In vivo imaging in mice reveals local cell dynamics and inflammation in obese adipose tissue
Satoshi Nishimura, … , Ryozo Nagai, Seiryo Sugiura
Satoshi Nishimura, … , Ryozo Nagai, Seiryo Sugiura
Published February 1, 2008; First published January 17, 2008
Citation Information: J Clin Invest. 2008;118(2):710-721. https://doi.org/10.1172/JCI33328.
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Categories: Research Article Metabolism

In vivo imaging in mice reveals local cell dynamics and inflammation in obese adipose tissue

Abstract

To assess physiological and pathophysiological events that involve dynamic interplay between multiple cell types, real-time, in vivo analysis is necessary. We developed a technique based on confocal laser microscopy that enabled us to analyze and compare the 3-dimensional structures, cellular dynamics, and vascular function within mouse lean and obese adipose tissue in vivo with high spatiotemporal resolution. We found increased leukocyte-EC-platelet interaction in the microcirculation of obese visceral adipose tissue in ob/ob and high-fat diet–induced obese mice. These changes were indicative of activation of the leukocyte adhesion cascade, a hallmark of inflammation. Local platelet activation in obese adipose tissue was indicated by increased P-selectin expression and formation of monocyte-platelet conjugates. We observed upregulated expression of adhesion molecules on macrophages and ECs in obese visceral adipose tissue, suggesting that interactions between these cells contribute to local activation of inflammatory processes. Furthermore, administration of anti–ICAM-1 antibody normalized the cell dynamics seen in obese visceral fat. This imaging technique to analyze the complex cellular interplay within obese adipose tissue allowed us to show that visceral adipose tissue obesity is an inflammatory disease. In addition, this technique may prove to be a valuable tool to evaluate potential therapeutic interventions.

Authors

Satoshi Nishimura, Ichiro Manabe, Mika Nagasaki, Kinya Seo, Hiroshi Yamashita, Yumiko Hosoya, Mitsuru Ohsugi, Kazuyuki Tobe, Takashi Kadowaki, Ryozo Nagai, Seiryo Sugiura

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