STOCHASTIC ORGANELLE BIOGENESIS [O'SHEA LAB]
June 10th, 2014
Cells are kind of like little people. Just like we have organs like our heart, lungs and brain that are responsible for core physiological functions keeping us alive, cells have little compartments known as organelles that provide optimal chemical environments for cell biological processes fundamental to life such as gene transcription in the nucleus and energy generation in the mitochondria. Now unlike macroscopic objects like our bodies and organs, however, cells are microscopic objects whose lives are constantly buffeted by randomizing forces like thermal noise or fluctuations due to the small number of molecules involved in many cellular processes. So while it is relatively easy to understand how large-scale chemical and mechanical feedbacks can keep organ numbers stable (the vast majority of us walk around with 1 heart, 2 lungs, 1 brain, etc.), the precision with which organelle numbers are maintained remained an open question. Do cells count the number of a given organelle they contain?
For some cases the answer is a resounding yes. Nuclei and centrioles, for example, are typically maintained at strictly maintained copy numbers under strong feedback control for obvious reasons – if these organelles were allowed to exhibit large copy number variability cells almost certainly would suffer massive genetic perturbations that could lead to terrible outcomes like cell death or uncontrolled proliferation. For other cases however it was not so clear, with the conventional wisdom being that cells do exert at least some control on the precision of organelle numbers. Lacking, however, were systematic comparisons of experimentally measured organelle copy number fluctuations with theoretical expectations of how big those copy number fluctuations could be. In a recent paper published in eLife, Shankar Mukherji and Erin O’Shea provided just such a comparison and came to the conclusion that cells appear to tolerate much more variability in organelle copy numbers than was expected.
The core of Mukherji and O’Shea’s work is an abstract mathematical model that compresses the myriad details of organelle biogenesis into four simple processes that can increase or decrease organelle number: de novo organelle synthesis and fission can create new organelles, while fusion and decay can reduce organelle numbers. They then used a powerful tool from the field of statistical physics, known as the fluctuation-dissipation theorem, to analyze their model and derive an equation that related how the magnitude of organelle number fluctuations depends on the processes of organelle creation and destruction. They then tested their mathematical framework on a collection of the endomembrane organelles of the budding yeast Saccharomyces cerevisiae.
In the cases of the Golgi apparatus and vacuole, whose biogenesis pathways are well known, the theoretically predicted and experimentally measured fluctuations matched well. Given that the model contained no feedback control mechanisms to stabilize organelle numbers, the close match between theory and experiment suggests that far from precisely controlling their numbers, cells appear to tolerate the theoretically maximum level of fluctuations that the Golgi and vacuole biogenesis pathways could generate.
Finally, having gained confidence in the model’s predictive power, they then turned to see if the fluctuations could yield insight into organelles whose biogenesis mechanisms were less understood. The case of the yeast peroxisome turned out to be just such an example. There has been a long-running debate over the origin of new peroxisomes in the cell, with compelling evidence supporting both de novo synthesis from the endoplasmic reticulum and fission from pre-existing peroxisomes. The equation Mukherji and O’Shea derived provided a clear way to distinguish between these possibilities: large fluctuations would favor fission dominated peroxisome production, while small fluctuations would favor de novo synthesis. Experimentally, Mukherji and O’Shea saw evidence for both – in conditions in which peroxisomes are relatively dispensable, measured peroxisome number fluctuations were small while in conditions in which peroxisomes are actively proliferated measured fluctuations were large, consistent with a switch from de novo synthesis to fission dominated peroxisome biogenesis. The case of the peroxisome points to the possibility that far from being an experimental nuisance, fluctuations in organelle copy number can actually be used to infer the mechanisms dominating the production of a subcellular structures generally.
Read more in eLife