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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.
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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
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2
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Wu R, Ji P, Hua Y, Li H, Zhang W, Wei Y. Research progress in isolation and identification of rumen probiotics. Front Cell Infect Microbiol 2024; 14:1411482. [PMID: 38836057 PMCID: PMC11148321 DOI: 10.3389/fcimb.2024.1411482] [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: 04/03/2024] [Accepted: 04/30/2024] [Indexed: 06/06/2024] Open
Abstract
With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.
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Affiliation(s)
| | - Peng Ji
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | | | | | | | - Yanming Wei
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
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3
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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.
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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.
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4
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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.
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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
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5
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Heljanko V, Tyni O, Johansson V, Virtanen JP, Räisänen K, Lehto KM, Lipponen A, Oikarinen S, Pitkänen T, Heikinheimo A. Clinically relevant sequence types of carbapenemase-producing Escherichia coli and Klebsiella pneumoniae detected in Finnish wastewater in 2021-2022. Antimicrob Resist Infect Control 2024; 13:14. [PMID: 38291521 PMCID: PMC10829384 DOI: 10.1186/s13756-024-01370-z] [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: 10/06/2023] [Accepted: 01/22/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Antimicrobial resistance (AMR) is a critical threat to human health. Escherichia coli and Klebsiella pneumoniae are clinically the most important species associated with AMR and are the most common carbapenemase-producing (CP) Enterobacterales detected in human specimens in Finland. Wastewater surveillance has emerged as a potential approach for population-level surveillance of AMR, as wastewater could offer a reflection from a larger population with one sample and minimal recognized ethical issues. In this study, we investigated the potential of wastewater surveillance to detect CP E. coli and K. pneumoniae strains similar to those detected in human specimens. METHODS Altogether, 89 composite samples of untreated community wastewater were collected from 10 wastewater treatment plants across Finland in 2021-2022. CP E. coli and K. pneumoniae were isolated using selective culture media and identified using MALDI-TOF MS. Antimicrobial susceptibility testing was performed using disk diffusion test and broth microdilution method, and a subset of isolates was characterized using whole-genome sequencing. RESULTS CP E. coli was detected in 26 (29.2%) and K. pneumoniae in 25 (28.1%) samples. Among E. coli, the most common sequence type (ST) was ST410 (n = 7/26, 26.9%), while ST359 (n = 4/25, 16.0%) predominated among K. pneumoniae. Globally successful STs were detected in both E. coli (ST410, ST1284, ST167, and ST405) and K. pneumoniae (ST512, ST101, and ST307). K. pneumoniae carbapenemases (KPC) were the most common carbapenemases in both E. coli (n = 11/26, 42.3%) and K. pneumoniae (n = 13/25, 52.0%), yet also other carbapenemases, such as blaNDM-5, blaOXA-48, and blaOXA-181, were detected. We detected isolates harboring similar ST and enzyme type combinations previously linked to clusters in Finland, such as E. coli ST410 with blaKPC-2 and K. pneumoniae ST512 with blaKPC-3. CONCLUSIONS Our study highlights the presence of clinically relevant strains of CP E. coli and K. pneumoniae in community wastewater. The results indicate that wastewater surveillance could serve as a monitoring tool for CP Enterobacterales. However, the specificity and sensitivity of the methods should be improved, and technologies, like advanced sequencing methods, should be utilized to distinguish data with public health relevance, harness the full potential of wastewater surveillance, and implement the data in public health surveillance.
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Affiliation(s)
- Viivi Heljanko
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland.
