Side effects of the addition of an adsorbent for the nitrification performance of a microbiome in the treatment of an antibiotic mixture

An enzymatically modified adsorbent derived from an agro-residue mitigates the environmental risks of toxic antibiotic mixtures

This study developed an enzymatically modified adsorbent derived from pine bark (PBEM), an agricultural residue feedstock, for the adsorptive removal of antibiotic contaminants. PBEM was synthesized by optimizing the feedstock selection and modifying it using fungal crude enzymes sustainable recoverable from natural sources. PBEM rapidly removed the antibiotics tetracycline and sulfamethoxazole from a mixed solution much more rapidly (4-99 times faster) and in higher quantities (2-5 times higher) than without enzyme modification. The outperforming removal performance was validated using adsorption kinetics and isotherm parameters over five repeated cycles. Analytical chemistry identified four novel byproducts (BPs) generated in the antibiotic mixture. Quantitative structure-activity relationship analysis revealed that two of these BPs with considerable toxicity potential comparable to the parent compounds, but they were transient and eventually removed using PBEM. As a result, PBEM effectively controlled the toxic effects of the original antibiotics and their BPs much more rapidly than the control adsorbent with no enzyme coating, as illustrated by experimental antimicrobial toxicity testing. These results thus demonstrate the potential of PBEM for both removing various antibiotic residuals via physicochemical adsorption and enzymatic breakdown and completely detoxifying solutions containing antibiotics and their BPs.

A metagenome-derived artificial intelligence modeling framework advances the predictive diagnosis and interpretation of petroleum-polluted groundwater

Groundwater (GW) quality monitoring is vital for sustainable water resource management. The present study introduced a metagenome-derived machine learning (ML) model aimed at enhancing the predictive understanding and diagnostic interpretation of GW pollution associated with petroleum. In this framework, taxonomic and metabolic profiles derived from GW metagenomes were combined for use as the input dataset. By employing strategies that optimized data integration, model selection, and parameter tuning, we achieved a significant increase in diagnostic accuracy for petroleum-polluted GW. Explanatory artificial intelligence techniques identified petroleum degradation pathways and Rhodocyclaceae as strong predictors of a pollution diagnosis. Metagenomic analysis corroborated the presence of gene operons encoding aminobenzoate and xylene biodegradation within the de novo assembled genome of Rhodocyclaceae. Our genome-centric metagenomic analysis thus clarified the ecological interactions associated with microbiomes in breaking down petroleum contaminants, validating the ML-based diagnostic results. This metagenome-derived ML framework not only enhances the predictive diagnosis of petroleum pollution but also offers interpretable insights into the interaction between microbiomes and petroleum. The proposed ML framework demonstrates great promise for use as a science-based strategy for the on-site monitoring and remediation of GW pollution.

Environmental consequences of transformation products from an antibiotic mixture and their mitigation in a wastewater microbiome using an HCl-modified adsorbent

This study enhanced our understanding of antibiotic mixtures' occurrence, transformation, toxicity, and ecological risks. The role of acid-modified biochar (BC) in treating antibiotic residues was explored, shedding light on how BC influences the fate, mobility, and environmental impact of antibiotics and transformation products (TPs) in an activated sludge (AS) microbiome. A mixture of oxytetracycline and sulfamethoxazole was found to synergistically (or additively) inhibit cell growth of AS and disrupt the microbiome structure, species richness/diversity, and function. The formation of TPs with potentially higher toxicity and persistence than the original compounds was identified, explaining the microbiome disruption. Agricultural waste-derived BC was optimized for contaminant adsorption, leading to a reduction in toxicity when added to AS by sequestering TPs on its surface. This work highlighted adsorbents as a practical engineering strategy for mitigating liquid-phase contaminants' toxicological consequences, proactively controlling the fate and effects of antibiotics and TPs.