Dataset Information

A Comparison of Methods to Measure Fitness in Escherichia coli.

ABSTRACT: In order to characterize the dynamics of adaptation, it is important to be able to quantify how a population's mean fitness changes over time. Such measurements are especially important in experimental studies of evolution using microbes. The Long-Term Evolution Experiment (LTEE) with Escherichia coli provides one such system in which mean fitness has been measured by competing derived and ancestral populations. The traditional method used to measure fitness in the LTEE and many similar experiments, though, is subject to a potential limitation. As the relative fitness of the two competitors diverges, the measurement error increases because the less-fit population becomes increasingly small and cannot be enumerated as precisely. Here, we present and employ two alternatives to the traditional method. One is based on reducing the fitness differential between the competitors by using a common reference competitor from an intermediate generation that has intermediate fitness; the other alternative increases the initial population size of the less-fit, ancestral competitor. We performed a total of 480 competitions to compare the statistical properties of estimates obtained using these alternative methods with those obtained using the traditional method for samples taken over 50,000 generations from one of the LTEE populations. On balance, neither alternative method yielded measurements that were more precise than the traditional method.

SUBMITTER: Wiser MJ

PROVIDER: S-EPMC4427439 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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A Comparison of Methods to Measure Fitness in Escherichia coli.

Wiser Michael J MJ Lenski Richard E RE

PloS one 20150511 5

In order to characterize the dynamics of adaptation, it is important to be able to quantify how a population's mean fitness changes over time. Such measurements are especially important in experimental studies of evolution using microbes. The Long-Term Evolution Experiment (LTEE) with Escherichia coli provides one such system in which mean fitness has been measured by competing derived and ancestral populations. The traditional method used to measure fitness in the LTEE and many similar experime ...[more]

PMID: 25961572

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Project description:Three different label-free proteome quantification methods - APEX, emPAI and iBAQ - were evaluated to measure proteome-wide protein concentrations in the cell. All the methods were applied to a sample from Escherichia coli chemostat culture. A Pearson squared correlation of approximately 0.6 among the three quantification methods was demonstrated. Importantly, the sum of quantified proteins by iBAQ and emPAI corresponded with the Lowry total protein quantification, demonstrating applicability of label-free methods for an accurate calculation of protein concentrations at the proteome level. The iBAQ method showed the best correlation between biological replicates, a normal distribution among all protein abundances, and the lowest variation among ribosomal protein abundances, which are expected to have equal amounts. Absolute quantitative proteome data enabled us to evaluate metabolic cost for protein synthesis and apparent catalytic activities of enzymes by integration with flux analysis. All the methods demonstrated similar ATP costs for protein synthesis for different cellular processes and that costs for expressing biomass synthesis related proteins were higher than those for energy generation. Importantly, catalytic activities of energy metabolism enzymes were an order or two higher than those of monomer synthesis. Interestingly, a staircase-like protein expression was demonstrated for most of the transcription units. Fragment MS/MS spectra from raw files were extracted as MSM files and then merged to peak lists using the Raw2MSM version 1.7 [29], selecting top six peaks for 100 Da. MSM files for the three technical replicates of the same sample were concatenated to generate a single large peak list file with a MultiRawPrepare.pl script (http://msquant.alwaysdata.net) and subsequently searched with the Mascot 2.2 search engine (Matrix Science, London, UK) against the E. coli K-12 MG1655 protein sequence database downloaded 22.09.2009 from EcoGene 2.0 (http://ecogene.org), supplemented with common contaminants. Search parameters were as follows: two missed trypsin cleavage, fixed modification was set as carbamidomethyl (C), variable modifications were set as oxidation (M) and acetyl (protein N-term), 5 ppm precursor mass tolerance and 0.6 Da MS/MS mass tolerance. In order to estimate the false discovery rate (FDR) decoy search option was allowed. The Mascot search results were validated by the PeptideProphet and ProteinProphet algorithms [30] before the absolute protein expression indexes (APEX) [19] were calculated by the APEX Quantitative Proteomics Tool [25]. An estimated false positive rate (FPR) cut-off of less than 5% was used, which corresponded to the ProteinProphet probability p greater than 0.5. FPR less than 5% was chosen, as this resulted in a reasonable number of quantified proteins (1220), comparable with the iBAQ dataset (1334 proteins). Limiting the FPR to less than 1% would result in the loss of more than 200 proteins.

Dataset Information

A Comparison of Methods to Measure Fitness in Escherichia coli.

Publications

A Comparison of Methods to Measure Fitness in Escherichia coli.

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