Wish you could do complex cellular and molecular biology from the comfort of your couch? The lab of your dreams (aka, sitting on your computer in front of your TV) may be just over the horizon.

Just as Peter L. Freddolino and Saeed Tavazoie title their July 20th commentary in Cell, this month has witnessed the “dawn of virtual cell biology” (Source). Published in the journal Cell, a group lead by researchers at Stanford University released the first ever whole-cell computational model capable of predicting phenotype from an associated genotype (Source).

The authors of the model, which describes a complete life cycle for the human pathogen Mycoplasma genitalium, claim their work accounts for all included molecules and their interactions. Using a combination of data aggregated from over 900 publications in addition to over 1900 individual experimental observations, the effort is certainly titanic. This is the first time that such a complete model has been published, and the confirming evidence is convincing; the group characterized their model with observations of, among other things, cell growth rate  (by OD550), gene expression levels (by mRNA) and metabolism (using the intracellular concentrations of ATP, GTP, FAD(H2), NAD(H), and NADP(H)).

Personally, I’m excited to see how the systems biology community responds to this paper. I’ve found that a recurring (and often times frustrating) statement in cellular and molecular biology is the “well, that’s not the whole story” line. While this model is certainly complex, information-dense and stands up to testing, I find it hard to look at it and say “yep, that’s all.” I can’t help but wonder how our lack of completely understanding biological regulation (a la methylation, post-transcriptional and translational modifications, cell signaling, etc) will lead to refinements of the model – but then again, that is exactly where models like this come in handy. When the model doesn’t agree with biology, that’s where insights are hiding. Both the paper and commentary are highly recommended reading.

References

• Freddolino, P.L. & Tavazoie, S. The Dawn of Virtual Cell Biology. Cell 150, 248-250 (2012). (Source)
• Karr, J.R. et al. A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell 150, 389-401 (2012). (Source)