Collaborations with K-12 teachers first inspired Data Nuggets, and continue to today

This post is by MSU postdocs Melissa Kjelvik and Liz Schultheis

Liz modeling the process of science within a Data Nugget.

Back when we were biology graduate students, the GK-12 program at the Kellogg Biological Station (KBS) exposed us to science education for the first time. When we signed up to work with K-12 teachers and go into schools as the “classroom scientist” we knew there would be benefits, such as time to hone our science communication skills, a venue to share our research with broad audiences, and of course saving us the hour and a half drive to MSU’s main campus to TA. However, we had no idea what we had really gotten ourselves into.

We were each assigned a partner teacher whose classroom we would visit a few times a week, and who would mentor us as we attempted to share our research with students for the first time. The experience of standing up in front of 30 sixth graders was intimidating at first. Yet, it was necessary to realize how hard it was to simplify and explain a topic, while also making it engaging for an audience who may never have thought about these ideas before. The teachers’ infectious enthusiasm boosted the passion we had for our research. They pushed us to describe why the things we were doing day-to-day mattered for the big picture. They were willing to stand in the back of the classroom and wave their arms when students checked out because we’d used too much jargon or started to nerd-out. These teachers had such a clear passion for improving student learning; they constantly stepped out of their comfort zone to try new ways to improve their teaching and integrate the latest effective science teaching strategies into their classrooms. Working with these teachers and their students quickly became our favorite time of the week.

Melissa running a professional development workshop for high school math and science teachers.

These same teachers originally inspired Data Nuggets; they shared that their students were struggling to make sense of data in most applications, but especially data from classroom inquiry projects that turned out messy or did not follow predictions. Students should not feel they have failed when their data has variation around the mean or does not support their hypothesis. Typically, students are only exposed to research and data published in textbooks, leading to the misconception that all science is a completed product with well established ideas and clear results. To get students to think like scientists, they need to be exposed to the process of science itself and how scientists work to develop, test, and refine their ideas. As early-career scientists, we knew that along the way, experiments often fail or yield unexpected results.

For continued support, we turned to BEACON, whose education objectives align with the Data Nuggets vision. Using these seed funds, we were able to work with Louise Mead and other BEACON scientists to develop Data Nuggets that connect students to real data and the motivation and passion of the scientists behind the research. Today we have 46 Data Nuggets (and counting) up on our website, freely available to teachers and students, many written by women and early career scientists.

As we wrapped up as graduate students, we realized there was so much more we wanted to do to improve and expand Data Nuggets. The support from BEACON allowed us time to fully develop our ideas and submit an NSF DRK-12 grant with Louise. As BEACON postdocs we are excited to have time to integrate all these great ideas into Data Nuggets. The main objective of the collaborative NSF DRK-12 grant, between MSU and Biological Science Curriculum Study (BSCS), is to assess whether Data Nuggets increase students’ quantitative reasoning abilities, along with their understanding of, and engagement with, science. In preparation for this efficacy study, we are currently revising each Data Nugget and integrating new ideas and feedback from our collaboration.

High school math and science teachers working to complete a Data Nugget during a professional development workshop.

This summer we worked with 4 teachers – Marcia Angle, Cheryl Hach, Ellie Hodges, and Kristy Campbell. Marcia and Cheryl have been with us since the beginning, and were among those who first helped us develop Data Nuggets. They were thrilled to see that we continued to develop Data Nuggets and were happy with how far they’d come since the original inception. This summer we had many insightful conversations about students’ struggles with certain scientific practices, including data interpretation and constructing explanations. The teachers shared their different teaching strategies, and researched new ones, in order to write guides to help other teachers cover these difficult topics. As a group we read through student responses to Data Nuggets piloted in the spring. This was a powerful way to think deeply about the areas students could improve, and ways for us to provide more context in our teacher guides to encourage rich classroom discussions. Along with BEACON postdoc Alexa Warwick, the teachers developed a grading rubric to help teachers score Data Nuggets and identify areas where their students need more practice. While reading student responses, the teachers collectively noticed that students had a difficult time using evidence to support their claims, so they worked on a new tool to ease students into this process. They presented this tool, along with other strategies, at professional development workshops for the KBS K-12 partnership teachers and all Kalamazoo Public Schools high school science teachers.

This year we are finalizing preparations for our Data Nugget efficacy study, taking place in 2017. Preliminary observations in classrooms, and feedback from teachers, indicate Data Nuggets effectively increase students’ quantitative and scientific literacy while engaging them with the story behind the research and building a connection to scientists. However, as scientists, we are of course not satisfied with anecdotal evidence and want data to support our claims! We are excited for the upcoming study to determine the ways in which Data Nuggets might contribute to a strong science education curriculum!

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Life Isn’t Fair


This post is by MSU PhD candidate Eli Strauss

PhD candidate Eli Strauss

“That’s not fair!” These were the words I uttered as a child anytime I felt that someone or something had unjustly slighted me. “Life isn’t fair,” my parents would tell me, which always seemed an unsatisfying solution to the real world problems of a spoiled kid. Flash forward a few decades, and I find myself doing a PhD motivated by that exact question: why isn’t life fair?

Certainly, we can point to many unfair aspects of modern and ancient human societies—racism, sexism, or feudalism, for example—in which some members of society benefit more than others. In these cases, the criteria for being a privileged member of society are arbitrary: a descendent of the royal bloodline rules a kingdom based entirely on birthright with no consideration of their abilities as a leader. The inheritance of socioeconomic status from parents means that children in our society don’t all start on an equal playing field, regardless of the innate abilities of the child. It is clear that humans are familiar with an unjust life, but is this specific to humans? Is “life not fair” for other animals as well? The short answer is yes.

The composition of a single hyena clan. Notice the difference in the sizes of high-ranking and low-ranking matrilines. High-rankers get priority while feeding and reproduce more quickly and successfully than low-rankers. Figure from Holekamp et al. 2012.

Social animals usually live in groups structured by a dominance hierarchy, where some members of society get priority when it comes to feeding or reproducing. This means that a low-ranking female paper wasp may never get to lay eggs, or that a high-ranking hyena may eat her fill before her lower-ranking sister gets to feed. Some of these hierarchies are organized based on size or fighting ability, where the dominant animals earn their status through physical prowess. In the societies of many primates and spotted hyenas, however, social rank isn’t earned; instead, it’s inherited. Although this inheritance is not mediated genetically, this means that the dominant female hyena gets to be the queen of her clan simply because of who her parents were. Sound familiar?

A current project of mine is focused on understanding what forces promote unfair societies in the animal kingdom. I’m using spotted hyenas as a model organism to answer these questions because their social standing is inherited and their societies are dramatically unfair. In a hyena clan, a high-ranking hyena can easily steal food and other resources from a lower-ranking group-mate. This means that  hyena that hunts and kills a gazelle may lose it to a higher-ranking individual without getting a single bite, even if the higher-ranking hyena is smaller than the animal who killed the gazelle! Rank in spotted hyenas has a large effect on fitness, and higher-ranking (and better fed) individuals reproduce around twice as much as lower-rankers (Holekamp et al. 1996). Clearly, low-rankers would stand to gain a lot by attempting to improve their social standing, but rank changes in hyenas are extremely rare. Fortunately, long-term research from the MSU Mara Hyena project has yielded a large dataset that allows for the study of such rare behaviors. Now, using nearly thirty years of data on multiple hyena clans, I have identified instances of rank change in order to understand why they are so uncommon.

