Bioprocess and Biosystems Engineering最新文献

In biologics drug discovery, transient protein expression is widely used to rapidly produce biologics, thereby accelerating the identification of lead candidates. However, the accuracy and consistency of predicting further product quality in large-scale production needs to be considered, especially with respect to physicochemical properties and posttranslational modifications. With this in mind, a transient expression system utilizing Chinese hamster ovary K1 (CHO-K1) has been established, which integrates high expression capability with quality profiles similar to those of the protein produced by stable cell lines. A well-designed vector containing transposon elements overcomes the blindness of random integration and ensures the sustained viability of cells and production capability, thus addressing the critical bottlenecks in classical transiently transfected workflows. Combined with the optimization of various transfection parameters, the customized platform achieved a titer over 1.5 g/L in the production of a bispecific antibody while maintaining a proportion of fragments, aggregates and glycosylation patterns that are comparable to those of the stable cell line protein. More importantly, this platform also demonstrated reliability in terms of quality across diverse antibody formats. This innovative protein expression platform bridges the gap between transient and stable expression on the basis of CHO-K1, ensuring the consistency of host cell types throughout the antibody discovery and development process.

In this study, the hydrodynamic cavitation (HC) process was adopted for the recovery of intracellular biopolymer, namely polyhydroxyalkanoates (PHAs), from mixed microbial culture (MMC). To investigate the potential and performance of HC process, two cavitation devices (orifice-1 and orifice-17) were employed. The impact of biomass concentration, orifice type and pressure differential on recovery yield was assessed. The HC-assisted PHA recovery protocol introduced a novel technique that uses HC for cell disruption and a solvent for biopolymer separation. The results demonstrate the feasibility of obtaining biopolymer within a short operation time (5 min), achieving 72% process efficiency using the HC-assisted recovery procedure. The biopolymer recovered via HC at optimal conditions exhibited a purity of 71.4%, indicating effective polyhydroxybutyrate (PHB) isolation. Its molecular weight of 0.15 × 10⁶ g/mol aligns with typical PHB ranges, suggesting its suitability for various applications. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed compatibility with commercial PHB. Thermal degradation profiles showed slightly lower stability compared to commercial PHB, with a 10% mass loss at 243.21 °C and a maximum degradation temperature of 262.12 °C. Despite these minor differences, HC presents a promising, greener method for PHA recovery, offering potential applications in sustainable industries.

This paper demonstrates an accurate and efficient methodology for fermentation contamination detection and reduction using two machine learning (ML) methods, including one-class support vector machine and autoencoders. We also optimize as many hyperparameters as possible prior to the training of the ML models to improve the model accuracy and efficiency, and choose a Python platform called Optuna, to enable the parallel execution of hyperparameter optimization (HPO). We recommend using Bayesian optimization with hyperband algorithm to carry out HPO. Results show that we can predict contaminated fermentation batches with recall up to 1.0 without sacrificing the precision and specificity of non-contaminated batches, which read up to 0.96 and 0.99, respectively. One-class support vector machine outperforms autoencoders in terms of precision and specificity even though they both achieve an outstanding recall of 1.0. These models demonstrate high accuracy in detecting contamination without requiring labeled contaminated data and are suitable for integration into real-time fermentation monitoring systems with minimal latency and retraining needs. In addition, we benchmark our ML methods against a traditional threshold-based contamination detection approach (mean $\pm$ 3 $\sigma$ rule) to quantify the added value of using data-driven models. Finally, we identify important independent variables contributing to the contaminated batches and give recommendations on how to regulate them to reduce the likelihood of contamination.

