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Single-cell RNA-sequencing makes possible to study the gene expression at the level of individual cells. However, one of the main challenges of the single-cell RNA-sequencing analysis today, is the identification and annotation of cell types. The current method consists in manually checking the expression of genes using top differentially expressed genes and comparing them with related cell-type markers available in scientific publications. It is therefore time-consuming and labour intensive. Nevertheless, in the last two years,numerous automatic cell-type identification and annotation tools which use different strategies have been created. But, the lack of specific comparisons of those tools in the literature and especially for immuno-oncologic and oncologic purposes makes difficult for laboratories and companies to know objectively what are the best tools for annotating cell types. In this project, a review of the current tools and an evaluation of R tools were carried out.The annotation performance, the computation time and the ease of use were assessed. After this preliminary results, the best selected R tools seem to be ClustifyR (fast and rather precise) and SingleR (precise) for the correlation-based tools, and SingleCellNet (precise and rather fast) and scPred (precise but a lot of cell types remains unassigned) for the supervised classificationtools. Finally, for the marker-based tools, MAESTRO and SCINA are rather robust if they are provided with high quality markers.

Cancer progression is accompanied with alterations in the cell biomechanical phenotype, including changes in cell structure, morphology, and responses to microenvironmental stress. These alterations result in an increased deformability of transformed cells and reduced resistance to mechanical stimuli, enabling motility and invasion. Therefore, single cell biomechanical properties could be served as a powerful label-free biomarker for effective characterization and early detection of single cancer cells. Advances and innovations in microsystems and nanotechnology have facilitated interrogation of the biomechanical properties of single cells to predict their tumorigenicity, metastatic potential, and health state. This dissertation utilized Atomic Force Microscopy (AFM) for the cell biomechanical phenotyping for cancer diagnosis and early detection, efficacy screening of potential chemotherapeutic agents, and also cancer stem-like/tumor initiating cells (CSC/TICs) characterization as the critical topics received intensive attention in the search for effective cancer treatment. Our findings demonstrated the capability of exogenous sphingosine to revert the aberrant biomechanics of aggressive cells and showed a unique, mechanically homogeneous, and extremely soft characteristic of CSC/TICs, suitable for their targeted isolation. To make full use of cell biomechanical cues, this dissertation also considered the application of nonlinear viscoelastic models such as Fractional Zener and Generalized Maxwell models for the naturally complex, heterogeneous, and nonlinear structure of living cells. The emerging need for a high-throughput clinically relevant alternative for evaluating biomechanics of individual cells led us to the development of a microfluidic system. Therefore, a high-throughput, label-free, automated microfluidic chip was developed to investigate the biophysical (biomechanical-bioelectrical) markers of normal and malignant cells. Most importantly, this dissertation also explored the biomechanical response of cells upon a dynamic loading instead of a typical transient stress. Notably, metastatic and non-metastatic cells subjected to a pulsed stress regimen exerted by AFM exhibited distinct biomechanical responses. While non-metastatic cells showed an increase in their resistance against deformation and resulted in strain-stiffening behavior, metastatic cells responded by losing their resistance and yielded slight strain-softening. Ultimately, a second generation microfluidic chip called an iterative mechanical characteristics (iMECH) analyzer consisting of a series of constriction channels for simulating the dynamic stress paradigm was developed which could reproduce the same stiffening/softening trends of non-metastatic and metastatic cells, respectively. Therefore, for the first time, the use of dynamic loading paradigm to evaluate cell biomechanical responses was used as a new signature to predict malignancy or normalcy at a single-cell level with a high (~95%) confidence level. / Ph. D.

