Our understanding of microbial evolution is largely dependent on available genomic data of diverse organisms. Yet, genome-sequencing efforts have mostly ignored the diverse uncultivable majority in favor of cultivable and sociologically relevant organisms. In this thesis, I have applied and developed cultivation independent methods to explore microbial diversity and obtain genomic data in an unbiased manner. The obtained genomes were then used to study the evolution of mitochondria, Rickettsiales and Haloarchaea. Metagenomic binning of oceanic samples recovered draft genomes for thirteen novel Alphaproteobacteria-related lineages. Phylogenomics analyses utilizing the improved taxon sample suggested that mitochondria are not related to Rickettsiales but rather evolved from a proteobacterial lineage closely related to all sampled alphaproteobacteria. Single-cell genomics and metagenomics of lake and oceanic samples, respectively, identified previously unobserved Rickettsiales-related lineages. They branched early relative to characterized Rickettsiales and encoded flagellar genes, a feature once thought absent in this order. Flagella are most likely an ancestral feature, and were independently lost during Rickettsiales diversification. In addition, preliminary analyses suggest that ATP/ADP translocase, the marker for energy parasitism, was acquired after the acquisition of type IV secretion systems during the emergence of the Rickettsiales. Further exploration of the oceanic samples yielded the first draft genomes of Marine Group IV archaea, the closest known relatives of the Haloarchaea. The halophilic and generally aerobic Haloarchaea are thought to have evolved from an anaerobic methanogenic ancestor. The MG-IV genomes allowed us to study this enigmatic evolutionary transition. Preliminary ancestral reconstruction analyses suggest a gradual loss of methanogenesis and adaptation to an aerobic lifestyle, respectively. The thesis further presents a new amplicon sequencing method that captures near full-length 16S and 23S rRNA genes of environmental prokaryotes. The method exploits PacBio's long read technology and the frequent proximity of these genes in prokaryotic genomes. Compared to traditional partial 16S amplicon sequencing, our method classifies environmental lineages that are distantly related to reference taxa more confidently. In conclusion, this thesis provides new insights into the origins of mitochondria, Rickettsiales and Haloarchaea and illustrates the power of cultivation independent methods with respect to the study of microbial evolution.

La bactérie Pseudomonas aeruginosa (PA) est un pathogène responsable de 20%-30% des infections nosocomiales en milieu hospitalier. Pour les individus sains, elle ne présente pas de réel danger, mais pour les personnes atteintes par la mucoviscidose et les patients immunodéprimés, elle est la cause principale de mortalité et des infections pulmonaires. PA a développé des souches multi-résistantes aux antibiotiques et des nouvelles approches thérapeutiques plus efficaces sont donc nécessaires. Elle se fixe à la surface des cellules-hôtes par une interaction entre des protéines (lectines) présentes sur sa membrane et des sucres présents sur la membrane cellulaire. L’interaction lectine-sucre joue un rôle important dans l’adhésion de la bactérie puis dans la fabrication d’un biofilm pathogène.Une nouvelle approche thérapeutique consiste à créer des molécules synthétiques (glycomimes) de plus grande affinité que les sucres présents sur les cellules. Pour cela, plus de 150 glycomimes ont été synthétisés et examinés afin de trouver le meilleur candidat pour empêche le processus d'infection de bactéries. Certains d'entre eux ont été choisis et étudiés par la Microscopie à Force Atomique (AFM). Cette thèse est consacrée à l’étude des interactions lectine-glycomime et aussi cellule-bactérie par AFM. L’imagerie combinée avec la modélisation permet de comprendre le rôle du glycomime sur la géométrie des complexes créés et la spectroscopie permet de mesurer les forces d’interaction présentes lors de l’adhésion, au niveau moléculaire et cellulaire. Une réduction de l’adhésion bactérienne a été observée après l’introduction du glycomime, confirmant