1
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Pu L, Shamir R. 4CAC: 4-class classifier of metagenome contigs using machine learning and assembly graphs. Nucleic Acids Res 2024:gkae799. [PMID: 39287139 DOI: 10.1093/nar/gkae799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 07/13/2024] [Accepted: 09/02/2024] [Indexed: 09/19/2024] Open
Abstract
Microbial communities usually harbor a mix of bacteria, archaea, plasmids, viruses and microeukaryotes. Within these communities, viruses, plasmids, and microeukaryotes coexist in relatively low abundance, yet they engage in intricate interactions with bacteria. Moreover, viruses and plasmids, as mobile genetic elements, play important roles in horizontal gene transfer and the development of antibiotic resistance within microbial populations. However, due to the difficulty of identifying viruses, plasmids, and microeukaryotes in microbial communities, our understanding of these minor classes lags behind that of bacteria and archaea. Recently, several classifiers have been developed to separate one or more minor classes from bacteria and archaea in metagenome assemblies. However, these classifiers often overlook the issue of class imbalance, leading to low precision in identifying the minor classes. Here, we developed a classifier called 4CAC that is able to identify viruses, plasmids, microeukaryotes, and prokaryotes simultaneously from metagenome assemblies. 4CAC generates an initial four-way classification using several sequence length-adjusted XGBoost models and further improves the classification using the assembly graph. Evaluation on simulated and real metagenome datasets demonstrates that 4CAC substantially outperforms existing classifiers and combinations thereof on short reads. On long reads, it also shows an advantage unless the abundance of the minor classes is very low. 4CAC runs 1-2 orders of magnitude faster than the other classifiers. The 4CAC software is available at https://github.com/Shamir-Lab/4CAC.
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Affiliation(s)
- Lianrong Pu
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
- School of Computer Science and Technology, Shandong University, Qingdao, China
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
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2
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Yan Q, Li S, Yan Q, Huo X, Wang C, Wang X, Sun Y, Zhao W, Yu Z, Zhang Y, Guo R, Lv Q, He X, Yao C, Li Z, Chen F, Ji Q, Zhang A, Jin H, Wang G, Feng X, Feng L, Wu F, Ning J, Deng S, An Y, Guo DA, Martin FM, Ma X. A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases. Cell 2024; 187:2969-2989.e24. [PMID: 38776919 DOI: 10.1016/j.cell.2024.04.043] [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: 03/24/2023] [Revised: 02/17/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.
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Affiliation(s)
- Qiulong Yan
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Shenghui Li
- Puensum Genetech Institute, Wuhan 430076, China; Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100091, China
| | - Qingsong Yan
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Xiaokui Huo
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Chao Wang
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; First Affiliated Hospital, Dalian Medical University, Dalian 116044, China.
| | - Xifan Wang
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100091, China; Department of Obstetrics and Gynecology, Columbia University, New York, NY 10027, USA
| | - Yan Sun
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Wenyu Zhao
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Zhenlong Yu
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Yue Zhang
- Puensum Genetech Institute, Wuhan 430076, China
| | - Ruochun Guo
- Puensum Genetech Institute, Wuhan 430076, China
| | - Qingbo Lv
- Puensum Genetech Institute, Wuhan 430076, China
| | - Xin He
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China
| | - Changliang Yao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China
| | | | - Fang Chen
- College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Qianru Ji
- Puensum Genetech Institute, Wuhan 430076, China
| | - Aiqin Zhang
- Puensum Genetech Institute, Wuhan 430076, China
| | - Hao Jin
- Puensum Genetech Institute, Wuhan 430076, China
| | - Guangyang Wang
- College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Xiaoying Feng
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Lei Feng
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Fan Wu
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Jing Ning
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Sa Deng
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Yue An
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China.
| | - Francis M Martin
- Université de Lorraine, Institut national de recherche pour l'agriculture, l'alimentation et l'environnement, UMR Interactions Arbres/Microorganismes, Centre INRAE Grand Est-Nancy, Champenoux 54280, France; Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100091, China.
| | - Xiaochi Ma
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China.
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3
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Hou S, Tang T, Cheng S, Liu Y, Xia T, Chen T, Fuhrman J, Sun F. DeepMicroClass sorts metagenomic contigs into prokaryotes, eukaryotes and viruses. NAR Genom Bioinform 2024; 6:lqae044. [PMID: 38711860 PMCID: PMC11071121 DOI: 10.1093/nargab/lqae044] [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: 09/07/2023] [Revised: 03/18/2024] [Accepted: 04/18/2024] [Indexed: 05/08/2024] Open
Abstract
Sequence classification facilitates a fundamental understanding of the structure of microbial communities. Binary metagenomic sequence classifiers are insufficient because environmental metagenomes are typically derived from multiple sequence sources. Here we introduce a deep-learning based sequence classifier, DeepMicroClass, that classifies metagenomic contigs into five sequence classes, i.e. viruses infecting prokaryotic or eukaryotic hosts, eukaryotic or prokaryotic chromosomes, and prokaryotic plasmids. DeepMicroClass achieved high performance for all sequence classes at various tested sequence lengths ranging from 500 bp to 100 kbps. By benchmarking on a synthetic dataset with variable sequence class composition, we showed that DeepMicroClass obtained better performance for eukaryotic, plasmid and viral contig classification than other state-of-the-art predictors. DeepMicroClass achieved comparable performance on viral sequence classification with geNomad and VirSorter2 when benchmarked on the CAMI II marine dataset. Using a coastal daily time-series metagenomic dataset as a case study, we showed that microbial eukaryotes and prokaryotic viruses are integral to microbial communities. By analyzing monthly metagenomes collected at HOT and BATS, we found relatively higher viral read proportions in the subsurface layer in late summer, consistent with the seasonal viral infection patterns prevalent in these areas. We expect DeepMicroClass will promote metagenomic studies of under-appreciated sequence types.
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Affiliation(s)
- Shengwei Hou
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Marine and Environmental Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Tianqi Tang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Siliangyu Cheng
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Yuanhao Liu
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Tian Xia
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Ting Chen
- Department of Computer Science and Technology, Institute of Artificial Intelligence & BNRist, Tsinghua University, Beijing 100084, China
| | - Jed A Fuhrman
- Marine and Environmental Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Fengzhu Sun
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
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4
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Barcenilla C, Cobo-Díaz JF, De Filippis F, Valentino V, Cabrera Rubio R, O'Neil D, Mahler de Sanchez L, Armanini F, Carlino N, Blanco-Míguez A, Pinto F, Calvete-Torre I, Sabater C, Delgado S, Ruas-Madiedo P, Quijada NM, Dzieciol M, Skírnisdóttir S, Knobloch S, Puente A, López M, Prieto M, Marteinsson VT, Wagner M, Margolles A, Segata N, Cotter PD, Ercolini D, Alvarez-Ordóñez A. Improved sampling and DNA extraction procedures for microbiome analysis in food-processing environments. Nat Protoc 2024; 19:1291-1310. [PMID: 38267717 DOI: 10.1038/s41596-023-00949-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 11/09/2023] [Indexed: 01/26/2024]
Abstract
Deep investigation of the microbiome of food-production and food-processing environments through whole-metagenome sequencing (WMS) can provide detailed information on the taxonomic composition and functional potential of the microbial communities that inhabit them, with huge potential benefits for environmental monitoring programs. However, certain technical challenges jeopardize the application of WMS technologies with this aim, with the most relevant one being the recovery of a sufficient amount of DNA from the frequently low-biomass samples collected from the equipment, tools and surfaces of food-processing plants. Here, we present the first complete workflow, with optimized DNA-purification methodology, to obtain high-quality WMS sequencing results from samples taken from food-production and food-processing environments and reconstruct metagenome assembled genomes (MAGs). The protocol can yield DNA loads >10 ng in >98% of samples and >500 ng in 57.1% of samples and allows the collection of, on average, 12.2 MAGs per sample (with up to 62 MAGs in a single sample) in ~1 week, including both laboratory and computational work. This markedly improves on results previously obtained in studies performing WMS of processing environments and using other protocols not specifically developed to sequence these types of sample, in which <2 MAGs per sample were obtained. The full protocol has been developed and applied in the framework of the European Union project MASTER (Microbiome applications for sustainable food systems through technologies and enterprise) in 114 food-processing facilities from different production sectors.
