Mixed dye degradation by Bacillus pseudomycoides and Acinetobacter haemolyticus isolated from industrial effluents: A combined affirmation with wetlab and in silico studies

Hossain, Md. Shamim; Paul, Gobindo Kumar; Mahmud, Shafi; Saleh, Md. Abu; Uddin, Md. Salah; Dutta, Amit Kumar; Roy, Arun K.; Saha, Ananda Kumar; Sheam, Md. Moinuddin; Ahmed, Sabbir; Rahman, Mizanur; Paul, Dipak; Biswas, Sudhangshu Kumar

doi:10.1016/j.arabjc.2022.104078

Cited by 8 publications

(2 citation statements)

References 64 publications

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“…It is worth noting that hydrogen bond energy plays a crucial role in the degradation of acid orange 7, cresol red, and methylene blue, while van der Waals interactions are involved in the degradation of malachite green. These results are in alignment with the previous analyses, providing further support to the overall findings (Zhang et al, 2016;Srinivasan and Sadasivam, 2018;Hossain et al, 2022;Alam et al, 2023). This result indicates that optimizing hydrogen bond interactions between acid orange 7, cresol red, and methylene blue and AzrBmH2 proteins, as well as optimizing van der Waals interactions between malachite green and AzrBmH2 proteins, could potentially enhance the degradation or decolorization of the AzrBmH2-dyes interaction.…”

Section: Mm-pbsa Binding Free Energy Calculationsupporting

confidence: 90%

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

Oyewusi,

Wahab,

Akinyede

et al. 2023

Preprint

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The present study aimed to investigate the decolorization of various commercial dyes through bioinformatics analysis, utilizing techniques such as molecular docking, molecular dynamics simulation, and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA). These analyses were conducted on different commercial dyes to evaluate their potential for biodegradation. In this study, four commercial dyes, namely acid orange 7, cresol red, methylene blue, and malachite green, were selected as potential targets for degradation by azoreductases (AzrBmH21, AzrBmH22/3, and AzrBmH24/5) derived from Bacillus megaterium H2. The prediction of ligand binding or catalytic sites for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 was performed using a machine learning algorithm based on the Prank Web and DeepSite chemoinformatic tool. The analysis revealed that several amino acids of AzrBmH2 interacted with the tested dyes, indicating the presence of distinct ligand-binding sites for AzrBmH2-dye complexes. The binding affinity for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 ranged from − 9.4 to -5.5 kcal/mol, -9.2 to -5.4 kcal/mol, and − 9.0 to -5.4 kcal/mol, respectively. Each complex was stabilized by a minimum of 0–5 hydrogen bonds. MD simulations revealed stable AzrBmH2-dye complexes (with RMSD 0.15–0.42 nm, RMSF 0.05–0.48 nm, Rg 1.75–1.88 nm). MMPBSA calculations indicated that the AzrBmH2-dye complexes, except for AzrBmH2-malachite green, exhibited the lowest binding energy (-191.05 ± 7.08 to 314.19 ± 6.88 kcal/mol). The AzrBmH2-malachite green complex showed a prevalence of hydrophobic interactions (-268.25 ± 12.25 to -418.92 ± 29.45 kcal/mol) through van der Waals forces. This study highlights the potential role of enzymes, specifically azoreductases from Bacillus megaterium H2, in predicting the decolorization of commercial dyes. These findings contribute to our understanding of enzyme mechanisms in bioremediation and for biotechnological applications.

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Section: Mm-pbsa Binding Free Energy Calculationsupporting

confidence: 90%

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

Oyewusi,

Wahab,

Akinyede

et al. 2023

Preprint

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“…Moreover, the microbial indicators can be used to determine the extent of anthropogenic disturbances and sources across the space and time. In the case of PRE sediments, the enrichment of microbial indicators of putative human pathogens (e.g., Mycoplasma hyosynoviae 91 and Mycobacterium noviomagense 92 ) and xenobiotic degraders (e.g., Mycolicibacterium vanbaalenii 93 and Bacillus pseudomycoides 94 ) in the nearshore samples suggests a high level of anthropogenic disturbances and the potential release of fecal matter and hazardous chemicals. Local environmental managers can accordingly trace the sources and implement control strategies to minimize their releases, and routine monitoring of the microbial indicators over time (e.g., by using quantitative PCR) can inform the effectiveness of those strategies.…”

Section: ■ Discussionmentioning

confidence: 99%

Metagenomics-Based Microbial Ecological Community Threshold and Indicators of Anthropogenic Disturbances in Estuarine Sediments

Bao,

Ruan,

et al. 2023

Environ. Sci. Technol.

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Assessing the impacts of cumulative anthropogenic disturbances on estuarine ecosystem health is challenging. Using spatially distributed sediments from the Pearl River Estuary (PRE) in southern China, which are significantly influenced by anthropogenic activities, we demonstrated that metagenomics-based surveillance of benthic microbial communities is a robust approach to assess anthropogenic impacts on estuarine benthic ecosystems. Correlational and threshold analyses between microbial compositions and environmental conditions indicated that anthropogenic disturbances in the PRE sediments drove the taxonomic and functional variations in the benthic microbial communities. An ecological community threshold of anthropogenic disturbances was identified, which delineated the PRE sediments into two groups (H and L) with distinct taxa and functional traits. Group H, located nearshore and subjected to a higher level of anthropogenic disturbances, was enriched with pollutant degraders, putative human pathogens, fecal pollution indicators, and functional traits related to stress tolerance. In contrast, Group L, located offshore and subjected to a lower level of anthropogenic disturbances, was enriched with halotolerant and oligotrophic taxa and functional traits related to growth and resource acquisition. The machine learning random forest model identified a number of taxonomic and functional indicators that could differentiate PRE sediments between Groups H and L. The identified ecological community threshold and microbial indicators highlight the utility of metagenomics-based microbial surveillance in assessing the adverse impacts of anthropogenic disturbances in estuarine sediments, which can assist environmental management to better protect ecosystem health.

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Decoding dye degradation: Microbial remediation of textile industry effluents

Das,

Cherwoo,

Singh

2023

Biotechnology Notes

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Mixed dye degradation by Bacillus pseudomycoides and Acinetobacter haemolyticus isolated from industrial effluents: A combined affirmation with wetlab and in silico studies

Cited by 8 publications

References 64 publications

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

Metagenomics-Based Microbial Ecological Community Threshold and Indicators of Anthropogenic Disturbances in Estuarine Sediments

Decoding dye degradation: Microbial remediation of textile industry effluents

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