ACD can configure probes for the various manual and automated assays for INS for RNAscope Assay, or for Basescope Assay compatible for your species of interest.
Cell (2018)
2018 Dec 06
Gibson EM, Nagaraja S, Ocampo A, Tam LT, Wood LS, Pallegar PN, Greene JJ, Geraghty AC, Goldstein AK, Ni L, Woo PJ, Barres BA, Liddelow S, Vogel H, Monje M.
| DOI: 10.1016/j.cell.2018.10.049
Neuron
2019 May 10
Geraghty AC, Gibson EM, Ghanem RA, Greene JJ, Ocampo A, Goldstein AK, Ni L, Yang T, Marton RM, Paşca SP, Greenberg ME, Longo FM, Monje M.
PMID: 31122677 | DOI: 10.1016/j.neuron.2019.04.032
Activity-dependent myelination is thought to contribute to adaptive neurological function. However, the mechanisms by which activity regulates myelination and the extent to which myelin plasticity contributes to non-motor cognitive functions remain incompletely understood. Using a mouse model of chemotherapy-related cognitive impairment (CRCI), we recently demonstrated that methotrexate (MTX) chemotherapy induces complex glial dysfunction for which microglial activation is central. Here, we demonstrate that remote MTX exposure blocks activity-regulated myelination. MTX decreases cortical Bdnf expression, which is restored by microglial depletion. Bdnf-TrkB signaling is a required component of activity-dependent myelination. Oligodendrocyte precursor cell (OPC)-specific TrkB deletion in chemotherapy-naive mice results in impaired cognitive behavioral performance. A small-molecule TrkB agonist rescues both myelination and cognitive impairment after MTX chemotherapy. This rescue after MTX depends on intact TrkB expression in OPCs. Taken together, these findings demonstrate a molecular mechanism required for adaptive myelination that is aberrant in CRCI due to microglial activation
Nature
2019 Jan 30
Baser A, Skabkin M, Kleber S, Dang Y, Gülcüler Balta GS, Kalamakis G, Göpferich M, Ibañez DC, Schefzik R, Lopez AS, Bobadilla EL, Schultz C, Fischer B, Martin-Villalba A.
PMID: 30700908 | DOI: 10.1038/s41586-019-0888-x
Whether post-transcriptional regulation of gene expression controls differentiation of stem cells for tissue renewal remains unknown. Quiescent stem cells exhibit a low level of protein synthesis1, which is key to maintaining the pool of fully functional stem cells, not only in the brain but also in the bone marrow and hair follicles2-6. Neurons also maintain a subset of messenger RNAs in a translationally silent state, which react 'on demand' to intracellular and extracellular signals. This uncoupling of general availability of mRNA from translation into protein facilitates immediate responses to environmental changes and avoids excess production of proteins, which is the most energy-consuming process within the cell. However, when post-transcriptional regulation is acquired and how protein synthesis changes along the different steps of maturation are not known. Here we show that protein synthesis undergoes highly dynamic changes when stem cells differentiate to neurons in vivo. Examination of individual transcripts using RiboTag mouse models reveals that whereas stem cells translate abundant transcripts with little discrimination, translation becomes increasingly regulated with the onset of differentiation. The generation of neurogenic progeny involves translational repression of a subset of mRNAs, including mRNAs that encode the stem cell identity factors SOX2 and PAX6, and components of the translation machinery, which are enriched in a pyrimidine-rich motif. The decrease of mTORC1 activity as stem cells exit the cell cycle selectively blocks translation of these transcripts. Our results reveal a control mechanism by which the cell cycle is coupled to post-transcriptional repression of key stem cell identity factors, thereby promoting exit from stemness.
Science advances
2022 Jun 10
Hu, Y;Jiang, Y;Behnan, J;Ribeiro, MM;Kalantzi, C;Zhang, MD;Lou, D;Häring, M;Sharma, N;Okawa, S;Del Sol, A;Adameyko, I;Svensson, M;Persson, O;Ernfors, P;
PMID: 35675414 | DOI: 10.1126/sciadv.abm6340
Neuron
2023 Apr 18
Liu, Y;Savier, EL;DePiero, VJ;Chen, C;Schwalbe, DC;Abraham-Fan, RJ;Chen, H;Campbell, JN;Cang, J;
PMID: 37086721 | DOI: 10.1016/j.neuron.2023.03.036
Cell Rep.
2019 Apr 23
Sala Frigerio C, Wolfs L, Fattorelli N, Thrupp N, Voytyuk I, Schmidt I, Mancuso R, Chen WT, Woodbury ME, Srivastava G, Möller T, Hudry E, Das S, Saido T, Karran E, Hyman B, Perry VH, Fiers M, De Strooper B.
PMID: 31018141 | DOI: 10.1016/j.celrep.2019.03.099
Gene expression profiles of more than 10,000 individual microglial cells isolated from cortex and hippocampus of male and female AppNL-G-Fmice over time demonstrate that progressive amyloid-β accumulation accelerates two main activated microglia states that are also present during normal aging. Activated response microglia (ARMs) are composed of specialized subgroups overexpressing MHC type II and putative tissue repair genes (Dkk2, Gpnmb, and Spp1) and are strongly enriched with Alzheimer's disease (AD) risk genes. Microglia from female mice progress faster in this activation trajectory. Similar activated states are also found in a second AD model and in human brain. Apoe, the major genetic risk factor for AD, regulates the ARMs but not the interferon response microglia (IRMs). Thus, the ARMs response is the converging point for aging, sex, and genetic AD risk factors.
