Three-Dimensional Human Bone Marrow Organoids for the Study and Application of Normal and Abnormal Hematoimmunopoiesis.

Hematoimmunopoiesis takes place in the adult human bone marrow (BM), which is composed of heterogeneous niches with complex architecture that enables tight regulation of homeostatic and stress responses. There is a paucity of representative culture systems that recapitulate the heterogeneous three-dimensional (3D) human BM microenvironment and that can endogenously produce soluble factors and extracellular matrix that deliver culture fidelity for the study of both normal and abnormal hematopoiesis. Native BM lymphoid populations are also poorly represented in current in vitro and in vivo models, creating challenges for the study and treatment of BM immunopathology. BM organoid models leverage normal 3D organ structure to recreate functional niche microenvironments. Our focus herein is to review the current state of the art in the use of 3D BM organoids, focusing on their capacities to recreate critical quality attributes of the in vivo BM microenvironment for the study of human normal and abnormal hematopoiesis.

Immune reconstitution and clinical recovery following anti-CD28 antibody (TGN1412)-induced cytokine storm.

Cytokine storm can result from cancer immunotherapy or certain infections, including COVID-19. Though short-term immune-related adverse events are routinely described, longer-term immune consequences and sequential immune monitoring are not as well defined. In 2006, six healthy volunteers received TGN1412, a CD28 superagonist antibody, in a first-in-man clinical trial and suffered from cytokine storm. After the initial cytokine release, antibody effect-specific immune monitoring started on Day + 10 and consisted mainly of evaluation of dendritic cell and T-cell subsets and 15 serum cytokines at 21 time-points over 2 years. All patients developed problems with concentration and memory; three patients were diagnosed with mild-to-moderate depression. Mild neutropenia and autoantibody production was observed intermittently. One patient suffered from peripheral dry gangrene, required amputations, and had persistent Raynaud's phenomenon. Gastrointestinal irritability was noted in three patients and coincided with elevated γδT-cells. One had pruritus associated with elevated IgE levels, also found in three other asymptomatic patients. Dendritic cells, initially undetectable, rose to normal within a month. Naïve CD8+ T-cells were maintained at high levels, whereas naïve CD4+ and memory CD4+ and CD8+ T-cells started high but declined over 2 years. T-regulatory cells cycled circannually and were normal in number. Cytokine dysregulation was especially noted in one patient with systemic symptoms. Over a 2-year follow-up, cognitive deficits were observed in all patients following TGN1412 infusion. Some also had signs or symptoms of psychological, mucosal or immune dysregulation. These observations may discern immunopathology, treatment targets, and long-term monitoring strategies for other patients undergoing immunotherapy or with cytokine storm.

Systematic Understanding of Recent Developments in Bacterial Cellulose Biosynthesis at Genetic, Bioprocess and Product Levels.

Engineering biological processes has become a standard approach to produce various commercially valuable chemicals, therapeutics, and biomaterials. Among these products, bacterial cellulose represents major advances to biomedical and healthcare applications. In comparison to properties of plant cellulose, bacterial cellulose (BC) shows distinctive characteristics such as a high purity, high water retention, and biocompatibility. However, low product yield and extensive cultivation times have been the main challenges in the large-scale production of BC. For decades, studies focused on optimization of cellulose production through modification of culturing strategies and conditions. With an increasing demand for BC, researchers are now exploring to improve BC production and functionality at different categories: genetic, bioprocess, and product levels as well as model driven approaches targeting each of these categories. This comprehensive review discusses the progress in BC platforms categorizing the most recent advancements under different research focuses and provides systematic understanding of the progress in BC biosynthesis. The aim of this review is to present the potential of 'modern genetic engineering tools' and 'model-driven approaches' on improving the yield of BC, altering the properties, and adding new functionality. We also provide insights for the future perspectives and potential approaches to promote BC use in biomedical applications.

Multiomics characterization of mesenchymal stromal cells cultured in monolayer and as aggregates.

