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Title: Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments

Authors:
; ; ;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1345285
Grant/Contract Number:
AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
Journal Name: PLoS Computational Biology (Online); Journal Volume: 12; Journal Issue: 6; Related Information: CHORUS Timestamp: 2017-06-24 13:21:23; Journal ID: ISSN 1553-7358
Publisher:
Public Library of Science (PLoS)
Country of Publication:
United States
Language:
English

Citation Formats

O’Brien, Edward J., Utrilla, Jose, Palsson, Bernhard O., and Maranas, ed., Costas D. Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments. United States: N. p., 2016. Web. doi:10.1371/journal.pcbi.1004998.
O’Brien, Edward J., Utrilla, Jose, Palsson, Bernhard O., & Maranas, ed., Costas D. Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments. United States. doi:10.1371/journal.pcbi.1004998.
O’Brien, Edward J., Utrilla, Jose, Palsson, Bernhard O., and Maranas, ed., Costas D. 2016. "Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments". United States. doi:10.1371/journal.pcbi.1004998.
@article{osti_1345285,
title = {Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments},
author = {O’Brien, Edward J. and Utrilla, Jose and Palsson, Bernhard O. and Maranas, ed., Costas D.},
abstractNote = {},
doi = {10.1371/journal.pcbi.1004998},
journal = {PLoS Computational Biology (Online)},
number = 6,
volume = 12,
place = {United States},
year = 2016,
month = 6
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1371/journal.pcbi.1004998

Citation Metrics:
Cited by: 14works
Citation information provided by
Web of Science

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  • Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 singlemore » nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). Furthermore, this study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.« less
  • Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 singlemore » nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). Furthermore, this study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.« less
  • Selected reaction monitoring-mass spectrometry (SRM-MS) is an emerging technology for high throughput targeted protein quantification and verification in biological and biomarker discovery studies; however, the cost associated with the use of stable isotope labeled synthetic peptides as internal standards is prohibitive for quantitatively screening large numbers of candidate proteins as often required in the pre-verification phase of biomarker discovery. Herein we present the proof-of-concept experiments of using an 18O-labeled 'universal' reference as comprehensive internal standards for quantitative SRM-MS analysis. With an 18O-labeled whole proteome sample as reference, every peptide of interest will have its own corresponding heavy isotope labeled internalmore » standard, thus providing an ideal approach for quantitative screening of a large number of candidates using SRM-MS. Our results showed that the 18O incorporation efficiency using a recently improved protocol was >99.5% for most peptides investigated, a level comparable to 13C/15N labeled synthetic peptides in terms of heavy isotope incorporation. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into mouse plasma with an 18O-labeled mouse plasma reference. A dynamic range of four orders of magnitude in relative concentration was obtained with high reproducibility (i.e., coefficient of variance <10%) based on the 16O/18O peak area ratios. Absolute and relative quantification of C-reactive protein and prostate-specific antigen were demonstrated by coupling an 18O-labeled reference with standard additions of protein standards. Collectively, our results demonstrated that the use of 18O-labeled reference provides a convenient and effective strategy for quantitative SRM screening of large number of candidate proteins.« less
  • The throughput for proteomics measurements that provide broad protein coverage is limited by the quality and speed of both the separations and the subsequent mass analysis; present analysis times can range anywhere from hours to days (or longer). We have explored the basis for ultrahigh-throughput proteomics measurements using high-speed reversed-phase liquid chromatography (RPLC) combined with high accuracy mass spectrometric measurements. Time-of-flight (TOF) and Fourier transform ion cyclotron resonance (FTICR) mass spectrometers were evaluated in conjunction with 0.8-µm porous C18 particle-packed RPLC using 50 µm i.d. capillary columns for identifying peptides using the Accurate Mass and Time (AMT) tag approach. Peptidemore » RPLC relative retention (elution) times could be correlated to within 5% to elution times that differed by at least 25-fold in speed, which allowed peptides to be identified using AMT tags identified from much slower RPLC-MS/MS analyses. When coupled with RPLC, the mass spectrometers operated at fast spectrum acquisition speeds (e.g., 0.2 sec for TOF and either 0.3 or 0.6 sec for FTICR), and peptide mass measurement accuracies of better than ±15 ppm were obtained. Ion population control during fast separations limited the mass accuracies obtained with FTICR, but the use of fast regulation of ion populations using automated gain control improved the mass accuracies. The detection of low abundance species was somewhat suppressed for fast analyses. The proteome coverage obtained using AMT tags was limited by the separation peak capacity, the sensitivity of the MS, and the accuracy of both the mass measurements and the relative RPLC peptide elution times. Experimental results demonstrated that accuracies of 5% for the RPLC relative elution times and better than ±15 ppm for mass measurements were sufficient for confident identification of >2800 peptides and >760 proteins from >13,000 different detected species from a Shewanella oneidensis tryptic digest.. The TOF instrumentation was found to be preferable for faster separations (of <120 sec), while FTICR MS was more effective for analysis times of >150 sec due to the improved mass accuracies achievable with longer spectrum acquisition times. The present work demonstrates the feasibility of very high throughput proteomics measurements and indicates additional significant improvements in throughput are achievable by further increasing the speed of high peak capacity separations, as well by increasing the measurement sensitivity and the accuracy of mass measurements.« less