reflection of my visit, I realized that if I had a little bit more time with the students I would be able to gage how interested they were as well as I would be able to answer underlying questions about evolution. This visit proved to be very important for me because I was able to use the knowledge I gained working with BEACON and a couple of classroom management skills from my Teacher Education classes at MSU, to talk with a group of high school students about a subject that I had not had an opportunity to learn about in my high school classroom. Education in the present is comprised of so many more components than I realized before and it is essential to meet students where they are and provide them with the skills to reach the next level.

For more information about Lazarius’ work, you can contact him at mill2321 at msu dot edu.

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BEACON Researchers at Work: Outreach in the lion’s den – An evolutionary biologist at a creationist conference

Posted on February 9, 2015 by Danielle Whittaker

This week’s BEACON Researchers at Work blog post is by MSU graduate student Carina Baskett. 

CarinaImagine that you are a construction worker, and one day a group of people set up a tent outside the house you are building. In this tent, people give impassioned lectures about how the fundamental physics of construction are wrong, how there is no evidence that nails actually hold wooden beams together, and how there is a direct connection between houses and Hitler (he lived in a house). How would you feel? What would you do?

This was the dilemma that Michigan State University biologists faced when we learned that a conference about young-Earth creationism was going to be held on campus November 1st last year. 

Personally—and I want to emphasize that this is my opinion, not necessarily representative of the diversity of opinions among the students and faculty at MSU—I felt upset that an anti-science, anti-fact conference would be held in the same building where I watch weekly seminars about ecology and evolutionary biology, on the campus of an institution supposedly devoted to discovering fundamental truths about the world. But the facilities were reserved through a student organization, so there was nothing to be done about blocking the event from taking place.

What to do, then? My fellow grad student Dan Brickley and I were dead set on responding in some way to the Creation Summit. We organized a couple of meetings with other students and faculty to discuss how best to respond. One idea was to ignore it completely, advice that we seriously considered but decided not to follow (see several reasons here). There were some confrontational ideas, such as staging a protest of the existence of the moon to mock the idea that evolution is debatable. But after much discussion over list-servs and other email threads, on Facebook, and in meetings, a few of us decided that the best course of action would be to channel outrage into outreach.

Outreach is a broad goal. Specifically, we aimed to engage in conversations with conference attendees to (1) give scientists a friendly face and to share our passion about science and research, (2) learn about misconceptions about science and evolution, and (3) dispel some of those misconceptions. However, we also wanted to avoid confrontation, which some of us feared would alienate attendees, and avoid direct debate about the evidence for evolution, which would give the impression that evolution is scientifically debatable.

We had grand ideas about educational displays, but there was not enough time to marshal the resources or obtain a university permit to set up a table. So I made a flyer that pictured two evangelical scientists (Francis Collins and Jennifer Wiseman) and text about how many Christians see no conflict between faith and evolution. On the back, there was a list of resources related to compatibility of Christianity and science, and introductory resources about evolution. I don’t know anything about the philosophical or theological arguments for how faith and evolution are compatible, but I thought that conference attendees would be more likely to ponder that message than a message about how they were wrong and we were right about evolution.

After all this planning and anticipation, I was nervous when the day of the conference arrived, but it was a bit underwhelming. There were less than 100 attendees, a third or less under age 30, plus 25 scientists, many who came just to watch and learn what creationists were saying, and others who came to engage (handing out flyers and/or having conversations with attendees). Dan, a campus minister named Brenda Kronemeijer-Heyink, and I handed out about 80 flyers.

I talked with a couple of attendees, including one who seemed to be a conference organizer. Dan and I talked with him for about an hour. I felt that we were able to convey the message that scientists are humans with no hidden anti-religion agenda, a sense of excitement about science and evolution, and to educate (to some small degree) about how science works.

However, it was harder than I’d anticipated to walk the fine line between answering questions about science and getting drawn into an unproductive discussion of creationist talking points. We had brainstormed in advance about how to strategically avoid debates, such as saying, “That’s not my expertise, please see these resources,” but it wasn’t always possible to shut down that line of conversation.

We were successfully able to avoid confrontations (e.g., shouting). There was fear among some MSU scientists that attending the conference would inevitably cause dramatic conflict and lead to bad press, but I think we proved that civil outreach is entirely possible. Maybe in the Internet age we have forgotten that it’s much easier to avoid nastiness in face-to-face conversations than online. Despite the fact that we were there in opposition to the creationist message of the conference, and that we represented the scientific establishment that creationists view as oppressive, people were friendly and gracious.

I learned so much from this experience. I wanted to humanize scientists, but I had not realized that humanization is a two-sided coin. Just like me, creationists are doing their best to understand how this crazy world works and what our place in it is. They have come to radically different conclusions from me, and I do not agree with their methods that ignore reason and evidence, but we both share a concern about the future of our society. Now creationists are not faceless enemies to me, and I hope that the ones I talked with feel the same about scientists.

I also really enjoyed the communal aspect of the experience. It was exciting to talk and brainstorm with so many people about what to do in response to the conference. I was incredibly grateful and humbled to receive the advice and support of people who are much more experienced than me with evolution outreach and education, like Josh Rosenau, Bjørn Østman, Erik Hanschen, Emily Weigel, and Louise Mead.

At the end of the conference, I needed a shower to wash off the nervous sweat, and I have to say that it was a lot of effort for just a few good conversations with attendees. However, I would definitely do it again. There are very few avenues for civilized dialogue between evolutionary biologists and creationists, so we need to take advantage of these opportunities when they arise.

