Pervasive functional translation of noncanonical human open reading frames

A vast pool of lineage-specific microproteins encoded by long non-coding RNAs in plants

Pervasive transcription of eukaryotic genomes results in expression of long non-coding RNAs (lncRNAs) most of which are poorly conserved in evolution and appear to be non-functional. However, some lncRNAs have been shown to perform specific functions, in particular, transcription regulation. Thousands of small open reading frames (smORFs, <100 codons) located on lncRNAs potentially might be translated into peptides or microproteins. We report a comprehensive analysis of the conservation and evolutionary trajectories of lncRNAs-smORFs from the moss Physcomitrium patens across transcriptomes of 479 plant species. Although thousands of smORFs are subject to substantial purifying selection, the majority of the smORFs appear to be evolutionary young and could represent a major pool for functional innovation. Using nanopore RNA sequencing, we show that, on average, the transcriptional level of conserved smORFs is higher than that of non-conserved smORFs. Proteomic analysis confirmed translation of 82 novel species-specific smORFs. Numerous conserved smORFs containing low complexity regions (LCRs) or transmembrane domains were identified, the biological functions of a selected LCR-smORF were demonstrated experimentally. Thus, microproteins encoded by smORFs are a major, functionally diverse component of the plant proteome.

Unraveling the hidden role of a uORF-encoded peptide as a kinase inhibitor of PKCs

Approximately 40% of human messenger RNAs (mRNAs) contain upstream open reading frames (uORFs) in their 5' untranslated regions. Some of these uORF sequences, thought to attenuate scanning ribosomes or lead to mRNA degradation, were recently shown to be translated, although the function of the encoded peptides remains unknown. Here, we show a uORF-encoded peptide that exhibits kinase inhibitory functions. This uORF, upstream of the protein kinase C-eta (PKC-η) main ORF, encodes a peptide (uPEP2) containing the typical PKC pseudosubstrate motif present in all PKCs that autoinhibits their kinase activity. We show that uPEP2 directly binds to and selectively inhibits the catalytic activity of novel PKCs but not of classical or atypical PKCs. The endogenous deletion of uORF2 or its overexpression in MCF-7 cells revealed that the endogenously translated uPEP2 reduces the protein levels of PKC-η and other novel PKCs and restricts cell proliferation. Functionally, treatment of breast cancer cells with uPEP2 diminished cell survival and their migration and synergized with chemotherapy by interfering with the response to DNA damage. Furthermore, in a xenograft of MDA-MB-231 breast cancer tumor in mice models, uPEP2 suppressed tumor progression, invasion, and metastasis. Tumor histology showed reduced proliferation, enhanced cell death, and lower protein expression levels of novel PKCs along with diminished phosphorylation of PKC substrates. Hence, our study demonstrates that uORFs may encode biologically active peptides beyond their role as translation regulators of their downstream ORFs. Together, we point to a unique function of a uORF-encoded peptide as a kinase inhibitor, pertinent to cancer therapy.

Translational control of stem cell function

Stem cells are characterized by their ability to self-renew and differentiate into many different cell types. Research has focused primarily on how these processes are regulated at a transcriptional level. However, recent studies have indicated that stem cell behaviour is strongly coupled to the regulation of protein synthesis by the ribosome. In this Review, we discuss how different translation mechanisms control the function of adult and embryonic stem cells. Stem cells are characterized by low global translation rates despite high levels of ribosome biogenesis. The maintenance of pluripotency, the commitment to a specific cell fate and the switch to cell differentiation depend on the tight regulation of protein synthesis and ribosome biogenesis. Translation regulatory mechanisms that impact on stem cell function include mTOR signalling, ribosome levels, and mRNA and tRNA features and amounts. Understanding these mechanisms important for stem cell self-renewal and differentiation may also guide our understanding of cancer grade and metastasis.

Little but Loud. The Diversity of Functions of Small Proteins and Peptides - Translational Products of Short Reading Frames

Cell functioning is tightly regulated process. For many years, research in the fields of proteomics and functional genomics has been focused on the role of proteins in cell functioning. The advances in science have led to the uncovering that short open reading frames, previously considered non-functional, serve a variety of functions. Short reading frames in polycistronic mRNAs often regulate their stability and translational efficiency of the main reading frame. The improvement of proteomic analysis methods has made it possible to identify the products of translation of short open reading frames in quantities that suggest the existence of functional role of those peptides and short proteins. Studies demonstrating their role unravel a new level of the regulation of cell functioning and its adaptation to changing conditions. This review is devoted to the analysis of functions of recently discovered peptides and short proteins.

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.

Exploring Evidence of Non-coding RNA Translation With Trips-Viz and GWIPS-Viz Browsers

Detection of translation in so-called non-coding RNA provides an opportunity for identification of novel bioactive peptides and microproteins. The main methods used for these purposes are ribosome profiling and mass spectrometry. A number of publicly available datasets already exist for a substantial number of different cell types grown under various conditions, and public data mining is an attractive strategy for identification of translation in non-coding RNAs. Since the analysis of publicly available data requires intensive data processing, several data resources have been created recently for exploring processed publicly available data, such as OpenProt, GWIPS-viz, and Trips-Viz. In this work we provide a detailed demonstration of how to use the latter two tools for exploring experimental evidence for translation of RNAs hitherto classified as non-coding. For this purpose, we use a set of transcripts with substantially different patterns of ribosome footprint distributions. We discuss how certain features of these patterns can be used as evidence for or against genuine translation. During our analysis we concluded that the MTLN mRNA, previously misannotated as lncRNA LINC00116, likely encodes only a short proteoform expressed from shorter RNA transcript variants.

How to Illuminate the Dark Proteome Using the Multi-omic OpenProt Resource

Ten of thousands of open reading frames (ORFs) are hidden within genomes. These alternative ORFs, or small ORFs, have eluded annotations because they are either small or within unsuspected locations. They are found in untranslated regions or overlap a known coding sequence in messenger RNA and anywhere in a "non-coding" RNA. Serendipitous discoveries have highlighted these ORFs' importance in biological functions and pathways. With their discovery came the need for deeper ORF annotation and large-scale mining of public repositories to gather supporting experimental evidence. OpenProt, accessible at https://openprot.org/, is the first proteogenomic resource enforcing a polycistronic model of annotation across an exhaustive transcriptome for 10 species. Moreover, OpenProt reports experimental evidence cumulated across a re-analysis of 114 mass spectrometry and 87 ribosome profiling datasets. The multi-omics OpenProt resource also includes the identification of predicted functional domains and evaluation of conservation for all predicted ORFs. The OpenProt web server provides two query interfaces and one genome browser. The query interfaces allow for exploration of the coding potential of genes or transcripts of interest as well as custom downloads of all information contained in OpenProt. © 2020 The Authors. Basic Protocol 1: Using the Search interface Basic Protocol 2: Using the Downloads interface.

