Genetically encoded fluorescent sensors for studying healthy and diseased nervous systems

Lin Tian, Loren L. Looger

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Neurons and glia are functionally organized into circuits and higher order structures via synaptic connectivity, well-orchestrated molecular signaling and activity-dependent refinement. Such organization allows the precise information processing required for complex behaviors. Disruption of nervous systems by genetic deficiency or events such as trauma or environmental exposure can produce a diseased state in which certain aspects of inter-neuron signaling are impaired. Optical imaging techniques allow the direct visualization of individual neurons in a circuit environment. Imaging probes specific for given biomolecules might help elucidate their contribution to proper circuit function. Genetically encoded sensors can visualize trafficking of particular molecules in defined neuronal populations, non-invasively in intact brain or reduced preparations. Sensor analysis in healthy and diseased brains might reveal important differences and shed light on the development and progression of nervous system disorders. We review the field of genetically encoded sensors for molecules and cellular events and their potential applicability to the study of nervous system disease.

Original languageEnglish (US)
Pages (from-to)27-35
Number of pages9
JournalDrug Discovery Today: Disease Models
Volume5
Issue number1
DOIs
StatePublished - Mar 2008
Externally publishedYes

Fingerprint

Nervous System Diseases
Neurons
Optical Imaging
Environmental Exposure
Brain Diseases
Automatic Data Processing
Neuroglia
Nervous System
Wounds and Injuries
Brain
Population

ASJC Scopus subject areas

  • Drug Discovery
  • Molecular Medicine

Cite this

Genetically encoded fluorescent sensors for studying healthy and diseased nervous systems. / Tian, Lin; Looger, Loren L.

In: Drug Discovery Today: Disease Models, Vol. 5, No. 1, 03.2008, p. 27-35.

Research output: Contribution to journalArticle

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