Bioimpedance presents a versatile, label-free means of monitoring biological cells and their responses to physical, chemical and biological stimuli. Breast cancer is the second most common type of cancer among women in the United States. Although significant progress has been made in diagnosis and treatment of this disease, there is a need for robust, easy-to-use technologies that can be used for the identification and discrimination of critical subtypes of breast cancer in biopsies obtained from patients. This dissertation makes contributions in three major areas towards addressing the goal. First, we developed miniaturized bioimpedance sensors using MEMS and microfluidics technology that have the requisite traits for clinical use including reliability, ease-of-use, low-cost and disposability. Here, we designed and fabricated two types of bioimpedance sensors. One was based on electric cell-substrate impedance sensing (ECIS) to monitor cell adhesion based events and the other was a microfluidic device with integrated microelectrodes to examine the biophysical properties of single cells. Second, we examined a panel of triple negative breast cancer (TNBC) cell lines and a hormone therapy resistant model of breast cancer in order to improve our understanding of the bioimpedance spectra of breast cancer subtypes. Third, we explored strategies to improve the sensitivity of the microelectrodes to bioimpedance measurements from breast cancer cells. We investigated nano-scale coatings on the surface of the electrode and geometrical variations in a branched electrode design to accomplish this. This work demonstrates the promise of bioimpedance technologies in monitoring diseased cells and their responses to pharmaceutical agents, and motivates further research in customization of this technique for use in personalized medicine. / Ph. D.

Gene expression regulation is dynamic and specific to various factors such as developmental stages, environmental conditions, and stimulation of pathogens. Nowadays, a tremendous amount of transcriptome data sets are available from diverse species. This trend enables us to perform comparative transcriptome analysis that identifies conserved or diverged gene expression responses across species using transcriptome data. The goal of this dissertation is to develop and apply approaches of comparative transcriptomics to transfer knowledge from model species to non-model species with the hope that such an approach can contribute to the improvement of crop yield and human health. First, we presented a comprehensive method to identify cross-species modules between two plant species. We adapted the unsupervised network-based module finding method to identify conserved patterns of co-expression and functional conservation between Arabidopsis, a model species, and soybean, a crop species. Second, we compared drought-responsive genes across Arabidopsis, soybean, rice, corn, and Populus in order to explore the genomic characteristics that are conserved under drought stress across species. We identified hundreds of common gene families and conserved regulatory motifs between monocots and dicots. We also presented a BLS-based clustering method which takes into account evolutionary relationships among species to identify conserved co-expression genes. Last, we analyzed single-cell RNA-seq data from monocytes to attempt to understand regulatory mechanism of innate immune system under low-grade inflammation. We identified novel subpopulations of cells treated with lipopolysaccharide (LPS), that show distinct expression patterns from pro-inflammatory genes. The data revealed that a promising therapeutic reagent, sodium 4-phenylbutyrate, masked the effect of LPS. We inferred the existence of specific cellular transitions under different treatments and prioritized important motifs that modulate the transitions using feature selection by a random forest method. There has been a transition in genomics research from bulk RNA-seq to single-cell RNA-seq, and scRNA-seq has become a widely used approach for transcriptome analysis. With the experience we gained by analyzing scRNA-seq data, we plan to conduct comparative single-cell transcriptome analysis across multiple species. / Doctor of Philosophy / All cells in an organism have the same set of genes, but there are different cell types, tissues, organs with different functions as the organism ages or under different conditions. Gene expression regulation is one mechanism that modulates complex, dynamic, and specific changes in tissues or cell types for any living organisms. Understanding gene regulation is of fundamental importance in biology. With the rapid advancement of sequencing technologies, there is a tremendous amount of gene expression data (transcriptome) from individual species in public repositories. However, major studies have been reported from several model species and research on non-model species have relied on comparison results with a few model species. Comparative transcriptome analysis across species will help us to transform knowledge from model species to non-model species and such knowledge transfer can contribute to the improvement of crop yields and human health. The focus of my dissertation is to develop and apply approaches for comparative transcriptome analysis that can help us better understand what makes each species unique or special, and what kinds of common functions across species have been passed down from ancestors (evolutionarily conserved functions). Three research chapters are presented in this dissertation. First, we developed a method to identify groups of genes that are commonly co-expressed in two species. We chose seed development data from soybean with the hope to contribute to crop improvement. Second, we compared gene expression data across five plant species including soybean, rice, and corn to provide new perspectives about crop plants. We chose drought stress to identify conserved functions and regulatory factors across species since drought stress is one of the major stresses that negatively impact agricultural production. We also proposed a method that groups genes with evolutionary relationships from an unlimited number of species. Third, we analyzed single-cell RNA-seq data from mouse monocytes to understand the regulatory mechanism of the innate immune system under low-grade inflammation. We observed how innate immune cells respond to inflammation that could cause no symptoms but persist for a long period of time. Also, we reported an effect of a promising therapeutic reagent (sodium 4-phenylbutyrate) on chronic inflammatory diseases. The third project will be extended to comparative single-cell transcriptome analysis with multiple species.

