Evidence map›Paper›PMID 31454571›Full record

ArticleEnvironmental pollution (Barking, Essex : 1987)2019

Dairy farm soil presents distinct microbiota and varied prevalence of antibiotic resistance across housing areas.

Jinxin Liu, Zhe Zhao, Johannetsy J Avillan, Douglas R Call, Margaret Davis, William M Sischo, Anyun Zhang

Open access · greenAbstract read
In one paragraph

Article in Environmental pollution (Barking, Essex : 1987), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

14 citing papers in PubMed, 38 citations in OpenAlex.

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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 4 institutions in 2 countries.

Jinxin LiuKey Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, Sichuan, PR China; Institute of Marine Biology, College of Oceanography, Hohai University, Nanjing, Jiangsu, PR China; Department of Food Science and Technology, Robert Mondavi Institute for Wine and Food Science, University of California, Davis, CA 95616, USA.
Zhe ZhaoInstitute of Marine Biology, College of Oceanography, Hohai University, Nanjing, Jiangsu, PR China.
Johannetsy J AvillanPaul G. Allen School for Global Animal Health, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA.
Douglas R CallPaul G. Allen School for Global Animal Health, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA.
Margaret DavisPaul G. Allen School for Global Animal Health, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA.
William M SischoPaul G. Allen School for Global Animal Health, College of Veterinary Medicine, Washington State University, Pullman, WA 99164, USA; Department of Veterinary Clinical Sciences, Washington State University, Pullman, WA, USA.
Anyun ZhangKey Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, Sichuan, PR China. Electronic address: zhanganyun@scu.edu.cn.
Washington State University · USHohai University · CNSichuan University · CNUniversity of California, Davis · US

Funding

TRAINING IN BIOTECHNOLOGY: EMPHASIS ON PROTEIN CHEMISTRYT32GM008336 · NIGMS · WASHINGTON STATE UNIVERSITY · PI CALL, DOUGLAS R. · 1989 to 2023
$8.9M
NIGMS NIH HHS T32 GM008336
6 · The paper itself

Abstract

Dairy cattle of different ages experience different living conditions and varied frequency of antibiotic administration that likely influence the distribution of microbiome and resistome in ways that reflect different risks of microbial transmission. To assess the degree of variance in these distributions, fecal and soil samples were collected from six distinct housing areas on commercial dairy farms (n = 7) in Washington State. 16S rRNA gene sequencing indicated that the microbiota differed between different on-farm locations in feces and soil, and in both cases, the microbiota of dairy calves was often distinct from others (P < 0.05). Thirty-two specific antibiotic resistance genes (ARGs) were widely distributed on dairies, of which several clinically relevant ARGs (including cfr, cfrB, and optrA) were identified for the first time at U.S. dairies. Overall, ARGs were observed more frequently in feces and soil from dairy calves and heifers than from hospital, fresh, lactation and dry pens. Droplet-digital PCR demonstrated that the absolute abundance of floR varied greatly across housing areas and this gene was enriched the most in calves and heifers. Furthermore, in an extended analysis with 14 dairies, environmental soils in calf pens had the most antibiotic-resistant Escherichia coli followed by heifer and hospital pens. All soil E. coli isolates (n = 1,905) are resistant to at least 4 different antibiotics, and the PFGE analysis indicated that florfenicol-resistant E. coli is probably shared across geographically-separated farms. This study identified a discrete but predictable distribution of antibiotic resistance genes and organisms, which is important for designing mitigation for higher risk areas on dairy farms.

Indexed as

DairyingAnti-Bacterial AgentsDrug Resistance, MicrobialEnvironmental MonitoringEscherichia coliEscherichia coli InfectionsFarmsFecesHousingMicrobiotaPrevalenceRNA, Ribosomal, 16SSoilSoil MicrobiologyWashingtonAnti-Bacterial AgentsRNA, Ribosomal, 16SSoilAntibiotic resistanceCalfDairy farmDiscrete distributionHousing areasSoil

Identifiers

PMID31454571
PMCPMC7646532
OpenAlexW2967924467

What OpenQuestion holds

Textmetadata
LicenceTDM
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.