Exploring Genetic Design Space with Phylosemantics

This post is written by UW grad student Bryan Bartley 

Synthetic biology is a fascinating, interdisciplinary field at the intersection of biology and engineering. Synthetic biologists envision that life can be re-programmed by rewriting the genetic code of organisms. A variety of biotechnologies for synthesizing, assembling, and editing DNA now make this possible. Of course, this idea has many profound and serious implications, one of many reasons why it is such an interesting field to work in.

Many people are uncomfortable with the idea of tinkering with the genetic code. My scientific and personal convictions lead me to believe that if humanity wants to live in harmony with nature, then we must learn to speak the language of life.

The language of life is written mostly in terms of A, C, T, or G, which, as you perhaps learned in biology, stand for the four molecular bases of the genetic code. These bases are strung together into long sequences of DNA by means of a polymeric backbone. It’s a bit of an oversimplification to describe DNA as genetic code, because frankly there is still a lot we don’t understand. However, every organism on earth, to our knowledge, uses DNA to encode living processes inside their cells. Human beings are related to the rest of the animal kingdom and in fact to all living organisms. The story is written in our DNA.

If you ever have the opportunity to take courses in biology or biochemistry, then you might just learn the basics of decoding DNA. However, unlocking the mysteries of the genetic code has taken decades, and continues to be a scientific challenge full of surprising discoveries. The approach I discuss in this week’s BEACON blog, called phylosemantics, is a technique for interpreting the genetic code that might be useful in some special cases.

Phylosemantics is a computational algorithm I developed as part of my PhD research in synthetic biology. It is a combination of methods called phylogenetics, which is commonly used in evolutionary biology, and semantic clustering, an idea with roots in artificial intelligence. Tree diagrams are used by all of these methods to classify information into families or groups with similar characteristics. There’s a good chance you have seen a phylogenetic tree before, and just don’t remember! In case you have forgotten what they look like, evogeneao.com has a nice interactive tree-of-life. Phylogenetics uses similarities in DNA sequence to group related sequences together. In contrast, phylosemantics makes a semantic comparison between different components of DNA.

For example, consider the Cox combinatorial promoter library1, which consists of 288 variant genetic promoters. Each individual promoter is composed of three genetic operators arranged sequentially in distal, medial, and proximal positions (Fig. 1). The boundary between positions are defined by the -35 and -10 sigma70 RNA polymerase binding sites. Promoter variants were derived by varying operator types at each position (repressor, neutral, or activator). Operator sites may also be varied by substituting operators derived from different species. For example G and H variants represent operators specific to LacI and TetR repressor proteins, respectively, while activator variants J and K represent AraC and LuxR binding sites. Thus, it is possible for two operators to be semantically equivalent, even while they differ in terms of their DNA sequence.

The phylosemantic tree (Fig. 2) diagrams 12 variant promoters from the Cox library. This tree systematically groups the promoter variants into 3 families based on similar configurations. The length of branches of the tree correspond to semantic distance between variant designs. If the adjacent branches have no length, then adjacent promoters have the same configuration. Tabulated next to each variant are levels of gene expression corresponding to each variant promoter. The advantage of graphing these data with a phylosemantic tree is that some patterns in gene expression become more apparent.

The first family of variants (FJK, IDD, FDB, and HEB) are clustered by my algorithm because they all have a repressor operator distally. These promoters exhibit high gene expression, despite the presence of a repression operator. In other words, repression in this family of promoters appears to fail. In contrast, the middle cluster contains similar promoters DGB and AFI with a medial repressor operator. Promoters with a medial repressor operator exhibit very low gene expression consistent with repression. This makes sense from a biophysical perspective—a repressor bound in medial position will sterically hinder RNA polymerase binding.. A design pattern may thus be stated that repressor operators in medial position exhibit a pronounced repression effect while repressor operators in distal position appear ineffective. The point of the phylosemantic tree is to systematically organize the different genetic architectures and find patterns in their behavior.

This brief explanation of phylosemantics barely scratches the surface, but I hope some readers will at least find it intriguing. Phylosemantics encompasses a number of related approaches that might apply in different scenarios. For example, different formulae for calculating semantic distance can produce trees that are more useful for one type of analysis versus another. Another choice with interesting implications is whether to construct a rooted versus unrooted tree. Scenarios in which phylosemantics might be useful include:

  • Phylosemantic classification might be useful for comparing different genetic architectures in natural biological variants
  • Phylosemantics can be used to discover genetic design rules for synthetic biology
  • Phylosemantic classification might be used to systematically classify permutations of genes in different orientations.
  • Phylosemantics could enable biodesign automation efforts by helping synthetic biologists plan rational assembly strategies starting from the given DNA templates.

