Evolutionary outcomes of plasmid-CRISPR conflicts in an opportunistic pathogen interactions of CRISPR-Cas systems and naturally occurring resistance plasmids percent mapped reads for mutant alleles

The persistence of antibiotic resistance plasmids in pathogens is a global health 13 concern. Plasmid persistence results from host-plasmid co-evolution that enhances 14 plasmid stability, where the role of CRISPR-Cas is not well understood. Enterococcus 15 faecalis is an opportunistic pathogen that disseminates antibiotic resistance via 16 conjugative plasmids. Some E. faecalis possess CRISPR-Cas that limit acquisition of 17 resistance plasmids; however, transconjugants arise despite CRISPR-Cas activity. We 18 utilized in vitro evolution to investigate how the conflict between CRISPR-Cas and 19 plasmid targets is resolved. We observed a cost to maintain both the plasmid and 20 functional CRISPR-Cas. Under antibiotic selection, heterogeneous populations with 21 compromised CRISPR-Cas emerged, which benefited acquisition of other plasmids. 22 Using targeted sequencing, we demonstrate RecA-independent allelic heterogeneity 23 provides an evolutionary basis for the emergence of compromised CRISPR-Cas. 24 Overall, antibiotic selection for plasmids targeted by CRISPR-Cas results in host 25 mutations that stabilize plasmid maintenance and reduce the barrier to future horizontal 26 gene transfer events. of its targets. These transconjugants present a unique opportunity to study the role of 81 CRISPR-Cas systems in plasmid-host interactions. In this study, we used a combination of in vitro evolution and deep sequencing analysis to investigate how E. faecalis resolves 83 conflicts between CRISPR-Cas and antibiotic resistance plasmids, and the role that antibiotic selection plays in this process. We conclude that antibiotic-driven PRP 85 maintenance in E. faecalis can lead to compromised genome defense and enhanced 86 susceptibility to other MGEs, ultimately transforming these strains into reservoirs for 87 antibiotic resistance and other virulence traits. These findings demonstrate that 88 antibiotics can alter pathogen evolution by accelerating the host-adaptation process that 89 results in antibiotic resistance plasmid persistence.

results showed that, for transconjugant populations where CRISPR array reduction was 183 observed, S 6 was either deleted from the array or had low sequencing quality (Table 2).
Low Sanger sequencing quality likely resulted from mixed populations with different deletion events arising stochastically, resulting in S 6 deletion. In contrast to the WT 186 populations, CRISPR3 arrays for the T11RF Δcas9 pAM714 transconjugants were 187 unchanged (Fig 3c and Table 2). We chose the Δ4 population as a representative of the

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The WT1 population is discussed further here. PCR analysis of transconjugant WT1 197 indicated that the wild-type CRISPR3 allele was present after 14 days of passage with 198 erythromycin (Fig 3c). However, Sanger sequencing detected a mixed population in the 199 region of S 6 and S 7 after passage day 1, which was not detected after passage day 14 200 (Table 2). Therefore, a S 6 deletion arose during the passage experiment but did not  Table 2). We observed variation in cas9 sequence in the 207 WT1, WT2, and WT3 populations ( Table 3). All of the mutations led to nonsynonymous 208 changes and are predicted to result in Cas9 loss of function (Table 3). In addition to cas9 209 mutations, we observed variation in six other genes in some of the populations

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We then expanded this analysis to the T11RF pAM714 transconjugants, excepting WT4.

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As expected, depletion of S 6 was detected for WT2, WT3, WT5, and WT6 populations 226 after 14 days of passage with antibiotic selection (Fig 4d-g). For WT3, WT5, and WT6 227 populations, S 6 depletion was evident after one day of passage with selection (Fig 4e-g).

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For WT1, depletion of S 6 was not detected after 14 days passage with selection (Fig 4c), 229 consistent with our Sanger sequencing results (Table 2).

