key: cord-0327465-ueczjd4u
authors: Wendling, Carolin C.; Lange, Janina; Liesegang, Heiko; Sieber, Michael; Pöhlein, Anja; Bunk, Boyke; Rajkov, Jelena; Goehlich, Henry; Roth, Olivia; Brockhurst, Michael A.
title: Higher viral virulence accelerates the evolution of host resistance
date: 2021-10-08
journal: bioRxiv
DOI: 10.1101/2021.03.26.437141
sha: 819bb7ae6aafd1bcd541bd3a064448715cbf54e1
doc_id: 327465
cord_uid: ueczjd4u

Parasites and pathogens vary strikingly in their virulence and the resulting selection they impose on their hosts. While the evolution of different virulence levels is well studied, the evolution of host resistance in response to different virulence levels is less understood and as of now mainly based on theoretical predictions. Increased virulence can increase selection for host resistance evolution if resistance costs are outweighed by the benefits of avoiding infection. To test this, we experimentally evolved the bacterium Vibrio alginolyticus against two variants of the filamentous phage, VALGΦ8, that differ in their virulence. The bacterial host exhibited two alternative defence strategies against future viral infection: (1) super infection exclusion (SIE) whereby viral-infected cells were immune to subsequent infection at a cost of reduced growth, and (2) surface receptor mutations in genes encoding the MSHA type-IV pilus providing resistance to infection by preventing viral binding. While SIE emerged rapidly against both viruses, resistance evolved faster against the high virulence compared to the low virulence virus. Using a mathematical model of our system we show that increasing virulence strengthens selection for resistance due to the higher costs of infection suffered by SIE immune hosts. In both the experiments and the model, higher levels of evolved resistance in the host population drove more rapid virus extinction. Thus, by accelerating the evolution of host resistance, more virulent viruses caused shorter epidemics.

Infectious organisms vary strikingly in their level of virulence and the resulting 57 selection they impose on hosts. Indeed, even closely related viruses, such as different 58 strains of myxoma (1) or corona viruses (2), can differ greatly in virulence. While the 59 evolution of virulence has been studied extensively during the last two decades, both 60 using selection experiments (3-5) and observations of parasites evolved in nature (6, 7), 61

how hosts respond to virulence-mediated selection is less well-explored. How virulence 62 will impact evolutionary trajectories of resistance in a host population, and how these 63 trajectories change with different levels of virulence, has been subjected to theoretical 64 investigation. In general, increased virulence strengthens selection for the evolution of 65 host resistance if the costs of resistance are outweighed by the benefits of avoiding 66 infection (8-10). As such, at very low virulence, although infection is common, resistance 67

is not favoured because the cost of resistance is likely to exceed any benefits of avoiding 68 mild disease (9). With increasing virulence, resistance is more strongly selected as the 69 cost of resistance becomes outweighed by the detrimental effects of more severe disease, 70 leading to the more rapid evolution of resistance (10). However, at extremely levels of 71 high virulence, selection for resistance can weaken once more, due to declining infection 72 prevalence (8). Experimental tests of these predictions are, however, lacking. 73

To explore how viral virulence influences the dynamics of host resistance evolution, 74

we designed a selection experiment using the model bacterium Vibrio alginolyticus 75 K01M1 as a host and two variants of the filamentous phage, VALGΦ8, that differ in their 76 virulence but are otherwise isogenic (Table 1) . Filamentous phages (family Inoviridae)-77

i.e., long, thin proteinaceous filaments which contain a circular single-stranded DNA 78 genome-have been shown to be ideal model systems to study virulence evolution (3, 5). 79

Filamentous phages establish chronic infections whereby virions are continuously 80 released without lysis. Although filamentous phages do not kill their host, infections 81 cause harm by reducing host growth rates. This is because the host cell pays the metabolic 82 costs resulting from phage replication and from phage-encoded proteins inserted into the 83 bacterial membrane (11). Thus, virulence here is defined as the reduction in bacterial 84 growth resulting from phage infection, which can be directly quantified by measuring the 85 reduction in bacterial growth rate caused by phage infection relative to the growth rate of 86 phage-free cultures. 87

