Biology subjects

Prosper, F.

Publications and source records attributed to Prosper, F..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

In vivo generation of heart and vascular system by blastocyst complementation

The generation of organs from stem cells by blastocyst complementation is a promising approach to cover the clinical need for transplants. In order to generate rejection-free organs, complementation of both parenchymal and vascular cells must be achieved, as endothelial cells play a key role in graft rejection. Here we used a lineage-specific cell ablation system to produce mouse embryos unable to form both the cardiac and vascular systems. By mouse intraspecies blastocyst complementation we rescued heart and vascular development separately and in combination, obtaining complemented hearts with cardiomyocytes and endothelial cells of exogenous origin. Complemented chimeras were viable and reached adult stage, showing normal cardiac function and no signs of histopathological defects in the heart. Furthermore, we implemented the cell ablation system for rat-to-mouse blastocyst complementation, obtaining xenogeneic hearts whose cardiomyocytes were completely of rat origin. These results represent an advance in the experimentation towards the in vivo generation of transplantable organs.

cell biology↗

bioRxiv2022

Systematic functional screening of chromatin factors identifies strong lineage and disease dependencies in normal and malignant haematopoiesis

Interactions between transcription factors (TF) and chromatin factors (CF) regulate gene expression programmes to determine cellular fate. However, unlike for TF, the exact role of CF in this process is poorly understood. Using haematopoiesis as a model system and utilising novel functional CRISPR screens ex vivo and in vivo, coupled with Perturb-Seq, CF binding and genome-wide chromatin accessibility in primary murine cells, we assess the role of 550 chromatin factors in lineage choice in normal haematopoiesis and the maintenance of acute myeloid leukaemia (AML). These studies demonstrate marked specificity for a large number of CFs in lineage determination, highlighting functional diversity within specific families of chromatin regulators, including MLL-H3K4-methyltransferases and different BAF-complexes, that regulate disparate lineage decisions across haematopoiesis. Conversely, we demonstrate that unrelated Repressive complexes function similarly to restrain excessive myeloid differentiation and protect lineage diversity. We identify interactions between CF and TF that, at least in part, explain the regulatory function of CF and link Brd9-loss to a premalignant state. Utilising similar experiments in a relevant murine AML model, we demonstrate opposing effects for CF in normal haematopoiesis and AML, where MLL-H3K4-methyltransferases, c-BAF-remodelers and Repressive complexes prevent differentiation and maintain leukaemic fitness. We show that this alteration relates to differential utilisation of TF by CF complexes between normal and malignant haematopoiesis, highlighting corrupted TF-CF interactions as potential novel avenues for therapeutic intervention in AML. Together, this study provides novel insights on the functional diversity of chromatin factors in governing cell-fate.

genomics↗

bioRxiv2022

An Atlas of Cells in the Human Tonsil

Palatine tonsils are secondary lymphoid organs representing the first line of immunological defense against inhaled or ingested pathogens. Here, we present a comprehensive census of cell types forming the human tonsil by applying single-cell transcriptome, epigenome, proteome and adaptive immune repertoire sequencing as well as spatial transcriptomics, resulting in an atlas of >357,000 cells. We provide a glossary of 121 annotated cell types and states, and disentangle gene regulatory mechanisms that drive cells through specialized lineage trajectories. Exemplarily, we stratify multiple tonsil-resident myeloid slancyte subtypes, establish a distant BCL6 superenhancer as locally active in both follicle-associated T and B cells, and describe SIX5 as a potentially novel transcriptional regulator of plasma cell maturation. Further, our atlas is a reference map to understand alterations observed in disease. Here, we discover immune-phenotype plasticity in tumoral cells and microenvironment shifts of mantle cell lymphomas (MCL). To facilitate such reference-based analysis, we develop HCATonsilData and SLOcatoR, a computational framework that provides programmatic and modular access to our dataset; and allows the straightforward annotation of future single-cell profiles from secondary lymphoid organs.

immunology↗

bioRxiv2022

The transcriptional regulator Sin3A balances IL-17A and Foxp3 expression in primary CD4 T cells

