Global Meta-analysis of Airborne Bacterial Communities and Associations with Anthropogenic Activities

Abstract

Airborne microbiome alterations, an emerging global health concern, have been linked to anthropogenic activities in numerous studies. However, these studies have not reached a consensus. To reveal general trends, we conducted a meta-analysis using 3226 air samples from 42 studies, including 29 samples of our own. We found that samples in anthropogenic activity-related categories showed increased microbial diversity, increased relative abundance of pathogens, increased co-occurrence network complexity, and decreased positive edge proportions in the network compared with the natural environment category. Most of the above conclusions were confirmed using the samples we collected in a particular period with restricted anthropogenic activities. Additionally, unlike most previous studies, we used 15 human-production process factors to quantitatively describe anthropogenic activities. We found that microbial richness was positively correlated with fine particulate matter concentration, NH₃ emissions, and agricultural land proportion and negatively correlated with the gross domestic product per capita. Airborne pathogens showed preferences for different factors, indicating potential health implications. SourceTracker analysis showed that the human body surface was a more likely source of airborne pathogens than other environments. Our results advance the understanding of relationships between anthropogenic activities and airborne bacteria and highlight the role of airborne pathogens in public health.

Keywords: NH3 emissions; PM2.5 concentration; airborne bacteria; anthropogenic activities; pathogens.

Figure 1

Airborne bacterial communities in the four categories. The Chao1 index (a) and Shannon index (b) of the four categories. Asterisks denote Wilcoxon rank-sum test results (ns: p > 0.05, *: p ≤ 0.05, **: p ≤ 0.01, and ****: p ≤ 0.0001). The Wilcoxon rank-sum test works well with unequal sample sizes. (c) Relative abundance of potential pathogens in the four categories. The co-occurrence network in the natural environment (d), human settlement (e), livestock farm (f), and WWTP (g) categories. Natural: The natural environment category; settlement: The human settlement category; livestock: The livestock farms category; WWTP: The wastewater treatment plant category. Red line: positive correlation and blue line: negative correlation.

Figure 2

Airborne bacterial communities in the APEC summit-related samples. The Chao1 index (a) and Shannon index (b) of the pre-APEC, during APEC, and post-APEC summit samples. The p-values of Wilcoxon rank-sum test results are shown above the boxes. (c) Relative abundance of potential pathogens in pre-APEC, during APEC, and post-APEC summit samples. The hub co-occurrence network in the pre-APEC (d), during APEC (e), and post-APEC (f) summit samples. Red line: positive correlation and gray line: negative correlation.

Figure 3

Relationship between airborne bacterial communities and factors. (a) Spearman’s correlation matrix of the microbial diversity (Chao1 index and Shannon index) is associated with different factors. Note: The correlations for the Shannon index are weak (correlation coefficient |r| < 0.3) but have the same trend as that of the Chao1 index. (b) Pairwise Spearman’s correlation matrix of pathogenic genera with factors. Pathogenic genera could be divided into four clusters according to their correlations with factors. Only associations with Spearman’s correlation coefficients |r| ≥ 0.3 and adjust p ≤ 0.05 were retained. Asterisks denote correlation test results (*: adjust p ≤ 0.05).