BioTech

A study of bacterial xylanases from Streptomyces prunicolor, Streptomyces carpinensis, and Streptomyces venezuelae was conducted. The xylanase-encoding genes were cloned from bacterial genomes. Recombinant producers based on E. coli M15(Rep4) and the pQE-30 vector were obtained, and the expression and purification of the recombinant proteins were carried out. Electrophoretically homogeneous preparations of four xylanases from the GH10 and GH11 families were obtained. The xylanases had a near-neutral pH optimum and moderate thermal stability (the enzymes were stable at 70 °C). The xylanases were more stable over a pH range of 5.0 to 8.0. The properties of the xylanases obtained correspond to the properties of most xylanase-producing bacteria of the Streptomyces genus described in the literature. Xylanases from the GH10 family of S. carpinensis form xylose, xylobiose and xylotetraose as main products of xylan hydrolysis. The GH10 xylanase from S. venezuelae hydrolyzes xylan into xylose, xylobiose, xylotriose, xylotetraose and xylopentaose. The main products of xylan hydrolysis by GH11 xylanase from S. prunicolor are xylobiose, xylopentaose and a trace amount of xylose. All four xylanases effectively saccharify cereals, indicating the biotechnological potential of these enzymes.

Small extracellular vesicles (sEVs), commonly referred to as exosomes, are nanoscale vesicles that mediate intercellular communication and represent promising biotechnological platforms for disease diagnosis, therapeutic intervention, and drug delivery. sEVs derived from plants, mesenchymal stem cells, tumor cells, and immune cells display pronounced source-dependent heterogeneity shaped by parental cell lineage, differentiation status, and the local microenvironment. Such heterogeneity influences not only their biological properties, including physicochemical characteristics, molecular cargo profiles, and immunomodulatory functions, but also their manufacturing characteristics, in vivo tropism, and translational potential as biotherapeutics. Nevertheless, a comprehensive evaluation framework from a medical biotechnology perspective remains insufficiently established. In this review, the core biological features of multi-source sEVs are first outlined to establish a foundation for subsequent analysis. We then examine their biomedical applications and discuss biotechnological bottlenecks, including isolation and purification workflows, quality-control metrics, batch-to-batch variability, scalable biomanufacturing, and biosafety assessment. Particular attention is also given to the incompletely characterized regulatory networks of immune-cell-derived sEVs. Furthermore, we discuss how multi-omics profiling, standardized production protocols, and precision-engineering strategies may facilitate the functional optimization of source-specific sEVs. Collectively, this review provides an integrated medical biotechnology framework for evaluating multi-source sEVs and highlights practical considerations for accelerating the bench-to-bedside translation of sEV-based biotherapeutics.

An artificial neural network (ANN)-based digital twin feed controller, aiming to optimise bioprocess performance, was implemented in fed-batch bioprocesses of Lactobacillus rhamnosus LRH30 for the production of biomass. The online data from several fed-batch bioprocesses in dairy-based cultivations with L. rhamnosus were utilised to develop an ANN that predicts the biomass and growth rate of L. rhamnosus in the process. This growth rate estimator was first validated through unit testing before being applied in model predictive control to select the best control action to drive feed addition to the process. The controller was implemented in fed-batch bioprocesses and the growth rate was estimated in real time, leading to the highest cell dry weight biomass concentrations obtained for L. rhamnosus LRH30 of 36.23 g/L in this study, with growth-rate overshoot and increased feed addition also contributing to the biomass accumulation despite imperfect setpoint tracking. The dose-dependent effect of L. rhamnosus LRH30 samples on cytokine secretion from murine macrophages was further explored, and an anti-inflammatory effect was found at a dosage of 10 mg/mL of bacterial cell dry weight. These experiments demonstrate the first steps in the implementation phase that will ultimately lead to a better controlled bioprocess with higher yields of L. rhamnosus biomass. Future research will focus on the continuous development of the ANN through the incorporation of more datasets, while simultaneously exploring the functional potential of L. rhamnosus LRH30.