During chronic infections, most phage genes are repressed to ensure host cell 88 viability (12). This is achieved through the action of prophage encoded repressor proteins 89 whose actions also prevent superinfection (i.e., superinfection exclusion, SIE) by the 90 same (or closely related (13)) phage(s). In the case of filamentous phages, SIE immunity 91 is provided through the production of the phage-encoded receptor-binding protein pIII 92 which blocks primary and secondary phage receptors (11). Alternatively, it is possible for 93 bacteria to acquire resistance to filamentous phage infection through mutations causing 94 alterations to the surface receptors that the phages bind to, thus preventing phage infection 95 (15). 96

Combining experimental evolution with whole genome sequencing, we show that 97 SIE immunity arose rapidly and at a similar rate against both phages, whereas resistance 98 evolved more rapidly against the high compared to the low virulence phage, driving faster 99 extinction of the high virulence phage. Using an experimentally parameterised 100 mathematical model we show that accelerated replacement of SIE immunity by resistance 101 was driven by increasing costs of infection, in terms of reduced growth, suffered by SIE 102 immune hosts with increasing viral virulence. Resistance mutations were identified in 103 genes encoding the MSHA type IV pilus, which pleiotropically caused reduced motility 104 of these resistant bacteria. Together these data show that higher viral virulence accelerated 105 the evolution of resistance, which consequently drove faster virus extinctions and shorter 106 viral epidemics. 107

To explore how variation in virulence influences the dynamics of host resistance 110 evolution, we experimentally evolved the bacterium Vibrio alginolyticus K01M1 with or 111 without one of two isogenic filamentous phages that differ in their virulence-112 VALGΦ8 K04M5 which reduces bacterial growth by 73% (higher virulence) or 113 VALGΦ8 K04M1 which reduces bacterial growth by 58% (lower virulence, Table 1 )-for 114 30 serial transfers (~240 bacterial generations). We first compared the ecological 115 dynamics of bacterial and phage populations between treatments. Phages reduced 116 bacterial densities by several orders of magnitude in both phage treatments compared to 117 no phage control populations (Figure 1a ). The immediate reduction (measured 24 hours 118 post infection [hpi]) in bacterial density was greater in populations exposed to the higher 119 virulence phage (VALGΦ8 K04M5 ) than the lower virulence phage (VALGΦ8 K04M1 ; Figure  120 1a). Correspondingly, in both treatments, phages amplified massively and rapidly, 121 reaching 3.01×10 12 PFU/ml (VALGΦ8 K04M5 ) 24 hpi and 2.83×10 12 PFU/ml 122 (VALGΦ8 K04M1 ) 48 hpi (Figure 1b) , before declining to levels comparable to control 123 populations (note that the genome of V. alginolyticus K01M1 contains a resident phage, 124 VALGΦ6, that produces phage particles at a low background rate). These data suggest 125 that the strong reduction in bacterial densities at the beginning of the experiment ( Figure  126 1a) directly resulted from the costly production of viral particles (Figure 1b) . Over time, 127 however, the densities of bacterial populations exposed to the higher virulence phage 128 recovered three times faster than populations exposed to the lower virulence phage 129 (significant phage:transfer interaction in gls-model: F 15,186 =6.58, p<0.001, Figure 1a) . 130