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Affiliation(s)
- Coral Barcenilla
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain
| | - José F Cobo-Díaz
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain
| | - Francesca De Filippis
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
- Task Force on Microbiome Studies, University of Naples Federico II, Naples, Italy
| | - Vincenzo Valentino
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
| | | | | | | | - Federica Armanini
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Niccolò Carlino
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Aitor Blanco-Míguez
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Federica Pinto
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Inés Calvete-Torre
- Dairy Research Institute of Asturias, Spanish National Research Council (IPLA-CSIC), Paseo Río Linares, Villaviciosa, Asturias, Spain
- Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario, Oviedo, Asturias, Spain
| | - Carlos Sabater
- Dairy Research Institute of Asturias, Spanish National Research Council (IPLA-CSIC), Paseo Río Linares, Villaviciosa, Asturias, Spain
- Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario, Oviedo, Asturias, Spain
| | - Susana Delgado
- Dairy Research Institute of Asturias, Spanish National Research Council (IPLA-CSIC), Paseo Río Linares, Villaviciosa, Asturias, Spain
- Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario, Oviedo, Asturias, Spain
| | - Patricia Ruas-Madiedo
- Dairy Research Institute of Asturias, Spanish National Research Council (IPLA-CSIC), Paseo Río Linares, Villaviciosa, Asturias, Spain
- Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario, Oviedo, Asturias, Spain
| | - Narciso M Quijada
- Austrian Competence Centre for Feed and Food Quality, Safety and Innovation, FFoQSI GmbH, Tulln an der Donau, Austria
- Department for Farm Animals and Veterinary Public Health, Unit of Food Microbiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine Vienna, Vienna, Austria
- Department of Microbiology and Genetics, Institute for Agribiotechnology Research (CIALE), University of Salamanca, Salamanca, Spain
| | - Monika Dzieciol
- Department for Farm Animals and Veterinary Public Health, Unit of Food Microbiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine Vienna, Vienna, Austria
| | | | - Stephen Knobloch
- Microbiology Research Group, Matís ohf., Reykjavík, Iceland
- Senckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany
| | - Alba Puente
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain
| | - Mercedes López
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain
| | - Miguel Prieto
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain
| | - Viggó Thór Marteinsson
- Microbiology Research Group, Matís ohf., Reykjavík, Iceland
- Faculty of Food Science and Nutrition, University of Iceland, Reykjavik, Iceland
| | - Martin Wagner
- Austrian Competence Centre for Feed and Food Quality, Safety and Innovation, FFoQSI GmbH, Tulln an der Donau, Austria
- Department for Farm Animals and Veterinary Public Health, Unit of Food Microbiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Abelardo Margolles
- Dairy Research Institute of Asturias, Spanish National Research Council (IPLA-CSIC), Paseo Río Linares, Villaviciosa, Asturias, Spain
- Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario, Oviedo, Asturias, Spain
| | - Nicola Segata
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Paul D Cotter
- Teagasc Food Research Centre, Moorepark, Cork, Ireland
- APC Microbiome Ireland and VistaMilk Research Centres, Cork, Ireland
| | - Danilo Ercolini
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
- Task Force on Microbiome Studies, University of Naples Federico II, Naples, Italy
| | - Avelino Alvarez-Ordóñez
- Department of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, León, Spain.
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5
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Lou YC, Chen L, Borges AL, West-Roberts J, Firek BA, Morowitz MJ, Banfield JF. Infant gut DNA bacteriophage strain persistence during the first 3 years of life. Cell Host Microbe 2024; 32:35-47.e6. [PMID: 38096814 PMCID: PMC11156429 DOI: 10.1016/j.chom.2023.11.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/27/2023] [Accepted: 11/16/2023] [Indexed: 01/13/2024]
Abstract
Bacteriophages are key components of gut microbiomes, yet the phage colonization process in the infant gut remains uncertain. Here, we establish a large phage sequence database and use strain-resolved analyses to investigate DNA phage succession in infants throughout the first 3 years of life. Analysis of 819 fecal metagenomes collected from 28 full-term and 24 preterm infants and their mothers revealed that early-life phageome richness increases over time and reaches adult-like complexity by age 3. Approximately 9% of early phage colonizers, which are mostly maternally transmitted and infect Bacteroides, persist for 3 years and are more prevalent in full-term than in preterm infants. Although rare, phages with stop codon reassignment are more likely to persist than non-recoded phages and generally display an increase in in-frame reassigned stop codons over 3 years. Overall, maternal seeding, stop codon reassignment, host CRISPR-Cas locus prevalence, and diverse phage populations contribute to stable viral colonization.
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Affiliation(s)
- Yue Clare Lou
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - LinXing Chen
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, CA 94709, USA
| | - Adair L Borges
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Jacob West-Roberts
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Brian A Firek
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Michael J Morowitz
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Jillian F Banfield
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA 94720, USA.
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6
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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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7
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Yadav BNS, Sharma P, Maurya S, Yadav RK. Metagenomics and metatranscriptomics as potential driving forces for the exploration of diversity and functions of micro-eukaryotes in soil. 3 Biotech 2023; 13:423. [PMID: 38047037 PMCID: PMC10689336 DOI: 10.1007/s13205-023-03841-3] [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: 03/27/2023] [Accepted: 11/02/2023] [Indexed: 12/05/2023] Open
Abstract
Micro-eukaryotes are ubiquitous and play vital roles in diverse ecological systems, yet their diversity and functions are scarcely known. This may be due to the limitations of formerly used conventional culture-based methods. Metagenomics and metatranscriptomics are enabling to unravel the genomic, metabolic, and phylogenetic diversity of micro-eukaryotes inhabiting in different ecosystems in a more comprehensive manner. The in-depth study of structural and functional characteristics of micro-eukaryote community residing in soil is crucial for the complete understanding of this major ecosystem. This review provides a deep insight into the methodologies employed under these approaches to study soil micro-eukaryotic organisms. Furthermore, the review describes available computational tools, pipelines, and database sources and their manipulation for the analysis of sequence data of micro-eukaryotic origin. The challenges and limitations of these approaches are also discussed in detail. In addition, this review summarizes the key findings of metagenomic and metatranscriptomic studies on soil micro-eukaryotes. It also highlights the exploitation of these methods to study the structural as well as functional profiles of soil micro-eukaryotic community and to screen functional eukaryotic protein coding genes for biotechnological applications along with the future perspectives in the field.
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Affiliation(s)
- Bhupendra Narayan Singh Yadav
- Molecular Biology and Genetic Engineering Laboratory, Department of Botany, Faculty of Science, University of Allahabad, Prayagraj, Uttar Pradesh 211002 India
| | - Priyanka Sharma
- Molecular Biology and Genetic Engineering Laboratory, Department of Botany, Faculty of Science, University of Allahabad, Prayagraj, Uttar Pradesh 211002 India
| | - Shristy Maurya
- Molecular Biology and Genetic Engineering Laboratory, Department of Botany, Faculty of Science, University of Allahabad, Prayagraj, Uttar Pradesh 211002 India
| | - Rajiv Kumar Yadav
- Molecular Biology and Genetic Engineering Laboratory, Department of Botany, Faculty of Science, University of Allahabad, Prayagraj, Uttar Pradesh 211002 India
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8
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Fan Y, Wu L, Zhai B. The mycobiome: interactions with host and implications in diseases. Curr Opin Microbiol 2023; 75:102361. [PMID: 37527562 DOI: 10.1016/j.mib.2023.102361] [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: 04/30/2023] [Revised: 06/29/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023]
Abstract
Over the past decade, our understanding of the composition and function of the human mucosal surface-associated fungal community (i.e. the mycobiome) has rapidly expanded. Fungi colonize at various sites of the mucosal surface at birth and play important roles in the development and homeostasis of immune system throughout adulthood. Here, we review the recent research progresses in the human mycobiome at different body sites, including the gastrointestinal (GI) tract, the respiratory tract, the urogenital tract, the oral cavity, the skin surface, and the tumor tissues. Researchers have made extensive effort in characterizing the interactions between mycobiome and immune system, especially in the GI tract. We discuss the mycobiome dysbiosis and its implications to the progression of diseases such as inflammatory bowel diseases, alcoholic liver diseases, systemic infections, cancers, and so on, indicating the potential of mycobiome-targeting intervention strategy for life-threatening diseases.
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Affiliation(s)
- Yani Fan
- Clinical laboratory, Shenzhen Bao'an Women's and Children's Hospital, Shenzhen, Guangdong Province, China; Maternal-Fetal Medicine Institute, Shenzhen Bao'an Women's and Children's Hospital, Shenzhen, China; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Lijuan Wu
- Clinical laboratory, Shenzhen Bao'an Women's and Children's Hospital, Shenzhen, Guangdong Province, China; Maternal-Fetal Medicine Institute, Shenzhen Bao'an Women's and Children's Hospital, Shenzhen, China.
| | - Bing Zhai
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
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9
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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.
