Bioprocess and Biosystems Engineering最新文献

This study aimed to improve methyl tertiary butyl ether (MTBE) degradation and power production in microbial fuel cells (MFCs) by employing an iron nanoparticle-coated graphite carbon electrode (Fe-GCE), co-metabolites (sodium acetate (SAC) and glucose (GLS)), and surfactants (sodium dodecyl sulfate (SDS) and cetyltrimethylammonium bromide (CTAB)). Fe-GCE enhanced the roughness and hydrophilicity of the electrodes, thereby promoting their electrochemical activity. This study compared the use of polyvinyl alcohol/glutaraldehyde (PVA/GA) and Nafion 117 membranes and the impact of carbon sources and surfactants on the performance of MFCs. The optimal conditions achieved 97.9% MTBE removal (10 mg/L) within 96 h by employing SAC and SDS in Nafion 117-MFC with a voltage of 335 mV in synthetic wastewater. Fe-GCE exhibited minimal antibacterial action and iron leaching (< 0.3 mg/L in 30 days), suggesting its stability during wastewater treatment. Bacterial community profiling revealed that Bacillus, Alcaligenes, Trichococcus, and Magnetospirillum were the main MTBE degraders. Statistical analysis validated substantial improvement in MTBE removal and voltage yield with the use of additives, and that PVA/GA-MFC had performance similar to Nafion 117-MFC, providing a cost-effective alternative with potential commercial success. This study provides insights into the potential use of MFCs for treating recalcitrant pollutants while producing green energy, paving the way for eco-friendly waste management strategies.

The rising global demand for sustainable energy has directed significant attention towards biohydrogen production via dark fermentation of organic wastes. Accurate yield prediction is crucial for optimizing process conditions and enhancing overall process. This study aims to develop a robust and interpretable predictive framework that integrates kinetic modeling with a hybrid Bayesian Optimization-Artificial Neural Network (BO-ANN) approach for precise biohydrogen yield prediction. The core novelty lies in representing each substrate not as a simple category, but by its quantitative kinetic parameters from the Modified Gompertz equation, providing a biologically meaningful input. A comprehensive database compiled from the literature incorporates key process variables, including temperature, pH, residence time, and substrate concentration, along with kinetic parameters from the Modified Gompertz equation characterizing each substrate. The BO algorithm was employed to optimize the ANN architecture, and 5-fold cross-validation was used to evaluate model generalization ability. The proposed hybrid model achieved outstanding predictive performance (R² = 0.9980, RMSE = 0.0117, MAE = 0.0062), confirming its accuracy and robustness. Furthermore, SHAP analysis and correlation metrics provided interpretable insights into feature contributions, particularly the relevance of kinetic descriptors. Overall, the proposed BO-ANN framework offers a scalable, interpretable, and biologically grounded tool to improve predictive accuracy and support the design of more efficient and sustainable biohydrogen production systems.

Accurate real-time estimation of system states and metabolic parameters is essential for effective bioprocess control. However, the dynamics of microbial adaptation-the rate at which a microorganism adapts to changes in the substrate concentration-is often overlooked, leading to early-stage plant-model mismatches and inaccurate estimation of relevant parameters, such as the biomass yield on carbon source ([Formula: see text]) or the maximum substrate uptake rate ([Formula: see text]). This work introduces a novel model-based observer for simultaneous state and parameter estimation that explicitly accounts for substrate uptake dynamics. By defining the substrate uptake rate ([Formula: see text]) as a state variable and introducing a random variable (λ) to represent the biomass-specific substrate uptake adaptability rate, we construct a Bayesian estimator that allows proper determination of the states and parameters in fed-batch fermentations of E. coli while maintaining near-zero centered residuals between the plant output and the proposed model stoichiometry. This work advances methods for robust state and adaptive parameter estimation in dynamic bioprocess environments under uncertainty.

Improving the reductive tricarboxylic acid (rTCA) pathway in facultative anaerobic bacteria has important implications for efficient succinic acid (SA) production. With respective to enhance SA production from lignocellulosic hydrolysates via improving the rTCA pathway of Klebsiella oxytoca, the overexpression of phosphoenolpyruvate carboxykinase (PCK) and carbonic anhydrase (CA) genes coupling with supplementation of sodium bicarbonate (NaHCO₃) were performed. The optimal concentrations of NaHCO₃ supplementation for wild (WT) and engineered (RT-pck, RT-ca.) strains were determined to be 3 g/L, 1 g/L and 4 g/L, respectively. The SA production achieved by RT-pck and RT-ca. strains with respective optimal NaHCO₃ supplementation reached 28.00 ± 0.33 g/L and 29.82 ± 0.35 g/L at 72 h of fermentation, resulting in the peak PCK enzyme and CA enzyme activities of 76.52 ± 6.36 pmol/(min·10⁴ cells) and 47.06 ± 8.99 pmol/(min·10⁴ cells), separately, as well as upregulation of several genes associated with the rTCA pathway. These findings elucidate the synergistic mechanism of pck/ca. gene overexpression and NaHCO₃ supplementation in improving the rTCA pathway to enhance SA production. Overall, this study provides an effective strategy for improving lignocellulosic hydrolysate-based SA production, offering promising applications in lignocellulosic biorefinery and bioproduct process.

