Tesis Doctorals - Facultat - Biologia

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Reaching a modular, generic and containerised development in Biomedical Natural Language Processing systems
(Universitat de Barcelona, 2025-07-08) Corvi, Javier; Capella Gutiérrez, Salvador Jesús, 1985-; Gelpi Buchaca, Josep Lluís; Universitat de Barcelona. Facultat de Biologia
[eng] The last century saw an exponential increase in scientific publications in the biomedical domain, generating a vast corpus of knowledge on different subfields. Despite the potential value of this knowledge, most of this data is only available as unstructured textual literature with variable degrees of digitisation, which have limited their systematic access, use and exploitation. This limitation can be avoided, or at least mitigated, by relying on text mining techniques to automatically extract relevant data and structure it from textual documents. Among the different alternatives for the automated processing of available texts, Natural Language Processing (NLP) workflows occupy a fundamental role. Biomedical Natural Language Processing (BioNLP) has been widely used to enhance the extraction, analysis, and interpretation of biomedical data from unstructured text, helping to streamline research, improve patient care, and support decision-making in healthcare. Applications range from mining vast corpora of scientific literature for drug discovery and gene-disease associations to processing clinical records for automating medical coding and extracting patient data for personalised medicine. Nowadays, there are still uncovered biomedical areas that require comprehensive analysis and research in order to develop appropriate text mining resources and systems. In the clinical domain, efforts have been made to generate annotated corpora and text mining tools focused on extracting diseases and drug-related adverse effects in humans for pharmacovigilance activities. However, in the preclinical phase of the drug development process, there are no text mining resources developed for analysing the growing number of existing toxicological studies. eTRANSAFE was a research project funded within the Innovative Medicines Initiative (IMI), which aimed at developing integrated databases and computational tools that support the translational safety assessment of new drugs. One of the milestones of eTRANSAFE was the development of a text mining framework designed to automatically extract treatment-related findings from preclinical toxicology reports. A treatment-related finding refers to any observable effect, outcome, or manifestation that occurs in a test subject as a direct or indirect result of a treatment or compound administration. Another field that currently lacks in terms of resources and tools for unstructured text analysis is the biomaterials domain. Biomaterials are natural or synthetic materials used for constructing artificial organs, fabricating prostheses, or replacing tissues. The effective use of biomaterials is critical for advancements in medical and dental applications, tissue engineering, and regenerative medicine. Developing advanced text mining and NLP tools tailored for the biomaterials domain could enhance data accessibility and usability. Such tools would enable researchers to systematically analyse existing literature, identify trends, and uncover relationships between different biomaterials and their applications. By bridging this gap, we can accelerate innovation and improve outcomes in biomaterials research and its applications in healthcare. A significant challenge for scientific software applications, including NLP systems, is the ability to share, distribute, and run these systems in a simple and efficient manner. Software containers provide a robust technological foundation to address this challenge. Containers encapsulate the application’s dependencies and auxiliary tools, ensuring isolation from the host environment, which enhances portability and reproducibility. Additionally, workflow managers can be employed to automate the orchestration and execution of text mining pipelines, streamlining the entire process and ensuring efficient, scalable execution. This thesis focuses on developing modular, flexible software components that utilise NLP techniques, allowing for their reuse and adaptation across various domains. In particular, this thesis addressed two BioNLP use cases; the main one is the development of PretoxTM, a text mining system for extracting treatment-related findings from preclinical toxicology reports, developed in the context of the eTRANSAFE project. A second use case is the development of DEBBIE (Database of Biomaterials and their Biological Effect), which aims to integrate metadata extracted from biomaterials publications by storing in its database indexed articles with relevant concepts. The introduction reviews the state of the art in NLP, offering historical context to illustrate the evolution of modern techniques that are currently transforming the field. It also addresses the challenge of modularising the developed components in isolation, utilising virtualisation and automating their execution through workflow managers. Additionally, it examines the current landscape of BioNLP, its diverse applications, and the motivations driving the use cases presented in this thesis. This thesis comprises three published articles: The first article describes the development of the Biomaterials Annotator: a system for ontology-based concept annotation of biomaterials text. This work represents a preliminary phase of the DEBBIE project. The second article encompasses the work undertaken within DEBBIE: The Open Access Database of Experimental Scaffolds and Biomaterials Built Using an Automated Text Mining Pipeline. It describes a novel text mining pipeline that optimises the acquisition, filtering, concept recognition, and storage of annotated biomaterials publications. Additionally, the article highlights the development of a user-friendly web application that allows users to access DEBBIE through keyword searches, displaying results in an intuitive format. The third article provides a comprehensive overview of the principal use case addressed in the thesis, the development of PretoxTM: a text mining system for extracting treatment-related findings from preclinical toxicology reports. It details the creation of the three core components, the PretoxTM Corpus, a gold-standard dataset of preclinical findings annotated by toxicology experts; the PretoxTM Pipeline, which automates the extraction of these findings from preclinical study reports; and the PretoxTM Web App, which facilitates expert review, visualisation, and validation of the extracted information. Finally, the General Discussion section highlights the overall achievements of this thesis, addresses the limitations of the developed systems, and proposes directions for future work to enhance the systems and adapt them to evolving requirements. Additionally, it examines the challenges faced, particularly those arising from the rapid advances in the field of NLP.
Advances in fallow land management and in the use of tracking technologies for steppe bird conservation in agricultural areas
(Universitat de Barcelona, 2025-07-15) Revilla Martín, Natalia; Giralt, David (Giralt i Jonama); Sardà Palomera, Francesc; Universitat de Barcelona. Facultat de Biologia
[eng] Agricultural lands are habitat of many species that are declining mainly due to agricultural intensification, a process that has deeply transformed these landscapes over the past decades. Intensification involves land-use change and homogenization, the loss of natural and non-cultivated elements, the increase in chemical inputs and higher frequency of agrarian practices. These changes are disproportionally affecting specialist species such as steppe birds, which in Europe are adapted to extensive rainfed cereal and pasture landscapes and find their main European strongholds in the Iberian Peninsula. The general objective of this thesis is to deepen our understanding of the effects of agricultural practices and conservation management on steppe birds in order to improve their unfavourable current conservation status. The study area is a protected cereal pseudo-steppe in Catalonia, north-eastern Spain. In this area, fallows are specifically managed for the conservation of steppe birds, as part of a compensatory measure of an implemented irrigation project. I used variance partitioning methods to disentangle the effects of factors operating at different spatial scales on the presence and abundance of steppe birds in these fallow lands. I found that larger fallows at a higher relative elevation were preferred, and that even if fallow management was optimized to meet the requirements of steppe birds, field characteristics and landscape context had important effects in maximizing occurrence and abundance. I also examined how mechanical treatments influence the arthropod community - an important food resource for farmland and steppe species - within these fallows using a field experiment. Low-intensity mechanical management of fallows had short-term negative effects on arthropod abundance, mediated by the reduction of vegetation height, green vegetation cover and flowering. Fallow lands are in the green architecture of the 2023-2027 CAP either as Eco-schemes or as Agri-Environment-Climate Measures. Incorporating low-intensity management indications for them – such as avoiding mechanical management during the breeding season, leaving non-treated strips in fallows to boost arthropod communities or prioritizing fallows larger than 3 ha – would increase fallow effectiveness as a conservation tool. In this thesis I also used biologging technologies to gain new insights into the habitat selection, movement, and behaviour of two emblematic steppe birds: the Eurasian Stone-curlew and the Little Bustard. GPS tracking allowed me to distinguish Eurasian Stone-curlew’s diurnal and nocturnal habitat selection across phenological phases - pre-breeding, incubation, chick-rearing, and post-breeding – and to assess breeding success across habitats. I found that fallow lands and low-intensified almond and olive orchards were preferred over other land uses. Nesting success was higher in fallows than in almond and olive orchards, primarily due to increased nest failure from tilling in the latter. Additionally, I expanded the potential of accelerometry for studying steppe birds by developing models to identify and classify the behaviours of Little Bustards recorded through accelerometer data. Machine learning models classified key behaviours - standing, lying, vigilance, locomotion, foraging, and male courtship - with separate models for each sex due to behavioural differences. Application of the models to free-ranging individuals showed marked seasonal and sexual differences in time-activity budgets. These models offer a valuable tool for understanding activity patterns and informing conservation strategies for this threatened species. In a context of serious difficulties in implementing ambitious conservation measures and limited budgets, conservation measures need to be designed and prioritized based on ecological scientific knowledge to be effective, and to consider the local socioeconomical context to favour its uptake by farmers and companies. This thesis offers insights on the needs of steppe birds in agricultural areas, reinforce the idea that not all fallows are equally valuable for biodiversity conservation and proposes management measures.
