Biology subjects

Carrillo de Santa Pau, E.

Publications and source records attributed to Carrillo de Santa Pau, E..

9 recordsLinked to original sources

bioRxiv2026

GATA4 loss promotes mutant Kras-driven pancreatic ductal adenocarcinoma in the absence of canonical precursor lesions

ABSTRACTGATA6 and GATA4 play key roles in pancreatic development and are essential to maintain the classical transcriptional program in pancreatic ductal adenocarcinoma (PDAC). Using genetic mouse models we show that, in contrast to GATA6, GATA4 is dispensable for the maintenance of acinar homeostasis in the adult pancreas. Deletion of Gata4 in mice expressing mutant Kras in the embryonic pancreas (KG4C) leads to PDAC development in the absence of tissue remodeling, pancreatic intraepithelial neoplasia (PanIN), or other canonical precursor lesions present in Gata4-proficient (KC) mice. Similar observations were made when Gata4 was selectively inactivated in adult, Kras-mutant, acinar cells. We identify Pale Acinar Lesions (PALes) as a previously unrecognized pancreatic lesion, distinct from acino-ductal metaplasia (ADM) and PanINs, present in KC and KG4C mice but not in wild type mice. PALes display weak expression of acinar and ductal markers and lack mucins; they have lower proliferation rates than PanINs. RNA-seq and ChIP-seq reveal that GATA4 and GATA6 partially share genomic binding sites and transcriptomic effects, but they exert opposing influences on mutant Kras-induced, haematopoietic cell-dependent, transcriptional inflammatory programs. Adenoviral-mediated pancreatic expression of IL17 restored the formation of ductal lesions in KG4C mice but failed to rescue PanIN development. Our data indicate that GATA4 functions through the coordinated action of multiple inflammatory factors that are required for ADM/PanIN formation but are dispensable for PDAC development. Collectively, these findings challenge current paradigms of PDAC initiation and progression.

cancer biology↗

bioRxiv2025

FungiGutDB: Curated database for taxonomic assignment of the gut mycobiome by whole genome sequencing

Fungi represent less than 1% of the gut microbiota; However, their importance in host homeostasis and disease is increasingly recognized. Accurate characterization of the gut mycobiome from metagenomic data remains a significant challenge due to the low abundance of fungal DNA, the performance of bacteria-oriented classifiers, and the limited availability of curated fungal reference databases. To overcome these issues, we developed FungiGutDB v1.0, a curated database containing 304 taxa previously identified in culture-dependent human studies, and we integrated the database in a reproducible workflow to ease its application (FungiGut). Benchmarking analyses demonstrated that FungiGut achieved a substantially lower false positive rate in mock communities compared to standard non-gut-specific fungi databases. When applied to real metagenomic datasets, FungiGut successfully characterized the gut mycobiome, identifying Saccharomyces cerevisiae as the predominant species in healthy individuals, along with common dietary fungi found in fermented dairy products (Penicillium camemberti, Debaryomyces hansenii, Kluyveromyces lactis, Pichia kudriavzevii). In contrast, samples from patients with non-responsive celiac disease showed a higher relative abundance of opportunistic pathogens and a lower number of diet-associated taxa, suggesting a trend toward a dysbiotic mycobiome profile. By limiting classification to fungal species previously isolated from the human gut, FungiGut minimizes misclassifications derived from environmental or plant-associated taxa, which often lead to mistaken interpretation of the results. Overall, FungiGut offers a biologically consistent and reproducible approach to gut mycobiome profiling, improving taxonomic accuracy and strengthening confidence in the interpretation of fungal metagenomic data in human microbiome research.

bioinformatics↗

bioRxiv2025

Gut microbial ecosystems differ across metabolic and obesity phenotypes

Obesity is a heterogeneous condition comprising a continuum of phenotypes with various metabolic and inflammatory profiles. Metabolically healthy obesity (MHO) identifies individuals with obesity but a relatively preserved metabolic state. However, the criteria defining MHO remain inconsistent, and little is known about the gut microbiome (GM) features underlying this intermediate phenotype. Here, we aim to describe microbial structures contributing to metabolic health and disease. To do so, we analyzed the GM of 959 individuals classified as metabolically healthy non-obese (MHNO), MHO, metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO), using stool shotgun metagenomics. MHO subjects display intermediate anthropometric and biochemical profiles, with a GM composition and diversity in an in-between state among MHNO and MUO individuals. Network science analyses reveal that metabolic health, rather than obesity, drives microbial connectivity: MHNO and MHO individuals harbor more robust and functionally cohesive microbial networks, whose most influential nodes are focused toward SCFA production. In contrast, MUO and MUNO communities exhibit a dysbiotic state with reduced connectivity and increased influence of low-abundance, ectopic and potentially pro-inflammatory species resulting in a damaged, unstable microbial community network. These findings suggest that metabolic disorders disrupt microbial ecology beyond compositional shifts, emphasizing the need for systems-level approaches. Our findings show differences in microbial connectivity and association patterns across metabolic and obesity phenotypes, shedding light on how distinct microbial structures may contribute to metabolic health and disease.

bioinformatics↗

bioRxiv2023

EPIGENOMIC VARIABILITY AND TRANSCRIPTOMICS AS A NOVEL MULTIOMIC COMPLEMENTARY APPROACH FOR PERSONALIZED NUTRITION IN COLORECTAL CANCER PATIENTS

