Third generation sequencing reveals spatial variation of microbial composition of airborne bacteria in intensive dairy farm

Qianqian Zhang^1*Luyu Ding^2*Xueying Xie¹Lin Ru²Qifeng Li²Chunxia Yao²Ruixiang Jiang²Johann Sölkner³

• ¹School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China
• ²Beijing Academy of Agriculture and Forestry Sciences Information Technology Research Center, Beijing, China
• ³Universitat fur Bodenkultur Wien, Vienna, Austria

The intensification of livestock farming has led to increased bacterial bioaerosol emissions, posing potential health risks to both animals and humans. This study aimed to investigate the bacterial community composition, abundance, diversity, and variation in different functional zones of cattle farms to assess their impact on public health and environmental quality. We employed the third generation sequencing in Pacbio platform to sequence16S rRNA sequences to analyze air samples, identifying a diverse range of bacterial phyla, including Proteobacteria, Firmicutes, Verrucomicrobia, Bacteroidetes, Fusobacteria, Actinobacteria, Deinococcus-Thermus, Cyanobacteria, and Acidobacteria. The phylogenetic tree was built using the microbiome abundance of these samples. Notably, Firmicutes and Proteobacteria were predominantly enriched in the samples, with genera such as Staphylococcus, Acinetobacter, Enterococcus, and Bacillus and family of unknow Enterobacteriaceae being particularly abundant. These bacteria are known to be associated with various infections and chronic diseases. Correlation and canonical correspondence analysis (CCA) revealed that environmental factors, particularly ultraviolet radiation (UV) and global horizontal irradiance (GHI), significantly influence microbial species distribution with R2 of 0.774 (P<0.05) and 0.769 (P<0.05). We further calculated the alpha and beta diversity of microbiome in these samples and observed that fermenting manure (F1), fresh manure (X2) and piled-up manure after fermentation (D3) samples have the highest alpha diversity, while PC1 from beta diversity i.e. weighted Principal Coordinates Analysis (PCoA) explained 32.66% of the variance in the data. Interestingly, it was observed that the relative abundance of Kocuria genus is significantly different between groups waste management area (FW) and the milking parlor (NT) (t-test, p<0.013). Our findings underscore the importance of understanding the complex microbial ecosystems in livestock farming environments and highlight the need for targeted interventions to mitigate the public health risks associated with bacterial bioaerosols.