1
|
Yamaguchi M, Uchihashi T, Kawabata S. Hybrid sequence-based analysis reveals the distribution of bacterial species and genes in the oral microbiome at a high resolution. Biochem Biophys Rep 2024; 38:101717. [PMID: 38708423 PMCID: PMC11066573 DOI: 10.1016/j.bbrep.2024.101717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/14/2024] [Accepted: 04/19/2024] [Indexed: 05/07/2024] Open
Abstract
Bacteria in the oral microbiome are poorly identified owing to the lack of established culture methods for them. Thus, this study aimed to use culture-free analysis techniques, including bacterial single-cell genome sequencing, to identify bacterial species and investigate gene distribution in saliva. Saliva samples from the same individual were classified as inactivated or viable and then analyzed using 16S rRNA sequencing, metagenomic shotgun sequencing, and bacterial single-cell sequencing. The results of 16S rRNA sequencing revealed similar microbiota structures in both samples, with Streptococcus being the predominant genus. Metagenomic shotgun sequencing showed that approximately 80 % of the DNA in the samples was of non-bacterial origin, whereas single-cell sequencing showed an average contamination rate of 10.4 % per genome. Single-cell sequencing also yielded genome sequences for 43 out of 48 wells for the inactivated samples and 45 out of 48 wells for the viable samples. With respect to resistance genes, four out of 88 isolates carried cfxA, which encodes a β-lactamase, and four isolates carried erythromycin resistance genes. Tetracycline resistance genes were found in nine bacteria. Metagenomic shotgun sequencing provided complete sequences of cfxA, ermF, and ermX, whereas other resistance genes, such as tetQ and tetM, were detected as fragments. In addition, virulence factors from Streptococcus pneumoniae were the most common, with 13 genes detected. Our average nucleotide identity analysis also suggested five single-cell-isolated bacteria as potential novel species. These data would contribute to expanding the oral microbiome data resource.
Collapse
Affiliation(s)
- Masaya Yamaguchi
- Bioinformatics Research Unit, Osaka University Graduate School of Dentistry, Suita, Osaka, Japan
- Department of Microbiology, Osaka University Graduate School of Dentistry, Suita, Osaka, Japan
- Bioinformatics Center, Research Institute for Microbial Diseases, Osaka University, Japan
- Center for Infectious Diseases Education and Research, Osaka University, Japan
| | - Toshihiro Uchihashi
- Department of Oral and Maxillofacial Surgery, Osaka University Graduate School of Dentistry, Suita, Osaka, Japan
| | - Shigetada Kawabata
- Department of Microbiology, Osaka University Graduate School of Dentistry, Suita, Osaka, Japan
- Center for Infectious Diseases Education and Research, Osaka University, Japan
| |
Collapse
|
2
|
Wang YC, Fu HM, Shen Y, Wang J, Wang N, Chen YP, Yan P. Biosynthetic potential of uncultured anammox community bacteria revealed through multi-omics analysis. BIORESOURCE TECHNOLOGY 2024; 401:130740. [PMID: 38677385 DOI: 10.1016/j.biortech.2024.130740] [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: 01/29/2024] [Revised: 03/11/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024]
Abstract
Microbial secondary metabolites (SMs) and their derivatives have been widely used in medicine, agriculture, and energy. Growing needs for renewable energy and the challenges posed by antibiotic resistance, cancer, and pesticides emphasize the crucial hunt for new SMs. Anaerobic ammonium-oxidation (anammox) systems harbor many uncultured or underexplored bacteria, representing potential resources for discovering novel SMs. Leveraging HiFi long-read metagenomic sequencing, 1,040 biosynthetic gene clusters (BGCs) were unearthed from the anammox microbiome with 58% being complete and showcasing rich diversity. Most of them showed distant relations to known BGCs, implying novelty. Members of the underexplored lineages (Chloroflexota and Planctomycetota) and Proteobacteria contained lots of BGCs, showcasing substantial biosynthetic potential. Metaproteomic results indicated that Planctomycetota members harbored the most active BGCs, particularly those involved in producing potential biofuel-ladderane. Overall, these findings underscore that anammox microbiomes could serve as valuable resources for mining novel BGCs and discovering new SMs for practical application.
Collapse
Affiliation(s)
- Yi-Cheng Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Hui-Min Fu
- National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing 400067, China
| | - Yu Shen
- National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing 400067, China
| | - Jin Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Nuo Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - You-Peng Chen
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Peng Yan
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China.
| |
Collapse
|
3
|
Agustinho DP, Fu Y, Menon VK, Metcalf GA, Treangen TJ, Sedlazeck FJ. Unveiling microbial diversity: harnessing long-read sequencing technology. Nat Methods 2024; 21:954-966. [PMID: 38689099 DOI: 10.1038/s41592-024-02262-1] [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: 09/08/2022] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads. We provide insights into the advantages and disadvantages of long reads over short reads and their evolution from the early days of long-read sequencing to their recent impact on metagenomics and clinical diagnostics. We further point out remaining challenges for the field such as the integration of methylation signals in sub-strain analysis and the lack of benchmarks.
Collapse
Affiliation(s)
- Daniel P Agustinho
- Human Genome Sequencing center, Baylor College of Medicine, Houston, TX, USA
| | - Yilei Fu
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Vipin K Menon
- Human Genome Sequencing center, Baylor College of Medicine, Houston, TX, USA
- Senior research project manager, Human Genetics, Genentech, South San Francisco, CA, USA
| | - Ginger A Metcalf
- Human Genome Sequencing center, Baylor College of Medicine, Houston, TX, USA
| | - Todd J Treangen
- Department of Computer Science, Rice University, Houston, TX, USA
- Department of Bioengineering, Rice University, Houston, TX, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing center, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
| |
Collapse
|
4
|
Wang YC, Mao Y, Fu HM, Wang J, Weng X, Liu ZH, Xu XW, Yan P, Fang F, Guo JS, Shen Y, Chen YP. New insights into functional divergence and adaptive evolution of uncultured bacteria in anammox community by complete genome-centric analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171530. [PMID: 38453092 DOI: 10.1016/j.scitotenv.2024.171530] [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: 09/26/2023] [Revised: 11/13/2023] [Accepted: 03/04/2024] [Indexed: 03/09/2024]
Abstract
Anaerobic ammonium-oxidation (anammox) bacteria play a crucial role in global nitrogen cycling and wastewater nitrogen removal, but they share symbiotic relationships with various other microorganisms. Functional divergence and adaptive evolution of uncultured bacteria in anammox community remain underexplored. Although shotgun metagenomics based on short reads has been widely used in anammox research, metagenome-assembled genomes (MAGs) are often discontinuous and highly contaminated, which limits in-depth analyses of anammox communities. Here, for the first time, we performed Pacific Biosciences high-fidelity (HiFi) long-read sequencing on the anammox granule sludge sample from a lab-scale bioreactor, and obtained 30 accurate and complete metagenome-assembled genomes (cMAGs). These cMAGs were obtained by selecting high-quality circular contigs from initial assemblies of long reads generated by HiFi sequencing, eliminating the need for Illumina short reads, binning, and reassembly. One new anammox species affiliated with Candidatus Jettenia and three species affiliated with novel families were found in this anammox community. cMAG-centric analysis revealed functional divergence in general and nitrogen metabolism among the anammox community members, and they might adopt a cross-feeding strategy in organic matter, cofactors, and vitamins. Furthermore, we identified 63 mobile genetic elements (MGEs) and 50 putative horizontal gene transfer (HGT) events within these cMAGs. The results suggest that HGT events and MGEs related to phage and integration or excision, particularly transposons containing tnpA in anammox bacteria, might play important roles in the adaptive evolution of this anammox community. The cMAGs generated in the present study could be used to establish of a comprehensive database for anammox bacteria and associated microorganisms. These findings highlight the advantages of HiFi sequencing for the studies of complex mixed cultures and advance the understanding of anammox communities.
Collapse
Affiliation(s)
- Yi-Cheng Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Yanping Mao
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518071, Guangdong, China
| | - Hui-Min Fu
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China; National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing 400067, China
| | - Jin Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Xun Weng
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Zi-Hao Liu
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Xiao-Wei Xu
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Peng Yan
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Fang Fang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Jin-Song Guo
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China
| | - Yu Shen
- National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing 400067, China
| | - You-Peng Chen
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environments of MOE, Chongqing University, Chongqing 400045, China.
| |
Collapse
|
5
|
Feng X, Li H. Evaluating and improving the representation of bacterial contents in long-read metagenome assemblies. Genome Biol 2024; 25:92. [PMID: 38605401 PMCID: PMC11007910 DOI: 10.1186/s13059-024-03234-6] [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: 11/21/2022] [Accepted: 03/29/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND In the metagenomic assembly of a microbial community, abundant species are often thought to assemble well given their deeper sequencing coverage. This conjuncture is rarely tested or evaluated in practice. We often do not know how many abundant species are missing and do not have an approach to recover them. RESULTS Here, we propose k-mer based and 16S RNA based methods to measure the completeness of metagenome assembly. We show that even with PacBio high-fidelity (HiFi) reads, abundant species are often not assembled, as high strain diversity may lead to fragmented contigs. We develop a novel reference-free algorithm to recover abundant metagenome-assembled genomes (MAGs) by identifying circular assembly subgraphs. Complemented with a reference-free genome binning heuristics based on dimension reduction, the proposed method rescues many abundant species that would be missing with existing methods and produces competitive results compared to those state-of-the-art binners in terms of total number of near-complete genome bins. CONCLUSIONS Our work emphasizes the importance of metagenome completeness, which has often been overlooked. Our algorithm generates more circular MAGs and moves a step closer to the complete representation of microbial communities.
Collapse
Affiliation(s)
- Xiaowen Feng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, USA.
| |
Collapse
|
6
|
Long DR, Bryson-Cahn C, Waalkes A, Holmes EA, Penewit K, Tavolaro C, Bellabarba C, Zhang F, Chan JD, Fang FC, Lynch JB, Salipante SJ. Contribution of the patient microbiome to surgical site infection and antibiotic prophylaxis failure in spine surgery. Sci Transl Med 2024; 16:eadk8222. [PMID: 38598612 DOI: 10.1126/scitranslmed.adk8222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/18/2024] [Indexed: 04/12/2024]
Abstract
Despite modern antiseptic techniques, surgical site infection (SSI) remains a leading complication of surgery. However, the origins of SSI and the high rates of antimicrobial resistance observed in these infections are poorly understood. Using instrumented spine surgery as a model of clean (class I) skin incision, we prospectively sampled preoperative microbiomes and postoperative SSI isolates in a cohort of 204 patients. Combining multiple forms of genomic analysis, we correlated the identity, anatomic distribution, and antimicrobial resistance profiles of SSI pathogens with those of preoperative strains obtained from the patient skin microbiome. We found that 86% of SSIs, comprising a broad range of bacterial species, originated endogenously from preoperative strains, with no evidence of common source infection among a superset of 1610 patients. Most SSI isolates (59%) were resistant to the prophylactic antibiotic administered during surgery, and their resistance phenotypes correlated with the patient's preoperative resistome (P = 0.0002). These findings indicate the need for SSI prevention strategies tailored to the preoperative microbiome and resistome present in individual patients.