Precision medicine for rare neuromuscular diseases: clinical, genetic and pathophysiological studies
(2025-07-23) Estévez Arias, Berta; Palau Martínez, Francesc; Natera de Benito, Daniel; Universitat de Barcelona. Facultat de Biologia
[eng] Neuromuscular disorders (NMDs) are a genetically diverse group of diseases affecting muscle and peripheral nerves, with over 600 genes identified to date. Their diagnosis is often complicated by genetic heterogeneity and pleiotropy, where similar symptoms may result from distinct genes, and a single gene can cause a broad range of phenotypes. While clinical suspicion guides initial evaluations, molecular confirmation is key for an accurate diagnosis. Next generation sequencing (NGS) has revolutionized the diagnostic approach to NMDs. Initially limited to selected cases in research settings, NGS is now routinely used in clinical settings due to improved technology and reduced costs. However, despite these advances, approximately 50% of individuals with NMDs remain without a definitive molecular diagnosis. This doctoral thesis aimed to reduce this diagnostic gap in individuals with childhood-onset NMDs by implementing a sequential analysis strategy. This approach was applied to affected individuals from the Neuromuscular Disorders Unit (Hospital Sant Joan de Déu, Barcelona) who had previously undergone standard genetic testing with inconclusive results. The study followed a dual strategy: (1) functional validation of candidate variants identified through routine NGS analyses, and (2) the application of multi-omics techniques (trio whole-genome sequencing and RNA sequencing) in cases lacking strong candidate variants. The results, presented across four publications, illustrate how combining detailed clinical phenotyping with advanced molecular techniques increases diagnostic yield and refines gene–disease associations. In two studies, functional analyses enabled the reclassification of variants of uncertain significance and the identification of novel phenotypic presentations associated with known disease genes (DARS2 and ATL3). The first publication reveals a novel association between DARS2 and peripheral axonal neuropathy, based on the study of five individuals from three unrelated families who presented biallelic variants in this gene. Previously, DARS2 was only associated with leukoencephalopathy with brain stem and spinal cord involvement and lactate elevation (LBSL). Functional studies in patient-derived fibroblasts confirmed the pathogenicity of the variants, identified a potential hypomorphic allele, and suggested a continuous disease spectrum associated with DARS2, ranging from isolated peripheral neuropathy to more complex phenotypes without typical LBSL features. The second publication explores two individuals from the same family with isolated motor axonal neuropathy, carrying a heterozygous variant in ATL3, previously associated only with sensory neuropathy. Structural modeling and functional studies revealed a novel pathogenic mechanism involving destabilization of the ATL3 globular domain, impairing ER-mitochondria interactions and autophagic ﬂux. These studies confirmed the pathogenicity of the variant and expanded the ATL3-related disease spectrum. The remaining two studies report the analysis of 58 cases using a multi-omics strategy and achieving a 40% diagnostic rate. The first publication includes the entire cohort, while the second one describes the identification of a maternal mosaicism in an individual with RYR1-related congenital myopathy. Overall, the findings show how combining multi-omics data with detailed phenotyping can resolve previously unsolved cases. In conclusion, this thesis demonstrates that, within the framework of personalized medicine and translational research, the integration of clinical, genomic, and pathophysiological investigations contributes significantly to improving the molecular diagnostic yield.
Evolution of drug resistance and associated trade-offs in non-albicans Candida pathogens
(Universitat de Barcelona, 2026-05-30) Núñez Rodríguez, Juan Carlos; Gabaldón Estevan, Juan Antonio, 1973-; Universitat de Barcelona. Facultat de Biologia
[eng] Antimicrobial resistance is considered as one of the most significant challenges that humanity will face in the future, as stated by the World Health Organization. Antifungal resistance is particularly concerning, as only three antifungal drug families are currently available for clinical use. Both antifungal resistance and fungal infections are on the rise, with an estimated 6.5 million people affected annually and approximately 2.5 million deaths directly attributed to invasive fungal diseases. To develop effective countermeasures, we need a comprehensive understanding of the mechanisms for evolutionary adaptation of these pathogens to antifungal drugs. Among fungal pathogens, non-albicans Candida (NAC) species have experienced a marked increase in infection rates, now accounting for more than half of all Candida infections. NAC species exhibit a striking degree of adaptability to antifungal treatments due to their high genomic plasticity and intrinsic resistance to certain drugs. In contrast to C. albicans, the antifungal resistance mechanisms of many NAC species remain poorly understood, with research primarily focused on a limited number of mutations in key genes. This thesis aims to improve our understanding of resistance mechanisms in NAC species through an integrated study of genotypic and phenotypic responses, focusing primarily on Nakaseomyces (Candida) glabratus and the three species within the Candida parapsilosis complex. To achieve this, a novel methodology, called Q-PHAST, has been developed that allows large-scale phenotypic studies, which, when combined with in vitro evolutionary experiments and whole genome sequencing, provide an unprecedented level of detail in the study of resistance processes in NAC species. Using this approach, we obtained a comprehensive view of the genomic processes underlying azole and echinocandin resistance in the C. parapsilosis complex, identifying a large catalog of novel variants and providing critical insights into the evolutionary dynamics of each species. In addition, in N. glabratus, we investigated whether antifungal resistance leads to collateral fitness trade-off and whether these vulnerabilities can be exploited to counteract resistant strains. As an outcome of this research, this thesis has also initiated a drug discovery project focused on developing novel antifungal compounds capable of eliminating multidrug resistant strains in NAC species. Overall, this thesis has employed a multidisciplinary approach to expand both fundamental and applied knowledge of antifungal resistance evolution and its consequences in pathogenic NAC species.
