Recent advances in mass spectrometry-based peptidomics workflows to identify short-open-reading-frame-encoded peptides and explore their functions

Glycoproteomic and proteomic analysis of Burkholderia cenocepacia reveals glycosylation events within FliF and MotB are dispensable for motility

Across the Burkholderia genus O-linked protein glycosylation is highly conserved. While the inhibition of glycosylation has been shown to be detrimental for virulence in Burkholderia cepacia complex species, such as Burkholderia cenocepacia, little is known about how specific glycosylation sites impact protein functionality. Within this study, we sought to improve our understanding of the breadth, dynamics, and requirement for glycosylation across the B. cenocepacia O-glycoproteome. Assessing the B. cenocepacia glycoproteome across different culture media using complementary glycoproteomic approaches, we increase the known glycoproteome to 141 glycoproteins. Leveraging this repertoire of glycoproteins, we quantitively assessed the glycoproteome of B. cenocepacia using Data-Independent Acquisition (DIA) revealing the B. cenocepacia glycoproteome is largely stable across conditions with most glycoproteins constitutively expressed. Examination of how the absence of glycosylation impacts the glycoproteome reveals that the protein abundance of only five glycoproteins (BCAL1086, BCAL2974, BCAL0525, BCAM0505, and BCAL0127) are altered by the loss of glycosylation. Assessing ΔfliF (ΔBCAL0525), ΔmotB (ΔBCAL0127), and ΔBCAM0505 strains, we demonstrate the loss of FliF, and to a lesser extent MotB, mirror the proteomic effects observed in the absence of glycosylation in ΔpglL. While both MotB and FliF are essential for motility, we find loss of glycosylation sites in MotB or FliF does not impact motility supporting these sites are dispensable for function. Combined this work broadens our understanding of the B. cenocepacia glycoproteome supporting that the loss of glycoproteins in the absence of glycosylation is not an indicator of the requirement for glycosylation for protein function.

IMPORTANCE

Burkholderia cenocepacia is an opportunistic pathogen of concern within the Cystic Fibrosis community. Despite a greater appreciation of the unique physiology of B. cenocepacia gained over the last 20 years a complete understanding of the proteome and especially the O-glycoproteome, is lacking. In this study, we utilize systems biology approaches to expand the known B. cenocepacia glycoproteome as well as track the dynamics of glycoproteins across growth phases, culturing media and in response to the loss of glycosylation. We show that the glycoproteome of B. cenocepacia is largely stable across conditions and that the loss of glycosylation only impacts five glycoproteins including the motility associated proteins FliF and MotB. Examination of MotB and FliF shows, while these proteins are essential for motility, glycosylation is dispensable. Combined this work supports that B. cenocepacia glycosylation can be dispensable for protein function and may influence protein properties beyond stability.

ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach.

Making sense of mRNA translational "noise"

The importance of translation fidelity has been apparent since the discovery of genetic code. It is commonly believed that translation deviating from the main coding region is to be avoided at all times inside cells. However, ribosome profiling and mass spectrometry have revealed pervasive noncanonical translation. Both the scope and origin of translational "noise" are just beginning to be appreciated. Although largely overlooked, those translational "noises" are associated with a wide range of cellular functions, such as producing unannotated protein products. Furthermore, the dynamic nature of translational "noise" is responsive to stress conditions, highlighting the beneficial effect of translational "noise" in stress adaptation. Mechanistic investigation of translational "noise" will provide better insight into the mechanisms of translational regulation. Ultimately, they are not "noise" at all but represent a signature of cellular activities under pathophysiological conditions. Deciphering translational "noise" holds the therapeutic and diagnostic potential in a wide spectrum of human diseases.