Speaking of which, if a creationist conference is coming to your town (University of Texas at Arlington, it’s coming your way at the end of April!), please get in touch. I’d be happy to share more about my experience.

For more information about Carina’s work, you can contact her at baskettc at msu dot edu.

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BEACON Researchers at Work: Evolving ways to switch genes on and off

Posted on February 2, 2015 by Danielle Whittaker

This week’s BEACON Researchers at Work blog post is by MSU graduate student Kurtulus Kok.

“In considering the Origin of Species, it is quite conceivable that a naturalist…might come to the conclusion that each species…had descended, like varieties, from other species. Nevertheless, such a conclusion, even if well founded, would be unsatisfactory, until it could be shown how the innumerable species inhabiting this world have been modified, so as to acquire that perfection of structure and coadaptation which most justly excites our admiration.” – Charles Darwin, Origin of Species, 1859 

KurtulusAt least since the appearance of Darwin’s seminal work, biologists have speculated on the sources of biological variation, and many current studies have pointed to the importance of variation in gene expression as a foundational principle. Exactly what changes at a molecular level is a topic of lively interest, with important ramifications for human health. My studies of the Hairy protein, a transcriptional repressor from the fruit fly Drosophila, have revealed new concepts on the consequence of “random” events affecting genomic interactions by transcription factors. These insights prompt us to reconsider mechanisms for the evolution of gene regulatory networks (GRNs).

Figure 1. Evolution of cis regulatory interactions through changes in DNA elements. (A) A transcriptional regulator normally regulating gene X may be recruited to an additional target gene Y by acquisition of a new binding site. (B) Interposing a new genetic link by such a modification can reconfigure a gene regulatory network (GRN).

Figure 1. Evolution of cis regulatory interactions through changes in DNA elements. (A) A transcriptional regulator normally regulating gene X may be recruited to an additional target gene Y by acquisition of a new binding site. (B) Interposing a new genetic link by such a modification can reconfigure a gene regulatory network (GRN).

One of the most important processes in biology is regulation of precise temporal and spatial use of genetic information to establish the physiological state of multicellular organisms. Proteins called transcription factors (TFs) bind to the genome and regulate the use of genetic information for embryonic development, cellular differentiation and cell fate in response to endogenous and exogenous signals. In other words, what cells are doing, how tissues work, and how organisms survive are dependent on transcriptional regulation. Therefore, understanding the mechanisms in transcription can inform and teach us about what happens when something goes wrong, which may result in diseases. TFs have to regulate gene expression at the right place at the right time (Figure 1A). In eukaryotes, this task is achieved by networks of very complex and combinatorial interactions between DNA binding proteins, co-regulators, and the matrix of DNA and histone proteins termed chromatin. Transcriptional networks represent an important evolutionary target for the development of morphological innovations. Molecular studies have demonstrated that the acquisition or loss of binding sites on DNA drive significant changes in gene expression that initiate critical evolutionary transitions (Figure 1B). Significantly, although relatively subtle changes have been linked to such important evolutionary innovations, it appears that sometimes gene expression is functionally conserved, even as there are major changes in the structure of transcription control regions. Thus, only some rearrangements of gene control elements alter output enough to meaningfully affect biological processes.

Figure 2. Patterning of the early Drosophila embryo is driven by spatially distinct expression patterns of transcriptional activators and repressors, including Hairy, which is expressed in transverse stripes.

Figure 2. Patterning of the early Drosophila embryo is driven by spatially distinct expression patterns of transcriptional activators and repressors, including Hairy, which is expressed in transverse stripes.

I am using an excellent model system, the fruit fly Drosophila melanogaster, for the study of transcriptional networks. Since it is subject to easy manipulations, a wide range of genetic and molecular approaches have been applied to characterize regulatory interactions for several decades. Understanding the fly regulatory circuitry will help reveal similar phenomena in other animal systems, since they use closely related genes in conserved genetic pathways. In the Drosophila embryo, localized transcriptional repressors provide essential patterning information that establishes the primary anterior-posterior and dorsal-ventral axes of the organism (Figure 2). The Hairy repressor, a founding member of the Hairy/Enhancer of Split (HES) transcription factors, plays essential and conserved roles in animal development, including segmental gene patterning in the early embryo and specification of neuronal differentiation. Disruption of HES signaling is a prominent aspect of leukemia, lung and prostate cancers. Thus, elucidation of molecular mechanisms of Hairy activity could shed light on a number of important gene circuits that are prominently represented in key developmental pathways. I carried out genome-wide analysis of dynamic transformations in gene expression, chromatin modifications and transcriptional machinery to get insight into direct molecular interactions of Hairy on genome systematically.

Figure 3. Chromatin marks for an “active” histone modification are lost in large blocks after expression of the Hairy transcriptional repressor. Only a small fraction of these Hairy-mediated events are associated with transcriptional regulation, however.

Figure 3. Chromatin marks for an “active” histone modification are lost in large blocks after expression of the Hairy transcriptional repressor. Only a small fraction of these Hairy-mediated events are associated with transcriptional regulation, however.