If you found this discussion interesting, I will be presenting this topic at the BEACON Congress and the International Workshop for Biodesign Automation in Pittsburgh, PA in August. I’m very interested in connecting with collaborators in industry or academia who are interested in applying phylosemantic approaches to a case study. Thanks for reading my post today!


[1] R. S. Cox et al., “Programming gene expression with combinatorial promoters,” Mol. Syst. Biol., vol. 3, no. 1, p. 145, 2007.

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STEMprov for improving science communication

This post is written by UT Austin grad student Rayna Harris

Communicating science is important, and there are plenty of ways to improve. Improv is a theatrical technique that can help scientists tell better stories, understand group dynamics, and say yes in the face of the unknown. Former UT graduate student Nichole Bennett has started hosting a STEMprov workshops to help STEM folks improve how they communicate with different audiences. Let me tell you about two of my favorites improv games Nichole taught that can be used to specifically improve science communication.

‘Yes but’ versus ‘Yes and’

Have you ever pitched an idea at a meeting only to have it ripped apart to shreds by your lab mates? I know that even when I have the best intentions, sometimes I’m too quick to point out the flaws in my colleague’s research plan rather than point out the strengths. To illustrate the difference between discouraging and encouraging peer ideas, we played two games. In both games, one person pitches and idea, but the peer’s response either with discouragement or encouragement. Compare these two games or lab meeting scenarios:

Yes but example: It would be awesome to build an automated video tracking system! Yes, but John already tried it and it failed. Yes, but you can’t do that and graduate on time. Yes, but we don’t have the money.

Yes and example: It would be awesome to build an automated video tracking system! Yes, and John could give you some advice. Yes, and this would really enhance your thesis. Yes, and we can apply for a technology grant to support it.

I’d like to have a lab meeting where we brainstorm and only provide positive feedback before we perform a more critical analysis of ideas. Let us know if you’ve ever tried this.

Story Spines

Nichol also taught us how we could use a template or a ‘story spine’ to tell a well-constructed story about our science or career. The format of the story spines is this

Once upon a time ___. Every day, ___. One day ___. Because of that, ___. Because of that, ___. Until finally ___. And, ever since then ___.

I think these are perfectly adaptable for science storying because it isn’t that different from the introduction, results, conclusions format we are used to using, but it is much more compelling. In the story spine, the world exists in a certain way with routines, but then sometime changes and there are consequences. Finally, there is a resolution and now the world is different.

After the workshop, I wrote a very short story spine about my career trajectory here. I encourage you to write a story spine today and tweet it to @BEACON with the hashtag #STEMprov.

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Mapping Antibiotic Resistance in Pseudomonas aeruginosa Biofilms to Develop Better Therapies for Cystic Fibrosis

This post is written by MSU DO-PhD student Michael Maiden

I have always been interested in bacterial resistance. My first science fair project was comparing antibacterial soap versus regular soap in terms of selecting for resistant bacteria with use. In addition, I have also always wanted to be a clinician to both better understand the human body and help those around me. At Michigan State University, I’ve found a program that allows me to continue my research while earning a medical degree at the same time. Currently, I am a 6th year DO-PhD student in the physician scientist training program in Dr. Christopher Water’s biofilm laboratory. Here, I study how Pseudomonas aeruginosa, the most common pathogen in cystic fibrosis, evolves resistance with long-term antibacterial treatment.

P. aeruginosa is the leading cause of death in patients with cystic fibrosis (CF). CF is a debilitating disease that compromises host immunity, most dramatically in the lungs, resulting in life-long chronic bacterial infections. The most important clinical obstacle in CF is treatment failure due to biofilms. Biofilms are a community of sessile cells enmeshed in a self-produced thick gel matrix that leads to thousands of times more resistance to antibacterial therapies, macrophages, and neutrophils. A hallmark of CF is a defective mucociliary transport system that results in dry mucus production and clogged airways, creating an environment that is ideal for colonization by P. aeruginosa. Central to this pathogen’s success is its biofilm mode of growth within the lungs of CF patients, which are essentially impossible to eradicate with current antibacterial therapies, leading to immune complex-mediated chronic inflammation, neutrophilic tissue damage, decreased lung function, and ultimately death. Furthermore, due to their high level of tolerance, cells often re-grow after multiple rounds of therapy becoming even more resistant with time. By early adulthood, P. aeruginosa evolves and establishes a chronic infection recalcitrant to intervention in 80% of patients. Numerous retrospective studies have shown that eradication of P. aeruginosa before its chronic infectious state leads to better clinical outcomes. A key step in accomplishing this goal is enhancing current eradication therapies.

