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Valenzuela JJ, Immanuel SRC, Wilson J, Turkarslan S, Ruiz M, Gibbons SM, Hunt KA, Stopnisek N, Auer M, Zemla M, Stahl DA, Baliga NS. Origin of biogeographically distinct ecotypes during laboratory evolution. Nat Commun 2024; 15:7451. [PMID: 39198408 PMCID: PMC11358416 DOI: 10.1038/s41467-024-51759-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/15/2024] [Indexed: 09/01/2024] Open
Abstract
Resource partitioning is central to the incredible productivity of microbial communities, including gigatons in annual methane emissions through syntrophic interactions. Previous work revealed how a sulfate reducer (Desulfovibrio vulgaris, Dv) and a methanogen (Methanococcus maripaludis, Mm) underwent evolutionary diversification in a planktonic context, improving stability, cooperativity, and productivity within 300-1000 generations. Here, we show that mutations in just 15 Dv and 7 Mm genes within a minimal assemblage of this evolved community gave rise to co-existing ecotypes that were spatially enriched within a few days of culturing in a fluidized bed reactor. The spatially segregated communities partitioned resources in the simulated subsurface environment, with greater lactate utilization by attached Dv but partial utilization of resulting H2 by low affinity hydrogenases of Mm in the same phase. The unutilized H2 was scavenged by high affinity hydrogenases of planktonic Mm, producing copious amounts of methane. Our findings show how a few mutations can drive resource partitioning amongst niche-differentiated ecotypes, whose interplay synergistically improves productivity of the entire mutualistic community.
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Affiliation(s)
| | | | - James Wilson
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | | | - Maryann Ruiz
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | - Sean M Gibbons
- Institute for Systems Biology, Seattle, WA, 98109, USA
- Department of Bioengineering, University of Washington, Seattle, WA, 98195, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
- eScience Institute, University of Washington, Seattle, WA, 98195, USA
| | - Kristopher A Hunt
- Civil and Environmental Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Nejc Stopnisek
- Civil and Environmental Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Manfred Auer
- Department of Biomedical Engineering, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
| | - Marcin Zemla
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - David A Stahl
- Civil and Environmental Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Department of Biology, University of Washington, Seattle, WA, USA.
- Department of Microbiology, University of Washington, Seattle, WA, USA.
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.
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Marbehan X, Roger M, Fournier F, Infossi P, Guedon E, Delecourt L, Lebrun R, Giudici-Orticoni MT, Delaunay S. Combining metabolic flux analysis with proteomics to shed light on the metabolic flexibility: the case of Desulfovibrio vulgaris Hildenborough. Front Microbiol 2024; 15:1336360. [PMID: 38463485 PMCID: PMC10920352 DOI: 10.3389/fmicb.2024.1336360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 01/24/2024] [Indexed: 03/12/2024] Open
Abstract
Introduction Desulfovibrio vulgaris Hildenborough is a gram-negative anaerobic bacterium belonging to the sulfate-reducing bacteria that exhibits highly versatile metabolism. By switching from one energy mode to another depending on nutrients availability in the environments" it plays a central role in shaping ecosystems. Despite intensive efforts to study D. vulgaris energy metabolism at the genomic, biochemical and ecological level, bioenergetics in this microorganism remain far from being fully understood. Alternatively, metabolic modeling is a powerful tool to understand bioenergetics. However, all the current models for D. vulgaris appeared to be not easily adaptable to various environmental conditions. Methods To lift off these limitations, here we constructed a novel transparent and robust metabolic model to explain D. vulgaris bioenergetics by combining whole-cell proteomic analysis with modeling approaches (Flux Balance Analysis). Results The iDvu71 model showed over 0.95 correlation with experimental data. Further simulations allowed a detailed description of D. vulgaris metabolism in various conditions of growth. Altogether, the simulations run in this study highlighted the sulfate-to-lactate consumption ratio as a pivotal factor in D. vulgaris energy metabolism. Discussion In particular, the impact on the hydrogen/formate balance and biomass synthesis is discussed. Overall, this study provides a novel insight into D. vulgaris metabolic flexibility.