[ES] La introducción de la secuenciación de ARN a nivel de célula única (scRNA-seq) en el ámbito de la transcriptómica ha redefinido nuestro entendimiento de la diversidad celular, arrojando luz sobre los mecanismos subyacentes a la heterogeneidad tisular. No obstante, al inicio de esta tesis, las limitaciones de a esta tecnología obstaculizaban su aplicación en el estudio de procesos complejos, entre ellos el splicing alternativo. A pesar de ello, los patrones de splicing a nivel celular planteaban incógnitas que esta tecnología tenía el potencial de resolver: ¿es posible observar, a nivel celular, la misma diversidad de isoformas que se detecta mediante RNA-seq a nivel de tejido? ¿Qué función desempeñan las isoformas alternativas en la constitución de la identidad celular? El objetivo de esta tesis es desbloquear el potencial del scRNA-seq para el análisis de isoformas, abordando sus dificultades técnicas y analíticas mediante el desarrollo de nuevas metodologías computacionales. Para lograrlo, se trazó una hoja de ruta con tres objetivos. Primero, se establecieron cuatro requisitos para el estudio de las isoformas mediante scRNA-seq, llevando a cabo una revisión de la literatura existente para evaluar su cumplimiento. Tras completar este marco con simulaciones computacionales, se identificaron las debilidades y fortalezas de los métodos de scRNA-seq y las herramientas computacionales disponibles. Durante la segunda etapa de la investigación, estos conocimientos se utilizaron para diseñar un protocolo óptimo de procesamiento de datos de scRNA-seq. En concreto, se integraron datos de lecturas largas a nivel de tejido con datos de scRNA-seq para garantizar una identificación adecuada de las isoformas así como su cuantificación a nivel celular. Este proceso permitió ampliar las estrategias computacionales disponibles para la reconstrucción de transcriptomas a partir de lecturas largas, mejoras que fueron implementadas en SQANTI3, software de referencia en transcriptómica. Por último, los datos procesados se utilizaron para desarrollar un nuevo método de análisis de co-expresión de isoformas a fin de desentrañar redes de regulación del splicing alternativo implicadas en la constitución de la identidad celular. Dada la elevada variabilidad de los datos de scRNA-seq, este método se basa en la utilización de una estrategia de correlación basada en percentiles que atenúa el ruido técnico y permite la identificación de grupos de isoformas co-expresadas. Una vez configurada la red de co-expresión, se introdujo una nueva estrategia de análisis para la detección de patrones de co-utilización de isoformas que suceden de forma independiente a la expresión a nivel de gen, denominada co-Differential Isoform Usage. Este enfoque facilita la identificación de una capa de regulación de la identidad celular atribuible únicamente a mecanismos post-transcripcionales. Para una interpretación biológica más profunda, se aplicó una estrategia de anotación computacional de motivos y dominios funcionales en las isoformas definidas con lecturas largas, revelando las propiedades biológicas de las isoformas involucradas en la red de co-expresión. Estas investigaciones culminan en el lanzamiento de acorde, un paquete de R que encapsula las diferentes metodologías desarrolladas en esta tesis, potenciando la reproducibilidad de sus resultados y proporcionando una nueva herramienta para explorar la biología de las isoformas alternativas a nivel de célula única. En resumen, esta tesis describe una serie de esfuerzos destinados a desbloquear el potencial de los datos de scRNA-seq para avanzar en la comprensión del splicing alternativo. Desde un contexto de escasez de herramientas y conocimiento previo, se han desarrollado soluciones de análisis innovadoras que permiten la aplicación de scRNA-seq al estudio de las isoformas alternativas, proporcionando recursos innovadores para profundizar en la regulación post-transcripcional y la función celular. / [CA] La introducció de la seqüenciació d'ARN a escala de cèl·lula única (scRNA-seq) en l'àmbit de la transcriptòmica ha redefinit el nostre enteniment de la diversitat cel·lular, projectant llum sobre els mecanismes subjacents a l'heterogeneïtat tissular. Malgrat les limitacions inicials d'aquesta tecnologia, especialment en el context de processos complexos com l'splicing alternatiu, els patrons d'splicing a escala cel·lular plantejaven incògnites amb potencial de resolució: és possible