Journal of Biological Engineering

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.

Compact tissue-specific promoters are highly desirable for gene therapy because viral vectors possess limited packaging capacity. However, existing promoter engineering strategies rely primarily on rational design or de novo sequence generation and lack efficient approaches for compressing long native promoters while preserving regulatory specificity. Although genome foundation models have substantially improved sequence-to-function prediction, they have not been effectively translated into computational platforms for promoter engineering. Here, we present VirEvo, a computational promoter engineering framework that integrates a virtual dual-luciferase assay (VirDLA), genome-foundation-model-guided genetic evolution, and an orthogonal Pan-Tissue Consistency Filter (PTCF). VirDLA introduces an internal-reference normalization strategy inspired by dual-luciferase reporter assays, enabling relative comparison of promoter activity across tissues without retraining AlphaGenome. Guided by these normalized activity scores, VirEvo iteratively optimizes promoter selectivity, off-target activity, and sequence length. Using the human p16INK4a promoter as a proof of concept, VirEvo evolved a compact synthetic promoter, SRP2M, of only 398 bp, representing an 85.9% reduction in sequence length. Experimental validation using dual-luciferase reporter assays in senescent IMR90 fibroblasts demonstrated that SRP2M retained 77% of wild-type senescence selectivity while reducing basal leakage to 52% of the wild-type level. Together, these results demonstrate the feasibility of genome-foundation-model-guided promoter engineering. VirEvo provides a generalizable framework for designing compact tissue-specific regulatory elements and extends the application of genome foundation models from functional prediction to synthetic regulatory engineering.

Here we introduce OpenEvo, a fully open-source, low-cost turbidostat platform for automated continuous culture and directed evolution experiments. Existing tools are expensive, complex, or lack open-source hardware; OpenEvo addresses this gap. OpenEvo is a complete, fully automated evolution platform with detailed, illustrated construction instructions for beginners, open-source software and firmware, and a single device priced around $300. An optional PC-based version offers enhanced functionality, including remote access, programmable evolution cycles, programmable LED stimulation, and a data visualization tool. OpenEvo can cycle through three types of media for positive, negative, and neutral selection conditions, supporting a wide range of experimental designs. We validate the use of OpenEvo by evolving H. volcanii to grow from 15% to 12% salt over ~150 cycles, ~1,000 hours. Evolved cells grew 36% faster than wild-type at 12% salt. Whole-genome sequencing of adapted cells found SNPs and large deletions. We also demonstrate positive and negative selection using the OpenEvo LEDs to drive optogenetics via a Phytochrome B-based optogenetic tool, with light as the selection stimulus during over 4000 hours of growth. OpenEvo lowers the technical and cost barriers for continuous evolution experiments, serves as a teaching tool, and is designed to grow an open community of users who share modifications.

Intestinal organoids are powerful in vitro models, but their use in large-scale analyses remains constrained by the low throughput, labor-intensive handling, and high reagent consumption of conventional Matrigel dome culture. Here, we present Organoid-in-Bead (OrB), a vortex-based compartmentalization workflow that partitions organoid fragments into thousands of discrete Matrigel microbeads, enabling scalable, high-density culture from a single batch preparation. OrB maintains dome-comparable organoid growth and epithelial polarity, supports passaging-based culture expansion, yields more than 5,000 organoids in the final 10 cm dish format, and reduces Matrigel and medium consumption by approximately 70% on a per-organoid basis. OrB therefore provides a practical and scalable upstream workflow for generating screening-scale intestinal organoids. HighlightsO_LIOrB generates Matrigel microcompartments by vortexing without microfluidics C_LIO_LIOrB enables scalable, high-density intestinal organoid culture in one batch C_LIO_LIOrB maintains dome-comparable growth and epithelial polarity and supports passaging C_LIO_LIOrB yields >5,000 organoids per batch with [~]70% less Matrigel/medium per organoid C_LI

