{"title":"Revealing of Potential Plant Growth-Enhancing Traits Through In Silico Genomic Analysis of Bacillus Rhizoplanae CIP111899","authors":"Guendouz Dif, A. Zitouni","doi":"10.37575/b/sci/230003","DOIUrl":null,"url":null,"abstract":"The objective of this study was to examine the whole genome of the bacterial strain CIP111899, isolated from the root surface of maize (Zea mays), in order to reveal the presence of genes implicated in enhancing plant growth. The genome-based taxonomy revealed that strain CIP111899 belongs to a new species called Bacillus rhizoplanae. In the second step, the genome of CIP111899 was analyzed on multiple levels using various information tools. This involved examining functional categories associated with genes using analytical techniques, namely, annotation using the RAST server, then identifying growth-promoting genes with the Prokka program, and finally detecting groups of genes responsible for secondary metabolism through antiSMASH analysis. The results of the genomic analysis of strain CIP111899 showed the presence of multiple genes that enhance stress tolerance, such as those encoding enzymes and antioxidants (superoxide dismutase, peroxidases, and catalase). Additionally, various plant growth-promoting genes were identified, including those involved in the solubility of inorganic phosphorus, phytohormone production, and iron uptake. In conclusion, strain CIP111899 has shown promise as a potential agent for promoting plant growth and thereby improving food security due to its genetic composition.","PeriodicalId":39024,"journal":{"name":"Scientific Journal of King Faisal University","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Journal of King Faisal University","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37575/b/sci/230003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Multidisciplinary","Score":null,"Total":0}
引用次数: 0
Abstract
The objective of this study was to examine the whole genome of the bacterial strain CIP111899, isolated from the root surface of maize (Zea mays), in order to reveal the presence of genes implicated in enhancing plant growth. The genome-based taxonomy revealed that strain CIP111899 belongs to a new species called Bacillus rhizoplanae. In the second step, the genome of CIP111899 was analyzed on multiple levels using various information tools. This involved examining functional categories associated with genes using analytical techniques, namely, annotation using the RAST server, then identifying growth-promoting genes with the Prokka program, and finally detecting groups of genes responsible for secondary metabolism through antiSMASH analysis. The results of the genomic analysis of strain CIP111899 showed the presence of multiple genes that enhance stress tolerance, such as those encoding enzymes and antioxidants (superoxide dismutase, peroxidases, and catalase). Additionally, various plant growth-promoting genes were identified, including those involved in the solubility of inorganic phosphorus, phytohormone production, and iron uptake. In conclusion, strain CIP111899 has shown promise as a potential agent for promoting plant growth and thereby improving food security due to its genetic composition.
期刊介绍:
The scientific Journal of King Faisal University is a biannual refereed scientific journal issued under the guidance of the University Scientific Council. The journal also publishes special and supplementary issues when needed. The first volume was published on 1420H-2000G. The journal publishes two separate issues: Humanities and Management Sciences issue, classified in the Arab Impact Factor index, and Basic and Applied Sciences issue, on June and December, and indexed in (CABI) and (SCOPUS) international databases.