Abstract
Enterococcus faecalis is a Gram-positive bacterium that natively colonizes the human gastrointestinal tract and opportunistically causes life-threatening infections. Multidrug-resistant (MDR) E. faecalis strains have emerged that are replete with mobile genetic elements (MGEs). Some E. faecalis strains possesses CRISPR-Cas systems, which reduce the conjugation frequency of pheromone-responsive plasmids. However, many transconjugants still arise, and we have demonstrated in previous studies that E. faecalis can transiently maintain both a functional CRISPR-Cas system and a CRISPR-Cas target. In this study, we used serial passage and deep sequencing to analyze CRISPR array dynamics over time in transconjugants which possess both a functional CRISPR-Cas system and a CRISPR-Cas target. In the presence of antibiotic selection for the plasmid, we found that plasmids ultimately escape CRISPR defense via the emergence of compromised CRISPR-Cas defense in host populations. As a consequence, these populations have enhanced abilities to acquire a second antibiotic resistance plasmid. In the absence of antibiotic selection, plasmids are lost from wild-type but not Δcas9 host populations over time. We conclude that the adaptive immune system of E. faecalis becomes compromised under antibiotic selection for MGEs, generating populations with enhanced abilities to undergo horizontal gene transfer.
Importance Enterococcus faecalis is a leading cause of hospital-acquired infections and known disseminator of drug resistance among Gram-positive bacteria. One of the main means of antibiotic resistance dissemination among E. faecalis populations is mediated by plasmids. We have previously shown that strains with an active CRISPR-Cas system can reduce plasmid acquisition and thus limit the transmission of antibiotic resistance determinants. In this study, we observed subpopulations with transient co-existence of active CRISPR-Cas and a plasmid target. Through serial passage and targeted sequencing analysis on these populations, we demonstrate that antibiotic treatment plays a key role in shaping the E. faecalis genome, resulting in compromised genome defense that facilitates acquisition of other resistance plasmids. These results are significant because they show how antibiotic selection for a plasmid can alter the evolutionary trajectory of E. faecalis populations rendering them vulnerable to the acceptance of multiple resistance plasmids.
Introduction
Enterococcus faecalis is a Gram-positive bacterium that normally colonizes the gastrointestinal tracts of humans and other animals (1). E. faecalis is also an opportunistic pathogen that can cause life-threatening antibiotic-resistant infections in hospitalized patients (2–4). Some E. faecalis strains have acquired antibiotic resistance through horizontal gene transfer (HGT), mediated primarily by plasmids and integrative conjugative elements (5–7). One of the most clinically relevant forms of HGT in E. faecalis is afforded through the pheromone-responsive plasmids (PRPs). The PRPs are narrow host range conjugative plasmids that disseminate antibiotic resistance and virulence genes among E. faecalis populations (5, 8–10). PRPs can also mobilize resistance genes to other clinically relevant bacterial pathogens (2, 11–14).
CRISPR-Cas systems provide prokaryotes with heritable sequence-specific genome defense against mobile genetic elements (MGEs) including plasmids and phage (15, 16). The structure and classification of these systems was reviewed recently (17). CRISPR-Cas systems consist of cas genes and a CRISPR array composed of spacers interspersed by direct and partially palindromic repeats (18, 19). Where sequence matches can be identified, the spacers generally have identity to MGEs of phage or plasmid origin (20). Some E. faecalis strains encode Type II CRISPR-Cas systems (21, 22) characterized by the Cas9 endonuclease, which cleaves DNA targets in a sequence-specific manner (23–25). Type II CRISPR-Cas defense is afforded in three stages. During adaptation, a Cas-protein complex, including Cas9, recognizes a protospacer from a newly encountered MGE in a PAM (Protospacer Adjacent Motif)-dependent manner, after which the protospacer is incorporated into the leader end of the CRISPR array (26–28). During expression, the CRISPR array is transcribed into pre-crRNA that is then then processed by the endonuclease RNase III in concert with Cas9 and tracrRNA (trans-activating crRNA), generating mature crRNAs (29). A mature crRNA bound by Cas9 and tracrRNA is an active targeting complex. When the bacterial host is invaded by a MGE that has complementarity to a crRNA, the targeting complex recognizes the MGE in a PAM-dependent manner and creates a double-stranded DNA break to prevent MGE invasion (30, 31).
