Evidence map›Paper›PMID 36267172›Full record

ArticleFrontiers in microbiology2022

Diversity and abundance of antibiotic resistance genes and their relationship with nutrients and land use of the inflow rivers of Taihu Lake.

Prilli Arista Fernanda, Shuang Liu, Tianma Yuan, Bharathi Ramalingam, Jing Lu, Raju Sekar

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

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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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Resistome Study in Aquatic Environments.Journal of microbiology and biotechnology · 2023
    Review
  6. Article
  7. Article
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.

Prilli Arista FernandaDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Shuang LiuDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Tianma YuanDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Bharathi RamalingamSuzhou Xishan Biotechnology Inc. (VRL Asia), Suzhou, China.
Jing LuMarie Skłodowska-Curie Actions, SDGine for Healthy People and Cities, Department of Forestry and Environmental Management, Technical University of Madrid (UPM), Madrid, Spain.
Raju SekarDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Taihu Lake is the third largest freshwater lake in China and an important source for drinking water, flood protection, aquaculture, agriculture, and other activities. This lake is connected to many principal and small rivers with inflow from west and outflow on the eastern side of the lake and these inflow rivers are believed to significantly contribute to the water pollution of the lake. This study was aimed at assessing the diversity and abundance of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs), and their relationship with water quality parameters and land use patterns. Water samples were collected from 10 major inflow rivers and the source water protection area of the Taihu Lake in spring and summer 2019. High-throughput profiling was used to detect and quantify 384 ARGs and MGEs and in addition, 11 water quality parameters were analyzed. The results showed that the number of ARGs/MGEs detected in each inflow river ranged from 105 to 185 in spring and 107 to 180 in summer. The aminoglycoside resistance genes were the most dominant types ARGs detected followed by beta-lactam resistance, multidrug resistance, macrolide-lincosamide-streptogramin B (MLSB) resistance genes, which contributed to 65% of the ARGs. The water quality parameters showed significant correlation with absolute abundance of ARGs. Furthermore, significant correlation between ARGs and MGEs were also observed which demonstrates potential gene transfer among organisms through horizontal gene transfer

Indexed as

antibiotic resistance genes (ARGs)high-throughput profilinginflow riversland useTaihu Lakewater quality

Identifiers

PMID36267172
PMCPMC9577174

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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.