Wednesday, July 9, 2014

Flexibility

"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.

Wednesday, November 13, 2013

Should I go to Grad School?

Given I live in a desert which -- for the most part -- lacks colorful deciduous trees, the one way that I know it's fall is a flurry of activity concerning grad school applications. Since I teach an upper division core class for microbiology majors, I often get questions from students about what to do after undergrad. The first thing I tell them is this: The one burning memory that I have from graduate school is from sometime in the spring of 2004. It was my third year and I distinctly remember getting hit with the combination of relationship problems (long distance girlfriend and I finally broke up) and the 3rd year grad school treat of having a bunch of experiments with no hope of any successful results. Everything was so confusing. It was 2am, I was in the lab on a Saturday, the only car in any of the parking lots outside was my own, what the hell was I doing with my life? I sat there on the floor of the lab and cried. Seriously...even went fetal position a couple of times. With the perspective I have now, and looking back on all of my 5 years in graduate school, I can honestly say that getting a PhD sucked. It was a slog, a war of attrition. There were so many times I wanted to quit...BUT it was also one of the greatest experiences in my life. I don't regret any moment of it, and would do it again and again and not change a thing.

Why did I stay with graduate school? I had other options, I was a decently compensated intern at a pharmaceutical company all throughout undergrad and had gotten offers to remain on but turned them down. The 9 to 5 life and a daily routine wasn't for me. Sure I was turning down a good job, but I knew deep down that I'd be much more happy as a university researcher. I just always knew that I got bored with routines, with dealing with the same problems over and over again. Industry jobs seemed like scenes from the movie Groundhog day (I'm not entirely right or wrong about this). It seemed as though a job in academia would bring different challenges every day (and it certainly does). I wanted to be challenged, constantly, always from different angles. I knew that that kind of changing landscape of problems is what satisfies my brain.

It was during my time as an intern that I realized I really enjoyed asking questions, finding out how the world worked. I knew I didn't want to go to medical school, and graduate school just seemed like a good way to continue learning about the world. I remember being amazed that I could actually get paid (not a lot by comparison to other things, but enough) to go to school!!! I still can't believe that there are actual jobs that pay me to learn about the world and share what I learn with others. During my first of second year in grad school, my view of life solidified completely. It was at this point that one of the experiments I had thought of and designed actually worked. There I was, the only person at that moment in time that knew a new fact about how the world worked. It was thrilling, it was addictive...there is simply nothing like the rush you get when you get new experimental results. Sure, the paper that came of this experiment was pretty niche, but I was hooked. It's a combination of all of those feelings that helped me stay the research course even when things looked so incredibly bleak.

So should you go to grad school? It's definitely not for everyone, and as I say above, it really really sucks sometimes. It's simply a personal decision that I can only provide one perspective on. Every department and lab is different, and it's up to you to find a place to thrive. You have to find ways to motivate yourself to keep putting one foot in front of the other, to continue performing experiments even though 95% of them fail. Starting in grad school -- and continuing throughout academic careers -- you are surrounded by rejection. Rejection is never fun or easy, but over time it becomes easier to deal with.

I didn't think I'd make a ton of money with a PhD, I didn't even know if I'd eventually have a job. To this point there are a couple of things I can say now that I didn't know before 1) it's much easier to get an industry job with a BS or Masters than a PhD (companies can hire people and train them the way they want) and 2) it's easy to start out as a Masters student (or PhD) and upgrade to Phd (or downgrade to Masters) so your path isn't set the moment you start grad school. I didn't know what I wanted to do with my PhD when I started grad school (in the beginning I didn't think I'd actually be good enough at research to be a PI), but I knew that I enjoyed learning. My love of learning kept me motivated.

