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

Indoor/Outdoor airborne microbiome characteristics in residential areas across four seasons and its indoor purification

Bioaerosols are more likely to accumulate in the residential environment, and long-term inhalation may lead to a variety of diseases and allergies. Here, we studied the distribution, influencing factors and diffusion characteristics of indoor and outdoor microbiota pollution in six residential buildings in Guangzhou, southern China over a period of one year. The results showed that the particle sizes of bioaerosol were mainly in the range of inhalable particle size (<4.7 μm) with a small difference among four seasons (74.61 % ± 2.17 %). The microbial communities showed obvious seasonal differences with high abundance in summer, but no obvious geographical differences. Among them, the bacteria were more abundant than the fungi. The dominant microbes in indoor and outdoor environments were similar, with Anoxybacillu, Brevibacillus and Acinetobacter as the dominant bacteria, and Cladosporium, Penicillium and Alternaria as the dominant fungi. The airborne microbiomes were more sensitive to temperature and particulate matter (PM2.5, PM10) concentrations. Based on the Sloan neutral model, bacteria were more prone to random diffusion than fungi, and the airborne microbiome can be randomly distributed in indoor and outdoor environments and between the two environments in each season. Bioaerosol in indoor was mainly from outdoor. The health risk evaluation showed that the indoor inhalation risks were higher than those outdoor. The air purifier had a better removal efficiency on 1.1-4.7 μm microorganisms, and the removal efficiency on Gram-negative bacteria was better than that on Gram-positive bacteria. This study is of great significance for the risk assessment and control of residential indoor bioaerosol exposure.

Development of sequencing-based methodologies to distinguish viable from non-viable cells in a bovine milk matrix: A pilot study

Although high-throughput DNA sequencing-based methods have been of great value for determining the composition of microbial communities in various environments, there is the potential for inaccuracies arising from the sequencing of DNA from dead microorganisms. In this pilot study, we compared different sequencing-based methods to assess their relative accuracy with respect to distinguishing between viable and non-viable cells, using a live and heat-inactivated model community spiked into bovine milk. The methods used were shotgun metagenomics with and without propidium monoazide (PMA) treatment, RNA-based 16S rRNA sequencing and metatranscriptomics. The results showed that methods were generally accurate, though significant differences were found depending on the library types and sequencing technologies. Different molecular targets were the basis for variations in the results generated using different library types, while differences in the derived composition data from Oxford Nanopore Technologies-and Illumina-based sequencing likely reflect a combination of different sequencing depths, error rates and bioinformatics pipelines. Although PMA was successfully applied in this study, further optimisation is required before it can be applied in a more universal context for complex microbiomes. Overall, these methods show promise and represent another important step towards the ultimate establishment of approaches that can be applied to accurately identify live microorganisms in milk and other food niches.

Sequencing introduced false positive rare taxa lead to biased microbial community diversity, assembly, and interaction interpretation in amplicon studies

BACKGROUND

Increasing studies have demonstrated potential disproportionate functional and ecological contributions of rare taxa in a microbial community. However, the study of the microbial rare biosphere is hampered by their inherent scarcity and the deficiency of currently available techniques. Sample-wise cross contaminations might be introduced by sample index misassignment in the most widely used metabarcoding amplicon sequencing approach. Although downstream bioinformatic quality control and clustering or denoising algorithms could remove sequencing errors and non-biological artifact reads, no algorithm could eliminate high quality reads from sample-wise cross contaminations introduced by index misassignment, making it difficult to distinguish between bona fide rare taxa and potential false positives in metabarcoding studies.

RESULTS

We thoroughly evaluated the rate of index misassignment of the widely used NovaSeq 6000 and DNBSEQ-G400 sequencing platforms using both commercial and customized mock communities, and observed significant lower (0.08% vs. 5.68%) fraction of potential false positive reads for DNBSEQ-G400 as compared to NovaSeq 6000. Significant batch effects could be caused by stochastically introduced false positive or false negative rare taxa. These false detections could also lead to inflated alpha diversity of relatively simple microbial communities and underestimated that of complex ones. Further test using a set of cow rumen samples reported differential rare taxa by different sequencing platforms. Correlation analysis of the rare taxa detected by each sequencing platform demonstrated that the rare taxa identified by DNBSEQ-G400 platform had a much higher possibility to be correlated with the physiochemical properties of rumen fluid as compared to NovaSeq 6000 platform. Community assembly mechanism and microbial network correlation analysis indicated that false positive or negative rare taxa detection could lead to biased community assembly mechanism and identification of fake keystone species of the community.

