Caractérisation des premières étapes de différenciation des cellules hématopoïétiques à l'échelle de la cellule unique

Despite intensively studies, the fundamental mechanisms of cell fate decision during cellular differentiation still remain unclear. The deterministic mechanisms, often based on studies of large cell populations, cannot explain the difference between individual cell fates choices placed in the same environment. The aim of my thesis work is to study the first steps of hematopoietic cell differentiation at the single cell level thanks to transcriptomic, proteomic and morphological analyses. Two differentiation models have been used: T regulatory lymphocytes and human cord blood-derived CD34+ cells. The behavior of individual cells following stimulation has been analyzed. Using time-lapse microscopy coupled to single cell molecular analyses, we could demonstrate that the cell fate choice is not a unique, programmed event. First, the cell reaches a metastable “multi-primed” state, which is characterized by a mixed lineage gene expression pattern. After transition through an “uncertain”, unstable state, characterized by fluctuations between two phenotypes, the cell reaches a stable state. Our observations are coherent with a stochastic model of cell fate decision. The differentiation is likely to be a spontaneous, dynamic, fluctuating and not a deterministic process. The cell fate decisions are taken by individual cells.Bien que largement étudiés, les mécanismes fondamentaux de prise de décision dans les processus de différenciation cellulaire restent mal compris. Les théories déterministes, souvent basées sur des études populationnelles, atteignent rapidement leur limite lorsqu’il s’agit d’expliquer les différences de choix individuels de cellules, pourtant exposées au même environnement. L’objectif de ma thèse est donc d’étudier les premières étapes de la différenciation des cellules hématopoïétiques à l’échelle de la cellule unique, par des analyses transcriptomiques, protéomiques et morphologiques. Ce travail a été effectué sur deux modèles de différenciation : les lymphocytes T régulateurs et les cellules CD34+ humaines issues de sang de cordon. Nous avons observé le comportement de ces cellules uniques après stimulation. Grâce à la combinaison de la microscopie en time lapse et des analyses moléculaires réalisées à l’échelle de la cellule individuelle, nous avons pu démontrer que le choix du devenir cellulaire n’était pas unique, programmé. La cellule passe d’abord par un état dit « multi-primed », métastable où elle exprime des gènes de plusieurs lignées différentes, puis elle passe par une phase dite « incertaine », instable où elle hésite entre deux phénotypes avant de se stabiliser dans un état fixe. Nos observations sont cohérentes avec une explication stochastique de la prise de décision. La différenciation serait donc un processus spontané, dynamique, fluctuant et non un processus prédéterminé. Les décisions du destin cellulaire sont prises séparément par les cellules individuelles

Characterisation of the first step of hematopoietic cell differentiation at the single cell level

Bien que largement étudiés, les mécanismes fondamentaux de prise de décision dans les processus de différenciation cellulaire restent mal compris. Les théories déterministes, souvent basées sur des études populationnelles, atteignent rapidement leur limite lorsqu’il s’agit d’expliquer les différences de choix individuels de cellules, pourtant exposées au même environnement. L’objectif de ma thèse est donc d’étudier les premières étapes de la différenciation des cellules hématopoïétiques à l’échelle de la cellule unique, par des analyses transcriptomiques, protéomiques et morphologiques. Ce travail a été effectué sur deux modèles de différenciation : les lymphocytes T régulateurs et les cellules CD34+ humaines issues de sang de cordon. Nous avons observé le comportement de ces cellules uniques après stimulation. Grâce à la combinaison de la microscopie en time lapse et des analyses moléculaires réalisées à l’échelle de la cellule individuelle, nous avons pu démontrer que le choix du devenir cellulaire n’était pas unique, programmé. La cellule passe d’abord par un état dit « multi-primed », métastable où elle exprime des gènes de plusieurs lignées différentes, puis elle passe par une phase dite « incertaine », instable où elle hésite entre deux phénotypes avant de se stabiliser dans un état fixe. Nos observations sont cohérentes avec une explication stochastique de la prise de décision. La différenciation serait donc un processus spontané, dynamique, fluctuant et non un processus prédéterminé. Les décisions du destin cellulaire sont prises séparément par les cellules individuelles.Despite intensively studies, the fundamental mechanisms of cell fate decision during cellular differentiation still remain unclear. The deterministic mechanisms, often based on studies of large cell populations, cannot explain the difference between individual cell fates choices placed in the same environment. The aim of my thesis work is to study the first steps of hematopoietic cell differentiation at the single cell level thanks to transcriptomic, proteomic and morphological analyses. Two differentiation models have been used: T regulatory lymphocytes and human cord blood-derived CD34+ cells. The behavior of individual cells following stimulation has been analyzed. Using time-lapse microscopy coupled to single cell molecular analyses, we could demonstrate that the cell fate choice is not a unique, programmed event. First, the cell reaches a metastable “multi-primed” state, which is characterized by a mixed lineage gene expression pattern. After transition through an “uncertain”, unstable state, characterized by fluctuations between two phenotypes, the cell reaches a stable state. Our observations are coherent with a stochastic model of cell fate decision. The differentiation is likely to be a spontaneous, dynamic, fluctuating and not a deterministic process. The cell fate decisions are taken by individual cells

Exposome-Explorer: a manually-curated database on biomarkers of exposure to dietary and environmental factors