An example of coalitionary aggression. The two smaller hyenas on the left are displaying aggressive postures (tail bristled, ears cocked forward, head high) while the larger hyena on the right displays submissively (ears plastered back, mouth open).

Why don’t low-ranking hyenas challenge the status quo and attempt to improve their rank? It is possible that they don’t have enough allies. In societies where social status is inherited, it is common to see coalitionary aggressions from multiple individuals to a single target. These aggressions are thought to either strengthen the status quo (‘conservative’ coalitions, directed from high-rankers to a single low-ranker) or challenge it (‘revolutionary’ coalitions, directed from low-rankers to a single-high ranker; Bissonnette et al. 2015). If coalitions are the key to maintaining or challenging the status quo, then low-rankers may rarely have the chance to challenge high-rankers because high-ranking hyenas have more social allies. High-rankers reproduce more quickly than low rankers and thus have more close kin with which to ally, and high-rankers also have mutual direct interest in maintaining the status quo (Holekamp et al. 2012, Smith et al. 2010). If rank change hinges on coalitionary aggression, we expect to see the instances of rank change associated with cases where a high-ranker loses many of its allies, thus exposing itself to revolutionary coalitions.

Alternatively, it is possible that low-rankers rarely challenge the status quo because they suffer a cost by doing so. This cost could be punishment inflicted by the challenged groupmates or could be due to subtler costs of living in unstable conditions. Dominance hierarchies are thought to exist because they bring stability and decrease conflict within a group (Schjelderup-Ebbe, 1922). Thus, challenging the status quo should carry costs associated with increased conflict. If the direct costs to challengers are deterring hyenas from challenging the status quo, we expect to see elevated amounts of wounding and high levels of stress hormones in hyenas that are involved in rank changes and unstable hierarchies. Even if we detect costs incurred by hyenas attempting to improve their social status, they will have to be weighed against the rate of success and the benefits gained by hyenas that successfully improve their rank.

Hopefully, this research will begin to shed light on the forces that maintain social inequality in animal societies. Hyena societies are similar to many primate societies, and are thus wonderful models to use to understand the inequality that exists throughout the animal kingdom. Viewing human inequality in the context of evolutionary patterns can help us understand why life isn’t fair, both for us and for our animal relatives.

Bissonnette, A. et al. 2015. Coalitions in theory and reality: a review of pertinent variables and processes. Behaviour 152:1–56.

Holekamp, K. E., L. Smale and M. Szykman. 1996. Rank and reproduction in the female spotted hyaena. Journal of Reproduction and Fertility 108:229–237.

Holekamp, K. E., J. E. Smith, C. C. Strelioff, R. C. Van Horn and H. E. Watts. 2012. Society, demography and genetic structure in the spotted hyena. Molecular Ecology 21:613–632.

Schjelderup-Ebbe T. Beitrage zur Sozialpsychologie des Haushuhns. Z Psychol 1922, 88:225-252.

Smith, J. E. et al. 2010. Evolutionary forces favoring intragroup coalitions among spotted hyenas and other animals. Behavioral Ecology 21:284–303.

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You Say “Cow” and I Hear “Milk” – The Joy of Interdisciplinary Work

This post is by MSU faculty Arend Hintze

While I was listening to the many interesting talks of this year’s BEACON congress (2016), I was pondering about the journey that we took together to get here. Fortunately, I was around to not only witness the first BEACON congress, but all others since then, except for 2015. Amazing, exciting, controversial, and interdisciplinary were only some of the words that popped into my mind, and I deeply enjoyed reflecting on that ride. But why? What is the thing I liked most, what made this so special?

That was the moment I had the idea for the title of this blog post, because it characterizes so absurdly what makes working with the people in BEACON so exciting and rewarding. It is the misunderstanding between the different disciplines. When I talk to biologists, for example about mate selection, or navigation, or foraging then this person has a specific animal with a specific repertoire of behavior and methods to study it in mind – the “cow” – and also the limitations of said model system. I can make our computational model systems without constraints, but also, most often, I have no experience or knowledge about the animal my collaborators are talking about. I know what it means to have the “feeling for the animal”[1,2], but that’s it, I don’t have that about model organisms in general (with the exception of C. elegans maybe). I have a feeling about abstract systems, selection pressures, and how to design experiments in the computer, and I code worlds and environments that are loose enough analogies to animal system to get things to evolve – the “milk”.

This necessarily leads to misunderstanding, and in the process of picking up the pieces, we typically both learn things. I understand the animal better, you understand the modeling process, and together we find the right abstractions, and are able to form the exact hypotheses and experiments to do in the future. It is enlightening and rewarding, and we haven’t even conducted experiment yet, but at least we think we know what is going on, until the results come in.

In many cases, these results shake both of our understandings, not because we again communicated poorly, but because neither of us understood what was going on in the first place; or I go and fix a bug and we meet next week, hoping for new and surprising results. However, it is exactly this dialog, where we try to explain to each other what we do and how our system works that allows us to be creative. When I was listening to many talks, I could see how well we now understand each other. Having results from computational systems right between results from organismal systems, and the audience doesn’t even flinch, is amazing. We reached a state where we talk each others language, and appreciate what everyone can bring to the table, without hearing “milk” or “cow” but knowing that we talk about bovine evolution.

I also had the feeling that we might start to lose out on exactly this quality that made us strong. The presentations were great, but also much more focused on each topic, without giving the broader context we all add when we know that the audience isn’t too familiar with what we are working on. It is a sign that the past made a difference, and we indeed learned from each other, and maybe we just rose to a new level? In one of our workshops about AVIDA and Markov Brains/MABE we tried to go back to the basics and explain things from scratch. While that might have been preaching to the choir, I also had the feeling that we could do this more often. The strength of our computational model systems doesn’t come from what we did with them in the past. Their strength comes from what we can do with them in the future. In summary, I think we came very far, we should just make sure that we keep misunderstanding each other in the familiar productive way I learned to love!

Cheers Arend

[1] Holmberg, T. (2008). A feeling for the animal: On becoming an experimentalist. Society & Animals, 16(4), 316-335.

[2] Keller, E.F. (1983) A feeling for the organism. The life and work of Barbara McClintock. New York: Owl Books

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STC Directors annual meeting invited keynote Rush Holt

We were very excited to meet our invited keynote Rush Holt (center) at this year’s STC Directors annual meeting, which BEACON organized. In his keynote address, Dr. Holt discussed how NSF-funded Science and Technology Centers like BEACON can help take on one of the greatest challenges facing the scientific community: communicating science and promoting evidence-based thinking among policymakers and the public.

Holt started his career as a physicist, heading a lab at Princeton. He then served as New Jersey’s U.S. Representative for 16 years. He is now the CEO of the American Association for the Advancement of Science, and Executive Publisher of the Science family of journals. Holt also beat the IBM computer Watson on an exhibition match of Jeopardy!

