Saturday, October 4, 2014

CAREER grant post mortem

I received the grant rejection email last week...and waited until today to look at the reviews. For a couple of reviewers I hit everything just right, and for a couple of other reviewers it was the opposite.

I'm not going to go through these line by line, but I think overall I got a fair shot. I could have gone into a lot more detail about what reviewer 2 wanted to see, and I actually have in previous iterations of this grant, but decided to not go to heavy on lots of work on gene duplications. Suffice it to say I grew up as a scientist in the EvoDevo program at Oregon, and my first paper is actually on gene duplications. Will admit to being a bit stung by the "overgeneralization" part, because anyone that knows me knows I am well aware of every nuance...but  in science these days, you win some you lose a lot more than some. The reviewers made good points, I just tried to go heavy on the outreach part of the grant and had to sacrifice some science to make the page limit. I would have also liked to have had some more preliminary data under my belt (KOs of some of the genes and phenotyping), but right now I've got two very capable undergrads working on that for next year. C'est la vie.

So, as a resource for everyone out there:

There were a total of 36 grants in my panel, MCB Genetic Mechanisms. 1 was ranked High priority, 21 (including this one) were ranked Medium priority, 10 were Low priority, and 4 were Non-competitive.

My grant can be found here
Reviews of the grant can be found here

Tuesday, September 16, 2014

My daughter's first birthday

One year ago I was sitting in a hospital room holding my daughter for the first time. That feeling was incredible and she has made the last year of my life indescribably happy. The last year of my life has also coincided with my fourth year as a PI. This blog is a product of me wanting to sit down and reflect on how those two parts have intersected. Everyone will obviously have different experiences, and the experiences will change from place to place, but I wanted to provide a bit of an optimistic view on an academic family.

1) I am my own greatest enemy

Through grad school and my postdoc, I always wanted to work as much as possible. Research felt a bit like a competition and I figured the more time I put in the more I would get out. I wasn't necessarily wrong, but I did get a bit burned out at times. The most difficult feeling I've encountered since having a munchkin is that it's inevitable to feel like you aren't accomplishing as much at work as before. Truth is you probably aren't. I quickly started to view this feeling like I view my own impostor syndrome though...that little voice is always going to be there no matter how much I work, so I might as well be satisfied with what I do get done. Each institution has its own bar for "good enough". My guess is that this bar is lower than the one in my own head. This has by far been the best year I've ever had for publications and grants, and that has to be OK. If it's not, then c'est la vie.

2) Efficiency and saying no are key

I had to be more efficient to survive if I was only on campus for X hours a day. I figured out what I could get done at home, and what I could only get done at the lab. I learned how to work from home and became quite good friends with Arizona's VPN system. While I highly valued walks around campus for getting my thoughts straight, I don't really have time for this anymore and found other ways. I became a much better planner than I was before. Although I spent less time preparing for lectures, I still managed to relay all the information I wanted to (I think). In class, I tried to limit the emotional energy spent on students to a realistic level and set up firm boundaries (no responding to emails after 6PM or before 9AM). I gave more online quizzes to limit my grading by hand. I actually said no to some reviews. There is only so much time in a day and I learned how to cut unnecessary expenditures, because that's what had to happen. You have to make sacrifices, the key is learning and cutting out superfluous actions.

3) Your community is key

I won't go too much into it, but both my wife and I worked full time during this last year and somehow managed to avoid daycare. She is, quite frankly, a superwoman. 

I also wouldn't have been able to survive the last year without the support of my department. They value my contributions, and understand my need for work/life balance (as far as I know, check back in two years when I'm up for tenure). Arizona even started granting paternity leave last year. I don't know how it is other places, but I can only hope that the tide is turning like this. 

I've also been able to survive because I've lucked out and had very good people in the lab. I've tried to embrace an environment where the only metric for success is having a set of goals and hitting certain checkpoints rather than working a specific number of hours. I don't question vacations or time spent with families, and magically enough we still come up with really good data. I fight for them whenever I need to. They know what I expect from them, and I know what they expect of me. I give everyone a lot of rope and foster independence. This certainly doesn't work for everyone, but it's the only way I can survive as a PI. 

