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Open Access Publications from the University of California

Scholarly Works (7 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2018)

Adult stem cells maintain structure and function of tissues under widely varying conditions, but the molecular and cellular mechanisms that underlie the development of diverse cell types during either tissue maintenance or injury-induced regeneration remain incompletely understood. This dissertation combines lineage tracing with single-cell RNA sequencing and assay for transposase-accessible chromatin (ATAC) sequencing to address the regulation of these phenomena in the olfactory epithelium, one of only a few sites of ongoing adult neurogenesis.

Olfactory stem cells, known as horizontal basal cells (HBCs), contribute to both maintenance and regeneration of the tissue. First, we consider the role of HBCs in homeostatic conditions. Classifying cells on the basis of gene expression, we identify three lineage trajectories arising from HBCs via two developmental bifurcations. We find that sustentacular cells arise by direct fate conversion of HBCs without cell division, as predicted by single-cell RNA-sequencing and validated by clonal lineage tracing. We also establish that multipotency of the HBC population arises from unipotent fate decisions of individual HBCs. Finally, single-cell RNA-sequencing indicates that canonical Wnt signaling promotes neuronal fate choices in HBCs, which we validate in vivo with gain-of-function and loss-of-function experiments.

Second, we consider the contribution of HBCs to injury-induced regeneration of the olfactory epithelium, and whether the HBC injury response differs from homeostatic maintenance. We discovered activated olfactory stem cell states that are both transient and unique to regeneration. The activated stem cells express genes associated with epithelial wound repair in other stem cell niches. These cells are also heterogeneous, giving rise to multiple lineages, including renewed HBCs. Moreover, renewed HBCs are themselves competent to produce differentiated cell types, and do so in a second wave of differentiation several days after injury, bypassing the transient activated states associated with the earliest stages of regeneration.

Finally, we begin investigation of the priming of quiescent HBCs for rapid transcriptional response to injury, using ATAC sequencing to query chromatin accessibility. We find the HBCs to have broadly accessible chromatin at gene promoters corresponding to more differentiated cells in the olfactory lineage, but they maintain a closed conformation over the coding regions of genes that are not actively expressed.

Taken together, these findings contribute to our understanding of how neurogenesis and regeneration are accomplished in a fully-developed, adult sensory tissue. Our integration of single-cell genomics with in vivo lineage tracing lays the groundwork for investigating outstanding questions relating to the development, maintenance, and repair of other tissues. This work may ultimately aid in the development of stem-cell based therapies to replace specialized cell types and tissues lost to damage and disease.

    Cover page: Identification of Olfactory Stem Cell Lineage Trajectories and Cell State Transitions
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2018)
    Mapping the paths that stem and progenitor cells take en route to differentiate and elucidating the underlying molecular controls are key goals in developmental and stem cell biology. However, with population level analyses it is difficult - if not impossible - to define the transition states and lineage trajectory branch points within complex developmental lineages. Single-cell RNA-sequencing analysis can discriminate heterogeneity in a population of cells and even identify rare or transient intermediates. In this review, we propose that using these data, one can infer the lineage trajectories of individual stem cells and identify putative branch points. Clonal lineage tracing of stem cells allows one to define the outcome of differentiation. Integrating these single cell-based approaches provides a robust strategy for establishing and testing models of how an individual stem cell changes through time to differentiate and self-renew.
      Cover page: Creating Lineage Trajectory Maps Via Integration of Single‐Cell RNA‐Sequencing and Lineage Tracing
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2018)
      Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of finding biologically meaningful subtypes within the samples. This is an application that is particularly appropriate when there are large numbers of samples, as in many human disease studies. With the increasing popularity of single-cell transcriptome sequencing (RNA-Seq), many more controlled experiments on model organisms are similarly creating large gene expression datasets with the goal of detecting previously unknown heterogeneity within cells. It is common in the detection of novel subtypes to run many clustering algorithms, as well as rely on subsampling and ensemble methods to improve robustness. We introduce a Bioconductor R package, clusterExperiment, that implements a general and flexible strategy we entitle Resampling-based Sequential Ensemble Clustering (RSEC). RSEC enables the user to easily create multiple, competing clusterings of the data based on different techniques and associated tuning parameters, including easy integration of resampling and sequential clustering, and then provides methods for consolidating the multiple clusterings into a final consensus clustering. The package is modular and allows the user to separately apply the individual components of the RSEC procedure, i.e., apply multiple clustering algorithms, create a consensus clustering or choose tuning parameters, and merge clusters. Additionally, clusterExperiment provides a variety of visualization tools for the clustering process, as well as methods for the identification of possible cluster signatures or biomarkers. The R package clusterExperiment is publicly available through the Bioconductor Project, with a detailed manual (vignette) as well as well documented help pages for each function.
        Cover page: clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2018)