observar, a escala cel·lular, la mateixa diversitat d'isoformes que es detecta mitjançant RNA-seq en teixits? Quina funció tenen les isoformes alternatives en la constitució de la identitat cel·lular? L'objectiu d'aquesta tesi és desbloquejar el potencial del scRNA-seq per a l'anàlisi d'isoformes alternatives, abordant les seues dificultats tècniques i analítiques amb noves metodologies computacionals. Per a això, es va traçar una ruta amb tres objectius. Primerament, es van establir quatre requisits per a l'estudi de les isoformes mitjançant scRNA-seq, amb una revisió de la literatura existent per avaluar-ne el compliment. Després de completar aquest marc amb simulacions computacionals, es van identificar les debilitats i fortaleses dels mètodes de scRNA-seq i de les eines computacionals disponibles. Durant la segona etapa de la investigació, aquests coneixements es van utilitzar per dissenyar un protocol òptim de processament de dades de scRNA-seq. En concret, es van integrar dades de lectures llargues a escala de teixit amb dades de scRNA-seq per a garantir una identificació adequada de les isoformes així com la seua quantificació a escala cel·lular. Aquest procés va permetre ampliar les estratègies computacionals disponibles per a la reconstrucció de transcriptomes a partir de lectures llargues, millores que van ser implementades en SQANTI3, un programari de referència en transcriptòmica. Finalment, les dades processades es van fer servir per a desenvolupar un nou mètode d'anàlisi de coexpressió d'isoformes amb l'objectiu de desentranyar xarxes de regulació de l'splicing alternatiu implicades en la constitució de la identitat cel·lular. Donada l'elevada variabilitat de les dades de scRNA-seq, aquest mètode es basa en la utilització d'una estratègia de correlació basada en percentils que minimitza el soroll tècnic i permet la identificació de grups d'isoformes coexpressades. Un cop configurada la xarxa de coexpressió, es va introduir una nova estratègia d'anàlisi per a la detecció de patrons de co-utilització d'isoformes que succeeixen de forma independent a l'expressió del seu gen, denominada co-Differential Isoform Usage. Aquest enfocament facilita la identificació d'una capa de regulació de la identitat cel·lular atribuïble únicament a mecanismes post-transcripcionals. Per a una interpretació biològica més profunda, es va aplicar una estratègia d'anotació computacional de motius i dominis funcionals en les isoformes definides amb lectures llargues, revelant les propietats biològiques de les isoformes involucrades en la xarxa de coexpressió. Aquestes investigacions culminen en el llançament d'acorde, un paquet de R que encapsula les diferents metodologies desenvolupades en aquesta tesi, potenciant la reproducibilitat dels seus resultats i proporcionant una nova eina per a explorar la biologia de les isoformes alternatives a escala de cèl·lula única. En resum, aquesta tesi descriu una sèrie d'esforços destinats a desbloquejar el potencial de les dades de scRNA-seq per a avançar en la comprensió de l'splicing alternatiu. Des d'un context de manca d'eines i coneixement previ, s'han desenvolupat solucions d'anàlisi innovadores que permeten l'aplicació de scRNA-seq a l'estudi de les isoformes alternatives, proporcionant recursos innovadors per a aprofundir en la regulació post-transcripcional i la funció cel·lular. / [EN] In the world of transcriptomics, the emergence of single-cell RNA sequencing (scRNA-seq) ignited a revolution in our understanding of cellular diversity, unraveling novel mechanisms in tissue heterogeneity, development and disease. However, when this thesis began, using scRNA-seq to understand Alternative Splicing (AS) was a challenging frontier due the inherent limitations of the technology. In spite of this research gap, pertinent questions persisted regarding cell-level AS patterns, particularly concerning the recapitulation of isoform diversity observed in bulk RNA-seq data at the cellular level and the roles played by cell and cell type-specific isoforms. The work conducted in the present thesis aims to harness the potential of scRNA-seq for alternative isoform analysis, outlining technical and analytical challenges and designing computational methods to overcome them. To achieve this, we established a roadmap with three main aims. First, we set requirements for studying isoforms using scRNA-seq and conducted an extensive review of existing research, interrogating whether