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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
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10
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Carter MM, Olm MR, Merrill BD, Dahan D, Tripathi S, Spencer SP, Yu FB, Jain S, Neff N, Jha AR, Sonnenburg ED, Sonnenburg JL. Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes. Cell 2023; 186:3111-3124.e13. [PMID: 37348505 PMCID: PMC10330870 DOI: 10.1016/j.cell.2023.05.046] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 02/12/2023] [Accepted: 05/26/2023] [Indexed: 06/24/2023]
Abstract
The gut microbiome modulates immune and metabolic health. Human microbiome data are biased toward industrialized populations, limiting our understanding of non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing on 351 fecal samples from the Hadza hunter-gatherers of Tanzania and comparative populations in Nepal and California. We recovered 91,662 genomes of bacteria, archaea, bacteriophages, and eukaryotes, 44% of which are absent from existing unified datasets. We identified 124 gut-resident species vanishing in industrialized populations and highlighted distinct aspects of the Hadza gut microbiome related to in situ replication rates, signatures of selection, and strain sharing. Industrialized gut microbes were found to be enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource, expands our understanding of microbes capable of colonizing the human gut, and clarifies the extensive perturbation induced by the industrialized lifestyle.
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Affiliation(s)
- Matthew M Carter
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Matthew R Olm
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Bryan D Merrill
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Dylan Dahan
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Surya Tripathi
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Sean P Spencer
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Feiqiao B Yu
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Sunit Jain
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Norma Neff
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Aashish R Jha
- Genetic Heritage Group, Program in Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Erica D Sonnenburg
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA.
| | - Justin L Sonnenburg
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Center for Human Microbiome Studies, Stanford University School of Medicine, Stanford, CA 94304, USA.
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11
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Bazant W, Blevins AS, Crouch K, Beiting DP. Improved eukaryotic detection compatible with large-scale automated analysis of metagenomes. MICROBIOME 2023; 11:72. [PMID: 37032329 PMCID: PMC10084625 DOI: 10.1186/s40168-023-01505-1] [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: 06/07/2022] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Eukaryotes such as fungi and protists frequently accompany bacteria and archaea in microbial communities. Unfortunately, their presence is difficult to study with "shotgun" metagenomic sequencing since prokaryotic signals dominate in most environments. Recent methods for eukaryotic detection use eukaryote-specific marker genes, but they do not incorporate strategies to handle the presence of eukaryotes that are not represented in the reference marker gene set, and they are not compatible with web-based tools for downstream analysis. RESULTS Here, we present CORRAL (for Clustering Of Related Reference ALignments), a tool for the identification of eukaryotes in shotgun metagenomic data based on alignments to eukaryote-specific marker genes and Markov clustering. Using a combination of simulated datasets, mock community standards, and large publicly available human microbiome studies, we demonstrate that our method is not only sensitive and accurate but is also capable of inferring the presence of eukaryotes not included in the marker gene reference, such as novel strains. Finally, we deploy CORRAL on our MicrobiomeDB.org resource, producing an atlas of eukaryotes present in various environments of the human body and linking their presence to study covariates. CONCLUSIONS CORRAL allows eukaryotic detection to be automated and carried out at scale. Implementation of CORRAL in MicrobiomeDB.org creates a running atlas of microbial eukaryotes in metagenomic studies. Since our approach is independent of the reference used, it may be applicable to other contexts where shotgun metagenomic reads are matched against redundant but non-exhaustive databases, such as the identification of bacterial virulence genes or taxonomic classification of viral reads. Video Abstract.
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Affiliation(s)
- Wojtek Bazant
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Ann S Blevins
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kathryn Crouch
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
| | - Daniel P Beiting
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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12
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Wilson A, Bogie B, Chaaban H, Burge K. The Nonbacterial Microbiome: Fungal and Viral Contributions to the Preterm Infant Gut in Health and Disease. Microorganisms 2023; 11:909. [PMID: 37110332 PMCID: PMC10144239 DOI: 10.3390/microorganisms11040909] [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: 03/03/2023] [Revised: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/29/2023] Open
Abstract
The intestinal microbiome is frequently implicated in necrotizing enterocolitis (NEC) pathogenesis. While no particular organism has been associated with NEC development, a general reduction in bacterial diversity and increase in pathobiont abundance has been noted preceding disease onset. However, nearly all evaluations of the preterm infant microbiome focus exclusively on the bacterial constituents, completely ignoring any fungi, protozoa, archaea, and viruses present. The abundance, diversity, and function of these nonbacterial microbes within the preterm intestinal ecosystem are largely unknown. Here, we review findings on the role of fungi and viruses, including bacteriophages, in preterm intestinal development and neonatal intestinal inflammation, with potential roles in NEC pathogenesis yet to be determined. In addition, we highlight the importance of host and environmental influences, interkingdom interactions, and the role of human milk in shaping fungal and viral abundance, diversity, and function within the preterm intestinal ecosystem.
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Affiliation(s)
| | | | - Hala Chaaban
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Kathryn Burge
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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13
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Lou YC, Hoff J, Olm MR, West-Roberts J, Diamond S, Firek BA, Morowitz MJ, Banfield JF. Using strain-resolved analysis to identify contamination in metagenomics data. MICROBIOME 2023; 11:36. [PMID: 36864482 PMCID: PMC9979413 DOI: 10.1186/s40168-023-01477-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 01/28/2023] [Indexed: 05/06/2023]
Abstract
BACKGROUND Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported. RESULTS Here, we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall, in both datasets, contamination is more significant in samples with lower biomass. CONCLUSION Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls. Video Abstract.
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Affiliation(s)
- Yue Clare Lou
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
| | - Jordan Hoff
- Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
| | - Matthew R Olm
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Jacob West-Roberts
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
| | - Spencer Diamond
- Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
| | - Brian A Firek
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Michael J Morowitz
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jillian F Banfield
- Department of Earth and Planetary Science, University of California, Berkeley, CA, USA.
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA.
- Innovative Genomics Institute, University of California, Berkeley, CA, USA.
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14
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Mukhopadhyay S, Lee JJ, Hartman E, Woodford E, Dhudasia MB, Mattei LM, Daniel SG, Wade KC, Underwood MA, Bittinger K. Preterm infants at low risk for early-onset sepsis differ in early fecal microbiome assembly. Gut Microbes 2022; 14:2154091. [PMID: 36474348 PMCID: PMC9733690 DOI: 10.1080/19490976.2022.2154091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Antibiotics are administered near-universally to very low birth weight (VLBW) infants after birth for suspected early-onset sepsis (EOS). We previously identified a phenotypic group of VLBW infants, referred to as low-risk for EOS (LRE), whose risk of EOS is low enough to avoid routine antibiotic initiation. In this cohort study, we compared 18 such infants with 30 infants categorized as non-LRE to determine if the lower risk of pathogen transmission at birth is accompanied by differences in microbiome acquisition and development. We did shotgun metagenomic sequencing of 361 fecal samples obtained serially. LRE infants had a higher human-to-bacterial DNA ratio than non-LRE infants in fecal samples on days 1-3 after birth, confirming lower bacterial acquisition among LRE infants. The microbial diversity and composition in samples from days 4-7 differed between the groups with a predominance of Staphylococcus epidermidis in LRE infants and Enterobacteriaceae sp. in non-LRE infants. Compositional differences were congruent with the distribution of virulence factors and antibiotic resistant genes. After the first week, the overall composition was similar, but changes in relative abundance for several taxa with increasing age differed between groups. Of the nine late-onset bacteremia episodes, eight occurred in non-LRE infants. Species isolated from the blood culture was detected in the pre-antibiotic fecal samples of the infant for all episodes, though these species were also found in infants without bacteremia. In conclusion, LRE infants present a distinct pattern of microbiome development that is aligned with their low risk for EOS. Further investigation to determine the impact of these differences on later outcomes such as late-onset bacteremia is warranted.
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Affiliation(s)
- Sagori Mukhopadhyay
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States,Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,Sagori Mukhopadhyay Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Roberts Center for Pediatric Research, 2716 South Street, Office 19-322, Philadelphia, PA19146, United States
| | - Jung-Jin Lee
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Erica Hartman
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Emily Woodford
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Miren B. Dhudasia
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Lisa M. Mattei
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Scott G. Daniel
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Kelly C. Wade
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
| | - Mark A. Underwood
- Department of Pediatrics, University of California Davis, Sacramento, California, United States
| | - Kyle Bittinger
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States,Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States,CONTACT Kyle Bittinger CHOP Microbiome Center, Children’s Hospital of Philadelphia, Roberts Center for Pediatric Research, 2716 South Street, Philadelphia, PA19146, United States
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15
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Delmont TO, Gaia M, Hinsinger DD, Frémont P, Vanni C, Fernandez-Guerra A, Eren AM, Kourlaiev A, d'Agata L, Clayssen Q, Villar E, Labadie K, Cruaud C, Poulain J, Da Silva C, Wessner M, Noel B, Aury JM, de Vargas C, Bowler C, Karsenti E, Pelletier E, Wincker P, Jaillon O. Functional repertoire convergence of distantly related eukaryotic plankton lineages abundant in the sunlit ocean. CELL GENOMICS 2022; 2:100123. [PMID: 36778897 PMCID: PMC9903769 DOI: 10.1016/j.xgen.2022.100123] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 12/10/2021] [Accepted: 04/04/2022] [Indexed: 12/20/2022]
Abstract
Marine planktonic eukaryotes play critical roles in global biogeochemical cycles and climate. However, their poor representation in culture collections limits our understanding of the evolutionary history and genomic underpinnings of planktonic ecosystems. Here, we used 280 billion Tara Oceans metagenomic reads from polar, temperate, and tropical sunlit oceans to reconstruct and manually curate more than 700 abundant and widespread eukaryotic environmental genomes ranging from 10 Mbp to 1.3 Gbp. This genomic resource covers a wide range of poorly characterized eukaryotic lineages that complement long-standing contributions from culture collections while better representing plankton in the upper layer of the oceans. We performed the first, to our knowledge, comprehensive genome-wide functional classification of abundant unicellular eukaryotic plankton, revealing four major groups connecting distantly related lineages. Neither trophic modes of plankton nor its vertical evolutionary history could completely explain the functional repertoire convergence of major eukaryotic lineages that coexisted within oceanic currents for millions of years.
