Long-run bacteria-phage coexistence dynamics under natural habitat conditions in an environmental biotechnology system

Abstract

Bacterial viruses are widespread and abundant across natural and engineered habitats. They influence ecosystem functioning through interactions with their hosts. Laboratory studies of phage–host pairs have advanced our understanding of phenotypic and genetic diversification in bacteria and phages. However, the dynamics of phage–host interactions have been seldom recorded in complex natural environments. We conducted an observational metagenomic study of the dynamics of interaction between Gordonia and their phages using a three-year data series of samples collected from a full-scale wastewater treatment plant. The aim was to obtain a comprehensive picture of the coevolution dynamics in naturally evolving populations at relatively high time resolution. Coevolution was followed by monitoring changes over time in the CRISPR loci of Gordonia metagenome-assembled genome, and reciprocal changes in the viral genome. Genome-wide analysis indicated low strain variability of Gordonia, and almost clonal conservation of the trailer end of the CRISPR loci. Incorporation of newer spacers gave rise to multiple coexisting bacterial populations. The host population carrying a shorter CRISPR locus that contain only ancestral spacers, which has not acquired newer spacers against the coexisting phages, accounted for more than half of the total host abundance in the majority of samples. Phages genome co-evolved by introducing directional changes, with no preference for mutations within the protospacer and PAM regions. Metagenomic reconstruction of time-resolved variants of host and viral genomes revealed how the complexity at the population level has important consequences for bacteria-phage coexistence.

Global Composition of the Bacteriophage Community in Honey Bees

“…Whether or not phages specialize on these functionally divergent bacteria and if phage host range evolution affects these bacterial communities remain interesting questions. Ecological models ( 65 ) and empirical studies ( 66 ) of phage and hosts show that the stable coexistence of phages with overlapping host ranges can occur under certain conditions, specifically when there is a fitness trade-off between generalist and specialist strategies or in spatially structured gut environments ( 67 ). As we learn more about phage ecology in animal guts, the bee gut microbiome provides a unique and convenient system to experimentally explore microbial ecosystems.…”

Long-term CRISPR array dynamics and stable host-virus co-existence in subsurface fractured shales

“…Successful incorporation of a spacer should provide the host future defense upon interaction with the same viral population. However, CRISPR arrays do not grow exponentially as spacers can indeed be lost, (34)(35)(36)(37), and host-viral co-existence despite CRISPR has been observed (38). Additionally, spacers nearest to the leading end of the CRISPR arrays are most likely to be effective, as they typically represent more recent viral interactions with less time for mutations to occur within the viral protospacer, although recombination can also influence CRISPR array architecture (8).…”

Dynamics of immune memory and learning in bacterial communities

“…The kinetics and interactions of phages and bacteria with CRISPR systems have been the subject of numerous experiments ( van Houte et al, 2016 ; Common et al, 2019 ; Common et al, 2020 ; Chabas et al, 2021 ; Dimitriu et al, 2022 ; Guillemet et al, 2021 ). Some themes have emerged from experimental studies of CRISPR immunity: (a) high spacer diversity relative to phage diversity increases the likelihood of phage extinction ( van Houte et al, 2016 ; Common et al, 2020 ; Guillemet et al, 2021 ), (b) bacteria become more immune to phages over time ( Laanto et al, 2017 ; Morley et al, 2017 ; Common et al, 2019 ; Pyenson and Marraffini, 2020 ), and (c) phages readily gain mutations ( Weinberger et al, 2012a ; Paez-Espino et al, 2013 ; Levin et al, 2013 ; Pyenson et al, 2017 ; Watson et al, 2019 ; Pyenson and Marraffini, 2020 ; Guillemet et al, 2021 ; Guerrero et al, 2021a ) and sometimes genome rearrangements ( Paez-Espino et al, 2015 ) to escape CRISPR targeting. Explorations of CRISPR immunity in natural environments have also documented ongoing spacer acquisition and phage escape mutations ( Weinberger et al, 2012a ; Guerrero et al, 2021a ).…”

“…Some themes have emerged from experimental studies of CRISPR immunity: (a) high spacer diversity relative to phage diversity increases the likelihood of phage extinction ( van Houte et al, 2016 ; Common et al, 2020 ; Guillemet et al, 2021 ), (b) bacteria become more immune to phages over time ( Laanto et al, 2017 ; Morley et al, 2017 ; Common et al, 2019 ; Pyenson and Marraffini, 2020 ), and (c) phages readily gain mutations ( Weinberger et al, 2012a ; Paez-Espino et al, 2013 ; Levin et al, 2013 ; Pyenson et al, 2017 ; Watson et al, 2019 ; Pyenson and Marraffini, 2020 ; Guillemet et al, 2021 ; Guerrero et al, 2021a ) and sometimes genome rearrangements ( Paez-Espino et al, 2015 ) to escape CRISPR targeting. Explorations of CRISPR immunity in natural environments have also documented ongoing spacer acquisition and phage escape mutations ( Weinberger et al, 2012a ; Guerrero et al, 2021a ). Likewise, previous theoretical work has addressed the impact of parameters such as spacer acquisition rate and phage mutation rate on spacer diversity ( Childs et al, 2012 ; Han et al, 2013 ; Han and Deem, 2017 ) and population survival and extinction ( Weinberger et al, 2012b ), how costs of CRISPR immunity impact bacteria-phage coexistence ( Skanata and Kussell, 2021 ) and the maintenance of CRISPR immunity ( Levin, 2010 ; Weinberger et al, 2012b ; Westra et al, 2015 ; Gurney et al, 2019 ), how spacer diversity impacts population outcomes ( He and Deem, 2010 ; Weinberger et al, 2012a ; Childs et al, 2012 ; Haerter and Sneppen, 2012 ; Han et al, 2013 ; Childs et al, 2014 ; Bradde et al, 2017 ; Han and Deem, 2017 ), and how stochasticity and initial conditions impact population survival ( Bradde et al, 2019 ; Chabas et al, 2018 ).…”