Separation and identification of mouse brain tissue microproteins using top‐down method with high resolution nanocapillary liquid chromatography mass spectrometry

Applications of tandem mass spectrometry (MS/MS) in antimicrobial peptides field: Current state and new applications

Antimicrobial peptides (AMPs) constitute a group of small molecular peptides that exhibit a wide range of antimicrobial activity. These peptides are abundantly present in the innate immune system of various organisms. Given the rise of multidrug-resistant bacteria, microbiological studies have identified AMPs as potential natural antibiotics. In the context of antimicrobial resistance across various human pathogens, AMPs hold considerable promise for clinical applications. However, numerous challenges exist in the detection of AMPs, particularly by immunological and molecular biological methods, especially when studying of newly discovered AMPs in proteomics. This review outlines the current status of AMPs research and the strategies employed in their development, considering resent discoveries and methodologies. Subsequently, we focus on the advanced techniques of mass spectrometry for the quantification of AMPs in diverse samples, and analyzes their application, advantages, and limitations. Additionally, we propose suggestions for the future development of tandem mass spectrometry for the detection of AMPs.

Identification of Microproteins in Saccharomyces cerevisiae under Different Stress Conditions

Small open reading frame-encoded peptides (SEPs) are microproteins with a length of 100 amino acids or less, which may play a critical role in maintaining cell homeostasis under stress. Therefore, we used mass spectrometry-based proteomics to explore microproteins potentially involved in cellular stress responses in Saccharomyces cerevisiae. A total of 225 microproteins with 1920 unique peptides were identified under six culture conditions: normal, oxidation, starvation, ultraviolet radiation, heat shock, and heat shock with starvation. Among these microproteins, we found 70 SEPs with 75 unique peptides. The annotated microproteins are involved in stress-related processes, such as cell redox reactions, cell wall modification, protein folding and degradation, and DNA damage repair. It suggests that SEPs may also play similar functions under stress conditions. For example, SEP IP_008057, translated from a short coding sequence of YJL159W, may play a role in heat shock. This study identified stress-responsive SEPs in S. cerevisiae and provided valuable information to determine the functions of these proteins, which enrich the genome and proteome of S. cerevisiae and show clues to improving the stress tolerance of S. cerevisiae.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Clinical significance of novel identified high-frequency tumor-specific peptides associated signature in predicting disease status of gastric cancer patients

The effectively early detection and determination of disease progression of gastric cancer (GC) are still required. An emerging demand for identifying the novel targets adherent to cancer cells has been still challenged since those valuable profilings not only could act as for early gastric tumor discovery but also being potential therapeutic views. We have retrospectively analyzed GC biopsies to identify those specific target peptides in association with disease progression. We have detected the polypeptide by liquid mass technology initiated BIO-HIGH innovational assay technology for tumor-specific target peptide identification. We have validated the accessibility and feasibility of multiple target cytotoxic T-lymphocyte for the assessment of potential molecular markers by equally comparing the frequencies of tumor peptides' loci identified in 138 GC patients. The aim was to separate peripheral blood lymphocytes by density gradient centrifugation and use specific target peptides in in vitro culture of lymphocytes. The Cell Counting Kit-8 assay was set up to prove the lymphocytes' proliferation stimulated by identified peptides. Both of GC-specific peptide and shared peptide were detected in the peripheral blood, and the frequencies and quantities were correlated with disease status and cancer differentiation, in which BHGa1510 (78%), BHGa1310 (66%), BHGa0910 (57%), BHGa0310 (54%), BHGa0210 (40%), BHGa0810 (35%), BHGa0110 (33%), and BHGa1410 (30%) were apparently scoped out as high-frequency (HF) peptides could be potentially specific tumor markers. Moreover, BHGa1410 was significantly associated with cancer progression, and BHGa0910 and BHGa0210 were significantly associated with TNM stage. The IHC data have shown that both the HF BHGa1510 and HF BHGa1310 were expressions by 100% in contrast with paracancerous tissues of 40% (p < 0.05) and 33%, respectively (p < 0.05). Those specific peptide pools could be valued in assessment of advanced tumor and differential status in GC patients.

Identification of Non-Canonical Translation Products in C. elegans Using Tandem Mass Spectrometry

Transcriptome and ribosome sequencing have revealed the existence of many non-canonical transcripts, mainly containing splice variants, ncRNA, sORFs and altORFs. However, identification and characterization of products that may be translated out of these remains a challenge. Addressing this, we here report on 552 non-canonical proteins and splice variants in the model organism C. elegans using tandem mass spectrometry. Aided by sequencing-based prediction, we generated a custom proteome database tailored to search for non-canonical translation products of C. elegans. Using this database, we mined available mass spectrometric resources of C. elegans, from which 51 novel, non-canonical proteins could be identified. Furthermore, we utilized diverse proteomic and peptidomic strategies to detect 40 novel non-canonical proteins in C. elegans by LC-TIMS-MS/MS, of which 6 were common with our meta-analysis of existing resources. Together, this permits us to provide a resource with detailed annotation of 467 splice variants and 85 novel proteins mapped onto UTRs, non-coding regions and alternative open reading frames of the C. elegans genome.

