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DOI 10.3791/66955

Медицинская библиотека · Journal of visualized experiments : JoVE · 2024

Optimizing Tear Collection in Mice for mRNA and Protein Analysis.

Bello Marysol, Morales-Farfán Andrea, Martínez-Colín Erick J, Lezama Ivonne, Lamas Monica

СтатьяVideo-Audio MediaПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

The tear film is a highly dynamic biofluid capable of reflecting pathology-associated molecular changes, not only in the ocular surface but also in other tissues and organs. Molecular analysis of this biofluid offers a non-invasive way to diagnose or monitor diseases, assess medical treatment efficacy, and identify possible biomarkers. Due to the limited sample volume, collecting tear samples requires specific skills and appropriate tools to ensure high quality and maximum efficiency. Various tear sampling methodologies have been described in human studies. In this article, a comprehensive description of an optimized protocol is presented, specifically tailored for extracting tear-related protein information from experimental animal models, especially mice. This method includes the pharmacological stimulation of tear production in 2-month-old mice, followed by sample collection using Schirmer strips and the evaluation of the efficacy and efficiency of the protocol through standard procedures, SDS-PAGE, qPCR, and digital PCR (dPCR). This protocol can be easily adapted for the investigation of the tear protein signature in a variety of experimental paradigms. By establishing an affordable, standardized, and optimized tear sampling protocol for animal models, the aim was to bridge the gap between human and animal research, facilitating translational studies and accelerating advancements in the field of ocular and systemic disease research.

Для цитирования: Bello Marysol, Morales-Farfán Andrea, Martínez-Colín Erick J, Lezama Ivonne, Lamas Monica. Optimizing Tear Collection in Mice for mRNA and Protein Analysis.. Journal of visualized experiments : JoVE. 2024. DOI: 10.3791/66955.

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