Evidence map›Paper›PMID 29661230›Full record

ArticleMicrobiome2018

A comparison of methods used to unveil the genetic and metabolic pool in the built environment.

Cinta Gomez-Silvan, Marcus H Y Leung, Katherine A Grue, Randeep Kaur, Xinzhao Tong, Patrick K H Lee, Gary L Andersen

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Article
  3. The indoors microbiome and human health.Nature reviews. Microbiology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Cinta Gomez-SilvanDepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA.
Marcus H Y LeungSchool of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.
Katherine A GrueDepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA.
Randeep KaurEnvironmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Xinzhao TongSchool of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.
Patrick K H LeeSchool of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. patrick.kh.lee@cityu.edu.hk.
Gary L AndersenDepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA. glandersen@lbl.gov.
City University of Hong Kong · HKLawrence Berkeley National Laboratory · USUniversity of California, Berkeley · US

Funding

Alfred P. Sloan Foundation G-2015-13977Research Grants Council, University Grants Committee 11276116
6 · The paper itself

Abstract

backgroundA majority of indoor residential microbes originate from humans, pets, and outdoor air and are not adapted to the built environment (BE). Consequently, a large portion of the microbes identified by DNA-based methods are either dead or metabolically inactive. Although many exceptions have been noted, the ribosomal RNA fraction of the sample is more likely to represent either viable or metabolically active cells. We examined methodological variations in sample processing using a defined, mock BE microbial community to better understand the scope of technique-based vs. biological-based differences in both ribosomal transcript (rRNA) and gene (DNA) sequence community analysis. Based on in vitro tests, a protocol was adopted for the analysis of the genetic and metabolic pool (DNA vs. rRNA) of air and surface microbiomes within a residential setting.

resultsWe observed differences in DNA/RNA co-extraction efficiency for individual microbes, but overall, a greater recovery of rRNA using FastPrep (> 50%). Samples stored with various preservation methods at - 80°C experienced a rapid decline in nucleic acid recovery starting within the first week, although post-extraction rRNA had no significant degradation when treated with RNAStable. We recommend that co-extraction samples be processed as quickly as possible after collection. The in vivo analysis revealed significant differences in the two components (genetic and metabolic pool) in terms of taxonomy, community structure, and microbial association networks. Rare taxa present in the genetic pool showed higher metabolic potential (RNA:DNA ratio), whereas commonly detected taxa of outdoor origins based on DNA sequencing, especially taxa of the Sphingomonadales order, were present in lower relative abundances in the viable community.

conclusionsAlthough methodological variations in sample preparations are high, large differences between the DNA and RNA fractions of the total microbial community demonstrate that direct examination of rRNA isolated from a residential BE microbiome has the potential to identify the more likely viable or active portion of the microbial community. In an environment that has primarily dead and metabolically inactive cells, we suggest that the rRNA fraction of BE samples is capable of providing a more ecologically relevant insight into the factors that drive indoor microbial community dynamics.

Indexed as

Built EnvironmentEnvironmental MicrobiologyMetabolomicsMetagenomicsMicrobiotaHumansPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16SAirDNAExtraction kitIndoor microbiomeRNARNAStableSample storageSurface

Identifiers

PMID29661230
PMCPMC5902888
OpenAlexW2805170795

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.