Periodic Reporting for period 3 - EVOIMMECH (The evolutionary ecology of bacterial immune mechanisms)
Periodo di rendicontazione: 2020-01-01 al 2021-06-30
Another important finding we made is that CRISPR-Cas immune systems can be maladaptive during infection with temperate phages. Temperate phages (viruses that infect bacteria) enter either the lytic or the lysogenic cycle upon infection of their host, causing host lysis and horizontal transmission or dormancy and vertical transmission, respectively. Co-culture experiments of bacteria and obligately killing temperate phage mutants - that are locked in the lytic cycle - have provided key insights into the evolutionary dynamics of CRISPR-Cas and phage interactions, but have ignored this dichotomy of temperate phage transmission strategies. Our work shows that type I CRISPR-Cas immune systems are much less efficient in clearing wildtype temperate phage infections from the bacterial population than phage mutants locked in the lytic cycle, and are in fact maladaptive to the host due to severe immunopathological effects that specifically manifest during vertical transmission of the phage. These fitness costs drive the loss of CRISPR-Cas from bacterial populations, unless the phage carries anti-CRISPR (acr) genes that suppress the immune system of the host. The opposing fitness consequences of CRISPR-Cas in the face of horizontally and vertically transmitting phages can therefore help to explain the frequent loss and gain of CRISPR-Cas immune systems across bacterial strains, and highlight the strong selective benefits of phage-encoded acr genes during long-lived infections associated with vertical transmission.
We have also found that host mutation rates negatively impact the evolution of CRISPR in favour of surface based resistance. Specifically, we examined how mutations in the bacterial mismatch repair system, which are frequently observed in natural and clinical isolates and cause elevated host mutation rates, influence the evolution of CRISPR-Cas-mediated immunity. We found that hosts with a high mutation rate very rarely evolved CRISPR-based immunity to phage compared to wild-type hosts. We explored the reason for this effect and found that the higher frequency at which surface mutants pre-exist in the mutator host background causes them to rapidly become the dominant phenotype under phage infection. These findings suggest that natural variation in bacterial mutation rates may, therefore, influence the distribution of CRISPR-Cas adaptive immune systems.
We also studied how phage can evolve to overcome CRISPR resistance. We found that some phage that encode so-called Anti-CRISPR genes can infect bacteria with CRISPR-Cas Immunity, but only if they work together. We found that this is needed because bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages often need to cooperate in order to overcome CRISPR resistance, with a first phage blocking the host CRISPR-Cas im- mune system to allow a second Acr-phage to successfully replicate. This cooperation leads to epidemiological tipping points in which the initial density of Acr-phage tips the balance from phage extinction to a phage epidemic. Furthermore, both higher levels of CRISPR-Cas immunity and weaker Acr activities shift the tipping points toward higher initial phage densities. Collectively, these data help elucidate how interactions between phage-encoded immune suppressors and the CRISPR systems they target shape bacteria-phage population dynamics. However, this cooperative behaviour of phages may also affect the ability of other phages in the environment to survive. We have studied this process, and indeed found that the Anti-CRISPR phages can greatly influence survival of other phages. Such information can help to design more effective phage cocktails for therapeutic use.
During the remainder of this project we will continue to use an experimental evolution approach to identify ecological drivers of different immune strategies. We will also explore how plasmids and plasmid-like phages impact resistance evolution, using a combination of theory (Westra, Levin, in prep) and experiments. Furthermore, we have now developed all the tools and acquired relevant metagenomic datasets to examine the ecological drivers of CRISPR immune systems in natural ecosystems. This will enable us to examine how ecological variables correlate with CRISPR abundance, using a range of statistical methods. Next, we plan to generate tools to detect abundances of other immune systems in these metagenomes. These observational studies will be complemented with mesocosm experiments to examine the evolution of immune mechanisms and co-evolutionary dynamics in a semi-real environment. We are in the process of setting up infection experiments in soils.