Bioconversion of Crude Glycerol into 1,3-Propanediol(1,3-PDO) with Bioelectrochemical System and Zero-Valent Iron Using Klebsiella pneumoniae L17

Kong, Da Seul; Park, Eun Joo; Sakuntala, Mutyala; Kim, Min‐Soo; Cho, Yunchul; Oh, Sang‐Eun; Kim, Changman; Kim, Eun Jung

doi:10.3390/en14206806

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…The high conversion of glycerol to 1,3-PDO in the MFC is probably related to the direction of glycerol metabolism toward the reducing branch due to the accumulation of electrons in the working electrode. Our results corroborate the work of Kong et al (2021) [28], who reported improved productivity of 1,3-PDO (28.3 mM) in a bioelectrochemical system compared to traditional fermentation (11.4 mM), with Klebsiella pneumoniae L17 as a biocatalyst.…”

Section: Glycerol Oxidation and By-products Formation During Mfc And ...supporting

confidence: 92%

A New Pseudomonas aeruginosa Isolate Enhances Its Unusual 1,3-Propanediol Generation from Glycerol in Bioelectrochemical System

Narcizo,

Mancilio,

Pedrino

et al. 2023

Catalysts

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The ability of some bacteria to perform Extracellular Electron Transfer (EET) has been explored in bioelectrochemical systems (BES) to obtain energy or chemicals from pure substances or residual substrates. Here, a new pyoverdine-producing Pseudomonas aeruginosa strain was isolated from an MFC biofilm oxidizing glycerol, a by-product of biodiesel production. Strain EL14 was investigated to assess its electrogenic ability and products. In an open circuit system (fermentation system), EL14 was able to consume glycerol and produce 1,3-propanediol, an unusual product from glycerol oxidation in P. aeruginosa. The microbial fuel cell (MFC) EL14 reached a current density of 82.4 mA m−2 during the first feeding cycle, then dropped sharply as the biofilm fell off. Cyclic voltammetry suggests that electron transfer to the anode occurs indirectly, i.e., through a redox substance, with redox peak at 0.22 V (vs Ag/AgCl), and directly probably by membrane redox proteins, with redox peak at 0.05 V (vs Ag/AgCl). EL14 produced added-value bioproducts, acetic and butyric acids, as well as 1,3 propanediol, in both fermentative and anodic conditions. However, the yield of 1,3-PDO from glycerol was enhanced from 0.57 to 0.89 (mol of 1,3-PDO mol−1 of glycerol) under MFC conditions compared to fermentation. This result was unexpected, since successful 1,3-PDO production is not usually associated with P. aeruginosa glycerol metabolism. By comparing EL14 genomic sequences related to the 1,3-PDO biosynthesis with P. aeruginosa reference strains, we observed that strain EL14 has three copies of the dhaT gene (1,3-propanediol dehydrogenase a different arrangement compared to other Pseudomonas isolates). Thus, this work functionally characterizes a bacterium never before associated with 1,3-PDO biosynthesis, indicating its potential for converting a by-product of the biodiesel industry into an emerging chemical product.

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Section: Glycerol Oxidation and By-products Formation During Mfc And ...supporting

confidence: 92%

A New Pseudomonas aeruginosa Isolate Enhances Its Unusual 1,3-Propanediol Generation from Glycerol in Bioelectrochemical System

Narcizo,

Mancilio,

Pedrino

et al. 2023

Catalysts

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“…A nonlinear dynamical system has been frst presented to describe the microbial continuous fermentation. To estimate the value of the parameter vector in the dynamical system, a parameter estimation model as presented in ( 28)- (30) has been proposed. Model ( 28)- (30) can minimize the sum of the squared steady-state concentration deviations from the experimental data and has many optimization variables and constraints.…”

Section: Discussionmentioning

confidence: 99%

“…To estimate the value of the parameter vector in the dynamical system, a parameter estimation model as presented in ( 28)- (30) has been proposed. Model ( 28)- (30) can minimize the sum of the squared steady-state concentration deviations from the experimental data and has many optimization variables and constraints. Terefore, if the number of experimental groups is large, then problem ( 28)-( 30) will be a large-scale, nonlinear, and nonconvex optimization problem.…”

