Biology subjects

Cvejic, A.

Publications and source records attributed to Cvejic, A..

11 recordsLinked to original sources

bioRxiv2023

Single-cell multi-omics map of human foetal blood in Down's Syndrome

Downs Syndrome (DS) predisposes individuals to haematological abnormalities, such as increased number of erythrocytes and leukaemia in a process that is initiated before birth and is not entirely understood. To understand dysregulated hematopoiesis in DS, we integrated single-cell transcriptomics of over 1.1 million cells with chromatin accessibility and spatial transcriptomics datasets using human foetal liver and bone marrow samples from three disomic and 15 trisomic foetuses. We found that differences in gene expression in DS were both cell type- and environment-dependent. Furthermore, we found multiple lines of evidence that DS haematopoietic stem cells (HSCs) are "primed" to differentiate. We subsequently established a DS-specific map of enhancer-gene relationships in disomic and trisomic HSCs using 10X Multiome data. By integrating this map with genetic variants associated with blood cell variation, we discovered that trisomy restructured enhancer-gene maps to dysregulate enhancer activity and gene expression critical to erythroid lineage differentiation. Further, as DS mutations display a signature of oxidative stress, we validated both increased mitochondrial mass and oxidative stress in DS, and observed that these mutations preferentially fell into regulatory regions of expressed genes in HSCs. Altogether, our single- cell, multi-omic resource provides a high-resolution molecular map of foetal haematopoiesis in Downs Syndrome and indicates significant enhancer-gene restructuring giving rise to co- occurring haematological conditions.

genomics↗

bioRxiv2021

SMaSH: A scalable, general marker gene identification framework for single-cell RNA sequencing and Spatial Transcriptomics

Spatial transcriptomics is revolutionising the study of single-cell RNA and tissue-wide cell heterogeneity, but few robust methods connecting spatially resolved cells to so-called marker genes from single-cell RNA sequencing, which generate significant insight gleaned from spatial methods, exist. Here we present SMaSH, a general computational framework for extracting key marker genes from single-cell RNA sequencing data for spatial transcriptomics approaches. SMaSH extracts robust and biologically well-motivated marker genes, which characterise the given data-set better than existing and limited computational approaches for global marker gene calculation.

bioinformatics↗

bioRxiv2020

Lineage tracing of human embryonic development and foetal haematopoiesis through somatic mutations

To date, ontogeny of the human haematopoietic system during foetal development has been characterized mainly through careful microscopic observations. Here we used whole-genome sequencing (WGS) of 511 single-cell derived haematopoietic colonies from healthy human foetuses of 8 and 18 post-conception weeks (pcw) coupled with deep targeted sequencing of tissues of known embryonic origin to reconstruct a phylogenetic tree of blood development. We found that in healthy foetuses, individual haematopoietic progenitors acquire tens of somatic mutations by 18 pcw. Using these mutations as barcodes, we timed the divergence of embryonic and extra-embryonic tissues during development and estimated the number of blood antecedents at different stages of embryonic development. Our analysis has shown that ectoderm originates from a smaller set of blood antecedents compared to endoderm and mesoderm. Finally, our data support a hypoblast origin of the extra-embryonic mesoderm and primitive blood in humans.

genomics↗

bioRxiv2020

Integrative Single-cell RNA-Seq and ATAC-Seq Analysis of Human Foetal Liver and Bone Marrow Haematopoiesis

Regulation of haematopoiesis during human development remains poorly defined. Here, we applied single-cell (sc)RNA-Seq and scATAC-Seq analysis to over 8,000 human immunophenotypic blood cells from foetal liver and bone marrow. We inferred their differentiation trajectory and identified three highly proliferative oligopotent progenitor populations downstream from haematopoietic stem cell/multipotent progenitors (HSC/MPPs). Along this trajectory, we observed opposing patterns of chromatin accessibility and differentiation that coincided with dynamic changes in the activity of distinct lineage-specific transcription factors. Integrative analysis of chromatin accessibility and gene expression revealed extensive epigenetic but not transcriptional priming of HSC/MPPs prior to their lineage commitment. Finally, we refined and functionally validated the sorting strategy for the HSC/MPPs and achieved around 90% enrichment. Our study provides a useful framework for future investigation of human developmental haematopoiesis in the context of blood pathologies and regenerative medicine.

