Evidence map›Paper›PMID 30707381›Full record

ArticleEnvironmental science and pollution research international2019

Detecting antibiotic resistance genes and human potential pathogenic Bacteria in fishmeal by culture-independent method.

Ying Han, Jing Wang, Zelong Zhao, Jingwen Chen, Hong Lu, Guangfei Liu

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 at 1 institution in 1 country.

Ying HanKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China.
Jing WangKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China. jwang@dlut.edu.cn.ORCID http://orcid.org/0000-0003-2395-3157
Zelong ZhaoKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China.
Jingwen ChenKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China.
Hong LuKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China.
Guangfei LiuKey Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, 2#Linggong Road, Ganjingzi District, Dalian, Liaoning, 116024, People's Republic of China.
Dalian University of Technology · CN

Funding

National Basic Research Program of China 2013CB430403
6 · The paper itself

Abstract

Fishmeal is a fundamental ingredient of feedstuffs and is used globally in aquaculture. However, there are few data on the antibiotic resistance genes (ARGs) and human pathogenic bacteria in fishmeal and little understanding of the potential risks of fishmeal application in mariculture systems. Here, we investigated the high-throughput profiles of ARGs and human potential pathogenic bacteria (HPPB) in representative fishmeals (n = 5) and the potential impact of fishmeal on mariculture sediments. ARGs were quantified with microbial DNA quantitative PCR arrays and HPPB were analyzed with Illumina sequencing of 16S rRNA genes. The impact of the fishmeal on the aquaculture sediments was assessed in a microcosm study. Twenty-four unique ARGs (3-14 per sample) and 25 HPPB species were detected in the fishmeal samples. The most prevalent ARGs were fluoroquinolone resistance genes. The overall abundance of HPPB was 5.0-25.5%, and the HPPB species were dominated by Vibrio parahaemolyticus, Clostridium novyi, and Escherichia coli. In the mariculture microcosm sediment, fishmeal significantly increased the normalized abundance of the class I integrase gene (25.4-fold), which plays an important role in the dissemination of ARGs. Dosing with fishmeal also contributed to increases in a resident sulfanilamide resistance gene (sulI gene) and the emergence of a macrolide resistance gene (ermB gene) in the sediment. These findings demonstrated that fishmeal itself is an underestimated reservoir and source of ARGs and HPPBs, and that the application of fishmeal facilitates the dissemination of ARGs in aquaculture sediments. Our results extend our knowledge of the ARGs and HPPB within fishmeal and may provide a feasible and effective approach to the detection of ARGs and HPPB in fishmeal during food safety inspection. Graphical abstract ᅟ.

Indexed as

AquacultureGenes, BacterialAnimal FeedAnti-Bacterial AgentsBacteriaDrug Resistance, MicrobialFood SafetyHumansRNA, Ribosomal, 16SAnti-Bacterial AgentsRNA, Ribosomal, 16SAntibiotic resistance genes (ARGs)FishmealHuman potential pathogenic bacteria (HPPB)Mariculture microcosm

Identifiers

PMID30707381
OpenAlexW2913100054

What OpenQuestion holds

Textmetadata
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.