| | - Olga Tyni
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Venla Johansson
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | | | - Kati Räisänen
- Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Kirsi-Maarit Lehto
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Anssi Lipponen
- Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland
| | - Sami Oikarinen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Tarja Pitkänen
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
- Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland
| | - Annamari Heikinheimo
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
- Finnish Food Authority, Seinäjoki, Finland
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6
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Jitsuno K, Hoshino T, Nishikawa Y, Kogawa M, Mineta K, Strasser M, Ikehara K, Everest J, Maeda L, Inagaki F, Takeyama H. Comparative single-cell genomics of Atribacterota JS1 in the Japan Trench hadal sedimentary biosphere. mSphere 2024; 9:e0033723. [PMID: 38170974 PMCID: PMC10826368 DOI: 10.1128/msphere.00337-23] [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: 07/13/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
Deep-sea and subseafloor sedimentary environments host heterotrophic microbial communities that contribute to Earth's carbon cycling. However, the potential metabolic functions of individual microorganisms and their biogeographical distributions in hadal ocean sediments remain largely unexplored. In this study, we conducted single-cell genome sequencing on sediment samples collected from six sites (7,445-8,023 m water depth) along an approximately 500 km transect of the Japan Trench during the International Ocean Discovery Program Expedition 386. A total of 1,886 single-cell amplified genomes (SAGs) were obtained, offering comprehensive genetic insights into sedimentary microbial communities in surface sediments (<1 m depth) above the sulfate-methane transition zone along the Japan Trench. Our genome data set included 269 SAGs from Atribacterota JS1, the predominant bacterial clade in these hadal environments. Phylogenetic analysis classified SAGs into nine distinct phylotypes, whereas metagenome-assembled genomes were categorized into only two phylotypes, advancing JS1 diversity coverage through a single cell-based approach. Comparative genomic analysis of JS1 lineages from different habitats revealed frequent detection of genes related to organic carbon utilization, such as extracellular enzymes like clostripain and α-amylase, and ABC transporters of oligopeptide from Japan Trench members. Furthermore, specific JS1 phylotypes exhibited a strong correlation with in situ methane concentrations and contained genes involved in glycine betaine metabolism. These findings suggest that the phylogenomically diverse and novel Atribacterota JS1 is widely distributed in Japan Trench sediment, playing crucial roles in carbon cycling within the hadal sedimentary biosphere.IMPORTANCEThe Japan Trench represents tectonically active hadal environments associated with Pacific plate subduction beneath the northeastern Japan arc. This study, for the first time, documented a large-scale single-cell and metagenomic survey along an approximately 500 km transect of the Japan Trench, obtaining high-quality genomic information on hadal sedimentary microbial communities. Single-cell genomics revealed the predominance of diverse JS1 lineages not recoverable through conventional metagenomic binning. Their metabolic potential includes genes related to the degradation of organic matter, which contributes to methanogenesis in the deeper layers. Our findings enhance understanding of sedimentary microbial communities at water depths exceeding 7,000 m and provide new insights into the ecological role of biogeochemical carbon cycling in the hadal sedimentary biosphere.
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Affiliation(s)
- Kana Jitsuno
- Graduate School of Advanced Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan
- CBBD-OIL, AIST-Waseda University, Shinjuku-ku, Tokyo, Japan
| | - Tatsuhiko Hoshino
- Kochi Institute for Core Sample Research, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nankoku, Kochi, Japan
| | - Yohei Nishikawa
- CBBD-OIL, AIST-Waseda University, Shinjuku-ku, Tokyo, Japan
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
| | - Masato Kogawa
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
| | - Katsuhiko Mineta
- CBBD-OIL, AIST-Waseda University, Shinjuku-ku, Tokyo, Japan
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
- Marine Open Innovation Institute, Shizuoka, Japan
| | - Michael Strasser
- Department of Geology, University of Innsbruck, Innsbruck, Austria
| | - Ken Ikehara
- Research Institute of Geology and Geoinformation, AIST Geological Survey of Japan, Tsukuba, Japan
| | | | - Lena Maeda
- Advanced Institute for Marine Ecosystem Change (WPI-AIMEC), JAMSTEC, Yokohama, Japan
| | - Fumio Inagaki
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
- Advanced Institute for Marine Ecosystem Change (WPI-AIMEC), JAMSTEC, Yokohama, Japan
- Department of Earth Sciences, Graduate School of Science, Tohoku University, Sendai, Japan
| | - Haruko Takeyama
- Graduate School of Advanced Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan
- CBBD-OIL, AIST-Waseda University, Shinjuku-ku, Tokyo, Japan
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, Tokyo, Japan
| | - IODP Expedition 386 ScientistsBellanovaPieroBrunetMorganeCaiZhirongCattaneoAntonioHochmuthKatharinaHsiungKanhsiIshizawaTakashiItakiTakuyaJitsunoKanaJohnsonJoelKanamatsuToshiyaKeepMyraKiokaArataMaerzChristianMcHughCeciliaMicallefAaronMinLuoPandeyDhananjaiProustJean NoelRasburyTroyRiedingerNataschaBaoRuiSatoguchiYasufumiSawyerDerekSeibertChloeSilverMaxwellStraubSusanneVirtasaloJoonasWangYonghongWuTing-WeiZellersSarahKöllingMartinHuangJyh-Jaan StevenNagahashiYoshitaka