Micropeptides: origins, identification, and potential role in metabolism-related diseases

With the development of modern sequencing techniques and bioinformatics, genomes that were once thought to be noncoding have been found to encode abundant functional micropeptides (miPs), a kind of small polypeptides. Although miPs are difficult to analyze and identify, a number of studies have begun to focus on them. More and more miPs have been revealed as essential for energy metabolism homeostasis, immune regulation, and tumor growth and development. Many reports have shown that miPs are especially essential for regulating glucose and lipid metabolism and regulating mitochondrial function. MiPs are also involved in the progression of related diseases. This paper reviews the sources and identification of miPs, as well as the functional significance of miPs for metabolism-related diseases, with the aim of revealing their potential clinical applications.

Microproteins-Discovery, structure, and function

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.

Mass spectrometry in the discovery of peptides involved in intercellular communication: From targeted to untargeted peptidomics approaches

Endogenous peptide hormones represent an essential class of biomolecules, which regulate cell-cell communications in diverse physiological processes of organisms. Mass spectrometry (MS) has been developed to be a powerful technology for identifying and quantifying peptides in a highly efficient manner. However, it is difficult to directly identify these peptide hormones due to their diverse characteristics, dynamic regulations, low abundance, and existence in a complicated biological matrix. Here, we summarize and discuss the roles of targeted and untargeted MS in discovering peptide hormones using bioassay-guided purification, bioinformatics screening, or the peptidomics-based approach. Although the peptidomics approach is expected to discover novel peptide hormones unbiasedly, only a limited number of successful cases have been reported. The critical challenges and corresponding measures for peptidomics from the steps of sample preparation, peptide extraction, and separation to the MS data acquisition and analysis are also discussed. We also identify emerging technologies and methods that can be integrated into the discovery platform toward the comprehensive study of endogenous peptide hormones.

Identification of novel α-glucosidase and ACE inhibitory peptides from Douchi using peptidomics approach and molecular docking

In this study, the effect of Douchi extract (DWE) on α-glucosidase and angiotensin-converting enzymes (ACE) were investigated, and several novel peptides with inhibitory activity against α-glucosidase and ACE were identified using peptidomics approach based on UPLC-MS/MS. The average inhibition rates of DWE on α-glucosidase and ACE were 73.75-78.10% and 4.56-27.07%, respectively. In the DWE, a total of 710 peptides were detected. Two novel peptides with potential inhibitory activity against α-glucosidase were identified using the correlation analysis, database alignment and molecular docking methods. They were DVFRAIPSEVL and DRPSINGLAGAN, with the IC50 values of 0.121 and 0.128 mg/mL, respectively. Also, four novel peptides with potential inhibitory activity against ACE were identified: PSSPFTDLWD, EEQDERQFPF, PVPVPVQQAFPF and PSSPFTDL, with IC50 values of 1.388, 0.041, 0.761 and 0.097 mg/mL, respectively. These results indicated that combining peptidomics and molecular docking is an effective alternative strategy for rapidly screening numbers of novel bioactive peptides from foods.

LncRNA-encoded peptides: unveiling their significance in cardiovascular physiology and pathology-current research insights

Long non-coding RNAs (lncRNAs), which are RNA transcripts exceeding 200 nucleotides were believed to lack any protein-coding capacity. But advancements in -omics technology have revealed that some lncRNAs have small open reading frames (sORFs) that can be translated by ribosomes to encode peptides, some of which have important biological functions. These encoded peptides subserve important biological functions by interacting with their targets to modulate transcriptional or signalling axes, thereby enhancing or suppressing cardiovascular disease (CVD) occurrence and progression. In this review, we summarize what is known about the research strategy of lncRNA-encoded peptides, mainly comprising predictive websites/tools and experimental methods that have been widely used for prediction, identification, and validation. More importantly, we have compiled a list of lncRNA- encoded peptides, with a focus on those that play significant roles in cardiovascular physiology and pathology, including ENSRNOT (RNO)-sORF6/RNO-sORF7/RNO-sORF8, dwarf open reading frame (DOWRF), myoregulin (NLN), etc. Additionally, we have outlined the functions and mechanisms of these peptides in cardiovascular physiology and pathology, such as cardiomyocyte hypertrophy, myocardial contraction, myocardial infarction, and vascular remodelling. Finally, an overview of the existing challenges and potential future developments in the realm of lncRNA-encoded peptides was provided, with consideration given to prospective avenues for further research. Given that many lncRNA-encoded peptides have not been functionally annotated yet, their application in CVD diagnosis and treatment still requires further research.

