In Search of Lost Small Peptides.

A large body of evidence indicates that genome annotation pipelines have biased our view of coding sequences because they generally undersample small proteins and peptides. The recent development of genome-wide translation profiling reveals the prevalence of small/short open reading frames (smORFs or sORFs), which are scattered over all classes of transcripts, including both mRNAs and presumptive long noncoding RNAs. Proteomic approaches further confirm an unexpected variety of smORF-encoded peptides (SEPs), representing an overlooked reservoir of bioactive molecules. Indeed, functional studies in a broad range of species from yeast to humans demonstrate that SEPs can harbor key activities for the control of development, differentiation, and physiology. Here we summarize recent advances in the discovery and functional characterization of smORF/SEPs and discuss why these small players can no longer be ignored with regard to genome function.

Identified Small Open Reading Frame-Encoded Peptides in Human Serum with Nanoparticle Protein Coronas.

The low-molecular-weight proteins (LMWP) in serum and plasma are related to various human diseases and can be valuable biomarkers. A small open reading frame-encoded peptide (SEP) is one kind of LMWP, which has been found to function in many bioprocesses and has also been found in human blood, making it a potential biomarker. The detection of LMWP by a mass spectrometry (MS)-based proteomic assay is often inhibited by the wide dynamic range of serum/plasma protein abundance. Nanoparticle protein coronas are a newly emerging protein enrichment method. To analyze SEPs in human serum, we have developed a protocol integrated with nanoparticle protein coronas and liquid chromatography (LC)/MS/MS. With three nanoparticles, TiO2, Fe3O4@SiO2, and Fe3O4@SiO2@TiO2, we identified 164 new SEPs in the human serum sample. Fe3O4@SiO2 and a nanoparticle mixture obtained the maximum number and the largest proportion of identified SEPs, respectively. Compared with acetonitrile-based extraction, nanoparticle protein coronas can cover more small proteins and SEPs. The magnetic nanoparticle is also fit for high-throughput parallel protein separation before LC/MS. This method is fast, efficient, reproducible, and easy to operate in 96-well plates and centrifuge tubes, which will benefit the research on SEPs and biomarkers.

Three-nucleotide periodicity of nucleotide diversity in a population enables the identification of open reading frames.

Accurate prediction of open reading frames (ORFs) is important for studying and using genome sequences. Ribosomes move along mRNA strands with a step of three nucleotides and datasets carrying this information can be used to predict ORFs. The ribosome-protected footprints (RPFs) feature a significant 3-nt periodicity on mRNAs and are powerful in predicting translating ORFs, including small ORFs (sORFs), but the application of RPFs is limited because they are too short to be accurately mapped in complex genomes. In this study, we found a significant 3-nt periodicity in the datasets of populational genomic variants in coding sequences, in which the nucleotide diversity increases every three nucleotides. We suggest that this feature can be used to predict ORFs and develop the Python package 'OrfPP', which recovers ~83% of the annotated ORFs in the tested genomes on average, independent of the population sizes and the complexity of the genomes. The novel ORFs, including sORFs, identified from single-nucleotide polymorphisms are supported by protein mass spectrometry evidence comparable to that of the annotated ORFs. The application of OrfPP to tetraploid cotton and hexaploid wheat genomes successfully identified 76.17% and 87.43% of the annotated ORFs in the genomes, respectively, as well as 4704 sORFs, including 1182 upstream and 2110 downstream ORFs in cotton and 5025 sORFs, including 232 upstream and 234 downstream ORFs in wheat. Overall, we propose an alternative and supplementary approach for ORF prediction that can extend the studies of sORFs to more complex genomes.

Probing the sORF-Encoded Peptides of Deinococcus radiodurans in Response to Extreme Stress.

Organisms have developed different mechanisms to respond to stresses. However, the roles of small ORF-encoded peptides (SEPs) in these regulatory systems remain elusive, which is partially because of the lack of comprehensive knowledge regarding these biomolecules. We chose the extremophile Deinococcus radiodurans R1 as a model species and conducted large-scale profiling of the SEPs related to the stress response. The integrated workflow consisting of multiple omics approaches for SEP identification was streamlined, and an SEPome of D. radiodurans containing 109 novel and high-confidence SEPs was drafted. Forty-four percent of these SEPs were predicted to function as antimicrobial peptides. Quantitative peptidomics analysis indicated that the expression of SEP068184 was upregulated upon oxidative treatment and gamma irradiation of the bacteria. SEP068184 was conserved in Deinococcus and exhibited negative regulation of oxidative stress resistance in a comparative phenotypic assay of its mutants. Further quantitative and interactive proteomics analyses suggested that SEP068184 might function through metabolic pathways and interact with cytoplasmic proteins. Collectively, our findings demonstrate that SEPs are involved in the regulation of oxidative resistance, and the SEPome dataset provides a rich resource for research on the molecular mechanisms of the response to extreme stress in organisms.