Microbial fermentation for succinic acid production has the advantages of a short production cycle, renewable raw materials, and mild reaction conditions, and is recognized as a promising green approach. However, the succinic acid fermentation process is often accompanied by by-products such as formic acid and acetic acid, which increase the cost of subsequent separation and waste resources. This study proposed a green integrated process in which Rhodotorula glutinis As2.703 was used to selectively metabolize formic acid and acetic acid in succinic acid fermentation broth to produce high-value-added single-cell protein (SCP), while succinic acid was retained. The results showed that R. glutinis As2.703 achieved a utilization rate of 100% for formic acid and acetic acid in succinic acid fermentation broth, with a biomass of 7.05 g/L and a biomass yield of 0.46 g/g. The protein, lipid, and carotenoid contents in SCP were 53.11%, 16.65%, and 194.15 µg/g, respectively. SuperPro Designer^® was used to simulate the process of producing 54,331 tons of succinic acid annually. After integrating the SCP production module, the process achieved an annual output of 11,935 tons of SCP, with an annual revenue of 19.81 million USD. The operating cost for the SCP module was only 8.27 million USD/year, resulting in a net annual profit of 11.54 million USD. This technology not only reduced the separation cost of succinic acid but also provided a high-quality protein source for the feed industry, significantly improving the economic viability and sustainability of succinic acid production.

Although microbial immobilization has been widely applied in wastewater treatment, the functional differences between suspended sludge and carrier-attached biofilms remain poorly understood. In this study, we investigated the microbial community structure and potential metabolic differences between suspended sludge (MIS) and polyurethane foam (PUF)-attached biofilms (MIC) in an immobilized biochemical tank (MI) from a chemical fiber plant. Compared to the conventional activated sludge process (CAS), the MI demonstrated significantly enhanced removal efficiencies of 39.4% for COD and 83.3% for BOD. The richness, diversity and unique microorganisms of MIS were higher than those of MIC. The dominant genera in MIS were Aridibacter, Diaphorobacter, Nostocoida, Pirellulaceae, Mucilaginibacter, and Rhodanobacter, while the dominant genera in MIC were Mucilaginibacter, Aridibacter, Nostocoida, Gemmata, Meiothermus, and Mycobacterium. Although the major genera were consistent, their relative abundance varied. Metabolic pathway analysis indicated that MIS showed stronger contributions to the transport of organic pollutants, while their role in nitrogen removal in the wastewater was greater than that of attached microorganisms. In contrast, carbon removal primarily occurred on the MIC. Moreover, the intensity of stochastic processes in shaping bacterial communities was observed as CAS (R² = 0.427) > MIS (R² = 0.261) > MIC (R² = 0.26), suggesting that the carriers enhanced the exposure of microbial communities to deterministic processes. These findings offer concrete theoretical support for the engineering application of microbial immobilization technology in treating industrial wastewater by elucidating key mechanistic insights.

DAAO is applied as a potential catalyst in the biosynthesis of L-PPT. However, its low solubility expression constrains its broader industrial application. Herein, a novel DAAO derived from Cladophialophora carrionii (CcDAAO) was identified, which demonstrated superior catalytic performance toward D-Ala (specific activity: 106.38 ± 1.21 U/mg, K_m: 1.56 ± 0.06 mM), along with remarkable thermostability and broad substrate spectrum. Under optimal culture conditions, the soluble expression level of CcDAAO was enhanced through a co-expression strategy with molecular chaperones, and the enzyme activity increased by 36.3% compared with the initial level. Subsequently, CcDAAO was constructed as a fusion protein (CGD) with catalase from Geobacillus sp. CHB1 (GbCAT) and applied in a D-amino acid aminotransferase (DAAT)-mediated cascade system. In a 2 L reaction system, this cascade system achieved complete conversion (> 99%) of 1 M D,L-PPT within 8 h, exhibiting a yield of 11.26 g/L/h for PPO, which represents a significant improvement over existing reports. This study presents a promising practical approach for the industrial production of optically pure L-PPT.

