Thoughts on T.S. Eliot, Ernest Hemingway and genetics

Cats are cool. Everybody knows that. Cats can also have very characteristic traits. Everybody knows this, too, particularly since Andrew Lloyd Webber’s musical Cats, where he popularised T.S.Eliot’s collection of poems Old Possum’s Book of Practical Cats. Remember them? Gus, the theatre cat? “His coat’s very shabby/ He’s thin as a rake/ And he suffers from palsy that makes his paw shake”. The Old Gumbie Cat? “Her name is Jennyanydots/ Her coat is of the tabby kind with tiger stripes and leopard spots”. And the list goes on.

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“Macavity. Macavity, there’s no one like Macavity. / He’s a fiend in feline shape. / A monster of depravity.”

Yet, not only lovers of literature and music are enthralled by the diversity of features that cats display. Geneticists have also long discovered this phenomenon, which can be very useful to figure the genetic changes that are responsible for a given trait (geneticists call these traits “phenotypes”). So, ok, obviously noone has ever found the Mr. Mistofelees-mutation or the Rum-Tum-Tugger allele, but some of the other things they’ve been looking into is still pretty amazing. Continue reading

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Added value: how a corrigendum should be

It has been a low-key week: with deadlines rapidly approaching I been busy writing applications for postdoc fellowships. And while I have been developing some ideas for longer, multi-part blog posts, they are not yet ready to be published. But, while I was going through the literature for my applications, I actually came across a rather heart-warming example of a great… corrigendum. OK, this might sound strange, but I think thorough follow-up of critique to a scientific paper can be just as essential to a paper as the initial results. Being wrong or making mistakes is OK, but not acknowledging this, is not. After all, an essential part of science is peer-review. And this includes not only the peer-review  associated directly with the publication process. A really good example of really bad, unscientific behaviour, is the “bacterium that can grow on arsenic” story, which was widely contested (see here and here), but – I believe – the authors never officially retracted the paper (?).

So, the post today is about a corrigendum, which is just like my vision of how a corrigendum should be like.

The story started about two years ago, when Matthias Selbach’s group in Germany published a research paper in Nature. They described a rather straightforward experiment to test how protein abundance is related to mRNA abundance, and how transcription and translation rates influence this relationship. In essence, they measured the abundance of proteins by mass spectrometry, and the abundance of the respective mRNAs by RNA-Seq in cultured cells. Moreover, by labeling newly synthesized proteins and RNAs they also measured transcription and translation rates. Yet, while theoretically straightforward, the experiment was technically challenging (made possible only through recent advances in sequencing and mass spectrometry technology), and definitely very timely, because previous, similar studies had only ever looked at a selected subset of genes. The Selbach paper found that ~40% of the variance in protein levels could potentially be explained by their mRNA levels, but including data of translation rates could very much increase the predictive power, indicating that translation rates have an important role in determining protein levels. As part of their analysis they also calculated absolute protein copy numbers. For this, they used proteins of known concentration, mixed them with their sample, and included them in the mass-spectrometry measurement. They then used these known amounts of proteins to calibrate “iBAQ intensities” (units obtained in mass spec), and subsequently converted the iBAQ values of the cellular proteins to molar amounts based on this calibration.

So far, so good.

However, in March this year, they published a corrigendum/erratum. It starts with: “Mark Biggin […] contacted us, noting that our mass-spectrometry-based protein copy number estimates are lower than several literature-based values.” How wonderful! No wishy-washy beating-about-the-bush. Instead: a precise explanation of the problem. Next, they explain how they checked their published data and identified a mistake in their calibrations (they used the calibration values from an unrelated experiment in their analysis pipeline). But it gets even better. They state: “To further validate copy numbers” and describe two more tests they performed for validation, one based on comparing band intensities on Western blots and another mass-spec approach, called selected reaction monitoring.