these requirements were met. Combining this acquired knowledge with several computational simulations allowed us to delineate the strengths and pitfalls of available data generation methods and computational tools. During the second research stage, this insight was used to design a suitable data processing pipeline, in which we jointly employed bulk long-read and short-read scRNA-seq sequenced from full-length cDNAs to ensure adequate isoform reconstruction as well as sensitive cell-level isoform quantification. Additionally, we refined available transcriptome curation strategies, introducing them as innovative modules in the transcriptome quality control software SQANTI3. Lastly, we harnessed single-cell isoform expression data and the rich biological diversity inherent in scRNA-seq, encompassing various cell types, in the design of a novel isoform co-expression analysis method. Percentile correlations effectively mitigated single-cell noise, unveiling clusters of co-expressed isoforms and exposing a layer of regulation in cellular identity that operated independently of gene expression. We additionally introduced co-Differential Isoform Usage (coDIU) analysis, enhancing our ability to interpret isoform cluster networks. This endeavour, combined with the computational annotation of functional sites and domains in the long read-defined isoform models, unearthed a distinctive functional signature in coDIU genes. This research effort materialized in the release of acorde, an R package that encapsulates all analyses functionalities developed throughout this thesis, providing a reproducible means for the scientific community to further explore the depths of alternative isoform biology within single-cell transcriptomics. This thesis describes a complex journey aimed at unlocking the potential of scRNA-seq data for investigating AS and isoforms: from a landscape marked by the scarcity of tools and guidelines, towards the development of novel analysis solutions and the acquisition of valuable biological insight. In a swiftly evolving field, our methodological contributions constitute a significant leap forward in the application of scRNA-seq to the study of alternative isoform expression, providing innovative resources for delving deeper into the intricacies of post-transcriptional regulation and cellular function through the lens of single-cell transcriptomics. / The research project was funded by the BIO2015-71658 and BES-2016-076994 grants awarded by the Spanish Ministry of Science and Innovation / Arzalluz Luque, Á. (2024). Understanding Isoform Expression and Alternative Splicing Biology through Single-Cell RNAseq [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203888

Primär kutane Lymphome sind typische Krankheitsbilder in der Dermatologie. Obwohl diese Erkrankungen zu den seltenen Krankheiten zählen, sind sie jedoch von therapeutischem und wissenschaftlichen Interesse. Der erste Teil der Arbeit beschäftigt sich mit der Klassifikation und Therapie primär kutaner Lymphome. Die 1997 veröffentlichte EORTC-Klassifikation wird mit ihren wichtigsten Entitäten erläutert. Die EORTC-Klassifikation geht auf spezifische Besonderheiten der primär kutanen Lymphome ein und orientiert sich an der guten Prognose dieser Erkrankungen. Therapeutische Strategien wie der Einsatz von für kutane Lymphome typische Behandlungsmethoden (PUVA, Exzision, Radiatio) als auch gentechnisch hergestellte Medikamente wie therapeutische Antikörper und Vakzinen werden erklärt. Der zweiten Teil der Habilitationsschrift konzentriert sich auf experimentelle Arbeiten zur molekularbiologischen Untersuchung von primär kutanen Lymphomen. Im Mittelpunkt steht die Methode der Mikromanipulation und Einzelzell-PCR. Für die Mykosis fungoides konnte gezeigt werden, daß im initialen Ekzemstadium nur wenige klonale maligne T-Zellen in der Probe nachzuweisen sind. Mit Zunahme des Infiltrates (Plaque) sind die malignen Zellen in der Epidermis oder gruppiert in der Dermis lokalisiert. Im Tumorstadium dominieren die malignen Zellen das dermale Infiltrat (Gellrich S, J Invest Dermatol, 2000). Die Tumorzellen primär kutaner B-Zell-Lymphome weisen einen dem Keimzentrum ähnlichen Mutationsstatus, nämlich somatische Mutationen und intraklonale Diversifikation, auf (Gellrich S, J Invest Dermatol, 1997; Gellrich S, J Invest Dermatol, 2001). Die Daten sprechen für einen noch aktiven Mutationsmechanismus, sogenannte ongoing mutations (Golembowski S, Immunobiology, 