The Sin3 transcriptional regulator homolog A (Sin3A) is the core member of a multi-protein chromatin-modifying complex known to control gene transcription via epigenetic mechanisms. Its inactivation in developing thymocytes halts T cell maturation. We and others had previously shown that Sin3A controls STAT3 transcriptional activity. Given the role of STAT3 in the differentiation of T helper 17 cells critical in inflammatory disorders and against opportunistic infections, we asked whether Sin3A could also contribute to their differentiation. To this aim, we exploited CD4-Cre and CD4-CreERT2deleter strains for conditional and inducible Sin3A deletion in CD4 cell subsets. We report that Sin3A inactivation in vivo arrested thymocyte development at the double positive stage, hindering the characterization of mature T cells. At difference, tamoxifen-inducible Sin3A deletion proved permissive for in vitro proliferation of T cells in Th17 skewing conditions and the acquisition of memory markers. Transcriptional profiling indicated that while Sin3A inactivation imprinted T cells with a mTORC1 signaling gene signature, Sin3A deficient cells lacked the expression of IL-17A, the signature Th17 cytokine. This reflected a defective induction of Il17a, and also of the Il23R and Il22 genes, which occurred in spite of proper upregulation of the lineage defining transcription factor ROR{gamma}t. We found that Sin3A inactivation was paralleled by increased STAT3 phosphorylation and nuclear representation, and by higher fractions of IL-2 and FoxP3 expressing cells. Such events proved causally linked as inhibiting Foxp3 partially rescued IL-17A expression, and neutralizing IL-2 simultaneously lowered the representation of FoxP3+cells, while rescuing IL- 17A+ ones. Thus, together our data underline a previously unappreciated role for Sin3A in Th17 differentiation and the shaping of their immunoregulatory potential. StatementThis study identifies a new role for the transcriptional regulator Sin3A in the shaping of Th17 cell differentiation. Data indicate that by controlling IL-2 expression, and mTORC1 signaling, it balances IL-17A and Foxp3 levels, shaping Th17 inflammatory potentials.

immunology↗

bioRxiv2022

Revealing cell populations catching the early stages of the human embryo development in naive pluripotent stem cells

Naive human pluripotent stem cells (hPSCs) are defined as the in vitro counterpart of the human preimplantation embryos epiblast and are used as a model system to study developmental processes. In this study, we report the discovery and characterization of distinct cell populations coexisting with epiblast-like cells in 5iLAF naive human induced PSCs (hiPSCs) cultures. Noteworthily these populations closely resemble different cell types of the human embryo at early developmental stages. While epiblast-like cells represented the main cell population, interestingly we detected a cell population with gene and transposable element expression profile closely resembling the totipotent 8-Cell (8C) stage human embryo, and three cell populations analogous to trophectoderm (TE) cells at different stages of their maturation process: transition, early and mature stage. Thus, 5iLAF naive hiPSCs cultures provide an excellent opportunity to model the earliest events of human embryogenesis, from the 8C stage to the peri-implantation period. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/482812v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@11b680eorg.highwire.dtl.DTLVardef@4c7e0forg.highwire.dtl.DTLVardef@1e84568org.highwire.dtl.DTLVardef@24ee65_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

WAT3R: Recovery of T-Cell Receptor Variable Regions From 3' Single-Cell RNA-Sequencing

SummaryDiversity of the T-cell receptor (TCR) repertoire is central to adaptive immunity. The TCR is composed of and {beta} chains, encoded by the TRA and TRB genes, of which the variable regions determine antigen specificity. To generate novel biological insights into the complex functioning of immune cells, combined capture of variable regions and single-cell transcriptomes provides a compelling approach. Recent developments enable the enrichment of TRA and TRB variable regions from widely used technologies for 3-biased single-cell RNA-sequencing (scRNA-seq). However, a comprehensive computational pipeline to process TCR-enriched data from 3 scRNA-seq is not available. Here we present an analysis pipeline to process TCR variable regions enriched from 3 scRNA-seq cDNA. The tool reports TRA and TRB nucleotide and amino acid sequences linked to cell barcodes, enabling the reconstruction of T-cell clonotypes with associated transcriptomes. We demonstrate the software using peripheral blood mononuclear cells (PBMCs) from a healthy donor and detect TCR sequences in a high proportion of single T-cells. Detection of TCR sequences is negligible in non-T-cell populations, demonstrating specificity. Finally, we show that TCR clones are larger in CD8 Memory T-cells than other T-cell types, indicating an association between T-cell clonotypes and differentiation states. Availability and implementationThe Workflow for Association of T-cell receptors from 3 single-cell RNA-seq (WAT3R), including test data, is available on GitHub (https://github.com/mainciburu/WAT3R), Docker Hub (https://hub.docker.com/r/mainciburu/wat3r), and a workflow on the Terra platform (https://app.terra.bio). The test dataset is available on GEO (accession number pending).

