Patient genetics is linked to chronic wound microbiome composition and healing
The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associ...
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| Published in | PLoS pathogens Vol. 16; no. 6; p. e1008511 |
|---|---|
| Main Authors | , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
San Francisco
Public Library of Science
01.06.2020
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1553-7374 1553-7366 1553-7374 |
| DOI | 10.1371/journal.ppat.1008511 |
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| Abstract | The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection. |
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| AbstractList | The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection.The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection. The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection. The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection. Chronic, or non-healing, wounds represent a costly burden to patients, and bacterial infection of wounds is an important driver of chronicity. A variety of bacterial species often occur in chronic wounds, but it is unknown why certain species are observed in some wound infections and not others. In this study, genetic variation of wound clinic patients was compared to the bacteria observed in their infected wounds. Through these comparisons, genetic variation in the TLN2 and ZNF521 genes was found to be associated with both the number of bacteria observed in wounds and the abundance of common pathogens (primarily Pseudomonas aeruginosa and Staphylococcus epidermidis). Moreover, Pseudomonas infected wounds were found to have fewer species present and wounds with fewer species were slower to heal. Furthermore, patient genes associated with microbiomes commonly encode proteins known to be important for cellular structures important to healing and to which bacteria directly interact. Experimental investigation of one such gene, TLN2, identified genotype-dependent differences in the expression of functionally different versions of TLN2 that is hypothesized to shape differences in cellular adhesion structures. Finally, a new statistical approach is presented in which patient biomarkers are used to predict the number of species observed during infection. Overall, our results describe how patient genetic variation influence the types of bacteria likely to infect an individual as well as influence healing. |
| Author | Fleming, Derek Pathak, Gita Tipton, Craig D. Wolcott, Randall D. Sanford, Nicholas E. Miller, Clint Rumbaugh, Kendra P. Sun, Jie Little, Todd D. Silzer, Talisa K. Phillips, Nicole Phillips, Caleb D. |
| AuthorAffiliation | 2 RTL Genomics, Lubbock, Texas, United States of America 4 Microbiology, Immunology & Genetics, University of North Texas Health Science Center, Fort Worth, Texas, United States of America 6 Burn Center of Excellence, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America 7 Department of Educational Psychology, Texas Tech University, Lubbock, Texas, United States of America 1 Department of Biological Sciences, Texas Tech University, Lubbock, Texas, United States of America 3 Southwest Regional Wound Care Center, Lubbock, Texas, United States of America 5 Department of Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America 8 Optentia Research Focus Area, North West University, Vanderbijlpark, South Africa 9 Natural Science Research Laboratory, Texas Tech University, Lubbock, Texas, United States of America University of North Carolina at Chapel Hil, UNITED STATES |
| AuthorAffiliation_xml | – name: 2 RTL Genomics, Lubbock, Texas, United States of America – name: 3 Southwest Regional Wound Care Center, Lubbock, Texas, United States of America – name: University of North Carolina at Chapel Hil, UNITED STATES – name: 9 Natural Science Research Laboratory, Texas Tech University, Lubbock, Texas, United States of America – name: 5 Department of Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America – name: 4 Microbiology, Immunology & Genetics, University of North Texas Health Science Center, Fort Worth, Texas, United States of America – name: 8 Optentia Research Focus Area, North West University, Vanderbijlpark, South Africa – name: 1 Department of Biological Sciences, Texas Tech University, Lubbock, Texas, United States of America – name: 6 Burn Center of Excellence, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America – name: 7 Department of Educational Psychology, Texas Tech University, Lubbock, Texas, United States of America |
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| Copyright | 2020 Tipton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2020 Tipton et al 2020 Tipton et al |
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