The Impact of Heterogeneity on Single-Cell Sequencing

Goldman, Samantha L.; MacKay, Matthew; Afshinnekoo, Ebrahim; Melnick, Ari; Wu, Shuxiu; Mason, Christopher E.

doi:10.3389/fgene.2019.00008

Cited by 106 publications

(86 citation statements)

References 75 publications

(89 reference statements)

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“…Genetic and molecular heterogeneity in cells of the same tissue type and lineage has become increasingly evident through advanced single-cell omics (43,44). Whether it originates from spontaneous changes in gene expression or stochastic responses to environmental perturbations, this inherent heterogeneity limits the potential efficacy of targeted therapeutics.…”

Section: Discussionmentioning

confidence: 99%

Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression

Nakajima

Guevara-Plunkett

Chuang

et al. 2020

J Virol

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Molecular mechanisms of Kaposi’s sarcoma-associated herpesvirus (KSHV) reactivation have been studied primarily by measuring the total or average activity of an infected cell population, which often consists of a mixture of both nonresponding and reactivating cells that in turn contain KSHVs at various stages of replication. Studies on KSHV gene regulation at the individual cell level would allow us to better understand the basis for this heterogeneity, and new preventive measures could be developed based on findings from nonresponding cells exposed to reactivation stimuli. Here, we generated a recombinant reporter virus, which we named “Rainbow-KSHV,” that encodes three fluorescence-tagged KSHV proteins (mBFP2-ORF6, mCardinal-ORF52, and mCherry-LANA). Rainbow-KSHV replicated similarly to a prototype reporter-KSHV, KSHVr.219, and wild-type BAC16 virus. Live imaging revealed unsynchronized initiation of reactivation and KSHV replication with diverse kinetics between individual cells. Cell fractionation revealed temporal gene regulation, in which early lytic gene expression was terminated in late protein-expressing cells. Finally, isolation of fluorescence-positive cells from nonresponders increased dynamic ranges of downstream experiments 10-fold. Thus, this study demonstrates a tool to examine heterogenic responses of KSHV reactivation for a deeper understanding of KSHV replication. IMPORTANCE Sensitivity and resolution of molecular analysis are often compromised by the use of techniques that measure the ensemble average of large cell populations. Having a research tool to nondestructively identify the KSHV replication stage in an infected cell would not only allow us to effectively isolate cells of interest from cell populations but also enable more precise sample selection for advanced single-cell analysis. We prepared a recombinant KSHV that can report on its replication stage in host cells by differential fluorescence emission. Consistent with previous host gene expression studies, our experiments reveal the highly heterogenic nature of KSHV replication/gene expression at individual cell levels. The utilization of a newly developed reporter-KSHV and initial characterization of KSHV replication in single cells are presented.

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Section: Discussionmentioning

confidence: 99%

Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression

Nakajima

Guevara-Plunkett

Chuang

et al. 2020

J Virol

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“…Often, only the most frequent or the most abundant molecular feature is the one detected on average in a given cell population. (Goldman et al 2019;Haghverdi et al 2016;Trapnell 2015). Although cellular heterogeneity is essential to the survival of a population, where increased diversity in cells allows increased adaptation to changes in the surrounding milieu (Goldman et al 2019), increases in cell-to-cell variability have also been associated to age and age-related diseases (Enge et al 2017;Hernando-Herraez et al 2019;Martinez-Jimenez et al 2017).…”

Section: The Individuality Of Cellsmentioning

confidence: 99%

Advances of single-cell genomics and epigenomics in human disease: where are we now?

Kamies

Martínez-Jiménez

2020

Mamm Genome

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Cellular heterogeneity is revolutionizing the way to study, monitor and dissect complex diseases. This has been possible with the technological and computational advances associated to single-cell genomics and epigenomics. Deeper understanding of cell-to-cell variation and its impact on tissue function will open new avenues for early disease detection, accurate diagnosis and personalized treatments, all together leading to the next generation of health care. This review focuses on the recent discoveries that single-cell genomics and epigenomics have facilitated in the context of human health. It highlights the potential of single-cell omics to further advance the development of personalized treatments and precision medicine in cancer, diabetes and chronic age-related diseases. The promise of single-cell technologies to generate new insights about the differences in function between individual cells is just emerging, and it is paving the way for identifying biomarkers and novel therapeutic targets to tackle age, complex diseases and understand the effect of life style interventions and environmental factors.

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“…Given the critical importance of cellular heterogeneity, whether due to extrinsic or intrinsic factors (recently reviewed in Goldman et al., 2019), simultaneous assessment of gene and protein level fluctuations at a single‐cell resolution is essential. Flow cytometry has been the gold standard for high‐throughput detection of intracellular or surface proteins at the single‐cell level, but a lack of reagent availability and discordant data from proteomic and genomic investigations have been common problems.…”

Section: Commentarymentioning

confidence: 99%

Single‐Cell Analysis of Cytokine mRNA and Protein Expression by Flow Cytometry

et al. 2020

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Understanding how immune cells respond to external stimuli such as pathogens or drugs is a key component of biomedical research. Critical to the immune response are the expression of cell‐surface receptors and the secretion of cytokines, which are tightly regulated by gene expression and protein synthesis. Previously, cytokine mRNA expression levels have been measured from bulk analysis of heterogeneous or sorted cell populations, and the correlation between cytokine mRNA expression and protein levels using these techniques can be highly variable. Flow cytometry is used to monitor changes in cell‐surface and intracellular proteins, but some proteins such as cytokines may be transient and difficult to measure. Thus, a flow cytometry method that can simultaneously measure cytokine mRNA and protein levels in single cells is a very powerful tool. We defined a flow cytometry method that combines the conventional measurement of T cell surface proteins (CD45, CD3, CD4, CD8) and intracellular cytokines (IL‐2, INF‐γ) with fluorescent in situ hybridization and branched DNA technology for amplification and detection of IL‐2 and INF‐γ mRNA transcripts in activated T cells. This method has been applied to frozen peripheral mononuclear blood cells (PBMCs) and frozen blood samples, making it applicable to clinical trial specimens that require shipment to the test site. In CD4+ cells from activated PBMCs, the concordance between mRNA and protein levels was 41% for IL‐2 and 21% for and INF‐γ. In CD8+ cells from activated PBMCs, the concordance was 15% for IL‐2 and 32% for INF‐γ. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Detection of IL‐2 and IFN‐γ mRNA and protein expression in frozen PBMCs Alternate Protocol: Detection of IL‐2 and IFN‐γ mRNA and protein expression in frozen blood

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The Impact of Heterogeneity on Single-Cell Sequencing

Cited by 106 publications

References 75 publications

Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression

Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression

Advances of single-cell genomics and epigenomics in human disease: where are we now?

Single‐Cell Analysis of Cytokine mRNA and Protein Expression by Flow Cytometry

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