the suspension were added to a 96-well plate, which was then hermetically closed and incubated for 24 or 48 h at 28, 37, or 42°C. Reference strains (AAEC189 and W3110) were included in all runs in triplicate for each medium, at all temperatures and time points. After incubation, OD was measured with an ELISA-reader (Synergy HT, BioTEK Instruments, Bad Friedrichshall, Germany) and bacteria were washed with aqua bidestillata, fixed in 99% methanol, stained with 0.1% crystal violet, and dissolved in 80:20 ethanol:acetone. After dissolution, OD was again measured, then biofilm formation capacity was computed (Martinez-Medina et al., 2009) and statistically analyzed using IBM SPSS Statistics for Windows, Version 20 (Dunn, 2013). Normal distributions of measuring points of all groups (strains) were tested using Kolmogorov-Smirnov (Smirnov, 1948). Based on the non-normal distributions of the measuring points of all groups, the non-parametric Wilcoxon rank-sum test (Mann-Whitney U-test; Wilcoxon, 1945) was used to estimate whether the observed biofilm formation capacity differences were statistically significant ($p = 0.05$). This assay was repeated three times in triplicate per temperature, and in two media for all strains.

## Motility Assays

Overnight culture (from a single colony grown in 5 mL BHI broth) was set to $OD_{600} = 1$. One milliliter was centrifuged and washed twice with $1 \times$ phosphate buffered saline (PBS). Five microliters of the suspension were dropped onto swim-agar plates (LB and 0.3% agar). Plates were incubated at 28, 37, and 42°C. The strain MG1655 (Hayashi et al., 2006; Richter, 2011) was used as a control for a positive swimming phenotype. After 48 h, colony diameters were measured (Harshey, 2003) and statistically analyzed using IBM SPSS Statistics for Windows, Version 20 (Dunn, 2013). Normal distributions of measuring points of all groups (strains) were tested using Kolmogorov-Smirnov (Smirnov, 1948). Based on the non-normal distributions of the measuring points of all groups, the non-parametric Wilcoxon rank-sum test (Wilcoxon, 1945) was used to estimate whether the observed swimming differences were statistically significant. The significance level for multiple comparisons between WT, PCV and T groups was adjusted to $p = 0.016$. This assay was repeated six times.

## RNA Sequencing

The RNA of IMT17433, PCV17433, and T17433 was sequenced. RNA was isolated from two biological replicates from each of two macrocolony and two motility plates. RNA was isolated from cells using the RNAsnap method (Stead et al., 2012) and shipped to LGC Genomics (Berlin, Germany) for RNA sequencing with an Illumina HiSeq2000 producing one channel paired end reads. The details of the company's standard protocols for quality control, RNA extraction from the RNAsnap technique and rRNA depletion (using Ribo-Zero (Epicentre), Biozym, Hessisch Oldendorf, Germany) can be found on their website (http://www.lgcgroup.com/services). cDNA synthesis, library generation, indexing and cluster generation were performed using Illumina technology (TruSeq RNA Sample Preparation Kit v2). Bioinformatic mRNA differential expression analysis

included the following processing steps: (a) generating FastQC reports to check the quality of sequenced reads; (b) clipping Illumina TruSeq sequencing adapters from the 3' ends of reads; (c) filtering rRNA reads using riboPicker (Schmieder et al., 2012); (d) aligning reads against IMT17433 as a reference using TopHat2 (Kim et al., 2013) and RSEM; (e) counting reads per gene using HTSeq-count, and per transcript and gene using RSEM (Li and Dewey, 2011); and (f) computing differential gene and transcript expression between different groups of samples (including technical and biological replicates) using R/Bioconductor packages DESeq (Anders and Huber, 2010), edgeR (Robinson et al., 2010), and Cuffdiff (part of the Cufflinks software package, Trapnell et al., 2013).

## RESULTS

### ESBL-Plasmid-“Curing” and Transformations

All PCVs kept their smaller plasmids and lost only the large ESBL-plasmid. Bioinformatic analysis of all WT and PCV genomes assured their genetic similarity, ruling out any changes in the PCVs' chromosomal content during the “curing” procedure (Schaufler et al., 2013; Von Mentzer et al., 2014). To verify detected phenotypic differences between WT and PCV strains, seven transformants containing the reintroduced large ESBL-plasmid were used (T17433, T19205, T27685, T16316, T17887, T21183, and T23463; Supplementary Table S1). These strains showed phenotypic cefotaxime-resistance (CLSI, 2008). Plasmid-profile analysis confirmed transformation of the large ESBL-plasmid.

### ESBL-Plasmid Characteristics

Whole genomes of all WT strains were used for plasmid characterization (http://www.sanger.ac.uk/resources/downloads/bacteria/escherichia-coli.html#project_2119; IMT17433 [ERR163891], IMT19205 [ERR163889], IMT16316 [ERR163879], IMT17887 [ERR163883], IMT21183 [ERR163880], IMT23463 [ERR163881]; http://www.sanger.ac.uk/resources/downloads/bacteria/escherichia-coli.html#project 2433; IMT27685 [ERR264283]). **Table 1** summarizes the most important ESBL-plasmid characteristics. Their sizes ranged from approximately 100–166 kb. Besides common *bla*<sub>CTX-M</sub> types (mostly the CTX-M-15 enzyme), non-beta-lactam resistance genes (e.g., *tet*(*A*)/*(*R*) and *aac*(6′)-*Ib*-cr) were found. Virulence-associated genes, mainly *finO* and *traT*, were present. All WT strains harbored at least one smaller non-ESBL-plasmid (**Table 1**). Analysis of PCV genomes showed complete loss of the MOB<sub>F12</sub>/IncF ESBL-plasmids in six of the seven genomes analyzed. Strain IMT19205 contained two IncF plasmids that were unresolvable by PLACNET. This strain lost its ESBL-phenotype along with one of the IncF plasmids.

**Figure 1** displays the annotated ESBL-plasmid sequences (pIMT17433, pIMT19205, pIMT27685, pIMT16316, pIMT17887, pIMT21183, and pIMT23463) as compared to ESBL-plasmid pEC_L8 (Smet et al., 2010a), showing both beta-lactam and non-beta-lactam resistance genes, as well as non-resistance genes, including *icc* (phosphodiesterase) and *hha*
(hemolysin expression modulating protein), which were present on all plasmids. Additionally, this comparison displays typical features of conjugative plasmids (*tra* regions and insertions sites) and plasmid partitioning (toxin-antitoxin systems: e.g., *vagC/D* and *pemI/K*).

In summary, although they contained similar genetic backbones and resistance determinants, ESBL-plasmids were rather diverse.

## Growth Curves and Omnilog® Phenotype Microarray (PM)

No differences were detected between the LB growth curves of WT ESBL-producing *E. coli* strains and the corresponding PCVs (data not shown).

Growth/metabolic activity and chemical sensitivity of all strains were then screened using the Omnilog® PM system. Only a minor proportion of strains showed significant differences between the 427 tested compounds (Supplementary Table S2). Exemplary for plate PM1, significant differences were observed for strain combinations 17433 and 17887. Additionally, plates PM2 and PM3 revealed few significant differences (Supplementary Table S2). In contrast, on plate PM4 (sulfur and phosphorus sources), significant differences were observed for 22 wells, of which 18 showed higher values in WT and T strains, while four showed higher values in PCV strains.

The chemical sensitivity plates PM13 and PM14 revealed expected significant differences for ESBL-carrying (WT and T) strains in antimicrobial-containing wells, which showed higher metabolic values than corresponding PCV strains (e.g., PM13, C6: Doxycycline and D4: Cefuroxime; and PM14, G8: Carbenicillin; Supplementary Table S2).

In summary, given the high numbers of substrates tested, only a small proportion of wells showed significant differences in the “area under the curve” parameter between WT, PCV, and T strains. The detected significant differences were bidirectional, meaning that in some cases the PCV strains showed higher growth/metabolic activity values, and in other cases the

ESBL-plasmid-carrying strains showed higher growth/metabolic activity values.

## Macrocolonies

The expression of the biofilm-associated extracellular matrix components cellulose and/or curli fimbriae was tested using macrocolony assays. Table 2 shows the results of the six follow-up runs, which were performed for those strains with differences in cellulose and/or curli fimbriae production during the initial screening (combinations 17433 and 16316).