Image shows P. aeruginosa resistant mutants spread on Pseudomonas Isolation Agar plates. Plates were then imaged using a UV-light. Lower right-hand corner is ancestral strain, moving counter clock-wise, you move through time and evolution, gradual loss of fluoresces is seen indicating loss of production of a fluorescent molecule along with the development of resistances to tobramycin and triclosan.

How P. aeruginosa evolves to become more resistant, is what I am most interested in studying. I’ve found that by treating with two specific antimicrobials, tobramycin and triclosan, I can drive P. aeruginosa down certain evolutionary trajectories that render them resistant to one antimicrobial (tobramycin) but sensitive to another (triclosan). In essences, out-smarting the bacteria at their own game. To do this, I serially treated P. aeruginosa biofilms over the course of 6-months with ever increasing concentrations of tobramycin and triclosan. Using this method, the biofilms gradually evolved resistance to the combination therapy and lost the ability to produce a fluorescent molecule shown in figure 1. To date, I have evolved 191 single colony isolates that are ~200x more resistant triclosan and tobramycin combined. Next, whole-genome sequencing will be performed on these evolved resistant mutants to look for genetic mutations that could explain how becoming resistant to one class of antimicrobial renders them sensitive to another.

As antimicrobial resistance continues to be a major threat to global health, it is important to develop better strategies that more effectively used our current antimicrobial arsenal. This is especially true for CF, where patients become infected with evolved strains of P. aeruginosa that are essentially impossible to kill with current therapies. For this reason, P. aeruginosa is the leading cause of lethality in these patients and is a major clinical concern. This approach, funded by BEACON, could yield insights into how bacteria evolve resistance and methods for out-smarting bacteria at their own game. As a future clinician-scientist, developing new therapies that could possibly improve clinical outcomes is an exciting opportunity that I am grateful to be a part of this research.

From my fist childhood experiments studying the effects of antimicrobial soap vs regular soap on bacterial selection, to studying how the human pathogen P. aeruginosa evolves resistance to antimicrobial therapies, it is clear that my curiosity for the invisible human foe has persisted. BEACON has, in-part, sustained this interest and allowed me to learn, not just about the human body, but how bacteria are so central to our evolution as a species. Evolution remains a largely un-tapped resource, and I hope this work inspires others to consider it as a tool for learning more about the world around us.


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BEACON goes back to Alaska!

This post is written by MSU postdoc Wendy Smythe.

IMG_7302We have just returned from another amazing trip to Alaska where we visited Ketchikan, and the Haida communities of Hydaburg and Kasaan Alaska located on Prince of Wales Island. The trip is an effort funded through BEACONs Native American/Alaska Native Institute (NAANI) to increase diversity in STEM and to raise cultural awareness for non-native future PIs. During the visit participants taught in the Hydaburg School K-12 classes; teaching evolution of butterfly vision, shipworms, and oceanography, participants took part in harvesting local dietary resources such as spruce tips, tea, seaweed, and sea cucumbers, we were lucky to get to take a cedar weaving class from community member Becky Frank. Visiting scientists learned about the Haida culture and language from community members and conducted interviews on Haida culture, Traditional Ecological Knowledge and how the Haida way of life uses STEM to build canoes and totem poles from large cedar trees, when and how to gather resources, and how to they monitor and protect the land and sea that they are very much a part of. Traditional Knowledge is passed on through oral traditions of story telling grounded in centuries of stewardship to the region. While in Hydaburg our group participated in the 4th Annual Science/Career Fair by presenting hands on demonstrations of our own science for the students and community. Interviews with community members and local scientists were conducted for a series of documentaries featuring Traditional Knowledge coupled with STEM for the creation of culturally relevant curriculum. During our trip we encountered and ran from an angry mother bear, and participated in a spiritual dip into the ocean (which was very cold!). Postdoc Wendy Smythe, is from Hydaburg and hosted the group of BEACON graduate students Klara Scharnagl, Carina Basket, and Aide Macias Munoz, we were accompanied by Christie Poitra from MSUs Native American Institute. On July 28 the documentaries produced during this trip will be shown at the Friday seminar.

Canoe that is being carved in Kasaan Alaska

Spruce tips used to make spruce tip jelly,

sea cucumbers

Harley Bell-Holter discussing the totem pole in Kasaan Alaska

Klara Scharnagl wrapping up an interview at sunset in Hydaburg, Alaska.






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BEACON Research Fellow Dr. Wendy F Smythe receives an AAAS Science & Technology Policy Fellowship

Michigan State University BEACON Research Fellow Dr. Wendy Smythe receives an AAAS Science & Technology Policy Fellowship. Wendy will be working at NSF within the EHR/Division of Research on Learning in Formal and Informal Settings/Innovative Technology Experiences for Students and Teachers/Discovery Research PreK-12.

