Strategies for metagenomic-guided whole-community proteomics of complex microbial environments.
Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predict...
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2011
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oai:doaj.org-article:668b5a86f28b45b38231d8828db584f92021-11-18T07:33:41ZStrategies for metagenomic-guided whole-community proteomics of complex microbial environments.1932-620310.1371/journal.pone.0027173https://doaj.org/article/668b5a86f28b45b38231d8828db584f92011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22132090/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predictions from environmental metagenomic sequences has been challenging because of the variable overlap between proteomic datasets and corresponding short-read nucleotide sequence data. In this study, we have benchmarked several strategies for increasing microbial peptide spectral matching in metaproteomic datasets using protein predictions generated from matched metagenomic sequences from the same human fecal samples. Additionally, we investigated the impact of mass spectrometry-based filters (high mass accuracy, delta correlation), and de novo peptide sequencing on the number and robustness of peptide-spectrum assignments in these complex datasets. In summary, we find that high mass accuracy peptide measurements searched against non-assembled reads from DNA sequencing of the same samples significantly increased identifiable proteins without sacrificing accuracy.Brandi L CantarelAlison R EricksonNathan C VerBerkmoesBrian K EricksonPatricia A CareyChongle PanManesh ShahEmmanuel F MongodinJanet K JanssonClaire M Fraser-LiggettRobert L HettichPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 11, p e27173 (2011) |
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Medicine R Science Q Brandi L Cantarel Alison R Erickson Nathan C VerBerkmoes Brian K Erickson Patricia A Carey Chongle Pan Manesh Shah Emmanuel F Mongodin Janet K Jansson Claire M Fraser-Liggett Robert L Hettich Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
description |
Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predictions from environmental metagenomic sequences has been challenging because of the variable overlap between proteomic datasets and corresponding short-read nucleotide sequence data. In this study, we have benchmarked several strategies for increasing microbial peptide spectral matching in metaproteomic datasets using protein predictions generated from matched metagenomic sequences from the same human fecal samples. Additionally, we investigated the impact of mass spectrometry-based filters (high mass accuracy, delta correlation), and de novo peptide sequencing on the number and robustness of peptide-spectrum assignments in these complex datasets. In summary, we find that high mass accuracy peptide measurements searched against non-assembled reads from DNA sequencing of the same samples significantly increased identifiable proteins without sacrificing accuracy. |
format |
article |
author |
Brandi L Cantarel Alison R Erickson Nathan C VerBerkmoes Brian K Erickson Patricia A Carey Chongle Pan Manesh Shah Emmanuel F Mongodin Janet K Jansson Claire M Fraser-Liggett Robert L Hettich |
author_facet |
Brandi L Cantarel Alison R Erickson Nathan C VerBerkmoes Brian K Erickson Patricia A Carey Chongle Pan Manesh Shah Emmanuel F Mongodin Janet K Jansson Claire M Fraser-Liggett Robert L Hettich |
author_sort |
Brandi L Cantarel |
title |
Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
title_short |
Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
title_full |
Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
title_fullStr |
Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
title_full_unstemmed |
Strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
title_sort |
strategies for metagenomic-guided whole-community proteomics of complex microbial environments. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2011 |
url |
https://doaj.org/article/668b5a86f28b45b38231d8828db584f9 |
work_keys_str_mv |
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1718423288505434112 |