Bacterial population recovery was accompanied by declining phage densities in both 131 treatments, but phage survival varied according to phage virulence (log-rank test: 132 Chisq 1 =4.9, p=0.03), with the higher virulence phage going extinct more rapidly than the 133 lower virulence phage (Figure 4a) . preventing phage from entering the host cell (15). To quantify the frequency of SIE 145 immunity we used PCR with primers that target specifically VALGΦ8 to test for the 146 presence of the relevant phage in the bacterial genome (the presence of a PCR product 147

suggests SIE due to the presence of VALGΦ8 and those clones are from here on denoted 148 as Φ-carriers). SIE rapidly increased in frequency and dominated bacterial populations in 149 both treatments after 24 hours ( Figure 1d ). However, after 48 hours, the proportion of SIE 150 hosts began to decline, and did so significantly faster in populations that had been exposed 

To test if the decline of SIE hosts after 24 hours was driven by the invasion of surface 167 receptor modification resistance, we used whole genome sequencing (WGS) of two 168 randomly chosen clones from each population isolated at transfer 2: one PCR-positive 169 clone (Φ-carrier; resistance through superinfection exclusion) and one PCR-negative 170 clone (resistant but not phage carrying) to identify mutations. We observed no loci with 171 mutations on chromosome 2 or the plasmid pl9064, but on chromosome 1 we identified 172 12 loci with mutations that were not present in clones from the control treatment, 173

suggesting that these were associated with phage-mediated selection. Of these 12 loci, 174 three were randomly distributed across PCR-positive and PCR-negative clones. This 175 included an intergenic region between tRNA-Val and the 23S ribosomal RNA, that has 176 been repeatedly hit in both clone-types and phage-treatments, but whose function we 177 cannot explain. The remaining nine loci were exclusive to PCR-negative clones 178 suggesting a potential role in evolved phage resistance. Of these nine loci, eight had 179 substitutions, duplications, insertions, or deletions in four different genes belonging to the 180 MSHA type IV pilus operon (mshL, mshE, mshG, K01M1_28150; Figure 2a / Table S1) . 181

Among those, three caused severe frameshift mutations that presumably have a high 182 impact on the function of these proteins. While one locus (K01M1_28150) was affected 183 twice in both phage treatments, all other loci were treatment specific with mutations in 184 mshL and mshE being exclusively found against the higher virulence phage and in mshG 185 against the lower virulence phage. Moreover, we found more mutated MSHA-loci among 186 clones exposed to the higher virulence (5/6) compared to the lower virulence phage (3/6). 187

This supports of our previous findings, which suggested a stronger selection for resistance 188 against the higher virulence virus. We found four PCR negative clones that were resistant to infections with ancestral 202 phages but did not acquire mutations within the MSHA operon or other loci that might 203 suggest a potential role in phage resistance. One explanation could be phenotypic 204 resistance, where phage adsorption to bacteria is strongly reduced (16). 205 Table S1 . simulating the infection dynamics over a wider range over virulence levels, we found 224 that this drop occurred later and was less strong with decreasing virulence. While phage 225 densities (irrespective of virulence) peaked 24 hpi, phages persisted longer and at higher 226 levels when they were less virulent ( Figure 3b ). Similar to the experiment, the model 227 predicts that SIE immunity emerges rapidly within 24 hpi ( Figure 3c ) but will only reach 228 high levels if virulence is < 1. To capture the displacement of SIE hosts by MSHA-229 mutants we implemented a cost of reduced growth for SIE hosts which is directly linked 230 to virulence (due to intracellular production of viral particles (Figure 4c )), i.e., the higher 231 the virulence of the infecting phage, the lower the growth rate of the SIE host. MSHA-232 mutants grew at the same rate as the non-resistant clones ( Figure 4e ). We found that 233

virulence (Figure 3 c,d). Our model shows that this replacement occurs across a wide 235 range of virulence levels, which we were not able to capture in the experiment. The 236 faster replacement of SIE hosts by MSHA-mutants at higher virulence levels is driven 237 by higher costs (i.e., reduced growth) of infection in SIE hosts, which increase 238 monotonically with increasing phage virulence. Overall, our simulations predict that 239 selection for resistance increases with virulence and that this is directly related to the 240 costs of SIE, and thus resistance is more likely to evolve against higher virulence 241

infections. This further suggests that to avoid extinction and enable long-term 

To directly test our model predictions, that the fitness benefit of resistance relative to 253 SIE immunity increases with increasing phage virulence, we performed a pairwise Table S3 ). 259