Mesenchymal stromal cells (MSCs) have failed to consistently demonstrate their therapeutic efficacy in clinical trials, due in part to variability in culture conditions used for their production. Of various culture conditions used for MSC production, aggregate culture has been shown to improve secretory capacity (a putative mechanism of action in vivo) compared with standard monolayer culture. The purpose of this study was to perform multiomics characterization of MSCs cultured in monolayer and as aggregates to identify aspects of cell physiology that differ between these culture conditions to begin to understand cellular-level changes that might be related to secretory capacity. Targeted secretome characterization was performed on multiple batches of MSC-conditioned media, while nontargeted proteome and metabolome characterization was performed and integrated to identify cellular processes differentially regulated between culture conditions. Secretome characterization revealed a reduction in MSC batch variability when cultured as aggregates. Proteome and metabolome characterization showed upregulation of multiple protein and lipid metabolic pathways, downregulation of several cytoskeletal processes, and differential regulation of extracellular matrix synthesis. Integration of proteome and metabolome characterization revealed individual lipid metabolites and vesicle-trafficking proteins as key features for discriminating between culture conditions. Overall, this study identifies several aspects of MSC physiology that are altered by aggregate culture. Further exploration of these processes and pathways is needed to determine their potential role in regulating cell secretory capacity.

A dual-parameter identification approach for data-based predictive modeling of hybrid gene regulatory network-growth kinetics in Pseudomonas putida mt-2.

Data integration to model-based description of biological systems incorporating gene dynamics improves the performance of microbial systems. Bioprocess performance, typically predicted using empirical Monod-type models, is essential for a sustainable bioeconomy. To replace empirical models, we updated a hybrid gene regulatory network-growth kinetic model, predicting aromatic pollutants degradation and biomass growth in Pseudomonas putida mt-2. We modeled a complex biological system including extensive information to understand the role of the regulatory elements in toluene biodegradation and biomass growth. The updated model exhibited extra complications such as the existence of oscillations and discontinuities. As parameter estimation of complex biological models remains a key challenge, we used the updated model to present a dual-parameter identification approach (the 'dual approach') combining two independent methodologies. Approach I handled the complexity by incorporation of demonstrated biological knowledge in the model-development process and combination of global sensitivity analysis and optimisation. Approach II complemented Approach I handling multimodality, ill-conditioning and overfitting through regularisation estimation, global optimisation, and identifiability analysis. To systematically quantify the biological system, we used a vast amount of high-quality time-course data. The dual approach resulted in an accurately calibrated kinetic model (NRMSE: 0.17055) efficiently handling the additional model complexity. We tested model validation using three independent experimental data sets, achieving greater predictive power (NRMSE: 0.18776) than the individual approaches (NRMSE I: 0.25322, II: 0.25227) and increasing model robustness. These results demonstrated data-driven predictive modeling potentially leading to bioprocess' model-based control and optimisation.

Energy-based culture medium design for biomanufacturing optimization: A case study in monoclonal antibody production by GS-NS0 cells.

Demand for high-value biologics, a rapidly growing pipeline, and pressure from competition, time-to-market and regulators, necessitate novel biomanufacturing approaches, including Quality by Design (QbD) principles and Process Analytical Technologies (PAT), to facilitate accelerated, efficient and effective process development platforms that ensure consistent product quality and reduced lot-to-lot variability. Herein, QbD and PAT principles were incorporated within an innovative in vitro-in silico integrated framework for upstream process development (UPD). The central component of the UPD framework is a mathematical model that predicts dynamic nutrient uptake and average intracellular ATP content, based on biochemical reaction networks, to quantify and characterize energy metabolism and its adaptive response, metabolic shifts, to maintain ATP homeostasis. The accuracy and flexibility of the model depends on critical cell type/product/clone-specific parameters, which are experimentally estimated. The integrated in vitro-in silico platform and the model's predictive capacity reduced burden, time and expense of experimentation resulting in optimal medium design compared to commercially available culture media (80% amino acid reduction) and a fed-batch feeding strategy that increased productivity by 129%. The framework represents a flexible and efficient tool that transforms, improves and accelerates conventional process development in biomanufacturing with wide applications, including stem cell-based therapies.

Optimal bioprocess design through a gene regulatory network - Growth kinetic hybrid model: Towards replacing Monod kinetics.

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications.

Recombinant biosynthesis of bacterial cellulose in genetically modified Escherichia coli.

Bacterial cellulose (BC) exhibits unique properties such as high purity compared to plant-based cellulose; however, commercial production of BC has remained a challenge, primarily due to the strain properties of cellulose-producing bacteria. Herein, we developed a functional and stable BC production system in genetically modified (GM) Escherichia coli by recombinant expression of both the BC synthase operon (bcsABCD) and the upstream operon (cmcax, ccp Ax). BC production was achieved in GM HMS174 (DE3) and in GM C41 (DE3) by optimization of the culture temperature (22 °C, 30 °C, and 37 °C) and IPTG concentration. BC biosynthesis was detected much earlier in GM C41 (DE3) cultures (3 h after IPTG induction) than those of Gluconacetobacter hansenii. GM HMS174 (DE3) produced dense fibres having a length of approximately 1000-3000 µm and a diameter of 10-20 µm, which were remarkably larger than the fibres of BC typically produced by G. hansenii.

