First of all, where did you grow up? What did you study in school?
I was born in Paris, to Parisian parents. I attended primary and high school in Paris, secondary education at the University of Paris (Jussieu campus). I was a “turbulent” student, especially in high school, so I got in trouble a lot. Through all of my studies, I did just well enough to move to the next grade. I learned very late (two years before the baccalauréat) that I was talented in math and physics, the whole time thinking myself “literary” and a poet!
Once at University (17-27 years old) I became passionate about all sorts of studies and disciplines (at that time universities offered that kind of flexibility). I was a rather good student, frequently top of the class in the various modules I took. I successively (and simultaneously) studied biology and biochemistry, then theoretical physics, then information technology, a new discipline in the early in 1970-72. I became intrigued by the computer programming of the time, notably in “binary” language directly at the console, then in assembly languages: Fortran, Basic, C, etc. I simultaneously began doctorate studies in theoretical particle physics and biophysics.
When did you realize you were interested in Bioinformatics? How would you describe it to someone who’s unfamiliar with the field? How did you begin your career in Bioinformatics?
In 1971, in the Biological Physics Laboratory of the
CNRS (
Centre national de la recherche scientifique – National Center of Scientific Research) at Jussieu, I began to formulate programs for the acquisition, in real time, of data from analytic ultracentrifugation and the analysis of the profiles of sedimentation for systems of macromolecules in interactions. I developed the first software of numerical modeling (finite element method) of equations of centrifugation of complex molecular systems. It’s thanks to my knowledge of theorists and my familiarity with perturbative methods used in particle physics (e.g. Green’s functions) that I was able to rapidly propose a master’s thesis (1973) then a doctoral thesis (1977) entitled “Numerical Modeling of Biological Systems.” I got my first steady job in 1975, at the
CNRS. At that time, I was probably one of the few French “biologists” capable of programming a computer. The methods of analysis that I published at that time are still used (and cited) today. Since I quit the field of biophysics just after my thesis, many people believe that they were written by a different Jean-Michel Claverie, who’s been dead a long time!
After my thesis, I used my time in military service (mandatory at the time) attempting my first post-doctoral work in Quebec (1977-1979) in a somatic cell genetics laboratory, in order to touch on experimental biology. I soon discovered that I was a catastrophic experimenter, and quickly resumed theoretical activities, notably in the elaboration of statistical tests to estimate the frequency of mutations in the cells we were studying. “This saved the day!” Then I returned to France for only a short while, since I’d become accustomed to “the American lifestyle.” My second post-doctoral posting took place at the Salk Institute (in La Jolla, near San Diego) where Melvin Cohn hired me, for my computer skills, to formulate a model of the immune system. There I found a great culture within the field of Biology and especially developed a flair for what to believe and what not to believe in scientific publications, thanks to my contact with Rod Langman, Melvin Cohn and Francis Crick, who was my first mentor at Salk.
L’institut Pasteur de Paris (the Pasteur Institute of Paris) then contacted me, in 1982, to create the first computer technology department dedicated to biology. Some years later, the first nucleic acid sequences were beginning to be produced, and so naturally I set myself to analyzing this new kind of data. This new field was developing simultaneously in the United States (Prof. Margaret Dayhoff) and in France (in Lyon, notably, around Dr. Grantham). I was part of the second wave of researchers in “Bioinformatics.” I’ve even been credited by some of my colleagues with the invention of the word “bioinformatics”, which didn’t really spread in the literature until after 1990.
What does a normal day of work look like for you? What are you studying at the moment?
70% in front of my computer: E-mail, writing/revising articles, writing grant proposals, administrative paperwork. 20% discussion in the hallways with other researchers. 10% analysis of new results. Currently we’re researching to discover/characterize new giant viruses that are even stranger than those we know of today. I also direct the decryption of a virus responsible for the regulation of the population of a microscopic plankton that is very ecologically important.
Why are you interested in viruses?
Just giant aquatic viruses! I came across [virology] by chance and because it’s the field (in which I have experience) that I feel most allows a perspective to call the fundamental concepts of biology and evolution into question right now.
