Biodegradation最新文献

Emerging contaminants (ECs), including pharmaceuticals, antibiotics, personal care products, endocrine-disrupting compounds and persistent industrial chemicals, are increasingly detected in wastewater effluents because many are poorly removed by conventional treatment and may form biologically active transformation products. This review critically evaluates hybrid constructed wetlands (HCWs) as engineered biodegradation platforms for EC attenuation, with emphasis on microbial pathways, redox-zonation and substrate-mediated transformation. HCWs integrate vertical-flow, horizontal subsurface-flow and free-water surface units to create coupled aerobic, anoxic, anaerobic, rhizospheric and photic microenvironments. These zones support filtration and sorption, but importantly promote biodegradation, cometabolism, nitrification–denitrification, anaerobic ammonium-oxidation and sulfur-driven autotrophic-denitrification. Anammox bacteria, including Candidatus Brocadia, Candidatus Jettenia, and Candidatus Scalindua, contribute to low-carbon nitrogen removal by coupling ammonium oxidation with nitrite reduction. Sulfur-oxidizing denitrifiers Thiobacillus, Sulfurimonas and Sulfuritalea further stabilize anoxic electron-transfer conditions under carbon-limited wastewater. Although these communities do-not directly mineralize all ECs, they regulate redox gradients, biofilm activity and enzymatic environments that favour transformation of biodegradable and cometabolizable compounds. Conventional gravel and sand provide hydraulic support and show limited dissolved EC-removal, generally below 20–30%, whereas biochar, zeolite and LECA improve removal to 60–90% by enhancing sorption and microbial colonization. Functionalized media, including TiO₂-coated substrates, Fe/Mn materials and nano-zero-valent (nZVI) iron, can achieve 70–98% removal for selected recalcitrant ECs. Field systems commonly report 50–85% removal, whereas laboratory systems often exceed 90%, indicating a scale-up gap. This review highlights microbial responses to HCW, redox conditions, substrates, rhizosphere-interactions and wastewater characteristics, while identifying future needs in transformation-product tracking, and functional-gene monitoring for SDG 6-oriented wastewater treatment.

The use of synthetic pesticides estimated at 4.1 million metric tons annually worldwide, has led to widespread contamination of soils and aquatic environments, with documented risks to ecosystem integrity and human health. Physicochemical remediation methods are costly and often generate secondary pollutants and toxic intermediates, making microbial bioremediation a lower-residue alternative to physicochemical treatment. Because pesticide degradation in natural environments is rarely achieved by single microbial species, this review critically synthesizes evidence on multi-species microbial consortia—natural, synthetic, and genetically engineered for the biodegradation of six major pesticide classes: organophosphates, carbamates, pyrethroids, neonicotinoids, organochlorines, and triazines. Integration of the ecological mechanisms underlying consortium synergism (sequential metabolic cooperation, metabolic division of labour, biosurfactant-mediated bioavailability enhancement, horizontal gene transfer, and extracellular enzyme cooperation) with the enzymatic and genetic basis of degradation for each pesticide class, and evaluate how emerging tools like multi-omics profiling, CRISPR-based strain engineering, immobilisation technologies, synthetic consortium design, and AI-assisted optimisation are reshaping consortium design. Reported removal efficiencies are consistently higher for consortia than for monocultures across the studies reviewed here, though direct comparisons vary by pesticide class and experimental design. The review closes by evaluating the principal barriers to field-scale translation, strain persistence, ecological risk and regulatory approval, and monitoring of introduced strains and proposes a tiered framework for matching consortium design to contamination scenario. To date, this is the review to integrate ecological interaction mechanisms, class-specific enzymatic pathways, and translational technologies for pesticide-degrading consortia within a single framework.

