BEACON Researchers at Work: Pacific Land Snail Evolution

This week’s BEACON Researchers at Work blog post is by University of Idaho postdoc Andrew Kraemer. 

Andrew Kraemer“When was the last time this island was searched for snails?” I asked as I picked my way through the loose cobble of lava rock.

“Over 100 years,” Christine replied. “The last time a malacologist searched Santa Fé was during the California Academy of Sciences Galápagos Expedition of 1905-1906.”

A 100-year gap between censuses is only one of the reasons I find myself looking for Galápagos snails (genus Naesiotus) during my postdoc with Dr. Christine Parent. Islands like Santa Fé, it turns out, are not particularly hospitable to snails. These islands are hot, dry, and often go through rapid shifts in climate. As a result, any snails found may be recent colonists from older, larger islands. Similarly, species found on the young volcanoes of the archipelago are also colonists. By comparing these young colonists to species found on older islands, we hope to learn more about the colonization process.

After a long ascent, we finally climb onto the heap of boulders that constitute one of Santa Fé’s small peaks. While much of the island is hot and dry, clouds passing over sometimes drift low enough to bump up against these peaks. As a result, snails are able to eke out a living in the moist grass clumps that grow at the highest points of the island. On our trip to Santa Fé, we find 4 adults and a handful of juvenile snails of Naesiotus cucullinus. A small and tenuous population, but a live population nonetheless.

Through this research I am lucky to explore corners of Galápagos that few are given access to. As a result, we sometimes rediscover species long presumed extinct (e.g. Naesiotus rabidensis) or even find snails that do not correspond to any species previously described.

Pacific land snailOur research requires us to seek out these snails wherever they live, whether that is on a tiny island, the rim of a volcano, or at a construction site. We use a portable spectrometer to measure shell coloration in the field and collect empty shells to measure shell shape back in the lab. Previous research on these species has indicated that shell size and shape are tightly linked to local environment, and our recent work suggests that bird predators may direct the evolution of shell coloration. As for the colonist species, we are finding phenotypic similarities among species found on young volcanoes and among those found on small, relatively inhospitable islands. This could be due to rapid evolution after colonization or a filtering process that determines which species become successful colonists in the first place. We are currently constructing a new phylogeny of all Galápagos Naesiotus snails, living and extinct, that should indicate which scenario is most likely.

Unfortunately, extinction is all too common in Galápagos and other Pacific islands. In particular, land snails like Naesiotus have been hit hard by many recent threats, including rats, invasive snails, habitat destruction, and even direct collection by humans. A reasonable question, then, is which species are we losing? Furthermore, why those species and not others? Another project I am working on will attempt to answer those questions for two snail groups (Galápagos Naesiotus snails and the tree snails of Hawaii), both of which have endured massive declines over the last 100 years. For this project I will visit several museums around the U.S. that have extensive snail shell collections. Using these collections and the records associated with them I will characterize distribution, shell size, shell shape, and shell coloration for each species. At the same time, my host lab (Parent) and a collaborator in Hawaii (the Holland Lab) will be expanding the phylogenies of each snail group using next generation and ancient DNA sequencing techniques. Together, we will find out if the catastrophic declines within these two major radiations are randomly distributed, or if the declines are funneling away the ecological and morphological diversity these groups are known for. The former result would be disturbing, but the latter result would prove ruinous for the evolutionary heritage of these two groups.

The voyage of the Beagle and Darwin’s theory of natural selection ensured Galápagos would forever be a mecca for biologists, the truly astounding species make it a place worth studying, and the shocking recent declines of some of its fauna adds urgency to this work. My hope is that our research will contribute to the important conservation efforts of other scientists in the Pacific.

For more information about Andy’s work, please see his website or email him at: akraemer at uidaho dot edu.

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BEACON Researchers at Work: Providing computational methods for biological research

This week’s BEACON Researchers at Work blog post is by University of Texas at Austin research scientist Dennis Wylie.

Chimera of goat and lionI’ve always been intrigued by the combination of seemingly incongruous things. As a child I loved stories about strange chimerical creatures composed of one part this animal, two parts that, and so on — not just for the fantastic nature of the imagery but also because I couldn’t stop asking myself questions like “how does the goat head feel when the lion head eats a goat?” As an adult I’ve therefore found it particularly interesting to be working in the field of computational biology: the goals and methods of one discipline often seem bizarre from the perspective of another, but sometimes the contrast helps to bring out something new and unexpected.