Novel bioinformatic methods for the metagenomic analysis of non-invasive samples from the endangered species Galemys pyrenaicus: monitoring population genomics, ecology, and health
(Universitat de Barcelona, 2025-05-30) Sapino Funes, Román; Castresana Villamor, José; Universitat de Barcelona. Facultat de Biologia
[eng] The use of genomic methods has become an important tool in conservation programs for endangered species. These methods have been used mainly to study population genomics, but they have the potential to provide additional information, especially about the trophic ecology and health of individuals and species. One promising way to expand conservation genomics methods is to analyze fecal samples using metagenomic techniques. Fecal samples can be collected with minimal disturbance to the animals, and they can provide important insights into diet, gut microbiome, and pathogens. Combining these samples with modern bioinformatic tools could help to learn critical aspects for the conservation of endangered species. However, metagenomic analysis in non-model species is a major challenge due to the lack of reference genome sequences or data limited to distantly related species. Fresh fecal samples of the Iberian desman (Galemys pyrenaicus) were used to construct metagenomic libraries, from which it was possible to analyze the overall composition of the DNA present in the feces. Using endogenous nuclear DNA, population structure was analyzed through Principal Components Analysis (PCA), while endogenous mitochondrial genomes were also reconstructed. For the analysis of exogenous DNA of eukaryotic origin, a novel bioinformatic method was developed that uses assembled consensus sequences for mapping instead of individual reads, which allowed improving classifications using various reference databases. This method facilitated the characterization of diet composition and the identification of parasites. Additionally, it enabled the estimation of relative abundances through depth of coverage. For the exogenous DNA of bacterial origin, a specific method was developed to detect potentially pathogenic bacteria at the species level from metagenomic sequences by mapping unassembled reads to complete reference genomes. The approach used the breadth of coverage rather than the number of mapped reads for species identification, thereby minimizing false positives due to conserved or repetitive genomic regions. The analysis revealed the presence of 19 potentially pathogenic bacterial species, with prevalences ranging from a single individual to 30% of the samples. Desmans with elevated or altered pathogen loads were detected, suggesting differences in individual health status or variations in exposure to environmental factors. Application of this method across populations and over time for endangered species may provide essential health and epidemiological information to improve conservation strategies.
Intrinsic tracers for the analysis of habitat use by large marine vertebrates
(Universitat de Barcelona, 2025-04-01) Cani, Alessandra; Cardona Pascual, Luis; Drago, Massimiliano; Universitat de Barcelona. Facultat de Biologia
[eng] The use of the stable isotopes of different chemical elements as intrinsic biogeochemical tracers offers a unique opportunity to infer information about the foraging and spatial ecology of large marine vertebrates from small tissue samples of alive or dead individuals. Historically, the most commonly used tracers to study the trophic ecology of marine species have been the stable isotope ratios of carbon (δ13C) and nitrogen (δ15N), since they allow to identify the contribution of different primary producers with distinct isotopic signatures to the diet of a consumer and to estimate the trophic position of species and individuals within an ecosystem. More recently, the use of these isotopic tracers to analyse the habitat use of marine animals has led to the inclusion of other chemical elements to explore new dimensions of the isotopic niche. Such is the case of the sulphur stable isotope ratio (δ34S) to differentiate between inshore/benthic habits from offshore/pelagic habits, and the oxygen stable isotope ratio (δ18O) to study migration patterns across areas with distinct salinity. Nevertheless, the advantages of using additional isotopic tracers to improve the definition of the isotopic niche will depend on the ecosystem and species involved and, particularly, on the existence and scale of environmental isotopic gradients that affect the stable isotope ratios in primary producers and along the respective food webs. Therefore, this thesis aims to assess the suitability of the δ34S and δ18O ratio as habitat tracers for two different aspects, (1) to evaluate the isotopic niche partitioning among species of the same community and (2) to identify individual movement patterns among isotopically distinct foraging grounds. To do this, the δ13C, δ15N, δ34S and/or δ18O ratios were analysed in two types of consumer tissues, bone of marine mammals and sea turtles and epidermis of sea turtles, inhabiting ecosystems with marked environmental isotopic gradients such as the Río de la Plata estuary, the Mauritanian coast and the North Atlantic Ocean-Mediterranean Sea system. On one hand, the addition of the δ18O and δ34S ratios to the δ13C and δ15N ratios allowed to better characterize the isotopic niche partitioning among marine consumers in an ecosystem with important inputs of freshwater and terrestrial particulate organic matter, since the spatial scale of the environmental isotopic gradients covered the area used by the species. However, this did not occur everywhere and hence, the inclusion of more tracers does not necessarily translate into an improvement of the characterization of the isotopic niche partitioning among species. On the other hand, the use of at least three of these intrinsic tracers allowed to identify individual specialization in habitat within populations, as well as to trace individual movements among isotopically distinct areas. Furthermore, accounting for as many physical and chemical processes as possible, both environmental and metabolic, is critical when using stable isotopes to assess the habitat use and trophic ecology of large marine vertebrates, as the isotopic ratios of the consumers can be jointly affected by many processes. Finally, results should be validated with other complementary research techniques, such as direct observations, satellite telemetry and genetic analysis.
Decoding Functional Genomics: Exploring Gene Expression Regulation and Unveiling the Drivers of Inter-Individual Variation
(Universitat de Barcelona, 2025-04-07) Oliveros Diez, Winona; Melé Messeguer, Marta; Universitat de Barcelona. Facultat de Biologia
[eng] Understanding gene expression and its regulation is crucial for uncovering the molecular mechanisms driving phenotypic diversity and disease susceptibility. Regulatory regions of the genome, including non-coding elements, play a pivotal role in controlling gene activity, yet their influence on transcriptomic variation remains incompletely understood. My work, conducted within the Transcriptomics and Functional Genomics group at the Barcelona Supercomputing Center under the guidance of Dr. Marta Melé, aims to unravel these complexities by leveraging high-throughput sequencing technologies and advanced computational analyses. This PhD thesis explores the regulatory mechanisms of the human transcriptome in health and disease, employing both large-scale transcriptomic analyses and functional genomics approaches. It consists of two main chapters, each addressing distinct aspects of gene regulation using complementary methodologies. The main goal is to elucidate how genetic, demographic, and environmental factors shape transcriptional and epigenetic regulation, ultimately contributing to phenotypic diversity and disease susceptibility. These insights pave the way for more effective and personalized medical approaches. The thesis is structured into two main chapters. In Chapter 1, we investigate how demographic factors (such as sex, age, ancestry, and BMI) collectively influence gene expression, alternative splicing, and DNA methylation across multiple human tissues. While previous transcriptomic studies have provided valuable insights into gene regulation, the full extent of inter-individual variability remains poorly characterized. Using large-scale publicly available datasets, we systematically quantify the contributions of these demographic traits, identify common and tissue-specific regulatory patterns, and explore the potential functional consequences of DNA methylation variations. Our findings reveal widespread hypermethylation in the female autosomal genome, particularly at Polycomb-repressed regions, across tissues. Additionally, we observe a systematic age-related hypermethylation pattern at Polycomb target regions and regulatory sites associated with developmental genes in both sexes across tissues, with the exception of the gonads. Furthermore, ancestry-related differences, particularly in ribosomal protein regulation and the epigenetic landscape, underscore the importance of population diversity in genomic studies. These insights highlight the need for inclusive research frameworks to better understand human biology and disease mechanisms across populations. In Chapter 2, we shift focus to the functional effects of non-coding genetic variants associated with cardiovascular traits. Many disease-associated variants identified through genome-wide association studies (GWAS) lie within regulatory regions, yet their precise roles remain unclear. To address this, we employ Massively Parallel Reporter Assays (MPRAs) to functionally assess 4,608 genetic variants linked to blood pressure regulation in vascular smooth muscle cells (VSMCs) and cardiomyocytes (CMs). By integrating MPRA results with publicly available epigenomic datasets, we refine a set of likely regulatory variants and identify their potential roles in cardiovascular disease. Our findings highlight the complexity of non-coding variant function, demonstrating that regulatory effects are often cell type-specific. This work not only advances our understanding of the genetic architecture of cardiovascular disease but also lays the foundation for future research aimed at developing targeted therapies. By combining large-scale transcriptomic analyses with high-throughput functional assays, this thesis provides a comprehensive view of gene regulation in both health and disease contexts. This research underscores the importance of considering demographic diversity in transcriptomic studies and highlights the power of functional genomics approaches in deciphering the roles of non-coding variants. These findings have important implications for personalized medicine, contributing to a deeper understanding of the molecular mechanisms underlying disease susceptibility.