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Polyethylene (PE) is a widely used synthetic polymer whose resistance to degradation poses a significant environmental challenge. In this study, landfill soils from municipal waste disposal sites in Mangaluru, India, were explored as potential sources of PE-degrading bacteria. Bacterial isolates were screened for their ability to utilize PE as a carbon source, and selected isolates were evaluated for degradation-related activity. Among the tested isolates, the highest PE weight reduction observed after 30 days was 15.38%. Physicochemical characterization of PE films revealed structural alterations, oxidative functional group formation, and surface damage following bacterial treatment. In addition, the laccase assay indicated a significant increase in the enzyme activity during the study period, highlighting the involvement of oxidative pathways. Among the PE-degrading genes screened, alkB was detected in all tested isolates. Molecular identification based on 16S rRNA gene sequencing revealed four bacterial species, among which Escherichia fergusonii and Leclercia adecarboxylata are reported for the first time as PE degraders. Overall, the findings highlight landfill environments as reservoirs of metabolically diverse microorganisms with potential relevance for future plastic biodegradation and bioremediation studies. Further studies focusing on enzymatic mechanisms and process optimization are essential to enhance biodegradation efficiency and enable large-scale applications.

Vinasse, a byproduct of the ethanol industry, poses significant challenges for anaerobic digestion due to its high concentration of recalcitrant phenolic compounds and its tendency to generate excessive foam, which destabilizes reactor hydrodynamics. This study introduces a methodologically transparent approach to pretreating vinasse for anaerobic digestion. While ozonation and polydimethylsiloxane (PDMS) antifoam are established individually, their combined application for processing highly recalcitrant agro-industrial wastewater requires precise control. PDMS was introduced as an operational prerequisite to suppress severe foaming and physically prevent reactor overflow. With physical stability maintained, Response Surface Methodology (RSM) via a central composite design (CCD) was employed to mathematically optimize the critical chemical process variables—pH, ozone flow rate, and contact time—to detoxify the substrate without inhibiting downstream microbial activity The results indicated that ozonation significantly enhanced biodegradability, with the optimal conditions determined at pH 4.0, an ozone flow rate of 2.0 L/min, and a contact time of 90 min. Under these conditions, the treatment achieved high removal efficiencies for COD and phenolic compounds while reducing the carbon-to-nitrogen (C/N) ratio to 16.7, thereby altering the substrate balance before final nutrient adjustment for methanogenesis. Validation experiments confirmed that the operationally stabilized ozonation process increased the methane yield to 0.22 L CH₄/g COD, a 37.5% increase over untreated vinasse (0.16 L CH₄/g COD). These findings demonstrate that integrating PDMS with ozonation shows strong lab-scale potential to overcome the mechanical and chemical barriers inherent in processing high-strength agro-industrial wastewater, warranting further pilot-scale engineering studies.

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Pharmaceutical residues are increasingly detected in freshwater systems at concentrations ranging from g/L to /L, raising concerns due to their persistence, bioactivity, and potential ecological and human health impacts. Conventional wastewater treatment plants typically achieve limited removal efficiencies (often 30–60% for many compounds such as carbamazepine and diclofenac), necessitating alternative treatment strategies. This review critically evaluates microalgae-based pond and consortia systems, emphasizing the key removal pathways of bioadsorption (10–40%), bioaccumulation (up to 20–30%), and biodegradation (40–90%, compound and condition dependent). It further examines microalgal physiological responses, including oxidative stress regulation, enzymatic transformation, and adaptive metabolic shifts under pharmaceutical exposure, which influence treatment performance. Major operational constraints, including seasonal variability, affect productivity and toxicity thresholds that inhibit algal growth at elevated contaminant concentrations. Recent advances in strain engineering, co-culture consortia, and process optimization have demonstrated removal efficiencies exceeding 80% under optimized conditions. Moreover, this review provides a systematic synthesis of mechanistic pathways, integrates recent process innovations, and identifies critical knowledge gaps related to by-product toxicity, scale-up stability, and long-term system performance, offering a more quantitative and application-oriented perspective on microalgae-based pharmaceutical removal.