You don't finish grad school, you survive grad school. Your job as a graduate student is to make mistakes and to learn how to avoid making mistakes in the future. Your job as a graduate student is to consume every possible piece of information you can and learn to filter out good from bad. Grades really shouldn't matter to you anymore (in fact, if you can, take every class Pass/Fail). Classes are there not to prove that you can get an A, but to give you an opportunity to truly internalize relevant information. As a grad student you are much more likely to figure out some very small thing about the world that only a handful of people really care about, and that leaves your mom to question why you aren't a REAL doctor, than you are of actually making difference to human health. That's OK, it's all about building a foundation for the future wherever that may lead.

Looking back, there is one extra unexpected bonus that made graduate school worthwhile. Apart from the rush of science and research, grad school happened at a time in my life when I was truly becoming who I actually am as a person. I had moved across the country from NY to Oregon, and had started a life completely on my own away from the training wheels that undergrad life can bring. Some of my best friends to this day are people from my grad school cohort. People who were always up for a beer or pizza, people who shared similar experiences to me growing up as a bit of a science nerd. People from all walks of life, with very different perspectives, who nonetheless all found ourselves diving headfirst into research. I would be a very different person if I did something other than graduate school, because that was the moment in time when I really ventured out from the nest.

Grad school is one of the most difficult things I've ever done, and it's not for everyone, but for me it was completely worth it.



Friday, November 1, 2013

Replication and Studies of Host-Pathogen Relationships

There has been a buzz around the interwebs (and on actual paper too, so I guess it must be real!) lately about how difficult it can be to replicate published results. Much of the popular press has focused on a couple of articles from The Economist called "How Science Goes Wrong" and "Trouble at the Lab". There have also been a variety of well thought out posts from the likes of Jerry Coyne, Ian Dworkin, Chris Waters among others.

Some of the chatter has been along the lines of "BUT...REPLICATION IS A PILLAR OF THE SCIENTIFIC METHOD. THERE IS A SERIOUS PROBLEM IF MOST STUDIES CAN'T BE REPLICATED. WASTE OF THE MONEYZ!!! GRUMBLE GRUMBLE..."

At the top of this post I'm hoping to add a slightly more nuanced opinion here, followed by some unpublished results at the bottom to serve as a cautionary tale. I don't really disagree with worries about the state of science. Replication is of the utmost importance for research, and if results aren't robust there must be a way to keep track. Perhaps post pub peer review and comments will fill this particular niche. Experiments now are built on a foundation of experiments and models pioneered over years and decades. If you are interested in getting involved in a new research direction, one of the most important things to do is actually see if you can replicate foundational results in your hands in your own lab. That being said, biology is hard. Replication of single experiments under well controlled conditions can easily be thrown off by Rumsfeldian unknown unknowns. I remember hearing from someone (I want to say it was Paco Moore and that there is a paper somewhere on this which I can't find with quick google searches) that measurement of fitness in the context of Rich Lenski's long term E. coli experiment can be slightly altered by University water quality. In grad school I remember Patrick Phillips describing an experiment with nematodes where the assay would only work for about two weeks a year because the stars and sun and temperature aligned to yield the perfect experimental environment. It turns out that physiology and behavior of living organisms can be extremely sensitive to just about everything if you measure closely enough.

This problem is compounded even more when you are dealing with multiple living organisms, for instance,  when your research area is host-pathogen (host-symbiont, same diff) relationships. I can't speak for anyone that works with animal models, but I can definitely attest that plant immune responses are EXTREMELY sensitive to pretty much every stimulus you can think of. Since plant immune responses are dependent on cross-regulation across multiple hormonal pathways, even the slightest change in some environmental factors can completely shift the likelihood of infection. This is exacerbated by having to grow plants for multiple weeks before you can actually do the experiments, all the time worrying that some random lab malfunction (3am growth chamber overheating anyone?) will render batches of host plants unreliable. Different labs will have different water, soil, temperatures, humidity (low humidity in Tucson is the bane of my lab existence sometimes!), etc...When I started working on P. syringae and plants as a postdoc, I would get very frustrated at my inability to replicate other peoples published experiments. The more time I spent in the lab, the more I realized that that's just the way it is sometimes. Don't get me wrong, there are a variety of other reasons that replication may fail, but when you're crying into your lab notebook at 3am keep in mind that it's incredibly hard to control both the host and pathogen growth in the exact way that the published experiments were performed.

