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Yang D, Zheng X, Jiang L, Ye M, He X, Jin Y, Wu R. Functional Mapping of Phenotypic Plasticity of Staphylococcus aureus Under Vancomycin Pressure. Front Microbiol 2021; 12:696730. [PMID: 34566908 PMCID: PMC8458881 DOI: 10.3389/fmicb.2021.696730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 08/23/2021] [Indexed: 11/17/2022] Open
Abstract
Phenotypic plasticity is the exhibition of various phenotypic traits produced by a single genotype in response to environmental changes, enabling organisms to adapt to environmental changes by maintaining growth and reproduction. Despite its significance in evolutionary studies, we still know little about the genetic control of phenotypic plasticity. In this study, we designed and conducted a genome-wide association study (GWAS) to reveal genetic architecture of how Staphylococcus aureus strains respond to increasing concentrations of vancomycin (0, 2, 4, and 6 μg/mL) in a time course. We implemented functional mapping, a dynamic model for genetic mapping using longitudinal data, to map specific loci that mediate the growth trajectories of abundance of vancomycin-exposed S. aureus strains. 78 significant single nucleotide polymorphisms were identified following analysis of the whole growth and development process, and seven genes might play a pivotal role in governing phenotypic plasticity to the pressure of vancomycin. These seven genes, SAOUHSC_00020 (walR), SAOUHSC_00176, SAOUHSC_00544 (sdrC), SAOUHSC_02998, SAOUHSC_00025, SAOUHSC_00169, and SAOUHSC_02023, were found to help S. aureus regulate antibiotic pressure. Our dynamic gene mapping technique provides a tool for dissecting the phenotypic plasticity mechanisms of S. aureus under vancomycin pressure, emphasizing the feasibility and potential of functional mapping in the study of bacterial phenotypic plasticity.
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Affiliation(s)
- Dengcheng Yang
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Xuyang Zheng
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Libo Jiang
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Meixia Ye
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Xiaoqing He
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Yi Jin
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China
| | - Rongling Wu
- Center for Computational Biology, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, China.,Department of Public Health Sciences and Statistics, Center for Statistical Genetics, The Pennsylvania State University, Hershey, PA, United States
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Inferring multilayer interactome networks shaping phenotypic plasticity and evolution. Nat Commun 2021; 12:5304. [PMID: 34489412 PMCID: PMC8421358 DOI: 10.1038/s41467-021-25086-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 07/12/2021] [Indexed: 02/07/2023] Open
Abstract
Phenotypic plasticity represents a capacity by which the organism changes its phenotypes in response to environmental stimuli. Despite its pivotal role in adaptive evolution, how phenotypic plasticity is genetically controlled remains elusive. Here, we develop a unified framework for coalescing all single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) into a quantitative graph. This framework integrates functional genetic mapping, evolutionary game theory, and predator-prey theory to decompose the net genetic effect of each SNP into its independent and dependent components. The independent effect arises from the intrinsic capacity of a SNP, only expressed when it is in isolation, whereas the dependent effect results from the extrinsic influence of other SNPs. The dependent effect is conceptually beyond the traditional definition of epistasis by not only characterizing the strength of epistasis but also capturing the bi-causality of epistasis and the sign of the causality. We implement functional clustering and variable selection to infer multilayer, sparse, and multiplex interactome networks from any dimension of genetic data. We design and conduct two GWAS experiments using Staphylococcus aureus, aimed to test the genetic mechanisms underlying the phenotypic plasticity of this species to vancomycin exposure and Escherichia coli coexistence. We reconstruct the two most comprehensive genetic networks for abiotic and biotic phenotypic plasticity. Pathway analysis shows that SNP-SNP epistasis for phenotypic plasticity can be annotated to protein-protein interactions through coding genes. Our model can unveil the regulatory mechanisms of significant loci and excavate missing heritability from some insignificant loci. Our multilayer genetic networks provide a systems tool for dissecting environment-induced evolution.
