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1. Characterizing the Interplay of Rubisco and Nitrogenase Enzymes in Anaerobic-Photoheterotrophically Grown Rhodopseudomonas palustris CGA009 through a Genome-Scale Metabolic and Expression Model

   https://doi.org/10.1128/spectrum.01463-22  

   Chowdhury, Niaz Bahar; Alsiyabi, Adil; Saha, Rajib (June 2022, Microbiology Spectrum)

   Gralnick, Jeffrey A. (Ed.)

   ABSTRACT Rhodopseudomonas palustris CGA009 is a Gram-negative purple nonsulfur bacterium that grows phototrophically by fixing carbon dioxide and nitrogen or chemotrophically by fixing or catabolizing a wide array of substrates, including lignin breakdown products for its carbon and fixing nitrogen for its nitrogen requirements. It can grow aerobically or anaerobically and can use light, inorganic, and organic compounds for energy production. Due to its ability to convert different carbon sources into useful products during anaerobic growth, this study reconstructed a metabolic and expression (ME) model of R. palustris to investigate its anaerobic-photoheterotrophic growth. Unlike metabolic (M) models, ME models include transcription and translation reactions along with macromolecules synthesis and couple these reactions with growth rate. This unique feature of the ME model led to nonlinear growth curve predictions, which matched closely with experimental growth rate data. At the theoretical maximum growth rate, the ME model suggested a diminishing rate of carbon fixation and predicted malate dehydrogenase and glycerol-3 phosphate dehydrogenase as alternate electron sinks. Moreover, the ME model also identified ferredoxin as a key regulator in distributing electrons between major redox balancing pathways. Because ME models include the turnover rate for each metabolic reaction, it was used to successfully capture experimentally observed temperature regulation of different nitrogenases. Overall, these unique features of the ME model demonstrated the influence of nitrogenases and rubiscos on R. palustris growth and predicted a key regulator in distributing electrons between major redox balancing pathways, thus establishing a platform for in silico investigation of R. palustris metabolism from a multiomics perspective. IMPORTANCE In this work, we reconstructed the first ME model for a purple nonsulfur bacterium (PNSB). Using the ME model, different aspects of R. palustris metabolism were examined. First, the ME model was used to analyze how reducing power entering the R. palustris cell through organic carbon sources gets partitioned into biomass, carbon dioxide fixation, and nitrogen fixation. Furthermore, the ME model predicted electron flux through ferredoxin as a major bottleneck in distributing electrons to nitrogenase enzymes. Next, the ME model characterized different nitrogenase enzymes and successfully recapitulated experimentally observed temperature regulations of those enzymes. Identifying the bottleneck responsible for transferring an electron to nitrogenase enzymes and recapitulating the temperature regulation of different nitrogenase enzymes can have profound implications in metabolic engineering, such as hydrogen production from R. palustris . Another interesting application of this ME model can be to take advantage of its redox balancing strategy to gain an understanding of the regulatory mechanism of biodegradable plastic production precursors, such as polyhydroxybutyrate (PHB). 

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2. Artificial Neural Network Reveals the Role of Transport Proteins in Rhodopseudomonas palustris CGA009 During Lignin Breakdown Product Catabolism

   https://doi.org/10.1101/2025.02.21.639544  

   Chowdhury, Niaz Bahar; Kathol, Mark; Shahreen, Nabia; Saha, Rajib (February 2025, bioRxiv)