Fellows demonstrate leadership and excellence in their research careers, in addition to an interest in promoting meaningful dialogue between science and society, learning first-hand about policymaking while contributing their knowledge and analytical skills in federal policy. Fellows serve year-long assignments in the executive, legislative, and judicial branches of the federal government in Washington.

Dr. Smythe received her doctorate in Oceanography/Environmental Science from Oregon Health & Sciences University in 2015 and investigates microbe-mineral interactions from groundwater ecosystems and the evolution of microbial populations in metalliferious springs. She is also a Co-PI on a collaborative NSF GEOGOLD project to increase awareness of diversity in Geoscience. In addition Smythe works to couple STEM with Traditional Ecological Knowledge in an effort to increase representation of Native American/Alaska Natives in STEM disciplines, working with her tribal Haida community in Hydaburg Alaska, a tribal community located on Prince of Wales Island.

The American Association for the Advancement of Science publishes the journals Science, Science Translational Medicine, Science Signaling, and Science Advances, a digital, open-access journal. Science has the largest paid circulation of any peer-reviewed general-science journal in the world. AAAS was founded in 1848 and includes nearly 250 affiliated societies and academies of science, serving 10 million individuals. The nonprofit organization is open to all and fulfills its mission to “advance science and serve society” through initiatives in science policy, international programs, science education, public engagement and more. To learn more about AAAS STPF go to www.aaas.org/page/stpf/become-st-policy-fellow.

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Interdisciplinarity in evolutionary science… and video game design.

This post is written by UI faculty Barrie Robison

One year ago, my colleague Terry Soule and I embarked on a somewhat crazy idea – we wanted to make a video game built upon the principles of evolutionary biology. The two of us had dabbled in this area before, and reasoned that the combination of biology and computer science would naturally result in a cool evolutionary video game. Our early results were comically inadequate (Figure 1A).

Figure 1. Procedurally generated creatures using a randomly mutating digital genome. A) The comically inadequate results of a computer scientist and a biologist. Their genomes determine their shape and color. B) Incorporating artists on the team can produce creatures that are fully animated and modeled in 3D. Their genomes affect most aspects of their morphology and coloration. These are early prototypes of creatures for this summer’s game.

Our team was very clearly missing some key members. This is when we began to grasp the extent of the inherent interdisciplinarity in video game design – an enterprise requiring a startlingly broad swathe of University Departments. One needs programmers, to be sure, but a compelling game requires art and design (contrast Figure1A with 1B), story and characters, business and marketing, music and sound, and no small amount of evangelism on social media.

Check out Scott Manley’s playthrough of our game here:

If we want to make an evolutionary game – add a biologist or two to the mix.

Last May, having learned from our early experiences, we established Polymorphic Games and began by recruiting such a team of undergraduates. Their task was simple (ish): Create an evolutionary version of the classic arcade game Space Invaders. We hoped they could get that done in 12 weeks, but were prepared for failure. After all, Terry and I had been collaborating on this project for 18 months and our results had been less than compelling. The team finished what we asked … in two weeks. We had learned a very important lesson: the benefits of interdisciplinary collaboration transcend scientific research.

Over the course of the rest of the summer, the students of Polymorphic Games took that simple evolutionary version of Space Invaders and turned it into something unique. And as they did it we watched them learn the tools of interdisciplinary collaboration – communication, respect, an understanding of roles, elements of leadership, and clarity of the shared vision. It was an amazing experience that resulted in “Darwin’s Demons”, named after the metaphorical Darwinian Demon – an organism that can evolve without constraint.

Darwin’s Demons is based on classic arcade games in which the player has to defeat waves of opponents. The evolutionary component was included by giving each opponent a digital genome that controls its appearance, traits, and behavior. After a wave in the game each opponent is assigned a fitness based on how well it performed against the player. Then each wave is treated as a generation in a generational evolutionary algorithm.

The player controls a space ship, and must destroy all of the opponents in each generation. The player has a limited number of lives and loses one each time either the ship is hit by an opponent’s projectile, an opponent reaches the bottom of the screen, or the ship is hit by an opponent (some ships are immune to hits from the side, allowing them to move into and destroy, opponents that move too far down the screen).

A concise (and much more visual) description of the science behind Darwin’s Demons is portrayed in our “science trailer” for the game.

Once Darwin’s Demons was complete, a key question was whether evolution was serving its design purpose. Was it making the game harder? Was it making the game more compelling? In a recent conference paper at EvoStar, we tested these hypotheses. We concluded that incorporating evolution caused the game to get progressively more difficult. In fact, this result led us to coin our tag-line: Evolution Always Wins. Changing the fitness function also led to different evolutionary trajectories, as did different player decisions regarding ships, armaments, and defensive systems.

