AntiSMASH and RAST Results for Bradyrhizobium sp. Ash2021

Secondary metabolite clusters were predicted for Bradyrhizobium sp. Ash2021 using antiSMASH v7.1.0 [1] and RAST [2].The AntiSMASH output can be found in the file: CP100604.1_AntiSMASH_Secondary_Metabolites.zip 13 secondary metabolites were predicted:RegionTypeFromToRegion 1T3PKS150,880191,932Region 2RiPP-like1,308,4091,319,263Region 3RiPP-like2,147,2792,158,103Region 4hserlactone2,234,6972,255,353Region 5T1PKS2,368,0992,413,222Region 6terpene3,465,3303,490,320Region 7LAP4,536,7774,560,506Region 8terpene5,099,1645,120,024Region 9RiPP-like6,091,4476,102,370Region 10NRPS-like7,068,1187,111,279Region 11RiPP-like7,217,8877,228,789Region 12redox-cofactor7,409,5607,431,853Region 13RiPP-like8,940,7088,951,634The RAST output of the predicted genes can be found in the spreadsheet: RAST_Annotations_Ash2021_Bradyrhizobium.xlsxWhich includes 3 predicted secondary metabolites, Alkaloid biosynthesis from L-lysine, Auxin biosynthesis, and Thiazole- oxazole-modified microcin (TOMM) synthesis[1] Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F, Alanjary M, Fetter A, Terlouw BR, Metcalf WW, Helfrich E, van Wezel GP, Medema MH, Weber T. 2023. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures, and visualisation. Nucl Acids Res 51 (W1) W46-W50. https://doi.org/10.1093/nar/gkad344[2] Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, Olson R, Overbeek R, Parrello B, Pusch GD, Shukla M, Thomason JA, Stevens R, Vonstein V, Wattam AR, Xia F. 2015. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Scientific reports 5: 8365https://doi.org/10.1038/srep08365