scholarly journals Whole-Brain Imaging with Single-Cell Resolution Using Chemical Cocktails and Computational Analysis

Cell ◽  
2014 ◽  
Vol 157 (3) ◽  
pp. 726-739 ◽  
Author(s):  
Etsuo A. Susaki ◽  
Kazuki Tainaka ◽  
Dimitri Perrin ◽  
Fumiaki Kishino ◽  
Takehiro Tawara ◽  
...  
2018 ◽  
Author(s):  
Adam Kimbrough ◽  
Daniel J. Lurie ◽  
Andres Collazo ◽  
Max Kreifeldt ◽  
Harpreet Sidhu ◽  
...  

SummaryThree main theories of the neurobiology of addiction have been proposed: (1) incentive salience mediated by a brainstem-striatal network, (2) habit mediated by a cortico-striato-thalamic network, and (3) hedonic allostasis mediated by an extended amygdala network. Efforts have been made to reconcile these theories within a three-stage model, but the relevance of each theory remains controversial. We tested the validity of each theory with a single dataset using unbiased single-cell whole-brain imaging and data-driven analyses of neuronal activity in a mouse model of alcohol use disorder. Abstinence in alcohol dependent mice decreased brain modularity and resulted in clustering of brain regions that correspond to each stage of the three-stage theory of addiction. Furthermore, we identified several brain regions whose activity highly predicted addiction-like behaviors and “hub” regions that may drive neural activation during abstinence. These results validate the three-stage theory of addiction and identify potential target regions for future study.


eNeuro ◽  
2021 ◽  
pp. ENEURO.0208-19.2021
Author(s):  
Adam Kimbrough ◽  
Marsida Kallupi ◽  
Lauren C. Smith ◽  
Sierra Simpson ◽  
Andres Collazo ◽  
...  

2019 ◽  
Author(s):  
Adam Kimbrough ◽  
Lauren C. Smith ◽  
Marsida Kallupi ◽  
Sierra Simpson ◽  
Andres Collazo ◽  
...  

AbstractNumerous brain regions have been identified as contributing to addiction-like behaviors, but unclear is the way in which these brain regions as a whole lead to addiction. The search for a final common brain pathway that is involved in addiction remains elusive. To address this question, we used male C57BL/6J mice and performed single-cell whole-brain imaging of neural activity during withdrawal from cocaine, methamphetamine, and nicotine. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical- to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway that leads to addiction.Significance StatementA key aspect of treating drug abuse is understanding similarities and differences of how drugs of abuse affect the brain. In the present study we examined how the brain is altered during withdrawal from psychostimulants. We found that each drug produced a unique pattern of activity in the brain, but that brains in withdrawal from cocaine and methamphetamine shared similar features. Interestingly, we found the major common link between withdrawal from all psychostimulants, when compared to controls, was a shift in the broad organization of the brain in the form of reduced modularity. Reduced modularity has been shown in several brain disorders, including traumatic brain injury, and dementia, and may be the common link between drugs of abuse.


Cell Reports ◽  
2021 ◽  
Vol 34 (5) ◽  
pp. 108709
Author(s):  
Xiaojun Wang ◽  
Hanqing Xiong ◽  
Yurong Liu ◽  
Tao Yang ◽  
Anan Li ◽  
...  

Author(s):  
Yu Zhao ◽  
Ulf Panzer ◽  
Stefan Bonn ◽  
Christian F. Krebs

AbstractSingle-cell biology is transforming the ability of researchers to understand cellular signaling and identity across medical and biological disciplines. Especially for immune-mediated diseases, a single-cell look at immune cell subtypes, signaling, and activity might yield fundamental insights into the disease etiology, mechanisms, and potential therapeutic interventions. In this review, we highlight recent advances in the field of single-cell RNA profiling and their application to understand renal function in health and disease. With a focus on the immune system, in particular on T cells, we propose some key directions of understanding renal inflammation using single-cell approaches. We detail the benefits and shortcomings of the various technological approaches outlined and give advice on potential pitfalls and challenges in experimental setup and computational analysis. Finally, we conclude with a brief outlook into a promising future for single-cell technologies to elucidate kidney function.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shengquan Chen ◽  
Guanao Yan ◽  
Wenyu Zhang ◽  
Jinzhao Li ◽  
Rui Jiang ◽  
...  

AbstractThe recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approaches, which utilize the information in existing datasets, may facilitate the analysis of scCAS data. Here, we present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Accessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models (1) the shared biological variation among scCAS data and the reference data, and (2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance when used on several scCAS datasets, and on references constructed using various approaches. Altogether, these analyses demonstrate the wide applicability of RA3 in analyzing scCAS data.


2018 ◽  
Vol 527 (13) ◽  
pp. 2122-2145 ◽  
Author(s):  
Jennifer D. Whitesell ◽  
Alex R. Buckley ◽  
Joseph E. Knox ◽  
Leonard Kuan ◽  
Nile Graddis ◽  
...  

2012 ◽  
Vol 107 (10) ◽  
pp. 2853-2865 ◽  
Author(s):  
Ji-Wei He ◽  
Fenghua Tian ◽  
Hanli Liu ◽  
Yuan Bo Peng

While near-infrared (NIR) spectroscopy has been increasingly used to detect stimulated brain activities with an advantage of dissociating regional oxy- and deoxyhemoglobin concentrations simultaneously, it has not been utilized much in pain research. Here, we investigated and demonstrated the feasibility of using this technique to obtain whole brain hemodynamics in rats and speculated on the functional relevance of the NIR-based hemodynamic signals during pain processing. NIR signals were emitted and collected using a 26-optodes array on rat's dorsal skull surface after the removal of skin. Following the subcutaneous injection of formalin (50 μl, 3%) into a hindpaw, several isolable brain regions showed hemodynamic changes, including the anterior cingulate cortex, primary/secondary somatosensory cortexes, thalamus, and periaqueductal gray ( n = 6). Time courses of hemodynamic changes in respective regions matched with the well-documented biphasic excitatory response. Surprisingly, an atypical pattern (i.e., a decrease in oxyhemoglobin concentration with a concomitant increase in deoxyhemoglobin concentration) was seen in phase II. In a separate group of rats with innocuous brush and noxious pinch of the same area ( n = 11), results confirmed that the atypical pattern occurred more likely in the presence of nociception than nonpainful stimulation, suggesting it as a physiological substrate when the brain processes pain. In conclusion, the NIR whole brain imaging provides a useful alternative to study pain in vivo using small-animal models. Our results support the notion that neurovascular response patterns depend on stimuli, bringing attention to the interpretation of vascular-based neuroimaging data in studies of pain.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Xiuwei Zhang ◽  
Nir Yosef

A combination of single-cell techniques and computational analysis enables the simultaneous discovery of cell states, lineage relationships and the genes that control developmental decisions.


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