- Graduate School of Advanced Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan
- CBBD-OIL, AIST-Waseda University, Shinjuku-ku, Tokyo, Japan
- Kochi Institute for Core Sample Research, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nankoku, Kochi, Japan
- Research organization for Nano and Life Innovation, Waseda University, Shinjuku-ku, Tokyo, Japan
- Marine Open Innovation Institute, Shizuoka, Japan
- Department of Geology, University of Innsbruck, Innsbruck, Austria
- Research Institute of Geology and Geoinformation, AIST Geological Survey of Japan, Tsukuba, Japan
- British Geological Survey, Edinburgh, United Kingdom
- Advanced Institute for Marine Ecosystem Change (WPI-AIMEC), JAMSTEC, Yokohama, Japan
- Department of Earth Sciences, Graduate School of Science, Tohoku University, Sendai, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, Tokyo, Japan
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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.
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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
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8
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Pedroza Matute S, Iyavoo S. Exploring the gut microbiota: lifestyle choices, disease associations, and personal genomics. Front Nutr 2023; 10:1225120. [PMID: 37867494 PMCID: PMC10585655 DOI: 10.3389/fnut.2023.1225120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 09/19/2023] [Indexed: 10/24/2023] Open
Abstract
The gut microbiota is a rich and dynamic ecosystem that actively interacts with the human body, playing a significant role in the state of health and disease of the host. Diet, exercise, mental health, and other factors have exhibited the ability to influence the gut bacterial composition, leading to changes that can prevent and improve, or favor and worsen, both intestinal and extra-intestinal conditions. Altered gut microbial states, or 'dysbiosis', associated with conditions and diseases are often characterized by shifts in bacterial abundance and diversity, including an impaired Firmicutes to Bacteroidetes ratio. By understanding the effect of lifestyle on the gut microbiota, personalized advice can be generated to suit each individual profile and foster the adoption of lifestyle changes that can both prevent and ameliorate dysbiosis. The delivery of effective and reliable advice, however, depends not only on the available research and current understanding of the topic, but also on the methods used to assess individuals and to discover the associations, which can introduce bias at multiple stages. The aim of this review is to summarize how human gut microbial variability is defined and what lifestyle choices and diseases have shown association with gut bacterial composition. Furthermore, popular methods to investigate the human gut microbiota are outlined, with a focus on the possible bias caused by the lack of use of standardized methods. Finally, an overview of the current state of personalized advice based on gut microbiota testing is presented, underlining its power and limitations.
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Affiliation(s)
| | - Sasitaran Iyavoo
- Nkaarco Diagnostics Limited, Norwich, United Kingdom
- School of Chemistry, College of Health and Science, University of Lincoln, Lincoln, United Kingdom
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9
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Madhu B, Miller BM, Levy M. Single-cell analysis and spatial resolution of the gut microbiome. Front Cell Infect Microbiol 2023; 13:1271092. [PMID: 37860069 PMCID: PMC10582963 DOI: 10.3389/fcimb.2023.1271092] [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: 08/01/2023] [Accepted: 09/11/2023] [Indexed: 10/21/2023] Open
Abstract
Over the past decade it has become clear that various aspects of host physiology, metabolism, and immunity are intimately associated with the microbiome and its interactions with the host. Specifically, the gut microbiome composition and function has been shown to play a critical role in the etiology of different intestinal and extra-intestinal diseases. While attempts to identify a common pattern of microbial dysbiosis linked with these diseases have failed, multiple studies show that bacterial communities in the gut are spatially organized and that disrupted spatial organization of the gut microbiome is often a common underlying feature of disease pathogenesis. As a result, focus over the last few years has shifted from analyzing the diversity of gut microbiome by sequencing of the entire microbial community, towards understanding the gut microbiome in spatial context. Defining the composition and spatial heterogeneity of the microbiome is critical to facilitate further understanding of the gut microbiome ecology. Development in single cell genomics approach has advanced our understanding of microbial community structure, however, limitations in approaches exist. Single cell genomics is a very powerful and rapidly growing field, primarily used to identify the genetic composition of microbes. A major challenge is to isolate single cells for genomic analyses. This review summarizes the different approaches to study microbial genomes at single-cell resolution. We will review new techniques for microbial single cell sequencing and summarize how these techniques can be applied broadly to answer many questions related to the microbiome composition and spatial heterogeneity. These methods can be used to fill the gaps in our understanding of microbial communities.