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Heavy metal (HM) contamination represents a persistent global threat, demanding bioremediation strategies that are both mechanistically robust and ecologically sustainable. This review provides a next-generation perspective on vermiremediation by integrating species-level physiology, gut microbiome functionality, molecular detoxification pathways, synthetic biology innovations, multi-omics insights, and artificial intelligence (AI)-driven modeling into a unified framework. A central novelty of this work lies in the detailed elucidation of earthworm-microbe consortia and their synergistic contributions to metal sequestration, transformation, and detoxification-moving beyond traditional organism-centric views toward eco-engineered host-symbiont systems. We synthesize species-specific bioaccumulation patterns, toxicological responses, and detoxification mechanisms, supported by enrichment kinetic models. At the molecular scale, we highlight antioxidant defense pathways involving catalase, glutathione-S-transferase, and superoxide dismutase, alongside oxidative stress signaling, macromolecular damage, and thresholds that differentiate adaptive resilience from system failure. Advancements in synthetic biology includes gene editing, pathway reconstruction, and designer symbiotic microbes which are examined as emerging tools to enhance gut microbial functionality and engineer targeted metal-binding pathways. Multi-omics approaches provide a systems-level view of detoxification networks, revealing previously uncharacterized genes, enzymes, and metabolic signatures associated with HM tolerance and early biomarkers of sub-lethal stress. The incorporation of AI-based models introduces a data-driven dimension, enabling accurate prediction of remediation outcomes and optimization of vermiremediation strategies. Overall, this review advances vermiremediation from an empirical practice to a programmable, systems-biotechnology platform for sustainable HM bioremediation.

In this study, a bacterial strain of Micrococcus yunnanensis was isolated from the discharge water of an organized industrial zone wastewater treatment plant and used in the bioremoval of Al, Ni, and As. The effects of different experimental conditions such as initial metal concentration, pH, temperature, contact time, and biomass concentration on metal bioremoval were evaluated, and peak removal conditions were identified. The highest removal rates were 80, 68, and 27.33% for Al, Ni, and As, respectively. The isotherm and kinetic results for all metals showed that they fit the non-linear Langmuir and pseudo-second-order models, respectively. Ten representative machine-learning algorithms from linear, tree-based, ensemble, kernel, instance-based, and neural-network approaches were comparatively evaluated using a combined multi-metal dataset. The Extra Trees model was found to exhibit the best generalization performance (CV R² = 0.948; test R² = 0.941; RMSE = 5.98; and MAE = 4.553). To improve the interpretability of the results, SHAP analysis was performed, and the most important parameters were identified as metal type, initial metal concentration, and contact time, respectively. Of the two different training strategies followed in our study, models trained with a complete metal dataset were shown to be more successful than models trained with subsets containing each metal separately. This study contributes to the growing application of explainable machine learning in bioremoval research by integrating an environmentally isolated M. yunnanensis strain with a unified multi-metal predictive framework for Ni, Al, and As bioremoval.

The environmental persistence of carbofuran, a potent methylcarbamate neurotoxin, necessitates the development of advanced biotechnological strategies to safeguard soil biodiversity. This study investigated the bioremediation potential of Bacillus paralicheniformis PPH2, a specialized symbiont isolated from a unique ecological niche, the gastrointestinal tract of the indigenous paddy field earthworm Glyphidrilus sp. Unlike traditional soil isolates, strain PPH2 exhibited superior metabolic resilience, growing on carbofuran as the sole carbon and energy source. Through Central Composite Design coupled with Response Surface Methodology, catabolic efficiency was optimized at pH 7.1, 34.7 °C, and 100 rpm, resulting in a validated degradation efficiency of 62.07 ± 1.12% within 120 h. LC–MS/MS analysis revealed the putative identification of carbofuran phenol (m/z 164.36) as the primary biotransformation intermediate, indicating that strain PPH2 likely initiates hydrolytic cleavage of the toxicophoric methylcarbamate ester bond. While the achieved biodegradation efficiency (62.07 ± 1.12%) in unsupplemented minimal medium remains modest compared to specialized multi-strain consortia, it provides substantial acute detoxification, demonstrated by a 1.66-fold reduction in 96-h acute lethality (LC₅₀ increasing from 5.458 to 9.061 mg a.i./kg) in the sentinel earthworm Eisenia fetida. Collectively, this study provides evidence supporting a potential strategy for improving soil health and safeguarding terrestrial ecosystems from pesticide-associated toxicity by bridging microbial kinetics, statistical optimisation, and quantitative ecotoxicology.