These fitness data are consistent with the more rapid decline of VALGΦ8 K04M5 -carriers 260 than VALGΦ8 K04M1 -carriers observed in the selection experiment and consistent with 261 model predictions suggest stronger selection for resistance when exposed to a higher 262 virulence phage. This explains the dynamics of the SIE hosts in the selection experiment, 263 which went to extinction in five out of six populations exposed to the higher virulence 264 phage 12 days post infection but were able to persist until the end of the experiment (i.e., 265 transfer 30), albeit at very low frequencies, in five out of six populations exposed to the 266 lower virulence phage. 

Bacterial population densities during the selection experiment were negatively 285 correlated with the number of SIE hosts per population (Pearson's correlation without 286 zero inflation Φ-K04M1: r=0.69, t 21 =-4.38, p<0.001, Φ-K04M5: r=0.92, t 7 =-6.29, 287 p<0.001; Figure S4 ). This implies that, even though the majority of the clones in the 288 populations were protected from further infection, bacterial populations were unable to 289 recover as long as the dominating mechanism of defence was SIE immunity, 290

presumably due to virulence, resulting from the strong reduction in bacterial growth 291 rate. To test this, we quantified differences in phage production and tested if phage 292 production impaired bacterial growth in evolved clones. VALGΦ8 K04M5 -carriers 293 produced approximately 3.5 times more phage particles than VALGΦ8 K04M1 -carriers 294 (VALGΦ8 K04M5 : mean = 2.39×10 13 PFU/ml ± 1.44×10 13 , VALGΦ8 K04M1 : mean = 295 8.92×10 12 PFU/ml ± 3.43×10 12 , Figure 4d ), and phage production significantly impaired 296 bacterial growth (significant negative correlation between the amount of produced 297 phages and bacterial growth rate, Figure 4c ). Direct comparisons of growth rates among 298 evolved clones showed that SIE hosts also grew slower than Φ-resistant mutants 299 (VALGΦ8 K04M5 : paired t-test: t 6.93 =-9.69, p<0.001; VALGΦ8 K04M1 : paired t-test: t 6.5 =-300 4.58, p=0.003, Figure 4e ). Together, these data suggest that SIE buys time, offering 301 protection against subsequent infection, but at the cost of suffering the virulence of 302 filamentous phage genomes into their own genome provides bacteria with immunity to 330 future infection-through SIE immunity mediated by phage-encoded genes-we show 331 that this comes at a fitness cost that scales positively with the virulence of the phage. 332

Higher phage virulence selects for the more rapid replacement of SIE immunity with 333 resistance, causing phage extinction (Figure 4a ). Thus, our data suggest, that to be able to 334 establish long-term chronic infections, filamentous phages must either evolve very low 335 levels of virulence (21), such that the resulting cost of virulence is outweighed by the cost 336 of resistance mutations, or they must contribute positively to bacterial fitness by providing 337 beneficial ecological functions (22). Those benefits may derive either from phage-338 encoded gene functions (e.g., toxins) (23-25), or from properties of the phage particles 339 themselves (e.g., forming the biofilm extracellular-matrix (26), or acting as decoys for 340 the vertebrate immune response (27)). Phage-mediated fitness benefits are often 341 environmentally dependent (24, 28-30) and the prevalence of filamentous phages in 342 bacterial genomes is higher in those isolated from eukaryotic infections (where 343 filamentous phages often encode important enterotoxins) than those isolated from natural 344 environments (11). Even though we have not yet identified its actual benefit, the high 345 prevalence of VALGΦ8 in natural V. alginolyticus isolates (19) suggests that this phage 346 provides a selective advantage outside the laboratory in its natural environment, i.e., the 347 pipefish. Conversely, however, bacterial genomes are graveyards of defective prophages 348 (31), including filamentous phages (32), suggesting that decay, rather than a peaceful 349 coexistence, may be a common outcome for phages integrated into bacterial genomes. 350

