Multi-protease Approach for the Improved Identification and Molecular Characterization of Small Proteins and Short Open Reading Frame-Encoded Peptides

Kaulich, Philipp T.; Cassidy, Liam; Bartel, Jürgen; Schmitz, Ruth A.; Tholey, Andreas

doi:10.1021/acs.jproteome.1c00115

Cited by 40 publications

(48 citation statements)

References 41 publications

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“…Solid-phase extracƟon [26,27,32,33]. Using reagents such as SDS or guanidinium hydrochloride can also aid the extraction of membrane-associated small proteins [34].…”

Section: Enrichment Of Small Proteinsmentioning

confidence: 99%

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Bottom‐up and top‐down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame‐encoded peptides

et al. 2021

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The recent discovery of alternative open reading frames creates a need for suitable analytical approaches to verify their translation and to characterize the corresponding gene products at the molecular level. As the analysis of small proteins within a background proteome by means of classical bottom-up proteomics is challenging, method development for the analysis of small open reading frame encoded peptides (SEPs) have become a focal point for research. Here, we highlight bottom-up and top-down proteomics approaches established for the analysis of SEPs in both pro-and eukaryotes. Major steps of analysis, including sample preparation and (small) proteome isolation, separation and mass spectrometry, data interpretation and quality control, quantification, the analysis of post-translational modifications, and exploration of functional aspects of the SEPs by means of proteomics technologies are described. These methods do not exclusively cover the analytics of SEPs but simultaneously include the low molecular weight proteome, and moreover, can also be used for the proteome-wide analysis of proteolytic processing events.

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“…Solid-phase extracƟon [26,27,32,33]. Using reagents such as SDS or guanidinium hydrochloride can also aid the extraction of membrane-associated small proteins [34].…”

Section: Enrichment Of Small Proteinsmentioning

confidence: 99%

“…Although the mainly used protease in proteomics is trypsin, the usage of multiple proteases can dramatically increase the sequence coverage and confidence of the identified small proteins [32,51,54].…”

Section: Digestionmentioning

confidence: 99%

Bottom‐up and top‐down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame‐encoded peptides

et al. 2021

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“…Much efforts have focused on optimizing MS-based workflows (Bartel et al, 2020;Peng et al, 2020;Fabre et al, 2021), where a traditional bottom-up strategy with an enzymatic digestion prior to MS-analysis has often been favored (Fabre et al, 2021). Several adaptations of the separation (Kaulich et al, 2020) or enrichment (Petruschke et al, 2020) and digestion methods (Kaulich et al, 2021) have been investigated and further applied in a wide variety of biological settings, but only a limited number of studies consider the top-down strategy as a potential workflow in SEP discovery (Li et al, 2017;Budamgunta et al, 2018;Cassidy et al, 2021). Nevertheless, unlike bottom-up workflows, this alternative method delivers valuable information about proteoforms, C-or N-terminal specific characteristics and post-translational modifications (Cassidy et al, 2021) that are linked to biological functions.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, unlike bottom-up workflows, this alternative method delivers valuable information about proteoforms, C-or N-terminal specific characteristics and post-translational modifications (Cassidy et al, 2021) that are linked to biological functions. Additionally, the potential limited number of tryptic peptides present in SEPs (Kaulich et al, 2021) or short neuropeptides is counteracted by omitting the enzymatic digestion prior to analysis. Here, 48 sORFs of 84 sORFs identified on non-coding regions are peptides without a basic C-terminus, which would have been lost during conventional bottom-up strategies.…”

Section: Discussionmentioning

confidence: 99%

Ion Mobility Coupled to a Time-of-Flight Mass Analyzer Combined With Fragment Intensity Predictions Improves Identification of Classical Bioactive Peptides and Small Open Reading Frame-Encoded Peptides

Peeters

Baggerman

Gabriels

et al. 2021

Front. Cell Dev. Biol.