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.

DeepCPP: a deep neural network based on nucleotide bias information and minimum distribution similarity feature selection for RNA coding potential prediction.

The development of deep sequencing technologies has led to the discovery of novel transcripts. Many in silico methods have been developed to assess the coding potential of these transcripts to further investigate their functions. Existing methods perform well on distinguishing majority long noncoding RNAs (lncRNAs) and coding RNAs (mRNAs) but poorly on RNAs with small open reading frames (sORFs). Here, we present DeepCPP (deep neural network for coding potential prediction), a deep learning method for RNA coding potential prediction. Extensive evaluations on four previous datasets and six new datasets constructed in different species show that DeepCPP outperforms other state-of-the-art methods, especially on sORF type data, which overcomes the bottleneck of sORF mRNA identification by improving more than 4.31, 37.24 and 5.89% on its accuracy for newly discovered human, vertebrate and insect data, respectively. Additionally, we also revealed that discontinuous k-mer, and our newly proposed nucleotide bias and minimal distribution similarity feature selection method play crucial roles in this classification problem. Taken together, DeepCPP is an effective method for RNA coding potential prediction.

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.

Identifying Small Open Reading Frames in Prokaryotes with Ribosome Profiling.

Small proteins encoded by open reading frames (ORFs) shorter than 50 codons (small ORFs [sORFs]) are often overlooked by annotation engines and are difficult to characterize using traditional biochemical techniques. Ribosome profiling has tremendous potential to empirically improve the annotations of prokaryotic genomes. Recent improvements in ribosome profiling methods for bacterial model organisms have revealed many new sORFs in well-characterized genomes. Antibiotics that trap ribosomes just after initiation have played a key role in these developments by allowing the unambiguous identification of the start codons (and, hence, the reading frame) for novel ORFs. Here, we describe these new methods and highlight critical controls and considerations for adapting ribosome profiling to different prokaryotic species.

Proteomics-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.

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.

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.

The Marek's Disease Virus Unique Gene MDV082 Is Dispensable for Virus Replication but Contributes to a Rapid Disease Onset.

Marek's disease virus (MDV) is a highly oncogenic alphaherpesvirus of chickens that causes lymphomas in various organs. Most MDV genes are conserved among herpesviruses, while others are unique to MDV and may contribute to pathogenesis and/or tumor formation. High transcript levels of the MDV-specific genes MDV082, RLORF11, and SORF6 were recently detected in lytically infected cells; however, it remained elusive if the respective proteins are expressed and if they play a role in MDV pathogenesis. In this study, we first addressed if these proteins are expressed by inserting FLAG tags at their N or C termini. We could demonstrate that among the three genes tested, MDV082 is the only gene that encodes a protein and is expressed very late in MDV plaques in vitro. To investigate the role of this novel MDV082 protein in MDV pathogenesis, we generated a recombinant virus that lacks expression of the MDV082 protein. Our data revealed that the MDV082 protein contributes to the rapid onset of Marek's disease but is not essential for virus replication, spread, and tumor formation. Taken together, this study sheds light on the expression of MDV-specific genes and unravels the role of the late protein MDV082 in MDV pathogenesis. IMPORTANCE MDV is a highly oncogenic alphaherpesvirus that causes Marek's disease in chickens. The virus causes immense economic losses in the poultry industry due to the high morbidity and mortality, but also the cost of the vaccination. MDV encodes over 100 genes that are involved in various processes of the viral life cycle. Functional characterization of MDV genes is an essential step toward understanding the complex virus life cycle and MDV pathogenesis. Here, we have identified a novel protein encoded by MDV082 and two potential noncoding RNAs (RLORF11 and SORF6). The novel MDV082 protein is not needed for efficient MDV replication and tumor formation. However, our data demonstrate that the MDV082 protein is involved in the rapid onset of Marek's disease.

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.

The role of micropeptides in biology.

Micropeptides are small polypeptides coded by small open-reading frames. Progress in computational biology and the analyses of large-scale transcriptomes and proteomes have revealed that mammalian genomes produce a large number of transcripts encoding micropeptides. Many of these have been previously annotated as long noncoding RNAs. The role of micropeptides in cellular homeostasis maintenance has been demonstrated. This review discusses different types of micropeptides as well as methods to identify them, such as computational approaches, ribosome profiling, and mass spectrometry.

Micropeptides translated from putative long non-coding RNAs.

