Summary
Heterogeneity amongst isogenic cells is pervasive throughout biology. Recently developed single-cell omics approaches are beginning to systematically reveal the repertoire of functionally distinct cell subpopulations within metazoan tissues. Pathogens frequently encounter changing and often hostile environments. To adapt to these challenges unicellular pathogen populations also exhibit a large degree of cell-to-cell heterogeneity, which often affects the outcome of infections. Yet, despite the importance of this cell-to-cell variation, very little is known about the mechanisms that control the level of heterogeneity in pathogen populations or why some isogenic populations are more heterogeneous than others. The goal of switchDecoding is to unveil the path to cellular variation. To this end I will go beyond identifying and describing new subpopulations of cells and elucidate the molecular pathways that establish them and modulate the level of cellular heterogeneity. As a model I will study the mechanism responsible for creating heterogeneity in surface antigen expression in the unicellular parasite Trypanosoma brucei. Antigenic variation is a widely employed strategy by evolutionarily divergent pathogens to evade the host immune response. Using a multidisciplinary approach, I will develop and combine single-cell multi-omics, lineage tracing and CRISPR-Cas-based genome manipulation strategies to characterize the processes, pathways and molecules regulating antigen switching in T. brucei. A better understanding of the mechanisms affecting the level of heterogeneity within a pathogen population will enable us to better predict how pathogens adapt to environmental challenges, including those that lead to the emergence of drug resistance. In the future this knowledge will enable the development of novel intervention strategies: drugs that modulate cell-to-cell heterogeneity to facilitate the clearance of infections.
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| Web resources: | https://cordis.europa.eu/project/id/101044320 |
| Start date: | 01-04-2023 |
| End date: | 31-03-2028 |
| Total budget - Public funding: | 1 999 825,00 Euro - 1 999 825,00 Euro |
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Original description
Heterogeneity amongst isogenic cells is pervasive throughout biology. Recently developed single-cell omics approaches are beginning to systematically reveal the repertoire of functionally distinct cell subpopulations within metazoan tissues. Pathogens frequently encounter changing and often hostile environments. To adapt to these challenges unicellular pathogen populations also exhibit a large degree of cell-to-cell heterogeneity, which often affects the outcome of infections. Yet, despite the importance of this cell-to-cell variation, very little is known about the mechanisms that control the level of heterogeneity in pathogen populations or why some isogenic populations are more heterogeneous than others. The goal of switchDecoding is to unveil the path to cellular variation. To this end I will go beyond identifying and describing new subpopulations of cells and elucidate the molecular pathways that establish them and modulate the level of cellular heterogeneity. As a model I will study the mechanism responsible for creating heterogeneity in surface antigen expression in the unicellular parasite Trypanosoma brucei. Antigenic variation is a widely employed strategy by evolutionarily divergent pathogens to evade the host immune response. Using a multidisciplinary approach, I will develop and combine single-cell multi-omics, lineage tracing and CRISPR-Cas-based genome manipulation strategies to characterize the processes, pathways and molecules regulating antigen switching in T. brucei. A better understanding of the mechanisms affecting the level of heterogeneity within a pathogen population will enable us to better predict how pathogens adapt to environmental challenges, including those that lead to the emergence of drug resistance. In the future this knowledge will enable the development of novel intervention strategies: drugs that modulate cell-to-cell heterogeneity to facilitate the clearance of infections.Status
SIGNEDCall topic
ERC-2021-COGUpdate Date
09-02-2023
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