Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.

Countless studies monitor the growth rate of microbial populations as a measure of fitness. However, an enormous gap separates growth-rate differences measurable in the laboratory from those that natural selection can distinguish efficiently. Taking advantage of the recent discovery that transcript...

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Main Authors: Kerry A Geiler-Samerotte, Tatsunori Hashimoto, Michael F Dion, Bogdan A Budnik, Edoardo M Airoldi, D Allan Drummond
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3783400?pdf=render
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spelling doaj-1e79a9a4385c4b17ba41b611abd5fc002020-11-24T20:50:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0189e7532010.1371/journal.pone.0075320Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.Kerry A Geiler-SamerotteTatsunori HashimotoMichael F DionBogdan A BudnikEdoardo M AiroldiD Allan DrummondCountless studies monitor the growth rate of microbial populations as a measure of fitness. However, an enormous gap separates growth-rate differences measurable in the laboratory from those that natural selection can distinguish efficiently. Taking advantage of the recent discovery that transcript and protein levels in budding yeast closely track growth rate, we explore the possibility that growth rate can be more sensitively inferred by monitoring the proteomic response to growth, rather than growth itself. We find a set of proteins whose levels, in aggregate, enable prediction of growth rate to a higher precision than direct measurements. However, we find little overlap between these proteins and those that closely track growth rate in other studies. These results suggest that, in yeast, the pathways that set the pace of cell division can differ depending on the growth-altering stimulus. Still, with proper validation, protein measurements can provide high-precision growth estimates that allow extension of phenotypic growth-based assays closer to the limits of evolutionary selection.http://europepmc.org/articles/PMC3783400?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Kerry A Geiler-Samerotte
Tatsunori Hashimoto
Michael F Dion
Bogdan A Budnik
Edoardo M Airoldi
D Allan Drummond
spellingShingle Kerry A Geiler-Samerotte
Tatsunori Hashimoto
Michael F Dion
Bogdan A Budnik
Edoardo M Airoldi
D Allan Drummond
Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
PLoS ONE
author_facet Kerry A Geiler-Samerotte
Tatsunori Hashimoto
Michael F Dion
Bogdan A Budnik
Edoardo M Airoldi
D Allan Drummond
author_sort Kerry A Geiler-Samerotte
title Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
title_short Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
title_full Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
title_fullStr Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
title_full_unstemmed Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
title_sort quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description Countless studies monitor the growth rate of microbial populations as a measure of fitness. However, an enormous gap separates growth-rate differences measurable in the laboratory from those that natural selection can distinguish efficiently. Taking advantage of the recent discovery that transcript and protein levels in budding yeast closely track growth rate, we explore the possibility that growth rate can be more sensitively inferred by monitoring the proteomic response to growth, rather than growth itself. We find a set of proteins whose levels, in aggregate, enable prediction of growth rate to a higher precision than direct measurements. However, we find little overlap between these proteins and those that closely track growth rate in other studies. These results suggest that, in yeast, the pathways that set the pace of cell division can differ depending on the growth-altering stimulus. Still, with proper validation, protein measurements can provide high-precision growth estimates that allow extension of phenotypic growth-based assays closer to the limits of evolutionary selection.
url http://europepmc.org/articles/PMC3783400?pdf=render
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AT bogdanabudnik quantifyingconditiondependentintracellularproteinlevelsenableshighprecisionfitnessestimates
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