Bring out your dead! (so their plague genome can be analyzed)

Many of us may have had our first introduction to medieval history thought this great Monty Python movie. And as is their nature, this bit from “The Holy Grail” is pretty accurate. The Black Death, the epidemic of plague that ripped through medieval England and Europe, killed thousands of people and led to creation of the middle class (people were finally in demand once 30-60% of them died). But I digress. The reason I’m writing about the Black Death is because a paper came out last week in the journal Nature describing a new genomic analysis of bacterial DNA samples collected from infected people buried in a cemetery outside of London. There was a great summary paper published in the same issue that described what the current paper found and some of the controversies that exist between scientists in this field. I highly recommend reading this, I think it is very widely accessible. Below I discuss some of the things I learned from the papers and why I think it’s interesting. (Note: unless you have access through a university you may not be able to see the primary source paper. Hopefully everyone can get to the summary paper, though)

First, a little background. Bubonic plague is caused by a flea-vectored bacteria, Yersinia pestis. Human cases of the plague are rare but still occur (are easily treatable with antibiotics) but plague epidemics are a big problem in some wildlife populations, such as prairie dogs in the American west. The Black Death describes the plague epidemic that occurred in Europe between 1347-1351. Since the sanitation conditions in a big city like London was probably more abysmal that we can imagine today, you can expect there to be fleas everywhere. So, the main questions people studying these old strains of the bacteria are trying to answer are, Why did the Black Death kill so many people?, and Why are cases today much less severe than symptoms described during this ancient period?

Two hypotheses that tried to explain these observed differences between the 14^th century plague and cases today are that the Black Death wasn’t actually caused by Yersinia and that a more virulent strain of the bacteria was the culprit for the deaths during medieval times. The first of these hypotheses was rejected when Y. pestis bacteria was recovered from the teeth of two individuals known to have died of the plague during the 14^th century. However, some researchers weren’t convinced of this conclusion because it was very difficult to repeat these methods, i.e. it is really had to get usable DNA from human remains that are 600 + years old and make sure the results aren’t contaminated. Subsequently, if it is hard to recover samples that are in good enough condition to be analyzed, it is almost impossible, with the tools available in the early 2000s, to construct a genome with a good amount of confidence, so scientists were not able to test that second hypothesis.

Enter this new paper and new fancy technology! Researchers from Canada, Germany, and the United States began collaborating to unearth new information from bodies buried in the East Smithfield cemetery (or “plague pit” as some called it) that was used during the Black Death. Samples that had been collected and stored over many years were re-analyzed using what is called next-generation pyroseqencing. This is a really amazing method that amplifies DNA from a sample thousands of times with extreme precision. This means that even if there is a very small amount of bacterial DNA in a tissue sample, it will be amplified to the point of detection. Older methods, like PCR (polymerase chain reaction), which is still the workhorse of a lot of microbiology, were not sensitive enough to extract detailed DNA sequence information from these medieval tissue samples. So, this new analysis was able to compile this new sequence data into a genome of Yersinia pestis and compare it to modern samples of this bacteria and see how they are related.

What they found was that the ancient and modern strains of the bacteria are very similar, showing not a whole lot of evolutionary changes between the 14^th century and now. It also showed that the Black Death strain of Yersinia is probably the ancestor to modern strains, meaning that the Black Death strain of the bacteria is the source of most modern cases (see the paper for a picture of the phylogeny if you’re interested). This means that the “strain with increased virulence” hypothesis that was proposed is not supported by this data. What this suggested to researchers was that there was some kind of environmental interaction with the Yersinia infection that caused people to be much more susceptible or have more severe symptoms. This could be due to wars that were happing around this time, wearing down the men that came back from fighting. Also, there are other flea hosts besides the rats living in the city, which may change the probably transmission of the bacteria to humans if the fleas were infected from this alternate reservoir.

