No description available.

Lung cancer is one of the most aggressive cancers and the leading cause of cancer mortality in the US, mainly due to the lack of early detection. Meanwhile, gene expression profiling can identify molecular responses to carcinogen exposure and tumorigenesis. We have previously identified lung cancer-associated gene expression alterations in the normal bronchial airway epithelium of ever smokers with and without lung cancer. These alterations are the basis of a diagnostic test that is useful in clinical decision-making in patients with suspect lung cancer. Despite this success, further improvements in early lung cancer diagnosis are needed, along with a better understanding of airway biology during the initiation and development of lung cancer. Towards these goals, for the first aim of my thesis, I explored whether normal-appearing bronchial airway gene expression reflects lung cancer histologic subtypes. Genes differentially expressed in the bronchial airway between patients with lung squamous cell carcinoma and lung adenocarcinoma were identified and confirmed in independent data. Using a method developed based on independent component analysis (ICA), cell type-specific gene modules were derived from airway single-cell RNA-sequencing data and shown to be altered between lung cancer subtypes. Secondly, I sought to investigate whether integrating the bronchial airway molecular biomarker with radiomic features (i.e., quantitative features derived from radiographic images) could yield a better diagnosis for lung cancer screening. Using clinical variables, molecular signatures, and radiomic imaging features, I built and tested an integrated biomarker to improve discrimination between malignant and benign Indeterminate Pulmonary Nodules (IPNs). Finally, as COVID-19 became a pandemic during my thesis work, I sought to utilize large-scale genomic data from multiple cohorts to investigate possible clinical risk factors related to SARS-CoV-2 entry and disease severity. My analysis showed that smoking affects the expression of host genes involved in SARS-CoV-2 entry differently in the nasal and bronchial airways. The work has implications about how smoking might modulate SARS-CoV-2 infection and COVID-19 disease severity. Collectively, this work leverages computational approaches to identify airway biology associated with lung cancer subtypes, improve the diagnosis of lung cancer in patients with IPNs, and reveal relationship between smoking and SARS-CoV-2 infection. / 2024-02-18T00:00:00Z

Pulmonary arterial hypertension (PAH) is a devastating lung disease characterized by arterial pruning, occlusive vascular remodeling, and inflammation contributing to increased pulmonary vascular resistance with resultant right heart failure. Endothelial cell (EC) injury and apoptosis are commonly considered triggers for PAH, the mechanisms leading from injury to complex arterial remodeling are incompletely understood. While current therapies can improving symptoms, with the exception of parenteral prostacyclin, they do not significantly prolong transplant free survival. As well, there are no therapies that can regenerate the damaged lung short of transplantation. In this project, I sought to both advance the understanding of disease pathogenesis and explore regenerative therapeutic options for PAH. To this end, I first employed single cell RNA sequencing (scRNA-seq) at multiple time points during the Sugen 5416 (SU) – chronic hypoxia (CH) model of PAH, to provide new insights into PAH pathogenesis both during onset and progression of disease. We also employed microCT analysis to visualize and quantify the arterial pruning associated with PH and found significant loss up to 65% of the healthy arteriolar volume in this model. Through scRNA-seq analysis performed at four timepoints spanning the onset and progression of disease, two disease-specific EC cell types emerged as key drivers of PAH pathogenesis. The first was the emergence of capillary ECs with a de-differentiated gene expression profile, which we termed dedifferentiated capillary (dCap) ECs, with enrichment for the Cd74 gene. Interestingly, RNA velocity analysis suggested that these cells may be undergoing endothelial to mesenchymal transition during PAH development. At later times, a second arterial EC population became apparent, which we termed activated arterial ECs (aAECs), since it uniquely exhibited persistently elevated levels of differential gene expression consistent with a migratory, invasive and proliferative state. Interestingly, the aAECs together with the smooth muscle (SM)-like pericytes, a population which was also greatly expanded in PAH, expressed Tm4sf1, a gene previously associated with a number of cancers and abnormal cell growth. Furthermore, by immunostaining, TM4SF1 was found to be spatially localized to sites of complex and occlusive arterial remodeling, associated with both endothelial cells and pericytes in these lesions, suggesting an important role for the aAECs and SM-like pericytes in arterial remodeling and PH progression. Together, these findings suggest that aAECs, dCap ECs, and SM-like pericytes are emerging cell populations responsible for lung arterial remodeling in PAH, which drives disease progression, and that TM4SF1 may be a novel therapeutic target for this disease. As a first step in trying to develop approaches to regenerate lung arterial bed that is lost in PAH, we investigated the potential role of endothelial colony forming cells (ECFCs) and mesenchymal stromal cell (MSC) derived extracellular vesicles (EVs) as novel therapeutics, on the premise that these stem/progenitor cells would stimulate lung regeneration by mainly paracrine mechanisms. Additionally, we used biomaterials to microencapsulate cells and EVs to improve their local delivery and retention. While ECFCs were found to be ineffective in treating the monocrotaline model on their own, they were poorly retained in the lung and microencapsulation of ECFCs led to enhanced lung delivery within the first 72 hours, with resultant hemodynamic improvements in this model of PAH. MSCs are well known to be immunomodulatory and proangiogenic, largely acting through paracrine mechanisms, including by the release of EVs. Yet, following intravenous administration, nano sized EVs are rapidly cleared from circulation, potentially limiting their therapeutic potential. I adapted our microencapsulation strategy for EVs, and demonstrated significantly greater retention of microgel-loaded EVs were within the lung, resulting in enhanced local cell uptake. Interestingly, the hydrogel used for microencapsulation induced a local immune response which made it unsuitable for testing any potential therapeutic benefits of MSC-EVs in this study. Nonetheless, this work demonstrated proof-of-principle for the utility of microencapsulation as a strategy to enhance EV lung delivery. Overall, this work has identified novel lung cell populations (aAECs, dCap ECs, SM-like pericytes) driving arterial remodeling associated with PH progression, demonstrated the potential of ECFCs as a regenerative cell for the treatment of PAH, and illustrated the utility of microencapsulation as a tool to enhance lung targeting of both cells and EVs.