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Liang Y, Li B, Zhang Q, Zhang S, He X, Jiang L, Jin Y. Interaction analyses based on growth parameters of GWAS between Escherichia coli and Staphylococcus aureus. AMB Express 2021; 11:34. [PMID: 33646434 PMCID: PMC7921238 DOI: 10.1186/s13568-021-01192-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 02/09/2021] [Indexed: 01/02/2023] Open
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.
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Zheng X, Bai J, Ye M, Liu Y, Jin Y, He X. Bivariate genome-wide association study of the growth plasticity of Staphylococcus aureus in coculture with Escherichia coli. Appl Microbiol Biotechnol 2020; 104:5437-5447. [PMID: 32350560 DOI: 10.1007/s00253-020-10636-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 04/15/2020] [Accepted: 04/20/2020] [Indexed: 12/20/2022]
Abstract
Phenotypic plasticity is the capacity to change the phenotype in response to different environments without alteration of the genotype. Despite sufficient evidence that microorganisms have a major role in the fitness and sickness of eukaryotes, there has been little research regarding microbial phenotypic plasticity. In this study, 45 strains of Staphylococcus aureus were grown for 12 days in both monoculture and in coculture with the same strain of Escherichia coli to create a competitive environment. Cell abundance was determined by quantitative PCR every 24 h, and growth curves of each S. aureus strain under the two sets of conditions were generated. Combined with whole-genome resequencing data, bivariate genome-wide association study (GWAS) was performed to analyze the growth plasticity of S. aureus in coculture. Finally, 20 significant single-nucleotide polymorphisms (eight annotated, seven unannotated, and five non-coding regions) were obtained, which may affect the competitive growth of S. aureus. This study advances genome-wide bacterial growth plasticity research and demonstrates the potential of bivariate GWAS for bacterial phenotypic plasticity research. KEY POINTS: • Growth plasticity of S. aureus was analyzed by bivariate GWAS. • Twenty significant SNPs may affect the growth plasticity of S. aureus.
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Affiliation(s)
- Xuyang Zheng
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China
| | - Jun Bai
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China
| | - Meixia Ye
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
| | - Yanxi Liu
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China
| | - Yi Jin
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China.
| | - Xiaoqing He
- College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China.
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Guo XY, Liu XJ, Hao JY. Gut microbiota in ulcerative colitis: insights on pathogenesis and treatment. J Dig Dis 2020; 21:147-159. [PMID: 32040250 DOI: 10.1111/1751-2980.12849] [Citation(s) in RCA: 127] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/16/2020] [Accepted: 02/06/2020] [Indexed: 12/11/2022]
Abstract
Gut microbiota constitute the largest reservoir of the human microbiome and are an abundant and stable ecosystem-based on its diversity, complexity, redundancy, and host interactions This ecosystem is indispensable for human development and health. The integrity of the intestinal mucosal barrier depends on its interactions with gut microbiota. The commensal bacterial community is implicated in the pathogenesis of inflammatory bowel disease (IBD), including ulcerative colitis (UC). The dysbiosis of microbes is characterized by reduced biodiversity, abnormal composition of gut microbiota, altered spatial distribution, as well as interactions among microbiota, between different strains of microbiota, and with the host. The defects in microecology, with the related metabolic pathways and molecular mechanisms, play a critical role in the innate immunity of the intestinal mucosa in UC. Fecal microbiota transplantation (FMT) has been used to treat many diseases related to gut microbiota, with the most promising outcome reported in antibiotic-associated diarrhea, followed by IBD. This review evaluated the results of various reports of FMT in UC. The efficacy of FMT remains highly controversial, and needs to be regularized by integrated management, standardization of procedures, and individualization of treatment.
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Affiliation(s)
- Xiao Yan Guo
- Department of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xin Juan Liu
- Department of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Jian Yu Hao
- Department of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
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