The plasticity of mRNA translation during cancer progression and therapy resistance

Translational control of mRNAs during gene expression allows cells to promptly and dynamically adapt to a variety of stimuli, including in neoplasia in response to aberrant oncogenic signalling (for example, PI3K-AKT-mTOR, RAS-MAPK and MYC) and microenvironmental stress such as low oxygen and nutrient supply. Such translational rewiring allows rapid, specific changes in the cell proteome that shape specific cancer phenotypes to promote cancer onset, progression and resistance to anticancer therapies. In this Review, we illustrate the plasticity of mRNA translation. We first highlight the diverse mechanisms by which it is regulated, including by translation factors (for example, eukaryotic initiation factor 4F (eIF4F) and eIF2), RNA-binding proteins, tRNAs and ribosomal RNAs that are modulated in response to aberrant intracellular pathways or microenvironmental stress. We then describe how translational control can influence tumour behaviour by impacting on the phenotypic plasticity of cancer cells as well as on components of the tumour microenvironment. Finally, we highlight the role of mRNA translation in the cellular response to anticancer therapies and its promise as a key therapeutic target.

Beneficial autoimmunity improves cancer prognosis

Many tumour antigens that do not arise from cancer cell-specific mutations are targets of humoral and cellular immunity despite their expression on non-malignant cells. Thus, in addition to the expected ability to detect mutations and stress-associated shifts in the immunoproteome and immunopeptidome (the sum of MHC class I-bound peptides) unique to malignant cells, the immune system also recognizes antigens expressed in non-malignant cells, which can result in autoimmune reactions against non-malignant cells from the tissue of origin. These autoimmune manifestations include, among others, vitiligo, thyroiditis and paraneoplastic syndromes, concurrent with melanoma, thyroid cancer and non-small-cell lung cancer, respectively. Importantly, despite the undesirable effects of these symptoms, such events can have prognostic value and correlate with favourable disease outcomes, suggesting 'beneficial autoimmunity'. Similarly, the occurrence of dermal and endocrine autoimmune adverse events in patients receiving immune-checkpoint inhibitors can have a positive predictive value for therapeutic outcomes. Neoplasias derived from stem cells deemed 'not essential' for survival (such as melanocytes, thyroid cells and most cells in sex-specific organs) have a particularly good prognosis, perhaps because the host can tolerate autoimmune reactions that destroy tumour cells at some cost to non-malignant tissues. In this Perspective, we discuss examples of spontaneous as well as therapy-induced autoimmunity that correlate with favourable disease outcomes and make a strong case in favour of this 'beneficial autoimmunity' being important not only in patients with advanced-stage disease but also in cancer immunosurveillance.

Cytoplasmic long noncoding RNAs are differentially regulated and translated during human neuronal differentiation

The expression of long noncoding RNAs is highly enriched in the human nervous system. However, the function of neuronal lncRNAs in the cytoplasm and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of human SH-SY5Y cells. We discovered 237 cytoplasmic lncRNAs up-regulated during early neuronal differentiation, 58%-70% of which are associated with polysome translation complexes. Among these polysome-associated lncRNAs, we find 45 small ORFs to be actively translated, 17 specifically upon differentiation. Fifteen of 45 of the translated lncRNA-smORFs exhibit sequence conservation within Hominidea, suggesting they are under strong selective constraint in this clade. The profiling of publicly available data sets revealed that 8/45 of the translated lncRNAs are dynamically expressed during human brain development, and 22/45 are associated with cancers of the central nervous system. One translated lncRNA we discovered is LINC01116, which is induced upon differentiation and contains an 87 codon smORF exhibiting increased ribosome profiling signal upon differentiation. The resulting LINC01116 peptide localizes to neurites. Knockdown of LINC01116 results in a significant reduction of neurite length in differentiated cells, indicating it contributes to neuronal differentiation. Our findings indicate cytoplasmic lncRNAs interact with translation complexes, are a noncanonical source of novel peptides, and contribute to neuronal function and disease. Specifically, we demonstrate a novel functional role for LINC01116 during human neuronal differentiation.

Proteomes Are of Proteoforms: Embracing the Complexity

Proteomes are complex-much more so than genomes or transcriptomes. Thus, simplifying their analysis does not simplify the issue. Proteomes are of proteoforms, not canonical proteins. While having a catalogue of amino acid sequences provides invaluable information, this is the Proteome-lite. To dissect biological mechanisms and identify critical biomarkers/drug targets, we must assess the myriad of proteoforms that arise at any point before, after, and between translation and transcription (e.g., isoforms, splice variants, and post-translational modifications [PTM]), as well as newly defined species. There are numerous analytical methods currently used to address proteome depth and here we critically evaluate these in terms of the current 'state-of-the-field'. We thus discuss both pros and cons of available approaches and where improvements or refinements are needed to quantitatively characterize proteomes. To enable a next-generation approach, we suggest that advances lie in transdisciplinarity via integration of current proteomic methods to yield a unified discipline that capitalizes on the strongest qualities of each. Such a necessary (if not revolutionary) shift cannot be accomplished by a continued primary focus on proteo-genomics/-transcriptomics. We must embrace the complexity. Yes, these are the hard questions, and this will not be easy…but where is the fun in easy?

Regulation, diversity and function of MECP2 exon and 3'UTR isoforms

The methyl-CpG-binding protein 2 (MECP2) is a critical global regulator of gene expression. Mutations in MECP2 cause neurodevelopmental disorders including Rett syndrome (RTT). MECP2 exon 2 is spliced into two alternative messenger ribonucleic acid (mRNA) isoforms encoding MECP2-E1 or MECP2-E2 protein isoforms that differ in their N-termini. MECP2-E2, isolated first, was used to define the general roles of MECP2 in methyl-deoxyribonucleic acid (DNA) binding, targeting of transcriptional regulatory complexes, and its disease-causing impact in RTT. It was later found that MECP2-E1 is the most abundant isoform in the brain and its exon 1 is also mutated in RTT. MECP2 transcripts undergo alternative polyadenylation generating mRNAs with four possible 3'untranslated region (UTR) lengths ranging from 130 to 8600 nt. Together, the exon and 3'UTR isoforms display remarkable abundance disparity across cell types and tissues during development. These findings indicate discrete means of regulation and suggest that protein isoforms perform non-overlapping roles. Multiple regulatory programs have been explored to explain these disparities. DNA methylation patterns of the MECP2 promoter and first intron impact MECP2-E1 and E2 isoform levels. Networks of microRNAs and RNA-binding proteins also post-transcriptionally regulate the stability and translation efficiency of MECP2 3'UTR isoforms. Finally, distinctions in biophysical properties in the N-termini between MECP2-E1 and E2 lead to variable protein stabilities and DNA binding dynamics. This review describes the steps taken from the discovery of MECP2, the description of its key functions, and its association with RTT, to the emergence of evidence revealing how MECP2 isoforms are differentially regulated at the transcriptional, post-transcriptional and post-translational levels.