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World

Small open reading frames (sORFs) are often overlooked features in genomes. In the past, they were labeled as noncoding or "transcriptional noise". However, accumulating evidence from recent years suggests that sORFs may be transcribed and translated to produce sORF-encoded polypeptides (SEPs) with less than 100 amino acids. The vigorous development of computational algorithms, ribosome profiling, and peptidome has facilitated the prediction and identification of many new SEPs. These SEPs were revealed to be involved in a wide range of basic biological processes, such as gene expression regulation, embryonic development, cellular metabolism, inflammation, and even carcinogenesis. To effectively understand the potential biological functions of SEPs, we discuss the history and development of the newly emerging research on sORFs and SEPs. In particular, we review a range of recently discovered bioinformatics tools for identifying, predicting, and validating SEPs as well as a variety of biochemical experiments for characterizing SEP functions. Lastly, this review underlines the challenges and future directions in identifying and validating sORFs and their encoded micropeptides, providing a significant reference for upcoming research on sORF-encoded peptides.

Identification of small open reading frames in plant lncRNA using class-imbalance learning

Recently, small open reading frames (sORFs) in long noncoding RNA (lncRNA) have been demonstrated to encode small peptides that can help study the mechanisms of growth and development in organisms. Since machine learning-based computational methods are less costly compared with biological experiments, they can be used to identify sORFs and provide a basis for biological experiments. However, few computational methods and data resources have been exploited for identifying sORFs in plant lncRNA. Besides, machine learning models produce underperforming classifiers when faced with a class-imbalance problem. In this study, an alternative method called SMOTE based on weighted cosine distance (WCDSMOTE) which enables interaction with feature selection is put forward to synthesize minority class samples and weighted edited nearest neighbor (WENN) is applied to clean up majority class samples, thus, hybrid sampling WCDSMOTE-ENN is proposed to deal with imbalanced datasets with the multi-angle feature. A heterogeneous classifier ensemble is introduced to complete the classification task. Therefore, a novel computational method that is based on class-imbalance learning to identify the sORFs with coding potential in plant lncRNA (sORFplnc) is presented. Experimental results manifest that sORFplnc outperforms existing computational methods in identifying sORFs with coding potential. We anticipate that the proposed work can be a reference for relevant research and contribute to agriculture and biomedicine.

Proteoforms expand the world of microproteins and short open reading frame-encoded peptides

Microproteins and short open reading frame-encoded peptides (SEPs) can, like all proteins, carry numerous posttranslational modifications. Together with posttranscriptional processes, this leads to a high number of possible distinct protein molecules, the proteoforms, out of a limited number of genes. The identification, quantification, and molecular characterization of proteoforms possess special challenges to established, mainly bottom-up proteomics (BUP) based analytical approaches. While BUP methods are powerful, proteins have to be inferred rather than directly identified, which hampers the detection of proteoforms. An alternative approach is top-down proteomics (TDP) which allows to identify intact proteoforms. This perspective article provides a brief overview of modified microproteins and SEPs, introduces the proteoform terminology, and compares present BUP and TDP workflows highlighting their major advantages and caveats. Necessary future developments in TDP to fully accentuate its potential for proteoform-centric analytics of microproteins and SEPs will be discussed.

Complementary peptides represent a credible alternative to agrochemicals by activating translation of targeted proteins

The current agriculture main challenge is to maintain food production while facing multiple threats such as increasing world population, temperature increase, lack of agrochemicals due to health issues and uprising of weeds resistant to herbicides. Developing novel, alternative, and safe methods is hence of paramount importance. Here, we show that complementary peptides (cPEPs) from any gene can be designed to target specifically plant coding genes. External application of synthetic peptides increases the abundance of the targeted protein, leading to related phenotypes. Moreover, we provide evidence that cPEPs can be powerful tools in agronomy to improve plant traits, such as growth, resistance to pathogen or heat stress, without the needs of genetic approaches. Finally, by combining their activity they can also be used to reduce weed growth.

