*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Biology
in the
School of Biological Sciences
Luz Karime Medina Cordoba
will defend her dissertation
Biofertilizers for Sustainable Agriculture: Isolation and Genomic Characterization of Nitrogen-Fixing Bacteria from Sugarcane
Tuesday, December 10, 2019
1:00 PM
Klaus Advanced Computing Building
Conference Room 1116 East
Thesis Advisor:
Dr. Joel E. Kostka
School of Biological Sciences
Georgia Institute of Technology
Co-Advisor:
Dr. I. King Jordan
School of Biological Sciences
Georgia Institute of Technology
Committee Members:
Dr. Frank Stewart
School of Biological Sciences
Georgia Institute of Technology
Dr. Jung H. Choi
School of Biological Sciences
Georgia Institute of Technology
Dr. Leonard W. Mayer
School of Medicine
Emory University
Abstract
The goal of my thesis research was to explore the use of bacterial biofertilizers, as an alternative or complementary approach to chemical fertilizers, in support of more sustainable agricultural practices. To this end, I worked to discover and characterize native nitrogen-fixing bacteria that are associated with sugarcane crops cultivated in the Cauca Valley of Colombia. I hypothesized that native nitrogen-fixing bacteria, found in association with local sugarcane crops could serve as potent biofertilizers with the potential to simultaneously increase crop yield while reducing the reliance on chemical fertilizers. I evaluated this hypothesis by isolating nitrogen-fixing bacteria isolated from Colombian sugarcane fields and characterizing their plant growth-promoting (PGP) potential using an integrated computational genomics and experimental approach.
A high-throughput cultivation approach was developed and applied for the enrichment and isolation of nitrogen-fixing bacteria from environmental samples. Pure cultures of nitrogen-fixing bacteria were isolated and tested for diazotrophic potential by PCR amplification of nifH genes, a common molecular marker for nitrogen-fixing capacity, and twenty-two distinct nifH positive isolates were selected for genome sequencing and analysis. Genome sequence analysis confirmed the presence of intact nifH genes and operons in the genomes of 18 of the isolates, and isolate genomes were found to encode operons for phosphate solubilization, siderophore production, and other PGP phenotypes. I characterized 14 of the 22 nitrogen-fixing isolates as distinct strains of Klebsiella pneumoniae, and four others were members of genera that are closely related to Klebsiella.
Computational phenotype predictions for PGP traits were validated with a series of experimental laboratory assays for nitrogen fixation and phosphate solubilization as well as the production of siderophores, gibberellic acid, and indole acetic acid. Results from the biochemical assays were consistent with the bioinformatic predictions for these isolates, in support of their PGP potential. The quantitative approach to computational phenotyping that I developed and applied to sugarcane bacterial isolates facilitates the screening for strains that have a high potential for nitrogen fixation and other PGP phenotypes while showing minimal risk for virulence and antibiotic resistance.
Finally, I developed and validated an automated method to curate and continuously update a nifH reference sequence database, which can be used to support the characterization of metagenomic or environmental amplicon sequences. This process yields a far smaller, but much more reliable, set of ‘gold-standard’ nifH sequences, against which users can compare their metagenomic or amplicon sequence data for accurate functional prediction and taxonomic characterization of environmental samples.