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The Evolution of the NSF-Funded BEACON Center: 2010-201

This post is by Patty Farrell-Cole, Ph.D., Marilyn Amey, Ph.D., Sarah Fitzgerald (Ph.D. candidate) and Alex Gardner (Ph.D. student)

The National Science Foundation (NSF) holds expectations of transformational research and education for Science and Technology Centers (STC). In 2010, the NSF-funded BEACON Center for the Study of Evolution in Action officially began its quest to produce transformative, synergistic research through an inclusive, collaborative culture that crosses disciplinary and institutional boundaries. To obtain unbiased formative insights on the workings of the Center, BEACON leadership commissioned us (a higher education research team) to conduct formative evaluations of its organizational effectiveness and impact. In this blog we tell a short story on the evolution of BEACON.

Since the beginning, BEACON’s leadership has had high expectations, including being an exemplary Center to NSF (L&M Optical Outcome #6, BEACON Strategic Plan, 2015, https://www3.beacon-center.org/). In the seven years of our studies, we have found that BEACON is a complex, non-linear system comprised of multiple institutions, colleges, departments, faculty, administrators, post docs, and students. We also learned that bringing together researchers from diverse disciplines and multiple institutions to answer difficult questions is not simple; it is a “puzzle of complexity” (Horton, late 1800s).

To gather both broad and deep understandings of the effectiveness of BEACON, we needed to gather data broadly across institutions and constituent groups using multiple methods. Since 2010, we have developed and conducted (a) multiple and diverse surveys focusing on the organization, research faculty, or the next generation of scientists; (b) individual and chair interviews; and (c) focus groups with post docs and graduate students.

2010-11 — We started our formative evaluation work by conducting a BEACON organizational baseline study focusing on mission, leadership, management, and culture. Our findings illustrated a Center that was in its forming stage where members acted with excitement but, at the same time, were unsure of their role, the future of the Center, or how the Center fully operated. The forming stage required high direction by the leaders, such as creating policies and procedures for funding, communication mechanisms, and a member activity data system.

2011-12 – Based on the baseline organizational findings, we conducted interviews with department chairs, who could be “gatekeepers” to involvement with BEACON. We found many chairs, even those at MSU, did not know much about BEACON. We also learned that participation in BEACON was perceived differently for many reasons, including variation in tenure and review policies across departments represented in the STC. In addition, we focused on the needs of the “next generation faculty and researchers” (i.e., doctoral students, post docs, and assistant faculty) to complete five short surveys on topics that were of interest to them, including 1) BEACON & department/college support and funding, 2) BEACON inter-disciplinary and inter-institutional work, 3) BEACON outreach and education, 4) BEACON career and professional development/mentoring, and 5) BEACON research thrusts. These surveys were important to assess BEACON sustainability and the findings helped BEACON leaders improve the communication, funding, and decision making processes.

2012-13 – We conducted a follow-up organizational evaluation survey and found the Center had committed itself to working on organizational aspects that were critical to its success (e.g., communications, funding, transparency). At the time, 79% of BEACONites indicated BEACON was achieving its mission and goals very well/well, and 92% told us BEACON impacted their own research.

2013-14 – Based on the 2013 organizational evaluation, we started studying the impact of BEACON in preparation for the NSF renewal grant proposal. We decided to conduct interviews with key faculty from the five universities and overwhelmingly heard that BEACONites were together building a new way of studying evolution in action. A few quotes:

These are important scientists doing important work and BEACON will definitely have impact on the field of evolutionary science. There is no doubt about it.

I would say that in the life sciences, it has made this an intellectually vibrant place to work. I mean, I found [my institution] deadly boring before BEACON showed up … BEACON has completely changed that.

BEACON has encouraged, influenced and brought together researchers from different disciplines to “pursue questions that we wouldn’t have been able to pursue. It has changed the direction and flow of some of the research.”

It’s had a profound impact on guiding research, generating a new skill set, not only in me, but in my students a well … giving me a great layer of interdisciplinary landscape.

2014-15 – Unlike a stand-alone organization or corporation which has control of human resources and operational processes and procedures, BEACON operates within the rules and cultures of five different institutions in addition to its own rules and culture. And even within the institutions, the culture and processes vary significantly across departments and disciplines. Our organizational evaluation survey findings in 2015 showed a Center that was staying true to its mission and is pretty successful operating within the rules and culture that the leaders cannot change.

Even as a complex system comprised of diverse members, we view BEACON as a conduit that has created a one-stop shop for faculty, postdocs and students to learn and study evolution in action across disciplines. BEACON is exemplifying the new world of research where collaboration is vital. We found that BEACON is providing opportunities to learn about one another including the work individuals conduct and want to conduct, the disciplinary cultures they are entwined in, and the research knowledge they create. “We are in a synergistic way, stronger when we look at these questions together [transcending disciplines] and interact with each other,” stated one BEACON faculty member. And research is not the only “exemplary” aspect of BEACON to NSF. NSF has also been very impressed with BEACON’s diversity and education efforts, which have increased significantly since its inception.

Through our studies, we recognize that creating a successful multi-institutional research collaborative takes forethought, maintenance, and on-going effort in order to thrive and achieve its mission and goals. Unlike university leaders, those involved in research collaborations often focus only on the work of the project and assume the context of the work derives organically or without much thought. Meeting the interdisciplinary and multi-institutional expectations of funders such as NSF requires intentional efforts from principal investigators, academic administrators, and faculty to foster learning organizations which support these important collaborations. Taking the context of faculty work into account while employing strategic leadership and organizational development strategies, and taking the context of faculty work into account, helps situate BEACON in ways that broaden the base of potential members rather than pit one set of goals and expectations against another. Garnering support from necessary gatekeepers and decision makers in these settings means more than obtaining signatures on grant proposals; it means developing effective, authentic, and on-going communication channels, promoting partnership outcomes and benefits, establishing means for socializing new members and building effective networks, while always keeping an eye on the future and long-term sustainability. As we have seen with BEACON, this approach to launching a multi-institutional research collaboration fosters a culture of continuous improvement and helps BEACON more effectively achieve its overall mission and goals.

2015-16 – This blog provides a glimpse into the work we have been conducting the past six years and is part one of two blogs. In 2016, we conducted a Social Network Analysis of BEACON, so please read the October 3 BEACON blog by doctoral students Sarah Fitzgerald and Alex Gardner. Social Network analysis is based on the intuitive notion that social patterns are important features of the lives of the individuals who display them and individual lives depend in large part on how each individual is tied into the larger web of social connections. Many believe, moreover, that the success or failure of organizations often depends on the patterning of their internal structure; this would include STCs such as BEACON and other multi-institution organizations. Through the SNA, we looked to answer, What is the pattern of collaboration between BEACON members?

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Evolutionary Trade-offs

This Evol 101 post is by MSU grad student Tyler Derr

Before even jumping into the evolutionary biology material, what is a trade-off? Well, a trade-off is when a choice must be made between multiple things that are either incompatible or an increase in one thing might lead to a decrease in another. Theodore Garland Jr. gave the perfect example, “…money spent on rent is not available to buy food.”, makes sense. In a past post we discussed correlated traits, one can think of a biological trade-off as simply negatively correlated traits (i.e. if one trait goes up, the other goes down).

A one-trait trade off is the result of an opposing selection on that one trait via a different environment or through perhaps a limiting resource (Agrawal, Conner, & Rasmann 2010). An example of a single trait trade-off in humans is the weight of a new born baby. A higher birth weight provides a higher chance of survival in the first few weeks, but babies that are too large have higher mortality rate (Karn & Penrose 1951). Thus there is a trade-off in the birth weight that greatly impacts the chance of survival.

