Live-seq enables temporal transcriptomic recording of single cells

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity(1). However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy(2,3), thus allowing to couple a cell's ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell's trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

A Tale of Two Tumors: Unraveling the Complexities of Epigenetic Dysregulation in Cancer

Maria Christine Donaldson

Epigenetics plays an important role in cancer development and progression. Cancer cells hijack the epigenome by modifying the histone protein units responsible for packaging DNA, or by modifying the DNA itself, resulting in changes to chromatin topology and transcriptional programming within the cell. In this thesis, I report our investigation to uncover the mechanisms of epigenetic regulation and how epigenetic control of transcriptional programming goes awry in cancer. We investigate these processes in two separate contexts. In our first study, we investigate the mechanisms by which EZH2 oncogenic mutations alter structure and function of topologically associating domains in non-Hodgkin lymphoma. The process of chromatin folding leads to a systematic arrangement of hierarchical structural and regulatory elements found within the nucleus. A topologically associating domain (TAD) is a regulatory unit of self interacting DNA, where the transcription of the genes within a TAD is usually dictated by the presence of active (H3K36me3) or inactive (H3K27me3) histone marks. In cancer, the somatic point mutation in EZH2Y646X leads to a genome wide increase in H3K27me3, associated with transcriptional repression. While this alteration leads to changes in the global epigenetic status of the cell, its impact on chromatin organization and TAD-related function remain unclear. By combining transcriptomics and epigenetics with analyses of chromatin structure, we demonstrate a functional interplay between TADs and the epigenetic and transcriptional program of the genes found within them. This balance is altered by EZH2Y646X, leading to the synergistic silencing of entire domains directly targeting cell differentiation and tumor suppressive programs. A closer look reveals that the silencing of tumor suppressive TADs are coupled with structural modifications and changes in promoter interactions within EZH2Y646X target TAD6.139. Impressively, the TADâs transcriptional and epigenetic programs are restored by pharmacological inhibition of EZH2Y646X. Our results indicate that EZH2Y646X alters the topology and function of chromatin domains to promote synergistic oncogenic programs. In our second study, we dissect the epigenetic, transcriptomic, and metabolic signaling dependencies using a novel model of central nervous system primitive neural ectodermal tumors (CNS-PNETs). Central nervous system (CNS) tumors are the leading cause of cancer-associated death in children. Primitive neural-ectodermal tumors (CNS-PNETs) are a particularly aggressive subtype of embryonal CNS-tumor, with a five-year overall survival rate in less than 50% of patients. Despite sharing a similar cell of origin of other CNS tumors, CNS-PNETs have a different anatomical location, unique genetic and epigenetic features, and significantly worse clinical outcome. In addition, a lack of in vivo models for studying CNS tumors challenges the opportunity to dissect the genetic variables that underlie the origin of these tumors. We developed a novel CNS-PNET mouse model, called CNS-NPCs, using neural progenitor cells derived from human-iPS cells. Through histological, DNA methylation, and RNA sequencing analyses, we find that the CNS-NPC model recapitulates the the morphologic, epigenetic, and transcriptomic features of primary CNS-PNETs. In addition, through in vivo metabolic analyses of CNS-NPCs and the patient derived cell line, PFSK-1, we identified dysregulation in the neurotransmitter...

