RNA Amplification in Brain Tissues

Recent developments in gene array technologies, specifically cDNA microarray platforms, have made it easier to try to understand the constellation of gene alterations that occur within the CNS. Unlike an organ that is comprised of one principal cell type, the brain contains a multiplicity of both neuronal (e.g., pyramidal neurons, interneurons, and others) and noneuronal (e.g., astrocytes, microglia, oligodendrocytes, and others) populations of cells. An emerging goal of modern molecular neuroscience is to sample gene expression from similar cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subtypes and noneuronal cells. At present, an optimal methodology to assess gene expression is to evaluate single cells, either identified physiologically in living preparations, or by immunocytochemical or histochemical procedures in fixed cells in vitro or in vivo. Unfortunately, the quantity of RNA harvested from a single cell is not sufficient for standard RNA extraction methods. Therefore, exponential polymerase-chain reaction (PCR) based analyses and linear RNA amplifications, including a newly developed terminal continuation (TC) RNA amplification methodology, have been used in combination with single cell microdissection procedures to enable the use of cDNA microarray analysis within individual populations of cells obtained from postmortem brain samples as well as the brains of animal models of neurodegeneration.     

单细胞转录组测序在药物成瘾研究中的应用

药物成瘾是复杂的中枢神经系统疾病，相关基础与临床研究均证实药物成瘾的神经机制及神经环路在成瘾行为形成的不同阶段逐渐发生改变。利用全基因组关联研究、全基因组测序、全外显子测序或高通量转录组测序等技术的组学研究对包括药物成瘾在内的精神疾病遗传的脆弱性进行了深入研究。上述单核苷酸多态性检测技术或测序技术主要预测疾病的遗传风险位点。然而，许多中枢神经系统疾病的发生与环境因素密切相关，而且在疾病发展的不同阶段，相关基因的表达存在脑区特异性的细胞异质性信息。因此，传统研究对发病机制的解释存在一定的局限性。单细胞转录组测序技术是针对单个细胞进行转录水平的测定，规避了传统测序对细胞群体平均转录水平检测的缺点，可以定量描述细胞异质性。近年来，单细胞转录测序技术在神经精神科学研究中的应用逐渐受到关注，本文总结了该技术在神经科学研究中的重要应用，并以药物成瘾为例，重点阐述说明其在中枢神经系统疾病中的应用价值。     

单细胞转录组高通量测序分析新进展

细胞异质性是生物组织的普遍特征。常规转录组测序(RNA-Seq)技术需要上万个细胞,所测结果实际上是一群细胞基因表达的平均值,所以难以鉴别细胞之间基因表达的异质性。单细胞RNA-Seq技术的分辨率精确至单个细胞,为辨别异质性群体中各种细胞类型的转录组特征提供了有力的工具。近年来单细胞RNA-Seq技术发展迅速,在方法学上包括cDNA扩增方法的多样化、对灵敏度和技术噪声的定量分析、浅覆盖高通量单细胞RNA-Seq方法和原位RNA-Seq技术等;在技术应用方面应用范围从早期胚胎发育扩大到组织器官发育、免疫和肿瘤等多个领域。文章对单细胞RNA-Seq在方法学和技术应用两方面的研究进展进行了详细阐述。     

Optimization of Single-Cell Electroporation Protocol for Forced Gene Expression in Primary Neuronal Cultures

The development and function of the central nervous system (CNS) are realized through interactions between many neurons. To investigate cellular and molecular mechanisms of the development and function of the CNS, it is thus crucial to be able to manipulate the gene expression of single neurons in a complex cell population. We recently developed a technique for gene silencing by introducing small interfering RNA into single neurons in primary CNS cultures using single-cell electroporation. However, we had not succeeded in forced gene expression by introducing expression plasmids using single-cell electroporation. In the present study, we optimized the experimental conditions to enable the forced expression of green fluorescent protein (GFP) in cultured cerebellar Purkinje neurons using single-cell electroporation. We succeeded in strong GFP expression in Purkinje neurons by increasing the inside diameter of micropipettes or by making the size of the original plasmid smaller by digestion and cyclizing it by ligation. Strong GFP expression in Purkinje neurons electroporated under the optimal conditions continued to be observed for more than 25 days after electroporation. Thus, this technique could be used for forced gene expression in single neurons to investigate cellular and molecular mechanisms of the development, function, and disease of the CNS.     

Localization of brain nitric oxide synthase (NOS) to human chromosome 12.

