Robustness encoded across essential and accessory replicons of the ecologically versatile bacterium Sinorhizobium meliloti
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journal.pgen.1007357.pdf
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4.11 MB
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Checksum (MD5)
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Author(s)
diCenzo, George C.
Benedict, Alex B.
Fondi, Marco
Finan, Turlough M.
Mengoni, Alessio
Griffitts, Joel S
Walker, Graham C.
Date Issued
April 2018
Journal
PLOS Genetics
Publisher
Public Library of Science
Citation
diCenzo, George C., Alex B. Benedict, Marco Fondi, Graham C. Walker, Turlough M. Finan, Alessio Mengoni, and Joel S. Griffitts. “Robustness Encoded Across Essential and Accessory Replicons of the Ecologically Versatile Bacterium Sinorhizobium Meliloti.” Edited by Josep Casadesús. PLOS Genetics 14, no. 4 (April 19, 2018): e1007357.
Version
Final published version
Abstract
Bacterial genome evolution is characterized by gains, losses, and rearrangements of functional genetic segments. The extent to which large-scale genomic alterations influence genotype-phenotype relationships has not been investigated in a high-throughput manner. In the symbiotic soil bacterium Sinorhizobium meliloti, the genome is composed of a chromosome and two large extrachromosomal replicons (pSymA and pSymB, which together constitute 45% of the genome). Massively parallel transposon insertion sequencing (Tn-seq) was employed to evaluate the contributions of chromosomal genes to growth fitness in both the presence and absence of these extrachromosomal replicons. Ten percent of chromosomal genes from diverse functional categories are shown to genetically interact with pSymA and pSymB. These results demonstrate the pervasive robustness provided by the extrachromosomal replicons, which is further supported by constraint-based metabolic modeling. A comprehensive picture of core S. meliloti metabolism was generated through a Tn-seq-guided in silico metabolic network reconstruction, producing a core network encompassing 726 genes. This integrated approach facilitated functional assignments for previously uncharacterized genes, while also revealing that Tn-seq alone missed over a quarter of wild-type metabolism. This work highlights the many functional dependencies and epistatic relationships that may arise between bacterial replicons and across a genome, while also demonstrating how Tn-seq and metabolic modeling can be used together to yield insights not obtainable by either method alone.
MIT Department
Massachusetts Institute of Technology. Department of Biology
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1371/journal.pgen.1007357
