The Redundancy Discrimination Analysis (RDA) and Spearman correlation coefficients were used to investigate relationships between airborne bacteria at the phylum and genus level and chemical species in winter and spring PM10 samples over Southeastern Italy. The identification of main chemical species/pollution sources that were related to and likely affected the bacterial community structure was the main goal of this work. The 16S rRNA gene metabarcoding approach was used to characterize airborne bacteria. Seventeen phyla and seventy-nine genera contributing each by mean within-sample relative abundance percentage > 0.01% were identified in PM10 samples, which were chemically characterized for 33 species, including ions, metals, OC, and EC (organic and elemental carbon, respectively). Chemical species were associated with six different pollution sources. A shift from winter to spring in both bacterial community structure and chemical species mass concentrations/sources and the relationships between them was observed. RDA triplots pointed out significant correlations for all tested bacterial phyla (genera) with other phyla (genera) and/or with chemical species, in contrast to correlation coefficient results, which showed that few phyla (genera) were significantly correlated with chemical species. More specifically, in winter Bacillus and Chryseobacterium were the only genera significantly correlated with chemical species likely associated with particles from soil-dust and anthropogenic pollution source, respectively. In spring, Enterobacter and Sphingomonas were the only genera significantly correlated with chemical species likely associated with particles from the anthropogenic pollution and the marine and soil-dust sources, respectively. The results of this study also showed that the correlation coefficients were the best tool to obtain unequivocal identifications of the correlations of phyla (genera) with chemical species. The seasonal changes of the PM10 chemical composition, the microbial community structure, and their relationships suggested that the seasonal changes of atmospheric particles may have likely contributed to seasonal changes of bacterial community in the atmosphere.
Airborne bacteria structure and chemical composition relationships in winter and spring PM10 samples over southeastern Italy
Romano S.
;Lucarelli F.;Rispoli G.;Perrone M. R.
2020-01-01
Abstract
The Redundancy Discrimination Analysis (RDA) and Spearman correlation coefficients were used to investigate relationships between airborne bacteria at the phylum and genus level and chemical species in winter and spring PM10 samples over Southeastern Italy. The identification of main chemical species/pollution sources that were related to and likely affected the bacterial community structure was the main goal of this work. The 16S rRNA gene metabarcoding approach was used to characterize airborne bacteria. Seventeen phyla and seventy-nine genera contributing each by mean within-sample relative abundance percentage > 0.01% were identified in PM10 samples, which were chemically characterized for 33 species, including ions, metals, OC, and EC (organic and elemental carbon, respectively). Chemical species were associated with six different pollution sources. A shift from winter to spring in both bacterial community structure and chemical species mass concentrations/sources and the relationships between them was observed. RDA triplots pointed out significant correlations for all tested bacterial phyla (genera) with other phyla (genera) and/or with chemical species, in contrast to correlation coefficient results, which showed that few phyla (genera) were significantly correlated with chemical species. More specifically, in winter Bacillus and Chryseobacterium were the only genera significantly correlated with chemical species likely associated with particles from soil-dust and anthropogenic pollution source, respectively. In spring, Enterobacter and Sphingomonas were the only genera significantly correlated with chemical species likely associated with particles from the anthropogenic pollution and the marine and soil-dust sources, respectively. The results of this study also showed that the correlation coefficients were the best tool to obtain unequivocal identifications of the correlations of phyla (genera) with chemical species. The seasonal changes of the PM10 chemical composition, the microbial community structure, and their relationships suggested that the seasonal changes of atmospheric particles may have likely contributed to seasonal changes of bacterial community in the atmosphere.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