Cyclin and DNA distributed cell cycle model for GS-NS0 cells.

Mammalian cell cultures are intrinsically heterogeneous at different scales (molecular to bioreactor). The cell cycle is at the centre of capturing heterogeneity since it plays a critical role in the growth, death, and productivity of mammalian cell cultures. Current cell cycle models use biological variables (mass/volume/age) that are non-mechanistic, and difficult to experimentally determine, to describe cell cycle transition and capture culture heterogeneity. To address this problem, cyclins-key molecules that regulate cell cycle transition-have been utilized. Herein, a novel integrated experimental-modelling platform is presented whereby experimental quantification of key cell cycle metrics (cell cycle timings, cell cycle fractions, and cyclin expression determined by flow cytometry) is used to develop a cyclin and DNA distributed model for the industrially relevant cell line, GS-NS0. Cyclins/DNA synthesis rates were linked to stimulatory/inhibitory factors in the culture medium, which ultimately affect cell growth. Cell antibody productivity was characterized using cell cycle-specific production rates. The solution method delivered fast computational time that renders the model's use suitable for model-based applications. Model structure was studied by global sensitivity analysis (GSA), which identified parameters with a significant effect on the model output, followed by re-estimation of its significant parameters from a control set of batch experiments. A good model fit to the experimental data, both at the cell cycle and viable cell density levels, was observed. The cell population heterogeneity of disturbed (after cell arrest) and undisturbed cell growth was captured proving the versatility of the modelling approach. Cell cycle models able to capture population heterogeneity facilitate in depth understanding of these complex systems and enable systematic formulation of culture strategies to improve growth and productivity. It is envisaged that this modelling approach will pave the model-based development of industrial cell lines and clinical studies.

Towards unravelling the kinetics of an acute myeloid leukaemia model system under oxidative and starvation stress: a comparison between two- and three-dimensional cultures.

A great challenge when conducting ex vivo studies of leukaemia is the construction of an appropriate experimental platform that would recapitulate the bone marrow (BM) environment. Such a 3D scaffold system has been previously developed in our group [1]. Additionally to the BM architectural characteristics, parameters such as oxygen and glucose concentration are crucial as their value could differ between patients as well as within the same patient at different stages of treatment, consequently affecting the resistance of leukaemia to chemotherapy. The effect of oxidative and glucose stress-at levels close to human physiologic ones-on the proliferation and metabolic evolution of an AML model system (K-562 cell line) in conventional 2D cultures as well as in 3D scaffolds were studied. We observed that the K-562 cell line can proliferate and remain alive for 2 weeks in medium with glucose close to physiological levels both in 20 and 5% O2. We report interesting differences on the cellular response to the environmental, i.e., oxidative and/or nutritional stress stimuli in 2D and 3D. Higher adaptation to oxidative stress under non-starving conditions is observed in the 3D system. The glucose level in the medium has more impact on the cellular proliferation in the 3D compared to the 2D system. These differences can be of significant importance both when applying chemotherapy in vitro and also when constructing mathematical tools for optimisation of disease treatment.

Free energy predictions of ligand binding to an α-helix using steered molecular dynamics and umbrella sampling simulations.

Free energy prediction of ligand binding to macromolecules using explicit solvent molecular dynamics (MD) simulations is computationally very expensive. Recently, we reported a linear correlation between the binding free energy obtained via umbrella sampling (US) versus the rupture force from steered molecular dynamics (SMD) simulations for epigallocatechin-3-gallate (EGCG) binding to α-helical-rich keratin. This linear correlation suggests a potential route for fast free energy predictions using SMD alone. In this work, the generality of the linear correlation is further tested for several ligands interacting with the α-helical motif of keratin. These molecules have significantly varying properties, i.e., octanol/water partition coefficient (log P), and/or overall charges (oleic acid, catechin, Fe(2+), citric acid, hydrogen citrate, dihydrogen citrate, and citrate). Using the constant loading rate of our previous study of the keratin-EGCG system, we observe that the linear correlation for keratin-EGCG can be extended to other uncharged molecules where interactions are governed by hydrogen bonds and/or a combination of hydrogen bonds and hydrophobic forces. For molecules where interactions with the keratin helix are governed primarily by electrostatics between charged molecules, a second, alternative linear correlation model is derived. While further investigations are needed to expand the molecular space and build a fully predictive model, the current approach represents a promising methodology for fast free energy predictions based on short SMD simulations (requiring picoseconds to nanoseconds of sampling) for defined biomolecular systems.