   Abstract Rhodopseudomonas palustris, a versatile bacterium with diverse biotechnological applications, can effectively breakdown lignin, a complex and abundant polymer in plant biomass. This study investigates the metabolic response ofR. palustriswhen catabolizing various lignin breakdown products (LBPs), including the monolignolsp-coumaryl alcohol, coniferyl alcohol, sinapyl alcohol,p-coumarate, sodium ferulate, and kraft lignin. Transcriptomics and proteomics data were generated for those specific LBP breakdown conditions and used as features to train machine learning models, with growth rates as the target. Three models—Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machine (SV)—were compared, with ANN achieving the highest predictive accuracy for both transcriptomics (94%) and proteomics (96%) datasets. Permutation feature importance analysis of the ANN models identified the top twenty genes and proteins influencing growth rates. Combining results from both transcriptomics and proteomics, eight key transport proteins were found to significantly influence the growth ofR. palustrison LBPs. Re-training the ANN using only these eight transport proteins achieved predictive accuracies of 86% and 76% for proteomics and transcriptomics, respectively. This work highlights the potential of ANN-based models to predict growth-associated genes and proteins, shedding light on the metabolic behavior ofR. palustrisin lignin degradation under aerobic and anaerobic conditions. ImportanceThis study is significant as it addresses the biotechnological potential ofRhodopseudomonas palustrisin lignin degradation, a key challenge in converting plant biomass into commercially important products. By training machine learning models with transcriptomics and proteomics data, particularly Artificial Neural Networks (ANN), the work achieves high predictive accuracy for growth rates on various lignin breakdown products (LBPs). Identifying top genes and proteins influencing growth, especially eight key transport proteins, offers insights into the metabolic niche ofR. palustris. The ability to predict growth rates using just these few proteins highlights the efficiency of ANN models in distilling complex biological systems into manageable predictive frameworks. This approach not only enhances our understanding of lignin derivative catabolism but also paves the way for optimizingR. palustrisfor sustainable bioprocessing applications, such as bioplastic production, under varying environmental conditions. 

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3. Enzyme-constrained metabolic model of Treponema pallidum identified glycerol-3-phosphate dehydrogenase as an alternate electron sink

   https://doi.org/10.1128/msystems.01555-24  

   Shahreen, Nabia; Chowdhury, Niaz Bahar; Stone, Edward; Knobbe, Elle; Saha, Rajib (May 2025, mSystems)

   Zhang, Ying (Ed.)

   ABSTRACT Treponema pallidum, the causative agent of syphilis, poses a significant global health threat. Its strict reliance on host-derived nutrients and difficulties inin vitrocultivation have impeded detailed metabolic characterization. In this study, we present iTP251, the first genome-scale metabolic model ofT. pallidum, reconstructed and extensively curated to capture its unique metabolic features. These refinements included the curation of key reactions such as pyrophosphate-dependent phosphorylation and pathways for nucleotide synthesis, amino acid synthesis, and cofactor metabolism. The model demonstrated high predictive accuracy, validated by a MEMOTE score of 92%. To further enhance its predictive capabilities, we developed ec-iTP251, an enzyme-constrained version of iTP251, incorporating enzyme turnover rate and molecular weight information for all reactions having gene-protein-reaction associations. Ec-iTP251 provides detailed insights into protein allocation across carbon sources, showing strong agreement with proteomics data (Pearson’s correlation of 0.88) in the central carbon pathway. Moreover, the thermodynamic analysis revealed that lactate uptake serves as an additional ATP-generating strategy to utilize unused proteomes, albeit at the cost of reducing the driving force of the central carbon pathway by 27%. Subsequent analysis identified glycerol-3-phosphate dehydrogenase as an alternative electron sink, compensating for the absence of a conventional electron transport chain while maintaining cellular redox balance. These findings highlightT. pallidum’s metabolic adaptations for survival and redox balance in nutrient-limited, extracellular host environments, providing a foundation for future research into its unique bioenergetics. IMPORTANCEThis study advances our understanding ofTreponema pallidum, the syphilis-causing pathogen, through the reconstruction of iTP251, the first genome-scale metabolic model for this organism, and its enzyme-constrained version, ec-iTP251. The work addresses the challenges of studyingT. pallidum, an extracellular, host-adapted pathogen, due to its strict dependence on host-derived nutrients and challenges inin vitrocultivation. Validated with strong agreement to proteomics data, the model demonstrates high predictive reliability. Key insights include unique metabolic adaptations such as lactate uptake for ATP production and alternative redox-balancing mechanisms. These findings provide a robust framework for future studies aimed at unraveling the pathogen's survival strategies and identifying potential metabolic vulnerabilities. 