When two or more traits are involved a multiple-trait trade-off can be thought of as having a single resource where it is impossible to use this resource to increase more than one trait at once. If it sounds a bit confusing, for now just think of the aforementioned example of taking your money (i.e. the resource) and either paying rent or buying food (which can be thought of as the two traits).

Fig. 1: Howler monkeys seen roaring. [Image Credit: Mariana Raño]

An example of a multiple-trait evolutionary trade-off can bee seen in different species of howler monkeys (shown in Fig. 1). Dunn et al. just recently had their paper “Evolutionary Trade-Off between Vocal Tract and Testes Dimensions in Howler Monkeys” published in Current Biology. In their research they discovered that the bigger a male’s vocal organ and louder the roar, the smaller their testes resulting in less sperm production.

The University of Cambridge made quite an interesting few minute clip, Calls vs. balls: An evolutionary trade-off, in which they discuss the findings of this paper and you get to hear Dr. Jacob Dunn imitate the roar of a howler monkey. Although it is not exactly a clear cut answer as to why this trade-off exists, it was observed that the loud species tend to live in a social model where there is only one male dominating a set of females, as compared to the species that instead have bigger testes (and weaker roar) live in groups of multiple males where the females mate with all the males. The first scenario would lead rise to selecting for a louder roar to claim territory and to ensure having females to reproduce with, while the second scenario would give rise to selecting for larger quantities of sperm since this would be the way to ensure offspring when the females are mating with all the males in their group. As mentioned before about the single resource and multiple traits to invest in, Dunn et. al suggests that the reason for this trade-off is simply the howler monkeys do not have sufficient energy to invest in the acts of loud roaring combined with large sperm production.

It is quite clear from the examples that although we might observe some evolutionary trade-offs in nature that we certainly do not always fully understand the reasoning behind such trade-offs. In the words of Dr. Jacob Dunn, “In evolutionary terms, all males strive to have as many offspring as they can, but when it comes to reproduction you can’t have everything.”

References:

1. Agrawal, Anurag A., Jeffrey K. Conner, and Sergio Rasmann. (2010). “Tradeoffs and negative correlations in evolutionary ecology.” Evolution since Darwin: The First 150 Years. 243-268.

2. Dunn, Jacob C., Lauren B. Halenar, Thomas G. Davies, Jurgi Cristobal-Azkarate, David Reby, Dan Sykes, Sabine Dengg, W. Tecumseh Fitch, Leslie A. Knapp. (2015). “Evolutionary Trade-Off between Vocal Tract and Testes Dimensions in Howler Monkeys”. Current Biology. 25(21): 2839-2844.

3. Garland Jr., Theodore. (2014) “Trade-offs”. Current Biology. 24(2): R60-R61.
4. Karn, M. N. and L. S. Penrose. (1951). “Birth weight and gestation time in relation to maternal age, parity and infant survival. Ann. Eugenic. 16: 147-164.

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Science and Social Justice

This post is by NCAT faculty Joe Graves

Yes, that’s me holding up the fist, next to the fist in the Science for the People banner stating: “Scientists Against Reagan’s War”. This picture was taken at a national march against US intervention in El Salvador, in Washington, DC on May 3rd 1981. Next to me in the picture are my life-long friends Dr. Brian Schultz, now a biologist and Cruz Phillips, now a rancher and social activist for the Farm Workers movement in California. We were graduate students then in the Department of Ecology and Evolution at the University of Michigan.

You didn’t have to be a scientist to march for this cause. Just like those who marched across the bridge in Selma, Alabama on March 7 (Bloody Sunday) were not scientists. They were simply good and courageous people demonstrating against social injustice. They were met with police, dogs, horses, tear gas, clubs, and whips. Many were severely beaten, including John Lewis (now Democratic Congressman for the 5th District, Georgia).

Definitions

However this post is not about social justice in general, but science and social justice. To start a discussion of the relationship between the two it is necessary to define what is meant by the term social justice. One definition of social justice is promoting a just society by challenging injustice and valuing diversity. In this definition diversity refers to various aspects of human identity (socially defined race, ancestry, gender, sexual orientation, national origin and others) that have been the subjects of social subordination. Accepting this definition suggests that you believe that all people have a right to equitable treatment, support for their human rights, and a fair allocation of community resources. In addition this definition suggests that individuals should not be discriminated against, nor their welfare and wellbeing constrained or prejudiced on the basis of any of these identity features or any other characteristic of background or group membership1.

With this definition in mind, we might want to ask to what degree historically or currently has science as an enterprise, or the actions of individual scientists been associated with this goal. First, scientists employ a supposedly neutral and objective method (the scientific method) to understand the workings of nature. This method, employed at its highest standards, should allow us to work out how various processes in nature work. A child might run along a field flapping their wings vigorously in an effort to fly, but the principles of physics tell us that this simply cannot happen. However, our ability to unravel the laws or rules of nature begins to diminish as we move from the physical to the biological and social sciences.

This is further complicated by the fact that science as an enterprise has always been more than working out the various principles of nature; it has always been imbedded in a social milieu, and therefore has always been tasked to addressing particular socially defined priorities. Some of these priorities have been neutral to or even in rare cases supported notions of social justice. For example general scientific principles such as the conservation of matter, organic evolution, or ecological food webs in themselves need not have had any specific impact on human society. Yet, on the other hand, Newtonian physics allowed improved methods of producing projectile weapons, thermodynamic principles helped to produce better explosives, the computer made possible better inscription and code breaking, ecological principles have been utilized to conduct biological attacks on crops, and microbiology has been deployed to produce better bacteriological and viral weapons2. Even one of the core principles of natural selection, the struggle of existence, was developed not in attempt to understand population growth in general, but specifically as an attempt by Reverend Thomas Malthus (1766—1834) to explain the poverty of the English poor. The gist of the essay was devoted to his analysis of the English Poor Law and the impact of the transition of the poor from agricultural to industrial labor3. While Malthus correctly reasoned that geometrical sequences increase more rapidly than arithmetic ones, he had no reason to assume that the food resources of human societies necessarily increased only arithmetically.

Science as power

What is clear then is that precisely because science allows us to understand the workings of nature, it has inherent power. Power than can be used for good or evil. Here I will make the controversial statement that for the most part, the scientific enterprise has aided and abetted social injustice. This statement should not be taken to mean that scientists are the only profession that can be tarred with this ugly moniker, as Karl Marx once said:

“The bourgeoisie has stripped of its halo every occupation hitherto honored and looked up to in reverent awe. It has converted the physician, the lawyer, the priest, the poet, the man of science, into its paid wage laborers4.”

In this passage, Marx was alluding to two things, first the obvious interpretation that the new economic system had converted occupations that had in the past been held mainly by persons of leisure into wage labor jobs, but also that this new economic system had won the ideological allegiance of these professions. Furthermore he thought that this new economic system was initially a great improvement over feudal relations. For example it had been responsible for the industrial revolution that had greatly improved the living conditions for the majority of Europe’s population. Scientists and engineers had played an important role in this transition, but unfortunately what had been good for Europeans had not been good for the rest of the world’s population. For example, the Guyanese economist Walter Rodney (1942—1980) explained how Europe’s primitive accumulation (the wealth required to drive the industrial revolution) had depended upon both the Trans-Atlantic slave trade and the colonization of Africa5.

