Data associated with the paper Antczak et al. "Environmental conditions shape the nature of a minimal bacterial genome" published in Nature Communications 2019

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3DLigandSite.txt

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Argot2.5.txt

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CATHFunFams.txt

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CombFunc.txt

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DISOPRED3.txt

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eggNOG-Mapper.txt

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FFPred3.txt

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InterPro.txt

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LocTree3.txt

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Pfam.txt

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Phyre2.txt

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TIGRFAM.txt

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TMHMM.txt

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TrSSP.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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indexcodes.txt

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LipoP.txt

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BLASTAgainstUniProt.txt

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README.txt

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http://eprints.org/relation/isVersionOf https://data.kent.ac.uk/id/document/434 http://eprints.org/relation/isVolatileVersionOf https://data.kent.ac.uk/id/document/434 http://eprints.org/relation/isIndexCodesVersionOf https://data.kent.ac.uk/id/document/434 archive 63 disk0/00/00/00/78 2019-06-04 07:57:37 2025-06-03 08:37:49 2019-06-04 07:57:37 data_collection show m.n.wass@kent.ac.uk Antczak Magdalena ma745@kent.ac.uk 0000-0003-1503-1849 Michaelis Martin m.michaelis@kent.ac.uk 0000-0002-5710-5888 Wass Mark N m.n.wass@kent.ac.uk 0000-0001-5428-6479 Data associated with the paper Antczak et al. "Environmental conditions shape the nature of a minimal bacterial genome" published in Nature Communications 2019 51100 public Of the 473 genes in the genome of the bacterium with the smallest genome generated to date, 149 genes have unknown function, emphasising a universal problem; less than 1% of proteins have experimentally determined annotations. Here, we combine the results from state-of-the-art in silico methods for functional annotation and assigned functions to 66 of the 149 proteins. Proteins that are still not be annotated lack orthologs, lack protein domains, and/ or are membrane proteins. Twenty-four likely transporter proteins are identified indicating the importance of nutrient uptake into and waste disposal out of the minimal bacterial cell in a nutrient-rich environment after removal of metabolic enzymes. Hence, the environment shapes the nature of a minimal genome. Our findings also show that the combination of multiple different state-of-the-art in silico methods for annotating proteins is able to predict functions, even for difficult to characterise proteins and identify crucial gaps for further development. 2019-05-29 dataset pub 2019-06-04 2019-06-04 2025-06-03 12100 Biosciences English 2017 2019 10.22024/unikent/01.01.78