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4. Phototrophic Lactate Utilization by Rhodopseudomonas palustris Is Stimulated by Coutilization with Additional Substrates

   https://doi.org/10.1128/AEM.00048-19  

   Govindaraju, Alekhya; McKinlay, James B.; LaSarre, Breah; Parales, Rebecca E. (June 2019, Applied and Environmental Microbiology)

   ABSTRACT The phototrophic purple nonsulfur bacterium Rhodopseudomonas palustris is known for its metabolic versatility and is of interest for various industrial and environmental applications. Despite decades of research on R. palustris growth under diverse conditions, patterns of R. palustris growth and carbon utilization with mixtures of carbon substrates remain largely unknown. R. palustris readily utilizes most short-chain organic acids but cannot readily use lactate as a sole carbon source. Here we investigated the influence of mixed-substrate utilization on phototrophic lactate consumption by R. palustris . We found that lactate was simultaneously utilized with a variety of other organic acids and glycerol in time frames that were insufficient for R. palustris growth on lactate alone. Thus, lactate utilization by R. palustris was expedited by its coutilization with additional substrates. Separately, experiments using carbon pairs that did not contain lactate revealed acetate-mediated inhibition of glycerol utilization in R. palustris . This inhibition was specific to the acetate-glycerol pair, as R. palustris simultaneously utilized acetate or glycerol when either was paired with succinate or lactate. Overall, our results demonstrate that (i) R. palustris commonly employs simultaneous mixed-substrate utilization, (ii) mixed-substrate utilization expands the spectrum of readily utilized organic acids in this species, and (iii) R. palustris has the capacity to exert carbon catabolite control in a substrate-specific manner. IMPORTANCE Bacterial carbon source utilization is frequently assessed using cultures provided single carbon sources. However, the utilization of carbon mixtures by bacteria (i.e., mixed-substrate utilization) is of both fundamental and practical importance; it is central to bacterial physiology and ecology, and it influences the utility of bacteria as biotechnology. Here we investigated mixed-substrate utilization by the model organism Rhodopseudomonas palustris . Using mixtures of organic acids and glycerol, we show that R. palustris exhibits an expanded range of usable carbon substrates when provided substrates in mixtures. Specifically, coutilization enabled the prompt consumption of lactate, a substrate that is otherwise not readily used by R. palustris . Additionally, we found that R. palustris utilizes acetate and glycerol sequentially, revealing that this species has the capacity to use some substrates in a preferential order. These results provide insights into R. palustris physiology that will aid the use of R. palustris for industrial and commercial applications. 

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5. Synthetic Biology Tool Development Advances Predictable Gene Expression in the Metabolically Versatile Soil Bacterium Rhodopseudomonas palustris

   https://doi.org/10.3389/fbioe.2022.800734  

   Immethun, Cheryl M.; Kathol, Mark; Changa, Taity; Saha, Rajib (March 2022, Frontiers in Bioengineering and Biotechnology)

   Harnessing the unique biochemical capabilities of non-model microorganisms would expand the array of biomanufacturing substrates, process conditions, and products. There are non-model microorganisms that fix nitrogen and carbon dioxide, derive energy from light, catabolize methane and lignin-derived aromatics, are tolerant to physiochemical stresses and harsh environmental conditions, store lipids in large quantities, and produce hydrogen. Model microorganisms often only break down simple sugars and require low stress conditions, but they have been engineered for the sustainable manufacture of numerous products, such as fragrances, pharmaceuticals, cosmetics, surfactants, and specialty chemicals, often by using tools from synthetic biology. Transferring complex pathways has proven to be exceedingly difficult, as the cofactors, cellular conditions, and energy sources necessary for this pathway to function may not be present in the host organism. Utilization of unique biochemical capabilities could also be achieved by engineering the host; although, synthetic biology tools developed for model microbes often do not perform as designed in other microorganisms. The metabolically versatile Rhodopseudomonas palustris CGA009, a purple non-sulfur bacterium, catabolizes aromatic compounds derived from lignin in both aerobic and anaerobic conditions and can use light, inorganic, and organic compounds for its source of energy. R. palustris utilizes three nitrogenase isozymes to fulfill its nitrogen requirements while also generating hydrogen. Furthermore, the bacterium produces two forms of RuBisCo in response to carbon dioxide/bicarbonate availability. While this potential chassis harbors many beneficial traits, stable heterologous gene expression has been problematic due to its intrinsic resistance to many antibiotics and the lack of synthetic biology parts investigated in this microbe. To address these problems, we have characterized gene expression and plasmid maintenance for different selection markers, started a synthetic biology toolbox specifically for the photosynthetic R. palustris , including origins of replication, fluorescent reporters, terminators, and 5′ untranslated regions, and employed the microbe’s endogenous plasmid for exogenous protein production. This work provides essential synthetic biology tools for engineering R. palustris ’ many unique biochemical processes and has helped define the principles for expressing heterologous genes in this promising microbe through a methodology that could be applied to other non-model microorganisms. 

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