Thyrotropin-releasing hormone induces Ca2+ increase in a subset of vagal nodose ganglion neurons

Neuropeptides

2022 Jun 03

Mamedova, E;Dmytriyeva, O;Rekling, JC;
PMID: 35704969 | DOI: 10.1016/j.npep.2022.102261

Thyrotropin-releasing hormone (TRH) plays a central role in metabolic homeostasis, and single-cell sequencing has recently demonstrated that vagal sensory neurons in the nodose ganglion express thyrotropin-releasing hormone receptor 1 (TRHR1). Here, in situ hybridization validated the presence of TRHR1 in nodose ganglion (NG) neurons and immunohistochemistry showed that the receptor is expressed at the protein level. However, it has yet to be demonstrated whether TRHR1 is functionally active in NG neurons. Using NG explants transduced with a genetically encoded Ca2+ indicator (GECI), we show that TRH increases Ca2+ in a subset of NG neurons. TRH-induced Ca2+ transients were briefer compared to those induced by CCK-8, 2-Me-5-HT and ATP. Blocking Na+ channels with TTX or Na+ substitution did not affect the TRH-induced Ca2+ increase, but blocking Gq signaling with YM-254890 abolished the TRH-induced response. Field potential recordings from the vagus nerve in vitro showed an increase in response to TRH, suggesting that TRH signaling produces action potentials in NG neurons. These observations indicate that TRH activates a small group of NG neurons, involving Gq pathways, and we hypothesize that these neurons may play a role in gut-brain signaling.

Profiling of G Protein-Coupled Receptors in Vagal Afferents Reveals Novel Gut-to-Brain Sensing Mechanisms

Molecular Metabolism

2018 Apr 03

Egerod KL, Petersen N ,Timshel PN, Rekling JC, Wang Y, Liu Q, Schwartz TW, Gautron L.
PMID: - | DOI: 10.1016/j.molmet.2018.03.016

Abstract

Objectives

G protein-coupled receptors (GPCRs) act as transmembrane molecular sensors of neurotransmitters, hormones, nutrients, and metabolites. Because unmyelinated vagalafferents richly innervate the gastrointestinal mucosa, gut-derived molecules may directly modulate the activity of vagal afferents through GPCRs. However, the types of GPCRs expressed in vagal afferents are largely unknown. Here, we determined the expression profile of all GPCRs expressed in vagal afferents of the mouse, with a special emphasis on those innervating the gastrointestinal tract.

Methods

Using a combination of high-throughput quantitative PCR, RNA sequencing, and in situhybridization, we systematically quantified GPCRs expressed in vagal unmyelinated Nav1.8-expressing afferents.

Results

GPCRs for gut hormones that were the most enriched in Nav1.8-expressing vagal unmyelinated afferents included NTSR1, NPY2R, CCK1R, and to a lesser extent, GLP1R, but not GHSR and GIPR. Interestingly, both GLP1R and NPY2R were coexpressed with CCK1R. In contrast, NTSR1 was coexpressed with GPR65, a marker preferentially enriched in intestinal mucosal afferents. Only few microbiome-derived metabolite sensors such as GPR35 and, to a lesser extent, GPR119 and CaSR were identified in the Nav1.8-expressing vagal afferents. GPCRs involved in lipid sensing and inflammation (e.g. CB1R, CYSLTR2, PTGER4), and neurotransmitters signaling (CHRM4, DRD2, CRHR2) were also highly enriched in Nav1.8-expressing neurons. Finally, we identified 21 orphan GPCRs with unknown functions in vagal afferents.

Conclusion

Overall, this study provides a comprehensive description of GPCR-dependent sensing mechanisms in vagal afferents, including novel coexpression patterns, and conceivably coaction of key receptors for gut-derived molecules involved in gut-brain communication.

