Reading in the lab

The winter break is a great opportunity to spend time in the lab with my students. One of the things we do, is read papers. Last week, we spent a morning reading the following paper:

Triple-Antiretroviral Prophylaxis to Prevent Mother-To-Child HIV Transmission through Breastfeeding—The Kisumu Breastfeeding Study, Kenya: A Clinical Trial. PLoS Medicine, 2011. Thomas , Masaba, Borkowf, et al. 

The paper shows that antiretroviral drugs taken by an HIV-infected mother help prevent transmission to the baby through breastfeeding. The reported rates of HIV infection of the infants during breastfeeding were less than half the previously reported rates from untreated women.

After everyone read the paper, and we all discussed it together, two students worked together to write an abstract and three students worked together to draw an abstract. Here are the results:

Abstract (by Kadie and Melissa)

The Kisumu Breastfeeding Study was a single-arm trial conducted with 522 HIV–infected pregnant women who took a triple antiretroviral regimen from 34 weeks of pregnancy to 6 months after delivery. The triple-ARV regimen consisted of zidovudine and lamivudine and either nevirapine or the protease inhibitor nelfinavir. The purpose of the study was to investigate how various ARV regimens given to mother and/or their infants affect mother to child transmission of HIV.

Data collected showed that between 0 and 24 months, the cumulative HIV transmission rate rose from 2.5% to 7.0%. The cumulative HIV transmission or death rate was 15.7%. Three percent of babies born to mothers with a low viral load were HIV-positive compared to 8.7% of babies born to mothers with a high viral load. Similarly, 8.4% of babies born to mothers with low baseline CD4 cell counts were HIV positive compared to 4.1% of babies born to mothers with high baseline CD4 cell counts. Although these findings are limited by the single-arm design, this study supports the idea that a simple triple-ARV regimen given to HIV-positive pregnant women regardless of their baseline CD4 cell count can reduce MTCT during pregnancy and breastfeeding in a resource-limited setting.

Graphical abstract (by Olivia, Patricia and Dasha)

 

Some recommended and not-recommended science-related books

Last year I read some really cool books that are somehow related to my work. I also read books that were so annoying, I didn’t even finish them. I wanted to share some of my thoughts here.

Jim Ottaviani, Maris Wicks: Primates

Lovely comic book about three women researchers who study primates (Jane Goodall, Dian Fossey, and Biruté Galdikas). Great gift idea! Link to book

Steven Strogatz, The joy of X.

Highly recommended! Great book with essays about fun math. Made me want to learn more. Link to book.

Jennine Capó Crucet: Make Your Home Among Strangers

I very much enjoyed this novel about a young cuban woman who is the first of her family to go to college. It’s an easy read, but it has some insights that may be useful for those of us who teach. Link to book.

Vanessa Woods: Bonobo handshake

Well written memoire by traveler, writer and bonobo researcher Woods, with a lot of background on Congo and neighboring countries. The descriptions of awful violence during the wars in Congo may be upsetting to some. Link to book.

Bill Nye: Undeniable

The topic of this book, evolution, is dear to my heart, but I didn’t manage to finish it. It is simply not well written / edited. Link to book

Frank Ryan: Virolution

This book was definitely worse than Bill Nye’s book! It is not well written and it is full of nonsense about evolution. Disappointing, because it would have been nice to have a good popular book on viruses and evolution. Here Carl Zimmer explains why the book is not recommended: link to book review.

 

 

 

 

15 papers on contemporary evolution in human viruses

In the fall semester of 2014 I taught a reading seminar for master students at SF State on contemporary evolution in human viruses. This blog post contains a list of the papers we read in the seminar.

I posted about this seminar previously here (about the seminar format) and here (no powerpoint allowed), and here (about being nervous for a talk).

The students’ work can be read and seen here (about H1N5), here (polio outbreak), here (Dengue), here (Ebola), here (HIV in court), here (doing my own homework), here (the origin of HIV), here (on bad small things) and here (Hep B).

These are the papers we read:

1. Fast evolution of drug resistance in HIV patient the 1980s

Resumption of HIV antigen production during continuous zidovudine treatment. Lancet. 1988 Feb 20;1(8582):421.
Reiss P, Lange JM, Boucher CA, Danner SA, Goudsmit J.

2. HIV: Doctor infects his ex-girlfriend, phylogenetic evidence in court

Metzker, Michael L., et al. “Molecular evidence of HIV-1 transmission in a criminal case.” Proceedings of the National Academy of Sciences 99.22 (2002): 14292-14297.

3. Very contemporary: the genomics of the West-African Ebola epidemic

Gire, Stephen K., et al. “Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak.” Science 345.6202 (2014): 1369-1372.

