Researchers from the University of Glasgow have developed paraCell, a new software tool designed to make single-cell RNA sequencing (scRNA-seq) data more accessible to parasitologists. While single-cell transcriptomic datasets have expanded dramatically, analyzing them often requires advanced computational skills, limiting their use among researchers without bioinformatics expertise.

Unlocking Single-Cell Insights in Parasitology

Single-cell RNA sequencing has revolutionized how scientists study parasites like Plasmodium (which causes malaria) and Trypanosoma (responsible for sleeping sickness). These datasets provide valuable insights into gene expression changes during different life cycle stages, in response to host environments, and under experimental conditions. However, many researchers struggle to integrate this data into their work due to complex computational barriers.

Introducing paraCell

paraCell is a user-friendly, open-access software tool that allows researchers to visualize and analyze pre-loaded scRNA-seq datasets without needing programming skills. The software can be installed remotely, and a web-based server enables users to explore previously published datasets, including those from Plasmodium and Trypanosoma studies. Additionally, the researchers generated new datasets for Toxoplasma (which infects mice) and Theileria (which affects cows), demonstrating paraCell’s ability to analyze pathogen-host interactions.

Overview of the four main options in paraCell

Advanced Gene Search – a custom gene-set is used to create a cellxgene VIP multi-gene violin plot (Plasmodium berghei dataset). Host-Parasite Interactions – selection made on the Parasite UMAP is used to update the Host UMAP (Cow-Theileria dataset). Database Integration – paraCell results table is shown alongside links to relevant external database systems (P. berghei dataset). Trajectory Inference – Slingshot trajectories drawn over PHATE space of single-cell data, enables tradeSeq to plot expression of genes over their “pseudo time” for different conditions – example relates the expression of the gene PAD2 to the progression of both trajectories in the WT and KO condition (Trypanosoma brucei dataset).

Host Responses to Parasitic Infections

Using paraCell, the team uncovered critical insights into how host immune responses impact parasite gene expression. For example, they observed how interferon-γ, a key immune signaling molecule, influences parasite behavior, shedding light on factors that may contribute to disease susceptibility. These findings highlight how single-cell RNA sequencing can advance our understanding of host-parasite interactions and potentially inform new treatment strategies.

Why paraCell is Important

By eliminating the need for advanced bioinformatics expertise, paraCell democratizes access to single-cell RNA sequencing data, allowing more researchers to explore how parasites interact with their hosts at the molecular level. This tool could accelerate discoveries in parasitology and contribute to the development of targeted therapies for parasitic diseases.

Availability – paraCell is an open-source project and MIT licensed application, available at https://github.com/sii-cell-atlas/paraCell/