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[Abstract] Syngas fermentation via the Wood-Ljungdahl (WL) pathway is a promising approach for converting gaseous pollutants (CO and CO2) into high-value commodities. Because the WL involves several enzymes with trace metal components, it requires an adequate supply of micronutrients in the fermentation medium for targeted bioprocessing such as bioethanol production. Plackett-Burman statistical analysis was performed to examine the most efficient trace elements (Ni, Mg, Ca, Mn, Co, Cu, B, W, Zn, Fe, and Mo) and their concentrations for Clostridium ljungdahlii on ethanol production. Overall, 1.5 to 2.5 fold improvement in ethanol production could be achieved with designed trace element concentrations. The effects of tungsten and copper on ethanol and biomass production were determined to be the most significant, respectively. The model developed was statistically significant and has the potential to significantly decrease the cost of trace element solutions by 18–22%. This research demonstrates the critical importance of optimizing the medium for syngas fermentation in terms of product distribution and economic feasibility.

Systems biology strives to understand complex multi-component biological processes and capture knowledge of their function through models. With metabolic and gene expression models (ME-models), we can mathematically and simultaneously represent the majority of these processes, including transcription, translation, and metabolism. This enables us to compute the molecular constituents of a cell as a function of genetic and environmental parameters. ME-models represent an improvement in current capabilities to predict phenotypes, as demonstrated by the reconstruction and validation of a ME-model for the acetogen Clostridium ljungdahlii. C. ljungdahlii can grow autotrophically on carbon monoxide (CO), and/or carbon dioxide + hydrogen (CO2+H2) and fix these gases into multicarbon organics, an ability that can be redirected to produce biocommodities. The C. ljungdahlii ME-model was able to improve growth rate predictions, identify previously unknown secretion products, and compute the transcriptome of C. ljungdahlii accurately. ME-models offer the opportunity to systematically explore the interface between protein and function. First, perturbations of tRNA co-expression in ME-models revealed unique organization solutions to two different selective pressures: Optimization of growth through minimal co-expression of tRNAs, and efficiency of resources through optimal grouping of tRNAs. Second, because of the incorporation of protein translocation and membrane function, a ME-model was able to recapitulate acetate production during glucose consumption due to membrane overcrowding. Third, a ME-model highlighted how variations in nickel availability impacts metalloproteins, thereby controlling growth and secretion rates of fermentation products. Thus, three features that could constrain the proteome of an organism – genome architecture, ultra-structure, and media requirements – were successfully interrogated using ME-models.

Systems biology strives to understand complex multi-component biological processes and capture knowledge of their function through models. With metabolic and gene expression models (ME-models), we can mathematically and simultaneously represent the majority of these processes, including transcription, translation, and metabolism. This enables us to compute the molecular constituents of a cell as a function of genetic and environmental parameters. ME-models represent an improvement in current capabilities to predict phenotypes, as demonstrated by the reconstruction and validation of a ME-model for the acetogen Clostridium ljungdahlii. C. ljungdahlii can grow autotrophically on carbon monoxide (CO), and/or carbon dioxide + hydrogen (CO2+H2) and fix these gases into multicarbon organics, an ability that can be redirected to produce biocommodities. The C. ljungdahlii ME-model was able to improve growth rate predictions, identify previously unknown secretion products, and compute the transcriptome of C. ljungdahlii accurately. ME-models offer the opportunity to systematically explore the interface between protein and function. First, perturbations of tRNA co-expression in ME-models revealed unique organization solutions to two different selective pressures: Optimization of growth through minimal co-expression of tRNAs, and efficiency of resources through optimal grouping of tRNAs. Second, because of the incorporation of protein translocation and membrane function, a ME-model was able to recapitulate acetate production during glucose consumption due to membrane overcrowding. Third, a ME-model highlighted how variations in nickel availability impacts metalloproteins, thereby controlling growth and secretion rates of fermentation products. Thus, three features that could constrain the proteome of an organism – genome architecture, ultra-structure, and media requirements – were successfully interrogated using ME-models.

Carboxydotrophic bacteria (CTB) have received attention due to their ability to synthesize commodity chemicals from producer gas and synthesis gas (syngas). CTB have an important advantage of a high product selectivity compared to chemical catalysts. However, the product spectrum of wild-type CTB is narrow. Our objective was to investigate whether a strategy of combining two wild-type bacterial strains into a single, continuously fed bioprocessing step would be promising to broaden the product spectrum. Here, we have operated a syngas-fermentation process with Clostridium ljungdahlii and Clostridium kluyveri with in-line product extraction through gas stripping and product condensing within the syngas recirculation line. The main products from C. ljungdahlii fermentation at a pH of 6.0 were ethanol and acetate at net volumetric production rates of 65.5 and 431 mmol C·L-1·d-1, respectively. An estimated 2/3 of total ethanol produced was utilized by C. kluyveri to chain elongate with the reverse β-oxidation pathway, resulting in n-butyrate and n-caproate at net rates of 129 and 70 mmol C·L-1·d-1, respectively. C. ljungdahlii likely reduced the produced carboxylates to their corresponding alcohols with the reductive power from syngas. This resulted in the longer-chain alcohols n-butanol, n-hexanol, and n-octanol at net volumetric production rates of 39.2, 31.7, and 0.045 mmol C·L-1·d-1, respectively. The continuous production of the longer-chain alcohols occurred only within a narrow pH spectrum of 5.7-6.4 due to the pH discrepancy between the two strains. Regardless whether other wild-type strains could overcome this pH discrepancy, the specificity (mol carbon in product per mol carbon in all other liquid products) for each longer-chain alcohol may never be high in a single bioprocessing step. This, because two bioprocesses compete for intermediates (i.e., carboxylates): (1) chain elongation; and (2)