ACD can configure probes for the various manual and automated assays for AIF1 for RNAscope Assay, or for Basescope Assay compatible for your species of interest.
Front. Neuroanat.
2018 Jan 23
Yuan X, Caron A, Wu H, Gautron L.
PMID: - | DOI: 10.3389/fnana.2018.00004
Past studies have suggested that non-neuronal brain cells express the leptin receptor. However, the identity and distribution of these leptin receptor-expressing non-neuronal brain cells remain debated. This study assessed the distribution of the long form of the leptin receptor (LepRb) in non-neuronal brain cells using a reporter mouse model in which LepRb-expressing cells are permanently marked by tdTomato fluorescent protein (LepRb-CretdTomato). Double immunohistochemistry revealed that, in agreement with the literature, the vast majority of tdTomato-tagged cells across the mouse brain were neurons (i.e., based on immunoreactivity for NeuN). Non-neuronal structures also contained tdTomato-positive cells, including the choroid plexus and the perivascular space of the meninges and, to a lesser extent, the brain. Based on morphological criteria and immunohistochemistry, perivascular cells were deduced to be mainly pericytes. Notably, tdTomato-positive cells were immunoreactive for vitronectin and platelet derived growth factor receptor beta (PDGFBR). In situ hybridization studies confirmed that most tdTomato-tagged perivascular cells were enriched in leptin receptor mRNA (all isoforms). Using qPCR studies, we confirmed that the mouse meninges were enriched in Leprb and, to a greater extent, the short isoforms of the leptin receptor. Interestingly, qPCR studies further demonstrated significantly altered expression for Vtn and Pdgfrb in the meninges and hypothalamus of LepRb-deficient mice. Collectively, our data demonstrate that the only intracranial non-neuronal cells that express LepRb in the adult mouse are cells that form the blood-brain barrier, including, most notably, meningeal perivascular cells. Our data suggest that pericytic leptin signaling plays a role in the integrity of the intracranial perivascular space and, consequently, may provide a link between obesity and numerous brain diseases.
Acta Neuropathol Commun.
2019 Apr 25
Elkjaer ML, Frisch T, Reynolds R, Kacprowski T, Burton M, Kruse TA, Thomassen M, Baumbach J, Illes Z.
PMID: 31023379 | DOI: 10.1186/s40478-019-0709-3
The heterogeneity of multiple sclerosis is reflected by dynamic changes of different lesion types in the brain white matter (WM). To identify potential drivers of this process, we RNA-sequenced 73 WM areas from patients with progressive MS (PMS) and 25 control WM. Lesion endophenotypes were described by a computational systems medicine analysis combined with RNAscope, immunohistochemistry, and immunofluorescence. The signature of the normal-appearing WM (NAWM) was more similar to control WM than to lesions: one of the six upregulated genes in NAWM was CD26/DPP4 expressed by microglia. Chronic active lesions that become prominent in PMS had a signature that were different from all other lesion types, and were differentiated from them by two clusters of 62 differentially expressed genes (DEGs). An upcoming MS biomarker, CHI3L1 was among the top ten upregulated genes in chronic active lesions expressed by astrocytes in the rim. TGFβ-R2 was the central hub in a remyelination-related protein interaction network, and was expressed there by astrocytes. We used de novo networks enriched by unique DEGs to determine lesion-specific pathway regulation, i.e. cellular trafficking and activation in active lesions; healing and immune responses in remyelinating lesions characterized by the most heterogeneous immunoglobulin gene expression; coagulation and ion balance in inactive lesions; and metabolic changes in chronic active lesions. Because we found inverse differential regulation of particular genes among different lesion types, our data emphasize that omics related to MS lesions should be interpreted in the context of lesion pathology. Our data indicate that the impact of molecular pathways is substantially changing as different lesions develop. This was also reflected by the high number of unique DEGs that were more common than shared signatures. A special microglia subset characterized by CD26 may play a role in early lesion development, while astrocyte-derived TGFβ-R2 and TGFβ pathways may be drivers of repair in contrast to chronic tissue damage. The highly specific mechanistic signature of chronic active lesions indicates that as these lesions develop in PMS, the molecular changes are substantially skewed: the unique mitochondrial/metabolic changes and specific downregulation of molecules involved in tissue repair may reflect a stage of exhaustion.
Description | ||
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sense Example: Hs-LAG3-sense | Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe. | |
Intron# Example: Mm-Htt-intron2 | Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection | |
Pool/Pan Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G) | A mixture of multiple probe sets targeting multiple genes or transcripts | |
No-XSp Example: Hs-PDGFB-No-XMm | Does not cross detect with the species (Sp) | |
XSp Example: Rn-Pde9a-XMm | designed to cross detect with the species (Sp) | |
O# Example: Mm-Islr-O1 | Alternative design targeting different regions of the same transcript or isoforms | |
CDS Example: Hs-SLC31A-CDS | Probe targets the protein-coding sequence only | |
EnEm | Probe targets exons n and m | |
En-Em | Probe targets region from exon n to exon m | |
Retired Nomenclature | ||
tvn Example: Hs-LEPR-tv1 | Designed to target transcript variant n | |
ORF Example: Hs-ACVRL1-ORF | Probe targets open reading frame | |
UTR Example: Hs-HTT-UTR-C3 | Probe targets the untranslated region (non-protein-coding region) only | |
5UTR Example: Hs-GNRHR-5UTR | Probe targets the 5' untranslated region only | |
3UTR Example: Rn-Npy1r-3UTR | Probe targets the 3' untranslated region only | |
Pan Example: Pool | A mixture of multiple probe sets targeting multiple genes or transcripts |
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