Since January I’ve worked at the Center for Computational Biology and Bioinformatics (CCBB) at the University of Texas as part of the bioinformatics consulting group. We work with faculty members across several departments pursuing a large variety of different projects which in one way or another involve large-scale data sets and complex computational analyses, largely (though certainly not exclusively) based around next-generation sequencing (NGS). In the few months since I have joined the group, I have worked on projects applying computational approaches for NGS variant calling, methylation profiling via bisulfite sequencing, RNA-Seq differential expression analysis, RIP-Seq analysis, and metagenomics, among other methods.


Probabilities of proneural vs. mesenchymal subtype (blue indicates higher probability of proneural, black of mesenchymal) predicted by toy SVM model designed to demonstrate overfitting and trained on RNA expression levels of two genes as measured by sequencing (GSE57872). Hollow inverted triangles are specimens which were assigned mesenchymal subtype according to Patel et al 2014 (Science 344: 1396-1401), while filled-in triangles represent specimens assigned to proneural subtype. Contours represent probability levels approximately equal to 50% or 100%; in each of the primarily mesenchymal and primarily proneural regions of the plot, a few samples of the opposite subtype create a “hole” region in which the prediction is flipped.

The project with which I have been most heavily involved here at UT is the ongoing study of the proteasome in Andreas Matouschek’s lab. While it has been well established for some time that the attachment of polyubiquitin chains to proteins targets them for degradation by the proteasome, some proteins are degraded with much less efficiency than others even when polyubiquitinated. Matouschek’s group has shown that the breakdown of polyubiquitinated proteins is accelerated by the presence of an unstructured region which can serve as an initiation site for the proteasome to begin the degradation process. Moreover, they have demonstrated through experiments varying the length and complexity of peptide tail sequences appended to fluorescent proteins that there are observable patterns in the types of peptides which serve as more or less effective initiation sites. The rich complexity of the space of relevant peptide structural features, combined with the increasingly large data sets the Matouschek lab is now generating, makes this a promising meeting ground for biophysical, computational, and statistical methodologies. In this context I am currently providing consultation applying algorithmic pattern recognition methods to help tease out in more detail which features determine proteasomal degradation efficiency.

Dennis WylieAt the CCBB I also have the opportunity to teach the methods I help apply in various research projects to students, postdocs, and anyone else who might be interested. At the end of every May we offer a slate of courses composing our “Summer School for Big Data in Biology,” for which this year I put together a course in machine learning methods for gene expression analysis (based both on my experience at UT and my prior work as a bioinformatician in industry developing molecular diagnostic tests). In planning the syllabus, assembling examples, teaching the techniques, and discussing the many potential applications with students, I had plenty of time to contemplate the interplay of ideas (and, more prosaically, of different jargons) from biology, mathematics, computer science, and many other fields. For example, the idea of model overfitting (e.g., see contour plot of overfit SVM classification model), whether done by human or by machine, lurks in the background of pretty much every scientific field (though not always known by that name).

It is my hope that in providing both research consultation and educational services at the CCBB we are assisting in the ongoing synthesis of scientific theory such that future generations will more easily appreciate the harmonies between disciplines. Combinations that today seem bizarre chimeras may one day be appreciated as natural fauna inhabiting the scientific landscape.

For more information about Dennis’ work, you can contact him at denniswylie at austin dot utexas dot edu.

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Misnomers and Mixed Intentions: Communicating Science is Hard

Reposted from the Teaching Evolution in Action blog

By Chris Symons

Chris SymonsThe route of information between the raw data of scientific experimentation to the public’s understanding is convoluted. The murky water of scientific communication is problematic at best, if anyone ever hopes to get the public united behind a scientific issue, they will need to learn to navigate these problems with science communication they can expect to encounter.

There are a couple key factors, notably term misuse and biased/sensational media, to be blamed for many communication misconceptions.

Term misuse causes inaccurate understandings of definitions. For example, pop culture and video games are sources of evolution being used incorrectly. In the Pokémon series the ‘evolution’ that transpires in the game is actually a metamorphosis, and while this mix up is certainly innocent enough, it is term misuse that reinforces evolution as being a deliberate, linear, immediate process. In other words, that two chimpanzees suddenly birthed a human child, for example. This is a common misunderstanding, that evolution occurs in a single glorious moment and a new species is born. Evolution is a process that occurs over generations, with no specific direction, resulting in very gradual changes to the gene pool.