son rôle d’inhibiteur et la validité de toute la démarche. L’objectif ultime est l’identification des meilleurs glycomimes à introduire afin de développer de nouveaux médicaments. / Pseudomonas aeruginosa (PA) is a human opportunistic pathogen responsible for 20% -30% of nosocomial infections in French hospitals. For healthy people, it presents no real danger, but for people with cystic fibrosis disease and immune-compromised patients, it is the leading cause of mortality and lung infections. PA has developed antibiotic multi-resistant strains and new and more effective therapeutic approaches are needed. It binds to the surface of the host cells by an interaction between proteins (lectins) present on the membrane and sugars of the host-cell membrane. The lectin-sugar interaction plays an important role in adherence of the bacteria and in the manufacture of a pathogenic biofilm.A new therapeutic approach is to create synthetic molecules (glycoclusters) of greater affinity than the natural sugars present on the cells. To this aim, more than 150 glycoclusters have been synthetized and screened to find the best candidate to inhibit the bacteria infection process. Some of them have been selected and studied by Atomic Force Microscopy (AFM). In particular, this thesis is devoted to study the lectin-glycocluster and cell-bacteria interactions by AFM. The combination of AFM imaging with molecular dynamic simulations let understanding the role of the geometry of the glycoclusters on the complex formation, while AFM spectroscopy accesses the lectin-glycocluster interaction forces at the molecular and cellular levels. The reduction of bacterial adhesion has been observed upon the addition of the glycocluster. This confirms the anti-adhesive properties of the glycocluster and validates the procedure. The ultimate goal is the identification of the best glycoclusters in order to develop new drugs.

Increasing useof nanomaterials in consumer products and biomedical applications creates the possibilities of intentional/unintentional exposure to humans and the environment. Beyond the physiological limit, the nanomaterialexposure to humans can induce toxicity. It is difficult to define toxicity of nanoparticles on humans as it varies by nanomaterialcomposition, size, surface properties and the target organ/cell line. Traditional tests for nanomaterialtoxicity assessment are mostly based on bulk-colorimetric assays. In many studies, nanomaterials have found to interfere with assay-dye to produce false results and usually require several hours or days to collect results. Therefore, there is a clear need for alternative tools that can provide accurate, rapid, and sensitive measure of initial nanomaterialscreening. Recent advancement in single cell studies has suggested discovering cell properties not found earlier in traditional bulk assays. A complex phenomenon, like nanotoxicity, may become clearer when studied at the single cell level, including with small colonies of cells. Advances in lab-on-a-chip techniques have played a significant role in drug discoveries and biosensor applications, however, rarely explored for nanomaterialtoxicity assessment. We presented such cell-integrated chip-based approach that provided quantitative and rapid response of cellhealth, through electrochemical measurements. Moreover, the novel design of the device presented in this study was capable of capturing and analyzing the cells at a single cell and small cell-population level. We examined the change in exocytosis (i.e. neurotransmitterrelease) properties of a single PC12 cell, when exposed to CuOand TiO2 nanoparticles. We found both nanomaterials to interfere with the cell exocytosis function. We also studied the whole-cell response of a single-cell and a small cell-population simultaneously in real-time for the first time. The presented study can be a reference to the future research in the direction of nanotoxicity assessment to develop miniature, simple, and cost-effective tool for fast, quantitative measurements at high throughput level. The designed lab-on-a-chip device and measurement techniques utilized in the present work can be applied for the assessment of othernanoparticles' toxicity, as well.

