Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields

Abstract Previous studies have shown the sugarcane microbiome harbors diverse plant growth promoting microorganisms, including nitrogen-fixing bacteria (diazotrophs), which can serve as biofertilizers. The genomes of 22 diazotrophs from Colombian sugarcane fields were sequenced to investigate potent...

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Autores principales: Luz K. Medina-Cordoba, Aroon T. Chande, Lavanya Rishishwar, Leonard W. Mayer, Lina C. Valderrama-Aguirre, Augusto Valderrama-Aguirre, John Christian Gaby, Joel E. Kostka, I. King Jordan
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Publicado: Nature Portfolio 2021
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spelling oai:doaj.org-article:252dea7e7a7740c1ad8c2ca0106b9f0d2021-12-02T14:53:43ZGenomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields10.1038/s41598-021-88380-82045-2322https://doaj.org/article/252dea7e7a7740c1ad8c2ca0106b9f0d2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88380-8https://doaj.org/toc/2045-2322Abstract Previous studies have shown the sugarcane microbiome harbors diverse plant growth promoting microorganisms, including nitrogen-fixing bacteria (diazotrophs), which can serve as biofertilizers. The genomes of 22 diazotrophs from Colombian sugarcane fields were sequenced to investigate potential biofertilizers. A genome-enabled computational phenotyping approach was developed to prioritize sugarcane associated diazotrophs according to their potential as biofertilizers. This method selects isolates that have potential for nitrogen fixation and other plant growth promoting (PGP) phenotypes while showing low risk for virulence and antibiotic resistance. Intact nitrogenase (nif) genes and operons were found in 18 of the isolates. Isolates also encode phosphate solubilization and siderophore production operons, and other PGP genes. The majority of sugarcane isolates showed uniformly low predicted virulence and antibiotic resistance compared to clinical isolates. Six strains with the highest overall genotype scores were experimentally evaluated for nitrogen fixation, phosphate solubilization, and the production of siderophores, gibberellic acid, and indole acetic acid. Results from the biochemical assays were consistent and validated computational phenotype predictions. A genotypic and phenotypic threshold was observed that separated strains by their potential for PGP versus predicted pathogenicity. Our results indicate that computational phenotyping is a promising tool for the assessment of bacteria detected in agricultural ecosystems.Luz K. Medina-CordobaAroon T. ChandeLavanya RishishwarLeonard W. MayerLina C. Valderrama-AguirreAugusto Valderrama-AguirreJohn Christian GabyJoel E. KostkaI. King JordanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Luz K. Medina-Cordoba
Aroon T. Chande
Lavanya Rishishwar
Leonard W. Mayer
Lina C. Valderrama-Aguirre
Augusto Valderrama-Aguirre
John Christian Gaby
Joel E. Kostka
I. King Jordan
Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
description Abstract Previous studies have shown the sugarcane microbiome harbors diverse plant growth promoting microorganisms, including nitrogen-fixing bacteria (diazotrophs), which can serve as biofertilizers. The genomes of 22 diazotrophs from Colombian sugarcane fields were sequenced to investigate potential biofertilizers. A genome-enabled computational phenotyping approach was developed to prioritize sugarcane associated diazotrophs according to their potential as biofertilizers. This method selects isolates that have potential for nitrogen fixation and other plant growth promoting (PGP) phenotypes while showing low risk for virulence and antibiotic resistance. Intact nitrogenase (nif) genes and operons were found in 18 of the isolates. Isolates also encode phosphate solubilization and siderophore production operons, and other PGP genes. The majority of sugarcane isolates showed uniformly low predicted virulence and antibiotic resistance compared to clinical isolates. Six strains with the highest overall genotype scores were experimentally evaluated for nitrogen fixation, phosphate solubilization, and the production of siderophores, gibberellic acid, and indole acetic acid. Results from the biochemical assays were consistent and validated computational phenotype predictions. A genotypic and phenotypic threshold was observed that separated strains by their potential for PGP versus predicted pathogenicity. Our results indicate that computational phenotyping is a promising tool for the assessment of bacteria detected in agricultural ecosystems.
format article
author Luz K. Medina-Cordoba
Aroon T. Chande
Lavanya Rishishwar
Leonard W. Mayer
Lina C. Valderrama-Aguirre
Augusto Valderrama-Aguirre
John Christian Gaby
Joel E. Kostka
I. King Jordan
author_facet Luz K. Medina-Cordoba
Aroon T. Chande
Lavanya Rishishwar
Leonard W. Mayer
Lina C. Valderrama-Aguirre
Augusto Valderrama-Aguirre
John Christian Gaby
Joel E. Kostka
I. King Jordan
author_sort Luz K. Medina-Cordoba
title Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
title_short Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
title_full Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
title_fullStr Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
title_full_unstemmed Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields
title_sort genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from colombian sugarcane fields
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/252dea7e7a7740c1ad8c2ca0106b9f0d
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