Dataset Information

Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

ABSTRACT: Listeria monocytogenes is a microorganism of great concern for the food industry and the cause of human foodborne disease. Therefore, novel methods of control are needed, and systems biology is one such approach to identify them. Using a combination of computational techniques and laboratory methods, genome-scale metabolic models (GEMs) can be created, validated, and used to simulate growth environments and discern metabolic capabilities of microbes of interest, including L. monocytogenes. The objective of the work presented here was to generate GEMs for six different strains of L. monocytogenes, and to both qualitatively and quantitatively validate these GEMs with experimental data to examine the diversity of metabolic capabilities of numerous strains from the three different serovar groups most associated with foodborne outbreaks and human disease. Following qualitative validation, 57 of the 95 carbon sources tested experimentally were present in the GEMs, and; therefore, these were the compounds from which comparisons could be drawn. Of these 57 compounds, agreement between in silico predictions and in vitro results for carbon source utilization ranged from 80.7% to 91.2% between strains. Nutrient utilization agreement between in silico predictions and in vitro results were also conducted for numerous nitrogen, phosphorous, and sulfur sources. Additionally, quantitative validation showed that the L. monocytogenes GEMs were able to generate in silico predictions for growth rate and growth yield that were strongly and significantly (p < 0.0013 and p < 0.0015, respectively) correlated with experimental results. These findings are significant because they show that these GEMs for L. monocytogenes are comparable to published GEMs of other organisms for agreement between in silico predictions and in vitro results. Therefore, as with the other GEMs, namely those for Escherichia coli, Staphylococcus aureus, Vibrio vulnificus, and Salmonella spp., they can be used to determine new methods of growth control and disease treatment.

SUBMITTER: Metz ZP

PROVIDER: S-EPMC6012718 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

Metz Zachary P ZP Ding Tong T Baumler David J DJ

PloS one 20180607 6

Listeria monocytogenes is a microorganism of great concern for the food industry and the cause of human foodborne disease. Therefore, novel methods of control are needed, and systems biology is one such approach to identify them. Using a combination of computational techniques and laboratory methods, genome-scale metabolic models (GEMs) can be created, validated, and used to simulate growth environments and discern metabolic capabilities of microbes of interest, including L. monocytogenes. The o ...[more]

PMID: 29879172

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Project description:Full title: Probing the pan genome of a foodborne bacterial pathogen Listeria monocytogenes: Implications for its niche adaptation, pathogenesis, and evolution Listeria monocytogenes is a foodborne bacterial pathogen well known for adaptability to diverse environmental and host niches, and a high fatality rate among infected, immuno-compromised individuals. Three genetic lineages have been identified within this species. Strains of genetic lineages I and II account for more than ninety percent of foodborne disease outbreaks worldwide, whereas strains from genetic lineage III are rarely implicated in human infectious for unknown, yet intriguing, reasons. Here we have probed the genomic diversity of 26 L. monocytogenes strains using both whole-genome sequences and a novel 385,000 probe pan-genome microarray, fully tiling the genomes of 20 representative strains. Using these methods to identify genes highly conserved in lineages I and II but rare in lineage III, we have identified 86 genes and 8 small RNAs that play roles in bacterial stress resistance, pathogenicity, and niche, potentially explaining the predominance of L. monocytogenes lineages I and II in foodborne disease outbreaks. Extending gene content analysis to all lineages revealed a L. monocytogenes core genome of approximately 2,350 genes (80% of each individual genome) and a pan-genomic reservoir of >4,000 unique genes. Combined gene content data from both sequences and arrays was used to reconstruct an informative phylogeny for the L. monocytogenes species that confirms three distinct lineages and describes the relationship of 9 new lineage III genomes. Comparative analysis of 18 fully sequenced L. monocytogenes lineage I and II genomes shows a high level of genomic conservation and synteny, indicative of a closed pan-genome, with moderate domain shuffling and sequence drift associated with bacteriophages is present in all lineages. In contrast with lineages I and II, notable genomic diversity and characteristics of an open pan-genome were observed in the lineage III genomes, including many strain-specific genes and a more complex conservation pattern. This indicates that the L. monocytogenes pan-genome has not yet been fully sampled by genome sequencing, and additional sequencing of lineage III genomes is necessary to survey the full diversity of this intriguing species and reveal its mechanisms for adaptability and virulence.

Dataset Information

Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

Publications

Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

Similar Datasets

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