[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

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.

Angeborene lymphatische Zellen (ILC) sind wichtige Effektorzellen der angeborenen Immunantwort, deren Entwicklung und Aktivierungswege attraktive therapeutische Ziele darstellen. Sie bestehen aus ILC der Gruppe 1 (Natürliche Killerzellen (NK) und ILC1), ILC2 und ILC3. Neben T-Zellen leisten ILCs einen entscheidenen Beitrag zu den Typ-1-, Typ-2- und Typ-3-Immunantworten. Die Entwicklung von ILCs beim Menschen wurde jedoch noch nicht systematisch untersucht, und frühere in vitro Untersuchungen stützten sich auf die Analyse einiger weniger Marker oder Zytokine, die für die Bestimmung der Identität der verschiedenen ILC-Linien suboptimal sind. Um diese Mängel zu beheben, stellen wir hier eine Plattform vor, die zuverlässig alle menschlichen ILC-Linien aus CD34+ CD45RA+ hämatopoetischen Vorläuferzellen, gewonnen aus Nabelschnurblut und Knochenmark, erzeugt. Mit einem systematischen Ansatz zeigt diese Arbeit, dass eine einzige Kulturbedingung nicht ausreicht, um alle ILC-Untergruppen zu generieren, sondern stattdessen bestimmte Kombinationen von Zytokinen und Notch-Signalen für die Entscheidung über das Schicksal der Linien wesentlich ist. Eine umfangreiche Analyse des Transkriptoms ergab, dass der Erwerb von CD161 robust eine globale ILC-Signatur identifiziert und in vitro ILCs von T-Zell-Signaturen trennt. Die Identität spezifischer in vitro generierter ILC-Linien (NK-Zellen und ILC1, ILC2 und ILC3) wurde durch Proteinexpression, funktionelle Assays und Transkriptomanalysen auf globaler sowie auf Einzelzellebene umfassend validiert. Diese in vitro erzeugten ILC-Linien rekapitulieren die Signaturen und Funktionen ihrer ex vivo isolierten ILC-Pendants. Des Weiteren, behandeln diese Daten die Einschränkungen der Unterscheidung von menschlichen NK Zellen und ILC1 sowohl in vitro als auch ex vivo an. Darüber hinaus löst diese Plattform gängige Probleme bei der Untersuchung menschlicher ILCs, wie z. B. unzureichende Zellzahlen oder die mangelnde Verfügbarkeit von Gewebeproben. Insgesamt stellt diese Arbeit eine Ressource dar, die nicht nur zur Klärung der Biologie und Differenzierung menschlicher ILCs beiträgt, sondern auch als wichtiges Instrument zur Untersuchung der Dysregulation von ILC-Funktionen dient, die bei verschiedenen entzündlichen Erkrankungen des Menschen eine Rolle spielen. / Innate lymphoid cells (ILCs) are critical effectors of innate immunity and inflammation that consist of Group 1 ILCs (natural killer (NK) cells and ILC1), ILC2, and ILC3. As tissue resident lymphocytes, they play a crucial role type 1, type 2 and type 3 immune responses, respectively. Importantly, dysregulated ILC populations have been linked to the pathogenesis of a variety of chronic inflammatory diseases and thus represent attractive therapeutic targets with a potential for autologous cell therapies. However, human ILC generation has not been systematically explored, and previous in vitro investigations have relied on the analysis of few markers or cytokines, which are suboptimal to assign lineage identity and full functional capacity. To address these faults, we present here an effective in vitro platform, which reliably generates the core human ILC lineages from CD34+ CD45RA+ hematopoietic progenitors derived from cord blood and bone marrow. With a systematic approach, this work shows that a single culture condition is insufficient to generate all ILC subsets, and instead, distinct combinations of cytokines and Notch signaling are essential for lineage fate making decisions. In depth transcriptomic analysis revealed that acquisition of CD161 robustly identifies a global ILC signature and separates them from T cell signatures in vitro. The identity of specific ILC subsets, (NK cells and ILC1, ILC2, and ILC3) generated in vitro was validated extensively by protein expression, functional assays, and both global and single-cell transcriptome analysis. These in vitro generated ILC subsets recapitulate the signatures and functions of their ex vivo ILC counterparts. Finally, these data shed light on the limitations in untying the identity of human NK cells and ILC1 in vitro, similarly correlating to lineage identification difficulties ex vivo. Additionally, this platform tackles common problems in human ILC studies such as insufficient cell numbers and scarce availability of tissue samples. Altogether, this work presents a resource not only to aid in clarifying human ILC biology and differentiation, but also to serve as an important tool to study dysregulation of ILC functions, which have been implied in various inflammatory diseases in humans.

No description available.