Ironically, the colonization of the tropics by European powers had important impacts of the development of scientific disciplines such as anthropology, agriculture, botany, ecology, and zoology6. It also had important influences on the demography and the development of scientific infrastructure in Africa. It is not accidental that African still lag behind European nations in the production of scientists or the building of scientific facilities. Similarly, persons of African-descent and other socially subordinated ethnic populations living in nations dominated by European populations (e.g. USA, England) still suffer from the hegemony of Eurocentric culture in science. This does not refer to the scientific method, but rather to the choice of research problems that the scientific community is engaged in and the way in which the scientific community repopulates itself7. In the 19th century, the majority of anthropologists were concerned with validating the overall superiority of persons of European descent. This was associated with social and legal programs that denied fundamental human and civil rights to non-Europeans. For example, the Supreme Court’s decision in the Dred Scott v. Sanford Case (1857) was premised on the scientific consensus that Africans/Negroes were members of a separate and inferior species8. These views dominated the field until the 1960’s. It is important to recognize that evolutionary biologists played a significant role in debunking this myth. This process began with Darwin and culminated with the thinking of evolutionary geneticists like Th. Dobzhansky, Richard C. Lewontin, and their intellectual progeny (of which I am one)9. However at the same time, there were just as many scientists who had played a role in developing the myths of racial superiority and actively worked to help implement racist policy. Examples of such individuals include Louis Agassiz, Samuel Morton, Josiah Nott, and George R. Gliddon (the four horsemen of American polygeny), John Jeffries, Herbert Spencer, Arthur Comte de Gobineau, Francis Galton, Charles B. Davenport, Eugen Fischer, Henry Garrett, Arthur Jensen, J. Phillipe Rushton, just to name a few10.

Science and social injustice: An Ongoing Problem

It this point the reader may argue that I have chosen scientific racism as an example of science and social injustice as a “low hanging” fruit. Clearly it was scientifically unfounded and morally reprehensible. My response to that claim would be that the scientists themselves never felt that they were unscientific in their analysis, and all of them felt that their work was morally defensible (and in some cases imperative), particularly from the point of view of improving human society. I would also argue that there are currently groups of scientists working in arenas that they feel adhere to the scientific method and that will ultimately be beneficial to human society. Yet to these individuals I lay down the challenge that a little more thinking is required before anyone can be satisfied with that position. One such example is the modern push for personalized medicine. While the readers of this post may question the degree to which medicine is “scientific” it certainly relies on the principles of biological science to develop its approaches and treatments. So in that regard, let’s briefly examine the scientific ideas behind personalized medicine.

Modern medicine is really only now beginning to fully appreciate the significance of individual and population variation11. With this in mind, physicians are beginning to recognize that there is no such thing as one treatment that is suitable for all patients suffering from a specific disease. Again part of the previous failures in this regard resulted from the past racist/sexist practices of primarily testing drugs in males of European descent. As more populations began to be tested for drug efficacy, it was found that there was significant variation in individuals that influenced the way drugs were metabolized12. In addition, individual variation can now be determined with accuracy not possible before the age of next generation sequencing (NGS). Now, physicians can genotype individuals quickly and cheaply. Furthermore, the use of NGS has revealed hitherto unrealized variation not just in patients, but also in some of their diseases (such as infectious disease and somatic tumors). All of these realizations have come together in a perfect storm, leading inexorably (or it would seem) to the necessity to develop personalized medicine.

Clearly, the scientific questions engaged in this effort are intellectually appealing. However, I would argue that whether something is of intrinsic interest to the scientist, should not be the sole criterion determining whether we pursue it. In the modern world, the vast majority of scientists depend upon public funding to support their work. Given this fact, the priorities of the scientific enterprise should be the subject for public discussion. On the surface of this, everyone should want to see the development of personalized medicine. However, the resources that we have to spend on scientific research are not unlimited. Also the resources that are available to implement societal interventions based upon research programs are not unlimited. So the question becomes, what do we really wish biomedical research to achieve? If one takes the view that biomedical research should improve the overall wellbeing and health of our society, than it turns out that the personalized medicine approach is a poor use of our limited funding. In a recent discussion with a cancer physician at Duke Medical School I learned that the cost of these next generation cancer drugs are well beyond what even well-employed persons can afford via insurance and their personal wealth. Furthermore, at the end of the day, these drugs do not cure cancer; they simply increase the patient’s life by several months. The cost of these drugs means that these treatments will be beyond the reach of the underemployed and poor in US society. This group is disproportionately ethnic minority, meaning that should we succeed with developing personalized medicine, its initial impact will be to widen the health disparity gap that already exists in American society.

On the other hand, we could reduce the health disparity gap by implementing good science that does not rely on NGS and complex drug regimes. The first would be to examine the causes of complex disease (e.g. heart disease, diabetes, cancer) and the causes of the differentials. In fact, this is something that ecologists, environmental scientists, nutritionists, and social scientists have understood for a long time. Poor people shoulder the burden of morbidity and mortality in all societies because they are the ones who are differentially exposed to the causes of disease (infectious, chemical, radiation, poor diet, etc.) For example, one of the most effective approaches to malarial disease in the tropics is not the development of new anti-malarial drugs, but reducing mosquito breeding habitat and provisioning people with sufficient anti-mosquito netting. Similarly with water-borne bacterial disease the most effective treatments are providing people with clean drinking water13. In the United States, ethnic minorities are differentially exposed to chemical toxins (lead, PCBs, organophosphate pesticides, socially-induced stress, and poor diet14.) Thus I have argued repeatedly that if our goal is to reduce morbidity and mortality in the United States our money would be better spent on research that helps us implement programs to reduce toxic waste exposure, racism, and provide people with nutritious food options15.

Again, these are not mutually exclusive options (NGS v. health/nutrition) however we should consider how social justice is served by these two approaches. In the former, high technology treatments may be developed by cutting edge genomic science. Who benefits from this? Clearly, people with sufficient wealth to afford the treatments, but also the genomic/biomedical scientific community, sequencer technology companies, drug companies, and health care companies. We can see the logic of this approach already impacting how government funding agency mechanisms (NSF, NIH, etc.) are already being structured. This is also seen in the new emphasis that universities have for “translational research” and “university-industry collaboration.” To be clear, it is not that these mechanisms are inherently wrong, but tied into an over-arching paradigm of “fixing the patient after the fact” there is much to be concerned about. In addition, at present, the demography of this consortium of interests still favors persons of European descent. This means that should this program achieve its goals it will only reify the social dominance of European Americans, and support the ongoing subordination of racial-ethnic minority groups.

On the other hand, the environmental approach will benefit a wider variety of persons, since the goal is to reduce and prevent complex disease, as opposed to treating it after you acquire it. Also a serious approach to environmental remediation would benefit a different demography of scientists and social scientists. Also to achieve such remediation would empower the communities most impacted by the pollution.   Again, I have argued that repairing the toxic environment experienced by racial/ethnic minorities is absolutely crucial to alleviating the opportunity gap16.

Conclusion: What is to be done?

It has been my experience that most scientists are quite comfortable living with or simply unaware of social injustice17. There are also many who have decried the unfairness of the world, but have simply felt powerless to make any significant impact on the state of affairs. Most scientists do not see how their science careers are connected to greater social issues. This last statement is less true of evolutionary biologists. Our discipline by its very nature has always been engaged in social controversy18.

