Airborne Bacteria in Outdoor Air and Air of Mechanically Ventilated Buildings at City Scale in Hong Kong across Seasons

Abundant Cyanobacteria in Autumn Adhering to the Heating, Ventilation, and Air-Conditioning (HVAC) in Shanghai

Cyanobacteria are ever-present, mainly flourishing in aquatic environments and surviving virtually in other habitats. The microbiota of indoor dust on the pre-filter of heating, ventilation, and air-conditioning (HVAC) systems, which reflect indoor microbial contamination and affect human health, has attracted attention. Contemporary studies on cyanobacteria deposited on the pre-filter of HVAC remain scant. By the culture-independent approach of qPCR and high throughput sequencing technologies, our results documented that the cyanobacterial concentrations were highest in autumn, occurred recurrently, and were about 2.60 and 10.57-fold higher than those in winter and summer. We proposed that aquatic and terrestrial cyanobacteria contributed to the pre-filter of HVAC by airborne transportation produced by wave breaks, bubble bursts, and soil surface by wind force, owing to the evidence that cyanobacteria were commonly detected in airborne particulate matters. The cyanobacteria community structure was characterized in Shanghai, where Chroococcidiopsaceae, norank_cyanobacteriales, Nostocaceae, Paraspirulinaceae, and others dominated the dust on the pre-filter of HVAC. Some detected genera, including Nodularia sp., Pseudanabaena sp., and Leptolyngbya sp., potentially produced cyanobacterial toxins, which need further studying to determine their potential threat to human health. The present work shed new insight into cyanobacteria distribution in the specific environment besides aquatic habitats.

Microfiber-loaded bacterial community in indoor fallout and air-conditioner filter dust

Microfibers (MFs) are widely existed in indoor air; however, characteristic of microbiota on MFs is largely unknown. In this study, air-borne MFs were collected from fallout or air-conditioner (AC) filter dust in three types of indoor space including living room, dormitory and office. Both plastic and natural MFs were identified by Fourier transform infrared spectroscopy. Ultramicroscopic observation showed dense biofilms adhering on surfaces of MFs. Fallout MFs contained more bacteria but fewer fungi than MFs from AC filter dust. MFs-loaded bacteria were of highest abundance in living rooms, following dormitories and offices. Bacterial community and its diversity were further analyzed by 16S rRNA High-throughput sequencing. Up to 4540 of bacterium OTUs were shared in these MFs samples, unique OTUs in fallout and AC filter samples accounting for 26.3 % and 25.7 % of the total. Compared to MFs fallout, AC filter MFs contained more species of pathogenic bacteria, such as Betaproteobacteriales and Ralstonia, with obviously different β-diversity between two groups. Phenotypic analysis showed that fallout and AC filter MFs bacteria presented high index values of film formation, oxidative stress tolerance and potential pathogenicity. Overall, these results suggest that abundant bacteria including pathogen can be loaded on MFs, and would pose health risks through delivery of indoor MFs.

A history of the MetaSUB consortium: Tracking urban microbes around the globe

The MetaSUB Consortium, founded in 2015, is a global consortium with an interdisciplinary team of clinicians, scientists, bioinformaticians, engineers, and designers, with members from more than 100 countries across the globe. This network has continually collected samples from urban and rural sites including subways and transit systems, sewage systems, hospitals, and other environmental sampling. These collections have been ongoing since 2015 and have continued when possible, even throughout the COVID-19 pandemic. The consortium has optimized their workflow for the collection, isolation, and sequencing of DNA and RNA collected from these various sites and processing them for metagenomics analysis, including the identification of SARS-CoV-2 and its variants. Here, the Consortium describes its foundations, and its ongoing work to expand on this network and to focus its scope on the mapping, annotation, and prediction of emerging pathogens, mapping microbial evolution and antibiotic resistance, and the discovery of novel organisms and biosynthetic gene clusters.

Airborne microbial community structure and potential pathogen identification across the PM size fractions and seasons in the urban atmosphere