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

Combinatorial analysis of translation dynamics reveals eIF2 dependence of translation initiation at near-cognate codons

Although ribosome-profiling and translation initiation sequencing (TI-seq) analyses have identified many noncanonical initiation codons, the precise detection of translation initiation sites (TISs) remains a challenge, mainly because of experimental artifacts of such analyses. Here, we describe a new method, TISCA (TIS detection by translation Complex Analysis), for the accurate identification of TISs. TISCA proved to be more reliable for TIS detection compared with existing tools, and it identified a substantial number of near-cognate codons in Kozak-like sequence contexts. Analysis of proteomics data revealed the presence of methionine at the NH₂-terminus of most proteins derived from near-cognate initiation codons. Although eukaryotic initiation factor 2 (eIF2), eIF2A and eIF2D have previously been shown to contribute to translation initiation at near-cognate codons, we found that most noncanonical initiation events are most probably dependent on eIF2, consistent with the initial amino acid being methionine. Comprehensive identification of TISs by TISCA should facilitate characterization of the mechanism of noncanonical initiation.

Aging: All roads lead to mitochondria

Mitochondria were described as early as 1890 as ubiquitous intracellular structures by Ernster and Schatz (1981) [1]. Since then, the accretion of knowledge in the past century has revealed much of the molecular details of mitochondria, ranging from mitochondrial origin, structure, metabolism, genetics, and signaling, and their implications in health and disease. We now know that mitochondria are remarkably multifunctional and deeply intertwined with many vital cellular processes. They are quasi-self organelles that still possess remnants of its bacterial ancestry, including an independent genome. The mitochondrial free radical theory of aging (MFRTA), which postulated that aging is a product of oxidative damage to mitochondrial DNA, provided a conceptual framework that put mitochondria on the map of aging research. However, several studies have more recently challenged the general validity of the theory, favoring novel ideas based on emerging evidence to understand how mitochondria contribute to aging and age-related diseases. One prominent topic of investigation lies on the fact that mitochondria are not only production sites for bioenergetics and macromolecules, but also regulatory hubs that communicate and coordinate many vital physiological processes at the cellular and organismal level. The bi-directional communication and coordination between the co-evolved mitochondrial and nuclear genomes is especially interesting in terms of cellular regulation. Mitochondria are dynamic and adaptive, rendering their function sensitive to cellular context. Tissues with high energy demands, such as the brain, seem to be uniquely affected by age-dependent mitochondrial dysfunction, providing a foundation for the development of novel mitochondrial-based therapeutics and diagnostics.

The RNA regulatory programs that govern lymphocyte development and function

Lymphocytes require of constant and dynamic changes in their transcriptome for timely activation and production of effector molecules to combat external pathogens. Synthesis and translation of messenger (m)RNAs into these effector proteins is controlled both quantitatively and qualitatively by RNA binding proteins (RBPs). RBP-dependent regulation of RNA editing, subcellular location, stability, and translation shapes immune cell development and immunity. Extensive evidences have now been gathered from few model RBPs, HuR, PTBP1, ZFP36, and Roquin. However, recently developed methodologies for global characterization of protein:RNA interactions suggest the existence of complex RNA regulatory networks in which RBPs co-ordinately regulate the fate of sets of RNAs controlling cellular pathways and functions. In turn, RNA can also act as scaffolding of functionally related proteins modulating their activation and function. Here we review current knowledge about how RBP-dependent regulation of RNA shapes our immune system and discuss about the existence of a hidden immune cell epitranscriptome. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

From Yeast to Mammals, the Nonsense-Mediated mRNA Decay as a Master Regulator of Long Non-Coding RNAs Functional Trajectory

The Nonsense-Mediated mRNA Decay (NMD) has been classically viewed as a translation-dependent RNA surveillance pathway degrading aberrant mRNAs containing premature stop codons. However, it is now clear that mRNA quality control represents only one face of the multiple functions of NMD. Indeed, NMD also regulates the physiological expression of normal mRNAs, and more surprisingly, of long non-coding (lnc)RNAs. Here, we review the different mechanisms of NMD activation in yeast and mammals, and we discuss the molecular bases of the NMD sensitivity of lncRNAs, considering the functional roles of NMD and of translation in the metabolism of these transcripts. In this regard, we describe several examples of functional micropeptides produced from lncRNAs. We propose that translation and NMD provide potent means to regulate the expression of lncRNAs, which might be critical for the cell to respond to environmental changes.

Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs

T cell-mediated immunity plays an important role in controlling SARS-CoV-2 infection, but the repertoire of naturally processed and presented viral epitopes on class I human leukocyte antigen (HLA-I) remains uncharacterized. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post infection using mass spectrometry. We found HLA-I peptides derived not only from canonical open reading frames (ORFs) but also from internal out-of-frame ORFs in spike and nucleocapsid not captured by current vaccines. Some peptides from out-of-frame ORFs elicited T cell responses in a humanized mouse model and individuals with COVID-19 that exceeded responses to canonical peptides, including some of the strongest epitopes reported to date. Whole-proteome analysis of infected cells revealed that early expressed viral proteins contribute more to HLA-I presentation and immunogenicity. These biological insights, as well as the discovery of out-of-frame ORF epitopes, will facilitate selection of peptides for immune monitoring and vaccine development.

Peptide-tiling screens of cancer drivers reveal oncogenic protein domains and associated peptide inhibitors

Gene fragments derived from structural domains mediating physical interactions can modulate biological functions. Utilizing this, we developed lentiviral overexpression libraries of peptides comprehensively tiling high-confidence cancer driver genes. Toward inhibiting cancer growth, we assayed ~66,000 peptides, tiling 65 cancer drivers and 579 mutant alleles. Pooled fitness screens in two breast cancer cell lines revealed peptides, which selectively reduced cellular proliferation, implicating oncogenic protein domains important for cell fitness. Coupling of cell-penetrating motifs to these peptides enabled drug-like function, with peptides derived from EGFR and RAF1 inhibiting cell growth at IC50s of 27-63 μM. We anticipate that this peptide-tiling (PepTile) approach will enable rapid de novo mapping of bioactive protein domains and associated interfering peptides.

