Temporal Dynamics of Air Bacterial Communities in a University Health Centre Using Illumina MiSeq Sequencing
01 Jan 2020-Aerosol and Air Quality Research (Taiwan Association for Aerosol Research)-Vol. 20, Iss: 5, pp 966-980
TL;DR: Routine air monitoring and microbiological survey is essential for air quality standards and potential human pathogens detection in health care settings and it is the first report from India to uncover the temporal dynamics of air bacterial communities in UHC using Illumina MiSeq (PE300) sequencing and Quantitative Insights into Microbial Ecology (QIIME).
Abstract: Bacterial contamination of air may have human health implications by the transmission of potential human pathogens. Therefore, assessment of air bacterial abundance and composition in different built environment is essential. Jawaharlal Nehru University health centre (UHC) is a primary healthcare setting providing need-based medication to university students. Using active air sampling method, we collected eight air samples from the indoor and outdoor area of UHC across four different seasons. The total genomic DNA was extracted from the air samples and subjected to 16S rRNA gene-based next-generation sequencing. We performed the taxonomic classification along with comparative analysis of air bacterial communities. This study revealed that Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes are the dominant phyla in the sampled air. Overall, the air bacterial composition in our studied samples was comparatively simple; only ten taxonomic families accounting for ~75% of the total sequences determined. We also observed ESKAPE pathogens in the air metagenomes in a low percentage (4.42%), which were dominated by Pseudomonas, Acinetobacter and Staphylococcus. Proteobacteria, Actinobacteria and Firmicutes showed significant correlation with PM2.5. We suggest that routine air monitoring and microbiological survey is essential for air quality standards and potential human pathogens detection in health care settings. It is the first report from India to uncover the temporal dynamics of air bacterial communities in UHC using Illumina MiSeq (PE300) sequencing and Quantitative Insights into Microbial Ecology (QIIME).
Citations
More filters
TL;DR: In this paper, the authors investigated the effects of multiple factors including landscapes, plant, soil, and anthropogenic factors on airborne microbial communities, especially bacterial and fungal pathogens, and provided insights into the importance of green space for providing health benefits for city dwellers by reducing pathogens in air, as well as supporting the inclusion of plant species in the management of urban green space to reduce exposure risk of airborne pathogens.
14 citations
TL;DR: In this article , the authors identify the recent trends of research on the topic through a systematic literature review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology.
Abstract: The adequate assessment and management of indoor air quality in healthcare facilities is of utmost importance for patient safety and occupational health purposes. This study aims to identify the recent trends of research on the topic through a systematic literature review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. A total of 171 articles published in the period 2015–2020 were selected and analyzed. Results show that there is a worldwide growing research interest in this subject, dispersed in a wide variety of scientific journals. A textometric analysis using the IRaMuTeQ software revealed four clusters of topics in the sampled articles: physicochemical pollutants, design and management of infrastructures, environmental control measures, and microbiological contamination. The studies focus mainly on hospital facilities, but there is also research interest in primary care centers and dental clinics. The majority of the analyzed articles (85%) report experimental data, with the most frequently measured parameters being related to environmental quality (temperature and relative humidity), microbiological load, CO2 and particulate matter. Non-compliance with the WHO guidelines for indoor air quality is frequently reported. This study provides an overview of the recent literature on this topic, identifying promising lines of research to improve indoor air quality in healthcare facilities.
7 citations
Peer Review•
TL;DR: An overview of the recent literature on this topic is provided, identifying promising lines of research to improve indoor air quality in healthcare facilities, and there is a worldwide growing research interest in this subject.
Abstract: : The adequate assessment and management of indoor air quality in healthcare facilities is of utmost importance for patient safety and occupational health purposes. This study aims to identify the recent trends of research on the topic through a systematic literature review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. A total of 171 articles published in the period 2015–2020 were selected and analyzed. Results show that there is a worldwide growing research interest in this subject, dispersed in a wide variety of scientific journals. A textometric analysis using the IRaMuTeQ software revealed four clusters of topics in the sampled articles: physicochemical pollutants, design and management of infrastructures, environmental control measures, and microbiological contamination. The studies focus mainly on hospital facilities, but there is also research interest in primary care centers and dental clinics. The majority of the analyzed articles (85%) report experimental data, with the most frequently measured parameters being related to environmental quality (temperature and relative humidity), microbiological load, CO 2 and particulate matter. Non-compliance with the WHO guidelines for indoor air quality is frequently reported. This study provides an overview of the recent literature on this topic, identifying promising lines of research to improve indoor air quality in healthcare facilities.