Food natural compounds are of interest as modulators of cancer progression and prognosis, as they participate in cellular processes such as growth and differentiation, DNA repair, programmed cell death and oxidative stress. Here we select dietary biocompounds for specific subgroups of 285 colorectal adenocarcinoma (COAD) samples by finding bioactives with opposite transcriptomic profiles to the subgroup-specific tumoral transcriptomes, hypothesizing they may counteract the cancer gene-expression profiles. To establish a CRC classification based on epigenetic variability, we selected 2,189 CpGs based on their differentially variable methylation between tumor and normal samples by a combination of linear and Bartlett tests. Samples were meta-clustered by 1) classifying each sample by 8 different methods (including k-means and hierarchical clustering), 2) building a network and 3) meta-clustering it by the edge-betweenness method. We extracted 6 main subgroups, 2 of them with immune-affected transcriptomes. We compared the transcriptomes of the 6 subgroups with the ones of 56 in vitro bioactive studies from GEO by Gene Set Enrichment Analysis (GSEA), resulting in a potential positive effect of resveratrol, japonicone A and vitamin D. In summary, we present a promising in silico strategy to suggest specific bioactives as co-adjuvants in cancer treatment.

bioinformatics↗

bioRxiv2023

Uncovering the link between gut microbiome, highly processed food consumption and diet quality through bioinformatics methods

The consumption of highly processed foods, along with other dietary and lifestyle poor habits, has an impact on health by increasing the risk of several non-communicable pathologies, such as diabetes. Gut microbiome composition, in specific, can be modulated by nutrients, deriving in different metabolic outcomes that have an influence on this high disease susceptibility and making it a possible therapeutic target for these comorbidities. In this work, gut microbiome of 60 and 46 individuals from 2 different studies focused, among other aspects, on diet-microbiome interactions, was characterised. By means of differential abundance analyses and supervised machine learning techniques based on random forest, gradient boosting and support vector machines, a set of microbial genera that could be potential biomarkers for the differentiation of individuals with poorer dietary patterns was discovered, after comparing coincidences in these taxa among classifiers and testing them for significant differences. Among these, Dialister, Phocea and Pseudoflavonifractor were suggested to have a role in the way highly processed foods affect health negatively, along with Prevotellaceae NK3B31 group and an undetermined genus from Muribaculaceae in the opposite sense. Furthermore, all the identified genera in this study had already been linked to type 2 diabetes, among which Bacteroides and Pseudoflavonifractor proved to be differentially abundant in groups of individuals with different levels of biomarkers for this disease. Nevertheless, further research via longitudinal studies and experimental validation of these genera should be carried out to confirm the association of these taxa with diet and diabetes.

bioinformatics↗

bioRxiv2022

Bioinformatic methods for stratification of obese patients and identification of cancer susceptibility biomarkers based on the analysis of the gut microbiome

Obesity has an impact on health by increasing the risk of various diseases. However, these risks might also depend on the metabolic health status, as it seems that metabolically healthy obese subjects are under a reduced risk of suffering comorbidities such as colorectal cancer. The gut microbiome has an effect on obesity and metabolic disorders through several integration pathways, making it a potential therapeutic target for these diseases. In this study, we characterized the gut microbiota of 356 obese and non-obese European individuals with different comorbidities associated with obesity. Using approaches based on supervised machine learning and network biology, we found a set of biomarkers of interest for differentiating metabolically healthy from unhealthy subjects. Then, we performed a linear discriminant analysis of effect size on a population of 1593 colorectal cancer, adenoma and control subjects assembled by the COST Action ML4Microbiome to investigate their role in colorectal cancer risk. Four of our biomarkers appeared in both approaches, suggesting their possible role in colorectal cancer development, prognosis and follow up: Clostridium leptum, Gordonibacter pamelaeae, Eggerthella lenta and Collinsella intestinalis. Further research via longitudinal studies or experimental validation of these microbial species would be necessary to confirm this association.

bioinformatics↗

bioRxiv2018

Epigenomic and functional dynamics of human bone marrow myeloid differentiation to mature blood neutrophils

Neutrophils are short-lived blood cells that play a critical role in host defense against infections. To better comprehend neutrophil functions and their regulation, we provide a complete epigenetic and functional overview of their differentiation stages from bone marrow-residing progenitors to mature circulating cells. Integration of epigenetic and transcriptome dynamics reveals an enforced regulation of differentiation, through cellular functions such as: release of proteases, respiratory burst, cell cycle regulation and apoptosis. We observe an early establishment of the cytotoxic capability, whilst the signaling components that activate antimicrobial mechanisms are transcribed at later stages, outside the bone marrow, thus preventing toxic effects in the bone marrow niche. Altogether, these data reveal how the developmental dynamics of the epigenetic landscape orchestrate the daily production of large number of neutrophils required for innate host defense and provide a comprehensive overview of the epigenomes of differentiating human neutrophils.\n\nKey pointsO_LIDynamic acetylation enforces human neutrophil progenitor differentiation.\nC_LI\n\nO_LINeutrophils cytotoxic capability is established early at the (pro)myelocyte stage.\nC_LI\n\nO_LICoordinated signaling component expression prevents unwanted toxic effects to the bone marrow niche.\nC_LI

immunology↗

bioRxiv2016

Genome-wide Analysis of Differential Transcriptional and Epigenetic Variability Across Human Immune Cell Types

BackgroundA healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability.\n\nResultsWe applied a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16- monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naive T cells, from the same 125 healthy individuals. We discovered substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression were found to be implicated in key immune pathways and to associate with cellular properties and environmental exposure. We also observed increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites were enriched at dynamic chromatin regions and active enhancers.\n\nConclusionsOur data highlight the importance of transcriptional and epigenetic variability for the neutrophils key role as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability.

molecular biology↗

bioRxiv2016

Searching for the chromatin determinants of human hematopoiesis

Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify forty-two human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet

genomics↗