MBPD: A multiple bacterial pathogen detection pipeline for One Health practices. Issue 1 (31st January 2023)

• Record Type: Journal Article
• Authors: Yang, Xinrun; Jiang, Gaofei; Zhang, Yaozhong; Wang, Ningqi; Zhang, Yuling; Wang, Xiaofang; Zhao, Fang‐Jie; Xu, Yangchun; Shen, Qirong; Wei, Zhong
• Is Part Of: IMeta. Volume 2:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-31
• Subjects: bacterial pathogen detection -- 16S rRNA gene sequencing -- One Health; Metagenomics -- Periodicals; Bioinformatics -- Periodicals; Bioinformatics; Metagenomics; Metagenomics; Metagenome; Computational Biology; Periodicals; Periodical; 576.5
• DOI: 10.1002/imt2.82
• Languages: English
• ISSNs: 2770-596X

Abstract

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. Abstract : Multiple bacterial pathogen detection (MBPD) provides the accurate and comprehensive detection of bacterial pathogens from biological and environmental samples based on 16S rRNA gene sequencing. By constructing a relatively complete database of 72, 685 sequences for wide identification across a broad range of bacterial pathogens causing animal, plant, and zoonotic diseases, MBPD can provide the appropriate threshold for common variable regions of 16S rRNA gene in taxonomy alignment based on the recommendation of in silico experiment. MBPD is freely available at https://github.com/LorMeBioAI/MBPDLorMeBioAI/MBPD . Highlights: Multiple bacterial pathogen detection (MBPD) is a 16S‐based pipeline for detecting animal, plant, and zoonotic bacterial pathogens. The curated reference database of MBPD contains 72, 685 sequences from 1986 known pathogen species. MBPD provides appropriate thresholds for taxonomic profiling of common 16S variable regions. MBPD outperforms other methods in detecting both causal and coinfecting pathogens.