cell biology↗

bioRxiv2020

Analysis of Endothelial-to-Haematopoietic Transition at the Single Cell Level identifies Cell Cycle Regulation as a Driver of Differentiation

Haematopoietic stem cells (HSC) first arise during development in the aorta-gonad-mesonephros (AGM) region of the embryo from a population of haemogenic endothelial cells which undergo endothelial-to-haematopoietic transition (EHT). Despite the progress achieved in recent years, the molecular mechanisms driving EHT are still poorly understood, especially in human where the AGM region is not easily accessible. In this study, we took advantage of a human pluripotent stem cell (hPSC) differentiation system and single-cell transcriptomics to recapitulate EHT in vitro and uncover mechanisms by which the haemogenic endothelium generates early haematopoietic cells. We show that most of the endothelial cells reside in a quiescent state and progress to the haematopoietic fate within a defined time window, within which they need to re-enter into the cell cycle. If cell cycle is blocked, haemogenic endothelial cells lose their EHT potential and adopt a non-haemogenic identity. Furthermore, we demonstrated that CDK4/6 and CDK1 play a key role not only in the transition but also in allowing haematopoietic progenitors to establish their full differentiation potential. Therefore, we propose a direct link between the molecular machineries that control cell cycle progression and EHT.

developmental biology↗

bioRxiv2019

Unsupervised generative and graph representation learning for modelling cell differentiation

Using machine learning techniques to build representations from biomedical data can help us understand the latent biological mechanism of action and lead to important discoveries. Recent developments in single-cell RNA-sequencing protocols have allowed measuring gene expression for individual cells in a population, thus opening up the possibility of finding answers to biomedical questions about cell differentiation. In this paper, we explore unsupervised generative neural methods, based on the variational autoencoder, that can model cell differentiation by building meaningful representations from the high dimensional and complex gene expression data. We use disentanglement methods based on information theory to improve the data representation and achieve better separation of the biological factors of variation in the gene expression data. In addition, we use a graph autoencoder consisting of graph convolutional layers to predict relationships between single-cells. Based on these models, we develop a computational framework that consists of methods for identifying the cell types in the dataset, finding driver genes for the differentiation process and obtaining a better understanding of relationships between cells. We illustrate our methods on datasets from multiple species and also from different sequencing technologies.

bioinformatics↗

bioRxiv2019

scAEspy: a unifying tool based on autoencoders for the analysis of single-cell RNA sequencing data

BackgroundSingle-cell RNA sequencing (scRNA-Seq) experiments are gaining ground to study the molecular processes that drive normal development as well as the onset of different pathologies. Finding an effective and efficient low-dimensional representation of the data is one of the most important steps in the downstream analysis of scRNA-Seq data, as it could provide a better identification of known or putatively novel cell-types. Another step that still poses a challenge is the integration of different scRNA-Seq datasets. Though standard computational pipelines to gain knowledge from scRNA-Seq data exist, a further improvement could be achieved by means of machine learning approaches. ResultsAutoencoders (AEs) have been effectively used to capture the non-linearities among gene interactions of scRNA-Seq data, so that the deployment of AE-based tools might represent the way forward in this context. We introduce here scAEspy, a unifying tool that embodies: (1) four of the most advanced AEs, (2) two novel AEs that we developed on purpose, (3) different loss functions. We show that scAEspy can be coupled with various batch-effect removal tools to integrate data by different scRNA-Seq platforms, in order to better identify the cell-types. We benchmarked scAEspy against the most used batch-effect removal tools, showing that our AE-based strategies outperform the existing solutions. ConclusionsscAEspy is a user-friendly tool that enables using the most recent and promising AEs to analyse scRNA-Seq data by only setting up two user-defined parameters. Thanks to its modularity, scAEspy can be easily extended to accommodate new AEs to further improve the downstream analysis of scRNA-Seq data. Considering the relevant results we achieved, scAEspy can be considered as a starting point to build a more comprehensive toolkit designed to integrate multi single-cell omics.

bioinformatics↗

bioRxiv2019

A cellular census of healthy lung and asthmatic airway wall identifies novel cell states in health and disease

Human lungs enable efficient gas exchange, and form an interface with the environment which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions between structural and immune cells are required to maintain lung homeostasis. Here, we use single cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in health. We report location-dependent airway epithelial cell states, and a novel subset of tissue-resident memory T cells. In lower airways of asthma patients, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report presence of pathogenic effector Th2 cells in asthma, and find evidence for type-2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identify a shift from airway structural cell communication in health to a Th2-dominated interactome in asthma.