2000). Eine Unterform der kutanen Lymphome stellen die primär kutanen CD30+ T-Zell Lymphome dar. In Untersuchungen mittels Mikromanipulation und Einzelzell-PCR wurden CD30+ Zellen aus primär kutanen CD30+ großzelligen Lymphomen hinsichtlich ihrer T-Zell-Klonalität untersucht. Dabei stellte sich heraus, daß nicht alle atypischen Zellen zur Tumorpopulation gehören. Es wird vermutet, daß ein unbekannter Stimulus zur Ausprägung der Zellmorphe und zur Expression des CD30-Moleküls führt (Gellrich S, J Invest Dermatol, 2003). Eine weitere Entität, bei welcher CD30+ Zellen eine Rolle spielen, ist die lymphomatoide Papulose. In den hier dargestellten Untersuchungen wurden CD30+ große atypische Zellen einzeln isoliert und anschließend mittels PCR für die Gene des T-Zell-Rezeptor-Gamma und des Immunglobulinrezeptors amplifiziert bei einem Patienten mit lymphomatoider Papulose und assoziierter Morbus Hodgkin-Erkankung. In zwei von drei Fällen waren diese CD30+ Zellen polyklonal. Die aus der Fragmentanalyse bekannte klonale T-Zell-Population konnte dagegen in CD3+CD30- kleinen Zellen gefunden werden. In einem dritten Fall enthielten die CD30+ Zellen klonale B-Zellen, welche die gleichen Immunglobulingene rearrangiert hatten wie Zellen aus einem zuvor bestehenden Hodgkin-Lymphom desselben Patienten. Diese Ergebnisse lassen vermuten, dass es für das Aufschießen und die Regredienz der Läsionen der lymphomatoiden Papulose einen Stimulus gibt und die klonalen T- und B-Zellen als Begleitinfiltrat ohne pathologische Bedeutung anzusehen sind. Insgesamt bilden die Daten dieser Arbeit eine Grundlage für eine Fortsetzung der Untersuchung zur Ätiopathogenese von primär kutanen Lymphomen und deren Therapie und bieten die Möglichkeiten vielfältiger wissenschaftlicher Kooperationen. / Primary cutaneous lymphomas present with typical clinical features in dermatology. Although these diseases are rare, they particularly are of scientific and therapeutic interest. The first part of this work deals with the classification and treatment of primary cutaneous lymphomas (PCBCL). The 1997 published EORTC classification will be explained according to the good prognosis of PCBCL. Therapeutic strategies as well as typical procedures (PUVA, excision, irradiation) and gene-technically produced drugs (therapeutic antibodies, vaccination) are illustrated in detail. The second part of this publication focuses on the experimental molecular biological work-out, done in primary cutaneous lymphomas by means of micromanipulation and single cell PCR. For the mycosis fungoides could be shown that in the patch stage only a few malignant T cells can be detected. Increasing infiltrates (plaque-stage) are characterized by epidermotrop or dermally grouped atypical cells. In tumor stage dermal atypical T cells are predominating (Gellrich S, J Invest Dermatol, 2003). The tumor cells of primary cutaneous B cell lymphomas are comparable with the stage of mutation of follicle centre cells: somatic mutations and intraclonal diversity (Gellrich S, J Invest Dermatol, 1997; Gellrich S, J Invest Dermatol, 2001). The data indicate, that there may be an active mutation mechanism, the so-called ongoing mutations (Golembowski S, Immunobiology, 2000). One subgroup of PCBCL, are presented by the CD30positve entities. By means of micromanipulation and PCR, single cells were investigated due to T cell clonality. Not all atypical cells belong to the malignant population. It is supposed that an unknown stimulus leads to morphological features and CD30 expression (Gellrich S, J Invest Dermatol, 2003). Another CD30positive entity is reflected by the lymphomatoid papulosis. In these experiments large atypical CD30positve cells were isolated and have been investigated via PCR for T cell receptor g or immunoglobuline heavy and light chain gene rearrangement. The majority of the large CD30postive cells (two cases) belong to a polyclonal T cell population. In the opposite, the small CD3positive cells are the cells persisting within the T cell clone. In another case B cells with the same immunoglobulin gene rearrangement like in a preceding Hodgkin disease of the same patient could be detected. The data seem to underline the fact that reactive polyclonal CD30positive cells are triggered by an unkown stimulus with clonal bystander cells without any pathological significance. In summary, this work could be the basis for further investigations about the etiopathogenesis of PCBCL.

