ArticlePlant cell reports2024
A snapshot of the Physcomitrella N-terminome reveals N-terminal methylation of organellar proteins.
Article in Plant cell reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Evolutionary Refinement of Mitochondrial and Plastid Targeting Sequences Coincides with the Late Diversification of Land Plants.Molecular biology and evolution · 2025Article
- Acylamino acid-releasing enzyme, a bifunctional protease with a potential role in aging.Journal of experimental botany · 2025Review
- Production of human papillomavirus type 16 virus-like particles in Physcomitrella photobioreactors.Plant cell reports · 2025Article
- Recombinant production of spider silk protein in Physcomitrella photobioreactors.Plant cell reports · 2025Article
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Authors and funding
7 authors.
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Abstract
key messageAnalysis of the N-terminome of Physcomitrella reveals N-terminal monomethylation of nuclear-encoded, mitochondria-localized proteins. Post- or co-translational N-terminal modifications of proteins influence their half-life as well as mediating protein sorting to organelles via cleavable N-terminal sequences that are recognized by the respective translocation machinery. Here, we provide an overview on the current modification state of the N-termini of over 4500 proteins from the model moss Physcomitrella (Physcomitrium patens) using a compilation of 24 N-terminomics datasets. Our data reveal distinct proteoforms and modification states and confirm predicted targeting peptide cleavage sites of 1,144 proteins localized to plastids and the thylakoid lumen, to mitochondria, and to the secretory pathway. In addition, we uncover extended N-terminal methylation of mitochondrial proteins. Moreover, we identified PpNTM1 (P. patens alpha N-terminal protein methyltransferase 1) as a candidate for protein methylation in plastids, mitochondria, and the cytosol. These data can now be used to optimize computational targeting predictors, for customized protein fusions and their targeted localization in biotechnology, and offer novel insights into potential dual targeting of proteins.
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