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Background Livestock-related emissions have been associated with aggravations of respiratory symptoms in patients with chronic obstructive pulmonary disease (COPD), potentially by altering the respiratory resistome. Objectives This study investigates the structure of the acquired oropharyngeal (OP) resistome of patients with COPD and controls, its interplay with the respiratory microbiome and associations with residential livestock exposure. Methods In a matched case–control study in the rural Netherlands, we analysed OP swabs from 35 patients with COPD and 34 controls, none of whom had used antibiotics in the preceding 4 weeks. Resistome profiling was performed using ResCap, complemented by prior characterization of the microbiome via 16S rRNA-based sequencing. Residential livestock farm exposure was defined using distance-based variables alongside modelled concentrations of livestock-emitted microbial pollutants. We compared resistome profiles between patients with COPD and controls, examining alpha and beta diversity as well as differential abundance. Additionally, we assessed the interplay between the resistome and microbiome using co-occurrence networks and Procrustes analysis. Variations in resistome profiles were also analysed based on residential livestock exposures. Results Patients with COPD exhibited higher resistome diversity than controls (Shannon diversity, P = 0.047), though resistome composition remained similar between groups (PERMANOVA, P = 0.19). Significant correlations were observed between the OP resistome and microbiome compositions, with distinct patterns in co-occurrence networks. Residential exposure to livestock farms was not associated with resistome alterations. Conclusions Our findings reveal the COPD airway as a hospitable environment for antimicrobial resistance genes, irrespective of recent antimicrobial usage. Demonstrating the interplay between the resistome and microbiome, our study underscores the importance of a deeper understanding of the resistome in respiratory health.
Background Livestock-related emissions have been associated with aggravations of respiratory symptoms in patients with chronic obstructive pulmonary disease (COPD), potentially by altering the respiratory resistome. Objectives This study investigates the structure of the acquired oropharyngeal (OP) resistome of patients with COPD and controls, its interplay with the respiratory microbiome and associations with residential livestock exposure. Methods In a matched case–control study in the rural Netherlands, we analysed OP swabs from 35 patients with COPD and 34 controls, none of whom had used antibiotics in the preceding 4 weeks. Resistome profiling was performed using ResCap, complemented by prior characterization of the microbiome via 16S rRNA-based sequencing. Residential livestock farm exposure was defined using distance-based variables alongside modelled concentrations of livestock-emitted microbial pollutants. We compared resistome profiles between patients with COPD and controls, examining alpha and beta diversity as well as differential abundance. Additionally, we assessed the interplay between the resistome and microbiome using co-occurrence networks and Procrustes analysis. Variations in resistome profiles were also analysed based on residential livestock exposures. Results Patients with COPD exhibited higher resistome diversity than controls (Shannon diversity, P = 0.047), though resistome composition remained similar between groups (PERMANOVA, P = 0.19). Significant correlations were observed between the OP resistome and microbiome compositions, with distinct patterns in co-occurrence networks. Residential exposure to livestock farms was not associated with resistome alterations. Conclusions Our findings reveal the COPD airway as a hospitable environment for antimicrobial resistance genes, irrespective of recent antimicrobial usage. Demonstrating the interplay between the resistome and microbiome, our study underscores the importance of a deeper understanding of the resistome in respiratory health.
Livestock barns are integral to modern agriculture, providing essential environments for raising animals. The air quality in these barns directly impacts livestock health, quality of production and environmental sustainability. Trends in key metrics such as gas concentrations, particulate matter levels, humidity content, and temperature can influence the overall health of livestock, barn operations, and broader ecological factors. Understanding these trends and their interrelationships is crucial for managing barn conditions effectively. To investigate air quality trends in livestock barns, data was collected using IoT multiple sensors device. These sensors recorded various metrics, including gas concentrations (hydrogen sulfide, ammonia, volatile organic compounds), particulate matter levels (PM2.5 and PM10), and humidity-related metrics such as relative humidity and dewpoint temperature. The collected data was analyzed using correlation and trend analyses to explore relationships between these variables and their influence on barn conditions. The analysis reveals key trends and positive correlations between the collected data.
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