Dataset Information

Seasonal variability in airborne biotic contaminants in swine confinement buildings.

ABSTRACT: Little is known about the seasonal dynamics of biotic contaminants in swine confinement buildings (SCBs). The biotic contaminants of seven SCBs were monitored during one visit in the winter and one during the summer. Paired-end Illumina sequencing of the 16S rRNA gene, V3 region, was used to examine seasonal shifts in bacterial community composition and diversity. The abundances of 16S rRNA genes and six tetracycline resistance genes (tetB, tetH, tetZ, tetO, tetQ, and tetW) were also quantified using real-time PCR. Bacterial abundances, community composition and diversity all showed strong seasonal patterns defined by winter peaks in abundance and diversity. Microclimatic variables of SCBs, particularly air speed, PM2.5 and total suspended particles (TSP) were found significantly correlated to abundances, community composition, and diversity of bacterial bioaerosols. Seasonal fluctuations were also observed for four tetracycline resistance genes, tetH, tetO, tetQ, and tetW. The frequency of occurrences of these resistance genes were significantly higher in samples collected during winter and was also significantly correlated with air speed, PM2.5 and TSP. Overall, our results indicate that biotic contaminants in SCBs exhibit seasonal trends, and these could be associated with the microclimatic variables of SCBs. The correlations established in the current study could be helpful in establishing better management strategies to minimize the potential health impacts on both livestock and humans working in this environment.

SUBMITTER: Kumari P

PROVIDER: S-EPMC4231085 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Seasonal variability in airborne biotic contaminants in swine confinement buildings.

Kumari Priyanka P Choi Hong L HL

PloS one 20141113 11

Little is known about the seasonal dynamics of biotic contaminants in swine confinement buildings (SCBs). The biotic contaminants of seven SCBs were monitored during one visit in the winter and one during the summer. Paired-end Illumina sequencing of the 16S rRNA gene, V3 region, was used to examine seasonal shifts in bacterial community composition and diversity. The abundances of 16S rRNA genes and six tetracycline resistance genes (tetB, tetH, tetZ, tetO, tetQ, and tetW) were also quantified ...[more]

PMID: 25393011

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Project description:The atmosphere represents an underexplored temporary habitat for airborne microbial communities such as eukaryotes, whose taxonomic structure changes across different locations and/or regions as a function of both survival conditions and sources. A preliminary dataset on the seasonal dependence of the airborne eukaryotic community biodiversity, detected in PM10 samples collected from July 2018 to June 2019 at a coastal site representative of the Central Mediterranean, is provided in this study. Viridiplantae and Fungi were the most abundant eukaryotic kingdoms. Streptophyta was the prevailing Viridiplantae phylum, whilst Ascomycota and Basidiomycota were the prevailing Fungi phyla. Brassica and Panicum were the most abundant Streptophyta genera in winter and summer, respectively, whereas Olea was the most abundant genus in spring and autumn. With regards to Fungi, Botrytis and Colletotrichum were the most abundant Ascomycota genera, reaching the highest abundance in spring and summer, respectively, while Cryptococcus and Ustilago were the most abundant Basidiomycota genera, and reached the highest abundance in winter and spring, respectively. The genus community structure in the PM10 samples varied day-by-day, and mainly along with the seasons. The impact of long-range transported air masses on the same structure was also proven. Nevertheless, rather few genera were significantly correlated with meteorological parameters and PM10 mass concentrations. The PCoA plots and non-parametric Spearman's rank-order correlation coefficients showed that the strongest correlations generally occurred between parameters reaching high abundances/values in the same season or PM10 sample. Moreover, the screening of potential pathogenic fungi allowed us to detect seven potential pathogenic genera in our PM10 samples. We also found that, with the exception of Panicum and Physcomitrella, all of the most abundant and pervasive identified Streptophyta genera could serve as potential sources of aeroallergens in the studied area.

Dataset Information

Seasonal variability in airborne biotic contaminants in swine confinement buildings.

Publications

Seasonal variability in airborne biotic contaminants in swine confinement buildings.

Similar Datasets

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