Engineering in Life Sciences最新文献

Angiogenesis is a vital step in tissue regeneration. Hence, the current study aimed to prepare oxidized dextran (Odex)/collagen (Col)-hydrogels with laminin (LMN), as an angiogenic extracellular matrix (ECM) component, for promoting human umbilical vein endothelial cell (HUVEC) proliferation and function. Odex/Col scaffolds were constructed at various concentrations and temperatures. Using oscillatory rheometry, scanning electron microscopy (SEM), and cell viability testing, the scaffolds were characterized, and then HUVEC proliferation and function was compared with or without LMN. The gelation time could be modified by altering the Odex/Col mass ratio as well as the temperature. SEM showed that Odex/Col hydrogels had a more regular three-dimensional (3D) porous structure than the Col hydrogels. Moreover, HUVECs grew faster in the Col scaffold (12 mg/mL), whereas the Odex (30 mg/mL)/Col (6 mg/mL) scaffold exhibited the lowest apoptosis index. Furthermore, the expression level of vascular endothelial growth factor (VEGF) mRNA in the group without LMN was higher than that with LMN, and the Odex (30 mg/mL)/Col (6 mg/mL) scaffold without LMN had the highest VEGF protein secretion, allowing the cells to survive and function effectively. Odex/Col scaffolds, with or without LMN, are proposed as a tissue engineering construct to improve HUVEC survival and function for angiogenesis.

Non-alcoholic fatty liver disease (NAFLD) represents a growing global health concern that can lead to liver disease and cancer. It is characterized by an excessive accumulation of fat in the liver, unrelated to excessive alcohol consumption. Studies indicate that the gut microbiota-host crosstalk may play a causal role in NAFLD pathogenesis, with epigenetic modification serving as a key mechanism for regulating this interaction. In this review, we explore how the interplay between gut microbiota and the host epigenome impacts the development of NAFLD. Specifically, we discuss how gut microbiota-derived factors, such as lipopolysaccharides (LPS) and short-chain fatty acids (SCFAs), can modulate the DNA methylation and histone acetylation of genes associated with NAFLD, subsequently affecting lipid metabolism and immune homeostasis. Although the current literature suggests a link between gut microbiota and NAFLD development, our understanding of the molecular mechanisms and signaling pathways underlying this crosstalk remains limited. Therefore, more comprehensive epigenomic and multi-omic studies, including broader clinical and animal experiments, are needed to further explore the mechanisms linking the gut microbiota to NAFLD-associated genes. These studies are anticipated to improve microbial markers based on epigenetic strategies and provide novel insights into the pathogenesis of NAFLD, ultimately addressing a significant unmet clinical need.

Mine wastewater often contains dissolved metals at concentrations too low to be economically extracted by existing technologies, yet too high for environmental discharge. The most common treatment is chemical precipitation of the dissolved metals using limestone and subsequent disposal of the sludge in tailing impoundments. While it is a cost-effective solution to meet regulatory standards, it represents a lost opportunity. In this study, we engineered Escherichia coli to overexpress its native NikABCDE transporter and a heterologous metallothionein to capture nickel at concentrations in local effluent streams. We found the engineered strain had a 7-fold improvement in the bioaccumulation performance for nickel compared to controls, but also observed a drastic decrease in cell viability due to metabolic burden or inducer (IPTG) toxicity. Growth kinetic analysis revealed the IPTG concentrations used based on past studies lead to growth inhibition, thus delineating future avenues for optimization of the engineered strain and its growth conditions to perform in more complex environments.