On the other hand, ethnic minority scientists have always understood the relationship between science and social injustice. Our very existence stood as living example of the fallacies of racist thinking in science. For example, Charles R. Davenport, director of the Eugenics Record Office at Cold Spring Harbor said of Ernest Everett Just (an early African American biologist) that he did not display any extraordinary talent19. The Howard University Anthropologist William Montague Cobb (b. 1904) spent much of his career debunking the racist claims of physical anthropology. Similarly I have spent much of my career debunking racist claims in genetics, anthropology, medicine, and psychology.

However, racism, sexism, or anti-gay bigotry are not the only topics in which science impacts social injustice. I would argue that all scientific research has the potential to contribute to or alleviate injustice. Therefore, all science falls within ethical discourse. Here we should always evaluate how our science impacts others (obligations), how it is influenced by our values (moral ideals), and what are the beneficial or detrimental consequences of our work. In addition, as science is a social enterprise, we must always be concerned with which persons have the opportunity to engage in it. All of us to some degree have the power to address injustice within the science community (as Richard Lenski did in my case).

If you choose to walk the path of social justice in science, understand that you are not alone. There have always been networks of individuals who have united to address specific justice issues in science. In the 1980’s I was a member of a group called “Science for the People” which grew out of an earlier iteration called “Scientists against the Vietnam War.” Some of you may have heard of the “Union of Concerned Scientists” whose purpose it was to alert society of the growing danger of nuclear annihilation. I am currently involved on the Race and Genetics List Serve that addresses ongoing racial misconceptions in genomic research and also the Social Justice and Science Think Tank, associated with Kalamazoo College20.

Finally, I end with one precautionary note. The pursuit of social justice can be a rabbit hole. There is so much to do, and it can seem like all you ever do, accomplishes nothing. This can be a real danger for graduate students. So I always caution students that their most important goal during their graduate training is to complete their training and earn their degree. You will have much more ability to accomplish your life and societal goals after you have the title of PhD after your name (as I explain in my “Belly of the Beast” essay). There are also more responsible ways of contributing to social justice initiatives without at least initially placing yourself on the “black list.” Of course I used to say, “…if it’s a black list, than I want my name on the top of it!” All, kidding aside, you cannot engage in this work without consequences, and you should decide if you are willing to accept them. This is the path I chose for my life and career, and quite frankly I don’t think I could have done otherwise.

Notes

  1. For a useful definition of social justice consider John Rawls, Justice as Fairness: A Restatement (Cambridge, MA: Harvard University Press, 2001).
  2. Bousquet, A. The Scientific Way of Warfare: Order and Chaos on the Battlefields of Modernity, (London: Hurst and Co), 2009.
  3. Gilbert, G. Economic growth and the poor in Malthus’ Essay on Population, History of Political Economy 12(1): 83—96, 1980.
  4. Marx, K. and Engels, F. Manifesto of the Communist Party, 1848.
  5. Rodney, W., How Europe Underdeveloped Africa, (London: Bogle-L’Ouverture Publications), 1972.
  6. Tilley, H., Africa as a Living Laboratory: Empire, Development, and the Problem of Scientific Knowledge, 1870—1950, (Chicago and London: U. Chicago Press), 2011.
  7. Mead et al. Mead, L.S., Forcino, F.L., Brown Clarke, J., and Graves J.L., Factors influencing the career pursuit of underrepresented minorities with an interest in biology, Evolution: Education and Outreach 8:6 DOI: 10.1186/s12052-015-0034-7, 2015.
  8. Graves, JL. The Emperor’s New Clothes: Biological Theories of Race at the Millennium, (New Brunswick, NJ: Rutgers U. Press), 2005. See Table 3.2 summarizing 19th century anthropologist’s views on the Negro as an inferior and separate species.
  9. Darwin outlined his views on race in the human species in The Descent of Man and Selection in Relation to Sex, 1871. Desmond and Moore’s Darwin’s Sacred Cause: How a Hatred of Slavery Shaped Darwin’s Views on Human Evolution (Boston/New York: Houghton, Mifflin, Harcourt), 2009 is an excellent read illustrating how social perspectives shaped Darwin’s reasoning. My intellectual descent from Dobzhansky and Lewontin can be seen on the Evolution Tree at http://academictree.org/evolution/ .
  10. I spend a great deal of time on these individuals and their work in The Emperor’s New Clothes, 2005.
  11. Hidaka BH, Asghar A, Aktipis CA, Nesse RM, Wolpaw TM, Skursky NK, Bennett KJ, Beyrouty MW, and Schwartz MD. The status of evolutionary medicine education in North American medical schools. BMC Med Educ. 2015 15:38. doi: 10.1186/s12909-015-0322-5.
  12. See excellent discussion of “What is a patient” in Stearns, S. and Medzhitov, R. Evolutionary Medicine, (Sinauer Associates) 2016.
  13. Ntonifor NH, Veyufambom S. Assessing the effective use of mosquito nets in the prevention of malaria in some parts of Mezam division, Northwest Region Cameroon. Malar J. 2016 15(1):390. doi: 10.1186/s12936-016-1419-y.
  14. Bullard, R. et al. Toxic Wastes and Race at Twenty, United Churches of Christ Justice and Witness Ministries, 2007.
  15. Graves, L., Evolutionary versus Racial Medicine: Why it Matters? In Race and the Genetic Revolution: Science, Myth and Culture, edited by Sheldon Krimsky and Kathleen Sloan, Columbia University Press, 2011.
  16. Graves, L, Looking at the World through ‘Race’ Colored Glasses: The Influence of Ascertainment Bias on Biomedical Research and Practice, in Laura Gomez and Nancy Lopez, eds. Mapping “Race”: A Critical Reader on Health Disparities Research, Rutgers University Press, 2013.
  17. Graves, L., Science in the Belly of the Beast: A Look Back at My Career in the Academy, in Voices of Historical and Contemporary Black American Pioneers, V.L. Farmer and E. Shepherd-Wynn Eds., (Westport, CT: Praeger Publishers), 2012.
  18. Berkman, M and Plutzer, E. Evolution, Creation, and the Battle to Control America’s Classrooms, (New York: Cambridge University Press), 2010.
  19. Manning, K. Black Apollo of Science: The Life of Ernest Everett Just, (New York and London: Oxford University Press), 1985.
  20. The link to the Social Justice and Science Think Tank, inaugural lectures can be found on the Science and Social Justice Praxis site of the ACSJL (https://reason.kzoo.edu/csjl/sciencesj/) .
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Exaptation

This Evol 101 post is by MSU grad student Alex Lalejini

Figure 1. Microwave oven

A Conceptual Analogy

Technological innovations throughout the history of human invention are often the result of co-­opting an existing technology to develop something new. The invention of the microwave depended on the development of the magnetron, a device initially developed for World War II era radar technology. The magnetron was invented and adapted for its radar application; the inventors certainly did not have the use-­case of reheating food in mind during its development. However, once it was discovered that the device could be used to reheat food, the magnetron was co­-opted and adapted for use in microwave ovens like the one shown in Fig. 1 (Fernández, 2014).

