At the start of the World Cup: Football and the Biosciences

As the World Cup begins, perhaps there is a point of talking about Biology in the context of Football.

I am a supporter of Athletic Bilbao and, like the main character in ‘fever pitch’ I sometimes see the world, life, through the eyes of football. The problem is that football has changed and so has life and that the optics need some readjustment. Football is not anymore what you breath in ‘fever pitch’.

When I was a child, and even when I was an undergraduate, football was about the teams, about special players who could conjure up a moment of excitement that sometimes led to a goal opportunity or, occasionally, better to a goal. Coaches were there, in the background, steering the teams but the attention was on the football and the players. How things have changed! Now the talk divides itself between the manager, the transfer market, the money a player is worth, the budgets of the teams, the referees and, above all, success. Modern football is about success and football is just a vehicle for success. Somewhere down the line there are teams and players who, with the exception of a few chosen ones, are just warholian searchers of an afternoon moment of glory, spendable units in a machine built to attempt to succeed. Nowadays football is part of a complicated circus in which you can only compete in the elite, and sometimes just compete, with money which buys success and success which brings in money. Living in the UK still allows me to savour some of the old flavours because here, there is a tradition which is hard to kill, but for the most part it is in the lower divisions. And, of course, there is my Athletic which with only basque born players (I am 50% basque genotypically) has made it to the 4th place and champions league next season……..because of a coach which has put football and the team, rather than himself, first. Sometimes miracles are possible; some of you might relate to this.

So it is with Science, particularly with the biological sciences. What drove me to where I am now in the first place were my readings, as a student in Madrid, of books that posed questions, which combined metaphors with visions, which spoke of the wonders of the unknown and the thrill of probing into it. As I started into science some teachers led me slowly into it, emphasizing the value of the problem and the question. I found my way to the works of Mendel, Morgan and his group, Avery and his colleagues, MacClintock, Sanger, Jacob and Monod; with their consistency and their steadiness, these became an inspiration. And like many of you, I started my sailing through the world of research following these examples, with science at the core and the scientists –defined as those which practice the art of finding out about Nature through experiments and reasoning- as a reference. Ah, yes, there were journals! In those days, a publication was the rendition into paper of hard earned findings, which reported, sometimes small and sometimes big, strides towards knowledge. Journals served scientists and published their work. There was a hierarchy but one was in general aware of the value of ones findings and so were the editors.

Like football, this has changed, and in a similar direction, though in a narrower manner. Today Science is a way of living for a lot of people (see the recent paper from Alberts et al “Rescuing US biomedical research from its systemic flaws” 2014 Proc Nat Acad Sci. doi: 10.1073/pnas.1404402111 which highlights a situation in the US but which is much more general) and the goal has changed. Noawadays, the aim is to succeed and this attracts attitudes and individuals which make research a tool for success rather than a pursue of the unknown. Science and the biological sciences in particular, has become a place in which, if you are lucky (I guess they say successful) after an ever increasing period of apprenticeship, you can set up your own business (sorry, lab) and become a PI. More often than not this means that you get a chance to apply for money, to get graduate students and postdocs to do the work that you would like to do, so that you can go to an ever increasing number of meetings to market their findings and hope that this will help you raise more money to start the cycle again. Journals have come to play a central role in this complex cycle and, for the most part, rather than serving the scientists, they have managed to turn the tables. Rather than being a tool for the scientists to disseminate our work, the scientists have become a commodity for the journals which now tell the scientists what they need to do and how they need to present it in order to survive. In this process, editors have become arbiters of the way money and influence are distributed and, conscious of this, they exert this power-you might have seen at meetings the queues to speak to the editors of the journals that ‘matter’ in the hope of catching their eye so that they will look at work and…….yes, it is like this. In the same manner than in football (biomedical research) we move away from the players (postdocs, young PIs) and the game (findings) and focus on the managers (PIs) and the influence of money (grants) which depend on the commercial enterprises (publicity/sponsors) that help this process. And the only thing that matters is success defined not by the value of the finding but by the value that the speculation in the publications market gives to your research. As in football, today Science is about money, returns, commercialism and above all, success, rather than about the essence of the enterprise.