4) Sleep is not overrated

When there is an infant in the house, your sleep patterns go out the window. This translates to a lot more spelling mistakes in documents (and lectures!) and a much lower tolerance for the everyday BS you deal with in academia. My advice is to proofread documents first thing after sleeping or a nap (or get others to proofread). My other advice is to try the best you can to avoid saying things you shouldn't while sleep deprived, even if you're teaching a class of 100. You'd be surprised how some of your comments are actually interpreted by the students, so it's better to just shut up. 

5) The fringe benefits of a munchkin are awesome

Research is hard. Our lives are filled with rejection day in and day out. There is no better cure for rejection emails than coming home and playing with my daughter. Absolutely nothing. Her little smile puts everything else into perspective.

Wednesday, August 27, 2014

Bacterial Genome Size and Ecology

 I often find myself wondering about general evolutionary pressures that shape bacterial genome sizes, and I'm going to use this space to try and crystalize some thoughts. Part of this is motivated by my interest in understanding how horizontal gene transfer affects adaptive trajectories (see here), and part is motivated by trying understand how to define (and what actually structures) bacterial populations in the context of ecology and selection (see here). In the latter case, Monod's famous quote doesn't necessarily hold true...if you wanted to define an elephant population you could go out and count them. This is sadly getting easier and easier every day. For bacteria, you can't go out and count total number of cells because micro-environments matter and all cells don't experience the same selection pressures. Chemical, geological, and biological gradients are much coarser for elephants than E. coli and this can be reflected in population subdivision. These kinds of questions don't really matter if you care solely about presence/absence of organisms...but if you want to try and predict evolutionary dynamics (strength of genetic drift, etc...), you have to understand what defines population size. This whole introduction is just a long winded way of introducing an interesting idea that has popped up across a couple of papers and lately in discussions I had with Steven Nayfach (from Katie Pollard's lab) over sushi. Can we use differences in average bacterial genome size across environments to say something about microbial ecology?

Bacterial genome size vs. number of annotated genes, from Wikipedia

Small Population Size + Host Association = Small Genome

Obligate microbial symbionts often have tiny genomes compared to free-living ancestors. This is due to the absence of purifying selection on genes no longer necessary within this symbiont lifestyle, an increase in effects of genetic drift due to small population sizes, and a slight deletion bias in mutations throughout the genome. Basically, when genes are no longer necessary in small populations they can accumulate and fix more mutations randomly, and these mutations tend to biased towards deletions. When vertical transmission is assured, all genes necessary for survival outside of this transmission cycle become superfluous. We see parallel increased rates of gene loss and inactivation (and overall smaller genome sizes) in some free-living bacterial pathogens as well with similar population size / relaxed selection explanations. For these cases, genetic drift is a key factor.

In terms of defining ecology, if you find a particularly small genome in your sequences with lots of pseudogenes, you might be able to a priori guess that this bacterium has particularly low effective population sizes and may be a parasite.

More DNA is Costly = Selection for Small Genome

Although patterns of genome evolution in symbiotic bacteria are likely driven by genetic drift, there are cases where selection appears to directly drive genome minimization. The best known example of this is referred to as "genome streamlining", and is seen in a wide variety of oceanic bacteria including the notorious SAR11 clade. These genomes are typified by a reduced but highly conserved core gene repertoire, a reduction in paralogs, and a reduction in intergenic spacer regions. Non-mutually exclusive explanations for such selective pressures include low Nitrogen and Phosphorous levels within the ocean (making extra DNA energetically costly) as well as optimization of cell surface to volume ratios. The cell surface / volume ratio theory is particularly interesting because it parallels discussions of genome size evolution all life (termed the C-value paradox). How are cell size and DNA content related...well, DNA takes up space and the more DNA in a genome the larger the cell size. An aside: there's scarce evidence that DNA replication is costly for bacteria across a variety of other environments where transcription and translation are thought to be the most costly processes.

So if you find a particularly small genome in your sequences (regardless of environment) with little evidence of genetic drift (low number of pseudogenes and low mutation fixation rate amongst core genes) it might be evidence of selection acting on genome size. This could in turn indicate competition for a scarce nutrient that makes up DNA or necessity of transport across cell membranes.