Collapse
Affiliation(s)
- Dustin R Long
- Division of Critical Care Medicine, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Chloe Bryson-Cahn
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Adam Waalkes
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Elizabeth A Holmes
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Kelsi Penewit
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Celeste Tavolaro
- Department of Orthopaedics and Sports Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Carlo Bellabarba
- Department of Orthopaedics and Sports Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Fangyi Zhang
- Department of Orthopaedics and Sports Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Jeannie D Chan
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Pharmacy, Harborview Medical Center, University of Washington School of Pharmacy, Seattle, WA 98104, USA
| | - Ferric C Fang
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Microbiology, University of Washington School of Medicine, Seattle, WA 98195, USA
- Clinical Microbiology Laboratory, Harborview Medical Center, Seattle, WA 98104, USA
| | - John B Lynch
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Stephen J Salipante
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| |
Collapse
|
7
|
Eisenhofer R, Nesme J, Santos-Bay L, Koziol A, Sørensen SJ, Alberdi A, Aizpurua O. A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics. Microbiol Spectr 2024; 12:e0359023. [PMID: 38451230 PMCID: PMC10986573 DOI: 10.1128/spectrum.03590-23] [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: 10/07/2023] [Accepted: 02/11/2024] [Indexed: 03/08/2024] Open
Abstract
Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.
Collapse
Affiliation(s)
- Raphael Eisenhofer
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Joseph Nesme
- Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Luisa Santos-Bay
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Adam Koziol
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Søren Johannes Sørensen
- Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Antton Alberdi
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Ostaizka Aizpurua
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
8
|
Cook R, Telatin A, Hsieh SY, Newberry F, Tariq MA, Baker DJ, Carding SR, Adriaenssens EM. Nanopore and Illumina sequencing reveal different viral populations from human gut samples. Microb Genom 2024; 10. [PMID: 38683195 DOI: 10.1099/mgen.0.001236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/01/2024] Open
Abstract
The advent of viral metagenomics, or viromics, has improved our knowledge and understanding of global viral diversity. High-throughput sequencing technologies enable explorations of the ecological roles, contributions to host metabolism, and the influence of viruses in various environments, including the human intestinal microbiome. However, bacterial metagenomic studies frequently have the advantage. The adoption of advanced technologies like long-read sequencing has the potential to be transformative in refining viromics and metagenomics. Here, we examined the effectiveness of long-read and hybrid sequencing by comparing Illumina short-read and Oxford Nanopore Technology (ONT) long-read sequencing technologies and different assembly strategies on recovering viral genomes from human faecal samples. Our findings showed that if a single sequencing technology is to be chosen for virome analysis, Illumina is preferable due to its superior ability to recover fully resolved viral genomes and minimise erroneous genomes. While ONT assemblies were effective in recovering viral diversity, the challenges related to input requirements and the necessity for amplification made it less ideal as a standalone solution. However, using a combined, hybrid approach enabled a more authentic representation of viral diversity to be obtained within samples.
Collapse
Affiliation(s)
- Ryan Cook
- Quadram Institute Bioscience, Norwich, NR4 7UQ, UK
| | | | | | - Fiona Newberry
- Department of Biosciences, Nottingham Trent University, Nottingham, NG11 8NS, UK
| | - Mohammad A Tariq
- Faculty of Health and Life Sciences, University of Northumbria, Newcastle upon Tyne, NE1 8ST, UK
| | - Dave J Baker
- Quadram Institute Bioscience, Norwich, NR4 7UQ, UK
| | - Simon R Carding
- Quadram Institute Bioscience, Norwich, NR4 7UQ, UK
- Norwich Medical School, University of East Anglia, Norwich, NR4 7TJ, UK
| | | |
Collapse
|
9
|
Yu W, Luo H, Yang J, Zhang S, Jiang H, Zhao X, Hui X, Sun D, Li L, Wei XQ, Lonardi S, Pan W. Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes. Genome Res 2024; 34:326-340. [PMID: 38428994 PMCID: PMC10984382 DOI: 10.1101/gr.278232.123] [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: 06/29/2023] [Accepted: 01/23/2024] [Indexed: 03/03/2024]
Abstract
Pacific Biosciences (PacBio) HiFi sequencing technology generates long reads (>10 kbp) with very high accuracy (<0.01% sequencing error). Although several de novo assembly tools are available for HiFi reads, there are no comprehensive studies on the evaluation of these assemblers. We evaluated the performance of 11 de novo HiFi assemblers on (1) real data for three eukaryotic genomes; (2) 34 synthetic data sets with different ploidy, sequencing coverage levels, heterozygosity rates, and sequencing error rates; (3) one real metagenomic data set; and (4) five synthetic metagenomic data sets with different composition abundance and heterozygosity rates. The 11 assemblers were evaluated using quality assessment tool (QUAST) and benchmarking universal single-copy ortholog (BUSCO). We also used several additional criteria, namely, completion rate, single-copy completion rate, duplicated completion rate, average proportion of largest category, average distance difference, quality value, run-time, and memory utilization. Results show that hifiasm and hifiasm-meta should be the first choice for assembling eukaryotic genomes and metagenomes with HiFi data. We performed a comprehensive benchmarking study of commonly used assemblers on complex eukaryotic genomes and metagenomes. Our study will help the research community to choose the most appropriate assembler for their data and identify possible improvements in assembly algorithms.
Collapse
Affiliation(s)
- Wenjuan Yu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Haohui Luo
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Jinbao Yang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Shengchen Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Heling Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Xianjia Zhao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Xingqi Hui
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Da Sun
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Liang Li
- Fruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350002, China
| | - Xiu-Qing Wei
- Fruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350002, China;
| | - Stefano Lonardi
- Department of Computer Science and Engineering, University of California, Riverside, California 92521, USA;
| | - Weihua Pan
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China;
| |
Collapse
|
10
|
Qiu Z, Yuan L, Lian CA, Lin B, Chen J, Mu R, Qiao X, Zhang L, Xu Z, Fan L, Zhang Y, Wang S, Li J, Cao H, Li B, Chen B, Song C, Liu Y, Shi L, Tian Y, Ni J, Zhang T, Zhou J, Zhuang WQ, Yu K. BASALT refines binning from metagenomic data and increases resolution of genome-resolved metagenomic analysis. Nat Commun 2024; 15:2179. [PMID: 38467684 PMCID: PMC10928208 DOI: 10.1038/s41467-024-46539-7] [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: 03/10/2023] [Accepted: 03/01/2024] [Indexed: 03/13/2024] Open
Abstract
Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.
Collapse
Affiliation(s)
- Zhiguang Qiu
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
| | - Li Yuan
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
- School of Electronic and Computer Engineering, Peking University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
| | - Chun-Ang Lian
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
| | - Bin Lin
- School of Electronic and Computer Engineering, Peking University, Shenzhen, China
| | - Jie Chen
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
- School of Electronic and Computer Engineering, Peking University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
| | - Rong Mu
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Xuejiao Qiao
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Liyu Zhang
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Zheng Xu
- Southern University of Sciences and Technology Yantian Hospital, Shenzhen, China
- Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Lu Fan
- Department of Ocean Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China
| | - Yunzeng Zhang
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Shanquan Wang
- Environmental Microbiomics Research Center, School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou, China
| | - Junyi Li
- School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, China
| | - Huiluo Cao
- Department of Microbiology, University of Hong Kong, Hong Kong, China
| | - Bing Li
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Baowei Chen
- Guangdong Provincial Key Laboratory of Marine Resources and Coastal Engineering, School of Marine Sciences, Sun Yat-sen University, Zhuhai, China
| | - Chi Song
- Institute of Herbgenomics, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Wuhan Benagen Technology Co., Ltd, Wuhan, China
| | - Yongxin Liu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Lili Shi
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
- State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Yonghong Tian
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China
- School of Electronic and Computer Engineering, Peking University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
| | - Jinren Ni
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China
- College of Environmental Sciences and Engineering, Key Laboratory of Water and Sediment Sciences, Ministry of Education, Peking University, Beijing, China
| | - Tong Zhang
- Department of Civil Engineering, University of Hong Kong, Hong Kong, China
| | - Jizhong Zhou
- Institute for Environmental Genomics, University of Oklahoma, Norman, OK, USA
| | - Wei-Qin Zhuang
- Department of Civil and Environmental Engineering, Faculty of Engineering, University of Auckland, Auckland, New Zealand
| | - Ke Yu
- Eco-environment and Resource Efficiency Research Laboratory, School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen, China.
- AI for Science (AI4S)-Preferred Program, Peking University, Shenzhen, China.
| |
Collapse
|
11
|
Hui X, Yang J, Sun J, Liu F, Pan W. MCSS: microbial community simulator based on structure. Front Microbiol 2024; 15:1358257. [PMID: 38516019 PMCID: PMC10956353 DOI: 10.3389/fmicb.2024.1358257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/20/2024] [Indexed: 03/23/2024] Open
Abstract
De novo assembly plays a pivotal role in metagenomic analysis, and the incorporation of third-generation sequencing technology can significantly improve the integrity and accuracy of assembly results. Recently, with advancements in sequencing technology (Hi-Fi, ultra-long), several long-read-based bioinformatic tools have been developed. However, the validation of the performance and reliability of these tools is a crucial concern. To address this gap, we present MCSS (microbial community simulator based on structure), which has the capability to generate simulated microbial community and sequencing datasets based on the structure attributes of real microbiome communities. The evaluation results indicate that it can generate simulated communities that exhibit both diversity and similarity to actual community structures. Additionally, MCSS generates synthetic PacBio Hi-Fi and Oxford Nanopore Technologies (ONT) long reads for the species within the simulated community. This innovative tool provides a valuable resource for benchmarking and refining metagenomic analysis methods. Code available at: https://github.com/panlab-bio/mcss.
Collapse
Affiliation(s)
- Xingqi Hui
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
| | - Jinbao Yang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
- College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Jinhuan Sun
- Key Laboratory of Plant Molecular Physiology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Fang Liu
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, China
| | - Weihua Pan
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
| |
Collapse
|
12
|
Ma J, Sun H, Li B, Wu B, Zhang X, Ye L. Horizontal transfer potential of antibiotic resistance genes in wastewater treatment plants unraveled by microfluidic-based mini-metagenomics. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133493. [PMID: 38228000 DOI: 10.1016/j.jhazmat.2024.133493] [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: 09/11/2023] [Revised: 12/30/2023] [Accepted: 01/08/2024] [Indexed: 01/18/2024]
Abstract
Wastewater treatment plants (WWTPs) are known to harbor antibiotic resistance genes (ARGs), which can potentially spread to the environment and human populations. However, the extent and mechanisms of ARG transfer in WWTPs are not well understood due to the high microbial diversity and limitations of molecular techniques. In this study, we used a microfluidic-based mini-metagenomics approach to investigate the transfer potential and mechanisms of ARGs in activated sludge from WWTPs. Our results show that while diverse ARGs are present in activated sludge, only a few highly similar ARGs are observed across different taxa, indicating limited transfer potential. We identified two ARGs, ermF and tla-1, which occur in a variety of bacterial taxa and may have high transfer potential facilitated by mobile genetic elements. Interestingly, genes that are highly similar to the sequences of these two ARGs, as identified in this study, display varying patterns of abundance across geographic regions. Genes similar to ermF found are widely found in Asia and the Americas, while genes resembling tla-1 are primarily detected in Asia. Genes similar to both genes are barely detected in European WWTPs. These findings shed light on the limited horizontal transfer potential of ARGs in WWTPs and highlight the importance of monitoring specific ARGs in different regions to mitigate the spread of antibiotic resistance.
