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Zoccarato L, Sher D, Miki T, Segrè D, Grossart HP. A comparative whole-genome approach identifies bacterial traits for marine microbial interactions. Commun Biol 2022; 5:276. [PMID: 35347228 PMCID: PMC8960797 DOI: 10.1038/s42003-022-03184-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/30/2021] [Indexed: 12/11/2022] Open
Abstract
Microbial interactions shape the structure and function of microbial communities with profound consequences for biogeochemical cycles and ecosystem health. Yet, most interaction mechanisms are studied only in model systems and their prevalence is unknown. To systematically explore the functional and interaction potential of sequenced marine bacteria, we developed a trait-based approach, and applied it to 473 complete genomes (248 genera), representing a substantial fraction of marine microbial communities. We identified genome functional clusters (GFCs) which group bacterial taxa with common ecology and life history. Most GFCs revealed unique combinations of interaction traits, including the production of siderophores (10% of genomes), phytohormones (3-8%) and different B vitamins (57-70%). Specific GFCs, comprising Alpha- and Gammaproteobacteria, displayed more interaction traits than expected by chance, and are thus predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Linked trait clusters (LTCs) identify traits that may have evolved to act together (e.g., secretion systems, nitrogen metabolism regulation and B vitamin transporters), providing testable hypotheses for complex mechanisms of microbial interactions. Our approach translates multidimensional genomic information into an atlas of marine bacteria and their putative functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.
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Affiliation(s)
- Luca Zoccarato
- Department of Plankton and Microbial Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), 16775, Stechlin, Germany.
| | - Daniel Sher
- Department of Marine Biology, Leon H. Charney School of Marine Sciences, University of Haifa, 3498838, Haifa, Israel.
| | - Takeshi Miki
- Faculty of Advanced Science and Technology, Ryukoku University, 520-2194, Otsu, Japan
| | - Daniel Segrè
- Departments of Biology, Biomedical Engineering, Physics, Boston University, 02215, Boston, MA, USA
- Bioinformatics Program & Biological Design Center, Boston University, 02215, Boston, MA, USA
| | - Hans-Peter Grossart
- Department of Plankton and Microbial Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), 16775, Stechlin, Germany.
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), 14195, Berlin, Germany.
- Institute of Biochemistry and Biology, Potsdam University, 14476, Potsdam, Germany.
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2
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Galvez G, Ortega J, Fredericksen F, Aliaga-Tobar V, Parra V, Reyes-Jara A, Pizarro L, Latorre M. Co-occurrence Interaction Networks of Extremophile Species Living in a Copper Mining Tailing. Front Microbiol 2022; 12:791127. [PMID: 35069487 PMCID: PMC8773694 DOI: 10.3389/fmicb.2021.791127] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
Copper mining tailings are characterized by high concentrations of heavy metals and an acidic pH, conditions that require an extreme adaptation for any organism. Currently, several bacterial species have been isolated and characterized from mining environments; however, very little is known about the structure of microbial communities and how their members interact with each other under the extreme conditions where they live. This work generates a co-occurrence network, representing the bacterial soil community from the Cauquenes copper tailing, which is the largest copper waste deposit worldwide. A representative sampling of six zones from the Cauquenes tailing was carried out to determine pH, heavy metal concentration, total DNA extraction, and subsequent assignment of Operational Taxonomic Units (OTUs). According to the elemental concentrations and pH, the six zones could be grouped into two sectors: (1) the "new tailing," characterized by neutral pH and low concentration of elements, and (2) the "old tailing," having extremely low pH (~3.5) and a high concentration of heavy metals (mainly copper). Even though the abundance and diversity of species were low in both sectors, the Pseudomonadaceae and Flavobacteriaceae families were over-represented. Additionally, the OTU identifications allowed us to identify a series of bacterial species with diverse biotechnological potentials, such as copper bioleaching and drought stress alleviation in plants. Using the OTU information as a template, we generated co-occurrence networks for the old and new tailings. The resulting models revealed a rearrangement between the interactions of members living in the old and new tailings, and highlighted conserved bacterial drivers as key nodes, with positive interactions in the network of the old tailings, compared to the new tailings. These results provide insights into the structure of the soil bacterial communities growing under extreme environmental conditions in mines.