My work revealed that Hairy removes chromatin marks associated with activators in large blocks of chromatin, at hundreds of loci throughout the genome (Figure 3). Hairy may therefore work through a dynamic competition with activators, undoing their positive effects on the chromatin states that would be necessary for RNA polymerase to engage genes to transcribe them. At the genome-wide level, an unexpected aspect of Hairy activity was observed on chromatin that may provide a pervasive and accessible entry point for evolution of novel gene regulatory switches. Metazoan TFs usually interact with thousands of regions in the genome, but only small subsets of these interactions are associated with changes in gene expression. In general, the overall view from other studies is that the majority of the interactions between TFs and genome may be non-functional, and are not important for activity of GRNs. My work demonstrates that Hairy interacts dynamica

lly with many parts of the genome; some genes are impacted but most are not. This finding let us to propose the so-called “shotgun model” for this apparent off-target activity of TFs on chromatin modifications; many pellets are fired, but few are expected to reach the duck flying overhead. Yet the Hairy molecules that don’t “hit the target” still appear to be quite active, biochemically, inducing chromatin modifications that are similar to those seen on transcriptionally controlled loci. Hairy may be relatively nonselective about where it can attract chromatin modifying agents across the genome.

What is the significance of this chromatin modification associated with non-functional binding? For the organism, it is another instance of the extravagance of Nature –all of that chromatin modification for naught! As long as it is not particularly onerous metabolically or genetically, however, it may be the price paid for hitting the duck. “Futile cycling” by Hairy may however provide a unique mechanism for creation of new genetic switch elements; most DNA regulatory modules involve the combined action of transcriptional activators and repressors, thus these off-target sites may provide a path for evolution of novel transcriptional connections through addition of new TF binding sites. Where Hairy is busy acting as if it were shutting down a regulatory circuit by chromatin remodeling, small changes in DNA sequence that draw in existing activators may be sufficient to create a novel genetic switch, and a new connection between nodes in a genetic circuit. Thus modification of core elements of gene expression machinery may be an important answer to the question Darwin raised 150 years ago. How influential this particular mechanism may be will be the focus of future molecular work.

For more information about Kurtulus’ work, you can contact him at kokkurtu at msu dot edu. 

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BEACON Researchers at Work: Coach, Put me on the bench! A Novice’s Journey into Old-Fashioned Experimental Evolution

Posted on January 26, 2015 by Danielle Whittaker

This week’s BEACON Researchers at Work blog is by MSU graduate student Jay Bundy.

Jay “on the bench” performing a transfer during a competition experiment.

Jay “on the bench” performing a transfer during a competition experiment.

As a kid I played a lot of basketball. I loved almost everything about the game. But there was one thing I hated: spending time riding the pine. In sports, nothing interesting happens on the bench. The bench is where players who aren’t very good spend most of the game sitting, like a spectator, watching all the action. If they’re lucky, the coach will put them in for a few minutes when the game is out of hand or a star player really needs to take a quick break.

When I came to BEACON last year, I was a research technician while finishing my master’s degree in Anthropology. Perhaps the most profound decision I made was to start working in the lab of Dr. Richard Lenski on his E. coli long-term experimental evolution (LTEE) project. I had never worked in a microbiology lab before. To be honest, I didn’t really know anything about E. coli other than that they were bacteria. As an anthropologist, I studied the evolutionary basis of mating behavior in contemporary human populations. What was I going to learn from a system of experimental evolution using germs?

After reading some of the early microbial and long-term experimental evolution papers, I began to realize that microbes were an awesome way to study evolution! They have really fast generation times, they are super easy to maintain in the lab, and they can be frozen to be revived years later (yes, a real-life time machine). I decided that I wanted to get trained in the methods of the Lenski lab. So I uttered those words that as a former basketball player I never thought I’d say. “Dr. Lenski, will you please put me on the bench?”

Unlike basketball, in evolutionary biology all of the action happens on the bench. The bench is the name for a researcher’s work area in a wet lab. A wet lab is a space with the proper equipment, ventilation, and plumbing to allow researchers to work directly with biological materials, often suspended in liquid solutions (hence the name wet lab). If MTV cribs were to visit science labs instead of celebrity homes, it would be the bench instead of a king-size bed associated with the cliché “this is where the magic happens.” In the Lenski lab, that magic is all about competition experiments. The basic protocol for a three-day competition is as follows:

Day -2: A small population of E. coli from two competitors is put into a flask with bacteria food to promote growth.

Day -1: The E. coli are transferred to new flasks containing a very minimal broth with 25 mg per liter of glucose added (DM25). This is the environment of the actual competition.

Day 0: Both competitors are put together in a common competition flask containing DM25. This marks the beginning of the actual competition.

A sample from this flask is immediately spread onto a petri dish containing TA (i.e. tetrazolium arabinose) in gelatin-like form. All competitions take place between an Ara+ strain, which can utilize arabinose and produces pinkish/white colonies and an Ara– strain, which cannot utilize arabinose and produces red colonies. “Plating” on Day 0 allows us to take an initial count of each visually identifiable strain at the beginning of the competition to be compared with the relative counts of each strain at the end of the competition. 

E. coli “plated” on TA (tetrazolium arabinose) and ready for counting. The pinkish/white colonies grow on arabinose (Ara+) whereas the red ones (Ara-) cannot.

E. coli “plated” on TA (tetrazolium arabinose) and ready for counting. The pinkish/white colonies grow on arabinose (Ara+) whereas the red ones (Ara-) cannot.

Day 1: 24 hours later a small sample from the competition flask is transferred into a fresh flask containing DM25 and the plates from Day 0 are counted.

Day 2: 24 hours later, a small sample is transferred into a fresh flask containing DM25.

Day 3: A small sample from the final competition flask is plated just like Day 0. Comparing the counts between the final day and Day 0 determines the winner. 

Fortunately, after finishing my master’s thesis I was accepted by Dr. Lenski into the PhD program in Zoology at MSU. As a first-year PhD student I have been primarily taking classes. However, Dr. Lenski and I have come up with a research agenda that I recently used to apply for an National Science Foundation graduate research fellowship.