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To identify specific mutant CRISPR alleles in the amplicon deep sequencing, we 232 manually constructed artificial CRISPR reference sequences for every possible spacer 233 deletion event (see Materials and Methods for more information). In total, 484 references 234 were constructed, where wild type CRISPR alleles were represented by the wild type 235 references: 5'-S x RS (x+1) -3' (0 ≤ x <21) and 5'-S 21 TRS T -3'. Mutant alleles were represented by 5'-S x RS y -3' (y ≠ x+1). For control T11RF passaged for 1 or 14 days in 237 plain BHI medium, all but 28 (day 1) and 4 (day 14) alleles out of 484 possible alleles 238 were detected. We conclude that CRISPR3 heterogeneity naturally occurs in T11RF 239 populations, possibly as a result of slippage during DNA replication and/or recombination 240 between CRISPR repeat sequences. This is consistent with previous research that

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We observed slightly higher forward spacer deletion rates than backward spacer 266 rearrangement rates for leader end spacers in Day 1 and Day 14 BHI-passaged T11RF,

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suggesting that spacers at the leader end are more readily deleted than flipped (Fig 6a).

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The forward deletion and backward rearrangement rates are similar at spacers S 9 -S 15 for  observed for spacers upstream of S 6 , indicating a positional preference for forward 287 deletion events upstream of S 6 . We speculate that this is because internal spacer deletions upstream of S 6 provide a selective advantage under these conditions. Finally, 289 we did not observe significant fluctuation of backward rearrangements in erythromycin-290 passaged transconjugants (Fig 6 c-   to BHI-passaged T11RF for all pCF10 plasmids (Fig 7). This was expected because the CRISPR-Cas activity against all CRISPR3 targets. In contrast, Day 14 erythromycin-327 passaged WT5 exhibited defense only against pCF10 bearing a target for S 1 (Fig 7). This is 328 consistent with the amplicon analysis that identified multiple CRISPR3 alleles with deletions 329 of S 6 and S 7 in the erythromycin-passaged WT5 population (Table 2).

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We also tested the WT4 transconjugant populations for CRISPR-Cas activity. We detected a 332 mutation within the RuvC catalytic domain coding region of cas9 in WT4 after passage day 333 1, and WT4 failed to deplete pAM714 when passaged without erythromycin selection (Fig   334   3a). We expected both the BHI-and erythromycin-passaged populations of WT4 to be 335 completely deficient for CRISPR-Cas activity if the observed mutation conferred loss of 336 Cas9 function. CRISPR-Cas activity against S 1 , S 6 , and S 7 targets was in fact absent in We observed that the transfer frequencies of pCF10 and its derivatives were higher for all Spacer deletion is not exclusively RecA-dependent. Under antibiotic selection, the 344 T11RF transconjugants lost S 6 to resolve the conflict between CRISPR-Cas and its 345 target. The loss of S 6 was often coupled with the loss of surrounding spacers, ranging 346 from S 1 to S 18 ( Table 2). The rearrangements associated with shortened CRISPR3-Cas 347 arrays occurred between repeat-spacer junctions leaving behind perfectly intact repeat- Type II CRISPR-Cas system, CRISPR1-Cas, that is related to but distinct from possesses the orphan CRISPR2 array (Fig 1). Previous research demonstrated that the 370 T11RF CRISPR2 array is active for genome defense in the presence of CRISPR1 cas9 371 (37). We interpret this to mean that the orphan CRISPR2 locus can be used as a native 372 genome defense system in E. faecalis OG1RF, due to the presence of endogenous 373 CRISPR1-Cas which was recently demonstrated to provide genome defense (45).

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We utilized the shuttle vector pLZ12, which confers chloramphenicol resistance, as a 376 backbone for the generation of artificial OG1RF CRISPR1-Cas and CRISPR2 377 protospacer targets (Table 1). The pKH12 plasmid does not natively contain a 378 protospacer that would be targeted by either CRISPR1-Cas or CRISPR2 spacers (45).

