Development of non-linear empirical models to estimate the abundance of carbapenem resistance genes during anaerobic digestion of wastewater sludge at mesophilic and thermophilic temperatures

Abstract

Antibiotic resistance genes (ARGs) encode resistance against antibiotic drugs in bacteria. Carbapenem antibiotics are one of the last lines of defence against bacterial infections and carbapenem resistance genes (CRGs) accumulate in sludge during wastewater treatment. Anaerobic digestion is the most used method for sludge treatment, and it is important to know the abundance and removal of CRGs in anaerobically digested sludge before land application due to their public health relevance. However, gene quantification is time-consuming, costly, and sensitive to contamination. Previous research indicates a nexus between ARGs, solids, and nutrients in sludge. This study aimed to develop multiple regression models to estimate the abundance of CRGs from solids and nutrient concentrations in sludge, which are routinely measured for the monitoring and design of anaerobic digesters. Batch and continuous reactors were operated at mesophilic and thermophilic temperatures. Sludge samples were taken during digestion. CRGs (blaGES, blaOXA-48 and blaIMP-27), 16S rRNA and integron class 1 were quantified. Solids, chemical oxygen demand, orthophosphate and ammonia were measured as well. Anaerobic digestion reduced the quantity of the genes. First and second-order Kinetic rate constants (K1 and K2) were affected by temperature, and K1 absolute value followed the order blaOXA-48 > blaGES > Int 1. Multiple regression modelling was conducted in linear (LM) and non-linear (NLM) modes. This study presents the first NLM models to simulate the quantities of CRGs during anaerobic digestion of wastewater sludge at mesophilic and thermophilic temperatures. Adjusted R2 ranged 0.352–0.988 and 0.916–0.996 for the LM and NLM models, respectively. NLM models estimated the gene abundance more accurately than LM models, and they may be useful for researchers and practitioners to estimate the removal rate of target genes under different operational conditions.