These findings are interesting for a lot of reasons, but some are very close to my research. First, I am planning on using the sequencing method used by the authors to analyze the bacterial communities in my ticks and rodent blood samples. Analyzing “meta-communities” is one of the main applications of next-generation sequencing because it gives you so much data on the composition, in terms of number and quantity, of microbial communities that wouldn’t be possible with previously used methods. Second, the finding that the ancient and modern strains of the bacteria are very closely related highlights how complex the pathogen-host interaction is. How a host will respond to an infection depends on a whole suite of characteristics, of both host and pathogen. Scaling up from the individual, how a population will respond to an epidemic will depend greatly on population composition, taking into account age structure, host quality or health, contact rates, and immuneocompetence. Some of these aspects may be very difficult to measure when your population lived over 600 years ago, but I bet the researchers in this field have methods they can use to figure them out. It is quite amazing what we are able to do now to investigate questions that have been unanswered for so long. And since this is a hot topic, I am sure there will be competing genomes and other analyses published in the near future.

I haven’t watched “Monty Pyton and the Holy Grail” for a long time, but I have the feeling I’ll be bringing this paper up next time. Sorry in advance to any family or friends that will have to bear with my extreme nerdyness!

A parasite more disgusting than ticks

** Warning: This post is going to maybe too gross for some people, so if you really are not too cool with parasites you may just want to skip this one (hehe).

The little white-footed mice that are the focal host of most of my research aren’t just hosts for ticks. They are the habitat for a multitude of macro- and microparasites. For instance, in our research we have collected three kinds of ectoparasites, ticks, fleas and mites. Many other researchers have studied intestinal worms, both acquired trophically (through eating infected food, like crickets), and by simple contact with worm eggs in the habitat. They can carry many vector-borne pathogens, bacteria and other microbes carried by ticks and fleas, such as Borrelia burgdorferi, the causative agent of Lyme disease, Bartonella, a flea-borne bacteria, and Babesia, a tick-borne protozoa similar to the causative agent of Malaria. And one of the more disgusting parasites that uses these mice as hosts is the bot fly.

You may have heard of bot flies in association with people coming back from the tropics with weird bumps, to then have a squishy larva pop out of them a few weeks later (see NBC story here). I had heard of them infecting primates and other tropical vertebrates, but didn’t know they were around in temperate areas as well. But, in our 2009 field season we were finding mice with what looked like tumors or extra testes (they were usually in their lower torso area). The size of the growth in relation to the mouse’s body size is pretty significant, like half the size of its torso in some cases (see below). We really had no idea what these were, so we took some pictures and sent them to John Whitaker, a mammal expert at Indiana State University. He identified the growths as bot flies right away. This year I saw a few more mice with similar infections, and one of the other researchers in my lab did too. And being nerdy scientists, we did some online searching to find out more about this gross parasite that is infecting our animals.

One of the mice we captured in 2009 with a botfly infection. Notice how big it is compared to the size of its body!

The most useful source we found was a Catts 1982 paper in the Annual Review of Entomology. It starts out with a great line:

“Maggots of cuterebrid bot flies are conspicuous, repulsive, and frequently encountered cutaneous parasites of mammals in the New World.”

I don’t know if I’ve seen the word “repulsive” in an academic paper before.* This went through a detailed overview of the life history of this parasite and what is known about different aspects of this larval and adult biology in the Americas. A drawing of a typical bot fly life-cycle is below, and is simply the adult fly lays eggs (1000-3000 per female, depending on species) usually close to host burrows, those eggs hatch into microscopic larvae when they sense and increase in temperature (a potential host), the larva get in to the host through eyes, nose, mouth or open cuts on the skin, they then migrate through the host’s body over a few days and then settle in the abdomen of the host to develop into the final larval stage. They create a “warble pore” through the host’s skin to breathe out of while developing. The larva then emerged out of the pore, develops into a pupae under leaf litter and can overwinter in this stage, and then emerges as an adult. Adults do not eat at all, they only mate and lay eggs.

Illustration of bot fly lifecycle from Catts 1982. The host is on the right side, and two alternate pathways are shown for infection (direct contact with larvae or females laying eggs on host, which is less common).