The laser has a similar story of unforeseen co-­option of functionality for a variety of domains. Since its invention, the laser has seen use in microsurgery, precision measurement, bomb guidance systems, barcode identification, holography, cutting, drilling, welding, printing, telecommunications, and many other domains (Bonifati, 2010). The inventors of the laser did not develop the laser with these domains in mind. The laser was initially developed as a proof of concept (first laser: Fig. 2). At first, people referred to the laser as a solution without a problem (Townes, 2003), but eventually, the laser was co-­opted and adapted to a huge variety of domains.

This process of co-­option is widespread and influential in innovation across many technological domains. The idea of co­-opting an invention for a totally different purpose – using the magnetron for microwaves, or lasers for microsurgery – is analogous to an important concept in evolutionary biology: exaptation.

The term exaptation was first coined by Stephen Jay Gould and Elisabeth S. Vrba in 1982. Gould and Vrba wanted a way to distinguish between two different ways evolution could produce adaptive or fitness­-enhancing features (Gould & Vrba, 1982):

  1. adaptation – the process by which natural selection shapes a feature for a particular use. Features produced by this process are often referred to as adaptations.
  2. exaptation – the process by which a feature previously shaped by natural selection for a particular function or a feature that is entirely non-­adaptive (i.e. a feature that came about through neutral mutations) is co-­opted for an entirely new use. Features produced by this process are often referred to as exaptations.

For example, Gould and Vrba would say that the magnetron was an adaptation for radar technology, but it was an exaptation for reheating food. The difference between an adaptation and an exaptation helps us to understand and explain many fitness­-enhancing characteristics we see in nature.

Figure 3. An artist’s impression of Zhenyuanlong suni. This velociraptor cousin posessed large, complex wings and looked bird-like. Image by Chuang Zhao

Exaptation in Nature

The evolution of complex features can seem unintuitive to those just considering the evolutionary process by which natural selection shapes a feature for a particular use. By Gould and Vrba’s definition, adaptation alone is not sufficient for the evolution of many complex traits we see in species today because what good is only part of a wing for flight? Feathered wings used by birds for flight provide a good example of exaptation in action.

Figure 4. Zhenyuanlong suni fossil by Junchang Lü & Stephen L. Brusatte

The earliest known examples of feathered appendages belong to dinosaurs incapable of flight. A recently found and well preserved fossil of the Zhenyuanlong suni species of dinosaur (artist’s impression: Fig. 3; fossil: Fig. 4) shows that this dinosaur species possessed feathered wings; however, it was unlikely to be capable of flight (Gill, 2015; Lü & Brusatte, 2015). If Zhenyuanlong suni had wings but could not fly, its feathered wings must have evolved for some reason other than flight, which implies that birds’ ability to fly via feathered wings is an exaptation.

It is thought that feathers may have initially evolved for insulation, for mating displays, or for social displays (Zimmer, 2011). Wings are hypothesized to have been initially beneficial for capturing small prey, for aiding bipedal animals in leaping, or for sexual displays (Hutchinson, 1996). Because it is unlikely that wings and feathers evolved initially and specifically for flight, the feathered wings we see on today’s flight-­capable birds are a clear example of an exaptation. This is just one example of an exaptation we see in modern species; evolutionary history is filled with many more!

Together: Exaptation and Adaptation

Gould and Vrba’s versions of adaptation and exaptation do not occur in isolation from one another. An exaptation like feathered wings for flight can be further enhanced through natural selection for more efficient flight. Any exaptation can undergo further adaptations for its particular purpose, and any adaptation may be subject to exaptation to a totally different function. Gould and Vrba’s concept of exaptation is meant to underline the incredible importance of the co­-option of existing traits, behaviors, or characteristics for new purposes in evolution. Exaptation enables us to see vestigial structures in modern species from a new perspective. Perhaps a given organ or structure has no current function today (e.g. the appendix), but through exaptation, it could one day take on a totally new and fitness-­enhancing function in the future!

References

Bonifati, Giovanni. “‘More is different’, exaptation and uncertainty: three foundational concepts for a complexity theory of innovation.” Economics of Innovation and New Technology 19.8 (2010): 743­760.

Fernández, Eliseo. “Evolution of organisms and invention of artifacts: Analogies and contrasts.” 57th Annual Meeting of the Midwest Junto for the History of Science (2014).

Gill, Victoria. “Dinosaur find: Velociraptor ancestor was ‘winged dragon'”, BBC News, (2015).

Gould, Stephen Jay, and Elisabeth S. Vrba. “Exaptation­a missing term in the science of form.” Paleobiology (1982): 4­15.

Hutchinson, John R. “Vertebrate Flight: The Evolution of Flight (a.k.a. How to Wing It)”. (1996).

Lü, Junchang, and Stephen L. Brusatte. “A large, short­armed, winged dromaeosaurid (Dinosauria: Theropoda) from the Early Cretaceous of China and its implications for feather evolution.” Scientific reports 5 (2015).

Townes, Charles H.”The first laser”. A Century of Nature: Twenty­One Discoveries that Changed Science and the World. University of Chicago Press (2003): pp. 107–12.

Zimmer, Carl. “The Evolution of Feathers: Their origin may have had nothing to do with flight. Photographs by Robert Clark. Art by Xing Lida.” National Geographic 219.2 (2011): 32.

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Getting to the Stem of Central Nervous System Regeneration

This post is by UW grad student Shawn Luttrell

Why do some animals regenerate missing or damaged tissue and organs while others do not? How are animals able to regenerate new tissue and do they all use the same genetic program? Was the common ancestor of all animals able to regenerate and that trait was passed down to multiple animal lineages while it was lost in others, or has this remarkable trait evolved independently numerous times throughout the animal kingdom? Many animals are able to regrow missing or damaged body parts and some can even regrow an entirely new animal from just a small segment of tissue. If you cut sponges, planarian worms, and hydra into pieces, they will regrow complete and normal animals from most, if not all, of the pieces (Alvarado, 2000). Chop certain kinds of sea stars or hemichordates in two and both halves will grow into complete animals (Carnevali, 2006; Humphreys et al., 2010; Rychel and Swalla, 2008). Nearly all annelid worms can regenerate tail segments and some can even regenerate their head. Some species of ctenophores, also known as comb jellies, can heal wounds and regrow new structures without generating any scar tissue. Some crickets and spiders can regrow missing legs and even some hard-shelled invertebrates, like crabs and lobsters will regenerate missing appendages during molting. Nearly every animal phyla has members that are able to regenerate to some degree (Alvarado, 2000). The vast regenerative abilities found throughout the different animal lineages suggest an ancient and ancestral mechanism for this trait. It is likely that the common ancestor of all animals was able to regenerate and this remarkable characteristic has been highly conserved in many groups. The answer to this question, as well as how and why certain animals regenerate, remains a mystery, but through the concentrated efforts of scientists studying this process, like myself, we are getting closer to finding the answers.

I am a fourth year Ph.D. student in the Biology Department at the University of Washington. Over the years, my research has been driven by these fundamental questions and has evolved into focused areas of regenerative science, including stem cells and central nervous system (CNS) regeneration. Humans have limited regenerative abilities, particularly in the CNS. When nerves are damaged or destroyed in the brain and spinal cord, they typically will not regrow. It is imperative to understand the barriers preventing this process and develop approaches to overcome these obstacles as millions of people suffer from brain and spinal cord injuries, as well as neurodegenerative diseases, like Parkinson’s, Alzheimer’s, and Huntington’s to name a few (Brown et al., 2005; Mahabaleshwarkar and Khanna, 2014). One way to gain a better understanding of CNS regeneration is to study animals with extensive regenerative abilities. This is the path my research has taken.

