Computational protocol: The Presence of Pretreated Lignocellulosic Solids from Birch during Saccharomyces cerevisiae Fermentations Leads to Increased Tolerance to Inhibitors – A Proteomic Study of the Effects

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Protocol publication

[…] MS raw data files were merged for relative quantification and identification using Proteome Discoverer version 1.3 (Thermo Fisher Scientific, Waltham, MA, USA). A database search for each set was performed with the Mascot search engine (Matrix Science Ltd., London, UK) using a custom-made yeast protein database (protein sequence file of CEN.PK113-7D from Saccharomyces genome database) with MS peptide tolerance of 10 ppm and MS/MS tolerance of 100 millimass units (mmu). The Mascot significance threshold was set at 0.01, protein relevance threshold score at 20, resulting in expectation values for lowest ions score at 0.2. Tryptic peptides were accepted with one missed cleavage and variable modifications of methionine oxidation, cysteine methylthiolation, and fixed modifications of N-terminal TMT6plex and lysine TMT6plex were selected.The detected peptide threshold in the software was set to 1% false discovery rate by searching against a reversed database [,], and proteins identified were grouped by sharing the same sequences to minimize redundancy. For TMT quantification, the ratios of the TMT reporter ion intensities in MS/MS spectra ([M+H]+ m/z 126–131) from raw data sets were used to calculate fold changes between samples. Ratios were derived with Proteome Discoverer using the following criteria: fragment ion tolerance = 100 mmu for the most confident centroid peak; TMT reagent purity corrections factors were used and missing values were replaced with minimum intensity. Only peptides unique for a given protein were considered for relative quantitation, excluding those common to other isoforms or proteins of the same family. The quantification was normalized using the protein median. The results were then exported to Excel for manual data interpretation, calculation of fold changes, and statistical analysis. […]

Pipeline specifications

Software tools Proteome Discoverer, Mascot Server
Databases SGD YPD
Application MS-based untargeted proteomics
Organisms Saccharomyces cerevisiae
Chemicals Ethanol, Carbon, Glucose, Oxygen, Pentosephosphates, Purines, Acetic Acid