The slow growth rate of anaerobic ammonium oxidation (anammox) bacteria and susceptibility of anammox sludge to washout pose significant challenges for the successful start-up and stable operation of the anammox process. Granulation may resolve this issue. This study investigated the effects of biotic and abiotic particle addition on the start-up and operation of anammox reactor by inoculating seed sludge with suspended, granular, magnesium ammonium phosphate (MAP) coupled anammox sludge, and pure MAP precipitates, aiming to promote granulation and preserve anammox functionality. The results showed that the start-up period of the reactor was consistent approximately 55 days, irrespective of inoculation type. Notably, the addition of anammox sludge and MAP precipitates did not notably expedite the start-up process. However, incorporating of biotic and abiotic particle additions significantly enhanced the nitrogen removal rate per unit volume of sludge (p < 0.05), achieving 2.20-2.62 kg N m⁻³ d⁻¹. In contrast, the control group and the group inoculated with suspended anammox sludge achieved only 1.32 and 1.38 kg N m⁻³ d⁻¹, respectively. Furthermore, particle addition stimulated the formation of high-density, larger-sized granular sludge, particularly when anammox-MAP and pure MAP particles were introduced. MAP may offer adsorption sites for bacterial retention and accelerate granulation, but it was ineffective for reactor start-up, which mainly involved the initial enrichment and activity manifestation of anammox bacteria. Although the experimental group with suspended anammox sludge exhibited comparable anammox activity, its stability deteriorated over time due to the washout of low-density sludge. Anammox bacteria was enriched in both biotic and abiotic particle addition groups. MAP contributed to a higher abundance of anammox bacteria and a shift in the dominant genus from Candidatus Brocadia to Candidatus Kuenenia, likely attributable to Candidatus Kuenenia's superior substrate affinity. Collectively, these findings provide a scalable approach to improving anammox reactor efficiency in wastewater treatment plants.

Plants serve as a rich source of bioactive agents and coupling them with carriers using nanotechnology has recently become an effective therapeutic approach in pharmacognosy. Metal oxides, especially copper oxide (CuO), have been employed in synthesizing nanoparticles due to their efficient reducing properties. The purpose of this work was to examine the physicochemical, antioxidant, antibacterial, anticancer, and wound healing abilities of copper oxide nanoparticles (CuONPs) synthesized using Plumeria rubra leaf extract. FTIR, XRD, FESEM, EDX, AFM, and UV-vis spectroscopy were used to confirm the formation of CuONPs, and the results showed that they were spherical in shape and 35 nm in size. DPPH and nitric oxide antioxidant assays revealed that they possess effective free radical scavenging ability. CuONPs showed bactericidal activity against human pathogenic bacteria. The anticancer effect of CuONPs was assessed on the Neuro-2a (N2a) neuroblastoma cells. Both P. rubra leaf extract and CuONPs exhibited dose-dependent cytotoxicity with morphological distortions and apoptosis, along with a loss of membrane integrity. In vivo analysis of CuONPs for their wound healing ability in Wistar albino rats showed a better wound closure percentage compared to that of the control animals. Based on our findings, CuONPs may be applied as a potential therapeutic agent in developing treatments for a spectrum of various diseases.

The addition of zero-valent iron (ZVI) to the anaerobic digestion of food and kitchen waste (FKW) can significantly improve methane production efficiency. However, the impact of nano ZVI (nZVI) addition during both acidification and methanogenic phases of the two-phase anaerobic digestion of FKW remains unclear. This study investigated the effect of different nZVI particle sizes (50, 100, and 300 nm) introduced during the acidification phase on the overall performance of two-phase anaerobic digestion. The results revealed that nZVI improved the performance of the acidification phase. Particularly, 50 nm nZVI increased protein concentrations, likely owing to its toxicity, which caused microbial cell damage. The addition of 300 nm nZVI led to higher concentrations of soluble chemical oxygen demand (SCOD) and total volatile fatty acids (TVFAs), reaching 40,302.45 and 10,375.00 mg/L, respectively. In the methanogenic phase, 300 nm nZVI achieved the highest methane production, reaching 799.78 mL/g VS, which was enhanced by the optimal concentrations of TVFAs and Fe²⁺. Moreover, the addition of 300 nm nZVI enriched Bifidobacterium (32.74%) and Clostridium sensu stricto 1 (37.57%), both of which promoted TVFA generation, increased Methanobacterium abundance, and facilitated rapid methane production. Furthermore, 300 nm nZVI enhanced key metabolic pathways, such as transport, catabolism, and amino acid metabolism, thereby increasing methane production in the anaerobic digestion system.

