De novo peptide sequencing: deep mining of high-resolution mass spectrometry data

Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, Shoba Ranganathan

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. Although the analysis of spectra by de novo sequences removes such biases and has been available for a long period of time, its uptake has been slow or almost nonexistent within the scientific community. In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.

LanguageEnglish
Title of host publicationProteome bioinformatics
Subtitle of host publicationMethods in molecular biology
EditorsShivakumar Keerthikumar, Suresh Mathivanan
Place of PublicationNew York
PublisherHumana Press Inc.
Chapter10
Pages119-134
Number of pages16
Edition1st
ISBN (Electronic)9781493967407
ISBN (Print)9781493967384
DOIs
Publication statusPublished - 2017

Publication series

NameMethods in Molecular Biology
PublisherHumana Press
Volume1549
ISSN (Print)1064-3745

Fingerprint

High-Throughput Nucleotide Sequencing
Mass Spectrometry
Peptides
Proteome
Proteomics
Spectrum Analysis
Fungi
Software
Genome
Databases
Proteins

Keywords

  • De novo peptide sequencing
  • Functional annotation
  • Hybrid peptide sequencing
  • MS evidence
  • MS validation

Cite this

Islam, M. T., Mohamedali, A., Fernandes, C. S., Baker, M. S., & Ranganathan, S. (2017). De novo peptide sequencing: deep mining of high-resolution mass spectrometry data. In S. Keerthikumar, & S. Mathivanan (Eds.), Proteome bioinformatics: Methods in molecular biology (1st ed., pp. 119-134). (Methods in Molecular Biology; Vol. 1549). New York: Humana Press Inc.. https://doi.org/10.1007/978-1-4939-6740-7_10
Islam, Mohammad Tawhidul ; Mohamedali, Abidali ; Fernandes, Criselda Santan ; Baker, Mark S. ; Ranganathan, Shoba. / De novo peptide sequencing : deep mining of high-resolution mass spectrometry data. Proteome bioinformatics: Methods in molecular biology. editor / Shivakumar Keerthikumar ; Suresh Mathivanan. 1st. ed. New York : Humana Press Inc., 2017. pp. 119-134 (Methods in Molecular Biology).
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Islam, MT, Mohamedali, A, Fernandes, CS, Baker, MS & Ranganathan, S 2017, De novo peptide sequencing: deep mining of high-resolution mass spectrometry data. in S Keerthikumar & S Mathivanan (eds), Proteome bioinformatics: Methods in molecular biology. 1st edn, Methods in Molecular Biology, vol. 1549, Humana Press Inc., New York, pp. 119-134. https://doi.org/10.1007/978-1-4939-6740-7_10

De novo peptide sequencing : deep mining of high-resolution mass spectrometry data. / Islam, Mohammad Tawhidul; Mohamedali, Abidali; Fernandes, Criselda Santan; Baker, Mark S.; Ranganathan, Shoba.

Proteome bioinformatics: Methods in molecular biology. ed. / Shivakumar Keerthikumar; Suresh Mathivanan. 1st. ed. New York : Humana Press Inc., 2017. p. 119-134 (Methods in Molecular Biology; Vol. 1549).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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Islam MT, Mohamedali A, Fernandes CS, Baker MS, Ranganathan S. De novo peptide sequencing: deep mining of high-resolution mass spectrometry data. In Keerthikumar S, Mathivanan S, editors, Proteome bioinformatics: Methods in molecular biology. 1st ed. New York: Humana Press Inc. 2017. p. 119-134. (Methods in Molecular Biology). https://doi.org/10.1007/978-1-4939-6740-7_10