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Adv Exp Med Biol. 2018;1090:211-233. doi: 10.1007/978-981-13-1286-1_12.

Current Genetic Techniques in Neural Circuit Control of Feeding and Energy Metabolism.

Wu Q1,2, Han Y3, Tong Q4.

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Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
Children's Nutrition Research Center, Research Service of Department of Agriculture of USA, Houston, TX, USA.
Department of Pediatrics, Baylor College of Medicine, USDA-ARS, Houston, TX, USA.
Center for Metabolic and Degenerative Diseases, Brown Foundation Institute of Molecular Medicine, University of Texas McGovern Medical School, Houston, TX, USA.


The current epidemic of obesity and its associated metabolic syndromes imposes unprecedented challenges to our society. Despite intensive research focus on obesity pathogenesis, an effective therapeutic strategy to treat and cure obesity is still lacking. The obesity development is due to a disturbed homeostatic control of feeding and energy expenditure, both of which are controlled by an intricate neural network in the brain. Given the inherent complexity of brain networks in controlling feeding and energy expenditure, the understanding of brain-based pathophysiology for obesity development is limited. One key limiting factor in dissecting neural pathways for feeding and energy expenditure is unavailability of techniques that can be used to effectively reduce the complexity of the brain network to a tractable paradigm, based on which a strong hypothesis can be tested. Excitingly, emerging techniques have been involved to be able to link specific groups of neurons and neural pathways to behaviors (i.e., feeding and energy expenditure). In this chapter, novel techniques especially those based on animal models and viral vector approaches will be discussed. We hope that this chapter will provide readers with a basis that can help to understand the literatures using these techniques and with a guide to apply these exciting techniques to investigate brain mechanisms underlying feeding and energy expenditure.


Body weight; Chemogenetics; Energy balance; Genome editing; Inducible and conditional gene targeting; Neural circuit mapping; Optogenetics

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