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Measuring the gene expression profiles of single cells has demonstrated extensive phenotypic heterogeneity within a tissue. This complexity has complicated our understanding of the biological networks that govern tissue function. Our group and others have explored this phenomenon in many tissues and conditions1,2,3,4,5,6. These experiments not only suggest that regulation of gene expression networks underlie such heterogeneity, but also that single-cell resolution reveals a complexity in tissue function that tissue-level resolution fails to appreciate. Indeed, merely a small minority of cells may respond to a specific condition or challenge, but the impact of those cells on overall physiology may be substantial. Additionally, a system biology approach that applies multivariate methods to high dimensional datasets from multiple cell types and tissues can elucidate system-wide treatment effects.
We combine LCM and microfluidic RT-qPCR to obtain such datasets. We take this approach here in contrast to gathering single cells via fluorescence-activated cell sorting (FACS) and using RNA sequencing (RNA-seq) to measure their transcriptome. The advantage of LCM over FACS is that the exact anatomic specificity of single cells can be documented with LCM, relatively and absolutely. Further, while RNA-seq can measure more features that RT-qPCR, microfluidic RT-qPCR is less expensive and has a higher sensitivity and specificity7.
In this representative experiment, we investigated the effects of opioid dependence and naltrexone-precipitated opioid withdrawal on rat neuronal, microglia, and astrocyte gene expression in the central nucleus of the amygdala (CeA) and gut microflora abundance4. Four treatment groups were analyzed: 1) Placebo, 2) Morphine, 3) Naltrexone, and 4) Withdrawal (Figure 1). We found that opioid dependence did not substantially alter gene expression, but that opioid withdrawal induced the expression of inflammatory genes, Tnf in particular. Astrocytes were the most affected cell type. The gut microbiome was profoundly impacted by opioid withdrawal as indicated by a decrease in the Firmicutes to Bacteroides ratio, which is an established marker of gut dysbiosis8,9.