Uncovering mitochondrial activity by transcriptome data with mitology

Uncovering mitochondrial activity by transcriptome data with mitology


Author(s): Stefania Pirrotta,Laura Masatti,Paolo Martini,Massimo Bonora,Enrica Calura

Affiliation(s): Biology Department, University of Padova



Mitochondria are dynamic organelles that play crucial roles in energy transformation, biosynthesis, and cellular signaling. They actively process biological information, detecting and reacting to both internal and external stimuli. Through intricate physical interactions and diffusion mechanisms within cellular networks, mitochondria integrate diverse inputs and generate signals that finely adjust cellular functions and overall physiology. As a result, the phenotypic expressions of impaired mitochondrial function can exhibit high variability. High-throughput transcriptomic data can capture these changes, but traditional pathway analyses performed on common databases often struggle to specifically detect mitochondrial alterations. This is primarily due to the size of pathways, where the mitochondrial component is typically a small portion of the examined signaling network. To allow a specific exploration of mitochondrial activity through transcriptomic profiles, we developed the mitology R package. We started with a collection of genes whose proteins localize in to the mitochondria, derived from specialized databases like MitoCarta, IMPI, MSeqDR, and from the Gene Ontology database (genes annotated with terms related to 'mitochondri-' in their description). Then, exploiting the mitochondrial gene list, mitology provides ready-to-use implementations of MitoCarta pathways and also a reorganization of general pathway databases, like Reactome and Gene Ontology, with a specific focus on the pathways related to mitochondria activity. Finally, mitology utilizes these mitochondria-focused pathways to conduct mitochondrial pathway analyses, enabling single-sample assessments. Furthermore, we extended the functionality of our package to accommodate classical gene expression data, as well as the newest technics of single-cell and spatial transcriptomic. Mitology emerges as a novel R package adept at dissecting and unraveling mitochondrial activity, serving as an instrument for conducting targeted mitochondrial studies.