Osteoarthritis (OA) drug development remains constrained by preclinical models that fail to recapitulate the multicellular interactions that regulate human joint inflammation and extracellular matrix degeneration in response to investigational drugs. Tanezumab, a humanized anti-nerve growth factor monoclonal antibody developed for non-opioid pain relief, advanced to late-stage clinical trials but was discontinued due to unresolved joint-localized safety concerns, including rapidly progressive OA. This study evaluated whether a human microfluidic joint-on-a-chip co-culture system could detect early biomarker responses to tanezumab exposure that were not apparent in conventional chondrocyte monoculture. Tanezumab was first tested in human chondrocyte monoculture under untreated and disease-like (i.e., IL-1{beta}-treated) conditions. Across a 20-analyte panel of inflammatory and matrix-remodeling biomarkers, statistically significant monoculture responses to tanezumab were limited to decreased IL-1{beta} from 335 to 132 pg/mL ([~]0.39-fold) and increased IL-8 from 575 to 675 pg/mL ([~]1.17-fold). Major OA-associated matrix-remodeling markers, including MMP-1, MMP-3, and MMP-13, remained largely unchanged, indicating that monoculture conditions are insufficiently sensitive to detect clinically predictive drug-related molecular changes. Tanezumab was then evaluated in co-cultures containing chondrocytes, osteoblasts, fibroblast-like cells, and macrophages under low-inflammation (i.e., M0 macrophage-based) and high-inflammation (i.e., M1 macrophage-based) conditions. In the M0-based co-culture, tanezumab increased MMP-1 from [~]4.20 x 104 to [~]6.20 x 104 pg/mL ([~]1.48-fold), MMP-3 from [~]8.00 x 104 to [~]1.20 x 105 pg/mL ([~]1.50-fold), and MCP-1 from 2.85 x 103 to 4.31 x 103 pg/mL ([~]1.51-fold). In contrast, the M1-based co-culture showed decreases in MMP-13 from [~]1.66 x 104 to [~]1.17 x 104 pg/mL ([~]0.70-fold) and IFN-{gamma} from [~]1.95 x 104 to [~]1.56 x 104 pg/mL ([~]0.80-fold), changes that may appear beneficial despite the drugs known clinical risks. Collectively, these findings show that low-inflammation multicellular co-culture revealed coordinated matrix remodeling and inflammatory responses to NGF blockade that were missed in monoculture and were partly obscured in highly stimulated disease-like conditions. This platform may provide a useful, human-relevant approach for safety signal assessment and early evaluation of OA therapeutics within a defined context of use focused on joint-specific, tissue-level drug-response testing.

Phage therapy offers a promising solution to the antimicrobial resistance crisis. However, a major concern preventing the adoption of phage therapy is the potential for unintended consequences of phage release; both in regard to preventing the spread of phage resistance, and the proliferation of a non-endemic virus into the microbial ecosystem. Conditional replication (biocontainment) of phages through bioengineering may address these concerns, but the impact on bactericidal efficacy is unknown. Here, we created a biocontained T7 phage (T7{Delta}capsid) lacking the major structural capsid gene, gp10AB, that can only replicate on Escherichia coli strains expressing gp10AB in trans, and assessed its bactericidal efficacy compared with wild-type T7. Congruent with model predictions, T7{Delta}capsid was only able to clear a well-mixed culture of E. coli at a multiplicity of infection (MOI) of 10 or higher, whereas wild-type T7 prohibited growth at an MOI of 0.1. The reduction in efficacy was more evident in a complex structured environment within a microfluidic device, where phage success depends on its ability to penetrate a microbial niche via propagation. In this environment, T7{Delta}capsid was unable to propagate into the bacterial population and unlike wild-type T7, had no impact on the population's growth. This study shows that whilst biocontainment of phages may improve the biosafety of phage therapy, it comes at the cost of its propagation efficacy and niche penetration in relevant environments.

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.

Mesenchymal Stromal Cells (MSC) face several heterogeneity challenges hindering clinical and commercial success. Employing a multiple response model, interplay between donor heterogeneity, and critical processing parameters (CPPs), effects on MSC potency and cell expansion attributes were investigated through computed composite attribute scores. Twelve unique CPP combinations were tested in thirteen marrow-derived MSC(M) and five adipose-tissue MSC(AT) training and test datasets, respectively. Donor heterogeneity and select CPP conditions affected a curated gene panel (surrogate for MSC potency); while MSC expansion was primarily influenced by CPPs. Model performances were evaluated against clinical effectiveness data from a previously deployed clinical trial; top-performing model predicted donor rankings coincided with clinical effectiveness data, validating the modeling approach used. Our model predicted that only 8% of tested donors were agnostic to CPPs; a majority (62%) of donors showed CPP-dependent optimal composite quality attributes, with MSC seeding density as a key driver; medium supplementation and oxygen preferences were highly donor dependent. Approximately 30% of donors performed poorly at all conditions tested and may be prospectively identified using a subset of genes (TGFB, VEGF, PDCD1LG1, PDCD1LG2, IDO). Model predicted optimal parameters worked for 69% of tested donors, while sub-optimal parameters worked for only 23% of donors and were confirmed in an independent CD14+ macrophage assay. Our integrated computational and experimental framework predictably identified interactive effects of donor heterogeneity and CPP conditions to optimize MSC potency attributes.

