LAUSR

Current studies have identified gut microbial signatures of host health using high-throughput sequencing (HTS) techniques. However, HTS is still expensive and time-consuming and requires a high technical ability, thereby impeding its application in routine monitoring in aquaculture. Hence, it is necessary to seek an alternative strategy to overcome these shortcomings. Herein, we establish a qPCR-based approach to detect the relative abundances of gut disease-discriminatory phyla, which in turn afford independent variables to quantitatively determine the incidence and onset of shrimp disease. Notably, there is a high consistency between the accuracies of disease diagnosis achieved by qPCR and HTS. This applicable technique makes important progress toward defining a diseased state in shrimp and toward solving an important animal health management-driven economic problem. ABSTRACT There is evidence that gut microbial signatures are indicative of host health status. However, few efforts have been devoted to establishing an applicable technique for determining disease incidence by using gut microbial signatures. Herein, we established a quantitative PCR (qPCR)-based approach to detect the relative abundances of gut disease-discriminatory phyla, which in turn afforded independent variables for quantitatively determining the incidence of shrimp disease. Given the temporal dynamics of gut bacterial communities as healthy shrimp aged, we identified disease-discriminatory phyla after ruling out age-discriminatory phyla. The top 10 disease-discriminatory phyla contributed to an overall 93.2% accuracy in diagnosis (n = 103 samples from shrimp that were determined with high confidence to be healthy or that exhibited apparent disease symptoms and subsequent death), with 70% diagnosis accuracy at the disease onset stage, when symptoms or signs of disease were not apparent. 16S rRNA gene-targeted group-specific primers of five disease-discriminatory phyla were then designed according to their compositions within shrimp gut microbiota, and other primers were borrowed from previous studies. The relative abundances of the 10 disease-discriminatory phyla assayed by qPCR exhibited a high consistency (r = 0.946, P < 0.001) with those detected by Illumina sequencing. Notably, using the profiles of disease-discriminatory phyla assayed by qPCR and the corresponding weight coefficients as independent variables, we were able to accurately estimate the incidences of future disease outcome. This work establishes an applicable technique to quantitatively determine the incidence and onset of shrimp disease, which is a valuable attempt to translate scientific research into a practical application. IMPORTANCE Current studies have identified gut microbial signatures of host health using high-throughput sequencing (HTS) techniques. However, HTS is still expensive and time-consuming and requires a high technical ability, thereby impeding its application in routine monitoring in aquaculture. Hence, it is necessary to seek an alternative strategy to overcome these shortcomings. Herein, we establish a qPCR-based approach to detect the relative abundances of gut disease-discriminatory phyla, which in turn afford independent variables to quantitatively determine the incidence and onset of shrimp disease. Notably, there is a high consistency between the accuracies of disease diagnosis achieved by qPCR and HTS. This applicable technique makes important progress toward defining a diseased state in shrimp and toward solving an important animal health management-driven economic problem.