Geography and location are the primary drivers of office microbiome composition
John Chase,Jennifer Fouquier,Mahnaz Zare,Derek L. Sonderegger,Rob Knight,Scott T. Kelley,Jeffrey A. Siegel,J. Gregory Caporaso +7 more
- Vol. 1, Iss: 2
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TLDR
A study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices finds that offices have city-specific bacterial communities, such that it can accurately predict which city an office microbiome sample is derived from, but office- specific bacterial communities are less apparent.Abstract:
In the United States, humans spend the majority of their time indoors, where they are exposed to the microbiome of the built environment (BE) they inhabit. Despite the ubiquity of microbes in BEs and their potential impacts on health and building materials, basic questions about the microbiology of these environments remain unanswered. We present a study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices. Our data elucidate several important features of microbial communities in BEs. First, under normal office environmental conditions, bacterial communities do not differ on the basis of surface material (e.g., ceiling tile or carpet) but do differ on the basis of the location in a room (e.g., ceiling or floor), two features that are often conflated but that we are able to separate here. We suspect that previous work showing differences in bacterial composition with surface material was likely detecting differences based on different usage patterns. Next, we find that offices have city-specific bacterial communities, such that we can accurately predict which city an office microbiome sample is derived from, but office-specific bacterial communities are less apparent. This differs from previous work, which has suggested office-specific compositions of bacterial communities. We again suspect that the difference from prior work arises from different usage patterns. As has been previously shown, we observe that human skin contributes heavily to the composition of BE surfaces. IMPORTANCE Our study highlights several points that should impact the design of future studies of the microbiology of BEs. First, projects tracking changes in BE bacterial communities should focus sampling efforts on surveying different locations in offices and in different cities but not necessarily different materials or different offices in the same city. Next, disturbance due to repeated sampling, though detectable, is small compared to that due to other variables, opening up a range of longitudinal study designs in the BE. Next, studies requiring more samples than can be sequenced on a single sequencing run (which is increasingly common) must control for run effects by including some of the same samples in all of the sequencing runs as technical replicates. Finally, detailed tracking of indoor and material environment covariates is likely not essential for BE microbiome studies, as the normal range of indoor environmental conditions is likely not large enough to impact bacterial communities.read more
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Environmental DNA metabarcoding: transforming how we survey animal and plant communities
Kristy Deiner,Holly M. Bik,Elvira Mächler,Elvira Mächler,Mathew Seymour,Anaïs Lacoursière-Roussel,Florian Altermatt,Florian Altermatt,Simon Creer,Iliana Bista,Iliana Bista,David M. Lodge,Natasha de Vere,Michael E. Pfrender,Louis Bernatchez +14 more
TL;DR: The use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance are reviewed, which distill what is known about the ability of different eDNA sample types to approximate richness in space and across time.
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Best practices for analysing microbiomes.
Rob Knight,Alison Vrbanac,Bryn C. Taylor,Alexander A. Aksenov,Chris Callewaert,Chris Callewaert,Justine W. Debelius,Antonio Gonzalez,Tomasz Kosciolek,Laura-Isobel McCall,Daniel McDonald,Alexey V. Melnik,James T. Morton,Jose Navas,Robert A. Quinn,Jon G. Sanders,Austin D. Swafford,Luke R. Thompson,Luke R. Thompson,Anupriya Tripathi,Zhenjiang Zech Xu,Jesse R. Zaneveld,Qiyun Zhu,J. Gregory Caporaso,Pieter C. Dorrestein,Pieter C. Dorrestein +25 more
TL;DR: This Review focuses on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis.
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Microbiome differential abundance methods produce different results across 38 datasets
Jacob T. Nearing,Gavin M. Douglas,Mary Hayes,Jocelyn MacDonald,Dhwani K. Desai,Nicole E. Allward,Casey M. A. Jones,Robyn J. Wright,Akhilesh S. Dhanani,André M. Comeau,Morgan G. I. Langille +10 more
TL;DR: In this paper , the authors compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups and test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups.
Journal ArticleDOI
Microbiome differential abundance methods produce different results across 38 datasets
Jacob T. Nearing,Gavin M. Douglas,Mary Hayes,Jocelyn MacDonald,Dhwani K. Desai,Nicole E. Allward,Casey M. A. Jones,Robyn J. Wright,Akhilesh S. Dhanani,André M. Comeau,Morgan G. I. Langille +10 more
TL;DR: In this paper , the authors compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups and test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups.
Journal ArticleDOI
Microbiology of the built environment
TL;DR: The history of the field of microbiology of the built environment is outlined and recent insights that have been gained into microbial ecology, adaptation and evolution of this ecosystem are discussed.
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