On plates containing sodium chloride, ESBL-carrying WT IMT17433 expressed cellulose and curli fimbriae, whereas its corresponding PCV did not (Figure 2). Another mutant (PCV16316) did not show any cellulose expression in any run as compared to its associated WT strain (IMT16316), which produced both cellulose and curli fimbriae. In both cases, in accordance with the corresponding WT strains, the transformants T17433 (Figure 2) and T16316 produced curli fimbriae and cellulose in most runs. Only combination 17433 showed the same results on plates lacking sodium chloride (Table 2).

In summary, PCV17433 and PCV16316 displayed reduced production of extracellular components as compared to their respective wild-type and transformant strains.

## Biofilm Formation Assays

Virulence-associated biofilm assays revealed significant differences among three WT/PCV combinations (IMT/PCV17433, IMT/PCV27685, and IMT/PCV17887) after 24 h and among two combinations (IMT/PCV17433 and IMT/PCV17887) after 48 h. IMT17433 and its corresponding PCV were particularly interesting. At all three temperatures and after both time points, the WT strain showed an enhanced biofilm formation capacity in glucose-containing M63 medium (28°C, 24 h: *p* = 0.222; 37°C, 24 h: *p* = 0.008; 42°C, 24 h: *p* = 0.094; 28°C, 48 h: *p* < 0.001; 37°C, 48 h: *p* < 0.001; 42°C, 48 h: *p* = 0.008) as compared to the PCV strain. In contrast, biofilm formation by PCV17433 was better in LB medium

<figure><img src="image_40.png" /><figcaption>FIGURE 2 | Exemplary macrocolonies of IMT/PCV/T17433. Span agar plates with congo red and sodium chloride, incubated for 5 days at 28°C.</figcaption></figure>
(28°C, 24 h: *p* < 0.001; 37°C, 24 h: *p* < 0.001; 42°C, 24 h: *p* < 0.001; 28°C, 48 h: *p* = 0.006; 37°C, 48 h: *p* = 0.004; 42°C, 48 h: *p* = 0.002; **Figures 3A,B**). Transformants did not show any biofilm formation.

In summary, some WT and PCV combinations showed differences in their biofilm formation capacities in both directions; these results were medium-dependent.

## Motility Assays

Motility assays were performed to test the swimming capacity of the strains at different temperatures. Two PCV strains (PCV17433 and PCV17887) showed significantly increased swimming capacity as compared to their corresponding WT strains (IMT17433 and IMT17887) at 28, 37, and 42°C (IMT/PCV17433: 28°C, *p* = 0.002; 37°C, *p* = 0.002; 42°C, *p* = 0.006; IMT/PCV17887: 28°C, *p* = 0.002; 37°C, *p* = 0.002; 42°C, *p* = 0.004). Both transformants (T17433 and T17887) showed significantly reduced swimming capacity as compared to their corresponding PCV strains, with the exception of T17887 at 28°C. (T/PCV17433: 28°C, *p* = 0.002; 37°C, *p* = 0.002; 42°C, *p* = 0.002; T/PCV17887: 28°C, *p* = 0.032; 37°C, *p* = 0.004; 42°C, *p* = 0.013; **Figures 4, 5A-C**).

In summary, PCV17433 and PCV17887 showed higher swimming capacity than their respective WT and T strains.

## RNA Sequencing

To gain insight into differential gene expression, RNA sequencing was performed for IMT/PCV/T17433. Only up- or downregulated genes detected with all three software packages and a threshold of 1.5 fold bidirectional regulation were considered for subsequent analysis.

Cellulose- and curli fimbriae-related differentially regulated genes from the macrocolony assay included: csgB (upregulation in WT compared to PCV: 9.8), csgA (8.6), csgE (6.0), csgF (5.5), csgD (5.5), csgG (4.0), csgC (3.6), and adrA (2.3). Differentially regulated genes important for swimming in the motility assay were, among others: fliZ (downregulation in WT compared to PCV: -1.9), flgH (-2.0), flgF (-2.5), flhC (-2.7), fliD (-2.7), flgL (-3.0), flgK (-3.1), flgC (-3.4), flhD (-3.5), fliL (-4.0), flgD (-4.2), and fliC (-5.7). Most genes were found to be up- or downregulated in both assays, except for csgD and csgC, which were only found to be upregulated in the macrocolony assay in the WT strain as compared to the PCV strain. Conversely, downregulation of flhC and flhD was only observed in the motility assay. All cellulose- and curli-related genes that were upregulated in the macrocolony assay in IMT17433 as compared to PCV17433, were also upregulated in T17433 as compared to PCV17433. Swimming-related genes that were downregulated in the motility assay were not detected in the transformant (e.g., fliZ, flgH, flgA, flgL, flgG, fliC).

In summary, RNA sequencing verified the observed phenotypes for WT17433, PCV17433, and T17433 at the transcriptional level.

## Candidate Genes

The observed phenotypic and transcriptomic differences were only explainable by differences at the genetic level. With only

the ESBL-plasmids differing between WT/T and PCV strains and resistance determinants not explaining the results, the next step in this study was to focus on the non-resistance genes encoded by these plasmids. **Table 3** shows candidate genes of the seven ESBL-plasmid sequences based on PLACNET analysis. Previous studies suggest their involvement in biofilm formation and motility. The candidate genes included *hha* (encoding the hemolysin expression modulating protein) and *yihA* (encoding a cell division protein), which were both present on pIMT17433, pIMT19205, and pIMT27685. The genes *icc* (encoding a phosphodiesterase) and *yfaX* (encoding a putative transcriptional factor) were encoded on pIMT17433 and pIMT27685. All ESBL-plasmids carried *tra* genes important for conjugation.

In summary, the detected candidate genes were mostly encoded on ESBL-plasmids of sequence type ST131 (pIMT17433, pIMT19205, and pIMT27685).

## DISCUSSION

The success of ESBL-producing *E. coli*, particularly the pandemic pathogenic clonal lineages, cannot be explained by antimicrobial resistance alone. To assess the possibility of interactions between ESBL-plasmids and chromosomal content, we conducted a study using an unconventional approach by constructing PCVs of ESBL-plasmid-carrying WT strains of ST131 and ST648. Based on growth curves in LB medium and detailed growth/metabolic activity under different conditions, WT and PCV strains showed similar behaviors and were thus regarded suitable for analysis in subsequent phenotypic assays. Phenotypic differences between WT and PCV strains were generally verified by T strains.

In PM assays, which are a consolidation of regular LB growth curve tests (Supplementary Table S2), significant differences were detected in select wells (plates PM1-4: 3% among all wells without combination 17433). When the results of PM4 were included for 17433, 15% of the wells showed differences; however, these results need to be treated with caution since the negative control (A01) had high values for PCV17433 even after several repetitions of the assay. High values for negative controls in PM assays have previously been described for *E. coli* (Vaas et al., 2012). Differences in antimicrobial sensitivity assays on plates PM13 and PM14 between ESBL-plasmid-carrying strains and PCVs are explainable by loss of ESBL-plasmids in PCVs, which, besides ESBL-genes, carry additional antimicrobial resistance genes (**Table 1**; e.g., PM13, C6: Doxycycline and D4: Cefuroxime; and PM14, G8: Carbenicillin). Overall, significant differences were bidirectional, meaning that each of the ESBL-plasmid-carrying strains and the PCVs showed higher values in select wells. This indicates, as underscored by LB growth curve results, that ESBL-plasmid-carriage does not necessarily lead to fitness loss. This contradicts the hypothesis that considerable trade-offs exist between antimicrobial resistance and fitness (Dasilva and Bailey, 1986; Lenski, 1997; Andersson and Hughes, 2010). Our finding applied to all seven strain combinations irrespective of origin, ST, or ESBL-plasmid characteristics.

Biofilm-related macrocolonies result from bacterial incubation over several days, where the biosynthesis of the
<figure><img src="image_41.png" /></figure>

**FIGURE 3** | (A) Box plots of the distributions of the specific biofilm formation capacities of IMT17433 and PCV17433 at 37°C after 48 h in LB medium. Plots were generated using IBM SPSS Statistics for Windows, Version 20. Positive control, AAEC189; Negative control, W3110. (B) Box plots of the distributions of the specific biofilm formation capacities of IMT17433 and PCV17433 at 37°C after 48 h in M63 medium. Plots were generated using IBM SPSS Statistics for Windows, Version 20. Positive control, AAEC189; Negative control, W3110.