Evolutionary Correlates of Larger Genomes

It's possible that increased genome size can be selected as a correlate of cell size. I don't know of any cases where such selective pressures have been directly demonstrated in bacteria, but the correlation between DNA content and cell size certainly appears to hold true. That's not to say that there are other emergent ecological properties that could also select for larger genome sizes. As long as DNA isn't too costly (an important caveat), in variable environments where cells must be capable of metabolizing a wide range of compounds, genome size can increase as additional metabolic pathways are acquired through horizontal gene transfer (here and example here). These extra pathways can keep accumulating as long as they aren't selected against too strongly (which, you guessed it, is going to be dependent on population size). Just a correlation at this point as far as I know, but many "soil" bacteria have relatively large genomes: pseudomonads, Burkholderia, assorted Rhizobia, etc...*

It's also possible that emergent evolutionary properties will arise as genome size passes a specific threshold. Since the success of long-distance horizontal gene transfer increases with genome size (that's a bit circular, but them's the data....could also be confounded by observation bias and correlated to environmental proximity), but it's possible that free-living bacteria with larger genomes undergo fundamentally different evolutionary dynamics than free-living cells with smaller genomes. Likewise, cells with larger genomes appear to grow more rapidly than those with smaller genomes. This might be due to number of ribosomal operons but also to the presence of multiple large secondary replicons in bacteria with larger genomes (the more replication forks there are, the faster total genomic content is replicated). Bacteria with larger genomes might also be able to better tolerate secondary replicons like megaplasmids, which may again fundamentally and qualitatively shift phenotypic and genotypic evolution (here and here). We like to think that everything that is true for E. coli is true for Pseudomonas, I'm not so sure given possible evolutionary feedback loops that are correlated with genome size. For instance, you see a lot more megaplasmids in Pseudomonas.*


I'm definitely missing some citations and angles on this, so please feel free to point me in any relevant research direction. It's an interesting idea to imaging extrapolating ecological data and evolutionary trends from differences in average genome size across microbial populations. There are a couple of papers I've stumbled into that try and to just that. There are probably a lot more out there...

Wednesday, July 9, 2014


"Everyone has a plan, until they get punched in the mouth" - Mike Tyson

The best thing you can do when preparing to transition from postdoc to PI is plan out 5-year research goals. Talk with your postdoc advisor about what projects are yours, think about what questions you are interested in, design experiments to test these hypotheses, and make lists of every construct you need to create or reagent you need. Even though everything around you will be moving quite quickly, there will actually also be some time as you are setting up the lab to just sit and think. We often get asked, if there were unlimited funds, what kinds of experiments would you perform? Starting a lab with a pool of undesignated money (startup) will likely be the closest you will come to this "do any experiment you want" utopian world. I didn't realize the full weight of this until my startup ran out, but having a pool of money for which you don't have to specifically justify each experiment a uniquely powerful situation.

It's great to hit the ground running with a definitive plan in hand, but always keep in mind that the real world can intervene. Many people I've sought advice from over the years have suggested the importance of having multiple lines of research within the lab at any given time. Don't be wed to a single question or system, especially in times like now when funding is tight. Keep reading and don't be afraid to try new assays or experiment with different systems. The early years of your lab, startup money in hand, may be the best/easiest time to branch out and ask completely new questions. However, the flip side of having multiple irons in the fire is that juggling experiments requires a skill not easily learned. While it can be quite easy to dream up the "next" experiment, it's often difficult to know when it's time to pull the plug on failed projects. Sometimes it's just a gut call. At least IMHO, knowing when to stop a particular line of research is one of the most intrinsically important skills for being a PI.

I started my lab with ideas for "easy" projects that would be straightforward extensions of postdoc experiments. After moving from North Carolina to Arizona, I realized that my bacteria and plants didn't behave the same in the dry air of Tucson as they did in soupy Chapel Hill. It was frustrating to say the least, and I was stuck with the decision to slog through and figure out a way to carry out these experiments or to cut bait and try a new direction. I moved the plant based experiments somewhat to the backburner, which is a bit tricky because I'm housed in the School of Plant Sciences, and decided to focus on investigating interactions between microbes. We just started reading papers and trying stuff, building off of research interests shared across all lab members. Looking back (over the last four years), there have been a lot of starts and stops, but I'm quite happy at how things are turning out. There are still experiments that I know I could get to work given more money and time, and strains sitting in my freezer for experiments I haven't come close to trying yet. These side experiments fail much more frequently than they work, but you have teach yourself to do the cost/benefit analyses to know the difference between when to stick it out and when to move on.