The goal of my research is to answer the question “How do the relative contributions of adaptation, history, and chance change over the course of long-term experimental evolution?”

Experimental design: X is 2,000 generations in E. coli and 20,000 updates in Avida. Following experimental evolution evolved values (i.e. ‘e’) are compared to ancestral values (i.e ‘a’). Yellow=initial laboratory environment, Blue=experimental environment. b. Hypothetical comparison for ancestral vs. evolved values when evolution is primarily by adaptation, history, and chance.

Experimental design: X is 2,000 generations in E. coli and 20,000 updates in Avida. Following experimental evolution evolved values (i.e. ‘e’) are compared to ancestral values (i.e ‘a’). Yellow=initial laboratory environment, Blue=experimental environment. b. Hypothetical comparison for ancestral vs. evolved values when evolution is primarily by adaptation, history, and chance.

To answer my research question I will be using the competition experiments described above. The long-term evolution experiment was started with a single genotype of E. coli strain B cloned to found 12 populations. These populations have been evolving in DM25 for over 60,000 generations since February of 1988. I will take a single genotype (isolate) from all 12 lines at 2,000, 10,000, and 50,000 generations into the long-term evolution experiment. I will then establish three replicate populations from each line (using clones of the isolate). I will then evolve these 108 populations (12 lines x 3 replicates x 3 time points) for 1,000 generations in maltose. I will be replacing the glucose in DM25 with maltose, an alternative sugar source. Substituting the maltose for glucose will allow me to answer my research question using experimental evolution in a novel environment for these bacteria. Following this initial period of evolution I will compete all 108 populations against their ancestors. Similarities across all 12 replicate lines (such as increased fitness in maltose) reflect the influence of adaptation because all populations are attaining similar results regardless of initial differences between them following 2,000, 10,000, or 50,000 generations of unique history in each lineage. Differences between the 12 replicate populations (such as differences in evolved cell size) reflect the influence of each population’s unique history, since all lineages were originally derived from a single genotype and hav

e evolved in the same environment. Differences between replicate populations (started from clones) within each lineage, reflect the influence of chance events, since differences between replicates will be caused by mutation and genetic drift events unique to each lineage that occur during the experiment (see figure above). Estimating the relative contributions of adaptation, chance, and history at 2,000, 10,000, and 50,000 generations will allow me to determine how the relative effects change over evolutionary time. I will also be performing a similar experiment in Avida, a digital evolution platform maintained by MSU’s digital evolution lab. I am truly honored to be at BEACON, where this type of research is possible. Stay tuned for more.

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

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BEACON Researchers at Work: How fast can hyenas learn?

Posted on January 19, 2015 by Danielle Whittaker

This week’s BEACON Researchers at Work blog post is by MSU postdoc Agathe Laurence.

“If monkeys could reach the point of being bored, they could turn into human beings,” said Goethe. More than a philosophical essay about boredom, that comparison between humans and monkeys is also a good illustration of what we now know about apes and monkeys’ cognitive abilities. In fact, as primates, we are a species that can claim one of the biggest relative brain size among mammals (Jerrison et al, 1973). However, you would be surprised by what some birds can do, or even honeybees (Komischke et al, 2002). Of course it all depends on what kind of cognitive tests you are considering. But, cognition can be divided in two categories: physical and social cognition. While the first helps us deal with inanimate objects, we are able to understand our conspecifics intentional actions, perception, and knowledge, thanks to the latest (Herrmann et al, 2008). Obviously, social cognition is most useful when living in a big enough society, which means frequent encounters with conspecifics. As a matter of fact, social complexity could be what drove individuals to have bigger and bigger brains throughout evolution (Byrne & Whitten, 1988). This indicates that living in a complex society involves the need to understand its social rules, as well as to predict and/or understand the intentions of your conspecifics, especially if they’re higher ranking.

Figure 1

Figure 1: Two of my study subjects resting in the Maasai Mara, Kenya

Even though I used to work with non-human primates, and then birds, it is the spotted hyenas studied by Kay Holekamp and her graduate students that have brought me from France to Michigan State University. Throughout 26 years of research about their anatomy, ecology, physiology and behavior, Holekamp and her collaborators have shown the complexity of their social groups (Holekamp et al, 2007). First of all, spotted hyenas (Crocuta crocuta) are the subject of many myths, so let’s reestablish some truths about them: they are not hermaphrodites, 80% of their food is what they hunt for themselves, and they are not ugly (although that might be a personal bias, but see Figure 1). Regarding social characteristics, they actually exhibit a lot of similarities to primate societies, particularly old-world monkeys (e.g. baboons or macaques). A group of hyenas, called clan, can contain up to 90 individuals, each of which is able to recognize every member. There is strict linear hierarchy within the group, where females are dominant, bigger, and more aggressive than males. Overall, they meet the criteria to fit the social intelligence hypothesis. Like monkeys, hyenas have a high level of social cognition: the acquisition process of one’s social rank happens through learning. Only then they are able to identify every conspecific’s social rank, predict the issue of an interaction between two other hyenas, and join other hyenas in an aggressive coalition against a third one.

On the other hand, we know very little regarding their physical cognition, and that is the focus of my work with wild spotted hyenas in the Maasai Mara, Kenya. The social intelligence hypothesis predicts a high level of physical cognition along with social cognition. The key is to choose a task that can be done by several species, so that a wide comparison between species is possible. Let’s forget about IQ tests right away, only a chimpanzee would give the pen back when he’s done. Behavioral flexibility, or the ability to adapt one’s behavior to solve a problem, is a good measure of general intelligence and can be adapted through various tasks.

