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Updated: Aug 27, 2025
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Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
Published on: November 11, 2016
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MEL-Index: Estimation of Tissue Melatonin Levels Using Gene Expression Data.
Pedro Augusto C M Fernandes1, Regina P Markus2, Gabriela Sarti Kinker3
1DDark Lab, Department of Physiology, Biosciences Institute, University of São Paulo, São Paulo, Brazil. pacmf@usp.br.
Methods in Molecular Biology (Clifton, N.J.)
|September 30, 2022
Summary
We developed the MEL-Index, a predictive model using gene expression to estimate tissue melatonin levels. This tool helps study melatonin
Area of Science:
- Biochemistry
- Molecular Biology
- Physiology
Background:
- Extrapineal melatonin synthesis influences physiological and pathophysiological processes.
- Direct measurement of local melatonin in tissues is challenging due to limited sample availability.
Purpose of the Study:
- To develop a predictive model, the MEL-Index, for estimating tissue melatonin content using gene expression data.
- To enable the study of melatonin's role in various biological contexts, including disease.
Main Methods:
- The MEL-Index combines z-normalized gene expression data for ASMT (Acetylserotonin O-Methyltransferase) and CYP1B1 (cytochrome P450 family enzyme).
- Gene expression data from RNA-seq datasets were analyzed to infer melatonin levels.
Main Results:
- The MEL-Index provides a method to infer tissue melatonin content from gene expression.
- Application of the MEL-Index to RNA-seq data revealed melatonin's role in modulating tumor progression and COVID-19 related lung infections.
Conclusions:
- The MEL-Index is a valuable tool for assessing tissue melatonin levels when direct measurement is not feasible.
- This model offers insights into the clinical significance of melatonin in diseases such as cancer and viral infections.
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