4. Using phylogenetics to determine origin of Dengue-3 outbreak in Australia

An explosive epidemic of DENV-3 in Cairns, Australia. PLoS One. 2013 Jul 16;8(7):e68137. doi: 10.1371/journal.pone.0068137. Print 2013. Ritchie SA1, Pyke AT, Hall-Mendelin S, Day A, Mores CN, Christofferson RC, Gubler DJ, Bennett SN, van den Hurk AF.

5. Classic paper from Beatrice Hahn’s lab on origin of HIV-1

Gao, Feng, et al. “Origin of HIV-1 in the chimpanzee Pan troglodytes troglodytes.” Nature 397.6718 (1999): 436-441.

6. Timing the start of the HIV-1 pandemic

Korber, Bette, et al. “Timing the ancestor of the HIV-1 pandemic strains.”Science 288.5472 (2000): 1789-1796.

7. Where did the polio outbreak in Dominican Republic and Haiti come from?

Kew, Olen, et al. “Outbreak of poliomyelitis in Hispaniola associated with circulating type 1 vaccine-derived poliovirus.” Science 296.5566 (2002): 356-359.

8. Within-patient evolution of vaccine-derived polio virus

Martín, Javier, et al. “Evolution of the Sabin strain of type 3 poliovirus in an immunodeficient patient during the entire 637-day period of virus excretion.”Journal of Virology 74.7 (2000): 3001-3010.

 9. Hepatitis B within-patient evolution

Lim, Seng Gee, et al. “Viral quasi-species evolution during hepatitis Be antigen seroconversion.” Gastroenterology 133.3 (2007): 951-958.

10. Permissive mutations and the evolution of drug resistance in Influenza

Bloom JD, Gong LI, Baltimore D. Permissive Secondary Mutations Enable the Evolution of Influenza Oseltamivir Resistance. Science (New York, NY). 2010;328(5983):1272-1275. doi:10.1126/science.1187816.

11. Controversial experiments on H5N1 Influenza

Airborne transmission of influenza A/H5N1 virus between ferrets. Science. 2012 Jun 22;336(6088):1534-41. doi: 10.1126/science.1213362.
Herfst S1, Schrauwen EJ, Linster M, Chutinimitkul S, de Wit E, Munster VJ, Sorrell EM, Bestebroer TM, Burke DF, Smith DJ, Rimmelzwaan GF, Osterhaus AD, Fouchier RA.

12. Influential study on treatment to prevent HIV

Grant, Robert M., et al. “Preexposure chemoprophylaxis for HIV prevention in men who have sex with men.” New England Journal of Medicine 363.27 (2010): 2587-2599.

 13. HIV drug resistance in women in Africa who were treated to prevent mother-to-child transmission

Eshleman, Susan H., et al. “Nevirapine (NVP) resistance in women with HIV-1 subtype C, compared with subtypes A and D, after the administration of single-dose NVP.” Journal of Infectious Diseases 192.1 (2005): 30-36.

 14. Evolution of Acyclovir resistance in Varicalla-Zoster Virus

Morfin, Florence, et al. “Phenotypic and genetic characterization of thymidine kinase from clinical strains of varicella-zoster virus resistant to acyclovir.”Antimicrobial agents and chemotherapy 43.10 (1999): 2412-2416.

 

15. Soft and hard sweeps during evolution of drug resistance in HIV

Loss and recovery of genetic diversity in adapting populations of HIV. PLoS Genet. 2014 Jan;10(1):e1004000. doi: 10.1371/journal.pgen.1004000. Epub 2014 Jan 23.
Pennings PS1, Kryazhimskiy S2, Wakeley J3.

How a collaboration on imperfect drug penetration got started

Almost three years ago, in early 2012, I attended a talk by Martin Nowak. He talked about cancer and one of the things he said was that treatment with multiple drugs at the same time is a good idea because it helps prevent the evolution of drug resistance. Specifically, he explained, when treatment is with multiple drugs, the pathogen (tumor cells in the case of cancer) needs to acquire multiple resistance mutations at the same time in order to escape drug pressure.

As I listened to Martin Nowak’s talk, I was thinking of HIV, not cancer. At that time, I had already spent about two years working on drug resistance in HIV. Treatment of HIV is always with multiple drugs, for the same reason that Martin Nowak highlighted in his talk: it helps prevent the evolution of drug resistance.

However, as I read the HIV drug resistance literature and analyzed sequence data from HIV patients, I found evidence that drug resistance mutations in HIV tend to accumulate one at a time. This is contrary to the generally accepted idea that the pathogen must acquire resistance mutations simultaneously.