7 citations
TL;DR: Wang et al. as mentioned in this paper analyzed 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.
Abstract: 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.
6 citations
TL;DR: A baseline of the bacterial and fungal population of two major hospitals in Kuwait dealing with COVID patients, and in a non-hospital setting through targeted amplicon sequencing, highlights the need for regular surveillance of indoor hospital environments to prevent future outbreaks.
Abstract: The airborne transmission of COVID-19 has drawn immense attention to bioaerosols. The topic is highly relevant in the indoor hospital environment where vulnerable patients are treated and healthcare workers are exposed to various pathogenic and non-pathogenic microbes. Knowledge of the microbial communities in such settings will enable precautionary measures to prevent any hospital-mediated outbreak and better assess occupational exposure of the healthcare workers. This study presents a baseline of the bacterial and fungal population of two major hospitals in Kuwait dealing with COVID patients, and in a non-hospital setting through targeted amplicon sequencing. The predominant bacteria of bioaerosols were Variovorax (9.44%), Parvibaculum (8.27%), Pseudonocardia (8.04%), Taonella (5.74%), Arthrospira (4.58%), Comamonas (3.84%), Methylibium (3.13%), Sphingobium (4.46%), Zoogloea (2.20%), and Sphingopyxis (2.56%). ESKAPEE pathogens, such as Pseudomonas, Acinetobacter, Staphylococcus, Enterococcus, and Escherichia, were also found in lower abundances. The fungi were represented by Wilcoxinia rehmii (64.38%), Aspergillus ruber (9.11%), Penicillium desertorum (3.89%), Leptobacillium leptobactrum (3.20%), Humicola grisea (2.99%), Ganoderma sichuanense (1.42%), Malassezia restricta (0.74%), Heterophoma sylvatica (0.49%), Fusarium proliferatum (0.46%), and Saccharomyces cerevisiae (0.23%). Some common and unique operational taxonomic units (OTUs) of bacteria and fungi were also recorded at each site; this inter-site variability shows that exhaled air can be a source of this variation. The alpha-diversity indices suggested variance in species richness and abundance in hospitals than in non-hospital sites. The community structure of bacteria varied spatially (ANOSIM r2 = 0.181–0.243; p < 0.05) between the hospital and non-hospital sites, whereas fungi were more or less homogenous. Key taxa specific to the hospitals were Defluvicoccales, fungi, Ganodermataceae, Heterophoma, and H. sylvatica compared to Actinobacteria, Leptobacillium, L. leptobacillium, and Cordycipitaceae at the non-hospital site (LefSe, FDR q ≤ 0.05). The hospital/non-hospital MD index > 1 indicated shifts in the microbial communities of indoor air in hospitals. These findings highlight the need for regular surveillance of indoor hospital environments to prevent future outbreaks.
4 citations
References
More filters
TL;DR: Timmomatic is developed as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data and is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.
Abstract: Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.
Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.
Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic
Contact: ed.nehcaa-htwr.1oib@ledasu
Supplementary information: Supplementary data are available at Bioinformatics online.
39,291 citations
Additional excerpts
...38 (Bolger et al., 2014) and FLASH (v1....
[...]
TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.
28,911 citations
TL;DR: The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% correct bases commonly reported by other methods.
Abstract: Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
11,329 citations
"Temporal Dynamics of Air Bacterial ..." refers methods in this paper
...The merged sequences after removing adapter sequences, ambiguous reads and low-quality sequences were defined as ‘trimmed sequences’, which were filtered out the chimaeras using the UPARSE (Edgar, 2013)....
[...]
TL;DR: FLASH is a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short and when FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds.
Abstract: Motivation: Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome.
Results: We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds.
Availability and Implementation: The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash.
Contact: moc.liamg@cogam.t
9,827 citations
TL;DR: The results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
Abstract: We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
6,679 citations
"Temporal Dynamics of Air Bacterial ..." refers methods in this paper
...py was used to calculate the beta diversity to compare the different bacterial communities, which could be illustrated as the PCoA plots using weighted UniFrac diversity metrics (Lozupone and Knight, 2005)....
[...]
...The QIIME script beta_diversity_through_ plots.py was used to calculate the beta diversity to compare the different bacterial communities, which could be illustrated as the PCoA plots using weighted UniFrac diversity metrics (Lozupone and Knight, 2005)....
[...]