In utero green space exposure, DNA methylation, and birth size metrics
(2025-03-24) Aguilar Lacasaña, Sofía; Vrijheid, Martine; Bustamante Pineda, Mariona; Universitat de Barcelona. Facultat de Biologia
[eng] An increasing body of evidence has established health benefits of exposure to green space. Notably, in utero exposure to green space has been linked to a reduced risk of adverse birth outcomes, such as low birth weight (LBW), a critical indicator of long-term heath throughout the life-course. Despite these associations, the biological mechanisms underlying the benefits of green space remain unclear, with epigenetic changes emerging as a potential explanation. The aim of this thesis was to investigate the epigenetic mechanisms, focusing on DNA methylation (DNAm) patterns, associated with green space exposure and birth size metrics. First, we examined the association between green space exposure and DNAm through epigenome-wide association studies (EWAS), focused on two tissue types: blood and placenta. In blood, we analyzed two exposure windows using data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children. After multiple-testing correction, in utero greenness exposure was associated with three differentially methylated regions (DMRs) in cord blood. These regions encompass the SLC6A12, ADAMTS2, and KCNQ1DN genes, with the latter two previously reported in the literature in relation to green space exposure. These genes regulate extracellular matrix organization, blood vessel development, cell growth inhibition, and TGF-beta receptor signaling. The cumulative exposure to greenness from conception to childhood was associated with one DMR in the SDK1 gene, related to immune regulation and neural development. None of the exposure windows was associated with individual differentially methylated positions (DMPs). In the placenta, data from 550 mother-child pairs from the Barcelona Life Study Cohort (BiSC) revealed a significant association between residential greenness and DNAm levels at a DMP located in the SLC25A10 gene. This gene is linked to metabolic processes and body mass index (BMI). Additional suggestive DMPs were identified, related to pathways involving glucocorticoid signaling, inflammatory responses, and oxidative stress. No DMRs were detected after adjusting for multiple testing and additional checks. Second, we explored the association between placental DNAm and birth size metrics, including birth weight (BW), birth length (BL), birth weight-for-length (WLR), and head circumference (HC) in 3,852 neonates from 16 international cohorts. DNAm at 1,106 CpGs was associated with at least one of the birth size metrics, with 1,000 of them being associated with BW. Through positional annotation, promoter-enhancer interactions, and expression quantitative trait methylations (eQTMs), key pathways for placental function and fetal growth were identified, including glucose metabolism, growth and hormonal signaling, immune regulation, vascularization, and hypoxia, as well as enrichment for certain placental transcription factors (TFs). Moreover, sex specific differences in DNAm patterns related to BW were observed, with nine female specific and 38 male-specific DMPs. Additionally, the comparison of the findings with those previously reported for cord blood indicated tissue-specific effects. Furthermore, we identified seven cell-dependent DMPs. The genetic contribution was also assessed, revealing that approximately 20% of the DMPs were influenced by fetal methylation quantitative trait loci acting in cis (cis-mQTLs). To infer causality between the DNAm and BW, bi-directional Mendelian randomization (MR) analyses were conducted, suggesting that DNAm at nine DMPs might affect BW, though further studies are needed to exclude horizontal pleiotropy. Potential causal CpGs were annotated to genes associated with placental development and function as well as obstetric complications (RASSF1, SEMA3F, SIK3, SLC2A4RG). Finally, we investigated whether placental DNAm markers could underlie the association between in utero exposure to green space and BW by applying the meet-in-middle approach. We observed that 37 out of the 1,000 BW-associated DMPs had consistent associations with green space exposure, suggesting a potential mediating role. Experimental or interventional studies are necessary to confirm causality. In summary, this thesis, through international multi-cohort studies, has elucidated placental epigenetic mechanisms involved in fetal growth. It also has pointed to biological pathways that aligned with benefits of green space, such as mental restoration and physical activity. Results, however, should be interpreted cautiously, and future research with more precise exposure assessments, cellular models, and interventional designs will be essential to fully confirm these findings.
From stem cells to cancer: novel methods for tracking clonal behavior and tumour heterogeneity
(Universitat de Barcelona, 2025-03-24) Singh, Indranil; Rodriguez-Fraticelli, Alejo E.; Universitat de Barcelona. Facultat de Biologia
[eng] Hematopoietic stem and progenitor cells serve as a cornerstone of tissue homeostasis, enabling the generation of diverse blood cell types and immune responses. However, aberrations in their clonal dynamics and differentiation trajectories underpin a range of pathological conditions, including hematological malignancies, cardiovascular diseases, and tumor progression. This thesis employs advanced single-cell and lineage-tracing methodologies to dissect the cellular and molecular mechanisms governing stem cell behavior, differentiation, and functional diversity across disease contexts. In the first study, we elucidate the role of the cellular state of origin in dictating leukemic phenotypes. Using clonal tracing in mouse models, we demonstrate that low fitness stem cells, typically outcompeted during normal hematopoiesis, gain a competitive advantage following mutations in Dnmt3a-R878H or Npm1c. These mutations not only amplify specific clones but also reprogram their differentiation trajectories, underscoring the role of clonal "reaction norms" in cancer heterogeneity. The second study presents EPI-clone, a transgene-free lineage-tracing framework leveraging somatic epimutations to resolve clonal dynamics at single-cell resolution. Applied to murine and human hematopoiesis, EPI-clone reveals that age-related myeloid bias arises from a restricted pool of expanded clones, while many functionally young-like clones persist. In humans, we identify a spectrum of age-related clonal expansions, both with and without driver mutations, establishing a continuum of clonal hematopoiesis in ageing. The third study investigates the role of hematopoietic stem cells (HSCs) in emergency hematopoiesis (EH) following myocardial infarction (MI). By profiling human bone marrow from cardiac surgery patients, we uncover transcriptional and functional shifts in HSCs that promote pro-inflammatory myelopoiesis, contributing to impaired cardiac repair. Therapeutically, enforcing HSC quiescence via 4-oxo-retinoic acid mitigates inflammatory myelopoiesis, preserving cardiac function post-MI and providing a potential strategy for modulating excessive immune responses. Finally, the fourth study explores neutrophil development and its implications for cancer progression. We identify the cationic amino acid transporter Slc7a7 as a critical regulator of neutrophil maturation and function. Loss of Slc7a7 disrupts differentiation trajectories, reduces pro-inflammatory responses, and diminishes neutrophil extracellular trap (NET) formation. Remarkably, Slc7a7 deficiency delays tumor progression in a melanoma model, highlighting amino acid metabolism as a promising therapeutic target to modulate neutrophil responses in inflammatory diseases and cancer. Collectively, this thesis provides a comprehensive exploration of stem and progenitor cell biology across diverse pathological contexts, offering novel insights into clonal dynamics, differentiation plasticity, and therapeutic interventions. These findings advance our understanding of the cellular hierarchies and molecular pathways that underpin disease progression, with implications for targeted therapies in cancer, cardiovascular disease, and immune dysregulation.