Yes, this is pretty gross and you may have visions of “Aliens” in your head right now. But surprisingly, it seems like hosts don’t suffer too many long-term effects of the infection. The Catts paper summarizes studies that found hosts have lower than usual protein levels during infection but seem to make up for the loss by eating more. The warble pore usually heals completely in a couple days with little infection, possibly due to compounds in the mucus the larva surrounds itself in.

Last week I did my last field sampling of the year and found a mouse with a really huge bot fly infection. I took a picture to show Angie, the other researcher who had found these infections while doing some mammal trapping. I said it would be really interesting if I caught the same guy again to see if the larva emerged, since it was so big already. 

Animal 595 with a big bot fly infection. The dark circle is the warble pore made by the developing larva. Hopefully you can see how huge this infection is at the time.

And, low and behold, I caught that same mouse the next day and the larvae had emerged. 

Same mouse, no bot fly. The pore is bloody from the larva emerging and his torso looks much more normal-shaped. But the mouse doesn't look too happy!

The little guy did not look like he was in good shape, go figure since a parasite the size of his torso just squirted out of him. When I released him after doing all the handling of the other animals, he just kind of sat on the ground, instead of running away quickly like they usually do. He was all hunched up and kind of wobbled as he walked away. I was even able to reach down and grab him off the ground, which I would never be able to do with a healthy animal. I am thinking he must have been in some significant pain after that lava emerged. I am hoping he is ok, after reading that the wounds heal pretty quickly. Poor little guy! But I guess since I do study parasites, I should be glad that I am studying a host that is so desirable for all these different things, and emphasizes that the host really is a community and that ecology matters at so many different levels.

* If you want to take a look at the paper, there is a lot of other somewhat non-academic language used. It’s kind of funny to see what you could get away with in older publications.

Its just Evolution, not a big deal…

I have been a bit lax on the blog posts lately due to some fall travel and trying to get lab work done before teaching gets too crazy. Speaking of teaching, that is what inspired the subject of today’s post. I will be heavier on the education (less on the musing) today because the biology majors students in our Evolution class seem to have more misconceptions on the basics of evolution than we expected. This prompted me to try to do my part to try and teach some of the non-sciencey people who read this blog a bit about evolution, maybe enough to pass on to someone else or decipher some of the spinning that happens in the popular media.

First, some basic definitions. Evolution is a change in gene frequencies in a population over time. This does not need to occur due to natural selection, it can happen by many different mechanisms. Natural selection as a mechanism for evolution describes that if individuals vary in heritable traits, and if those traits are associated with different probabilities of success in survival and reproduction (i.e. fitness), there will be a shift in the gene frequencies in the next generation to have more of the genes associated with higher fitness.

Natural selection happens to individuals and Evolution happens to populations.

-          Individuals vary and those with poor fitness are selected against (i.e. if you aren’t good at surviving and reproducing you don’t get your genes represented in the next generation).

-          Evolution describes changes in gene frequencies or proportions, so you need to consider more than one individual in order to measure or calculate this change.

Unlike in Pokémon, one individual does not evolve into something else during its lifetime. However, like in X-men, genetic mutations within a population can cause certain individuals to be different, and if there is an advantage to the mutation (say, if being able to control someone’s mind increased your fitness, something Prof. X could have taken advantage of) that mutation would increase in frequency and cause an evolutionary change.

Some things evolution is not:

…directed

·         The process of evolution does not predict the future, i.e. it cannot predict that next year will be particularly dry and have individual plants produce more drought-tolerant offspring. Certain organisms may have more variable genes than others or could be more susceptible to mutation, but these traits may simply allow for rapid adaptation to changing environmental conditions.

…for the good of the species                                

·         Evolutionary changes in a population or species are not always positive or going towards an optimal state that makes a species perfectly suited for its environment. Natural selection does act on individuals that are less-suitable or fit in the current environment, selecting against them, resulting in individuals that are more capable of surviving and reproducing in an environment producing more/better offspring. But, this does not mean there is some guiding force making these changes. There are also negative or neutral processes (genetic drift, bottlenecks, inbreeding depression) that also result in evolution that may not have any positive effects on a population or species. 

