Evidence map›Paper›PMID 41039010›Full record

ArticleBiodegradation2025

The mechanism underlying lignite biodegradation by Cupriavidus sp isolated from sludge.

Yaya Wang, Weilong Cao, Tianyu Zhu, Jiaxuan Li, Damir Nussipov, Kuanysh Tastambek, Xiangrong Liu

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Article in Biodegradation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yaya WangCollege of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, 58 Yanta Zhonglu, Xi'an, 710054, Shaanxi, China. wangyaya@xust.edu.cn.
Weilong CaoCollege of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, 58 Yanta Zhonglu, Xi'an, 710054, Shaanxi, China.
Tianyu ZhuCollege of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, 58 Yanta Zhonglu, Xi'an, 710054, Shaanxi, China.
Jiaxuan LiCollege of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, 58 Yanta Zhonglu, Xi'an, 710054, Shaanxi, China.
Damir NussipovSustainability of Ecology and Bioresources, Al-Farabi Kazakh National University, Almaty, Kazakhstan.
Kuanysh TastambekSustainability of Ecology and Bioresources, Al-Farabi Kazakh National University, Almaty, Kazakhstan.
Xiangrong LiuCollege of Chemistry and Chemical Engineering, Xi'an University of Science and Technology, 58 Yanta Zhonglu, Xi'an, 710054, Shaanxi, China. liuxiangrongxk@163.com.

Funding

National Natural Science Foundation of China No. 42202206National Natural Science Foundation of China U24A20552
6 · The paper itself

Abstract

Lignite, a low-rank coal, is commonly utilized as a fuel source. However, its high sulfur and ash content can result in the release of harmful substances during combustion. Microbial coal degradation offers a more environmentally friendly alternative to traditional chemical and physical methods of coal treatment. In this study, we obtained a bacterium, named as Cupriavidus sp isolated from activated sludge that exhibits potential for lignite degradation. After identification via 16S rDNA sequencing, the degradation characteristics and mechanisms of strain S4 on lignite from Shanxi, were systematically evaluated. Extracellular enzyme activities of strain S4 were measured, revealing the secretion of lignin peroxidase, manganese peroxidase, laccase, alkaline protease, and amylase, indicating its capacity for multi-enzyme synergistic degradation. Scanning electron microscopy (SEM) observations confirmed that the bacterium could adsorb onto the coal surface. Fourier transform infrared spectroscopy (FTIR) analysis demonstrated a significant increase in free hydroxyl groups on the coal, which facilitates degradation. Gas chromatography-mass spectrometry (GC-MS) and three-dimensional fluorescence spectroscopy analyses of the liquid-phase products showed a notable increase in long-chain alkanes and phenolic compounds in the degradation liquid, along with the detection of humic substances. Further studies indicated that strain S4 mediates initial adsorption through the secretion of extracellular polymers (EPS) rich in proteins and polysaccharides, highlighting the key mechanism of microbial-coal interface interaction. This study provides a theoretical foundation for the development of lignite bioremediation technologies and the resource-based application of functional bacterial strains.

Indexed as

CoalCupriavidusSewageBiodegradation, EnvironmentalLigninCoalLigninSewageBiodegradationBiological enzymesExtracellular polymersLigniteMicroorganisms

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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.