17887

Incubated at
28°C, 48h

<figure><img src="image_42.png" /></figure>

<figure><img src="image_43.png" /></figure>

<figure><img src="image_44.png" /></figure>

Incubated at
37°C, 48h

<figure><img src="image_45.png" /></figure>

<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /></figure>

Incubated at
42°C, 48h

<figure><img src="image_48.png" /></figure>

<figure><img src="image_49.png" /></figure>

<figure><img src="image_50.png" /></figure>

**FIGURE 4** | Exemplary swimming motility of IMT/PCV/T17887. LB plates with 0.3% agar. Incubation at 28, 37, and 42°C for 48 h.

important virulence-related extracellular matrix components cellulose and curli fimbriae typically occurs below 30°C (Bokranz et al., 2005; Richter et al., 2014). Curli fimbriae promote adhesions to abiotic surfaces (Zogaj et al., 2001) and are associated with virulence, as they play key roles during internalization into epithelial cells (Gophna et al., 2001) and

persistence in avian guts (La Ragione et al., 1999). Bacteria produce cellulose mainly as protection from both chemical and mechanical influences (Ross et al., 1991). Considering the results of the macrocolony assays for those combinations with differences, the enhanced ability of ESBL-plasmid-carrying WT and T strains to synthesize curli fimbriae and/or cellulose
<figure><img src="image_51.png" /><figcaption>TABLE 3 | Candidate genes based on annotated PLACNET ESBL-plasmid sequences, literature survey, and RNA sequencing results.</figcaption></figure>

<table><thead><tr><td>Gene</td><td>Protein</td><td>Predicted function</td><td>Presence</td><td>References</td></tr></thead><tbody><tr><td>hha</td><td>Hemolysin expression modulating protein</td><td>Involved in biofilm formation and motility</td><td>pIMT17433, pIMT19205, pIMT27685</td><td>Barrios et al., 2006</td></tr><tr><td>icc</td><td>Phosphodiesterase</td><td>Involved in biofilm formation</td><td>pIMT17433, pIMT27685</td><td>Kalivoda et al., 2013</td></tr><tr><td>yfaX</td><td>Predicted DNA-binding transcriptional regulator</td><td>Putative HTH-type transcription factor</td><td>pIMT17433, pIMT27685</td><td>Perez-Rueda and Collado-Vides, 2000</td></tr><tr><td>yihA</td><td>Cell division protein, predicted checkpoint GTPase</td><td>GTP binding</td><td>pIMT17433, pIMT19205, pIMT27685</td><td>Lehoux et al., 2003</td></tr><tr><td>tra</td><td>Transfer regions of the F-conjugative plasmid</td><td>Involved in biofilm formation</td><td>all seven pIMT ESBL-plasmids</td><td>Ghigo, 2001</td></tr></tbody></table>

in contrast to their respective PCV strains was particularly notable. This indicates that ESBL-plasmid carriage confers benefits in terms of biosynthesis of virulent- and survival-associated extracellular matrix components to some bacterial strains. Several prior studies have described an influence of conjugative plasmids on biofilm formation (Ghigo, 2001; Yang et al., 2008). May and Okabe (May and Okabe, 2008) investigated the influence of natural IncF F-plasmids on biofilm formation and maturation. In this study, both conjugative (tra regions) and non-conjugative plasmid genes seemed to play a role. In our study, all seven ESBL-plasmids belonged to incompatibility group IncF. Furthermore, all encoded different tra genes are important for conjugation; however, since not all WT strains showed differences in extracellular matrix component production as compared to PCV strains, these factors are probably not solely responsible for our observed results.

Biofilm results from IMT/PCV17433 underline the complexity of biofilm formation, which is also dependent on nutrient availability. The enhanced ability of IMT17433 to form biofilms in M63 medium as compared to PCV17433 may point toward plasmid encoded features that enable the WT strain to use limited nutrients efficiently, perhaps via phosphate-dependent pathways. PM results revealing that select phosphate-containing wells in which IMT17433 showed higher

respiration values than PCV17433 reinforce the latter hypothesis. Explanations of the observed enhanced ability of the PCV strain to form biofilms in LB medium, however, remain speculative. There may have been no need for planktonic IMT17433 to transform into a biofilm due to optimal utilization of the rich LB medium. A switch from a sessile (multicellular behavior, biofilm) to a planktonic (motility) way of life, and vice versa, underlies subtle interactions at a molecular level that include numerous complex cascades. Flagellar biosynthesis, for instance, seems not only crucial for bacterial swimming but also leads to surface colonization and subsequent biofilm formation. Insufficient nutrient supply leads to detachment of the cells from the biofilm and adoption of a planktonic lifestyle (Harshey, 2003).

Explanations of the observed enhanced swimming capacity among some PCV strains as compared to their corresponding WT and T strains in the motility assays remain similarly speculative. Flagellar synthesis has been shown to be energetically costly, and ESBL-plasmid-carrying strains might use their energy more strategically (Zhao et al., 2007). Alternately, due to better nutrient utilization, ESBL-plasmid-carrying strains may not have to swim as well as PCV strains to reach peripheral zones with, presumably, richer nutrition supplies.

Phenotypic differences in cellulose and curli fimbriae production as well as swimming capacity, particularly those
observed between the 17433 strains, were confirmed by RNA sequencing results showing upregulation of chromosomally encoded extracellular matrix-related genes and downregulation of chromosomally encoded flagellar-related genes in IMT17433 as compared to PCV17433. Reversible RNA sequencing results for T17433 strengthen the reliability of the differences seen at phenotypic and transcriptomic levels. The key role of the transcription factor csgD is notable in biofilm formation and motility capacity. csgD regulates not only the second curli fimbriae operon csgBAC and adrA, whose product is not only accountable for several other genes involved in cellulose production, but also influences flhDC, the main operon for flagellar synthesis and thus motility (Ogasawara et al., 2011; Chambers and Sauer, 2013). In our study, RNA sequencing results revealed upregulation of csgD, csgBAC, and adrA and downregulation of flhDC in IMT17433 as compared to PCV17433. These results not only confirm the phenotypic data, but also emphasize the central importance of the CsgD protein in regulating the subtle interaction between bacterial sessile and planktonic ways of life.

Overall, the phenotypic tests performed for all seven strain combinations did not show a consistent pattern. Although, this is expected due to high diversity among the group of ESBL-plasmids as well as in the origins of host strains and their phylogenetic backgrounds, such inconsistencies weaken the generalizability of our conclusions. Rather, our results should be seen as an impetus for prospective studies. Interestingly, despite ESBL-plasmid diversity, each of pIMT17433, pIMT19205, and pIMT27685 carried different candidate genes, including *hha* and *icc*, which both have been described to be involved in biofilm formation and motility (Barrios et al., 2006; Kalivoda et al., 2013). Only further experiments that include cloning and knockout methods will provide more information on underlying molecular mechanisms.

In conclusion, this pilot study showed that ESBL-plasmid carriage does not necessarily lead to a growth/metabolic fitness loss. Some ESBL-plasmids in select strains may possess the potential to influence chromosomal gene expression, particularly of those genes that are important for the subtle interactions

between the sessile and planktonic ways of life, such as csgD. We hypothesize that this may contribute to their virulence potential and pandemic success in different habitats, although underlying mechanisms remain to be identified and characterized.

## AUTHOR CONTRIBUTIONS

All authors gave their final approval of the version to be published. Conception and Design: SG, CE, KS, LW, FD. Data analysis: KS, SG, TS, DP, MD. Data acquisition: KS, SG, TS. Writing: KS, SG, LW, CE, DP, TS, MD, FD.

## FUNDING

This work was supported by grants from the German Research Foundation (DFG) to SG and CE entitled, "Functional analysis of non-resistance genes of extended-spectrum beta-lactamases-associated sequence types of *Escherichia coli*" (grants GU 1283/3-1 and EW116/2-1). KS was supported by a grant from SONNENFELD-Stiftung. Sequencing was partly financed by the Wellcome Trust Sanger Institute (Cambridge, United Kingdom-study number 24331LB). The foundations that funded this work had no role in study design, data collection or interpretation, or the decision to submit the work for publication.

