Imaging biomarkers of inflammation in situ with functionalized quantum dots in the dextran sodium sulfate (DSS) model of mouse colitis

• Published in: Inflammation research Vol. 56; no. 12; p. 502
• Main Authors: Karwa, A, Papazoglou, E, Pourrezaei, K, Tyagi, S, Murthy, S
• Format: Journal Article
• Language: English
• Published: Switzerland 01.12.2007
• Subjects: Animals; Biomarkers - metabolism; Colitis - chemically induced; Colitis - metabolism; Colitis - pathology; Dextran Sulfate; Female; Inflammation - metabolism; Interleukin-1alpha - metabolism; Mice; Peroxidase - metabolism; Quantum Dots; Tumor Necrosis Factor-alpha - metabolism
• ISSN: 1023-3830
• DOI: 10.1007/s00011-007-7046-x

Myeloperoxidase (MPO) and proinflammatory cytokines play an important role in the development of inflammation. These markers are generally measured using tedious ELISA procedures. In this study, a novel technique utilizing antibody conjugated quantum dot nanoparticles was developed to detect Myeloperoxidase, Interleukin-1alpha (IL-1alpha) and Tumor Necrosis Factor-alpha (TNF-alpha) in vivo in the dextran sodium sulfate (DSS) model of experimental colitis. Colitis was induced in animals (n = 8 animals/group) by feeding 4% DSS solution ad libitum for seven to eight days. Quantum Dots (QDs) exhibiting fluorescence at various wavelengths were conjugated to MPO, IL-1alpha and TNF-alpha polyclonal antibodies and tested in vivo at various stages of colitis. Tissue sections obtained were imaged with confocal microscope. The image intensity obtained from the tissue specimen was correlated with clinical activity measured as Disease Activity Index (DAI). Myeloperoxidase, IL-1alpha and TNF-alpha were visualized with quantum dots on various days of disease. The intensity of quantum dots increased with the increase in inflammation. The increase in intensity showed an excellent correlation with the DAI based on the clinical parameters. The study demonstrated that multiple biomarkers can be detected simultaneously and their quantitative expression correlated well with clinical disease severity. This novel technology should facilitate design of a novel optical platform for imaging various biomarkers of inflammation, early detection of acute and chronic disease markers and inflammation-mediated cancer markers. This detection may also facilitate determination of therapeutic success.