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Affiliation(s)
- Gabriel Galvez
- Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
| | - Jaime Ortega
- Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
| | - Fernanda Fredericksen
- Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
| | - Victor Aliaga-Tobar
- Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
| | - Valentina Parra
- Departamento de Bioquímica y Biología Molecular and Advanced Center for Chronic Diseases (ACCDiS), Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile
| | - Angélica Reyes-Jara
- Laboratorio de Microbiología y Probióticos, INTA, Universidad de Chile, Santiago, Chile
| | - Lorena Pizarro
- Laboratorio de Inmunidad Vegetal, Instituto de Ciencias Agroalimentarias, Animales y Ambientales, Universidad de O’Higgins, Rancagua, Chile
| | - Mauricio Latorre
- Laboratorio de Bioingeniería, Instituto de Ciencias de la Ingeniería, Universidad de O’Higgins, Rancagua, Chile
- Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile
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3
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Mataigne V, Vannier N, Vandenkoornhuyse P, Hacquard S. Microbial Systems Ecology to Understand Cross-Feeding in Microbiomes. Front Microbiol 2021; 12:780469. [PMID: 34987488 PMCID: PMC8721230 DOI: 10.3389/fmicb.2021.780469] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 11/25/2021] [Indexed: 12/26/2022] Open
Abstract
Understanding how microorganism-microorganism interactions shape microbial assemblages is a key to deciphering the evolution of dependencies and co-existence in complex microbiomes. Metabolic dependencies in cross-feeding exist in microbial communities and can at least partially determine microbial community composition. To parry the complexity and experimental limitations caused by the large number of possible interactions, new concepts from systems biology aim to decipher how the components of a system interact with each other. The idea that cross-feeding does impact microbiome assemblages has developed both theoretically and empirically, following a systems biology framework applied to microbial communities, formalized as microbial systems ecology (MSE) and relying on integrated-omics data. This framework merges cellular and community scales and offers new avenues to untangle microbial coexistence primarily by metabolic modeling, one of the main approaches used for mechanistic studies. In this mini-review, we first give a concise explanation of microbial cross-feeding. We then discuss how MSE can enable progress in microbial research. Finally, we provide an overview of a MSE framework mostly based on genome-scale metabolic-network reconstruction that combines top-down and bottom-up approaches to assess the molecular mechanisms of deterministic processes of microbial community assembly that is particularly suitable for use in synthetic biology and microbiome engineering.
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Affiliation(s)
- Victor Mataigne
- Université de Rennes 1, CNRS, UMR6553 ECOBIO, Rennes, France
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Nathan Vannier
- Université de Rennes 1, CNRS, UMR6553 ECOBIO, Rennes, France
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4
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Dittami SM, Arboleda E, Auguet JC, Bigalke A, Briand E, Cárdenas P, Cardini U, Decelle J, Engelen AH, Eveillard D, Gachon CMM, Griffiths SM, Harder T, Kayal E, Kazamia E, Lallier FH, Medina M, Marzinelli EM, Morganti TM, Núñez Pons L, Prado S, Pintado J, Saha M, Selosse MA, Skillings D, Stock W, Sunagawa S, Toulza E, Vorobev A, Leblanc C, Not F. A community perspective on the concept of marine holobionts: current status, challenges, and future directions. PeerJ 2021; 9:e10911. [PMID: 33665032 PMCID: PMC7916533 DOI: 10.7717/peerj.10911] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 01/16/2021] [Indexed: 12/19/2022] Open
Abstract
Host-microbe interactions play crucial roles in marine ecosystems. However, we still have very little understanding of the mechanisms that govern these relationships, the evolutionary processes that shape them, and their ecological consequences. The holobiont concept is a renewed paradigm in biology that can help to describe and understand these complex systems. It posits that a host and its associated microbiota with which it interacts, form a holobiont, and have to be studied together as a coherent biological and functional unit to understand its biology, ecology, and evolution. Here we discuss critical concepts and opportunities in marine holobiont research and identify key challenges in the field. We highlight the potential economic, sociological, and environmental impacts of the holobiont concept in marine biological, evolutionary, and environmental sciences. Given the connectivity and the unexplored biodiversity specific to marine ecosystems, a deeper understanding of such complex systems requires further technological and conceptual advances, e.g., the development of controlled experimental model systems for holobionts from all major lineages and the modeling of (info)chemical-mediated interactions between organisms. Here we propose that one significant challenge is to bridge cross-disciplinary research on tractable model systems in order to address key ecological and evolutionary questions. This first step is crucial to decipher the main drivers of the dynamics and evolution of holobionts and to account for the holobiont concept in applied areas, such as the conservation, management, and exploitation of marine ecosystems and resources, where practical solutions to predict and mitigate the impact of human activities are more important than ever.