Perhaps the most interesting result, however, occurred during one of our outreach activities. Prior to release, we hosted a high score competition at a University of Idaho video game event called Vandal Overnight. Our grand prize was that we would let the winner design a new ship for the game. Many players participated in the contest, and most fared poorly – they were only able to play the game for 4 to 5 minutes. A few players, though, were able to play continuously for more than 30 minutes. Were they more skilled? No. They were exploiting the evolutionary model. They were destroying the most aggressive and accurate aliens first, and letting the dumbest aliens persist for a long time in each generation. The result? They DOMESTICATED the aliens, turning them into metaphorical space cows that never fired projectiles and hovered stupidly in the upper corner of the screen.

As educators in evolutionary biology, this outcome was truly wonderful. Exploiting the evolutionary model implies understanding of the evolutionary model. As game designers, this result was alarming. We reasoned that “Space Cows – the video game” would not be well received by discerning gamers. We had to modify our fitness functions prior to game release to mitigate this strategy.

We continued to polish our game after the summer with a much smaller team, and commercially released Darwin’s Demons the day after Darwin Day. After three months, we’ve sold over 600 copies and added to over 1200 “wishlists” on Steam:


The sales aren’t bad for the first release for an indie game studio. But sales aren’t the point. I indulge in a loose comparison between sales of a game and citations of a published paper, I couldn’t be more proud of a work produced by a team of undergraduates.

Of course, one of our clearest indicators that Polymorphic Games is on the right track is the degree to which we are irritating pseudoscientists:

Darwinian Theory Proved by Video Game? Robert J. Marks Begs to Differ

Their irritation appears to stem from the fact that the aliens in Darwin’s Demons did not evolve to become sentient. We have excoriated our team of undergraduates for failing to create SkyNet. This summer for sure!

A new team of undergraduates have just begun “Project Hastur”, our new evolutionary game. The team consists of three programmers, two biologists, a musician, three artists, an evangelist, an entrepreneur, a creative writer, and a video production expert. I conclude that our ability to build and facilitate this interdisciplinary team was no accident. It was a direct result of BEACON’s unique culture – a culture that values a collaborative, interdisciplinary approach.

With this new game, we hope to further push the integration of evolutionary principles with game-play. Project Hastur takes the struggle to the ground, where both the player and the environment will drive the evolution of the game opponents. Polymorphic Games will have an exhibitor’s booth at Evolution 2017 in Portland. If you have ideas about how to use evolutionary games for education and outreach, or if you just want to check out our games, please drop by.

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Amoeba hugs are often deadly, and sometimes they set your career

This post is written by NCAT faculty Misty Thomas

My passion for Microbiology first started when I was in my undergraduate microbiology class at the Collège Universitaire de St. Boniface, in Winnipeg, Manitoba, Canada. I’m sure it was a cold day, as it almost always is in Winnipeg, but we were feeding amoebas small planktonic crustaceans called daphnia under the microscope. I watched the amoebas’ pseudopods (blobby arms) try to grab the daphnia to eat it three times, the daphnia kept teasing the amoeba until finally, on the fourth try, the daphnia met its death. After being engulfed, the amoebas’ digestive enzymes (internal fork and knife) came out and obliterated the daphnia. If you want a view of what I saw, here is a YouTube video of an amoeba eating two paramecia (https://www.youtube.com/watch?v=pvOz4V699gk), let me know what you think! What I learned from this moment on was that I was destined for a life in Microbiology. When I first started my undergraduate career, my plan was to be a high school chemistry and physics teacher, but after becoming more interested in Microbiology (and reading the Hot Zone), I ended up double majoring in Microbiology and Biochemistry. Then, in my second year, I went to a seminar which discussed alternative careers to medicine (because that apparently is where all the other science majors want to go) and I was then convinced I was going to graduate school.

With not a minute of real research experience, I originally had a hard time finding an advisor for grad school, and was told directly that I didn’t have what it took to be successful in a PhD program. I persisted and found an advisor and started graduate school directly after undergrad in the department of Microbiology at the University of Manitoba (also in Winterpeg). Here my advisor Dr. Brian Mark introduced me to research through studying proteins involved in antibiotic resistance, a perfect combo for a micro/biochem major. The goal of my PhD work was to study proteins involved in making the bacterial cells wall (a hard case-like structure around the cell that gives it strength and protection) and find ways to stop them and as a result kill the bacteria. Since humans don’t have cell walls we can design drugs that target the bacteria without causing harm to us, this is knowns as selective toxicity. Throughout this work I studied two proteins, one that helped to build the cell wall called NagZ and a DNA binding protein called AmpR that regulated the bacterial penicillin resistance gene ampC. Our work used a technique called protein crystallography which is a way to take a snapshot of the three-dimensional position of every atom in a protein so that you can get an accurate picture of it, as you cannot look at them under a microscope since protein are so small (although, this may not be entirely true as much nowadays). We believe that if you can see what a protein looks like, you can better understand what it does (its function), so that you can then design drugs specifically to stop the protein from doing what it is supposed to do (like making the cell wall (NagZ) or turning on antibiotic resistance (AmpR)) and then you will have an easier time killing the infectious bacteria, this is called structure based drug design. Despite my lack of experience going in, I had a successful graduate career, I won 2nd place at my first poster competition at an international conference (ACA 2007, Picture 1D), in my third year submitted a PhD fellowship grant that was rated number 1 in the province and I published 4 papers on my PhD work.