This thesis is concerned with analytical modeling of Wireless Local Area Networks (WLANs) that are based on IEEE 802.11 Distributed Coordination Function (DCF). Such networks are popularly known as WiFi networks. We have developed accurate analytical models for the following three network scenarios: (S1) A single cell WLAN with homogeneous nodes and Poisson packet arrivals, (S2) A multi-cell WLAN (a) with saturated nodes, or (b) with TCP-controlled long-lived downloads, and (S3) A multi-cell WLAN with TCP-controlled short-lived downloads. Our analytical models are simple Markovian abstractions that capture the detailed network behavior in the considered scenarios. The insights provided by our analytical models led to two applications: (i) a faster “model-based'” simulator, and (ii) a distributed channel assignment algorithm. We also study the stability of the network through our Markov models. For scenario (S1), we develop a new approach as compared to the existing literature. We apply a “State Dependent Attempt Rate'” (SDAR) approximation to reduce a single cell WLAN with non-saturated nodes to a coupled queue system. We provide a sufficient condition under which the joint queue length Markov chain is positive recurrent. For the case when the arrival rates into the queues are equal we propose a technique to reduce the state space of the coupled queue system. In addition, when the buffer size of the queues are finite and equal we propose an iterative method to estimate the stationary distribution of the reduced state process. Our iterative method yields accurate predictions for important performance measures, namely, “throughput'”, “collision probability” and “packet delay”. We replace the detailed implementation of the MAC layer in NS-2 with the SDAR contention model, thus yielding a ``model-based'' simulator at the MAC layer. We demonstrate that the SDAR model of contention provides an accurate model for the detailed CSMA/CA protocol in scenario (S1). In addition, since the SDAR model removes much of the details at the MAC layer we obtain speed-ups of 1.55-5.4 depending on the arrival rates and the number of nodes in the single cell WLAN. For scenario (S2), we consider a restricted network setting where a so-called “Pairwise Binary Dependence” (PBD) condition holds. We develop a first-cut scalable “cell-level” model by applying the PBD condition. Unlike a node- or link-level model, the complexity of our cell-level model increases with the number of cells rather than with the number of nodes/links. We demonstrate the accuracy of our cell-level model via NS-2 simulations. We show that, as the “access intensity” of every cell goes to infinity the aggregate network throughput is maximized. This remarkable property of CSMA, namely, “maximization of aggregate network throughput in a distributed manner” has been proved recently by Durvy et al. (TIT, March, 2009) for an infinite linear chain of nodes. We prove it for multi-cell WLANs with arbitrary cell topology (under the PBD condition). Based on this insight provided by our analytical model we propose a distributed channel assignment algorithm. For scenario (S3), we consider the same restricted network setting as for scenario (S2). For Poisson flow arrivals and i.i.d. exponentially distributed flow sizes we model a multi-cell WLAN as a network of processor-sharing queues with state-dependent service rates. The state-dependent service rates are obtained by applying the model for scenario (S2) and taking the access intensities to infinity. We demonstrate the accuracy of our model via NS-2 simulations. We also demonstrate the inaccuracy of the service model proposed in the recent work by Bonald et al. (SIGMETRICS 2008) and identify the implicit assumption in their model which leads to this inaccuracy. We call our service model which accurately characterizes the service process in a multi-cell WLAN (under the PBD condition) “DCF scheduling” and study the “stability region” of DCF scheduling for small networks with single or multiple overlapping “contention domains”.

Les voies aériennes humaines sont bordées d'un épithélium pseudostratifié composé principalement de cellules basales et de cellules pyramidales parmi lesquelles figurent les cellules sécrétrices de mucus et les cellules multiciliées. Toutes ces cellules contribuent à la clairance mucociliaire des voies respiratoires. Cet épithélium se régénère lentement dans des conditions homéostatiques, mais il est capable de se régénérer rapidement après agression grâce à des processus de prolifération, de migration, de polarisation et de différenciation. Chez les patients atteints de maladies respiratoires chroniques telles que la broncho-pneumopathie chronique obstructive, l'asthme ou la mucoviscidose, la réparation tissulaire est souvent défectueuse, caractérisée par une perte de cellules multiciliées et une hyperplasie des cellules sécrétrices, ayant pour conséquence une clairance mucociliaire affectée. La séquence des événements cellulaires conduisant à un tissu