Norwich Single-Cell Symposium 2021

Cellular diversity in cancer

I will discuss the analysis of the extensive phenotypic and genetic diversity of clonal populations in cancer. This diversity reflects cellular origins of cancer and mutational drivers. The diversification process in individual patients is highly dynamic and mirrors Darwinian evolution of asexually reproducing cells with ecosystems.

Single cell multi-omics profiling reveals a hierarchical epigenetic landscape during mammalian germ layer specification

Formation of the three primary germ layers during gastrulation is an essential step in the establishment of the vertebrate body plan. Recent studies employing single cell RNA-sequencing have identified major transcriptional changes associated with germ layer specification. Global epigenetic reprogramming accompanies these changes, but the role of the epigenome in regulating early cell fate choice remains unresolved, and the coordination between different epigenetic layers is unclear.

Here we describe the first single cell triple-omics map of chromatin accessibility, DNA methylation and RNA expression during the exit from pluripotency and the onset of gastrulation in mouse embryos. We find dynamic dependencies between the different molecular layers, with evidence for distinct modes of epigenetic regulation. The initial exit from pluripotency coincides with the establishment of a global repressive epigenetic landscape, followed by the emergence of local lineage-specific epigenetic patterns during gastrulation.

Notably, cells committed to mesoderm and endoderm undergo widespread coordinated epigenetic rearrangements, driven by TET-mediated demethylation in enhancer marks and a concomitant increase of chromatin accessibility. In striking contrast, the DNA methylation and chromatin accessibility landscape of ectodermal cells is already established in the early epiblast. Hence, regulatory elements associated with each germ layer are either epigenetically primed or epigenetically remodelled prior to overt cell fate decisions during gastrulation, providing the molecular logic for a hierarchical emergence of the primary germ layers.

Combining electrophysiology and single-cell transcriptomics reveals a gradient of states amongst dopaminergic neurons

Dopaminergic neurons in the olfactory bulb are inhibitory interneurons that co-release dopamine and GABA to regulate the transmission of information at the earliest stages of sensory processing. The vast majority of bulbar dopaminergic neurons are of the non-axon-bearing subtype, and are one of the few neuronal types in the mammalian brain that are continually generated throughout postnatal life. Here, we investigate whether this continuous neuronal production results in a gradient of cell states within the resident population of bulbar dopaminergic neurons.

We address this question by birthdating resident DA neurons and performing simultaneous electrophysiological recordings and single-cell RNA sequencing (patch-Seq). Birthdating in 4-week old DAT-IRES-Cre/Floxed-tdT mice revealed that resident dopaminergic neurons span an age range of at least 3 weeks. Cell trajectory analysis of single-cell transcriptomic data from manually sorted dopaminergic neurons showed a gradient along which 680 genes were differentially expressed. This gene set was significantly enriched for GO terms related to neuronal and synaptic function, indicating that the identified trajectory may reflect a maturational gradient of dopaminergic cell state.

Ongoing analysis of electrophysiological properties along the identified trajectory will reveal whether it describes a gradient of functional states. Finally, combining EdU birth-dating with immunostaining for markers differentially expressed along the trajectory will assign a temporal label to the single-cell transcriptional profiles. In summary, we describe a hitherto unanticipated gradient of cell state within a specific neuronal subtype, a gradient which could underpin the functional maturation of dopaminergic cells in the postnatal brain.

Multidimensional single-cell analysis resolves molecular signatures of clonal evolution in myeloid leukemia

Single-cell RNA-sequencing has emerged as a powerful tool to resolve transcriptional heterogeneity. However, its application to study cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells, which prevents correlation of genetic and transcriptional readouts from the same single cell.

To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single-cells from both genomic and coding DNA, in parallel with unbiased whole transcriptome analysis.

Following extensive validation in cell lines, we applied this technique to study myeloproliferative neoplasms (MPNs), which are clonal disorders driven by mutant-positive hematopoietic stem/progenitor cells (HSPC). Resolving the multiple layers of heterogeneity encompassed within the MPN-HSPC compartment has crucial implications for MPN biology, yet very little is currently known about HSPC heterogeneity in MPNs. TARGET-seq analysis of over 4500 single cells allowed us to identify distinct molecular signatures corresponding to genetically-distinct subclones, including patients acquiring multiple mutations in different orders. We identified putative biomarkers of JAK2V617F mutant cells such as GAS2, RXFP1, STAT1 and G6B. Crucially, we were also able to characterize disruption of gene expression in non-mutant HSPCs, showing enrichment of inflammatory signatures.

In summary, TARGET-seq allowed us to identify distinct and biologically relevant molecular signatures of stem/progenitor cells in MPN, representing a powerful tool for biomarker and therapeutic target discovery that could also be broadly applied to other types of cancers.

Single cell M&T-seq reveals heterogeneity in methylation reprogramming and genome activation in human pre-implantation embryos.

The terminally differentiated gametes unite at fertilization to form a totipotent zygote that can differentiate into all cells and tissues of the developing embryo. In mammals, the zygote undergoes several cleavage divisions to form a blastocyst. During this pre-implantation stage, maternally stored material promotes both the erasure of the sperm and oocyte epigenetic profiles and is responsible for concomitant genome activation.