I'm guessing that every PI that works with phytopathogens and plants has a story where there was an interesting phenotype which couldn't be replicated when they moved to a different lab/University. As a postdoc I remember screening through 50 or so very closely related isolates of P. syringae pv. phaseolicola to look for subtle differences in virulence on Green (French) bean. The goal here was to minimize random genomic variability between strains, by choosing very closely related strains, so that I could hopefully quickly pin down genotypic differences underlying interesting phenotypic differences simply by looking at the genomes. Basically GWAS for microbes to use a looser term.  This was one of the experimental directions I started as a postdoc and was hoping to continue as PI in my own lab. One of the most solid results I had was a subtle difference in growth between two strains on French bean cultivar Canadian wonder. Canadian wonder is the universal susceptible cultivar to P. syringae pv. phaseolicola, which basically means that this plant was thought to be highly susceptible to all flavors of this particular pathogen. I had actually found that one strain (Pph 2708) grew 10-fold less than a very closely related strain (Pph 1516) in this cultivar (Fig. 1).







When I did pod inoculations, although the response was somewhat variable, there did seem to be some immune recognition of Pph 2708 compared to other strains (Fig. 2).




You can tell that there is something different in this inoculation because the water soaked halo is smaller for Pph 2708 than other strains, except for the avirulent mutant that lacks a functioning type III secretion system (Pph 1448a hrcC-).

So there it is, I've got two very closely related strains of P. syringae that slightly differ in pathogenicity. I have genome sequences for these (will link when I've stored up the strength to navigate the Genbank submission). There aren't many differences between them, on the order of hundreds of SNPs and tens of gene presence/absence. I had everything set up and ready to go to finish off the story once I got to Tucson and set up shop.

Here's where the problem arises...even though the result is solidly replicated under North Carolina conditions there is no growth difference between Pph 1516 and Pph 2708 in Tucson. A lot of strains I've worked with behave differently here in the desert compared to the land of tobacco and barbecue, and my guess is that it's because there is literally no humidity in the air. Since plant immune responses are linked to abscisic acid I'm guessing that the lack of humidity really annoys them when I take plants out of the growth chamber to perform inoculations. Not necessarily the lack of humidity per se, but the necessary change in humidity that accompanies taking plants out of the growth chamber. Yes, there are ways to Rube-Goldberg my way around this problem, and I have thought about a walk in growth chamber, but truth is other things worked better and I've concentrated on them. On top of that I'm using slightly different soil (what I could get my hands on), it's a different growth chamber, etc...Point is, I have a result that I would not think twice about publishing if only I hadn't tried to replicate this experiment in a different place. This happens a lot.

Monday, September 2, 2013

Fear and Reviewing in Academia

I've got at least two things going against me. For one, most of human communication is non-verbal. Whatever I say or write in critique of a paper is always more easily misinterpreted than if I were to say the exact same words to the authors in person. Second, it's likely that inherent biases in our brains will always influence how you read and interpret a critique. Malcolm Gladwell sold a lot of books on this premise.

Within the last year I was a reviewer on a paper for a journal where technical aspects of experiments within the manuscript are the most important factor in acceptance. As a reviewer I had absolutely no problem with the technical aspects of the manuscript, but I personally think that the introduction and discussion should be completely rewritten to de-emphasize what ends up being the take home story. I wrote that I didn't think the manuscript should be accepted in this state and suggested a variety of other ways to report and analyze the data which would allow the paper to be received by a larger percentage of the relevant audience. I was essentially arguing over subjective differences between the authors and I, even though the paper was technically OK. Ultimately the paper was published without the changes. This is how the system works, and I'm OK with this outcome (again, the paper is technically OK).