SCAMPR, a single-cell automated multiplex pipeline for RNA quantification and spatial mapping

Cell reports methods

2022 Oct 24

Ali Marandi Ghoddousi, R;Magalong, VM;Kamitakahara, AK;Levitt, P;
PMID: 36313803 | DOI: 10.1016/j.crmeth.2022.100316

Spatial gene expression, achieved classically through in situ hybridization, is a fundamental tool for topographic phenotyping of cell types in the nervous system. Newly developed techniques allow for visualization of multiple mRNAs at single-cell resolution and greatly expand the ability to link gene expression to tissue topography, yet there are challenges in efficient quantification and analysis of these high-dimensional datasets. We have therefore developed the single-cell automated multiplex pipeline for RNA (SCAMPR), facilitating rapid and accurate segmentation of neuronal cell bodies using a dual immunohistochemistry-RNAscope protocol and quantification of low- and high-abundance mRNA signals using open-source image processing and automated segmentation tools. Proof of principle using SCAMPR focused on spatial mapping of gene expression by peripheral (vagal nodose) and central (visual cortex) neurons. The analytical effectiveness of SCAMPR is demonstrated by identifying the impact of early life stress on gene expression in vagal neuron subtypes.

A multidimensional coding architecture of the vagal interoceptive system

Nature

2022 Mar 01

Zhao, Q;Yu, CD;Wang, R;Xu, QJ;Dai Pra, R;Zhang, L;Chang, RB;
PMID: 35296859 | DOI: 10.3760/cma.j.cn112151-20210719-00516

Interoception, the ability to timely and precisely sense changes inside the body, is critical for survival1-4. Vagal sensory neurons (VSNs) form an important body-to-brain connection, navigating visceral organs along the rostral-caudal axis of the body and crossing the surface-lumen axis of organs into appropriate tissue layers5,6. The brain can discriminate numerous body signals through VSNs, but the underlying coding strategy remains poorly understood. Here we show that VSNs code visceral organ, tissue layer and stimulus modality-three key features of an interoceptive signal-in different dimensions. Large-scale single-cell profiling of VSNs from seven major organs in mice using multiplexed projection barcodes reveals a 'visceral organ' dimension composed of differentially expressed gene modules that code organs along the body's rostral-caudal axis. We discover another 'tissue layer' dimension with gene modules that code the locations of VSN endings along the surface-lumen axis of organs. Using calcium-imaging-guided spatial transcriptomics, we show that VSNs are organized into functional units to sense similar stimuli across organs and tissue layers; this constitutes a third 'stimulus modality' dimension. The three independent feature-coding dimensions together specify many parallel VSN pathways in a combinatorial manner and facilitate the complex projection of VSNs in the brainstem. Our study highlights a multidimensional coding architecture of the mammalian vagal interoceptive system for effective signal communication.

Gut-brain communication by distinct sensory neurons differently controls feeding and glucose metabolism

Cell metabolism

2021 May 21

Borgmann, D;Ciglieri, E;Biglari, N;Brandt, C;Cremer, AL;Backes, H;Tittgemeyer, M;Wunderlich, FT;Brüning, JC;Fenselau, H;
PMID: 34043943 | DOI: 10.1016/j.cmet.2021.05.002

Sensory neurons relay gut-derived signals to the brain, yet the molecular and functional organization of distinct populations remains unclear. Here, we employed intersectional genetic manipulations to probe the feeding and glucoregulatory function of distinct sensory neurons. We reconstruct the gut innervation patterns of numerous molecularly defined vagal and spinal afferents and identify their downstream brain targets. Bidirectional chemogenetic manipulations, coupled with behavioral and circuit mapping analysis, demonstrated that gut-innervating, glucagon-like peptide 1 receptor (GLP1R)-expressing vagal afferents relay anorexigenic signals to parabrachial nucleus neurons that control meal termination. Moreover, GLP1R vagal afferent activation improves glucose tolerance, and their inhibition elevates blood glucose levels independent of food intake. In contrast, gut-innervating, GPR65-expressing vagal afferent stimulation increases hepatic glucose production and activates parabrachial neurons that control normoglycemia, but they are dispensable for feeding regulation. Thus, distinct gut-innervating sensory neurons differentially control feeding and glucoregulatory neurocircuits and may provide specific targets for metabolic control.

	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

Search form

Probes for INS

Content for comparison

Gene

Product

Research area

Category

Advanced Cell Diagnostics

Bio-Techne

Advanced Cell Diagnostics China