We reported in a previous study that Type II CRISPR-Cas systems with spacers targeting PRPs can reduce PRP dissemination in E. faecalis colony biofilms by ~80-fold (32). However, PRP transconjugants were still observed at high densities (~105 cfu/mL) in these mating experiments. In contrast, in several other bacterial species, no or few transconjugants were observed when CRISPR-Cas defense in recipient cells targeted the conjugative element (16, 33–35). Some of these studies sequenced the CRISPR-Cas loci of the CRISPR-escaping transconjugants, determining that the transconjugants possessed mutations that compromised or inactivated CRISPR-Cas defense (33, 34). Deletions of CRISPR spacers were commonly observed, as well as mutations in cas genes (34, 36). These studies concluded that conjugation occurred into recipient cells that had pre-existing mutations in CRISPR-Cas (33, 34). Similar observations have been made for CRISPR-escape mutants obtained in plasmid transformation experiments (37, 38). Collectively, these studies are consistent with the inability of cells to concomitantly maintain both a functional CRISPR-Cas system and a target of the CRISPR-Cas system. However, in recent studies from our lab using engineered shuttle plasmids mobilized by a PRP, we determined that multidrug-resistant E. faecalis can transiently tolerate both CRISPR systems and their plasmid targets, albeit at a fitness cost (reduced growth rate), and that selection can determine the outcome of these conflicts (39). Specifically, CRISPR spacer deletion mutants emerged over time when antibiotic selection for the plasmid was present, and plasmids were lost when selection was absent (39). Similar observations of transient tolerance of CRISPR/target co-maintenance have been made in Pseudomonas aueruginosa and Listeria monocytogenes (40, 41).
In the present study, we further investigated how antibiotic selection impacts CRISPR-Cas systems and their targets in E. faecalis, specifically investigating PRP transconjugants using serial passage and deep sequencing experiments. Overall, our data provide evidence that antibiotic-selected PRP maintenance in E. faecalis can lead to compromised CRISPR-Cas defense and enhanced abilities to acquire other MGEs.
Results
Design of serial passage experiments
E. faecalis T11RF possesses a Type II CRISPR-Cas system, CRISPR3-Cas, that has 21 unique spacers (Fig S1) (32). Spacer 6 has 100% sequence identity to the repB gene of the model PRP pAD1 (42, 43), a well-characterized PRP that encodes a haemolytic bacteriocin, cytolysin; the virulence factor aggregation substance; and the toxin-antitoxin system par (8, 44). Previous research from our lab demonstrated that CRISPR3-Cas of T11RF significantly reduces the conjugation frequency of pAM714, a derivative of pAD1 conferring erythromycin resistance via ermB on Tn917 (32). However, despite the activity of CRISPR3-Cas, a large number (~105) of presumptive T11RF(pAM714) transconjugants were obtained from these conjugation reactions. We set out to analyze these transconjugants further.
Conjugation reactions between E. faecalis OG1SSp(pAM714) donors and T11RF recipients were performed for 18 hours on agar plates without erythromycin selection as previously described (32). Biofilms were then scraped from the plates, resuspended and diluted, and plated on agar selective for donors, recipients, and transconjugants. Conjugation frequencies from these assays were previously reported (32). Colonies arising on transconjugant selection agar were used for this study (Fig 1a). We randomly selected transconjugant colonies from two mating schemes, T11RF(pAM714) and T11RFΔcas9(pAM714); the Δcas9 strain possesses no CRISPR3-Cas activity through an in-frame deletion of the cas9 coding region (32). We performed serial passage on a total of six T11RF(pAM714) transconjugants (referred to as WT1-WT6) and six T11RFΔcas9(pAM714) transconjugants (referred to as Δ1-Δ6) that were derived from two independent conjugation experiments. The transconjugant colonies were each resuspended in brain heart infusion (BHI) broth, and the percentage of erythromycin-resistant cells and the size and Sanger sequence of the CRISPR3 amplicon was determined for each (Fig S2; these data are discussed below). These data are referred to as “Day 0.” Next, the colony resuspensions were split equally into BHI medium and BHI medium with erythromycin. These populations were then passaged daily over a period of 14 days. Every 24 h during the course of the passage, the percentage of erythromycin-resistant cells relative to the total viable population and the size and Sanger sequence of the CRISPR3 amplicon were determined.
At Day 0, erythromycin resistance was detected in both the T11RF(pAM714) and T11RFΔcas9(pAM714) transconjugant populations, with the T11RF(pAM714) colonies having overall less erythromycin-resistant cells, indicative of active CRISPR defense (Fig S2a). The CRISPR3 arrays of all transconjugants analyzed were of wild-type size based on PCR (Fig S2b) and Sanger sequencing analysis.
Erythromycin resistance is eliminated by WT but not Δcas9 transconjugants during passage in non-selective medium
For serial passages in the absence of erythromycin, a gradual decrease in the frequency of erythromycin-resistant cells was observed for five of the six WT transconjugants (Fig 1b). In contrast, erythromycin resistance was stably maintained at high frequencies in all of the T11RFΔcas9(pAM714) transconjugant populations (Fig 1b). CRISPR3 array size remained wild-type over the course of serial passage for both T11RF(pAM714) and T11RFΔcas9(pAM714) transconjugant populations (Fig 1d and Fig S3).