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Affiliation(s)
| | | | - Maayan Levy
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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10
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Abate A, Li X, Xu L, Demaree B, Noecker C, Bisanz J, Weisgerber D, Modavi C, Turnbaugh P. Microbiome single cell atlases generated with a commercial instrument. RESEARCH SQUARE 2023:rs.3.rs-3253785. [PMID: 37790580 PMCID: PMC10543498 DOI: 10.21203/rs.3.rs-3253785/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes' genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform.
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11
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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.
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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
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12
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Hosokawa M, Iwai N, Arikawa K, Saeki T, Endoh T, Kamata K, Yoda T, Tsuda S, Takeyama H. Target enrichment of uncultured human oral bacteria with phage-derived molecules found by single-cell genomics. J Biosci Bioeng 2023:S1389-1723(23)00116-0. [PMID: 37188549 DOI: 10.1016/j.jbiosc.2023.04.005] [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: 02/23/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 05/17/2023]
Abstract
Advances in culture-independent microbial analysis, such as metagenomics and single-cell genomics, have significantly increased our understanding of microbial lineages. While these methods have uncovered a large number of novel microbial taxa, many remain uncultured, and their function and mode of existence in the environment are still unknown. This study aims to explore the use of bacteriophage-derived molecules as probes for detecting and isolating uncultured bacteria. Here, we proposed multiplex single-cell sequencing to obtain massive uncultured oral bacterial genomes and searched prophage sequences from over 450 obtained human oral bacterial single-amplified genomes (SAGs). The focus was on the cell wall binding domain (CBD) in phage endolysin, and fluorescent protein-fused CBDs were generated based on several CBD gene sequences predicted from Streptococcus SAGs. The ability of the Streptococcus prophage-derived CBDs to detect and enrich specific Streptococcus species from human saliva while maintaining cell viability was confirmed by magnetic separation and flow cytometry. The approach to phage-derived molecule generation based on uncultured bacterial SAG is expected to improve the process of designing molecules that selectively capture or detect specific bacteria, notably from uncultured gram-positive bacteria, and will have applications in isolation and in situ detection of beneficial or pathogenic bacteria.
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Affiliation(s)
- 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.
