Biotechnology and Bioengineering

The suspension culture of pluripotent stem (PS) cells in stirred bioreactors poses a delicate balance between maintaining homogeneous cell dispersion and avoiding excessive shear stress that can compromise cell viability and pluripotency. In this study, we used computational fluid dynamics (CFD) coupled with a discrete particle method (DPM) to simulate iPS cell behavior in a 5 mL delta-impeller stirred tank. Our analysis revealed that upward flow at the tank bottom and downward flow at the top are critical for maintaining a stable suspension. To optimize the stirring protocol, we applied Bayesian optimization to identify a time-dependent stirring schedule that begins with a high-speed phase for resuspension, followed by a low-speed phase for sustained suspension with minimal hydrodynamic stress. The optimized schedule demonstrated improved suspension ratio and reduced slip velocity, indicating lower mechanical stress on cells. These findings provide engineering insights into scalable bioreactor operation, contributing to the design of robust iPS cell manufacturing systems.

Human pluripotent stem cells (hPSCs) hold significant promise for regenerative medicine, yet optimizing their expansion in three-dimensional bioreactor systems remains challenging due to complex interactions between mechanical forces, metabolic constraints, and aggregate formation dynamics. This study developed and validated a mechanistic mathematical model to predict hPSC proliferation dynamics in vertical-wheel bioreactor (VWBR) systems, incorporating the effects of shear stress and energy dissipation rate (EDR) on cell growth and aggregate dynamics. Seven model variants employing different kinetic formulations for shear stress and energy dissipation rate effects were systematically evaluated through model selection, identifiability analyses, and experimental validation. Experimental data from six bioreactor conditions varying in initial cell density (2 x 104-15 x 104 cells/mL), agitation rate (30-60 RPM), and working volume (100-500 mL) were used for model calibration and selection. Bayesian Information Criterion analysis identified a model combining Michaelis-Menten kinetics for shear stress inhibition with a EDR-mediated aggregate detachment formulation as the best-performing variant, achieving a Mean Relative Prediction Error of 13.97%, comparable to the experimental variability of 16.29%. Independent validation experiments using leave-out data gathered under different media exchange schedules confirmed model accuracy with prediction errors below 14%, consistent with observed experimental variability around 12%. The validated model was used to optimize the media exchange protocol, leading to a 37.5% reduction in media consumption with only a 13.5% reduction in final cell yield, demonstrating its utility for prospective, quantitative bioprocess design in VWBR systems.

We describe a cost-effective Escherichia coli (E. coli)-based platform for producing endotoxin-free cytokines. As a proof of concept, we applied this protocol to purify four representative human and mouse cytokines - mouse leukemia inhibitory factor (mLIF), human interleukin-2 (hIL-2), and human and mouse interleukin-33 (hIL-33 and mIL-33) - and demonstrated their bioactivity to be equivalent to commercial counterparts for direct use in stem cell culture and immune cell activation, both in vitro and in vivo. Reagent costs for producing these proteins are approximately 5%-10% of commercial list prices. This platform is readily adaptable to other costly cytokines and growth factors, providing a scalable and affordable approach to accelerate research in cell biology, tissue engineering, and biomanufacturing.