Ultimately, their level of virulence will dictate the fate of filamentous phages: Whereas 351 lower virulence variants may enter into stable co-existence, higher virulence variants will 352 be more prone to resistance-driven extinction and mutational decay if they do not provide 353 a selective advantage. 354

Experiments were conducted using the Vibrio alginolyticus strain K01M1 (33 The method is based on small-scale precipitation of phages by single PEG-407 precipitation. After centrifuging 1500 µl of the phage containing overnight culture at 408 13,000 ×g for 2 min, 1200 µl of the supernatant was mixed with 300 µl PEG/NaCl 5× and 409 incubated on ice for 30 min. Afterwards phage particles were pelleted by two rounds of 410 centrifugation at 13,000 ×g for 2 min, resuspended in 120 µl TBS 1× and incubated on 411 ice. After one hour the suspension was cleaned by centrifugation at 13,000 ×g for 1 min 412 and absorbance was measured at 269 and 320 nm. 413

Quantification of filamentous phages using spectrometry is likely to be erroneous if 414 viral load is low. Therefore, we additionally quantified phage prevalence/ phage 415 extinction in each of the populations on every second transfer day by standard spot assays 416 with a serial dilution (up to 10 -6 ) on the ancestral host (for details see (14) To determine differences in fitness between both resistance forms, we measured the 459 competitive fitness of three randomly selected Φ-carrier relative to three randomly 460 selected Φ-resistant mutants from each treatment. Each competition culture was done in 461 triplicates as described in (37). In brief, overnight cultures of both competing strains (of 462 which one was labelled with a GFP-marker) were mixed 1:1 and 60 µl of this mixture 463 was inoculated to 6 ml Medium 101 to initiate each competitive culture. After 24 hours, To determine fitness parameters that could explain observed differences in competitive 472 fitness we additionally quantified bacterial growth rate (µ) by means of 24-hour growth 473 curves and phage production using PEG precipitation (as described in (c)) of the same 474 clones used for the competition assays (i.e., one Φ-carrier and one Φ-resistant mutant 475 from each phage-treated population and two random phage-susceptible clones from the 476 control populations plus ancestors). 477 478 (g) Motility 479

Motility was visualized on mid-exponential growth cultures using a light 480 microscope and swimming was captured for 50s. per strain (coverage range was from 88× to 157×). The reads were quality controlled using 516 the program FastQC Version 0.11.5. All illumina reads that passed the FastQC filtering 517

were used for hybrid assemblies as well as for single nucleotide variation analysis. 518

Genome assemblies were performed in two different ways: (i) long-read data was 519 generated for all replicates where the presence of the infecting phage was confirmed by 520 PCR. The Assemblies were performed as hybrid assemblies using short-read and long 521 read data in a short-read first approach. In brief: An initial assembly was performed with 522

short-read only using spades (v3.13.0) as provided within Unicycler (39). The resulting 523 contigs were co-assembled with long-read data using miniasm (v0.2-r168) (40) and 524 curated using the racon software (41). This step resulted in complete closed replicons. All 525 long reads were mapped and integrated into the contigs. All replicons were polished using 526 Pilon (v1.22) to clear any small-scale assembly errors (42). Finally, all replicons were 527 rearranged according to the origin of replication. (ii) the assembly for the ancestral 528 K01M1 strain, as has been described in (14) being chosen to be error-corrected with "shorter" long reads in a process named 534

preassembly. Hereby, a length cut-off is computed automatically separating the "longer" 535 reads (for genome assembly) and the "shorter" reads (for error-correction). The level of 536 error-correction is being estimated with a per-read accuracy of 99%. Finally, error-537 corrected long read data is being assembled with Celera Assembler (v7.0) (44). 538 539 (i) SNV analysis and reconstruction of infecting phages 540