| | - Naoya Iwai
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
| | - 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
| | - Tatsuya Saeki
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Taruho Endoh
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Kazuma Kamata
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Takuya Yoda
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Soichiro Tsuda
- bitBiome, Inc., 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Haruko Takeyama
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, 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
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13
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Berihu M, Somera TS, Malik A, Medina S, Piombo E, Tal O, Cohen M, Ginatt A, Ofek-Lalzar M, Doron-Faigenboim A, Mazzola M, Freilich S. A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data. MICROBIOME 2023; 11:8. [PMID: 36635724 PMCID: PMC9835355 DOI: 10.1186/s40168-022-01438-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND The design of ecologically sustainable and plant-beneficial soil systems is a key goal in actively manipulating root-associated microbiomes. Community engineering efforts commonly seek to harness the potential of the indigenous microbiome through substrate-mediated recruitment of beneficial members. In most sustainable practices, microbial recruitment mechanisms rely on the application of complex organic mixtures where the resources/metabolites that act as direct stimulants of beneficial groups are not characterized. Outcomes of such indirect amendments are unpredictable regarding engineering the microbiome and achieving a plant-beneficial environment. RESULTS This study applied network analysis of metagenomics data to explore amendment-derived transformations in the soil microbiome, which lead to the suppression of pathogens affecting apple root systems. Shotgun metagenomic analysis was conducted with data from 'sick' vs 'healthy/recovered' rhizosphere soil microbiomes. The data was then converted into community-level metabolic networks. Simulations examined the functional contribution of treatment-associated taxonomic groups and linked them with specific amendment-induced metabolites. This analysis enabled the selection of specific metabolites that were predicted to amplify or diminish the abundance of targeted microbes functional in the healthy soil system. Many of these predictions were corroborated by experimental evidence from the literature. The potential of two of these metabolites (dopamine and vitamin B12) to either stimulate or suppress targeted microbial groups was evaluated in a follow-up set of soil microcosm experiments. The results corroborated the stimulant's potential (but not the suppressor) to act as a modulator of plant beneficial bacteria, paving the way for future development of knowledge-based (rather than trial and error) metabolic-defined amendments. Our pipeline for generating predictions for the selective targeting of microbial groups based on processing assembled and annotated metagenomics data is available at https://github.com/ot483/NetCom2 . CONCLUSIONS This research demonstrates how genomic-based algorithms can be used to formulate testable hypotheses for strategically engineering the rhizosphere microbiome by identifying specific compounds, which may act as selective modulators of microbial communities. Applying this framework to reduce unpredictable elements in amendment-based solutions promotes the development of ecologically-sound methods for re-establishing a functional microbiome in agro and other ecosystems. Video Abstract.
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Affiliation(s)
- Maria Berihu
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
| | - Tracey S. Somera
- United States Department of Agriculture-Agricultural Research Service Tree Fruit Research Lab, 1104 N. Western Ave, Wenatchee, WA 98801 USA
| | | | - Shlomit Medina
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
| | - Edoardo Piombo
- Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Grugliasco, Italy
- Department of Forest Mycology and Plant Pathology, Uppsala Biocenter, Swedish University of Agricultural Sciences, P.O. Box 7026, 75007 Uppsala, Sweden
| | - Ofir Tal
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
- Kinneret Limnological Laboratory (KLL) Israel Oceanographic and Limnological Research (IOLR), P.O. Box 447, 49500 Migdal, Israel
| | - Matan Cohen
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
| | - Alon Ginatt
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
| | | | - Adi Doron-Faigenboim
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
| | - Mark Mazzola
- United States Department of Agriculture-Agricultural Research Service Tree Fruit Research Lab, 1104 N. Western Ave, Wenatchee, WA 98801 USA
- Department of Plant Pathology, Stellenbosch University, Private Bag X1, Matieland, 7600 South Africa
| | - Shiri Freilich
- Agricultural Research Organization (ARO), Institute of Plant Sciences, Rishon LeZion/Ramat Yishay, Israel
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14
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Kogawa M, Nishikawa Y, Saeki T, Yoda T, Arikawa K, Takeyama H, Hosokawa M. Revealing within-species diversity in uncultured human gut bacteria with single-cell long-read sequencing. Front Microbiol 2023; 14:1133917. [PMID: 36910196 PMCID: PMC9998913 DOI: 10.3389/fmicb.2023.1133917] [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: 12/29/2022] [Accepted: 02/06/2023] [Indexed: 03/14/2023] Open
Abstract
Obtaining complete and accurate bacterial genomes is vital for studying the characteristics of uncultured bacteria. Single-cell genomics is a promising approach for the culture-independent recovery of bacterial genomes from individual cells. However, single-amplified genomes (SAGs) often have fragmented and incomplete sequences due to chimeric and biased sequences introduced during the genome amplification process. To address this, we developed a single-cell amplified genome long-read assembly (scALA) workflow to construct complete circular SAGs (cSAGs) from long-read single-cell sequencing data of uncultured bacteria. We used the SAG-gel platform, which is both cost-effective and high-throughput, to obtain hundreds of short-read and long-read sequencing data for specific bacterial strains. The scALA workflow generated cSAGs by repeated in silico processing for sequence bias reduction and contig assembly. From 12 human fecal samples, including two cohabitant groups, scALA generated 16 cSAGs of three specifically targeted bacterial species: Anaerostipes hadrus, Agathobacter rectalis, and Ruminococcus gnavus. We discovered strain-specific structural variations shared among cohabiting hosts, while all cSAGs of the same species showed high homology in aligned genomic regions. A. hadrus cSAGs exhibited 10 kbp-long phage insertions, various saccharide metabolic capabilities, and different CRISPR-Cas systems in each strain. The sequence similarity of A. hadrus genomes did not necessarily correspond with orthologous functional genes, while host geographical regionality seemed to be highly related to gene possession. scALA allowed us to obtain closed circular genomes of specifically targeted bacteria from human microbiota samples, leading to an understanding of within-species diversities, including structural variations and linking mobile genetic elements, such as phages, to hosts. These analyses provide insight into microbial evolution, the adaptation of the community to environmental changes, and interactions with hosts. cSAGs constructed using this method can expand bacterial genome databases and our understanding of within-species diversities in uncultured bacteria.
