Evidence map›Paper›PMID 29382378›Full record

ArticleMicrobiome2018

Filter forensics: microbiota recovery from residential HVAC filters.

Juan P Maestre, Wiley Jennings, Dennis Wylie, Sharon D Horner, Jeffrey Siegel, Kerry A Kinney

Abstract 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 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Indoor Microbiome: Sampling, Analysis and Emerging Trends.Environmental microbiology reports · 2026
    Pooled it
  2. Article
  3. Article
  4. The indoors microbiome and human health.Nature reviews. Microbiology · 2024
    Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Bioaerosol Sampling: Classical Approaches, Advances, and Perspectives.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2020
    Article
  13. Article
  14. Article
  15. Article
  16. Sampling Devices for Indoor Allergen Exposure: Pros and Cons.Current allergy and asthma reports · 2019
    Review
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

6 authors.

Juan P MaestreDepartment of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX, USA. Juanpedro.maestre@utexas.edu.
Wiley JenningsDepartment of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX, USA.
Dennis WylieGenome Sequencing and Analysis Facility, The University of Texas at Austin Center for Biomedical Research Support, The University of Texas at Austin, Austin, TX, USA.
Sharon D HornerSchool of Nursing, The University of Texas at Austin, Austin, TX, USA.
Jeffrey SiegelDepartment of Civil Engineering, University of Toronto, Ontario, Canada.
Kerry A KinneyDepartment of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX, USA.

Funding

U.S. Department of Housing and Urban Development TXHHU0023-13
6 · The paper itself

Abstract

backgroundEstablishing reliable methods for assessing the microbiome within the built environment is critical for understanding the impact of biological exposures on human health. High-throughput DNA sequencing of dust samples provides valuable insights into the microbiome present in human-occupied spaces. However, the effect that different sampling methods have on the microbial community recovered from dust samples is not well understood across sample types. Heating, ventilation, and air conditioning (HVAC) filters hold promise as long-term, spatially integrated, high volume samplers to characterize the airborne microbiome in homes and other climate-controlled spaces. In this study, the effect that dust recovery method (i.e., cut and elution, swabbing, or vacuuming) has on the microbial community structure, membership, and repeatability inferred by Illumina sequencing was evaluated.

resultsThe results indicate that vacuum samples captured higher quantities of total, bacterial, and fungal DNA than swab or cut samples. Repeated swab and vacuum samples collected from the same filter were less variable than cut samples with respect to both quantitative DNA recovery and bacterial community structure. Vacuum samples captured substantially greater bacterial diversity than the other methods, whereas fungal diversity was similar across all three methods. Vacuum and swab samples of HVAC filter dust were repeatable and generally superior to cut samples. Nevertheless, the contribution of environmental and human sources to the bacterial and fungal communities recovered via each sampling method was generally consistent across the methods investigated.

conclusionsDust recovery methodologies have been shown to affect the recovery, repeatability, structure, and membership of microbial communities recovered from dust samples in the built environment. The results of this study are directly applicable to indoor microbiota studies utilizing the filter forensics approach. More broadly, this study provides a better understanding of the microbial community variability attributable to sampling methodology and helps inform interpretation of data collected from other types of dust samples collected from indoor environments.

Indexed as

Air MicrobiologyAir ConditioningAir Pollution, IndoorBacteriaDNA, BacterialDNA, FungalDustFungiHeatingHigh-Throughput Nucleotide SequencingHumansMicrobiotaSequence Analysis, DNAVentilationDNA, BacterialDNA, FungalDustBacteriaBuilt environmentFilter forensicsFungiHVACIndoor microbiology

Identifiers

PMID29382378
PMCPMC5791358

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.