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Tec-Campos D, Posadas C, Tibocha-Bonilla JD, Thiruppathy D, Glonek N, Zuñiga C, Zepeda A, Zengler K. The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions. PLoS Comput Biol 2023; 19:e1011371. [PMID: 37556472 PMCID: PMC10441798 DOI: 10.1371/journal.pcbi.1011371] [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: 12/02/2022] [Revised: 08/21/2023] [Accepted: 07/18/2023] [Indexed: 08/11/2023] Open
Abstract
The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R. palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R. palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R. palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R. palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R. palustris Bis A53 (iDT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. iDT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.
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Affiliation(s)
- Diego Tec-Campos
- Facultad de Ingeniería Química, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
| | - Camila Posadas
- Facultad de Ingeniería Química, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Juan D. Tibocha-Bonilla
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, California, United States of America
| | - Deepan Thiruppathy
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
- Department of Bioengineering, University of California, San Diego, La Jolla California, United States of America
| | - Nathan Glonek
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
| | - Cristal Zuñiga
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
| | - Alejandro Zepeda
- Facultad de Ingeniería Química, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Karsten Zengler
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
- Department of Bioengineering, University of California, San Diego, La Jolla California, United States of America
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, California, United States of America
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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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Liu H, Liu D, Huang Z, Chen Y. Bioaugmentation reconstructed nitrogen metabolism in full-scale simultaneous partial nitrification-denitrification, anammox and sulfur-dependent nitrite/nitrate reduction (SPAS). BIORESOURCE TECHNOLOGY 2023; 367:128233. [PMID: 36332873 DOI: 10.1016/j.biortech.2022.128233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/25/2022] [Accepted: 10/27/2022] [Indexed: 06/16/2023]
Abstract
To enhance nitrogen removal of fermentation pharmaceutical wastewater with high nitrogen load, a full-scale process based on simultaneous partial nitrification-denitrification/ anammox/ sulfur autotrophic denitrification (SPAS) was established via inoculating with bioaugmentation consortia in a modified two-stage AO. More than 93 % TN and 98 % NH4+-N removal were obtained at a rate of 0.8 kg-N/ m3/d in the first A/O stage, in which short-cut SND was involved with 96.05 % ESND when bioaugmented with SND, while S0-SAD could coordinate with anammox to exert further deep denitrification in the second A/O stage. KEGG analysis demonstrated that the SPAS process was synergism of HD, PN/PDN, SND, SAD and anammox metabolism, bioaugmentation could significantly up-regulate genes related to microbial metabolism (TCA cycle, Carbon metabolism, ABC transporters) and environmental adaptation (Two-component system, Quorum sensing) based on the FAPROTAX and Picrust2 functional prediction. This study provided a new perspective in engineering applications.
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Affiliation(s)
- Huimin Liu
- School of Environment and Energy, Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, Guangdong 510006, PR China
| | - Dejin Liu
- School of Environment and Energy, Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, Guangdong 510006, PR China
| | - Zhenyu Huang
- School of Environment and Energy, Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, Guangdong 510006, PR China
| | - Yuancai Chen
- School of Environment and Energy, Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, Guangdong 510006, PR China.
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