Mining proteomic data to expose protein modifications in Methanosarcina mazei strain Gö1

Frontiers in Microbiology
Deborah R LeonRachel R Ogorzalek Loo

Abstract

Proteomic tools identify constituents of complex mixtures, often delivering long lists of identified proteins. The high-throughput methods excel at matching tandem mass spectrometry data to spectra predicted from sequence databases. Unassigned mass spectra are ignored, but could, in principle, provide valuable information on unanticipated modifications and improve protein annotations while consuming limited quantities of material. Strategies to "mine" information from these discards are presented, along with discussion of features that, when present, provide strong support for modifications. In this study we mined LC-MS/MS datasets of proteolytically-digested concanavalin A pull down fractions from Methanosarcina mazei Gö1 cell lysates. Analyses identified 154 proteins. Many of the observed proteins displayed post-translationally modified forms, including O-formylated and methyl-esterified segments that appear biologically relevant (i.e., not artifacts of sample handling). Interesting cleavages and modifications (e.g., S-cyanylation and trimethylation) were observed near catalytic sites of methanogenesis enzymes. Of 31 Methanosarcina protein N-termini recovered by concanavalin A binding or from a previous study, only M. mazei S...Continue Reading

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Methods Mentioned

BETA
electrophoresis
immunoprecipitation
pull down
glycosylation
acetylation
pull-down

Software Mentioned

SecretomeP
Exprot
MuDPIT
ProteinLynx Global [UNK]
UniMod
NetNGlyc
LipoP
PLGS
IDA (
SignalP

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