Abstract
To accurately explore the interaction mechanism between Escherichia coli and Staphylococcus aureus, we designed an ecological experiment to monoculture and co-culture E. coli and S. aureus. We co-cultured 45 strains of E. coli and S. aureus, as well as each species individually to measure growth over 36 h. We implemented a genome wide association study (GWAS) based on growth parameters (λ, R, A and s) to identify significant single nucleotide polymorphisms (SNPs) of the bacteria. Three commonly used growth regression equations, Logistic, Gompertz, and Richards, were used to fit the bacteria growth data of each strain. Then each equation’s Akaike’s information criterion (AIC) value was calculated as a commonly used information criterion. We used the optimal growth equation to estimate the four parameters above for strains in co-culture. By plotting the estimates for each parameter across two strains, we can visualize how growth parameters respond ecologically to environment stimuli. We verified that different genotypes of bacteria had different growth trajectories, although they were the same species. We reported 85 and 52 significant SNPs that were associated with interaction in E. coli and S. aureus, respectively. Many significant genes might play key roles in interaction, such as yjjW, dnaK, aceE, tatD, ftsA, rclR, ftsK, fepA in E. coli, and scdA, trpD, sdrD, SAOUHSC_01219 in S. aureus. Our study illustrated that there were multiple genes working together to affect bacterial interaction, and laid a solid foundation for the later study of more complex inter-bacterial interaction mechanisms.
Highlights
There are extremely complex interactions between organisms and their environment, which play a crucial role in nature, in microbial environments (Grativol et al 2017; He et al 2017; Madsen et al 2018; Pires et al 2015; van Overbeek and Saikkonen 2016)
Genetic analyses of microbial growth in monocultures Manhattan plots were obtained by employing genome-wide association study (GWAS) combined with functional mapping of 45 E. coli and 45 S. aureus strains to identify polymorphisms associated with different growth phenotypes
85 and 97 significant single-nucleotide polymorphism (SNPs) were beyond the genome-wide critical thresholds determined for E. coli and S. aureus, respectively, and were annotated
Summary
There are extremely complex interactions between organisms and their environment, which play a crucial role in nature, in microbial environments (Grativol et al 2017; He et al 2017; Madsen et al 2018; Pires et al 2015; van Overbeek and Saikkonen 2016). A genome-wide association study (GWAS) with longitudinal phenotypes provides a novel platform to identify genetic variant associations and how they change over time (Sikorska et al 2018). Many bacterial phenotypes can be linked to the presence or absence of significant genes, which partly explains different responses to similar environmental conditions. Bacterial GWAS have overcame some limitations of the traditional genetic association studies, such as sample sizes and population structure, which is able to associate genetic variation in genomes with phenotypes to analyze genetic mechanisms (Lees et al 2016). We have applied GWAS analyses to find many significant genes in E. coli and S. aureus and have explored the phenotypic plasticity of S. aureus (He et al 2017; Jiang et al 2018; Rong et al 2019). Our analyses provide a strong basis for interaction experiments of bacteria in future studies
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