It is sometimes hard to think that all the vast diversity of life that we have on earth today, and that has existed in the past, came about by the simple process of some individuals making more or better babies than others in response to the conditions they find themselves in. But there has been a long time for this to happen (we think life emerged somewhere around 3.8 billion years ago) and life or death consequences for what traits an individual has. The power of artificial selection (selection of desired traits by humans) can be seen in creating modern corn from the grass teocinte, broccoli, cauliflower, kale, and almost every other vegetable you’ll see at the grocery store from one primitive cultivar (wild cabbage), and dogs of every shape and size (still all the same species), simply from breeding individuals with desired traits over many generations, exemplifies the amount of genetic variation that can be present in one species or population. Now, think of this same process but the species being selected on are confronted with almost infinite combinations of environmental conditions, competing species, available resources, and random mutations. I think it becomes less crazy to think of evolution leading to all of life on earth once you put it in this kind of perspective.

Modern corn/maize on the left, the primitive cultivar teocinte on the right. A bit different, right?

The thing that is maybe the most important is that variation is a constant in biological systems. Unlike physics, where there are laws that if they are wrong we wouldn’t have things like planets, matter, and the universe, biological processes are fundamentally based in the fact that variation at the individual, population, community and ecosystem level is always present or possible. For me, this makes me think that there is always something totally new around the corner as well sets up a framework for making all kinds of predictions about biological processes.

I hope this has given a good primer to the basic ideas of evolution. I have a couple more things that I think are interesting on the basic subject of how evolution works and why it is important, but I will touch on that in the next post.

Déjà vu and the Balancing Act

Thanks to my brother Jake for altering this comic for me.

We have come to the time of year all grad students dread: the end of the summer, which means the return of the undergrads and our various semester-related duties (classes and/or teaching). In these last few uninterrupted days I am cramming in an immune assay that will be much easier to do when I’m not having to schedule it around meetings and teaching obligations.

This transition along with a New York Times special section on graduate school (came out a few weeks ago, but a professor just brought it to my attention) has me thinking about what the life of a grad student is “normally” like (and I guess when I say normal, I mean during the school year). We are always transitioning between one thing and another, going from teaching a discussion section in the morning to working on a grant application to doing some lab work, having to prioritize what we actually will get done (i.e. what can we half-ass the best today and what is going to take the front burner), with our constant companion being a guilty feeling like we should be working more, especially when we aren’t working and doing something like eating, watching TV, sleeping, or spending time with our spouse.

With any full-time job comes the multi-tasking and extra-busy periods, but I think the biggest difference is with a lot of jobs when you come home you leave your work at work. There isn’t the nagging feeling that you could or should be working on something all the time. Some grad students, they do work all the time, and a lot of them are really happy doing that and often have very productive PhDs as the result. But for those of us that can’t work all the time, it takes a while to find a balance between work and non-work where we don’t feel guilty and still get everything done.

The need for breaks was really solidified for me during pre-lims (part of our qualifying exams). This is a very intense period during our second year in grad school where we have six months to answer four essay questions and then orally defend those questions. There is so much to read and write that you can work all the time, and I did pretty much work on pre-lims whenever I wasn’t in class or sleeping. I did decide that I would take Saturdays off, or at least not work very much those days. I also started doing yoga that semester, which has become a regular part of my routine now. Making the decision to have a break helped be not worry all weekend that I should be working on my pre-lim answers. But, because I was taking a pretty hard class at the same time, I did end up working on the homework for that class with other people on Saturdays, which killed my one free day. The homeworks being really difficult for me would sometimes send me over the edge of stress, making me incapable of working at all that day and undoing any productivity. I felt like a huge bitch on the weeks where I ended up not having a break, even though my friends deny that I actually was.