Collapse
Affiliation(s)
- Jiachen Ma
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Haohao Sun
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China; School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Bing Li
- State Environmental Protection Key Laboratory of Microorganism Application and Risk Control, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Bing Wu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Xuxiang Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Lin Ye
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
| |
Collapse
|
13
|
Law SR, Mathes F, Paten AM, Alexandre PA, Regmi R, Reid C, Safarchi A, Shaktivesh S, Wang Y, Wilson A, Rice SA, Gupta VVSR. Life at the borderlands: microbiomes of interfaces critical to One Health. FEMS Microbiol Rev 2024; 48:fuae008. [PMID: 38425054 PMCID: PMC10977922 DOI: 10.1093/femsre/fuae008] [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: 07/26/2023] [Revised: 02/12/2024] [Accepted: 02/27/2024] [Indexed: 03/02/2024] Open
Abstract
Microbiomes are foundational components of the environment that provide essential services relating to food security, carbon sequestration, human health, and the overall well-being of ecosystems. Microbiota exert their effects primarily through complex interactions at interfaces with their plant, animal, and human hosts, as well as within the soil environment. This review aims to explore the ecological, evolutionary, and molecular processes governing the establishment and function of microbiome-host relationships, specifically at interfaces critical to One Health-a transdisciplinary framework that recognizes that the health outcomes of people, animals, plants, and the environment are tightly interconnected. Within the context of One Health, the core principles underpinning microbiome assembly will be discussed in detail, including biofilm formation, microbial recruitment strategies, mechanisms of microbial attachment, community succession, and the effect these processes have on host function and health. Finally, this review will catalogue recent advances in microbiology and microbial ecology methods that can be used to profile microbial interfaces, with particular attention to multi-omic, advanced imaging, and modelling approaches. These technologies are essential for delineating the general and specific principles governing microbiome assembly and functions, mapping microbial interconnectivity across varying spatial and temporal scales, and for the establishment of predictive frameworks that will guide the development of targeted microbiome-interventions to deliver One Health outcomes.
Collapse
Affiliation(s)
- Simon R Law
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Canberra, ACT 2601, Australia
| | - Falko Mathes
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Floreat, WA 6014, Australia
| | - Amy M Paten
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Canberra, ACT 2601, Australia
| | - Pamela A Alexandre
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, St Lucia, Qld 4072, Australia
| | - Roshan Regmi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
| | - Cameron Reid
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Urrbrae, SA 5064, Australia
| | - Azadeh Safarchi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Westmead, NSW 2145, Australia
| | - Shaktivesh Shaktivesh
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Data 61, Clayton, Vic 3168, Australia
| | - Yanan Wang
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Adelaide SA 5000, Australia
| | - Annaleise Wilson
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Geelong, Vic 3220, Australia
| | - Scott A Rice
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture, and Food, Westmead, NSW 2145, Australia
| | - Vadakattu V S R Gupta
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
| |
Collapse
|
14
|
Vancaester E, Blaxter ML. MarkerScan: Separation and assembly of cobionts sequenced alongside target species in biodiversity genomics projects. Wellcome Open Res 2024; 9:33. [PMID: 38617467 PMCID: PMC11016177 DOI: 10.12688/wellcomeopenres.20730.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2023] [Indexed: 04/16/2024] Open
Abstract
Contamination of public databases by mislabelled sequences has been highlighted for many years and the avalanche of novel sequencing data now being deposited has the potential to make databases difficult to use effectively. It is therefore crucial that sequencing projects and database curators perform pre-submission checks to remove obvious contamination and avoid propagating erroneous taxonomic relationships. However, it is important also to recognise that biological contamination of a target sample with unexpected species' DNA can also lead to the discovery of fascinating biological phenomena through the identification of environmental organisms or endosymbionts. Here, we present a novel, integrated method for detection and generation of high-quality genomes of all non-target genomes co-sequenced in eukaryotic genome sequencing projects. After performing taxonomic profiling of an assembly from the raw data, and leveraging the identity of small rRNA sequences discovered therein as markers, a targeted classification approach retrieves and assembles high-quality genomes. The genomes of these cobionts are then not only removed from the target species' genome but also available for further interrogation. Source code is available from https://github.com/CobiontID/MarkerScan. MarkerScan is written in Python and is deployed as a Docker container.
Collapse
Affiliation(s)
| | - Mark L. Blaxter
- Tree of Life, Wellcome Sanger Institute, Hinxton, England, UK
| |
Collapse
|
15
|
Hosokawa M, Nishikawa Y. Tools for microbial single-cell genomics for obtaining uncultured microbial genomes. Biophys Rev 2024; 16:69-77. [PMID: 38495448 PMCID: PMC10937852 DOI: 10.1007/s12551-023-01124-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/23/2023] [Indexed: 03/19/2024] Open
Abstract
The advent of next-generation sequencing technologies has facilitated the acquisition of large amounts of DNA sequence data at a relatively low cost, leading to numerous breakthroughs in decoding microbial genomes. Among the various genome sequencing activities, metagenomic analysis, which entails the direct analysis of uncultured microbial DNA, has had a profound impact on microbiome research and has emerged as an indispensable technology in this field. Despite its valuable contributions, metagenomic analysis is a "bulk analysis" technique that analyzes samples containing a wide diversity of microbes, such as bacteria, yielding information that is averaged across the entire microbial population. In order to gain a deeper understanding of the heterogeneous nature of the microbial world, there is a growing need for single-cell analysis, similar to its use in human cell biology. With this paradigm shift in mind, comprehensive single-cell genomics technology has become a much-anticipated innovation that is now poised to revolutionize microbiome research. It has the potential to enable the discovery of differences at the strain level and to facilitate a more comprehensive examination of microbial ecosystems. In this review, we summarize the current state-of-the-art in microbial single-cell genomics, highlighting the potential impact of this technology on our understanding of the microbial world. The successful implementation of this technology is expected to have a profound impact in the field, leading to new discoveries and insights into the diversity and evolution of microbes.
Collapse
Affiliation(s)
- Masahito Hosokawa
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-Cho, Shinjuku-Ku, Tokyo, 162-8480 Japan
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-Ku, Tokyo, 169-8555 Japan
- Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-Cho, Shinjuku-Ku, Tokyo, 162-0041 Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, 3-4-1 Okubo, Shinjuku-Ku, Tokyo, 169-8555 Japan
- bitBiome, Inc., 513 Wasedatsurumaki-Cho, Shinjuku-Ku, Tokyo, 162-0041 Japan
| | - Yohei Nishikawa
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-Ku, Tokyo, 169-8555 Japan
- Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-Cho, Shinjuku-Ku, Tokyo, 162-0041 Japan
| |
Collapse
|
16
|
Babajanyan SG, Garushyants SK, Wolf YI, Koonin EV. Microbial diversity and ecological complexity emerging from environmental variation and horizontal gene transfer in a simple mathematical model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.17.576128. [PMID: 38313259 PMCID: PMC10836074 DOI: 10.1101/2024.01.17.576128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Microbiomes are generally characterized by high diversity of coexisting microbial species and strains that remains stable within a broad range of conditions. However, under fixed conditions, microbial ecology conforms with the exclusion principle under which two populations competing for the same resource within the same niche cannot coexist because the less fit population inevitably goes extinct. To explore the conditions for stabilization of microbial diversity, we developed a simple mathematical model consisting of two competing populations that could exchange a single gene allele via horizontal gene transfer (HGT). We found that, although in a fixed environment, with unbiased HGT, the system obeyed the exclusion principle, in an oscillating environment, within large regions of the phase space bounded by the rates of reproduction and HGT, the two populations coexist. Moreover, depending on the parameter combination, all three major types of symbiosis obtained, namely, pure competition, host-parasite relationship and mutualism. In each of these regimes, certain parameter combinations provided for synergy, that is, a greater total abundance of both populations compared to the abundance of the winning population in the fixed environments. These findings show that basic phenomena that are universal in microbial communities, environmental variation and HGT, provide for stabilization of microbial diversity and ecological complexity.
Collapse
Affiliation(s)
- Sanasar G. Babajanyan
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Sofya K. Garushyants
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Yuri I. Wolf
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Eugene V. Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| |
Collapse
|
17
|
Haft DH, Badretdin A, Coulouris G, DiCuccio M, Durkin A, Jovenitti E, Li W, Mersha M, O’Neill K, Virothaisakun J, Thibaud-Nissen F. RefSeq and the prokaryotic genome annotation pipeline in the age of metagenomes. Nucleic Acids Res 2024; 52:D762-D769. [PMID: 37962425 PMCID: PMC10767926 DOI: 10.1093/nar/gkad988] [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: 09/15/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 11/15/2023] Open
Abstract
The Reference Sequence (RefSeq) project at the National Center for Biotechnology Information (NCBI) contains over 315 000 bacterial and archaeal genomes and 236 million proteins with up-to-date and consistent annotation. In the past 3 years, we have expanded the diversity of the RefSeq collection by including the best quality metagenome-assembled genomes (MAGs) submitted to INSDC (DDBJ, ENA and GenBank), while maintaining its quality by adding validation checks. Assemblies are now more stringently evaluated for contamination and for completeness of annotation prior to acceptance into RefSeq. MAGs now account for over 17000 assemblies in RefSeq, split over 165 orders and 362 families. Changes in the Prokaryotic Genome Annotation Pipeline (PGAP), which is used to annotate nearly all RefSeq assemblies include better detection of protein-coding genes. Nearly 83% of RefSeq proteins are now named by a curated Protein Family Model, a 4.7% increase in the past three years ago. In addition to literature citations, Enzyme Commission numbers, and gene symbols, Gene Ontology terms are now assigned to 48% of RefSeq proteins, allowing for easier multi-genome comparison. RefSeq is found at https://www.ncbi.nlm.nih.gov/refseq/. PGAP is available as a stand-alone tool able to produce GenBank-ready files at https://github.com/ncbi/pgap.