Microbe-assisted synthesis of metallic nanoparticles (NPs) has carved a niche among different NP generation methods owing to its simplicity, non-toxicity, low energy requirements, and potential scalability. Microorganisms have ability to produce NPs both intracellularly and extracellularly due to the presence of enzymes, proteins, and other biomolecules that can act as reducing and capping agents. However, a complete mechanistic understanding of this biosynthesis remains elusive. Biosynthesis is influenced by a myriad of factors, such as pH, temperature, reactant concentrations, reaction time, and light. The physicochemical factors associated with the synthesis process affect the morphological, biological, and catalytic properties of the NPs produced. This review focuses on the current paradigm and gaps in our understanding of microbial production pathways and the effects of physicochemical factors on the synthesis and application of various types of metallic NPs. The surveyed literature clearly elucidated the effect of these factors on the size, shape, dispersity, surface properties, and the reaction kinetics. The variations in morphological and surface properties were found to affect the performance of NPs in different applications such as catalysis, antimicrobial, and anticancer activities. Understanding the mechanistic pathways and the influence of physicochemical factors on synthesis can be potentially beneficial for the production of NPs with controlled shapes and sizes, tailored for specific applications.

The main goal of this study was to evaluate the potential of four yeasts-Rhodotorula mucilaginosa CCT 7688, Sporidiobolus pararoseus CCT 7689, Pichia fermentans CCT 7677, and Phaffia rhodozyma NRRL Y-17268-to produce carotenoids using soybean molasses as the sole nutrient source. Initially, they were cultivated in the medium-containing soybean molasses (C1, 34.32 g L^-1) and compared to the standard medium Yeast Malt (YM). R. mucilaginosa showed similar performance in both media. S. pararoseus had better performance in soybean molasses than in YM, since biomass and carotenoid production was higher. On the other hand, P. fermentans showed higher growth in soybean molasses, but pigment production was lower. P. rhodozyma outperformed in soybean molasses, resulting in higher biomass production (7.21 g L⁻¹), total carotenoid production, expressed as β-carotene (129.49 µg g⁻¹ and 914.71 µg L⁻¹), and astaxanthin production (188.25 µg g⁻¹ and 1388.84 µg L⁻¹). In addition, the use of soybean molasses showed potential to reduce about 90% of culture medium costs, in the case of this strain, in comparison with YM. Thus, P. rhodozyma was selected for the assays at different soybean molasses concentrations: 100 (C2), 150 (C3), 200 (C4), and 250 (C5) g L⁻¹. The best results were observed at C3, which provided significant increase in biomass (15.73 g L⁻¹) and total carotenoids, expressed as β-carotene (2229.30 µg L⁻¹) and astaxanthin (3519.65 µg L⁻¹). Compared to the initial medium (C1), gains exceeded 150% in some parameters, demonstrating that soybean molasses is an efficient, low-cost cultivation substrate with high potential to enable yeasts to produce carotenoids.

Wheat straw is a renewable biomass with potential for bioethanol and biorefinery applications, offering potential value-added products such as enzymes and oligosaccharides. However, its complex lignocellulosic structure, costly pretreatment requirements, and formation of inhibitory compounds hinder its utilization. Moreover, commercial enzymes used in saccharification are expensive, highlighting the need for efficient in-house enzyme production. This study investigates the application of a biological pretreatment using Trametes versicolor as an eco-friendly and cost-effective method to enhance cellulose content in wheat straw. The pretreated biomass was analyzed via acid hydrolysis and employed as a substrate for cellulase production by Penicillium chrysogenum through solid-state fermentation (SSF). The liquid extract obtained after washing the biomass was evaluated for laccase and manganese peroxidase (MnP) activities. In addition, acid hydrolysis was performed to detect oligosaccharides. Biological pretreatment increased cellulose content from 36.24 ± 1.74 to 41.25 ± 1.65% and reduced lignin from 28.66 ± 1.08 to 21.12 ± 1.22%, confirming effective delignification. The pretreated straw supported cellulase production with activities of 2.66 ± 0.044 U/g (FPU), 20.77 ± 1.91 U/g (BGL), and 75.02 ± 2.48 U/g (CMC). Also, xylooligosaccharides reached 1.15 ± 0.06 g/L on day 21. These results demonstrate the potential of combining biological pretreatment and SSF as a sustainable approach to enhance enzyme yields and recover oligosaccharides for biorefinery applications.