Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells

Virginie’s first paper on her thesis work, “Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells” was published yesterday at PeerJ. She first put it up as a preprint (v1 here
revised v2 here and then submitted it – my first experience of this and something I will certainly do again.

At the heart of the paper is a simple question: “What is stemness?” The definition of an embryonic stem cell is that it can self-renew and form all parts of the body. So the question is central to our understanding of metazoan cell biology. To get to what could be termed a first level answer, Virginie performed a meta analysis of published transcriptome data. This highlights a major problem: we have few standards in biology and meta analyses are not straightforward. Indeed, some datasets are pretty much incompatible.
What we were particularly interested in was the relation between extracellular proteins, transcription and stemness. This is because the extracellular space and plasma membrane seem to be at the edge of the map in many analyses. Yet it is the extracellular proteins of metazoa that have changed the most and complexity of these proteins scale with organism complexity (excellent paper by Vogel and Chothia on the subject here).

Indeed, it is precisely the extracellular proteins that are manipulated in attempts to generate defined culture conditions for stem cell maintenance and their differentiation. Yet we lack systematic analyses of these proteins in the context of stemness.

As Virginie points out in the paper, using mRNA as a proxy for proteins is, of course, a major approximation. Nevertheless, the analyses demonstrate that beyond the outer surface of the embryonic stem cell plasma membrane lies a rich field, ready for picking. It is complicated, but then to expect that molecular phenomena that underlie fundamental biology to be simple is never going to happen. So the way is open to test some of these candidates to see whether the mRNA-based analyses do indeed identify extracellular proteins with a role in stemness and then it will be time for multidimensional proteomics – as beautifully described in different systems by Angus Lamond in the very stimulating seminar he delivered here on September 22.

I will end on subjects close to my heart.

My “natural” prejudice was that heparin-binding proteins might be particularly interesting and this looks to be true from Virginie’s data. So another angle to pursue is the large bull elephant that lurks in the small room of systems biology: glycosaminoglycans. These are not primary gene products so never figure in analyses of protein function.

Our catalogue of interactions is grossly incomplete. I think I am allowed to say this, as someone who has spent most of his career trying to measure protein-protein and protein polysaccharide interactions. Protein-protein interactions are catalogued according to “stringency”, a measure of the strength of the evidence for an interaction. However, we have to use these data on a ‘global’ basis. That is, experimental evidence for an interaction acquired in biological system A is assumed to hold true in biological system B. We have to make this assumption, because our coverage of molecular interactions is so very poor.

Open access and preprints. PeerJ was again an excellent experience and so was the preprint. Something I realised rather late in the day was that my use of supplementary information was entirely directed by the notion of print media: you put lots of stuff there to save paper. We caught this one at revision and re-organised the manuscript, so most of the data are in the paper. It makes sense and only a side story or “raw” annotated data for which there is no central data repository need go into supplementary.

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