Metagenomics is a powerful tool to identify novel or unexpected pathogens, since it is generic and relatively unbiased. The limit of detection (LOD) is a critical parameter for the routine application of methods in the clinical diagnostic context. Although attempts for the determination of LODs for metagenomics next-generation sequencing (mNGS) have been made previously, these were only applicable for specific target species in defined samples matrices. Therefore, we developed and validated a generalized probability-based model to assess the sample-specific LOD of mNGS experiments (LOD mNGS ). Initial rarefaction analyses with datasets of Borna disease virus 1 human encephalitis cases revealed a stochastic behavior of virus read detection. Based on this, we transformed the Bernoulli formula to predict the minimal necessary dataset size to detect one virus read with a probability of 99%. We validated the formula with 30 datasets from diseased individuals, resulting in an accuracy of 99.1% and an average of 4.5 ± 0.4 viral reads found in the calculated minimal dataset size. We demonstrated by modeling the virus genome size, virus-, and total RNA-concentration that the main determinant of mNGS sensitivity is the virus-sample background ratio. The predicted LOD mNGS for the respective pathogenic virus in the datasets were congruent with the virus-concentration determined by RT-qPCR. Theoretical assumptions were further confirmed by correlation analysis of mNGS and RT-qPCR data from the samples of the analyzed datasets. This approach should guide standardization of mNGS application, due to the generalized concept of LOD mNGS .
【저자키워드】 sensitivity, qPCR, Next-generation sequencing, metagenomics, Detection limit, Bernoulli process, 【초록키워드】 diagnostic, virus, Encephalitis, Probability, RT-qPCR, Accuracy, limit of detection, Pathogens, dataset, experiment, Critical, predict, Analysis, Standardization, Correlation analysis, average, powerful tool, assumption, datasets, parameter, virus genome, pathogenic virus, approach, defined, resulting, predicted, analyzed, identify, detect, calculated, demonstrated, individuals, Borna disease virus, viral read, 【제목키워드】 limit of detection, approach,