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Affiliation(s)
- Tom O. Delmont
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Morgan Gaia
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Damien D. Hinsinger
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Paul Frémont
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Chiara Vanni
- Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Antonio Fernandez-Guerra
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - A. Murat Eren
- Helmholtz Institute for Functional Marine Biodiversity at Oldenburg, Germany
| | - Artem Kourlaiev
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Leo d'Agata
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Quentin Clayssen
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Emilie Villar
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
| | - Karine Labadie
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Corinne Cruaud
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Julie Poulain
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Corinne Da Silva
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Marc Wessner
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Benjamin Noel
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Jean-Marc Aury
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Colomban de Vargas
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
- Sorbonne Université and CNRS, UMR 7144 (AD2M), ECOMAP, Station Biologique de Roscoff, Roscoff, France
| | - Chris Bowler
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
- Institut de Biologie de l’ENS, Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Eric Karsenti
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
- Sorbonne Université and CNRS, UMR 7144 (AD2M), ECOMAP, Station Biologique de Roscoff, Roscoff, France
- Directors’ Research, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Eric Pelletier
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Patrick Wincker
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
| | - Olivier Jaillon
- Génomique Métabolique, Genoscope, Institut François-Jacob, CEA, CNRS, Université d'Evry, Université Paris-Saclay, 91057 Evry, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
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16
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Duncan A, Barry K, Daum C, Eloe-Fadrosh E, Roux S, Schmidt K, Tringe SG, Valentin KU, Varghese N, Salamov A, Grigoriev IV, Leggett RM, Moulton V, Mock T. Metagenome-assembled genomes of phytoplankton microbiomes from the Arctic and Atlantic Oceans. MICROBIOME 2022; 10:67. [PMID: 35484634 PMCID: PMC9047304 DOI: 10.1186/s40168-022-01254-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Phytoplankton communities significantly contribute to global biogeochemical cycles of elements and underpin marine food webs. Although their uncultured genomic diversity has been estimated by planetary-scale metagenome sequencing and subsequent reconstruction of metagenome-assembled genomes (MAGs), this approach has yet to be applied for complex phytoplankton microbiomes from polar and non-polar oceans consisting of microbial eukaryotes and their associated prokaryotes. RESULTS Here, we have assembled MAGs from chlorophyll a maximum layers in the surface of the Arctic and Atlantic Oceans enriched for species associations (microbiomes) with a focus on pico- and nanophytoplankton and their associated heterotrophic prokaryotes. From 679 Gbp and estimated 50 million genes in total, we recovered 143 MAGs of medium to high quality. Although there was a strict demarcation between Arctic and Atlantic MAGs, adjacent sampling stations in each ocean had 51-88% MAGs in common with most species associations between Prasinophytes and Proteobacteria. Phylogenetic placement revealed eukaryotic MAGs to be more diverse in the Arctic whereas prokaryotic MAGs were more diverse in the Atlantic Ocean. Approximately 70% of protein families were shared between Arctic and Atlantic MAGs for both prokaryotes and eukaryotes. However, eukaryotic MAGs had more protein families unique to the Arctic whereas prokaryotic MAGs had more families unique to the Atlantic. CONCLUSION Our study provides a genomic context to complex phytoplankton microbiomes to reveal that their community structure was likely driven by significant differences in environmental conditions between the polar Arctic and warm surface waters of the tropical and subtropical Atlantic Ocean. Video Abstract.
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Affiliation(s)
- Anthony Duncan
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR47TJ, UK
| | - Kerrie Barry
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Chris Daum
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Emiley Eloe-Fadrosh
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Simon Roux
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Katrin Schmidt
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR47TJ, UK
| | - Susannah G Tringe
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Klaus U Valentin
- Alfred-Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - Neha Varghese
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Asaf Salamov
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Igor V Grigoriev
- US Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | | | - Vincent Moulton
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR47TJ, UK
| | - Thomas Mock
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR47TJ, UK.
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17
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Merrill BD, Carter MM, Olm MR, Dahan D, Tripathi S, Spencer SP, Yu B, Jain S, Neff N, Jha AR, Sonnenburg ED, Sonnenburg JL. Ultra-deep Sequencing of Hadza Hunter-Gatherers Recovers Vanishing Microbes.. [PMID: 36238714 PMCID: PMC9558438 DOI: 10.1101/2022.03.30.486478] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The gut microbiome is a key modulator of immune and metabolic health. Human microbiome data is biased towards industrialized populations, providing limited understanding of the distinct and diverse non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing and strain cultivation on 351 fecal samples from the Hadza, hunter-gatherers in Tanzania, and comparative populations in Nepal and California. We recover 94,971 total genomes of bacteria, archaea, bacteriophages, and eukaryotes, 43% of which are absent from existing unified datasets. Analysis of in situ growth rates, genetic pN/pS signatures, high-resolution strain tracking, and 124 gut-resident species vanishing in industrialized populations reveals differentiating dynamics of the Hadza gut microbiome. Industrialized gut microbes are enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource that expands our understanding of microbes capable of colonizing the human gut and clarifies the extensive perturbation brought on by the industrialized lifestyle.
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18
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Guzzo GL, Andrews JM, Weyrich LS. The Neglected Gut Microbiome: Fungi, Protozoa, and Bacteriophages in Inflammatory Bowel Disease. Inflamm Bowel Dis 2022; 28:1112-1122. [PMID: 35092426 PMCID: PMC9247841 DOI: 10.1093/ibd/izab343] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Indexed: 12/14/2022]
Abstract
The gut microbiome has been implicated in the pathogenesis of inflammatory bowel disease (IBD). Studies suggest that the IBD gut microbiome is less diverse than that of the unaffected population, a phenomenon often referred to as dysbiosis. However, these studies have heavily focused on bacteria, while other intestinal microorganisms-fungi, protozoa, and bacteriophages-have been neglected. Of the nonbacterial microbes that have been studied in relation to IBD, most are thought to be pathogens, although there is evidence that some of these species may instead be harmless commensals. In this review, we discuss the nonbacterial gut microbiome of IBD, highlighting the current biases, limitations, and outstanding questions that can be addressed with high-throughput DNA sequencing methods. Further, we highlight the importance of studying nonbacterial microorganisms alongside bacteria for a comprehensive view of the whole IBD biome and to provide a more precise definition of dysbiosis in patients. With the rise in popularity of microbiome-altering therapies for the treatment of IBD, such as fecal microbiota transplantation, it is important that we address these knowledge gaps to ensure safe and effective treatment of patients.