The WT4 population did not exhibit erythromycin resistance loss in the absence of antibiotic selection. We Sanger-sequenced the cas9 coding region of the WT4 population at Day 0 and after 1 day of passage in the presence of erythromycin and identified a mutation resulting in an Ala749Thr substitution. Ala749 occurs within the RuvC nuclease domain in T11RF Cas9 and is conserved in the model Streptococcus pyogenes Cas9 (32). Due to the critical catalytic function of the RuvC domain, we hypothesize that the Ala749Thr substitution confers a loss of Cas9 function. We tested the ability of the BHI- and erythromycin-passaged WT4 populations to interfere with plasmid transfer using derivatives of the PRP, pCF10 (45), that are targeted by CRISPR3 spacers 1, 6, and 7. These experiments revealed that the Ala749 mutation indeed renders these populations deficient for CRISPR-Cas activity (Fig 2).
Under continuous antibiotic selection, CRISPR-Cas mutants emerge over time in WT transconjugant populations
When the transconjugant populations were serially passaged in the presence of erythromycin, we observed stable maintenance of erythromycin resistance in both WT and Δcas9 transconjugants (Fig 1c). We amplified the CRISPR3 region of erythromycin-passaged transconjugants and observed significant heterogeneity in the CRISPR3 array for WT transconjugant populations. By Day 14, four of the six T11RF(pAM714) transconjugant lineages had visibly reduced CRISPR3 arrays (Fig 1d). The variation in array size initiated sporadically over the 14 days and each transconjugant had a unique pattern (SFig 3). Sanger sequencing of the CRISPR3 array from Day 1 and Day 14 erythromycin-passaged populations revealed that S6 was either deleted from the array or had low sequencing quality (Table 2). In contrast to WT populations, CRISPR3 arrays for the T11RFΔcas9(pAM714) transconjugants were unchanged (Fig 1d and Table 2). We chose the Δ4 population as a representative of the T11RFΔcas9(pAM714) transconjugant populations for future analyses.
To investigate the possibility of mutations within cas genes, we performed whole genome Illumina sequencing on five Day 14 erythromycin-passaged T11RF(pAM714) transconjugant populations and a control population, Δ4. We observed variation in the cas9 sequence of the WT1, WT2, and WT3 populations (Table 3). All of the mutations led to nonsynonymous changes and are predicted to result in a loss of function in Cas9 (Table 3). In addition to cas9 mutations, some of the populations possessed variation in one or more genes, none of which are predicted to have an impact on the phenotypes observed in our study (STable2). No mutations were identified in the S6 protospacer or PAM region of the repB gene in pAM714. However, we did identify a mutation within repB, not associated with the protospacer or PAM, in the WT2 population (STable2). The sequencing also allowed us to investigate the possibility of Tn917 transposition into the T11RF chromosome. We observed no evidence of Tn917 hopping into the T11 chromosome as all reads overlapping the ends of Tn917 also overlapped the pAD1 reference sequence.
Reduced tolerance of S6 in T11RF(pAM714) transconjugant populations
To attain greater resolution of CRISPR3 alleles present in our transconjugant populations, we used Illumina sequencing to sequence CRISPR3 amplicons from populations of interest. Using this method, we attained an average of 16 million reads for our amplicons (STable3). We first mapped CRISPR3 amplicon reads to the T11 reference sequence and calculated coverage depth to analyze mapping efficiency for BHI-passaged T11RF (lacking pAM714) (Fig. 3a) and the Δ4 transconjugant population passaged in erythromycin (Fig. 3b) as controls. We then expanded this analysis to the T11RF(pAM714) transconjugants. As expected, depletion of S6 was detected in WT2, WT3, WT5, and WT6 populations after 14 days of passage with antibiotic selection (Fig 3d-g). For WT3, WT5, and WT6 populations, S6 depletion was evident after one day of passage with selection (Fig 3e-g). For WT1, depletion of S6 was not detected after 14 days passage with selection (Fig 3c), consistent with our Sanger sequencing results (Table 2).
To identify specific mutant CRISPR3 alleles in the amplicon sequencing, we manually constructed artificial CRISPR3 reference sequences for every possible spacer deletion event (see Materials and Methods for more information). Each artificial reference is 96 bp in length and contains two spacers connected by a T11 CRISPR3-Cas direct repeat: 5’-spacer[x]-repeat-spacer[y]-3’ (5’-SxRSy-3’), where spacer[x] and spacer[y] could be 30 bp upstream of the first repeat (leader end; or S0 hereafter; see Fig S1a), or any internal spacer within the CRISPR3 array (from spacer 1 to spacer 21; or S1 to S21; Fig S1a). The terminal repeat following S21 in the CRISPR3 array is divergent from the direct repeat sequence, so references containing 5’-spacer[x]-TerminalRepeat-ST-3’ (5’-SxTRST-3’) were constructed, where spacer[x] ranges from S0 to S21 and spacer ST represents the sequence 30 bp downstream of the terminal repeat (Fig S1a). In total, 484 references were constructed. Wild-type CRISPR3 alleles were represented by the reference sequences where 5’-SxRS(x+1)-3’ (0 ≤ x <21) and 5’-S21TRST-3’ and mutant alleles were represented by 5’-SxRSy-3’ (y ≠ x+1). For the control population, which was BHI-passaged T11RF lacking pAM714, all but 28 (Day 1) and 4 (Day 14) of the 484 possible alleles were represented in our amplicon reads. We resolved the most abundant mutant CRISPR3 alleles in transconjugant populations by mapping amplicon reads to wild-type and mutant CRISPR3 references (Fig 4). Of the five T11RF transconjugant populations analyzed, all other than WT1 possessed at least one mutant CRISPR3 allele after 14 days of passage with antibiotic selection, and each of those alleles lacked S6 (Table 2).
