Evidence map›Paper›PMID 33865329›Full record

ArticleBMC microbiology2021

Resistance-guided isolation and characterization of antibiotic-producing bacteria from river sediments.

Nowreen Arefa, Ashish Kumar Sarker, Md Ajijur Rahman

Abstract read
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

4 citing papers in PubMed.

  1. Article
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  3. NovelFrontiers in microbiology · 2025
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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

3 authors.

Nowreen ArefaDepartment of Pharmacy, University of Rajshahi, Rajshahi, Bangladesh.
Ashish Kumar SarkerDepartment of Pharmacy, Pabna University of Science and Technology, Pabna, Bangladesh.
Md Ajijur RahmanDepartment of Pharmacy, University of Rajshahi, Rajshahi, Bangladesh. ajijurrahman.pharm@ru.ac.bd.

Funding

Rajshahi University Recurring Fund 2019-20
6 · The paper itself

Abstract

backgroundTo tackle the problem of antibiotic resistance, an extensive search for novel antibiotics is one of the top research priorities. Around 60% of the antibiotics used today were obtained from the genus Streptomyces. The river sediments of Bangladesh are still an unexplored source for antibiotic-producing bacteria (APB). This study aimed to isolate novel APB from Padma and Kapotakkho river sediments having the potential to produce antibacterial compounds with known scaffolds by manipulating their self-protection mechanisms.

resultsThe antibiotic supplemented starch-casein-nitrate agar (SCNA) media were used to isolate antibiotic-resistant APB from the river sediments. The colonies having Streptomyces-like morphology were selectively purified and their antagonistic activity was screened against a range of test bacteria using the cross-streaking method. A notable decrease of the colony-forming units (CFUs) in the antibiotic supplemented SCNA plates compared to control plates (where added antibiotics were absent) was observed. A total of three azithromycin resistant (AZR) and nine meropenem resistant (MPR) isolates were purified and their antagonistic activity was investigated against a series of test bacteria including Shigella brodie, Escherichia coli, Pseudomonas sp., Proteus sp., Staphylococcus aureus, and Bacillus cereus. All the AZR isolates and all but two MPR isolates exhibited moderate to high broad-spectrum activity. Among the isolates, 16S rDNA sequencing of NAr5 and NAr6 were performed to identify them up to species level. The analyses of the sequences revealed that both belong to the genus Streptomyces.

conclusionsThe results from these studies suggest that manipulation of the self-resistance property of APB is an easy and quick method to search for novel APB having the potential to produce potentially novel antibacterial compounds with known scaffolds.

Indexed as

Bacterial Physiological PhenomenaDrug Resistance, MicrobialAnti-Bacterial AgentsBangladeshGeologic SedimentsMicrobial InteractionsRiversRNA, Ribosomal, 16SStreptomycesAnti-Bacterial AgentsRNA, Ribosomal, 16S16S rDNA sequencingAntibiotic resistanceAntibiotic-resistant isolatesStreptomyces

Identifiers

PMID33865329
PMCPMC8053276

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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.