Biotechnology and Bioengineering最新文献

Purification of recombinantly produced biopharmaceuticals involves removal of host cell material, such as host cell proteins (HCPs). For lysates of the common expression host Escherichia coli (E. coli) over 1500 unique proteins can be identified. Currently, understanding the behavior of individual HCPs for purification operations, such as preparative chromatography, is limited. Therefore, we aim to elucidate the elution behavior of individual HCPs from E. coli strain BLR(DE3) during chromatography. Understanding this complex mixture and knowing the chromatographic behavior of each individual HCP improves the ability for rational purification process design. Specifically, linear gradient experiments were performed using ion exchange (IEX) and hydrophobic interaction chromatography, coupled with mass spectrometry-based proteomics to map the retention of individual HCPs. We combined knowledge of protein location, function, and interaction available in literature to identify trends in elution behavior. Additionally, quantitative structure–property relationship models were trained relating the protein 3D structure to elution behavior during IEX. For the complete data set a model with a cross-validated R² of 0.55 was constructed, that could be improved to a R² of 0.70 by considering only monomeric proteins. Ultimately this study is a significant step toward greater process understanding.

Sucrose is a commonly utilized nutritive sweetener in food and beverages due to its abundance in nature and low production costs. However, excessive intake of sucrose increases the risk of metabolic disorders, including diabetes and obesity. Therefore, there is a growing demand for the development of nonnutritive sweeteners with almost no calories. d-Allulose is an ultra-low-calorie, rare six-carbon monosaccharide with high sweetness, making it an ideal alternative to sucrose. In this study, we developed a cell factory for d-allulose production from sucrose using Escherichia coli JM109 (DE3) as a chassis host. The genes cscA, cscB, cscK, alsE, and a6PP were co-expressed for the construction of the synthesis pathway. Then, the introduction of ptsG-F and knockout of ptsG, fruA, ptsI, and ptsH to reprogram sugar transport pathways resulted in an improvement in substrate utilization. Next, the carbon fluxes of the Embden-Meyerhof-Parnas and the pentose phosphate pathways were regulated by the inactivation of pfkA and zwf, achieving an increase in d-allulose titer and yield of 154.2% and 161.1%, respectively. Finally, scaled-up fermentation was performed in a 5 L fermenter. The titer of d-allulose reached 11.15 g/L, with a yield of 0.208 g/g on sucrose.

The cover image is based on the Article Tailoring polishing steps for effective removal of polysorbate-degrading host cell proteins in antibody purification by Melanie Maier et al., https://doi.org/10.1002/bit.28767.

Enantiopure 1,2-diols are widely used in the production of pharmaceuticals, cosmetics, and functional materials as essential building blocks or bioactive compounds. Nevertheless, developing a mild, efficient and environmentally friendly biocatalytic route for manufacturing enantiopure 1,2-diols from simple substrate remains a challenge. Here, we designed and realized a step-wise biocatalytic cascade to access chiral 1,2-diols starting from aromatic aldehyde and formaldehyde enabled by a newly mined benzaldehyde lyase from Sphingobium sp. combined with a pair of tailored-made short-chain dehydrogenase/reductase from Pseudomonas monteilii (PmSDR-MuR and PmSDR-MuS) capable of producing (R)- and (S)-1-phenylethane-1,2-diol with 99% ee. The planned biocatalytic cascade could synthesize a series of enantiopure 1,2-diols with a broad scope (16 samples), excellent conversions (94%–99%), and outstanding enantioselectivity (up to 99% ee), making it an effective technique for producing chiral 1,2-diols in a more environmentally friendly and sustainable manner.

The harvesting of microalgae is the main bottleneck of its large-scale biomass production, and seeking an efficient, green, and low-cost microalgae harvesting technology is one of the urgent problems to be solved. Microbubble air flotation has been proven to be an effective measure, but the mechanisms of microbubbles-algal cell attachment are still unclear. In this study, microbubble air flotation was used as a harvesting method for Microcystis cultured in agricultural wastewater. The process mechanism of microbubble air flotation harvesting microalgae in wastewater was fully revealed from three aspects (the design of bubble formation, the adhesion law, and the recovery rate of microalgae under different working conditions). The results show that the length of the release pipe is the main factor affecting the proportion of microbubbles with a particle size of less than 50 μm. In the process of adhesion, when the particle size of microbubbles is 0.6–1.7 times the size of Microcystis, the adhesion efficiency of microbubbles to Microcystis is the highest. Under the conditions of pressure 0.45 MPa, gas–liquid ratio 5%, and release pipe length 100 cm, the harvesting performance of Microcystis was the best. Microbubble air flotation has better harvesting performance (63.5%, collection rate) of Microcystis with higher density. By understanding the mechanism of microbubble flotation, the technical parameters of microbubble flotation for harvesting energy microalgae are optimized to provide support for the development of efficient and low-cost devices and equipment for collecting microalgae.

