Quantitative Proteomics Analysis

All MS/MS spectra were analyzed using Proteome Discoverer (version 2.2.0.388, Thermo Fisher Scientific) with the Sequest-HT searching engines against an in-house annotated draft genome sequence of K. chersonesos MA5789 Wt (GCA_002319055.1, assembly ASM231905v1, NCBI) (Tesei et al., 2017) consisting of 9.818 predicted protein coding gene models. The genome was annotated using funannotate (v1.3.4) (doi: 10.5281/zenodo.1284502), which combined predictions from ab initio gene predictors with Augustus trained by BUSCO gene models (fungi_odb9) (Zdobnov et al., 2017) and GeneMark.hmm (Ter-Hovhannisyan et al., 2008) informed by protein evidence from Swiss-Prot (Boutet et al., 2007) together into composite gene models with EvidenceModeler (Haas et al., 2008). Functional predictions for genes was assigned by protein homology to Pfam (El-gebali et al., 2019), Swiss-Prot/UniProt (v 2018_05), and EggNog (v1.10) databases (Huerta-Cepas et al., 2019). The following parameters were selected for the search: A maximum of two missed cleavage sites, a minimum peptide length of six residues, 5 ppm tolerance for precursor ion masses, and 0.6 Da tolerance for fragment ion masses. The static modification settings included carbamidomethyl of cysteine residues, and dynamic modifications included oxidation of methionine, TMT modification of lysine ε-amino groups and peptide N-termini, and acetyl modification of protein N-terminus. A false discovery rate (FDR) of 1% for peptides and proteins was obtained using a target-decoy database search. The reporter ions integration tolerance was 0.5 Da while the co-isolation threshold was 75%. The average signal-to-noise threshold of all reporter peaks was greater than 10. The quantitative abundance of each protein was determined from the total intensity of the detected reporter ions. For statistical analysis, the sum of reporter ion intensities for each protein was log2 transformed, and the technical triplicate measurements for each protein were averaged. Only the proteins that were identified with at least one peptide and quantified in all technical (n = 3) and biological replicates (n = 2), were considered for the statistical analysis. Student’s t-test was performed to identify differentially expressed proteins between each LSSMG-exposed and 1G-exposed group as well as between all groups. To compare all four experimental conditions, each condition was normalized to the reference channel, which contained equal amounts of peptides from each group. To evaluate changes between treatment (LSSMG) and control (1G), the protein abundance levels of each LSSMG-exposed sample were normalized to the 1G-exposed counterpart. Proteins with p-values of ≤0.05 were further evaluated for increased or decreased abundance using a cut-off value of ≥ ± 1.5-fold change (log2 fold change of ≥ ± 0.584).