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pKHS96 is a pKH12 derivative with an engineered CRISPR1-Cas protospacer that is 380 targeted by OG1RF CRISPR1-Cas S 4 . pKHS5 is a pKH12 derivative with an engineered 381 CRISPR2 protospacer that is targeted by OG1RF CRISPR2 S 6 The consensus PAM 382 sequence for both CRISPR1-Cas and CRISPR2 is NGG (37) and was included adjacent 383 to the engineered protospacers. pKH12, pKHS96 and pKHS5 were each transformed 384 into electrocompetent OG1RF. Twenty random transformants for each plasmid were 385 selected as templates for PCR to determine the initial integrity of the CRISPR1-Cas and 386 CRISPR2 arrays using Sanger sequencing. We determined that the CRISPR1-Cas and was transformed.
We randomly selected three transformants for each plasmid to be used for in vitro 391 evolution experiments. Each transformant was passaged in plain BHI medium and BHI 392 medium supplemented with chloramphenicol for a period of 14 days. Similar to our 393 observations for T11RF pAM714 transconjugants, we observed loss of pKHS5 and 394 pKHS96 over the course of passaging without antibiotic selection (Fig 9a). The interactions of CRISPR-Cas systems and naturally occurring resistance plasmids 417 are poorly understood, as is the impact of selection (in this case, strong antibiotic 418 selection) on these evolutionary interactions. This is of particular concern in the 419 opportunistic pathogen E. faecalis due to its propensity to engage in intra-and

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Our results demonstrate that recA is not required for CRISPR compromisation by spacer 434 deletion. However, the fact that we observed flipped spacers, where x > y in 5'-S x RS y -3',

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indicates that homologous recombination likely does play a role. It is likely that both 436 mechanisms contribute to the emergence of heterogeneous CRISPR alleles. We do not 437 have an estimate of which process has a greater effect, nor whether additional stresses 438 beyond antibiotic selection could influence rates for each. Moreover, we do not know heterogeneity could alter outcomes of these conflicts.

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This study also concluded that the ability of a MGE to escape CRISPR-Cas defense was 451 dependent on the existence of pre-existing CRISPR mutants in recipient populations.

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This is in contrast to our results, where functional CRISPR-Cas and its plasmid target 453 can co-exist in conflict in E. faecalis cells, although over time, this conflict is resolved by 454 either plasmid loss or the emergence of mutants with compromised CRISPR-Cas.

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Our studies utilized pAM714, which encodes a toxin-antitoxin system (53-55). The 457 system encodes a stable toxin that will kill daughter cells that have not inherited a 458 plasmid copy; an unstable antitoxin is encoded from the same locus that blocks toxin 459 translation in cells with proper plasmid segregation. However, in our study, we observed

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The annealed oligos were ligated into the pLT06 derivative pWH107 that includes 504 sequence from pCF10 uvrB, to insert these sequences into the uvrB gene of pCF10 by 505 homologous recombination. A knock-in protocol was performed as previously described

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The stringent mapping conditions require 100% of each mapped read to have ≥95% 568 identity to the reference. The percent mapped reads were calculated by dividing the 569 number of reads mapped by the total number of reads, these percentages are listed in PCR amplicon region using CLC Genomics Workbench, normalized using reads per 572 million, and plotted against reference positions (Fig 4).

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To further analyze CRISPR3 spacer deletions and rearrangements, we manually created  (Fig 1a). The 5'-585 S 21 TRS T -3' reference represents the wild-type. In total, 484 references with length of 96 586 bp were generated for the CRISPR3 amplicon. Considering that the read length is 150 587 bp, we manually split each read into two subsequences (one subsequence was 75 bp; 588 with the remainder of the read being the second subsequence) to enhance mapping 589 efficiency, allowing for retrieval of maximal sequence information. The split amplicon 590 sequencing reads were mapped to the 5'-SxRSy-3' and 5'-SxTRS T -3' references using 591 stringent mapping parameters in CLC Genomics Workbench (Qiagen). The stringent 592 mapping parameters require 100% of each mapped read to be ≥95% identical to one 593 unique reference. Thus, the sequencing reads from different CRISPR alleles will be 594 distinguished. These amplicon mapping results were applied to the calculation of forward 595 spacer deletion and backward spacer rearrangement rates.
To further evaluate the mapping efficiency, the unmapped reads from initial mapping to the T11 CRISPR3 reference (STable3, step 1) were subjected to additional quality 599 control analysis. The unmapped reads were mapped to the 484 manually created   where n is the total number of spacers within a CRISPR array, hence S n represents 623 terminal spacer, as described above (Fig 1a).

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The following source data is available for Figure 4:

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The percent mapped reads to mutant alleles (dots) are shown here with average (thick red 899 bar) and standard deviation (thin red bar). A detection cutoff value was applied so that 900 mutant alleles with high abundances can be detected.

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The following source data is available for Figure 5:

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The following source data is available for Figure 6:

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The following source data is available for