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Interaction analyses based on growth parameters of GWAS between Escherichia coli and Staphylococcus aureus

Overview of attention for article published in AMB Express, March 2021
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Title
Interaction analyses based on growth parameters of GWAS between Escherichia coli and Staphylococcus aureus
Published in
AMB Express, March 2021
DOI 10.1186/s13568-021-01192-x
Pubmed ID
Authors

Yajing Liang, Beibei Li, Qi Zhang, Shilong Zhang, Xiaoqing He, Libo Jiang, Yi Jin

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.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Student > Bachelor 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Unspecified 1 25%
Biochemistry, Genetics and Molecular Biology 1 25%
Agricultural and Biological Sciences 1 25%
Unknown 1 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2021.
All research outputs
#16,599,610
of 18,763,644 outputs
Outputs from AMB Express
#909
of 1,117 outputs
Outputs of similar age
#259,116
of 309,495 outputs
Outputs of similar age from AMB Express
#1
of 1 outputs
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