Activation of the antiviral factor RNase L triggers translation of non-coding mRNA sequences

Ribonuclease L (RNase L) is activated as part of the innate immune response and plays an important role in the clearance of viral infections. When activated, it endonucleolytically cleaves both viral and host RNAs, leading to a global reduction in protein synthesis. However, it remains unknown how widespread RNA decay, and consequent changes in the translatome, promote the elimination of viruses. To study how this altered transcriptome is translated, we assayed the global distribution of ribosomes in RNase L activated human cells with ribosome profiling. We found that RNase L activation leads to a substantial increase in the fraction of translating ribosomes in ORFs internal to coding sequences (iORFs) and ORFs within 5' and 3' UTRs (uORFs and dORFs). Translation of these alternative ORFs was dependent on RNase L's cleavage activity, suggesting that mRNA decay fragments are translated to produce short peptides that may be important for antiviral activity.

Identification of presented SARS-CoV-2 HLA class I and HLA class II peptides using HLA peptidomics

The human leukocyte antigen (HLA)-bound viral antigens serve as an immunological signature that can be selectively recognized by T cells. As viruses evolve by acquiring mutations, it is essential to identify a range of presented viral antigens. Using HLA peptidomics, we are able to identify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-derived peptides presented by highly prevalent HLA class I (HLA-I) molecules by using infected cells as well as overexpression of SARS-CoV-2 genes. We find 26 HLA-I peptides and 36 HLA class II (HLA-II) peptides. Among the identified peptides, some are shared between different cells and some are derived from out-of-frame open reading frames (ORFs). Seven of these peptides were previously shown to be immunogenic, and we identify two additional immunoreactive peptides by using HLA multimer staining. These results may aid the development of the next generation of SARS-CoV-2 vaccines based on presented viral-specific antigens that span several of the viral genes.

From Recoding to Peptides for MHC Class I Immune Display: Enriching Viral Expression, Virus Vulnerability and Virus Evasion

Many viruses, especially RNA viruses, utilize programmed ribosomal frameshifting and/or stop codon readthrough in their expression, and in the decoding of a few a UGA is dynamically redefined to specify selenocysteine. This recoding can effectively increase viral coding capacity and generate a set ratio of products with the same N-terminal domain(s) but different C-terminal domains. Recoding can also be regulatory or generate a product with the non-universal 21st directly encoded amino acid. Selection for translation speed in the expression of many viruses at the expense of fidelity creates host immune defensive opportunities. In contrast to host opportunism, certain viruses, including some persistent viruses, utilize recoding or adventitious frameshifting as part of their strategy to evade an immune response or specific drugs. Several instances of recoding in small intensively studied viruses escaped detection for many years and their identification resolved dilemmas. The fundamental importance of ribosome ratcheting is consistent with the initial strong view of invariant triplet decoding which however did not foresee the possibility of transitory anticodon:codon dissociation. Deep level dynamics and structural understanding of recoding is underway, and a high level structure relevant to the frameshifting required for expression of the SARS CoV-2 genome has just been determined.

MetamORF: a repository of unique short open reading frames identified by both experimental and computational approaches for gene and metagene analyses

The development of high-throughput technologies revealed the existence of non-canonical short open reading frames (sORFs) on most eukaryotic ribonucleic acids. They are ubiquitous genetic elements conserved across species and suspected to be involved in numerous cellular processes. MetamORF (https://metamorf.hb.univ-amu.fr/) aims to provide a repository of unique sORFs identified in the human and mouse genomes with both experimental and computational approaches. By gathering publicly available sORF data, normalizing them and summarizing redundant information, we were able to identify a total of 1 162 675 unique sORFs. Despite the usual characterization of ORFs as short, upstream or downstream, there is currently no clear consensus regarding the definition of these categories. Thus, the data have been reprocessed using a normalized nomenclature. MetamORF enables new analyses at locus, gene, transcript and ORF levels, which should offer the possibility to address new questions regarding sORF functions in the future. The repository is available through an user-friendly web interface, allowing easy browsing, visualization, filtering over multiple criteria and export possibilities. sORFs can be searched starting from a gene, a transcript and an ORF ID, looking in a genome area or browsing the whole repository for a species. The database content has also been made available through track hubs at UCSC Genome Browser. Finally, we demonstrated an enrichment of genes harboring upstream ORFs among genes expressed in response to reticular stress. Database URL  https://metamorf.hb.univ-amu.fr/.

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.

smORFer: a modular algorithm to detect small ORFs in prokaryotes

Emerging evidence places small proteins (≤50 amino acids) more centrally in physiological processes. Yet, their functional identification and the systematic genome annotation of their cognate small open-reading frames (smORFs) remains challenging both experimentally and computationally. Ribosome profiling or Ribo-Seq (that is a deep sequencing of ribosome-protected fragments) enables detecting of actively translated open-reading frames (ORFs) and empirical annotation of coding sequences (CDSs) using the in-register translation pattern that is characteristic for genuinely translating ribosomes. Multiple identifiers of ORFs that use the 3-nt periodicity in Ribo-Seq data sets have been successful in eukaryotic smORF annotation. They have difficulties evaluating prokaryotic genomes due to the unique architecture (e.g. polycistronic messages, overlapping ORFs, leaderless translation, non-canonical initiation etc.). Here, we present a new algorithm, smORFer, which performs with high accuracy in prokaryotic organisms in detecting putative smORFs. The unique feature of smORFer is that it uses an integrated approach and considers structural features of the genetic sequence along with in-frame translation and uses Fourier transform to convert these parameters into a measurable score to faithfully select smORFs. The algorithm is executed in a modular way, and dependent on the data available for a particular organism, different modules can be selected for smORF search.

Roles of lncRNA MAGI2-AS3 in human cancers

Long noncoding RNAs (lncRNAs) are noncoding RNAs more than 200 nucleotides in length. A growing number of reports indicate that lncRNAs play a key role in multiple cancers by serving as oncogenes or tumor suppressor genes. MAGI2 antisense RNA 3 (MAGI2-AS3) is ubiquitously expressed in human cancers, and the level of MAGI2-AS3 expression is associated with the progression and prognosis of cancers. Moreover, dysregulation of MAGI2-AS3 has been found to regulate cancer cell proliferation, cell death, invasion and metastasis and treatment resistance by serving as a competing endogenous RNA (ceRNA), epigenomic regulator, and transcriptional regulator. Moreover, increasing evidence shows that MAGI2-AS3 may be a potential biomarker for cancer prognosis and a potential target for cancer therapy. In this review, we summarize current research on the functions, mechanisms and clinical significance of the lncRNA MAGI2-AS3 in cancer development.