BackgroundThe use of autologous or allogeneic cell therapies has now entered to the clinical practice in several fields of medicine, especially in oncology and hematology. From this regard, 2D-cell manufacturing is complex and costly and bioreactors have attracted major interest for efficient and cost-effective mass production of cells. Bioreactors have several advantages such as homogeneous repartition of nutrients and gas, control of all culture parameters and increased yield. However, the important shear stress generated by those bioreactors is an important disadvantage as it can affect cell survival or cell quality. This important shear stress is the result of the mixing method using either blades (used in stirred-tanked bioreactors) or gas bubbles (used in airlift bioreactors). Another downside of the use of bioreactors is the difficulty to scale-up. As the volume increases, the shear stress generated by blades radically increases leading to cell death and a decrease of cell quality. DescriptionIn this study, we describe a bioreactor developed using a different mixing method effectively reducing the shear stress and facilitating scale-up. This bladeless method uses an inclination of the bioreactor as well as rotation to mix fluids in a container. Here we described different steps that led to the adaptation of this bioreactor, initially developed for fragile microalgae culture, for mammalian cell culture amplification. The bioreactor was tested to amplify a natural killer (NK) cell line NK92 which is an IL-2 dependent cell line used in clinical trials for cancer therapy. We have tested the influence of 1-The number of cells seeded; 2-The influence of the rotation speed on cell growth and viability; 3-The influence of the bioreactor angle on the above parameters; 4-The duration of the culture. ResultsCells were initially seeded at 2.5.105 / ml in a volume of 380 ml. According to the rotation speed of 15, 30, 45 and 60 rpm, we have observed an increase of cell numbers at day 3 (3-fold), day 5 (7-fold) and day 7 (10-fold) compared to seeding, the best expansion being obtained at day 7 with a rotation speed of 45 rpm. The optimal angle of rotation was found to be 3 degree, with an optimal amplification at day 7 versus day 3 (p < 0.01). The viability was also found to be optimal in the latter condition. ConclusionsThese preliminary results demonstrate that NK92 cells could be amplified using this bioreactor. In the best tested condition, neither cell viability nor cell growth was impacted. These results strongly suggest the potential use of this device in future clinically applicable conditions.

The optimization and control of bioprocesses require robust in silico models that can accurately capture the complex and dynamic behavior of living cells. While hybrid models that combine machine learning with mechanistic equations have emerged as a powerful tools, they often require relatively large datasets and might yield inconsistent predictions that violate the stoichiometry of metabolism. In this study, we introduce FBA-Hyb, a multi-scale hybrid modeling framework that tightly integrates genome-scale metabolic networks via flux balance analysis (FBA) into its architecture. In our FBA-Hyb framework, artificial neural networks predict key FBA inputs (substrate uptake rates and cellular objectives) while a surrogate FBA module translates them into the metabolic fluxes that govern the bioprocess. A key novelty is that the FBA optimization step is replaced by a surrogate generated with symbolic regression, which encapsulates the FBA model into a compact analytical expression. This allows easy backpropagation through the integration of the neural controlled differential equationbased FBA-Hyb bioprocess model. We validated FBA-Hyb against a standard hybrid model (Std-Hyb) using two Escherichia coli fedbatch case studies. In the first study, FBA-Hyb achieved a 42 % average improvement in predictive accuracy (R2) during a leave-one-process-out cross validation. Crucially, FBA-Hyb maintains strict stoichiometric feasibility even during extrapolation. Meanwhile, an alternative approach based on standard architectures leads to stoichiometrically inconsistent solutions in 22 % of the cases analyzed. In the second case study, we demonstrate how FBA-Hyb effectively simulates unmeasured chemical species and discovers a metabolic shift in sulfate-limited regimes during bioprocessing. By providing a modular, biologically consistent, and computationally efficient architecture, FBA-Hyb offers a robust foundation for the next generation of bioprocess models and sustainable process optimization. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/720062v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@16f011eorg.highwire.dtl.DTLVardef@b25b5borg.highwire.dtl.DTLVardef@18bd178org.highwire.dtl.DTLVardef@65274e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIFBA-Hyb integrates flux balance analysis (FBA) into hybrid bioprocess models. C_LIO_LISymbolic regression discovers a simple closed-form FBA surrogate model. C_LIO_LIThe FBA surrogate ensures accurate reaction stoichiometry. C_LIO_LIA neural network predicting the FBA objective keeps the model flexible. C_LIO_LIFBA-Hyb has superior capabilities and accuracy compared to the current standard. C_LI