Lentiviral vectors are highly efficient gene delivery vehicles used extensively in the rapidly growing field of cell and gene therapy. Demand for efficient, large-scale, lentiviral vector bioprocessing is growing as more therapies reach late-stage clinical trials and are commercialized. However, despite substantial progress, several process inefficiencies remain. The unintended auto-transduction of viral vector-producing cells by newly synthesized lentiviral vector particles during manufacturing processes constitutes one such inefficiency which remains largely unaddressed. In this study, we determined that over 60% of functional lentiviral vector particles produced during an upstream production process were lost to auto-transduction, highlighting a major process inefficiency likely widespread within the industry. Auto-transduction of cells by particles pseudotyped with the widely used vesicular stomatitis virus G protein was inhibited via the adoption of a reduced extracellular pH during vector production, impairing the ability of the vector to interact with its target receptor. Employing a posttransfection pH shift to pH 6.7–6.8 resulted in a sevenfold reduction in vector genome integration events, arising from lentiviral vector-mediated transduction, within viral vector-producing cell populations and ultimately resulted in improved lentiviral vector production kinetics. The proposed strategy is scalable and cost-effective, providing an industrially relevant approach to improve lentiviral vector production efficiencies.

Pretreatment is crucial for effective enzymatic saccharification of lignocellulose such as sugarcane bagasse (SCB). In the present study, SCB was pretreated with five kinds of heterogeneous Fenton-like systems (HFSs), respectively, in which α-FeOOH, α-Fe₂O₃, Fe₃O₄, and FeS₂ worked as four traditional heterogeneous Fenton-like catalysts (HFCs), while FeVO₄ worked as a novel HFC. The enzymatic reducing sugar conversion rate was then compared among SCB after different heterogeneous Fenton-like pretreatments (HFPs), and the optimal HFS and pretreatment conditions were determined. The mechanism underlying the difference in saccharification efficiency was elucidated by analyzing the composition and morphology of SCB. Moreover, the ion dissolution characteristics, variation of pH and Eh values, H₂O₂ and hydroxyl radical (·OH) concentration of FeVO₄ and α-Fe₂O₃ HFSs were compared. The results revealed that the sugar conversion rate of SCB pretreated with FeVO₄ HFS reached up to 58.25%, which was obviously higher than that under other HFPs. In addition, the surface morphology and composition of the pretreated SCB with FeVO₄ HFS were more conducive to enzymatic saccharification. Compared with α-Fe₂O₃, FeVO₄ could utilize H₂O₂ more efficiently, since the dissolved Fe³⁺ and V⁵⁺ can both react with H₂O₂ to produce more ·OH, resulting in a higher hemicellulose and lignin removal rate and a higher enzymatic sugar conversion rate. It can be concluded that FeVO₄ HFP is a promising approach for lignocellulose pretreatment.

Cryopreservation presents a critical challenge due to cryo-damage, such as crystallization and osmotic imbalances that compromise the integrity of biological tissues and cells. In contrast, various organisms in nature exhibit remarkable freezing tolerance, leveraging complex molecular mechanisms to survive extreme cold. This review explores the adaptive strategies of freeze-tolerant species, including the regulation of specific genes, proteins, and metabolic pathways, to enhance survival in low-temperature environments. We then discuss recent advancements in cryopreservation technologies that aim to mimic these natural phenomena to preserve cellular and tissue integrity. Special focus is given to the roles of glucose metabolism, microRNA expression, and cryoprotective protein modulation in improving cryopreservation outcomes. The insights gained from studying natural antifreeze mechanisms offer promising directions for advancing cryopreservation techniques, with potential applications in medical, agricultural, and conservation fields. Future research should aim to further elucidate these molecular mechanisms to develop more effective and reliable cryopreservation methods.

Organism-specific genome-scale metabolic models (GSMMs) can unveil molecular mechanisms within cells and are commonly used in diverse applications, from synthetic biology, biotechnology, and systems biology to metabolic engineering. There are limited studies incorporating time-series transcriptomics in GSMM simulations. Yeast is an easy-to-manipulate model organism for tumor research. Here, a novel approach (TS-GSMM) was proposed to integrate time-series transcriptomics with GSMMs to narrow down the feasible solution space of all possible flux distributions and attain time-series flux samples. The flux samples were clustered using machine learning techniques, and the clusters' functional analysis was performed using reaction set enrichment analysis. A time series transcriptomics response of Yeast cells to a chemotherapeutic reagent—doxorubicin—was mapped onto a Yeast GSMM. Eleven flux clusters were obtained with our approach, and pathway dynamics were displayed. Induction of fluxes related to bicarbonate formation and transport, ergosterol and spermidine transport, and ATP production were captured. Integrating time-series transcriptomics data with GSMMs is a promising approach to reveal pathway dynamics without any kinetic modeling and detects pathways that cannot be identified through transcriptomics-only analysis. The codes are available at https://github.com/karabekmez/TS-GSMM.