We tested the ability of the Day 14 WT5 population to prevent the acquisition of pCF10 and pCF10 derivatives that are targeted by CRISPR3 spacers 1, 6 and 7. Based on deep sequencing data (Table 2), we expected that the WT5 population would interfere with transfer of pCF10 bearing spacer 1, but not pCF10 bearing spacers 6 or 7. Compared to the BHI-passaged WT5 population that significantly reduced the acquisition of each of the pCF10 derivatives, the erythromycin-passaged WT5 population was unable to interfere with pCF10 bearing targets of spacers 6 and 7 (Fig 2).
Preference for spacer deletion over spacer inversion events
Spacer deletion events due to plasmid-CRISPR conflict have been previously reported (33, 37). However, the occurrence of spacer inversions, where a leader distal spacer becomes more leader proximal, have not been extensively studied. Due to the high sequence depth achieved in our study, we were able to observe both events and monitor their dynamics for the duration of the serial passaging experiments. Among our 484 artificial references, the spacer deletion group is represented by the mutant alleles where a spacer has been removed from its natural position (5’-SxRSy-3’ where y > x+1 and 5’-SxTRST-3’ where x < 21), while the spacer inversion group is represented by the mutant alleles where a terminal spacer has become more leader-proximal (5’-SxRSy-3’ where y < x). We calculated spacer deletion and spacer inversion rates for each spacer as described in Materials and Methods.
In Day 1 and Day 14 BHI-passaged T11RF amplicons, we observed slightly higher spacer deletion rates than spacer inversion rates for leader end spacers, suggesting that spacers at the leader end are more readily deleted than inverted in naturally occurring CRISPR3 arrays (Fig 5a). On average, Day 14 T11RF showed slightly lower rates for deletion and inversion events than Day 1 T11RF. However, the deletion and inversion rates were similar at spacers S9-S15 for Day 1 and Day 14 T11RF populations, indicating an equal chance of spacer deletion and inversion (Fig 5a). Terminal end spacers are associated with decreased deletion and inversion rates compared to leader end spacers. Interestingly, the inversion rates of terminal end spacers are slightly higher than the rates for leader end spacers. We hypothesize that the increased spacer inversion rates for terminal spacers is due to a greater number of homologous sequences (direct repeats) toward the leader end of the array, suggesting that homologous recombination played a role in spacer inversion events.
The deletion and inversion rates of five T11RF(pAM714) transconjugants and the Δ4 population from Day 1 and Day 14 erythromycin passages were evaluated in the same manner as the T11RF population. The distribution of deletion and inversion rates in the Δ4 and WT1 populations (Fig 5b and c) were similar to T11RF (Fig 5a). We did observe an elevated deletion rate at S5 for WT1 at Day 1, consistent with deep sequencing results which detected alleles containing S6 deletions in this population. The spacer deletion events in the other T11RF(pAM714) erythromycin-passaged transconjugants (WT2, WT3, WT5 and WT6) have unique positional preferences based on an increase in the average number of reads mapped to the mutant allele references (Fig 5 d-g; red or black dots). Elevated spacer deletion rates were frequently observed for spacers upstream of S6, indicating a selective advantage for spacer deletion events occurring upstream of S6. Finally, we did not observe significant fluctuation of spacer inversion rates in erythromycin-passaged transconjugants (Fig 5 d-g), indicating that spacers are more readily deleted than rearranged.
Spacer deletion is not exclusively RecA-dependent
Under antibiotic selection, T11RF(pAM714) transconjugants lost S6 to resolve the conflict between CRISPR-Cas and its target. The loss of S6 was often coupled with the loss of surrounding spacers, ranging from S1 to S18 (Table 2). From our amplicon sequencing data, we noticed that the rearrangements associated with shortened CRISPR3 arrays occurred between repeat-spacer junctions leaving behind perfectly intact repeat-spacer-repeat sequences that are still functional for CRISPR interference (Fig 2). This observation led us to hypothesize that either homologous recombination or slippage during DNA replication plays a role in eliminating spacers from the array, as has also been hypothesized by other groups (33, 34, 37, 38).
To study if homologous recombination had an impact on spacer loss, we constructed an inframe deletion of recA in T11RF, generating strain T11RFΔrecA, and used it as a recipient in conjugation reactions with the donor OG1SSp(pAM714). We confirmed the presence of a wild type CRISPR3 array in the recA mutant with Sanger sequencing. Across three independent trials, only 12 transconjugant colonies were obtained. We selected two transconjugants (recA.TC1 and recA.TC2) for 14 day serial passaging with continuous erythromycin selection. PCR analysis for CRISPR3 amplicons of Day 0 recA.TC1 and recA.TC2 transconjugant colonies and the amplicons after 1 and 14 days of passage in erythromycin are shown in Figure 6. We used Sanger sequencing to assess spacer loss events in Day 1 and Day 14 populations, but not Day 0 transconjugants. We determined that recA.TC1 had lost S6 after 1 day of passage in erythromycin, while the recA.TC2 population had a deletion of S6-S7. The same CRISPR3 alleles detected by Sanger sequencing after 1 day of passage were also observed at Day 14.
