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

Insight into the microbial community of denitrification process using different solid carbon sources: Not only bacteria

There is a lack of understanding about the bacterial, fungal and archaeal communities' composition of solid-phase denitrification (SPD) systems. We investigated four SPD systems with different carbon sources by analyzing microbial gene sequences based on operational taxonomic unit (OTU) and amplicon sequence variant (ASV). The results showed that the corncob-polyvinyl alcohol sodium alginate-polycaprolactone (CPSP, 0.86±0.04 mg NO3--N/(g·day)) and corncob (0.85±0.06 mg NO3--N/(g·day)) had better denitrification efficiency than polycaprolactone (PCL, 0.29±0.11 mg NO3--N/(g·day)) and polyvinyl alcohol-sodium alginate (PVA-SA, 0.24±0.07 mg NO3--N/(g·day)). The bacterial, fungal and archaeal microbial composition was significantly different among carbon source types such as Proteobacteria in PCL (OTU: 83.72%, ASV: 82.49%) and Rozellomycota in PVA-SA (OTU: 71.99%, ASV: 81.30%). ASV methods can read more microbial units than that of OTU and exhibit higher alpha diversity and classify some species that had not been identified by OTU such as Nanoarchaeota phylum, unclassified_ f_ Xanthobacteraceae genus, etc., indicating ASV may be more conducive to understand SPD microbial communities. The co-occurring network showed some correlation between the bacteria fungi and archaea species, indicating different species may collaborate in SPD systems. Similar KEGG function prediction results were obtained in two bioinformatic methods generally and some fungi and archaea functions should not be ignored in SPD systems. These results may be beneficial for understanding microbial communities in SPD systems.

Impact of climate zones and seasons on indoor airborne microbial communities: Insights from a comprehensive analysis

Bacteria and fungi are ubiquitous throughout built environments and are suspended in the air, potentially affecting human health. However, the impacts of climate zones on the diversity, structure, and stochastic assembly of indoor airborne microbes remain unknown. This study comprehensively analyzed indoor airborne microbes across five climate zones in China during the summer and winter using high-throughput sequencing. The diversity and structure of indoor airborne communities vary across climatic zones. A random forest model was used to identify biomarkers in different climate zones. The results showed no relationship between the biomarkers and their rankings in mean relative abundance. The Sloan neutral model fitting results indicated that the impact of climate zones on the stochastic process in the assembly of indoor airborne microbes was considerably more important than that of seasons. Additionally, the influence of seasons on the diversity, structure, and stochastic assembly process of indoor airborne microbes differed among different climate zones. The diversity, structure, and stochastic assembly processes of bacteria present distinctive outcomes in climate zones and seasons compared with those of fungi. Overall, these findings indicate that customized strategies are necessary to manage indoor airborne microbial communities in each climate zone, season, and for specific microbial species.

Screening of hazardous groundwater pollutants responsible for microbial ecological consequences by integrated nontargeted analysis and high-throughput sequencing technologies

Organic contaminants, especially hydrophobic organic contaminants (HOCs), pose potential ecological threats even at environmental concentrations. Characterization of HOC profiles and identification of key environmental stressors are vital but still challenging in groundwater quality management. In this study, a strategy for identifying the key environmental stressors among HOCs in groundwater based on integrated chemical monitoring technologies and microbial ecology analysis methods was proposed and applied to typical groundwater samples. Specifically, the characteristics of HOCs were systematically analyzed based on nontargeted and targeted approaches, and microbial community assembly and specific biomarker analysis were combined to determine the major ecological processes and key environmental stressors. The results showed that a total of 234 HOCs were detected in groundwater collected from Tongzhou, Beijing; among them, phthalate esters (PAEs) were screened out as key environmental stressors, considering that they made relatively higher microbial ecology contributions. Furthermore, their influences on the structure and function of the groundwater microbial community were evaluated by adopting high-throughput sequencing and bioinformatics analysis technologies. These findings confirmed PAEs as vital determinants driving microbial assembly, shifting community structure, and regulating community function in groundwater; in addition, the findings validated the feasibility and suitability of the proposed strategy.

Efficiency and sensitivity optimization of a protocol to quantify indoor airborne SARS-CoV-2 levels

Background

Development of methodologies to quantify airborne micro-organisms is needed for the prevention and control of infections. It is difficult to conclude which is the most efficient and sensitive strategy to assess airborne SARS-CoV-2 RNA levels due to the disparity of results reported in clinical settings.

Aim

To improve our previously reported protocol of measuring SARS-CoV-2 RNA levels, which was based on bioaerosol collection with a liquid impinger and RNA quantification with droplet digital polymerase chain reaction (ddPCR).

Methods

Air samples were collected in COVID-19 patient rooms to assess efficiency and/or sensitivity of different air samplers, liquid collection media, and reverse transcriptases (RT).

Findings

Mineral oil retains airborne RNA better than does hydrophilic media without impairing integrity. SARS-CoV-2 ORF1ab target was detected in 80% of the air samples using BioSampler with mineral oil. No significant differences in effectiveness were obtained with MD8 sampler equipped with gelatine membrane filters, but the SARS-CoV-2 copies/m³ air obtained with the latter were lower (28.4 ± 6.1 vs 9 ± 1.7). SuperScript II RT allows the detection of a single SARS-CoV-2 genome RNA molecule by ddPCR with high efficiency. This was the only RT that allowed the detection of SARS-CoV-2 N1 target in air samples.

Conclusion

The collection efficiency and detection sensivity of a protocol to quantify SARS-CoV-2 RNA levels in indoor air has been improved in the present study. Such optimization is important to improve our understanding of the microbiological safety of indoor air.