All of this in mind...a brief sidenote. As I mentioned above, you will never be as free to experiment as when you have startup funds. The tendency can be to bring in people (technicians/postdocs) to carry out exact experiments written down in your 5-year plan. Although this may work in many situations, I made a conscious decision to do the opposite. I tried to hire independent postdocs whose interests overlapped with mine, but who wanted to branch out into completely new research directions within the context of my lab's interests. At the outset I had no clue how this would go, and there were certainly some nervous moments. Looking back, I can honestly say that this plan worked out about as well as possible. We have developed numerous new research directions and both postdocs have also contributed greatly to more "basic" projects. For the young PIs, don't be afraid to leap in directions that are uncomfortable because you might just find yourself in interesting new places. For the postdocs, given the lack of funding opportunities, don't be afraid to find your way into the labs of young PIs. They will often have freedom to spend money whatever way they chose (unlike if you are brought in on a grant), and you might have a greater chance of developing your own independent research programs.

Thursday, May 22, 2014

Causation, Correlation, and H. pylori

Thanks to the end of the spring semester, I finally have time to sit and get some thoughts down. This post was specifically motivated by a couple of recent items that have been making their rounds on the internet. The first of these is a new book and associated book tour by Dr. Martin Blaser entitled "Missing Microbes: How Overuse of Antibiotics is Fueling our Modern Plagues". While I haven't read the book yet (but plan too on a couple of upcoming cross country flights), I have seen a couple of interviews with Marty. Without saying much else, to my microbiologist ears some of these interviews have been filled with a little bit too much hyperbole. I say this carefully as I have an immense amount of respect and admiration for Marty as a scientist. I also say this knowing that some believe the only way to draw public attention to the problems of antibiotic overuse is to stand up confidently and surely and overemphasize solidity of the scientific basis for these arguments.  It's quite OK if that is your viewpoint, although on the other hand this same logic has fueled a campaign of mistrust of climate scientists over global warming. Since I worked with H. pylori (HP) during graduate school, have been in the HP literature, and since I've had some conversations with Marty, I've been thinking about the topics of his book for a while. Hopefully I can provide a slightly different yet still enlightening viewpoint. In my mind microbes rule the world and overuse of antibiotics is a horrible problem of modernity, but some nuanced, yet key, points have been glossed over in the media coverage. Won't say too much since they're pretty self explanatory, but the second motivation for this post was a brilliant set of spurious correlations.

So let's dive in to the nougat of some of Blaser's arguments using published articles. Helicobacter pylori is a well known human pathogen and causative agent of ulcers, chronic gastritis, and stomach cancer. A Nobel prize was even awarded to Drs. Marshall and Warren for demonstrating this link to gastric disease. The estimated number of infected worldwide is 50%, which I 'm pretty sure is required citation in the introduction of every HP article. This is a pretty old estimate, however, and I'm not sure it's still that high (not going to go there in this post). Of that 50%, only a small percentage (~10% is a number that seems to pop up a lot) actually develop gastric disease due to HP. By these numbers, there are a significant amount of non-disease causing infections, and this has partly contributed to the speculation that HP might have some benefits to humans. It's likely that every mammal has some kind of Helicobacter if you look closely enough, but HP seems to only naturally reside within humans. There are also other species of Helicobacter that infect humans. There are few if any natural reservoirs of HP other than humans (it really doesn't survive well outside of hosts, although researchers are always looking and occasionally find interesting leads), and HP has been associated with humans for pretty much as long as there have been humans. Given this information, there is a lot of fodder for thinking that HP might have co-evolved with humans and to potentially help humans. The data, and our understanding of evolution, doesn't necessarily back this idea up.