You’ve worked on several discoveries: mimivirus, mamavirus and now megavirus. What is it like to be one of the few people associated with such important steps for the scientific community?
Not
mamavirus! (which is just a variant of
mimivirus). It’s of course very gratifying, but also gives the feeling that in biology, luck (of coming across some interesting phenomenon) is a factor of success at least as important as hard work, intelligence, or prior knowledge: we still know so little that making a important discovery (one that challenges well-established concepts) is possible even for “normal” people. Very quickly in Physics I convinced myself I didn’t have enough luck for that. One exception could be the accidental discovery of “superluminal” neutrinos by researchers who weren’t looking for them.
Had your research made you believe in some “megavirus” before having discovered it, or was it a surprise that such a virus exists?
We hypothesized that there wasn’t truly a natural limit to the size and genetic complexity of big viruses. We were also looking for a cousin of mimivirus that was, contrary to the too-close mamavirus, sufficiently far away genetically to be able to draw conclusions regarding the evolutionary origins of these viruses.
Megavirus was discovered near Chile. Do you travel frequently for your job? What’s the coolest place you’ve ever been?
We went to Chile :
1) because it was very far from France, therefore in the hope of finding a virus genetically very distant from mimivirus (arguably naïve, but also a little rational)
2) because we could find a financier for the project (Grant Assemble)
3) because my collaborator (and spouse) speaks Spanish and adores Latin America
It’s a superb place, and one that’s not – yet – spoiled by tourism. The people there are still nice and “normal.” The coolest place (and my favorite on this planet) is the Grand Canyon. I travel abroad relatively little (10 times a year), to respond to invitations to conferences, but without leaving my family for too long: 2 children and a spouse who is equally very active in research: Chantal Abergel, co-director of our laboratory.
Organisms are obviously very diverse across the globe. Where, if anywhere in particular, do you think we’ll find the next big discovery?
As far as giant viruses are concerned, we have our ideas, but allow me to not reveal them! For all organisms, it’s clear that the oceans remain largely unexplored and the probable sources for numerous future discoveries.
What do you see happening in the field of Bioinformatics in the next 5 years?
As a pioneer of the field, it’s disappointed me for the last 10 years. Not one veritably novel algorithm has been developed since 1995, and the progress of the research is incremental, if not infinitesimal. It’s difficult to know if the little progress recorded is not simply due to the larger reference databases (3D structure of proteins, sequences) and the greater power of the processors. Key fields, almost founders of the discipline, are still at a standstill: like the ab initio prediction of the 3D structure of proteins, or that of their function as a result of their sequence.
Some “new” fields such as “system biology”, or the study of interactomes, have only delivered the obvious and seem to be more like the field of “bull-shit” than real science. Very old methods (dating from the ‘80s and ‘90s) are now decked out with complicated mathematical names and wrapped up in fashionable notions (bayesian, markov chains…) without achieving any greater predictive power. We don’t have any functional prediction of more than 50% of the genes we’ve sequenced. This is a clear failure of Bioinformatics. I think that it is going to become simply a technique of molecular biology that biologists must incorporate in their curriculum to avoid incompetence.
What will you be doing in 5 years?
Technically, I’ll be retired (mandatory in France). If I’m still in good health, I’ll find the means (abroad) to continue to research. The field could be totally different from the one I work in now. I’m an opportunist. I prefer by far the excitement of pure discovery.
Aside from scientific conventions…if you could name a virus anything you wanted, what would you name it and why?
A name that refers to its most prominent properties, and the place it was discovered, or the name of its discoverer. The dream would be, of course,
megavirus marsiensis or
megavirus titanensis, for viruses discovered on Mars, or Titan – a discovery that would support a theory I take very seriously – that of panspermia.
Questional would like to thank Jean-Michel Claverie for being so generous with his time, and to congratulate him on all he's done to contribute to our understanding of the world's workings, big and small.
For more information on megavirus chilensis. check out the Questional blog here
This interview was translated from the original French by Jason Taylor. If you're interested in reading the French transcript please see below!
Original French Version
