In Spain, you would call a lion león, or arslan in Mongolia. But thanks to the naming system created in the 18th century by Swedish naturalist Carl Linnaeus, the lion is known by only one scientific name no matter where you are in the world: Panthera leo.
Unfortunately, a similar common language doesn’t exist in the field of immunology—although it could use it. Immune cells often consist of a myriad of complex and specialised cellular subtypes, each with its distinct genetic profile and function, all of which are crucial for advancing research.
For example, immunologists are interested in a group of immune cells called mononuclear phagocytes (MNPs) because of their role in immune defence. However, the diversity of MNP types — which includes macrophages, monocytes and dendritic cells — and their functions have made them difficult to study.
“In the last few years, we have seen a lot of annotation of the same cells but with different names, which has led to a lot of confusion in the field,” said Florent Ginhoux, a Principal Investigator at A*STAR’s Singapore Immunology Network (SIgN). “For scientists, the integration of various datasets and their common annotations would allow us to speak in the same language.”
With COVID-19 stay-at-home orders keeping them out of the laboratory, Ginhoux and colleague Charles-Antoine Dutertre decided to take a computational approach to make sense of MNPs. They examined single-cell RNA sequencing data extracted from nearly 180,000 MNPs across 41 healthy and diseased samples, organising and standardising the data in a first-of-its-kind open-access database called the MNP-VERSE.
In addition to serving as a public platform to store all existing MNP research, the MNP-VERSE also allowed the team to identify major MNP populations and subsets. Having established this broad overview of MNP data, the team then extracted just macrophage and monocyte data and re-integrated them into a second database called MoMac-VERSE.
By navigating the databases based on parameters such as cell type, gene expression and pathology, the team could explore how diseased MNPs differed from their healthy counterparts, allowing them to link specific MNP subtypes with different diseases.
“When we integrated data from COVID-19 patients, we could see that there were some common problems of activation, inflammation, monocytes, and macrophages across diseases including cancer,” said Ginhoux, adding that these commonalities in disease response could be investigated as potential therapeutic targets.
The team’s next steps are centred around refining the MNP-VERSE and MoMac-VERSE by enriching them with more experimental data. They also plan to develop a third database specifically for cataloguing dendritic cells, which will provide insight into how the immune system recognises foreign pathogens.
The A*STAR-affiliated researchers contributing to this research are from the Singapore Immunology Network (SIgN) and Genome Institute of Singapore (GIS).