Recombinant adeno-associated viruses (rAAVs) have gained increasing importance in gene therapy due to their safe and precise gene delivery. However, certain indications require substantially higher vector doses, pushing manufacturing capacity and cost of goods (COG) to its limits. In this study, we present for the first time a continuous twin-column capture process (CaptureSMB) enabling direct purification of rAAV5 from unprocessed perfusion harvest without prior concentration or processing. This approach differs fundamentally from conventional batch workflows which typically mandate clarification and concentration before affinity capture and offers a novel process integration in viral vector manufacturing. A single-column batch capture process was developed first and subsequently compared to continuous CaptureSMB configurations. Optimized CaptureSMB operation achieved consistent yields over four cycles, with recoveries exceeding batch operation (+ 14.3%) with concomitant higher productivity (+ 11.4%) and reduced buffer consumption (- 79.2%). Critical quality attribute analysis showed lower host cell protein levels and lower residual DNA in early CaptureSMB cycles, while full capsid ratios, thermal stability and transduction efficiency of rAAV5 particles remained unaltered across cycles and process modes. These findings highlight that continuous twin-column CaptureSMB directly from perfusion harvest can not only improve yield and manufacturing efficiency but also maintain and in some respects enhance product quality. This novel strategy provides a promising route to address manufacturing capacity and cost challenges in rAAV gene therapy production.

Improving the reconstituted translation system is a key requirement for bottom-up synthetic biology. Here, we developed a two-step in vitro evolutionary method that can be used for improving translational proteins. In this method, two distinct conditions were sequentially applied while maintaining genotype-phenotype linkage in water-in-oil droplets. Using this method, we performed in vitro evolution of four translation factors, IleRS, PheRS, EF-G, and EF-Tu, and identified mutations that modestly enhanced translation activity in in vitro expression assays. One of the EF-G mutations (P610S) increased activity per protein approximately 2-fold for the recombinant protein purified from E. coli. This selection method is useful for improving translational proteins for bottom-up synthetic biology.

Extracellular vesicles (EVs) are mediators of intercellular communication, yet their impact on Chinese Hamster Ovary (CHO) cell physiology and bioprocess performance remains poorly understood. Here, we investigated whether small EVs (sEVs) and large EVs (LgEVs) that accumulate during fed-batch and perfusion cultures modulate CHO cell growth, metabolism, apoptosis, and monoclonal antibody (mAb) production. EVs isolated from early- and late-stage cultures were added to fresh CHO cultures grown with or without glutamine supplementation. Only LgEVs had a significant impact. Late-stage LgEVs markedly altered CHO-cell behavior, reducing cell proliferation, increasing apoptosis under glutamine-limited conditions, and substantially enhancing mAb productivity in a dose-dependent manner. Glutamine supplementation largely alleviated the growth-inhibitory and pro-apoptotic effects of LgEVs while preserving their positive impact on productivity, suggesting that glutamine decouples EV-mediated stress from productivity enhancement. Metabolic analyses revealed increased glucose consumption, a glutamine-dependent shift between glycine and alanine overflow metabolism, and remodeling of amino-acid utilization. Metabolic flux analysis further demonstrated enhanced glycolytic overflow and increased reliance on amino acid-supported anaplerosis. Conversely, selective removal of LgEVs from perfusion medium significantly improved cell expansion without reducing antibody production, supporting an inhibitory role for late-stage LgEVs. These LgEVs were enriched in let-7 family miRNAs and miR-21, consistent with RNAseq analyses demonstrating stress-associated enrichment of these miRNAs in CHO EVs and with functional studies showing that let-7a and miR-21reduce CHO-cell growth. Together, these observations suggest that selective miRNA loading contributes to the growth, metabolic, and productivity phenotypes elicited by late-stage LgEVs. Our findings identify LgEVs as endogenous regulators of CHO-cell physiology and potential targets for optimizing high-density fed-batch and perfusion biomanufacturing processes. HighlightsO_LIEndogenous late-stage Large Extracellular Vesicles (LgEVs) reduce CHO cell growth but boost specific mAb productivity. C_LIO_LIGlutamine supplementation rescues LgEV-mediated growth inhibition and apoptosis. C_LIO_LIMetabolic Flux Analysis (MFA) based on the dynamic behavior of amino acid and other metabolite and substrate concentrations reveals the pyruvate node as a metabolic bottleneck and the associated lactate overflow metabolism as resulting from LgEV exposure. C_LIO_LIStress-associated let-7 and miR-21 microRNAs are highly enriched on a per-EV basis in late-stage LgEVs. C_LIO_LISelective removal of LgEVs improves perfusion cell growth without impacting antibody titer. C_LI

