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The neuronal cell-specific proteomeThe neuronal cell transcriptomeBrain excitatory neuronsBrain inhibitory neuronsRetinal amacrine cellsRetinal horizontal cellsRetinal ganglion cellsRetinal bipolar cellsRod photoreceptor cellsCone photoreceptor cellsOther brain neuronsDeep Visual Proteomics analysis of neuronal cellNeuronsNeuronal cell functionBackgroundRelevant links and publications
Single cell type methods
DVP methods
The neuronal cell-specific proteomeThe function of the brain, defined as the central nervous system, is to receive, process and execute the coordinated higher functions of perception, motion and cognition that signify human life. Retina is an extension of the CNS responsible specifically for vision. The cellular components of the underlying and highly complex network of transmitted signals include neurons and supportive glial cells. Transcriptome analysis shows that 67% (n=13603) of all human proteins (n=20162) are detected in neuronal cells and 2445 of these genes show an elevated expression in any neuronal cells compared to other cell type groups. In-depth analysis of the elevated genes in neuronal cells using scRNA-seq and antibody-based protein profiling allowed us to visualize the expression patterns of these proteins in the following types of neuronal cells: Brain exitatory neurons, Brain inhibitory neurons, Retinal amacrine cells, Retinal horizontal cells, Retinal ganglion cells, Retinal bipolar cells, Rod photoreceptor cells, Cone photoreceptor cells and other Brain neurons. In addition, we utilized proteomic data from a mass spectrometry (MS)-based, cell type–resolved atlas of the human body, generated via Deep Visual Proteomics (DVP), a spatial proteomics platform that combines imaging-guided cell selection with high-resolution protein analysis. The analysis includes neuronal cells. Out of a total of 14361 detected proteins in all cell types, 8361 were detected in neuronal cells, and 2114 were classified as elevated in neuronal cells. Further details on cell type specific proteome profiles, as well as examples of enriched proteins in neuronal cells, are provided below.
The neuronal cell transcriptomeThe scRNA-seq-based neuronal cell transcriptome can be analyzed with regard to specificity, illustrating the number of genes with elevated expression in each specific neuronal cell type compared to other cell types (Table 1). Genes with an elevated expression are divided into three subcategories:
Table 2. Number of genes in the subdivided specificity categories of elevated expression in the respective neuronal cell types compared to other cell types.
Brain excitatory neuronsExcitatory neuons primarly release glutamate to activate downsteram targets and promite neural circuit activity. Brain excitatory neurosn are important for information transmission, learning, and snyaptic placticity throughout the brain. As shown in Table 2, 1612 genes show elevated expression in excitatory neurons of the brain, compared to other cell types. NEUROD6 a member of the NEUROD family of genes is one of the genes with elevated expression in excitatory neurons and may be a trans-acting factor involved in the development and maintenance and differentiation of the CNS. Another exampled of gene with enriched expression is CBLN3 which is a synaptic protein specific for cerebellar granular cells, the most abundant neuron of the human brain. The representation of brain excitatory neurons spans several brain regions, regional specificity can be found in the brain specific UMAP that holds detailed cluster names.
Brain inhibitory neuronsInhibitory neurosn mainly release GABA to supress or fine-tune the activity of downstream targets and neural circuit activity. They maintain network balance, pervent overexcitation, and shape synchronized brain activity. As shown in Table 2, 1619 genes show elevated expression in inhibitory neurons of the brain, compared to other cell types. Glutamate decarboxylase 1 (GAD1) is an essential enzyme in the biosynthesis of GABA and known to be expressed in the majority of cortical GABAergic interneurons as well as in purkinjecells of the cerebellum.
Retinal amacrine cellsAmacrine cells are interneurons that modulate signaling between bipolar and ganglion cells within the inner plexiform layer of retina. They contribute to temporal processing, motion detection, and modulation of visual signals before it leaves the retina. As shown in Table 2, 715 genes show elevated expression in retinal amacrine cells, compared to other cell types.SLC32A1 show elevated expression in amacrine cells, as well as expression in the horizontal cells, however, at protein level it is mainly detected in the inner plexiform layer- further supporting the relation to amacrine cells.
Retinal horizontal cellsHorizontal cells provide lateral inhibition at the level of photoreceptor-bipolar synapses in the outer plexiform layer. They help enhance visual contrast and contriute to spatial processing by integrating signals across photoreceptors. As shown in Table 2, 581 genes show elevated expressio in horizontal cells compared to other cell types.
Retinal ganglion cellsRetinal gnalgion cells receive processed input from bipolar and amacrine cells and trasmit visual information to the brain via the optic nerve. They are the final output neurons of the retina and encode key visual features such as contrast, motion and color. As shown in Table 2, 592 genes show elevated expression in horizontal cells compared to other cell types.
Retinal bipolar cellsBipolar cells relay visual signals from photoreceptors to ganglion cells through distinct ON and OFF pathways. They play a critical role in separating light and dark responses and maintaining parallel processing channels in the retina. As shown in Table 2, 658 genes show elevated expression in bipolar cells compared to other cell types. Transient receptor potential cation channel subfamily M member 1 (TRPM1) is an example of a protein expressed in bipolar cells. It is a cation channel necessary for the activation of ON-bipolar cells in light conditions.
Rod photoreceptor cellsRod photoreceptors are hihgli sensitive to low light and allowing for vision under dim conditions. They detect light intensity but not color. Out of the two types of photoreceptor cells, rods are the more abundant type. As shown in Table 2, 645 genes show elevated expression in rod photoreceptor cells compared to other cell types. Two proteins essential for rod function are rhodopsin (RHO) and G protein subunit gamma transducin 1 (GNGT1). They are involved in two different steps of phototransduction, the process of conversion from light to nerve signals.