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Affiliation(s)
- Masato Kogawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan
| | - Yohei Nishikawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan.,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| | | | | | | | - Haruko Takeyama
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan.,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.,Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan.,Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan
| | - Masahito Hosokawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan.,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.,bitBiome, Inc., Tokyo, Japan.,Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan.,Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan
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15
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Anderson BD, Bisanz JE. Challenges and opportunities of strain diversity in gut microbiome research. Front Microbiol 2023; 14:1117122. [PMID: 36876113 PMCID: PMC9981649 DOI: 10.3389/fmicb.2023.1117122] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 01/24/2023] [Indexed: 02/19/2023] Open
Abstract
Just because two things are related does not mean they are the same. In analyzing microbiome data, we are often limited to species-level analyses, and even with the ability to resolve strains, we lack comprehensive databases and understanding of the importance of strain-level variation outside of a limited number of model organisms. The bacterial genome is highly plastic with gene gain and loss occurring at rates comparable or higher than de novo mutations. As such, the conserved portion of the genome is often a fraction of the pangenome which gives rise to significant phenotypic variation, particularly in traits which are important in host microbe interactions. In this review, we discuss the mechanisms that give rise to strain variation and methods that can be used to study it. We identify that while strain diversity can act as a major barrier in interpreting and generalizing microbiome data, it can also be a powerful tool for mechanistic research. We then highlight recent examples demonstrating the importance of strain variation in colonization, virulence, and xenobiotic metabolism. Moving past taxonomy and the species concept will be crucial for future mechanistic research to understand microbiome structure and function.
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Affiliation(s)
- Benjamin D Anderson
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States
| | - Jordan E Bisanz
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States.,The Penn State Microbiome Center, Huck Institutes of the Life Sciences, University Park, PA, United States
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Mozota M, Castro I, Gómez-Torres N, Arroyo R, Gutiérrez-Díaz I, Delgado S, Rodríguez JM, Alba C. Administration of Ligilactobacillus salivarius CECT 30632 to elderly during the COVID-19 pandemic: Nasal and fecal metataxonomic analysis and fatty acid profiling. Front Microbiol 2022; 13:1052675. [PMID: 36590434 PMCID: PMC9800801 DOI: 10.3389/fmicb.2022.1052675] [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: 09/24/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Elderly was the most affected population during the first COVID-19 and those living in nursing homes represented the most vulnerable group, with high mortality rates, until vaccines became available. In a previous article, we presented an open-label trial showing the beneficial effect of the strain Ligilactobacillus salivarius CECT 30632 (previously known as L. salivarius MP101) on the functional and nutritional status, and on the nasal and fecal inflammatory profiles of elderly residing in a nursing home highly affected by the pandemic. The objective of this post-hoc analysis was to elucidate if there were changes in the nasal and fecal bacteriomes of a subset of these patients as a result of the administration of the strain for 4 months and, also, its impact on their fecal fatty acids profiles. Culture-based methods showed that, while L. salivarius (species level) could not be detected in any of the fecal samples at day 0, L. salivarius CECT 30632 (strain level) was present in all the recruited people at day 120. Paradoxically, the increase in the L. salivarius counts was not reflected in changes in the metataxonomic analysis of the nasal and fecal samples or in changes in the fatty acid profiles in the fecal samples of the recruited people. Overall, our results indicate that L. salivarius CECT 30632 colonized, at least temporarily, the intestinal tract of the recruited elderly and may have contributed to improvements in their functional, nutritional, and immunological status, without changing the general structure of their nasal and fecal bacteriomes when assessed at the genus level. They also suggest the ability of low abundance bacteria to train immunity.
