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.
Am J Respir Crit Care Med.
2019 Apr 09
Savary G, Dewaeles E, Diazzi S, Buscot M, Nottet N, Fassy J, Courcot E, Henaoui IS, Lemaire J, Martis N, Van der Hauwaert C, Pons N, Magnone V, Leroy S, Hofman V, Plantier L, Lebrigand K, Paquet A, Lino Cardenas CL, Vassaux G, Hofman P, Günther A, Crestani B, Wallaert B, Rezzonico R, Brousseau T, Glowacki F, Bellusci S, Perrais M, Broly F, Barbry P, Marquette CH, Cauffiez C, Mari B, Pottier N.
PMID: 30964696 | DOI: 10.1164/rccm.201807-1237OC
Abstract
RATIONALE:
Given the paucity of effective treatments for Idiopathic Pulmonary Fibrosis (IPF), new insights into the deleterious mechanisms controlling lung fibroblast activation, the key cell type driving the fibrogenic process, are essential to develop new therapeutic strategies. Transforming growth factor β (TGF-β) is the main pro-fibrotic factor, but its inhibition is associated with severe side effects due to its pleiotropic role.
OBJECTIVES:
We hypothesized that downstream non-coding effectors of TGF-β in fibroblasts may represent new effective therapeutic targets whose modulation may be well-tolerated.
METHODS:
We investigated the whole non-coding fraction of TGF-β-stimulated lung fibroblast transcriptome to identify new genomic determinants of lung fibroblast differentiation into myofibroblast. Differential expression of the long non-coding RNA DNM3OS and its associated miRNAs was validated in a murine model of pulmonary fibrosis and in IPF tissue samples. Distinct and complementary antisense oligonucleotide-based strategies aiming at interfering with DNM3OS were used to elucidate the role of DNM3OS and its associated miRNAs in IPF pathogenesis.
MEASUREMENTS AND MAIN RESULTS:
We identified DNM3OS as a fibroblast-specific critical downstream effector of TGF-β-induced lung myofibroblast activation. Mechanistically, DNM3OS regulates this process in trans by giving rise to three distinct profibrotic mature miRNAs (i.e. miR-199a-5p/3p and miR-214-3p), which influence both SMAD and non-SMAD components of TGF-β signaling in a multifaceted way. In vivo, we showed that interfering with DNM3OS function not only prevents lung fibrosis but also improves established pulmonary fibrosis.
CONCLUSION:
Pharmacological approaches aiming at interfering with DNM3OS may represent new effective therapeutic strategies in IPF.
Osteoarthritis and Cartilage
2021 Apr 01
Zhu, L;Miotla Zarebska, J;Batchelor, V;Lin, W;Goldberg, R;Klein, J;Vincent, T;
| DOI: 10.1016/j.joca.2021.02.239
bioRxiv : the preprint server for biology
2023 Feb 04
Anderson, T;Mo, J;Gagarin, E;Sherwood, D;Blumenkrantz, M;Mao, E;Leon, G;Chen, HJ;Tseng, KC;Fabian, P;Crump, JG;Smeeton, J;
PMID: 36778403 | DOI: 10.1101/2023.02.03.527039
Vet Immunol Immunopathol.
2017 Oct 27
Rusk RA, Palmer MV, Waters WR, McGill JL.
PMID: 29129226 | DOI: 10.1016/j.vetimm.2017.10.004
Bovine γδ T cells are amongst the first cells to accumulate at the site of Mycobacterium bovis infection; however, their role in the developing lesion remains unclear. We utilized transcriptomics analysis, in situ hybridization, and a macrophage/γδ T cell co-culture system to elucidate the role of γδ T cells in local immunity to M. bovis infection. Transcriptomics analysis revealed that γδ T cells upregulated expression of several novel, immune-associated genes in response to stimulation with M. bovis antigen. BCG-infected macrophage/γδ T cell co-cultures confirmed the results of our RNAseq analysis, and revealed that γδ T cells from M. bovis-infected animals had a significant impact on bacterial viability. Analysis of γδ T cells within late-stage M. bovis granulomas revealed significant expression of IFN-γ and CCL2, but not IL-10, IL-22, or IL-17. Our results suggest γδ T cells influence local immunity to M. bovis through cytokine secretion and direct effects on bacterial burden.