CONCLUSIONS

We highly suggest proper positive/negative/blank controls, technical replicate settings, and proper sequencing platform selection in future amplicon studies, especially when the microbial rare biosphere would be focused.

Responses of Cyanobacterial Crusts and Microbial Communities to Extreme Environments of the Stratosphere

How microbial communities respond to extreme conditions in the stratosphere remains unclear. To test this effect, cyanobacterial crusts collected from Tengger Desert were mounted to high balloons and briefly exposed (140 min) to high UV irradiation and low temperature in the stratosphere at an altitude of 32 km. Freezing and thawing treatments were simulated in the laboratory in terms of the temperature fluctuations during flight. Microbial community composition was characterized by sequencing at the level of DNA and RNA. After exposure to the stratosphere, the RNA relative abundances of Kallotenue and Longimicrobium increased by about 2-fold, while those of several dominant cyanobacteria genera changed slightly. The RNA relative abundances of various taxa declined after freezing, but increased after thawing, whereas cyanobacteria exhibited an opposite change trend. The DNA and RNA relative abundances of Nitrososphaeraceae were increased by 1.4~2.3-fold after exposure to the stratosphere or freezing. Exposure to stratospheric environmental conditions had little impact on the total antioxidant capacity, photosynthetic pigment content, and photosynthetic rate, but significantly increased the content of exopolysaccharides by 16%. The three treatments (stratospheric exposure, freezing, and thawing) increased significantly the activities of N-acetyl-β-D-glucosidase (26~30%) and β-glucosidase (14~126%). Our results indicated cyanobacterial crust communities can tolerate exposure to the stratosphere. In the defense process, extracellular organic carbon degradation and transformation play an important role. This study makes the first attempt to explore the response of microbial communities of cyanobacterial crusts to a Mars-like stratospheric extreme environment, which provides a new perspective for studying the space biology of earth communities.

Insights into the Profile of the Human Expiratory Microbiota and Its Associations with Indoor Microbiotas

Microorganisms residing in the human respiratory tract can be exhaled, and they constitute a part of environmental microbiotas. However, the expiratory microbiota community and its associations with environmental microbiotas remain poorly understood. Here, expiratory bacteria and fungi and the corresponding microbiotas from the living environments were characterized by DNA amplicon sequencing of residents' exhaled breath condensate (EBC) and environmental samples collected from 14 residences in Nanjing, China. The microbiotas of EBC samples, with a substantial heterogeneity, were found to be as diverse as those of skin, floor dust, and airborne microbiotas. Model fitting results demonstrated the role of stochastic processes in the assembly of the expiratory microbiota. Using a fast expectation-maximization algorithm, microbial community analysis revealed that expiratory microbiotas were differentially associated with other types of microbiotas in a type-dependent and residence-specific manner. Importantly, the expiratory bacteria showed a composition similarity with airborne bacteria in the bathroom and kitchen environments with an average of 12.60%, while the expiratory fungi showed a 53.99% composition similarity with the floor dust fungi. These differential patterns indicate different relationships between expiratory microbiotas and the airborne microbiotas and floor dust microbiotas. The results here illustrated for the first time the associations between expiratory microbiotas and indoor microbiotas, showing a potential microbial exchange between the respiratory tract and indoor environment. Thus, improved hygiene and ventilation practices can be implemented to optimize the indoor microbial exposome, especially in indoor bathrooms and kitchens.

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.

