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.
PLoS Comput Biol. 2023 Aug 9;19(8):e1011371. doi: 10.1371/journal.pcbi.1011371. eCollection 2023 Aug.
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.
沼泽红假单胞菌被认为是氮碳循环中的关键微生物之一，也是废水处理群落中最常见的成员之一。这种细菌在代谢上非常多样化。它能够在有氧和无氧条件下进行异养生长，也能够进行光自养和混合营养生长。因此，R. palustris 可以适应多种环境，并与其他生物建立共生关系，表达各种支持氨基酸、碳水化合物、核苷酸和复杂聚合物降解的酶。此外，R. palustris 可以在厌氧条件下降解多种污染物，例如芳香族化合物如苯甲酸和咖啡酸，使其能够在化学污染的环境中茁壮成长。然而，R. palustris 在化学异养或光异养条件下分解和同化不同碳氮源的许多代谢机制仍然未知。系统生物学方法，如代谢建模，已被广泛用于揭示代谢的复杂机制。以前，已经构建了代谢模型来研究 R. palustris 在有限实验条件下的选定能力。在这里，我们为 R. palustris Bis A53 (iDT1294) 构建了一个综合代谢模型 (M 模型)，该模型包含 2721 个反应、2123 种代谢物和 1294 个基因。我们使用高通量表型、生理和动力学数据对模型进行了验证，测试了超过 350 种生长条件。iDT1294 对各种碳氮源的生长预测准确率达到 90%，对芳香族化合物的同化预测准确率接近 80%。此外，M 模型准确预测了在 9 种化学异养条件下随时间变化的生长和底物消耗率的动态变化，并在光异养和光自养条件之间的代谢变化预测方面表现出很高的精度。这个综合的 M 模型将有助于阐明与多种碳氮源同化、缺氧光合作用、芳香族化合物降解以及分子氢和聚羟基丁酸酯生产相关的代谢过程。
