Fate of antibiotic resistance genes and class 1 integrons during sludge treatment using pilot-scale anaerobic digestion with thermal hydrolysis pretreatment

Leveraging machine learning for prediction of antibiotic resistance genes post thermal hydrolysis-anaerobic digestion in dairy waste

Anaerobic digestion holds promise as a method for removing antibiotic resistance genes (ARGs) from dairy waste. However, accurately predicting the efficiency of ARG removal remains a challenge. This study introduces a novel appproach utilizing machine learning to forecast changes in ARG abundances following thermal hydrolysis-anaerobic digestion (TH-AD) treatment. Through network analysis and redundancy analyses, key determinants of affect ARG fluctuations were identified, facilitating the development of machine learning models capable of accurately predicting ARG changes during TH-AD processes. The decision tree model demonstrated impressive predictive power, achieving an impessive R2 value of 87% against validation data. Feature analysis revealed that the genes intI2 and intI1 had a critical impact on the absolute abundance of ARGs. The predictive model developed in this study offers valuable insights for improving operational and managerial practices in dairy waste treatment facilities, with the ultimate goal of mitigating the spread of antibiotic resistance.

Effect of reactor operation modes on mitigating antibiotic resistance genes (ARGs) and methane production from hydrothermally-pretreated pig manure

Numerous efforts have been made to enhance the performance of anaerobic digestion (AD) for accelerating renewable energy generation, however, it remains unclear whether the intensified measures could enhance the proliferation and transmissions of antibiotic resistance genes (ARGs) in the system. This study assessed the impact of an innovative pig manure AD process, which includes hydrothermal pretreatment (HTP) and a two-stage configuration with separated acidogenic and methanogenic phases, on biomethane (CH4) production and ARGs dynamics. Results showed that HTP significantly increase CH4 production from 0.65 to 0.75 L/L/d in conventional single-stage AD to 0.82 and 0.91 L/L/d in two-stage AD. This improvement correlated with a rise in the relative abundance of Methanosarcina, a key methanogenesis microorganism. In the two-stage AD, the methanogenic stage offered an ideal environment for methanogens growth, resulting in substantially faster and higher CH4 production by about 10% compared to single-stage AD. Overall, the combined use of HTP and the two-stage AD configuration enhanced CH4 production by 40% compared to traditional single-stage AD. The abundance and diversity of ARGs were significantly reduced in the acidogenic reactors after HTP. However, the ARGs levels increased by about two times in the following methanogenesis stage and reached similar or higher levels than in single stage AD. The erm(F), erm(G), ant(6)-Ia, tet(W), mef(A) and erm(B) were the six main ARGs with significant differences in relative abundances in various treatments. The two-stage AD mode could better remove sul2, but it also had a rebound which elevated the risk of ARGs to the environment and human health. Network analysis identified pH and TVFAs as critical factors driving microbial communities and ARG proliferation in the new AD process. With the results, this study offers valuable insights into the trade-offs between AD performance enhancement and ARG-related risks, pinpointing essential areas for future research and practical improvements.

Performance of sewage sludge treatment for the removal of antibiotic resistance genes: Status and prospects

Wastewater treatment plants (WWTPs) receive wastewater containing antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs), which are predominant contributors to environmental pollution in water and soil. Of these sources, sludge is a more significant contributor than effluent. Knowing how sludge treatment affects the fate of ARGs is vital for managing the risk of these genes in both human and natural environments. This review therefore discusses the sources and transmission of ARGs in the environment and highlights the risks of ARGs in sludge. The effects of co-existing constituents (heavy metals, microplastics, etc.) on sludge and ARGs during treatment are collated to highlight the difficulty of treating sludge with complex constituents in ARGs. The effects of various sludge treatment methods on the abundances of ARGs in sludge and in soil from land application of treated sludge are discussed, pointing out that the choice of sludge treatment method should take into account various potential factors, such as soil and soil biology in subsequent land application. This review offers significant insights and explores the abundances of ARGs throughout the process of sludge treatment and disposal. Unintentional addition of antibiotic residues, heavy metals, microplastics and organic matter in sludge could significantly increase the abundance and reduce the removal efficiency of ARGs during treatment, which undoubtedly adds a barrier to the removal of ARGs from sludge treatment. The complexity of the sludge composition and the diversities of ARGs have led to the fact that no effective sludge treatment method has so far been able to completely eliminate the ecological risk of ARGs. In order to reduce risks resulting by transmission of ARGs, technical and management measures need to be implemented.