A mechanistic classification framework for RT-qPCR inhibitors in wastewater-based epidemiology

Reverse transcription quantitative PCR (RT-qPCR) is widely used in wastewater-based epidemiology (WBE) but is frequently compromised by matrix-associated inhibition. While mitigation strategies abound, a systematic framework for diagnosing RT-qPCR inhibition in wastewater remains lacking. Here, a mechanistic classification framework for RT-qPCR inhibitors in wastewater is established based on two orthogonal dimensions: kinetic effect (linear vs. exponential inhibition) and molecular target (nucleic acid sequestrators vs. enzyme activity inhibitors). This framework enables diagnosis of the dominant inhibitor types in a given sample and predicts the efficacy of mitigation strategies. Guided by this framework, the following findings are demonstrated: (1) sample dilution effectively relieves enzyme activity inhibition but fails to address nucleic acid sequestrators; (2) two-step RT-qPCR-by decoupling reverse transcription and PCR amplification-effectively circumvents RT-qPCR inhibition under the tested conditions. Notably, supplementation with T4 gene 32 protein (gp32), a single-stranded DNA-binding protein predicted by the framework to selectively relieve RNA sequestrators, did not produce consistent improvement across wastewater samples-a result that, within the diagnostic logic of the framework, implicates enzyme inhibitors as the predominant inhibitory species in our sample set. The deinhibition rate, introduced here as a quantitative metric, varied predictably with wastewater characteristics, extraction method, and target RNA concentration, with high-abundance RNA viruses showing disproportionately stronger effects. These findings provide a theoretical foundation and practical guidance for improving the accuracy and reliability of RT-qPCR-based wastewater surveillance.