immunology↗

bioRxiv2021

Identifying Lethal Dependencies with HUGE Predictive Power from Large-Scale Functional Genomic Screens

Recent functional genomic screens -such as CRISPR-Cas9 or RNAi screening-have fostered a new wave of targeted treatments based on the concept of synthetic lethality. These approaches identified LEthal Dependencies (LEDs) by estimating the effect of genetic events on cell viability. The multiple-hypothesis problem related to the large number of gene knockouts limits the statistical power of these studies. Here, we show that predictions of LEDs from functional screens can be dramatically improved by incorporating the "HUb effect in Genetic Essentiality" (HUGE) of gene alterations. We analyze three recent genome-wide loss-of-function screens - Project Score, CERES score and DEMETER score-identifying LEDs with 75 times larger statistical power than using state-of-the-art methods. HUGE shows an increased enrichment in a recent harmonized knowledgebase of clinical interpretations of somatic genomic variants in cancer (with an AUROC up to 0.87). Our approach is effective even in tumors with large genetic heterogeneity such as acute myeloid leukemia, where we identified LEDs not recalled by previous pipelines, including FLT3-mutant genotypes sensitive to FLT3 inhibitors. Interestingly, in-vitro validations confirm lethal dependencies of either NRAS or PTPN11 depending on the NRAS mutational status. HUGE will hopefully help discover novel genetic dependencies amenable for precision-targeted therapies in cancer.

genomics↗

bioRxiv2021

Transcriptional regulation of HSCs in Aging and MDS reveals DDIT3 as a Potential Driver of Transformation

Myelodysplastic syndromes (MDS) are hematopoietic stem cell (HSC) malignancies characterized by ineffective hematopoiesis, with increased incidence in elderly individuals. In this work, we analyzed the transcriptome of human HSCs purified from young and elderly healthy donors, as well as MDS patients, identifying transcriptional alterations following eight different patterns of expression. While aging-associated lesions seemed to predispose HSCs to myeloid transformation, disease-specific alterations may trigger MDS development. Among MDS-specific lesions, we detected the upregulation of the transcription factor DDIT3. Overexpression of DDIT3 in human healthy HSCs induced an MDS-like transcriptional state, and a delay in erythropoiesis. Such effect was associated with downregulation of transcription factors required for normal erythropoiesis, and with a failure in the activation of their transcriptional programs. Moreover, DDIT3 knockdown in CD34+ cells from MDS patients with anemia was able to restore erythropoiesis. These results identify DDIT3 as a driver of dyserythropoiesis, and a potential therapeutic target to restore the inefficient erythropoiesis characterizing MDS patients. STATEMENT OF SIGNIFICANCEThis study defines how human aging and MDS development are characterized by transcriptional alterations in HSCs that follow different patterns, some of which may contribute to myeloid transformation. Among them, we demonstrate how MDS-specific upregulation of DDIT3 in HSCs induces dyserythropoiesis, while its knockdown in HSPCs from MDS patients restores proper erythroid differentiation.

cancer biology↗

bioRxiv2021

A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

Synthetic Lethality (SL) is a promising concept in cancer research. A number of computational methods have been developed to predict SL in cancer metabolism, among which our network-based computational approach, based on genetic Minimal Cut Sets (gMCSs), can be found. A major challenge of these approaches to SL is to systematically consider tumor environment, which is particularly relevant in cancer metabolism. Here, we propose a novel definition of SL for cancer metabolism that integrates genetic interactions and nutrient availability in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase inhibition in different environments. Finally, our novel approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

systems biology↗

bioRxiv2021

A diabetic milieu increases cellular susceptibility to SARS-CoV-2 infections in engineered human kidney organoids and diabetic patients

