bims-micpro Biomed News
on Discovery and characterization of microproteins
Issue of 2021‒09‒05
four papers selected by
Thomas Martinez
Salk Institute for Biological Studies


  1. Mol Ther. 2021 Aug 31. pii: S1525-0016(21)00454-8. [Epub ahead of print]
      We and others have shown that MPM (micropeptide in mitochondria) regulates myogenic differentiation and muscle development. However, the roles of MPM in cancer development remain unknown. Here we revealed that MPM was significantly down-regulated in human hepatocellular carcinoma (HCC) tissues, and its decrease was associated with increased metastasis potential and HCC recurrence. Both in vitro and in vivo orthotopic xenograft models disclosed that the in vitro migration/invasion and in vivo liver/lung metastasis of hepatoma cells were repressed by restoring MPM expression and increased by silencing MPM. Mechanism investigations revealed that MPM interacted with NDUFA7. The mitochondrial complex I activity was inhibited by overexpressing MPM and enhanced by siMPM, and this effect of siMPM was attenuated by knocking down NDUFA7. Consistently, the NAD+/NADH ratio, which was regulated by complex I, was reduced by MPM but increased by siMPM. And treatment with NAD+ precursor nicotinamide abrogated the inhibitory effect of MPM on hepatoma cell migration. Further investigations showed that miR-17-5p bound to MPM and inhibited MPM expression. MiR-17-5p up-regulation was associated with MPM down-regulation in HCC tissues. These findings indicate that decrease of MPM expression may promote hepatoma metastasis by increasing mitochondrial complex I activity and NAD+/NADH ratio.
    DOI:  https://doi.org/10.1016/j.ymthe.2021.08.032
  2. Front Biosci (Landmark Ed). 2021 Aug 30. 26(8): 272-278
      Background: Small open reading frames (sORFs) with protein-coding ability present unprecedented challenge for genome annotation because of their short sequence and low expression level. In the past decade, only several prediction methods have been proposed for discovery of protein-coding sORFs and lack of objective and uniform negative datasets has become an important obstacle to sORFs prediction. The prediction efficiency of current sORFs prediction methods needs to be further evaluated to provide better research strategies for protein-coding sORFs discovery. Methods: In this work, nine mainstream existing methods for predicting protein-coding potential of ORFs are comprehensively evaluated based on a random sequence strategy. Results: The results show that the current methods perform poorly on different sORFs datasets. For comparison, a sequence based prediction algorithm trained on prokaryotic sORFs is proposed and its better prediction performance indicates that the random sequence strategy can provide feasible ideas for protein-coding sORFs predictions. Conclusions: As a kind of important functional genomic element, discovery of protein-coding sORFs has shed light on the dark proteomes. This evaluation work indicates that there is an urgent need for developing specialized prediction tools for protein-coding sORFs in both eukaryotes and prokaryotes. It is expected that the present work may provide novel ideas for future sORFs researches.
    Keywords:  Gene prediction; Genome annotation; Protein-coding gene; Small open reading frames; Small protein
    DOI:  https://doi.org/10.52586/4943
  3. Nucleic Acids Res. 2021 Sep 01. pii: gkab749. [Epub ahead of print]
      Retinal development is tightly regulated to ensure the generation of appropriate cell types and the assembly of functional neuronal circuitry. Despite remarkable advances have been made in understanding regulation of gene expression during retinal development, how translational regulation guides retinogenesis is less understood. Here, we conduct a comprehensive translatome and transcriptome survey to the mouse retinogenesis from the embryonic to the adult stages. We discover thousands of genes that have dynamic changes at the translational level and pervasive translational regulation in a developmental stage-specific manner with specific biological functions. We further identify genes whose translational efficiencies are frequently controlled by changing usage in upstream open reading frame during retinal development. These genes are enriched for biological functions highly important to neurons, such as neuron projection organization and microtubule-based protein transport. Surprisingly, we discover hundreds of previously uncharacterized micropeptides, translated from putative long non-coding RNAs and circular RNAs. We validate their protein products in vitro and in vivo and demonstrate their potentials in regulating retinal development. Together, our study presents a rich and complex landscape of translational regulation and provides novel insights into their roles during retinogenesis.
    DOI:  https://doi.org/10.1093/nar/gkab749
  4. Bioinformatics. 2021 Sep 03. pii: btab635. [Epub ahead of print]
      SUMMARY: Whole genome sequencing of patient populations is identifying thousands of new variants in UnTranslated Regions(UTRs). While the consequences of UTR mutations are not as easily predicted from primary sequence as coding mutations are, there are some known features of UTRs that modulate their function. utr.annotation is an R package that can be used to annotate potential deleterious variants in the UTR regions for both human and mouse species. Given a CSV or VCF format variant file, utr.annotation provides information of each variant on whether and how it alters known translational regulators including: upstream Open Reading Frames (uORFs), upstream Kozak sequences, polyA signals, Kozak sequences at the annotated translation start site, start codons, and stop codons, conservation scores in the variant position, and whether and how it changes ribosome loading based on a model derived from empirical data.AVAILABILITY: utr.annotation is freely available on Bitbucket (https://bitbucket.org/jdlabteam/utr.annotation/src/master/) and CRAN (https://cran.r-project.org/web/packages/utr.annotation/index.html).
    SUPPLEMENTARY INFORMATION: Supplementary data are available at https://wustl.box.com/s/yye99bryfin89nav45gv91l5k35fxo7z.
    DOI:  https://doi.org/10.1093/bioinformatics/btab635