Recent research has shown that nitric oxide is a novel neuronal second messenger and transmitter that may be involved in neuronal cell death and damage in neurological illness. To map the chromosomal localization of this important brain enzyme, a rat cDNA probe was prepared by RNA PCR from rat cerebellum RNA. This rat cDNA was used to isolate a human nitric oxide synthase (NOS) cDNA from a human cerebellum cDNA library. The human cDNA clone containing 1.2 kb of brain NOS cDNA was hybridized to Southern blots containing DNAs obtained from human-rodent hybrid cell line panels using EcoRI and HindIII digestion to ascertain the location of the human NOS gene. These data showed that the human brain nitric oxide synthase mapped within 12q14-qter on human chromosome 12.     

The Vasculome of the Mouse Brain

The blood vessel is no longer viewed as passive plumbing for the brain. Increasingly, experimental and clinical findings suggest that cerebral endothelium may possess endocrine and paracrine properties – actively releasing signals into and receiving signals from the neuronal parenchyma. Hence, metabolically perturbed microvessels may contribute to central nervous system (CNS) injury and disease. Furthermore, cerebral endothelium can serve as sensors and integrators of CNS dysfunction, releasing measurable biomarkers into the circulating bloodstream. Here, we define and analyze the concept of a brain vasculome, i.e. a database of gene expression patterns in cerebral endothelium that can be linked to other databases and systems of CNS mediators and markers. Endothelial cells were purified from mouse brain, heart and kidney glomeruli. Total RNA were extracted and profiled on Affymetrix mouse 430 2.0 micro-arrays. Gene expression analysis confirmed that these brain, heart and glomerular preparations were not contaminated by brain cells (astrocytes, oligodendrocytes, or neurons), cardiomyocytes or kidney tubular cells respectively. Comparison of the vasculome between brain, heart and kidney glomeruli showed that endothelial gene expression patterns were highly organ-dependent. Analysis of the brain vasculome demonstrated that many functionally active networks were present, including cell adhesion, transporter activity, plasma membrane, leukocyte transmigration, Wnt signaling pathways and angiogenesis. Analysis of representative genome-wide-association-studies showed that genes linked with Alzheimer’s disease, Parkinson’s disease and stroke were detected in the brain vasculome. Finally, comparison of our mouse brain vasculome with representative plasma protein databases demonstrated significant overlap, suggesting that the vasculome may be an important source of circulating signals in blood. Perturbations in cerebral endothelial function may profoundly affect CNS homeostasis. Mapping and dissecting the vasculome of the brain in health and disease may provide a novel database for investigating disease mechanisms, assessing therapeutic targets and exploring new biomarkers for the CNS.     

Profiling gene expression in whole blood samples following an in-vitro challenge.

Genomics tools (gene- and protein-expression studies) can be used to find possible target genes involved in a quantifiable trait or disease state. However in many instances, cells and tissues directly involved in the trait's expression, for example, brain tissue, are not amenable for gene expression analysis. Whole blood cells share a molecular make-up for cellular communication and gene regulation systems with many other cell types, for example, neuronal cells, and have the advantage of being very accessible for gene profiling. We investigated the feasibility of nationwide blood sample collection for lymphocyte RNA isolation and real-time PCR analysis to quantify genomic responses. We tested several designs for blood collection and storage: blood sampling in PAXgene blood collection tubes and storage at -20 degrees C, blood sampling in heparin tubes and decanting the samples (with or without in-vitro stimulus) into either PAXgene blood collection tubes and storage at -20 degrees C, or polypropylene tubes followed by snap-freezing and storage at -80 degrees C. The latter procedure is the best cost-wise when only small amounts of total RNA are needed for downstream applications. Lymphocyte gene expression studies are most likely hampered by the quality of isolated RNA rather than the sampling method. We show that large-scale nationwide sample collections did not alter RNA quality or gene expression levels when compared to sampling and processing in a more controlled way. To this end, we present an optimized protocol for easy and standardized isolation of high quality RNA using the PAXgene isolation kit. Based on these results, we suggest that whole blood genomic data can be used as a genomic probe in experimental and clinical research.     

Elevated ATG5 expression in autoimmune demyelination and multiple sclerosis

Multiple sclerosis (MS) is an inflammatory central nervous system (CNS) disorder characterized by T cell mediated demyelination. In MS, prolonged T cell survival and increased T cell proliferation have been linked to disease relapse and progression. Recently, the autophagy related gene 5 (Atg5) has been shown to modulate T cell survival. In this study, we examined the expression of Atg5 using both a mouse model of autoimmune demyelination as well as blood and brain tissues from MS cases. Quantitative real-time PCR analysis of RNA isolated from blood samples of experimental autoimmune encephalomyelitis (EAE) mice revealed a strong correlation between Atg5 expression and clinical disability. Analysis of protein extracted from these cells confirmed both upregulation and post-translational modification of Atg5 the latter of which was positively correlated with EAE severity. Analysis of RNA extracted from T cells isolated by negative selection, indicated that Atg5 expression was significantly elevated in individuals with active relapsing-remitting MS compared to non-diseased controls. Brain tissue sections from relapsing-remitting MS cases examined by immunofluorescent histochemistry suggested that encephalitogenic T cells are a source of Atg5 expression in MS brain samples. Together these data suggest that increased T cell expression of Atg5 may contribute to inflammatory demyelination in MS.     