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Affiliation(s)
- Marta Mozota
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain
| | - Irma Castro
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain
| | - Natalia Gómez-Torres
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain
| | - Rebeca Arroyo
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain
| | - Isabel Gutiérrez-Díaz
- Department of Microbiology and Biochemistry, Dairy Research Institute of Asturias (IPLA-CSIC), Villaviciosa, Spain
| | - Susana Delgado
- Department of Microbiology and Biochemistry, Dairy Research Institute of Asturias (IPLA-CSIC), Villaviciosa, Spain
| | - Juan Miguel Rodríguez
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain,*Correspondence: Juan Miguel Rodríguez,
| | - Claudio Alba
- Department of Nutrition and Food Science, Complutense University of Madrid, Madrid, Spain,Claudio Alba,
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17
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Aoki W, Kogawa M, Matsuda S, Matsubara K, Hirata S, Nishikawa Y, Hosokawa M, Takeyama H, Matoh T, Ueda M. Massively parallel single-cell genomics of microbiomes in rice paddies. Front Microbiol 2022; 13:1024640. [PMID: 36406415 PMCID: PMC9669790 DOI: 10.3389/fmicb.2022.1024640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Plant growth-promoting microbes (PGPMs) have attracted increasing attention because they may be useful in increasing crop yield in a low-input and sustainable manner to ensure food security. Previous studies have attempted to understand the principles underlying the rhizosphere ecology and interactions between plants and PGPMs using ribosomal RNA sequencing, metagenomic sequencing, and genome-resolved metagenomics; however, these approaches do not provide comprehensive genomic information for individual species and do not facilitate detailed analyses of plant-microbe interactions. In the present study, we developed a pipeline to analyze the genomic diversity of the rice rhizosphere microbiome at single-cell resolution. We isolated microbial cells from paddy soil and determined their genomic sequences by using massively parallel whole-genome amplification in microfluidic-generated gel capsules. We successfully obtained 3,237 single-amplified genomes in a single experiment, and these genomic sequences provided insights into microbial functions in the paddy ecosystem. Our approach offers a promising platform for gaining novel insights into the roles of microbes in the rice rhizomicrobiome and to develop microbial technologies for improved and sustainable rice production.
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Affiliation(s)
- Wataru Aoki
- Division of Applied Life Sciences, Graduate School of Agriculture, Kyoto University, Kyoto, Japan,*Correspondence: Wataru Aoki,
| | - Masato Kogawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan
| | | | | | | | - Yohei Nishikawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| | - Masahito Hosokawa
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan,Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan,Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan
| | - Haruko Takeyama
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan,Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan,Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan,Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan,Haruko Takeyama,
| | - Toru Matoh
- Kyoto Agriculture Research Institute KARI, Kyoto, Japan,Toru Matoh,
| | - Mitsuyoshi Ueda
- Division of Applied Life Sciences, Graduate School of Agriculture, Kyoto University, Kyoto, Japan,Mitsuyoshi Ueda,
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18
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Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics. Int J Mol Sci 2022; 23:ijms23179834. [PMID: 36077231 PMCID: PMC9456280 DOI: 10.3390/ijms23179834] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 12/21/2022] Open
Abstract
Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.