Collapse
Affiliation(s)
- Daniel H Haft
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Azat Badretdin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - George Coulouris
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Michael DiCuccio
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - A Scott Durkin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Eric Jovenitti
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Wenjun Li
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Megdelawit Mersha
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Kathleen R O’Neill
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Joel Virothaisakun
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| |
Collapse
|
18
|
Benoit G, Raguideau S, James R, Phillippy AM, Chikhi R, Quince C. High-quality metagenome assembly from long accurate reads with metaMDBG. Nat Biotechnol 2024:10.1038/s41587-023-01983-6. [PMID: 38168989 DOI: 10.1038/s41587-023-01983-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 09/08/2023] [Indexed: 01/05/2024]
Abstract
We introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.
Collapse
Affiliation(s)
- Gaëtan Benoit
- Organisms and Ecosystems, Earlham Institute, Norwich, UK
| | | | - Robert James
- Gut Microbes and Health, Quadram Institute, Norwich, UK
| | - Adam M Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Rayan Chikhi
- Sequence Bioinformatics, Department of Computational Biology, Institut Pasteur, Paris, France
| | - Christopher Quince
- Organisms and Ecosystems, Earlham Institute, Norwich, UK.
- Gut Microbes and Health, Quadram Institute, Norwich, UK.
- School of Biological Sciences, University of East Anglia, Norwich, UK.
- Warwick Medical School, University of Warwick, Coventry, UK.
| |
Collapse
|
19
|
Cerk K, Ugalde‐Salas P, Nedjad CG, Lecomte M, Muller C, Sherman DJ, Hildebrand F, Labarthe S, Frioux C. Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing. Microb Biotechnol 2024; 17:e14396. [PMID: 38243750 PMCID: PMC10832553 DOI: 10.1111/1751-7915.14396] [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: 01/09/2023] [Revised: 11/27/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024] Open
Abstract
Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.
Collapse
Affiliation(s)
- Klara Cerk
- Quadram Institute BioscienceNorwichUK
- Earlham InstituteNorwichUK
| | | | - Chabname Ghassemi Nedjad
- Inria, University of Bordeaux, INRAETalenceFrance
- University of Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800TalenceFrance
| | - Maxime Lecomte
- Inria, University of Bordeaux, INRAETalenceFrance
- INRAE STLO¸University of RennesRennesFrance
| | | | | | - Falk Hildebrand
- Quadram Institute BioscienceNorwichUK
- Earlham InstituteNorwichUK
| | - Simon Labarthe
- Inria, University of Bordeaux, INRAETalenceFrance
- INRAE, University of Bordeaux, BIOGECO, UMR 1202CestasFrance
| | | |
Collapse
|
20
|
Burz SD, Causevic S, Dal Co A, Dmitrijeva M, Engel P, Garrido-Sanz D, Greub G, Hapfelmeier S, Hardt WD, Hatzimanikatis V, Heiman CM, Herzog MKM, Hockenberry A, Keel C, Keppler A, Lee SJ, Luneau J, Malfertheiner L, Mitri S, Ngyuen B, Oftadeh O, Pacheco AR, Peaudecerf F, Resch G, Ruscheweyh HJ, Sahin A, Sanders IR, Slack E, Sunagawa S, Tackmann J, Tecon R, Ugolini GS, Vacheron J, van der Meer JR, Vayena E, Vonaesch P, Vorholt JA. From microbiome composition to functional engineering, one step at a time. Microbiol Mol Biol Rev 2023; 87:e0006323. [PMID: 37947420 PMCID: PMC10732080 DOI: 10.1128/mmbr.00063-23] [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] [Indexed: 11/12/2023] Open
Abstract
SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.
Collapse
Affiliation(s)
- Sebastian Dan Burz
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Senka Causevic
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Alma Dal Co
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Marija Dmitrijeva
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Philipp Engel
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Daniel Garrido-Sanz
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Gilbert Greub
- Institut de microbiologie, CHUV University Hospital Lausanne, Lausanne, Switzerland
| | | | | | | | - Clara Margot Heiman
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | | | | - Christoph Keel
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | | - Soon-Jae Lee
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
| | - Julien Luneau
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Lukas Malfertheiner
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Sara Mitri
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Bidong Ngyuen
- Institute of Microbiology, ETH Zürich, Zürich, Switzerland
| | - Omid Oftadeh
- Laboratory of Computational Systems Biotechnology, EPF Lausanne, Lausanne, Switzerland
| | | | | | - Grégory Resch
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, CHUV University Hospital Lausanne, Lausanne, Switzerland
| | | | - Asli Sahin
- Laboratory of Computational Systems Biotechnology, EPF Lausanne, Lausanne, Switzerland
| | - Ian R. Sanders
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
| | - Emma Slack
- Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | | | - Janko Tackmann
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Robin Tecon
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | | - Jordan Vacheron
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | | - Evangelia Vayena
- Laboratory of Computational Systems Biotechnology, EPF Lausanne, Lausanne, Switzerland
| | - Pascale Vonaesch
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | |
Collapse
|
21
|
Hamilton T, Joris BR, Shrestha A, Browne TS, Rodrigue S, Karas BJ, Gloor GB, Edgell DR. De Novo Synthesis of a Conjugative System from Human Gut Metagenomic Data for Targeted Delivery of Cas9 Antimicrobials. ACS Synth Biol 2023; 12:3578-3590. [PMID: 38049144 PMCID: PMC10729033 DOI: 10.1021/acssynbio.3c00319] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 11/03/2023] [Accepted: 11/08/2023] [Indexed: 12/06/2023]
Abstract
Metagenomic sequences represent an untapped source of genetic novelty, particularly for conjugative systems that could be used for plasmid-based delivery of Cas9-derived antimicrobial agents. However, unlocking the functional potential of conjugative systems purely from metagenomic sequences requires the identification of suitable candidate systems as starting scaffolds for de novo DNA synthesis. Here, we developed a bioinformatics approach that searches through the metagenomic "trash bin" for genes associated with conjugative systems present on contigs that are typically excluded from common metagenomic analysis pipelines. Using a human metagenomic gut data set representing 2805 taxonomically distinct units, we identified 1598 contigs containing conjugation genes with a differential distribution in human cohorts. We synthesized de novo an entire Citrobacter spp. conjugative system of 54 kb containing at least 47 genes and assembled it into a plasmid, pCitro. We found that pCitro conjugates from Escherichia coli to Citrobacter rodentium with a 30-fold higher frequency than to E. coli, and is compatible with Citrobacter resident plasmids. Mutations in the traV and traY conjugation components of pCitro inhibited conjugation. We showed that pCitro can be repurposed as an antimicrobial delivery agent by programming it with the TevCas9 nuclease and Citrobacter-specific sgRNAs to kill C. rodentium. Our study reveals a trove of uncharacterized conjugative systems in metagenomic data and describes an experimental framework to animate these large genetic systems as novel target-adapted delivery vectors for Cas9-based editing of bacterial genomes.
Collapse
Affiliation(s)
- Thomas
A. Hamilton
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - Benjamin R. Joris
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - Arina Shrestha
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - Tyler S. Browne
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - Sébastien Rodrigue
- Départment
de Biologie, Université de Sherbrooke, Sherbrooke J1K 2R1, QC, Canada
| | - Bogumil J. Karas
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - Gregory B. Gloor
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| | - David R. Edgell
- Department
of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London N6A 5C1, ON, Canada
| |
Collapse
|
22
|
Sun Y, Wang M, Cao L, Seim I, Zhou L, Chen J, Wang H, Zhong Z, Chen H, Fu L, Li M, Li C, Sun S. Mosaic environment-driven evolution of the deep-sea mussel Gigantidas platifrons bacterial endosymbiont. MICROBIOME 2023; 11:253. [PMID: 37974296 PMCID: PMC10652631 DOI: 10.1186/s40168-023-01695-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 10/11/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND The within-species diversity of symbiotic bacteria represents an important genetic resource for their environmental adaptation, especially for horizontally transmitted endosymbionts. Although strain-level intraspecies variation has recently been detected in many deep-sea endosymbionts, their ecological role in environmental adaptation, their genome evolution pattern under heterogeneous geochemical environments, and the underlying molecular forces remain unclear. RESULTS Here, we conducted a fine-scale metagenomic analysis of the deep-sea mussel Gigantidas platifrons bacterial endosymbiont collected from distinct habitats: hydrothermal vent and methane seep. Endosymbiont genomes were assembled using a pipeline that distinguishes within-species variation and revealed highly heterogeneous compositions in mussels from different habitats. Phylogenetic analysis separated the assemblies into three distinct environment-linked clades. Their functional differentiation follows a mosaic evolutionary pattern. Core genes, essential for central metabolic function and symbiosis, were conserved across all clades. Clade-specific genes associated with heavy metal resistance, pH homeostasis, and nitrate utilization exhibited signals of accelerated evolution. Notably, transposable elements and plasmids contributed to the genetic reshuffling of the symbiont genomes and likely accelerated adaptive evolution through pseudogenization and the introduction of new genes. CONCLUSIONS The current study uncovers the environment-driven evolution of deep-sea symbionts mediated by mobile genetic elements. Its findings highlight a potentially common and critical role of within-species diversity in animal-microbiome symbioses. Video Abstract.
Collapse
Affiliation(s)
- Yan Sun
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Minxiao Wang
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Lei Cao
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Inge Seim
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, 210046, China
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Li Zhou
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Jianwei Chen
- BGI Research-Qingdao, BGI, Qingdao, 266555, China
| | - Hao Wang
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Zhaoshan Zhong
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Hao Chen
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Lulu Fu
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Mengna Li
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China
| | - Chaolun Li
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China.
- South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Song Sun
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
- Laboratory for Marine Ecology and Environmental Science, Laoshan Laboratory, Qingdao, 266237, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| |
Collapse
|
23
|
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.
Collapse
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.
| |
Collapse
|
24
|
Rojas CA, Gardy J, Eisen JA, Ganz HH. Recovery of 52 bacterial genomes from the fecal microbiome of the domestic cat ( Felis catus) using Hi-C proximity ligation and shotgun metagenomics. Microbiol Resour Announc 2023; 12:e0060123. [PMID: 37695121 PMCID: PMC10586161 DOI: 10.1128/mra.00601-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 08/08/2023] [Indexed: 09/12/2023] Open
Abstract
We used Hi-C proximity ligation with shotgun sequencing to retrieve metagenome-assembled genomes (MAGs) from the fecal microbiomes of two domestic cats (Felis catus). The genomes were assessed for completeness and contamination, classified taxonomically, and annotated for putative antimicrobial resistance (AMR) genes.
