Bacteria engage in a diverse range of social behaviors, including the formation of multicellular structures and the secretion of shareable public goods. Bacterial cooperation is typically controlled by communication processes, which allow group coordinated actions. While the mechanistic details of these communication systems are well studied, their evolution is poorly understood. One aspect regards closely related bacteria, which use slightly different signaling molecules, and thus ‘speak different languages’. This signal diversification could be driven by conflict, which arises due to cheating mutants. Both signaling and cooperation can be exploited by cheating mutants, which no longer produce signals and/or public goods. Signal diversification could thus represent an evolutionary response to limit eavesdropping and exploitation of information by cheats. To test this hypothesis, we will use a combination of individual-based evolution simulations, experimental evolution with the bacterium Pseudomonas aeruginosa and genome sequencing, elucidating both the genetic and evolutionary basis of bacterial language diversification. Our project will make three major contributions: (i) testing whether key predictions of evolutionary signaling theory also apply to bacteria; (ii) providing an integrative view on communication diversification, as we will combine mechanistic and evolutionary aspects of signaling; and (iii) it will advance signaling theory through individual-based modeling implementing mechanistic details of communication, which will allow us to identify the key evolutionary drivers of language diversification.
PhD-Student: Alexandre Figueiredo
Viruses are widespread and infect all forms of life. They are a threat to humans and livestock, and difficult to fight due to their high genetic variability and intricate control of host immunity. Respiratory viruses, e.g. seasonal and potentially pandemic Influenza, and Rhinovirus, the causative agent of the common cold, cause acute respiratory tract infections with world-wide hundreds of thousands of deaths per year and billions of $ economic loss. Vaccines are available against seasonal but not pandemic Influenza. Chemicals targeting Influenza or Rhinovirus are not effective due to rapid virus drug resistance. Viral resistance mechanisms to chemicals targeting host rather than viral factors are poorly understood. Here, we explore real-time evolution of Influenza and Rhinovirus by NGS-based sequencing of viral genomes under the selection pressure of chemicals. We will neutralize endosomal pH blocking infection by three mechanisms: (i) proton entry into endosomes (Bafilomycin), (ii) proton neutralization in endosomes (ammonium chloride) and (iii) shuttling protons out of endosomes (Niclosamide). We expect to find drug-invariant hot spots with compensatory mutations adapting virus to neutral pH. The genomes of mutants, which are resistant to one of the three compounds, will be scrutinized for mutations revealing pH-independent signatures, such as physiological compensations of neutral endosomal pH, and results will be validated using reverse genetics. The project will generate a dynamic time-resolved view of virus evolution, and explore the cell biological mode-of-action of host-directed antivirals.
PhD-Student: Luca Murer
The human gut microbiome is considered of great importance to human health, e.g., to understand the current obesity pandemic. This project will use novel molecular research methods on ancient Egyptian mummies and viscera samples (from canopic storage jars) to study the evolution of the human gut microbiome. We focus particularly on the contents of canopic jars, as these viscera samples (including the stomach and intestines) are an especially important source when looking for human gut microbiomes. We are currently gathering 82 canopic jars and 15 mummies from major collections such as Berlin, Turin, and Boston, spanning numerous ancient Egyptian time periods. In respect for ethics, samples will be extracted from the mummies and canopic jars to undergo molecular analyses, i.e. to assess DNA preservation, assess co-infection by various bacterial pathogens, and investigate specific ancient microbiomes using NGS-based techniques. Microbiomes will be compared between different organs from the same individuals and across all individuals to assess the variability. In addition, the ancient data will be compared with modern human microbiomes from existing databases, e.g. SILVA, to address change over time. We already performed a pilot study showing the feasibility of retrieving and analyzing ancient DNA, in which pathogenic DNA (e.g. Clostridium botulinum) could be identified as well. This is the first such study worldwide.
PhD-Student: Enrique Rayo
The adaption of viruses to escape recognition by the immune system is a case in point for evolution in action and of the highest clinical importance for vaccine design. One of the best studied of these interactions is that of HIV and HLA (Markov, 2015): At the level of individual patients, both a role of HLA alleles and viral escape from HLA binding have been well documented. It is, however, only poorly understood how this diversity affects transmission and evolution of the virus at an epidemic scale. Here, we will address this question using the unique data (18’000 patients, 11’000 with viral sequences, 5’000 with human SNP/Exome data) from the Swiss HIV Cohort Study and the samples from the associated biobank (Swiss HIV Cohort Study, 2010). We will characterize transmission chains with phylogenetic methods and map the information on HLA alleles on these transmission chains. This will yield an extremely detailed representation of the fluctuating selective pressures the virus is confronted with at an epidemic scale. Quantifying HLA diversity along transmission chains and comparing this with neutral expectation will then allow evaluating to what extent HLA diversity can limit transmission of the virus. We will assess the clinical and evolutionary impact of HLA diversity by determining its association with outbreak size, virulence, and evolutionary rate across transmission chains. Finally, we will explore the impact of HLA diversity on viral adaption using population genetic models calibrated with the observed HLA data and escape rates. Overall, these projects will provide an unprecedented insight into the clinical and epidemiological impact of HLA diversity but also an ideal real-world, clinically relevant example for evolution in action.
PhD-Student: Huyen Nguyen