Abstract
Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. With the advent of high-throughput techniques, significant amount of protein interaction (PPI) data has been catalogued for organisms such as yeast, which has in turn fueled computational methods for systematic identification and study of protein complexes. However, many complexes are dynamic entities - their subunits are known to assemble at a particular cellular space and time to perform a particular function and disassemble after that - and while current computational analyses have concentrated on studying the dynamics of individual or pairs of proteins in PPI networks, a crucial aspect overlooked is the dynamics of whole complex formations. In this work, using yeast as our model, we incorporate 'time' in the form of cell-cycle phases into the prediction of complexes from PPI networks and study the temporal phenomena of complex assembly and disassembly across phases. We hypothesize that 'staticness' (constitutive expression) of proteins might be related to their temporal "reusability" across complexes, and test this hypothesis using complexes predicted from large-scale PPI networks across the yeast cell cycle phases. Our results hint towards a biological design principle underlying cellular mechanisms - cells maintain generic proteins as 'static' to enable their "reusability" across multiple temporal complexes. We also demonstrate that these findings provide additional support and alternative explanations to findings from existing works on the dynamics in PPI networks.
Highlights
Most biological processes within the cell are carried out by proteins that physically interact to form stoichiometrically stable complexes
Even in the relatively simple model organism Saccharomyces cerevisiae, these complexes are comprised of many subunits that work in a coherent fashion
If a subset of proteins in one complex is temporally involved in the formation of another complex but at a different sub-cellular time, existing complex detection methods working solely on protein complexes from protein interaction (PPI) networks cannot disambiguate the two complexes, instead they produce a whole fused cluster of proteins originating from both complexes as a single predicted complex
Summary
Most biological processes within the cell are carried out by proteins that physically interact to form stoichiometrically stable complexes. Since the advent of “high-throughput” techniques in molecular biology, several screens have been introduced to infer physical interactions among proteins from organisms in a large-scale (“genome-wide”) fashion These have helped to catalogue significant amount of protein interactions in organisms such as yeast, thereby fueling computational techniques to systematically mine and analyse protein complexes from protein interaction (PPI) networks; for a survey of these methods, see [1]. If a subset of proteins in one complex is temporally involved in the formation of another complex but at a different sub-cellular time, existing complex detection methods working solely on PPI networks cannot disambiguate the two complexes, instead they produce a whole fused cluster of proteins originating from both complexes as a single predicted complex This severely impacts the accuracy of the predictions, but more critically our understanding of the underlying cellular organization. They suggest that if suitable information about the ‘timing activities’ of proteins can be obtained, the dynamical nature of the underlying organizational principles guiding protein interaction networks and complexes can be better understood
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