There seemed to be a clear mismatch between data and theory. Data show mutations are acquired one at a time, and theory says mutations must be acquired simultaneously. One of the two must be wrong, and it can’t be the data![1]

Interesting!

After Martin Nowak’s talk, I went up to him and told him how I thought data didn’t fit the theory. Martin’s response: “Oh, that is interesting!” (Imagine this being said with an Austrian accent). “Let’s meet and talk about it.”

So, we met. Logically, Alison Hill and Daniel Rosenbloom, then grad students in Martin’s group, were there too. I had already met with Alison and Daniel many times, since they were also working on drug resistance in HIV.  John Wakeley (my advisor at Harvard) came to the meeting too.

Between the five of us, we brainstormed and fairly quickly realized that one solution to the conundrum was to assume that a body’s patient consisted of different compartments and that each drug may not penetrate into each compartment. Maybe we found this solution quickly because Alison and Daniel had already been thinking of the issue of drug penetration in the context of another project. A body compartment that has only one drug instead of two or three would allow a pathogen that has acquired one drug resistance mutation to replicate. If a pathogen with just one mutation has a place to replicate, this makes it possible for the pathogen to acquire resistance mutations one at a time.

We decided to start a collaboration to analyze a formal model to see whether our intuition was correct. Over the following three years, there were some personnel changes and several moves, graduations and new jobs. Stefany Moreno joined the project as a student from the European MEME Master’s program when she spent a semester in Martin’s group. When I moved to Stanford, Dmitri Petrov became involved in the project. Next, Alison and Daniel each got their PhD and started postdocs (Alison at Harvard, Daniel at Columbia), Stefany got her MSc and started a PhD in Groningen, I had a baby and became an assistant professor at SFSU. No one would have been surprised if the project would never have been finished! But we stuck with it and after many hours of work, especially by the first authors Alison and Stefany, and uncountable Google Hangout meetings, we can now confidently say that our initial intuition from that meeting in 2012 was correct. Compartments with imperfect drug penetration indeed allow pathogens to acquire drug resistance one mutation at a time. And, importantly, the evolution of multi-drug resistance can happen fast if mutations can be acquired one at a time, much faster than when simultaneous mutations are needed.

Our manuscript can be found on the BioRxiv (link). It is entitled “Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multi-drug resistance.” We hope you find it useful!

[1]Of course, it could be my interpretation of the data!

Stefany Moreno (in large window), Alison Hill, Daniel Rosenbloom and myself in one of the many Google Hangout meetings we had.

A reading seminar where every student reads, writes and contributes to the discussion in class

I remember reading seminars as follows: one student spends the entire week preparing for a powerpoint presentation, which often turns out to be stressful for the student and somewhat boring and uninformative for the audience. The other students only glanced over the paper and so any discussion quickly falls flat. I therefore decided to have multiple short presentations without powerpoint (less preparation, more fun to listen to, plus repetition is good for learning a skill). I also decided to use short writing assignments as homework to make sure that all students were prepared to contribute to the discussion in class. At the same time, I wanted to keep things manageable for everyone.

1. Learning to present: every student does multiple short presentations without powerpoint.

No powerpoint: I didn’t want students to spend too much time preparing a presentation. I believe that often, when students spend a lot of time preparing presentations, they focus too much on making powerpoint slides and not enough on informing the audience and telling a story.

Short presentations: Doing an engaging 45 minute presentation is extremely difficult, and a skill that most postdoc don’t have, so why do we use 45 minute presentations in our graduate seminars? I decided in stead to let each student do three 10 minute presentations.

Feedback: After each presentation the presenters got feedback (from the other students and myself), so that they could improve their presentation skills during the semester.

Easy listening: An added benefit of 10 minute presentations is that it is much easier for the audience. Each week started with three student presentations, one on the background and main question of the paper, one on the data and the results of the paper, and one on the conclusion and implications of the paper.

2. Practice writing: every student does a different writing assignment every week.

Graded homework each week: A paper discussion can only work if people have read the paper. If students don’t read, they may spend most of their energy to try to hide that they didn’t read (I know I was in that situation!). So even though I understand that life and research get in the way of reading, I really wanted to make sure that the students were prepared for the seminar. To do that, I made every student do a written assignment every week that would count towards their grade (unless they were presenting that week).

A different assignment for each student: I had a long list of assignments so that each week, many different assignments were done AND so that over the course of the semester each student did many different assignments. This guaranteed that the students read the paper, but each with a different question in mind.

