Project

FROM EXPLAINING TO PREDICTING

Intracellular pathogens such as Chlamydia and Brucella spp. can be genetically very closely related, yet differ in virulence, zoonotic potential, and/or host species. For example, the highly zoonotic B. melitensis is genetically very closely related to the less zoonotic B. suis (90 percent of the genes are 98 to 100% similar), but they prefer a different host (sheep vs. pig). This small difference in the DNA made it difficult to make predictions about behavior such as risk, preference for a host species, and zoonotic potential in newly discovered species based on genome data (e.g. presence/absence of known virulence genes).

Some groups of intracellular pathogens such as Brucella and Chlamydia spp. are genetically very closely related1, but may still differ in zoonotic potential and/or host specificity (they have different “behavior”). The strong relationship makes it very difficult to determine at DNA level what causes these differences. It turned out to be difficult to predict the behavior of a newly introduced species using only DNA data. It is therefore interesting to look at the bacterial RNA (i.e. gene expression, controlled, among other things, by DNA methylation) to explain the differences ab initio. In current RNA methodology we often look for biomarkers. These are genes whose expression correlates with certain behavior. But for closely related species, such as Brucella spp. it appears to be difficult to find specific biomarkers.In this project, we want to use a published algorithm2,3 to look beyond the expression of individual genes (biomarkers), and work with patterns of expression, which together lead to a so-called “archetype”. An archetype is a theoretical prediction of the optimal pattern of gene expression in a particular situation, such as growing in a human or animal cell line. We can then use an in-vitro measurement and in-silico prediction to determine the distance to an archetype of a new strain or species. This way, instead of explaining behavior afterwards, we can make specific predictions in advance about the behavior and zoonotic potential of a new species.

Publications