The quest for solutions to infectious diseases and life-debilitating disease states has been ongoing for centuries now. Natural products researches have revealed bioactive compounds of plant and microbial origin that offer solutions to health conditions but with poor yield. This study reports yield improvement of a novel macroidin bacteriocin through robust comparative process optimization involving statistical and machine learning approaches. Response surface methodology (RSM), artificial neural network (ANN), and extreme gradient boosting (XGBoost) models showed adequate fitting capabilities considering statistical indices and performance errors as: RSM (R² = 0.9389; MSE = 0.3877), ANN (R² = 0.9727; MSE = 0.1379) and XGBoost (R² = 0.8758; MSE = 0.6272). The ANN model, with superior prediction results, was further optimized by evolutionary (genetic algorithm-GA) and swarm (particle swarm optimization) intelligence techniques which increased macroidin concentration by 2.38-fold and 2.2-fold, respectively. ANN's superior parameter generalization and remarkable validation accuracy by GA at 23.1 °C, pH 8.89, 0.5 vvm aeration, and 248.6 rpm agitation selected the ANN-GA model for bioreactor production. The scale-up study revealed a volumetric oxygen transfer coefficient of 33.95 h^-1 at 250 rpm and 0.5 vvm, at which a macroidin yield, Y_p/x of 0.93 g g^-1 and productivity of 2.00 g L^-1 h^-1 were achieved. Evaluated pharmaco-clinical potentials of macroidin revealed significant (p < 0.05) anti-proliferative effects against HepG2 and MCF-7 cell lines and bactericidal and antibiofilm activities against ESKAPE pathogens. The bactericidal action was revealed to proceed through membrane permeability, electrolyte, and ATP depletion, to cell lysis.

Polysaccharide has been widely used in the fields of industry, agriculture, food and medicine because of its excellent physicochemical properties and bioactivities. Compared to plant and animal polysaccharides, microbial exopolysaccharide has advantages of occupying less cultivated land, short fermentation period, controllable fermentation process and not restricted by seasons. However, due to the deterioration of global climates and outbreak of conflicts, food crisis has become more and more serious. Therefore, searching alternative substrates for microbial exopolysaccharide production has attracted worldwide attention, waste materials might be an ideal substitute due to its high-content nutrients. Present work discussed and reviewed the production of microbial exopolysaccharide from molasses, cheese whey, lignocellulosic biomass, fruit pomace and/or husk, crude glycerol and kitchen waste. It was found that commercial grade exopolysaccharides were mainly produced from waste materials via submerged fermentation, and pretreatment of waste materials is a commonly used strategy. Although industrial production of microbial exopolysaccharides with waste materials as substrate has not been reported, we hoped that this work could not only provide contribution for efficient utilization of waste materials, but also help for alleviating global food crises.

The present study investigates the influence of polyethylene glycol (PEG) and glutaraldehyde (GA) on the synthesis and enzymatic activity of lipase hybrid nanoflowers. The effect of lipase concentration on hybrid nanoflower formation was first assessed, revealing that the optimum lipase concentration was 0.2 mg/mL. At this concentration, the encapsulation of lipase within the hybrid nanoflowers reached its maximum efficiency. Further, the effects of PEG and GA concentrations, as well as pH, on the enzymatic activity of the nanoflowers were evaluated. The results demonstrated that 2% (v/v) PEG and 3% (v/v) GA were the most effective concentrations, with the highest activity observed at pH 8. Comparative studies showed that GA-treated lipase hybrid nanoflowers exhibited a remarkable 160% increase in enzymatic activity over the free lipase, outperforming PEG in terms of catalytic performance. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy analyses confirmed that both PEG and GA treatments altered the morphology and structural characteristics of the hybrid nanoflowers, with GA inducing more pronounced changes. Despite these morphological alterations, the enzymatic activity was significantly enhanced, particularly in the GA-treated hybrid nanoflowers. In conclusion, this study highlights the superior performance of glutaraldehyde as an enhancer for the production of highly active lipase hybrid nanoflowers, offering promising applications in biocatalysis and enzyme immobilization.

Dark anoxic incubation has been identified as a low-cost method to facilitate the mechanical rupture of microalgae such as Nannochloropsis via autolysis-induced cell wall thinning. During this process, concentrated slurries of cells are incubated in the dark at an elevated temperature, to deprive them of light and oxygen. This work analyzed the integrity of proteins and lipids during dark anoxic incubation and investigated the cellular responses of Nannochloropsis through an in-depth proteomic analysis. Proteomic analysis identified enzymes associated with cellulose hydrolysis and glycolytic and fermentative pathways that are presumably activated to produce energy in the absence of light and oxygen. Progressive biochemical degradation was observed during 48 h of incubation, including the proteolysis and leakage of proteins, and the lipolysis and subsequent peroxidation of lipids. This provides further evidence of autolytic processes occurring during prolonged incubation, which can be attributed to uncontrolled action of intracellular proteases and lipases. Importantly, the resultant formation of peptides and free fatty acids will affect their use in food and fuel applications. It is therefore important to optimise the incubation time and parameters to achieve cell weakening while minimising the unnecessary degradation of biomacromolecules.