A novel perfused rotary bioreactor for cardiomyogenesis of embryonic stem cells.

Developments in bioprocessing technology play an important role for overcoming challenges in cardiac tissue engineering. To this end, our laboratory has developed a novel rotary perfused bioreactor for supporting three-dimensional cardiac tissue engineering. The dynamic culture environments provided by our novel perfused rotary bioreactor and/or the high-aspect rotating vessel produced constructs with higher viability and significantly higher cell numbers (up to 4 × 10(5) cells/bead) than static tissue culture flasks. Furthermore, cells in the perfused rotary bioreactor showed earlier gene expressions of cardiac troponin-T, α- and ß-myosin heavy chains with higher percentages of cardiac troponin-I-positive cells and better uniformity of sacromeric α-actinin expression. A dynamic and perfused environment, as provided by this bioreactor, provides a superior culture performance in cardiac differentiation for embryonic stem cells particularly for larger 3D constructs.

An in silico erythropoiesis model rationalizing synergism between stem cell factor and erythropoietin.

Stem cell factor (SCF) and erythropoietin (EPO) are two most recognized growth factors that play in concert to control in vitro erythropoiesis. However, exact mechanisms underlying the interplay of these growth factors in vitro remain unclear. We developed a mathematical model to study co-signaling effects of SCF and EPO utilizing the ERK1/2 and GATA-1 pathways (activated by SCF and EPO) that drive the proliferation and differentiation of erythroid progenitors. The model was simplified and formulated based on three key features: synergistic contribution of SCF and EPO on ERK1/2 activation, positive feedback effects on proliferation and differentiation, and cross-inhibition effects of activated ERK1/2 and GATA-1. The model characteristics were developed to correspond with biological observations made known thus far. Our simulation suggested that activated GATA-1 has a more dominant cross-inhibition effect and stronger positive feedback response on differentiation than the proliferation pathway, while SCF contributed more to the activation of ERK1/2 than EPO. A sensitivity analysis performed to gauge the dynamics of the system was able to identify the most sensitive model parameters and illustrated a contribution of transient activity in EPO ligand to growth factor synergism. Based on theoretical arguments, we have successfully developed a model that can simulate growth factor synergism observed in vitro for erythropoiesis. This hypothesized model can be applied to further computational studies in biological systems where synergistic effects of two ligands are seen.

Alginate Beads as a Promising Tool for Successful Production of Viable and Pluripotent Human-Induced Pluripotent Stem Cells in a 3D Culture System.

Purpose: Two-dimensional (2D)-based cell culture systems, limited by their inherent heterogeneity and scalability, are a bottleneck in the production of high-quality cells for downstream biomedical applications. Finding the optimal conditions for large-scale stem cell culture while maintaining good cellular status is challenging. The aim of this study was to assess the effects of three-dimensional (3D) culture on the viability, proliferation, self-renewal, and differentiation of human induced pluripotent stem cells (IPSCs). Patients and Methods: Various culture conditions were evaluated to determine the optimal conditions to maintain the viability and proliferation of human IPSCs in a 3D environment: static versus dynamic culture, type of adhesion protein added to alginate (Matrigel™ versus gelatin), and the addition of Y-27632t on long-term 3D culture. The proliferation ability of the cells was evaluated via the MTS proliferation assay; the expression levels of the pluripotency markers Nanog and Oct3/4, PAX6 as an ectoderm marker, and laminin-5 and fibronectin as markers of extracellular matrix synthesis were assessed; and HIF1α and HIF2α levels were measured using quantitative reverse transcription polymerase chain reaction. Results: Using a high-aspect-ratio vessel bioreactor with a gentle, low-sheer, and low-turbulence environment with sufficient oxygenation and effective mass transfer of nutrients and waste, we verified its ability to promote cell proliferation and self-renewal. The findings showed that human IPSCs have the ability to maintain pluripotency in a feeder-free system and by inhibiting ROCK signaling and using hypoxia to improve single-cell viability in 3D culture. Furthermore, these cells demonstrated increased self-renewal and proliferation when inoculated as single cells in 3D alginate beads by adding RI during the culture period. Conclusion: Dynamic 3D culture is desirable for the large-scale expansion of undifferentiated human IPSCs.