immunology↗

bioRxiv2018

Single-cell transcriptional analysis reveals naïve helper ILC-like cells in zebrafish

Innate lymphoid cells (ILCs) are important mediators of the immune response and homeostasis in barrier tissues of mammals. However, the existence and function of ILCs in other vertebrates is poorly understood. Here, we use single-cell RNA sequencing to generate a comprehensive atlas of zebrafish lymphocytes during tissue homeostasis and following immune challenge. We profiled 14,080 individual cells from the gut of wild-type zebrafish, as well as of rag1-deficient fish which lack T and B cells, and discovered diverse populations of helper ILC-like cells. Unexpectedly, fish displayed a rorc-positive, naive subset that established a Type 3 or Type 2 response only upon immune challenge. Specifically, naive ILC-like cells expressed il22 and tnfa following exposure to inactivated bacteria, or il13 following exposure to helminth extract. Cytokine-producing ILC-like cells express a specific repertoire of novel immune-type receptors, likely involved in recognition of environmental cues. We identified additional novel markers of zebrafish ILCs and generated a cloud repository for their in-depth exploration.

immunology↗

bioRxiv2017

Single-cell RNA-Sequencing uncovers transcriptional states and fate decisionsin haematopoiesis

The success of marker-based approaches for dissecting haematopoiesis in mouse and human is reliant on the presence of well-defined cell-surface markers specific for diverse progenitor populations. An inherent problem with this approach is that the presence of specific cell surface markers does not directly reflect the transcriptional state of a cell. Here we used a marker-free approach to computationally reconstruct the blood lineage tree in zebrafish and order cells along their differentiation trajectory, based on their global transcriptional differences. Within the population of transcriptionally similar stem and progenitor cells our analysis revealed considerable cell-to-cell differences in their probability to transition to another, committed state. Once fate decision was executed, the suppression of transcription of ribosomal genes and up-regulation of lineage specific factors coordinately controlled lineage differentiation. Evolutionary analysis further demonstrated that this haematopoietic program was highly conserved between zebrafish and higher vertebrates.

cell biology↗

bioRxiv2016

Loss of the homologous recombination gene rad51 leads to Fanconi anemia-like symptoms in zebrafish

RAD51 is an indispensable homologous recombination protein, necessary for strand invasion and crossing over. It has recently been designated as a Fanconi anemia (FA) gene, following the discovery of two patients carrying dominant negative mutations. FA is a hereditary DNA repair disorder characterized by various congenital abnormalities, progressive bone marrow failure and cancer predisposition. In this paper, we describe the first viable vertebrate model of RAD51 loss. Zebrafish rad51 loss-of-function mutants developed key features of FA, including hypocellular kidney marrow, sensitivity to crosslinking agents and decreased size. We show that some of these symptoms stem from both decreased proliferation and increased apoptosis of embryonic hematopoietic stem and progenitor cells. Co-mutation of p53 was able to rescue the hematopoietic defects seen in the single mutants, but led to tumor development. We further demonstrate that prolonged inflammatory stress can exacerbate the hematological impairment, leading to an additional decrease in kidney marrow cell numbers. These findings strengthen the assignment of RAD51 as a Fanconi gene and provide more evidence for the notion that aberrant p53 signaling during embryogenesis leads to the hematological defects seen later in life in FA. Further research on this novel zebrafish FA model will lead to a deeper understanding of the molecular basis of bone marrow failure in FA and the cellular role of RAD51.\n\nSignificance statementThe homologous recombination protein RAD51 has been extensively studied in prokaryotes and lower eukaryotes. However, there is a significant lack of knowledge of the role of this protein and its regulation in an in-vivo context in vertebrates. Here we report the first viable vertebrate mutant model of rad51 in zebrafish. These mutant fish enabled us to confirm for the first time the recently discovered role of RAD51 in Fanconi anemia pathogenesis. We report that p53 linked embryonic stem cell defects directly lead to hematological impairments later in life. Co-mutation of rad51 with p53 rescues the observed hematological defects, but predisposes the fish to early tumor development. The application of this model opens new possibilities to advance Fanconi anemia drug discovery.

genetics↗