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Bioactive peptides exhibit key roles in a wide variety of complex processes, such as regulation of body weight, learning, aging, and innate immune response. Next to the classical bioactive peptides, emerging from larger precursor proteins by specific proteolytic processing, a new class of peptides originating from small open reading frames (sORFs) have been recognized as important biological regulators. But their intrinsic properties, specific expression pattern and location on presumed non-coding regions have hindered the full characterization of the repertoire of bioactive peptides, despite their predominant role in various pathways. Although the development of peptidomics has offered the opportunity to study these peptides in vivo, it remains challenging to identify the full peptidome as the lack of cleavage enzyme specification and large search space complicates conventional database search approaches. In this study, we introduce a proteogenomics methodology using a new type of mass spectrometry instrument and the implementation of machine learning tools toward improved identification of potential bioactive peptides in the mouse brain. The application of trapped ion mobility spectrometry (tims) coupled to a time-of-flight mass analyzer (TOF) offers improved sensitivity, an enhanced peptide coverage, reduction in chemical noise and the reduced occurrence of chimeric spectra. Subsequent machine learning tools MS2PIP, predicting fragment ion intensities and DeepLC, predicting retention times, improve the database searching based on a large and comprehensive custom database containing both sORFs and alternative ORFs. Finally, the identification of peptides is further enhanced by applying the post-processing semi-supervised learning tool Percolator. Applying this workflow, the first peptidomics workflow combined with spectral intensity and retention time predictions, we identified a total of 167 predicted sORF-encoded peptides, of which 48 originating from presumed non-coding locations, next to 401 peptides from known neuropeptide precursors, linked to 66 annotated bioactive neuropeptides from within 22 different families. Additional PEAKS analysis expanded the pool of SEPs on presumed non-coding locations to 84, while an additional 204 peptides completed the list of peptides from neuropeptide precursors. Altogether, this study provides insights into a new robust pipeline that fuses technological advancements from different fields ensuring an improved coverage of the neuropeptidome in the mouse brain.

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“…Further, the use of alternative digestion protocols has been proposed to further facilitate the discovery of SEPs and to increase the number of peptides produced (Kaulich et al, 2021). Creating an in silico S. typhimurium tryptic digestion map for all annotated (genome assembly ASM21085v2; 2 missed cleavages allowed) proteins results in 4420 identifiable SEP-derived peptides falling within typical MS-detection limits (mass range of 600-4,600 Da, ≥7 aa), originating from 423 out of 476 annotated S. Typhimurium SEPs.…”

Section: Introductionmentioning

confidence: 99%

Small Protein Enrichment Improves Proteomics Detection of sORF Encoded Polypeptides

2021

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With the rapid growth in the number of sequenced genomes, genome annotation efforts became almost exclusively reliant on automated pipelines. Despite their unquestionable utility, these methods have been shown to underestimate the true complexity of the studied genomes, with small open reading frames (sORFs; ORFs typically considered shorter than 300 nucleotides) and, in consequence, their protein products (sORF encoded polypeptides or SEPs) being the primary example of a poorly annotated and highly underexplored class of genomic elements. With the advent of advanced translatomics such as ribosome profiling, reannotation efforts have progressed a great deal in providing translation evidence for numerous, previously unannotated sORFs. However, proteomics validation of these riboproteogenomics discoveries remains challenging due to their short length and often highly variable physiochemical properties. In this work we evaluate and compare tailored, yet easily adaptable, protein extraction methodologies for their efficacy in the extraction and concomitantly proteomics detection of SEPs expressed in the prokaryotic model pathogen Salmonella typhimurium (S. typhimurium). Further, an optimized protocol for the enrichment and efficient detection of SEPs making use of the of amphipathic polymer amphipol A8-35 and relying on differential peptide vs. protein solubility was developed and compared with global extraction methods making use of chaotropic agents. Given the versatile biological functions SEPs have been shown to exert, this work provides an accessible protocol for proteomics exploration of this fascinating class of small proteins.

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Multi-protease Approach for the Improved Identification and Molecular Characterization of Small Proteins and Short Open Reading Frame-Encoded Peptides

Cited by 40 publications

References 41 publications

Bottom‐up and top‐down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame‐encoded peptides

Bottom‐up and top‐down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame‐encoded peptides

Ion Mobility Coupled to a Time-of-Flight Mass Analyzer Combined With Fragment Intensity Predictions Improves Identification of Classical Bioactive Peptides and Small Open Reading Frame-Encoded Peptides

Small Protein Enrichment Improves Proteomics Detection of sORF Encoded Polypeptides

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