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A Pan-Genome Guided Metabolic Network Reconstruction of Five Propionibacterium Species Reveals Extensive Metabolic Diversity.

Abstract：

:Propionibacteria have been studied extensively since the early 1930s due to their relevance to industry and importance as human pathogens. Still, their unique metabolism is far from fully understood. This is partly due to their signature high GC content, which has previously hampered the acquisition of quality sequence data, the accurate annotation of the available genomes, and the functional characterization of genes. The recent completion of the genome sequences for several species has led researchers to reassess the taxonomical classification of the genus Propionibacterium, which has been divided into several new genres. Such data also enable a comparative genomic approach to annotation and provide a new opportunity to revisit our understanding of their metabolism. Using pan-genome analysis combined with the reconstruction of the first high-quality Propionibacterium genome-scale metabolic model and a pan-metabolic model of current and former members of the genus Propionibacterium, we demonstrate that despite sharing unique metabolic traits, these organisms have an unexpected diversity in central carbon metabolism and a hidden layer of metabolic complexity. This combined approach gave us new insights into the evolution of Propionibacterium metabolism and led us to propose a novel, putative ferredoxin-linked energy conservation strategy. The pan-genomic approach highlighted key differences in Propionibacterium metabolism that reflect adaptation to their environment. Results were mathematically captured in genome-scale metabolic reconstructions that can be used to further explore metabolism using metabolic modeling techniques. Overall, the data provide a platform to explore Propionibacterium metabolism and a tool for the rational design of strains.

journal_name

Genes (Basel)

journal_title

Genes

authors

McCubbin T,Gonzalez-Garcia RA,Palfreyman RW,Stowers C,Nielsen LK,Marcellin E

doi

10.3390/genes11101115

subject

Has Abstract

pub_date

2020-09-23 00:00:00

issue

10

issn

2073-4425

pii

genes11101115

journal_volume

11

pub_type

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