Identification of bacterial mechanisms critical for maintenance of infection

The project relies on previous studies showing that it is possible to reveal gene expression of bacteria in host tissue, where data for persistent infections indicates importance of gene products involved in adaptation to the tissue environment.

To study adaption strategies at a molecular level we use Yersinia pseudotuberculosis and Salmonella enterica serovar Typhimurium (both with mouse models for persistent infections) as model pathogens, complemented with studies of bacteria in patient samples of infected tissue.

We determine in vivo gene-expression profiles of bacteria in different tissues and use the information for identification of gene products to be explored as potential targets for new antimicrobial therapies.

We use RNA-scope/-FISH to reveal information of spatial/heterogenous gene expression, and we are developing protocols for single cell RNA-seq of bacteria for this purpose.

To extract hidden important information in transcriptomes of bacteria in tissue we apply systems biology/machine learning-based approaches.

Here our database with in vivo transcriptomic profiles of more than 30 human pathogens exposed to different stress conditions allow identification active regulons and novel players therein.

From initial analyses, we are investigating a set of candidate genes using a battery of experimental approaches, the candidate group include genes encoding regulators, sensors, metabolic and stress defense proteins, of which some not are expressed at all in vitro.