Pictured: Not evolution

Another word that is under constant contention is ‘theory’, which suffers from different use by scientists, as opposed to the general public. People attach the uncertainty that the common understanding of ‘theory’ has, to the way scientists use it, and this is highly confusing. When scientists use the term ‘theory’, it means an idea that is heavily tested, and heavily reinforced and supported by evidence. Gravity, evolution, continental drift, heavy bombardment, and relativity are all theories- yet we do not see the heavy doubt and denial with all of them.

There is another great divide in communication, due to differing goals of all the people the information must get through to get to the public ear. The scientist may want to convey his data neutrally, and make sure she is not making any assertions her colleagues and fellow scientists will question too harshly. That information could be picked up by a researcher, who wants to use particular points from the dense and technical write up of the findings for a specific purpose. The researcher will emphasize these specific points to suit their purpose. If the media gets involved, their prerogative is getting as many viewers or page views as possible, so they will often lean towards sensationalism by exaggerating points further. Even though the information is still the same, the way it is presented and viewed changes the way it is received and understood. This leads to misunderstanding.

Both of these processes occur commonly, and warp the public’s understanding of scientific information. Communication is critical for re-establishing a higher degree of trust and understanding between the public and the people who do science for their careers. The potential oversight of these roadblocks can be nothing short of disastrous to the relationship between citizens and science. My advice to the general public would be to look hard at your sources of news, and stay engaged and curious about the world. My advice to scientists is to avoid highbrow scientific jargon, or writing too dryly and complexly, when dealing with the public. I also highly recommend every scientist engage actively in social media. What better way to relay information directly to the public than to access them directly? For citizens to obtain information from scientists directly, would be a fantastic step towards a more educated public body- and I have no doubt this educated public would be more united to act on issues like climate change, vaccinations, and evolution.

I have recently discovered a wonderfully inspiring TEDx talk delivered by Sheril Kirshenbaum, all about communicating science. Check it out here-

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Passing of Prof. John Holland, father of genetic algorithms and pioneer in complex systems

August 10, 2015

Dear BEACONites,

It is with great sadness that I report the death yesterday of Prof. John H. Holland, Professor of Psychology and of Computer Science and Engineering at the University of Michigan. John, 86, succumbed to an illness he had been dealing with for a few years, although he did manage to publish two books in the last three years in spite of it. Until very recently, he was as full of ideas and as animated as ever.

John HollandJohn invented genetic algorithms in the 1960’s, proving a number of theorems about them before they had been so named. He also pioneered then what are now called “learning classifier systems,” although he called them only “classifier systems.” John led the development of a marvelous multi-disciplinary Ph.D. program at UM, in “Computer and Communication Sciences.” He was the reason I went to UM for my Ph.D., and was my teacher and mentor in learning about genetic algorithms, although his former student Bernie Zeigler served as my academic advisor, so I am formally Holland’s “academic grandchild.” John founded the Logic of Computers Group with the late Prof. Art Burks, another brilliant thinker (logician and automata theorist) and co-inventor of the ENIAC Computer at Penn. John was largely responsible for making that research group an inspiring place to work and a fun place to spend as many hours as possible each week!

After publication of John’s book “Analysis of Natural and Artificial Systems” in 1975, he became widely recognized and lauded as the father of GA’s. He received many awards, including the MacArthur Fellowship, the Louis Levy Medal, and UM’s highest award for a faculty member.

John was also a co-founder and still a Trustee and External Professor of the Santa Fe Institute, which has been for many years a leading place where economists, physicists, computer scientists, biologists and others formulated the concepts of complex systems that are so important in science and economics today. Many of these leaders were Nobel Laureates, and John was highly esteemed among them. He wrote many books on complex systems, many of which were inspired by his study of the basic requirements for spawning of living organisms.

UM’s Center for the Study of Complex Systems was the brain-child of the highly multidisciplinary BACH group, of which John Holland was a founder–Burks (Art), Axelrod (Bob), Cohen (Michael), and Holland (John). Others joined the group after the 1980’s.

I am greatly saddened by John’s passing–he has always been a great inspiration to me–but I take consolation from knowing that his memory and his legacy will survive long beyond our generation of scientists.

