Pavlou, S. | Search bioRxiv

bioRxiv2022

HNRNPH1 regulates the neuroprotective cold-shock protein RBM3 expression through poison exon exclusion

Enhanced expression of the cold-shock protein RNA binding motif 3 (RBM3) is highly neuroprotective both in vitro and in vivo. Whilst upstream signalling pathways leading to RBM3 expression have been described, the precise molecular mechanism of RBM3 induction during cooling remains elusive. To identify temperature-dependent modulators of RBM3, we performed a genome-wide CRISPR-Cas9 knockout screen using RBM3-reporter human iPSC-derived neurons. We found that RBM3 mRNA and protein levels are robustly regulated by several splicing factors, with heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1) being the strongest positive regulator. Splicing analysis revealed that moderate hypothermia significantly represses the inclusion of a poison exon, which, when retained, targets the mRNA for nonsense-mediated decay. Importantly, we show that HNRNPH1 mediates this cold-dependent exon skipping via its interaction with a G-rich motif within the poison exon. Our study provides novel mechanistic insights into the regulation of RBM3 and provides further targets for neuroprotective therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/514062v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@ef0a5org.highwire.dtl.DTLVardef@d907a5org.highwire.dtl.DTLVardef@85176aorg.highwire.dtl.DTLVardef@1c4306a_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

NICEgame: A workflow for annotating the knowledge gaps in metabolic reconstructions, using known and hypothetical reactions

Advances in medicine and biotechnology rely on the further understanding of biological processes. Despite the increasingly available types and amounts of omics data, significant biochemical knowledge gaps remain uncharacterized. Several approaches have been developed during the past years to identify missing metabolic annotations in genome-scale. However, these approaches suggest missing metabolic reactions within a limited set of already characterized metabolic capabilities. In this study, we introduce NICEgame (Network Integrated Computational Explorer for Gap Annotation of Metabolism), a workflow to characterize missing metabolic capabilities in genome-scale metabolic models using the ATLAS of Biochemistry. NICEgame suggests alternative sets of known and hypothetical reactions to resolve gaps in metabolic networks, assesses their thermodynamic feasibility, and suggests candidate genes and proteins to catalyze the introduced reactions. We use gene essentiality data use to identify metabolic gaps in the latest genome-scale model of Escherichia coli, iML1515. We apply our gap-filling approach and further enhance its genome annotation, by suggesting reactions and putative genes to resolve 46 % of the false negative gene essentiality predictions.

systems biology↗