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Affiliation(s)
| | - Magali Roger
- BIP-UMR 7281, Laboratoire de Bioénergétique et Ingénierie des Protéines, Aix-Marseille Université, CNRS, Marseille, France
| | | | - Pascale Infossi
- BIP-UMR 7281, Laboratoire de Bioénergétique et Ingénierie des Protéines, Aix-Marseille Université, CNRS, Marseille, France
| | | | - Louis Delecourt
- BIP-UMR 7281, Laboratoire de Bioénergétique et Ingénierie des Protéines, Aix-Marseille Université, CNRS, Marseille, France
- LISM-UMR 7255, Laboratoire d’Ingénierie des Systèmes Macromoléculaires, Aix-Marseille Université, CNRS, Marseille, France
| | - Régine Lebrun
- IMM-FR3479, Marseille Protéomique, Aix-Marseille Université, CNRS, Marseille, France
| | - Marie-Thérèse Giudici-Orticoni
- BIP-UMR 7281, Laboratoire de Bioénergétique et Ingénierie des Protéines, Aix-Marseille Université, CNRS, Marseille, France
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Germann AT, Nakielski A, Dietsch M, Petzel T, Moser D, Triesch S, Westhoff P, Axmann IM. A systematic overexpression approach reveals native targets to increase squalene production in Synechocystis sp. PCC 6803. FRONTIERS IN PLANT SCIENCE 2023; 14:1024981. [PMID: 37324717 PMCID: PMC10266222 DOI: 10.3389/fpls.2023.1024981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 04/28/2023] [Indexed: 06/17/2023]
Abstract
Cyanobacteria are a promising platform for the production of the triterpene squalene (C30), a precursor for all plant and animal sterols, and a highly attractive intermediate towards triterpenoids, a large group of secondary plant metabolites. Synechocystis sp. PCC 6803 natively produces squalene from CO2 through the MEP pathway. Based on the predictions of a constraint-based metabolic model, we took a systematic overexpression approach to quantify native Synechocystis gene's impact on squalene production in a squalene-hopene cyclase gene knock-out strain (Δshc). Our in silico analysis revealed an increased flux through the Calvin-Benson-Bassham cycle in the Δshc mutant compared to the wildtype, including the pentose phosphate pathway, as well as lower glycolysis, while the tricarboxylic acid cycle predicted to be downregulated. Further, all enzymes of the MEP pathway and terpenoid synthesis, as well as enzymes from the central carbon metabolism, Gap2, Tpi and PyrK, were predicted to positively contribute to squalene production upon their overexpression. Each identified target gene was integrated into the genome of Synechocystis Δshc under the control of the rhamnose-inducible promoter Prha. Squalene production was increased in an inducer concentration dependent manner through the overexpression of most predicted genes, which are genes of the MEP pathway, ispH, ispE, and idi, leading to the greatest improvements. Moreover, we were able to overexpress the native squalene synthase gene (sqs) in Synechocystis Δshc, which reached the highest production titer of 13.72 mg l-1 reported for squalene in Synechocystis sp. PCC 6803 so far, thereby providing a promising and sustainable platform for triterpene production.