Induktiv gekoppelte Plasma-Massenspektrometrie mit Laserablation (LA-ICP-MS) wird zunehmend für die Einzelzellanalyse eingesetzt, jedoch wird eine weitere verbreitete Verbreitung durch den geringen Durchsatz behindert. Daher wurde in dieser Arbeit der Durchsatz von Einzelzellen-LA-ICP-MS untersucht und verbessert. Zunächst werden die beiden möglichen Ablationsmodi, Bildgebung und Einzelpunktanalyse (SSA), hinsichtlich ihrer analytischen Gütezahlen (Signal-Rausch-Verhältnis, Präzision, Genauigkeit, Durchsatz) verglichen. Hierfür wurden adhärente 3T3-Fibroblastenzellen mit zwei Metallfarbstoffen angefärbt und mit beiden Methoden mehrere Dutzend Zellen vermessen. SSA zeigte überlegene Eigenschaften hinsichtlich Durchsatz und Nachweisgrenzen. Darüber hinaus wurde gezeigt, dass >400 Zellen analysiert werden müssen, um zufriedenstellende Statistiken für einen quantitativen Vergleich der Ergebnisse zu erhalten, was als zu mühsam befunden wurde. Daher wurde ein Einzelzellen-Arraying-Schritt integriert, um eine automatisierte LA-ICP-MS-Analyse zu ermöglichen. Hierfür wurden zwei Arrayingverfahren getestet: Zunächst wurde das mikrofluidische Arraying von Zellen getestet, jedoch verhinderte das Einklemmen von weichen PDMS-Chips eine erfolgreiche Anwendung, und eine Neugestaltung des Chips wäre erforderlich. Daraufhin wurde eine neuartige Technologie getestet, die auf dem Arraying von Tröpfchen in Verbindung mit der Bilderkennung von Zellen beruht, wobei ein Anordnungsdurchsatz von 550 Zellen pro Stunde und eine beispiellose Einzelzellengenauigkeit (> 99%) gefunden wurde. In einem Proof-of-Principle-Experiment wurde ein Zellarray von THP-1-Suspensionszellen mittels LA-ICP-TOF-MS analysiert und erstmals gleichzeitig endogene und exogene Isotope einzelner Zellen als Isotopen-Fingerabdrücke von Zellen mit Nachweisgrenzen von lediglich wenigen hundert attogramm. Schließlich wurden diese Ergebnisse mit der derzeit gebräuchlichsten Analysemethode Single-Cell (sc)-ICP-MS verglichen. / Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is increasingly used for single-cell analysis. However, a more widespread use of LA-ICP-MS in single cell analysis is hampered by its low throughput. Hence, in this work the throughput of single cell LA-ICP-MS was studied and improved. First, the two possible ablation modes, imaging and single spot analysis (SSA) of single cells using a large laser spot, are compared regarding their analytical figures of merit (signal to noise, precision, accuracy, throughput), as well as regarding ease of operation and data evaluation. For that, adherent 3T3 fibroblast cells were stained with two metal dyes and several dozen cells were measured using both modes. SSA showed superior characteristics regarding throughput and detection limits. Moreover, it was shown that >400 cells must be analyzed to reach satisfactory statistics for a quantitative comparison of results, which would have been too laborious. Thus, a single cell arraying step was integrated to enable automated LA-ICP-MS analysis. Two different arraying methods were evaluated: First, arraying via hydrodynamic front trapping of cells using a microfluidic device was tested, but clamping of soft PDMS-chips prevented successful arraying and it was concluded that a major redesign of the chip is necessary. Secondly, and a novel technology relying on a microdroplet arrayer in conjunction with image recognition of cells was tested and a moderate arraying throughput (550 cells per hour) and an unprecedented single-cell accuracy (>99%) was found. In a proof of principle experiment, a cell array of THP-1 suspension cells was analyzed using LA-ICP-TOF-MS and endogenic and exogenic isotopes of individual cells were detected for the first time simultaneously as isotopic fingerprints of cells with detection limits as low as hundred attogram. Finally, these results were compared to the currently more commonly used analysis method single-cell (sc)-ICP-MS.