Here we have utilized single cell methylome & transcriptome sequencing (scM&T-seq), a multi-omic method that allows for simultaneous quantification of both mRNA expression and DNA methylation, in human oocytes and a developmental series of human embryos. We fully characterize zygotic and embryonic genome activation (ZGA & EGA, respectively), maternal transcript degradation and map key epigenetic reprogramming events in high quality, developmentally viable embryos.

In depth analysis reveals subtle, but biologically significant changes in the timing of key events between mouse and humans. Finally, we compare these signatures with early embryos that have undergone spontaneous cleavage-stage arrest as determined by time-lapse imaging.

Single cell transcriptomes of the Arabidopsis tapetum reveal novel signalling pathways controlling pollen development.

The tapetum is a somatic nurse cell layer which performs a wide variety of functions to support the development of mature pollen grains. Pseudotemporal ordering of single cell tapetum transcriptomes can recapitulate known gene expression profiles and has revealed novel stage-specific gene expression.

This has highlighted a role for small peptide signalling from the tapetum controlling multiple aspects of pollen development. Inferred transcriptional networks have revealed candidate regulators of this pathway, expanding our knowledge of tapetal gene regulation.

Using single cell sequencing to uncover the “uncoverable” in breast cancer

Breast cancer is responsible for the highest occurrence and mortality rates among the global female population, with one in eight British women diagnosed with the disease in 2019. Despite attempts at ‘personalised’ treatment approaches, most women receive surgery for their disease; for most women this inevitably means receiving systemic antibiotic treatment before and/or after surgery. Whilst antibiotics represent a critical treatment for bacterial infection, they do not discriminate between pathogenic and beneficial microbes, such as those that reside in the gut, i.e. the microbiota. The gut microbiota represents a diverse and dense microbial ecosystem that plays a key role in promoting health through development and priming of the immune system.

Given its key role in regulating immune processes, it is not surprising that the gut microbiota has recently been described as playing a key role in programming anti-cancer responses. Using mouse models of breast cancer, we have been investigating the influence of clinically relevant antibiotics on microbiota composition and tumour immune responses. We have noted that antibiotic induced disturbances of the microbiota accelerate disease progression.

To our surprise, classical approaches to examining changes in the cancer fighting immune system (flow cytometry and whole tumour RNA-seq) uncovered very little. Afraid we were missing subtle changes in immune cell populations or activity pathways by conducting bulk tumour analyses, we adopted a single cell sequencing approach which has allowed us to uncover changes in the immune system that may drive breast cancer progression.

Keeping an Eye on Single Cell Sequencing

Abstract (TBC)

Decoding bacterial heterogeneity at single-cell level

Cell heterogeneity improves the survival of bacterial populations under variable environmental conditions. Heterogeneity in bacterial populations can be attributed to phenotypic and genotypic changes. While the first manifests itself at the level of gene expression, genotypic heterogeneity results from mutational or recombinational events.

Traditionally, bacterial heterogeneity studies are carried out in bulk, assuming individual cell variation is represented by the population. Whilst informative, these results often neglect heterogeneity within the population. Recent studies have shown that heterogeneity at both cellular and molecular levels in isogenic populations could be an order of magnitude greater than previously thought, highlighting the importance of studying microbiology at the single-cell level. While advances in single-cell genomics have aided the characterisation of complexity in eukaryotic cells.

We aimed to develop an approach to study the Salmonella genome at individual cell level. Single cells were isolated by Fluorescence-activated cell sorting (FACS) into 96 well plates. Genomes were amplified using Multiple Displacement Amplification (MDA). Then, pair-ended libraries were prepared using Nextera XT on a robotic platform. Sequencing of 384 samples (including 350 single cells) was performed using the NovaSeq platform and reads were mapped to the Salmonella enterica subsp. enterica serovar Enteritidis, str. P125109 genome.

Salmonella genome from individual cells was successfully amplified by MDA and sequencing results showed in some cases, coverage of nearly 100% of the genome. Overall, the results suggest that our approach allows to generate single amplified genomes of Salmonella and to provide a powerful tool to investigate the bacterial genomic heterogeneity at individual cell level.

Combined short and long read single-cell sequencing identify aging related transcriptional profile and splicing landscape in hematopoietic stem cells and progenitors

Single-cell RNA sequencing analysis has recently provided snapshots of gene expression of stem cells and progenitors across the haematopoietic hierarchy and alterations they undergo during ageing.

As well as transcriptional changes, alternative splicing events and modifications of components of splicing machinery actively contributes to the ageing process.

Current high-throughput single-cell RNA sequencing methods are based on short-read (Illumina) counting of unique 3’ tag sequences. This enables identification of cell types within a complex population of cells but has limitations in terms of resolving transcriptional heterogeneity in closely related cell types and lacks any information on cell-specific isoform expression. Therefore, these methods are missing key aspects of transcriptional regulation and cell fate choice, and perhaps the resolution to distinguish functionally distinct sub-populations of stem and progenitor cells.

In the present work we introduce a novel approach using the 10X Genomics Chromium to generate short-read (Illumina) and long-read (Pacific Biosciences Sequel II) RNA-sequencing libraries from the same single cells. We demonstrate the potential of this approach in defining age dependent changes in sub-populations of cells and annotating cell-type specific isoform expression and splicing alterations associated with ageing in haematopoietic stem and progenitor cells.