There were several types of written assignments. Descriptive: 1. Describe the background and main question of the paper, 2. describe the data and the results, 3. describe the conclusions, 4. describe which virus the paper is about. Critical: 5. What is your opinion of the paper? 6. What do you think the authors should have done differently? 7. Play the devil’s advocate: why should the paper not have been published? Summaries: 8. Summarize the paper in your own words, as if writing to a friend, 9. summarize the paper using only the most common 1000 words of the English language, 10. summarize the paper in a graphical abstract, 11. summarize the paper in a tweet. Meta: 12. Who are the authors of the paper? 13. How often is the paper cited, do you think it is influential?

Short! Each written assignment could not be more than 150 words, to keep the workload manageable for me and for the students.

Surprisingly hard: Some of the assignments were harder than the others. Summarizing the paper using only the 1000 most common words from the English language turned out to be very hard, but some of the students did a great job (see here and here). The graphical abstract was also hard for some students, but others liked it just because it was so different from their usual work (see here and here). The ”devil’s advocate” writing assignment was always very interesting to read.

Easy: Grading the written assignments was quite easy. I simply gave a plus or minus for 5 categories (answered the question, scientific accuracy, clarity, grammar and word count).

Revisions allowed: After a request from a student, I decided that the students could redo any assignment where they had gotten less than 100% because I believe that feedback is most useful when it can be applied to a revision.

3. Promoting equity: thanks to the written assignments, every student could contribute to every class.

Everyone contributes: One of the nice things about the homework schedule with different assignments for everyone is that in class, I could ask each student about their homework. This way, each student contributed to the class, promoting equity, and the brief discussions of the homework assignments always let to questions from other students. Even if I didn’t ask, some students would volunteer to share information they found while they researched for their homework. For example, I remember someone remarking at the end of a presentation: “In your presentation, you said this result may be very important, but I found that the paper hardly has any citations even though it was published ten years ago, so I think it may not have been picked up by anyone.”

Sharing homework: I also encouraged the students to share their written assignments on the online forum we had for the class, so that the other students (and not just me) could read them. Sometimes they led to interesting forum threads. I also published some of the written assignments on my blog, after asking the students for permission. This way even more people could enjoy them.

A missed opportunity

[Note: I originally wrote this article in Dutch for a newspaper for biologists (201409EbolaBionieuws) and translated it to publish here as well.]

“Ebola virus virion” by CDC/Cynthia Goldsmith – Public Health Image Library, #10816

Randomized placebo-controlled clinical trials are often large and very complex, but they don’t have to be, according to professor Joanna Masel. In an article for Scientia Salon, Masel argues that the few doses of ZMapp that were available to treat ebola patients should have been used for a small clinical trial. Even a very small trial is better than no trial at all. That this didn’t happen is a missed opportunity.

Ebola is a horrible disease and, as you can’t have missed, there is an epidemic going on in West Africa. About two-and-a-half thousand people already died of ebola in the last couple of months. There is no drug to treat ebola patients. At least, there is no drug of which we know that it works. There are a few experimental drugs, of which ZMapp is the best known. ZMapp consists of a mixture of three monoclonal antibodies. The press wrote a lot about whether ZMapp should be used and who should get the first available doses.

Because Ebola is associated with a very high mortality (>50%), experts agreed quickly that ZMapp should be made available to patients, even though it hasn’t gone through all the usual tests. Another question was who should get the first doses. If Africans would be the first to be treated, then the risk would be that it would be seen as using Africans as guinea pigs for a new drug. However, if non-Africans would be treated first, it could look as if whites were given priority. This is not easy decision.

ZMapp in a small trial?

Another discussion received less attention. ZMapp has never been tested in a clinical trial. But if we are going to give ZMapp to people, shouldn’t we use the opportunity to do a randomized trial right away? In such a study we can find out whether ZMapp is saving lives and we can potentially save lives at the same time. Professor Joanna Masel from the University of Arizona suggested the following: if you only have six doses , and many more sick people , then obviously most of the sick will not get the medicine. That’s terrible. But, she says, let us try to make the best of this bad situation. Let’s not pick six, but twelve people who qualify for the medications. And then lets give a placebo to half of the twelve and the real medicine to the other half. In this way we do a very small randomized, placebo-controlled clinical trial. And if we are lucky, the results of that trial will tell us whether the drug works.

But wait, we can hear the critics say, isn’t a study of twelve people far too small? In her article, Masel uses standard calculations (see also here) to determine whether a trial with twelve patients would make sense. It turns out that if the drug works extremely well, so that everyone gets the drug also survives, then in a study with twelve people we have an 80% chance that we find a significant difference between the placebo and ZMapp. And 80% is pretty decent for a clinical trial.

