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      Performance evaluation of high-volume electret filter air samplers in aerosol microbiome research

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          Abstract

          Background

          Reliable identification and quantification of bioaerosols is fundamental in aerosol microbiome research, highlighting the importance of using sampling equipment with well-defined performance characteristics. Following advances in sequencing technology, shotgun metagenomic sequencing (SMS) of environmental samples is now possible. However, SMS of air samples is challenging due to low biomass, but with the use of high-volume air samplers sufficient DNA yields can be obtained. Here we investigate the sampling performance and comparability of two hand-portable, battery-operated, high-volume electret filter air samplers, SASS 3100 and ACD-200 Bobcat, previously used in SMS-based aerosol microbiome research.

          Results

          SASS and Bobcat consistently delivered end-to-end sampling efficiencies > 80% during the aerosol chamber evaluation, demonstrating both as effective high-volume air samplers capable of retaining quantitative associations. Filter recovery efficiencies were investigated with manual and sampler-specific semi-automated extraction procedures. Bobcat semi-automated extraction showed reduced efficiency compared to manual extraction. Bobcat tended towards higher sampling efficiencies compared to SASS when combined with manual extraction. To evaluate real-world sampling performance, side-by-side SASS and Bobcat sampling was done in a semi-suburban outdoor environment and subway stations. SMS-based microbiome profiles revealed that highly abundant bacterial species had similar representation across samplers. While alpha diversity did not vary for the two samplers, beta diversity analyses showed significant within-pair variation in subway samples. Certain species were found to be captured only by one of the two samplers, particularly in subway samples.

          Conclusions

          SASS and Bobcat were both found capable of collecting sufficient aerosol biomass amounts for SMS, even at sampling times down to 30 min. Bobcat semi-automated filter extraction was shown to be less effective than manual filter extraction. For the most abundant species the samplers were comparable, but systematic sampler-specific differences were observed at species level. This suggests that studies conducted with these highly similar air samplers can be compared in a meaningful way, but it would not be recommended to combine samples from the two samplers in joint analyses. The outcome of this work contributes to improved selection of sampling equipment for use in SMS-based aerosol microbiome research and highlights the importance of acknowledging bias introduced by sampling equipment and sample recovery procedures.

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          Most cited references41

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          Cutadapt removes adapter sequences from high-throughput sequencing reads

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            Structure, Function and Diversity of the Healthy Human Microbiome

            Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin, and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics, and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analyzed the largest cohort and set of distinct, clinically relevant body habitats to date. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families, and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology, and translational applications of the human microbiome.
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              Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations

              Next-generation sequencing approaches in microbiome research have allowed surveys of microbial communities, their genomes, and their functions with higher sensitivity than ever before. However, this sensitivity is a double-edged sword because these tools also efficiently detect contaminant DNA and cross-contamination, which can confound the interpretation of microbiome data. Therefore, there is an urgent need to integrate key controls into microbiome research to improve the integrity of microbiome studies. Here, we review how contaminant DNA and cross-contamination arise within microbiome studies and discuss their negative impacts, especially during the analysis of low microbial biomass samples. We then identify several key measures that researchers can implement to reduce the impact of contaminant DNA and cross-contamination during microbiome research. We put forward a set of minimal experimental criteria, the 'RIDE' checklist, to improve the validity of future low microbial biomass research.
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                Author and article information

                Contributors
                marius.dybwad@ffi.no
                Journal
                Environ Microbiome
                Environ Microbiome
                Environmental Microbiome
                BioMed Central (London )
                2524-6372
                28 July 2020
                28 July 2020
                2020
                : 15
                : 14
                Affiliations
                [1 ]GRID grid.450834.e, ISNI 0000 0004 0608 1788, Norwegian Defence Research Establishment FFI, ; P O Box 25, NO-2027 Kjeller, Norway
                [2 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Department of Analytics, Environmental & Forensic Sciences, , King’s College London, ; 150 Stamford Street, London, SE1 9NH UK
                Author information
                http://orcid.org/0000-0002-0521-9955
                Article
                362
                10.1186/s40793-020-00362-x
                8067322
                33902714
                e52b3973-1e4c-4164-92da-2c1e471e197d
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 29 February 2020
                : 13 July 2020
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                air,bioaerosol,acd-200 bobcat,dna,electret,filter,high-volume,microbiome,sampler,sass 3100,shotgun metagenomic sequencing

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