During vertebrate development, gastrulation leads to the formation of three distinct germlayers. In zebrafish a central process is the delamination and the ingression of single cells from a common ancestor tissue - that will lead to the formation of the germlayers. Several molecules have been identified to regulate this process but the precise cellular mechanisms are poorly understood. Differential adhesiveness, a concept first introduced by Steinberg over 40 years ago, has been proposed to represent a key phenomena by which single hypoblast cells separate from the epiblast to form the mesendoderm at later stages. In this work it is shown that differential adhesion among the germlayer progenitor cells alone cannot predict germlayer formation. It is a combination of several mechanical properties such as cell cortex tension, cell adhesion and membrane mechanical properties that influence the migratory behavior of the constituent cells.

The local microenvironment of hematopoietic stem cells (HSCs) in the bone marrow -referred to as stem cell niche- is thought to regulate the balance of stem cell maintenance and differentiation by a complex interplay of extrinsic signals including spatial constraints, extracellular matrix (ECM) components and cell-cell interactions. To dissect the role of niche ECM components, a set of well-defined matrix biomolecular coatings including fibronectin, laminin, collagen IV, tropocollagen I, heparin, heparan sulphate, hyaluronic acid and co-fibrils of collagen I with heparin or hyaluronic acid were prepared and analyzed with respect to adhesive interactions of human CD133+ HSCs in vitro. ECM molecule dependent adhesion areas as well as fractions of adherent HSCs were assessed by reflection interference contrast microscopy and differential interference contrast microscopy. HSCs, so far mostly classified as suspension cells, exhibited intense adhesive interactions with fibronectin, laminin, collagen IV, heparin, heparan sulphate, and collagen I based co-fibrils. An integrin mediated adhesion on fibronectin and a L-selectin mediated adhesion on heparin pointed to specific interactions based on different adhesion mechanisms. As a consequence of HSC adhesion to molecules of the vascular and the endosteal regions, both regions were confirmed as possible stem cell niches and adhesive signals were suggested as potential regulators of stem cell fate. Furthermore, the impact of a spatially organized ECM on the HSC behavior was analyzed by single cell tracking. These studies required the development of engineered three-dimensional, ECM coated microcavities with the option for single cell tracking. A semi-automated cell-tracking tool was established to accelerate data access from time-lapse image sequences. From this analysis it was possible to reveal the genealogy, localization, morphology and migration of single HSCs over a time period of 4 days. A decreased cycling frequency was observed depending on the HSC localization in the spatially constraining microcavities. Besides the revealed impact of spatial constraints on HSC fate, the newly engineered ECM-coated microcavity setup and the semi-automated cell tracking tool provide new options to study the cell fate in engineered microenvironments at single cell level for other cell types ex vivo. / Die lokale Mikroumgebung von Blutstammzellen (BSZ) im Knochenmark, bezeichnet als Stammzellnische, reguliert das Gleichgewicht von Stammzellerhaltung und -differenzierung durch ein komplexes Zusammenspiel von extrinsischen Signalen wie räumliche Beschränkungen, Komponenten der extrazellulären Matrix (EZM) und Zell-Zell Wechselwirkungen. Um die Rolle der EZM-Komponenten zu analysieren, wurden definierte Beschichtungen von Fibronektin, Laminin, Kollagen IV, monomerem Kollagen I, Heparin, Heparan Sulphat, Hyaluronsäure und Co-Fibrillen aus Kollagen I und Heparin oder Hyaluronsäure hergestellt und in vitro bezüglich der adhäsiven Wechselwirkungen von humanen CD133+ BSZ untersucht. Die Adhäsionsflächen und der Anteil adhärenter Zellen wurden in Abhängigkeit von der EZM-Beschichtung mittels Reflexions- Interferenz-Kontrast-Mikroskopie und Differentieller Interferenz Kontrast Mikroskopie bestimmt. BSZ, bisher als Suspensionszellen definiert, zeigten intensive adhäsive Wechselwirkungen mit Fibronektin, Laminin, Kollagen IV, Heparin, Heparan Sulphat und den Co-Fibrillen. Eine Integrin abhängige Adhäsion auf Fibronektin und eine L-Selektin abhängige