By now, the available doses have all been used. It is said that ZMapp has saved lives (link), but no one knows for sure. The patients who received ZMapp were probably in better condition and were treated in better hospitals than the average ebola patient. We don’t know what the real effect of ZMapp was. That’s a missed an opportunity.

There are simple tools that calculate the power of clinical trials. The screenshot is from a website http://www.sealedenvelope.com .

Doing my own homework

This week I decided to do some of my own homework. Just for fun.

It’s a graphical abstract of a classic paper we read in class.

Turns out, making a graphical abstract is no easy task! Next week, there’ll be students’ work here again.

What I found most surprising about this paper is that they had to sequence the chimps’ MtDNA to find out what subspecies they were. I would have expected that experts could simply look at a chimp and know what subspecies it is.

Origin of HIV-1 in the chimpanzee Pan troglodytes troglodytes.
Gao F, Bailes E, Robertson DL, Chen Y, Rodenburg CM, Michael SF, Cummins LB, Arthur LO, Peeters M, Shaw GM, Sharp PM, Hahn BH. Nature. 1999 Feb 4;397(6718):436-41.

Genomics of the Ebola outbreak in Sierra Leone

I am teaching a graduate seminar at SF State on contemporary evolution of human viruses. Colleagues advised me to pick the papers for the entire semester beforehand, to reduce work during the semester. I didn’t do that, however, because I wanted to be flexible and choose (partly) based on what the students liked or what the students had trouble with. The result was that in the second week of class, I could hand out a brand new paper on the 2014 Ebola outbreak. Now that is contemporary!

The only trouble is that from now on, every other paper I choose will seem old; a Dengue outbreak in 2008? How ancient!

Here is some of the homework by the students in my class. I hope you enjoy reading it.

The context and main question of the paper

This paper focused on identifying the transmission route of the Ebola virus disease (EVD) outbreak throughout West Africa, whether the outbreak continues to be supplied by new vectors, and how the virus has changed to infect humans. The scientists used parallel viral sequencing and they ended up generating 99 EBOV genome sequences from 78 confirmed EVD patients. Phylogenetic comparison of all genomes from earlier outbreaks, suggests that the 2014 EBOV likely spread from Middle Africa within 10 years. Patients sharing intrahost variation showed specific transmission patterns in West Africa, and this suggests that transmission of viral genetics may be common.

Something new found in this study was that in contrast to previous EVD outbreaks, human-reservoir exposure is unlikely to have contributed to the growth of this epidemic. In addition, the EBOV catalog of mutations will aid in future studies. One main question that this paper addresses is whether or not future studies can monitor viral changes and adaptation, and understand how to contain this expanding epidemic.

Ryan Marder

The main conclusion of the paper

As this paper was largely descriptive in nature, I am wary to try to define the main scientific conclusion. With regard to concrete discoveries, however, their data suggests quite strongly a single point of origin for the outbreak of Ebola virus disease (EVD) in Sierra Leone, involving two different strains of the virus introduced simultaneously. Additionally, they document with high fidelity possible transmission links between groups of patients.

More important is the demonstration of the utility and information density available through the types of rapid sequencing and analysis employed in this work. Although not a protocol paper, the authors have produced a technical tour de force with a great deal of insight into the disease dynamics involved in the recent Ebola outbreak. I am sure that, as sequencing costs continue their steep decline techniques of this sort will only become more common, and the community will begin to adopt standard practices for these types of studies.

This sort of adoption and standardization will have broad implications for the future of disease mitigation. Tempered by the human genome project’s underwhelming applicability to medical breakthroughs, I remain optimistic that as genetic data is more readily applied to patient treatment, it is likely that information of this kind will contribute to tangible medical interventions which will directly benefit patients around the world.

Graham Larue

The devil’s advocate

The paper mentioned that when the first Sierra Leone case of Ebola virus disease (EVD) was confirmed, the tracing led to 13 more sick females who attended the burial of a traditional healer. It was misleading to seem the females are more prone to contract the disease than the males because the gender ratio of the funeral attendees wasn’t provided.

It was informative but boring to read when a bunch of numbers were given like single nucleotide polymorphisms (SNPs) between the 2014 EBOV genome sequences and the previous EBOV outbreak, and the numbers of intrahost single nucleotide variant (iSNV) in Sierra Leone patients. The wording was a bit confusing sometimes. One ethical issue could be sequencing for other pathogens when the 35 EDV suspected cases turned out negative for EBOV.

Emily Chang

Make a graphical abstract of the paper

Nicolas Cole

Two tweets about the paper

Arturo Altamirano (@articluateartie)