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Affiliation(s)
- Simon M Dittami
- Integrative Biology of Marine Models (LBI2M), Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
| | - Enrique Arboleda
- FR2424, Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
| | | | - Arite Bigalke
- Institute for Inorganic and Analytical Chemistry, Bioorganic Analytics, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Enora Briand
- Laboratoire Phycotoxines, Ifremer, Nantes, France
| | - Paco Cárdenas
- Pharmacognosy, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Ulisse Cardini
- Integrative Marine Ecology Dept, Stazione Zoologica Anton Dohrn, Napoli, Italy
| | - Johan Decelle
- Laboratoire de Physiologie Cellulaire et Végétale, Université Grenoble Alpes, CNRS, CEA, INRA, Grenoble, France
| | | | - Damien Eveillard
- Laboratoire des Sciences Numériques de Nantes (LS2N), Université de Nantes, CNRS, Nantes, France
| | - Claire M M Gachon
- Scottish Marine Institute, Scottish Association for Marine Science, Oban, United Kingdom
| | - Sarah M Griffiths
- School of Science and the Environment, Manchester Metropolitan University, Manchester, United Kingdom
| | | | - Ehsan Kayal
- FR2424, Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
| | | | - François H Lallier
- Adaptation and Diversity in the Marine Environment, Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
| | - Mónica Medina
- Department of Biology, Pennsylvania State University, University Park, United States of America
| | - Ezequiel M Marzinelli
- Ecology and Environment Research Centre, The University of Sydney, Sydney, Australia.,Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore.,Sydney Institute of Marine Science, Mosman, Australia
| | | | - Laura Núñez Pons
- Section Biology and Evolution of Marine Organisms, Stazione Zoologica Anton Dohrn, Napoli, Italy
| | - Soizic Prado
- Molecules of Communication and Adaptation of Microorganisms (UMR 7245), National Museum of Natural History, CNRS, Paris, France
| | - José Pintado
- Instituto de Investigaciones Marinas, CSIC, Vigo, Spain
| | - Mahasweta Saha
- Benthic Ecology, Helmholtz Center for Ocean Research, Kiel, Germany.,Marine Ecology and Biodiversity, Plymouth Marine Laboratory, Plymouth, United Kingdom
| | - Marc-André Selosse
- National Museum of Natural History, Département Systématique et Evolution, Paris, France.,Faculty of Biology, University of Gdansk, Gdansk, Poland
| | - Derek Skillings
- Philosophy Department, University of Pennsylvania, Philadelphia, United States of America
| | - Willem Stock
- Laboratory of Protistology & Aquatic Ecology, Department of Biology, Ghent University, Ghent, Belgium
| | - Shinichi Sunagawa
- Dept. of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH, Zürich, Switzerland
| | - Eve Toulza
- IHPE, Univ. de Montpellier, CNRS, IFREMER, UPDV, Perpignan, France
| | - Alexey Vorobev
- CEA - Institut de Biologie François Jacob, Genoscope, Evry, France
| | - Catherine Leblanc
- Integrative Biology of Marine Models (LBI2M), Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
| | - Fabrice Not
- Adaptation and Diversity in the Marine Environment, Station Biologique de Roscoff, Sorbonne Université, CNRS, Roscoff, France
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5
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Tao J, Liu X, Luo X, Teng T, Jiang C, Drewniak L, Yang Z, Yin H. An integrated insight into bioleaching performance of chalcopyrite mediated by microbial factors: Functional types and biodiversity. BIORESOURCE TECHNOLOGY 2021; 319:124219. [PMID: 33254450 DOI: 10.1016/j.biortech.2020.124219] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 09/30/2020] [Accepted: 10/01/2020] [Indexed: 06/12/2023]
Abstract
Six artificial communities with different function or biodiversity were reconstructed by six typical bioleaching species for chalcopyrite leaching. Absence of sulfur oxidizers in communities significantly reduced copper extraction rates, and low diversity communities also exhibited slightly poor bioleaching performances. The variations of pH, redox potential, ferrous and copper ions indicated that the community with both sulfur oxidizers and high diversity showed fast adaptation to the environment and rapid dissolution of chalcopyrite. Integrated analysis of mineralogical and microbial parameters demonstrated that functional types of microorganisms made more contributions in mediating chalcopyrite dissolution than microbial diversity. Further correlation analysis between microbial types and chalcopyrite dissolution performances showed that sulfur oxidizers, especially Acidithiobacillus caldus, could greatly accelerate chalcopyrite dissolution by regulating solution physicochemical factors, such as redox potential and pH. This study provided a theoretical basis for improving bioleaching efficiency by balancing microbial functional types and biodiversity.