Methanogenic archaea, such as Methanothermobacter marburgensis, represent a powerful biological platform for carbon capture and valorization, directly converting carbon dioxide (CO2) and molecular hydrogen (H2) into proteinogenic amino acids (AAs). In this study, we present a controlled and scalable strategy for tailoring AA production (biosynthesis and secretion) in continuous gas fermentation. By applying various Design of Experiments (DOE) techniques, we systematically identified and optimized key process parameters governing AA biosynthesis and shaping a targeted AA secretion profile. A hybrid modeling framework combining experimental data with scale-independent parameters derived from computational fluid dynamics (CFD) enabled robust performance prediction across bioreactor scales. This model-driven approach successfully translated the process from 120 mL glass bottles via 2 L to 150 L reactors, corresponding to a reaction-volume scale-up factor of 2000. These findings set the foundation for a robust and predictive platform for sustainable AA production, positioning archaea as a high-potential alternative in industrial biotechnology.

The rapid emergence of SARS-CoV-2 variants that evade neutralizing antibodies underscores the need for next-generation antiviral biologics that combine molecular precision with scalable, cost-effective manufacturing. Computationally designed miniproteins targeting the receptor-binding domain (RBD) of the spike protein offer a compelling alternative to monoclonal antibodies due to their small size, high thermal stability, and compatibility with microbial expression systems. Here we report the end-to-end development and cGMP production of IPD-52520, a de novo antiviral miniprotein, using an optimized E. coli platform. Two miniprotein candidates, a homotrimeric construct (Trimer is referred to as IPD-52520, 17 kDa) and a tandem fusion (Daisy is referred to as IPD-52521, 25 kDa), were evaluated in parallel through systematic optimization of strain selection, media composition, fed-batch fermentation, inclusion-body solubilization, refolding, and chromatographic purification. The Trimer was downselected as the lead molecule based on superior preclinical efficacy, favorable pharmacokinetic properties, and higher volumetric manufacturing yields. The optimized process delivers approximately 2 g/L of purified protein at greater than 90% purity. Scale-up from 5 L to 50 L under cGMP conditions demonstrated excellent batch-to-batch reproducibility across six independent batches, supporting nonclinical and Phase 1 clinical supply. Comprehensive biophysical characterization confirmed a well-folded, predominantly alpha-helical trimer (Tm = 73.4 {degrees}C; polydispersity = 1.005) with an intact primary structure and strong target-binding affinity (KD < 1 pM). Real-time stability studies indicate that the drug substance is stable at 2-8 {degrees}C for at least 12 months, with ongoing stability studies. These results demonstrate the feasibility of translating computationally designed antiviral miniproteins into manufacturable biologics and provide a platform applicable to rapid-response therapeutics against current and future pandemic threats.

Saccharomyces cerevisiae is an excellent microbial platform for sustainable production of next generation biofuels such as the branched chain higher alcohols (BCHAs) isobutanol and isopentanol. A cytosolic pathway for BCHA production is generated from expression of prokaryotic orthologs of branched-chain amino acid (BCAA) enzymes acetolactate synthase (ALS), mutant NADH-dependent ketol-acid reductoisomerase (KARIP2D1-A1), and dihydroxy-acid dehydratase (DHAD). The potential for this pathway has been hindered by the availability of iron-sulfur clusters, particularly the 2Fe-2S cluster, required for DHAD to function in the cytosol. ILV3, the endogenous yeast DHAD located in the mitochondria, can be deleted to create a valine auxotroph. In this study we use bioinformatics, heterologous gene library synthesis, and a valine complementation assay to find prokaryotic iron-sulfur cluster biosynthetic gene clusters (BGC) and accessory genes that aid DHAD function in the yeast cytosol. This work presents, to our knowledge, the first functional BGC that enhances the cytosolic activity of prokaryotic DHADs in S. cerevisiae. The SUF BGC from Bacillus subtilis combined with a ferritin-like protein (FTNB) from Escherichia coli and the Lactococcus lactis DHAD enhanced the production of BCHAs. Combined expression gave an average isobutanol titer of 412mg/L, 1.8-fold greater than L. lactis DHAD expressed alone. This work establishes a blueprint for better biofuel production by improving iron-sulfur cluster dependent enzyme activity in the yeast cytosol.