Das Herz eines Zebrafishs ist bemerkenswert, da es sich nach einer Verletzung vollständig regenerieren kann. Der Regenerationsprozess wird von Fibrose begleitet - der Bildung von überschüssigem Gewebe der extrazellulären Matrix (ECM). Anders als bei Säugetieren ist die Fibrose im Zebrafish nur transient. Viele Signalwege wurden identifiziert, die an der Herzregeneration beteiligt sind. Allerdings sind die Zelltypen, insbesondere Nicht-Kardiomyozyten, die für die Regulation des Regenerationsprozesses verantwortlich sind, weitgehend unbekannt. In dieser Arbeit haben wir systematisch alle Zelltypen des gesunden und des verletzten Zebrafischherzens mithilfe einer auf Mikrofluidik basierenden Hoch-Durchsatz- Einzelzell-RNA-Sequenzierung bestimmt. Wir fanden eine große Heterogenität von ECM-produzierenden Zellen, einschließlich einer Reihe neuer Fibroblasten, die nach einer Verletzung mit unterschiedlicher Dynamik auftreten. Wir konnten aktivierte Fibroblasten beschreiben und Fibroblasten-Subtypen mit einer pro-regenerativen Funktion identifizieren. Darüber hinaus haben wir eine Methode entwickelt, um die Transkriptomanalyse und die Rekonstruktion von Zell-Verwandtschaften auf Einzelzellebene zu kombinieren. Unter Verwendung der CRISPR-Cas9-Technologie führten wir zufällige Mutationen in bekannte und ubiquitär transkribierte DNA-Loci während der Embryonalentwicklung von Zebrafischen ein. Diese Mutationen dienten als zellspezifische, permanente und vererbbare “Barcodes”, die zu einem späteren Zeitpunkt erfasst werden konnten. Mit maßgeschneiderten Analysealgorithmen konnten wir dann Stammbäume der sequenzierten Einzelzellen erstellen. Mit dieser neuen Methode haben wir gezeigt, dass im sich regenerierenden Zebrafischherz ECM-produzierende Zellpopulationen entweder mit dem Epi- oder mit dem Endokardium verwandt sind. Zusätzlich entdeckten wir, dass vom Endokardium abgeleitete Zelltypen vom Wnt-Signalweg abhängig sind. / The zebrafish heart has the remarkable capacity to fully regenerate after injury. The regeneration process is accompanied by fibrosis - the formation of excess extracellular matrix (ECM) tissue, at the injury site. Unlike in mammals, the fibrosis of the zebrafish heart is only transient. While many pathways involved in heart regeneration have been identified, the cell types, especially non-myocytes, responsible for the regulation of the regenerative process have largely remained elusive. Here, we systematically determined all different cell types of both the healthy and cryo-injured zebrafish heart in its regeneration process using microfluidics based high-throughput single-cell RNA sequencing. We found a considerable heterogeneity of ECM producing cells, including a number of novel fibroblast cell types which appear with different dynamics after injury. We could describe activated fibroblasts that extensively switch on gene modules for ECM production and identify fibroblast sub- types with a pro-regenerative function. Furthermore, we developed a method that is capable of combining transcriptome analysis with lineage tracing on the single-cell level. Using CRISPR-Cas9 technology, we introduced random mutations into known and ubiquitously transcribed DNA loci during the zebrafish embryonic development. These mutations served as cell-unique, permanent, and heritable barcodes that could be captured at a later stage simultaneously with the transcriptome by high-throughput single-cell RNA sequencing. With custom tailored analysis algorithms, we were then able to build a developmental lineage tree of the sequenced single cells. Using this new method, we revealed that in the regenerating zebrafish heart, ECM contributing cell populations derive either from the epi- or the endocardium. Additionally, we discovered in a functional experiment that endocardial derived cell types are Wnt signaling dependent.

Populationen kanzeröser Zellen können aus verschiedenen Subpopulationen mit distinkten phänotypischen Profilen bestehen. Diese Dissertation verwendet mathematische Modellierung sowie die Analyse von Einzelzell-Genexpressionsdaten zur Beantwortung von Fragen über die Entstehung, das Wachstum und die Behandlung von Tumoren im Kontext einer solchen intratumoralen Heterogenität. / Tumoural cell populations may consist of different subpopulations with distinct phenotypic profiles. This thesis applies mathematical modelling as well as the analysis of single-cell gene expression data to questions related to the emergence, growth and treatment of tumours in the context of such an intratumoural heterogeneity.