As a vital component of airborne bioaerosols, bacteria and fungi seriously endanger human health as pathogens and allergens. However, comprehensive effects of environmental variables on airborne microbial community structures remain poorly understood across the PM sizes and seasons. We collected atmospheric PM_1.0, PM_2.5, and PM₁₀ samples in Hefei, a typical rapidly-developing city in East China, across three seasons, and performed a comprehensive analysis of airborne microbial community structures using qPCR and high-throughput sequencing. Overall the bacterial and fungal abundances in PM_1.0 were one to two orders of magnitude higher than those in PM_2.5 and PM₁₀ across seasons, but their α-diversity tended to increase from PM_1.0 to PM₁₀. The bacterial gene abundances showed a strong positive correlation (P < 0.05) with atmospheric SO₂ and NO₂ concentrations and air quality index. The bacterial gene abundances were significantly higher (P = 0.001) than fungi, and the bacterial diversity showed stronger seasonality. The PM sizes influenced distribution patterns for airborne microbial communities within the same season. Source-tracking analysis indicated that soils, plants, human and animal feces represented important sources of airborne bacteria with a total relative abundance of more than 60% in summer, but total abundance from the unidentified sources surpassed in fall and winter. Total 10 potential bacterial and 12 potential fungal pathogens were identified at the species level with the highest relative abundances in summer, and their abundances increased with the PM sizes. Together, our results indicated that a complex set of environmental factors, including water-soluble ions in PM, changes in air pollutant levels and meteorological conditions, and shifts in the relative importance of available microbial sources, acted to control the seasonal compositions of microbial communities in the urban atmosphere.

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

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.

Where environmental microbiome meets its host: subway and passenger microbiome relationships

Subways are urban transport systems with high capacity. Every day around the world, there are more than 150 million subway passengers. Since 2013, thousands of microbiome samples from various subways worldwide have been sequenced. Skin bacteria and environmental organisms dominate the subway microbiomes. The literature has revealed common bacterial groups in subway systems; even so, it is possible to identify cities by their microbiome. Low-frequency bacteria are responsible for specific bacterial fingerprints of each subway system. Furthermore, daily subway commuters leave their microbial clouds and interact with other passengers. Microbial exchange is quite fast; the hand microbiome changes within minutes, and after cleaning the handrails, the bacteria are re-established within minutes. To investigate new taxa and metabolic pathways of subway microbial communities, several high-quality metagenomic-assembled genomes (MAG) have been described. Subways are harsh environments unfavorable for microorganism growth. However, recent studies have observed a wide diversity of viable and metabolically active bacteria. Understanding which bacteria are living, dormant, or dead allows us to propose realistic ecological interactions. Questions regarding the relationship between humans and the subway microbiome, particularly the microbiome effects on personal and public health, remain unanswered. This review summarizes our knowledge of subway microbiomes and their relationship with passenger microbiomes.

Indoor microbiome, air pollutants and asthma, rhinitis and eczema in preschool children - A repeated cross-sectional study

BACKGROUND

Indoor microbiome exposure is associated with asthma, rhinitis and eczema. However, no studies report the interactions between environmental characteristics, indoor microbiome and health effects in a repeated cross-sectional framework.

METHODS

1,279 and 1,121 preschool children in an industrial city (Taiyuan) of China were assessed for asthma, rhinitis and eczema symptoms in 2012 and 2019 by self-administered questionnaires, respectively. Bacteria and fungi in classroom vacuum dust were characterized by culture-independent amplicon sequencing. Multi-level logistic/linear regression was performed in two cross-sectional and two combined models to assess the associations.

RESULTS

The number of observed species in bacterial and fungal communities in classrooms increased significantly from 2012 to 2019, and the compositions of the microbial communities were drastically changed (p < 0.001). The temporal microbiome variation was significantly larger than the spatial variation within the city (p < 0.001). Annual average outdoor SO₂ concentration decreased by 60.7%, whereas NO₂ and PM₁₀ concentrations increased by 63.3% and 40.0% from 2012 to 2019, which were both associated with indoor microbiome variation (PERMANOVA p < 0.001). The prevalence of asthma (2.0% to 3.3%, p = 0.06) and rhinitis (28.0% to 25.3%, p = 0.13) were not significantly changed, but the prevalence of eczema was increased (3.6% to 7.0%; p < 0.001). Aspergillus subversicolor, Collinsella and Cutibacterium were positively associated with asthma, rhinitis and eczema, respectively (p < 0.01). Prevotella, Lactobacillus iners and Dolosigranulum were protectively (negatively) associated with rhinitis (p < 0.01), consistent with previous studies in the human respiratory tract. NO₂ and PM₁₀ concentrations were negatively associated with rhinitis in a bivariate model, but a multivariate mediation analysis revealed that Prevotella fully mediated the health effects.

CONCLUSIONS

This is the first study to report the interactions between environmental characteristics, indoor microbiome and health in a repeated cross-sectional framework. The mediating effects of indoor microorganisms suggest incorporating biological with chemical exposure for a comprehensive exposure assessment.