Developmental cell
2022 Oct 24
Muhl, L;Mocci, G;Pietilä, R;Liu, J;He, L;Genové, G;Leptidis, S;Gustafsson, S;Buyandelger, B;Raschperger, E;Hansson, EM;Björkegren, JLM;Vanlandewijck, M;Lendahl, U;Betsholtz, C;
PMID: 36283392 | DOI: 10.1016/j.devcel.2022.09.015
Frontiers in immunology
2022 Jul 29
Tran, M; Yoon, S ;Teoh, M; Andersen, S; Lam, PY; Purdue, BW; Raghubar, A; Hanson, SJ; Devitt, K; Jones, K; Walters, S; Monkman, J; Kulasinghe, A; Tuong, ZK; Soyer, HP; Frazer, IH; Nguyen, Q
Nature.
2018 Feb 14
Vanlandewijck M, He L, Mäe MA, Andrae J, Ando K, Del Gaudio F, Nahar K, Lebouvier T, Laviña B, Gouveia L, Sun Y, Raschperger E, Räsänen M, Zarb Y, Mochizuki N, Keller A, Lendahl U, Betsholtz C.
PMID: 29443965 | DOI: 10.1038/nature25739
Cerebrovascular disease is the third most common cause of death in developed countries, but our understanding of the cells that compose the cerebral vasculature is limited. Here, using vascular single-cell transcriptomics, we provide molecular definitions for the principal types of blood vascular and vessel-associated cells in the adult mouse brain. We uncover the transcriptional basis of the gradual phenotypic change (zonation) along the arteriovenous axis and reveal unexpected cell type differences: a seamless continuum for endothelial cells versus a punctuated continuum for mural cells. We also provide insight into pericyte organotypicity and define a population of perivascular fibroblast-like cells that are present on all vessel types except capillaries. Our work illustrates the power of single-cell transcriptomics to decode the higher organizational principles of a tissue and may provide the initial chapter in a molecular encyclopaedia of the mammalian vasculature.
Developmental cell
2023 Feb 26
Goodwin, K;Lemma, B;Zhang, P;Boukind, A;Nelson, CM;
PMID: 36868232 | DOI: 10.1016/j.devcel.2023.02.002
Aging cell
2022 Nov 17
Xu, Q;Rydz, C;Nguyen Huu, VA;Rocha, L;Palomino La Torre, C;Lee, I;Cho, W;Jabari, M;Donello, J;Lyon, DC;Brooke, RT;Horvath, S;Weinreb, RN;Ju, WK;Foik, A;Skowronska-Krawczyk, D;
PMID: 36397653 | DOI: 10.1111/acel.13737
Immunity.
2018 Nov 13
Girbl T, Lenn T, Perez L, Rolas L, Barkaway A, Thiriot A, del Fresno C, Lynam E, Hub E, Thelen M, Graham G, Alon R, Sancho D, von Andrian UH, Voisin MB, Rot A, Nourshargh S.
PMID: 30446388 | DOI: 10.1016/j.immuni.2018.09.018
Neutrophils require directional cues to navigate through the complex structure of venular walls and into inflamed tissues. Here we applied confocal intravital microscopy to analyze neutrophil emigration in cytokine-stimulated mouse cremaster muscles. We identified differential and non-redundant roles for the chemokines CXCL1 and CXCL2, governed by their distinct cellular sources. CXCL1 was produced mainly by TNF-stimulated endothelial cells (ECs) and pericytes and supported luminal and sub-EC neutrophil crawling. Conversely, neutrophils were the main producers of CXCL2, and this chemokine was critical for correct breaching of endothelial junctions. This pro-migratory activity of CXCL2 depended on the atypical chemokine receptor 1 (ACKR1), which is enriched within endothelial junctions. Transmigrating neutrophils promoted a self-guided migration response through EC junctions, creating a junctional chemokine "depot" in the form of ACKR1-presented CXCL2 that enabled efficient unidirectional luminal-to-abluminal migration. Thus, CXCL1 and CXCL2 act in a sequential manner to guide neutrophils through venular walls as governed by their distinct cellular sources.
Cell reports
2022 Jul 12
Angelozzi, M;Pellegrino da Silva, R;Gonzalez, MV;Lefebvre, V;
PMID: 35830813 | DOI: 10.1016/j.celrep.2022.111045
Nature communications
2021 Sep 06
Cui, M;Atmanli, A;Morales, MG;Tan, W;Chen, K;Xiao, X;Xu, L;Liu, N;Bassel-Duby, R;Olson, EN;
PMID: 34489413 | DOI: 10.1038/s41467-021-25653-w
Description | ||
---|---|---|
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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