If you are a young aspiring scientist you need to understand this, and adapt. Good science is just a start. If you want to be able to practice it you will need to intuitively develop, or learn, a number of skills amidst which the ability to influence people, in particular editors, is a must. Salesmanship is more important than scientific talent and if you don’t have it, learn it because things are not going to change quickly. As in football, there are many who start but few that make it and remember that, for the most part, the limelight is on the managers, what people want to be is a PI not a scientist (and there are differences nowadays). Two very common questions that you will get often are ‘how many grants you have’ and ‘how big is your lab’ -as if the bigger the better when what this amounts to is that a PI with a big lab (say over7/8 people) really doesn’t know what is going on and that while the lab is productive in terms of churning out results, there might be little content to it.

Will this change? I don’t know; and I do not want to despair about it because there is a lot that is good, interesting and exciting about modern science. But something has to change, something deep about the spirit of how we go about science. It would be good if we could find a way to reel in some of the values of old and blend them with some of the modern attitudes. It would be good if we could put, again, science at the center of the game rather than the hype, the marketing, the publicity and the futile pursue of a fleeting sense of success. The focus of football in success has not been that good for the game but at least, if you want to enjoy football, all you need is a ball, an open space and time. Science needs a community, to support a structure which now is, increasingly, being restricted to an ever increasing minority which is selected not on merit but on the money they can get which, of course, will lead to a winner gets all situation that will take many people out of the arena. Let us hope that we can find a way forward which will be good for science and those who want to do science.

PS. As I was about to post this I hear about events at Kings College London ( It confirms the worst of the analogy: only success narrowly defined will suffice. Scientists are just commodities valued by what money they attract and not by what they produce (there is even a scale of value). Of course, we have been fostering this attitude and, in many ways, it is implemented by stealth when people (and this is true of many institutions) are asked for certain kinds of publications which imply two or three rounds of sterile but money draining reviews which never change the message. Only those with that kind of money have access to those journals which makes the circle: funding, research, jobs narrower and narrower.

There ought to be a way to progress out of this situation because in the medium term it does not favour creativity nor what we used to call science.

Chemistry, the missing link in “The Double Helix”

Last week there was a celebration of the 60th anniversary of the publication of the papers (sometimes it seems as if there was only one but, actually there were three) on the structure of DNA. The occasion invited recollection and reflection and, perhaps for the last time, allowed some of the protagonists to tell the world famous events in Cambridge, UK.  Much ink has been poured over this to the point that some times it does not feel like Science but rather like a fairy tale, a legend about a girl in the midst of boys chasing a structure which only she could get at the time but which only they could interpret. There is a holy grail (the structure contained the secret of life), there is a race for it, there are goodies and baddies, magicians, traitors, there is ambition, frustration…….the stuff of great stories and great movies, and a movie was made by the BBC called ‘Life Story’. It is not commercially available, which is a shame, but it was screened during the events last week. It is a great movie and if you have a chance to see it: enjoy.

History is written by those who can write it for those that want to read it, often without asking questions. Scientists, particularly life scientists, rarely become chroniclers of their own fields so, it was somewhat surprising to all involved when James Watson produced “The double helix”, his iconoclastic account of events in Cambridge and London in 1952-1953. It is a riveting account that sweeps you into the story at the expense of the science which is, as they would say today, dumbed down. The undoubted significance of its conclusion and the manner in which this unfolds makes you not think that there is something missing.

The story, as perceived from the multiple re-tales of Watson, is more an adventure than actual History or Science, and this is perhaps the reason why it feels as if a vial with DNA had been gathering dust in some cupboard in Kings College since 1869, when F. Miescher purified it from the leukocytes in pus bandages of a hospital in Tübingen (Germany), waiting for Watson and Crick to reveal its secrets from their astute interpretation of the photo 51 of Rosalind Franklin. However: how did they know what to fit the photograph to? How did they know the structure of the nucleotides? How did they know that DNA was a polymer? This bit of the story is never told and the fairy tale aspect of the account makes it sound unimportant, a given. After all, was it not in the picture, Watson’s drive and the brilliant mind of Crick that conjured up the helix? But if you think about it, the X ray photograph did not tell them the components they had to fit (a sugar, a phosphate and a base in each unit of the polymer), it did not tell them how they were linked, nor what were the molecular dimensions and forms they were looking for. This was Chemistry and Chemistry always plays little cameos (if at all) in the accounts of Watson, and always as a distraction from the main plot. And yet, model building was derived from Linus Pauling’s insights into the chemical bond but, more significantly, there are two instances in the story at which Chemistry makes significant contributions. The first one through the famous Chargaff rules, central for the determination of the structure. The second one in the suggestion of Jerry Donahue (a biochemist who shared an office with them) to use the right tautomeric forms of the bases when trying to build the model; this proved crucial. Both contributions were significant and are always underplayed. However, even before this, the discovery of the components of DNA, the clarification of the differences between DNA and RNA, the discovery of the structure of the nucleotides, all this were major pieces of Science without which Photo 51 would not have a reason to be and it certainly would not have been possible to read. But these findings, their history and their role in the double helix have been relegated to ‘specialized books”, if not to obscurity,  by the trailblazing account of the race to get the structure of the DNA.