LINC00998-encoded micropeptide SMIM30 promotes the G1/S transition of cell cycle by regulating cytosolic calcium level

The biological functions of short open reading frame (sORF)-encoded micropeptides remain largely unknown. Here, we report that LINC00998, a previously annotated lncRNA, was upregulated in multiple cancer types and the sORF on LINC00998 encoded a micropeptide named SMIM30. SMIM30 was localized in the membranes of the endoplasmic reticulum (ER) and mitochondria. Silencing SMIM30 inhibited the proliferation of hepatoma cells in vitro and suppressed the growth of tumor xenografts and N-nitrosodiethylamine-induced hepatoma. Overexpression of the 5'UTR-sORF sequence of LINC00998, encoding wild-type SMIM30, enhanced tumor cell growth, but this was abolished when a premature stop codon was introduced into the sORF via single-base deletion. Gain- and loss-of-function studies revealed that SMIM30 peptide but not LINC00998 reduced cytosolic calcium level, increased CDK4, cyclin E2, phosphorylated-Rb and E2F1, and promoted the G1/S phase transition and cell proliferation. The effect of SMIM30 silencing was attenuated by a calcium chelator or the agonist of sarco/endoplasmic reticulum calcium ATPase (SERCA) pump. These findings suggest a novel function of micropeptide SMIM30 in promoting G1/S transition and cell proliferation by enhancing SERCA activity and reducing cytosolic calcium level.

Do photosynthetic cells communicate with each other during cell death? From cyanobacteria to vascular plants

As in metazoans, life in oxygenic photosynthetic organisms relies on the accurate regulation of cell death. During development and in response to the environment, photosynthetic cells activate and execute cell death pathways that culminate in the death of a specific group of cells, a process known as regulated cell death (RCD). RCD control is instrumental, as its misregulation can lead to growth penalties and even the death of the entire organism. Intracellular molecules released during cell demise may act as 'survival' or 'death' signals and control the propagation of cell death to surrounding cells, even in unicellular organisms. This review explores different signals involved in cell-cell communication and systemic signalling in photosynthetic organisms, in particular Ca2+, reactive oxygen species, lipid derivates, nitric oxide, and eATP. We discuss their possible mode-of-action as either 'survival' or 'death' molecules and their potential role in determining cell fate in neighbouring cells. By comparing the knowledge available across the taxonomic spectrum of this coherent phylogenetic group, from cyanobacteria to vascular plants, we aim at contributing to the identification of conserved mechanisms that control cell death propagation in oxygenic photosynthetic organisms.

Prediction, Discovery, and Characterization of Plant- and Food-Derived Health-Beneficial Bioactive Peptides

Nature may have the answer to many of our questions about human, animal, and environmental health. Natural bioactives, especially when harvested from sustainable plant and food sources, provide a plethora of molecular solutions to nutritionally actionable, chronic conditions. The spectrum of these conditions, such as metabolic, immune, and gastrointestinal disorders, has changed with prolonged human life span, which should be matched with an appropriately extended health span, which would in turn favour more sustainable health care: "adding years to life and adding life to years". To date, bioactive peptides have been undervalued and underexploited as food ingredients and drugs. The future of translational science on bioactive peptides-and natural bioactives in general-is being built on (a) systems-level rather than reductionist strategies for understanding their interdependent, and at times synergistic, functions; and (b) the leverage of artificial intelligence for prediction and discovery, thereby significantly reducing the time from idea and concept to finished solutions for consumers and patients. This new strategy follows the path from benefit definition via design to prediction and, eventually, validation and production.