Adhäsion auf Heparin, wiesen auf spezifische Wechselwirkungen hin, die auf unterschiedlichen Mechanismen basieren. Aufgrund der Adhäsion von BSZ sowohl zu Molekülen der vaskulären als auch der endostealen Knochenmarkregion, wurden beide Bereiche als mögliche Stammzellnische bestätigt. Adhäsive Signale sind potentielle Regulatoren der Stammzellentwicklung. Im Weiteren wurde der Einfluss einer räumlich beschränkenden EZM auf das Verhalten der BSZ durch Einzelzellverfolgung untersucht. Diese Studien erforderten die Entwicklung von dreidimensionalen EZM-beschichteten Mikrokavitäten, die das Verfolgen einzelner Zellen ermöglichten. Es wurde ein halbautomatischer Algorithmus für die Zellverfolgung etabliert, um die Datengenerierung von den Zeitreihenaufnahmen zu beschleunigen. Die Analysen ermöglichten Aussagen über die Genealogie, Lokalisierung, Morphologie und Migration einzelner BSZ während einer Analysenzeit von 4 Tagen. Eine verringerte Zellteilungsaktivität wurde in Abhängigkeit von der BSZ Lokalisierung innerhalb der räumlich einschränkenden Mikrokavitäten festgestellt. Neben diesen Erkenntnissen bieten die entwickelten Mikrokavitäten und die etablierte Einzelzellverfolgung neue Möglichkeiten auch andere Zelltypen auf Einzelzellniveau ex vivo zu untersuchen.

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The fundamental question of how cells maintain their characteristic size remains open. Cell size measurements made through microscopic time-lapse imaging of microfluidic single cell cultivations have posed serious challenges to classical cell growth models and are supporting the development of newer, nuanced models that explain empirical findings better. Yet current models are limited, either to specific types of cells and/or to cell growth under specific microenvironmental conditions. Together with the fact that tools for robust analysis of said time-lapse images are not widely available as yet, the above-mentioned point presents an opportunity to progress the cell growth and size homeostasis discourse through generative, probabilistic modeling and analysis of the utility of different statistical estimation and inference techniques in recovering the parameters of the same. In this thesis, I present a novel Model Framework for simulating microfluidic single-cell cultivations with 36 different simulation modalities, each integrating dominant cell growth theories and generative modelling techniques. I also present a comparative analysis of how different Frequentist and Bayesian probabilistic inference techniques such as Nuisance Variable Elimination and Variational Inference work in the context of a case study of the estimation of a single model describing a microfluidic cell cultivation.

Tissue-resident stem cells are present in many adult organs, where they are important for organ homeostasis and repair in response to injury. However, the signals that activate these cells and the mechanisms governing how these cells self-renew or differentiate are highly context dependent and incompletely understood, particularly in non-hematopoietic tissues. In the skin, melanocyte stem cells (McSCs) are responsible for replenishing mature pigmented melanocytes. In mammals, these cells reside in the hair follicle bulge and bulb niches where they are activated during homeostatic hair follicle turnover and following melanocyte destruction, as occurs in vitiligo and other skin hypopigmentation disorders. Recently, we identified adult McSCs in the zebrafish. To elucidate mechanisms governing McSC self-renewal and differentiation fates we analyzed individual transcriptomes from thousands of melanocyte lineage cells during the regeneration process. We identified transcriptional signatures for McSCs, deciphered transcriptional changes and intermediate cell states during regeneration, and analyzed cell-cell signaling changes to discover mechanisms governing melanocyte regeneration. We identified KIT signaling via the RAS/MAPK pathway as a regulator of McSC direct differentiation. Analysis of the scRNAseq dataset also revealed a population of mitfa/aox5 co-expressing cells that divides following melanocyte destruction, likely corresponding to cells that undergo self-renewal. Our findings show how different subpopulations of mitfa-positive cells underlie regeneration and differentiation of at least one subpopulation requires reactivation of developmental KIT signaling to properly reconstitute the melanocyte stripe.