fonctionnel ou remodelé est encore mal décrite. Notre principal objectif a été d’identifier les types cellulaires successifs mis en jeu lors de la régénération tissulaire et les événements moléculaires responsables d'une régénération saine ou pathologique. Nous avons analysé la composition cellulaire de l’épithélium des voies respiratoires à plusieurs stades de différenciation en utilisant un modèle de culture 3D in vitro qui reproduit la composition cellulaire in vivo. En appliquant une méthode de transcriptomique sur cellule unique couplée à des méthodes bioinformatiques, nous avons établi les hiérarchies cellulaires permettant de reconstruire les différentes trajectoires cellulaires mises en jeu lors de la régénération de l’épithélium des voies respiratoires humaines. Après avoir confirmé les lignages cellulaires qui ont été précédemment décrits, nous avons découvert une nouvelle trajectoire reliant les cellules sécrétrices de mucus aux cellules multiciliées. Nous avons également caractérisé de nouvelles populations cellulaires et de nouveaux acteurs moléculaires impliqués dans le processus de régénération de l'épithélium des voies respiratoires humaines. Enfin, grâce à ces approches, nous avons mis en évidence des réponses spécifiques de chaque type cellulaire survenant dans des situations pathologiques d’hyperplasie sécrétoire. Ainsi, nos données, en apportant d'importantes contributions à la compréhension de la dynamique de différenciation de l’épithélium des voies respiratoires humaines, ouvrent de nouvelles voies vers l’identification de cibles thérapeutiques. / Human airways are lined by a pseudostratified epithelium mainly composed of basal and columnar cells, among these cells we can find multiciliated, secretory cells and goblet cells. All these cells work together in the mucociliary clearance of the airways. This epithelium regenerates slowly under homeostatic conditions but is able to recover quickly after aggressions through proliferation, migration, polarization and differentiation processes. However, in patients with chronic pulmonary diseases such as chronic obstructive pulmonary disease, asthma or cystic fibrosis, epithelial repair is defective, tissue remodeling occurs, leading to loss of multiciliated cells and goblet cell hyperplasia, impairing correct mucociliary clearance. The sequence of cellular events leading to a functional or remodelled tissue are still poorly described. Hence, we aim at identifying the successive cell types appearing during tissue regeneration and the molecular events that are responsible for healthy or pathological regeneration. We have analysed airway epithelial cell composition at several stages of differentiation using an in vitro 3D culture model which reproduces in vivo epithelial cell composition. Applying single cell transcriptomics and computational methods, we have identified cell lineage hierarchies and thus constructed a comprehensive cell trajectory roadmap in human airways. We have confirmed the cell lineages that have been previously described and have discovered a novel trajectory linking goblet cells to multiciliated cells. We have also discovered novel cell populations and molecular interactors involved in the process of healthy human airway epithelium regeneration. Using these approaches, we have finally shed light on cell-type specific responses involved in pathological goblet cell hyperplasia. Our data, by bringing significant contributions to the understanding of differentiation’s dynamics in the context of healthy and pathological human airway epithelium, may lead to the identification of novel therapeutic targets.

Les diatomées sont des micro-algues unicellulaires, qui jouent un rôle primordial dans l’eco-système marin. En effet, elles sont responsables de 20% de l’activité photosynthétique sur Terre, et sont à la base de la chaîne alimentaire marine, toujours plus menacée par le changement climatique. Les diatomées établissent diverses interactions microbiennes avec des organismes issus de l’ensemble de l’arbre du vivant, à travers des méchanismes complexes tels que la symbiose, le parasitisme ou la compétition. L’objectif de ma thèse a été de comprendre comment ces interactions structurent la communauté du plancton, à grande échelle spatiale. Pour ce faire, j’ai développé de nouvelles approches basées sur le jeu de données inédit de Tara Océans, une expédition mondiale qui a exploré la diversité et les fonctions des microbes marins, en récoltant plus de 40.000 échantillons à travers 210 sites autour du monde. Grâce à l’analyse de réseaux de co-occurrence microbiens, je montre d’une part que les diatomées agissent comme des « ségrégateurs répulsifs » à l’échelle globale, en particulier envers les organismes potentiellement dangeureux tels que les prédateurs et les parasites, et d’autre part que la co-occurrence des espèces ne s’explique qu’en minorité par les facteurs environnementaux. Grâce à la richesse des données Tara Océans, j’ai par ailleurs permis la charactérisation d’une interaction