CRISPR-plasmid conflict leads to array-specific diversification in functionally linked CRISPR loci
Some E. faecalis strains possess the CRISPR1-Cas locus, a Type II CRISPR-Cas system that is distinct in sequence and function from the CRISPR3-Cas system of E. faecalis T11RF (22, 32). The CRISPR1-Cas system possesses identical repeats and is functionally linked to the orphan CRISPR2 locus, which occurs in all E. faecalis (22, 32, 39, 46). We wanted to determine if introducing a plasmid targeted by either CRISPR1-Cas or CRISPR2 would impact the integrity of the other locus within the same cell under continuous antibiotic selection for the plasmid target.
For these studies, we used the well-characterized human oral isolate OG1RF in combination with pKH12-derived plasmids (Table 1) that were described by Hullahalli et al (39). pKH12 is a chloramphenicol resistant shuttle vector that is mobilizable by the oriT sequence derived from the PRP, pCF10. Unlike pAD1, it does not encode any post segregational killing mechanisms and its antibiotic resistance determinant is not encoded on a transposable element. pKHS96 contains an engineered CRISPR1-Cas protospacer that is targeted by OG1RF CRISPR1-Cas S4 and pKHS5 contains an engineered CRISPR2 protospacer that is targeted by OG1RF CRISPR2 S6. The consensus PAM sequence for both CRISPR1-Cas and CRISPR2 is NGG (32) and was included adjacent to the engineered protospacers. pKH12, pKHS96 and pKHS5 were each transformed into electrocompetent OG1RF. The initial integrity of the CRISPR1-Cas and CRISPR2 arrays, regardless of the plasmid transformed, was confirmed to be wild-type by Sanger sequencing.
Three transformants for each plasmid were selected to be used in serial passaging experiments. Each transformant was passaged in plain BHI medium and BHI medium supplemented with chloramphenicol for a period of 14 days. Similar to our observations for T11RF(pAM714) transconjugants, we observed plasmid loss in the absence of antibiotic (Fig 7a) and variation in the size of the CRISPR1 and CRISPR2 arrays after 14 days of passage in the presence of chloramphenicol (Fig 7b). Under antibiotic selection, all pKHS96 transformants had reduced CRISPR1 arrays (all with a loss of S4), while the integrity of the CRISPR2 array remained intact. Similarly, after 14 days of antibiotic selection, two of three pKHS5 transformants had reduced CRISPR2 arrays, (both with a loss of S6) while their CRISPR1 array remained of wild type size. These results show that CRISPR array mutations that relieve the conflict between CRISPR and its target are restricted to the locus that the crRNA is derived from. The otherwise functionally linked CRISPR array that coexists in the same cell experiences no diversification.
Discussion
It has been well documented that antibiotic use contributes to the dissemination of antibiotic resistance plasmids and the emergence of MDR organisms. However, bacteria encode genome defense systems such as CRISPR-Cas to reduce plasmid acquisition. The interactions of CRISPR-Cas systems and naturally occurring resistance plasmids are poorly understood, which is of particular concern in the opportunistic pathogen E. faecalis due to its propensity to engage in intra- and interspecies HGT.
We previously demonstrated that the CRISPR3-Cas system of the natively drug sensitive E. faecalis isolate T11RF significantly reduced acquisition of the PRP pAM714 in a cas9- and spacer 6-dependent mechanism (32). The plasmid pAM714 is a derivative of the model PRP pAD1, obtained by spontaneous Tn917 insertion between the par and rep loci of pAD1 (42, 47). Antibiotic resistance on PRPs is commonly encoded within conjugative and transposable elements that are integrated into the PRP backbone (5). In this regard, pAM714 is representative of the broader pool of PRPs conferring antibiotic resistance. Although not directly assessed for their contributions here, pAM714 also encodes cytolysin and aggregation substance, two well-studied virulence factors conferred by PRPs in E. faecalis.
