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MBPD: A multiple bacterial pathogen detection pipeline for One Health practices

iMeta2023Vol. 2(1), pp. e82–e82

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Xinrun Yang, Gaofei Jiang, Yaozhong Zhang, Ningqi Wang, Yuling Zhang, Xiaofang Wang, Fang‐Jie Zhao, Yangchun Xu, Qirong Shen, Zhong Wei

Abstract

Bacterial pathogens are one of the major threats to biosafety and environmental health, and advanced assessment is a prerequisite to combating bacterial pathogens. Currently, 16S rRNA gene sequencing is efficient in the open-view detection of bacterial pathogens. However, the taxonomic resolution and applicability of this method are limited by the domain-specific pathogen database, taxonomic profiling method, and sequencing target of 16S variable regions. Here, we present a pipeline of multiple bacterial pathogen detection (MBPD) to identify the animal, plant, and zoonotic pathogens. MBPD is based on a large, curated database of the full-length 16S genes of 1986 reported bacterial pathogen species covering 72,685 sequences. In silico comparison allowed MBPD to provide the appropriate similarity threshold for both full-length and variable-region sequencing platforms, while the subregion of V3-V4 (mean: 88.37%, accuracy rate compared to V1-V9) outperformed other variable regions in pathogen identification compared to full-length sequencing. Benchmarking on real data sets suggested the superiority of MBPD in a broader range of pathogen detections compared with other methods, including 16SPIP and MIP. Beyond detecting the known causal agent of animal, human, and plant diseases, MBPD is capable of identifying cocontaminating pathogens from biological and environmental samples. Overall, we provide a MBPD pipeline for agricultural, veterinary, medical, and environmental monitoring to achieve One Health.

Citations Over TimeTop 1% of 2023 papers

Abstract

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