Dissecting TGFβ-Driven Resistance to αPD-L1 Therapy in Colorectal Cancer Liver Metastases. Enhanced T Cell Motility and Proliferation for Effective Anti-Tumor Responses
(Universitat de Barcelona, 2025-01-16) Salvany Celades, Maria; Batlle Gómez, Eduard; Prados Martín, Alejandro; Universitat de Barcelona. Facultat de Biologia
[eng] Colorectal cancer (CRC), particularly its metastatic forms, poses signiﬁcant therapeutic challenges, with immune checkpoint blockade (ICB) therapies providing limited beneﬁts to patients whose metastasis lack T cell inﬁltration. This highlights the need to target mechanisms underlying T cell exclusion to improve clinical outcomes. TGF-β signaling plays a pivotal role in regulating the tumor microenvironment (TME) and promoting immune suppression. Using experimental models of metastatic CRC, we demonstrate how TGF-β inhibition enables immune cell inﬁltration and enhances the efﬁcacy of ICB therapy. Our ﬁndings reveal that TGF-β imposes dual immunosuppressive barriers by preventing the migration of memory-like CD8+ T cells from the periphery into the TME and by directing macrophages to suppress the clonal expansion T cells within metastases. We also observed that while TGF-β signaling drives the formation of a dense, collagen-rich extracellular matrix (ECM), it does not inherently restrict T cell motility within the tumor. Instead, PD-1/PD-L1 interactions primarily regulate T cell movement in the TME. Moreover, our study identiﬁes a key role for TGF-β in instructing tumor-associated macrophages (TAMs) to adopt an immunosuppressive phenotype characterized by SPP1 expression, contributing to immune evasion and metastasis. The TGF-β–SPP1 axis was found to correlate with poor prognosis in CRC patients, emphasizing the therapeutic potential of targeting SPP1+ macrophages to overcome immune suppression. Overall, this study provides novel insights into the mechanisms of TGF-β -mediated immune evasion and highlights the importance of targeting TGF-β signaling in both peripheral T cells and TAMs to improve the efﬁcacy of ICB therapies in metastatic CRC.
Understanding, predicting and preventing the impact of nonsense mutations on gene expression by deep mutational scanning
(Universitat de Barcelona, 2025-01-17) Toledano Martin, Ignasi; Supek, Fran; Lehner, Ben, 1978-; Universitat de Barcelona. Facultat de Biologia
[eng] Premature termination codons (PTCs) are responsible for ~10–20% of inherited diseases and represent a major mechanism of tumor suppressor gene inactivation in cancer. Traditionally, PTCs are considered to induce transcript degradation via nonsense-mediated mRNA decay (NMD) and lead to the production of truncated non-functional proteins. Nonsense suppression therapies aim to promote translational readthrough over PTCs, enabling the synthesis of full-length proteins. Both NMD and readthrough modulate the severity of disease phenotypes by regulating the abundance of the mRNA and the full-length protein; respectively. However, their efficiencies vary across PTCs. In this thesis, we employed deep mutagenesis methods to systematically quantify how sequence context and other genetic factors influence the mRNA levels and the full-length protein abundance of PTC-containing transcripts. First, we developed a methodological improvement for deep mutagenesis libraries generation. Second, a comprehensive assessment of drug-induced readthrough was performed, encompassing over 140,000 measurements and generating readthrough scores for 6,000 PTCs that cause genetic diseases and cancer. This massive dataset was subsequently leveraged to elucidate the effect of sequence context on readthrough and to train accurate predictive models to estimate drug-specific PTC readthrough genome-wide. We envisage these datasets will become a valuable resource to improve clinical trial design and the development of personalized nonsense suppression therapies. Third, we combined different libraries to test and extend hypotheses for how PTC position, exon length, sequence context and translation reinitiation interplay to determine NMD efficiency. Overall, this thesis provides a comprehensive view of how the sequence landscape influences the fate of PTC-containing transcripts. More broadly, it demonstrates the effectiveness of deep mutagenesis in uncovering sequence-to- activity relationships, highlighting the potential of this approach for investigating other mRNA-related processes.
CPEB1 and CPEB4 in skin homeostasis and tumorigenesis
(Universitat de Barcelona, 2025-01-24) Ferrer Caelles, Anna; Méndez de la Iglesia, Raúl; Universitat de Barcelona. Facultat de Biologia
[eng] The skin epidermis is a continuously renewing tissue that requires a tightly regulated balance between keratinocyte proliferation and terminal differentiation to ensure proper structure and function. Despite substantial progress in characterizing the epigenomic and transcriptional regulatory mechanisms, the intricate control of epidermal homeostasis is still not fully understood. Emerging evidence is beginning to unveil the important role of post-transcriptional regulation by RNA-binding proteins, providing an additional layer of gene expression control essential for maintaining epidermal homeostasis and influencing skin tumor development. Cytoplasmic Polyadenylation Element Binding Proteins (CPEBs) are a family of four RNA-binding proteins (CPEB1-4) that regulate mRNA translation and stability by dynamically modulating the poly(A) tail length of specific mRNA targets. Although initially discovered during meiotic maturation, CPEBs have also been identified in somatic cells, extending their role beyond meiosis. However, CPEB1 and CPEB4 have not been examined together in the context of epidermal homeostasis, and their specific contributions to this tissue remain unknown. In this work, we have characterized the roles of CPEB1 and CPEB4 in keratinocytes and the interfollicular epidermis. Our findings reveal opposing functions of CPEB1 and CPEB4 in epidermal homeostasis and skin tumorigenesis. We have identified their mRNA targets in keratinocytes and uncovered a novel and contrasting role of CPEB1 and CPEB4 in keratinocyte differentiation. Both proteins are upregulated during keratinocyte differentiation and mediate a specific post-transcriptional control that fine-tunes cellular profiles toward either proliferation or differentiation. Notably, by focusing on the Notch signaling pathway, we found that the deletion of CPEB1 and CPEB4 in keratinocytes results in opposing patterns of Notch activation, which correlate with distinct keratinocyte differentiation states. Altogether, our results provide mechanistic insights into how CPEB1 and CPEB4 are involved in keratinocyte differentiation, potentially through the modulation of Notch signaling. This study further underscores the relevance of post-transcriptional regulation by RNA-binding proteins in maintaining tissue homeostasis and offers new perspectives on the role of CPEBs in skin biology.