biotique impliquant une diatomée et un cilié hétérotrophe à l’échelle de l’eco-système, illustrant de surcroît le succès des approches dirigées par les données. Dans l’ensemble, ma thèse contribue à notre compréhension des interactions biotiques impliquant les diatomées, de l’échelle globale à la cellule unique. / Diatoms are unicellular photosynthetic microeukaryotes that play a critical role in the functioning of marine ecosystems. They are responsible for 20% of global photosynthesis on Earth and lie at the base of marine food webs, ever more threatened by climate change.Diatoms establish microbial interactions with numerous organisms across the whole tree of life, through complex mechanisms including symbiosis, parasitism and competition. The goal of my thesis was to understand how those biotic interactions structure the planktonic community at large spatial scales, by using new approaches based on the unprecedented Tara Oceans dataset, a unique and worldwide circumnavigation that collected over 40.000 samples across 210 sites to explore the diversity and functions of marine microbes. Through the analysis of microbial association networks, I show that diatoms act as repulsive segregators in the ocean, in particular towards potentially harmful organisms such as predators as well as parasites, and that species co-occurrence is driven by environmental factors in a minority of cases. By leveraging the singularity of the Tara Oceans data, I provide a comprehensive characterization of a prevalent biotic interaction between a diatom and heterotrophic ciliates at large spatial scale, illustrating the success of data-driven research. Overall, my thesis contributes to our understanding of diatom biotic interactions, from the global patterns to the single cell.

Metabolic heterogeneity (MH) occurs when isogenic microbial populations display cell-to-cell differences in metabolic traits, albeit exposed to homogeneous conditions. Despite the increasing focus on MH, its triggering factors remain largely unknown. In the present thesis, I used stable isotope probing and chemical imaging with nanoscale Secondary Ion Mass Spectrometry (nanoSIMS) to study MH at single-cell level, in model organisms, synthetic and natural communities, to understand i) how abiotic factors, biotic interactions and antibiotics exposure influence MH and ii) its potential ecological role. Moreover, I optimized sample preparation for chemical and high-resolution imaging and suggested two different indices as ‘unit measure’ of MH. As results, I have shown for the first time that MH is displayed by microorganisms under favorable growth conditions, although none of the tested abiotic factors prevailed as the main trigger of MH. I brought insights on how biotic interactions play a role in the functional heterogeneity using bacteria pseudo-fungi co-cultures. I found that antibiotics reduce Carbon and Nitrogen assimilation rates of targeted phylogenetic groups in river-water communities, while increasing their MH, pointing to its ecological importance in natural environments. To conclude, I provided novel insights on the phenomenon of MH and its dynamics at different ecological scales.:Abbreviation list Summary Introduction Knowledge gaps Results and discussion - Optimization of sample preparation - Validation of quantitation methods - Abiotic factors shaping metabolic heterogeneity in bacterial populations - Influence of biotic factors in shaping heterogeneity - Metabolic Heterogeneity and ecophysiology of natural microbial populations influenced by emerging contaminants Conclusions Outlook Bibliography Appendix Acknowledgments Curriculum Vitae List of publications

Models using 3D cell culture techniques are increasingly accepted as the most biofidelic in vitro representations of tissues for research. These models are generated using biomatrices and bulk populations of cells derived from tissues or cell lines. This thesis study focuses on an alternate method to culture individually selected cells in relative isolation from the rest of the population under physiologically relevant matrix conditions. Matrix gel islands are spotted on a cell culture dish to act as support for receiving and culturing individual single cells; a glass capillary-based microfluidic setup is used to extract each desired single cell from a population and seed it on top of an island. Using examples of breast and colorectal cancers, we show that individual cells evolve into tumors or aspects of tumors displaying different characteristics of the initial cancer type and aggressiveness. By implementing a morphometry assay with luminal A breast cancer, we demonstrate the potential of the proposed approach to studying phenotypic heterogeneity. Results reveal that intertumor heterogeneity increases with time in culture and that varying degrees of intratumor heterogeneity may originate from individually seeded cells. Moreover, we observe a positive correlation between fast-growing tumors and the size and heterogeneity of their nuclei.