Collapse
Affiliation(s)
| | - Jennifer Gardy
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Jonathan A. Eisen
- Evolution and Ecology, University of California, Davis, California, USA
| | | |
Collapse
|
25
|
Li K, Xu P, Wang J, Yi X, Jiao Y. Identification of errors in draft genome assemblies at single-nucleotide resolution for quality assessment and improvement. Nat Commun 2023; 14:6556. [PMID: 37848433 PMCID: PMC10582259 DOI: 10.1038/s41467-023-42336-w] [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: 02/13/2023] [Accepted: 10/05/2023] [Indexed: 10/19/2023] Open
Abstract
Assembly of a high-quality genome is important for downstream comparative and functional genomic studies. However, most tools for genome assembly assessment only give qualitative reports, which do not pinpoint assembly errors at specific regions. Here, we develop a new reference-free tool, Clipping information for Revealing Assembly Quality (CRAQ), which maps raw reads back to assembled sequences to identify regional and structural assembly errors based on effective clipped alignment information. Error counts are transformed into corresponding assembly evaluation indexes to reflect the assembly quality at single-nucleotide resolution. Notably, CRAQ distinguishes assembly errors from heterozygous sites or structural differences between haplotypes. This tool can clearly indicate low-quality regions and potential structural error breakpoints; thus, it can identify misjoined regions that should be split for further scaffold building and improvement of the assembly. We have benchmarked CRAQ on multiple genomes assembled using different strategies, and demonstrated the misjoin correction for improving the constructed pseudomolecules.
Collapse
Affiliation(s)
- Kunpeng Li
- State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, the Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Peng Xu
- State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, the Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jinpeng Wang
- State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, the Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xin Yi
- State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, the Chinese Academy of Sciences, Beijing, China
- China National Botanical Garden, Beijing, China
| | - Yuannian Jiao
- State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, the Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- China National Botanical Garden, Beijing, China.
| |
Collapse
|
26
|
Du Y, Sun F. MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data. Nat Commun 2023; 14:6231. [PMID: 37802989 PMCID: PMC10558524 DOI: 10.1038/s41467-023-41209-6] [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: 03/16/2023] [Accepted: 08/25/2023] [Indexed: 10/08/2023] Open
Abstract
Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.
Collapse
Affiliation(s)
- Yuxuan Du
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Fengzhu Sun
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
| |
Collapse
|
27
|
Ahmad N, Ritz M, Calchera A, Otte J, Schmitt I, Brueck T, Mehlmer N. Biosynthetic gene cluster synteny: Orthologous polyketide synthases in Hypogymnia physodes, Hypogymnia tubulosa, and Parmelia sulcata. Microbiologyopen 2023; 12:e1386. [PMID: 37877655 PMCID: PMC10582450 DOI: 10.1002/mbo3.1386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/15/2023] [Accepted: 09/26/2023] [Indexed: 10/26/2023] Open
Abstract
Lichens are symbiotic associations consisting of a photobiont (algae or cyanobacteria) and a mycobiont (fungus), which together generate a variety of unique secondary metabolites. To access this biosynthetic potential for biotechnological applications, deeper insights into the biosynthetic pathways and corresponding gene clusters are necessary. Here, we provide a comparative view of the biosynthetic gene clusters of three lichen mycobionts derived from Hypogymnia physodes, Hypogymnia tubulosa, and Parmelia sulcata. In addition, we present a high-quality PacBio metagenome of Parmelia sulcata, from which we extracted the mycobiont bin containing 214 biosynthetic gene clusters. Most biosynthetic gene clusters in these genomes were associated with T1PKSs, followed by NRPSs and terpenes. This study focused on biosynthetic gene clusters related to polyketide synthesis. Based on ketosynthase homology, we identified nine highly syntenic clusters present in all three species. Among the four clusters belonging to nonreducing PKSs, two are putatively linked to lichen substances derived from orsellinic acid (orcinol depsides and depsidones, e.g., lecanoric acid, physodic acid, lobaric acid), one to compounds derived from methylated forms of orsellinic acid (beta orcinol depsides, e.g., atranorin), and one to melanins. Five clusters with orthologs in all three species are linked to reducing PKSs. Our study contributes to sorting and dereplicating the vast PKS diversity found in lichenized fungi. High-quality sequences of biosynthetic gene clusters of these three common species provide a foundation for further exploration into biotechnological applications and the molecular evolution of lichen substances.
Collapse
Affiliation(s)
- Nadim Ahmad
- Department of Chemistry, Werner Siemens Chair of Synthetic Biotechnology, TUM School of Natural SciencesTechnical University of Munich (TUM)GarchingGermany
| | - Manfred Ritz
- Department of Chemistry, Werner Siemens Chair of Synthetic Biotechnology, TUM School of Natural SciencesTechnical University of Munich (TUM)GarchingGermany
| | - Anjuli Calchera
- Senckenberg Biodiversity and Climate Research Centre (SBiK‐F)Frankfurt am MainGermany
| | - Jürgen Otte
- Senckenberg Biodiversity and Climate Research Centre (SBiK‐F)Frankfurt am MainGermany
| | - Imke Schmitt
- Senckenberg Biodiversity and Climate Research Centre (SBiK‐F)Frankfurt am MainGermany
- Institute of Ecology, Evolution and DiversityGoethe University FrankfurtFrankfurt am MainGermany
| | - Thomas Brueck
- Department of Chemistry, Werner Siemens Chair of Synthetic Biotechnology, TUM School of Natural SciencesTechnical University of Munich (TUM)GarchingGermany
| | - Norbert Mehlmer
- Department of Chemistry, Werner Siemens Chair of Synthetic Biotechnology, TUM School of Natural SciencesTechnical University of Munich (TUM)GarchingGermany
| |
Collapse
|
28
|
Ho H, Chovatia M, Egan R, He G, Yoshinaga Y, Liachko I, O’Malley R, Wang Z. Integrating chromatin conformation information in a self-supervised learning model improves metagenome binning. PeerJ 2023; 11:e16129. [PMID: 37753177 PMCID: PMC10519199 DOI: 10.7717/peerj.16129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023] Open
Abstract
Metagenome binning is a key step, downstream of metagenome assembly, to group scaffolds by their genome of origin. Although accurate binning has been achieved on datasets containing multiple samples from the same community, the completeness of binning is often low in datasets with a small number of samples due to a lack of robust species co-abundance information. In this study, we exploited the chromatin conformation information obtained from Hi-C sequencing and developed a new reference-independent algorithm, Metagenome Binning with Abundance and Tetra-nucleotide frequencies-Long Range (metaBAT-LR), to improve the binning completeness of these datasets. This self-supervised algorithm builds a model from a set of high-quality genome bins to predict scaffold pairs that are likely to be derived from the same genome. Then, it applies these predictions to merge incomplete genome bins, as well as recruit unbinned scaffolds. We validated metaBAT-LR's ability to bin-merge and recruit scaffolds on both synthetic and real-world metagenome datasets of varying complexity. Benchmarking against similar software tools suggests that metaBAT-LR uncovers unique bins that were missed by all other methods. MetaBAT-LR is open-source and is available at https://bitbucket.org/project-metabat/metabat-lr.
Collapse
Affiliation(s)
- Harrison Ho
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
- School of Natural Sciences, University of California, Merced, CA, United States
| | - Mansi Chovatia
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | - Rob Egan
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | - Guifen He
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | - Yuko Yoshinaga
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | | | - Ronan O’Malley
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Lab, Berkeley, CA, United States
| | - Zhong Wang
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Lab, Berkeley, CA, United States
- School of Natural Sciences, University of California, Merced, CA, United States
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Lab, Berkeley, CA, United States
| |
Collapse
|
29
|
Li S, Lian WH, Han JR, Ali M, Lin ZL, Liu YH, Li L, Zhang DY, Jiang XZ, Li WJ, Dong L. Capturing the microbial dark matter in desert soils using culturomics-based metagenomics and high-resolution analysis. NPJ Biofilms Microbiomes 2023; 9:67. [PMID: 37736746 PMCID: PMC10516943 DOI: 10.1038/s41522-023-00439-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 09/14/2023] [Indexed: 09/23/2023] Open
Abstract
Deserts occupy one-third of the Earth's terrestrial surface and represent a potentially significant reservoir of microbial biodiversity, yet the majority of desert microorganisms remain uncharacterized and are seen as "microbial dark matter". Here, we introduce a multi-omics strategy, culturomics-based metagenomics (CBM) that integrates large-scale cultivation, full-length 16S rRNA gene amplicon, and shotgun metagenomic sequencing. The results showed that CBM captured a significant amount of taxonomic and functional diversity missed in direct sequencing by increasing the recovery of amplicon sequence variants (ASVs) and high/medium-quality metagenome-assembled genomes (MAGs). Importantly, CBM allowed the post hoc recovery of microbes of interest (e.g., novel or specific taxa), even those with extremely low abundance in the culture. Furthermore, strain-level analyses based on CBM and direct sequencing revealed that the desert soils harbored a considerable number of novel bacterial candidates (1941, 51.4%), of which 1095 (from CBM) were culturable. However, CBM would not exactly reflect the relative abundance of true microbial composition and functional pathways in the in situ environment, and its use coupled with direct metagenomic sequencing could provide greater insight into desert microbiomes. Overall, this study exemplifies the CBM strategy with high-resolution is an ideal way to deeply explore the untapped novel bacterial resources in desert soils, and substantially expands our knowledge on the microbial dark matter hidden in the vast expanse of deserts.
Collapse
Affiliation(s)
- Shuai Li
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China
- School of Life Science, Jiaying University, Meizhou, 514015, China
| | - Wen-Hui Lian
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China
| | - Jia-Rui Han
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China
| | - Mukhtiar Ali
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China
| | - Zhi-Liang Lin
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China
| | - Yong-Hong Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
| | - Li Li
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
| | - Dong-Ya Zhang
- Microbiome Research Center, Moon (Guangzhou) Biotech Ltd., Guangzhou, 510700, China
| | - Xian-Zhi Jiang
- Microbiome Research Center, Moon (Guangzhou) Biotech Ltd., Guangzhou, 510700, China
| | - Wen-Jun Li
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China.
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
| | - Lei Dong
- State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat‑sen University, Guangzhou, 510275, China.
| |
Collapse
|
30
|
Seong HJ, Kim JJ, Sul WJ. ACR: metagenome-assembled prokaryotic and eukaryotic genome refinement tool. Brief Bioinform 2023; 24:bbad381. [PMID: 37889119 DOI: 10.1093/bib/bbad381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/16/2023] [Accepted: 10/03/2023] [Indexed: 10/28/2023] Open
Abstract
Microbial genome recovery from metagenomes can further explain microbial ecosystem structures, functions and dynamics. Thus, this study developed the Additional Clustering Refiner (ACR) to enhance high-purity prokaryotic and eukaryotic metagenome-assembled genome (MAGs) recovery. ACR refines low-quality MAGs by subjecting them to iterative k-means clustering predicated on contig abundance and increasing bin purity through validated universal marker genes. Synthetic and real-world metagenomic datasets, including short- and long-read sequences, evaluated ACR's effectiveness. The results demonstrated improved MAG purity and a significant increase in high- and medium-quality MAG recovery rates. In addition, ACR seamlessly integrates with various binning algorithms, augmenting their strengths without modifying core features. Furthermore, its multiple sequencing technology compatibilities expand its applicability. By efficiently recovering high-quality prokaryotic and eukaryotic genomes, ACR is a promising tool for deepening our understanding of microbial communities through genome-centric metagenomics.