I'm going to focus on asthma, but for the most part any other "benefit" of HP you may stumble across falls into the same explanatory ballpark. There does seem to be a negative correlation between HP and asthma (more HP, less asthma) as well as links to immune responses. HP also appears to protect neonatal mice from asthma in relevant model systems.  I'm not going to dispute these pieces of data, the work is pretty solid, but it's unclear what else correlates with these observations. Those that grow up in first world countries grow up in a much cleaner environment than their ancestors. There is a growing body of evidence that animal and plant (unpublished but it's coming) immune systems need to be trained by some microbes while developing. Therefore, growing up in more "sterile" environments could lead to immune disfunction. This line of thought has been crystallized in the "hygiene hypothesis". HP is likely disappearing in frequency due to modern living, but so is our exposure to other microbes. It's tempting to focus on associations between HP and asthma, but such correlations could be explained though the loss of other microbes (singly or as flora). The article I linked to above didn't test other members of the microbiome or gastric pathogens for the ability to tone down asthma, and it's unclear whether living or dead HP would suffice for this effect. I also want to point out that the main pathogenesis factor identified for HP in the gastric environment (CagA toxin) is not required for asthma protection. There's some smoke there, but there are a lot of other possibilities that could explain correlations between HP and asthma. Moreover, and this is total handwaving speculation, but if it's just the antigenic effects of HP that matter immune responses we may be able to just synthesize an antigen pill or vaccinate to replace the effect.

I also want to touch a bit on the idea that we are driving "good" microbes extinct with antibiotics. While it's clear that antibiotic doses certainly alter our microbiomes temporarily, it's unclear whether any microbes are truly going extinct. Current data supports the idea that the human microbiome is fairly resilent to change. That is, if you perturb the microbiome (say with antibiotic doses) it tends to bounce back into shape given enough time. Since very few of us are on constant antibiotic doses, it's still unclear whether there is a huge change in your microbiome over the course of your life or through multiple random antibiotic treatments. Of course, while acute infections by pathogens like Clostridium difficile can occur if you clear out most of your resident microbes, these situations seem to be cured through exchange of microbes from other sources. It's also important to keep in mind that it appears to be very difficult to drive microbes to extinction in any instance. We've only eliminated two pathogens in nature through vaccination regimes during the course of modern medicine, rinderpest and smallpox. There is no reason to believe overall selection pressures to develop antibiotic resistance are any different across bacteria, and we worry (rightly so) about multi-drug resistant bacterial pathogens. Why would antibiotics only selectively kill the good guys?

Lastly, a point on Human-H. pylori co-evolution. HP might very well affect the incidence of asthma (or other chronic disorders like Crohn's disease) and such chronic situations can make our lives very, very difficult. When researcher's speak of "benefits" of microbiota, they are implicitly speaking about co-evolution. For instance, since X bacteria does Ygood,  this relationship has evolved to be beneficial to humans over time. This equation is leaving out discussion of an intrinsically important metric, human fitness. While evolution can discriminate between very small fitness differences in human populations, I'm going to go out on a limb and guess that asthma has not been a huge selective force throughout the course of human history. Fitness is all about your offspring surviving, and while asthma may make like a little more difficult, there is no evidence that chronic conditions such as asthma really and truly affect human fitness. In the absence of a fitness effect, it's impossible to have co-evolution. I may be completely wrong about this (and if I am, please point me towards the data!), but in the absence of changes to human fitness a lot of these microbiome links become just-so stories.

One story to finish this piece off....I started working with H. pylori in 2001 in graduate school in Oregon. It wasn't until Spring of 2004 I had my first asthma attack. Was it HP that gave me asthma, or was it the constant flood of pollen from very frisky trees? It's an N of 1, but at least in my case there is a positive correlation between HP and asthma.

Tuesday, February 25, 2014

How I became an evolutionary biologist

I was asked on twitter last week how I decided to study evolutionary biology, and what actually motivates my research. The story is a bit more complicated than can be parsed in 140 character bits, so here's a slightly longer version of it (the short version as relayed in <140 characters is simply "Lenski").