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Affiliation(s)
- Anna T. Germann
- Institute for Synthetic Microbiology, Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andreas Nakielski
- Institute for Synthetic Microbiology, Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Maximilian Dietsch
- Institute for Synthetic Microbiology, Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tim Petzel
- Institute for Synthetic Microbiology, Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Daniel Moser
- Institute for Plant Sciences and Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, Cologne, Germany
| | - Sebastian Triesch
- Institute of Plant Biochemistry, Cluster of Excellence on Plant Science (CEPLAS), Heinrich Heine University, Düsseldorf, Germany
| | - Philipp Westhoff
- Plant Metabolism and Metabolomics Laboratory, Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ilka M. Axmann
- Institute for Synthetic Microbiology, Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Cross-Feedings, Competition, and Positive and Negative Synergies in a Four-Species Synthetic Community for Anaerobic Degradation of Cellulose to Methane. mBio 2023; 14:e0318922. [PMID: 36847519 PMCID: PMC10128006 DOI: 10.1128/mbio.03189-22] [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: 03/01/2023] Open
Abstract
Complex interactions exist among microorganisms in a community to carry out ecological processes and adapt to changing environments. Here, we constructed a quad-culture consisting of a cellulolytic bacterium (Ruminiclostridium cellulolyticum), a hydrogenotrophic methanogen (Methanospirillum hungatei), an acetoclastic methanogen (Methanosaeta concilii), and a sulfate-reducing bacterium (Desulfovibrio vulgaris). The four microorganisms in the quad-culture cooperated via cross-feeding to produce methane using cellulose as the only carbon source and electron donor. The community metabolism of the quad-culture was compared with those of the R. cellulolyticum-containing tri-cultures, bi-cultures, and mono-culture. Methane production was higher in the quad-culture than the sum of the increases in the tri-cultures, which was attributed to a positive synergy of four species. In contrast, cellulose degradation by the quad-culture was lower than the additive effects of the tri-cultures which represented a negative synergy. The community metabolism of the quad-culture was compared between a control condition and a treatment condition with sulfate addition using metaproteomics and metabolic profiling. Sulfate addition enhanced sulfate reduction and decreased methane and CO2 productions. The cross-feeding fluxes in the quad-culture in the two conditions were modeled using a community stoichiometric model. Sulfate addition strengthened metabolic handoffs from R. cellulolyticum to M. concilii and D. vulgaris and intensified substrate competition between M. hungatei and D. vulgaris. Overall, this study uncovered emergent properties of higher-order microbial interactions using a four-species synthetic community. IMPORTANCE A synthetic community was designed using four microbial species that together performed distinct key metabolic processes in the anaerobic degradation of cellulose to methane and CO2. The microorganisms exhibited expected interactions, such as cross-feeding of acetate from a cellulolytic bacterium to an acetoclastic methanogen and competition of H2 between a sulfate reducing bacterium and a hydrogenotrophic methanogen. This validated our rational design of the interactions between microorganisms based on their metabolic roles. More interestingly, we also found positive and negative synergies as emergent properties of high-order microbial interactions among three or more microorganisms in cocultures. These microbial interactions can be quantitatively measured by adding and removing specific members. A community stoichiometric model was constructed to represent the fluxes in the community metabolic network. This study paved the way toward a more predictive understanding of the impact of environmental perturbations on microbial interactions sustaining geochemically significant processes in natural systems.
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Zhang Z, Guo Q, Qian J, Ye C, Huang H. Construction and application of the genome-scale metabolic model of Streptomyces radiopugnans. Front Bioeng Biotechnol 2023; 11:1108412. [PMID: 36873364 PMCID: PMC9982006 DOI: 10.3389/fbioe.2023.1108412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 02/07/2023] [Indexed: 02/19/2023] Open
Abstract
Geosmin is one of the most common earthy-musty odor compounds, which is mainly produced by Streptomyces. Streptomyces radiopugnans was screened in radiation-polluted soil, which has the potential to overproduce geosmin. However, due to the complex cellular metabolism and regulation mechanism, the phenotypes of S. radiopugnans were hard to investigate. A genome-scale metabolic model of S. radiopugnans named iZDZ767 was constructed. Model iZDZ767 involved 1,411 reactions, 1,399 metabolites, and 767 genes; its gene coverage was 14.1%. Model iZDZ767 could grow on 23 carbon sources and five nitrogen sources, which achieved 82.1% and 83.3% prediction accuracy, respectively. For the essential gene prediction, the accuracy was 97.6%. According to the simulation of model iZDZ767, D-glucose and urea were the best for geosmin fermentation. The culture condition optimization experiments proved that with D-glucose as the carbon source and urea as the nitrogen source (4 g/L), geosmin production could reach 581.6 ng/L. Using the OptForce algorithm, 29 genes were identified as the targets of metabolic engineering modification. With the help of model iZDZ767, the phenotypes of S. radiopugnans could be well resolved. The key targets for geosmin overproduction could also be identified efficiently.