The hard part was to choose a task that hyena could solve without the use of hands, as most of the experiments have been conducted on primates. Moreover, wild hyenas are very cautious toward man-made objects, hence I chose a task that could be done in several steps, to eliminate any bias of novelty on their ability to solve the task. So, to test their ability to display flexible behavior, I’m using a reversal learning test where the hyenas have to pull ropes to get access to meat as a reward (Figures 2 & 3). They first have to learn to discriminate between two colors (black versus yellow), one associated with the reward, the other one associated with the absence of that reward (Figure 4). Once they have learn that, the rewarded and the non-rewarded colors are reversed and they have to suppress one behavior in favor of another to get the meat.

Figure 2: That young subadult is pulling the rope so that the tray containing the meat slides to the edge of the device.

Figure 2: That young subadult is pulling the rope so that the tray containing the meat slides to the edge of the device.

Figure 3: After pulling the rope, the same hyena can get the meat and thus associate the color of the rope (here, the black one) with a positive reinforcement (the meat).

Figure 3: After pulling the rope, the same hyena can get the meat and thus associate the color of the rope (here, the black one) with a positive reinforcement (the meat).

Figure 4: After getting the reward on the "black side", this hyena is trying to get the meat on the "yellow side", which is blocked and the meat will remain inaccessible. After several trial, that hyena will learn to pull only the black rope.

Figure 4: After getting the reward on the “black side”, this hyena is trying to get the meat on the “yellow side”, which is blocked and the meat will remain inaccessible. After several trial, that hyena will learn to pull only the black rope.

Conducting an experiment on wild hyenas takes time, especially when I have to find them across their wide territory and to get them to interact with the device. After a very long habituation phase, I have now started the learning phase, trusting that my beloved subjects will learn it quick (because I believe that they are very smart). Then, the best part begins: reversal learning!

 

Picnic Trees, SerenaI went to Rennes 1 University in France, where I graduated with a Master’s degree in ethology studying hand preference in non-humans primates and then received a PhD studying the impact of chronic stress on behavioral development in birds. Afterwards I wished to study more specifically behaviors in a social mammal. I won a 2-year grant awarded by the Fyssen foundation (website) to study cognition in wild spotted hyenas at MSU.

References

  • Byrne RW, Whiten A (1988): Machiavellian Intelligence..Oxford, Clarendon Press.
  • Jerison HJ (1973): Evolution of the Brain and Intelligence. London, Academic Press.
  • Hermann et al (2007): Humans have evolved specialized skills for social cognition: the cultural intelligence hypothesis. Science (317), 1360-1365.
  • Holekamp et al (2007): Social intelligence in the spotted hyena (Crocuta crocuta). Phil. Trans. R. Soc. B (362), 523-538.
  • Komischke et al (2002): Successive olfactory reversal earning in honeybees. Learning & Memory (9), 122–129

For more information about Agathe’s work, you can contact her at ag dot laurence at gmail dot com.

 

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BEACON Researchers at Work: Seeing double? Genome duplication and the teleost fish retina

Posted on January 12, 2015 by Danielle Whittaker

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

Figure 1. The cells and layers of the retina

Figure 1. The cells and layers of the retina

The sense of vision is mediated by a specialized projection of the central nervous system located in the back of the eye, the retina. The retina is a highly conserved structure consisting of cellular and synaptic layers that establish physiological pathways capable of converting light stimulus from our environment into a perceivable image (figure 1). This is possible because of the specialized circuits that detect different aspects of vision such as color, edges, and movement. Light first stimulates photoreceptors at the back of the retina, which propagate this information to innernerons that modulate this signal before the retinal ganglion cells send this information to the brain.

Our lab is interested in how this structure has evolved, and we operate with a focus on the visual system of teleost fish. The visual system observed in teleost fish is interesting because of its ability to regenerate damaged neurons, maintain constant neurogenesis throughout their lifespan, detect a wide range of light, and adapt to novel visual environments, and they contain an increased number of retinal cell types. We hypothesize that the specialization and unique traits that are observed in the teleost visual system was influenced by the Teleost Genome Duplication (TGD). This was a large scale genetic rearrangement event that took place roughly 350 million years ago, providing the the teleost lineage with a duplicated genome that resulted in an explosion of diversity.

Figure 2. Spotted Gar retina with antibody to short wavelength cone opsin. A clear gradient was observed in cellular density between dorsal and ventral regions of the retina. Density between the two regions was significant (p= 2.07x10-41).

Figure 2. Spotted Gar retina with antibody to short wavelength cone opsin. A clear gradient was observed in cellular density between dorsal and ventral regions of the retina. Density between the two regions was significant (p= 2.07×10-41).

As a first step to understanding the role of TGD on the evolution of the visual system, we have characterized a basal model, the spotted gar, which diverged in lineage prior to the TGD. This gave us the unique opportunity to study a retina that evolved under similar environmental pressures, but with only a single genome. Consistent with our hypothesis, we found the retina of the spotted gar to have conserved structure and cell types to that of the teleost, but some key differences were observed. The teleost retina is well known to have a highly ordered photoreceptor mosaic. The retina of the spotted gar was organized, but not to the level and consistency that was observed in teleost. The spotted gar retina also contains gradients of cellular density throughout the eye; a trait seen in mammals but not in teleost fish (figure 2). The spotted gar retina also contained thinner cellular layers, supporting the hypothesis that teleost retinas contain more retinal cell types overall. Through this characterization, we have been able to identify and label major cell popluations in the retina, as well as many different individual cell populations including cones and amacrine cells (figure 3). This will be beneficial to the our project going forward, as well as future research involving the spotted gar retina.