When I started graduate school at the U of Oregon, I wanted to study ecological questions in large charismatic megafauna (I imagined myself roaming around the African savannah chasing elephant or rhinos. cynical viewpoint: this job is now much easier and sadder than it was 13 years ago). I started as a pre-med undergraduate motivated by a certain tv show about emergency rooms, but quickly discovered that I didn't want to go to med school. To put it bluntly, I found myself worrying about how getting a "B" on any test would kill my chances at med school. As class sizes dropped I also found myself surrounded by larger percentages of hyper-competitive students with that same "B=death" mindset. Parallel experience...I worked as an intern at Aventis making flu shots during the summers of my sophomore, junior, and senior years. The money was great, but the industry life (at that moment) didn't really click with me. I made my mind up to go to grad school for biology, with an interest in animal ecology. At this point I distinctly remember applying to Liz Hadley's lab at Stanford (and bombing a phone interview), emailing John Ford about orca research at UBC, and being denied acceptance at the University of Arizona (that last one is particularly awesome looking back). I also looked at working with Nick Gotelli at the University of Vermont. From what I could tell, Oregon offered me the best opportunities in terms of money and research experiences so I picked up and moved to the west coast. Truth be told, I was hoping that I could somehow swing a research project into the ecology of sea otters.

I was fortunate enough during my first year at Oregon to rotate through three very different labs. I had written a senior paper on zebrafish genetics (I was particularly drawn to a bunch of blood mutants with names like vampire and vlad tepes) and, despite my dreams of ecology, signed on to rotate through John Postlethwait's lab under the direction of a young postdoc named Bill Cresko. During that rotation, I found myself learning all about things like evo-devo, PCR, and fish called stickleback. There was an incredibly good zebrafish/stickleback group at UO buoyed by an IGERT program to study Evolution, Development, and Genomics. As an undergraduate it had actually never occurred to me that you could study evolutionary questions using genetics. Sure I knew that evolution was pretty solid scientifically, but I didn't have an intuitive feel for how you could design experiments within an evolutionary framework. Looking back I remember being blown away that there was a journal called "Evolution" and that you could publish about things like genetic variance in wolves. This rotation in John's lab had changed my way of thinking. That first rotation got me hooked on the power of studying genomics and evolution, but I wasn't sure I wanted to work on fish. It also dawned on me that I wasn't made for camping out in the African savannah (I'm a fan of things like lattes and daily showers) and that I wasn't completely sold on the ability to control ecological experiments (for me, too much worrying about how the environment can shift results...too much rain in one year vs. the other and whatnot and having to control with statistics post hoc). My second rotation was working with Bitty Roy on molecular typing of some kind but I couldn't get the assay to work for the life of me. My third and last rotation was with a new PI in the Institute of Molecular Biology at Oregon, Karen Guillemin working with the bacterium Helicobacter pylori. I was still fighting some psychological battles against working with bacteria given my premed and industry training, but some times you can't deny your true research interests. Even though we were all kind of learning on the job, Karen was an amazing advisor for the cadre of young scientists who joined her when she started her lab. It was a great group of people, and those interactions are largely why I grew to love science as much as I do. 

Karen wasn't directly working on evolutionary questions at that time. Her work was focused on investigating virulence factors within H. pylori as well as establishing a gnotobiotic zebrafish facility. When this third rotation started I happened to read a paper out of Rich Lenski's lab on evolution of E. coli. Like many young kids, and in addition to dreaming about chasing rhinos, I had also once dreamed about being an archeologist. Digging through history, understanding the past from what remained, it felt like one big entertaining logic puzzle. Reading Rich's paper it dawned on me that I could study genetics and evolution together in real time in bacteria. In reading further papers I found myself drawn to studying questions about horizontal gene transfer and how this affected evolutionary rates. I don't quite remember when, but there was a lightbulb moment when it dawned on me that I could use H. pylori to study how natural transformation affected rates of evolution in bacteria in real time a la Rich Lenski. I could freeze the cultures and actually measure adaptation. It was so clean an elegant and, unlike my thoughts about what I was reading in ecology*, I knew I could control many aspects of the environment. Furthermore, I was able to be co-advised by Patrick Phillips, who is completely different than Karen as an advisor but equally awesome as a mentor. Patrick works mainly on nematodes, and even tried to get me to study nematode trapping fungi as a system (almost worked!), but was also completely willing to help guide Karen and I through evolutionary experiments. They both gave me enough rope to explore, but pulled me back when I was going too far off the rails. Exactly what I needed to channel my energy in grad school.

So what draws me to study evolution? Being able to hold adaptive potential within your hand. Not knowing exactly how different populations will play out, but knowing that adaptation will occur. The lure of letting nature tell you what's going on at both molecular and genetic levels...experimental evolution is a great way to figure out new ways that proteins function or interact! Studying evolution within bacteria enables me to ask a variety of questions and constantly be amazed and surprised (and at least in some cases in bacteria to perform those experiments overnight). Once you understand how evolution works, you see interesting questions in every research area. While it took me a while to convince myself of my true research calling, I can't imagine it being any different now.