Regulatory Potential of Competing Endogenous RNAs in Myotonic Dystrophies

Non-coding RNAs (ncRNAs) have been reported to be implicated in cell fate determination and various human diseases. All ncRNA molecules are emerging as key regulators of diverse cellular processes; however, little is known about the regulatory interaction among these various classes of RNAs. It has been proposed that the large-scale regulatory network across the whole transcriptome is mediated by competing endogenous RNA (ceRNA) activity attributed to both protein-coding and ncRNAs. ceRNAs are considered to be natural sponges of miRNAs that can influence the expression and availability of multiple miRNAs and, consequently, the global mRNA and protein levels. In this review, we summarize the current understanding of the role of ncRNAs in two neuromuscular diseases, myotonic dystrophy type 1 and 2 (DM1 and DM2), and the involvement of expanded CUG and CCUG repeat-containing transcripts in miRNA-mediated RNA crosstalk. More specifically, we discuss the possibility that long repeat tracts present in mutant transcripts can be potent miRNA sponges and may affect ceRNA crosstalk in these diseases. Moreover, we highlight practical information related to innovative disease modelling and studying RNA regulatory networks in cells. Extending knowledge of gene regulation by ncRNAs, and of complex regulatory ceRNA networks in DM1 and DM2, will help to address many questions pertinent to pathogenesis and treatment of these disorders; it may also help to better understand general rules of gene expression and to discover new rules of gene control.

Monitoring mammalian mitochondrial translation with MitoRiboSeq

Several essential components of the electron transport chain, the major producer of ATP in mammalian cells, are encoded in the mitochondrial genome. These 13 proteins are translated within mitochondria by 'mitoribosomes'. Defective mitochondrial translation underlies multiple inborn errors of metabolism and has been implicated in pathologies such as aging, metabolic syndrome and cancer. Here, we provide a detailed ribosome profiling protocol optimized to interrogate mitochondrial translation in mammalian cells (MitoRiboSeq), wherein mitoribosome footprints are generated with micrococcal nuclease and mitoribosomes are separated from cytosolic ribosomes and other RNAs by ultracentrifugation in a single straightforward step. We highlight critical steps during library preparation and provide a step-by-step guide to data analysis accompanied by open-source bioinformatic code. Our method outputs mitoribosome footprints at single-codon resolution. Codons with high footprint densities are sites of mitoribosome stalling. We recently applied this approach to demonstrate that defects in mitochondrial serine catabolism or in mitochondrial tRNA methylation cause stalling of mitoribosomes at specific codons. Our method can be applied to study basic mitochondrial biology or to characterize abnormalities in mitochondrial translation in patients with mitochondrial disorders.

Noncanonical open reading frames encode functional proteins essential for cancer cell survival

Although genomic analyses predict many noncanonical open reading frames (ORFs) in the human genome, it is unclear whether they encode biologically active proteins. Here we experimentally interrogated 553 candidates selected from noncanonical ORF datasets. Of these, 57 induced viability defects when knocked out in human cancer cell lines. Following ectopic expression, 257 showed evidence of protein expression and 401 induced gene expression changes. Clustered regularly interspaced short palindromic repeat (CRISPR) tiling and start codon mutagenesis indicated that their biological effects required translation as opposed to RNA-mediated effects. We found that one of these ORFs, G029442-renamed glycine-rich extracellular protein-1 (GREP1)-encodes a secreted protein highly expressed in breast cancer, and its knockout in 263 cancer cell lines showed preferential essentiality in breast cancer-derived lines. The secretome of GREP1-expressing cells has an increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth-inhibitory effect of GREP1 knockout. Our experiments suggest that noncanonical ORFs can express biologically active proteins that are potential therapeutic targets.

A peptide encoded within a 5' untranslated region promotes pain sensitization in mice

ABSTRACT

Translational regulation permeates neuronal function. Nociceptors are sensory neurons responsible for the detection of harmful stimuli. Changes in their activity, termed plasticity, are intimately linked to the persistence of pain. Although inhibitors of protein synthesis robustly attenuate pain-associated behavior, the underlying targets that support plasticity are largely unknown. Here, we examine the contribution of protein synthesis in regions of RNA annotated as noncoding. Based on analyses of previously reported ribosome profiling data, we provide evidence for widespread translation in noncoding transcripts and regulatory regions of mRNAs. We identify an increase in ribosome occupancy in the 5' untranslated regions of the calcitonin gene-related peptide (CGRP/Calca). We validate the existence of an upstream open reading frame (uORF) using a series of reporter assays. Fusion of the uORF to a luciferase reporter revealed active translation in dorsal root ganglion neurons after nucleofection. Injection of the peptide corresponding to the calcitonin gene-related peptide-encoded uORF resulted in pain-associated behavioral responses in vivo and nociceptor sensitization in vitro. An inhibitor of heterotrimeric G protein signaling blocks both effects. Collectively, the data suggest pervasive translation in regions of the transcriptome annotated as noncoding in dorsal root ganglion neurons and identify a specific uORF-encoded peptide that promotes pain sensitization through GPCR signaling.

Somatic Functional Deletions of Upstream Open Reading Frame-Associated Initiation and Termination Codons in Human Cancer

Upstream open reading frame (uORF)-mediated translational control has emerged as an important regulatory mechanism in human health and disease. However, a systematic search for cancer-associated somatic uORF mutations has not been performed. Here, we analyzed the genetic variability at canonical (uAUG) and alternative translational initiation sites (aTISs), as well as the associated upstream termination codons (uStops) in 3394 whole-exome-sequencing datasets from patient samples of breast, colon, lung, prostate, and skin cancer and of acute myeloid leukemia, provided by The Cancer Genome Atlas research network. We found that 66.5% of patient samples were affected by at least one of 5277 recurrent uORF-associated somatic single nucleotide variants altering 446 uAUG, 347 uStop, and 4733 aTIS codons. While twelve uORF variants were detected in all entities, 17 variants occurred in all five types of solid cancer analyzed here. Highest frequencies of individual somatic variants in the TLSs of NBPF20 and CHCHD2 reached 10.1% among LAML and 8.1% among skin cancer patients, respectively. Functional evaluation by dual luciferase reporter assays identified 19 uORF variants causing significant translational deregulation of the associated main coding sequence, ranging from 1.73-fold induction for an AUG.1 > UUG variant in SETD4 to 0.006-fold repression for a CUG.6 > GUG variant in HLA-DRB1. These data suggest that somatic uORF mutations are highly prevalent in human malignancies and that defective translational regulation of protein expression may contribute to the onset or progression of cancer.

Improved Identification of Small Open Reading Frames Encoded Peptides by Top-Down Proteomic Approaches and De Novo Sequencing

Small open reading frames (sORFs) have translational potential to produce peptides that play essential roles in various biological processes. Nevertheless, many sORF-encoded peptides (SEPs) are still on the prediction level. Here, we construct a strategy to analyze SEPs by combining top-down and de novo sequencing to improve SEP identification and sequence coverage. With de novo sequencing, we identified 1682 peptides mapping to 2544 human sORFs, which were all first characterized in this work. Two-thirds of these new sORFs have reading frame shifts and use a non-ATG start codon. The top-down approach identified 241 human SEPs, with high sequence coverage. The average length of the peptides from the bottom-up database search was 19 amino acids (AA); from de novo sequencing, it was 9 AA; and from the top-down approach, it was 25 AA. The longer peptide positively boosts the sequence coverage, more efficiently distinguishing SEPs from the known gene coding sequence. Top-down has the advantage of identifying peptides with sequential K/R or high K/R content, which is unfavorable in the bottom-up approach. Our method can explore new coding sORFs and obtain highly accurate sequences of their SEPs, which can also benefit future function research.

