Peptide and Protein Identification Using MaxQuant and Perseus

RAW spectra were submitted to an Andromeda search (Cox et al., 2011) in MaxQuant (v.1.6.2.6) using the default settings (Cox and Mann, 2008). Label-free quantification (LFQ) (Cox et al., 2014) and match between runs was activated. MS/MS spectra data were searched against the self-constructed TspE_proteome_AA_new.fasta file (2182 entries; see above for reference). All searches included a contaminants database (as implemented in MaxQuant, 246 sequences). The contaminants database contains known MS contaminants and was included to estimate the level of contamination. Andromeda searches allowed oxidation of methionine residues (16 Da) and acetylation of the protein N-terminus (42 Da) as dynamic modifications while carbamidomethylation of cysteine residues (57 Da, alkylation with IAM) was selected as static modification. Enzyme specificity was set to “Trypsin/P.” The instrument type in Andromeda searches was set to Orbitrap and the precursor mass tolerance was set to ±20 ppm (first search) and ±4.5 ppm (main search). The MS/MS match tolerance was set to ±20 ppm. The peptide spectrum match FDR and the protein FDR were set to 0.01 (based on target-decoy approach). Minimum peptide length was 7 amino acids. For protein quantification, unique and razor peptides were allowed. In addition to unmodified peptides, modified peptides with dynamic modifications were allowed for quantification. The minimum score for modified peptides was set to 40.

Further data analysis and filtering of the MaxQuant output was done in Perseus (v.1.6.2.1) (Tyanova et al., 2016). LFQ intensities were loaded into the matrix from the proteinGroups.txt file and potential contaminants as well as reverse hits from the reverse database and hits only identified based on peptides with a modification site were removed. For all MS-based proteomics experiments, biological replicates were combined into categorical groups to allow comparison of the different treatment groups and the data was transformed to the log₂-scale. For the full proteome analysis, the data was filtered to keep only hits with a valid LFQ intensity for at least three out of four replicates for samples from cells grown on xylan. For the identification of glycoside hydrolases enriched with JJB384, the data was separately filtered for the two sugar substrates under investigation. Only hits with a valid LFQ intensity for a minimum of two out of three of the probe-labeled sample replicates were retained for further analysis. Prior to quantification, missing values were imputed from a normal distribution (width 0.3, down shift 1.8). Comparison of normalized protein group quantities (relative quantification) between different MS runs was solely based on the LFQ intensities as calculated by MaxQuant (MaxLFQ algorithm) (Cox et al., 2014). Briefly, label-free protein quantification was switched on and unique and razor peptides were considered for quantification with a minimum ratio count of 2. Retention times were recalibrated based on the built-in non-linear time-rescaling algorithm. MS/MS identifications were transferred between LC-MS/MS runs with the “Match between runs” option in which the match time window was set to 0.7 min and the alignment time window to 20 min. The quantification was based on the “value at maximum” of the extracted ion current. At least two quantitation events were required for a quantifiable protein. The log₂-fold enrichment of protein groups for samples from cells grown on xylan was calculated based on the mean LFQ intensity compared to the samples from cells grown on any of the other sugars. Statistical significance was calculated based on a two-sided Student’s t-test. Full MS data for the comparative full proteome analysis can be found in Supplementary Table 1. The log₂-fold enrichment of protein groups with JJB384 was calculated based on the mean LFQ intensity compared to the DMSO control. Protein groups with a negative fold enrichment were excluded from further analysis. Full MS data for the ABPP with JJB384 can be found in Supplementary Table 2.