Single-cell multimodal transcriptomics to study neuronal diversity in human stem cell-derived brain tissue and organoid models

https://doi.org/10.1016/j.jneumeth.2019.108350Get rights and content

Highlights

  • Cellular reprogramming enables human brain tissue and organoid engineering in vitro.

  • iPSC disease models are challenged by neuronal type heterogeneity.

  • Single-cell RNA-sequencing permits detailed and unbiased cell type delineation.

  • Single-cell analysis is valuable for benchmarking and optimizing tissue engineering.

  • Multimodal single-cell technologies reveal neuronal types and states.

Abstract

Advances in human cell reprogramming and induced pluripotent stem cell technologies generate tremendous potential for neuroscience studies in health and disease, while the neuroscientist toolbox for engineering a range of brain tissues and neuronal cell types is rapidly expanding. Here, we discuss how the emergence of new single-cell genomics methods may help benchmarking and optimizing the tissue engineering process. The inherent heterogeneity and variability of reprogrammed brain tissue may conceal important disease mechanisms if not accounted for by rigorous experimental design. Single-cell genomics methods may address this technical challenge and ultimately improve the development of new therapeutics for neurological and psychiatric disorders.

Introduction

A thorough understanding of the cellular and molecular mechanisms underlying neurological and psychiatric disorders is necessary to discover new therapeutic targets and treatment strategies. The advent of induced pluripotent stem cell (iPSC) (Lowry et al., 2008; Park et al., 2008; Takahashi et al., 2007; Takahashi and Yamanaka, 2006; Yu et al., 2007) and direct cell fate conversion technologies (Caiazzo et al., 2011; Pfisterer et al., 2011; Son et al., 2011) has enabled the derivation of patient-specific live human neurons from easily accessible and renewable somatic cell types, such as skin fibroblasts. While in vitro tissue engineering with stem cells holds great potential for future scientific discoveries, the variability and heterogeneity of lab-engineered brain tissue may conceal important disease mechanisms that preclude therapeutic effects of novel drug candidates. Recent advances in single-cell genomics technologies and bioinformatics have enabled comprehensive and unbiased deconvolution of complex tissue into cellular subtypes based on molecular profiles (Stuart and Satija, 2019). Throughput, sensitivity and multimodal integration of these single-cell genomics methodologies are rapidly and continuously advancing, and it has become easier than ever to measure gene expression and other cellular data in thousands of single cells in an individual experiment. In this review, we discuss the current use, challenges and future perspectives of single-cell genomics methods for the characterization of cellular diversity in human stem cell-derived neuronal tissue. In addition, we detail how single-cell measurements can provide valuable insights into the quality and efficiency of the tissue engineering process, and guide the design of optimized protocols for neuronal differentiation.

Section snippets

Human neuronal tissue engineering: progress and challenges

The ability to derive, manipulate, and differentiate pluripotent stem cells (PSCs) has opened new avenues for generating neural tissue for disease modeling and drug candidate screening in vitro. In recent years, a panoply of protocols has been published for the generation of functional human neurons of specific brain region identities and neurotransmitter phenotypes [e.g., midbrain/dopaminergic (Boyer et al., 2012; Cho et al., 2008; Ma et al., 2011; Tofoli et al., 2019; Zhang et al., 2014),

Single-cell RNA-sequencing to characterize cell diversity and quality in neuronal tissue engineering

The quality of neuronal tissue generated in vitro has traditionally been assessed by morphological and functional (i.e., electrophysiological) characterization of generated neuronal subtypes, and by immunohistochemical detection of proteins that are known to be expressed in vivo. Analysis of transcriptome data from whole tissue can also reveal expression of cell type-relevant genes, but bulk RNA expression profiles represent average measures of gene expression in cells pooled en masse, thus

Multimodal single-cell analysis methods to study neuronal diversity

To acquire a more comprehensive understanding of the molecular-biological mechanisms underlying neuronal function in health, development and disease, recent research endeavors have been geared towards measuring multiple cellular aspects at the individual cell level. These “multimodal” single-cell analysis methods typically combine single-cell transcriptome profiling with the analysis of other cell-specific features, such as electrophysiological function, morphology, genome sequence, epigenetic

Current challenges in single-cell transcriptomics

While single-cell transcriptomics methods create unprecedented opportunities for profiling cellular heterogeneity, careful experimental considerations are necessary to address some important technical limitations, such as tradeoff between sequencing depth and number of cells profiled, detection of low expressed genes, presence of cell doublets, single-cell dissociation bias, and maintaining spatial context of single cells. We discuss these limitations below.

Conclusion and future perspectives

Advances in cell reprogramming and induced pluripotent stem cell technologies have opened new avenues for generating brain tissue for pre-clinical neuroscience studies. However, the large degree of cellular diversity within in vitro engineered neuronal tissue may confound disease phenotypes, hindering accurate detection of novel molecular targets. Single-cell genomics methods address this challenge by enabling a detailed, accurate and unbiased characterization of cellular types and states.

Acknowledgements

This work was supported by the Netherlands Organisation for Scientific Research Rubicon Fellowship (019.163LW.032) (to MvdH); the Brain Foundation, the Perpetual Impact Philanthropy (IPAP2017/0717), Rebecca L. Cooper Foundation and Flinders Foundation (to CB).

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