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

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.

Mapping Microproteins and ncRNA-Encoded Polypeptides in Different Mouse Tissues

Small open reading frame encoded peptides (SEPs), also called microproteins, play a vital role in biological processes. Plenty of their open reading frames are located within the non-coding RNA (ncRNA) range. Recent research has demonstrated that ncRNA-encoded polypeptides have essential functions and exist ubiquitously in various tissues. To better understand the role of microproteins, especially ncRNA-encoded proteins, expressed in different tissues, we profiled the proteomic characterization of five mouse tissues by mass spectrometry, including bottom-up, top-down, and de novo sequencing strategies. Bottom-up and top-down with database-dependent searches identified 811 microproteins in the OpenProt database. De novo sequencing identified 290 microproteins, including 12 ncRNA-encoded microproteins that were not found in current databases. In this study, we discovered 1,074 microproteins in total, including 270 ncRNA-encoded microproteins. From the annotation of these microproteins, we found that the brain contains the largest number of neuropeptides, while the spleen contains the most immunoassociated microproteins. This suggests that microproteins in different tissues have tissue-specific functions. These unannotated ncRNA-coded microproteins have predicted domains, such as the macrophage migration inhibitory factor domain and the Prefoldin domain. These results expand the mouse proteome and provide insight into the molecular biology of mouse tissues.

Developing mass spectrometry for the quantitative analysis of neuropeptides

INTRODUCTION

Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.

AREAS COVERED

We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.

EXPERT OPINION

Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.

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

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.

Multidimensional separation schemes enhance the identification and molecular characterization of low molecular weight proteomes and short open reading frame-encoded peptides in top-down proteomics

Short open reading frame-encoded peptides (SEP) represent a widely undiscovered part of the proteome. The detailed analysis of SEP has, despite inherent limitations such as incomplete sequence coverage, challenges encountered with protein inference, the identification of posttranslational modifications and the assignment of potential N- and C-terminal truncations, predominantly been assessed using bottom-up proteomic workflows. The use of top-down based proteomic workflows is capable of providing an unparalleled level of characterization information, which is of increased importance in the case of alternatively encoded protein products. However, top-down based analysis is not without its own limitations, for which efficient separation prior to MS analysis is a major issue. We established a sample preparation approach for the combined bottom-up and top-down proteomic analysis of SEP. Key improvements were made by the application of solid phase extraction (SPE), which supported enrichment of proteins below ca. 20 kDa, followed by 2D-LC-MS top-down analysis encompassing both HCD and EThcD ion activation. Bottom-up experiments were used to support and confirm top-down data interpretation. This strategy allowed for the top-down characterization of 36 proteoforms mapping to 12 SEP from the archaeon Methanosarcina mazei strain Gö1, with the concurrent detection and identification of several posttranslational modifications in SEP. BIOLOGICAL SIGNIFICANCE: Small or short open reading frames (sORF) have been widely neglected in genome research in the past. With their increasing discovery, the question about the presence and molecular function of their translation products, the short open reading frame-encoded peptides (SEP), arises. As these small proteins are usually below the 10 kDa range, the number of peptides identifiable by bottom-up proteomics is limited which hampers both the identification and the recognition of potential posttranslational modifications. The presented top-down approach allowed for the detection of full length SEP, as well as of terminally truncated proteoforms, and further enabled the identification of disulfide bonds in these small proteins. This demonstrates, that this yet widely undiscovered part of the proteome undergoes the same modifications as classical proteins which is an essential step for future understanding of the biological functions of these molecules.

Top-Down Proteomics Enables Comparative Analysis of Brain Proteoforms Between Mouse Strains

Over the past decade, advances in mass spectrometry-based proteomics have accelerated brain proteome research aimed at studying the expression, dynamic modification, interaction and function of proteins in the nervous system that are associated with physiological and behavioral processes. With the latest hardware and software improvements in top-down mass spectrometry, the technology has expanded from mere protein profiling to high-throughput identification and quantification of intact proteoforms. Murine systems are broadly used as models to study human diseases. Neuroscientists specifically study the mouse brain from inbred strains to help understand how strain-specific genotype and phenotype affect development, functioning, and disease progression. This work describes the first application of label-free quantitative top-down proteomics to the analysis of the mouse brain proteome. Operating in discovery mode, we determined physiochemical differences in brain tissue from four healthy inbred strains, C57BL/6J, DBA/2J, FVB/NJ, and BALB/cByJ, after probing their intact proteome in the 3.5-30 kDa mass range. We also disseminate these findings using a new tool for top-down proteomics, TDViewer and cataloged them in a newly established Mouse Brain Proteoform Atlas. The analysis of brain tissues from the four strains identified 131 gene products leading to the full characterization of 343 of the 593 proteoforms identified. Within the results, singly and doubly phosphorylated ARPP-21 proteoforms, known to inhibit calmodulin, were differentially expressed across the four strains. Gene ontology (GO) analysis for detected differentially expressed proteoforms also helps to illuminate the similarities and dissimilarities in phenotypes among these inbred strains.