Figure 3. Spotted Gar retina section stained with Recoverin (photoreceptors), PNA (cone pedicles), and DAPI (nuclear stain). Retina structure is conserved compared to zebrafish and mammals. Scale bar is 20 um.

Figure 3. Spotted Gar retina section stained with Recoverin (photoreceptors), PNA (cone pedicles), and DAPI (nuclear stain). Retina structure is conserved compared to zebrafish and mammals. Scale bar is 20 um.

Next we hope to assay the function of paralogs in the zebrafish retina. The zebrafish is a member of the teleost lineage, and is a common model for eye research. When gene duplication occurs, there are three possible outcomes. Neofunctionalization occurs when the duplicated gene develops a completely novel function(s). Pseudogenization occurs when the gene becomes obsolete and its expression is lost. Subfunctionalization occurs where the two genes each retain a “subset” of the original gene function and are possibly relegated to expression in a specific tissue or cell type.

We will initially target two cell adhesion molecule families, the sidekick (SDK) and Down syndrome cell adhesion molecule (DSCAM) families, both essential in the organization of the retina. These are ideal candidates because the zebrafish genome contains twice as many copies as the spotted gar (and mouse). We will use genomic informatics and molecular approaches to assay whether both copies of the duplicated genes have been retained in teleost retina.

We will begin by performing in situ hybridization assays on the paralogs of our target genes. This will be done across development for the zebrafish to determine whether expression patterns have diverged. We will utilize developmental assays performed with the use of two different gene knockdown techniques. Morpholino oligonucleotides are small miRNA sequences that target specific mRNA sequences and reduce translation of these transcripts. The CRISPR/Cas9 technique was only recently discovered, but provides a unique way to target specific sequences in the genome directly. This will allow us to assay if the respective function of each gene has diverged compared to its paralog and therefore test if neofunctionalization has occurred. We predict the genome duplication and associated increase in genetic material could have enhanced the potential of the teleost lineage to develop novel visual circuitry. Future plans include adapting a place preference test in order to look at visual acuity in the mutant fish we develop.

Joshua SukeenaMy path to a PhD program has not been traditional. I began at The College of Idaho in pursuit of a degree in history and education. However, spending time in a cognitive research lab drastically changed my outlook for my future. This experience inspired me, but I knew that my biggest interests were at the molecular level; specifically in the field of genetics. I joined the University of Idaho in the lab of Dr. Peter Fuerst in the fall of 2013. Having grown up in Idaho, I have become aware of the problems facing scientific education. It is a state that ranks near the bottom of the country in number of students that go on to get a technical degree, college degree, or post-graduation degree. I am determined to make sure these statistics do not persist. I know that a doctoral degree will not only lead to an opportunity to conduct research and contribute the scientific community as a whole, but also put me in a position
to make a significant impact on the way my community looks at science and education as tools for improvement. Idaho has abundant environmental resources and opportunity for young scientists. I have a dream of establishing an educational program which allows children to travel and learn about different disciplines of science all over our state from geology to wildlife science and microbiology. I believe in a future where scientific inquiry and research understanding is a commonplace in our educational system; allowing it to persist and lead to a more stable future.

 For more information about Joshua’s work, you can contact him at jmsukeena at gmail dot com.

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BEACON Researchers at Work: Of Milk and Microbes

Posted on January 5, 2015 by Danielle Whittaker

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

JanetMilk and microbes, what do these two things have to do with each other? For many years, milk was thought to be sterile and any bacteria present were considered to be pathogenic or due to “contamination” of milk. It is true that certain bacteria, like Salmonella, E. coli and Listeria, in unpasteurized milk can be cause for concern. However, recent evidence has clearly demonstrated that “healthy” milk contains diverse bacterial communities (Figures 1 and 2 below)1,2. And what’s even more intriguing is the thought that certain bacteria in milk are actually good for the newborn. These bacterial communities in milk likely serve important roles in maturation of the nursing newborn’s gastrointestinal (GI) tract and immune system.3 Hmmm… bacteria in a food being consumed and conferring a health benefit to the host. Sound familiar? Sounds like a probiotic to me. This concept may or may not surprise you. In fact, you can now most likely find infant formulas supplemented with probiotics on the shelves of your local grocery store. If you are curious and want to read more about this, check out the recent review by McGuire and McGuire (2014)4 that explores the idea that milk is actually Mother Nature’s prototypical probiotic food.

Figure 1: Example of immune and bacterial cells found in “healthy” human milk

Figure 1: Example of immune and bacterial cells found in “healthy” human milk

Here is another interesting thought… milk has not only evolved to contain nutrients to “meet the diverse reproductive and environmental demands of different species” but to also contain bacteria that increase the chance of survival and development of the nursing young in diverse environments.

So are milk bacterial communities similar across different mammals? Are milk bacterial communities similar across different human populations? Does maternal diet influence milk bacterial communities? Do host genetics play a role in structuring the milk bacterial communities? What components in milk influence the structure of milk bacterial communities? How has the evolution of those components impacted the microbial diversity found in milk? What types of bacteria-bacteria interactions may be at play in structuring the bacterial communities? I could go on for a long time adding to this list. I’m fascinated with how all these factors are intertwined and how together they influence maternal and newborn health. 