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Affiliation(s)
- Gina L Guzzo
- Address correspondence to: Gina L. Guzzo, The University of Adelaide, Adelaide, South Australia, Australia ()
| | - Jane M Andrews
- Inflammatory Bowel Disease Service, Department of Gastroenterology and Hepatology, Royal Adelaide Hospital and School of Medicine, Faculty of Health Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Laura S Weyrich
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia,Department of Anthropology and Huck Institutes of the Life Sciences, Pennsylvania State University, State College, PA, USA
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19
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Karlicki M, Antonowicz S, Karnkowska A. Tiara: deep learning-based classification system for eukaryotic sequences. Bioinformatics 2021; 38:344-350. [PMID: 34570171 PMCID: PMC8722755 DOI: 10.1093/bioinformatics/btab672] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 08/02/2021] [Accepted: 09/21/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding of eukaryotic diversity. RESULTS We developed Tiara, a deep-learning-based approach for the identification of eukaryotic sequences in the metagenomic datasets. Its two-step classification process enables the classification of nuclear and organellar eukaryotic fractions and subsequently divides organellar sequences into plastidial and mitochondrial. Using the test dataset, we have shown that Tiara performed similarly to EukRep for prokaryotes classification and outperformed it for eukaryotes classification with lower calculation time. In the tests on the real data, Tiara performed better than EukRep in analyzing the small dataset representing eukaryotic cell microbiome and large dataset from the pelagic zone of oceans. Tiara is also the only available tool correctly classifying organellar sequences, which was confirmed by the recovery of nearly complete plastid and mitochondrial genomes from the test data and real metagenomic data. AVAILABILITY AND IMPLEMENTATION Tiara is implemented in python 3.8, available at https://github.com/ibe-uw/tiara and tested on Unix-based systems. It is released under an open-source MIT license and documentation is available at https://ibe-uw.github.io/tiara. Version 1.0.1 of Tiara has been used for all benchmarks. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Michał Karlicki
- Institute of Evolutionary Biology, Faculty of Biology & Biological and Chemical Research Centre, University of Warsaw, Warszawa 02-089, Poland
| | - Stanisław Antonowicz
- Institute of Evolutionary Biology, Faculty of Biology & Biological and Chemical Research Centre, University of Warsaw, Warszawa 02-089, Poland
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20
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Lou YC, Olm MR, Diamond S, Crits-Christoph A, Firek BA, Baker R, Morowitz MJ, Banfield JF. Infant gut strain persistence is associated with maternal origin, phylogeny, and traits including surface adhesion and iron acquisition. Cell Rep Med 2021; 2:100393. [PMID: 34622230 PMCID: PMC8484513 DOI: 10.1016/j.xcrm.2021.100393] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 05/11/2021] [Accepted: 08/11/2021] [Indexed: 12/24/2022]
Abstract
Gut microbiome succession affects infant development. However, it remains unclear what factors promote persistence of initial bacterial colonizers in the developing gut. Here, we perform strain-resolved analyses to compare gut colonization of preterm and full-term infants throughout the first year of life and evaluate associations between strain persistence and strain origin as well as genetic potential. Analysis of fecal metagenomes collected from 13 full-term and 9 preterm infants reveals that infants' initially distinct microbiomes converge by age 1 year. Approximately 11% of early colonizers, primarily Bacteroides and Bifidobacterium, persist during the first year of life, and those are more prevalent in full-term, compared with preterm infants. Examination of 17 mother-infant pairs reveals maternal gut strains are significantly more likely to persist in the infant gut than other strains. Enrichment in genes for surface adhesion, iron acquisition, and carbohydrate degradation may explain persistence of some strains through the first year of life.
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Affiliation(s)
- Yue Clare Lou
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Matthew R. Olm
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Spencer Diamond
- Department of Earth and Planetary Science, University of California, Berkeley, CA 94709, USA
| | - Alexander Crits-Christoph
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Brian A. Firek
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Robyn Baker
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Michael J. Morowitz
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Jillian F. Banfield
- Department of Earth and Planetary Science, University of California, Berkeley, CA 94709, USA
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA 94720, USA
- Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94705, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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21
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Metagenome-Assembled Genomes Contribute to Unraveling of the Microbiome of Cocoa Fermentation. Appl Environ Microbiol 2021; 87:e0058421. [PMID: 34105982 DOI: 10.1128/aem.00584-21] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Metagenomic studies about cocoa fermentation have mainly reported on the analysis of short reads for determination of operational taxonomic units. However, it is also important to determine metagenome-assembled genomes (MAGs), which are genomes deriving from the assembly of metagenomics. For this research, all the cocoa metagenomes from public databases were downloaded, resulting in five data sets: one from Ghana and four from Brazil. In addition, in silico approaches were used to describe putative phenotypes and the metabolic potential of MAGs. A total of 17 high-quality MAGs were recovered from these microbiomes, as follows: (i) for fungi, Yamadazyma tenuis (n = 1); (ii) lactic acid bacteria, Limosilactobacillus fermentum (n = 5), Liquorilactobacillus cacaonum (n = 1), Liquorilactobacillus nagelli (n = 1), Leuconostoc pseudomesenteroides (n = 1), and Lactiplantibacillus plantarum subsp. plantarum (n = 1); (iii) acetic acid bacteria, Acetobacter senegalensis (n = 2) and Kozakia baliensis (n = 1); and (iv) Bacillus subtilis (n = 1), Brevundimonas sp. (n = 2), and Pseudomonas sp. (n = 1). Medium-quality MAGs were also recovered from cocoa microbiomes, including some that, to our knowledge, were not previously detected in this environment (Liquorilactobacillus vini, Komagataeibacter saccharivorans, and Komagataeibacter maltaceti) and others previously described (Fructobacillus pseudoficulneus and Acetobacter pasteurianus). Taken together, the MAGs were useful for providing an additional description of the microbiome of cocoa fermentation, revealing previously overlooked microorganisms, with prediction of key phenotypes and biochemical pathways. IMPORTANCE The production of chocolate starts with the harvesting of cocoa fruits and the spontaneous fermentation of the seeds in a microbial succession that depends on yeasts, lactic acid bacteria, and acetic acid bacteria in order to eliminate bitter and astringent compounds present in the raw material, which will be further roasted and grinded to originate the cocoa powder that will enter the food processing industry. The microbiota of cocoa fermentation is not completely known, and yet it advanced from culture-based studies to the advent of next-generation DNA sequencing, with the generation of a myriad of data that need bioinformatic approaches to be properly analyzed. Although the majority of metagenomic studies have been based on short reads (operational taxonomic units), it is also important to analyze entire genomes to determine more precisely possible ecological roles of different species. Metagenome-assembled genomes (MAGs) are very useful for this purpose; here, MAGs from cocoa fermentation microbiomes are described, and the possible implications of their phenotypic and metabolic potentials are discussed.
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22
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West PT, Peters SL, Olm MR, Yu FB, Gause H, Lou YC, Firek BA, Baker R, Johnson AD, Morowitz MJ, Hettich RL, Banfield JF. Genetic and behavioral adaptation of Candida parapsilosis to the microbiome of hospitalized infants revealed by in situ genomics, transcriptomics, and proteomics. MICROBIOME 2021; 9:142. [PMID: 34154658 PMCID: PMC8215838 DOI: 10.1186/s40168-021-01085-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 04/22/2021] [Indexed: 05/14/2023]
Abstract
BACKGROUND Candida parapsilosis is a common cause of invasive candidiasis, especially in newborn infants, and infections have been increasing over the past two decades. C. parapsilosis has been primarily studied in pure culture, leaving gaps in understanding of its function in a microbiome context. RESULTS Here, we compare five unique C. parapsilosis genomes assembled from premature infant fecal samples, three of which are newly reconstructed, and analyze their genome structure, population diversity, and in situ activity relative to reference strains in pure culture. All five genomes contain hotspots of single nucleotide variants, some of which are shared by strains from multiple hospitals. A subset of environmental and hospital-derived genomes share variants within these hotspots suggesting derivation of that region from a common ancestor. Four of the newly reconstructed C. parapsilosis genomes have 4 to 16 copies of the gene RTA3, which encodes a lipid translocase and is implicated in antifungal resistance, potentially indicating adaptation to hospital antifungal use. Time course metatranscriptomics and metaproteomics on fecal samples from a premature infant with a C. parapsilosis blood infection revealed highly variable in situ expression patterns that are distinct from those of similar strains in pure cultures. For example, biofilm formation genes were relatively less expressed in situ, whereas genes linked to oxygen utilization were more highly expressed, indicative of growth in a relatively aerobic environment. In gut microbiome samples, C. parapsilosis co-existed with Enterococcus faecalis that shifted in relative abundance over time, accompanied by changes in bacterial and fungal gene expression and proteome composition. CONCLUSIONS The results reveal potentially medically relevant differences in Candida function in gut vs. laboratory environments, and constrain evolutionary processes that could contribute to hospital strain persistence and transfer into premature infant microbiomes. Video abstract.