Chemistry is the great important missing character in the story and this, in a way, has had a price; more on this below. First, a brief account of what is placed, literally, under the carpet, as dust that might contaminate the racy account of the race for the double helix by James Watson with the help of Francis Crick. If you want to read about this in a context I suggest you look at “The path to the double helix” by R. Olby (University of Washington Press 1974) and “A century of DNA” by FH Portugal and J. Cohen (MIT Press 1977).

DNA was not dormant since 1869, and one can weave a good account of how it revealed its secrets slowly from the chemical and the biological angles, through the first half of the XX century. The biological one, largely centered on Griffith in London and Avery and his team at Rockefeller in New York, is well known and there is little need to recount it here. In fact it was Watson’s knowledge of the experiments of O. Avery that drove his quest for the Holy Grail and made him want to know the structure (at all costs) so that he could interpret this work. The importance of this intuition, which fuelled the race, cannot be underestimated. But, on the other hand the Chemistry, is less known, and without it nobody would have known where to start in 1952.

DNA was thought to be important because it made up so much of the nuclei of animal cells, where the chromosomes resided, and where increasingly people thought the material basis of heredity resided. Miescher already knew that there was phosphorus in nuclein and that phosphorous was not present in proteins, which were a component of nuclein. By 1878 Albrech Kossel isolated (to some degree of purity) the non protein component of nuclein and showed that, in addition to phosphorous, it contained five organic compounds, the bases as we know them today: A, C, T, G and U. Thus at the dawn of the XX century elements are in need of a global structure and this task befell to Phoebe Levene  (1869-1940) a Russian émigré medical doctor, turned brilliant biochemist at the Rockefeller research Institute in New York, who pursued the fundamental structure of the units of nucleic acids. He found and characterized the sugars in DNA and RNA –which at the time were thought to divide themselves between animals (DNA) and plants (RNA), and found the basic unit of these acids: the nucleotide. He uncovered the bonds and thereby the structure between the different elements: the familiar P-sugar-base, the nucleotide. Needless to say that this a central piece in the puzzle and the key element in the interpretation of Photo 51. It was also a piece of structural work, chemical structural work, and had its little dramas and certainly its toilings, but nobody wrote a best seller about it. There are many reasons one can think why this is left out of the story: lack of glamour, a time dilution effect, the tediousness of Chemistry……but there is something that perhaps made a major contribution to this. Levene, using data that was not correct, suggested that the basic unit of DNA was a tetranucleotide (ATCG each with their P and sugar bound in an uncomfortable ring) and that nuclein was a sum, of these molecules. This was wrong but nevertheless is said to have influenced much of the functional thinking about DNA at the time. Such a molecule did not have the ‘informational content’ , as we would say today, to code for heredity and favoured the hypothesis, widely spread at the time, that the keeper of heredity was the protein in the nuclein. Everybody? Well, in one of those little jokes of historical fate, as Levene was moving away from DNA as the basis for heredity, a few meters away in Rockefeller Avery and his team were toiling away on their experiments on Pneumoccocus which established DNA as the ‘transforming principle”. Also, paradoxically, Levene showed that DNA was a large polymer with a MW above 106, something that would question the tetranucleotide hypothesis and which had been seen before and would be confirmed later. The coming together of the notion that DNA is a polymer with the detailed structure of the monomer is, as one can imagine, the essential seed for the X-ray structures, which were being undertaken before R. Franklin is charged with getting the structure at Kings.