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Affiliation(s)
- Zhidong Zhang
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Technology University, Nanjing, China.,Institute of Microbiology, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Qi Guo
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Technology University, Nanjing, China
| | - Jinyi Qian
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
| | - Chao Ye
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
| | - He Huang
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Technology University, Nanjing, China.,School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
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Wendering P, Nikoloski Z. COMMIT: Consideration of metabolite leakage and community composition improves microbial community reconstructions. PLoS Comput Biol 2022; 18:e1009906. [PMID: 35320266 PMCID: PMC8942231 DOI: 10.1371/journal.pcbi.1009906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 02/09/2022] [Indexed: 11/18/2022] Open
Abstract
Composition and functions of microbial communities affect important traits in diverse hosts, from crops to humans. Yet, mechanistic understanding of how metabolism of individual microbes is affected by the community composition and metabolite leakage is lacking. Here, we first show that the consensus of automatically generated metabolic reconstructions improves the quality of the draft reconstructions, measured by comparison to reference models. We then devise an approach for gap filling, termed COMMIT, that considers metabolites for secretion based on their permeability and the composition of the community. By applying COMMIT with two soil communities from the Arabidopsis thaliana culture collection, we could significantly reduce the gap-filling solution in comparison to filling gaps in individual reconstructions without affecting the genomic support. Inspection of the metabolic interactions in the soil communities allows us to identify microbes with community roles of helpers and beneficiaries. Therefore, COMMIT offers a versatile fully automated solution for large-scale modelling of microbial communities for diverse biotechnological applications.
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Affiliation(s)
- Philipp Wendering
- Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Zoran Nikoloski
- Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
- Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
- * E-mail:
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7
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Herencias C, Salgado-Briegas S, Prieto MA, Nogales J. Providing new insights on the biphasic lifestyle of the predatory bacterium Bdellovibrio bacteriovorus through genome-scale metabolic modeling. PLoS Comput Biol 2020; 16:e1007646. [PMID: 32925899 PMCID: PMC7529429 DOI: 10.1371/journal.pcbi.1007646] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 10/01/2020] [Accepted: 07/20/2020] [Indexed: 12/30/2022] Open
Abstract
In this study we analyze the growth-phase dependent metabolic states of Bdellovibrio bacteriovorus by constructing a fully compartmented, mass and charge-balanced genome-scale metabolic model of this predatory bacterium (iCH457). Considering the differences between life cycle phases driving the growth of this predator, growth-phase condition-specific models have been generated allowing the systematic study of its metabolic capabilities. Using these computational tools, we have been able to analyze, from a system level, the dynamic metabolism of the predatory bacteria as the life cycle progresses. We provide computational evidences supporting potential axenic growth of B. bacteriovorus's in a rich medium based on its encoded metabolic capabilities. Our systems-level analysis confirms the presence of "energy-saving" mechanisms in this predator as well as an abrupt metabolic shift between the attack and intraperiplasmic growth phases. Our results strongly suggest that predatory bacteria's metabolic networks have low robustness, likely hampering their ability to tackle drastic environmental fluctuations, thus being confined to stable and predictable habitats. Overall, we present here a valuable computational testbed based on predatory bacteria activity for rational design of novel and controlled biocatalysts in biotechnological/clinical applications.
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Affiliation(s)
- Cristina Herencias
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
| | - Sergio Salgado-Briegas
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
| | - M. Auxiliadora Prieto
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
| | - Juan Nogales
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
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Curran DM, Grote A, Nursimulu N, Geber A, Voronin D, Jones DR, Ghedin E, Parkinson J. Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets. eLife 2020; 9:e51850. [PMID: 32779567 PMCID: PMC7419141 DOI: 10.7554/elife.51850] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 07/14/2020] [Indexed: 12/17/2022] Open
Abstract
The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia-present in many filariae-which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.
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Affiliation(s)
- David M Curran
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
| | - Alexandra Grote
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
| | - Nirvana Nursimulu
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
- Department of Computer Science, University of TorontoTorontoCanada
| | - Adam Geber
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
| | | | - Drew R Jones
- Department of Biochemistry and Molecular Pharmacology, New York University School of MedicineNew YorkUnited States
| | - Elodie Ghedin
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
- Department of Epidemiology, School of Global Public Health, New York UniversityNew YorkUnited States
| | - John Parkinson
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
- Department of Computer Science, University of TorontoTorontoCanada
- Department of Biochemistry, University of TorontoTorontoCanada
- Department of Molecular Genetics, University of TorontoTorontoCanada
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