In our previous study, we observed a substantial number of T11RF(pAM714) transconjugants, despite CRISPR3-Cas activity. Based on previous data in other organisms (33, 34, 38), we hypothesized that conjugation occurred into T11RF recipient cells with pre-existing CRISPR-inactivating mutations. However, recent data from our lab on another CRISPR-Cas system in E. faecalis and using different model strains indicated that this hypothesis was incomplete. Specifically, we observed spacer deletion mutants emerging over time in E. faecalis populations having CRISPR-Cas and a plasmid target in intracellular conflict (39). To attain deeper resolution, in the present study we tracked six distinct pAM714 transconjugant lineages that were predicted to experience intracellular conflict due to the presence of an active CRISPR-Cas system and its plasmid target. Our results describe multiple possible outcomes for conflict resolution between plasmids and CRISPR, with the outcome dependent on the presence or absence of antibiotic selection for the plasmid: 1) pre-existing cas9 mutation (WT4); 2) emergence of cas9 mutation (WT1), mutant CRISPR arrays with internal spacer deletions (WT5 and WT6), or both (WT2 and WT3) during passage with selection; and 3) plasmid loss in the absence of selection. Importantly, we did not observe spacer adaptation against the plasmid during passage in the absence of selection; this in in contrast to other studies where spacer acquisition against non-selected plasmids was observed (23). Rather, we hypothesize that plasmid-containing cells are at a competitive disadvantage due to intracellular CRISPR/plasmid conflict (39) and are depleted from the population over time, or, a slow-acting CRISPR-Cas system progressively scrubs the plasmid from the population over time.
We used erythromycin resistance as a marker for pAM714 carriage. We acknowledge that the erythromycin marker is encoded within Tn917, which could theoretically integrate into the chromosome and escape CRISPR targeting of the pAM714 backbone. However, erythromycin resistance was lost from five T11RF lineages passaged in the absence of selection, but not from the Δcas9 transconjugants. This indicates that Tn917 was lost, along with the pAM714 backbone, from the T11RF lineages in a CRISPR-dependent mechanism. Moreover, our analysis of the whole genome sequencing from 8 independent populations found no evidence for Tn917 hopping under erythromycin selection.
The plasmid pAM714 encodes a toxin-antitoxin system (44, 48, 49). The system encodes a stable toxin that will kill daughter cells that have not inherited a plasmid copy; an unstable antitoxin is encoded from the same locus that blocks toxin translation in cells with proper plasmid segregation. However, in our study, we observed a gradual decrease of erythromycin-resistant cells when we passaged T11RF(pAM714) in BHI for 14 days, indicating that the toxin-antitoxin system does not have robust activity in our experiments.
We performed high-coverage Illumina sequencing to assess the dynamics of the entire set of repeats and spacers that make up the CRISPR3 array. We determined that natural heterogeneity in CRISPR3 exists at a low frequency in wild-type T11RF populations. We reason that heterogeneity could result from slippage during DNA replication and/or recombination between CRISPR3 direct repeat sequences, consistent with previous research that proposed that heterogeneity exists within CRISPR arrays in bacterial populations (33, 34, 38). Furthermore, our results demonstrate that spacer deletion can occur in the absence of recA, which implicates DNA replication slippage in the emergence of mutant CRISPR alleles. However, the fact that we observed the occurrence of spacer inversions indicates that homologous recombination does play a role in the inherent allelic diversity of CRISPR arrays. It is likely that both recombination and replication slippage contribute to the emergence of heterogeneous CRISPR alleles. We do not have an estimate of which process has a greater effect, nor whether additional stresses beyond antibiotic selection could influence rates for each.
There were consequences to the resolution of CRISPR/plasmid conflicts in E. faecalis populations. In one case, in which pAM714 conjugated into a recipient with a pre-existing cas9 mutation (WT4), the population could no longer impede entry of PRPs bearing CRISPR targets. For another population, WT5, its susceptibility to future plasmid transfer events was dependent upon whether it was passaged with erythromycin. The WT5 population passaged without erythromycin could impede entry of PRPs bearing CRISPR targets at levels comparable to the wild-type control. However, the WT5 population passaged with erythromycin, in which multiple CRISPR deletion alleles arose, lost the ability to defend against PRPs bearing certain spacer targets. In effect, antibiotic selection for pAM714 selected for the emergence of mutants with compromised CRISPR-Cas. We also observed that the acquisition frequencies of pCF10 and its derivatives were higher for all populations possessing pAM714 (WT5-Erm, WT4-BHI, and WT4-Erm). We infer that pAM714 enhances pCF10 conjugation frequency via an unknown mechanism. This was an unanticipated additional outcome of the enforced maintenance of pAM714, and it remains to be determined whether acquisition of other conjugative elements is also enhanced in pAM714-containing populations.
In this study, we investigated outcomes of CRISPR/plasmid conflicts in E. faecalis using two model strains (T11RF and OG1RF), three CRISPR loci (CRISPR3-Cas, and CRISPR1-Cas and CRISPR2), two plasmid families (pAM714, a PRP, and the pKH12 family of mobilizable shuttle vectors), and two antibiotic selection regimes (erythromycin and chloramphenicol). Our work underscores the impact short-term antibiotic usage has on the evolutionary trajectory of the opportunistic pathogen, E. faecalis.