*Two points to be made here in a prologue A: Please don't read this as a slight ecologists. I respect the hell out of everyone that studies ecological questions, I'm just not wired to do that kind of research full time B: I learned quickly that "control" is relative in the context of growing bacteria

Thursday, November 21, 2013

So you want to do "experimental evolution"

Rich Lenski and his lab are getting a lot of well deserved publicity lately because they have published yet another awesome paper from their long term evolution experiment (LTEE). The success of the LTEE has no doubt sparked a bunch of researchers out there to go "hmm...I can do that!". I'm guessing that I was in third grade or so when Rich started the LTEE, and I have only been tangentially associated with the Lenski research lineage (who in my own experience are as smart and helpful as their mentor), but I've set up long-ish term lab passage experiments a couple of different times with different systems. There are a few things I've learned along the way that I think would be helpful to share with others jumping into the experimental evolution game, and hence this post. Please feel free to add suggestions to this list, or to contact me off-blog if you'd like to talk shop. The best tribute I can have for Rich is to provide as much help for the community as he and his students have for me over the years. I say this every time, but thank you very much!

1. Let the question guide your experiment.  We all have our favorite microbes (OFM), and the reaction that I've seen time and time again is to want to perform an evolution experiment with OFM just to see what would happen. I can assure you that OFM will evolve and adapt to passage conditions and will do so quickly, but what does this really tell you? My first piece of advice colors everything from here on out, and it's to focus on finding a question to ask and only then find the best microbial system to work with. E. coli works great for understanding general evolutionary principles, and in fact one of the most important questions to ask yourself should be "why not do this with E. coli?", but this would be a terrible system to study sporulation. Find the question that excites you and then find the system, it's easy enough to set one up if you know what to look for.

2. Once you've got the system, make sure you can measure fitness. A major piece of the LTEE is the ability to compare phenotypes and genotypes of cells from one generation vs. all others. For any evolution experiment to work, however, you need to be able to demonstrate that that evolution takes place. Competitive fitness assays are just one way to do this, but they are a very powerful test because they enable direct comparisons between strains. In order to carry out competitive fitness experiments, you need to be able to distinguish two strains from one another within a single culture under conditions that closely approximate passage. Rich's experiment directly competes strains that differ in arabinose utilization (Ara+/Ara-), which under the correct plating conditions enables you to visualize different strains by color (red/white). In many cases, such a simple phenotypic comparison isn't easily accomplished. In my first stab at an evolution experiment I was investigating the effect of natural transformation in Helicobacter pylori. Out of necessity, I designed my competitive fitness experiments slightly different than Lenski's because I was using antibiotic markers. Instead of directly competing evolved strains against each other, I would compete evolved strains vs. an ancestral "control" strain which was doubly marked with kanamycin and chloramphenicol. This isn't quite as elegant as I'd like, but I wanted to avoid confounding my evolution results with compensation for these phenotypic markers (in Rich's case, he spent a lot of time demonstrating that the Ara marker is a neutral change under his passage conditions, this often isn't the case for antibiotic resistance). At first I simply tried to plate out the same competition onto non-selective media and kan/cam media, but found that the variance in ratio of evolved/control strains was way too high to be reliable for fitness estimates. For instance, in some cases there would be more colonies on the kan/cam plates than on the non-selective media. To get around this issue and control for such plating variance, I decided to first plate the competition out on non-selective media and then to replica plate to the kan/cam selective conditions. This change allowed me to actually measure fitness using antibiotic markers and all was happy and good for the time being.  It completely sucked to replica plate everything, but it was the only way to get reliable numbers.

