Séquençage de l'ARN | EPFL Graph Search

Le séquençage de l'ARN (RNA-Seq, de l’anglais RNA sequencing), également appelé séquençage aléatoire du transcriptome entier (whole transcriptome shotgun sequencing en anglais), est une technologie qui utilise le séquençage à haut débit (next-generation sequencing en anglais) pour identifier et quantifier l'ARN issu de la transcription du génome à un moment donné. Introduction Le transcriptome d'une cellule est dynamique, en constante évolution. Les technologies de séquençage à haut débit ont permis la lecture de l'ADN d'une cellule, base par base. Ces technologies permettent également la lecture de l'ARN dans une cellule, ce qui facilite la compréhension des mécanismes d'épissage alternatif de gènes, comprenant les modifications post-transcriptionnelles, les gènes de fusion, les polymorphismes nucléotidiques (SNP en anglais) et les changements dans l'expression génique. En plus de l'ARNm, la technologie RNA-Seq permet d'identifier d'autres types d'ARN, tels que les microARN

Inference methods for the study of interacting biological oscillators in single-cells

Colas Noé Droin

Biological oscillators are pervasive in biology, covering all aspects of life from enzyme kinetics reactions to population dynamics. Although their behaviour has been intensively studied in the last decades, the recent advances of high-throughput experimental technologies in the fields of omics and microscopy has called for the development of new analysis methods. Among the many types of models and quantitative analyses, parametric approaches are promising as they enable for a mechanistic or physical explanation of the phenomena under study. In particular, dynamical systems theory seems particularly adapted as the vast majority of oscillators can be modelled through differential equations. Dynamical systems parameters can also be easily opti-mized via maximum likelihood approaches. The validity of the inferred model can then be assessed from the quality of its predictions. We here present three different scientific questions regarding noisy biological oscillators, which are answered using maximum-likelihood inference approaches applied to parametric models. We first take interest in the characterisation of the influence of the cell-cycle over the circadi-an clock in individual mammalian cells. To this end, we develop a method combining a Hidden Markov Model with an Expectation-Maximization algorithm to infer their coupling from single-cell microscopy traces. We show that this coupling predicts multiple phase-locked states exhib-iting different degrees of robustness against molecular fluctuations inherent to cellular scale bio-logical oscillators. We then try to understand how the mammalian transcriptome behaves in the liver. Thence, we use single-cell RNA sequencing (scRNA-seq) along with mixed-models to investigate the interplay between gene regulation in space and time. Categorising mRNA expression profiles using mixed-effect models and smFISH validations, we find that many genes in the liver are both zonated and rhythmic, most of them showing multiplicative space-time effects. Finally, we look more closely at the cell-cycle, as it is one of the main drivers of gene expres-sion cell-to-cell heterogeneity in otherwise homogeneous cell populations. Here, we would like to understand if and how cell-cycle velocity changes depending on the phase of the cycling cells. To that end, we formulate the problem in terms of an autonomous dynamical system and use this to infer consistent dynamics for the cell-cycle from scRNA-seq data. Phase inference being paramount in all of these three studies, a short technical review on the topic is also provided at the end of this thesis, along with Julia scripts for the main inference methods presented. Various computational tools assisting the understanding of the scientific questions at stake are also presented, including a Python Dash web-app, a D3 widget and many Matplotlib animations and widgets.

EPFL2020

Identification and functional characterization of protein kinases that modulate Notch signaling under physiological conditions and in cancer

