bims-micpro Biomed News
on Discovery and characterization of microproteins
Issue of 2023–05–14
five papers selected by
Thomas Farid Martínez, University of California, Irvine



  1. Cell Syst. 2023 May 05. pii: S2405-4712(23)00086-8. [Epub ahead of print]
      Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. A representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response, and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.
    Keywords:  de novo gene birth; evolutionary genomics; genome annotation; microproteins; noncanonical translation; protein evolution; ribosome profiling; smORFs
    DOI:  https://doi.org/10.1016/j.cels.2023.04.002
  2. Biochem Soc Trans. 2023 May 12. pii: BST20221074. [Epub ahead of print]
      Thousands of unannotated small and alternative open reading frames (smORFs and alt-ORFs, respectively) have recently been revealed in mammalian genomes. While hundreds of mammalian smORF- and alt-ORF-encoded proteins (SEPs and alt-proteins, respectively) affect cell proliferation, the overwhelming majority of smORFs and alt-ORFs remain uncharacterized at the molecular level. Complicating the task of identifying the biological roles of smORFs and alt-ORFs, the SEPs and alt-proteins that they encode exhibit limited sequence homology to protein domains of known function. Experimental techniques for the functionalization of these gene classes are therefore required. Approaches combining chemical labeling and quantitative proteomics have greatly advanced our ability to identify and characterize functional SEPs and alt-proteins in high throughput. In this review, we briefly describe the principles of proteomic discovery of SEPs and alt-proteins, then summarize how these technologies interface with chemical labeling for identification of SEPs and alt-proteins with specific properties, as well as in defining the interactome of SEPs and alt-proteins.
    Keywords:  alt-protein; chemical biology; microprotein; proteogenomics; proteomics; smORF
    DOI:  https://doi.org/10.1042/BST20221074
  3. Methods Mol Biol. 2023 ;2661 257-280
      To understand the human mitochondrial translation process, tools are required to dissect this system at a global scale. The mechanisms and regulation of translation in mitochondria are different from those in the cytosol, and mitochondrial ribosomes have distinct biochemical properties. In this chapter, we describe in detail the modifications we have made to the ribosome profiling approach to adapt it to the unique characteristics of the human mitochondrial ribosome. This approach maximizes the fraction of mitochondrial ribosomes recovered, providing a snapshot of the mitochondrial translation landscape with minimal bias. We also describe the use of mouse lysate as an internal spike-in control for normalization, allowing quantification of global changes in translation across samples. Finally, we outline the bioinformatic pipelines to process the raw reads and identify mitoribosome A sites in the absence of untranslated regions flanking open reading frames. This method offers a subcodon-resolution time-sensitive global approach to explore the mitochondrial translation process in human cells.
    Keywords:  Human mitochondrial translation; Mitochondrial ribosome profiling
    DOI:  https://doi.org/10.1007/978-1-0716-3171-3_15
  4. Sci China Life Sci. 2023 May 05.
      Long noncoding RNAs (lncRNAs) have been extensively identified in eukaryotic genomes and have been shown to play critical roles in the development of multiple cancers. Through the application and development of ribosome analysis and sequencing technologies, advanced studies have discovered the translation of lncRNAs. Although lncRNAs were originally defined as noncoding RNAs, many lncRNAs actually contain small open reading frames that are translated into peptides. This opens a broad area for the functional investigation of lncRNAs. Here, we introduce prospective methods and databases for screening lncRNAs with functional polypeptides. We also summarize the specific lncRNA-encoded proteins and their molecular mechanisms that promote or inhibit cancerous. Importantly, the role of lncRNA-encoded peptides/proteins holds promise in cancer research, but some potential challenges remain unresolved. This review includes reports on lncRNA-encoded peptides or proteins in cancer, aiming to provide theoretical basis and related references to facilitate the discovery of more functional peptides encoded by lncRNA, and to further develop new anti-cancer therapeutic targets as well as clinical biomarkers of diagnosis and prognosis.
    Keywords:  lncRNA; peptide; translatome; tumor
    DOI:  https://doi.org/10.1007/s11427-022-2289-6
  5. Nucleic Acids Res. 2023 May 09. pii: gkad381. [Epub ahead of print]
      Recent advances have shown that some biologically active non-coding RNAs (ncRNAs) are actually translated into polypeptides that have a physiological function as well. This paradigm shift requires adapted computational methods to predict this new class of 'bifunctional RNAs'. Previously, we developed IRSOM, an open-source algorithm to classify non-coding and coding RNAs. Here, we use the binary statistical model of IRSOM as a ternary classifier, called IRSOM2, to identify bifunctional RNAs as a rejection of the two other classes. We present its easy-to-use web interface, which allows users to perform predictions on large datasets of RNA sequences in a short time, to re-train the model with their own data, and to visualize and analyze the classification results thanks to the implementation of self-organizing maps (SOM). We also propose a new benchmark of experimentally validated RNAs that play both protein-coding and non-coding roles, in different organisms. Thus, IRSOM2 showed promising performance in detecting these bifunctional transcripts among ncRNAs of different types, such as circRNAs and lncRNAs (in particular those of shorter lengths). The web server is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.
    DOI:  https://doi.org/10.1093/nar/gkad381