Cone photoreceptor cellsCone photoreceptors function in bright light and enable color vision. Different cone types respond to specific wavelenghts, supporting color discrimination. Cone photoreceptors cells are the less abundant of the two types of photoreceptor cells found in the retina.As shown in Table 2, 704 genes show elevated expression in cone photoreceptor cells compared to other cell types. One example of a protein expressed in cone photoreceptor cells is arrestin 3 (ARR3), a protein involved in the return of photoreceptor cells to a deactivated state at the end of the phototransduction.
Other brain neuronsAs shown in Table 2, 1469 genes are classified as elevated in other brain neurons, compared to other cell types. The group of "other brain neurons" includes neurons not included in the simple division of exitatory and inhibitory neurons, such as dopaminergic, hypthalamic magnocellular neurons and unassigned clusters of neuronal cell types. An examples of a gene with elevated expression in these neuronal cell types is SLC6A3, a solute carrier, also called DAT, a dopamin transporter specificly expressed by the dopaminergic neurons. Another example is OXT, coding for Oxytocin/neurophysin I prepropeptide, specifically expressed by the magnocellular neurrosn of hypothalamus.
Deep Visual Proteomics analysis of neuronal cellProteomic data from a mass spectrometry (MS)-based, cell type–resolved atlas of the human body, generated via Deep Visual Proteomics (DVP), a spatial proteomics platform that combines imaging-guided cell selection with high-resolution protein analysis, is integrated to the Single Cell Type resrouce. This enables exploration of global protein detection profiles with RNA expression profiles. The DVP data includes 13496 detected proteins and covers 27 cell types which is grouped into 24 main cell types used for classification and the RNA comparison. The cell type specificity categories were applied to the protein data. Here, we describe the included neuronal cell and show examples of proteins with elevated detection. NeuronsDVP resulted in 2114 proteins classified as elevated in neurons. In total, 8361 proteins were detected in neurons, out of these, 192 were only detected in neurons, compared to the other 23 DVP samples. Cerebral cortex represents the brain in the DVP, and the selection of neurons is based on the pan-neuronal marker NeuN (RBFOX3). Note, the segmentation of the neurons is focused on the cell body, i.e. includes cell nuclus and cytoplasm, but limited cell membrane and is missing neurites. The astrocyte and microglia DVP samples include neuropil, and therefore many synaptic proteins are detected in those samples instead of this neuron sample. The 355 proteins enriched in neurons are strongly enriched for neuronal differentiation, synaptic regulation, and RNA processing programs. Key neurodevelopmental and neuronal identity factors such as TBR1, DLX1, DNER, and RNA-binding/splicing regulators including RBFOX1, RBFOX3, NOVA1, and NOVA2, along with neuronal ELAVL proteins (ELAVL3, ELAVL4), highlight active control of gene expression underlying neuronal specification and synaptic function. Additional components like ion channel–related proteins (KCNJ6, KCNS2) and signaling/regulatory molecules (RGS8, DOK6) further support roles in excitability and neuronal signaling. Proteins elevated in the DVP neuron sample highlights the regulatory aspect of a neuron, and even if several specific markers are there, this signature may not represent only the most canonical “pan-neuronal” markers, such as SNAP25. However, synaptic markers such as SNAP25, with high specificity at RNA-level does not match the protein profile. Immunostained brain section illustrates this, with a "negative" neuronal cell body compared to detecton throughout the neuropil of the brain section. Learn more about the comparison between matched RNA and protein levels here, and use the search fields to filter on overlap, partial or no overlap. Note, there are several technical limitations to this comparison, comparing RNA with protein is a complex and context-dependent quest. Neuronal cell functionNeuronal cells are electrically excitatory cells that communicate through their synapses that connect to other neurons within its neuronal network. There are classes of neurons that serve different functions. Among those are sensory neurons, that receive signals from sensory organs such as skin, eyes and ears when affected by a stimulus, motor neurons that control movement and muscle contraction when receiving signals from the spinal cord and the brain, and interneurons, a network that connects neurons with other neurons and forming a neuronal circuit. The typical neuronal cell consists of an axon, a cell body and dendrites. The signaling in neurons can be inhibitory or excitatory where the signal is driven by a membranous voltage gradient called action potential that generates a pulse that travels through the axon into the synapses. The histology of organs that contain neuronal cells, including interactive images, is described in the Protein Atlas Histology Dictionary. BackgroundHere, the protein-coding genes expressed in neuronal cells are described and characterized, together with examples of immunohistochemically stained tissue sections that visualize corresponding protein expression patterns of genes with elevated expression in different neuronal cell types. The transcript profiling was based on publicly available genome-wide expression data from scRNA-seq and snRNA-seq experiments (36 datasets) covering 34 tissues. All datasets (unfiltered read counts of cells) were clustered independenty using leiden clustering, resulting in a total of 1175 different cell type clusters. The clusters were then manually annotated based on a survey of known tissue and cell type-specific markers. The RNA-seq data from each cluster of cells was aggregated to mean normalized protein-coding counts per million (nCPM) for all protein-coding genes. A specificity and distribution classification was performed for both single cell types individually, as well as grouped into 53 main cell type groups. The specificity classification determined the number of elevated genes, while the distribution determined whether genes are detected in one, several or all cell types or cell type groups. It should be noted that since the analysis was limited to datasets representing 34 tissue types, not all human cell types are represented. Furthermore, some cell types are present only in low amounts, or identified only in mixed cell clusters, which may affect the results and bias the cell type specificity. Relevant links and publications Uhlén M et al., Tissue-based map of the human proteome. Science (2015) |
The Human Protein Atlas project is funded