Interactions of cells with their environment regulate important cellular functions and are required for the organization of cells into tissues and complex organisms. These interactions involve different types of adhesion receptors. Interactions with extracellular matrix (ECM) proteins are mainly mediated by the integrin family of adhesion molecules. Situations in which integrin-ECM interactions are deregulated cause diseases and play a crucial role in cancer cell invasion. Thus, the mechanisms underlying integrin-binding and regulation are of high interest, particularly at the molecular level. How can cell-ECM interactions be studied? While there are several methods to analyze cell adhesion, few provide quantitative data on adhesion forces. One group, single-cell force spectroscopy (SCFS), quantifies adhesion at the single-cell level and can therefore differentiate the adhesive properties of individual cells. One implementation of SCFS is based on atomic force microscopy (AFM); this technique has been employed in the presented work. Advantageously AFM-SCFS combines high temporal and spatial cell manipulation, the ability to measure a large range of adhesion forces and sufficiently high-force resolution to allow the study of single-molecule binding events in the context of a living cell. Since individual adhesion receptors can be analyzed within their physiological environment, AFM-SCFS is a powerful tool to study the mechanisms underlying integrin-regulation. The presented work is split into six chapters. Chapter one gives background information about cell-ECM interactions. In chapter two, different adhesion assays are compared and contrasted. The theoretical Bell-Evans model which is used to interpret integrin-mediated cell adhesion is discussed in chapter three. Thereafter, the three projects that form the core of the thesis are detailed in chapters four through six. In the first project (chapter 4), α2β1-integrin mediated cell adhesion to collagen type I, the most abundant structural protein in vertebrates, was quantified using CHO cells. Firstly, α2β1-collagen interactions were investigated at the single-molecule level. Dynamic force spectroscopy permitted calculation of bond specific parameters, such as the bond dissociation rate koff (1.3 ± 1.3 sec-1) and the barrier width xu (2.3 ± 0.3 Å). Next, α2β1-integrin mediated cell adhesion to collagen type I was monitored over contact times between 0 and 600 sec. Thereby the kinetics of α2β1-integrin mediated interactions was explored and insights into the underlying binding mechanisms were gained. In the second project (chapter five), effects of cryptic integrin binding sites within collagen type I exerted on pre-osteoblasts were investigated. Collagen type I matrices were thermally denatured which lead to exposure of cryptic RGD (Arg-Gly-Asp)-motifs. As a consequence pre-osteoblasts enhanced their adhesion to denatured collagen. Compared to native collagen type I, adhesion to denatured collagen was mediated by a different set of integrins, including αv- and α5β1-integrins. Cells grown on denatured collagen showed enhanced spreading and motility, which correlated with increased focal adhesion kinase phosphorylation levels. Moreover, osteogenic differentiation kinetics and differentiation potential were increased on denatured collagen. The findings of this project open new perspectives for optimization of tissue engineering substrates. In the third part (chapter six), the effect of the fusion protein BCR/ABL, a hallmark of chronic myeloid leukemia, on adhesion of myeloid progenitor cells was studied. Adhesion between BCR/ABL transformed progenitor cells to bone marrow derived stromal cells and to different ECM proteins was quantitatively compared to that of control cells. The tyrosine kinase activity of BCR/ABL enhanced cell adhesion, which was blocked by imatinib mesylate, a drug interfering with BCR/ABL activity. BCR/ABL-enhanced adhesion correlated with increased β1-integrin cell surface concentrations. Since adhesion of leukemic cells to the bone marrow compartment is critical for the development of drug resistance, the