Prodigiosin is a red pigment produced by various bacteria, including Serratia marcescens. Despite its wide and promising range of biological activities, the large-scale production of prodigiosin is currently limited by its high cost and low yields. Here we propose and optimize an innovative, low-cost, peanut-based solid culture medium that enhances the yield of prodigiosin produced by Serratia marcescens. Colorimetric assays revealed that peanut significantly stimulates prodigiosin synthesis. Further HPLC-MS analysis allowed us to unambiguously identify prodigiosin and shows that our medium specifically improves the yield of prodigiosin. Overall, our innovative culture medium could help lower prodigiosin production costs and, ultimately, open new industrial applications.

Matrix-bound nanovesicles (MBVs) are a type of small extracellular vesicle (EV) embedded in the extracellular matrix (ECM) throughout the body. MBVs have been previously isolated from various tissues and in vitro-cultured cell sheets, demonstrating remarkable attributes in regenerative medicine. However, differences between MBVs and conditioned culture medium-derived EVs (liquid-EVs) have yet to be characterized, and the field currently lacks specific protein markers that can identify MBVs from other EV subtypes. Here, we isolate MBVs and liquid-EVs from bone marrow mesenchymal stem cell (MSC) sheets and define differences in size, protein, and zeta potential between these EVs. We show that there is a correlation between cell-driven ECM deposition and MBV and liquid-EV production. We also find that MBVs are smaller, contain less protein per particle, and possess lower zeta potential than liquid-EVs. Interestingly, MBVs also comprise a distinct tetraspanin profile compared to liquid-EVs, with MBVs containing more CD63 and little to no CD81. Finally, we define that CD63, LAMP1, Alix, ITG{beta}1, and GRP94 and their abundance, may be markers specifically used to identify MBVs from liquid-EVs. Our study paves the way for the characteristic differentiation between MBVs from liquid-EVs, elucidates their differences in biogenesis, and reveals a potential connection between EV and ECM production.

Acidithiobacillus ferrooxidans, a chemolithoautotrophic iron- and sulfur-oxidizing acidophile, is a key contributor to industrial-scale copper metal bioleaching. These cells naturally produce magnetosomes, and they may serve as an emerging platform for magnetosome bioproduction, as magnetotactic bacteria (MTB) are difficult to cultivate and to genetically modify. Here we manipulated the expression of the endogenous homologs to the magA and mamB genes in A. ferrooxidans, which are implicated in iron transport required for magnetosome synthesis. Modulation of mamB had no impact on cell behavior. Overexpression of magA increased magnetosome formation and magnetic responsiveness and theses effects were attenuated by CRISPRi knockdown of magA. The augmented magnetosome formation in the magA overexpression cells also led to enhanced bioleaching of pyrite, which is weakly paramagnetic, and this could be further enhanced by addition of an external magnetic field. These results confirm that magA plays a critical role in magnetosome formation in A. ferrooxidans and that magnetosome expression can be enhanced through genetic engineering. In addition, these results demonstrate the potential to improve metal sulfide bioleaching through the manipulation of genes involved in magnetosome formation. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/727969v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@593bd9org.highwire.dtl.DTLVardef@685e35org.highwire.dtl.DTLVardef@10a9corg.highwire.dtl.DTLVardef@5f89d1_HPS_FORMAT_FIGEXP M_FIG C_FIG

