scholarly journals Acoustically Targeted Chemogenetics for Noninvasive Control of Neural Circuits

2018 ◽  
Author(s):  
Jerzy O. Szablowski ◽  
Brian Lue ◽  
Audrey Lee-Gosselin ◽  
Dina Malounda ◽  
Mikhail G. Shapiro

ABSTRACTNeurological and psychiatric diseases often involve the dysfunction of specific neural circuits in particular regions of the brain. Existing treatments, including drugs and implantable brain stimulators, aim to modulate the activity of these circuits, but are typically not cell type-specific, lack spatial targeting or require invasive procedures. Here, we introduce an approach to modulating neural circuits noninvasively with spatial, cell-type and temporal specificity. This approach, called acoustically targeted chemogenetics, or ATAC, uses transient ultrasonic opening of the blood brain barrier to transduce neurons at specific locations in the brain with virally-encoded engineered G-protein-coupled receptors, which subsequently respond to systemically administered bio-inert compounds to activate or inhibit the activity of these neurons. We demonstrate this concept in mice by using ATAC to noninvasively modify and subsequently activate or inhibit excitatory neurons within the hippocampus, showing that this enables pharmacological control of memory formation. This technology allows a brief, noninvasive procedure to make one or more specific brain regions capable of being selectively modulated using orally bioavailable compounds, thereby overcoming some of the key limitations of conventional brain therapies.

2007 ◽  
Vol 51 (8) ◽  
pp. 459-466 ◽  
Author(s):  
Xiangning Bu ◽  
Ping Huang ◽  
Zhifeng Qi ◽  
Nan Zhang ◽  
Song Han ◽  
...  

2019 ◽  
Author(s):  
Song-Lin Ding ◽  
Zizhen Yao ◽  
Karla E. Hirokawa ◽  
Thuc Nghi Nguyen ◽  
Lucas T. Graybuck ◽  
...  

SummarySubicular region plays important roles in spatial processing and many cognitive functions and these were mainly attributed to subiculum (Sub) rather than prosubiculum (PS). Using single-cell RNA-sequencing (scRNA-seq) technique we have identified up to 27 distinct transcriptomic clusters/cell types, which were registered to anatomical sub-domains in Sub and PS. Based on reliable molecular markers derived from transcriptomic clustering and in situ hybridization data, the precise boundaries of Sub and PS have been consistently defined along the dorsoventral (DV) axis. Using these borders to evaluate Cre-line specificity and tracer injections, we have found bona fide Sub projections topographically to structures important for spatial processing and navigation. In contrast, PS along DV axis sends its outputs to widespread brain regions crucial for motivation, emotion, reward, stress, anxiety and fear. Brain-wide cell-type specific projections of Sub and PS have also been revealed using specific Cre-lines. These results reveal two molecularly and anatomically distinct circuits centered in Sub and PS, respectively, providing a consistent explanation to historical data and a clearer foundation for future functional studies.Highlights27 transcriptomic cell types identified in and spatially registered to “subicular” regions.Anatomic borders of “subicular” regions reliably determined along dorsal-ventral axis.Distinct cell types and circuits of full-length subiculum (Sub) and prosubiculum (PS).Brain-wide cell-type specific projections of Sub and PS revealed with specific Cre-lines.In BriefDing et al. show that mouse subiculum and prosubiculum are two distinct regions with differential transcriptomic cell types, subtypes, neural circuits and functional correlation. The former has obvious topographic projections to its main targets while the latter exhibits widespread projections to many subcortical regions associated with reward, emotion, stress and motivation.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jiao Li ◽  
Jakob Seidlitz ◽  
John Suckling ◽  
Feiyang Fan ◽  
Gong-Jun Ji ◽  
...  

AbstractMajor depressive disorder (MDD) has been shown to be associated with structural abnormalities in a variety of spatially diverse brain regions. However, the correlation between brain structural changes in MDD and gene expression is unclear. Here, we examine the link between brain-wide gene expression and morphometric changes in individuals with MDD, using neuroimaging data from two independent cohorts and a publicly available transcriptomic dataset. Morphometric similarity network (MSN) analysis shows replicable cortical structural differences in individuals with MDD compared to control subjects. Using human brain gene expression data, we observe that the expression of MDD-associated genes spatially correlates with MSN differences. Analysis of cell type-specific signature genes suggests that microglia and neuronal specific transcriptional changes account for most of the observed correlation with MDD-specific MSN differences. Collectively, our findings link molecular and structural changes relevant for MDD.


Gene Therapy ◽  
2007 ◽  
Vol 14 (7) ◽  
pp. 575-583 ◽  
Author(s):  
J P Chhatwal ◽  
S E Hammack ◽  
A M Jasnow ◽  
D G Rainnie ◽  
K J Ressler

Cell ◽  
2014 ◽  
Vol 157 (5) ◽  
pp. 1216-1229 ◽  
Author(s):  
Ivo Spiegel ◽  
Alan R. Mardinly ◽  
Harrison W. Gabel ◽  
Jeremy E. Bazinet ◽  
Cameron H. Couch ◽  
...  

Neurogenesis ◽  
2015 ◽  
Vol 2 (1) ◽  
pp. e1122699 ◽  
Author(s):  
Joshua Shing Shun Li ◽  
Grace Ji-eun Shin ◽  
S Sean Millard

2019 ◽  
Vol 36 (3) ◽  
pp. 782-788 ◽  
Author(s):  
Jiebiao Wang ◽  
Bernie Devlin ◽  
Kathryn Roeder

Abstract Motivation Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects. Results Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). Availability and implementation We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. Supplementary information Supplementary data are available at Bioinformatics online.


Immunity ◽  
2019 ◽  
Vol 50 (2) ◽  
pp. 317-333.e6 ◽  
Author(s):  
Xiaoyu Liu ◽  
Daniel P. Nemeth ◽  
Daniel B. McKim ◽  
Ling Zhu ◽  
Damon J. DiSabato ◽  
...  

2012 ◽  
Vol 23 (4) ◽  
pp. 242-254 ◽  
Author(s):  
Aurélie Delzor ◽  
Noelle Dufour ◽  
Fanny Petit ◽  
Martine Guillermier ◽  
Diane Houitte ◽  
...  

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