Figure 1. Ptychodera flava, a hemichordate, from Honolulu, Hawaii.

Figure 2. Ptychodera flava collection sites. A) Tetiaroa, French Polynesia. B) Paiko Bay, Honolulu, Hawaii.

Figure 3. Deuterostome phylogeny. Humans are vertebrates, to the right. Hemichordates are a sister group to the well known echinoderms.

I study CNS regeneration in the solitary hemichordate, Ptychodera flava. This animal is also known as an acorn worm and is closely related to echinoderms, like sea stars and sea urchins. Hemichordates are strictly marine animals and all have a tripartite body plan with anterior proboscis that is used for digging and burrowing in the sand and mud, a middle collar region, a ventral mouth between the proboscis and collar, and a long posterior trunk (Figure 1). This particular species of hemichordates lives in the tropical waters of the Indo-Pacific and we collect them in Hawaii and Tahiti (Figure 2). Hemichordates are in the same group of animals as chordates, including humans, and as such, share numerous developmental and morphological features (Figure 3). Most notably for my research, P. flava has a hollow, dorsal neural tube in the collar region that our lab has shown develops in a very similar fashion to the chordate neural tube. In humans, the neural tube becomes the brain and spinal cord. More impressive is the fact that P. flava can regenerate its neural tube after complete ablation. In fact, they can regenerate all of their body structures. I bisected adult worms in the trunk region (Figure 4) and after two weeks of regenerating at 26°C, the posterior half of the animal has regrown a new proboscis, collar and neural tube, and anterior region of the trunk (Figure 5). As humans, we have lost most of our regenerative abilities, and our lab is interested in whether we still have the genes that are important for regeneration, as we share many developmental genes with hemichordates.

Figure 4. Bisected Ptychodera flava. The boxed area indicates the regeneration site of the posterior half of the animal.

Figure 5. Regenerating Ptychodera flava. A) The open wound of the cut site on day zero of regeneration. B) Day 1 of regeneration showing the wound has healed. C) Day 7 of regeneration showing the proboscis and partial collar. D) Day 14 of regeneration showing complete proboscis and collar regeneration.

We have recently submitted a manuscript for publication that details the regeneration transcriptome for Ptychodera flava. A transcriptome shows all of the genes that are being turned on and off at a particular time when that tissue was collected. We sequenced and analyzed nine different time points during early hemichordate regeneration and identified hundreds of genes regulated during this process. This was part of an overarching transcriptome project that is looking at numerous animals that are able to regenerate to see if there is a common gene or set of genes that starts the regeneration program. If the common ancestor of all animals was able to regenerate and that trait was passed down, it’s likely that the regeneration program will be similar in all animals. Importantly, humans will likely possess many, if not all, of the genes required for the regeneration program. If that is the case, it may be possible to reactivate those genetic pathways using the regeneration program from other animals.

Aside from activating the correct genes to start the regeneration program, another possible way to regrow new CNS neurons is to use stem cells. These special cells have the ability to become any type of cell in the body. Hemichordates may use stem cells to regrow missing or damaged tissue. The other possibility is that they use existing cells in their body and reprogram those cells in regenerating structures. For example, a muscle cell in the existing tissue might be reprogrammed to become a nerve cell in the new tissue. To help answer this question, I was awarded a grant though the National Science Foundation as part of the East Asia and Pacific Summer Institute (EAPSI) program to work on a project with one of our collaborators in Taiwan. I am currently at Academia Sinica, the premier Science and Technology Research Institute in Taiwan, using molecular methods with stem cell markers to try and identify what type of cells hemichordates use to generate new tissue. In humans, when a cell differentiates into a particular cell type the cell fate can usually not be reversed or altered. If hemichordates employ this method during regeneration, it will give us a model to study how cell fates can be reassigned. If, on the other hand, hemichordates use stem cells to populate new tissue, this will give us a model to study how stem cells are activated and recruited during regeneration. Hemichordates may use both models to regenerate new tissue and this possibility is exciting because it will give us two models in one system to develop methods for regenerating missing or damaged tissue, including CNS neurons, in humans.

References

Brown R.C., Lockwood A.H., Sonawane B.R. 2005. Neurodegenerative diseases: an overview of environmental risk factors. Environ Health Perspect. 113(9): 1250-1256.

Mahabaleshwarkar R, Khanna R. 2014. National hospitalization burden associated with spinal cord injuries in the United States. Spinal Cord 52(2): 139-44.

Candia Carnevali, M.D. (2006). Regeneration in echinoderms: Repair, regrowth, cloning. Invert Surv J. 3, 64-76.

Humphreys, T., Sasaki, A., Uenishi, G., Taparra, K., Arimoto, A,. Tagawa, K. (2010). Regeneration in the hemichordate Ptychodera flava. Zoolog Sci. 27(2), 91-95.

Rychel, A.L. and Swalla, B.J. (2008). Anterior regeneration in the hemichordate Ptychodera flava. Dev. Dyn. 237(11), 3222-3232.

Sánchez Alvarado, A. (2000). Regeneration in the metazoans: Why does it happen? Bioessays. 22, 578-590.

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BEACON at GECCO 2016

We are very excited to acknowledge the success of some fellow BEACONites. Kalyanmoy Deb and students of the COIN (Computational Optimization and Innovation) lab this year received multiple awards and nominations at the GECCO conference (The Genetic and Evolutionary Computation Conference).

For the Real-World Applications (RWA) track, Zhichao Lu, Kalyanmoy Deb (Michigan State University) and Ankur Sinha (Aalto University) were nominated for the Best Paper Award for their paper: Finding Reliable Solutions in Bilevel Optimization Problems Under Uncertainties.

In the Evolutionary Multi-objective Optimization (EMO) track, Rayan Hussein and Kalyanmoy Deb (Michigan State University) were nominated for the Best Paper Award for their paper A Generative Kriging Surrogate Model for Constrained and Unconstrained Multi-objective Optimization.

In the Genetic Algorithms track, Kalyanmoy Deb (Michigan State University) and Christie Myburgh (MapTek) won the Best Paper Award voted by the GECCO participants for their paper Breaking the Billion Variable Barrier in Real-World Optimization Using a Customized Evolutionary Algorithm.

20160724_130959 IMG_3625The Niching Methods for Multi-modal Optimization Competition Award was awarded to Ali Ahrari (ME PhD student, Michigan State University), Kalyanmoy Deb (Michigan State University), and Mike Preuss (University of Munster, Germany) for their paper Benchmarking Covariance Matrix Self Adaption Evolution Strategy with Repelling Subpopulations.

Lastly ACM’s SIGEVO Impact Award, recognizing papers previously published 10 years earlier in the GECCO conference that are highly cited and deemed to be seminal by the SIGEVO Executive Committee, was awarded to Kalyanmoy Deb, and J. Sundar for their paper Reference point based multi-objective optimization using evolutionary algorithms in Proceedings of the 8th annual conference on Genetic and evolutionary computation. ACM, 2006.

Congratulations!

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