Erik Goodman, BEACON Director

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BEACON Researchers at Work: Partnerships between plants and bacteria

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

Colleen Friel at the lab benchMy foray into the world of science started back when I was a high school student dead set on becoming a large animal veterinarian. To pursue that goal, I attended the Pennsylvania Governor’s School for Agricultural Sciences the summer before I graduated high school. While there, I performed my first rectal exam on an obviously displeased dairy cow and realized that veterinary medicine was not the career for me. After this rude awakening, I unexpectedly found myself fascinated by my classes in plant science and agronomy – here was a way to engage in science that fed the world (and, as an added benefit, did not involve orifices of any kind!). As an undergraduate, I performed research in microbiology, forestry, and plant biology, a combination that led to my interest in my current field of research, plant-microbe interactions. I was fascinated by how interactions between plants and organisms too small for the naked eye to see were so important on so many scales–they are vital to the functioning of natural ecosystems and goals of feeding the growing population sustainably.

Here in the Friesen lab at Michigan State, my research focuses on how plant and soil microbes exchange resources. One system I study is the mutualism between legumes (plants such as peas, beans, and clover) and soil bacteria called rhizobia. Rhizobia induce some plants to form specialized organs on their roots, called nodules. The rhizobia live in the nodules and fix nitrogen gas from the atmosphere into a form that the plants are able to use. In return for fixing nitrogen, the plant supplies the rhizobia with photosynthetically fixed carbon.

Nodules on a Trifolium plant (courtesy of Maren Friesen)

Nodules on a Trifolium plant (courtesy of Maren Friesen)

This interaction is like a biological market, where the plant and rhizobia trade carbon for nitrogen vice versa. Each organism must decide how much effort they will put into independently acquiring resources (e.g., the plant deciding how much effort to put into root growth to directly take up nitrogen from the soil) and how much effort they will put into trading for resources (e.g., the plant deciding how much carbon to supply to its rhizobia in exchange for nitrogen). Using economic theory about how markets work, it is possible to create mathematical models that describe the costs and benefits legumes and rhizobia incur through this trading agreement. In a collaborative project with the Yair-Shachar Hill lab at MSU and Emily Grman at Eastern Michigan University, we are currently working experimentally validating an existing mathematical model to describe the outcome of the legume-rhizobia mutualism in different environmental conditions. We are using photosynthesis, biomass, and carbon and nitrogen content measurements to estimate parameter values for a previously written model that we adapted to the legume-rhizobia symbiosis. We will test the model by comparing its predicted outcomes to those observed in nature or a novel set of experiments. This work is making important connections between theoretical ecological models and empirical physiological studies, while helping us understand the context-dependent effects of mutualisms on community structure.

Another economic theory that can be applied to the legume-rhizobia mutualism is the tragedy of the commons, where an individual acts against the common interest of the group by depleting a resource for its own benefit. The tragedy of the commons is a situation faced by farmers who are able to graze livestock on village commons: each farmer is motivated to graze as many animals as possible to maximize his or her personal benefit, but this will lead to overgrazing of the commons and depletion of the resource for everyone. In the context of legume-rhizobia interactions, one would imagine that rhizobia would often become “cheaters” in this system-that is, that they would direct their resources towards their own growth and reproduction rather than toward fixing nitrogen for their host plant. Thus, we would expect rhizobial populations to be dominated by these cheaters who fix little or no nitrogen while still acquiring carbon from the plant. However, this is not the case: rhizobia are very diverse and are not dominated by cheating strains.

One possible mechanism that could be stabilizing the mutualism is sanctioning, or the plant “punishing” cheaters for being less cooperative. Plants may punish rhizobia by decreasing nodule carbon or oxygen supply or by promoting early nodule death, but we do not currently understand the exact mechanism of these sanctions. I am making a mutant strain of rhizobia that is unable to fix nitrogen because of a missing protein. Once I finish generating this mutant, I hope to use it for a number of experiments where I will use techniques such as RNA sequencing to determine how the plant’s response differs between cheating and fixing rhizobia at the molecular level. This project will help us identify the genes and proteins that plants use to sanction cheaters, which could help us to understand how legumes and rhizobia co-evolved.

My research seeks to better understand how legumes negotiate interactions with their rhizobial partners. With it, I hope to provide insights into important questions in ecology and evolution about the stabilization of mutualisms, their context-dependency, and their effects on community structure. 

For more information about Colleen’s work, you can follow her on Twitter (@colleen_friel) or email her at frielcol at gmail dot com.

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