Neuroinflammation plays a central role in neurodegenerative diseases and involves a large number of interactions between different brain cell types. Unraveling the complexity of cell-cell interaction in neuroinflammation is crucial for both clarifying the molecular mechanisms involved and increasing efficacy in drug development. Here, we provide a versatile analytical method for specifically addressing cell-to-cell communication, using primary brain cells, a microfluidic device, and a multiparametric readout approach. Different cell types are plated in separate chambers of a microfluidic network so that culturing conditions can be independently controlled and single cell types can be selectively primed with different stimuli. When chambers are microfluidically connected, the specific contribution of each cell type can be finely monitored by analyzing morphology, vitality, calcium dynamics, and electrophysiology parameters. We exemplify this approach by examining the role of astrocytes derived from two different brain regions (cortex and hippocampus) on neuronal viability in two types of neuroinflammatory insults, namely, metabolic stress and exposure to amyloid β fibrils, and demonstrate regional differences in glial control of neuronal physiopathology. In particular, we show that during metabolic stress, cortical but not hippocampal astrocytes play a neuroprotective role; also, in an exacerbated inflammatory scenario consisting in the exposure to Aβ + IL-1β, hippocampal but not cortical astrocytes play a detrimental role on neurons. Aside from bringing novel insights into the glial role in neuroinflammation, the method presented here represents a promising tool for addressing a wide range of biological and biochemical phenomena, characterized by a complex interaction of multiple cell types.

Overflow microfluidic networks : application to the biochemical analysis of brain cell interactions in complex neuroinflammatory scenarios

Matteoli M
2012-01-01

Abstract

Neuroinflammation plays a central role in neurodegenerative diseases and involves a large number of interactions between different brain cell types. Unraveling the complexity of cell-cell interaction in neuroinflammation is crucial for both clarifying the molecular mechanisms involved and increasing efficacy in drug development. Here, we provide a versatile analytical method for specifically addressing cell-to-cell communication, using primary brain cells, a microfluidic device, and a multiparametric readout approach. Different cell types are plated in separate chambers of a microfluidic network so that culturing conditions can be independently controlled and single cell types can be selectively primed with different stimuli. When chambers are microfluidically connected, the specific contribution of each cell type can be finely monitored by analyzing morphology, vitality, calcium dynamics, and electrophysiology parameters. We exemplify this approach by examining the role of astrocytes derived from two different brain regions (cortex and hippocampus) on neuronal viability in two types of neuroinflammatory insults, namely, metabolic stress and exposure to amyloid β fibrils, and demonstrate regional differences in glial control of neuronal physiopathology. In particular, we show that during metabolic stress, cortical but not hippocampal astrocytes play a neuroprotective role; also, in an exacerbated inflammatory scenario consisting in the exposure to Aβ + IL-1β, hippocampal but not cortical astrocytes play a detrimental role on neurons. Aside from bringing novel insights into the glial role in neuroinflammation, the method presented here represents a promising tool for addressing a wide range of biological and biochemical phenomena, characterized by a complex interaction of multiple cell types.
2012
Amyloid beta-peptides; animals; astrocytes; brain; brain ischemia; cell survival; cerebral cortex; hippocampus; inflammation; microfluidic analytical techniques; neurons; peptide fragments; protein multimerization; protein structure; secondary; rats; cell communication; analytical chemistry
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11699/1724
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