        Background

        Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve.

        Results

        We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods.

        Conclusions

        Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression.
          Cover page: Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2017)
          A detailed understanding of the paths that stem cells traverse to generate mature progeny is vital for elucidating the mechanisms governing cell fate decisions and tissue homeostasis. Adult stem cells maintain and regenerate multiple mature cell lineages in the olfactory epithelium. Here we integrate single-cell RNA sequencing and robust statistical analyses with in vivo lineage tracing to define a detailed map of the postnatal olfactory epithelium, revealing cell fate potentials and branchpoints in olfactory stem cell lineage trajectories. Olfactory stem cells produce support cells via direct fate conversion in the absence of cell division, and their multipotency at the population level reflects collective unipotent cell fate decisions by single stem cells. We further demonstrate that Wnt signaling regulates stem cell fate by promoting neuronal fate choices. This integrated approach reveals the mechanisms guiding olfactory lineage trajectories and provides a model for deconstructing similar hierarchies in other stem cell niches.
            Cover page: Deconstructing Olfactory Stem Cell Trajectories at Single-Cell Resolution.
            • Article
            • Peer Reviewed
            UC Berkeley Previously Published Works (2017)
            Tissue homeostasis and regeneration are mediated by programs of adult stem cell renewal and differentiation. However, the mechanisms that regulate stem cell fates under such widely varying conditions are not fully understood. Using single-cell techniques, we assessed the transcriptional changes associated with stem cell self-renewal and differentiation and followed the maturation of stem cell-derived clones using sparse lineage tracing in the regenerating mouse olfactory epithelium. Following injury, quiescent olfactory stem cells rapidly shift to activated, transient states unique to regeneration and tailored to meet the demands of injury-induced repair, including barrier formation and proliferation. Multiple cell fates, including renewed stem cells and committed differentiating progenitors, are specified during this early window of activation. We further show that Sox2 is essential for cells to transition from the activated to neuronal progenitor states. Our study highlights strategies for stem cell-mediated regeneration that may be conserved in other adult stem cell niches.
              Cover page: Injury Activates Transient Olfactory Stem Cell States with Diverse Lineage Capacities
              • Article
              • Peer Reviewed
              UC Berkeley Previously Published Works (2020)
              Altered olfactory function is a common symptom of COVID-19, but its etiology is unknown. A key question is whether SARS-CoV-2 (CoV-2) - the causal agent in COVID-19 - affects olfaction directly, by infecting olfactory sensory neurons or their targets in the olfactory bulb, or indirectly, through perturbation of supporting cells. Here we identify cell types in the olfactory epithelium and olfactory bulb that express SARS-CoV-2 cell entry molecules. Bulk sequencing demonstrated that mouse, non-human primate and human olfactory mucosa expresses two key genes involved in CoV-2 entry, ACE2 and TMPRSS2. However, single cell sequencing revealed that ACE2 is expressed in support cells, stem cells, and perivascular cells, rather than in neurons. Immunostaining confirmed these results and revealed pervasive expression of ACE2 protein in dorsally-located olfactory epithelial sustentacular cells and olfactory bulb pericytes in the mouse. These findings suggest that CoV-2 infection of non-neuronal cell types leads to anosmia and related disturbances in odor perception in COVID-19 patients.
                Cover page: Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia.
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