- Nota editorial - Autoridades - El Centro de Innovación y Transferencia Tecnológica. Dra. Cecilia Sanz e Ing. Santiago Medina - Los nuevos desafíos: Innovación e Interdisciplina. Profesor Emérito Ing. Armando De Giusti - Ciudades inteligentes y sustentables. Proyecto ERASMUS CAP4CITY. Dra. Elsa Estevez - Concurso INNOVAR 2019 - Premio a la Innovación de la UNLP 2019 para “Diabetes Link, una aplicación móvil para controlar diabetes” - El rol de la Secretaría de Vinculación e Innovación Tecnológica de la UNLP. Lic. Javier Diaz - Espacio Ruta Darwin - La innovación como eje común en la muestra del CIyTT - Estación de trabajo 1, proyectos desarrollados por el III-LIDI - Estación de trabajo 2, proyectos desarrollados por el LIFIA - Estación de trabajo 3, proyectos desarrollados por el III-LIDI - Estación de trabajo 4, proyectos desarrollados por el III-LIDI - Estación de trabajo 5, proyectos desarrollados por el III-LIDI - Estación de trabajo 6, proyectos desarrollados por el LINTI - Estación de trabajo 7, proyectos desarrollados por el LINTI - Estación de trabajo 8, proyecto desarrollado por el LINTI - Estación de trabajo 9, proyecto desarrollado por la Secretaría de Vinculación e Innovación Tecnológica - Egresados Destacados 2019 - Premios UNLP y Municipalidad de la Plata 2019 - VIII Jornadas de Cloud Computing, Big Data & Emerging Topics - VII Expo Ciencia y Tecnología de la Facultad de Informática - Desarrollos TecnológicosFacultad de Informátic

Constraints on Human CD34+ Cell Fate due to Lentiviral Vectors Can Be Relieved by Valproic Acid

International audienc

Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.

Individual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterising transcriptional changes in cord blood-derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the 2 stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the 2 phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology, and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process (which is different from a simple binary switch between 2 options, as it is usually envisioned)

Global genome decompaction leads to stochastic activation of gene expression as a first step toward fate commitment in human hematopoietic cells

When human cord blood-derived CD34+ cells are induced to differentiate, they undergo rapid and dynamic morphological and molecular transformations that are critical for fate commitment. In particular, the cells pass through a transitory phase known as "multilineage-primed" state. These cells are characterized by a mixed gene expression profile, different in each cell, with the coexpression of many genes characteristic for concurrent cell lineages. The aim of our study is to understand the mechanisms of the establishment and the exit from this transitory state. We investigated this issue using single-cell RNA sequencing and ATAC-seq. Two phases were detected. The first phase is a rapid and global chromatin decompaction that makes most of the gene promoters in the genome accessible for transcription. It results 24 h later in enhanced and pervasive transcription of the genome leading to the concomitant increase in the cell-to-cell variability of transcriptional profiles. The second phase is the exit from the multilineage-primed phase marked by a slow chromatin closure and a subsequent overall down-regulation of gene transcription. This process is selective and results in the emergence of coherent expression profiles corresponding to distinct cell subpopulations. The typical time scale of these events spans 48 to 72 h. These observations suggest that the nonspecificity of genome decompaction is the condition for the generation of a highly variable multilineage expression profile. The nonspecific phase is followed by specific regulatory actions that stabilize and maintain the activity of key genes, while the rest of the genome becomes repressed again by the chromatin recompaction. Thus, the initiation of differentiation is reminiscent of a constrained optimization process that associates the spontaneous generation of gene expression diversity to subsequent regulatory actions that maintain the activity of some genes, while the rest of the genome sinks back to the repressive closed chromatin state.ISSN:1544-9173ISSN:1545-788

Evidence for close molecular proximity between reverting and undifferentiated cells

International audienc

Quantitative analysis of dynamic phenotypes as determined by time-lapse data.

<p>(A) Association between the morphology, switch frequency, cell cycle length, and the type of cell divisions of second- and third-generation cells. Each point represents a single cell. Siblings with different dynamic behaviour and morphology (in green) are usually characterised by high switch frequencies. Siblings with similar dynamic behaviour and morphologies are shown in blue. The morphology is given as a ratio of time spent in round/polarised shape by a cell during the cell cycle. Switch frequency is given in number of morphological transformations per hour. Cell cycle length is in hours. (B) Dynamic phenotype change during the first 2 cell divisions as determined on the basis of time-lapse records. Three different dynamic phenotypes were identified: stable polarised, frequent switchers, and stable round. Cells tended to transmit dynamic phenotypes to daughter cells during cell division. Polarised and frequent switchers produced round cells, and frequent switchers were always produced by polarised mothers. Phenotypic change is not associated with asymmetric division; it can occur at any time in the cell cycle. Since round cells always produce round daughters, the whole process is biased and the proportion of this phenotype increases. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s012" target="_blank">S2 Data</a>.)</p

Single-cell gene expression in ‘high’, ‘medium’, and ‘low’ CD133 cells.

<p>(A) t-stochastic neighbour embedding (t-SNE) map of single-cell transcriptional data. Each point represents a single cell highlighted in a different colour for ‘high’, ‘medium’, and ‘low’ CD133 cells. ‘High’ and ‘low’ cells are in separated clusters corresponding to cluster #1 and #2 in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.g001" target="_blank">Fig 1B</a>. ‘Medium’ CD133 cells are distributed in and between these 2 clusters, indicating their intermediate character. (B) Scatter plot representation of PU1 and GATA1 expression in individual cells of the ‘high’, ‘medium’, and ‘low’ CD133 fraction. Note that GATA1 is not expressed in ‘high’ cells. Coexpression of the 2 genes is observed only in some ‘medium’ and ‘low’ cells. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.)</p