Impact of uORFs in mediating regulation of translation in stress conditions

Background

A large fraction of genes contains upstream ORFs (uORFs) in the 5′ untranslated region (5’UTR). The translation of uORFs can inhibit the translation of the main coding sequence, for example by causing premature dissociation of the two ribosomal units or ribosome stalling. However, it is currently unknown if most uORFs are inhibitory or if this activity is restricted to specific cases. Here we interrogate ribosome profiling data from three different stress experiments in yeast to gain novel insights into this question.

Results

By comparing ribosome occupancies in different conditions and experiments we obtain strong evidence that, in comparison to primary coding sequences (CDS), which undergo translational arrest during stress, the translation of uORFs is mostly unaffected by changes in the environment. As a result, the relative abundance of uORF-encoded peptides increases during stress. In general, the changes in the translational efficiency of regions containing uORFs do not seem to affect downstream translation. The exception are uORFs found in a subset of genes that are significantly up-regulated at the level of translation during stress; these uORFs tend to be translated at lower levels in stress conditions than in optimal growth conditions, facilitating the translation of the CDS during stress. We find new examples of uORF-mediated regulation of translation, including the Gcn4 functional homologue fil1 and ubi4 genes in S. pombe.

Conclusion

We find evidence that the relative amount of uORF-encoded peptides increases during stress. The increased translation of uORFs is however uncoupled from the general CDS translational repression observed during stress. In a subset of genes that encode proteins that need to be rapidly synthesized upon stress uORFs act as translational switches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-021-00363-9.

The IDIP framework for assessing protein function and its application to the prion protein

The quest to determine the function of a protein can represent a profound challenge. Although this task is the mandate of countless research groups, a general framework for how it can be approached is conspicuously lacking. Moreover, even expectations for when the function of a protein can be considered to be 'known' are not well defined. In this review, we begin by introducing concepts pertinent to the challenge of protein function assignments. We then propose a framework for inferring a protein's function from four data categories: 'inheritance', 'distribution', 'interactions' and 'phenotypes' (IDIP). We document that the functions of proteins emerge at the intersection of inferences drawn from these data categories and emphasise the benefit of considering them in an evolutionary context. We then apply this approach to the cellular prion protein (PrP^C ), well known for its central role in prion diseases, whose function continues to be considered elusive by many investigators. We document that available data converge on the conclusion that the function of the prion protein is to control a critical post-translational modification of the neural cell adhesion molecule in the context of epithelial-to-mesenchymal transition and related plasticity programmes. Finally, we argue that this proposed function of PrP^C has already passed the test of time and is concordant with the IDIP framework in a way that other functions considered for this protein fail to achieve. We anticipate that the IDIP framework and the concepts analysed herein will aid the investigation of other proteins whose primary functional assignments have thus far been intractable.

Minireview: Novel Micropeptide Discovery by Proteomics and Deep Sequencing Methods

A novel class of small proteins, called micropeptides, has recently been discovered in the genome. These proteins, which have been found to play important roles in many physiological and cellular systems, are shorter than 100 amino acids and were overlooked during previous genome annotations. Discovery and characterization of more micropeptides has been ongoing, often using -omics methods such as proteomics, RNA sequencing, and ribosome profiling. In this review, we survey the recent advances in the micropeptides field and describe the methodological and conceptual challenges facing future micropeptide endeavors.

Computational Analysis Predicts Hundreds of Coding lncRNAs in Zebrafish

Simple Summary

Noncoding RNAs (ncRNAs) regulate a variety of fundamental life processes such as development, physiology, metabolism and circadian rhythmicity. RNA-sequencing (RNA-seq) technology has facilitated the sequencing of the whole transcriptome, thereby capturing and quantifying the dynamism of transcriptome-wide RNA expression profiles. However, much remains unrevealed in the huge noncoding RNA datasets that require further bioinformatic analysis. In this study, we applied six bioinformatic tools to investigate coding potentials of approximately 21,000 lncRNAs. A total of 313 lncRNAs are predicted to be coded by all the six tools. Our findings provide insights into the regulatory roles of lncRNAs and set the stage for the functional investigation of these lncRNAs and their encoded micropeptides.

Abstract

Recent studies have demonstrated that numerous long noncoding RNAs (ncRNAs having more than 200 nucleotide base pairs (lncRNAs)) actually encode functional micropeptides, which likely represents the next regulatory biology frontier. Thus, identification of coding lncRNAs from ever-increasing lncRNA databases would be a bioinformatic challenge. Here we employed the Coding Potential Alignment Tool (CPAT), Coding Potential Calculator 2 (CPC2), LGC web server, Coding-Non-Coding Identifying Tool (CNIT), RNAsamba, and MicroPeptide identification tool (MiPepid) to analyze approximately 21,000 zebrafish lncRNAs and computationally to identify 2730–6676 zebrafish lncRNAs with high coding potentials, including 313 coding lncRNAs predicted by all the six bioinformatic tools. We also compared the sensitivity and specificity of these six bioinformatic tools for identifying lncRNAs with coding potentials and summarized their strengths and weaknesses. These predicted zebrafish coding lncRNAs set the stage for further experimental studies.

Increased expression of peptides from non-coding genes in cancer proteomics datasets suggests potential tumor neoantigens

Neoantigen-based immunotherapy has yielded promising results in clinical trials. However, it is limited to tumor-specific mutations, and is often tailored to individual patients. Identifying suitable tumor-specific antigens is still a major challenge. Previous proteogenomics studies have identified peptides encoded by predicted non-coding sequences in human genome. To investigate whether tumors express specific peptides encoded by non-coding genes, we analyzed published proteomics data from five cancer types including 933 tumor samples and 275 matched normal samples and compared these to data from 31 different healthy human tissues. Our results reveal that many predicted non-coding genes such as DGCR9 and RHOXF1P3 encode peptides that are overexpressed in tumors compared to normal controls. Furthermore, from the non-coding genes-encoded peptides specifically detected in cancers, we predict a large number of “dark antigens” (neoantigens from non-coding genomic regions), which may provide an alternative source of neoantigens beyond standard tumor specific mutations.

Rong Xiang et al. analyze the expression of non-coding genes encoded peptides in publicly-available proteomics data from five cancer types and matched controls. They identify peptides from non-coding genes including DGCR9 and RHOXF1P3 that are upregulated in tumors compared to controls, suggesting that non-coding gene-encoded peptides may be a source of neoantigens in some cancers.