Optical diffraction tomography (ODT) is a tomographic technique that can be used to measure the threedimensional (3D) refractive index distribution within living cells without the requirement of any marker. In principle, ODT can be regarded as a generalization of optical projection tomography which is equivalent to computerized tomography (CT). Both optical tomographic techniques require projection-phase images of cells measured at multiple angles. However, the reconstruction of the 3D refractive index distribution post-measurement differs for the two techniques. It is known that ODT yields better results than projection tomography, because it takes into account diffraction of the imaging light due to the refractive index structure of the sample. Here, we apply ODT to biological cells in a micro uidic chip which combines optical trapping and microfluidic flow to achieve an optofluidic single-cell rotation. In particular, we address the problem that arises when the trapped cell is not rotating about an axis perpendicular to the imaging plane, but instead about an arbitrarily tilted axis. In this paper we show that the 3D reconstruction can be improved by taking into account such a tilted rotational axis in the reconstruction process.

Titanium alloys are frequently used in the medical field as bone implant materials due to their excellent biocompatibility and corrosion resistance. Yet, their elastic modulus is usually significantly higher than the one of bone, which can lead to a reduction of bone tissue at the implant site. The current research is therefore focused on the development of highly porous implants, which promise a low elastic modulus close to that of bone, an enhanced bone ingrowth and an improved vascularization. However, the appropriate pore size for an optimal osseointegration still remains unclear. To that end, a transparent tubular microsystem is developed to mimic such a porous microenvironment in order to study single bone cell behavior and early bone formation processes. The system is fabricated out of an implant material (β-stabilized Ti-45Nb (wt%)). It is demonstrated that the bulk material composition, which is consisting of a high Nb content, can be closely transferred to transparent thin films by using reactive sputtering. These films then self-assemble into tubular microscaffolds (TS) with a diameter range between 10-42 μm. Biological studies are subsequently performed to investigate the response (e.g. cell adhesion, migration, osteogenic differentiation) of human Mesenchymal Stem Cells (MSC) to the TS. It is shown that cells form fewer, more diffuse focal adhesion points inside the TS compared to a planar surface and the spatial confinement causes a switch in between amoeboid and mesenchymal migration modes. In addition, it is demonstrated that cells can survive inside the TS for at least 12 days during osteogenic differentiation and partly mineralize the TS interior. The observed mineralization process is furthermore linked to the formation of hydroxyapatite crystals inside dead cells bodies, which leads to a crystallization over time. All in all, the TS platform offers an easy way to identify key factors of bone cell-implant interactions that can be used to improve the biocompatibility of the bone-implant interface in the future.

