A workflow to increase the detection rate of proteins from unsequenced organisms in high‐throughput proteomics experiments

Abstract

We present and evaluate a strategy for the mass spectrometric identification of proteins from organisms for which no genome sequence information is available that incorporates cross-species information from sequenced organisms. The presented method combines spectrum quality scoring, de novo sequencing and error tolerant BLAST searches and is designed to decrease input data complexity. Spectral quality scoring reduces the number of investigated mass spectra without a loss of information. Stringent quality-based selection and the combination of different de novo sequencing methods substantially increase the catalog of significant peptide alignments. The de novo sequences passing a reliability filter are subsequently submitted to error tolerant BLAST searches and MS-BLAST hits are validated by a sampling technique. With the described workflow, we identified up to 20% more groups of homologous proteins in proteome analyses with organisms whose genome is not sequenced than by state-of-the-art database searches in an Arabidopsis thaliana database. We consider the novel data analysis workflow an excellent screening method to identify those proteins that evade detection in proteomics experiments as a result of database constraints.

Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

“…1) which is in line with other published reports [19]. Recently, employment of PepNovo and NovoHMM with stringent filtering criteria succeeded in high-throughput de novo sequencing of peptides of spinach chloroplast, bell pepper chromoplast and Cassave leave and root proteome [34]. …”

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

“…This only becomes problematic if the species under investigation is very distantly related to species where protein sequences are available in the search database. In these cases, peptide and protein identification can be performed by estimating the quality of a tandem mass spectrum, and if the quality is sufficient, de-novo sequencing followed by MS homology searching (Siddique et al, 2006; Grossmann et al, 2007; Vertommen et al, 2011). The major advantage of first generating a SSTDB is usually the increased sensitivity in the number of protein identifications as well as the number of peptides identified per protein.…”

Protein identification pipeline for the homology-driven proteomics

“…They produce and score error-tolerant alignments of compared peptide sequences and, in principle, do not require long and identical sequence stretches to produce a confident protein hit. Mass Spectrometry driven BLAST (MS BLAST), a high –throughput web- accessible searching tool, simultaneously processes queries comprising redundant, degenerate and partially inaccurate peptide sequence candidates obtained by automated interpretation of tandem mass spectra [7, 14, 18–20] [21]. …”