{beta}-galactosidases (BGs) are essential enzymes widely used in the food industry, particularly in the production of lactose-free products. Among them, the BG from Aspergillus oryzae is of industrial relevance due to its activity at acidic pH and moderate thermal tolerance. However, enhancing its catalytic performance remains a key challenge. Traditional enzyme engineering methods are time-consuming and resource-intensive, limiting their scalability. Recent advances in Artificial Intelligence (AI), particularly those based on Natural Language Processing, offer a promising alternative by enabling efficient exploration of protein sequence space and prediction of beneficial mutations. In this study, we introduce an ensemble-based, zero-shot Protein Language Model pipeline that reconciles predictions from six independent models (ESM2 and the five ESM1v variants) combined with a diversity-aware candidate selection strategy. Applied to the BG from A. oryzae, this approach identified beneficial mutations leading to novel enzyme variants with up to a four-fold increase in catalytic efficiency on oNPGal, a two-fold increase on lactose, and, independently, a T338I variant with markedly enhanced thermostability ({approx}80% residual activity after 24 h at 60 {degrees}C), all without requiring supervised fine-tuning on experimental fitness data. Our results demonstrate that consensus across an ensemble of PLMs can efficiently enrich beneficial substitutions in industrially relevant enzymes and substantially reduce the number of wet-lab candidates that need to be screened. Table of Contents graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/726739v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@18084f7org.highwire.dtl.DTLVardef@99a102org.highwire.dtl.DTLVardef@19a64forg.highwire.dtl.DTLVardef@1f59cff_HPS_FORMAT_FIGEXP M_FIG C_FIG

The purification of industrial enzymes typically relies on costly, multi-step chromatographic protocols. To address this, we developed a novel platform termed Coated Bacterial Enzymes (CBEs), which enables one-step purification and immobilization of recombinant proteins fused to the SlpA cell wall binding domain. As a proof of concept, we used a {beta}-galactosidase from Bifidobacterium bifidum of dairy relevance. The chimeric enzyme BbgII-SlpA was expressed in Escherichia coli and captured from crude lysate onto glutaraldehyde-inactivated Bacillus subtilis cells via SlpA domain. Binding was characterized by a dissociation constant (Kd) of 16.2 {micro}M and maximum binding capacity (Bmax) of 144 {micro}mol/g. The resulting CBE biocatalyst exhibited optimal activity at pH 6.0 for ONPG and lactose, with a broader pH profile than the free enzyme. Optimal temperatures were 60 {degrees}C for ONPG and 50 {degrees}C for lactose, and CBE retained >80% activity after 390 min at 45 {degrees}C, compared to 20% for the free enzyme. Catalytic efficiencies (kcat/Km) were 2.62 x106 M-1{middle dot}s-1 for ONPG and 4.40 x102 M-1{middle dot}s-1 for lactose. Moreover, CBE showed improved tolerance to cations such as Ca2+ and Fe2+. These results suggest that the CBE platform offers a cost-effective alternative for producing high-purity, immobilized enzymes for diverse industrial bioprocesses.

Automated platforms such as Chi.Bio enable simultaneous monitoring of optical density and fluorescent reporter expression in 20 ml reactor cultures with controllable pump systems. As such, they provide an appealing option for contemporary gene expression quantification, quantitative physiology, and laboratory evolution and ecology experiments. While optical density calibration for this device is well established, no equivalent calibration framework exists for fluorescence, making quantitative comparison with reference instruments unreliable. Here, we characterize Chi.Bio fluorescence capabilities using fluorescent calibration microspheres and fixed GFP-expressing S. cerevisiae and E. coli cells, compared with orthogonal plate-reader measurements. We show that microsphere fluorescence is detectable and scales linearly with concentration, whereas the GFP signal from both species falls below the device detection limit. Comparison of background-correction strategies indicates that direct subtraction of a non-fluorescent control measured within the same device yields more reliable fluorescence estimates than the commonly used on-line normalization method. Knowledge of these sensitivity boundaries of the device provides practical guidelines for experimental design of future studies.