One coda to the chemistry of DNA, and an important one. Chemical structures are abstractions from the sorcery of the chemical laboratory. The proof of the structure lies in synthesizing it de novo. In the case of the nucleotides this was achieved by Alexander Todd, curiously working not far away from the Cavendish. He and his group synthesized ATP in the 1950s and later a dinucleotide, crucial in interpreting the polymer in the proposed structure.

Together the work of Kossel, particularly Levene and later Todd, provide the elements that need to be modelled from Photo 51. Levene and Todd must have had their Eureka moments, but never told any one or we have not been told about them.  For all that we hear about Watson’s, the photograph and the rest, where would all this be without knowing that a nucleotide was made of a phosphate, a sugar and a base and that one had to use the correct chemical form of the bases? One has to separate two things in the ‘discovery’ and, unfortunately, this is not done often enough. On the one hand there is the structure. This is what chemists worried about, this is what Franklin was interested in and this is what has gone down in history as the prize. It has been argued, probably correctly, that chemistry failed to deliver the structure. In many ways, it could not have done this but nothing should be taken out from the fact that it did its job, to deliver the elements needed to interpret the biophysical data. On the other hand there was the meaning of the structure. This is more subtle but this is the really important contribution of Watson and Crick. Sure, this cannot be gauged without the structure but this bit, the function, might have gone unnoticed by most of the biophysicists of the time and who knows how much time it would have taken for people to notice once someone produced the double helix; and there is little doubt that this would have happened because DNA, as we have seen, had its own momentum with what journals would call today ‘incremental advances in knowledge”……..For Watson, the structure was the gamble. He and Crick were able to read genetics into it and this is their major and unique contribution, not the structure which was a culmination of almost 100 years of work. Reading and listening (on the web) to Crick one gets the impression that he is extremely well aware of this (remember that he was not overjoyed when he read “the double helix”).

So, Watson’s account is biased to highlight the role of Watson and of Watson and Crick in the structure, on the race, on the goal; we all know that. In doing so he sidesteps the contribution of Chemistry to the story. It leaves a blank between Miescher and London and Cambridge in the early 50s. It is done, I am sure, inadvertently, maybe a literary license in the fantasy he made up of an interesting piece of History, but it has consequences- though I am not sure that Watson’s account is the main reason for this. It proposes a way of doing Science that was alien to most people at the time. More importantly, leaving gaps like that in Science, could be important.

Biology is Chemistry, and much of the molecular underpinning of the cell is chemical. The fantastic contributions of Genetics to our understanding of the workings of the cell have overshadowed this and today the interplay between Genetics and Molecular Biology dominates as the main tool of discovery. If the sequence of a gene shows a kinase like domain, it must code for a kinase that works like a kinase; we rarely check. If the sequence of a protein says it has to be in the nucleus and, when we look for the protein, sometimes we find it outside the nucleus, it must be an artefact and thereby wrong. We trust the homology. Biochemistry is, for the most part, associated with structural biology and the chemical underpinning of the cell has been relegated to a second plane that we can extract from the sequences. There are, of course, counterexamples and the discovery that cytochrome c plays in apoptosis is one of these but, in general, we have forgotten that much of our knowledge about the cell comes from Biochemistry, real Bio-Chemistry. We would do well in revising this because at this moment there are too many things that do not fit the picture provided by the Genetics. We understand well replication, transcription and translation but beyond this, as we are starting to measure (to be quantitative), there are too many questions: interactions between components generate carefully controlled quantitative outputs e,g those associated with the homeostasis of tissues, temperature adaptable circadian clocks or periodic patterns of gene expression. One of the best understood cellular processes, the cell cycle, is a good example of the insights that a combination of Genetics and Biochemistry can produce.

Structure encodes function but sometimes, the details of function lie in…. function itself…..we would do well in reflecting on how much Photo 51 owes to Chemistry and see if we can find a way to sort out questions of cellular dynamics from a reinvention of Bio-Chemistry which today, I would say, needs to be a Bio-Physical Chemistry to understand rates and compartmentalization and the dynamics of the structural biology of the cell. Maybe this kind of Chemistry is a way towards the much needed Physiology of the Cell.