La mesure de cellules biologiques constitue une étape de routine dans de nombreuses investigations en biologie. Les techniques actuelles utilisées par les biologistes sont principalement basées sur l'utilisation marqueurs optiques de coloration ou fluorescents, qui fournissent des observations moléculaires et cellulaires très précises et efficaces. Dans ce contexte, la spectroscopie diélectrique micro-ondes pour analyse cellulaire constitue une méthode nouvelle et attrayante, en raison du manque de préparation et manipulation des cellules, sans besoin d'ajout de produits chimiques, qui pourraient interférer avec d'autres constituants cellulaires. Sa compatibilité avec l'analyse de cellules uniques, potentiellement en temps réel, constitue également deux atouts importants de la technique d'analyse. Les travaux de cette thèse ont donc porté sur l'optimisation d'un biocapteur hyperfréquence microfluidique, dédié à la spectroscopie diélectrique de cellules biologiques uniques, et au développement de sa métrologie pour accéder au comportement diélectrique de cellule soumise à des stimuli chimique. Après un état de l'art sur les techniques courantes d'analyse de cellule individuelle, nous nous sommes attachés à optimiser le biocapteur hyperfréquence pour en améliorer les performances en sensibilité et en répétabilité. Ces optimisations ont porté sur le procédé de micro-fabrication, l'architecture du composant, que ce soit au niveau mécanique vis à vis de l'efficacité de blocage d'une cellule unique, mais aussi d'un point de vue électromagnétique avec une étude paramétrique. Ces études ont été validées dans un premier temps expérimentalement par la mesure de billes de polystyrène, modèle diélectrique simplifié par rapport à la complexité d'une cellule biologique, puis sur cellules individuelles vivantes dans leur milieu de culture. Le banc de caractérisation a également été optimisé afin de permettre la mesure diélectrique de cellules au cours du temps, et notamment en réaction à un stimulus d'ordre chimique. La cinétique de réaction d'une cellule unique soumise à de la saponine a été enregistrée automatiquement pour différentes cellules. Ces travaux ouvrent ainsi la voie à l'analyse à l'échelle cellulaire par spectroscopie diélectrique micro-onde de processus biologiques complexes en temps réel. / The measurement of biological cells is a routine step in many biological investigations. Current techniques used by biologists are mainly based on staining or fluorescent labelings, which provide very precise and effective molecular and cellular observations. Within this context, the microwave dielectric spectroscopy for cell analysis represents a new and attractive method, due to the lack of cells preparation and manipulation, without adding chemicals that could interfere with other cellular constituents. Its compatibility with the analysis of single-cells, potentially in real-time monitoring, constitute also two major assets of the analysis technique. This PhD thesis therefore focused on the optimization of a microfluidic and microwave based biosensor, which is dedicated to the dielectric spectroscopy of individual biological cells, and the development of its metrology to assess the dielectric behavior of cells subjected to chemical stimuli. After a state of the art on the current techniques available to analyze single cells, we focused on the optimization of the microwave biosensor to improve its performances in terms of sensitivity and repeatability. These optimizations dealt with the microfabrication process, the component architecture through the investigation of single cell loading efficacy as well as an electromagnetic parametric study. These developments were validated first experimentally with the measurement of polystyrene beads, which present a simplified dielectric model compared to the complexity of a biological cell, followed then by living individual cells in their culture medium. The test bench was also optimized to allow the dielectric measurement of cells over time, and especially in response to a chemical stimulus. The reaction kinetics of a single-cell subjected to saponin was recorded automatically for different cells. This work opens the door to single-cell analysis with microwave dielectric spectroscopy of complex biological processes in real-time.

Mechanical properties of cells and their environment have an undeniable impact on physiological and pathological processes such as tissue development or cancer metastasis. Hence, there is a pressing need for establishing and validating methodologies for measuring the mechanical properties of cells, as well as for deciphering the molecular underpinnings that govern the mechanical phenotype. During my doctoral research, I addressed these needs by pushing the boundaries of the field of single-cell mechanics in four projects, two of which were method-oriented and two explored important biological questions. First, I consolidated real-time deformability cytometry as a method for high-throughput single-cell mechanical phenotyping and contributed to its transformation into a versatile image-based cell characterization and sorting platform. Importantly, this platform can be used not only to sort cells based on