High-quality plasmid DNA purification at high throughput remains a significant bottleneck in molecular biology and bioengineering. Current methods frequently fail to deliver sufficient yields of pure, transfection-grade DNA required for genetic engineering applications in mammalian cells. Here, we present a Biofoundry-based automated pipeline using the CyBio FeliX robotic liquid handling platform to rapidly purify plasmid DNA with minimal manual intervention. The protocol leverages Solid Phase Reversible Immobilisation (SPRI)-based magnetic bead technology to ensure consistency, scalability, and DNA purity suitable for downstream viral particle production and mammalian cell transfection. The pipeline supports flexible processing of between 8 and 96 samples per run, making it adaptable across a wide range of experimental scales. The protocol is openly available via Earlham Institute GitHub repository, enabling broad adoption across the bioscientific community and contributing to the growing toolkit of reproducible, scalable engineering biology workflows. In this work, we employed an integrated robotic pipeline to process 528 pooled DNA plasmids and built a Lentiviral DNA plasmid library for lineage tracing, validated the library by sequencing, and demonstrated efficacy in downstream mammalian cell transfection experiments.

Optogenetic control enables light-actuated regulation of gene expression and provides a programmable interface between living cells and electronic systems. However, routine prototyping of optogenetic constructs remains limited by infrastructure. Existing closed-loop platforms often require chemostats, microfluidics, robotic handling, or custom optical sensors, which can increase cost, reduce accessibility, or constrain measurement performance. Here, we present LEMOS 2.0, an updated LED-Embedded Microplate for Optogenetic Studies, a low-cost device for optogenetic stimulation and gene-circuit characterization inside standard off-the-shelf microplate readers. LEMOS 2.0 builds on the original LEMOS platform by increasing throughput from 16 to 32 microwells and reducing light leakage between adjacent microwells, allowing dark conditions to be used as an additional illumination state. The device consists of a 3D-printed frame, individually addressable LEDs positioned next to each microwell, a rechargeable battery, and an onboard microcontroller for Bluetooth-based wireless communication. Biocompatible polydimethylsiloxane microwells are cast directly into the device by replica molding, allowing bacterial cultures to be stimulated while optical density and fluorescence are measured by the microplate reader. This protocol describes the full LEMOS 2.0 workflow, including device fabrication, circuit assembly, Arduino programming, PDMS microwell casting, plate-reader setup, strain and culture preparation, automated experiment execution, device cleanup, and fluorescence/OD600 data analysis. As a demonstration, the protocol uses the CcaSR optogenetic system, in which sfGFP expression is activated by green light and repressed by red light. LEMOS 2.0 is intended to make optogenetic perturbation and gene-expression characterization more accessible to wet-lab users, enabling faster design-build-test-learn cycles without requiring specialized bioreactor or microfluidic infrastructure.

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

Adoptive T-cell therapies rely on the identification and expansion of rare tumor-reactive T cells, yet current enrichment strategies are limited by the low abundance of these cells and complexity of their functional enrichment. Here, we present a microfluidic platform that exploits hydrodynamic shear as a controllable parameter for enriching antigen-specific T cells through peptide-major histocompatibility complex (pMHC)-mediated capture. An eight-channel microfluidic device was engineered to simultaneously interrogate a range of wall shear stresses while maintaining uniform cell delivery, enabling systematic identification of shear conditions that maximize antigen-specific enrichment. Using engineered MART-1-specific Jurkat cells, we demonstrate that T-cell capture is jointly regulated by wall shear stress and pMHC density, with intermediate shear preferentially enriching antigen-specific cells over nonspecific binders. Translation of the optimal operating condition to a high-throughput single-shear device enabled approximately 35-fold enrichment of antigen-specific T cells from peripheral blood mononuclear cells containing only 0.05% target cells. We further show that peptide-MHC complexes isolated directly from melanoma whole-cell lysates support shear-dependent enrichment comparable to recombinant pMHCs. Finally, primary MART-1-specific CD8 T cells enriched using tumor-derived pMHCs retained the ability to recognize melanoma cells and upregulated the activation marker CD137 following antigen-specific stimulation. Together, these findings establish hydrodynamic shear as an orthogonal parameter for antigen-specific T-cell enrichment and provide a framework for integrating force-based selection with tumor-derived pMHCs to isolate functional antigen-specific T cells using tumor-derived pMHCs.

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.

We developed a convolutional neural network-based machine learning technique to simultaneously analyze the morphology and motility of spirochetal bacteria swimming with continuous cellular deformation. Matching probabilities between experimental images and learned models realizes quantification of cell morphology and association with motility. This method can be applied to diverse transformable cells, offering critical biophysical insights into microbial dynamics.

