bims-micpro Biomed News
on Discovery and characterization of microproteins
Issue of 2020–11–15
two papers selected by
Thomas Farid Martínez, University of California, Irvine
  1. The Small Toxic Salmonella Protein TimP Targets the Cytoplasmic Membrane and Is Repressed by the Small RNA TimR.
  2. HRIBO - High-throughput analysis of bacterial ribosome profiling data.
  1. mBio. 2020 Nov 10. pii: e01659-20. [Epub ahead of print]11(6):
    The Small Toxic Salmonella Protein TimP Targets the Cytoplasmic Membrane and Is Repressed by the Small RNA TimR.
    Liis Andresen, Yolanda Martínez-Burgo, Josefin Nilsson Zangelin, Alisa Rizvanovic, Erik Holmqvist.
      Small proteins are gaining increased attention due to their important functions in major biological processes throughout the domains of life. However, their small size and low sequence conservation make them difficult to identify. It is therefore not surprising that enterobacterial ryfA has escaped identification as a small protein coding gene for nearly 2 decades. Since its identification in 2001, ryfA has been thought to encode a noncoding RNA and has been implicated in biofilm formation in Escherichia coli and pathogenesis in Shigella dysenteriae Although a recent ribosome profiling study suggested ryfA to be translated, the corresponding protein product was not detected. In this study, we provide evidence that ryfA encodes a small toxic inner membrane protein, TimP, overexpression of which causes cytoplasmic membrane leakage. TimP carries an N-terminal signal sequence, indicating that its membrane localization is Sec-dependent. Expression of TimP is repressed by the small RNA (sRNA) TimR, which base pairs with the timP mRNA to inhibit its translation. In contrast to overexpression, endogenous expression of TimP upon timR deletion permits cell growth, possibly indicating a toxicity-independent function in the bacterial membrane.IMPORTANCE Next-generation sequencing (NGS) has enabled the revelation of a vast number of genomes from organisms spanning all domains of life. To reduce complexity when new genome sequences are annotated, open reading frames (ORFs) shorter than 50 codons in length are generally omitted. However, it has recently become evident that this procedure sorts away ORFs encoding small proteins of high biological significance. For instance, tailored small protein identification approaches have shown that bacteria encode numerous small proteins with important physiological functions. As the number of predicted small ORFs increase, it becomes important to characterize the corresponding proteins. In this study, we discovered a conserved but previously overlooked small enterobacterial protein. We show that this protein, which we dubbed TimP, is a potent toxin that inhibits bacterial growth by targeting the cell membrane. Toxicity is relieved by a small regulatory RNA, which binds the toxin mRNA to inhibit toxin synthesis.
    Keywords:  TA system; growth inhibition; membrane stress; posttranscriptional control; ryfA ; sRNA; small RNA; small protein; toxin-antitoxin
    DOI:  https://doi.org/10.1128/mBio.01659-20
  2. Bioinformatics. 2020 Nov 11. pii: btaa959. [Epub ahead of print]
    HRIBO - High-throughput analysis of bacterial ribosome profiling data.
    Rick Gelhausen, Sarah L Svensson, Kathrin Froschauer, Florian Heyl, Lydia Hadjeras, Cynthia M Sharma, Florian Eggenhofer, Rolf Backofen.
       MOTIVATION: Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50-100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs).
    RESULTS: We present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization.
    AVAILABILITY: HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO.
    DOI:  https://doi.org/10.1093/bioinformatics/btaa959
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