Evidence map›Paper›PMID 40175441›Full record

ArticleScientific reports2025

Characterization and optimization of azo dyes degrading microbes isolated from textile effluent.

Arshiya Khan, Anuraj Nayarisseri, Sanjeev Kumar Singh

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

11 citing papers in PubMed.

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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.

Arshiya KhanIn silico Research Laboratory, Eminent Biosciences, Indore, 452010, Madhya Pradesh, India.ORCID http://orcid.org/0000-0002-1556-586X
Anuraj NayarisseriIn silico Research Laboratory, Eminent Biosciences, Indore, 452010, Madhya Pradesh, India.ORCID https://orcid.org/0000-0003-2567-9630
Sanjeev Kumar SinghComputer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630 003, Tamil Nadu, India. skysanjeev@gmail.com.ORCID http://orcid.org/0000-0003-4153-6437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Azo dyes are highly recalcitrant, persistent, and toxic compounds, extensively used in the textile industry. The untreated discharge of dye effluents from the textile industry poses severe environmental and health risks. This research aimed to isolate and identify bacterial strains from textile wastewater that can decolorize azo dyes. After the subsequent screening of 89 isolates, 4 novel strains were identified utilizing the 16S rRNA gene sequencing technique that could effectively decolorize and degrade azo dyes, methyl red, direct yellow 12, and acid black 210. A thorough assessment of physicochemical parameters was conducted to optimize for maximum decolorization for all four strains. At pH 7, 37° C, and 50 mg/L dye concentration, the maximum decolorization for methyl red, direct yellow 12, and acid black 210 was 79.09% > 72.20% > 64.76%; 84.45% > 62.59% > 54.29%; 83.12% > 70.22% > 61.42%; and 92.71% > 83.02% > 69.84%, for isolate 1, isolate 2, isolate 3, and isolate 4, respectively. The novel strains belonged to the Sphingomonas, Pseudomonas, Shewanella, and Priestia species. The unique sequences of these bacterial strains have been submitted to the GenBank database under the accession numbers "OQ202071", "PP708911", "PP708909", and "PP086977," respectively. Further, an enzyme study and statistical optimization of Priestia flexa species was performed. A Central Composite Design and Response Surface Methodology has been applied for synergistic effects of process parameters namely pH (5-9), initial dye concentration (100-250 mg/L), and temperature (25°-45° C) on the decolorization of the model dyes. The regression analysis indicated a strong correlation between the experimental data and the second-order polynomial supported by a high coefficient of determination (R²). For all three dyes analyzed, the difference between the experimental and predicted values was found to be less than 10%. Fourier Transform Infrared spectroscopy was further employed to analyze and confirm the degradation of the three dyes.

Indexed as

Azo CompoundsBacteriaColoring AgentsTextile IndustryWastewaterWater Pollutants, ChemicalBiodegradation, EnvironmentalHydrogen-Ion ConcentrationIndustrial WastePhylogenyRNA, Ribosomal, 16SAzo CompoundsColoring AgentsIndustrial WasteRNA, Ribosomal, 16SWastewaterWater Pollutants, ChemicalAzo dyesAzoreductaseBiodegradationFTIRLaccaseRSMTextile wastewater

Identifiers

PMID40175441
PMCPMC11965336

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Registered trials

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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.