{beta}4-galactosylation is a critical quality attribute of therapeutic monoclonal antibodies (mAbs), enhancing complement-dependent cytotoxicity, antibody-dependent cytotoxicity, and antibody-dependent cellular phagocytosis. Despite its therapeutic importance, galactosylation remains the most variable glycosylation motif due to its sensitivity to cell culture conditions. Here, we describe a dual genetic engineering strategy applied to two mAb-producing CHO cell lines, DP12 and VRC01, to simultaneously overcome the cellular machinery and metabolic bottlenecks that limit {beta}4-galactosylation. The first engineering event knocks out COSMC, the chaperone required for core 1 {beta}-1,3-galactosyltransferase 1 activity, to redirect UDP-Gal consumption from O-linked {beta}3-galactosylation towards mAb Fc N-linked {beta}4-galactosylation. The second event overexpresses {beta}-1,4-galactosyltransferase 1 ({beta}4GalT1) to augment cellular galactosylation machinery. Each modification was characterised individually (COSMC- and GalT+) and in combination (C-/GT+) across both cell lines in batch and fed batch cultures. The combined C-/GT+ strategy consistently achieved greater than 90% mAb Fc {beta}4-galactosylation, irrespective of host cell line or culture mode. Metabolic characterisation confirmed that both engineering events alleviate their respective bottlenecks: COSMC knockout redirects UDP-Gal flux and {beta}4GalT1 overexpression increases N-galactosylation capacity. The C-/GT+ strategy also reduced production of Man5 glycans, which accelerate serum clearance and pose immunogenicity risks. Metabolic profiling suggests that the COSMC knockout attenuates UTP consumption and contributes to reduced Man5 production. C-/GT+ glycoengineering had no negative impact on mAb titre. Our results establish the C-/GT+ dual glycoengineering strategy as a robust approach for consistently achieving high mAb galactosylation across diverse cell culture conditions, with the additional benefit of reduced Man5 glycans. HighlightsO_LIDual COSMC KO and {beta}4GalT1 overexpression achieves >90% mAb Fc galactosylation. C_LIO_LICOSMC KO redirects UDP-Gal from O-glycans to mAb Fc without impacting cell growth. C_LIO_LIDual glycoengineering reduces production of undesired Man5 glycans. C_LI

In biotherapeutic manufacturing, product quality such as glycosylation profile is typically assessed only after harvest, limiting opportunities for corrective action during cell culture operation. Intracellular nucleotide sugar donors (NSD) directly determine glycosylation outcomes but are rarely measured, even offline, due to analytical complexity and process disruption. As a result, quality-related decisions remain constrained to fixed operating strategies. This work introduces a model-based soft sensing framework to infer NSD concentrations from readily available extracellular measurements. A Bayesian state estimation approach based on the Ensemble Kalman Filter (EnKF) is developed to reconstruct unmeasured intracellular states during CHO cell culture. An imperfect kinetic process model is combined with noisy extracellular measurements, explicitly accounting for process variability and measurement uncertainty through ensemble-based propagation and updates. The framework is validated using four independent experiments with distinct feeding perturbations that are not used for model calibration. Although the open-loop model exhibited substantial mismatch for both extracellular metabolites and intracellular NSDs, EnKF assimilation of extracellular measurements corrected key metabolic profiles. Building on these corrected extracellular dynamics, the EnKF demonstrated robust estimation of a growth-determining amino acid, asparagine, from correlated extracellular states. Based on the improved extracellular and amino acid estimates, the framework further enabled reliable inference of intracellular NSDs across all experiments.

Engineering the ethanologenic Gram-negative bacterium Z. mobilis for the secretion of hydrolytic enzymes is a key step towards establishing a biofuel cell factory that uses complex waste material as feedstock. Secretion strategies in Z. mobilis have exclusively relied on signal peptides, which limit protein transport to the periplasm. To achieve single-step secretion across the Z. mobilis double-layered membrane, we sought to identify a native Type I Secretion System (T1SS) tag for fusion to proteins of interest. While a T1SS operon had been identified in the Z. mobilis genome, its native cargo had remained unknown and the use of T1SS secretion tags had so far been unexplored. Here, bioinformatic analysis identified the Major Intrinsic Protein (MIP) as a putative T1SS cargo, and its role validated through fusion of C-terminal sequences of two lengths (61 and 141 amino acids) to a heterologous {beta}-galactosidase from Bacteroides thetaiotaomicron, expressed in Z. mobilis. The 141 amino acid tag, including two RTX domains, resulted in significantly higher secretion efficiency than the 61 amino acid tag lacking RTX repeats, consistent with the established role of RTX domains in preventing premature cytoplasmic folding, thus improving secretion. As extracellular secretion of hydrolytic enzymes has remained a major bottleneck in the development of Z. mobilis as a sustainable cell factory, the identification of a native T1SS secretion tag directly addresses this limitation, introducing a novel tool for enzyme delivery.