ObjectiveTo develop and apply a preclinical functional imaging assay for visualizing and analyzing activated synovial fibroblasts (SFs) at single-cell resolution using high-content imaging. MethodsA multiparametric functional imaging assay was developed to simultaneously interrogate six key cellular processes in cultured SFs from non-inflammatory control (NIC), osteoarthritis (OA) and rheumatoid arthritis (RA) patients. Two complementary fluorescent panels -- comprising LipidTOX, MitoSOX, TMRM, EdU Click-iT, CYTO-ID, and Sir-Lysosome -- collectively captured autophagy dynamics, mitochondrial health, lipid metabolism, and cellular proliferation within a single imaging workflow. Automated image acquisition and quantitative feature extraction via CellProfiler yielded approximately 1,200 morphological and intensity-based features per cell, enabling high-dimensional, unbiased phenotypic profiling at the individual cell level. ResultsApplication of this assay revealed marked heterogeneity in basal cellular functions among SFs stratified by disease state, and robustly differentiated between NIC, OA and RA SFs. Stimulation with inflammatory cytokines (TNF-, IL-1{beta}, IFN{gamma}) and toll-like receptor ligands (LPS, poly I:C) elicited distinct, stimulus-dependent phenotypic responses across disease groups. Multiparametric analysis and feature importance ranking identified IL-1{beta} as a key driver of enhanced autophagic activity, accompanied by significant remodeling of lipid metabolic profiles. ConclusionWe developed a scalable, sensitive approach for dissecting functional heterogeneity in primary SF cultures, revealing previously unappreciated complexity in SF biology across disease states. Our approach provides a robust framework for high-throughput drug screening and identification of candidate therapeutics selectively targeting pathogenic fibroblast functions in inflammatory arthritis.

Glioblastoma (GBM) is a highly aggressive brain tumor with a five-year survival rate of less than 5%. The current standard of care established 20 years ago includes maximal surgical resection and administration of alkylating agent temozolomide (TMZ). GBM is highly invasive, and GBM cells that evade surgical resection can become resistant to TMZ and develop new aggressive secondary tumors. Post-relapse there are few treatment options available to patients. Tissue engineering approaches suggest the opportunity to develop in vitro models of the GBM tumor microenvironment that may accelerate the discovery of novel therapies for GBM. Here, we report the adaptation of hydrogel microdroplets (microgels) to encapsulate GBM cells in a tailorable 3D matrix to assess patterns of growth and to screen TMZ drug response using patient-derived xenograft (PDX) specimens. We exploit a unique aspect of the microgel system to account for the cellular heterogeneity within the tumor microenvironment (TME). We combine cell-laden microgels generated from TMZ-resistant and TMZ responsive variants of the same PDX specimens to create heterogeneous populations with varying levels of drug sensitivity. We demonstrate a range of drug resistance phenotypes as a function of the ratio of TMZ-responsive to resistance cells and identify the population required for TMZ-resistance to overtake take the response. We then investigate the influence of tumor mimetic shifts in hyaluronic acid bioavailability and hypoxia on patterns of TMZ resistance. We show exposure to matrix-bound hyaluronan increases TMZ resistance and the glioma stem cell population in both cell variants. Lastly, we report an increase in TMZ sensitivity but divergent changes in the GSC subfraction for TMZ resistant vs responsive GBM in the presence of hypoxia. Together, we demonstrate the versatility of cell-laden microgel approach to replicate heterogenous tumor populations, model shifts in the tumor microenvironment, and rapidly screen therapeutic response.

Optogenetics enables experiments in out-of-equilibrium conditions to clarify biological mechanisms and quantify biophysical parameters. However, modelling and control techniques to study mammalian cell biology under optogenetic perturbation remain underutilised. Here, we benchmark these methods within mammalian cells by steering nucleocytoplasmic transport via the optogenetic LEXY protein in outcome-driven microscopy. First, we employ system identification to obtain models that predict transport dynamics by minimising the prediction error. We quantify this prediction accuracy for one biophysical model and two black-box models. Second, we evaluate closed-loop control efficacy by steering transport along a predefined trajectory using model-free Proportional Integral (PI) control, model-based Linear Quadratic Regulation (LQR) and Model Predictive Control (MPC). Both the predictive models and the applied control techniques demonstrate robust performance against cell-to-cell variation. This biological variation is quantified by the parameter distributions obtained from model identification with single-cell trajectories. While we show that model-free techniques such as PI and gain-scheduled PI achieve steering without explict model knowledge, predictive architectures offer better performance under this cell-to-cell variation and time-varying setpoints. Moreover, black-box predictive accuracy suggests that this model-based control is possible, even when explicit mechanistic understanding is missing. Ultimately, we demonstrate that predictive modelling and optogenetics enable quantitative characterisation and precise manipulation of mammalian cells, while offering practical guidelines for the implementation of these techniques.