The decay of airborne bacteria and fungi in a constant temperature and humidity test chamber

Despite substantial research to profile the microbial characteristics in the atmosphere, the changing metabolism underpinning microbial successional dynamics remains ambiguous. Herein, we applied qPCR, high-throughput sequencing of the genes encoding 16S and ITS rRNA to render the bacterial/fungal dynamics of ambient PM_2.5 filters maintained at constant conditions of temperature (20 ± 2 °C) and humidity (50 ± 5%). The incubation experiments which lasted for 50 days aim to simulate a metabolic process of microbe in two types PM_2.5 (polluted and non-polluted). The results show that microbial community species in polluted PM_2.5 had faster decay rates, more bacterial diversity and less fungal community compared to the non-polluted ones. For bacteria, the proportion of anaerobic species is higher than aerobic ones, and their performance of contain mobile elements, form-biofilms, and pathogenic risks declined rapidly as times went by. Whereas for fungi, saprotroph species occupied about 70% of the population, resulting in a specified peak of abundance due to the adequacy nutrients supplied by the apoptosis cells. Combining the classified microbial species, we found stable community structure and the volatile ones related to the various metabolic survival strategies during different time. Without the input of peripheral environment, the health risks of airborne microbe descend to a healthy level after 20 days, implying their biologic effectiveness was about 20 days no matter the air is polluted or not. This study provided new insights into the different metabolic survival of airborne microorganisms in ideal and stable conditions.

City-Scale Meta-Analysis of Indoor Airborne Microbiota Reveals that Taxonomic and Functional Compositions Vary with Building Types

Currently, there is a lack of understanding on the variations of the indoor airborne microbiotas of different building types within a city, and how operational taxonomic unit (OTU)- and amplicon sequence variant (ASV)-based analyses of the 16S rRNA gene sequences affect interpretation of the indoor airborne microbiota results. Therefore, in this study, the indoor airborne bacterial microbiotas between commercial buildings, residences, and subways within the same city were compared using both OTU- and ASV-based analytic methods. Our findings suggested that indoor airborne bacterial microbiota compositions were significantly different between building types regardless of the bioinformatics method used. The processes of ecological drift and random dispersal consistently played significant roles in the assembly of the indoor microbiota across building types. Abundant taxa tended to be more centralized in the correlation network of each building type, highlighting their importance. Taxonomic changes between the microbiotas of different building types were also linked to changes in their inferred metabolic function capabilities. Overall, the results imply that customized strategies are necessary to manage indoor airborne bacterial microbiotas for each building type or even within each specific building.

Seasonal Variation Characteristics of Bacteria and Fungi in PM2.5 in Typical Basin Cities of Xi’an and Linfen, China

Microorganisms existing in airborne fine particulate matter (PM2.5) have key implications in biogeochemical cycling and human health. In this study, PM2.5 samples, collected in the typical basin cities of Xi’an and Linfen, China, were analyzed through high-throughput sequencing to understand microbial seasonal variation characteristics and ecological functions. For bacteria, the highest richness and diversity were identified in autumn. The bacterial phyla were dominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. Metabolism was the most abundant pathway, with the highest relative abundance found in autumn. Pathogenic bacteria (Pseudomonas, Acinetobacter, Serratia, and Delftia) were positively correlated with most disease-related pathways. Besides, C cycling dominated in spring and summer, while N cycling dominated in autumn and winter. The relative abundance of S cycling was highest during winter in Linfen. For fungi, the highest richness was found in summer. Basidiomycota and Ascomycota mainly constituted the fungal phyla. Moreover, temperature (T) and sulfur dioxide (SO2) in Xi’an, and T, SO2, and nitrogen dioxide (NO2) in Linfen were the key factors affecting microbial community structures, which were associated with different pollution characteristics in Xi’an and Linfen. Overall, these results provide an important reference for the research into airborne microbial seasonal variations, along with their ecological functions and health impacts.

Profiling Airborne Microbiota in Mechanically Ventilated Buildings Across Seasons in Hong Kong Reveals Higher Metabolic Activity in Low-Abundance Bacteria

Metabolically active bacteria within built environments are poorly understood. This study aims to investigate the active airborne bacterial microbiota and compare the total and active microbiota in eight mechanically ventilated buildings over four consecutive seasons using the 16S rRNA gene (rDNA) and the 16S rRNA (rRNA), respectively. The relative abundances of the taxa of presumptive occupants and environmental origins were significantly different between the active and total microbiota. The Sloan neutral model suggested that ecological drift and random dispersal played a smaller role in the assembly of the active microbiota than the total microbiota. The seasonal nature of the active microbiota was consistent with that of the total microbiota in both indoor and outdoor environments, while only the indoor environment was significantly affected by geography. The relative abundances of the active and total taxa were positively correlated, suggesting that the high-abundance members were also the greatest contributors to the community-level metabolic activity. Based on the rRNA/rDNA ratio, the low-abundance members consistently had a higher taxon-level metabolic activity than the high-abundance members over seasons, suggesting that the low-abundance members may have the ability to survive and thrive in the indoor environment and their impact on the health of occupants cannot be overlooked.