Materials and Methods
Strains, reagents, and routine molecular biology procedures
Bacterial strains and plasmids used in this study are listed in Table 1. E. faecalis strains were grown in Brain Heart Infusion (BHI) broth or on agar plates at 37°C unless otherwise noted. Antibiotics were used for E. faecalis at the following concentrations: erythromycin, 50 μg/mL; chloramphenicol, 15 μg/mL; streptomycin, 500 μg/mL; spectinomycin, 500 μg/mL; rifampicin, 50 μg/mL; fusidic acid, 25 μg/mL. Escherichia coli strains used for plasmid propagation and were grown in lysogeny broth (LB) broth or on agar plates at 37°C. Chloramphenicol was used at 15 μg/mL for E. coli. PCR was performed using Taq (New England Biolabs) or Phusion (Fisher Scientific) polymerases. Primer sequences used are in STable 1. Routine Sanger sequencing was carried out at the Massachusetts General Hospital DNA core facility (Boston, MA). E. faecalis electrocompetent cells were made using the lysozyme method as previously described (50).
Generation of mutant E. faecalis strains and plasmids
In-frame deletion of recA in T11RF was generated using a previously established protocol (51). Briefly, ~750 bp regions up- and downstream of recA in E. faecalis T11RF were amplified, digested, and ligated into pLT06 (51) to generate pWHrecA. The resulting plasmid was transformed into competent T11RF cells via electroporation (50). Following transformation at 30°C, a shift to the non-permissive temperature of 42°C and counterselection on p-chloro-phenylalanine were performed to generate an in-frame, markerless deletion.
To insert the T11 CRISPR3 spacer 1 (S1), S6, and S7 sequences and CRISPR3 PAM (TTGTA) into pCF10, 47 bp and 39 bp single stranded DNA oligos were annealed to each other to generate dsDNA with restriction enzyme overhangs for BamHI and PstI. The annealed oligos were ligated into the pLT06 derivative pWH107 that includes sequence from pCF10 uvrB, to insert these sequences into the uvrB gene of pCF10 by homologous recombination. A knock-in protocol was performed as previously described (32).
Conjugation experiments
E. faecalis donor and recipient strains were grown in BHI overnight to stationary phase. A 1:10 dilution was made for both donor and recipient cultures in fresh BHI broth and incubated for 1.5 hr to reach mid-exponential phase. A mixture of 100 μL donor cells and 900 μL recipient cells was pelleted and plated on BHI agar to allow conjugation. After 18 h incubation, the conjugation mixture was scraped from the plate using 2 mL 1X PBS supplemented with 2 mM EDTA. Serial dilutions were prepared from the conjugation mixture and plated on selective BHI agars. After 24-48 h incubation, colony forming units per milliliter (CFU/mL) was determined using plates with 30 - 300 colonies. The conjugation frequency was calculated as the CFU/mL of transconjugants divided by the CFU/mL of donors.
Serial passage
Transconjugant or transformant colonies were suspended in 50 μL BHI broth. The 50 μL suspension was used as follows: 3 μL was used for PCR to confirm the integrity of the CRISPR array, 10 μL was inoculated into plain BHI broth, another 10 μL was inoculated into selective BHI broth for plasmid selection, and another 10 μL was used for serial dilution and plating on selective medium to enumerate the initial number of plasmid-containing cells in the transconjugant colonies. Broth cultures were incubated for 24 h, followed by 1:1000 dilution into either fresh plain BHI or fresh selective BHI. At each 24 h interval, 3 μL of each culture from the previous incubation was used for PCR to check CRISPR array integrity, and 10 μL was used for serial dilution and plating on agars to determine CFU/mL for total viable cells and plasmid-containing cells. The cultures were passaged in this manner for 14 days; cryopreserved culture stocks were made daily in glycerol. To use the Day 14 transconjugant populations in conjugation reactions, the glycerol stocks were completely thawed on ice, and 20 μL was inoculated into plain BHI broth. The cultures were incubated for 6-8 h to allow them to reach mid-exponential phase (OD600nm ≈ 0.5–0.7), and 900 μL was used as recipient in conjugation reactions as described above.
Deep sequencing of CRISPR3 amplicons and genomic DNA
For CRISPR3 amplicon sequencing, 3 μL from a broth culture was used as template in PCR using Phusion Polymerase with CR3_seq_F/R primers (STable1). The PCR products were purified using the Thermo Scientific PCR purification kit (Thermo Scientific). Genomic DNA was isolated using the phenol-chloroform method (52). The purified PCR amplicons and genomic DNA samples were sequenced using 2 x 150 bp paired end sequencing chemistry by Molecular Research LP (MR DNA; Texas).
Whole genome sequencing analysis
T11 supercontig and pAD1 plasmid contig references were downloaded from NCBI (accession numbers: T11: NZ_GG688637.1-NZ_GG688649; pAD1: AB007844, AF394225, AH011360, L01794, L19532, L37110, M84374, M87836, U00681, X17214, X62657, X62658). Reads were aligned to these references using default parameters in CLC Genomics Workbench (Qiagen) where ≥50% of each mapped read has ≥80% sequence identity to the reference. Variations occurring with ≥35% frequency at positions with ≥10X coverage between our samples and the reference contigs were detected using the Basic Variant Detector. At the same time, local realignment was performed, followed by Fixed Ploidy variant detection using default parameters and variants probability ≥90% in CLC Genomics Workbench. The basic variants and fixed ploidy variants were combined for each sequencing sample and subjected to manual inspection. The variants that were detected in the T11 genome from all samples were inferred to be variants in our parent T11 stock and were manually removed. The variants that were detected in pAD1 genome from all transconjugant samples were inferred to be variants in our pAM714 stock, hence were also manually removed. Next, variants within the CRISPR3 array were removed as we analyzed CRISPR3 alleles using a different approach (amplicon deep sequencing; see below). All variants detected from all populations were manually checked for coverage depth to eliminate the detection bias. The variants detected in all samples are shown in STable2.