Figure 2: Community composition of 15 abundant bacterial genera in milk samples, from Hunt et al 2011

Figure 2: Community composition of 15 abundant bacterial genera in milk samples, from Hunt et al 2011

Right now, we don’t have the answers to many of these questions. This is one of the reasons I am pursuing a PhD in Bioinformatics and Computational Biology at the University of Idaho. I work in the laboratory of Dr. Mark McGuire (Animal & Veterinary Sciences Dept, UI) and in close collaboration with Dr. Shelley McGuire (School of Biological Sciences, WSU). The McGuire labs have been engaged in the study and hands-on collection, extraction, and analysis of various components of interest from human and cow milk (e.g., lipid, protein, sugars, host RNA) for many years. We are now venturing into the computational arena of processing and interpreting massive amounts of sequencing data from bacterial DNA.

I work on both the “wet lab bench” side and the computational side of things in the laboratory. Although most of my experience prior to starting the PhD program was at the lab bench, my current focus is analyzing 16S rRNA sequence data from a variety of samples (human and cow milk, human fecal, dairy cow rumen and fecal, and newt skin swabs). I am trying to understand some of the complexities in the dynamics in the microbial communities and how other factors (e.g. diet and/or spatial/geographical location) may influence the structure of these communities.

For the human milk samples, we are currently working to address the question of how diet influences the milk microbiome in much the same way that others have looked at how diet influences the gastrointestinal (GI) microbiota. Initially it’s just about characterization of what bacteria populations are present over the course of lactation at the different taxonomic levels. The next step is to see if there is any structure to the variation of the bacterial communities. Can a large part of the variation in the milk bacterial communities be explained by maternal diet? By time postpartum? By some other nutrient or component in human milk? It’s important to understand the composition of the bacterial communities that are present as it has been suggested that the milk microbiota may be directly involved in colonization of the newborn GI tract and the GI microbial composition has potential short- and long-term effects on the health of that individual.

One of the reasons that I’m a part of BEACON is because I’d also like to try and investigate the evolutionary forces that potentially influence milk composition and the microbial communities in milk. And that’s where you, the reader, might be able to provide insight or suggestions. Now that you know some of what we do, what thoughts or ideas have come to mind as you have read this in how we might approach some of the questions above? Let me know what you think. I’d be interested in having a conversation with you. 

1Hunt K, Foster J, Forney L, Schütte U, Beck D, Abdo Z, et al. (2011). Characterization of the diversity and temporal stability of bacterial communities in human milk. PloS ONE 6:e21313.

2Quigley L, O’Sullivan O, Stanton C, Beresford TP, Ross RP, Fitzgerald GF, Cotter PD (2013) The complex microbiota of raw milk. FEMS Microbiol Rev 37:664-698.

3Fernández L, Langa S, Martín V, Maldonado A, Jiménez E, Martín R, Rodríguez JM (2013) The human milk microbiota: Origin and potential roles in health and disease. Pharm Res 69:1-10.

4McGuire MK, McGuire MA (2015) Human milk: Mother nature’s prototypical probiotic food? Adv Nutr (in press).

For more information about Janet’s work, you can contact her at janetw at uidaho dot edu.

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Tips for Thriving in Your Research Career

Posted on December 22, 2014 by Danielle Whittaker

This blog post is written by University Texas at Austin graduate student Rayna Harris, and was inspired by the “NIH and You: How to Survive and Thrive in Your Research Career” Symposium at the 2014 Society for Neuroscience Annual Meeting in Washington D.C. on Saturday, November 15, 2014.

NIH Panel Members included:

  • Stephen J. Korn, Director of the Office of Training, Career Development, and Workforce Diversity
  • Nancy L. Desmond, Office Director and Associate Director for Research Training and Career Development
  • Michelle Jones-London, Director of Diversity Training and Workforce Development
  • Alan L. Williard, Acting Deputy Director of NINDS

#1. When it comes to choosing mentors, be promiscuous!

Successful experimenting! L-R: Manisha Sinha, Hilary Katz, Dalia Salloum. Photo credit: Rayna Harris

Successful experimenting! L-R: Manisha Sinha, Hilary Katz, Dalia Salloum. Photo credit: Rayna Harris

Choosing the right mentor is one of the most critical decisions grad students and post-doctoral fellows must make (see # 2). However, don’t forget the importance of having multiple mentors during each stage of your research career.

Other mentors will not only nurture and advise you, but they can also fill the voids in your relationship with your primary mentor. For instance, if your principal investigator (PI) is not a statistician, seek the advice of one who is to verify that your results are statistically sound. Or, if your mentor is a single male and you are a soon to be mother, seek the guidance of a female PI with children to discuss work-family balance.

#2. But seriously, choose the right mentor for you

It is important to join a lab where you will be supported in your training and your career; receiving good mentorship support is pivotal for success in your career. When choosing a lab, do your homework first and find out where former trainees have gone. Did they continue down their chosen career path? Do they still have a good relationship with the PI? These are important questions you need to have the answers to.

A good mentor should have the experience and the connections to get you were you want to be!

Altmetric score for Barres 2013 Neuron article.

Altmetric score for Barres 2013 Neuron article.

Once you join a lab, develop a relationship with your mentor that is built on good communication. How, when, and how often you communicate will be different for each mentor-mentee relationship, so find a strategy that works for both of you. Don’t be afraid to talk to your mentor about your goals! Work together to create an individual development plan and revisit it periodically.

For more on this subject, the following articles are highly recommended:

  1. Barres, Ben A. (2013) How to pick a graduate advisor. Neuron 80: 275-9.
  2. Wood, Charles (2012) When lab leaders take too much control. Nature 491: 785-786
  3. Raman, Indira M (2014) How to Be a Graduate Advisee. Neuron 81: 9-11.