Deciphering the importance of heterogeneity in Myotonic Dystrophy type 1
(Universitat de Barcelona, 2024-12-16) Núñez Manchón, Judit; Nogales Gadea, Gisela; Universitat de Barcelona. Facultat de Biologia
[eng] Myotonic dystrophy type 1 (DM1) is a genetic and multisystemic muscular dystrophy with autosomal dominant inheritance. It is caused by a CTG expansion in the 3’ end of DMPK gene. Symptoms are mainly caused by the accumulation of toxic RNA aggregates, called RNA foci, which sequester MBNL1 protein, a splicing regulator. The symptoms can appear at any age and they are highly heterogeneous between patients. This heterogeneity is partially derived from the CTG repeat length, which due to both somatic and intergenerational instability, differs both between patients and between different tissues of a single patient. In this thesis the main focus is put on DM1 heterogeneity, which is often ignored in studies. Heterogeneity is an important feature to consider because it could have an influence in the molecular DM1 alterations at cellular level and in the efficacy of a therapy, meaning that DM1 models representing said heterogeneity would be useful. The thesis is divided in three chapters, each of which, explores DM1 heterogeneity from a different perspective. Chapter 1 is focused on the study of heterogeneity from a molecular point of view. The study analyses differences in RNA foci and MBNL1 aggregates expression between different cell types or DM1 subtypes. On the one hand, the analysis of four different cell types (lymphoblasts, fibroblasts, myoblasts and myotubes) revealed significant differences between them, being myotubes the cell type with a higher number of RNA foci and myoblasts the cell type with a higher MBNL1 sequestration. Myoblasts were also used to perform a single cell study to determine heterogeneity in expression levels and whether it correlates with the number of RNA foci expressed in the same cell. Results revealed no correlation. On the other hand, the analysis of RNA foci in the 5 subtypes of DM1 (congenital, infantile, juvenile, adult and late-onset) revealed a higher accumulation of RNA foci in patients with an earlier age of onset. In this chapter the existence of molecular heterogeneity both between and within patients is confirmed. Chapter 2 is focused on how DM1 heterogeneity impacts the degree of efficacy of a treatment. The study assesses the therapeutic potential of antagomiRs 23b and 218, two antisense oligonucleotides that block MBNL1 repressors miRNAs 23b and 218. A previous study proved that these antagomiRs have a positive impact in DM1 pathogenesis, however DM1 heterogeneity was not assessed. In this study eight independent human DM1 primary myoblast lines with CTG repeats ranging from 117 to 1054 were treated with both antagomiRs. It was found that miR-23b and 218 are upregulated in patient myoblasts and that miRNAs overexpression correlated with CTG expansion size. The treatment reduced the miRNAs activity, increasing MBNL1 protein levels and reducing DMPK expression and foci number. Moreover, MBNL1- dependent splicing events were significantly rescued and the degree of MBNL1 enhancement correlated with splicing rescue. In this chapter it is concluded that antagomiRs 23b and 218 have therapeutic potential across different genetic backgrounds. Chapter 3 is focused on the need for in vitro models to study DM1 and to validate therapies that represent the clinical and genetic heterogeneity observed in DM1 patients. In the study, three DM1 muscle lines derived from patients with different DM1 subtypes and clinical backgrounds were immortalized and characterized at the genetic, epigenetic, and molecular levels. Results showed that the three immortalized cell lines displayed all the expected DM1 hallmarks with significant differences between the cell lines for several of the studied alterations. Moreover, the response of the immortalized cell lines to the previously tested therapeutics was also analysed with positive results. In this chapter it is concluded that the three immortalized DM1 cell lines developed in this study are suitable to study the pathophysiological heterogeneity of DM1 and to test future therapeutic options.
Towards a large-scale human inflammation atlas at single-cell resolution
(Universitat de Barcelona, 2024-12-12) Jiménez Gracia, Laura; Heyn, Holger; Gut, Ivo G.; Universitat de Barcelona. Facultat de Biologia
[eng] Inflammation is a physiological response essential for maintaining homeostasis, but when the immune system becomes dysregulated, it can drive a range of pathological conditions and become a key contributor to many diseases. Understanding these complex, disease-specific inflammatory mechanisms is crucial for developing effective treatments. Single-cell sequencing technologies offer a powerful approach to study the immune system at high resolution, providing detailed insights into cellular heterogeneity and immune dynamics. To fully exploit their potential in large-scale studies, standardized protocols for sample collection and processing, coupled with advanced computational methods for robust data analysis, are needed. Since immune-driven diseases often target specific tissues and exhibit distinct inflammatory profiles, a comprehensive approach is required. Blood, as a minimally invasive sample, offers a valuable opportunity to monitor inflammation by tracking cytokine levels and cellular activity, making it ideal for elucidating disease mechanisms and therapeutic responses. In this thesis, experimental protocols and computational approaches were developed for large-scale studies focused on analyzing human inflammatory profiles using single-cell RNA sequencing (scRNA-seq). First, we implemented FixNCut, a protocol that preserves transcriptional profiles and tissue composition by fixing samples at the time of collection, enabling subsequent tissue dissociation with minimal stress-induced artifacts. We then generated a comprehensive reference of the inflammatory spectrum in circulating immune cells using single-cell transcriptomic profiles from over 1,000 patients suffering from 20 immune-driven diseases and healthy individuals. By analyzing the immune cell composition and inflammatory molecule expression, we characterized the immune response across diseases, identifying both commonalities and disease-specific differences. Using interpretable machine learning algorithms, we captured disease-specific inflammatory genes at the cell type level that could serve as clinical biomarkers. Furthermore, we proposed a framework for classifying patients based on their blood-derived inflammatory profiles. Finally, we studied the immunomodulatory effects of albumin treatment in patients with acute decompensated cirrhosis, which resulted in immune transcriptional reprogramming that primarily affected B lymphocytes and enhanced neutrophil antimicrobial activity, boosting the patients' immune response against infections. In summary, this thesis integrates scRNA-seq experimental and computational methods to facilitate large-scale, decentralized research on immune-driven diseases with the goal of applying these approaches for disease diagnosis, monitoring progression, and assessing therapy responses in clinical settings.
Enhancing variant classification in hereditary breast and ovarian cancer predisposition genes through splicing analysis and new tumour evidence
(Universitat de Barcelona, 2024-12-09) Domènech Vivó, Joanna; Gutiérrez Enríquez, Sara; Díez Gibert, Orland; Universitat de Barcelona. Facultat de Biologia
[eng] The clinical management of hereditary breast and ovarian cancer (HBOC) families relies on identifying germline pathogenic variants in cancer susceptibility genes, such as BRCA1 and BRCA2. However, genetic testing often yields an inconclusive result due to detection of only neutral variants or to the identification of variants of unknown significance (VUS), whose effects on gene function and associated cancer risk are unknown. While carriers of pathogenic variants benefit from options available for early cancer detection, preventive measures and targeted therapies, VUSs carriers are generally managed without regard to the result of genetic testing, thus limiting the options for these patients. The primary aim of this thesis is to increase the number of patients receiving a genetic diagnosis of HBOC by improving the accuracy of classifying germline genetic variants. To achieve this, we focused on improving the detection of potentially splicing-altering variants in poorly understood deep intronic regions (Part 1), evaluating the relevance of mRNA splicing experimental validation for variant classification (Part 2) and exploring the potential use of tumour information in the classification of germline variants (Part 3). Deep intronic regions may contain variants that affect RNA splicing by introducing “pseudoexons” or other changes, which could potentially explain cases where the genetic cause of HBOC remains unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. In Part 1 of this thesis, we have assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterised the SREs profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. This indicates that intronic regions with a high potential to be included as pseudoexons can be systematically identified throughout the HBOC genes. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. Both tools combined were tested in a tumour RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provided a framework to detect deep intronic variants disrupting splicing. A possible pathogenic mechanism for a subset of VUS is the disruption of normal mRNA splicing. However, experimental validation is generally restricted to variants affecting dinucleotide splice site positions. Consequently, variants outside these regions are not consistently evaluated across laboratories, leading to conflicting and uncertain interpretations. Additionally, variants leading to in- frame isoforms affecting clinically relevant domains are challenging to classify due to the limited knowledge about in-frame encoded proteins. One clear example of both issues are the variants located in the in-frame exon 18 (legacy number) of BRCA1. The results of a comprehensive study conducted within the ENIGMA consortium to identify spliceogenic variants mapping to this exon and characterize the severity of their impact are presented in Part 2 of this thesis. Patient RNA, splicing reporter minigene, and mouse embryonic stem cell (mESC)-based functional assays were combined to determine the impact of 166 variants on splicing and estimate the tolerability functional range of exon 18 skipping (∆18). Splicing, functional and clinical data were integrated for variant interpretation according to the recently ClinGen-approved BRCA1/BRCA2- specified ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular-Pathology) classification guidelines. Our results demonstrated that exon ∆18 is not a rescue event and that per-allele levels up to 34%, combined with at least 59% of the full-length (FL) isoform, are tolerable. Furthermore, we show that applying the recently developed BRCA1/2 specifications significantly reduced the rate of VUS in this exon from 45.7% to 8.5%, being experimental mRNA testing essential in solving uncertainty for approximately 10% of variants Lastly, despite the existence of multiple types of evidence for classifying germline variants, additional information is still required to classify many of them. Accordingly, we explored the potential use of tumour homologous recombination repair (HRR) status by RAD51 foci immunofluorescence detection (RAD51 test) as a predictor of pathogenicity or benignity for BRCA1/2 and PALB2 germline variants. HRR status by RAD51 test was successfully assessed in a total of 148 primary untreated breast and ovarian tumours, from Vall d’Hebron Hospital, ENIGMA and EraPerMed RAD51predict collaborators. Samples were split into three cohorts depending on patients’ germline status: pathogenic (91), benign (47) and VUS (8). Our results demonstrated that the RAD51 test could distinguish pathogenic from benign variants with high sensitivity (91.5%) and specificity (70.2%) (AUC 0.91). Likelihood ratios (LR) were calculated for the association of RAD51 test outcomes (HRR deficiency-HRD or proficiency-HRP), with BRCA1, BRCA2 and PALB2 variant pathogenicity considering patients' clinical features. Then LR estimates were aligned to ACMG/AMP code strengths. Overall, RAD51-HRD status provided moderate evidence for pathogenicity if detected in primary breast tumours diagnosed before age 50, whereas RAD51-HRP provided informative moderate evidence against pathogenicity if detected in primary breast tumour independently of age at diagnosis. Lastly, we applied our recommendations to classify the eight VUS and about 38% (3/8) of variants were classified as likely benign, thus demonstrating the utility of the RAD51 test in variant classification.
