A number of badly-trained technicians complained in twitter (e.g. check here) about a biochemist from UT Southwestern and compared him with Dan Graur. That is one step below comparing someone with Atilla the Hun or Genghis Khan, and we had to check what this biochemist is up to.
Based on what we found, we believe this guy is the real deal !! We agree with much of what he says and recommend you to listen to him as well. Here are the last three commentaries from Steven McKnight.
Starting with the latter of these problems, I give a humorous example of how things have gone haywire. Several years ago my colleagues Jian Wang, Peter Alexander and I reported our discovery that mouse embryonic stem cells consume threonine as a hydrocarbon fuel. Mouse ES cells grow at an incredibly rapid clip. Their mitotic doubling time is only four to five hours in duration, exceeding that of the most rapidly growing cancer cells and approaching the doubling time of laboratory strains of yeast. Hypothesizing that this might reflect the possibility that ES cells exist in an unusual metabolic state, we measured the levels of scores of metabolites as a function of ES cell differentiation. When cued to differentiate upon withdrawal of leukemia inhibiting factor and administration of retinoic acid, the growth rate of ES cells slows from a four- to five-hour doubling time to 24 hours.
By observing profound changes in the levels of metabolites associated with one carbon metabolism, we stumbled over the fact that pluripotent ES cells express the threonine dehydrogenase, or TDH, enzyme at a 1,000-fold higher level than any mouse tissue or cell line that we tested, and they use the enzyme to consume threonine as a metabolic fuel. Depletion of threonine from the culture medium killed mouse ES cells, and specific inhibitors of the TDH enzyme kill mouse ES cells while having no effect on any other cultured cells tested to date. We recognized this to be analogous to the metabolic state of rapidly growing bacterial and yeast cells, and we made reference to microbiologists upon whose shoulders we stood.
Three years later, the Harvard University labs of Lewis Cantley and George Daley published a nice follow-up paper in the journal Science. My colleagues and I were delighted to see the replication and extension of our earlier work, yet I was mortified to see that the Harvard manuscript made reference to a paper that I had entirely missed. Yes, the Cantley/Daley paper did cite our paper, yet it also attributed the discovery of threonine dependence of mouse ES cells to a paper from the laboratory of Eric Lander of the Broad Institute. The latter paper was published a full year before our 2009 Science paper.
I immediately downloaded the Broad paper and scoured it from end to end. To my confusion, I could not find the word threonine in the entire paper, much less threonine dehydrogenase or anything to do with the metabolic state of mouse ES cells. Inquiries to Cantley and Daley led me to a postdoctoral fellow who instructed me to view the supplemental data included in the Broad paper. Sure enough, the study listed thousands of genes selectively expressed in undifferentiated ES cells, and the gene encoding threonine dehydrogenase was embedded within the list. This was an Alice in Wonderland moment for me, showing that an entirely new era of attribution had evolved. Any discovery that stems from any gene listed in the supplemental data of the Broad manuscript can now be attributed to that paper! Instead of thinking Are you kidding me?, I recognize that we are now adapting to the new reality: Citations are no longer your fathers Oldsmobile.
This is very similar to our experience with another Broadster working closely with Lander.
Now, to the second of two evils: the evolution of scientific clubs. Back when we used to walk miles to school, the scientific meetings we attended had some level of breadth. Among all meetings I attended back in the 1970s and 1980s, the two best were the Gordon Conference on Biological Regulatory Mechanisms and the Arolla Workshop. Both were relatively small meetings, including only perhaps 100 to 150 participants. Despite the small size of these meetings, both sported an intellectually thrilling breadth of scientific scope. One might hear about mobile genetic elements in maize, mating type switching in yeast (where sirtuin proteins came from), UV-mediated release of phage lambda from its lysogeic state, or the genetics of pattern formation in fruit fly embryos. Methods of genetics, biochemistry and molecular biology were applied to zoo- or botanical garden-like distributions of animals, microbes and plants. When one left such meetings, horizons of perspective were broadened. Boy, were those meetings fun.
Fast-forward 30 years, and what do we now have? The typical modern biomedical meeting spends a week on a ridiculously thin slice of biology. There are entire meetings devoted to the hypoxic response pathway, sirtuin proteins, P53, mTor or NFkB. If a scientist studies some aspect of any of these domains, he or she absolutely has to attend these mindless meetings where, at most, some miniscule increment of advancement is all to be learned.
Damn the fool who does not attend these meetings: The consequence is failure to maintain club membership. And why is club membership of such vital importance? Yes, precisely, there is nearly a one-to-one correspondence between these clubs and CSR study sections. To think that a grant applicant would have even a prayer of winning a fundable score from a study section wherein the applicant is not a club member is to be equated with idiocy.
Whether clubs came from committees or vice versa matters not that is where evolution of our biomedical enterprise has taken us. Upon closing out his presidency in 1960, Dwight Eisenhower offered the cautionary statement, Beware of the military industrial complex. I close with a similar warning: Beware of the biomedical industrial complex. In subsequent essays, I will offer ideas on how we might reverse untoward trends.
and the best of all -
Here is the idea on big science. Once we gather enough of it, really smart people will be able to extract all of the diamonds of biology. Magically, for example, they will be able to use big data to predict correctly that cells have an enzyme that senses intracellular DNA and then triggers the production of cyclic GAMP, which then activates the STING enzyme to mount an innate immune response. When this happens, we wont need the biochemical skills of James Chen, who painstakingly discovered the aforementioned pathway.
Had we had access to big data science 30 years ago, we would not have needed Tom Cechs chemical and biochemical acumen to discover catalytic RNA. Geez, would life have been simpler! The magic claw of big data science could have seen all of the discoveries of significance and simply plucked them out of the pile of massive data sets.
OK, enough foolishness. There is a place for everything, including big data science. The point I seek to make in this inaugural essay is the simple prediction that, as we peer into the looking glass of the future, Chen- and Cech-like discoveries abound. Not being a gambler, I will not short the stock of big data in anticipation of the bursting of its bubble. On the other hand, given that the market cap of mechanistic biochemistry may be at an all-time low, I could not be more bullish on our stock.
Time will tell whether big data science is just a Ponzi scheme or will instead dazzle us with magnificent discoveries. If it does, the reductionist, mechanistic approaches now out of fashion may fade into extinction. I trust that readers will see where my money is: We biochemists are down but not out.