Method for identification and quantification of intact teduglutide peptide using (RP)UHPLC-UV-(HESI/ORBITRAP)MS

Teduglutide (Revestive®, 10 mg mL^-1) is a recombinant human glucagon-like peptide 2 analogue, used in the treatment of short bowel syndrome, a serious and highly disabling condition which results from either too small a length of intestine or loss of critical intestinal function. The determination of therapeutic compounds of protein-nature is always challenging due to their complex structure. In this work, we present a fast, straightforward reversed phase (RP)UHPLC-UV-(HESI/ORBITRAP)MS method for the identification and quantification of the intact teduglutide peptide. The method has been developed and validated in accordance with the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines; therefore, linearity, limits of detection and quantification, accuracy (precision and trueness), robustness, system suitability and specificity using the signal from the UV and MS, have been evaluated. The validation performance parameters obtained from the UV and MS signals were compared throughout the work, to select the most suitable. To study the specificity of the method and the impact of medicine mishandling under hospital conditions, force degradation studies were performed, i.e. thermal (40 °C and 60 °C), shaking (mechanical) and light (accelerated exposition) effects. Identification by the exact mass of teduglutide was achieved and it was confirmed that the peptide does not undergo any post-translational modifications (PTMs). To the best of our knowledge, the present work reports the first method developed for the simultaneous identification, structural characterization, and quantification of the therapeutic teduglutide peptide. Finally, the proposed method is able to indicate stability when quantifying the intact teduglutide since detects and characterises the exact mass of the degradation/modification products.

Pervasive translation of small open reading frames in plant long non-coding RNAs

Long non-coding RNAs (lncRNAs) are primarily recognized as non-coding transcripts longer than 200 nucleotides with low coding potential and are present in both eukaryotes and prokaryotes. Recent findings reveal that lncRNAs can code for micropeptides in various species. Micropeptides are generated from small open reading frames (smORFs) and have been discovered frequently in short mRNAs and non-coding RNAs, such as lncRNAs, circular RNAs, and pri-miRNAs. The most accepted definition of a smORF is an ORF containing fewer than 100 codons, and ribosome profiling and mass spectrometry are the most prevalent experimental techniques used to identify them. Although the majority of micropeptides perform critical roles throughout plant developmental processes and stress conditions, only a handful of their functions have been verified to date. Even though more research is being directed toward identifying micropeptides, there is still a dearth of information regarding these peptides in plants. This review outlines the lncRNA-encoded peptides, the evolutionary roles of such peptides in plants, and the techniques used to identify them. It also describes the functions of the pri-miRNA and circRNA-encoded peptides that have been identified in plants.

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.

Functional Micropeptides Encoded by Long Non-Coding RNAs: A Comprehensive Review

Long non-coding RNAs (lncRNAs) were originally defined as non-coding RNAs (ncRNAs) which lack protein-coding ability. However, with the emergence of technologies such as ribosome profiling sequencing and ribosome-nascent chain complex sequencing, it has been demonstrated that most lncRNAs have short open reading frames hence the potential to encode functional micropeptides. Such micropeptides have been described to be widely involved in life-sustaining activities in several organisms, such as homeostasis regulation, disease, and tumor occurrence, and development, and morphological development of animals, and plants. In this review, we focus on the latest developments in the field of lncRNA-encoded micropeptides, and describe the relevant computational tools and techniques for micropeptide prediction and identification. This review aims to serve as a reference for future research studies on lncRNA-encoded micropeptides.

In Depth Exploration of the Alternative Proteome of Drosophila melanogaster

Recent studies have shown that hundreds of small proteins were occulted when protein-coding genes were annotated. These proteins, called alternative proteins, have failed to be annotated notably due to the short length of their open reading frame (less than 100 codons) or the enforced rule establishing that messenger RNAs (mRNAs) are monocistronic. Several alternative proteins were shown to be biologically active molecules and seem to be involved in a wide range of biological functions. However, genome-wide exploration of the alternative proteome is still limited to a few species. In the present article, we describe a deep peptidomics workflow which enabled the identification of 401 alternative proteins in Drosophila melanogaster. Subcellular localization, protein domains, and short linear motifs were predicted for 235 of the alternative proteins identified and point toward specific functions of these small proteins. Several alternative proteins had approximated abundances higher than their canonical counterparts, suggesting that these alternative proteins are actually the main products of their corresponding genes. Finally, we observed 14 alternative proteins with developmentally regulated expression patterns and 10 induced upon the heat-shock treatment of embryos, demonstrating stage or stress-specific production of alternative proteins.