Subcellular spatially resolved gene neighborhood networks in single cells.

Image-based spatial omics methods such as fluorescence in situ hybridization (FISH) generate molecular profiles of single cells at single-molecule resolution. Current spatial transcriptomics methods focus on the distribution of single genes. However, the spatial proximity of RNA transcripts can play an important role in cellular function. We demonstrate a spatially resolved gene neighborhood network (spaGNN) pipeline for the analysis of subcellular gene proximity relationships. In spaGNN, machine-learning-based clustering of subcellular spatial transcriptomics data yields subcellular density classes of multiplexed transcript features. The nearest-neighbor analysis produces heterogeneous gene proximity maps in distinct subcellular regions. We illustrate the cell-type-distinguishing capability of spaGNN using multiplexed error-robust FISH data of fibroblast and U2-OS cells and sequential FISH data of mesenchymal stem cells (MSCs), revealing tissue-source-specific MSC transcriptomics and spatial distribution characteristics. Overall, the spaGNN approach expands the spatial features that can be used for cell-type classification tasks.

Development of a Novel Perfusion Rotating Wall Vessel Bioreactor with Ultrasound Stimulation for Mass-Production of Mineralized Tissue Constructs.

BACKGROUND: As stem cells are considered a promising cell source for tissue engineering, many culture strategies have been extensively studied to generate in vitro stem cell-based tissue constructs. However, most approaches using conventional tissue culture plates are limited by the lack of biological relevance in stem cell microenvironments required for neotissue formation. In this study, a novel perfusion rotating wall vessel (RWV) bioreactor was developed for mass-production of stem cell-based 3D tissue constructs. METHODS: An automated RWV bioreactor was fabricated, which is capable of controlling continuous medium perfusion, highly efficient gas exchange with surrounding air, as well as low-intensity pulsed ultrasound (LIPUS) stimulation. Embryonic stem cells encapsulated in alginate/gelatin hydrogel were cultured in the osteogenic medium by using our bioreactor system. Cellular viability, growth kinetics, and osteogenesis/mineralization were thoroughly evaluated, and culture media were profiled at real time. The in vivo efficacy was examined by a rabbit cranial defect model. RESULTS: Our bioreactor successfully maintained the optimal culture environments for stem cell proliferation, osteogenic differentiation, and mineralized tissue formation during the culture period. The mineralized tissue constructs produced by our bioreactor demonstrated higher void filling efficacy in the large bone defects compared to the group implanted with hydrogel beads only. In addition, the LIPUS modules mounted on our bioreactor successfully reached higher mineralization of the tissue constructs compared to the groups without LIPUS stimulation. CONCLUSION: This study suggests an effective biomanufacturing strategy for mass-production of implantable mineralized tissue constructs from stem cells that could be applicable to future clinical practice.

A Spatiotemporal Microenvironment Model to Improve Design of a Three-Dimensional Bioreactor for Red Cell Production.

Cellular microenvironments provide stimuli, including paracrine and autocrine growth factors and physicochemical cues, which support efficient in vivo cell production unmatched by current in vitro biomanufacturing platforms. While three-dimensional (3D) culture systems aim to recapitulate niche architecture and function of the target tissue/organ, they are limited in accessing spatiotemporal information to evaluate and optimize in situ cell/tissue process development. Herein, a mathematical modeling framework is parameterized by single-cell phenotypic imaging and multiplexed biochemical assays to simulate the nonuniform tissue distribution of nutrients/metabolites and growth factors in cell niche environments. This model is applied to a bone marrow mimicry 3D perfusion bioreactor containing dense stromal and hematopoietic tissue with limited red blood cell (RBC) egress. The model characterized an imbalance between endogenous cytokine production and nutrient starvation within the microenvironmental niches and recommended increased cell inoculum density and enhanced medium exchange, guiding the development of a miniaturized prototype bioreactor. The second-generation prototype improved the distribution of nutrients and growth factors and supported a 50-fold increase in RBC production efficiency. This image-informed bioprocess modeling framework leverages spatiotemporal niche information to enhance biochemical factor utilization and improve cell manufacturing in 3D systems. Impact statement Three-dimensional (3D) culture systems are becoming increasingly important because they recapitulate the architecture and, consequently, physiological function of the target tissue/organ. Design and optimization of these 3D biomanufacturing platforms require evaluation of in situ spatiotemporal information. We have developed an integrated experimental-computational framework that captures the spatiotemporal distribution of cells, nutrients, and cytokines within a marrow biomimicry perfusion bioreactor. The model simulated biochemical factor utilization and guided the design of an improved second-generation bioreactor that achieved 50-fold increase in RBC production with improved cost efficiency. Such a modeling framework provides an essential platform for the optimization of 3D biomanufacturing systems.

