Toward scalable in vitro models: a novel experimental and computational pipeline for the identification of cellular metabolic parameters

Oxygen utilization by cells has a crucial role in the design of advanced in vitro models. The aim of this study is to develop an experimental and computational pipeline for identifying oxygen metabolism parameters. We applied the approach to HepG2 cell monolayer cultures, demonstrating that such parameters depend on cell density

A Millifluidic Chamber for Controlled Shear Stress Testing: Application to Microbial Cultures

In vitro platforms such as bioreactors and microfluidic devices are commonly designed to engineer tissue models as well as to replicate the crosstalk between cells and microorganisms hosted in the human body. These systems promote nutrient supply and waste removal through culture medium recirculation; consequently, they intrinsically expose cellular structures to shear stress, be it a desired mechanical stimulus to drive the cell fate or a potential inhibitor for the model maturation. Assessing the impact of shear stress on cellular or microbial cultures thus represents a crucial step to define proper environmental conditions for in vitro models. In this light, the aim of this study was to develop a millifluidic device enabling to generate fully controlled shear stress profiles for quantitatively probing its influence on tissue or bacterial models, overcoming the limitations of previous reports proposing similar devices. Relying on this millifluidic tool, we present a systematic methodology to test how adherent cellular structures react to shear forces, which was applied to the case of microbial biofilms as a proof of concept. The results obtained suggest our approach as a suitable testbench to evaluate culture conditions in terms of shear stress faced by cells or microorganisms

Ottimizzazione di un bioreattore per lo sviluppo di un modello in vitro del microbiota intestinale umano

L’obiettivo del presente lavoro di tesi è consistito nell’ottimizzazione e nella fabbricazione di una camera di coltura che consenta di coltivare in vitro il microbiota intestinale umano e di riprodurne un modello dinamico fisiologicamente rilevante, passando attraverso la definizione quantitativa delle specifiche di progetto per un tale sistema, su cui è stato fondato un paradigma di confronto sistematico tra possibili design di un bioreattore. Particolare attenzione è stata posta sui requisiti riguardanti lo sforzo di taglio: è stata infatti progettata e fabbricata una camera fluidica a sforzo di taglio controllato propedeutica allo sviluppo della camera di coltura, utilizzata per lo studio dell’influenza di questa azione meccanica su biofilm di singoli ceppi microbici e sul microbiota intestinale. La tesi è articolata nei capitoli elencati e brevemente descritti di seguito: • Capitolo 1: definizione del ruolo dei bioreattori nell’ambito dell’ingegneria tessutale e descrizione tecnica delle loro funzionalità, con particolare riferimento ad applicazioni di simulazione dell’ambiente intestinale e di generazione di profili di sforzo di taglio controllati. • Capitolo 2: introduzione al ruolo dei modelli agli elementi finiti nella progettazione ingegneristica e determinazione del design ottimale per la realizzazione di una camera fluidica a sforzo di taglio controllato basata su simulazioni di fluidodinamica computazionale. • Capitolo 3: studio di fabbricazione dei singoli componenti per due prototipi successivi della camera fluidica a sforzo di taglio controllato e progettazione e realizzazione di un adeguato sistema di chiusura che ne garantisca la tenuta idraulica. • Capitolo 4: progettazione, fabbricazione e prototipazione elettronica di un box per la generazione ed il monitoraggio di condizioni di anaerobiosi, finalizzato a prove biologiche in cui siano coinvolti ceppi batterici anaerobi o il microbiota intestinale. • Capitolo 5: descrizione delle prove sperimentali svolte per mezzo della camera fluidica ai fini della valutazione dell’influenza dello sforzo di taglio sulla crescita di biofilm composti da singole specie microbiche e di campioni di microbiota intestinale completo. • Capitolo 6: individuazione dei principali requisiti di un bioreattore per lo sviluppo di costrutti batterici e definizione sulla base di essi di un paradigma per il confronto quantitativo tra le possibili geometrie di un tale dispositivo, al fine di ottimizzarne il design. Questa metodologia è stata quindi applicata per lo sviluppo e la fabbricazione di un prototipo di una camera di coltura per il microbiota intestinale umano, a partire dall’analisi agli elementi finiti dei principali fenomeni di trasporto in essa coinvolti