Note: I owe the idea to jottle these lines to my colleague Christian Schroeter who, in attending the Crick Symposium in Cambridge (UK) last week, remarked to me that a most interesting part of the Symposium was an acknowledgment by Jack Dunitz of the chemical background of the history of DNA. He like many did not know very much about this.



The emerging impact of modelling and theory in Cell and Developmental Biology

At the BSDB meeting, Michael White (University of Manchester), pioneer of the imaging of gene expression in living cells, gave one of his customarily sound, interesting, inspiring and enlightening talks in which he discussed his work on the dynamics of NFkB expression and its regulatory consequences. The accumulation of measured variables and the dynamic nature of the information gathered by his experiments demand models and, in the course of the talk, he managed to slip some statements about why do we need models in Biology. And I do not think he meant Cell/Nature or Science Figure 9 models (a collection of gene names joined by arrows which satisfy editors but fail to capture the reality they aim for) but rather actual dynamical systems which incorporate the variables, test the hypotheses under consideration and generate new hypotheses. Most important, the models he was talking about are quantitative and make us think quantitatively. Curiously Genetics and Biochemistry have very strong foundations of this kind but the gene hunt that has characterized Biology over the last few years have made us forget this and over the last few years some of us have been discovering that Natural Selection has not just been shaping the DNA landscape but also the output of the information contained there in the form of numbers.

The gathering of quantitative data which incorporate a dynamics have, since the time of Newton, required models that uncover the relationships between the variables, reproduce (or not as it may be the case) the situation being modelled and either make predictions or generate more experiments. Mike made these points beautifully and insisted on what some of us believe, namely that as Biology becomes data rich, models become an integral part of our work. However, for the most part, biologists, cell and molecular biologists in particular, do not know how to develop models, and much less how to use them. Enter the theorist.

Models require an uncanny ability to read data, abstract, find relationships between variables and make testable predictions. In some instances, models can give rise to Theories. The theorist is a figure common in the physical sciences, particularly Physics, whose job is to generate models from data and to provide theories that explain the phenomena. Theoretical physicists do not do experiments but they get others to do them. Sometimes at a huge public expense; the search for the Higgs Boson is a very good example of this. There is an asymmetry here because while theorists do not do experiments, experimentalists do modelling and sometimes also theory; although they engage in discussions with theorists, in Physics and, more so in Chemistry, experimentalists really do not need them and they will enjoy dealing with their own data. Biology is different. Excluding certain areas of population biology and, certainly, epidemiology, there are no theorists (a la Physics) in Biology. However, as quantitative data in cell, molecular and developmental biology has began to emerge, it is acting as a baie for physicists. The reasons are complex. Perhaps it is because, outside certain aspects of Astronomy, there is not much of high caliber left in need of an explanation in Physics; String Theory, as a physicist explained to me a while ago is an example of the problem because it is neither Physics –because one cannot do experiments on it – nor mathematics –because one cannot prove completely much of it. Chemistry is a different matter but here, Schrodinger’s equation and what follows said the fundamental and whereas much of what is alloy cannot be totally understood (in the predictive way physicists like), a lot of what is around are ‘details’, important but details and, in any case theory and experiments go together. Biology is an open book of blank pages with lots of facts and limited understanding. Perhaps this is what makes it attractive to theorists. Be that as it may, over the last few years there has been a steady influx of physicists into Cell and Molecular Biology which is now peaking. For the most part, this is being very positive and the physicists are making good contributions. An interesting aspect of this influx is that they get very close to the data, to the experiments. For the moment in Biology, there is no room for Einsteins,  Boltzmanns, Schroedingers or Heisenbergs, not sure how much room there is for theory but sure there is room for people who can help us deal with the data, model it, extract principles and understanding. Above all, demand numbers from us and teach us their value. The role of the physicists is to help us sort the messy data produced by our experiments and, in some instances of Cell Biology, help us design experiments. This is very fine and very fun, and those of us who have had the pleasure of collaborating with physicists in our work, know how valuable and inspiring these interactions are.