CNS neurotrophins are biologically active and expressed by multiple cell types

Neutrotrophins are increasingly appreciated as potential modulators of neuronal function in the adult central nervous system (CNS). To describe the neurotrophin environment within the adult CNS, mRNA and protein expression patterns of neurotrophins-3 and –4 and of brain-derived neurotrophin were investigated in adult rat spinal cord and brain. Co-localization studies with CNS cell type-specific markers demonstrates that multiple cell types, including both neurons and glia, express these neurotrophins in the normal adult CNS. Although widely implicated in important CNS functions such as synaptic plasticity, biological activity of endogenous CNS neurotrophins has not been directly demonstrated. With a sensitive neurite outgrowth bioassay we demonstrate that CNS neurotrophins elicit neurite outgrowth and are biologically active. Moreover, antibody-blocking studies suggest that these three neurotrophins may comprise the bulk of adult CNS neurotrophic activity.     

Single-cell analysis of gene expression in the nervous system

The characteristic functions of tissues and organs results from the integrated activity of individual cells. Nowhere is this more evident than in the nervous system, where the activities of single neurons communicating via electrical and chemical signals mediate complex functions, such as learning and memory. The past decade has seen an explosion in the identification of genes encoding proteins, such as voltage-gated channels and neurotransmitter receptors, responsible for neuronal excitability. These studies have highlighted the fact that even within a neuroanatomically defined region, the coexistence of multiple cell types makes it difficult, if not impossible, to correlate patterns of gene expression with function The recent development of techniques sensitive enough to, study gene expression at the single-cell level promises to break this bottleneck to our further understanding. Using examples taken from our own laboratories and the work of others, we review these techniques, their application, and discuss some of the difficulties associated with the interpretation of the data.     

Cloning and identification of a novel human gene PDLIM5, a homolog of AD-associated neuronal thread protein (AD7c-NTP).

A novel human gene cDNA was successfully cloned from the human fetal brain cDNA library constructed by our lab, and this gene was termed PDLIM5 after acquiring the agreement of HUGO. BLASTX searching revealed that the hypothetical protein is a homolog of AD-associated neuronal thread protein (AD7c-NTP), which is over-expressed in Alzheimer disease (AD) beginning early in the course of disease, and over-expression of the AD7c-NTP gene would cause neuritic sprouting and cell death. SMART analysis showed that both our predicted protein and AD7c-NTP comprise BCL domain (only contains BH1 and BH2 regions). RT-PCR experiment revealed that the expression level of PDLIM5 in brain, skeletal muscle, prostate, colon and leukocyte is obviously higher than that in other tissues.     

Identifying Cell Types from Spatially Referenced Single-Cell Expression Datasets

Complex tissues, such as the brain, are composed of multiple different cell types, each of which have distinct and important roles, for example in neural function. Moreover, it has recently been appreciated that the cells that make up these sub-cell types themselves harbour significant cell-to-cell heterogeneity, in particular at the level of gene expression. The ability to study this heterogeneity has been revolutionised by advances in experimental technology, such as Wholemount in Situ Hybridizations (WiSH) and single-cell RNA-sequencing. Consequently, it is now possible to study gene expression levels in thousands of cells from the same tissue type. After generating such data one of the key goals is to cluster the cells into groups that correspond to both known and putatively novel cell types. Whilst many clustering algorithms exist, they are typically unable to incorporate information about the spatial dependence between cells within the tissue under study. When such information exists it provides important insights that should be directly included in the clustering scheme. To this end we have developed a clustering method that uses a Hidden Markov Random Field (HMRF) model to exploit both quantitative measures of expression and spatial information. To accurately reflect the underlying biology, we extend current HMRF approaches by allowing the degree of spatial coherency to differ between clusters. We demonstrate the utility of our method using simulated data before applying it to cluster single cell gene expression data generated by applying WiSH to study expression patterns in the brain of the marine annelid Platynereis dumereilii. Our approach allows known cell types to be identified as well as revealing new, previously unexplored cell types within the brain of this important model system.