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Kim H, Jeon J, Lee KK, Lee YH. Compositional Shift of Bacterial, Archaeal, and Fungal Communities Is Dependent on Trophic Lifestyles in Rice Paddy Soil. Front Microbiol 2021; 12:719486. [PMID: 34539610 PMCID: PMC8440912 DOI: 10.3389/fmicb.2021.719486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/16/2021] [Indexed: 11/29/2022] Open
Abstract
The soil environment determines plants’ health and performance during their life cycle. Therefore, ecological understanding on variations in soil environments, including physical, chemical, and biological properties, is crucial for managing agricultural fields. Here, we present a comprehensive and extensive blueprint of the bacterial, archaeal, and fungal communities in rice paddy soils with differing soil types and chemical properties. We discovered that natural variations of soil nutrients are important factors shaping microbial diversity. The responses of microbial diversity to soil nutrients were related to the distribution of microbial trophic lifestyles (oligotrophy and copiotrophy) in each community. The compositional changes of bacterial and archaeal communities in response to soil nutrients were mainly governed by oligotrophs, whereas copiotrophs were mainly involved in fungal compositional changes. Compositional shift of microbial communities by fertilization is linked to switching of microbial trophic lifestyles. Random forest models demonstrated that depletion of prokaryotic oligotrophs and enrichment of fungal copiotrophs are the dominant responses to fertilization in low-nutrient conditions, whereas enrichment of putative copiotrophs was important in high-nutrient conditions. Network inference also revealed that trophic lifestyle switching appertains to decreases in intra- and inter-kingdom microbial associations, diminished network connectivity, and switching of hub nodes from oligotrophs to copiotrophs. Our work provides ecological insight into how soil nutrient-driven variations in microbial communities affect soil health in modern agricultural systems.
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Affiliation(s)
- Hyun Kim
- Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea
| | - Jongbum Jeon
- Interdisciplinary Program in Agricultural Genomics, Seoul National University, Seoul, South Korea
| | - Kiseok Keith Lee
- Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea
| | - Yong-Hwan Lee
- Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea.,Interdisciplinary Program in Agricultural Genomics, Seoul National University, Seoul, South Korea.,Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.,Center for Fungal Genetic Resources, Seoul National University, Seoul, South Korea.,Plant Genomics and Breeding Institute, Seoul National University, Seoul, South Korea.,Plant Immunity Research Center, Seoul National University, Seoul, South Korea
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Tudela H, Claus SP, Saleh M. Next Generation Microbiome Research: Identification of Keystone Species in the Metabolic Regulation of Host-Gut Microbiota Interplay. Front Cell Dev Biol 2021; 9:719072. [PMID: 34540837 PMCID: PMC8440917 DOI: 10.3389/fcell.2021.719072] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/02/2021] [Indexed: 12/12/2022] Open
Abstract
The community of the diverse microorganisms residing in the gastrointestinal tract, known as the gut microbiota, is exceedingly being studied for its impact on health and disease. This community plays a major role in nutrient metabolism, maintenance of the intestinal epithelial barrier but also in local and systemic immunomodulation. A dysbiosis of the gut microbiota, characterized by an unbalanced microbial ecology, often leads to a loss of essential functions that may be associated with proinflammatory conditions. Specifically, some key microbes that are depleted in dysbiotic ecosystems, called keystone species, carry unique functions that are essential for the balance of the microbiota. In this review, we discuss current understanding of reported keystone species and their proposed functions in health. We also elaborate on current and future bioinformatics tools needed to identify missing functions in the gut carried by keystone species. We propose that the identification of such keystone species functions is a major step for the understanding of microbiome dynamics in disease and toward the development of microbiome-based therapeutics.