Monocytes and macrophages in cancer: investigating their potential as disease biomarkers and therapeutic targets
(Universitat de Barcelona, 2024-12-02) Paul, Tony; Sarrias Fornés, Maria Rosa; Universitat de Barcelona. Facultat de Biologia
[eng] Cancer is the leading cause of death worldwide, with lung and liver cancers being major contributors. Liver cancer is often preceded by cirrhosis, considered as the final stage of chronic liver disease. Recognizing the crucial role of the immune system in cancer, ongoing research focuses on improving immunotherapy effectiveness to benefit a broader patient population. Circulating monocytes and tumor-associated macrophages (TAMs) play key roles in the immune response, contributing to tumor progression, treatment outcomes, and survival in various cancers, including lung and liver. TAMs are the most abundant immune cells in the tumor microenvironment (TME). They can adopt either a pro-inflammatory (M1) or immunosuppressive (M2) phenotype, with the M2 correlating with poorer survival outcomes in cancers. Current research is exploring TAM reprogramming as a novel cancer immunotherapy, with monoclonal antibodies offering safer and more effective alternatives to chemotherapy. On the other hand, monocytes are promising biomarker candidates due to their diverse phenotype and accessibility. The two main objectives of this thesis were to investigate the role of macrophage secreted protein CD5L expression in TAMs in lung and liver cancers, contributing to the development of a new CD5L-targeted immunotherapy, and to analyze the proteome of circulating monocytes in cirrhosis and liver cancer to identify new biomarkers and altered biological pathways occurring in hepatocellular carcinoma (HCC). We show that CD5L expression in TAMs is linked to poor prognosis in papillary lung adenocarcinoma (PAC) and HCC. Additionally, targeting CD5L in a mouse model reduced tumor size and reprogrammed the TME into a pro-inflammatory state. We also discovered deregulated pathways affecting monocyte activity in cirrhosis and HCC, and identified a new cell receptor panel as a potential blood-based biomarker for HCC. These findings mark significant progress in creating a novel anticancer immunotherapy that induces beneficial changes in the TME and identifying a promising biomarker for HCC detection.
Spatiotemporal Changes in Mountain Plant Communities of the Central-Eastern Region of the Trans-Mexican Volcanic Belt Over the Last 17,000 Years
(Universitat de Barcelona, 2024-11-26) Rodríguez Pérez, Erandi Tzayani; Montoya Romo, Encarnación; Universitat de Barcelona. Facultat de Biologia
[eng] Neotropical mountains are known for their high biodiversity and endemism, providing numerous ecosystem services to the surrounding areas. However, mountain biodiversity is rapidly declining due to climate change and anthropogenic activities. The present thesis uses pollen analysis to investigate changes in high mountain neotropical plant communities in the central-eastern region of the Trans- Mexican Volcanic Belt (TMVB), in Central Mexico, over the past 17 kyr. Two study sites have been integrated into this thesis: Cofre de Perote and Iztaccíhuatl volcanos. At an elevation of 3700 m asl, the pollen assemblage of a sedimentary record from Cofre de Perote volcano was analysed, supported by charcoal, Magnetic Susceptibility (MS), and Ti concentration analyses. This research documented the vegetation reorganisation and plant colonisation of high elevations after the glacial retreated due to temperature increase during the Early and Mid-Holocene. The results suggested that during the Early Holocene, forests were maybe closer and/or at higher elevations in Cofre de Perote, near the coast, than at similar elevations in inland sites. The results also revealed that the influence of winds on long-distance pollen arrival could play a crucial role in understanding the pollen assemblages in highland sites. Additionally, Picea pollen presence indicated the occurrence of non-analogue communities in this site and its potential role as microrefugia during the Early Holocene. In the Iztaccíhuatl volcano, the pollen deposition in surface soil samples from the current plant communities along an elevation gradient was analysed. The results suggested that high percentages of Abies were related to the presence of a Fir Forest. High Pinus values and Arceuthobium pollen presence could be associated with Pine Forest. Pollen taxa such as Apiaceae, Eryngium, Valerianaceae, and Caryophyllaceae are linked to Pine Forest and Alpine Grassland. Secondly, the research focused on studying past plant communities' distribution along the volcano's elevation gradient via pollen analysis of palaeosol samples from three elevation transects. The samples collected in each elevation transect spanned a specific age (time window) during the Late Quaternary. The recovery of samples was made using three tephras that potentially sealed the soil protecting the palynomorphs from degradation, and at the same time, worked as chronostratigraphic markers for this research: Tutti Frutti (~17 cal kyr BP), Ochre (~5.7 cal kyr BP), and Pink (~1.1 cal kyr BP/840 CE) Pumices. In addition, the eruption events resulting in the tephra deposits occurred coeval to three distinct climatic events: Heinrich Event-1 (HE-1), Holocene Thermal Maximum (HTM), and Medieval Climatic Anomaly (MCA). Results indicated that samples at ~17 cal kyr BP lack sufficient pollen grains to propose an accurate paleoenvironmental interpretation. At ~5.7 cal kyr BP, high Poaceae pollen values suggested the extensive presence of open vegetation. At ~1.1 cal kyr BP, the presence of Mixed Forest between ~3300 and 3450 m asl, Pine Forest between 3450 and 3700 m asl, and a more extended ecotone zone between Pine Forest and Alpine Grassland was proposed. Inferred plant community distribution and structure changes at ~5.7 and ~1.1 cal yr BP may be linked to warm and dry conditions during HTM and MCA, which seemed to have a larger effect on trees than on herbs. The join interpretation of this thesis has revealed the vulnerability of coniferous forests to global warming and human activities. These past and current threats could be involved in: (i) a possible recent expansion of Fir Forest around the Iztaccíhuatl volcano and other areas of the TMVB; and (ii) the evidence of Picea local extinction in TMVB during the Early Holocene, suggesting that species with restricted distributions or isolated populations are at risk. Finally, the importance of natural reserves and conservation programs is highlighted.