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Affiliation(s)
- Patrick T. West
- Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Samantha L. Peters
- Graduate School of Genome Science and Technology, The University of Tennessee, Knoxville, TN USA
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN USA
| | - Matthew R. Olm
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305 USA
| | | | - Haley Gause
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA USA
| | - Yue Clare Lou
- Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Brian A. Firek
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Robyn Baker
- Division of Newborn Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA USA
| | - Alexander D. Johnson
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305 USA
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA USA
| | - Michael J. Morowitz
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Robert L. Hettich
- Graduate School of Genome Science and Technology, The University of Tennessee, Knoxville, TN USA
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN USA
| | - Jillian F. Banfield
- Chan Zuckerberg Biohub, San Francisco, CA USA
- Department of Earth and Planetary Science, University of California, Berkeley, CA USA
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA USA
- Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
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23
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Xu L, Dong Z, Chiniquy D, Pierroz G, Deng S, Gao C, Diamond S, Simmons T, Wipf HML, Caddell D, Varoquaux N, Madera MA, Hutmacher R, Deutschbauer A, Dahlberg JA, Guerinot ML, Purdom E, Banfield JF, Taylor JW, Lemaux PG, Coleman-Derr D. Genome-resolved metagenomics reveals role of iron metabolism in drought-induced rhizosphere microbiome dynamics. Nat Commun 2021; 12:3209. [PMID: 34050180 PMCID: PMC8163885 DOI: 10.1038/s41467-021-23553-7] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 04/27/2021] [Indexed: 02/04/2023] Open
Abstract
Recent studies have demonstrated that drought leads to dramatic, highly conserved shifts in the root microbiome. At present, the molecular mechanisms underlying these responses remain largely uncharacterized. Here we employ genome-resolved metagenomics and comparative genomics to demonstrate that carbohydrate and secondary metabolite transport functionalities are overrepresented within drought-enriched taxa. These data also reveal that bacterial iron transport and metabolism functionality is highly correlated with drought enrichment. Using time-series root RNA-Seq data, we demonstrate that iron homeostasis within the root is impacted by drought stress, and that loss of a plant phytosiderophore iron transporter impacts microbial community composition, leading to significant increases in the drought-enriched lineage, Actinobacteria. Finally, we show that exogenous application of iron disrupts the drought-induced enrichment of Actinobacteria, as well as their improvement in host phenotype during drought stress. Collectively, our findings implicate iron metabolism in the root microbiome's response to drought and may inform efforts to improve plant drought tolerance to increase food security.
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Affiliation(s)
- Ling Xu
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA ,grid.22935.3f0000 0004 0530 8290State Key Laboratory of Plant Physiology and Biochemistry, Department of Microbiology and Immunology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Zhaobin Dong
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Dawn Chiniquy
- grid.184769.50000 0001 2231 4551Department of Energy, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
| | - Grady Pierroz
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Siwen Deng
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Cheng Gao
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Spencer Diamond
- grid.47840.3f0000 0001 2181 7878Department of Earth and Planetary Science, University of California, Berkeley, CA USA
| | - Tuesday Simmons
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Heidi M.-L. Wipf
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Daniel Caddell
- grid.507310.0Plant Gene Expression Center, USDA-ARS, Albany, CA USA
| | - Nelle Varoquaux
- grid.463716.10000 0004 4687 1979CNRS, University Grenoble Alpes, TIMC-IMAG, Grenoble, France
| | - Mary A. Madera
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Robert Hutmacher
- grid.27860.3b0000 0004 1936 9684Westside Research & Extension Center, UC Department of Plant Sciences, University of California, Davis, CA USA
| | - Adam Deutschbauer
- grid.184769.50000 0001 2231 4551Department of Energy, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
| | | | - Mary Lou Guerinot
- grid.254880.30000 0001 2179 2404Department of Biological Scienes, Dartmouth College, Hanover, NH USA
| | - Elizabeth Purdom
- grid.47840.3f0000 0001 2181 7878Department of Statistics, University of California, Berkeley, CA USA
| | - Jillian F. Banfield
- grid.47840.3f0000 0001 2181 7878Department of Earth and Planetary Science, University of California, Berkeley, CA USA
| | - John W. Taylor
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Peggy G. Lemaux
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA
| | - Devin Coleman-Derr
- grid.47840.3f0000 0001 2181 7878Department of Plant and Microbial Biology, University of California, Berkeley, CA USA ,grid.507310.0Plant Gene Expression Center, USDA-ARS, Albany, CA USA
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24
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Leung MHY, Tong X, Bøifot KO, Bezdan D, Butler DJ, Danko DC, Gohli J, Green DC, Hernandez MT, Kelly FJ, Levy S, Mason-Buck G, Nieto-Caballero M, Syndercombe-Court D, Udekwu K, Young BG, Mason CE, Dybwad M, Lee PKH. Characterization of the public transit air microbiome and resistome reveals geographical specificity. MICROBIOME 2021; 9:112. [PMID: 34039416 PMCID: PMC8157753 DOI: 10.1186/s40168-021-01044-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/09/2021] [Indexed: 05/21/2023]
Abstract
BACKGROUND The public transit is a built environment with high occupant density across the globe, and identifying factors shaping public transit air microbiomes will help design strategies to minimize the transmission of pathogens. However, the majority of microbiome works dedicated to the public transit air are limited to amplicon sequencing, and our knowledge regarding the functional potentials and the repertoire of resistance genes (i.e. resistome) is limited. Furthermore, current air microbiome investigations on public transit systems are focused on single cities, and a multi-city assessment of the public transit air microbiome will allow a greater understanding of whether and how broad environmental, building, and anthropogenic factors shape the public transit air microbiome in an international scale. Therefore, in this study, the public transit air microbiomes and resistomes of six cities across three continents (Denver, Hong Kong, London, New York City, Oslo, Stockholm) were characterized. RESULTS City was the sole factor associated with public transit air microbiome differences, with diverse taxa identified as drivers for geography-associated functional potentials, concomitant with geographical differences in species- and strain-level inferred growth profiles. Related bacterial strains differed among cities in genes encoding resistance, transposase, and other functions. Sourcetracking estimated that human skin, soil, and wastewater were major presumptive resistome sources of public transit air, and adjacent public transit surfaces may also be considered presumptive sources. Large proportions of detected resistance genes were co-located with mobile genetic elements including plasmids. Biosynthetic gene clusters and city-unique coding sequences were found in the metagenome-assembled genomes. CONCLUSIONS Overall, geographical specificity transcends multiple aspects of the public transit air microbiome, and future efforts on a global scale are warranted to increase our understanding of factors shaping the microbiome of this unique built environment.
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Affiliation(s)
- M H Y Leung
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
| | - X Tong
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
| | - K O Bøifot
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - D Bezdan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - D J Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - D C Danko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - J Gohli
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway
| | - D C Green
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - M T Hernandez
- Environmental Engineering Program, College of Engineering and Applied Science, University of Colorado, Boulder, CO, USA
| | - F J Kelly
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - S Levy
- HudsonAlpha Institute of Biotechnology, Huntsville, AL, USA
| | - G Mason-Buck
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - M Nieto-Caballero
- Environmental Engineering Program, College of Engineering and Applied Science, University of Colorado, Boulder, CO, USA
| | - D Syndercombe-Court
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - K Udekwu
- Department of Aquatic Sciences & Assessment, Swedish University of Agriculture, Uppsala, Sweden
| | - B G Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - C E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
| | - M Dybwad
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK.
| | - P K H Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China.
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25
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Beghini F, McIver LJ, Blanco-Míguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, Valles-Colomer M, Weingart G, Zhang Y, Zolfo M, Huttenhower C, Franzosa EA, Segata N. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. eLife 2021; 10:65088. [PMID: 33944776 PMCID: PMC8096432 DOI: 10.7554/elife.65088] [Citation(s) in RCA: 832] [Impact Index Per Article: 277.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 04/21/2021] [Indexed: 02/06/2023] Open
Abstract
Culture-independent analyses of microbial communities have progressed dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1262 metagenomes) and IBD (1635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.
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Affiliation(s)
| | - Lauren J McIver
- Harvard T.H. Chan School of Public Health, Boston, United States
| | | | | | | | - Sagun Maharjan
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Ana Mailyan
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Paolo Manghi
- Department CIBIO, University of Trento, Trento, Italy
| | - Matthias Scholz
- Department of Food Quality and Nutrition, Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Italy
| | | | | | - George Weingart
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Yancong Zhang
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Moreno Zolfo
- Department CIBIO, University of Trento, Trento, Italy
| | - Curtis Huttenhower
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Eric A Franzosa
- Harvard T.H. Chan School of Public Health, Boston, United States.,The Broad Institute of MIT and Harvard, Cambridge, United States
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy.,IEO, European Institute of Oncology IRCCS, Milan, Italy
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26
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Lind AL, Pollard KS. Accurate and sensitive detection of microbial eukaryotes from whole metagenome shotgun sequencing. MICROBIOME 2021; 9:58. [PMID: 33658077 PMCID: PMC7931531 DOI: 10.1186/s40168-021-01015-y] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 02/02/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Microbial eukaryotes are found alongside bacteria and archaea in natural microbial systems, including host-associated microbiomes. While microbial eukaryotes are critical to these communities, they are challenging to study with shotgun sequencing techniques and are therefore often excluded. RESULTS Here, we present EukDetect, a bioinformatics method to identify eukaryotes in shotgun metagenomic sequencing data. Our approach uses a database of 521,824 universal marker genes from 241 conserved gene families, which we curated from 3713 fungal, protist, non-vertebrate metazoan, and non-streptophyte archaeplastida genomes and transcriptomes. EukDetect has a broad taxonomic coverage of microbial eukaryotes, performs well on low-abundance and closely related species, and is resilient against bacterial contamination in eukaryotic genomes. Using EukDetect, we describe the spatial distribution of eukaryotes along the human gastrointestinal tract, showing that fungi and protists are present in the lumen and mucosa throughout the large intestine. We discover that there is a succession of eukaryotes that colonize the human gut during the first years of life, mirroring patterns of developmental succession observed in gut bacteria. By comparing DNA and RNA sequencing of paired samples from human stool, we find that many eukaryotes continue active transcription after passage through the gut, though some do not, suggesting they are dormant or nonviable. We analyze metagenomic data from the Baltic Sea and find that eukaryotes differ across locations and salinity gradients. Finally, we observe eukaryotes in Arabidopsis leaf samples, many of which are not identifiable from public protein databases. CONCLUSIONS EukDetect provides an automated and reliable way to characterize eukaryotes in shotgun sequencing datasets from diverse microbiomes. We demonstrate that it enables discoveries that would be missed or clouded by false positives with standard shotgun sequence analysis. EukDetect will greatly advance our understanding of how microbial eukaryotes contribute to microbiomes. Video abstract.
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Affiliation(s)
- Abigail L Lind
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, CA, USA.
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
- Institute for Computational Health Sciences, University of California, San Francisco, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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Saary P, Mitchell AL, Finn RD. Estimating the quality of eukaryotic genomes recovered from metagenomic analysis with EukCC. Genome Biol 2020; 21:244. [PMID: 32912302 PMCID: PMC7488429 DOI: 10.1186/s13059-020-02155-4] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 08/24/2020] [Indexed: 12/23/2022] Open
Abstract
Microbial eukaryotes constitute a significant fraction of biodiversity and have recently gained more attention, but the recovery of high-quality metagenomic assembled eukaryotic genomes is limited by the current availability of tools. To help address this, we have developed EukCC, a tool for estimating the quality of eukaryotic genomes based on the automated dynamic selection of single copy marker gene sets. We demonstrate that our method outperforms current genome quality estimators, particularly for estimating contamination, and have applied EukCC to datasets derived from two different environments to enable the identification of novel eukaryote genomes, including one from the human skin.
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Affiliation(s)
- Paul Saary
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Alex L Mitchell
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
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28
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Metataxonomics contributes to unravel the microbiota of a Brazilian dairy. J DAIRY RES 2020; 87:360-363. [PMID: 32883375 DOI: 10.1017/s0022029920000837] [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: 11/06/2022]
Abstract
For this research communication, 90 samples of a Brazilian dairy were combined into four groups (raw material, final product, food-contact and non-food contact surfaces) and analyzed by metataxonomics based on 16S rRNA gene sequencing. The results showed high alpha-diversity indexes for final product and non-food contact surfaces but, overall, beta-diversity indexes were low. The samples were separated in two main clusters, and the core microbiota was composed by Macrococcus, Alkaliphilus, Vagococcus, Lactobacillus, Marinilactibacillus, Streptococcus, Lysinibacillus, Staphylococcus, Clostridium, Halomonas, Lactococcus, Enterococcus, Bacillus and Psychrobacter. These results highlight that rare taxa occur in dairies, and this may aid the development of strategies for food protection.
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29
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Abstract
Shotgun metagenomic sequencing has revolutionized our ability to detect and characterize the diversity and function of complex microbial communities. In this review, we highlight the benefits of using metagenomics as well as the breadth of conclusions that can be made using currently available analytical tools, such as greater resolution of species and strains across phyla and functional content, while highlighting challenges of metagenomic data analysis. Major challenges remain in annotating function, given the dearth of functional databases for environmental bacteria compared to model organisms, and the technical difficulties of metagenome assembly and phasing in heterogeneous environmental samples. In the future, improvements and innovation in technology and methodology will lead to lowered costs. Data integration using multiple technological platforms will lead to a better understanding of how to harness metagenomes. Subsequently, we will be able not only to characterize complex microbiomes but also to manipulate communities to achieve prosperous outcomes for health, agriculture, and environmental sustainability.
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Affiliation(s)
- Felicia N New
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14853, USA;
| | - Ilana L Brito
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14853, USA;
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30
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Transcriptome reconstruction and functional analysis of eukaryotic marine plankton communities via high-throughput metagenomics and metatranscriptomics. Genome Res 2020; 30:647-659. [PMID: 32205368 PMCID: PMC7197479 DOI: 10.1101/gr.253070.119] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Accepted: 03/18/2020] [Indexed: 11/25/2022]
Abstract
Large-scale metagenomic and metatranscriptomic data analyses are often restricted by their gene-centric approach, limiting the ability to understand organismal and community biology. De novo assembly of large and mosaic eukaryotic genomes from complex meta-omics data remains a challenging task, especially in comparison with more straightforward bacterial and archaeal systems. Here, we use a transcriptome reconstruction method based on clustering co-abundant genes across a series of metagenomic samples. We investigated the co-abundance patterns of ∼37 million eukaryotic unigenes across 365 metagenomic samples collected during the Tara Oceans expeditions to assess the diversity and functional profiles of marine plankton. We identified ∼12,000 co-abundant gene groups (CAGs), encompassing ∼7 million unigenes, including 924 metagenomics-based transcriptomes (MGTs, CAGs larger than 500 unigenes). We demonstrated the biological validity of the MGT collection by comparing individual MGTs with available references. We identified several key eukaryotic organisms involved in dimethylsulfoniopropionate (DMSP) biosynthesis and catabolism in different oceanic provinces, thus demonstrating the potential of the MGT collection to provide functional insights on eukaryotic plankton. We established the ability of the MGT approach to capture interspecies associations through the analysis of a nitrogen-fixing haptophyte-cyanobacterial symbiotic association. This MGT collection provides a valuable resource for analyses of eukaryotic plankton in the open ocean by giving access to the genomic content and functional potential of many ecologically relevant eukaryotic species.
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31
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Chen LX, Anantharaman K, Shaiber A, Eren AM, Banfield JF. Accurate and complete genomes from metagenomes. Genome Res 2020; 30:315-333. [PMID: 32188701 PMCID: PMC7111523 DOI: 10.1101/gr.258640.119] [Citation(s) in RCA: 210] [Impact Index Per Article: 52.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.
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Affiliation(s)
- Lin-Xing Chen
- Department of Earth and Planetary Sciences, University of California, Berkeley, California 94720, USA
| | - Karthik Anantharaman
- Department of Earth and Planetary Sciences, University of California, Berkeley, California 94720, USA
| | - Alon Shaiber
- Graduate Program in Biophysical Sciences, University of Chicago, Chicago, Illinois 60637, USA.,Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA
| | - A Murat Eren
- Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA.,Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts 02543, USA
| | - Jillian F Banfield
- Department of Earth and Planetary Sciences, University of California, Berkeley, California 94720, USA.,Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94720, USA.,Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, University of California, Berkeley, California 94720, USA
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32
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R Marcelino V, Holmes EC, Sorrell TC. The use of taxon-specific reference databases compromises metagenomic classification. BMC Genomics 2020; 21:184. [PMID: 32106809 PMCID: PMC7045516 DOI: 10.1186/s12864-020-6592-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 02/19/2020] [Indexed: 11/10/2022] Open
Abstract
A recent article in BMC Genomics describes a new bioinformatics tool, HumanMycobiomeScan, to classify fungal taxa in metagenomic samples. This tool was used to characterize the gut mycobiome of hunter-gatherers and Western populations, resulting in the identification of a range of fungal species in the vast majority of samples. In the HumanMycobiomeScan pipeline, sequence reads are mapped against a reference database containing fungal genome sequences only. We argue that using reference databases comprised of a single taxonomic group leads to an unacceptably high number of false-positives due to: (i) mapping to conserved genetic regions in reference genomes, and (ii) sequence contamination in the assembled reference genomes. To demonstrate this, we replaced the HumanMycobiomeScan's fungal reference database with one containing genome sequences of amphibians and reptiles and re-analysed their case study. The classification pipeline recovered all species present in the reference database, revealing turtles (Geoemydidae), bull frogs (Pyxicephalidae) and snakes (Colubridae) as the most abundant herpetological taxa in the human gut. We also re-analysed their case study using a kingdom-agnostic pipeline. This revealed that while the gut of hunter-gatherers and Western subjects may be colonized by a range of microbial eukaryotes, only three fungal families were retrieved. These results highlight the pitfalls of using taxon-specific reference databases for metagenome classification, even when they are comprised of curated whole genome data. We propose that databases containing all domains of life provide the most suitable option for metagenomic species profiling, especially when targeting microbial eukaryotes.
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Affiliation(s)
- Vanessa R Marcelino
- Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW, 2006, Australia.
- Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW, 2145, Australia.
