An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for three- or six-frame-translation, impede the use of mRNA-seq data for the construction of a protein sequence search database. With that in mind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesis-based sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5′-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.

To understand the impact of alternative translation initiation on a proteome, we performed a proteome‐wide study on protein turnover using positional proteomics and ribosome profiling to distinguish between N‐terminal proteoforms of individual genes. By combining pulsed SILAC with N‐terminal COFRADIC, we monitored the stability of 1,941 human N‐terminal proteoforms, including 147 N‐terminal proteoform pairs that originate from alternative translation initiation, alternative splicing or incomplete processing of the initiator methionine. N‐terminally truncated proteoforms were less abundant than canonical proteoforms and often displayed altered stabilities, likely attributed to individual protein characteristics, including intrinsic disorder, but independent of N‐terminal amino acid identity or truncation length. We discovered that the removal of initiator methionine by methionine aminopeptidases reduced the stability of processed proteoforms, while susceptibility for N‐terminal acetylation did not seem to influence protein turnover rates. Taken together, our findings reveal differences in protein stability between N‐terminal proteoforms and point to a role for alternative translation initiation and co‐translational initiator methionine removal, next to alternative splicing, in the overall regulation of proteome homeostasis.

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes.