Bridging disciplines towards wastewater-based surveillance of antimicrobial resistance: frequency, local dynamics, and genomic characteristics of carbapenemase-producing Klebsiella pneumoniae

Abstract

The World Health Organization (WHO) has designated carbapenemase-producing Klebsiella pneumoniae (CP-KP) as a critical priority pathogen due to its increasing importance for human health. As wastewater-based surveillance (WBS) is discussed as a complementary tool for classical systems regarding hazard forecasting and early-warning, we designed a "wet-lab to genomics" workflow to target CP-KP in raw influent wastewater samples to support method development processes across different scientific disciplines. The CP-KP screening workflow was set up based on membrane filtration, selective chromogenic media for selective cultivation and the modified carbapenem inactivation method (mCIM) for confirming carbapenemase-production using 33 samples from four different wastewater treatment plants in North-Eastern Germany. All samples tested positive for CP-KP, with concentrations ranging between 102 and 104 colony-forming units (cfu) per 100 ml across the sample set. As a result, 320 isolates belonged to the Klebsiella, Enterobacter, Citrobacter (KEC)- group, with the majority being identified as KP (n= 297; 93%), including n= 253 (79%) verified CP-KP. Genotypic characterization of CP-KP by PCR revealed the predominance of blaOXA-48-related genes (n= 83) among isolates from all WWTPs. As quality parameters, colony counts for viable Escherichia coli (EC) were employed as a proxy for valid wastewater samples and extended-spectrum beta-lactamase-producing E. coli (ESBL-EC) as indicator for AMR, with cfu/100 ml ranges from 10 to 10 and 102 to 10, respectively. To verify the screening outcome, a subset of 58 CP-KP from two WWTPs were subjected to whole genome sequencing (WGS). As a result, eight different sequence types (STs), i.e., ST147 and ST273 (both: clonal group 147), ST258, ST35, ST15, ST37, ST307, and ST485 were identified. These include clinically relevant STs clustering closest with fecal isolates from Germany when compared with Pathogenwatch-database entries. Moreover, WGS data enabled the identification of antibiotic resistance genes (ARGs), and the detection of closely related isolates within the WWTP dataset.