Project description:Positive and negative ecological interactions shape the dynamics and composition of natural microbial communities. The mechanisms behind microbe-microbe interactions, particularly those protein-based, are not well understood and only a small percentage of such interactions has been studied. We hypothesize that secreted proteins are a powerful and highly specific toolset to shape and defend a favorable plant niche. Here, we have studied Albugo candida, an obligate plant parasite from the protist Oomycota phylum, for its potential to inhibit and promote the growth of bacteria through secretion of proteins into the apoplast. Amplicon sequencing and network analysis of Albugo-infected and uninfected samples revealed an abundance of negative correlations between Albugo and other phyllosphere microbes. Analysis of the secreted proteome of Albugo candida combined with machine-learning predictors enabled the selection of candidates for heterologous expression and study of their inhibitory activity in vitro. We found that three of the candidate proteins showed a selective antimicrobial activity on several gram-positive bacterial strains isolated from Arabidopsis thaliana. We could ascribe the antibacterial activity of the candidates to their intrinsically disordered regions and positively correlate it with their net charge. This is the first report of protist proteins that have an antimicrobial activity under apoplastic conditions and therefore are potential biocontrol tools for a targeted manipulation of the microbiome.
Project description: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.