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Lin Y, Zhang Y, Sun H, Jiang H, Zhao X, Teng X, Lin J, Shu B, Sun H, Liao Y, Zhou J. NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing. Brief Bioinform 2023; 25:bbad499. [PMID: 38189540 PMCID: PMC10772945 DOI: 10.1093/bib/bbad499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 11/21/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024] Open
Abstract
Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequencing. We present a deep learning framework, NanoDeep, to overcome these limitations by incorporating convolutional neural network and squeeze and excitation. We first showed that the raw squiggle derived from native DNA sequences determines the origin of microbial and human genomes. Then, we demonstrated that NanoDeep successfully classified bacterial reads from the pooled library with human sequence and showed enrichment for bacterial sequence compared with routine nanopore sequencing setting. Further, we showed that NanoDeep improves the sequencing efficiency and preserves the fidelity of bacterial genomes in the mock sample. In addition, NanoDeep performs well in the enrichment of metagenome sequences of gut samples, showing its potential applications in the enrichment of unknown microbiota. Our toolkit is available at https://github.com/lysovosyl/NanoDeep.
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Affiliation(s)
- Yusen Lin
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Yongjun Zhang
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Hang Sun
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Hang Jiang
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Xing Zhao
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
- Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
| | - Xiaojuan Teng
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Jingxia Lin
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Bowen Shu
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Hao Sun
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
- Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
| | - Yuhui Liao
- Dermatology Hospital, Southern Medical University, Guangzhou, China
| | - Jiajian Zhou
- Dermatology Hospital, Southern Medical University, Guangzhou, China
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Fu S, Zhang Y, Wang R, Qiu Z, Song W, Yang Q, Shen L. A novel culture-enriched metagenomic sequencing strategy effectively guarantee the microbial safety of drinking water by uncovering the low abundance pathogens. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 345:118737. [PMID: 37657296 DOI: 10.1016/j.jenvman.2023.118737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/21/2023] [Accepted: 07/31/2023] [Indexed: 09/03/2023]
Abstract
Assessing the presence of waterborne pathogens and antibiotic resistance genes (ARGs) is crucial for managing the environmental quality of drinking water sources. However, detecting low abundance pathogens in such settings is challenging. In this study, a workflow was developed to enrich for broad spectrum pathogens from drinking water samples. A mock community was used to evaluate the effectiveness of various enrichment broths in detecting low-abundance pathogens. Monthly metagenomic surveillance was conducted in a drinking water source from May to September 2021, and water samples were subjected to five enrichment procedures for 6 h to recover the majority of waterborne bacterial pathogens. Oxford Nanopore Technology (ONT) was used for metagenomic sequencing of enriched samples to obtain high-quality pathogen genomes. The results showed that selective enrichment significantly increased the proportions of targeted bacterial pathogens. Compared to direct metagenomic sequencing of untreated water samples, targeted enrichment followed by ONT sequencing significantly improved the detection of waterborne pathogens and the quality of metagenome-assembled genomes (MAGs). Eighty-six high-quality MAGs, including 70 pathogen MAGs, were obtained from ONT sequencing, while only 12 MAGs representing 10 species were obtained from direct metagenomic sequencing of untreated water samples. In addition, ONT sequencing improved the recovery of mobile genetic elements and the accuracy of phylogenetic analysis. This study highlights the urgent need for efficient methodologies to detect and manage microbial risks in drinking water sources. The developed workflow provides a cost-effective approach for environmental management of drinking water sources with microbial risks. The study also uncovered pathogens that were not detected by traditional methods, thereby advancing microbial risk management of drinking water sources.
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Affiliation(s)
- Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, 710069, China; Key Laboratory of Environment Controlled Aquaculture (Dalian Ocean University), Ministry of Education, 116023, China.
| | - Yixiang Zhang
- CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences. Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Rui Wang
- Key Laboratory of Environment Controlled Aquaculture (Dalian Ocean University), Ministry of Education, 116023, China
| | - Zhiguang Qiu
- School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Weizhi Song
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, SAR, Hong Kong, China
| | - Qian Yang
- Center for Microbial Ecology and Technology, Ghent University, Ghent, Belgium
| | - Lixin Shen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, 710069, China.
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Rosenzweig AF, Burian J, Brady SF. Present and future outlooks on environmental DNA-based methods for antibiotic discovery. Curr Opin Microbiol 2023; 75:102335. [PMID: 37327680 PMCID: PMC11076179 DOI: 10.1016/j.mib.2023.102335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 04/28/2023] [Accepted: 05/17/2023] [Indexed: 06/18/2023]
Abstract
Novel antibiotics are in constant demand to combat a global increase in antibiotic-resistant infections. Bacterial natural products have been a long-standing source of antibiotic compounds, and metagenomic mining of environmental DNA (eDNA) has increasingly provided new antibiotic leads. The metagenomic small-molecule discovery pipeline can be divided into three main steps: surveying eDNA, retrieving a sequence of interest, and accessing the encoded natural product. Improvements in sequencing technology, bioinformatic algorithms, and methods for converting biosynthetic gene clusters into small molecules are steadily increasing our ability to discover metagenomically encoded antibiotics. We predict that, over the next decade, ongoing technological improvements will dramatically increase the rate at which antibiotics are discovered from metagenomes.
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Affiliation(s)
- Adam F Rosenzweig
- Laboratory of Genetically Encoded Small Molecules, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA
| | - Ján Burian
- Laboratory of Genetically Encoded Small Molecules, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA
| | - Sean F Brady
- Laboratory of Genetically Encoded Small Molecules, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA.
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