A multidimensional coding architecture of the vagal interoceptive system.
A multidimensional coding architecture of the vagal interoceptive system.
复制标题
DOI:
10.1038/s41586-022-04515-5
复制
发表时间:
2022-03
期刊:
影响因子:
64.8
通讯作者:
Chang RB
中科院分区:
文献类型:
--
作者:
Zhao Q;Yu CD;Wang R;Xu QJ;Dai Pra R;Zhang L;Chang RB
Interoception, the ability to timely and precisely sense changes inside the body, is critical for survival. 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 layers. 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. Single-cell profiling of vagal sensory neurons from seven organs in mice and calcium-imaging-guided spatial transcriptomics reveal that interoceptive signals are coded through three distinct dimensions, allowing efficient processing of multiple signals in parallel using a combinatorial strategy.
登录
查看更多内容
影响因子:
14.9
作者:
Gene Ontology Consortium
通讯作者:
Gene Ontology Consortium
影响因子:
16.6
作者:
Angelidis, Ilias;Simon, Lukas M.;Schiller, Herbert B.
通讯作者:
Schiller, Herbert B.
影响因子:
9.9
作者:
Cutsforth-Gregory, Jeremy K.;Benarroch, Eduardo E.
通讯作者:
Benarroch, Eduardo E.
DOI:
10.1073/pnas.1804938115
发表时间:
2018-08-07
影响因子:
11.1
作者:
Alcaino C;Knutson KR;Treichel AJ;Yildiz G;Strege PR;Linden DR;Li JH;Leiter AB;Szurszewski JH;Farrugia G;Beyder A
通讯作者:
Beyder A
影响因子:
64.5
作者:
Chang RB;Strochlic DE;Williams EK;Umans BD;Liberles SD
通讯作者:
Liberles SD