Abstract
We proposed a novel interaction potential landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the interaction landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent interaction potential landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins prefer to interact with other essential proteins. Overall, we showed that the interaction potential landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.
Highlights
We proposed a novel interaction potential landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae
We hypothesize that the uncoupling of proteome and transcriptome in replicative aging may lead to protein–protein interaction profile changes, which motivated us to construct age-dependent Protein Interaction Potential landscapes (PIPLs) using the age-dependent proteome and transcriptome data along the yeast replicative aging[15]
The present work on the protein interaction potential landscape during aging suggest that essential hub genes and their interactions may be a critical factor of proteostasis and/ or aging
Summary
We hypothesize that the uncoupling of proteome and transcriptome in replicative aging may lead to protein–protein interaction profile changes, which motivated us to construct age-dependent PIPLs using the age-dependent proteome and transcriptome data along the yeast replicative aging[15]. We listed the numbers of proteins (Fig. 5b) or transcripts (Fig. 5c) that were included in both the PIN the aging proteomics and transcriptomics data set These trends of protein and/or transcript abundances may partly explain the basins and ridges observed in the protein interaction potential landscapes. The protein turnover data were taken from (a) the CellSys2017 set and (b) the CellRep2014 set, respectively The landscapes from both sets showed significant differences between the protein abundance-based (top panels) and transcript level-based (bottom panels) PIPLs. The contour maps of the landscapes of the aging cells at young (10.7 h) and old (72.3 h) are shown for comparisons. The morphology parameters from the SCMD2 d atabase[36] had been used in the PIPL as shown in Figure S2 of the supplementary materials
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