Physicists who turn to Biology come in different flavours but the best ones, in my view, are the ones who to a larger or lesser degree become experimentalists. Some names come to mind, but this is not the place for namedropping. There are others who are purely theoretical and this, again, come in two flavours. Ones align themselves to a particular group and work very closely with it to improve the experiments, generate data and provide insights.; they engage with experiments. There are others who move from place to place looking for data they can model. The latter are, these days, taking advantage of the fashion and the interest and need that biologists have of them. It is with this latter class that I have an issue.

Many years ago, the early 80s, A. Garcia Bellido (of clonal analysis in development fame) had a bee in his bonnet on theorists and Biology. He told me that he did not respect theorists in Biology because theorists could produce a theory and be wrong and nobody would care, they then would go on to produce another theory tomorrow without a blush. On the other hand if an experimentalist makes a mistake, that could be it; the blotch will remain. Those were other times, but he still might have a point today. The problem in my view does not lie with the theorists but with us. We should get ownership of our data, we should learn how to model, we should learn how to theorize. A physicist whom I know well and respect a great deal claims to be disarmed without data, that without data her work is disabled. Every time I hear this I scream inside: and what about us? Experimentalists are as disabled without data as a theorist. The difference between the experimentalist and the theorist is that we (the first ones) cannot choose the data we work with, theorists can…… long as we allow them to.

My friend Jeremy Gunwardena has argued that Biology is more theoretical than Physics  and he may have a point, but within reason and one day I should (and will) take him to task on this matter. But in the meantime the point I want to make here is not that different from his. Biology has much that is theoretical, after all every experiment tests (or should test) some hypothesis and in that sense, formally, it is a theory. What has changed over the year, what is making the difference, is that the data now is quantitative and this will require a new kind of model. Population biologists and epidemiologists are versed in modelling, but what they do is unlikely to be for cell and molecular biologists; we have to learn to do that so that if we share our data with a theorist, we know what we are doing.

As I have said above, models can, on occasion, lead to Theories and there is very little of this in Biology though the work of G. Mendel, C. Darwin, R. Fisher and H. Driesch could fit these categories though, remarkably, all of them did a great deal of experimental work. At the moment there is a fertile ground that stems from the interactions of physicists and biologists but I can see a future in which biologists catch up and we have a new science, we could call it the Physics of Living Matter. In the end, Biology is a chapter of Physics.

NB1. For a very lucid account of the role of the theorist in Biology, read F. Crick “what a mad pursuit’. Although the questions are not huge these days, the guidelines for the work are, in my view, very well laid out here.

NB2. Two important readings on this matters:

Cohen JE (2004) Mathematics Is Biology’s Next Microscope, Only Better; Biology Is Mathematics’ Next Physics, Only Better. PLoS Biol 2(12): e439. doi:10.1371/journal.pbio.0020439

Roth, S. (2011) Mathematics and Biology: a kantian view on the history of pattern formation theory. Dev Genes and Evol. 211, 255-279.

The end of the biological sciences… we knew them

In his book “The end of Science”(1997), James Horgan explores in depth what is left to be known about Nature and the Universe at the end of the XX century. It is an interesting question and one that lies at the heart of the scientific endeavour. Advances in the Physical Sciences, in particular, give the impression that all there is left to know are a few footnotes and, yes, there was the Higgs Boson……. But what about Biology?

It has been said that Science will end when we learn more and more about less and less and while Physics has always had its questions well defined –and thus we know when the end is nigh- of late, research in Biology feels like a supermarket trolley of exactly that: more and more about less and less. A look at the indexes of leading journals reveals an uncanny interest in arcane subjects which, of course, are interesting and provide knowledge but are hardly the stuff of the genetic code, the relationship between DNA and proteins of the nature of the genes that control development. Most of the time what we read about is a “new function” of a well known protein, or some isoform or new gene participating in a process where we already have dozens of participants. Additions to ever-growing lists, bean counting…… Every now and then we do get an interesting idea or result and the rightly famous Yamanaka experiment is a good example of this but, for the most part, Biology is an interesting parade of data in search of a good question. In order to raise the importance of our toilings (and get funding), scientists use hyperbole and when it is not us, it is the journals we publish in that foist this upon us. Looking at the journals, by the criterion put above (the end will come when we learn more and more about less and less) we face ‘the end of Biology”… we know it. But there might be more to this.