SARS-CoV-2 infections lead to a high risk of hospitalization and mortality in diabetic patients. Why diabetic individuals are more prone to develop severe COVID-19 remains unclear. Here, we established a novel human kidney organoid model that mimics early hallmarks of diabetic nephropathy. High oscillatory glucose exposure resulted in metabolic changes, expansion of extracellular membrane components, gene expression changes determined by scRNAseq, and marked upregulation of angiotensin-converting enzyme 2 (ACE2). Upon SARS-CoV-2 infection, hyperglycemic conditions lead to markedly higher viral loads in kidney organoids compared to normoglycemia. Genetic deletion of ACE2, but not of the candidate receptor BSG/CD147, in kidney organoids demonstrated the essential role of ACE2 in SARS-CoV-2 infections and completely prevented SARS-CoV-2 infection in the diabetogenic microenvironment. These data introduce a novel organoid model for diabetic kidney disease and show that diabetic-induced ACE2 licenses the diabetic kidney to enhanced SARS-CoV-2 replication.

cell biology↗

bioRxiv2021

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single cell resolution

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single cell RNA sequencing (scRNAseq) to characterize an enriched population of human hematopoietic stem and progenitor cells (HSPC) obtained from young and elderly healthy individuals. Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain age-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRN regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2 and RUNX1 suggesting a role of these TF in the pathogenesis of the disease. In summary, we demonstrate that the combination of single cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.

genomics↗

bioRxiv2021

Deep deconvolution of the hematopoietic stem cell regulatory microenvironment reveals a high degree of specialization and conservation between mouse and human.

Understanding the regulation of normal and malignant human hematopoiesis requires comprehensive cell atlas of the hematopoietic stem cell (HSC) regulatory microenvironment. Here, we develop a tailored bioinformatic pipeline to integrate public and proprietary single-cell RNA sequencing (scRNA-seq) datasets. As a result, we robustly identify for the first time 14 intermediate cell states and 11 stages of differentiation in the endothelial and mesenchymal BM compartments, respectively. Our data provide the most comprehensive description to date of the murine HSC-regulatory microenvironment and suggests a higher level of specialization of the cellular circuits than previously anticipated. Furthermore, this deep characterization allows to infer conserved features in human, suggesting that the layers of microenvironmental regulation of hematopoiesis may also be shared between species. Our resource and methodology are a steppingstone towards a comprehensive cell atlas of the BM microenvironment.

immunology↗

bioRxiv2020

scMomentum: Inference of Cell-Type-Specific Regulatory Networks and Energy Landscapes

Recent progress in single-cell genomics has generated multiple tools for cell clustering, annotation, and trajectory inference; yet, inferring their associated regulatory mechanisms is unresolved. Here we present scMomentum, a model-based data-driven formulation to predict gene regulatory networks and energy landscapes from single-cell transcriptomic data without requiring temporal or perturbation experiments. scMomentum provides significant advantages over existing methods with respect to computational efficiency, scalability, network structure, and biological application. AvailabilityscMomentum is available as a Python package at https://github.com/larisa-msoto/scMomentum.git

systems biology↗

bioRxiv2020

BOSO: a novel feature selection algorithm for linear regression with high-dimensional data

MotivationWith the frenetic growth of high-dimensional datasets in different biomedical domains, there is an urgent need to develop predictive methods able to deal with this complexity. Feature selection is a relevant strategy in machine learning to address this challenge. ResultsWe introduce a novel feature selection algorithm for linear regression called BOSO (Bilevel Optimization Selector Operator). We conducted a benchmark of BOSO with key algorithms in the literature, finding a superior performance in highdimensional datasets. Proof-of-concept of BOSO for predicting drug sensitivity in cancer is presented. A detailed analysis is carried out for methotrexate, a well-studied drug targeting cancer metabolism. AvailabilityA Matlab implementation of BOSO is available as a Supplementary Material. Contactfplanes@tecnun.es Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

Renal proximal tubule cell state and metabolism are coupled by nuclear receptors

Kidney disease development is poorly understood due to the complex cellular interactions of more than 25 different cell types, each with specialized functions. Here, we used single cell RNA-sequencing to resolve cell type-specific and cell fraction changes in kidney disease. Whole kidney RNA-sequencing results were strongly influenced by cell fraction changes, but minimally informative to detect cell type-specific gene expression changes. Cell type-specific differential expression analysis identified proximal tubule cells (PT cells) as the key vulnerable cell type in diseased kidneys. Through unbiased cell trajectory analyses, we show that PT cell differentiation state is altered in disease state. Lipid metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and reproducible association with PT cells state. The coupling of cell state and metabolism is established by nuclear receptors such as PPARA and ESRRA that not only control cellular metabolism but also the expression of PT cell-specific genes in mice and patient samples.

