Spatial and seasonal variation of the airborne microbiome in a rapidly developing city of China

Li, Hu; Zhou, Xinyuan; Yang, Xiao-Ru; Zhu, Yong‐Guan; Hong, Youwei; Su, Jian‐Qiang

doi:10.1016/j.scitotenv.2019.01.367

Cited by 85 publications

(75 citation statements)

References 67 publications

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“…For instance, Li et al . 58 report seasonal differences in community structure of Aeolian communities sampled in China, whereas Park et al . 59 report no seasonal difference over Japan.…”

Section: Discussionmentioning

confidence: 99%

Functional metagenomic analysis of dust-associated microbiomes above the Red Sea

Aalismail

Ngugi

Díaz‐Rúa

et al. 2019

Sci Rep

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Atmospheric transport is a major vector for the long-range transport of microbial communities, maintaining connectivity among them and delivering functionally important microbes, such as pathogens. Though the taxonomic diversity of aeolian microorganisms is well characterized, the genomic functional traits underpinning their survival during atmospheric transport are poorly characterized. Here we use functional metagenomics of dust samples collected on the Global Dust Belt to initiate a Gene Catalogue of Aeolian Microbiome (GCAM) and explore microbial genetic traits enabling a successful aeolian lifestyle in Aeolian microbial communities. The GCAM reported here, derived from ten aeolian microbial metagenomes, includes a total of 2,370,956 non-redundant coding DNA sequences, corresponding to a yield of ~31 × 106 predicted genes per Tera base-pair of DNA sequenced for the aeolian samples sequenced. Two-thirds of the cataloged genes were assigned to bacteria, followed by eukaryotes (5.4%), archaea (1.1%), and viruses (0.69%). Genes encoding proteins involved in repairing UV-induced DNA damage and aerosolization of cells were ubiquitous across samples, and appear as fundamental requirements for the aeolian lifestyle, while genes coding for other important functions supporting the aeolian lifestyle (chemotaxis, aerotaxis, germination, thermal resistance, sporulation, and biofilm formation) varied among the communities sampled.

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“…For instance, Li et al . 58 report seasonal differences in community structure of Aeolian communities sampled in China, whereas Park et al . 59 report no seasonal difference over Japan.…”

Section: Discussionmentioning

confidence: 99%

Functional metagenomic analysis of dust-associated microbiomes above the Red Sea

Aalismail

Ngugi

Díaz‐Rúa

et al. 2019

Sci Rep

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“…Both studies are congruent with the results presented here; bacterial numbers increased from spring through summer and decrease towards winter. Several studies have observed seasonality in atmospheric microbiome composition [22–24]. With the outdoors being an important source for BE microbiomes [25], this suggests that seasonal variations in subway microbiomes may be influenced, at least partly, by seasonal changes in atmospheric microbial communities.…”

Section: Discussionmentioning

confidence: 99%

“…Seasonality is a time-dependent, fundamental shift in environmental conditions that is expected to vary greatly across geographical scales. It is well known that outdoor microbiomes show significant variation across seasons [22–24] and that outdoor air strongly contributes to indoor microbiome composition [25]. Hence, seasonal effects on BE microbiomes are to be expected.…”

Section: Introductionmentioning

confidence: 99%

The subway microbiome: seasonal dynamics and direct comparison of air and surface bacterial communities

et al. 2019

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BackgroundMass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats.MethodsWe performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses.ResultsThere were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature.ConclusionsThe results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world.

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“…For example, Lee, et al have analyzed airborne microbiota of 108 samples collected from Beijing, Seoul, and Nagasaki, and determined that Beijing had the most diverse bacterial community and was influenced by meteorological factors [ 13 ]. Other studies found that bacterial structure was associated with airborne particulate matter as well as spatial and seasonal variation [ 14 , 15 ]. However, the microbiota in occupational settings with animal exposure has never been investigated in China.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Associated Microbiota Between Pig Farm and Pig Slaughterhouse in Guangdong, China

Zhu

Guo

et al. 2020

Curr Microbiol

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The goal of this study was to compare the microbiota in different pig-present settings in China. Bioaerosol samples from pig farms and slaughterhouses and nasal samples from pig farmers and slaughterhouse workers were collected in Guangdong, southern China. The bacterial genomic DNA was isolated and subjected to 16S sequencing. The data were analyzed using QIIME2 with the DADA2 pipeline. A total of 14,923,551 clean reads and 2785 operational taxonomic units (OTUs) were obtained, which were mostly grouped into 4 phyla (Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria) and 220 families. The microbiota richness of nasal samples in pig-present workers was higher than that of bioaerosols collected in the vicinity of the pig enclosures. There were 31.7% (620/1954) shared OTUs between pig farm bioaerosols and pig farmers which was higher than that between pig slaughterhouses and slaughterhouse workers (23.4%, 364/1553) (p < 0.001). Acinetobacter and Pseudomonas were the most abundant in pig-present bioaerosols, and Staphylococcus, Pseudomonas, and Corynebacterium were dominant bacterial genus in pig farmers. The bacterial patterns are also specific to the location of sample collected. The results suggest that bioaerosol microbiota interact with human nasal microbes in the vicinity of the pig farm enclosures, providing the basis for further analysis of microbial transmission across hosts in pig-present settings.

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Spatial and seasonal variation of the airborne microbiome in a rapidly developing city of China

Cited by 85 publications

References 67 publications

Functional metagenomic analysis of dust-associated microbiomes above the Red Sea

Functional metagenomic analysis of dust-associated microbiomes above the Red Sea

The subway microbiome: seasonal dynamics and direct comparison of air and surface bacterial communities

A Comparative Study of Associated Microbiota Between Pig Farm and Pig Slaughterhouse in Guangdong, China

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