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19
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Ide K, Saeki T, Arikawa K, Yoda T, Endoh T, Matsuhashi A, Takeyama H, Hosokawa M. Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing. Front Microbiol 2022; 13:955404. [PMID: 35992707 PMCID: PMC9389210 DOI: 10.3389/fmicb.2022.955404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 07/06/2022] [Indexed: 12/03/2022] Open
Abstract
To understand the role of the skin commensal bacterial community in skin health and the spread of pathogens, it is crucial to identify genetic differences in the bacterial strains corresponding to human individuals. A culture-independent genomics approach is an effective tool for obtaining massive high-quality bacterial genomes. Here we present a single-cell genome sequencing to obtain comprehensive whole-genome sequences of uncultured skin bacteria from skin swabs. We recovered 281 high-quality (HQ) and 244 medium-quality single-amplified genomes (SAGs) of multiple skin bacterial species from eight individuals, including cohabiting group. Single-cell sequencing outperformed in the genome recovery from the same skin swabs, showing 10-fold non-redundant strain genomes compared to the shotgun metagenomic sequencing and binning approach. We then focused on the abundant skin bacteria and identified intra-species diversity, especially in 47 Moraxella osloensis derived HQ SAGs, characterizing the strain-level heterogeneity at mobile genetic element profiles, including plasmids and prophages. Even between the cohabiting individual hosts, they have unique skin bacterial strains in the same species, which shows microdiversity in each host. Genetic and functional differences between skin bacterial strains are predictive of in vivo competition to adapt bacterial genome to utilize the sparse nutrients available on the skin or produce molecules that inhibit the colonization of other microbes or alter their behavior. Thus, single-cell sequencing provides a large number of genomes of higher resolution and quality than conventional metagenomic analysis and helps explore the skin commensal bacteria at the strain level, linking taxonomic and functional information.
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Affiliation(s)
- Keigo Ide
- Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- bitBiome, Inc., Tokyo, Japan
| | | | | | | | | | | | - Haruko Takeyama
- Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan
| | - Masahito Hosokawa
- Department of Life Science and Medical Bioscience, Waseda University, Tokyo, Japan
- Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- bitBiome, Inc., Tokyo, Japan
- Research Organization for Nano and Life Innovation, Waseda University, Tokyo, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Tokyo, Japan
- *Correspondence: Masahito Hosokawa,
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Lloréns-Rico V, Simcock JA, Huys GR, Raes J. Single-cell approaches in human microbiome research. Cell 2022; 185:2725-2738. [DOI: 10.1016/j.cell.2022.06.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/20/2022] [Accepted: 06/20/2022] [Indexed: 10/17/2022]
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21
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Grujcic V, Taylor GT, Foster RA. One Cell at a Time: Advances in Single-Cell Methods and Instrumentation for Discovery in Aquatic Microbiology. Front Microbiol 2022; 13:881018. [PMID: 35677911 PMCID: PMC9169044 DOI: 10.3389/fmicb.2022.881018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Studying microbes from a single-cell perspective has become a major theme and interest within the field of aquatic microbiology. One emerging trend is the unfailing observation of heterogeneity in activity levels within microbial populations. Wherever researchers have looked, intra-population variability in biochemical composition, growth rates, and responses to varying environmental conditions has been evident and probably reflect coexisting genetically distinct strains of the same species. Such observations of heterogeneity require a shift away from bulk analytical approaches and development of new methods or adaptation of existing techniques, many of which were first pioneered in other, unrelated fields, e.g., material, physical, and biomedical sciences. Many co-opted approaches were initially optimized using model organisms. In a field with so few cultivable models, method development has been challenging but has also contributed tremendous insights, breakthroughs, and stimulated curiosity. In this perspective, we present a subset of methods that have been effectively applied to study aquatic microbes at the single-cell level. Opportunities and challenges for innovation are also discussed. We suggest future directions for aquatic microbiological research that will benefit from open access to sophisticated instruments and highly interdisciplinary collaborations.
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Affiliation(s)
- Vesna Grujcic
- Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden
| | - Gordon T Taylor
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, United States
| | - Rachel A Foster
- Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden
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22
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Abstract
The human gut microbiome is crucial for human health and disease but exhibits extensive individual-level strain variation. Distinct strains encode and express different functions. The resulting emergent properties therefore differentially affect human health and disease in a personalized manner. Pryszlak et al. have made strides in tackling the challenge of genome-based microbiome screening which will ultimately yield strain-level understanding of the functional roles played by the human gut microbiome.
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Affiliation(s)
- Catherine Sedrani
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Paul Wilmes
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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