PurposeExtracellular vesicles (EVs) are increasingly explored as natural vehicles for drug delivery and gene therapy approaches. However, reproducible yield and scalability of EV production still pose major challenges in the clinical translation of EV-based therapies. In this study, we sought to quantify and characterize EVs released by suspension-cultured HEK293 cells (Expi293F cells) grown in shaker flasks or small-scale bioreactors, to investigate how the culturing environment affects EV production yield. MethodsExpi293F cells were cultivated (N=3) in either shaker flasks or a bioreactor system, and total cell density, viability, and size were monitored. Supernatants were drawn daily post-cell seeding and were analyzed for EV quantity, size, morphology, and CD63 expression. ResultsNo significant differences were observed in terms of total cell density, viability, and cell size between both cultivation settings. However, cultivation of Expi293F cells in the bioreactor environment significantly increased EV yield by 3-fold compared to shaker flask cultivation (p < 0.01). Other parameters such as average nanoparticle size, EV morphology, and CD63 expression remained comparable between both cultivation methods. ConclusionThese results demonstrate that Expi293F-derived EV yield can be increased by culturing cells in a scalable bioreactor system. These findings pave the way towards the production of therapeutic-based EVs in a scalable and reproducible manner suitable for future (pre-)clinical applications.

Adeno-associated virus (AAV)-based gene therapy has made steady progress towards efficient delivery to numerous target cell populations, yet the virus's 5 kb packaging limit remains a challenge for effective and in some cases cell-selective cargo expression. Here, we introduce Expression-Linked Promoter Selection (ELiPS), a high-throughput platform for generating and functionally screening >106 engineered, short promoter variants using an AAV expression platform. ELiPS relies on a Golden Gate cloning method to build random oligomers of selected transcription factor binding sites (TFBSs) upstream of a minimal promoter, GFP, and a unique 3' barcode. As a proof of concept, to engineer short (~250 bp), synthetic, ubiquitous promoters, we applied ELiPS to build two libraries composed of TFBSs for ubiquitously expressed transcription factors (TFs) and screened them via AAV-mediated transduction in vitro. This strategy identified promoters with expression surpassing human cytomegalovirus (CMV) and CAG in vitro, and one variant was capable of driving therapeutic expression of B-domain-deleted Factor VIII (BDDFVIII) in vivo at levels comparable to a liver-specific promoter benchmark. ELiPS thus establishes a scalable framework for promoter discovery, enabling the design of compact, ubiquitous or cell-selective expression cassettes that enable further precision and efficacy in AAV-based gene therapies.

Background: Human induced pluripotent stem cells (hiPSCs) hold promise for vascular regeneration, but preliminary research often relies on neonatal donors, whereas clinical applications will use cells derived from aged individuals. Although the impact of donor age on reprogramming efficiency has been studied, its effect on the functionality of hiPSC-derived endothelial progenitors (hiPSC-EPs) remains unclear. This question is the focus of the current study. Methods and Results: We derived EPs from iPSCs sourced from three neonatal donors (ND) and three mature donors (MD) matched 1:1 for sex and somatic cell origin. We assessed their functional, epigenetic, and transcriptomic characteristics. Despite higher CD34? yields from MD-iPSCs, MD-hiPSC-EPs formed poorly interconnected and non-lumenized vascular structures in 3D hydrogels, compared to neonatal donor (ND) lines. In 2D culture, MD-hiPSC-EPs exhibited reduced cell density and aberrant VE-Cadherin localization. DNA methylation analysis revealed that somatic cell origin was the dominant driver of variance, but consistent differences in methylation of mesoderm commitment, angiogenesis, ECM remodeling, and cytoskeleton-related genes were observed between age groups. Epigenetic age prediction showed MD-hiPSC-EPs had more developmentally advanced signatures, potentially explaining their shift away from vasculogenic competence. Our RNA-sequencing findings confirm trends seen in the DNA methylation data and show differential expression of pathways linked to mitochondrial regulation and nitric oxide signaling. Conclusions: Donor age significantly alters the vasculogenic function of hiPSC-EPs. These findings underscore the necessity of donor-specific considerations in hiPSC-based vascular engineering and highlight potential barriers to translating hiPSC-derived therapeutics into aged patient populations.