mitology: a new tool to dissect mitochondrial activity from transcriptome

mitology: a new tool to dissect mitochondrial activity from transcriptome


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

Affiliation(s): Biology Department, University of Padova



Mitochondria are a main control center for metabolism and OXPHOS. As a consequence, the phenotypic manifestations of an impaired mitochondrial function may be highly heterogeneous. Therefore, an analysis of high-throughput trascriptomic data from a disease condition may show heavy alterations in the mitochondrial activity. Further, with the new technologies of single-cell and spatial transcriptomics it is now possible to explore the mitochondrial alterations and dissect its heterogeneity at a single-cell resolution. With the aim to provide a tool able to explore mitochondrial activity in different types of trascriptomic profiles, we developed the mitology R package. To achieve our goal, a list of 3328 genes was obtained collecting mitochondrial related genes from mitochondrial-specific databases (MitoCarta, IMPI and MSeqDR) and from Gene Ontology database (genes annotated in terms including “mitochondri-” in the description). Then, from the Reactome pathway database and from the Gene Ontology database, pathways and terms enriched in our list were selected and reorganized in categories used to determine mitochondrial processes associated with well-defined gene sets. Leveraging these categories, we can now dissect mitochondrial processes at different specificity levels: going from most strict mitochondrial-specific databases to broader pathway and Gene Ontology databases. Our tool uses this information to perform a single-transcriptome analysis from gene expression input of samples, cells or spots. Here, we provide a new tool that can effectively help in inspecting and dissecting mitochondrial activity. It represents a strong instrument for mitochondrial studies and their impact in disease onset and progression as high-throughput genomic datasets can now be studied from the mitochondrial point of view and provide a powerful contribution in clinical studies.