Metabolic scaling as a novel paradigm for biomimetic design

Metabolic scaling is an inherent feature of living systems holding across species. As organismal metabolism governs resource management in biological communities and underpins any physiological process, the power-law formulation (i.e., the Kleiber's law - KL) of this phenomenon sets a universal constraint for life. Hence, KL has started to be considered relevant also in the biomedical field, being reasonably assumed as a necessary condition to design biomimetic models. However, current scaling frameworks are yet to provide an exhaustive description of metabolic patterns, since a number of biophysical traits and mechanisms potentially affecting size-related scaling are still underrated or even neglected. Several aspects of paramount importance thus need to be addressed before properly exploiting metabolic scaling as a testbench for predictivity and translatability of cellular models. In this light, the overall aim of my Ph.D. has been to tackle some of these challenges for broadening the view on metabolic scaling and refining its actual formulation, moving towards the development of a novel paradigm for biomimetic design based on the coherence with such ubiquitous characteristic of life as a fundamental criterion. A suite of quantitative engineering methods underlying the systematic integration of computational and experimental tools have been used for all studies performed to this purpose and reported in the thesis. Specifically, my effort has mainly focused on three scaling-related aspects: the kinetics of cellular oxygen (O2) consumption as a function of the aggregation state and experimental conditions of the system (Chapters 2 and 3), the estimation of whole-construct metabolic rates and eventually associated allometries in real in vitro contexts (Chapters 4 and 5) and the impact of biological heterogeneities on such scaling behaviours (Chapter 6). Each point has been investigated in in silico or in vitro aggregates of hepatic (i.e., HepG2) cells throughout different levels of complexity, spanning from single cells up to ensembles of 3D constructs, under the hypothesis that O2 metabolism represents a reliable proxy of the overall metabolism of a living system. Since the way cells consume O2 and modulate its uptake crucially influences metabolic scaling, the first analysis has regarded the characterization of O2 consumption kinetics. In particular, empirical parameters defining the Micahealis-Menten (MM) kinetic model (i.e., sOCR and kM) have been identified in single cells as well as monolayer cultures and cell-laden microspheres at different cell densities by means of cutting-edge sensing technologies combined with a purposely developed multiparameter identification algorithm. The generality of the implemented procedure for identifying kinetic parameters has allowed the extraction of sOCR and kM from O2 concentration profiles irrespective of the specific aggregation level tested. Remarkably, HepG2 cells have displayed lower values of sOCR and higher of kM when in isolation rather than in 2D and 3D aggregates, suggesting that aggregation enhances O2 consumption probably due to endogenous interactions and the more in vivo-like microenvironment that cells are exposed to. This characterization step has highlighted that such MM parameters also depend on cell density, leading to a decrease in the average O2 uptake of cells when more densely packed in both monolayers and microspheres. This may indicate a cooperative behaviour in terms of O2 metabolism in conditions of resource sharing, which is not explicitly expressed in the current formulation of the MM model. No systematic differences have been instead noticed between the two spatial arrangements of cell aggregates. The cooperative dynamics revealed in this thesis might be integrated in the MM formulation of the consumption kinetics as an explicit dependency of sOCR and kM on a purposely defined index, describing the aggregate dimensionality rather than just the cell density. An experimental procedure for measuring metabolic rates of cell aggregates has been then developed and applied to cell-laden microspheres, isolated or coexisting in a common environment. In the former case, microspheres crafted at a standard in vitro cell density have been tested to evaluate their metabolic scaling behaviour. To date, this has represented the first attempt of empirically assessing the physiological relevance of cellular models leveraging on KL. Whole-construct metabolic rates estimated from O2 concentration profiles are in line with computational predictions; specifically, they have displayed isometric scaling, thus suggesting that currently fabricated hepatic microspheres may lack predictive and translational power. In vitro constructs based on the encapsulation of cells in hydrogel matrices shaped through extrusion-based techniques are indeed characterized by cell densities far from values observed in vivo (~ two orders of magnitude lower), because of limitations imposed by physical constraints related to the fabrication process. In addition, the investigated size range cannot be extended to higher masses due to the diffusion-limited O2 supply and potential onset of significant necrotic cores. Given that, further increasing the complexity of 3D cell aggregates to achieve the quarter-power scaling of their O2 consumption needs the