Proteomic-driven identification of short open reading frame-encoded peptides

Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods. This article is protected by copyright. All rights reserved.

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

Identification of Microproteins in Hep3B Cells at Different Cell Cycle Stages

Microproteins are generated from small open reading frames and turn out to play various vital biological functions. As an essential biological event of eukaryotic cells, the cell cycle is involved in cell replication and division. For such a highly regulated event, microproteins associated with cell cycle regulation remained unclarified. Utilizing a combination of bottom-up and top-down proteomics, we analyzed microproteins at specific cell cycle stages of Hep3B cells. A total of 657 microproteins were identified under three cell cycle stages, including 151 in the G0/G1 stage, 163 in the S stage, and 132 in the G2/M stage. The annotation of these microproteins showed their cell cycle-specific functions, such as translation, nuclear assembly, chromatin organization, and the G2/M transition of the mitotic cell cycle. Meanwhile, more than 50% of identified microproteins were ncRNA-encoded. These nonannotated novel microproteins contain several function domains, such as the nucleoside diphosphate kinase domain, the high mobility group domain, and the DNA-binding domain. This suggested the potential functions of these novel microproteins in specific cell cycle stages. This study presented a large-scale profile of microproteins at different cell cycle stages from Hep3B and may provide new perspectives on the regulation mechanism of the cell cycle. Liquid chromatography-mass spectrometry data were deposited to ProteomeXchange using the identifier PXD030286.

Small Open Reading Frames, How to Find Them and Determine Their Function

Advances in genomics and molecular biology have revealed an abundance of small open reading frames (sORFs) across all types of transcripts. While these sORFs are often assumed to be non-functional, many have been implicated in physiological functions and a significant number of sORFs have been described in human diseases. Thus, sORFs may represent a hidden repository of functional elements that could serve as therapeutic targets. Unlike protein-coding genes, it is not necessarily the encoded peptide of an sORF that enacts its function, sometimes simply the act of translating an sORF might have a regulatory role. Indeed, the most studied sORFs are located in the 5′UTRs of coding transcripts and can have a regulatory impact on the translation of the downstream protein-coding sequence. However, sORFs have also been abundantly identified in non-coding RNAs including lncRNAs, circular RNAs and ribosomal RNAs suggesting that sORFs may be diverse in function. Of the many different experimental methods used to discover sORFs, the most commonly used are ribosome profiling and mass spectrometry. These can confirm interactions between transcripts and ribosomes and the production of a peptide, respectively. Extensions to ribosome profiling, which also capture scanning ribosomes, have further made it possible to see how sORFs impact the translation initiation of mRNAs. While high-throughput techniques have made the identification of sORFs less difficult, defining their function, if any, is typically more challenging. Together, the abundance and potential function of many of these sORFs argues for the necessity of including sORFs in gene annotations and systematically characterizing these to understand their potential functional roles. In this review, we will focus on the high-throughput methods used in the detection and characterization of sORFs and discuss techniques for validation and functional characterization.

The Small Open Reading Frame-Encoded Peptides: Advances in Methodologies and Functional Studies

Small open reading frames (sORFs) are an important class of genes with less than 100 codons. They were historically annotated as noncoding or even junk sequences. In recent years, accumulating evidence suggests that sORFs could encode a considerable number of polypeptides, many of which play important roles in both physiology and disease pathology. However, it has been technically challenging to directly detect sORF-encoded peptides (SEPs). Here, we discuss the latest advances in methodologies for identifying SEPs with mass spectrometry, as well as the progress on functional studies of SEPs.

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.

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.