## ACKNOWLEDGMENTS

We thank Ivonne Stamm and Peter A. Kopp (IDEXX Vet. Med. Lab., Ludwigsburg, Germany) for providing some of the wild-type strains used in this study and Gordon Dougan (Wellcome Trust Sanger Institute, Cambridge, United Kingdom) for his support during sequencing.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb.2016.00336

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Schaufler, Semmler, Pickard, de Toro, de la Cruz, Wieler, Ewers and Guenther. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# Fitness Cost of Fluoroquinolone Resistance in Clinical Isolates of *Pseudomonas aeruginosa* Differs by Type III Secretion Genotype

Melissa Agnello¹, Steven E. Finkel² and Annie Wong-Beringer¹*

¹School of Pharmacy, University of Southern California, Los Angeles, CA, USA, ²Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA

Fluoroquinolone (FQ) resistance is highly prevalent among clinical strains of *Pseudomonas aeruginosa*, limiting treatment options. We have reported previously that highly virulent strains containing the *exoU* gene of the type III secretion system are more likely to be FQ-resistant than strains containing the *exoS* gene, as well as more likely to acquire resistance-conferring mutations in *gyrA/B* and *parC/E*. We hypothesize that FQ-resistance imposes a lower fitness cost on *exoU* compared to *exoS* strains, thus allowing for better adaptation to the FQ-rich clinical environment. We created isogenic mutants containing a common FQ-resistance conferring point mutation in *parC* from three *exoU* to three *exoS* clinical isolates and tested fitness *in vitro* using head-to-head competition assays. The mutation differentially affected fitness in the *exoU* and *exoS* strains tested. While the addition of the *parC* mutation dramatically increased fitness in one of the *exoU* strains leaving the other two unaffected, all three *exoS* strains displayed a general decrease in fitness. In addition, we found that *exoU* strains may be able to compensate for the fitness costs associated with the mutation through better regulation of supercoiling compared to the *exoS* strains. These results may provide a biological explanation for the observed predominance of the virulent *exoU* genotype in FQ-resistant clinical subpopulations and represent the first investigation into potential differences in fitness costs of FQ-resistance that are linked to the virulence genotype of *P. aeruginosa*. Understanding the fitness costs of antibiotic resistance and possibilities of compensation for these costs is essential for the rational development of strategies to combat the problem of antibiotic resistance.

**Keywords:** *Pseudomonas aeruginosa*, fluoroquinolone resistance, type III secretion, fitness, virulence

## OPEN ACCESS

**Edited by:**
Axel Cloeckaert,
French National Institute
for Agricultural Research, France

**Reviewed by:**
Henrietta Venter,
University of South Australia, Australia
César De La Fuente-Núñez,
Massachusetts Institute
of Technology, USA
Alessandra Polissi,
University of Milan, Italy

*Correspondence:
Annie Wong-Beringer
anniew@usc.edu

**Specialty section:**
This article was submitted to
Antimicrobials, Resistance
and Chemotherapy,
a section of the journal
Frontiers in Microbiology

**Received:** 26 April 2016
**Accepted:** 22 September 2016
**Published:** 04 October 2016

**Citation:**
Agnello M, Finkel SE and
Wong-Beringer A (2016) Fitness Cost
of Fluoroquinolone Resistance
in Clinical Isolates of *Pseudomonas*
*aeruginosa* Differs by Type III
Secretion Genotype.
*Front. Microbiol.* 7:1591.
doi: 10.3389/fmicb.2016.01591

## INTRODUCTION

*Pseudomonas aeruginosa* is a Gram-negative pathogen that is the leading cause of nosocomial pneumonia (Restrepo and Anzueto, 2009; Quartin et al., 2013). Resistance to the fluoroquinolone (FQ) antibiotics has risen dramatically due to the widespread prescribing of this class of drug, limiting treatment options for *P. aeruginosa* infections (Linder et al., 2005). *P. aeruginosa* acquires resistance to the FQs through mutations in genes regulating the expression of efflux pumps and through point mutations in target site genes. The target enzymes of the FQs are the type II
topoisomerases, GyrA/B and ParC/E (Hooper, 2001). Resistance-conferring mutations in these genes, known as target site mutations, have been well described in *P. aeruginosa* (Nakano et al., 1997; Mouneimné et al., 1999; Higgins et al., 2003).

*Pseudomonas aeruginosa* has the ability to cause a variety of severe infections due to its many virulence factors. Specifically, *P. aeruginosa* utilizes the type III secretion system (TTSS) during acute infections to evade phagocytosis, invade host cells, and cause cell death (Veesenmeyer et al., 2009). The TTSS consists of a molecular syringe-like apparatus that extends through the inner and outer membranes and directly contacts the host cell. This allows effector toxins (ExoU, ExoS, ExoY, and/or ExoT) to be directly injected into the cytoplasm of host cells. Although residing at entirely separate loci, the genes encoding the toxins ExoU and ExoS are mutually exclusive in most strains, with the *exoS* genotype accounting for about 70% of clinical and environmental strains (Feltman et al., 2001; Garey et al., 2008). While less prevalent in general, *exoU* strains are more virulent than *exoS* strains, as has been shown in animal models of acute pneumonia (Shaver and Hauser, 2004). Importantly, infection with these strains leads to poor outcomes in patients with ventilator-associated pneumonia (Roy-Burman et al., 2001; El Solh et al., 2008) as well as increased persistence and severity of disease (Schulert et al., 2003).

Alarmingly, clinical studies have shown a correlation between FQ-resistance and virulence. We have previously reported that patients infected with FQ-resistant strains of *P. aeruginosa* had threefold higher mortality or prolonged illness by an additional 5 days compared to those infected with FQ-susceptible strains (Hsu et al., 2005). In addition, clinical isolates with the more virulent *exoU* genotype were shown to more likely be FQ-resistant than *exoS* strains (Wong-Beringer et al., 2008; Agnello and Wong-Beringer, 2012). Others have reported similar results in isolates from various infection sites (Zhang et al., 2014; Peña et al., 2015). Furthermore, in a separate study, we found that the combined traits of FQ-resistance and *exoU* genotype among respiratory isolates of *P. aeruginosa* were significantly associated with the development of pneumonia rather than bronchitis or colonization (Sullivan et al., 2014), suggesting that resistance and virulence traits may be linked, negatively impacting disease severity.

In a large study of 270 clinical isolates, we found that significantly more *exoU* strains were FQ-resistant, compared to *exoS* strains (63% vs. 49%, *p* = 0.03). Sequencing of the FQ target site genes *gyrA/B* and *parC/E* revealed that *exoU* strains were more likely than *exoS* strains to acquire two or more resistance-conferring target site mutations (Agnello and Wong-Beringer, 2012). Specifically, we found that while FQ-resistant *exoU* and *exoS* strains were similarly likely to possess a mutation in *gyrA*, *exoU* isolates were more likely to also have acquired an additional mutation in *parC*, resulting in greatly increased levels of resistance. While there is mounting evidence for the co-selection of resistance and virulence traits among pathogenic bacteria (Beceiro et al., 2013), the biological mechanisms underlying these observations are not well understood. Since the identification of the ExoU and ExoS toxins of the *P. aeruginosa* type III secretion

system, many studies have investigated the roles of each toxin during infection (Allewelt et al., 2000; Schulert et al., 2003; Shaver and Hauser, 2004, 2006) while others have described the association of *exoU* strains with increased FQ resistance (Lakkis and Fleiszig, 2001; Maatallah et al., 2011) supporting our own observations. The aim of the current study was to gain insights into the biological basis underlying the differential development of resistance in *exoU* vs. *exoS* strains, which previous studies have not explored. We hypothesize that the greater propensity of *exoU* strains to acquire multiple target site mutations compared to *exoS* strains reflects a difference in the fitness costs associated with FQ-resistance mutations, favoring the strains with the *exoU* genetic background.