Now that I am back at the point in the year when I can’t do whatever I need to do whenever I want because of teaching responsibilities and meetings, I need to get back to honing my multi-tasking skills. There is a lot of work to get done and never enough time to do it all. But making down-time one of the things that balances out the week will hopefully make this an efficient and enjoyable semester.

http://www.phdcomics.com/comics/archive.php?comicid=1073

ESA - more mobile blogging

This week is ESA (the Ecological Society of America) meeting in Austin, TX. Where 3,000 ecologists get together to talk about anything you can think of that goes under the umbrella of "ecology" (which is a lot!). I am giving a talk on my research Friday morning (the last session, where an unfortunate number of friends are giving overlapping talks). I am going to try some mobile blogging again, adding to this post throughout the day.

Me and my lab-mate Dan got in yesterday (Monday) afternoon. Pretty successful so far. Saw some mediocre talks go before my friend's very good talk, saw a couple people I've met at EEID meetings, and saw a former Madison classmate (we did a project on leaf-cutter ants for our tropical botany class) who will be defending his PhD from Princeton next week.

First session on trait-based approaches to disease ecology was pretty interesting. The best thing to come out of it was a discuss with a few of the other women working with tick-borne disease. Have a meeting with one of them who is worked on things really similar to me, immune function and how that relates to ticks and disease, since she will miss my talk on Friday. Its so nice to have the people who have the possibility of being academic rivals are actually really nice!

Doing the right thing

http://xkcd.com/552/

I’m not a very good liar, never have been (much to the chagrin of my teenage self). I have a big problem when people outwardly lie or try to deceive people (don’t even get me started on our current political situation). I sometime wonder if this is why I like science to think I make a good scientist, because ultimately we are looking for what’s true about the world. We look at data and see what it tells us about our research questions. A true scientist can have his preconceived views come crashing in around him at any moment if the evidence is there to overturn what he previously thought. There could be books written on “the best science at the time” and the significant repercussions of acting on what we thought was true then, and that we know isn’t true now. This can be really scary to people, knowing that you probably don’t have all the answers or that what you think one day can be completely challenged on the next. While most of the time this makes me feel good about my work, that it is honest and forthright, but there are days when I wish I wasn’t so truthful.

Sometimes it is really annoying to be a person who has to do thing, in this case concerning the data I am working on writing up as a manuscript to be submitted to a journal. Because I am dealing with field data, which is inherently messy, and a diverse community of multiple host and tick species, there are a lot of ways to analyze the data. There are many opinions on what the best way is. Which stats are best suited for the data, how to divide up and compare groups, how to/if transforming some of the data will improve the analysis. My head has been spinning the last couple weeks with all the data that I have available, how to describe it in a way that makes sense, and how to emphasize the patterns we think are the most important.

Unfortunately, the best solution on how to approach some of these issues would diminish the impact of our results a little bit. For instance, the data I have from the immune response assays I did with serum from the rodents needed to be transformed to deal with a handful of individuals who has somewhat strange patterns in the results of their test (I am going to withhold some of the details because this is unpublished work). There were two camps of how to transform the data, and I tried both out. Analyzing one kind of transformed data led to some near significant differences between groups of hosts. The other way showed far less statistically significant differences, and after digesting the pros and cons of each method seemed to be the more correct way to do things. This is pretty annoying because the differences I was seeing in these results we’re super significant and I thought this may diminish the impact of the story I was trying to tell. But in the long run I will feel better about presenting the results I think are the most accurate than cherry-picking the results that I “like” best. Still annoying, though.

This constant tug of war with wanting to find the answers and have mind-blowing results, and scientific integrity is a tough one. You’re not going to always get what you expect and you have to remember that negative or unexpected results are still results and they always teach you something. Whether it’s telling you that the pattern you expected isn’t actually what is happening, shows you that you need to improve your methods, or helps you design your next experiment. Because all scientists have probably experienced this in some way is probably why there is always such an uproar when its found out that someone faked their results. Top researchers have lost their jobs, or at least their credibility for doing dodgy science (for example: http://www.scientificamerican.com/article.cfm?id=fudge-factor). While I am definitely not at that extreme a point with my work, I can understand how tempting it is to present the results you think are true, even if they are not actually true. But that isn’t what being a scientist is about, and I think I’m ok with that.

