Quantitative single cell dynamics of signaling and transcriptional response in mammalian cells

Cells live in ever-changing environments, thereby facing a variety of dynamic environmental signals. Environmental stimuli elicit intracellular responses through signaling pathways, which converge on transcriptional activation or repression of target genes. Despite intensive research, dissecting the complex interactions between pathway components that modulate mRNA and protein production still remains a difficult task. To this end, single-cell approaches provide unique insights into intracellular processes and cell responses to environmental stimuli, otherwise inaccessible with traditional bulk studies. Single-cell measurements have revealed that isogenic cells sharing the same environment display substantial heterogeneity in both transcript and protein level. As the initial step in gene expression, transcription is an important source of such variability in eukaryotic cells due to low number of molecules involved, transcription factor dynamics and the discrete nature of biochemical reactions. Notably, production of mRNA during transcription occurs in short periods of activity, termed as transcriptional bursts, followed by longer periods of inactivity. Despite widespread observations of transcriptional dynamics in mammals, upstream molecular mechanisms shaping the eukaryotic transcription remained elusive. In this study, we quantitatively linked upstream factors and transcriptional kinetics by developing an experimental system to temporally monitor, simultaneously, inputs (transcription factors) and outputs (target gene expression) in mammalian cells, in response to stimulus. We established two Tet-On inducible stable cell lines each expressing a fusion protein of a luminescence (Nanoluciferase) reporter to either SMAD4 or SMAD2, the two main transcrip- tion factors downstream of the TGF-Î² pathway. These cell lines that also contain a short-lived firefly luciferase reporter for the expression of the target endogenous connective tissue growth factor (ctgf ) gene allowed us to quantitatively link nuclear accumulation of SMADs upon TGF-Î² stimulation to the target gene expression in real-time single cell measurements. Time- lapse luminescence microscopy and image analysis with the custom developed CAST (Cell Automated Segmentation and Tracking platform) platform provided quantitative single-cell data to link the upstream transcription factor profile to its target gene activity. The data revealed weak single-cell correlations between translocation level and the target gene expression response which suggests a mechanism in which the translocation of SMADs initiates the transcriptional response but affects the response amplitude minimally. However, SMAD4 expression levels influenced the target gene response dynamics such that cells with high SMAD4 abundance favored to respond in a more sustained and even oscillatory manner. This suggests a mechanism consisting of a dynamic interplay between the transcriptional activators and feedback mechanisms in TGF-Î² signaling. We explored further the effect of different factors such as ligand concentration, ligand type on both signaling and target gene response. Taken together, this study proposes an experimental and quantitative framework that dissect mechanisms underlying transcriptional response to stimulus.

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

Quantitative analysis of gene expression and transcriptional memory in mouse embryonic stem cells

Aleksandra Mandic

Quantitative studies of gene expression in have shown widespread variability in transcript and protein product abundance at the single-cell level. Such fluctuations in gene expression have been shown to lead to heterogeneous cellular responses and phenotypes, acting in a range of systems, from immunity, cancer to development. To better understand heterogeneity in cellular populations, we developed a novel method for the precise quantification of gene expression in single living cells. Furthermore, we focused on whether and to which extent transcriptional expression profiles are transmitted during cell division. In the first section, we described a new approach for quantitative measurements of gene expression, based on internal tagging of endogenous proteins with a reporter allowing luminescence and fluorescence time-lapse imaging. Using the currently brightest luminescent reporter, fluctuations of protein expression levels could be monitored in single living cells with high sensitivity and temporal resolution over extended time periods. Moreover, our system allowed measurement of single-cell protein degradation rates in the absence of protein synthesis inhibitors, as well as calculation of absolute synthesis rates over the cell cycle. Finally, the internal tag could be excised by inducible expression of Cre recombinase, which enabled estimation of endogenous mRNA half-lives by monitoring the decay of luminescent signal. Second, to monitor transcriptional activity and quantify memory across multiple endogenous genes in mouse embryonic stem cells, we generated cell lines in which a short-lived luciferase reporter allowed sensitive monitoring of transcriptional kinetics by luminescence imaging at high time resolution over long periods of time. By coupling live single-cell monitoring of transcriptional activity of 9 different promoters with mathematical modelling, we found that different levels of expression fluctuations shape transcriptional memory. Long fluctuations (1-10 generations) and short fluctuations (1-3 h), as well as their amplitudes, vary widely between across different genes and together shape transcriptional memory. Surprisingly, we have shown that there was a large level of gene-specific cell-to-cell synchronicity in transcriptional profiles. Overall, we uncovered that noise and timescales of slow and fast fluctuations, as well as their synchronisation over the cell cycle, defined how transcriptional dynamics were correlated within a lineage of related cells. In conclusion, this thesis described an innovative method that allows measurement of absolute protein expression levels, protein turnover, as well as mRNA half-lives for endogenously expressed genes. Our approach opens new avenues in quantitative studies of gene expression in single living cells. Furthermore, we revealed different levels of transcriptional fluctuations that shape gene specific transcriptional memory and its timescales in mouse embryonic stem cells.

EPFL2018

Quantitative relationships between SMAD dynamics and target gene activation kinetics in single live cells

Torgil Elias Friman, Felix Naef, David Michael Suter, Onur Tidin

The transduction of extracellular signals through signaling pathways that culminate in a transcriptional response is central to many biological processes. However, quantitative relationships between activities of signaling pathway components and transcriptional output of target genes remain poorly explored. Here we developed a dual bioluminescence imaging strategy allowing simultaneous monitoring of nuclear translocation of the SMAD4 and SMAD2 transcriptional activators upon TGF-beta stimulation, and the transcriptional response of the endogenous connective tissue growth factor (ctgf) gene. Using cell lines allowing to vary exogenous SMAD4/2 expression levels, we performed quantitative measurements of the temporal profiles of SMAD4/2 translocation and ctgf transcription kinetics in hundreds of individual cells at high temporal resolution. We found that while nuclear translocation efficiency had little impact on initial ctgf transcriptional activation, high total cellular SMAD4 but not SMAD2 levels increased the probability of cells to exhibit a sustained ctgf transcriptional response. The approach we present here allows time-resolved single cell quantification of transcription factor dynamics and transcriptional responses and thereby sheds light on the quantitative relationship between SMADs and target gene responses.