#3. Be a good advisee

It would not be fair to demand quality from your mentor without returning the favor. By being a good advisee, you can actually help your mentor be a good mentor. Be proactive, and ask for your mentor’s time or advice when you need it. This way, both of you can shine!

If you ever find yourself in the unfortunate situation of being in a toxic relationship, swallow your pride and ask for outside help. Talk to your graduate program director, your department chair, or one of your other mentors. These people can either help you work it out with your mentor or can help you find a new lab.

Be proactive and talk to your mentors. Downloaded from http://www.phdcomics.com/comics/archive.php?comicid=1025

Be proactive and talk to your mentors. Downloaded from http://www.phdcomics.com/comics/archive.php?comicid=1025

 

#4. Have plans and follow through with them.

I recall The Serial Mentor saying that the number one common mistake grad students make is proposing an overly ambitious thesis. Don’t be one of those folks! Propose a doable project. Then do it. Persist even when parts of it fail, and do not take rejection personally.

Stay focused and learn to balance the time and effort you spend on your projects with classes, grant writing (see #8), reading, publishing, exercising, relaxing, and the plethora of other responsibilities you may have.

If you are a post-doctoral fellow, your focus should be to develop a research program that you can take with you! Discuss this early on with your mentor, and don’t join if you suspect that you won’t be able to.

Of course, a healthy dose of ambition is fantastic. Ambition is probably one of the most common shared traits among people who are “the first” to do something. The trick is, though, to not be so overly ambitious that you have little to present in your next job talk or award acceptance speech.

#5. Learn to cope with failure and develop grit

In addition to technical training, accumulate transferable skills throughout your career. These skills will help you succeed no matter what you choose to pursue and include (but are not limited to) critical thinking, communication, leadership, reasoning, grit, and perseverance.

Empowerment, resiliency, and grit are essential characteristics in a good researcher. Learn to cope with failure and you will have much more success in life. Take control of your academic environment rather than stumbling along after failure. Your mentors are there to help you up when you fall, but you must empower yourself.

#6. “You’ve got to know when to hold ’em, know when to fold ’em”

Don’t let failure stress you out! Image from: http://goo.gl/XOrfHq

Don’t let failure stress you out! Image from: http://goo.gl/XOrfHq

This quote is actually from a song about gambling by Kenny Rogers, but I think the advice really applies publishing goals and whether or not you really want to stay on the tenure track.

Set your aims high. If you aim to publish in top tier journals, then will you have a good chance of publishing in journals ranging from good to the very best. However, don’t spend 6 years trying to get one project into the
best journal and then never publish. Ask yourself if publishing small bits early in a solid journal is a better career move or if you really want to hold out for that chance to revolutionize the field with one great piece.

Remember, industry is not easier; it’s just different.

Many of my peers struggle with deciding whether or not to stay in academia. The most common advice I’ve heard is to stick with research as long as you passionately love it and to not quit until you have to. Every minute you spend in academia is useful, so don’t think that you’re wasting your time. If you are considering leaving academia, peruse opportunities as they present themselves and seize the right one when it comes along.

#7. Network whenever possible and don’t burn bridges.

Networking at conferences is a must #SfN14

Networking at conferences is a must #SfN14

When you go to meetings, don’t just socialize with people from home. Schedule lunch or coffee with your letter writers to keep them updated or with potential employers to get to know them better. Meet new people at posters or socials or during interactive sessions.

Along those lines, try to keep positive relationships with all your colleagues and don’t burn bridges. Our communities are small, so try to be nice to even to your bad colleagues. You never know you will need something from them or someone they know.

#8. Talk to your program officer before and after applying for grants

I’ve saved the final tip for the topic of funding. This could probably be a 1000 word blog all by itself, but I’ll keep it short. Visit the National Institute for Allergy and Infectious Disease (NIAID) for more online resources.

Remember, your program officer (PO) is there to help you get funding! I’m sure you have heard that you should call or email them before submitting a grant, but what’s the best approach? The POs say that the best way is to send an email with your Specific Aims page and your Biosketch attached.

Also, contact your PO to discuss interpreting the summary statement of a grant that is not funded. This is especially useful if you have a hard time understanding the essence of the comments or if the reviews are conflicting.

Applying for grants as a grad student or post doc is a great idea because it gives you experience with the whole process and will help you thrive in your research career. However, you don’t need a grant at this stage to get a faculty position. If you have heard this, know that it is a myth! According toDr. Stephen J. Korn only 15% of new assistant professors had a K99 award.

Final thoughts

There is a pretty good chance you have heard most of this advice before. My mentors (yes I have multiple) and other great scientists have said this over and over again. But, sometimes it’s good to hear things more than once

I hope you found pieces of advice contained herein useful and worth sharing with others. Best wishes in your journey as a research scientist!

E.O. Wilson’s advice for thriving in sciencing

E.O. Wilson’s advice for thriving in sciencing

 

Disclaimer

I have a great mentor and a good relationship with him. But, I strive for perfection and am always looking for advice on how to do things better.

One of my live tweets from #SfN14

One of my live tweets from #SfN14

 

Acknowledgments

Many thanks to @karinaalbab and @maruca221 for comments and suggestions for this blog, the organizers of #SfN14 for providing a great forum for discussion, and to @PLOSNeuro and @emilyjanedennis for inspiring me to blog and tweet at #SfN14.

This story was originally published here on Medium and here on PLOS as part of the PLOS Neuroscience Community.

For more information, you can contact Rayna at rayna.harris at utexas dot edu.

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

Posted on December 15, 2014 by Danielle Whittaker

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

Posted on December 8, 2014 by Danielle Whittaker

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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