P.S. The comic found here was shared by some friends on Facebook. It’s funny and true, it can makes the average grad student happy and sad at the same time (hehe)

Some reflections on looking outside your scientific box

Overall it’s been an interesting week participating in the ABS conference here in Bloomington. An opportunity to see talks and posters on subjects I never would otherwise, like bird song, aggression and face coloration in paper wasps, and competition between seasonally sympatric wren species. I went to a talk just because it was on Beldings ground squirrels (they are very cute!).  It was also interesting to go to the handful of talks on parasites and immune function and see how they are presented at a behavior, as opposed to a disease or epidemiology, meeting. These were interesting, but often with less rigor or complexity than I have come to expect from the studies presented at the disease meetings.

I keep saying this is a very “hard-core behavior” meeting, and I think that still is the best way to describe it. This is where the folk who do focal observations, activity pattern analysis, song pattern analysis, play behavior, and sex role-reversal research present their work. These are things I have not thought about for a long time. There is very little applied or mechanistic work, so less kind of comprehensive or interdisciplinary work looking at the evolutionary mechanisms and patterns in behavior. There are of course talks on those subjects, but they don’t seem to be in the majority. Being a person to dips her scientific quill into the ecology, eco-immunology, and behavior wells, which seems to be the case of a lot of disease ecologists, it’s a bit strange to step back to see work that only work in one of these fields. This research is very interesting and worth-while but I don’t think it would be as satisfying for me. Maybe it is more fun to get to see talks on cool things animals do instead of studying it all the time, I need ecology and interconnectedness for my real work.

So one of the themes of this week has been thinking about how other biologists do their science. I went to a genomics lab meeting on Monday, one of the students who rotated in my lab is doing some work on genome sequences from lonestar ticks and presented her work. She has been looking at genetic sequences from this tick species, comparing it to other available sequenced genomes and trying to find matches for possible genes. When Mandy was showing some candidate gene matches and talked about how they could be related to the biology of the tick, mainly blood-feeding, one thing the PI (principle investigator) said during the meeting was, “Great, we can really emphasize the biology when we present these findings.” Because so much of genomic research is descriptive and mechanistic at a very basic, functional level (Mel can scold me if I am making too much of a generalization here), I guess its not always the case that the researcher brings their story back to the biology or natural history of the study species. You rarely have to remind someone to “emphasize the biology” in a community ecology study, for instance.

During the poster session last night, another IU grad student friend had similar sentiments about the meeting not being very mechanism heavy, and she said you didn’t hear the term “evolution” in the presentations at this meeting. This isn’t an issue of people not “believing” in evolution, more that the evolutionary biology (and sometimes the ecology) of the behaviors they study isn’t always the first priority for their research. This is not the case at more integrative behavior meetings that she is used to going to. It also made us think about the personality of the IU biology department, which is quite interdisciplinary, and in the animal behavior section in particular very strong in terms of evolutionary mechanisms. It was also clear that the people studying disease and parasites in animals do not come to these meetings, or the growing interest in parasites that seems to be everywhere I look hadn’t made it to this community. I had maybe 5 people come to my poster last night, and most of those people were friends or professors who already know about what I do. This is a change from the EEID meeting in Santa Barbara where I was talking to people about my poster for 3 hours. I also got very few questions on my methods or details of the work that I was hammered with at EEID. The behavioral ecology poster next to mine, which was very interesting, had a crowd around it the whole session.

I’m glad everyone is interested in different things. If we all liked the same kind of research it would be pretty boring. We need experts and people that integrate different things, this is what helps us get real understanding. The big thing is that I think scientists from different fields need to be ok talking to each other, thinking about how they can work together and what connections there are between our work. This is where science can be really exciting and innovative.