Periodic Reporting for period 4 - EVOIMMECH (The evolutionary ecology of bacterial immune mechanisms)
Période du rapport: 2021-07-01 au 2022-12-31
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. 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. Furthermore, we have applied bioinformatics approaches to demonstrate how bacterial immune systems are distributed across different ecosystems, and how they shape the flux of mobile DNA across bacterial genomes. 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.
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 a broad range of ecological factors. For example, we found that bacteria evolve much higher levels of CRISPR resistance when they are part of a microbial community. 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. The opposing fitness consequences of CRISPR-Cas in the face of horizontally and vertically transmitting phages helps 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 also studied how bacteria with CRISPR resistance and phage coevolve, in simple lab environments and more complex semi-natural environments. We found for example that some phage can overcome CRISPR immunity using so-called Anti-CRISPR genes but this is prone to "cheating" by phage that lack anti-CRISPR genes. Bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages need to cooperate in order to overcome CRISPR resistance, with a first phage blocking the host CRISPR-Cas immune 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. However, this cooperative behaviour of phages may also affect the ability of other phages in the environment to survive. Indeed found that the Anti-CRISPR phages can greatly influence survival of other phages.
We have demonstrated that CRISPR immune systems are particularly abundant in environments with high levels of phage predation, and we have found that bacteria with CRISPR-Cas immune systems are less likely to carry antibiotics resistance genes in their genome probably because the immune systems block horizontal gene transfer. Finally, we demonstrated key differences in the evolution on phage resistance in simple lab environments and more complex, semi-natural environments (e.g. in the presence of competitors or antibiotics). This helps to understand how bacteria and phage interact in natural environments by bridging simple lab models with complex natural ecosystems.
We also studied how bacteria with CRISPR resistance and phage coevolve, in simple lab environments and more complex semi-natural environments. We found for example that some phage can overcome CRISPR immunity using so-called Anti-CRISPR genes but this is prone to "cheating" by phage that lack anti-CRISPR genes. Bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages need to cooperate in order to overcome CRISPR resistance, with a first phage blocking the host CRISPR-Cas immune 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. However, this cooperative behaviour of phages may also affect the ability of other phages in the environment to survive. Indeed found that the Anti-CRISPR phages can greatly influence survival of other phages.
We have demonstrated that CRISPR immune systems are particularly abundant in environments with high levels of phage predation, and we have found that bacteria with CRISPR-Cas immune systems are less likely to carry antibiotics resistance genes in their genome probably because the immune systems block horizontal gene transfer. Finally, we demonstrated key differences in the evolution on phage resistance in simple lab environments and more complex, semi-natural environments (e.g. in the presence of competitors or antibiotics). This helps to understand how bacteria and phage interact in natural environments by bridging simple lab models with complex natural ecosystems.