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Affiliation(s)
- Jiemeng Tao
- School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China; Key Laboratory of Biometallurgy, Ministry of Education, Changsha 410083, China
| | - Xueduan Liu
- School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China; Key Laboratory of Biometallurgy, Ministry of Education, Changsha 410083, China
| | - Xinyang Luo
- School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China
| | - Tingkai Teng
- School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Chengying Jiang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Lukasz Drewniak
- Department of Environmental Microbiology and Biotechnology, Institute of Microbiology, Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland
| | - Zhendong Yang
- Department of Environmental Microbiology and Biotechnology, Institute of Microbiology, Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland
| | - Huaqun Yin
- School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China; Key Laboratory of Biometallurgy, Ministry of Education, Changsha 410083, China.
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6
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Ma L, Wang H, Wu J, Wang Y, Zhang D, Liu X. Metatranscriptomics reveals microbial adaptation and resistance to extreme environment coupling with bioleaching performance. BIORESOURCE TECHNOLOGY 2019; 280:9-17. [PMID: 30743055 DOI: 10.1016/j.biortech.2019.01.117] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 01/22/2019] [Accepted: 01/23/2019] [Indexed: 06/09/2023]
Abstract
Chalcopyrite bioleaching by 2, 4 and 6 acidophilic strains with the same inoculation density were studied, respectively. The results indicated that the 6-strain community firstly adapted to bioleaching environment, dissolved the chalcopyrite rapidly and maintained an efficient work until late stage. Transcriptome profiles of the 6-strain community at 6th and 30th day during bioleaching process were investigated by RNA-seq. Comparative transcriptomics identified 226 and 737 significantly up-regulated genes at early and late stage, respectively. Gene annotation results revealed that microorganisms adapted to the oligotrophic environment by enhancing cell proliferation, catalytic activation and binding action to maintain their life activities at early stage, and genes related to signal transduction, localization and transporter were highly expressed as an effective response to the stressful late stage. A graphical representation was presented to show how microorganisms adapted and resisted to the extreme environment by their inner functional properties and promoted the bioleaching efficiency.
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Affiliation(s)
- Liyuan Ma
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, China; Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha 410083, China.
| | - Hongmei Wang
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Jiangjun Wu
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Yuguang Wang
- Key Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography, State Oceanic Administration, Xiamen 361005, China
| | - Du Zhang
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha 410083, China
| | - Xueduan Liu
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha 410083, China
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7
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Eveillard D, Bouskill NJ, Vintache D, Gras J, Ward BB, Bourdon J. Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle. Front Microbiol 2019; 9:3298. [PMID: 30745899 PMCID: PMC6360161 DOI: 10.3389/fmicb.2018.03298] [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: 06/11/2018] [Accepted: 12/18/2018] [Indexed: 11/15/2022] Open
Abstract
Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.