Acid mine drainage (AMD) is characterized by persistent acidity, high sulfate and dissolved metal concentrations. Sulfate-reducing bacteria (SRB) are attractive candidates for AMD remediation because dissimilatory sulfate reduction generates alkalinity while producing sulfide that can facilitate metal removal through precipitation. Extending these processes to acidic conditions has increased interest in acidophilic and acid-tolerant SRB (aSRB and atSRB), yet evidence from cultivation, molecular surveys and treatment systems has often been interpreted separately. This systematic review synthesized 53 culture-dependent, culture-independent, and treatment system studies from 2014 to 2024 to examine relationships among taxonomic occurrence, physiological capability, demonstrated low-pH sulfate reduction and treatment performance. Phylogenetic analysis showed that low-pH sulfate-reducing phenotypes were distributed across multiple lineages and 16S rRNA relatedness alone did not predict acid tolerance. Desulfosporosinus was the most consistently represented genus across studies, although its recurrence was influenced by cultivation strategies. Sulfate reduction was demonstrated below pH 3, with sustained low-pH activity most strongly supported by controlled reactor studies; approximately pH 4.0–5.5 emerged as a comparatively well-supported range, while activity at lower pH was more dependent on microbial physiology and experimental conditions. Low-pH sulfate reduction also emerged as a community-level process shaped by electron-donor use, metabolite turnover and complementary microbial functions, while treatment performance additionally depended on biomass retention, hydraulic conditions and sulfide management. The reviewed studies support a distinction between taxonomic presence, demonstrated activity and treatment contribution. Future work should prioritize standardized reporting of active sulfate-reduction conditions, stronger taxon-function validation and long-term field testing of low-pH sulfidogenic systems.

Reliable candidate indicators of recovery following petroleum contamination remain limited, as remediation success is commonly assessed using hydrocarbon removal alone rather than restoration of soil characteristics. This study integrated physicochemical profiling with untargeted liquid chromatography-mass spectrometry (LC–MS) metabolomics to resolve biochemical recovery trajectories across polluted soil (PS), soil undergoing bioremediation (UB), bioremediated soil (BS), and uncontaminated reference soil (CNTR) in Ogoniland, Nigeria. Total petroleum hydrocarbon (TPH) concentrations decreased progressively from 78.26 ± 6.04 mg/kg in PS to 41.23 ± 1.40 mg/kg in UB and 23.38 ± 1.81 mg/kg in BS, corresponding to an overall 70.1% reduction in BS relative to the PS. Sulphur decreased from 6.36 ± 0.70 wt% to 0.152 ± 0.052 wt%, whereas phosphorus increased from 0.068 ± 0.006 wt% to 0.325 ± 0.025 wt% after remediation. Principal component analysis of physicochemical variables explained 99.3% of total variance and resolved a directional restoration gradient (PS → UB → BS → CNTR). Untargeted metabolomics similarly separated treatment states, with PCA explaining 73.7% of total biochemical variance. Polluted and transitional soils were enriched in aromatic stress metabolites, including fluorene, triphenylphosphine oxide, quinolinic acid, and 2,4-dinitrophenol, whereas remediated soils accumulated recovery-associated metabolites such as citric acid, aconitic acid, ectoine, pyridoxamine, lipoic acid, and geranic acid. Integrated analyses showed strong positive correlations between TPH and fluorene (r = 0.88) and Triphenylphosphine oxide (TPPO) (r = 0.84), but negative correlations with citric acid (r = −0.82) and pyridoxamine (r = −0.78). These results demonstrate that hydrocarbon attenuation is tightly coupled to coordinated metabolic reprogramming and nutrient restoration. Functional metabolite signatures may provide a framework for the assessment of biochemical changes associated with soil recovery following petroleum contamination. Thus, our study demonstrates coordinated physicochemical and metabolomic shifts associated with soil recovery during bioremediation.