Chhavi Jain

The Notch signaling pathway is a key regulator of cell fate decisions in embryonic development and in adult tissue homeostasis. Mounting evidence suggests that Notch signaling is frequently deregulated in human neoplasms, where depending upon the cellular context it can function both as an oncogene or a tumor suppressor. A plethora of studies shed light on how Notch crosstalks with signaling pathways downstream to manifest either its oncogenic or tumor suppressive activity. However, regulatory networks upstream of the Notch signaling pathway are still poorly understood. Since protein kinases are well-known regulators of a majority of cell signaling pathways, the aim of the current study was to identify novel positive and negative regulatory kinases that modulate Notch signaling. Using a HeLa cell based co-culture assay to read Notch-dependent luciferase activity, a small interference RNA (siRNA) library against the human kinase genome was previously tested in a high-throughput manner. Validation of top candidate kinases from the screening using both siRNA as well as pharmacological inhibitors led to further elimination of false positives and identification of Protein Kinase B (AKT2) and Calmodulin Kinase II (CaMKII) as key positive while Janus kinases (JAKs) as key negative regulators of the Notch signaling pathway. In the first part of the study, we analyzed the positive regulation of AKT2 and CaMKII kinases on Notch signaling in the T-cell acute lymphoblastic leukemia (T-ALL) cells where Notch is oncogenic. It was shown that pharmacological inhibition of either AKT2 or CaMKII kinase in T-ALL cell lines in vitro abrogated the expression of active Notch1 intracellular domain (N1-ICD) as well as of Notch target genes. Moreover, inhibition of these kinases blocked proliferation of T-ALL cells. In the second part of the study, we analyzed the negative regulation of JAK kinases on Notch signaling using a distinct physiological context where Notch is tumor suppressive. It was shown that pharmacological inhibition of JAK kinases led to an induction of Notch receptor transcription and of Notch target genes in the human primary epidermal keratinocytes (HPEK) as well as in the skin squamous cell carcinoma (SCC) cell lines. In addition, the pharmacological inhibition of JAK kinases induced a block in proliferation, cell cycle arrest and differentiation in HPEKs and skin SCCs by increased expression of early differentiation markers. Suppression of Notch signaling in primary keratinocytes counteracted the differentiation-inducing effect of JAK inhibition. Since JAK inhibition affected Notch transcription, global gene expression profiling using RNA sequencing was done to identify transcription factors involved in an indirect regulation of JAK kinases on the Notch cascade. EGR1 and EGR2 belonging to the early growth response family of transcription factors were significantly modulated downstream of JAK inhibition. In vivo, topical inhibition of JAK kinases provided marked resistance against chemically induced cutaneous carcinogenesis.Taken together, our data reveals a key role of AKT2 and CaMKII kinases in positive regulation while of JAK kinases in the negative regulation of Notch signaling, of potential relevance for combinatory approaches for cancer therapy. Pharmacological inhibitors against these kinases could be tested for their ability to modulate Notch signaling and may prove highly beneficial in the therapy of Notch-driven cancers.

EPFL2016

Assessing the role of Hes1 and identification of target genes in human and murine T-ALL

Silvia Wirth

The Notch signalling pathway is an ancient cell signalling mechanism that enables short-range communications between cells and controls a broad spectrum of cell fates and developmental processes. In the haematopoietic system Notch signalling has been linked to physiological, but also to pathological phenotypes of T cell development. Identification of numerous activating mutations within the NOTCH1 receptor in human T cell acute lymphoblastic leukaemia (T-ALL) patient samples demonstrated that aberrant activation of this signalling pathway is a frequent event in T-ALL. Active Notch signalling leads to the expression of a plethora of genes that might be drivers or passengers in tumorigenesis including Hes1, which encodes a transcriptional repressor. We have therefore studied Hes1 in the context of T-ALL in mouse models that mimic human disease and in human T-ALL cell lines with the aim to evaluate whether Hes1 affects disease development and disease maintenance and to characterize its function on a molecular level. The first part of this study is dedicated to the functional characterisation of Hes1 in vivo in T-ALL mouse models and in vitro in human T-ALL cell lines. Using a retroviral bone marrow transplant model of T-ALL in which progenitor cells are transduced with a retrovirus expressing constitutive active Notch1 intracellular domain (NICD) we could show that Hes1 is not required in established, late stage T-ALL cells, but that it promotes tumour progression in the early stages of the disease. We have also investigated the function of HES1 in human T-ALL and can show that the overexpression of dominant negative versions of Hes1 in two patient derived cell lines (T-ALL1, CUTLL-1) does not affect proliferation or apoptosis, emphasising that HES1 does not affect cell viability once cells are fully transformed to the leukemic state. In the second part of the study we set out to systematically delineate the gene regulatory networks down-stream of Hes1 by combining RNA-seq and ChIP-seq analysis. Comparing the gene expression of murine premalignant, early stage NICD induced CD4+CD8+ DP cells in the presence and absence of Hes1 by RNA-seq, we unexpectedly found a predominant upregulation of genes in cells expressing Hes1 indicating that Hes1 might rather act as a positive regulator of transcription than as a transcriptional repressor of distinct target genes. Hes1 might influence transcription through secondary or indirect effects as combinatorial analysis of RNA-seq and ChIP-seq led to the identification of only a small number of potential direct target genes that are transcriptionally regulated by Hes1. In summary, the role of Hes1 in promoting the early stages of the disease appears to be highly complex and is likely to involve both direct and indirect control of gene regulatory networks.

EPFL2014