Collapse
Affiliation(s)
- Hoon Je Seong
- Korean Medicine Data Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Jin Ju Kim
- Department of Systems Biotechnology, Chung-Ang University, Anseong, Republic of Korea
| | - Woo Jun Sul
- Department of Systems Biotechnology, Chung-Ang University, Anseong, Republic of Korea
| |
Collapse
|
31
|
Arikawa K, Hosokawa M. Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics. Comput Struct Biotechnol J 2023; 21:4508-4518. [PMID: 37771751 PMCID: PMC10523443 DOI: 10.1016/j.csbj.2023.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/10/2023] [Accepted: 09/10/2023] [Indexed: 09/30/2023] Open
Abstract
Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.
Collapse
Affiliation(s)
- Koji Arikawa
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Masahito Hosokawa
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
- Research Organization for Nano and Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
| |
Collapse
|
32
|
van Dijk EL, Naquin D, Gorrichon K, Jaszczyszyn Y, Ouazahrou R, Thermes C, Hernandez C. Genomics in the long-read sequencing era. Trends Genet 2023; 39:649-671. [PMID: 37230864 DOI: 10.1016/j.tig.2023.04.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 05/27/2023]
Abstract
Long-read sequencing (LRS) technologies have provided extremely powerful tools to explore genomes. While in the early years these methods suffered technical limitations, they have recently made significant progress in terms of read length, throughput, and accuracy and bioinformatics tools have strongly improved. Here, we aim to review the current status of LRS technologies, the development of novel methods, and the impact on genomics research. We will explore the most impactful recent findings made possible by these technologies focusing on high-resolution sequencing of genomes and transcriptomes and the direct detection of DNA and RNA modifications. We will also discuss how LRS methods promise a more comprehensive understanding of human genetic variation, transcriptomics, and epigenetics for the coming years.
Collapse
Affiliation(s)
- Erwin L van Dijk
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France.
| | - Delphine Naquin
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Kévin Gorrichon
- National Center of Human Genomics Research (CNRGH), 91000 Évry-Courcouronnes, France
| | - Yan Jaszczyszyn
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Rania Ouazahrou
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Claude Thermes
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Céline Hernandez
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| |
Collapse
|
33
|
Bzikadze AV, Pevzner PA. UniAligner: a parameter-free framework for fast sequence alignment. Nat Methods 2023; 20:1346-1354. [PMID: 37580559 DOI: 10.1038/s41592-023-01970-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 07/05/2023] [Indexed: 08/16/2023]
Abstract
Even though the recent advances in 'complete genomics' revealed the previously inaccessible genomic regions, analysis of variations in centromeres and other extra-long tandem repeats (ETRs) faces an algorithmic challenge since there are currently no tools for accurate sequence comparison of ETRs. Counterintuitively, the classical alignment approaches, such as the Smith-Waterman algorithm, fail to construct biologically adequate alignments of ETRs. We present UniAligner-the parameter-free sequence alignment algorithm with sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. UniAligner prioritizes matches of rare substrings that are more likely to be relevant to the evolutionary relationship between two sequences. We apply UniAligner to estimate the mutation rates in human centromeres, and quantify the extremely high rate of large duplications and deletions in centromeres. This high rate suggests that centromeres may represent some of the most rapidly evolving regions of the human genome with respect to their structural organization.
Collapse
Affiliation(s)
- Andrey V Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
| |
Collapse
|
34
|
Huang R, Wang Y, Liu D, Wang S, Lv H, Yan Z. Long-Read Metagenomics of Marine Microbes Reveals Diversely Expressed Secondary Metabolites. Microbiol Spectr 2023; 11:e0150123. [PMID: 37409950 PMCID: PMC10434046 DOI: 10.1128/spectrum.01501-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/14/2023] [Indexed: 07/07/2023] Open
Abstract
Microbial secondary metabolites play crucial roles in microbial competition, communication, resource acquisition, antibiotic production, and a variety of other biotechnological processes. The retrieval of full-length BGC (biosynthetic gene cluster) sequences from uncultivated bacteria is difficult due to the technical constraints of short-read sequencing, making it impossible to determine BGC diversity. Using long-read sequencing and genome mining, 339 mainly full-length BGCs were recovered in this study, illuminating the wide range of BGCs from uncultivated lineages discovered in seawater from Aoshan Bay, Yellow Sea, China. Many extremely diverse BGCs were discovered in bacterial phyla such as Proteobacteria, Bacteroidota, Acidobacteriota, and Verrucomicrobiota as well as the previously uncultured archaeal phylum "Candidatus Thermoplasmatota." The data from metatranscriptomics showed that 30.1% of secondary metabolic genes were being expressed, and they also revealed the expression pattern of BGC core biosynthetic genes and tailoring enzymes. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional expression of BGCs in environmental processes. IMPORTANCE Genome mining of metagenomic data has become the preferred method for the bioprospecting of novel compounds by cataloguing secondary metabolite potential. However, the accurate detection of BGCs requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until recently with new long-read technologies. We used high-quality metagenome-assembled genomes generated from long-read data to determine the biosynthetic potential of microbes found in the surface water of the Yellow Sea. We recovered 339 highly diverse and mostly full-length BGCs from largely uncultured and underexplored bacterial and archaeal phyla. Additionally, we present long-read metagenomic sequencing combined with metatranscriptomic analysis as a potential method for gaining access to the largely underutilized genetic reservoir of specialized metabolite gene clusters in the majority of microbes that are not cultured. The combination of long-read metagenomic and metatranscriptomic analyses is significant because it can more accurately assess the mechanisms of microbial adaptation to the environment through BGC expression based on metatranscriptomic data.
Collapse
Affiliation(s)
- Ranran Huang
- Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
| | - Yafei Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
| | - Daixi Liu
- School of Pharmaceutical Sciences, Shandong University, Jinan, Shandong, China
| | - Shaoyu Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
| | - Haibo Lv
- Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
| | - Zhen Yan
- Shandong Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, Qingdao, Shandong, China
- Suzhou Research Institute, Shandong University, Suzhou, Jiangsu, China
| |
Collapse
|
35
|
Benoit G, Raguideau S, James R, Phillippy AM, Chikhi R, Quince C. Efficient High-Quality Metagenome Assembly from Long Accurate Reads using Minimizer-space de Bruijn Graphs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.07.548136. [PMID: 37786716 PMCID: PMC10541625 DOI: 10.1101/2023.07.07.548136] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
We introduce a novel metagenomics assembler for high-accuracy long reads. Our approach, implemented as metaMDBG, combines highly efficient de Bruijn graph assembly in minimizer space, with both a multi-k' approach for dealing with variations in genome coverage depth and an abundance-based filtering strategy for simplifying strain complexity. The resulting algorithm is more efficient than the state-of-the-art but with better assembly results. metaMDBG was 1.5 to 12 times faster than competing assemblers and requires between one-tenth and one-thirtieth of the memory across a range of data sets. We obtained up to twice as many high-quality circularised prokaryotic metagenome assembled genomes (MAGs) on the most complex communities, and a better recovery of viruses and plasmids. metaMDBG performs particularly well for abundant organisms whilst being robust to the presence of strain diversity. The result is that for the first time it is possible to efficiently reconstruct the majority of complex communities by abundance as near-complete MAGs.
Collapse
Affiliation(s)
- Gaëtan Benoit
- Organisms and Ecosystems, Earlham Institute, Norwich, NR4 7UZ, UK
| | | | - Robert James
- Gut Microbes and Health, Quadram Institute, Norwich, NR4 7UQ, UK
| | - Adam M. Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Rayan Chikhi
- Sequence Bioinformatics, Department of Computational Biology, Institut Pasteur, Paris, France
| | - Christopher Quince
- Organisms and Ecosystems, Earlham Institute, Norwich, NR4 7UZ, UK
- Gut Microbes and Health, Quadram Institute, Norwich, NR4 7UQ, UK
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| |
Collapse
|
36
|
Pan S, Zhao XM, Coelho LP. SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing. Bioinformatics 2023; 39:i21-i29. [PMID: 37387171 PMCID: PMC10311329 DOI: 10.1093/bioinformatics/btad209] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Metagenomic binning methods to reconstruct metagenome-assembled genomes (MAGs) from environmental samples have been widely used in large-scale metagenomic studies. The recently proposed semi-supervised binning method, SemiBin, achieved state-of-the-art binning results in several environments. However, this required annotating contigs, a computationally costly and potentially biased process. RESULTS We propose SemiBin2, which uses self-supervised learning to learn feature embeddings from the contigs. In simulated and real datasets, we show that self-supervised learning achieves better results than the semi-supervised learning used in SemiBin1 and that SemiBin2 outperforms other state-of-the-art binners. Compared to SemiBin1, SemiBin2 can reconstruct 8.3-21.5% more high-quality bins and requires only 25% of the running time and 11% of peak memory usage in real short-read sequencing samples. To extend SemiBin2 to long-read data, we also propose ensemble-based DBSCAN clustering algorithm, resulting in 13.1-26.3% more high-quality genomes than the second best binner for long-read data. AVAILABILITY AND IMPLEMENTATION SemiBin2 is available as open source software at https://github.com/BigDataBiology/SemiBin/ and the analysis scripts used in the study can be found at https://github.com/BigDataBiology/SemiBin2_benchmark.
Collapse
Affiliation(s)
- Shaojun Pan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China
| | - Xing-Ming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Luis Pedro Coelho
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China
| |
Collapse
|
37
|
McCallum GE, Rossiter AE, Quraishi MN, Iqbal TH, Kuehne SA, van Schaik W. Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts. Microb Genom 2023; 9:mgen001030. [PMID: 37272920 PMCID: PMC10327510 DOI: 10.1099/mgen.0.001030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 04/11/2023] [Indexed: 06/06/2023] Open
Abstract
The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut.
Collapse
Affiliation(s)
- Gregory E. McCallum
- Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Amanda E. Rossiter
- Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | | | - Tariq H. Iqbal
- Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Sarah A. Kuehne
- Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
- School of Dentistry, Institute of Clinical Sciences, University of Birmingham, Birmingham, UK
| | - Willem van Schaik
- Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| |
Collapse
|
38
|
Li L. Accessing hidden microbial biosynthetic potential from underexplored sources for novel drug discovery. Biotechnol Adv 2023:108176. [PMID: 37211187 DOI: 10.1016/j.biotechadv.2023.108176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 05/15/2023] [Accepted: 05/16/2023] [Indexed: 05/23/2023]
Abstract
Microbial natural products and their structural analogues have widely used as pharmaceutical agents, especially for infectious diseases and cancer. Despite this success, new structural classes with innovative chemistry and modes of action are urgently needed to be developed to combat the growing antimicrobial resistance and other public health problems. The advances in next-generation sequencing technologies and powerful computational tools open up new opportunities to explore microbial biosynthetic potential from underexplored sources, with millions of secondary metabolites awaiting discovery. The review highlights challenges associated with discovery of new chemical entities, rich reservoirs provided by untapped taxa, ecological niches or host microbiomes, emerging synthetic biotechnologies to unearth the hidden microbial biosynthetic potential for novel drug discovery at scale and speed.