cell biology↗

bioRxiv2020

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

We report a systematic analysis of the biological and clinical implications of DNA methylation variability in five categories of B-cell tumors derived from B cells spanning the entire maturation spectrum. We used 2056 primary samples including training and validation series and show that 88% of the human DNA methylome is dynamically modulated under normal and neoplastic conditions. B-cell tumors display both epigenetic imprints of their cellular origin and de novo, disease-specific epigenetic alterations that in part are related to differential transcription factor binding. These differential methylation patterns were used by a machine-learning approach to create a diagnostic algorithm that accurately classifies 14 B-cell tumor entities and subtypes with different clinical management. Beyond this, we identified extensive patient-specific epigenetic variability targeting constitutively silenced chromatin regions, a phenomenon we could relate to the proliferative history of normal and neoplastic B cells. We observed that, depending on the maturation stage of the tumor cell of origin, mitotic activity leaves different imprints into the DNA methylome. Subsequently, we constructed a novel DNA methylation-based mitotic clock called epiCMIT (epigenetically-determined Cumulative MIToses), whose lapse magnitude represents a strong independent prognostic variable within specific B-cell tumor subtypes and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracker of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of the outcome of the patients.

cancer biology↗

bioRxiv2019

Targeting aberrant DNA methylation in mesenchymal stromal cells as a treatment for myeloma bone disease

Multiple myeloma (MM) progression and myeloma-associated bone disease (MBD) are highly dependent on the bone marrow (BM) microenvironment, in particular on mesenchymal stromal cells (MSCs). MSCs from MM patients exhibit an abnormal transcriptional profile, suggesting that epigenetic alterations could be governing the tumor-promoting functions of MSCs and their prolonged osteoblast (OB) suppression in MM. In this study, we analyzed the DNA methylome of BM-derived MSCs from patients with monoclonal gammopathy of undetermined significance, smoldering myeloma and symptomatic MM at diagnosis in comparison with their normal counterparts. DNA methylation alterations were found at each of the myeloma stage in association with deregulated expression levels of Homeobox genes involved in osteogenic differentiation. Moreover, these DNA methylation changes were recapitulated in vitro by exposing MSCs from healthy individuals to MM plasma cells. Pharmacological targeting of DNMTs and G9a with the dual inhibitor CM-272, reverted the expression of aberrantly methylated osteogenic regulators and promoted OB differentiation of MSCs from myeloma patients. Most importantly, in a mouse model of bone marrow-disseminated MM, administration of CM-272 prevented tumor-associated bone loss and reduced tumor burden. Our results demonstrated that not only was aberrant DNA methylation a main contributor to bone formation impairment found in MM patients, but also its targeting by CM-272 was able to reverse MM-associated bone loss.\n\nKEY POINTS- Bone marrow-derived mesenchymal stromal cells (MSCs) from monoclonal gammopathy of undetermined significance, smoldering myeloma and myeloma patients exhibit an aberrant DNA methylome compared to their healthy counterparts.\n- These DNA methylation changes are associated with an altered expression of genes of the Homeobox loci that orchestrate osteogenic differentiation of mesenchymal precursors.\n- MM plasma cell-exposed healthy MSCs recapitulate the DNA methylation alterations observed in MSCs isolated from myeloma patients.\n- Dual targeting of DNMTs and the histone methyltransferase G9a with CM-272 not only controls MM tumor burden but also prevents myeloma-associated bone loss.

cancer biology↗

bioRxiv2019

Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation

Despite recent advances, the dynamics of genome architecture and chromatin function during human cell differentiation and its potential reorganization upon neoplastic transformation remains poorly characterized. Here, we integrate in situ Hi-C and nine additional omic layers to define and biologically characterize the dynamic changes in three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) patients. Beyond conventional active (A) and inactive (B) compartments, an integrative analysis of Hi-C data reveals the presence of a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, we detect that 28% of the compartments change at defined maturation stages and mostly involve the intermediate compartment. The transition from naive to germinal center B cells is associated with widespread chromatin activation, which mostly reverts into the naive state upon further maturation of germinal center cells into memory B cells. The analysis of CLL and MCL neoplastic cells points both to entity and subtype-specific alterations in chromosome organization. Remarkably, we observe that large chromatin blocks containing key disease-specific genes alter their 3D genome organization. These include the inactivation of a 2Mb region containing the EBF1 gene in CLL and the activation of a 6.1Mb region containing the SOX11 gene in clinically aggressive MCL. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

genomics↗