A) Self-portrait B) Participating in the Marbles Museum Family Science Fair outreach day C) Teaching about cloning in the NIEHS-Scholars Connect Program D) Winning 2nd place for my poster at the ACA 2007 D,E) My students (Telah Wingate (D) and Perice Manns (E) at their poster session presenting their work on cloning and expression of the CusS protein variants at the NCAT Undergraduate Research Symposium (Perice, won 3rd place for her poster)

I then moved to Durham NC for my Post-Doc at the National Institute of Environmental Health Sciences (I can talk about this another time), and after 4 years there, found my calling, doing what I wanted to do in the first place…teaching. I was lucky to have a mentor that let me explore teaching opportunities while a Post-doc (Picture B and C). These experiences then led me to taking a position at NCA&T as a lecturer in the department of Biology, where I have been for the last 3 years. During my time at A&T I have been able to thoroughly develop my skills as an instructor teaching General Microbiology (I don’t get to let them feed amoebas but I at least show them the video) and Molecular Biology. Now, what I have been really passionate about, is the work I have done over the last 2 years incorporating my research interests into the courses that I teach. As a lecturer, I have had to adapt the types of projects that I can take on, in addition to becoming creative in searching for research funding, which is why course teaching supplies has been a great asset to me in progressing my work forward. In addition, when students like your classes you can attract high caliber students that belong to programs that come along with research supply money as well. More recently, my research endeavors have been accelerated this past year all thanks to a collaboration that I have been able to develop with Dr. Joseph Graves at the Joint School of Nanoscience and Nanoengineering here at NCAT. Dr. Graves uses experimental evolution and whole-genome sequencing to understand how different bacteria become resistant to heavy metals which normally kill them. Dr. Graves has been studying silver resistance in E. coli, as it was thought that silver is too potent of an antibacterial agent for them to develop resistance to. They then found that they could evolve bacteria to become resistant to 10x the normal toxic levels of silver in only a matter of 9 days! Now in order for bacteria to change what they can do (be resistant) they have to in some way change their DNA, so he sequenced the entire genome (DNA) of his newly resistant E. coli and found changes in three main genes, rpoB which is the RNA polymerase B subunit, involved in transcription (conversion of DNA into RNA), ompR, which helps make protein pumps that let things into the cell and CusS, a protein that senses silver and helps make other proteins that can remove silver from the cell. As a microbiologist/protein biochemist (thanks undergrad!) I was very interested in this project, specifically looking at the CusS protein. I wanted to understand how a single change in this protein could result in a bacterium that was resistant to silver. Therefore, I took this problem into my Molecular Biology class at NCAT where 12 groups designed different version of the protein to be used for protein crystallography and for biochemical analysis to see how the function of this protein changes between the normal one and the resistant one. Incorporation of authentic research experiences into the undergraduate classroom has been one of my major goals as an instructor so that all of my students will have the opportunity to work on a real research project before graduation (unlike me). During the class I had 8 groups successfully clone proteins and 2 groups express soluble protein. After the semester was over 4 students joined my lab to continue their class projects working on CusS (Picture 1E and F). This system of training my students in the classroom has enabled me to start up a small undergraduate run research program in the Department of Biology, that focuses on mechanisms of antimicrobial resistance and right now we are working hard to continue to get protein suitable for protein crystallography and we hope that this information will provide some insight into the actual mechanism of silver resistance in E. coli and to help us understand the ways in which we can potentially counteract this in the future.

When I look back on things now, I am excited about the direction that my career has taken me, and believe that every bump in the road has taken me right to where I am supposed to be. I started out wanting to be a teacher and my education has added a passion for research and now my current career allows me the freedom to take my love for education and my love for research and put them together in a way to excite me and all of my students that I teach every day.

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On Microbial Individuality

This post is written by UI postdoc Jessica Lee

Selfie with scanners

I’m writing this blog post in hopes of convincing you to see every microbial cell as a unique individual. It’s a big ask, because microbes are numerous, and even card-carrying microbe lovers have a tendency to think of them as populations rather than as single cells. I’ve been guilty of the same thing; it’s only since I started working as a postdoc in the Marx Lab at UI that I’ve started to appreciate microbial individuality. And doing so has also forced me out of my comfort zone and into using tools to study microbes in unusual ways—an experience that I’m thrilled to share with you.