Neuron
2022 Sep 26
Bulstrode, H;Girdler, GC;Gracia, T;Aivazidis, A;Moutsopoulos, I;Young, AMH;Hancock, J;He, X;Ridley, K;Xu, Z;Stockley, JH;Finlay, J;Hallou, C;Fajardo, T;Fountain, DM;van Dongen, S;Joannides, A;Morris, R;Mair, R;Watts, C;Santarius, T;Price, SJ;Hutchinson, PJA;Hodson, EJ;Pollard, SM;Mohorianu, I;Barker, RA;Sweeney, TR;Bayraktar, O;Gergely, F;Rowitch, DH;
PMID: 36174572 | DOI: 10.1016/j.neuron.2022.09.002
Cell reports methods
2022 Aug 22
Agnew-Svoboda, W;Ubina, T;Figueroa, Z;Wong, YC;Vizcarra, EA;Roebini, B;Wilson, EH;Fiacco, TA;Riccomagno, MM;
PMID: 36046623 | DOI: 10.1016/j.crmeth.2022.100276
Life (Basel, Switzerland)
2021 Oct 18
Paterson, C;Kilmister, EJ;Brasch, HD;Bockett, N;Patel, J;Paterson, E;Purdie, G;Galvin, S;Davis, PF;Itinteang, T;Tan, ST;
PMID: 34685477 | DOI: 10.3390/life11101106
Nature neuroscience
2021 Dec 01
Pellegrino, G;Martin, M;Allet, C;Lhomme, T;Geller, S;Franssen, D;Mansuy, V;Manfredi-Lozano, M;Coutteau-Robles, A;Delli, V;Rasika, S;Mazur, D;Loyens, A;Tena-Sempere, M;Siepmann, J;Pralong, FP;Ciofi, P;Corfas, G;Parent, AS;Ojeda, SR;Sharif, A;Prevot, V;
PMID: 34795451 | DOI: 10.1038/s41593-021-00960-z
J Cell Biol.
2017 Sep 06
Kourtidis A, Necela B, Lin WH, Lu R, Feathers RW, Asmann YW, Thompson EA, Anastasiadis PZ.
PMID: 28877994 | DOI: 10.1083/jcb.201612125
Cumulative evidence demonstrates that most RNAs exhibit specific subcellular distribution. However, the mechanisms regulating this phenomenon and its functional consequences are still under investigation. Here, we reveal that cadherin complexes at the apical zonula adherens (ZA) of epithelial adherens junctions recruit the core components of the RNA-induced silencing complex (RISC) Ago2, GW182, and PABPC1, as well as a set of 522 messenger RNAs (mRNAs) and 28 mature microRNAs (miRNAs or miRs), via PLEKHA7. Top canonical pathways represented by these mRNAs include Wnt/β-catenin, TGF-β, and stem cell signaling. We specifically demonstrate the presence and silencing of MYC, JUN, and SOX2 mRNAs by miR-24 and miR-200c at the ZA. PLEKHA7 knockdown dissociates RISC from the ZA, decreases loading of the ZA-associated mRNAs and miRNAs to Ago2, and results in a corresponding increase of MYC, JUN, and SOX2 protein expression. The present work reveals a mechanism that directly links junction integrity to the silencing of a set of mRNAs that critically affect epithelial homeostasis.
Front. Surg.
2018 Oct 26
Shivapathasundram G, Wickremesekera AC, Brasch HD, Marsh R, Tan ST, Itinteang T.
PMID: - | DOI: 10.3389/fsurg.2018.00065
Aim: The presence of cells within meningioma (MG) that express embryonic stem cell (ESC) markers has been previously reported. However, the precise location of these cells has yet to be determined.
Methods: 3,3-Diaminobenzidine (DAB) immunohistochemical (IHC) staining was performed on 11 WHO grade I MG tissue samples for the expression of the ESC markers OCT4, NANOG, SOX2, KLF4 and c-MYC. Immunofluorescence (IF) IHC staining was performed to investigate the localization of each of these ESC markers. NanoString and colorimetric in situ hybridization (CISH) mRNA expression analyses were performed on six snap-frozen MG tissue samples to confirm transcriptional activation of these proteins, respectively.
Results: DAB IHC staining demonstrated expression of OCT4, NANOG, SOX2, KLF4, and c-MYC within all 11 MG tissue samples. IF IHC staining demonstrated the expression of the ESC markers OCT4, NANOG, SOX2, KLF4, and c-MYC on both the endothelial and pericyte layers of the microvessels. NanoString and CISH mRNA analyses confirmed transcription activation of these ESC markers.
Conclusion: This novel finding of the expression of all aforementioned ESC markers in WHO grade I MG infers the presence of a putative stem cells population which may give rise to MG.
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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