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Affiliation(s)
- Damien Eveillard
- LS2N, UMR6004 CNRS, Université de Nantes, Centrale Nantes, IMTA, Nantes, France.,Research Federation (FR2022) Tara Oceans GO-SEE, Paris, France
| | - Nicholas J Bouskill
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Damien Vintache
- LS2N, UMR6004 CNRS, Université de Nantes, Centrale Nantes, IMTA, Nantes, France.,Research Federation (FR2022) Tara Oceans GO-SEE, Paris, France
| | - Julien Gras
- LS2N, UMR6004 CNRS, Université de Nantes, Centrale Nantes, IMTA, Nantes, France
| | - Bess B Ward
- Geoscience Department, Princeton University, Princeton, NJ, United States
| | - Jérémie Bourdon
- LS2N, UMR6004 CNRS, Université de Nantes, Centrale Nantes, IMTA, Nantes, France
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8
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Muller EE, Faust K, Widder S, Herold M, Martínez Arbas S, Wilmes P. Using metabolic networks to resolve ecological properties of microbiomes. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.coisb.2017.12.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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9
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Thomas F, Bordron P, Eveillard D, Michel G. Gene Expression Analysis of Zobellia galactanivorans during the Degradation of Algal Polysaccharides Reveals both Substrate-Specific and Shared Transcriptome-Wide Responses. Front Microbiol 2017; 8:1808. [PMID: 28983288 PMCID: PMC5613140 DOI: 10.3389/fmicb.2017.01808] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 09/05/2017] [Indexed: 11/13/2022] Open
Abstract
Flavobacteriia are recognized as key players in the marine carbon cycle, due to their ability to efficiently degrade algal polysaccharides both in the open ocean and in coastal regions. The chemical complexity of algal polysaccharides, their differences between algal groups and variations through time and space, imply that marine flavobacteria have evolved dedicated degradation mechanisms and regulation of their metabolism during interactions with algae. In the present study, we report the first transcriptome-wide gene expression analysis for an alga-associated flavobacterium during polysaccharide degradation. Zobellia galactanivorans DsijT, originally isolated from a red alga, was grown in minimal medium with either glucose (used as a reference monosaccharide) or one selected algal polysaccharide from brown (alginate, laminarin) or red algae (agar, porphyran, ι- or κ-carrageenan) as sole carbon source. Expression profiles were determined using whole-genome microarrays. Integration of genomic knowledge with the automatic building of a co-expression network allowed the experimental validation of operon-like transcription units. Differential expression analysis revealed large transcriptomic shifts depending on the carbon source. Unexpectedly, transcriptomes shared common signatures when growing on chemically divergent polysaccharides from the same algal phylum. Together with the induction of numerous transcription factors, this hints at complex regulation events that fine-tune the cell behavior during interactions with algal biomass in the marine environment. The results further highlight genes and loci that may participate in polysaccharide utilization, notably encoding Carbohydrate Active enZymes (CAZymes) and glycan binding proteins together with a number of proteins of unknown function. This constitutes a set of candidate genes potentially representing new substrate specificities. By providing an unprecedented view of global transcriptomic responses during polysaccharide utilization in an alga-associated model flavobacterium, this study expands the current knowledge on the functional role of flavobacteria in the marine carbon cycle and on their interactions with algae.