Much of microbiology has been built on the assumption that if two bacterial cells have the same genes and live in the same environment, they’ll behave in the same way. This assumption stems partly from necessity: it’s hard to study a single cell, so for most of the history of bacteriology, we’ve studied microbes by growing billions of genetically identical (“clonal”) cells in flasks and quantifying their bulk properties– for instance, measuring how fast the mass of the population doubles, rather than watching individual cells divide. We’ve long known that this is an oversimplification, but it’s a very effective oversimplification, one that has often allowed us to make predictions with stunning accuracy.

Except… sometimes even a clonal population of bacteria contains some cells insist on doing their own thing. One well-known example of such “phenotypic heterogeneity” is microbial persistence in the face of antibiotic-induced death. When a sensitive population of bacteria is treated with bacteriocidal antibiotics, most of them die at a rate that is so predictable it can be used to model precisely how much drug and how much exposure time are necessary to eliminate the population. But amid all the antibiotic carnage, we often find a small minority of cells that, nevertheless, persist.

The researchers who first examined this phenomenon by observing individual cells in action found that persister-type cells die slowly because they were previously growing slowly: they just happen to be a minority sub-population that hasn’t been actively reproducing. In general, that’s not a great strategy for a bacterium, because the whole point of being a bacterium is to make more bacteria. But it does turn out to be a good strategy if a pulse of antibiotics suddenly shows up, because antibiotics are more harmful to growing cells, so non-growing cells are able to withstand exposure longer. The most remarkable thing is that persistence is, ironically, transient—a cell can pop in and out of the persistent state, and doesn’t give its offspring any special ability to withstand antibiotics. (This makes it fundamentally different from the genetic antibiotic resistance that is a growing problem in hospitals today.) We even have evidence that this phenotypic diversity can be a useful evolutionary strategy, allowing the microbial population to “hedge its bets” by keeping a few non-growing cells on hand even while most are reproducing normally, ensuring that there will be a some survivalists ready to hunker down and wait it out a pulse of antibiotics should strike.

What does all of this have to do with my own research? Phenotypic heterogeneity seems to play a role in the way bacteria deal with a variety of different stresses, and in the Marx Lab, we study a very specific stressor: formaldehyde. Our model organism, Methylobacterium extorquens, is able to eat methanol, but when it does it produces formaldehyde as a metabolic intermediate. And somehow it manages the constant presence of that toxin quite well. We’ve recently observed some examples of phenotypic heterogeneity in M. extorquens populations, both when dealing with formaldehyde in its environment and when simply initiating methanol growth, and we’re curious to find out whether heterogeneity might be a survival strategy, or at least provide a clue about the mechanisms that M. extorquens uses to manage formaldehyde stress.

Colony growth trajectories. Each line represents an individual bacterial colony and its increase in size over time. Red lines and blue lines are two different genotypes; even within the blue genotype, there is marked variability in the amount of time it takes a colony to start growing (less so in the red genotype).

There are a few ways to observe differences among individual bacterial cells, many of them involving very fancy equipment, but one of my favorite methods is one of the simplest: looking at bacterial colonies on petri dishes. Of course, a colony is a dense mass of millions of cells, but each colony began as a single cell, so if you watch a lot of colonies, you can learn something about the variation in the single cells that started those colonies. For instance, we’ve found that if we stress cells with formaldehyde and then plate them out onto a formaldehyde-free petri dish to recover, some pop up right away and others take a long time to start growing. The distribution of colony arisal times may therefore give us some information about the growth state of the bacteria when they were stressed, or the nature of the cellular damage from the formaldehyde.

Timecourse of images of colonies developing on a culture plate over several days.

What’s more, you can observe an awful lot of colonies as they grow if you place your petri dishes on a flatbed photo scanner and scan them every hour! For real—I’m talking about the kind of scanner you can buy at your local office supply store. I’ve fallen in love with this method not only because it generates really cool data, but also because building it has been uncommonly fun. There doesn’t yet exist a company (that I’m aware of) that sells petri-dish scanners, though there are other labs who have built these systems and happily offer guidance. I’m a biologist who started in on this project all geared up for pipetting and plating and culturing, certainly not expecting that I’d find myself setting up a custom scanner array—routing cables galore through our lab ceiling, troubleshooting power supply issues, calibrating temperature probes, and writing code for image analysis. It has been a fantastic growing experience not only for my bacteria but for me as well. I’ve also been amazed at the enthusiasm and generosity of friends and strangers—biologists and non—who have offered their help. I’m hoping that this project will not only further our understanding of microbial biology in a new direction, but continue pushing me in a new direction too.

