Research paperHighly multiplexed quantitation of gene expression on single cells
Introduction
Cellular processes require the intricate coordination of expression of many gene products. Increasingly, our understanding of complex biologic systems depends on the ability to distinguish the genes critical in a cellular process from the myriad of other expressed transcripts. Determining the coordinate expression patterns for multiple genes uniquely defines cellular (and pathophysiological) states than cannot be achieved by measuring a single marker (Seder et al., 2008, Bedognetti et al., 2010). For these reasons, there is a need for methods that simultaneously measure many gene transcripts from a single cell.
Since its introduction over ten years ago, microarray technology has been used in a wide variety of settings (Shaffer et al., 2001, Caskey et al., 2011, Reddy et al., 2012) to identify gene signatures that describe cellular, disease, or vaccine processes. The power of microarrays lies in the high degree of multiplexing: more than 40,000 gene transcripts are analyzed from a single sample. However, typical methods require large numbers of cells (on the order of 106) or substantial nonlinear pre-amplification, limiting the sensitivity and utility of this technology. Importantly, information is lost about coordinate regulation of genes within a cell.
A system that combines the sensitivity and utility of single-cell qPCR with the multiplexed capabilities of microarray analyses is therefore valuable. The Fluidigm Dynamic Array (or BioMark™ system) for single-cell gene expression was recently developed to address this need; the assay is performed on 96 samples simultaneously, and can measure 96 (or more) genes on each sample. It has been used recently in disparate biological settings (Flatz et al., 2011, Narsinh et al., 2011b, Citri et al., 2012); however, methodologic details for optimal and quantitative application of this technology have not been detailed.
Here, we describe methods for qualifying the TaqMan™ primers and probes used in the BioMark™ technology. We determined the optimal methodological parameters ensuring quantitative results, and defined quantitative aspects of assay performance to show, for example, that the limit of detection is a single mRNA transcript. We also investigated whether “endogenous controls” provide useful information in this setting.
We illustrate applications of this technology to immunologic assessments. We show that the measurement of small “bulk” (100-cell) samples, which we term “pooled-cell array,” provides remarkable sensitivity for identifying gene signatures. Finally, we demonstrate the unique power of this technology by applying it to single-cell samples. In particular, we identify genes that are modulated following T-cell activation, and illustrate the heterogeneity of gene expression patterns by activated T-cells.
Section snippets
Biological samples
PBMC were used from human and nonhuman primate specimens. Human specimens were obtained from fully anonymized donors and used under IRB (NIAID, NIH) exemption. NHP specimens were obtained from our cryo-repository of NHP specimens; all specimens were collected as part of IACUC (VRC, NIH)-approved studies.
Primer selection
Assay targets were selected based on their relevance to T-cell immunity, and included genes for T-cell homing, cytokines, cytolytic enzymes, apoptosis, signal transduction, and transcription
Primer qualification
Although TaqMan™ primer/probe sets are nominally tested by the manufacturer for standard qPCR assays, reaction volumes and conditions in the BioMark™ system are significantly different. Therefore, it is important to qualify all primers for this system. Our initial tests showed that primers targeting highly abundant transcripts qualified with highly diluted bulk mRNA; the Et saturated with increasing concentrations of template RNA (e.g., CD7 and MAPK3, Fig. 2A). However, transcripts with low
Discussion
Over the past five years, highly multiplexed, single-cell gene expression has been used increasingly to interrogate complex biological systems. These studies demonstrate that significant heterogeneity underlies cell populations previously thought to be relatively uniform, including early embryonic stages (Guo et al., 2010), neuronal populations (Citri et al., 2012), pluripotent stem cells (Narsinh et al., 2011a), and tumors (Powell et al., 2012). Comparatively little work, however, has been
Conclusions
Quantitative, high throughput qPCR is a powerful technology for identifying gene signatures and unique cell subsets associated with immunological states. As we show here, rigorous optimization and qualification of the technology can provide a wealth of information at either the many-cell level (pooled-cell array) or the single-cell level with similar sensitivity and accuracy.
The following are the supplementary data related to this article.
Acknowledgments
The authors would like to acknowledge the following individuals and contributions: Margaret Beddall, Stephen P. Perfetto, David Ambrozak, and Richard Nguyen (for cell processing, flow cytometry, and cell sorting); Ken Livak, Alain Mir, Andy May, Candida Brown, John Lynch, and Gajus Worthington (for discussion and advice on gene expression assays); the Nonhuman Primate Core of the Vaccine Research Center (for obtaining and preparing Rhesus macaque samples); Christopher Fletez-Brant for
References (25)
- et al.
A deep profiler's guide to cytometry
Trends Immunol.
(2012) - et al.
The stimulatory potency of T cell antigens is influenced by the formation of the immunological synapse
Immunity
(2007) - et al.
Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst
Dev. Cell
(2010) - et al.
Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
Methods
(2013) - et al.
Direct lineage conversion of terminally differentiated hepatocytes to functional neurons
Cell Stem Cell
(2011) - et al.
Signatures of the immune response
Immunity
(2001) - et al.
Gene-expression profiling in vaccine therapy and immunotherapy for cancer
Expert Rev. Vaccines
(2010) - et al.
Synthetic double-stranded RNA induces innate immune responses similar to a live viral vaccine in humans
J. Exp. Med.
(2011) - et al.
A live-cell assay to detect antigen-specific CD4 + T cells with diverse cytokine profiles
Nat. Med.
(2005) - et al.
Comprehensive qPCR profiling of gene expression in single neuronal cells
Nat. Protoc.
(2012)
Stochastic gene expression in a single cell
Science
Cited by (0)
- 1
Contributed equally to this work.