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Affiliation(s)
- François Thomas
- Sorbonne Universités, UPMC Univ Paris 06, Centre National de la Recherche Scientifique, UMR 8227, Integrative Biology of Marine Models, Station Biologique de RoscoffRoscoff, France
| | - Philippe Bordron
- Sorbonne Universités, UPMC Univ Paris 06, Centre National de la Recherche Scientifique, FR2424, Analysis and Bioinformatics for Marine Science, Station Biologique de RoscoffRoscoff, France.,Mathomics, Center for Mathematical Modeling, Universidad de ChileSantiago, Chile.,Center for Genome Regulation (Fondap 15090007), Universidad de ChileSantiago, Chile
| | - Damien Eveillard
- Université de Nantes, Laboratoire des Sciences du Numérique de Nantes, Centre National de la Recherche Scientifique, ECN, IMTANantes, France
| | - Gurvan Michel
- Sorbonne Universités, UPMC Univ Paris 06, Centre National de la Recherche Scientifique, UMR 8227, Integrative Biology of Marine Models, Station Biologique de RoscoffRoscoff, France
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10
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Ofaim S, Ofek-Lalzar M, Sela N, Jinag J, Kashi Y, Minz D, Freilich S. Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation. Front Microbiol 2017; 8:1606. [PMID: 28878756 PMCID: PMC5572346 DOI: 10.3389/fmicb.2017.01606] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Accepted: 08/07/2017] [Indexed: 12/25/2022] Open
Abstract
Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs.
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Affiliation(s)
- Shany Ofaim
- Newe Ya'ar Research Center, Agricultural Research OrganizationRamat Yishay, Israel.,Faculty of Biotechnology and Food Engineering, Technion-Israel Institute of TechnologyHaifa, Israel
| | - Maya Ofek-Lalzar
- Institute of Soil, Water and Environmental Sciences, Agricultural Research OrganizationBeit Dagan, Israel
| | - Noa Sela
- Department of Plant Pathology and Weed Research, Agricultural Research Organization, The Volcani CenterBeit Dagan, Israel
| | - Jiandong Jinag
- Department of Microbiology, College of Life Sciences, Nanjing Agricultural UniversityNanjing, China
| | - Yechezkel Kashi
- Faculty of Biotechnology and Food Engineering, Technion-Israel Institute of TechnologyHaifa, Israel
| | - Dror Minz
- Institute of Soil, Water and Environmental Sciences, Agricultural Research OrganizationBeit Dagan, Israel
| | - Shiri Freilich
- Newe Ya'ar Research Center, Agricultural Research OrganizationRamat Yishay, Israel
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Budinich M, Bourdon J, Larhlimi A, Eveillard D. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems. PLoS One 2017; 12:e0171744. [PMID: 28187207 PMCID: PMC5302800 DOI: 10.1371/journal.pone.0171744] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 01/25/2017] [Indexed: 12/20/2022] Open
Abstract
Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.
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Affiliation(s)
- Marko Budinich
- Computational Biology group, LINA UMR 6241 CNRS, EMN, Université de Nantes, Nantes, France
| | - Jérémie Bourdon
- Computational Biology group, LINA UMR 6241 CNRS, EMN, Université de Nantes, Nantes, France
| | - Abdelhalim Larhlimi
- Computational Biology group, LINA UMR 6241 CNRS, EMN, Université de Nantes, Nantes, France
| | - Damien Eveillard
- Computational Biology group, LINA UMR 6241 CNRS, EMN, Université de Nantes, Nantes, France
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Bordron P, Latorre M, Cortés MP, González M, Thiele S, Siegel A, Maass A, Eveillard D. Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach. Microbiologyopen 2015; 5:106-17. [PMID: 26677108 PMCID: PMC4767419 DOI: 10.1002/mbo3.315] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 10/12/2015] [Accepted: 10/19/2015] [Indexed: 12/25/2022] Open
Abstract
Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.
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Affiliation(s)
- Philippe Bordron
- Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.,Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile
| | - Mauricio Latorre
- Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.,Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.,Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile
| | - Maria-Paz Cortés
- Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.,Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile
| | - Mauricio González
- Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.,Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile
| | - Sven Thiele
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Anne Siegel
- IRISA, UMR 6074, CNRS, Rennes, France.,INRIA, Dyliss Team, Centre Rennes-Bretagne-Atlantique, Rennes, France
| | - Alejandro Maass
- Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.,Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.,Department of Mathematical Engineering, Universidad de Chile, Santiago, Chile
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