Long non-coding RNAs (lncRNAs) transcribed in mammals and eukaryotes were thought to have no protein coding capability. However, recent studies have suggested that plenty of lncRNAs are mis-annotated and virtually contain coding sequences which are translated into functional peptides by ribosomal machinery, and these functional peptides are called micropeptides or small peptides. Here we review the rapidly advancing field of micropeptides translated from putative lncRNAs, describe the strategies for their identification, and elucidate their critical roles in many fundamental biological processes. We also discuss the prospects of research in micropeptides and the potential applications of micropeptides.

LINC00116 codes for a mitochondrial peptide linking respiration and lipid metabolism.

Genes coding for small peptides have been frequently misannotated as long noncoding RNA (lncRNA) genes. Here we have demonstrated that one such transcript is translated into a 56-amino-acid-long peptide conserved in chordates, corroborating the work published while this manuscript was under review. The Mtln peptide could be detected in mitochondria of mouse cell lines and tissues. In line with its mitochondrial localization, lack of the Mtln decreases the activity of mitochondrial respiratory chain complex I. Unlike the integral components and assembly factors of NADH:ubiquinone oxidoreductase, Mtln does not alter its enzymatic activity directly. Interaction of Mtln with NADH-dependent cytochrome b5 reductase stimulates complex I functioning most likely by providing a favorable lipid composition of the membrane. Study of Mtln illuminates the importance of small peptides, whose genes might frequently be misannotated as lncRNAs, for the control of vitally important cellular processes.

A simple organic solvent precipitation method to improve detection of low molecular weight proteins.

Mass spectrometry-based proteomics revolutionized global proteomic profiling. Although high molecular weight abundant proteins are readily sampled in global proteomics studies, less abundant low molecular weight proteins are often underrepresented. This includes biologically important classes of low molecular weight proteins including ligands, growth factors, peptide hormones and cytokines. Although extensive fractionation can facilitate achieving better coverage of proteome, it requires additional infrastructure, mass spectrometry time and labour. There is need for a simple method that can selectively deplete high molecular weight abundant proteins and enrich for low molecular weight less abundant proteins to improve their coverage in proteomics studies. We present a simple organic-solvent based protein precipitation method that selectively depletes high molecular weight proteins and enriches low molecular weight proteins in the soluble fraction. Using this strategy, we demonstrate identification of low molecular weight proteins that are generally underrepresented in proteomics datasets. In addition, we show the utility of this approach in identifying functional cleavage products from precursor proteins and low molecular weight short open reading frame proteins encoded by non-coding regions such as lncRNAs and UTRs. As the method does not require additional infrastructure, it can complement existing proteomics workflows to increase detection and coverage of low molecular weight proteins that are less abundant.

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

The identification of proteins below approximately 70-100 amino acids in bottom-up proteomics is still a challenging task due to the limited number of peptides generated by proteolytic digestion. This includes the short open reading frame-encoded peptides (SEPs), which are a subset of the small proteins that were not previously annotated or that are alternatively encoded. Here, we systematically investigated the use of multiple proteases (trypsin, chymotrypsin, LysC, LysargiNase, and GluC) in GeLC-MS/MS analysis to improve the sequence coverage and the number of identified peptides for small proteins, with a focus on SEPs, in the archaeon Methanosarcina mazei. Combining the data of all proteases, we identified 63 small proteins and additional 28 SEPs with at least two unique peptides, while only 55 small proteins and 22 SEP could be identified using trypsin only. For 27 small proteins and 12 SEPs, a complete sequence coverage was achieved. Moreover, for five SEPs, incorrectly predicted translation start points or potential in vivo proteolytic processing were identified, confirming the data of a previous top-down proteomics study of this organism. The results show clearly that a multi-protease approach allows to improve the identification and molecular characterization of small proteins and SEPs. LC-MS data: ProteomeXchange PXD023921.

The hidden world of membrane microproteins.

Proteins are critical components of biological membranes and play key roles in many essential cellular processes. Membrane proteins are a structurally and functionally diverse family of proteins that have recently expanded to include a number of newly discovered tiny proteins called microproteins, or micropeptides. These microproteins are generated from small open reading frames, which produce protein products that are less than 100 amino acids in length. While not all microproteins are membrane proteins, this review will focus specifically on this subclass to highlight some of the important biological activities that have been ascribed to these molecules and to emphasize their promise as exciting new players in membrane biology.

The hunt for sORFs: A multidisciplinary strategy.

Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their function as biologically relevant regulators. The characterization of the full small proteome has potential applications in many fields. Continuous development of techniques and tools led to an improved sORF discovery, where these can originate from bioinformatics analyses, from sequencing routines or proteomics approaches. In this mini review, we discuss the ongoing trends in the three fields and suggest some strategies for further characterization of high potential candidates.