All short-read sequences were mapped on a high quality closed reference genome of 541 Vibrio alginolyticus Strain K01M1 (14) using Bowtie2 (45). Single nucleotide variation 542 (SNV) analysis was done using the Breseq pipeline as described in (46) analysis aimed to compare the two different phage treatments to one another, control 554 populations (i.e., those that evolved without phages) were excluded. When comparing 555 temporal dynamics between phage-treatments, we excluded the starting time-point T0, 556 because these measurements were taken before phages were added to the populations. 557 558

Bacterial and phage densities were analysed over time using a generalized least 560 squares model to control for autocorrelation of residuals over time using the gls function 561 (package nlme) with phage treatment, transfer as categorical variable as well as their 562 interaction as fixed effect. 563

We considered phages to be prevalent in the population if opaque zones of reduced 564 growth were visible during standard spot assays. Phage prevalence was subsequently 565 quantified by a serial dilution, which were assigned with invers values (i.e., if reduced 566 growth zones were visible up to dilution of 10 -6 we assigned to it a value of 7, whereas if 567 they were only visible on an undiluted spot, we assigned to it a value of 1, if no zone of 568 reduced growth was visible it was scored as 0). Phage extinction events across phage-569 treatments were analysed using a log-rank test. 570 571

We observed a bimodal histogram on all RBG values with a local minimum at RBG 573 = 0.82 ( Figure S2 ). Thus, we considered an infection as positive if RBG < 0.82. The 574

proportion of clones per population that could not get infected by the ancestral phage as 575 well as the proportion of clones that tested positive for PCR (targeting the VALGΦ8) 576

were analysed using a generalized linear model with a binomial error distribution using 577 the glm function (package lme4) with phage treatment, transfer and their interaction as 578 fixed effect. 579 580

We determined differences in relative fitness between MSHA-mutants and SIE hosts 582 using a linear model with resistance mechanisms and GFP-label and the interaction 583 thereof as fixed effects. Maximum growth rates (µ) were estimated for each strain by 584 fitting generalized logistic models to individual growth curves using the open-source 585 software package Curveball (https://github.com/yoavram/curveball) (50) in python. To 586 determine differences in the amount of free phages and in growth rates produced 587 between ancestral strains and evolved strains and between both resistance forms, we 588 used Welch's pairwise t-tests with sequential Bonferroni correction. We further 589 performed a Pearson's correlation analysis to determine whether phage production 590 impacted bacterial growth rates. determines whether maximum growth is attained at an early point in the growth phase 608 (w < 1) or at a late point (w > 1). We assume that SIE hosts (I and IR) suffer a growth 609 rate reduction relative to the non-resistant evolved bacteria due to virulence caused by MSHA type IV pilus operon. We assume that MSHA-mutants have the same growth 620 rate as the non-resistant evolved bacteria. 621

All bacterial types grow until the carrying capacity (K) is reached, but bacteria-virus 622 interactions continue to occur as long as there are sensitive bacteria and viruses left. 623 After a certain time tmax a portion (here 1/1000th) of the entire community is transferred 624 to fresh medium and the process restarts. 625 626 Data availability: All experimental data have been deposited on dryad (a link will be 637 provided upon acceptance of the manuscript). Genomic data is available at NCBI 638 (accession number will be provided upon acceptance of the manuscript), and in the 639 supplemental data file Table S1 and S2. 640 641

A comparison of the virulence for European rabbits 644 (Oryctolagus cuniculus) of strains of myxoma virus

Virulence evolution in a virus obeys 649 a trade-off

Tradeoff between Horizontal

Vertical Modes of Transmission in Bacterial Plasmids

Selection of Benevolence in a Host-Parasite 654

Population structure and the evolution of virulence in nematode 656 parasites of fig wasps

