Signal Transduction, Control of Metabolism, and Gene Regulation

19 Jun 2013 11:50

Things happen to cells: they run into various chemicals, they get heated and cooled, they get hit by photons of various frequencies, they get stretched and sheared and electrified. Cells are also sensitive to some of these events; they respond to them in characteristic, and generally adaptive, ways. The process linking the detection of certain kinds of external events to biochemical responses on the part of the cell is called signal transduction, even when the events aren't what one might plausibly think of as signals.

Two very important kinds of responses cells can make to signals are to change what and how they metabolize things, and how much of which of their genes they are expressing. Of course, since genes are expressed as proteins, and many (I think most) proteins are enzymes, i.e., metabolically active, control of metabolism and the regulation of gene expression are intimately linked, though you can alter one without (immediate) affect on the other. Sometimes metabolic control aims at homeostasis --- at maintaining constant levels of some variables, or constant rates of some processes --- but not always; sometimes adaptation demands change.

The metabolic network of even a simple cell is huge and convoluted; gene regulation is also huge and convoluted, and the only reason diagrams of signal transduction pathways aren't as bad is that their study is much younger.

There is no possible way I can master the literature on these subjects. I don't think even the experts can. (Certainly the larval experts, like my little brother, don't even bother --- i.e., everyone specializes.) It's said that the number of published papers on signal transduction alone doubles every year, though I can't remember where I read that.


Why do so many different signal transduction pathways share common chemicals? How does the cell keep its messages from getting crossed? Are the different pathways spatially segregated, or do they use the same chemicals in different ways, or perhaps just to different amounts?

How far can one go in inferring regulatory networks and connections from "black box", input-output data, e.g., gene expression data obtained from microarrays? What such things give one, directly, is a very abstract model of the dynamics of metabolism and gene expression; how can this be connected with chemical kinetics? Can kinetics be used to constrain and improve the inference of the dynamics? What can we say about functional architecture (wiring diagrams), as opposed to kinetic mechanisms, from black box data? --- This subject now has a notebook of its own.

What are the common kinetic mechanisms, and why?

What are the common functional architectures, and why?

What do people mean by "robustness" here? What should they mean?

For a cell to respond adaptively to changes in its environment, it must be able to sense that environment, distinguish different kinds of environmental signals (including those produced by other cells), and determine and execute an appropriate reaction. At each step, but especially the last, it faces a computational task. So: What kind of computation is this? What kinds of formal models of computation are appropriate to it? How can one combine computational information with black-boxs transduction and kinetics?

See also: Biochemical Network Evolution; Bioinformatics; Biological Computers; Biotechnology; Claude Bernard; Complex Networks; Developmental Biology; Gene Expression Data Analysis; Molecular Biology; Random Boolean Networks; Transducers.