Characterization of maternal histone mRNAs
(Universitat de Barcelona, 2024-11-29) Pérez Roldán, Juan Francisco; Azorín, F.; Carbonell Sanroma, Albert; Universitat de Barcelona. Facultat de Biologia
[eng] In eukaryotes, histone proteins bind and pack genomic DNA into chromatin. The basic structural subunit of chromatin is the nucleosome, which is formed by the interaction of an octamer of the core histone proteins H2A, H2B, H3 and H4 with 147 bp of DNA. In addition, linker histones H1 bind to the nucleosome core particle at the entry/exit site of nucleosomal DNA and interact with the internucleosomal linker DNA. According to their pattern of expression during the cell cycle, histones are classified into replication dependent (RD), whose expression is tightly linked to DNA replication, and replication independent (RI). RD histones include the four canonical core histones and most linker histones H1 and are involved in packaging the newly generated DNA during replication. On the other hand, histone variants are generally RI. RD histone mRNAs are distinct from every other mRNA in the cell since they are not polyadenylated. Instead, they have a conserved sequence forming a stem-loop at the 3’UTR, which is recognized by the Stem-Loop Binding Protein (SLBP). SLBP is responsible for processing, stabilization, and translation of RD histone mRNAs, as well as for cell cycle coordination of their expression. In contrast, RI histone mRNAs are polyadenylated. In metazoans, early embryogenesis usually involves rapid nuclear divisions in the absence of zygotic expression. The number and speed of these divisions are generally higher in species with external development. In Drosophila, there are 13 syncytial nuclear divisions before zygotic genome activation (ZGA). During these early divisions, dSLBP is absent, and packaging of the rapidly generated DNA relies on maternal histones. Core RD histones are maternally deposited as both proteins and mRNAs. Instead, we found that the single RD linker histone of Drosophila, dH1, is deposited only as mRNAs. In addition to dH1, Drosophila encodes for a germline-specific linker histone dBigH1 variant, which is maternally deposited as both protein and mRNA. In this study, we show that, in Drosophila, maternally deposited RD histone mRNAs are polyadenylated and have a truncated 3’UTRs that disrupts the characteristic 3’ stem-loop structure. We also show that these unusual RD histone transcripts are generated during oogenesis, in stage 10 egg chambers, through an alternative processing that surprisingly requires dSLBP and involves cytoplasmic polyadenylation. Polyadenylation of maternal RD histone mRNAs does not appear to be restricted to Drosophila since it is also observed in Xenopus, which also undergoes external development. Intriguingly, we found that maternal RD histone mRNAs remain largely untranslated during early embryogenesis. In particular, despite being maternally deposited as mRNAs, expression of the single RD linker histone of Drosophila, dH1, is not detected during the early embryo divisions. Instead, at these stages, the germline-specific linker histone dBigH1 variant is expressed. dH1 expression starts at nuclear division 6 and increases progressively during ZGA, fully replacing dBigH1 at cellularization. Notably, we found that loss of dBigH1 in homozygous null bigH1 mutant embryos induces the early expression of dH1 from the first nuclear division, which is concomitant to increased translation of maternal dH1 mRNAs. Interestingly, homozygous null bigH1 mutant embryos progress normally through development. These results unveil the compensatory expression of dH1 in the absence of dBigH1, supporting functional redundancy of dBigH1 and dH1 during early embryogenesis. Finally, we show that translation of the rest of maternal RD histone transcripts is also increased in the absence of dBigH1. Altogether, these results suggest that translation of the maternal pool of RD histone transcripts serves as a backup mechanism that is induced in response to reduced supply of maternal histone proteins.
WNT pathway regulation of lipid handling and inflammation in organ function: the role of LRP5
(Universitat de Barcelona, 2024-10-09) Luquero Gomez, Aureli; Borrell Pagès, Maria; Badimón, Lina, 1953-; Universitat de Barcelona. Facultat de Biologia
[eng] INTRODUCTION: cardiovascular diseases are the first cause of premature mortality worldwide. Atherosclerosis is the most common underlying cause of cardiovascular disease. This is a complex condition triggered by the accumulation of modified cholesterol in the vascular wall, which induces inflammatory and fibrotic processes. Hypercholesterolemia is the elevation of circulating cholesterol levels in blood, which affects cholesterol homeostasis in different tissues and organs. Canonical WNT pathway is an evolutionary conserved signalling pathway with a role in embryonic development and cell fate. Low-density Lipoprotein Receptor – related protein 5 (LRP5) is a receptor that triggers the canonical WNT signalling and uptakes circulating low-density lipoproteins (LDL). It is our hypothesis that LRP5 and the canonical WNT signalling play a key role in the cellular response to cholesterol exposure in different tissues. OBJECTIVES: the aim of this thesis is to identify the role of LRP5 in different cell types and tissues modulated by hypercholesterolemia including circulating macrophages and cell lineages of the liver and the adipose tissue. Additionally, this thesis focuses on the study of LRP5 roles during the inflammatory response induced by atherosclerosis and its role in the brain (an organ with a heavily regulated cholesterol homeostasis).
Exploring the chromatin landscape and gene expression mechanisms
(Universitat de Barcelona, 2024-10-15) Sala Huerta, Alba; Orozco López, Modesto; Battistini, Federica; Universitat de Barcelona. Facultat de Biologia
[eng] The interplay between chromatin, transcription factors and genes defines a complex gene regulatory system whose study is essential to understand cell differentiation and how relevant cell functions are maintained or disrupted during biological processes. This is the main area of interest of what is known as 4D genomics, a field that has been evolving on the wave of high-throughput methods producing extensive amounts of data on gene location, chromatin structure and gene expression. 4D genomics data is each day more accessible, the challenge being to interpret it. In this sense Machine Learning (ML) and Artificial Intelligence (AI) methods are becoming crucial to transform noisy experimental data into biological information. The aim of this thesis is to untangle some of the mechanisms that constitute regulatory networks while integrating various state-of-the-art techniques to further understand some of the currently unanswered challenges. During my PhD thesis I have been exploring the chromatin landscape and gene expression mechanisms at different levels of detail and this volume summarizes the main results obtained. In the Introduction, a brief overview of gene expression and transcriptional regulation mechanisms is provided. I also discuss the underpinnings of chromatin organization and stress conditions. Chapters 1 through 5 are a compendium of articles where I describe the different research projects that I undertook during my PhD thesis. These projects have either been published in peer-review journals, are currently under review or in preparation. More specifically in Chapter 1 we started by studying the first regulatory layer, the double-stranded helical structure of DNA and its binding to effector proteins. We developed a ML model that predicted with high accuracy the in vitro affinities and binding sites of various transcription factors based on physical properties of the DNA. Our method also successfully reproduced in vivo data when combined with a second layer of information, the chromatin organization of the nucleosomes. In Chapter 2 we explored nucleosome positioning preferences in yeast genomic DNA by first developing a predictor of nucleosome free regions around the transcription start and terminating sites which are known to comprise critical binding sites. Our method allowed us to predict the nucleosome architecture within gene bodies by using signal theory from two strongly positioned nucleosomes referred to as +1 and -last (the nucleosomes immediately downstream of the TSS or upstream of the TTS respectively). We additionally studied the link between nucleosome arrangements and gene expression mechanisms. In Chapter 3, the effects of oxidative stress damage on nucleosome organization and overall chromatin structure are described. In order to clarify the effect of these lesions, we performed statistical analysis on a series of gene expression mechanisms through different experimental techniques such as MNase-Seq, Hi-C and Micro-C experiments. Chapters 4 and 5 introduce the study of RNA as a distinct structure and discuss its properties and capability of playing a key role in some regulatory mechanisms such as triplex forming oligonucleotides. A general discussion that encompasses the significance and future perspectives of these 5 projects is presented in Chapter 6, together with the main conclusions of this work in Chapter 7.

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