reported results may provide a basis for optimized target therapies. In the three described projects AFM-based SCFS was applied to investigate early steps of integrin-mediated adhesion at the molecular level. Taken together, the results demonstrate that AFM-SCFS is a versatile tool that permits monitoring of cell adhesion from single-molecule interactions to the formation of more complex adhesion sites at the force level. / Interaktionen zwischen Zellen und ihrer Umgebung sind maßgeblich an der Regulierung zellulärer Funktionen beteiligt und daher notwendig für die Organisation von Zellen in Geweben und komplexen Organismen. Zellinteraktionen mit der extrazellulären Matrix (EZM) werden hauptsächlich durch Integrine vermittelt. Situationen, in denen Integrin- EZM Interaktionen verändert sind, können Krankheiten verursachen und spielen zudem eine wichtige Rolle bei der Invasion von Krebszellen. Daher besteht ein großes Interesse darin, die molekularen Mechanismen, die Integrin-EZM Interaktionen regulieren, besser zu verstehen. Wie können Zell-EZM Interaktionen untersucht werden? Obwohl es mehrere Methoden gibt, mit denen Zelladhäsion untersucht werden kann, sind die wenigsten dazu geeignet, Zelladhäsionskräfte zu quantifizieren. Einzelzellspektroskopie erfasst die Adhäsionskräfte einzelner Zellen quantitativ und ermöglicht dadurch eine differenzierte Betrachtung der Adhäsion individueller Zellen. Eine Variante der Einzelzellspektroskopie basiert auf der Rasterkraftmikroskopie (AFM); diese Technik wurde in der vorliegenden Arbeit verwendet. Ein Vorteil von AFM- Einzelzellspektroskopie besteht darin, dass Zellen mit hoher zeitlicher und räumlicher Präzision manipuliert werden können. Zelladhäsionskräfte können zudem über einen großen Kraftbereich hinweg untersucht werden. Dabei ermöglicht es die hohe Kraftauflösung, einzelne Integrin-Ligandenbindungen in lebenden Zellen zu untersuchen. Die vorliegende Arbeit gliedert sich in sechs Kapitel. Kapitel eins gibt Hintergrundinformationen über Zell-EZM Wechselwirkungen. In Kapitel zwei werden verschiedene Adhäsionsassays einander gegenüber gestellt. Das theoretische Bell-Evans Modell, mit dessen Hilfe die gewonnenen Daten interpretiert wurden, wird in Kapitel drei diskutiert. Im Anschluss werden drei Projekte, welche das Herzstück dieser Doktorarbeit bilden, in Kapiteln vier bis sechs näher ausgeführt. Im ersten Projekt (Kapitel vier) wurde die Adhäsion von α2β1-Integrin exprimierenden CHO Zellen zu Kollagen I, dem häufigsten strukturellen Protein in Wirbeltieren, quantitativ untersucht. Zunächst wurden α2β1-Kollagen-Interaktionen auf Einzelmolekülebene analysiert. Mithilfe der dynamischen Kraftspektroskopie wurden für diese Bindung Dissoziationsrate koff (1.3 ± 1.3 sec-1) und Potentialbarrierenbreite xu (2.3 ± 0.3 Å) bestimmt. Daraufhin wurde die α2β1-vermittelte Adhäsion über einen Zeitraum von zehn Minuten untersucht. Dadurch konnten Einblicke in die Kinetik von α2β1-integrin vermittelter Zelladhäsion sowie in die zugrunde liegenden Regulationsmechanismen gewonnen werden. Im zweiten Projekt (Kapitel fünf) wurde die Rolle von kryptischen Integrin-Bindungsstellen in Kollagen I untersucht. Die zuvor verwendeten Kollagenoberflächen wurden thermisch denaturiert, wodurch versteckte RGD (Arg-Gly-Asp)-Sequenzen freigelegt wurden. Die partielle Denaturierung hatte- verglichen mit nativem Kollagen I- eine erhöhte Adhäsion von Präosteoblasten (MC3T3-E1) zur Folge, was auf das Binden zusätzlicher Integrine zurückgeführt wurde. Im Unterschied zu nativem Kollagen wurde die Zelladhäsion zu denaturiertem Kollagen I u.a. durch αv- and α5β1-Integrine vermittelt. Präosteoblasten zeigten verstärktes Zellspreiten sowie höhere Motilität auf denaturiertem Kollagen I; zudem wurde ein erhöhtes Differenzierungpotential der Präosteoblasten festgestellt. Die in diesem Projekt erhaltenen Einblicke bilden eine hilfreiche Basis für die Entwicklung optimierter Oberflächen für diverse Zell- und Gewebekulturanwendungen. Im dritten Projekt (Kapitel sechs) wurde der Einfluss des Fusionproteins BCR/ABL, charakteristisch für chronische myeloische Leukämie, auf die