A recent meta-analysis of studies conducted on fitness costs of resistance to a variety of antibiotic classes in different organisms showed that most point mutations are generally costly (Melnyk et al., 2015). However, there is great variability depending on organism, drug, and mechanism of resistance. Furthermore, fitness costs can be mitigated through the accumulation of compensatory mutations that restore fitness to wild-type levels without loss of resistance (Andersson and Hughes, 2010). FQ-conferring mutations have been shown to impose variable fitness costs, depending on strain background and specific combinations of mutations (Komp Lindgren et al., 2005; Luo et al., 2005; Marcusson et al., 2009; Machuca et al., 2014; Wasels et al., 2015).

In the current study, we compared the fitness effects of a target site mutation in *parC* using isogenic mutants created from clinical *exoU* and *exoS* isolates. We investigated the fitness effects of this mutation using *in vitro* head-to-head competition experiments. Changes in supercoiling level and mutation frequency between mutants and parent strains were also assessed to explore potential mechanisms for the difference in fitness observed.

Our results suggest that the FQ resistance-conferring point mutation in *parC* studied here may confer less of a fitness cost to *exoU* strains than to *exoS* strains, with *exoU* strains showing evidence of compensation for the fitness costs. These results provide a potential biological explanation for the observed predominance of *exoU* strains in the clinical FQ-resistant population. The co-selection of FQ-resistance in highly virulent *exoU* strains will likely have a negative impact on patient outcomes, which underscores the importance to gain a better understanding of the biological basis for this observation.

# MATERIALS AND METHODS

## Ethics Statement

The institutional review boards at both Huntington Hospital and the University of Southern California have approved this study. Informed consent was waived from all participants since bacteria cultures were saved as part of a longitudinal epidemiological surveillance study. All data from respiratory cultures were analyzed anonymously to protect patient privacy.
<table><caption>TABLE 1 | Characteristics of Strains.</caption><thead><tr><th></th><th>Name</th><th>LVX<sup>a</sup> MIC (µg/ml)</th><th>LVX + EPI<sup>b</sup> MIC (µg/ml)</th><th>Amino Acid Change</th><th>Doubling Time, h (–/+ SEM)<sup>c</sup></th></tr></thead><tbody><tr><td rowspan="6">exoU</td><td>U-37</td><td>16</td><td>0.5</td><td>GyrA: T83I</td><td>2.0 (1.7–2.4)</td></tr><tr><td>U-37PC*</td><td>16</td><td>0.5</td><td>GyrA: T83I<br>ParC: S87L</td><td>1.7 (1.5–1.9)</td></tr><tr><td>U-91</td><td>2</td><td>2</td><td>GyrA: T83I</td><td>3.9 (3.78–3.93)</td></tr><tr><td>U-91PC*</td><td>16</td><td>2</td><td>GyrA: T83I<br>ParC: S87L</td><td>3.9 (3.87–3.96)</td></tr><tr><td>U-92</td><td>16</td><td>0.5</td><td>GyrA: T83I</td><td>2.5 (2.3–2.7)</td></tr><tr><td>U-92PC*</td><td>16</td><td>0.5</td><td>GyrA: T83I<br>ParC: S87L</td><td>2.8 (2.6–3.0)</td></tr><tr><td rowspan="6">exoS</td><td>S-139</td><td>4</td><td>0.5</td><td>GyrA: T83I</td><td>3.4 (3.3–3.6)</td></tr><tr><td>S-139PC*</td><td>32</td><td>0.25</td><td>GyrA: T83I<br>ParC: S87L</td><td>3.1 (2.9–3.3)</td></tr><tr><td>S-247</td><td>16</td><td>1</td><td>GyrA: T83I</td><td>2.5 (2.4–2.6)</td></tr><tr><td>S-247PC*</td><td>16</td><td>8</td><td>GyrA: T83I<br>ParC: S87L</td><td>2.5 (2.4–2.7)</td></tr><tr><td>S-215</td><td>16</td><td>1</td><td>GyrA: T83I</td><td>2.4 (2.2–2.7)</td></tr><tr><td>S-215PC*</td><td>16</td><td>1</td><td>GyrA: T83I<br>ParC: S87L</td><td>2.3 (2.2–2.5)</td></tr></tbody></table>

Mutants with Ser87Leu substitution in ParC denoted PC*. <sup>a</sup>LVX, Levofloxacin; <sup>b</sup>EPI, efflux pump inhibitor; <sup>c</sup>Doubling time during exponential phase.

## Bacterial Strains and Culture Conditions

Strains of *P. aeruginosa* used in this study (Table 1) were selected from a collection of isolates obtained from the respiratory tract of hospitalized patients at Huntington Hospital, Pasadena, CA, USA from 2005 to 2009 and were stored in cryovials at –80°C in 30% glycerol. All strains had been previously characterized for: the presence of the *exoU* or *exoS* gene, resistance to levofloxacin, presence of mutations in the quinolone-resistance determining regions of *gyrA/B* and *parC/E*, and clonal relatedness by RAPD PCR, as described in Agnello and Wong-Beringer (2012). Strains were routinely grown as 5 ml cultures in Luria-Bertani (LB) broth in 12 ml polypropylene culture tubes at 37°C and shaking at 250 rpm for liquid culture, or grown on *Pseudomonas* Isolation Agar (PIA) plates at 37°C. Strains were routinely sub-cultured twice after inoculation from the frozen stock by 1:100 dilution (vol:vol) before use in any experiment.

## Susceptibility Testing and Sequencing

Susceptibility testing to levofloxacin and rifampicin was performed by broth microdilution in twofold dilutions at concentrations ranging from 0.25 to 128 µg/ml according to guidelines recommended by CLSI (Clinical and Laboratory Standards Institute, 2007). In order to assess the involvement of the multidrug Mex efflux pumps to resistance, MIC of levofloxacin was also measured with the addition of an efflux pump inhibitor (EPI, MC-0228; Sigma) at 20 µg/ml (Kriengkauykiat et al., 2005).

For sequencing, genomic DNA was extracted and purified from isolates using the DNeasy Mini Kit (Qiagen). The quinolone-resistance determining regions of target genes *gyrA*, *gyrB*, *parC*, and *parE* were amplified by PCR using previously published primers and conditions and sequenced to identify

mutations compared to wild-type strain PAO1 (Table 2) (Jalal and Wretlind, 1998; Lee et al., 2005; Winsor et al., 2011).

## Creation of Target Site Mutants

Since most FQ-resistant isolates have *gyrA* mutations, three *exoU* and three *exoS* isolates with a pre-existing *gyrA* FQ-resistance mutation (Thr83→Ile substitution) were selected for mutagenesis. A site-directed point mutation in the *parC* gene leading to the amino acid substitution Ser87→Leu was introduced via electroporation of an oligonucleotide in order to create isogenic mutants, using the technique of oligonucleotide recombination as described previously (Swingle et al., 2010; Agnello and Wong-Beringer, 2014). Briefly, a single-stranded oligonucleotide 60 bases in length was designed using the *parC* gene sequence of reference strain PAO1 (Winsor et al., 2011) (Table 2). The oligo is identical to the PAO1 sequence from nucleotides 230 to 289, save for the point mutation TCG→TTG at location 31 of the oligo, corresponding to nucleotide 260 in the *parC* gene. This point mutation, which is the most common *parC* mutation observed among fluoroquinolone-resistant clinical strains, gives rise to the Ser87→Leu amino acid change in the ParC protein.

Strains were made electro-competent by several washes with 300 mM sucrose solution as described in Choi et al. (2006) and transformed by electroporation at 2.5 kV in a 0.2 cm cuvette using a Micropulser (Bio-Rad, Hercules, CA, USA). SOC medium (1 ml) was immediately added and the cells were outgrown overnight at 37°C on PIA plus levofloxacin at concentrations two and fourfold above the original minimum inhibitory concentration (MIC) of the isolates for selection. Single colonies were collected and the *parC* gene was sequenced as described above to confirm that recombination had occurred.

## Growth Rate Measurements

Independent overnight cultures were diluted to OD<sub>600</sub> ~0.1 and grown at 37°C with shaking in 50 ml LB broth in a 100 ml flask. An aliquot of the culture (150 µl) was sampled every 30 min for 8 h and turbidity was measured at OD<sub>600</sub> using a Tecan Sunrise microplate reader (Tecan Group Ltd., Switzerland). Results were reported as an average of at least three independent experiments in terms of doubling time per hour.

