PlasmoRhythm: A comprehensive database for malaria-associated rhythmic transcripts, proteins, and metabolites

Abstract

Abstract: Motivation: The malaria transmission cycle is temporally organized across three interacting biological systems: the parasite, vertebrate host, and mosquito vector. Rhythms in parasite development, host physiology, and vector behavior govern infection dynamics, transmission, and the efficacy of stage-specific antimalarial interventions. However, the molecular architecture connecting these rhythms remains difficult to interrogate because time-resolved omics datasets are distributed across species, experimental paradigms, and analytical frameworks, with no unified resource for comparative analysis. Results: We developed PlasmoRhythm, a curated database integrating 67 transcriptomic, proteomic, and metabolomic datasets from 15 studies, encompassing 1,126 sampling events across Plasmodium species, mammalian hosts, and Anopheles vectors. Harmonized metadata and rhythmicity outputs from JTK_CYCLE, ARSER, Lomb-Scargle, and the meta2d function support interactive cross-study interrogation of molecular profiles. Dedicated modules enable the exploration of rhythmic virulence factors and antimalarial drug interactors, providing a unified framework for hypothesis generation across the malaria transmission cycle. Availability: PlasmoRhythm is freely accessible at https://project.iith.ac.in/cgntlab/PlasmoRhythm/.