Exploring the Alternative Splicing of Long Noncoding RNAs

Like protein-coding genes, long noncoding RNA (lncRNA) genes are composed of introns and exons. After their transcription, lncRNAs are subject to constitutive and/or alternative splicing. Here, we describe the current knowledge on lncRNA splice variants and their functional implications in cell biology.

The largely unexplored biology of small proteins in pro- and eukaryotes

The large abundance of small open reading frames (smORFs) in prokaryotic and eukaryotic genomes and the plethora of smORF-encoded small proteins became only apparent with the constant advancements in bioinformatic, genomic, proteomic, and biochemical tools. Small proteins are typically defined as proteins of < 50 amino acids in prokaryotes and of less than 100 amino acids in eukaryotes, and their importance for cell physiology and cellular adaptation is only beginning to emerge. In contrast to antimicrobial peptides, which are secreted by prokaryotic and eukaryotic cells for combatting pathogens and competitors, small proteins act within the producing cell mainly by stabilizing protein assemblies and by modifying the activity of larger proteins. Production of small proteins is frequently linked to stress conditions or environmental changes, and therefore, cells seem to use small proteins as intracellular modifiers for adjusting cell metabolism to different intra- and extracellular cues. However, the size of small proteins imposes a major challenge for the cellular machinery required for protein folding and intracellular trafficking and recent data indicate that small proteins can engage distinct trafficking pathways. In the current review, we describe the diversity of small proteins in prokaryotes and eukaryotes, highlight distinct and common features, and illustrate how they are handled by the protein trafficking machineries in prokaryotic and eukaryotic cells. Finally, we also discuss future topics of research on this fascinating but largely unexplored group of proteins.

Genetic basis of mitochondrial diseases

Mitochondrial disorders are monogenic disorders characterized by a defect in oxidative phosphorylation and caused by pathogenic variants in one of over 340 different genes. The implementation of whole-exome sequencing has led to a revolution in their diagnosis, duplicated the number of associated disease genes, and significantly increased the diagnosed fraction. However, the genetic etiology of a substantial fraction of patients exhibiting mitochondrial disorders remains unknown, highlighting limitations in variant detection and interpretation, which calls for improved computational and DNA sequencing methods, as well as the addition of OMICS tools. More intriguingly, this also suggests that some pathogenic variants lie outside of the protein-coding genes and that the mechanisms beyond the Mendelian inheritance and the mtDNA are of relevance. This review covers the current status of the genetic basis of mitochondrial diseases, discusses current challenges and perspectives, and explores the contribution of factors beyond the protein-coding regions and monogenic inheritance in the expansion of the genetic spectrum of disease.

Atypical acute myeloid leukemia-specific transcripts generate shared and immunogenic MHC class-I-associated epitopes

Acute myeloid leukemia (AML) has not benefited from innovative immunotherapies, mainly because of the lack of actionable immune targets. Using an original proteogenomic approach, we analyzed the major histocompatibility complex class I (MHC class I)-associated immunopeptidome of 19 primary AML samples and identified 58 tumor-specific antigens (TSAs). These TSAs bore no mutations and derived mainly (86%) from supposedly non-coding genomic regions. Two AML-specific aberrations were instrumental in the biogenesis of TSAs, intron retention, and epigenetic changes. Indeed, 48% of TSAs resulted from intron retention and translation, and their RNA expression correlated with mutations of epigenetic modifiers (e.g., DNMT3A). AML TSA-coding transcripts were highly shared among patients and were expressed in both blasts and leukemic stem cells. In AML patients, the predicted number of TSAs correlated with spontaneous expansion of cognate T cell receptor clonotypes, accumulation of activated cytotoxic T cells, immunoediting, and improved survival. These TSAs represent attractive targets for AML immunotherapy.

Translational remodeling by RNA-binding proteins and noncoding RNAs

Responsible for generating the proteome that controls phenotype, translation is the ultimate convergence point for myriad upstream signals that influence gene expression. System-wide adaptive translational reprogramming has recently emerged as a pillar of cellular adaptation. As classic regulators of mRNA stability and translation efficiency, foundational studies established the concept of collaboration and competition between RNA-binding proteins (RBPs) and noncoding RNAs (ncRNAs) on individual mRNAs. Fresh conceptual innovations now highlight stress-activated, evolutionarily conserved RBP networks and ncRNAs that increase the translation efficiency of populations of transcripts encoding proteins that participate in a common cellular process. The discovery of post-transcriptional functions for long noncoding RNAs (lncRNAs) was particularly intriguing given their cell-type-specificity and historical definition as nuclear-functioning epigenetic regulators. The convergence of RBPs, lncRNAs, and microRNAs on functionally related mRNAs to enable adaptive protein synthesis is a newer biological paradigm that highlights their role as "translatome (protein output) remodelers" and reinvigorates the paradigm of "RNA operons." Together, these concepts modernize our understanding of cellular stress adaptation and strategies for therapeutic development. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Translation > Translation Regulation Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

Disrupting upstream translation in mRNAs is associated with human disease

Ribosome-profiling has uncovered pervasive translation in non-canonical open reading frames, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5’UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals, respectively, and elucidate their impact on protein expression in human cells. Our results suggest translation disrupting mechanisms relating uORF variation to reduced protein expression, and demonstrate that translation at uORFs is genetically constrained in 50% of human genes.

The significance of translated upstream open reading frames is not well known. Here, the authors investigate genetic variants in these regions, finding that they are under high evolutionary constraint and may contribute to disease.

Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

BACKGROUND

The intestinal microbiota plays a crucial role in protecting the host from pathogenic microbes, modulating immunity and regulating metabolic processes. We studied the simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species with a particular focus on the discovery of novel small proteins with less than 100 amino acids (= sProteins), some of which may contribute to shape the simplified human intestinal microbiota. Although sProteins carry out a wide range of important functions, they are still often missed in genome annotations, and little is known about their structure and function in individual microbes and especially in microbial communities.

RESULTS

We created a multi-species integrated proteogenomics search database (iPtgxDB) to enable a comprehensive identification of novel sProteins. Six of the eight SIHUMIx species, for which no complete genomes were available, were sequenced and de novo assembled. Several proteomics approaches including two earlier optimized sProtein enrichment strategies were applied to specifically increase the chances for novel sProtein discovery. The search of tandem mass spectrometry (MS/MS) data against the multi-species iPtgxDB enabled the identification of 31 novel sProteins, of which the expression of 30 was supported by metatranscriptomics data. Using synthetic peptides, we were able to validate the expression of 25 novel sProteins. The comparison of sProtein expression in each single strain versus a multi-species community cultivation showed that six of these sProteins were only identified in the SIHUMIx community indicating a potentially important role of sProteins in the organization of microbial communities. Two of these novel sProteins have a potential antimicrobial function. Metabolic modelling revealed that a third sProtein is located in a genomic region encoding several enzymes relevant for the community metabolism within SIHUMIx.