## Insertion of Fluorescent Tag

Mini-Tn7 vectors developed and generously shared with us by Dr. Herbert Schweizer (Choi et al., 2005) were utilized to insert cassettes containing the genes encoding YFP or CFP as well as a cassette containing the *lux* operon into strains used for competition experiments and supercoiling experiments, respectively. The cassette inserts into the *P. aeruginosa* genome at a single location (*attTn7* site downstream of the *glmS* gene) and contains the gene for the fluorescent protein under the control of a constitutive promoter or the *lux* operon under the control of a supercoiling-sensitive promoter (Moir et al., 2007), as well as a gentamicin-resistance marker for selection. The delivery plasmid was co-electroporated with a helper plasmid (pTNS3) encoding the necessary transposase function for insertion. The electroporation protocol used for
<table><caption>TABLE 2 | Genetic elements used.</caption><thead><tr><th></th><th>Sequence</th><th>Reference</th></tr></thead><tbody><tr><td><strong>Primer name PCR</strong></td><td></td><td></td></tr><tr><td>gImS-up</td><td>CTGTGCGACTGCTGGAGCTGA</td><td>Choi and Schweizer, 2006</td></tr><tr><td>gImS-down</td><td>GCACATCGGCGACGTGCTCTC</td><td>Choi and Schweizer, 2006</td></tr><tr><td>Tn7-R</td><td>CACAGCATAACTGGACTGATTTC</td><td>Choi and Schweizer, 2006</td></tr><tr><td>Tn7-L</td><td>ATTAGCTTACGACGCTACACC</td><td>Choi and Schweizer, 2006</td></tr><tr><td><strong>Oligo for recombination</strong></td><td></td><td></td></tr><tr><td>PC*</td><td>TGCTCGGCAAGTTCCACCCGCACGGCGACTTGGCCTGCTA<br>CGAGGCCATGGTGCTGATGG</td><td>Agnello and Wong-Beringer, 2012</td></tr><tr><td><strong>Plasmid</strong></td><td><strong>Function</strong></td><td><strong>References</strong></td></tr><tr><td>pTNS3</td><td>Helper plasmid, encodes Tn-7 transposition pathway</td><td>Choi et al., 2005</td></tr><tr><td>pUC18T-mini-Tn7T-Gm-eyfp</td><td>Delivery plasmid for Gm<sup>R</sup> marker and YFP</td><td>Choi and Schweizer, 2006</td></tr><tr><td>pUC18T-mini-Tn7T-Gm-ecfp</td><td>Delivery plasmid for Gm<sup>R</sup> marker and CFP</td><td>Choi and Schweizer, 2006</td></tr><tr><td>TOP10/mini-Tn7-PA0614 promoter-Gm-luxCDABE</td><td>Delivery plasmid for Gm<sup>R</sup> marker and lux operon</td><td>Choi and Schweizer, 2006</td></tr></tbody></table>

transformation is described in detail in Choi and Schweizer (2006); briefly, strains were made electro-competent through a series of washes with 300 mM sucrose, subjected to electroporation as described above, and plated on LB plates containing 30 µg/ml gentamicin for selection. To confirm insertion had occurred, PCR was performed to amplify the insertion region using primers listed in Table 2 and protocol as previously described (Choi and Schweizer, 2006) (data not shown).

## In vitro Competition Assays

To investigate the effects of the *parC* mutation (PC\*) on fitness, mutants were directly competed against isogenic parent strains in co-culture. Strains were tagged with either CFP or YFP for differentiation as described above. PC\* mutant strains were initially tagged with CFP, and competed against the respective isogenic parent strain tagged with YFP. To confirm neutrality of the tags, experiments were also performed with YFP-mutants and CFP-parents.

Strains were grown overnight in LB, and 10⁵ CFU of each strain was co-inoculated into 10 ml LB in a 50 ml flask, and grown with shaking at 37°C. Every 24 h, 10 µl of the culture was transferred to a new flask containing 10 ml fresh LB, and a sample of the culture was serially diluted then plated on PIA for CFU enumeration. Colonies of each color were counted using a fluorescent wide-field microscope (Zeiss Axio Zoom.V16). Experiment duration ranged from 4 to 7 days. The ratio of the number of CFUs of the mutant-to-parent strain on each day of the experiment was calculated and used to determine the relative fitness of the mutant. Experiments were repeated a minimum of five times. Assays were also performed with the addition of levofloxacin equal to 1/8 the MIC (2 or 0.5 µg/ml). At day 7 of each competition experiment, colonies were selected from plates, inoculated into LB, grown overnight, and stored at -80°C in 30% glycerol until ready for use in subsequent experiments. These were described as 'aged' strains. Aged strains were subjected to a secondary competition experiment vs. the original strains. Secondary competition with

aged strains was performed as described above, and lasted for 4 days.

## Supercoiling Assay

We adapted a reporter assay to estimate the ability to maintain supercoiling levels in mutants compared to parent strains by inserting a Tn7 cassette containing the *lux* operon under the control of a supercoiling-sensitive *P. aeruginosa* promoter from the gene *PA0614* (Moir et al., 2007). The cassette was inserted as described above. Luminescent strains were grown to mid-exponential phase, then diluted 1:4 in LB+ levofloxacin at 1/4, 1/2, and 1x the measured MIC, and grown in triplicate in a deep well 96-well plate for 7 h. Luminescence was measured using the Envision Multi-Label plate reader (Perkin-Elmer) as well as OD₆₀₀ as described above. Relative Luminescence Units (RLU) was normalized to OD₆₀₀ for all comparisons.

## Mutation Frequency Assay

Mutation frequency was estimated during competition experiments using the spontaneous rifampicin resistance method (Oliver et al., 2000). At each 24-h interval, competition cultures were plated on PIA+ rifampicin at 5x the MIC (ranging from 40 to 500 µg/ml depending on the strain) in addition to plating on PIA. The mutation frequency reported is the number of colonies that grew on PIA + rifampicin after 48 h divided by the number of colonies on PIA alone. Colonies of each strain were differentiated and counted based on fluorescence as described above. For strain 139, 5x the MIC of rifampicin corresponds to 500 µg/ml, which turned the plates a dark shade of red and prevented the differentiation of the fluorescence of the colonies. Thus, for this strain, each rifampicin-containing plate was replica-plated using sterile velvets onto a fresh PIA plate and incubated for an additional 24 h before colonies were counted.

## Statistical Analysis

GraphPad Prism v.6 (GraphPad.com, San Diego, CA, USA) was used to perform statistical analysis. ANOVA was used to compare continuous variables where appropriate, and student's
t-test was used to compare mean ratios to the null hypothesis of 1 (indicating no difference). A *p* value ≤ 0.05 denotes significance.

## RESULTS

We previously created isogenic mutants from 6 clinical isolates of *P. aeruginosa* (three *exoU* and three *exoS*) by inserting a point mutation commonly observed in fluoroquinolone-resistant isolates into the *parC* gene (Agnello and Wong-Beringer, 2012). The goal of the current study was to investigate the biological effects of this target site mutation in a controlled genetic background. Mutants are denoted PC*. Interestingly, the addition of the *parC* mutation increased the levofloxacin MIC in only two of the six isolates. Characteristics of mutant and parent strains used in this study are summarized in Table 1.

### Growth Rate in Monoculture

As an initial comparison of the relative fitness of mutant vs. parent strains, we tested the doubling time in independent cultures by measuring optical density every 30 min over an 8-h period; results are an average of at least three independent experiments (Table 1). Doubling time during exponential phase was calculated by dividing the time interval over the number of generations. Growth rates of all six mutants were comparable to parent strains.

### *parC* Mutation Differentially Affects Competitive Fitness of *exoU* vs. *exoS* Strains

To investigate the fitness costs of the *parC* mutation, we performed head-to-head competition assays. Each PC* mutant was directly competed against its isogenic parent strain by growth in co-culture for 4 days. Because the strains competed are identical save for the point mutation, any fitness cost is attributable to the mutation. In each individual competition experiment, one strain is tagged with CFP (cyan fluorescent protein), and the other with YFP (yellow fluorescent protein). This allows for the direct enumeration of the number of colonies of each strain after serial dilution onto agar plates. Colonies were counted every 24 h, and the relative fitness of the mutant is determined from the ratio of mutant-to-parent CFU/ml. Each experiment was independently repeated at least five times. We confirmed the neutrality of the YFP and CFP tags by repeating each experiment with each strain carrying the opposite tag. No difference was found, and therefore results from all experiments were combined.

