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Filter forensics: microbiota recovery from residential HVAC filters

Overview of attention for article published in Microbiome, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)

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16 X users
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Citations

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38 Dimensions

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123 Mendeley
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1 CiteULike
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Title
Filter forensics: microbiota recovery from residential HVAC filters
Published in
Microbiome, January 2018
DOI 10.1186/s40168-018-0407-6
Pubmed ID
Authors

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

Abstract

Establishing 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. The 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. Dust 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.

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X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 22%
Student > Ph. D. Student 16 13%
Professor > Associate Professor 9 7%
Student > Doctoral Student 8 7%
Student > Bachelor 8 7%
Other 23 19%
Unknown 32 26%
Readers by discipline Count As %
Environmental Science 18 15%
Engineering 17 14%
Agricultural and Biological Sciences 15 12%
Biochemistry, Genetics and Molecular Biology 9 7%
Medicine and Dentistry 7 6%
Other 15 12%
Unknown 42 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 October 2022.
All research outputs
#3,852,974
of 23,530,272 outputs
Outputs from Microbiome
#1,206
of 1,513 outputs
Outputs of similar age
#84,974
of 442,860 outputs
Outputs of similar age from Microbiome
#50
of 52 outputs
Altmetric has tracked 23,530,272 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.9. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,860 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.