CONCLUSIONS

We outline an integrated experimental and bioinformatics workflow for the discovery of novel sProteins in a simplified intestinal model system that can be generically applied to other microbial communities. The further analysis of novel sProteins uniquely expressed in the SIHUMIx multi-species community is expected to enable new insights into the role of sProteins on the functionality of bacterial communities such as those of the human intestinal tract. Video abstract.

A Novel, Universally Active C-terminal Protein Degradation Signal Generated by Alternative Splicing

Proteome integrity is crucial for cellular homeostasis and adaptation to stress conditions such as hypoxia. One mechanism for rapid adaptation of the proteome in response to changing environmental signals is alternative splicing. In addition to generating different protein isoforms, alternative splicing is also capable of controlling total protein levels by the regulated synthesis of non-productive mRNA isoforms. The hypoxia-induced isoform E of the tumor suppressor MAX is produced by retention and translation of the last intron. This leads to an alternative C-terminus that harbors a potent C-degron, the isoE degron. Strikingly, the isoE degron represents a universal protein degradation signal that is not only functional in mammalian cells, but also in yeast and even in bacteria. Essential for efficient protein decay is a conserved (F/W)xxW motif. Degradation of isoE tagged proteins is mediated by the proteasome in eukaryotes and Lon protease in bacteria. Thus, the isoE degron is a broadly applicable and highly efficient tool in protein analyses.

Prognostic Signatures of Metabolic Genes and Metabolism-Related Long Non-coding RNAs Accurately Predict Overall Survival for Osteosarcoma Patients

In this study, we identified eight survival-related metabolic genes in differentially expressed metabolic genes by univariate Cox regression analysis based on the therapeutically applicable research to generate effective treatments (n = 84) data set and genotype tissue expression data set (n = 396). We also constructed a six metabolic gene signature to predict the overall survival of osteosarcoma (OS) patients using least absolute shrinkage and selection operator (Lasso) Cox regression analysis. Our results show that the six metabolic gene signature showed good performance in predicting survival of OS patients and was also an independent prognostic factor. Stratified correlation analysis showed that the metabolic gene signature accurately predicted survival outcomes in high-risk and low-risk OS patients. The six metabolic gene signature was also verified to perform well in predicting survival of OS patients in an independent cohort (GSE21257). Then, using univariate Cox regression and Lasso Cox regression analyses, we identified an eight metabolism-related long noncoding RNA (lncRNA) signature that accurately predicts overall survival of OS patients. Gene set variation analysis showed that the apical surface and bile acid metabolism, epithelial mesenchymal transition, and P53 pathway were activated in the high-risk group based on the eight metabolism-related lncRNA signature. Furthermore, we constructed a competing endogenous RNA (ceRNA) network and conducted immunization score analysis based on the eight metabolism-related lncRNA signature. These results showed that the six metabolic gene signature and eight metabolism-related lncRNA signature have good performance in predicting the survival outcomes of OS patients.

Characterization of Bicistronic Transcription in Budding Yeast

Bicistronic transcripts (operon-like transcripts) have occasionally been reported in eukaryotes, including unicellular yeasts, plants, and humans, despite the fact that they lack trans-splice mechanisms. However, the characteristics of eukaryotic bicistronic transcripts are poorly understood, except for those in nematodes. Here, we describe the genomic, transcriptomic, and ribosome profiling features of bicistronic transcripts in unicellular yeasts. By comparing the expression level of bicistronic transcripts with their monocistronic equivalents, we identify two main categories of bicistronic transcripts: highly and lowly expressed. These two categories exhibit quite different features. First, highly expressed bicistronic transcripts have higher conservation within and between strains and shorter intergenic spacers with higher GC content and less stable secondary structure. Second, genes in highly expressed bicistronic transcripts have lower translation efficiency, with the second gene showing statistically significant lower translation efficiency than the first. Finally, the genes found in these highly expressed bicistronic transcripts tend to be younger, with more recent origins. Together, these results suggest that bicistronic transcripts in yeast are heterogeneous. We further propose that at least some highly expressed bicistronic transcripts appear to play a role in modulating monocistronic translation.IMPORTANCE Operons, where a single mRNA transcript encodes multiple adjacent proteins, are a widespread feature of bacteria and archaea. In contrast, the genes of eukaryotes are generally considered monocistronic. However, a number of studies have revealed the presence of bicistronic transcripts in eukaryotes, including humans. The basic features of these transcripts are largely unknown in eukaryotes, especially in organisms lacking trans-splice mechanisms. Our analyses characterize bicistronic transcripts in one such eukaryotic group, yeasts. We show that highly expressed bicistronic transcripts have unusual features compared to lowly expressed bicistronic transcripts, with several features influencing translational modulation.

Determinants of genome-wide distribution and evolution of uORFs in eukaryotes

Upstream open reading frames (uORFs) play widespread regulatory functions in modulating mRNA translation in eukaryotes, but the principles underlying the genomic distribution and evolution of uORFs remain poorly understood. Here, we analyze ~17 million putative canonical uORFs in 478 eukaryotic species that span most of the extant taxa of eukaryotes. We demonstrate how positive and purifying selection, coupled with differences in effective population size (Ne), has shaped the contents of uORFs in eukaryotes. Besides, gene expression level is important in influencing uORF occurrences across genes in a species. Our analyses suggest that most uORFs might play regulatory roles rather than encode functional peptides. We also show that the Kozak sequence context of uORFs has evolved across eukaryotic clades, and that noncanonical uORFs tend to have weaker suppressive effects than canonical uORFs in translation regulation. This study provides insights into the driving forces underlying uORF evolution in eukaryotes.

One-shot analysis of translated mammalian lncRNAs with AHARIBO

A vast portion of the mammalian genome is transcribed as long non-coding RNAs (lncRNAs) acting in the cytoplasm with largely unknown functions. Surprisingly, lncRNAs have been shown to interact with ribosomes, encode peptides, or act as ribosome sponges. These functions still remain mostly undetected and understudied owing to the lack of efficient tools for genome-wide simultaneous identification of ribosome-associated and peptide-producing lncRNAs. Here, we present AHA-mediated RIBOsome isolation (AHARIBO), a method for the detection of lncRNAs either untranslated, but associated with ribosomes, or encoding small peptides. Using AHARIBO in mouse embryonic stem cells during neuronal differentiation, we isolated ribosome-protected RNA fragments, translated RNAs, and corresponding de novo synthesized peptides. Besides identifying mRNAs under active translation and associated ribosomes, we found and distinguished lncRNAs acting as ribosome sponges or encoding micropeptides, laying the ground for a better functional understanding of hundreds of lncRNAs.