16S rRNA metabarcoding unearths responses of rare gut microbiome of fathead minnows exposed to benzo[a]pyrene

Activities of gut microbiomes are often overlooked in assessments of ecotoxicological effects of environmental contaminants. Effects of the polycyclic aromatic hydrocarbon, benzo[a]pyrene (BaP) on active gut microbiomes of juvenile fathead minnows (Pimephales promelas) were investigated. Fish were exposed for two weeks, to concentrations of 0, 1, 10, 100, or 1000 μg BaP g^-1 in the diet. The active gut microbiome was characterized using 16S rRNA metabarcoding to determine its response to dietary exposure of BaP. BaP reduced alpha-diversity at the greatest exposure concentrations. Additionally, exposure to BaP altered community composition of active microbiome and resulted in differential proportion of taxa associated with hydrocarbon degradation and fish health. Neighborhood selection networks of active microbiomes were not reduced with greater concentrations of BaP, which suggests ecological resistance and/or resilience of gut microbiota. The active gut microbiome had a similar overall biodiversity as that of the genomic gut microbiota, but had a distinct composition from that of the 16S rDNA profile. Responses of alpha- and beta-diversities of the active microbiome to BaP exposure were consistent with that of genomic microbiomes. Normalized activity of microbiome via the ratio of rRNA to rDNA abundance revealed rare taxa that became active or dormant due to exposure to BaP. These differences highlight the need to assess both 16S rDNA and rRNA metabarcoding to fully derive bacterial compositional changes resulting from exposure to contaminants.

RNA metabarcoding helps reveal zooplankton community response to environmental stressors

DNA metabarcoding can provide a high-throughput and rapid method for characterizing responses of communities to environmental stressors. However, within bulk samples, DNA metabarcoding hardly distinguishes live from the dead organisms. Here, both DNA and RNA metabarcoding were applied and compared in experimental freshwater mesocosms conducted for assessment of ecotoxicological responses of zooplankton communities to remediation treatment until 38 days post oil-spill. Furthermore, a novel indicator of normalized vitality (NV), sequence counts of RNA metabarcoding normalized by that of DNA metabarcoding, was developed for assessment of ecological responses. DNA and RNA metabarcoding detected similar taxa richness and rank of relative abundances. Both DNA and RNA metabarcoding demonstrated slight shifts in measured α-diversities in response to treatments. NV presented relatively greater magnitudes of differential responses of community compositions to treatments compared to DNA or RNA metabarcoding. NV declined from the start of the experiment (3 days pre-spill) to the end (38 days post-spill). NV also differed between Rotifer and Arthropoda, possibly due to differential life histories and sizes of organisms. NV could be a useful indicator for characterizing ecological responses to anthropogenic influence; however, the biology of target organisms and subsequent RNA production need to be considered.

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.

Understanding Microbial Arsenic-Mobilization in Multiple Aquifers: Insight from DNA and RNA Analyses

Biogeochemical processes critically control the groundwater arsenic (As) enrichment; however, the key active As-mobilizing biogeochemical processes and associated microbes in high dissolved As and sulfate aquifers are poorly understood. To address this issue, the groundwater-sediment geochemistry, total and active microbial communities, and their potential functions in the groundwater-sediment microbiota from the western Hetao basin were determined using 16S rRNA gene (rDNA) and associated 16S rRNA (rRNA) sequencing. The relative abundances of either sediment or groundwater total and active microbial communities were positively correlated. Interestingly, groundwater active microbial communities were mainly associated with ammonium and sulfide, while sediment active communities were highly related to water-extractable nitrate. Both sediment-sourced and groundwater-sourced active microorganisms (rRNA/rDNA ratios > 1) noted Fe(III)-reducers (induced by ammonium oxidation) and As(V)-reducers, emphasizing the As mobilization via Fe(III) and/or As(V) reduction. Moreover, active cryptic sulfur cycling between groundwater and sediments was implicated in affecting As mobilization. Sediment-sourced active microorganisms were potentially involved in anaerobic pyrite oxidation (driven by denitrification), while groundwater-sourced organisms were associated with sulfur disproportionation and sulfate reduction. This study provides an extended whole-picture concept model of active As-N-S-Fe biogeochemical processes affecting As mobilization in high dissolved As and sulfate aquifers.