Insights into kinetic and regression models developed to estimate the abundance of antibiotic-resistant genes during biological digestion of wastewater sludge

Abstract

Wastewater treatment plants are hubs of antibiotic-resistant genes (ARGs). During wastewater treatment, ARGs accumulate in wastewater sludge and some survive biological digestion. After land application of digested sludge, ARGs are transported to soil, water, and air, and may encounter humans and animals. ARGs are typically quantified by quantitative polymerase chain reaction (qPCR) on isolated DNA. Nevertheless, DNA isolation and qPCR are time-consuming, expensive, and prone to contamination. Therefore, there is a need to estimate ARGs quantities via methods that can be readily employed. Such estimation would help to protect public health via modifying biological digestion to maximize the removal of ARGs. Two approaches that make such estimation are kinetic and regression modeling. The kinetic models have been mainly of the first order. This review examines the application of the kinetic models to estimate the abundance of ARGs during biological sludge digestion. It also discusses how biological sludge digesters can be designed using kinetic models. The literature provides single and multiple regression models, from which an ARGs -Solids -Nutrients nexus, a focal point of this review, is inferred. This review demonstrates that regression models are mathematical expressions of that nexus. Also, existing challenges are highlighted and suggestions for future are provided.