- School of Life & Environmental Sciences, Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Edward C Holmes
- Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW, 2006, Australia
- School of Life & Environmental Sciences, Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Tania C Sorrell
- Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW, 2006, Australia
- Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW, 2145, Australia
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Olm MR, Bhattacharya N, Crits-Christoph A, Firek BA, Baker R, Song YS, Morowitz MJ, Banfield JF. Necrotizing enterocolitis is preceded by increased gut bacterial replication, Klebsiella, and fimbriae-encoding bacteria. SCIENCE ADVANCES 2019; 5:eaax5727. [PMID: 31844663 PMCID: PMC6905865 DOI: 10.1126/sciadv.aax5727] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 09/30/2019] [Indexed: 05/16/2023]
Abstract
Necrotizing enterocolitis (NEC) is a devastating intestinal disease that occurs primarily in premature infants. We performed genome-resolved metagenomic analysis of 1163 fecal samples from premature infants to identify microbial features predictive of NEC. Features considered include genes, bacterial strain types, eukaryotes, bacteriophages, plasmids, and growth rates. A machine learning classifier found that samples collected before NEC diagnosis harbored significantly more Klebsiella, bacteria encoding fimbriae, and bacteria encoding secondary metabolite gene clusters related to quorum sensing and bacteriocin production. Notably, replication rates of all bacteria, especially Enterobacteriaceae, were significantly higher 2 days before NEC diagnosis. The findings uncover biomarkers that could lead to early detection of NEC and targets for microbiome-based therapeutics.
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MESH Headings
- Enterobacteriaceae/genetics
- Enterocolitis, Necrotizing/genetics
- Enterocolitis, Necrotizing/microbiology
- Feces/microbiology
- Fimbriae, Bacterial/genetics
- Fimbriae, Bacterial/microbiology
- Gastrointestinal Microbiome/genetics
- Humans
- Infant, Newborn
- Infant, Premature
- Infant, Premature, Diseases/genetics
- Infant, Premature, Diseases/microbiology
- Klebsiella/genetics
- Metagenomics
- Multigene Family/genetics
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Affiliation(s)
- Matthew R. Olm
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
| | | | | | - Brian A. Firek
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Robyn Baker
- Division of Newborn Medicine, UPMC Magee-Womens Hospital, Pittsburgh, PA, USA
| | - Yun S. Song
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Michael J. Morowitz
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jillian F. Banfield
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
- Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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34
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Bender JM, Li F, Purswani H, Capretz T, Cerini C, Zabih S, Hung L, Francis N, Chin S, Pannaraj PS, Aldrovandi G. Early exposure to antibiotics in the neonatal intensive care unit alters the taxonomic and functional infant gut microbiome. J Matern Fetal Neonatal Med 2019; 34:3335-3343. [PMID: 31744351 DOI: 10.1080/14767058.2019.1684466] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
INTRODUCTION The infant gut microbiome is thought to play a key role in developing metabolic and immunologic pathways. Antibiotics have been shown to disrupt the human microbiome, but the impact they have on infants during this key window of development remains poorly understood. Through this study, we further characterize the effect antibiotics have on the gut microbiome of infants by looking at metagenomic sequencing data over time. MATERIALS AND METHODS Stool samples were collected on infants from a large tertiary care neonatal intensive care unit. After DNA extraction, metagenomics libraries were generated and sequenced. Taxonomic and functional analyses were then performed. Further directed specimen sequencing for fungal species was also performed. RESULTS A total of 51 stool samples from 25 infants were analyzed: seven infants were on antibiotics during at least one of their collection time points. Antibiotics given at birth altered the microbiome (PERMANOVA R2 = 0.044, p = .002) but later courses did not (R2 = 0.023, p = .114). Longitudinal samples collected while off antibiotics were more similar than those collected during a transition on or off antibiotics (mean Bray-Curtis distance 0.29 vs. 0.63, Wilcoxon p = .06). Functional analysis revealed four microbial pathways that were disrupted by antibiotics given at-birth (p < .1, folate synthesis, glycerolipid metabolism, fatty acid biosynthesis, and glycolysis). No functional changes associated with current antibiotic use were identified. In a limited sample set, we saw little evidence of fungal involvement in the overall infant microbiome. CONCLUSION Through this study, we have further characterized the role antibiotics have in the development of the infant microbiome. Antibiotics given at birth were associated with alterations in the microbiome and had significant impact on the functional pathways involved in folate synthesis and multiple metabolic pathways. Later courses of antibiotics led to stochastic dysbiosis and a significant decrease in Escherichia coli. Further characterization of the infant mycobiome is still needed.
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Affiliation(s)
- Jeffrey M Bender
- Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Fan Li
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Heena Purswani
- Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Taylor Capretz
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Chiara Cerini
- Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Sara Zabih
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Long Hung
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Nicole Francis
- Department of Pediatrics, Kaiser Permanente, Southern California Permanente Medical Group, Los Angeles, California, USA
| | - Steven Chin
- Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Pia S Pannaraj
- Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Grace Aldrovandi
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
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Marcelino VR, Irinyi L, Eden JS, Meyer W, Holmes EC, Sorrell TC. Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities - a proof of concept under laboratory conditions. IMA Fungus 2019; 10:12. [PMID: 32355612 PMCID: PMC7184889 DOI: 10.1186/s43008-019-0012-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/19/2019] [Indexed: 12/21/2022] Open
Abstract
High-throughput sequencing (HTS) enables the generation of large amounts of genome sequence data at a reasonable cost. Organisms in mixed microbial communities can now be sequenced and identified in a culture-independent way, usually using amplicon sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several advantages over DNA-based amplicon sequencing: it is less susceptible to amplification biases, it captures only living organisms, and it enables a larger set of genes to be used for taxonomic identification. Using a model mock community comprising 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, from which the vast majority (99.5%) were correctly identified at the species level. Of the 15 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to Cryptococcus were classified as one of the four strains used in the mock community. Laboratory contaminants and/or misclassifications were diverse, but represented only 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate species- and strain-level fungal identification from metatranscriptome data as long as taxa identified at low abundance are discarded to avoid false-positives derived from contamination or misclassifications. This study highlights both the advantages and current challenges in the application of metatranscriptomics in clinical mycology and ecological studies.
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Affiliation(s)
- Vanesa R Marcelino
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW 2145 Australia.,4School of Life & Environmental Sciences, Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006 Australia
| | - Laszlo Irinyi
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW 2145 Australia
| | - John-Sebastian Eden
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW 2145 Australia
| | - Wieland Meyer
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW 2145 Australia.,3Westmead Hospital (Research and Education Network), Westmead, NSW 2145 Australia
| | - Edward C Holmes
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,4School of Life & Environmental Sciences, Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006 Australia
| | - Tania C Sorrell
- 1Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW 2006 Australia.,Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW 2145 Australia
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Kantor RS, Miller SE, Nelson KL. The Water Microbiome Through a Pilot Scale Advanced Treatment Facility for Direct Potable Reuse. Front Microbiol 2019; 10:993. [PMID: 31139160 PMCID: PMC6517601 DOI: 10.3389/fmicb.2019.00993] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 04/18/2019] [Indexed: 01/01/2023] Open
Abstract
Advanced treatment facilities for potable water reuse of wastewater are designed to achieve high removal levels of specific pathogens, as well as many other constituents. However, changes to the microbial community throughout treatment, storage, and distribution of this water have not been well characterized. We applied high-throughput amplicon sequencing, read-based, assembly-based, and genome-resolved metagenomics, and flow cytometry to investigate the microbial communities present in a pilot-scale advanced water treatment facility. Advanced treatment of secondary-treated wastewater consisted of ozonation, chloramination, microfiltration, reverse osmosis (RO), advanced oxidation (UV/H2O2), granular activated carbon (GAC) filtration, and chlorination. Treated water was fed into bench-scale simulated distribution systems (SDS). Cell counts and microbial diversity in bulk water decreased until GAC filtration, and the bacterial communities were significantly different following each treatment step. Bacteria grew within GAC media and contributed to a consistent microbial community in the filtrate, which included members of the Rhizobiales and Mycobacteriaceae. After chlorination, some of the GAC filtrate community was maintained within the SDS, and community shifts were associated with stagnation. Putative antibiotic resistance genes and potential opportunistic pathogens were identified before RO and after advanced oxidation, although few if any members of the wastewater microbial community passed through these treatment steps. These findings can contribute to improved design of advanced treatment trains and management of microbial communities in post-treatment steps.
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Affiliation(s)
- Rose S Kantor
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, United States.,Engineering Research Center for Re-inventing the Nation's Urban Water Infrastructure, Berkeley, CA, United States
| | - Scott E Miller
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, United States.,Engineering Research Center for Re-inventing the Nation's Urban Water Infrastructure, Berkeley, CA, United States
| | - Kara L Nelson
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, United States.,Engineering Research Center for Re-inventing the Nation's Urban Water Infrastructure, Berkeley, CA, United States
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