Viable cell concentration (VCC) is an essential parameter that is required to support the efficient cultivation of mammalian cells. Although commonly determined using at-line or off-line analytics, in-line capacitance measurements represent a suitable alternative method for the determination of VCC. In addition, these latter efforts are complimentary with the Food and Drug Administration's initiative for process analytical technologies (PATs). However, current applications for online determination of the VCC often rely on single frequency measurements and corresponding linear regression models. It has been reported that this may be insufficient for application at all stages of a mammalian cell culture processes due to changes in multiple cell parameters over time. Alternatively, dielectric spectroscopy, measuring capacitance at multiple frequencies, in combination with multivariate mathematical models, has proven to be more robust. However, this has only been applied for retrospective data analysis. Here, we present the implementation of an O-PLS model for the online processing of multifrequency capacitance signals and the on-the-fly integration of the models’ VCC results into a supervisory control and data acquisition (SCADA) system commonly used for cultivation observation and control. This system was evaluated using a Chinese hamster ovary (CHO) cell perfusion process.

Since 2008, European and German legislative initiatives for climate protection and reduced dependency on fossil resources led to the introduction of biofuels as CO₂-reduced alternatives in the heating oil sector. In the case of biodiesel, customers were confronted with accelerated microbial contaminations during storage. Since then, other fuel alternatives, like hydrogenated vegetable oils (HVOs), gas-to-liquid (GtL) products, or oxymethylene ether (OME) have been developed. In this study, we use online monitoring of microbial CO₂ production and the simulation of onset of microbial contamination to investigate the contamination potential of fuel alternatives during storage. As references, fossil heating oil of German refineries are used. Biodiesel blends with fossil heating oils confirmed the promotion of microbial activity. In stark contrast, OMEs have an antimicrobial effect. The paraffinic Fischer–Tropsch products and biogenic hydrogenation products demonstrate to be at least as resistant to microbial contamination as fossil heating oils despite allowing a diversity of representative microbes. Through mass spectrometry, elemental analysis, and microbial sequencing, we can discuss fuel properties that affect microbial contaminations. In summary, novel, non-fossil heating oils show clear differences in microbial resistance during long-term storage. Designing blends with an intrinsic resistance against microbial contamination and hence reduced activity might be an option.

Adherent cells, mammalian or human, are ubiquitous for production of viral vaccines, in gene therapy and in immuno-oncology. The development of a cell-expansion process with adherent cells is challenging as scale-up requires the expansion of the cell culture surface. Microcarrier (MC)-based cultures are still predominate. However, the development of MC processes from scratch possesses particular challenges due to their complexity. A novel approach for the reduction of development times and costs of cell propagation processes is the combination of mathematical process models with statistical optimization methods, called model-assisted Design of Experiments (mDoE). In this study, an mDoE workflow was evaluated successfully for the design of a MC-based expansion process of adherent L929 cells at a very early stage of development with limited prior knowledge. At the start, the analytical methods and the screening of appropriate MCs were evaluated. Then, cause-effect relationships (e.g., cell growth related to medium conditions) were worked out, and a mathematical process model was set-up and adapted to experimental data for modeling purposes. The model was subsequently used in mDoE to identify optimized process conditions, which were proven experimentally. An eight-fold increase in cell yield was achieved basically by reducing the initial MC concentration.

The biological treatment process is responsible for removing organic and inorganic matter in wastewater. This process relies heavily on microorganisms to successfully remove organic and inorganic matter. The aim of the study was to model biomass growth in the biological treatment process. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to model biomass growth. Three metrics: coefficient of determination (R²), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the model. Sensitivity analysis was applied to confirm variables that have a strong influence on biomass growth. The results of the study showed that MLP ANN algorithm was able to model biomass growth successfully. R² values were 0.844, 0.853, and 0.823 during training, validation, and testing phases, respectively. RMSE values were 0.7476, 1.1641, and 0.7798 during training, validation, and testing phases respectively. MSE values were 0.5589, 1.3551, and 0.6081 during training, validation, and testing phases, respectively. Sensitivity analysis results showed that temperature (47.2%) and dissolved oxygen (DO) concentration (40.2%) were the biggest drivers of biomass growth. Aeration period (4.3%), chemical oxygen demand (COD) concentration (3.2%), and oxygen uptake rate (OUR) (5.1%) contributed minimally. The biomass growth model can be applied at different wastewater treatment plants by different plant managers/operators in order to achieve optimum biomass growth. The optimum biomass growth will improve the removal of organic and inorganic matter in the biological treatment process.