Virulence and Local Adaptation of a Horizontally Transmitted 658 Parasite

The Evolution of Costly Resistance in Host-Parasite 660

Shared control of epidemiological traits in a 662 coevolutionary model of host-parasite interactions

Coevolution of recovery ability and virulence

Big things in small packages: the genetics of 666 filamentous phage and effects on fitness of their host'

Beneficial Effects of Prophages on Bacterial Fitness

Within-host competition determines reproductive success of 672 temperate bacteriophages

Tripartite species interaction: eukaryotic hosts suffer more 674 from phage susceptible than from phage resistant bacteria

The Vibrio cholerae mannose-sensitive hemagglutinin is 677 the receptor for a filamentous bacteriophage from V. cholerae O139

Phenotypic 680 resistance and the dynamics of bacterial escape from phage control

Virulence reduction in bacteriophage resistant bacteria. 683 Front Microbiol

Pili in Gram-negative and Gram-positive bacteria -685 structure, assembly and their role in disease

Closely 688 Related Vibrio alginolyticus Strains Encode an Identical Repertoire of 689

Caudovirales-Like Regions and Filamentous Phages

Cryptic inoviruses revealed as pervasive in bacteria and archaea 691 across Earth's biomes

The "steady state" of coliphage f1: DNA synthesis late in 693 infection

Filamentous phages: masters of a microbial sharing 695 economy

Lysogenic conversion by a filamentous phage 697 encoding cholera toxin

Conserved 699 filamentous prophage in Escherichia coli O18:K1:H7 and Yersinia pestis biovar 700 orientalis

The biofilm life cycle and virulence of Pseudomonas aeruginosa 702 are dependent on a filamentous prophage

Filamentous Bacteriophage Promote Biofilm Assembly and 704 Function

Bacteriophage trigger antiviral immunity and prevent 706 clearance of bacterial infection

Fitness benefits to bacteria of carrying 708 prophages and prophage-encoded antibiotic-resistance genes peak in different 709 environments

Insights into the 711 infective properties of Ypf Phi, the Yersinia pestis filamentous phage

A horizontally acquired filamentous phage contributes to the 714 pathogenicity of the plague bacillus

Pervasive domestication of defective 716 prophages by bacteria

CTX prophages in 718 classical biotype Vibrio cholerae: functional phage genes but dysfunctional 719 phage genomes

Genomic variation 721 among closely related Vibrio alginolyticus strains is located on mobile genetic 722 elements

The structure of temperate phage-bacteria 724 infection networks changes with the phylogenetic distance of the host bacteria

The 727 evolution of specificity in evolving and coevolving antagonistic interactions 728 between a bacteria and its phage

Filamentous phages reduce bacterial 730 growth in low salinities

Parallel 732 Compensatory Evolution Stabilizes Plasmids across the Parasitism-Mutualism 733 Continuum

Long-Term Experimental 735 Evolution in Escherichia-Coli .1. Adaptation and Divergence during 2,000 736 Generations

SPAdes: a new genome assembly algorithm and its 738 applications to single-cell sequencing

Minimap and miniasm: fast mapping and de novo assembly for noisy long 740 sequences

Fast and accurate de novo genome 742 assembly from long uncorrected reads

Pilon: an integrated tool for comprehensive microbial variant 744 detection and genome assembly improvement

Nonhybrid, finished microbial genome assemblies from long-746 read SMRT sequencing data

Consensus generation and variant detection by Celera 748

Fast gapped-read alignment with Bowtie 2

Identification of mutations in laboratory-evolved 752 microbes from next-generation sequencing data using breseq

progressiveMauve: multiple genome 755 alignment with gene gain, loss and rearrangement

Easyfig: a genome comparison 757 visualizer

R: A language and environment for statistical computing. R 759 Foundation for Statistical Computing

Predicting microbial growth in a mixed culture from growth curve 763 data

We thank Pratheeba Pandiaraj, Katja Trübenbach, Veronique 629