introduction of multiple cell phenotypes – be they artificially embedded in multi-cellular microspheres or self-organized in organoids – properly chosen to promote the onset of specific crosstalk and signalling pathways characteristic of the biological tissue of interest, which could drive the modulation of O2 metabolism and thus the emergence of non-isometric scaling. On the other hand, the estimation of individual metabolic rates in multi-construct systems has been oriented to develop an in silico-in vitro framework for investigating whether and how coexistence affects O2 consumption and subsequent scaling behaviours. Suitable configurations have been implemented in silico and then adapted to be reproduced in vitro. Computationally, spheroidal constructs have been shown to reduce their metabolic rate when closely coexisting in high number. In accordance, such conditions also lead to the narrowing of the size range corresponding to non-isometric scaling as well as to lower values of the associated exponent. Such results have been corroborated by experimental tests. These preliminary results suggest the use of in silico and in vitro models of simple cellular systems as promising tools to study metabolic dynamics typical of biological communities at larger scales, such as natural ecosystems, with fundamental implications which might go beyond the biomedical field. Further investigations are needed to achieve this goal, extending the analysis to multi-construct systems involving individuals characterized, for instance, by different phenotypical traits, sizes and random spatial distribution within the shared environment, as well as exposed to fluctuating exercise conditions. The majority of scaling studies still consider living systems as exhaustively defined by average physiological parameters, as KL does. However, heterogeneities constitute an essential and unavoidable feature in biology, also underlying whole-system consequences of resource utilization as well as community adaptations to external stimuli or disturbances. In this light, the last part of this thesis has focused on the introduction of stochasticity in the current scaling framework. In particular, an in silico pipeline for the assessment of metabolic scaling in the presence of variability has been developed and, as a proof of concept, applied to scale joint distributions of mass and metabolic rate of computer-generated populations of spheroidal cell aggregates. The methodology is gathered around an optimization algorithm for the normalization and collapse of simulated datasets, allowing the identification of scaling exponents according to the generalized formulation of KL. Using the pipeline, a size window of physiological relevance has been determined for such digital spheroids laden with two different cell phenotypes, defined as the intersection of mass ranges in which a negligible non-viable volume forms and a non-isometric scaling of metabolic rates holds. The results show a physiologically relevant window narrower than those previously estimated by means of a deterministic approach and associated to non-isometric exponents significantly deviating from 3/4. Moreover, the amplitude of introduced heterogeneities has been demonstrated to modulate scaling parameters. This represents quantitative evidence that fluctuations must be incorporated for consistently studying metabolic scaling in biological systems and claims for the role of diversity – and its extent – in shaping the demand and intake of resources in living communities. Beyond the proof-of-concept application, the designed pipeline is aimed at a broad use for scaling experimental joint distributions of size and metabolism from samples of different origin, such as cellular models in vitro or organismal populations in natural ecosystems. However, as estimated in this thesis exploiting the potential of in silico methods, at least 104 joint measurements are necessary to get statistically significant collapses, calling for the establishment of novel, high-throughput methodologies to experimentally probe size-related metabolism. Alternatively, model fitting and data augmentation strategies (e.g., Markov Chain-based Monte Carlo methods) could be included as a support to create useful joint datasets. More specifically, such Bayesian approaches might be evaluated to merge actual data and a priori knowledge, in order to construct posterior probability density functions representative of the joint distributions of interest. Furthermore, the stochastic scaling framework proposed here might be used for quantitatively evaluating the impact of specific stressors or perturbations on metabolic patterns in communities. To conclude, this Ph.D. thesis has moved a crucial step to establish metabolic scaling as a necessary constraint for biomimetic design, providing a quantitative paradigm to fully tap the potential of in silico and in vitro cell-based modelling. Ground-breaking implications may regard the development of human-relevant models for applications in tissue engineering and precision medicine, as well as the improvement of alternative approaches to animal testing. Given the centrality of metabolism to life, results and further developments of this work might have broader significance, concerning metabolic processes of ecological interest with possible impact on species conservation, developmental biology or climate dynamics