I want to be able to describe the specifics of this experience in a blog post, and maybe even a manuscript because I think it highlights one major downside of the "publish if experiments are technically OK" suite of journals. I want to write a post-publication critique of this article and include my actual review. I'm motivated enough to write a paper highlighting the dangers of crystallizing subjective interpretations in the form of a manuscript that glosses over this subjectivity. All this being said, I am currently an assistant professor on the tenure track. I don't want to make enemies, even though (as anybody who knows me will attest) nothing I say is ever meant as an ad hominem attack. I can be direct and this is off-putting to some, but I do this for the sake of making the story better (It's the New Yorker in me). I think that science advances much further without in-fighting and with colloquiality. I simply want science and research to progress in an efficient way with self-corrections of confusing statements. We can disagree, but let's do this over a beer and shake hands at the end.

Since I'm currently untenured, I'm absolutely terrified at inadvertently pissing the wrong people off and therefore tanking my career (and my family's well being). There are always camps in science which disagree with one another. Some of the best examples are described in Provine's "The origins of Theoretical Population Genetics" and Hull's "Science as a process". Ultimately, I'm OK if I'm lumped into a camp in some way or another but I want this to be for strictly science reasons not personal ones. In order to get tenure in the US, I must have outside letter-writers from peer institutions (some chosen by me, some by the college). These letters will hopefully describe how I make worthwhile contributions and further research in my area of expertise. One bad letter can tank my career. It's possible that someone may read a blog post (or critique of a paper) and simply take it the wrong way. Since I'm reviewing these papers, they are definitely within my realm of expertise, and so the authors have a chance at being selected by my higher ups as letter writers. I worry that critiquing a paper I've reviewed will be looked down upon by the editor, who in many cases is within the ballpark of potential letter writers. If I critique a paper over subjective and controversial interpretations, there are others out there who may hold the same viewpoints (who aren't authors on the manuscript) that could be off put by my critique. Letters are just one aspect of tenure. What if these critiques limit the chances of me being asked to speak about my work at conferences? What if these critiques make it more difficult for me to publish my own papers or get grants due simply to psychology? Is that risk worth it even if post-publication review might make a difference or open up an important discussion?

There are a bunch of folks that describe a utopian world where post-pub review is the norm, reviewers are always named, and reviews made public. I want to live in a world where I can sign my name to reviews and comment and critique papers in blog form or in a comment box next to the article. I want to be able to write papers with an opposing viewpoint. Often times fears of this world are stated hypothetically. I'm aching for a real and open discussion about the topics I raised in my original review, I think this would hugely benefit the field. I'm terrified, at least at this point in my young career, at what happens if I become the dog that catches the car. Maybe anonymity and pseudonyms are best for some things...

 I don't know that there is a fix because of the way human brains work.

Update: For some the comment box works, for others not so much. Feel free to email me comments and I'll post (I'm pretty easy to find).

Comment from Rich Lenski (http://telliamedrevisited.wordpress.com):

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I think there are three issues here that I’ll try to unpack.  Issue #1 is the worry over potential repercussions for your career from the authors of the paper. That’s obviously important, but let’s set it aside and look at the other two issues.

Issue #2 is that the authors of this paper ignored your useful suggestions.  Nonetheless, the paper was accepted and published.  That’s annoying.  But from what you wrote, it seems you don’t think that particular paper is a very important one in the grand scheme of science.  So I think you can let it go with respect to #2, and focus on the interesting and important work that you yourself are doing.

Issue #3 is your broader concern that journals that require only technical correctness may be weakening or diluting the scientific literature.  In that case, if you feel strongly about it, then I suggest you look for an outlet where you could write a short editorial or perspective on this issue.  You could mention that you were involved in such a situation, but there's no need to name authors or even the journal (or you might mention several journals where this is the policy).  To illustrate what you’re talking about, you could construct a strictly hypothetical case where: a paper is technically correct but ignores some issue; a reviewer asks that issue to be explicitly noted; the authors ignore the advice; and, because the paper is technically correct, the editor gives the go-ahead and it’s published.  Given all the subtleties and complexities of real science, it will probably be easier for you to construct and explain a hypothetical case than to explain the actual case that bothers you.  Plus, notice that issue #1 has gone away!


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