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Affiliation(s)
- Héloïse Tudela
- YSOPIA Bioscience, Bordeaux, France
- ImmunoConcEpT, CNRS UMR 5164, University of Bordeaux, Bordeaux, France
| | | | - Maya Saleh
- ImmunoConcEpT, CNRS UMR 5164, University of Bordeaux, Bordeaux, France
- Department of Medicine, McGill University, Montreal, QC, Canada
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Daisley BA, Reid G. BEExact: a Metataxonomic Database Tool for High-Resolution Inference of Bee-Associated Microbial Communities. mSystems 2021; 6:e00082-21. [PMID: 33824193 PMCID: PMC8546966 DOI: 10.1128/msystems.00082-21] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 03/08/2021] [Indexed: 01/04/2023] Open
Abstract
High-throughput 16S rRNA gene sequencing technologies have robust potential to improve our understanding of bee (Hymenoptera: Apoidea)-associated microbial communities and their impact on hive health and disease. Despite recent computation algorithms now permitting exact inferencing of high-resolution exact amplicon sequence variants (ASVs), the taxonomic classification of these ASVs remains a challenge due to inadequate reference databases. To address this, we assemble a comprehensive data set of all publicly available bee-associated 16S rRNA gene sequences, systematically annotate poorly resolved identities via inclusion of 618 placeholder labels for uncultivated microbial dark matter, and correct for phylogenetic inconsistencies using a complementary set of distance-based and maximum likelihood correction strategies. To benchmark the resultant database (BEExact), we compare performance against all existing reference databases in silico using a variety of classifier algorithms to produce probabilistic confidence scores. We also validate realistic classification rates on an independent set of ∼234 million short-read sequences derived from 32 studies encompassing 50 different bee types (36 eusocial and 14 solitary). Species-level classification rates on short-read ASVs range from 80 to 90% using BEExact (with ∼20% due to "bxid" placeholder names), whereas only ∼30% at best can be resolved with current universal databases. A series of data-driven recommendations are developed for future studies. We conclude that BEExact (https://github.com/bdaisley/BEExact) enables accurate and standardized microbiota profiling across a broad range of bee species-two factors of key importance to reproducibility and meaningful knowledge exchange within the scientific community that together, can enhance the overall utility and ecological relevance of routine 16S rRNA gene-based sequencing endeavors.IMPORTANCE The failure of current universal taxonomic databases to support the rapidly expanding field of bee microbiota research has led to many investigators relying on "in-house" reference sets or manual classification of sequence reads (usually based on BLAST searches), often with vague identity thresholds and subjective taxonomy choices. This time-consuming, error- and bias-prone process lacks standardization, cripples the potential for comparative cross-study analysis, and in many cases is likely to incorrectly sway study conclusions. BEExact is structured on and leverages several complementary bioinformatic techniques to enable refined inference of bee host-associated microbial communities without any other methodological modifications necessary. It also bridges the gap between current practical outcomes (i.e., phylotype-to-genus level constraints with 97% operational taxonomic units [OTUs]) and the theoretical resolution (i.e., species-to-strain level classification with 100% ASVs) attainable in future microbiota investigations. Other niche habitats could also likely benefit from customized database curation via implementation of the novel approaches introduced in this study.
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Affiliation(s)
- Brendan A Daisley
- Department of Microbiology & Immunology, The University of Western Ontario, London, Ontario, Canada
- Canadian Centre for Human Microbiome and Probiotics Research, London, Ontario, Canada
| | - Gregor Reid
- Department of Microbiology & Immunology, The University of Western Ontario, London, Ontario, Canada
- Canadian Centre for Human Microbiome and Probiotics Research, London, Ontario, Canada
- Department of Surgery, Schulich School of Medicine, London, Ontario, Canada
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Nardelli C, Granata I, D'Argenio V, Tramontano S, Compare D, Guarracino MR, Nardone G, Pilone V, Sacchetti L. Characterization of the Duodenal Mucosal Microbiome in Obese Adult Subjects by 16S rRNA Sequencing. Microorganisms 2020; 8:microorganisms8040485. [PMID: 32235377 PMCID: PMC7232320 DOI: 10.3390/microorganisms8040485] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 03/24/2020] [Accepted: 03/27/2020] [Indexed: 12/20/2022] Open
Abstract
The gut microbiota may have an impact on obesity. To date, the majority of studies in obese patients reported microbiota composition in stool samples. The aim of this study was to investigate the duodenal mucosa dysbiosis in adult obese individuals from Campania, a region in Italy with a very high percentage of obese people, to highlight microbial taxa likely associated with obesity. Duodenum biopsies were taken during upper gastrointestinal endoscopy in 19 obese (OB) and 16 lean control subjects (CO) and microbiome studied by 16S rRNA gene sequencing. Duodenal microbiome in our groups consisted of six phyla: Proteobacteria, Firmicutes, Actinobacteria, Fusobacteria, Bacteroidetes and Acidobacteria. Proteobacteria (51.1% vs. 40.1%) and Firmicutes (33.6% vs. 44.9%) were significantly (p < 0.05) more and less abundant in OB compared with CO, respectively. Oribacterium asaccharolyticum, Atopobium parvulum and Fusobacterium nucleatum were reduced (p < 0.01) and Pseudomonadales were increased (p < 0.05) in OB compared with CO. Receiver operating characteristic curve analysis showed Atopobium and Oribacterium genera able to discriminate with accuracy (power = 75% and 78%, respectively) OB from CO. In conclusion, increased Proteobacteria and decreased Firmicutes (Lachnospiraceae) characterized the duodenal microbiome of obese subjects. These data direct to further studies to evaluate the functional role of the dysbiotic-obese-associated signature.