3. Carefully think about your passage conditions.  When you are performing a passage experiment, EVERYTHING MATTERS. Are you going to passage under batch culture conditions where there are such things as lag/log/stationary phase, are you going to passage in a chemostat, are you going to passage in vivo, etc...? Every change you make to your passage conditions can affect the results in subtle or not so subtle ways as selection will operate differently under different conditions. If you are passaging in vivo (mouse, plants, whatever), how do you control interactions between other microbes and your targets of interest or sample your focal microbe for freezing? Even the way that you passage your microbes in vivo can change selection pressures. For instance, motility will be a target of selection if you simply place your microbes on a plant leaf and select for infection BUT if you inoculate a leaf with a syringe (bypassing the need for microbes to invade), motility likely doesn't matter at all for infection and my guess is that you'll quickly get amotile mutants. Along these lines, always try to set up cultures using defined media even if you aren't quite sure that all components are necessary (plus, if you carry out LTEE long enough, cool things happen with the "unnecessary components"). With my H. pylori cultures, applicable to passage experiments with many pathogenic microbes, I was forced to use media which contained fetal bovine serum (FBS). The problem here is that every batch of FBS is different because every calf is different! I no doubt missed out on some fine scale evolutionary events simply because my H. pylori populations adapted to growth in different batches of FBS. LB is a little bit better, but remember that a major component of LB is actually yeast extract which can differ significantly from batch to batch and company to company. Something else to keep in mind is that LB media and other types of rich media provide a wider range of niches than defined media which can promote crazy scenarios of dependence between microbes (such as acetate cross-feeding).

What is your dilution factor going to be each passage? Even though effective population sizes are calculated based on harmonic means, differences in dilution can change evolutionary dynamics within cultures. Passage to densely and your cultures will spend more time at stationary phase than if you passage less densely (unless you time things perfectly). I always try to find the dilution scheme that allows me to catch ancestral populations just after they've started to hit stationary phase at some multiple of 24 hours. For H. pylori a 1:50 dilution achieved this every other day, for Pseudomonas stutzeri (in my experiment) a 1:1000 dilution achieves this every other day. I can't emphasize this enough, for your own sanity you want to design the conditions so that you can come in and passage at regular intervals!

4. How will you archive your populations? Another powerful characteristic of the LTEE is the ability to freeze populations to create a "fossil record". Carefully consider how frequently you want to freeze, and how much of a population you will freeze. The answers here will depend on the hypothesis you are testing. For frequency, consider that frozen cultures take up space that your PI can't allocate to other projects. One of my graduate school advisors still (maybe) has my H. pylori populations frozen down in her freezer (Sorry Karen! We're BSL2 now and I can finally take them off your hands!) even though she is not working with these lines anymore. As the generations pile up, you have to allocate more and more space. As for how much of the population you'd like to freeze, just remember that unless you freeze the whole culture you will be losing some of the population. This doesn't necessarily matter for high frequency genotypes but it does for the low frequency variants. Think of this as a good example of human influenced genetic drift just like an actual passage.

5. Catastrophes will happen. You can have the best planned experiment in the world, but that doesn't prevent your lab mates from "accidentally" (shifty eyes) knocking over your cultures. Before you start, make a plan for what happens if you lose a passage or if your freezer melts. For me, I always keep the previous passage in the fridge until the next passage is complete. Sure, it's a slightly different selection pressure than constant passage...but so is going into the freezer stocks. Also remember that catastrophes happen to everyone, even Rich Lenski, and it's a part of science. It sucks at the time, but exhale and move on. Trust me, you'll be much happier in the end.

6. Can you tell if you've cross-contaminated your experimental lines? Trust me again on this, cross contamination happens so figure out ways to identify it. I always try and alternate between pipetting and passaging phenotypically different strains. For H. pylori this meant having one set of strains be kanamycin resistant while the other set was not (had to perform an extra experiment after the fact to control for this difference). However, I was able to spot one instance where one of the lines had a low frequency of kanamycin resistant colonies. In the final analysis I threw out this line, which is why there are only 5 competent lineages in my Evolution paper. You might say "well Dave, I'm not that sloppy in the lab". That could be a very true statement, but I guarantee that if you run the experiment long enough you will have other people perform the passages. People make mistakes when they aren't as invested, haven't designed the experiments, and are reading from a written protocol. They don't mean to, but it's a fact of life.

7. Be curious. I suppose this works for every single experiment ever done...but curiosity is one of the most important characteristics for research. You will grow to love your cultures, to see them flourish and change. If you understand what to expect from your cultures, you can identify interesting yet unexpected events. Know what to look for and note any changes from this search image. That's where you find really cool results.

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