Stressed-out bacteria form colonies at different times; the ones that recover fastest end up being the biggest.

Balaban, N.Q., Merrin, J., Chait, R., Kowalik, L., and Leibler, S. (2004). Bacterial persistence as a phenotypic switch. Science 305, 1622–1625.

Ackermann, M. (2015). A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Micro 13, 497–508.

Levin-Reisman, I., Fridman, O., and Balaban, N.Q. (2014). ScanLag: High-throughput Quantification of Colony Growth and Lag Time. J Vis Exp.

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The evolution of code is like the evolution of DNA nanotechnology

This post is written by UI faculty Peter Allen

I’m Peter Allen, a professor of Chemistry at the University of Idaho. I use DNA nanotechnology to build tiny things like autonomous nanomachines. DNA is more than genes and heredity. When I tell people that I work with DNA, they often ask me what species I got my DNA from. I didn’t get my DNA from any living creature. I invented the sequence. I synthesized the molecule. It doesn’t correspond to a gene or to heredity or to biology at all. The DNA I made is just a chemical. It has interesting chemical properties like no other molecule.

As a chemical, DNA has rules that I can understand. With a few exceptions, DNA has four components that bind together in a specific pattern: adenosine (A) binds to thymidine (T); guanine (G) binds to cytosine (C). Synthetic DNA can be made that has any sequence of these components. When DNA is synthesized, it only has half of the double helix. A piece of DNA can be made with a sequence like AATGC. That piece of DNA wants to bind to another piece of DNA with the reverse-complement sequence, GCATT. When they bind together, they make the spiral we’re all familiar with.

With that simple rule set, people have built some amazing and complex things. People have folded DNA into 2D and 3D shapes. People have used DNA to manipulate light. Remarkable reactions including catalysts and amplifiers have been built using these base pairing rules. I am particularly inspired by the work of Yin et al. I adapted the Yin designs to make a DNA nanomachine that walked around on microscopic particles. As they walked, they created a signal I could see with my eyes.

This technological field is evolving like Linux does: through the sharing of code. I think that’s weird. DNA is the physical embodiment of biological evolution, but this synthetic DNA is evolving in our brains and computers. Building a structure by hand is too hard, so software is used to design the DNA interactions that will create a structure. That software is often open source. That software also evolves in the same way that Linux distributions evolve.

DNA nanotechnology is a strange mix of literal evolution and digital/social evolution. The open source software used to create DNA origami (like CADnano) presumably will evolve like Linux. If you look at the Linux timeline, it looks like a phylogenetic tree. This is more than a passing resemblance: Linux has almost literally evolved. Linux is an open source operating system. Anyone can change the code. Programmers make changes in their personal copy. That’s like a mutation. If those changes are good, they might be adopted by the official community or added to the “distribution” (a shared package of official code). That’s selection and reproduction. Sometimes, a change is very radical. The community splits and creates a second distribution entirely which then evolves separately. That’s speciation. This process of gradual change with occasional splits in the lineage (and occasional extinctions) is the same kind of process that creates phylogenetic trees in nature.

DNA nanotechnology software evolution will depend on the kinds of rules we discover. If we can inform this software with new data, maybe we can help this software do more. DNA, by itself, can make some interesting structures aside from the double helix. For instance, DNA can make a folded “quadruplex” structure if it has enough G’s in the sequence. But what about DNA when it is mixed with other things like proteins?

Aptamers are DNA that has evolved to bind a target molecule like a protein. By repeatedly amplifying and collecting DNA that binds to some target molecule (and removing non-binding DNA), one can select strong binders. Aptamers are like synthetic antibodies. Aptamers can be used for all kinds of things. If a scientist or physician needs to determine if a specific biomolecule is present, it can be detected with an aptamer. This can be especially powerful when combined with DNA nanotechnology. Some enterprising folks even took aptamer binding and used it to create a signal that could be amplified using DNA circuits.

How will DNA design software evolve to incorporate aptamer binding? I suspect that there are patterns in aptamer sequences. I suspect that there are rules for what kinds of sequences aptamers come from. One of the projects we are working on in the Allen lab is to get deep sequence information from aptamer selections. Maybe with that data in hand, we can start to tease out some new rules and artificial selection and evolution can inform digital evolution.

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National Alliance for Broader Impacts Guiding Principles

The National Alliance for Broader Impacts has recently put out a “Guiding Principles and Questions for National Science Foundation Proposals” informational PDF.


It provides great info if you’re thinking of broader impacts for a NSF proposal as well as if you’re thinking about broader impacts for any other purpose!

There is also a push for NSF review panels to use the NABI handout as a guideline when reviewing grants, so it’s worth checking out!




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