A 3D Bioprinted in vitro Model of Neuroblastoma Recapitulates Dynamic Tumor-Endothelial Cell Interactions Contributing to Solid Tumor Aggressive Behavior.

Neuroblastoma (NB) is the most common extracranial tumor in children resulting in substantial morbidity and mortality. A deeper understanding of the NB tumor microenvironment (TME) remains an area of active research but there is a lack of reliable and biomimetic experimental models. This study utilizes a 3D bioprinting approach, in combination with NB spheroids, to create an in vitro vascular model of NB for exploring the tumor function within an endothelialized microenvironment. A gelatin methacryloyl (gelMA) bioink is used to create multi-channel cubic tumor analogues with high printing fidelity and mechanical tunability. Human-derived NB spheroids and human umbilical vein endothelial cells (HUVECs) are incorporated into the biomanufactured gelMA and cocultured under static versus dynamic conditions, demonstrating high levels of survival and growth. Quantification of NB-EC integration and tumor cell migration suggested an increased aggressive behavior of NB when cultured in bioprinted endothelialized models, when cocultured with HUVECs, and also as a result of dynamic culture. This model also allowed for the assessment of metabolic, cytokine, and gene expression profiles of NB spheroids under varying TME conditions. These results establish a high throughput research enabling platform to study the TME-mediated cellular-molecular mechanisms of tumor growth, aggression, and response to therapy.

Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach.

The majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is proposed, linking biomass growth and substrate consumption rates to the gene regulatory programmes that control these processes. A dynamic model of the TOL (pWW0) plasmid of Pseudomonas putida mt-2 has been developed, describing the molecular interactions that lead to the transcription of the upper and meta operons, known to produce the enzymes for the oxidative catabolism of m-xylene. The genetic circuit model was combined with a growth kinetic model decoupling biomass growth and substrate consumption rates, which are expressed as independent functions of the rate-limiting enzymes produced by the operons. Estimation of model parameters and validation of the model's predictive capability were successfully performed in batch cultures of mt-2 fed with different concentrations of m-xylene, as confirmed by relative mRNA concentration measurements of the promoters encoded in TOL. The growth formation and substrate utilisation patterns could not be accurately described by traditional Monod-type models for a wide range of conditions, demonstrating the critical importance of gene regulation for the development of advanced models closely predicting complex bioprocesses. In contrast, the proposed strategy, which utilises quantitative information pertaining to upstream molecular events that control the production of rate-limiting enzymes, predicts the catabolism of a substrate and biomass formation and could be of central importance for the design of optimal bioprocesses.

Long-term immunologically competent human peripheral lymphoid tissue cultures in a 3D bioreactor.

Peripheral lymphoid organs (PLOs), the primary sites of development of adaptive immune responses, display a complex structural organization reflecting separation of cellular subsets (e.g., T and B lymphocytes) and functional compartments which is critical for immune function. The generation of in vitro culture systems capable of recapitulating salient features of PLOs for experimental, biotechnological, and clinical applications would be highly desirable, but has been hampered so far by the complexity of these systems. We have previously developed a three-dimensional bioreactor system for long-term, functional culture of human bone marrow cells on macroporous microspheres in a packed-bed bioreactor with frequent medium change. Here we adapt the same system for culture of human primary cells from PLOs (tonsil) in the absence of specific exogenous growth factors or activators. Cells in this system displayed higher viability over several weeks, and maintain population diversity and cell surface markers largely comparable to primary cells. Light microscopy showed cells organizing in large diverse clusters within the scaffold pores and presence of B cell-enriched areas. Strikingly, these cultures generated a significant number of antibody-producing B cells when challenged with a panel of diverse antigens, as expected from a lymphoid tissue. Thus the three-dimensional tonsil bioreactor culture system may serve as a useful model of PLOs by recapitulating their structural organization and function ex vivo.