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Title: Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates

Abstract

Here, system-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now"º and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption thatmore » isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.« less

Authors:
ORCiD logo; ; ; ;
Publication Date:
Research Org.:
Boston Univ., MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1340026
Alternate Identifier(s):
OSTI ID: 1347524
Grant/Contract Number:  
SC0012627
Resource Type:
Published Article
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Name: PLoS ONE Journal Volume: 12 Journal Issue: 1; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science (PLoS)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; evolutionary rate; deletion mutation; Saccharomyces cerevisiae; enzyme metabolism; enzymes; gene mapping; evolutionary genetics; epistasis

Citation Formats

Jacobs, Christopher, Lambourne, Luke, Xia, Yu, Segrè, Daniel, and Galli, ed., Alvaro. Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates. United States: N. p., 2017. Web. https://doi.org/10.1371/journal.pone.0170164.
Jacobs, Christopher, Lambourne, Luke, Xia, Yu, Segrè, Daniel, & Galli, ed., Alvaro. Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates. United States. https://doi.org/10.1371/journal.pone.0170164
Jacobs, Christopher, Lambourne, Luke, Xia, Yu, Segrè, Daniel, and Galli, ed., Alvaro. Fri . "Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates". United States. https://doi.org/10.1371/journal.pone.0170164.
@article{osti_1340026,
title = {Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates},
author = {Jacobs, Christopher and Lambourne, Luke and Xia, Yu and Segrè, Daniel and Galli, ed., Alvaro},
abstractNote = {Here, system-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now"º and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.},
doi = {10.1371/journal.pone.0170164},
journal = {PLoS ONE},
number = 1,
volume = 12,
place = {United States},
year = {2017},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1371/journal.pone.0170164

Figures / Tables:

Fig. 1 Fig. 1: Comparison of the gene dispensability metrics: function-loss cost and gene-loss cost. Each toy scenario (A–C) represents a possible gene-to-reaction mapping configuration in its simplest form. Gene-loss cost (orange arrows, top row) propagates gene deletions “downwards” through logic gates to determine which reaction(s) are removed from the network, whichmore » in turn determine model fitness predictions. Function-loss cost (green arrows, bottom row) conceptually reverses this process, first calculating the fitness cost of removing each reaction in the network and then propagating these costs “upwards” to all associated genes, whereby they are summed together. For enzyme complexes (A), gene-loss cost and function-loss cost are identical and are equal to the fitness cost of the associated reaction’s removal. For isoenzymes (B), the gene-loss cost is zero in all cases (because either gene will satisfy the logic gate’s requirement that at least one enzyme is present), however the function-loss cost is as in scenario (A). For multi-function enzymes (C), the gene-loss cost is determined by the cost of removal of all reactions that are dependent on that gene according to the gene-to-reaction mapping, while function-loss cost is equal to the total summed cost of all its associated reactions’ removal cost.« less

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    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.