**Figure 1** shows the average mutant-to-parent ratios over time for each strain. Each strain has a unique pattern of fitness costs associated with this mutation; however, in general, there appears to be a higher fitness cost for the *exoS* strains. The *exoS* strains S-139PC*, S-247PC*, and S-215PC* show a consistent fitness defect over all time points, with strain S-139PC* the most affected. On the other hand, strain U-92 has the smallest fitness effect, with the mutant/parent ratios ranging from 1.2 to 2.0 over 2–4 days of competition. Strain U-37 shows a similar

pattern except the mutant starts with lower fitness (ratio 0.5 at day 2), but catches up to the parent strain by day 4 with a ratio of 0.99. Strain U-91 is unique and interestingly shows a striking increase in fitness due to the mutation; the mutant rapidly outcompetes the parent strain and completely takes over the culture by day 3.

### *exoU-PC*\* Mutants can Better Maintain Wild-Type Supercoiling Levels than *exoS-PC*\* Mutants

We assessed supercoiling of parent vs. mutants in *exoU* strains U-92 and U-37 and *exoS* strains S-215 and S-139 by inserting a Tn7 genetic element in which a supercoiling sensitive promoter controls the *lux* operon (Moir et al., 2007). Due to challenges inserting the reporter, only two strains of each background were chosen as representative strains. Strains with the insertion were grown under levels of levofloxacin at and below the MIC in order to maximally induce expression of the reporter, and luminescence values were normalized to OD₆₀₀. We measured the level of luminescence in the parent strain as an indirect reporter of the baseline level of supercoiling; any difference in luminescence expression for the PC* strain reflects a change in supercoiling due to the *parC* mutation. Results show that the PC* mutants in general have decreased luminescence compared to parent strains; however, this decrease was significantly more pronounced in *exoS-PC*** strains (Figure 2), suggesting that *exoS* strains with the PC* mutation are somehow less able to maintain the supercoiling level of the parent strains, which may have negative effects on fitness. This is surprising given that the primary role of topoisomerase IV (ParC) is decatenation of daughter replicons and not regulation of supercoiling (Hooper, 2001); however, in this context it may suggest an overall difference in supercoiling regulation in *exoU* vs. *exoS* strains.

### Analysis of Aged Strains

Because, we observed that the fitness of *exoU-PC*\* mutants tended to increase after 24 h of competition, we investigated whether stable changes were occurring during competition that allowed the strains to compensate for fitness costs associated with the *parC* mutation. We collected colonies of parent and PC* strains from a primary competition experiment (parent vs. mutant) after 7 days and labeled these 'aged' strains. In addition, we investigated the effect of sub-inhibitory levels of fluoroquinolone exposure on competitive fitness and ability to compensate for fitness costs by collecting aged strains from primary competition experiments in which 1/8 MIC of levofloxacin was added to the media.

We were not able to collect aged colonies from the primary competition experiments of strain 91 due to the vast difference in fitness between the PC* mutant and parent strains; the PC* strain completely overtook the culture by day 3. Because this left us with only two *exoU* strains (U-92 and U-37), we chose two *exoS* strains in order to have an equal number in each group for comparison. We chose strains 215 and 139 because these represent both ends of the spectrum in terms of fitness of the PC* mutants *in vitro*; strain S-215PC* shows the least fitness cost of
<figure><img src="image_53.png" /></figure>

**FIGURE 1** | *In vitro* fitness of *exoU* and *exoS-PC*\* mutants. The average $log_{10}$ CFU/ml ratio of PC\* vs. parent strains per day of *in vitro* competition are shown. Ratios above zero indicate the mutant is more fit, while ratios below zero indicate a fitness cost. The ratio for *exoS* strains generally decreases over the course of the experiment, while the ratios for *exoU* strains either increases or remains stable. Results are an average of at least five independent experiments. Error bars = SEM. For strain U-91, the dotted line and circles indicate ratios after day 2 are beyond the limit of detection. \*Indicates the PC\*/parent CFU ratio is significantly different than 1 at *p* < 0.05.

<figure><img src="image_54.png" /></figure>

**FIGURE 2** | Supercoiling changes in PC\* mutants compared to parent strains. Each strain contains a chromosomal reporter construct in which the *lux operon* is under the control of a supercoiling-sensitive promoter. Strains were grown in concentrations of levofloxacin equal to 1/4, 1/2, and 1x the MIC. Luminescence was normalized to cell count using $OD_{600}$. Results are an average of three independent experiments, and error bars represent SEM. \* *p* < 0.05; \*\* *p* < 0.01.

all the *exoS* strains, while strain S-139PC\* exhibits the greatest fitness cost.

Sequencing the FQ-target site genes of the aged strains revealed that no changes occurred in the genes associated with FQ-resistance except for *exoU* strain U-92, in which the parent acquired the Ser87Leu substitution in *ParC* during competition under levofloxacin exposure (+LVX) at 1/8 MIC. All PC\* strains maintained the *parC* mutation. The MIC to levofloxacin did not change in any of the aged strains (data not shown).

## Aged PC\* Mutant *exoU* vs. *exoS* Strains Show Dramatic Difference in Fitness

To investigate whether the aged strains had acquired adaptations during competition that rendered them more fit, we compared the fitness of each aged strain to its un-aged counterpart. Aged strains were subjected to a secondary competition experiment in which they were competed against the original, un-aged strain that contained the opposite fluorescent tag, enabling the discrimination and enumeration of each strain during competition. Results reflect the aged-to-un-aged ratio at Day
2 (Figure 3). Because each aged strain was competed directly against an un-aged version of itself, we were able to directly observe if fitness had changed in the aged strains. All parent strains had a negligible change in fitness. Both *exoU-PC*\* aged strains increased in fitness greater than fourfold, while the *exoS-PC*\* aged strains showed a 50% decrease in fitness; S-139PC\* was greater than 100 times less fit than before aging.

We also investigated whether growth under sub-inhibitory levels of levofloxacin affected fitness, and if mechanisms to compensate for fitness costs evolved under these conditions. The addition of levofloxacin did not affect the results of primary competition experiments (data not shown), but notable results were seen in the secondary competition experiments of the aged vs. un-aged strains, which also included 1/8 MIC of levofloxacin. Upon subsequent exposure to the drug, *exoU-PC*\* strains were much more fit, outcompeting the un-aged strain rapidly. Specifically, the aged PC\* mutants of *exoU* strains U-37 and U-92 outcompeted the un-aged strains significantly and rapidly, much more so than in the competition experiments without the drug. Interestingly, the measured MICs of the aged and un-aged strains remain unchanged. *exoS-PC*\* strains showed conflicting results; S-215PC\* had gained fitness, while S-139PC\* had slightly decreased fitness (Figure 3).

## Mutation Frequency

Compensation for potential fitness costs of a resistance-conferring mutation can evolve through the accumulation of beneficial mutations. Therefore, we investigated whether the rate of spontaneous mutation frequency could explain the increase in fitness during competition that was seen in *exoU-PC*\* strains. Mutation frequency was estimated by calculating the frequency of spontaneous resistance to rifampicin (RifR\*) (Oliver et al., 2000). We estimated mutation frequency during the primary competition experiments for *exoU* strains U-92 and U-37, and

*exoS* strains S-215 and S-139 by plating the mixed competition culture on agar containing 5x the MIC of rifampicin at each time point (Days 1–7), and counting the number of colonies based on fluorescence of each strain that were able to grow on the rifampicin-containing plates compared to the overall CFU counts. At Day 7, the *exoU-PC*\* strains have both a higher mutation frequency than the parent strains as well as a higher mutation frequency compared to Day 1. *exoS* strain S-215PC\* had a lower frequency at Day 7 compared to its parent strain as well as a lower frequency compared to Day 1. Surprisingly, *exoS* strain S-139PC\*, which is significantly less fit than its parent strain, has a twofold higher mutation frequency than the parent strain at Day 7. However, its mutation frequency at Day 7 decreased almost threefold from Day 1 (Figure 4). Therefore, mutation frequencies seem to generally correlate with fitness results.

