In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation

Chen, Jin; Henson, Michael A.

doi:10.1016/j.ymben.2016.10.002

Cited by 38 publications

(16 citation statements)

References 51 publications

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“…In addition, since growth rates estimated by genomescale reconstructions of C. ljungdahlii and C. autoethanogenum [25,37] used the same µ max value reported by [47], their estimations are also comparable with those made by the biothermodynamics-based black-box model (see Additional file 1: Figure S4).…”

Section: Assessment Of Kinetic Parametersmentioning

confidence: 60%

“…Several types of mathematical models have been proposed for understanding and predicting the behavior of microorganisms in gas fermentations [21][22][23][24][25][26][27]; other simpler models have been used for estimating process performance [4,5,[28][29][30][31]. The most popular of the modeling strategies employed recently by researchers is the genome-scale modeling (GSM), which has been used for assessing several features of the intracellular processes in C. ljungdahlii and C. autoethanogenum during syngas fermentations, e.g, the influence of the link between energy conservation and carbon metabolism on the selectivity between ethanol and acetic acid [25,[32][33][34], the co-factor specificity of certain enzymes linked to energy conservation [32,33,35], the formation of biofilms [26], the possibility of boosting ATP production by supplying arginine [36], and the feasibility of gene knock-out to reach overproduction of native and non-native products of acetogens [37]. Alternatively, with issues generally regarding on the accuracy of the quantitative predictions, GSM has also been used to assess the behavior of simulated microorganism inside large-scale bioreactors [21,26,37,38]; the main cause for these latter issues may be credited to the interlinking between the intracellular processes and the environmental conditions given by the bioreactor, besides GSM's large dependency on the objective function and the constraints applied to solve the intracellular rates of reaction [25].…”

Section: Introductionmentioning

confidence: 99%

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Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

Benalcázar

Noorman

Filho

et al. 2020

Biotechnol Biofuels

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Background: Ethanol production through fermentation of gas mixtures containing CO, CO 2 and H 2 has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requirements have been lacking in literature; such are invaluable tools for process improvements and better systems design. The present study describes the construction of a hybrid model for simulating ethanol production inside a 700 m 3 bubble column bioreactor fed with gas of two possible compositions, i.e., pure CO and a 3:1 mixture of H 2 and CO 2. Results: Estimations made using the thermodynamics-based black-box model of microbial reactions on substrate threshold concentrations, biomass yields, as well as CO and H 2 maximum specific uptake rates agreed reasonably well with data and observations reported in literature. According to the bioreactor simulation, there is a strong dependency of process performance on mass transfer rates. When mass transfer coefficients were estimated using a model developed from oxygen transfer to water, ethanol productivity reached 5.1 g L −1 h −1 ; when the H 2 /CO 2 mixture is fed to the bioreactor, productivity of CO fermentation was 19% lower. Gas utilization reached 23 and 17% for H 2 /CO 2 and CO fermentations, respectively. If mass transfer coefficients were 100% higher than those estimated, ethanol productivity and gas utilization may reach 9.4 g L −1 h −1 and 38% when feeding the H 2 /CO 2 mixture at the same process conditions. The largest energetic requirements for a complete manufacturing plant were identified for gas compression and ethanol distillation, being higher for CO fermentation due to the production of CO 2. Conclusions: The thermodynamics-based black-box model of microbial reactions may be used to quantitatively assess and consolidate the diversity of reported data on CO, CO 2 and H 2 threshold concentrations, biomass yields, maximum substrate uptake rates, and half-saturation constants for CO and H 2 for syngas fermentations by acetogenic bacteria. The maximization of ethanol productivity in the bioreactor may come with a cost: low gas utilization. Exploiting the model flexibility, multi-objective optimizations of bioreactor performance might reveal how process conditions and configurations could be adjusted to guide further process development.

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Section: Assessment Of Kinetic Parametersmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

Benalcázar

Noorman

Filho

et al. 2020

Biotechnol Biofuels

View full text Add to dashboard Cite

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“…By contrast, 2,3‐butanediol was produced in appreciable amounts only with the recycle reactors, which was attributable to higher volumetric CO consumption rates across the column compared with the conventional reactors. Further increases in 2,3‐butanediol production could be achieved in silico by modifying the C. autoethanogenum reconstruction according to published metabolic engineering strategies (Chen & Henson, ). The conventional reactors produced higher dissolved CO concentrations (Figure b) due to reduced reaction rate, lower CO conversions and higher CO concentrations in the gas phase.…”

Section: Resultsmentioning

confidence: 99%

Incorporating hydrodynamics into spatiotemporal metabolic models of bubble column gas fermentation

Griffin

et al. 2018

Biotech & Bioengineering

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Gas fermentation has emerged as a technologically and economically attractive option for producing renewable fuels and chemicals from carbon monoxide (CO) rich waste streams. LanzaTech has developed a proprietary strain of the gas fermentating acetogen Clostridium autoethanogenum as a microbial platform for synthesizing ethanol, 2,3-butanediol, and other chemicals. Bubble column reactor technology is being developed for the large-scale production, motivating the investigation of multiphase reactor hydrodynamics. In this study, we combined hydrodynamics with a genome-scale reconstruction of C. autoethanogenum metabolism and multiphase convection-dispersion equations to compare the performance of bubble column reactors with and without liquid recycle. For both reactor configurations, hydrodynamics was predicted to diminish bubble column performance with respect to CO conversion, biomass production, and ethanol production when compared with bubble column models in which the gas phase was modeled as ideal plug flow plus axial dispersion. Liquid recycle was predicted to be advantageous by increasing CO conversion, biomass production, and ethanol and 2,3-butanediol production compared with the non-recycle reactor configuration. Parametric studies performed for the liquid recycle configuration with two-phase hydrodynamics showed that increased CO feed flow rates (more gas supply), smaller CO gas bubbles (more gasliquid mass transfer), and shorter column heights (more gas per volume of liquid per time) favored ethanol production over acetate production. Our computational results demonstrate the power of combining cellular metabolic models and two-phase hydrodynamics for simulating and optimizing gas fermentation reactors.

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“…Moreover, genome-scale metabolic flux balance analysis has been used to construct spatiotemporal metabolic models for Clostridium ljungdahlii [131]. When combined with the Optknock computation, the models could predict new gene knockout targets relevant to the overproduction of ethanol, lactate and 2,3-BDO in a bubble column reactor [132]. …”

Section: Use Of Omics Based Technology To Monitor Bioprocess Performancementioning

confidence: 99%

Gas fermentation: cellular engineering possibilities and scale up

2017

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Low carbon fuels and chemicals can be sourced from renewable materials such as biomass or from industrial and municipal waste streams. Gasification of these materials allows all of the carbon to become available for product generation, a clear advantage over partial biomass conversion into fermentable sugars. Gasification results into a synthesis stream (syngas) containing carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2) and nitrogen (N2). Autotrophy–the ability to fix carbon such as CO2 is present in all domains of life but photosynthesis alone is not keeping up with anthropogenic CO2 output. One strategy is to curtail the gaseous atmospheric release by developing waste and syngas conversion technologies. Historically microorganisms have contributed to major, albeit slow, atmospheric composition changes. The current status and future potential of anaerobic gas-fermenting bacteria with special focus on acetogens are the focus of this review.

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In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation

Cited by 38 publications

References 51 publications

Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

Incorporating hydrodynamics into spatiotemporal metabolic models of bubble column gas fermentation

Gas fermentation: cellular engineering possibilities and scale up

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