Infectious diseases represent a major worldwide threat to human health. Novel strategies to combat infectious disease are urgently needed because of rising resistance of pathogens to antimicrobial therapy, an increasing number of immunosuppressed patients that are highly susceptible to infection, increasing travel which enhances transmission and worldwide spread of novel and re-emerging pathogens, and potential bioterrorism threats.
The substantial progress in infection biology research in the last two decades could provide a basis for novel control strategies. However, it has remained difficult to translate this extensive knowledge into effective new control strategies. One potential reason why it is so difficult to translate basic research to effective strategies for combating infectious diseases, could be the prevailing focus on the action of individual pathogen or host components. While this reductionist approach was highly successful to identify and characterize key virulence and immune factors, it can not explain the course of complex multifactorial infectious diseases involving hundreds of interacting pathogen and host factors. Our goal is therefore to integrate the vast existing knowledge and to develop appropriate methodology to analyze interacting host/pathogen networks using FACS sorting of pathogens from infected host cells and tissues, quantitative proteomics, metabolomics, molecular genetics, animal infection models, and in silico modeling.
For our research we use Salmonella as well as Shigella as model pathogens. Both pathogens cause diarrhea and Salmonella can also cause typhoid fever and nontyphoidal Salmonella (NTS) bacteremia, which together cause over a million deaths each year. In addition to their importance as human pathogens, Salmonella and Shigella are among the best-studied model pathogens.
A large number of Salmonella proteins with detectable expression during infection have metabolic functions. Many of these enzymes could represent promising targets for antimicrobial chemotherapy. However, we have previously shown that actually only a very small minority of enzymes is sufficiently relevant for Salmonella virulence to qualify as a potential target. To understand the differential relevance of metabolic enzymes we systematically characterize the entire Salmonella metabolic network during infection by integrating large-scale data on in vivo nutrient availability and enzyme abundance with a genome-scale in silico model that provides a consistent large-scale description of Salmonella metabolism during infection. The results revealed a surprisingly large diversity of host nutrients. However each of these nutrients was available in only minute amounts. This paradoxical situation (“starving in paradise”) has two major consequences, i) broad nutrient supplementation buffers many Salmonella metabolic defects thus limiting opportunites for antimicrobials, ii) Salmonella growth in infected mice is rather slow and nutrient-limited. Both findings reiterate the major importance of metabolism for infectious disease outcome.
Within the framework of the SystemsX.ch RTD project BattleX (coordinator: Dirk Bumann) we have recently started to analyze pathogen and host metabolism in Shigella infections together with five collaborating groups across Switzerland. Initial results suggest that Shigella (like Salmonella) has access to diverse host nutrients. However, in this case excess nutrient quantities that support very fast pathogen growth seem to be available. These differences likely reflect differential localization of Salmonella in a membrane-delimited vacuole vs. Shigella freely residing in the host cell cytosol with unrestricted access to cytosolic metabolites. Metabolomics data suggest that Shigella infection causes major rearrangements of metabolic fluxes in the host cells. We currently explore such host cell activities as alternative targets for controlling infection.
Analysis of pathogen subpopulations
Salmonella reside in several distinct host microenvironments within the same infected tissue. These microenvironments differ in density of host defense cell types such as neutrophils and inflammatory macrophages and likely provide substantially different conditions for Salmonella. We are developing a set of complementary tools to isolate distinct Salmonella subpopulations from various microenvironments for system-level analysis. Current results suggest dramatic differences in stress exposure and growth rate in Salmonella subpopulations.
Amos Bairoch (Swiss Institute of Bioinformatics, Geneva, CH)
Ivan Dikic (Goethe-Universität Frankfurt, D)
Wolf-Dietrich Hardt (ETH Zurich, CH)
Vassily Hatzimanikatis (EPFL Lausanne, CH)
Ralph Schlapbach (FGC Zurich, CH)
Julia Vorholt (ETH Zurich, CH)