A sense of proximity: Cell packing modulates oxygen consumption

Accurately modeling oxygen transport and consumption is crucial to predict metabolic dynamics in cell cultures and optimize the design of tissue and organ models. We present a methodology to characterize the Michaelis–Menten oxygen consumption parameters in vitro, integrating novel experimental techniques and computational tools. The parameters were derived for hepatic cell cultures with different dimensionality (i.e., 2D and 3D) and with different surface and volumetric densities. To quantify cell packing regardless of the dimensionality of cultures, we devised an image-based metric, referred to as the proximity index. The Michaelis–Menten parameters were related to the proximity index through an uptake coefficient, analogous to a diffusion constant, enabling the quantitative analysis of oxygen dynamics across dimensions. Our results show that Michaelis–Menten parameters are not constant for a given cell type but change with dimensionality and cell density. The maximum consumption rate per cell decreases significantly with cell surface and volumetric density, while the Michaelis–Menten constant tends to increase. In addition, the dependency of the uptake coefficient on the proximity index suggests that the oxygen consumption rate of hepatic cells is superadaptive, as they modulate their oxygen utilization according to its local availability and to the proximity of other cells. We describe, for the first time, how cells consume oxygen as a function of cell proximity, through a quantitative index, which combines cell density and dimensionality. This study enhances our understanding of how cell–cell interaction affects oxygen dynamics and enables better prediction of aerobic metabolism in tissue models, improving their translational value

Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of threedimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol center dot m-3) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolicrate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design of more predictive and physiologically relevant in vitro models.ECH

Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of three-dimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol c5m 123) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolic-rate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design of more predictive and physiologically relevant in vitro models

Teaching Design Standards and Regulations on Medical Devices Through a Collaborative Project-Based Learning Approach

The final goal a course of Medical Device Design is to convey the importance of multidisciplinary approach in Biomedical Engineering (BME), where scientific and technical knowledge has to address the clinical needs of patients and healthcare providers, and has to promote problem-solving abilities and teamwork. In such context, project/problem-based teaching- learning methods have been suggested among the more effective strategies for bridging technical competences with the development of transversal skills and consequently in the professional formation of engineering students. In the BME field, standards and regulations on medical technologies have a paramount role, as they ensure safety and efficacy of the devices but, despite their importance, it is difficult to engage students’ attention when teaching norms and legislations. This paper describes the teaching/learning experience in a new course on Laboratory of Biomedical Technologies at the first year of the Master’s Degree programme in BME at University of Pisa (Italy), where standards and regulations were introduced as design constraints for the project-based final examination. The collaborative design and prototyping of a walking frame are discussed in detail, to demonstrate the feasibility and the challenges of the proposed approach

Size-related variability of oxygen consumption rates in individual human hepatic cells

Accurate descriptions of the variability in single-cell oxygen consumption and its size-dependency are key to establishingmore robust tissue models. By combining microfabricated devices with multiparameter identification algorithms, wedemonstrate that single human hepatocytes exhibit an oxygen level-dependent consumption rate and that their maximaloxygen consumption rate is significantly lower than that of typical hepatic cell cultures. Moreover, we found that clusters oftwo or more cells competing for a limited oxygen supply reduced their maximal consumption rate, highlighting their abilityto adapt to local resource availability and the presence of nearby cells. We used our approach to characterize the covarianceof size and oxygen consumption rate within a cell population, showing that size matters, since oxygen metabolism covarieslognormally with cell size. Our study paves the way for linking the metabolic activity of single human hepatocytes to theirtissue- or organ-level metabolism and describing its size-related variability through scaling laws