Adhäsion von myeloischen Vorläuferzellen untersucht. Dazu wurde die Adhäsion von BCR/ABL transformierten Vorläuferzellen (32D Zellen) bzw. Kontrollzellen zu Stromazellen (M2-10B4) sowie verschiedenen EZM Proteinen untersucht. BCR/ABL erhöhte die Zelladhäsion der myeloischen Vorläuferzellen signifikant. Dieser Effekt wurde durch die Zugabe von Imatinib, welches die Tyrosinkinaseaktivität von BCR/ABL inhibiert, aufgehoben. Die BCR/ABL-verstärkte Zelladhäsion korrelierte mit erhöhten β1-Integrin-konzentrationen. Da die Adhäsion von Leukämiezellen im Knockenmark bekanntermaßen kritisch für die Entwicklung von Resistenzen gegenüber verschiedenen Wirkstoffen ist, könnten die Ergebnisse dieser Studie eine Grundlage für die Entwicklung optimierter Target-Therapien sein. In den drei beschriebenen Projekten wurde AFM Einzelzellspektroskopie verwendet, um Integrin- vermittelte Adhäsion auf molekularer Ebene zu untersuchen. Die Ergebnisse zeigen, dass AFM-Einzelzellspektroskopie ein vielseitiges Werkzeug darstellt, das überaus geeignet dazu ist, Zelladhäsion- ausgehend von Einzelmolekülinteraktionen bis hin zur Entstehung komplexerer Adhäsionsstellen- auf der Kraftebene zu verfolgen.

The mortality rate is high for cancer patients and treatments are only efficient in a fraction of patients. To be able to cure more patients, new treatments need to be invented. Immunotherapy activates the immune system to fight against cancer and one treatment targets immune checkpoints. If more targets are found, more patients can be treated successfully. In this project, interactions between immune and cancer cells that drive tumour growth were investigated in an attempt to find new potential targets. This was achieved by creating a machine learning model that finds genes expressed in cells involved in tumour-driving interactions. Single-cell RNA sequencing and spatial transcriptomic data from breast cancer patients were utilised as well as single-cell RNA sequencing data from healthy patients. The tumour rate was based on the cumulative expression of G2/M genes. The G2/M related genes were excluded from the analysis since these were assumed to be cell cycle genes. The machine learning model was based on a supervised variational autoencoder architecture. By using this kind of architecture, it was possible to compress the input into a low dimensional space of genes, called a latent space, which was able to explain the tumour rate. Optuna hyperparameter optimizer framework was utilised to find the best combination of hyperparameters for the model. The model had a R2 score of 0.93, which indicated that the latent space was able to explain the growth rate 93% accurately. The latent space consisted of 20 variables. To find out which genes that were in this latent space, the correlation between each latent variable and each gene was calculated. The genes that were positively correlated or negatively correlated were assumed to be in the latent space and therefore involved in explaining tumour growth. Furthermore, the correlation between each latent variable and the growth rate was calculated. The up- and downregulated genes in each latent variable were kept and used for finding out the pathways for the different latent variables. Five of these latent variables were involved in immune responses and therefore these were further investigated. The genes in these five latent variables were mapped to cell types. One of these latent variables had upregulated immune response for positively correlated growth, indicating that immune cells were involved in promoting cancer progression. Another latent variable had downregulated immune response for negatively correlated growth. This indicated that if these genes would be upregulated instead, the tumour would be thriving. The genes found in these latent variables were analysed further. CD80, CSF1, CSF1R, IL26, IL7, IL34 and the protein NF-kappa-B were interesting finds and are known immune-modulators. These could possibly be used as markers for pro-tumour immunity. Furthermore, CSF1, CSF1R, IL26, IL34 and the protein NF-kappa-B could potentially be targeted in immunotherapy.