So, all in all, I think that’s pretty decent, and – at least for this week – it restored my faith in the scientific community. I wish I would always perform two additional experiments, when someone points out a potential flaw in my work. Luckily, their error did not influence the major findings of their original paper, but I hope they would have been so open about correcting their mistakes, even if it had.

The Uncommon Microscopist

I am an ardent admirer of Alan Bennett’s work. One of my favourite books of all time, The Uncommon Reader, was penned by him. It’s a fictional story about the Queen of England, and what happens when she starts reading books. While the moral of the story is about how literature can broaden your horizon, it also contains an extremely comic description of the grave consequences the Queen’s reading has on her entire entourage and ultimately her country.

the-uncommon-reader-by-alan-bennettWell, yesterday, I stumbled upon a little post by the Schuh lab in Cambridge. The page documents the Queen’s visit to the lab, when she came to Cambridge for the opening ceremony of the new MRC LMB building in May 2013. The page has the title “the queen learns about research in the Schuh lab”, and contains a picture with the caption: „The Queen even looked down the microscoscope to study a group of mouse oocytes“. I do wonder. If reading a book can have a profound impact on the Queen, her followers and her country – what might happen when she learns about research, not to mention when she studies a group of mouse oocytes…?

Is more really better?

As long as I can remember, I’ve heard teachers, professors and politicians say that we should encourage more high-school and university students to pursue a career in science. And I used to be a believer. After all, the people who said this, were the ones at the top, the ones with a proper oversight of things. However, today, I’m not so sure anymore. In fact, I’m becoming more and more convinced that encouraging people to pursue a career in science (or at least research) may just be a way for universities to generate competition and thus obtain a source of cheap labor.

conspiracy-theory-alert_display_imageSounds like a conspiracy theory? Maybe. But here’s why:

As I grow older, more and more of my friends, who used to work in research (and who really liked doing so) drop out. They move towards alternative careers, such as science communication, industry, teaching etc. And they generally list the same reasons for doing so:

1. Early-career researchers get little reward for their work: this primarily means that they consider themselves being underpaid and overworked. Money matters.

2. There’s too much insecurity, pressure and competition as you move up the ranks: there are many, many good scientists with great publication records, who’d all like to have a junior group leader or tenure track position. Obviously, the more people you feed into the system at the lower ranks, the more will compete for the jobs at the top. But there are increasingly less long-term contracts handed out . Security matters. Moreover…

3. … science is becoming less of a vocation and more like a job: It seems to be less crucial nowadays how good or creative you are, and increasingly important how well you can manage and advertise yourself. Your ideas and hands-on experience seem to matter less than what your CV looks like, in what labs you’ve worked and how well you’ve published. And since the results of your first five to ten years of research may therefore define your later career options, this discourages “outiside-the-box-thinking” and taking on risky projects. Often this also means, that science-related non-research activities are undervalued: I’ve filled in fellowship applications where there is no option to include teaching or the organization of science events as an asset.This is extremely frustrating, if you consider that much of science knowledge is actually passed through the grapevine: by great teachers and lecturers who transmit their love of science as well as up-to-date knowledge, and by experienced lab staff who show you the do’s and do not’s of experimental design and lab techniques.

Motivated teachers matter!

Motivated teachers matter!
from “Piled Higher and Deeper” by Jorge Cham http://www.phdcomics.com

So, all in all, my interpretation of the data: thanks to increasing numbers of PhD students and postdocs, there’s plenty of “raw material” to chose from. Therefore PIs and legislators can get away with providing low job security, as well as relatively low salaries. Also, having more early-career researchers also requires less personal touch and more standardized metrics.  And keeping it this way means a cheap workforce, which is why people at the top encourage more students to pursue a career in research. And thus the vicious circle continues…

Still think it’s a conspiracy theory? Maybe. Maybe also have a look at Paula Stephan’s book, How Economics Shapes Science. It provides a much broader and nuanced overview of the interplay between economics and science, including a detailed analysis of supply and demand in research.

But please keep this rant in mind, next time someone tells you we need to recruit more students into science!