Periodic Reporting for period 3 - EVOIMMECH (The evolutionary ecology of bacterial immune mechanisms)
Période du rapport: 2020-01-01 au 2021-06-30
Understanding the interactions between bacteria and their viruses is important, because of the increasing interest in using these viruses as alternatives for - or in combination with - antibiotics. Understanding interactions between bacteria and mobile pieces of DNA, such as plasmids, is also important, because these mobile pieces of DNA can move important genes between bacteria that for example confer antibiotics resistance or virulence determinants. Bacterial immune systems, which protect against these viruses and mobile pieces of DNA, play a key role in mediating these interactions. Bacteria have a range of immune mechanisms, but it is unclear why this diverse armamentarium evolved. The most important immune mechanisms are (1) Surface Modification (SM) (2) Abortive infection (Abi) (3) Restriction Modification (R-M) (4) CRISPR-Cas and (5) prokaryotic Argonaute (pAgo), all of which can occur as stand-alone mechanisms or in combination. This project applies a combined in vitro and in vivo approaches to tease apart the variables that drive the evolution of these diverse stand-alone and integrated bacterial immune strategies in nature, and examine their associated co-evolutionary dynamics. In vitro manipulations using the opportunistic human pathogen Pseudomonas aeruginosa PA14, equipped with either single or multiple immune mechanisms will identify important drivers of resistance strategies. Metagenomics, transcriptomics and viromics will provide observational data from environments that differ in ecological variables that are important in vitro, to examine their importance in vivo. Key ecological mechanisms identified in the first two parts of the project will be used to guide mesocosm experiments to experimentally confirm that these mechanisms are the drivers of the observed patterns of resistance and co-evolution in nature. Finally, data are shared with mathematical biologists to generate theoretical models to predict and manipulate the evolution of bacterial immune mechanisms.
The aim of the project is to tease apart how ecology drives the evolution of bacterial immune mechanisms. This ERC project has revealed that both biotic and abiotic factors are important determinants of the evolution of CRISPR versus surface-based immunity in bacteria. Furthermore, we have found that the genetic context in which these systems exist also has important consequences for the levels of CRISPR-based resistance that evolve. Specifically, in bacteria with high mutation rates, it is less likely to observe evolution of CRISPR-based resistance against phages. This matters, because we also found that the type of resistance that this bacterium evolves against phage has important knock-on effects for the virulence levels of this opportunistic human pathogen, which obviously needs to be considered in the context of phage therapy. Our work has also looked at coevolution between bacteria with CRISPR-Cas and phages, showing that the composition of the host population influences whether or not phage can evolve to overcome the resistance of the host, and that if they are able to do so, this can result in an arms race of spacer acquisition by the host and escape mutation by the phage. Apart from a fundamental interest in understanding how viruses of bacteria drive microbial population and evolutionary dynamics, this is also of applied interest for successful application of phage cocktails for therapeutic purposes. We also studied how phages use anti-CRISPR strategies to overcome the host immune system, and the wider implications of these genes for the existence of other phages in the environment. These experimental studies are complemented with observational studies, where we interrogate existing metagenomic datasets to ask how ecological variables correlate with abundances of difference immunity genes. We are setting up mesocosm experiments to explore the evolution of immune mechanisms and co-evolutionary dynamics in a semi-real environments, so more closely mimic natural environments and to move away from test tube observations. This work is done using Pseudomonads and Bacilli as model systems.
The ERC project has led to important novel insights into the coevolutionary interactions between bacteria and phages, and how the outcome of this interactions depends on the ecological context. For example, we found that bacteria evolve much higher levels of CRISPR resistance when they are part of a microbial community. This is important: half of all bacterial species encode CRISPR-Cas adaptive immune systems, which provide immunological memory by inserting short DNA sequences from phage and other parasitic DNA elements into CRISPR loci on the host genome. Whereas CRISPR loci evolve rapidly in natural environments, bacterial species typically evolve phage resistance by the mutation or loss of phage receptors under laboratory conditions. We have found that this discrepancy may in part be explained by differences in the biotic complexity of in vitro and natural environments. Specifically, using the opportunistic pathogen Pseudomonas aeruginosa and its phage DMS3vir, we show that coexistence with other human pathogens amplifies the fitness trade-offs associated with phage receptor mutation, and therefore tips the balance in favour of CRISPR-based resistance evolution. We also demonstrate that this has important knock-on effects for P. aeruginosa virulence, which became attenuated only if the bacteria evolved surface-based resistance. Our data reveal that the biotic complexity of microbial communities in natural environments is an important driver of the evolution of CRISPR-Cas adaptive immunity, with key implications for bacterial fitness and virulence.
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.
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.