Collapse
Affiliation(s)
- Lei Li
- State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China.
| |
Collapse
|
39
|
Ahmad N, Ritz M, Calchera A, Otte J, Schmitt I, Brueck T, Mehlmer N. Biosynthetic Potential of Hypogymnia Holobionts: Insights into Secondary Metabolite Pathways. J Fungi (Basel) 2023; 9:jof9050546. [PMID: 37233257 DOI: 10.3390/jof9050546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 05/27/2023] Open
Abstract
Lichens are symbiotic associations consisting of a photobiont (algae or cyanobacteria) and a mycobiont (fungus). They are known to produce a variety of unique secondary metabolites. To access this biosynthetic potential for biotechnological applications, deeper insights into the biosynthetic pathways and corresponding gene clusters are necessary. Here we provide a comprehensive view of the biosynthetic gene clusters of all organisms comprising a lichen thallus: fungi, green algae, and bacteria. We present two high-quality PacBio metagenomes, in which we identified a total of 460 biosynthetic gene clusters. Lichen mycobionts yielded 73-114 clusters, other lichen associated ascomycetes 8-40, green algae of the genus Trebouxia 14-19, and lichen-associated bacteria 101-105 clusters. The mycobionts contained mainly T1PKSs, followed by NRPSs, and terpenes; Trebouxia reads harbored mainly clusters linked to terpenes, followed by NRPSs and T3PKSs. Other lichen-associated ascomycetes and bacteria contained a mix of diverse biosynthetic gene clusters. In this study, we identified for the first time the biosynthetic gene clusters of entire lichen holobionts. The yet untapped biosynthetic potential of two species of the genus Hypogymnia is made accessible for further research.
Collapse
Affiliation(s)
- Nadim Ahmad
- Werner Siemens Chair of Synthetic Biotechnology, Department of Chemistry, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Manfred Ritz
- Werner Siemens Chair of Synthetic Biotechnology, Department of Chemistry, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Anjuli Calchera
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage 25, 60325 Frankfurt am Main, Germany
| | - Jürgen Otte
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage 25, 60325 Frankfurt am Main, Germany
| | - Imke Schmitt
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage 25, 60325 Frankfurt am Main, Germany
- Institute of Ecology, Evolution and Diversity, Goethe University Frankfurt, Max-von-Laue-Straße 13, 60438 Frankfurt am Main, Germany
| | - Thomas Brueck
- Werner Siemens Chair of Synthetic Biotechnology, Department of Chemistry, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Norbert Mehlmer
- Werner Siemens Chair of Synthetic Biotechnology, Department of Chemistry, Technical University of Munich (TUM), 85748 Garching, Germany
| |
Collapse
|
40
|
Jia L, Wu Y, Dong Y, Chen J, Chen WH, Zhao XM. A survey on computational strategies for genome-resolved gut metagenomics. Brief Bioinform 2023; 24:7145904. [PMID: 37114640 DOI: 10.1093/bib/bbad162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 03/20/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
Recovering high-quality metagenome-assembled genomes (HQ-MAGs) is critical for exploring microbial compositions and microbe-phenotype associations. However, multiple sequencing platforms and computational tools for this purpose may confuse researchers and thus call for extensive evaluation. Here, we systematically evaluated a total of 40 combinations of popular computational tools and sequencing platforms (i.e. strategies), involving eight assemblers, eight metagenomic binners and four sequencing technologies, including short-, long-read and metaHiC sequencing. We identified the best tools for the individual tasks (e.g. the assembly and binning) and combinations (e.g. generating more HQ-MAGs) depending on the availability of the sequencing data. We found that the combination of the hybrid assemblies and metaHiC-based binning performed best, followed by the hybrid and long-read assemblies. More importantly, both long-read and metaHiC sequencings link more mobile elements and antibiotic resistance genes to bacterial hosts and improve the quality of public human gut reference genomes with 32% (34/105) HQ-MAGs that were either of better quality than those in the Unified Human Gastrointestinal Genome catalog version 2 or novel.
Collapse
Affiliation(s)
- Longhao Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Yingjian Wu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Yanqi Dong
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Jingchao Chen
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Wei-Hua Chen
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
- Institution of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China
| | - Xing-Ming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Ministry of Education, Shanghai 200433, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| |
Collapse
|
41
|
Sereika M, Petriglieri F, Jensen TBN, Sannikov A, Hoppe M, Nielsen PH, Marshall IPG, Schramm A, Albertsen M. Closed genomes uncover a saltwater species of Candidatus Electronema and shed new light on the boundary between marine and freshwater cable bacteria. THE ISME JOURNAL 2023; 17:561-569. [PMID: 36697964 PMCID: PMC10030654 DOI: 10.1038/s41396-023-01372-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 01/26/2023]
Abstract
Cable bacteria of the Desulfobulbaceae family are centimeter-long filamentous bacteria, which are capable of conducting long-distance electron transfer. Currently, all cable bacteria are classified into two candidate genera: Candidatus Electronema, typically found in freshwater environments, and Candidatus Electrothrix, typically found in saltwater environments. This taxonomic framework is based on both 16S rRNA gene sequences and metagenome-assembled genome (MAG) phylogenies. However, most of the currently available MAGs are highly fragmented, incomplete, and thus likely miss key genes essential for deciphering the physiology of cable bacteria. Also, a closed, circular genome of cable bacteria has not been published yet. To address this, we performed Nanopore long-read and Illumina short-read shotgun sequencing of selected environmental samples and a single-strain enrichment of Ca. Electronema aureum. We recovered multiple cable bacteria MAGs, including two circular and one single-contig. Phylogenomic analysis, also confirmed by 16S rRNA gene-based phylogeny, classified one circular MAG and the single-contig MAG as novel species of cable bacteria, which we propose to name Ca. Electronema halotolerans and Ca. Electrothrix laxa, respectively. The Ca. Electronema halotolerans, despite belonging to the previously recognized freshwater genus of cable bacteria, was retrieved from brackish-water sediment. Metabolic predictions showed several adaptations to a high salinity environment, similar to the "saltwater" Ca. Electrothrix species, indicating how Ca. Electronema halotolerans may be the evolutionary link between marine and freshwater cable bacteria lineages.
Collapse
Affiliation(s)
- Mantas Sereika
- Center for Microbial Communities, Aalborg University, Aalborg, Denmark
| | | | | | - Artur Sannikov
- Center for Electromicrobiology, Aarhus University, Aarhus, Denmark
| | - Morten Hoppe
- Center for Electromicrobiology, Aarhus University, Aarhus, Denmark
| | | | - Ian P G Marshall
- Center for Electromicrobiology, Aarhus University, Aarhus, Denmark
| | - Andreas Schramm
- Center for Electromicrobiology, Aarhus University, Aarhus, Denmark
| | - Mads Albertsen
- Center for Microbial Communities, Aalborg University, Aalborg, Denmark.
| |
Collapse
|
42
|
Zhu G, Chao H, Sun M, Jiang Y, Ye M. Toxicity sharing model of earthworm intestinal microbiome reveals shared functional genes are more powerful than species in resisting pesticide stress. JOURNAL OF HAZARDOUS MATERIALS 2023; 446:130646. [PMID: 36587599 DOI: 10.1016/j.jhazmat.2022.130646] [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: 10/07/2022] [Revised: 12/06/2022] [Accepted: 12/19/2022] [Indexed: 06/17/2023]
Abstract
Earthworm intestinal bacteria and indigenous soil bacteria work closely during various biochemical processes and play a crucial role in maintaining the internal stability of the soil environment. However, the response mechanism of these bacterial communities to external pesticide disturbance is unknown. In this study, soil and earthworm gut contents were metagenomically sequenced after exposure to various concentrations of nitrochlorobenzene (0-1026.7 mg kg-1). A high degree of similarity was found between the microbial community composition and abundance in the worm gut and soil, both of which decreased significantly (P < 0.05) under elevated pesticide stress. The toxicity sharing model (TSM) showed that the toxicity sharing capacity was 97.4-125.7 % and 100.4-130.2 % for Egenes (genes in the worm gut) and Emet(degradation genes in the worm gut) in the earthworm intestinal microbiome, respectively. This indicated that the earthworm intestinal microbiome assisted in relieving the pesticide toxicity of the indigenous soil microbiome. This study showed that the TSM could quantitatively describe the toxic effect of pesticides on the earthworm intestinal microbiome. It provides a new analytical model for investigating the ecological alliance between earthworm intestinal microbiome and indigenous soil microbiome under pesticide stress while contributing a more profound understanding of the potential to use earthworms to mitigate pesticide pollution in soils and develop earthworm-based soil remediation techniques.
Collapse
Affiliation(s)
- Guofan Zhu
- National Engineering Laboratort of Soil Nutrients Management, Pollution Control and Remediation Technoligies, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Huizhen Chao
- Soil Ecology Lab, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Mingming Sun
- Soil Ecology Lab, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuji Jiang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 210008 Nanjing, China
| | - Mao Ye
- National Engineering Laboratort of Soil Nutrients Management, Pollution Control and Remediation Technoligies, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China.
| |
Collapse
|
43
|
Loy JD, Clawson ML, Adkins PRF, Middleton JR. Current and Emerging Diagnostic Approaches to Bacterial Diseases of Ruminants. Vet Clin North Am Food Anim Pract 2023; 39:93-114. [PMID: 36732002 DOI: 10.1016/j.cvfa.2022.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
The diagnostic approaches and methods to detect bacterial pathogens in ruminants are discussed, with a focus on cattle. Conventional diagnostic methods using culture, isolation, and characterization are being replaced or supplemented with new methods. These include molecular diagnostics such as real-time polymerase chain reaction and whole-genome sequencing. In addition, methods such as matrix-assisted laser desorption ionization-time-of-flight mass spectrometry enable rapid identification and enhanced pathogen characterization. These emerging diagnostic tools can greatly enhance the ability to detect and characterize pathogens, but performance and interpretation vary greatly across sample and pathogen types, disease syndromes, assay performance, and other factors.
Collapse
Affiliation(s)
- John Dustin Loy
- Nebraska Veterinary Diagnostic Center, School of Veterinary Medicine and Biomedical Sciences, University of Nebraska-Lincoln, Lincoln, NE, USA.
| | - Michael L Clawson
- USDA, Agriculture Research Service US Meat Animal Research Center, Clay Center, NE, USA
| | - Pamela R F Adkins
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| | - John R Middleton
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| |
Collapse
|
44
|
Eco-evolutionary implications of helminth microbiomes. J Helminthol 2023; 97:e22. [PMID: 36790127 DOI: 10.1017/s0022149x23000056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
The evolution of helminth parasites has long been seen as an interplay between host resistance to infection and the parasite's capacity to bypass such resistance. However, there has recently been an increasing appreciation of the role of symbiotic microbes in the interaction of helminth parasites and their hosts. It is now clear that helminths have a different microbiome from the organisms they parasitize, and sometimes amid large variability, components of the microbiome are shared among different life stages or among populations of the parasite. Helminths have been shown to acquire microbes from their parent generations (vertical transmission) and from their surroundings (horizontal transmission). In this latter case, natural selection has been strongly linked to the fact that helminth-associated microbiota is not simply a random assemblage of the pool of microbes available from their organismal hosts or environments. Indeed, some helminth parasites and specific microbial taxa have evolved complex ecological relationships, ranging from obligate mutualism to reproductive manipulation of the helminth by associated microbes. However, our understanding is still very elementary regarding the net effect of all microbiome components in the eco-evolution of helminths and their interaction with hosts. In this non-exhaustible review, we focus on the bacterial microbiome associated with helminths (as opposed to the microbiome of their hosts) and highlight relevant concepts and key findings in bacterial transmission, ecological associations, and taxonomic and functional diversity of the bacteriome. We integrate the microbiome dimension in a discussion of the evolution of helminth parasites and identify fundamental knowledge gaps, finally suggesting research avenues for understanding the eco-evolutionary impacts of the microbiome in host-parasite interactions in light of new technological developments.