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Affiliation(s)
- Carmela Nardelli
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, 80131 Naples, Italy;
- CEINGE Biotecnologie Avanzate S. C. a R. L., 80131 Naples, Italy;
- Task Force on Microbiome Studies, University of Naples Federico II, 80100 Naples, Italy
| | - Ilaria Granata
- Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), 80131 Naples, Italy; (I.G.); (M.R.G.)
| | - Valeria D'Argenio
- CEINGE Biotecnologie Avanzate S. C. a R. L., 80131 Naples, Italy;
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Open University, 00166 Rome, Italy
| | - Salvatore Tramontano
- Department of Medicine and Surgery, University of Salerno, 84084 Salerno, Italy; (S.T.); (V.P.)
| | - Debora Compare
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (D.C.); (G.N.)
| | - Mario Rosario Guarracino
- Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), 80131 Naples, Italy; (I.G.); (M.R.G.)
- Department of Economics and Law, University of Cassino and Southern Lazio, 03043 Cassino, Italy
| | - Gerardo Nardone
- Department of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (D.C.); (G.N.)
| | - Vincenzo Pilone
- Department of Medicine and Surgery, University of Salerno, 84084 Salerno, Italy; (S.T.); (V.P.)
| | - Lucia Sacchetti
- CEINGE Biotecnologie Avanzate S. C. a R. L., 80131 Naples, Italy;
- Task Force on Microbiome Studies, University of Naples Federico II, 80100 Naples, Italy
- Correspondence: ; Tel.: +39-0813737827
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Pinna NK, Dutta A, Monzoorul Haque M, Mande SS. Can Targeting Non-Contiguous V-Regions With Paired-End Sequencing Improve 16S rRNA-Based Taxonomic Resolution of Microbiomes?: An In Silico Evaluation. Front Genet 2019; 10:653. [PMID: 31354793 PMCID: PMC6640118 DOI: 10.3389/fgene.2019.00653] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Accepted: 06/20/2019] [Indexed: 12/14/2022] Open
Abstract
Background: Next-generation sequencing (NGS) technologies have enabled probing of microbial diversity in different environmental niches with unprecedented sequencing depth. However, due to read-length limitations of popular NGS technologies, 16S amplicon sequencing-based microbiome studies rely on targeting short stretches of the 16S rRNA gene encompassing a selection of variable (V) regions. In most cases, such a short stretch constitutes a single V-region or a couple of V-regions placed adjacent to each other on the 16S rRNA gene. Given that different V-regions have different resolving ability with respect to various taxonomic groups, selecting the optimal V-region (or a combination thereof) remains a challenge. Methods: The accuracy of taxonomic profiles generated from sequences encompassing 1) individual V-regions, 2) adjacent V-regions, and 3) pairs of non-contiguous V-regions were assessed and compared. Subsequently, the discriminating capability of different V-regions with respect to different taxonomic lineages was assessed. The possibility of using paired-end sequencing protocols to target combinations of non-adjacent V-regions was finally evaluated with respect to the utility of such an experimental design in providing improved taxonomic resolution. Results: Extensive validation with simulated microbiome datasets mimicking different environmental and host-associated microbiome samples suggest that targeting certain combinations of non-contiguously placed V-regions might yield better taxonomic classification accuracy compared to conventional 16S amplicon sequencing targets. This work also puts forward a novel in silico combinatorial strategy that enables creation of consensus taxonomic profiles from experiments targeting multiple pair-wise combinations of V-regions to improve accuracy in taxonomic classification. Conclusion: The study suggests that targeting non-contiguous V-regions with paired-end sequencing can improve 16S rRNA–based taxonomic resolution of microbiomes. Furthermore, employing the novel in silico combinatorial strategy can improve taxonomic classification without any significant additional experimental costs and/or efforts. The empirical observations obtained can potentially serve as a guideline for future 16S microbiome studies, and facilitate researchers in choosing the optimal combination of V-regions for a specific experiment/sampled environment.
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Affiliation(s)
- Nishal Kumar Pinna
- Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., Pune, Maharashtra, India
| | - Anirban Dutta
- Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., Pune, Maharashtra, India
| | - Mohammed Monzoorul Haque
- Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., Pune, Maharashtra, India
| | - Sharmila S Mande
- Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., Pune, Maharashtra, India
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