Two parallel developments are contributing to this situation. The first one is in the nature of Biology and its multifaceted structure. Our interest in description and classification has collided with the structure of the cell and the advent of modern genetics to generate a machine of data collection, description and classification which could easily have no end. In the XIX century naturalists collected, described and classified animals and plants. At the beginning of the XXI century we do the same with genes and proteins. Nobody will doubt the value of this enterprise (information is the currency of Science and, certainly of Biology) but we should recognize its limited value and its role in avoiding the important questions (if we can find them) –see the posting on maps, December 2012. Thinking about this you may wonder what happened in the XX century. Well, some of the same took place in the small scale but, forced by a number of events, we were busy creating the technology and the frameworks to understand what we had classified before. In doing so, modern Biology emerges but instead of pursuing the lines of thought that were laid out we decided to come back to classifications………in a new framework.

There is a sequence in Science: data collection and classification always precede the emergence of a framework. Thus, J Kepler wanted to work in Prague because Tycho Brahe had the data about the objects in the sky that he needed to develop his theoretical framework. Later on, Newton needed Kepler’s work and more data to develop his celestial mechanics. And the data for Kepler and Newton neeeded to be good quality and well organized. Two centuries later, Darwin thrived on the work of amateur and professional naturalists. The analogy with today is easy. The high throughput work feeds on the toiling of the low throughput biologists to generate archives of enhancers, promoters, histone modifications and microRNAs, and Evo-Devo thrives on the work of genetics and model organisms. The problem with all this, at the moment, is that really it is more and more about less and less. All necessary, probably, but, in some ways, it is not clear what is important, what is essential and what is just data in papers.

How much information do we need to answer a question? What are the questions? Or as Horgan would put it, are there questions? If there are (and I am not interested in what journals sell us as questions in the disguise of hyped small findings) they are being brushed under the carpet. Of course, Biomedical research does show some progress but this is to Biology what Engineering is to Physics. More on this later.

There is something else happening in parallel with the narrowing of our questions which is having an impact on the dynamics of knowledge. It is a subtle transformation of how we go about it from an enquiry based endeavour into a business orientated one. Finding out things about Nature has changed to publishing papers and getting grants. Questions have turned into finding funding. Competition for publications and funding has transformed trying to answer questions commonly recognized as important to defining a niche in which one can work. Labs have become small businesses that try to obtain funding to continue to do what they/we do, and publications are the means to obtain more funding. A complex loop has been created between publications, careers, funding and positions where the nature and the quality of the research are secondary. The main aim is survival and the measure of whether we will has been defined the impact factor and how well you sell your product which, by the way, is not knowledge (though this is what the marketing says) but the publication and the maintenance of small labour groups. Instead of watches or textile products, we sell genes and proteins, but the mechanics is the same. We use students and postdocs not as people whom we teach how to peer into Nature but as employees which have to work for the success of our business in the belief that they are helping their future.

And thus, the fact that there are many genes, many functions and many cell types fuels the competition between the different business. Each lab selling from journal based soap box their (our) findings, extolling the virtues of the genes we work on. It often surprises me the way our science is measured with questions like “how many people you have in your lab” or with statements like “ did you see the publication of X in Y”, both above an interest in the actual question of the research. Maybe this is what it should be in the time of the You Tube generation, but I surely hope that we do not lose sight of our traditional ways and content. I am not saying that we need to go back to the 1960s or the 1980s, but, if we want Biology to remain interesting at large (and not in a statistical manner) we do need to change the fabric of what we do and blend what is good in the new world in which we live, with some of the spirit of old. And, at this, you may want to ask: are there Questions in Biology? I would say yes and will endeavour to pose some of them here in a near future. Watch this space.

Maps: resolution and insight in biology


(thoughts after reading Simon Garfield “On the map: why the world looks the way it does” Gothan books 2012 )

Much of Biology is about maps . Maps of genomes, of cells, of genetic interactions, protein interactions, of the brain, networks. Maps are essential because they orient us, guide us, help us find relationships between objects of the same kind which are otherwise invisible, and  reveal how global pictures emerge from components. But how accurate are our maps? How good are our current biological maps as representations of the reality they try to capture?