Collapse
|
45
|
Improved Assembly of Metagenome-Assembled Genomes and Viruses in Tibetan Saline Lake Sediment by HiFi Metagenomic Sequencing. Microbiol Spectr 2023; 11:e0332822. [PMID: 36475839 PMCID: PMC9927493 DOI: 10.1128/spectrum.03328-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
With the development and reduced costs of high-throughput sequencing technology, environmental dark matter, such as novel metagenome-assembled genomes (MAGs) and viruses, is now being discovered easily. However, due to read length limitations, MAGs and viromes often suffer from genome discontinuity and deficiencies in key functional elements. Here, by applying long-read sequencing technology to sediment samples from a Tibetan saline lake, we comprehensively analyzed the performance of high-fidelity (HiFi) reads and the possibility of integration with short-read next-generation sequencing (NGS) data. In total, 207 full-length nonredundant 16S rRNA gene sequences and 19 full-length nonredundant 18S rRNA genes were directly obtained from HiFi reads, which greatly surpassed the retrieval performance of NGS technology. We carried out a cross-sectional comparison among multiple assembly strategies, referred to as 'NGS', 'Hybrid (NGS+HiFi)', and 'HiFi'. Two MAGs and 29 viruses with circular genomes were reconstructed using HiFi reads alone, indicating the great power of the 'HiFi' approach to assemble high-quality microbial genomes. Among the 3 strategies, the 'Hybrid' approach produced the highest number of medium/high-quality MAGs and viral genomes, while the ratio of MAGs containing 16S rRNA genes was significantly improved in the 'HiFi' assembly results. Overall, our study provides a practical metagenomic resolution for analyzing complex environmental samples by taking advantage of both the short-read and HiFi long-read sequencing methods to extract the maximum amount of information, including data on prokaryotes, eukaryotes, and viruses, via the 'Hybrid' approach. IMPORTANCE To expand the understanding of microbial dark matter in the environment, we did the first comparative evaluation of multiple assembly strategies based on high-throughput short-read and HiFi data from lake sediments metagenomic sequencing. The results demonstrated great improvement of the 'Hybrid' assembly method (short-read next-generation sequencing data plus HiFi data) in the recovery of medium/high-quality MAGs and viral genomes. Further analysis showed that HiFi data is important to retrieve the complete circular prokaryotic and viral genomes. Meanwhile, hundreds of full-length 16S/18S rRNA genes were assembled directly from HiFi data, which facilitated the species composition studies of complex environmental samples, especially for understanding micro-eukaryotes. Therefore, the application of the latest HiFi long-read sequencing could greatly improve the metagenomic assembly integrity and promote environmental microbiome research.
Collapse
|
46
|
Sun S, Zhang M, Gu X, Yan P, He S, Chachar A. New insight and enhancement mechanisms for Feammox process by electron shuttles in wastewater treatment - A systematic review. BIORESOURCE TECHNOLOGY 2023; 369:128495. [PMID: 36526117 DOI: 10.1016/j.biortech.2022.128495] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
Ammonium oxidation coupled to Fe(III) reduction (Feammox) is a newly discovered iron-nitrogen cycle process of microbial catalyzed NH4+ oxidation coupled with iron reduction. Fe(III) often exists in the form of insoluble iron minerals resulting in reduced microbial availability and low efficiency of Feammox. Electron shuttles(ESs) can be reversibly oxidized and reduced which has the potential to improve Feammox efficiency. This review summarizes the discovery process, electron transfer mechanism, influencing factors and driven microorganisms of Feammox, ang expounds the possibility and potential mechanism of ESs to enhance Feammox efficiency. Based on an in-depth analysis of the current research situation of Feammox for nitrogen removal, the knowledge gaps and future research directions including how to apply ESs enhanced Feammox to promote nitrogen removal in practical wastewater treatment have been highlighted. This review can provide new ideas for the engineering application research of Feammox and strong theoretical support for its development.
Collapse
Affiliation(s)
- Shanshan Sun
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Manping Zhang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Xushun Gu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Pan Yan
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Shengbing He
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 20092, PR China; Shanghai Engineering Research Center of Landscape Water Environment, Shanghai 200031, PR China.
| | - Azharuddin Chachar
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
| |
Collapse
|
47
|
Jiang F, Li Q, Wang S, Shen T, Wang H, Wang A, Xu D, Yuan L, Lei L, Chen R, Yang B, Deng Y, Fan W. Recovery of metagenome-assembled microbial genomes from a full-scale biogas plant of food waste by pacific biosciences high-fidelity sequencing. Front Microbiol 2023; 13:1095497. [PMID: 36699587 PMCID: PMC9869026 DOI: 10.3389/fmicb.2022.1095497] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 12/20/2022] [Indexed: 01/12/2023] Open
Abstract
Background Anaerobic digestion (AD) is important in treating of food waste, and thousands of metagenome-assembled genomes (MAGs) have been constructed for the microbiome in AD. However, due to the limitations of the short-read sequencing and assembly technologies, most of these MAGs are grouped from hundreds of short contigs by binning algorithms, and the errors are easily introduced. Results In this study, we constructed a total of 60 non-redundant microbial genomes from 64.5 Gb of PacBio high-fidelity (HiFi) long reads, generated from the digestate samples of a full-scale biogas plant fed with food waste. Of the 60 microbial genomes, all genomes have at least one copy of rRNA operons (16S, 23S, and 5S rRNA), 54 have ≥18 types of standard tRNA genes, and 39 are circular complete genomes. In comparison with the published short-read derived MAGs for AD, we found 23 genomes with average nucleotide identity less than 95% to any known MAGs. Besides, our HiFi-derived genomes have much higher average contig N50 size, slightly higher average genome size and lower contamination. GTDB-Tk classification of these genomes revealed two genomes belonging to novel genus and four genomes belonging to novel species, since their 16S rRNA genes have identities lower than 95 and 97% to any known 16S rRNA genes, respectively. Microbial community analysis based on the these assembled genomes reveals the most predominant phylum was Thermotogae (70.5%), followed by Euryarchaeota (6.1%), and Bacteroidetes (4.7%), and the most predominant bacterial and archaeal genera were Defluviitoga (69.1%) and Methanothrix (5.4%), respectively. Analysis of the full-length 16S rRNA genes identified from the HiFi reads gave similar microbial compositions to that derived from the 60 assembled genomes. Conclusion High-fidelity sequencing not only generated microbial genomes with obviously improved quality but also recovered a substantial portion of novel genomes missed in previous short-read based studies, and the novel genomes will deepen our understanding of the microbial composition in AD of food waste.
Collapse
Affiliation(s)
- Fan Jiang
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Qiang Li
- Biogas Institute of Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China,Key Laboratory of Development and Application of Rural Renewable Energy, Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China
| | - Sen Wang
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Ting Shen
- Biogas Institute of Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China,Key Laboratory of Development and Application of Rural Renewable Energy, Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China
| | - Hengchao Wang
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Anqi Wang
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Dong Xu
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lihua Yuan
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lihong Lei
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Rong Chen
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Boyuan Yang
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Yu Deng
- Biogas Institute of Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China,Key Laboratory of Development and Application of Rural Renewable Energy, Ministry of Agriculture and Rural Affairs, Chengdu, Sichuan, China,*Correspondence: Yu Deng, ; Wei Fan,
| | - Wei Fan
- Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China,*Correspondence: Yu Deng, ; Wei Fan,
| |
Collapse
|
48
|
Improving cassava bacterial blight resistance by editing the epigenome. Nat Commun 2023; 14:85. [PMID: 36604425 PMCID: PMC9816117 DOI: 10.1038/s41467-022-35675-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 12/15/2022] [Indexed: 01/07/2023] Open
Abstract
Pathogens rely on expression of host susceptibility (S) genes to promote infection and disease. As DNA methylation is an epigenetic modification that affects gene expression, blocking access to S genes through targeted methylation could increase disease resistance. Xanthomonas phaseoli pv. manihotis, the causal agent of cassava bacterial blight (CBB), uses transcription activator-like20 (TAL20) to induce expression of the S gene MeSWEET10a. In this work, we direct methylation to the TAL20 effector binding element within the MeSWEET10a promoter using a synthetic zinc-finger DNA binding domain fused to a component of the RNA-directed DNA methylation pathway. We demonstrate that this methylation prevents TAL20 binding, blocks transcriptional activation of MeSWEET10a in vivo and that these plants display decreased CBB symptoms while maintaining normal growth and development. This work therefore presents an epigenome editing approach useful for crop improvement.
Collapse
|
49
|
Ferrillo A, Kobel CM, Vera-Ponce de León A, La Rosa SL, Kunath BJ, Pope PB, Hagen LH. Long-Read Metagenomics and CAZyme Discovery. Methods Mol Biol 2023; 2657:253-284. [PMID: 37149537 DOI: 10.1007/978-1-0716-3151-5_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Microorganisms play a primary role in regulating biogeochemical cycles and are a valuable source of enzymes that have biotechnological applications, such as carbohydrate-active enzymes (CAZymes). However, the inability to culture the majority of microorganisms that exist in natural ecosystems restricts access to potentially novel bacteria and beneficial CAZymes. While commonplace molecular-based culture-independent methods such as metagenomics enable researchers to study microbial communities directly from environmental samples, recent progress in long-read sequencing technologies are advancing the field. We outline key methodological stages that are required as well as describe specific protocols that are currently used for long-read metagenomic projects dedicated to CAZyme discovery.
Collapse
Affiliation(s)
- Alessandra Ferrillo
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
| | - Carl Mathias Kobel
- Faculty of Bioscience, Norwegian University of Life Sciences, Aas, Norway
| | - Arturo Vera-Ponce de León
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
- Faculty of Bioscience, Norwegian University of Life Sciences, Aas, Norway
| | - Sabina Leanti La Rosa
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
| | | | - Phillip Byron Pope
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
- Faculty of Bioscience, Norwegian University of Life Sciences, Aas, Norway
| | - Live Heldal Hagen
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
| |
Collapse
|
50
|
Affiliation(s)
- Mads Albertsen
- Center for Microbial Communities, Aalborg University, Aalborg, Denmark.
| |
Collapse
|