ABSTRACT
Melatonin synthesis by extrapineal sources adjusts physiological and pathophysiological processes in several types of cells and tissues. As measuring locally produced melatonin in fresh tissues might be a challenge due to limited material availability, we created a simple predictive model, the MEL-Index, which infers the content of tissue melatonin using gene expression data. The MEL-Index can be a powerful tool to study the role of melatonin in different contexts. Applying the MEL-Index method to RNA-seq datasets, we have shed light into the clinical relevance of melatonin as a modulator tumor progression and lung infection due to COVID-19. The MEL-Index combines the z-normalized expressions of ASMT (Acetylserotonin O-Methyltransferase), last enzyme of the biosynthetic pathway, and CYP1B1 (cytochrome P450 family enzyme), which encodes the enzyme that metabolizes melatonin in extrahepatic tissues. In this chapter, we describe the steps for calculating the MEL-Index.