EPFL2019

Roles of Epigenetic Dysregulation in Cancer Progression and Metastasis

Mohammad Sadegh Saghafinia

Nearly all the cells of an organism share the same DNA sequence or genome, and yet they show different phenotypes and carry out different functions. This diversity is made possible by a verity of molecular modifications acting on the DNA sequence that collectively define the cell's epigenome. Failure in the proper regulation of epigenome can lead to abnormal activation or inhibition of vital signaling pathways, which contributes to the initiation and progression of multiple diseases, including cancer. In this thesis, I used a combination of in silico, in vitro, and in vivo techniques to explore the roles of epigenetic dysregulation in tumor progression and metastasis. In the first part, I performed a systematic and unbiased investigation of cancer-associated DNA methylation and gene expression changes across human cancers. I designed a novel algorithmic approach (RESET) to identify aberrant DNA methylation and associated gene expression changes across >6,000 human tumors. We identified a DNA Methylation Instability (DMI) phenotype in tumors acquiring numerous hyper and hypomethylated transcription start sites, which is associated with mutations of chromatin remodeling factors and Wnt-signaling. We showed that silenced genes coalesced in specific pathways including apoptosis, transcriptional regulation, and cell metabolism. The majority of the enhanced genes belonged to cancer-germline antigens (CG), whose expression correlated with response to anti-PD-1 in melanoma patients. Finally, we demonstrated the potential of RESET to explore aberrant DNA methylation in pediatric tumors; pediatric Wilms tumors with diffuse anaplasia exhibit DMI, and specific silencing events predict a worse outcome in cases with favorable histology. These results established a new approach to explore pan-cancer epigenetic modifications and provided a resource of candidate oncogenic events for future functional and therapeutic studies. In the second part, I studied the dynamics of cancer progression and metastasis in Pancreatic Neuroendocrine Tumors (PanNET). This rare tumor is the second most common form of pancreatic cancer. Two principal subtypes of PanNET has been identified: insulinomas (IT) and metastasis-like primaries (MLP), corresponding to the low and high grade of human PanNETs, respectively. From the mouse model of PanNET (RT2), we profiled the single-cell, bulk mRNA and miRNA transcriptomes, and the proteomes of primary and metastasis specimens. We demonstrated that the tumor progression from IT to MLP follows the reverse embryonic and postnatal developmental path. Transcriptomic data from human patients showed that aggressive human PanNETs also follow the same reverse developmental trajectory of dedifferentiation. We established one possible mechanism underlying IT-to-MLP transition. Over-expression of the miR-181cd cluster in IT-like cancer cell-lines resulted in acquisition of the MLP phenotypes. miR-181cd mediated its effect through suppressing the expression of Meis2 and, indirectly, inducing the expression of Hmgb3 and Mycn transcription factors. Inhibiting the expression of Hmgb3 in MLP-like cancer cell-lines resulted in a significant growth decrease both in vitro and in vivo, demonstrating the importance of Hmgb3 in the maintenance of MLP-like cell state. These data presented dedifferentiation as a mechanism by which malignant neuroendocrine cancer cells acquire progenitor-like features, enabling them to become more aggressive and metastatic.

EPFL2020

Single-cell lipidomics reveals a role for cell-to-cell sphingolipid heterogeneity in fibroblast activation

Laura Capolupo

Cell-to-cell variability plays a key role in tissue patterning by setting initial asymmetry that primes cell fate decisions. Fluctuations in the activity of regulatory molecules can commit individual cells to divergent differentiation pathways, and cell-to-cell variability can diversify the response of an otherwise homogeneous cell community to its environment. Recent advances have provided scientists with tools to study the variability associated with individual cells. However, while single-cell data are available for genomes, transcriptomes and proteomes, they are scarce for metabolic products, such as lipids. Eukaryotic cells produce thousands of lipids â each potentially contributing to specific biological functions. Furthermore, a number of metabolic switches involving lipids have been described to occur in development and cell differentiation. Few studies have directly addressed cell-to-cell lipid variations in syngeneic cell populations suggesting that lipid heterogeneity contributes to the emergence of multicellular patterns. Nonetheless, lipid biologists have so far addressed lipidomes in bulk cell extracts or selected lipids at the single-cell level. Thus, how lipidomes vary from one cell to another and which cell-to-cell lipid variations have biological meaning remains to be defined. Recent developments have provided mass spectrometry with sufficient sensitivity to reveal molecules in few hundred copies, making single-cell lipidomics possible. A rapidly emerging technique with a potential use in single-cell lipidomics is imaging mass spectrometry. Here, we devised a high-resolution MALDI imaging mass spectrometry pipeline to study cell-to-cell variability of the lipidome of hundreds of primary dermal human fibroblasts. We found that sphingolipid metabolism shows high cell-to-cell heterogeneity and that specific sphingolipids mark distinct cell sub-populations: coined herein as âlipotypesâ. Furthermore, we found that fibroblast lipotypes correspond to cell states endowed with proliferative, inflammatory or fibrogenic properties. Finally, we asked whether lipotypes participate in the specification of cell states and find that specific glycosphingolipids modulate signalling pathways (i.e., the FGF and TGF-b) to shape the transcriptional cell landscape. In summary, through the use of single-cell omics techniques, we found that: (i) specific lipid metabolic segments (i.e., the sphingolipid pathways) have cell-to-cell variation; (ii) given lipid configurations mark discrete cell states; and (iii) sphingolipids modulate dermal fibroblast activation involved in wound healing and skin homeostasis. Altogether, this study is among the first to demonstrate the potential of MALDI-IMS for single-cell lipidomics and to reveal cell-to-cell lipidome heterogeneity. It also demonstrates a role for lipids in the determination of cell states and in tissue patterning and reveals a new regulatory component to the self-organization of multicellular systems.

EPFL2021