Section: Discussionmentioning

confidence: 99%

“…Remark 10. In parameter estimation problem ( 28)- (30), the number of optimization variables is 15m + 16, the number of equality constraints is 15m, the number of lower bound constraints is 15m + 16, and the number of upper bound constraints is 5m + 16. Terefore, if the number m of experimental groups is large, then problem ( 28)-( 30) will be a large-scale, nonlinear, and nonconvex optimization problem.…”

Section: Parameter Estimation Model Of the Dynamical Systemmentioning

confidence: 99%

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Sequential Geometric Programming Method for Parameter Estimation of a Nonlinear System in Microbial Continuous Fermentation

Xu,

Liu

2023

International Journal of Chemical Engineering

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This paper addresses the problem of parameter estimation for the microbial continuous fermentation of glycerol to 1,3-propanediol. A nonlinear dynamical system is first presented to describe the microbial continuous fermentation. Some mathematical properties of the dynamical system in the microbial continuous fermentation are also presented. A parameter estimation model is proposed to estimate the parameters of the dynamical system. The proposed estimation model is a large-scale, nonlinear, and nonconvex optimization problem if the number of experimental groups is large. A sequential geometric programming (SGP) method is proposed to efficiently solve the parameter estimation problem. The results indicated that our proposed SGP method can yield smaller errors between the experimental and calculated steady-state concentrations than the existing seven methods. For the five error indices considered, that is, the concentration errors of biomass, glycerol, 1,3-propanediol, acetic acid, and ethanol, the results obtained using the proposed SGP method are better than those obtained using the methods in the literature (Xiu et al., Gao et al., Sun et al., Sun et al., Li and Qu, Wang et al., and Zhang and Xu), with improvements of approximately 71.86–95.03%, 52.08–94.87%, 99.70–99.98%, 5.39–90.29%, and 12.67–80.83%, respectively. This concludes that the established dynamical system can better describe the microbial continuous fermentation. We also present that our established dynamical system has multiple positive steady states in some fermentation conditions. We observe that there are two regions of multiple positive steady states at relatively high values of substrate glycerol concentration in feed medium.

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Mathematical Modeling and Simulation of 1,3‐Propanediol Production by Klebsiella pneumoniae BLh‐1 in a Batch Bioreactor Using Bayesian Statistics

Moraes,

de Vilhena,

Rossi

et al. 2024

Biotech & Bioengineering

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Mathematical modeling and computer simulation are fundamental for optimizing biotechnological processes, enabling cost reduction and scalability, thereby driving advancements in the bioindustry. In this work, mathematical modeling and estimation of fermentative kinetic parameters were carried out to produce 1,3‐propanediol (1,3‐PDO) from residual glycerol and Klebsiella pneumoniae BLh‐1. The Markov chain Monte Carlo method, using the Metropolis‐Hastings algorithm, was applied to experimental data from a batch bioreactor under aerobic and anaerobic conditions. Sensitivity analysis and parameter evolution studies were conducted. The root‐mean‐square error (rRMSE) was chosen as the validation and calibration metric for the developed mathematical model. The results indicated that the average tolerance of glycerol was 174.68 and 44.85 g L−1, the inhibitory products was 150.95 g L−1 for ethanol and 35.56 g L−1 for 1,3‐PDO, and the maximum specific rate of cell growth was 0.189 and 0.275 h−1, for aerobic and anaerobic cultures, respectively. The model presented excellent fits in both crops, with rRMSE values between 0.09 − 33.74% and 3.58 − 31.82%, for the aerobic and anaerobic environment, respectively. With this, it was possible to evaluate and extract relevant information for a better understanding and control of the bioprocess.

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Bioconversion of Crude Glycerol into 1,3-Propanediol(1,3-PDO) with Bioelectrochemical System and Zero-Valent Iron Using Klebsiella pneumoniae L17

Cited by 10 publications

References 32 publications

A New Pseudomonas aeruginosa Isolate Enhances Its Unusual 1,3-Propanediol Generation from Glycerol in Bioelectrochemical System

A New Pseudomonas aeruginosa Isolate Enhances Its Unusual 1,3-Propanediol Generation from Glycerol in Bioelectrochemical System

Sequential Geometric Programming Method for Parameter Estimation of a Nonlinear System in Microbial Continuous Fermentation

Mathematical Modeling and Simulation of 1,3‐Propanediol Production by Klebsiella pneumoniae BLh‐1 in a Batch Bioreactor Using Bayesian Statistics

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