image-derived parameters, but also to train neural networks to recognize and sort cells of interest based on raw images. Second, I performed a cross-laboratory study comparing three microfluidics-based deformability cytometry approaches operating at different timescales in two standardized assays of osmotic shock and actin disassembly. This study revealed that while all three methods are sensitive to osmotic shock-induced changes in cell deformability, the method operating at the shortest timescale is not suited for detection of actin cytoskeleton changes. Third, I demonstrated changes in cell mechanical phenotype associated with cell fate specification on the example of differentiation and de-differentiation along the neural lineage. In the process of reprogramming to pluripotency, neural precursor cells acquired progressively stiffer phenotype, that was reversed in the process of neural differentiation. The stiff phenotype of induced pluripotent stem cells was equivalent to that of embryonic stem cells, suggesting that mechanical properties of cells are inherent to their developmental stage. Finally, I identified and validated novel target genes involved in the regulation of mechanical properties of cells. The targets were identified using machine learning-based network analysis of transcriptomic profiles associated with mechanical phenotype change, and validated computationally as well as in genetic perturbation experiments. In particular, I showed that the gene with the best in silico performance, CAV1, changes the mechanical properties of cells when silenced or overexpressed. Identification of novel targets for mechanical phenotype modification is crucial for future explorations of physiological and pathological roles of cell mechanics. Together, this thesis encompasses a collection of contributions at the frontier of single-cell mechanical characterization across timescales and cell state transitions, and lays ground for turning cell mechanics from a correlative phenomenological parameter to a controllable property.:Abstract Kurzfassung List of Publications Contents Introduction Chapter 1 — Background 1.1. Mechanical properties as a marker of cell state in health and disease 1.2. Functional relevance of single-cell mechanical properties 1.3. Internal structures determining mechanical properties of cells 1.4. Cell as a viscoelastic material 1.5. Methods to measure single-cell mechanical properties Aims and scope of this thesis Chapter 2 — RT-DC as a versatile method for image-based cell characterization and sorting 2.1. RT-DC for mechanical characterization of cells 2.1.1. Operation of the RT-DC setup 2.1.2. Extracting Young’s modulus from RT-DC data 2.2. Additional functionalities implemented to the RT-DC setup 2.2.1. 1D fluorescence readout in three spectral channels 2.2.2. SSAW-based active cell sorting 2.3. Beyond assessment of cell mechanics — emerging applications 2.3.1. Deformation-assisted population separation and sorting 2.3.2. Brightness-based identification and sorting of blood cells 2.3.3. Transferring molecular specificity into label-free cell sorting 2.4. Discussion 2.5. Key conclusions 2.6. Materials and experimental procedures 2.7. Data analysis Chapter 3 — A comparison of three deformability cytometry classes operating at different timescales 3.1. Results 3.1.1. Representatives of the three deformability cytometry classes 3.1.2. Osmotic shock-induced deformability changes are detectable in all three methods 3.1.3. Ability to detect actin disassembly is method-dependent 3.1.4. Strain rate increase decreases the range of deformability response to actin disassembly in sDC 3.2. Discussion 3.3. Key conclusions 3.4. Materials and methods Chapter 4 — Mechanical journey of neural progenitor cells to pluripotency and back 4.1. Results 4.1.1. fNPCs become progressively stiffer during reprogramming to pluripotency 4.1.2. Transgene-dependent F-class cells are more compliant than ESC-like iPSCs 4.1.3. Surface markers unravel mechanical subpopulations at intermediate reprogramming stages 4.1.4. Neural differentiation of iPSCs mechanically mirrors reprogramming of fNPCs 4.1.5. The closer to the pluripotency, the higher the cell stiffness 4.2. Discussion 4.3. Key conclusions 4.4. Materials and methods Chapter 5 — Data-driven approach for de novo identification of cell mechanics regulators 5.1. Results 5.1.1. An overview of the mechanomics approach 5.1.2. Model systems characterized by mechanical phenotype changes 5.1.3. Discriminative network analysis on discovery datasets 5.1.4. Conserved functional network module comprises five genes 5.1.5. CAV1 performs best at classifying soft and stiff cell states in validation datasets 5.1.6. Perturbing expression levels of CAV1 changes cells stiffness 5.2. Discussion 5.3. Key conclusions 5.4. Materials and methods Conclusions and Outlook Appendix A Appendix B Supplementary Tables B.1 – B.2 Supplementary Figures B.1 – B.9 Appendix C Supplementary Tables C.1 – C.2. Supplementary Figures C.1 – C.5 Appendix D Supplementary Tables D.1 – D.6 Supplementary Figures D.1 – D.7 List of Figures List of Tables List of Abbreviations. List of Symbols References Acknowledgements

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