I often worry about these issues and in one of these musings, recently, I learnt the story of R.L. Stevenson’s Treasure Island map. Apparently the story emerged from a map that he drew, as the detail in the map grew, he saw a story emerging and one fed back onto the other until Treasure Island was finished.  He then sent the book to the publisher in London but the map, as a central illustration, went in a different post. The text made it to the publisher but not the map. Stevenson found himself in the position of having to redraw the map but as he could not remember every detail, he had to draw it from the story he had written. He was not happy. Not only because he had to read the story to get details, but because he knew the map the book was suggesting was nothing like the original map –and had another person drawn a map from the same story, the island would look different (look up Treasure island map (adding Stevenson if you want to narrow the search) in Google images).

Hearing this story made me think about our endeavours to figure out how a cell works, the use we make of maps in this exercise and the source of those maps. The map that Stevenson used to write the book was a real map. When he saw the map, he saw the story, he understood what was happening and how it happened and used it to run the adventure. But once the map was lost, the story is orphan because the story is not the map. The story uses the map as a background for the adventures, for the readers for the publishers. But it ain’t the map. Had he been interested in mapping the map, he would have used a different narrative. What he produced from the text is only an inaccurate and probably misleading representation of a reality. He only realized this once he lost the map. There is much for us, biologists, in this story.

Mapping genomes is a first hand exercise, there is a straightforward relationship between the plot (the sequence) and the map (the large scale genome). What it represents, a sequence of A, T, G and Cs is exactly what is supposed to represent. Protein structure is not very different and, for that reason, pretty good –though molecular interactions are a different matter. The problem arises when we go one level up and try to get maps about cells, their structure and how this generates function. And things get worst as we go up and try to represent how these molecular interactions at the cellular level generate tissues and organs. What we get from out toilings, largely through genetics, is a narrative which, in the format that we have at the moment, we express as Figure 7 or 8 or 9, of a paper. And we leave it there to act as a seed for another figure 7, 8 or 9 of another paper or the basis of the review. The problem is that, if we are serious, what we have to picture is the island that Stevenson wrote from the book and not the real one, the one that led him to the book. How do we solve this?

We know that the maps that we draw are not accurate and this spurs us to try better maps, and by ‘better’ we mean more resolution, more detail …and thus we forget that the beauty of maps does not lie (only) in their detail but (more importantly) in the insights they generate, in their ability to show us the shape of things, the relationship between different elements. More resolution will not give us that. As my colleague Ben Simons often reminds me, in the end one can have a 1:1 map but this, as Lewis Carroll tells us: such map ” has never been spread out, yet, the farmers objected: they said it would cover the whole country, and shut out the sunlight!” and of course, they cannot harvest anything. Their solution is ingenious: “ So we now use the country itself, as its own map, and I assure you it does nearly as well” (Sylvie and Bruno Concluded by Lewis Carroll, 1893) . Whereas a 1:1 map (as long as we choose the right dimensions) of the map and the mapped, might suit genomes it does not provide us any information that we did not have already. This approach is clearly not working for the cell, let alone the inaccuracies on which it is often based. This is not surprising as we are creating the narrative and the map at the same time and, really, with few exceptions we never test if it works. Figures 7, 8 or 9 are just gimmicks to get our papers published, regurgitations of the data and not something that we can (or want) to test.

Engineers and architects also use maps but these are different. They do not try to represent anything that preexist but are blueprints for existence. The object, the building, does not predates the map. If an engineer or an architect would make fanciful designs (like many that appear in computer games or sci-fi movies) they might not be able to exist. A design needs to work. In fact, our knowledge of DNA and some basic properties of proteins does allow us today to make such designs for some of simple tasks. This is the burgeoning field of ‘synthetic biology’ and it works. But this is not what we need to do when we try to work out the functional essence of the cell. In Biology and beyond DNA, we have hardly had a chance to test our maps.

We need to think about our approaches. We need to think about the questions that we want or need to answer and then work accordingly. Use the right scale for our maps, but also and more importantly, what it is that we want to map. The detail that is required for a map of Madrid is not useful when trying to map the coastline of Spain. The contours that tell us so  much about mountains and ridges are of no interest when we find our way when riding the underground. I do not have an answer yet, but wanted to call our attention to the fact that we might be misguided in our approaches. Anybody who has looked at a cell with an open mind will feel like RL Stevenson with the map he drew from the book: it is not the original one. The original one is more interesting.