Analysis of CRISPR3 amplicon sequencing
Reads from the 1,763 bp CRISPR3 amplicon were mapped to the T11 CRISPR3 reference (NZ_GG688647.1, positions 646834 - 648596) using stringent mapping conditions in CLC Genomics Workbench. The stringent mapping conditions require 100% of each mapped read to have ≥95% identity to the reference. The percent mapped reads were calculated by dividing the number of reads mapped by the total number of reads, these percentages are listed in STable3, step 1. The coverage depth was then calculated for each position within the PCR amplicon region using CLC Genomics Workbench, normalized using reads per million, and plotted against reference positions (Fig 3).
To further analyze CRISPR3 spacer deletions and rearrangements, we manually created CRISPR3 references. The CRISPR3 amplicon references contain two spacers connected by a T11 CRISPR3-Cas repeat: 5’-spacer[x]-repeat-spacer[y]-3’ (5’-SxRSy-3’), where spacer[x] and spacer[y] could be 30 bp upstream of the first repeat (leader end; or S0 hereafter; Fig S1a), or any internal spacer within the CRISPR3 array (from spacer 1 to spacer 21; or S1 to S21; Fig S1a). Each manually generated CRISPR3 amplicon reference is 96 bp in length. The references where y=x+1 represent wild-type alleles. The terminal repeat following S21 in the CRISPR3 array is divergent from the regular direct repeat sequence, so references containing 5’-spacer[x]-TerminalRepeat-ST-3’ (5’-SxTRST-3’) were constructed, where spacer[x] ranges from S0 to S21 and spacer ST represents the sequence 30 bp downstream of the terminal repeat (Fig S1a). The 5’-S21TRST-3’ reference represents the wild-type. In total, 484 references with length of 96 bp were generated for the CRISPR3 amplicon. Considering that the read length is 150 bp, we manually split each read into two subsequences (one subsequence was 75 bp; with the remainder of the read being the second subsequence) to enhance mapping efficiency, allowing for retrieval of maximal sequence information. The split amplicon sequencing reads were mapped to the 5’-SxRSy-3’ and 5’-SxTRST-3’ references using stringent mapping parameters in CLC Genomics Workbench (Qiagen). The stringent mapping parameters require 100% of each mapped read to be ≥95% identical to one unique reference. Thus, the sequencing reads from different CRISPR alleles will be distinguished. These amplicon mapping results were applied to the calculation of forward 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 control analysis. The unmapped reads were mapped to the 484 manually created spacer[x]-repeat-spacer[y] references using the same mapping parameters in CLC as above (STable3, step 2 mapping; ignore unspecific mapping). The unmapped reads from step 2 were subjected to mapping to all possible references (CRISPR3 region plus manually created references) using default mapping parameters, ignoring unspecific mapping (80% of each mapped read has at least 50% identity to the reference sequence; STable3, step 3 mapping). The unmapped reads from step 3 were mapped to all possible references using the default mapping parameters and randomly map unspecific matching reads (STable3, step 4 mapping).
Forward spacer deletion and backward spacer rearrangement
We observed two categories of mutant CRISPR3 alleles: 5’-SxRSy-3’ (y > x+1) and 5’-SxRSy-3’ (y < x). The forward deletion mutants with 5’-SxRSy-3’ (y > x+1) are the result of spacer deletions, with spacers from Sx+1 to Sy-1 deleted; while the backward rearrangement mutants with 5’-SxRSy-3’ (y < x) are the result of spacer rearrangement, where a downstream spacer Sy flips to become upstream of an upstream spacer Sx. To study if there were positional preferences, the average forward spacer deletion rate and backward spacer rearrangement rate was calculated for each 5’-Sx (0 < x < 21) within the CRISPR3 array. For each 5’-Sx, the average forward deletion and backward rearrangement rate are calculated as: where n is the total number of spacers within a CRISPR array, hence Sn represents terminal spacer, as described above (Fig S1a).
Accession number
The sequencing data for amplicon and whole genome sequencing analysis of transconjugant populations has been deposited in the NCBI Sequence Read Archive under BioProject ID: PRJNA418345.
Acknowledgements
This work was supported by Public Health Service grant R01AI116610 to K.L.P and the Cecil H. and Ida Green Chair to M.Q.Z. We thank Karthik Hullahalli for construction of pKH12 and its derivatives. We thank Dr. Chen Jia for consultation on data analysis methods.