## DISCUSSION

Pseudomonas aeruginosa is considered one of six bacteria that pose an immediate threat to public health, according to the Infectious Diseases Society of America, due to its increasing prevalence, broad arsenal of virulence factors, and emergence of resistance to all available antibiotics (Boucher et al., 2009). In its recent report entitled “Antibiotic Resistance Threats in the United States” the Centers for Disease Control named *P. aeruginosa* a serious threat that requires prompt action and continual monitoring to prevent a worsening of the problem of resistance (Centers for Disease Control [CDC], 2013). Notably, resistance rates of *P. aeruginosa* to the once-effective fluoroquinolone (FQ) antibiotics are now greater than 30% in the United States, with many of those strains also multi-drug resistant (Rosenthal et al., 2012).

<figure><img src="image_55.png" /><figcaption>**FIGURE 3** | Fitness of aged strains. Strains were collected at the end of a 7-day primary competition experiment (PC\* vs. parent) with and without the addition of sub-inhibitory concentration of levofloxacin (+LVX) and subsequently re-competed in a secondary competition experiment (aged vs. un-aged) with or without levofloxacin at the same concentration. Results shown reflect the average fitness of aged strains after 48 h of competition. Experiments were performed in duplicate. Error bars = SEM.</figcaption></figure>
<figure><img src="image_56.png" /><figcaption>**FIGURE 4 |** Mutation frequency of PC\* mutants vs. parent strains measured during competition experiments. The frequency of spontaneous rifampicin resistance was used to estimate mutation frequency at each time point during a 7-day competition experiment. Bars represent fold difference of the PC\* vs. parent at Day 7 and the fold difference at Day 7 vs. Day 1 for each PC\* strain. Error bars = SEM. \*p < 0.05; \*\*p < 0.01.</figcaption></figure>

During acute disease, *P. aeruginosa* utilizes the toxins of the type III secretion system to circumvent the host immune system and establish infection. Of the four exotoxins, *exoU* is the most virulent, encoding a potent phospholipase that disrupts the plasma membrane and leads to rapid cell death (Sato et al., 2003). ExoU activity induces excessive inflammation and tissue damage in the host as well as increased bacterial dissemination that can lead to septic shock (Kurahashi et al., 1999) and higher rates of mortality compared to infections with ExoS-secreting strains (Shaver and Hauser, 2004; Zhang et al., 2014; Peña et al., 2015).

As the problem of antibiotic resistance continues to worsen, it is becoming apparent that the evolution of virulence factors and antibiotic resistance cannot be considered strictly independent processes (Beceiro et al., 2013; Hauser, 2014). Previously, we found that infection by FQ-resistant *P. aeruginosa* was an independent predictor for threefold higher mortality or prolonged illness by an additional 5 days compared to those infected with FQ-susceptible strains (Hsu et al., 2005). In a separate study, we reported that among patients from whom *P. aeruginosa* was isolated from the respiratory tract, strains with the combined traits of *exoU* and FQ-resistance were much more likely to cause pneumonia than *exoS*, FQ-resistant strains or either trait alone (Sullivan et al., 2014).

Analysis of 270 of our *P. aeruginosa* clinical isolates led to the observation that *exoU* strains are not only enriched in the FQ resistant sub-population, but are also more likely to have acquired two or more target site mutations than *exoS* strains, especially in the *parC* gene (Agnello and Wong-Beringer, 2012).

In order to study the biological effects of a resistance-conferring mutation in a controlled, isogenic background, we adapted a technique for inserting point mutations into bacterial genomes for use in our clinical isolates (Swingle et al., 2010). Using the technique of oligonucleotide recombination, we created 6 FQ-resistant mutants (three *exoU* and three *exoS*) (Agnello and Wong-Beringer, 2014) from clinical strains by inserting a mutation into the *parC* gene.

Because the target site mutation, we inserted in *parC* rarely occurs in clinical isolates without a pre-existing mutation in *gyrA* (Jalal and Wretlind, 1998), we chose clinical strains that had a pre-existing *gyrA* mutation (Thr83Ile) in order to mimic FQ-resistant strains encountered in the clinical setting. These specific point mutations in *gyrA* and *parC* are commonly found in FQ-resistant clinical strains of *P. aeruginosa* (Nakano et al., 1997; Mouneimné et al., 1999; Higgins et al., 2003; Agnello and Wong-Beringer, 2012). The goal of the current study was to assess the biological effects on fitness of the *parC* mutation and determine if the magnitude of the effects differ in *exoU* vs. *exoS* strains.

The acquisition of resistance is generally thought to be accompanied by a fitness cost to the bacterium (Andersson and Levin, 1999); however, there are many reports of neutral fitness effects or enhanced fitness due to resistance-conferring mutations. Evidence from FQ-resistant *E. coli*, *S. pneumoniae*, and *N. gonorrhoeae* suggest that a secondary resistance mutation does not further decrease fitness and may restore the low fitness of primary mutants back to wild-type levels (Komp Lindgren et al., 2005; Rozen et al., 2007; Marcusson et al., 2009; Kunz et al., 2012; Machuca et al., 2014). Furthermore, many fitness effects seem to be strain dependent, as was shown in a study of ciprofloxacin-resistant *Campylobacter jejuni*, in which a *gyrA* mutation conferred a high cost to one strain but actually increased fitness for a different strain (Luo et al., 2005). Similar results were seen in *S. pneumoniae*, in which some FQ-resistant mutant strains had increased fitness while others had a significant cost (Balsalobre and de la Campa, 2008). This suggests that fitness effects are highly dependent on strain genetic background, which may explain the differences, we have seen between *exoU* and *exoS* strains.

Head-to-head competition assays are a standard method for investigating the relative fitness of a mutant strain compared to its isogenic parent strain, and it is possible to detect differences in fitness as small as 1% (Andersson and Levin, 1999; Corzett et al., 2013). Strains are mixed together in co-culture, and must compete for the limited available resources (Finkel, 2006; Kraigsley and Finkel, 2009). In most studies, strains are differentiated based on selective growth on antibiotic plates. However, since the *parC* mutation, we inserted did not increase the levofloxacin MIC in all strains, we had to develop a different approach. We took advantage of a Tn7-based system developed by Schweizer (Choi et al., 2005) in order to insert a cassette containing either YFP or CFP under the control of a strong promoter.

The growth of the PC\* strains did not differ dramatically from those of the parents when grown in monoculture; however, differences were seen when strains had to compete for resources in the same culture flask during competition experiments.
Overall, the *parC* mutation imposed a moderate to considerable fitness cost on *exoS* strains, while *exoU* strains were able to better tolerate the mutation. Notably, fitness of *exoU*-PC\* strains ranged from maintaining the wild-type level of fitness to outcompeting the parent strain by more than 10-fold, whereas *exoS*-PC\* strains were consistently less fit than parent strains.

The FQ target site mutation investigated in the current study occurs in a topoisomerase enzyme and therefore may have an effect on the regulation of supercoiling. Common methods for investigating supercoiling levels rely on reporter plasmids that need to be selected for and maintained. Because, we are using clinical isolates, there is a high level of multi-drug resistance that precludes the use of standard selection antibiotics. To circumvent this, we inserted a Tn7 element (Moir et al., 2007) onto the chromosome in which a supercoiling sensitive promoter controls *lux* expression. *exoU*-PC\* mutants were better able to maintain the supercoiling levels of the parent strains, while *exoS*-PC\* mutants showed a more drastic change in supercoiling, as observed by decreased *lux* expression. Other studies have shown that changes in supercoiling are correlated with changes in fitness (Kugelberg et al., 2005; Marcusson et al., 2009), and therefore the regulation of supercoiling may reflect the level of overall fitness and may explain the fitness differences seen in our strains. The ability of *exoU*-PC\* strains to better regulate supercoiling levels under the stress of FQ exposure reflects increased fitness of these strains overall. The supercoiling level of the cell affects global gene expression and replication efficiency, and changes in supercoiling may alter response to environmental stressors, or even modulate pathogenesis in the host (Redgrave et al., 2014).

In the primary competition experiments, *exoU*-PC\* mutants tended to increase in fitness over the course of the 4-day experiment. This suggests that *exoU* strains may be acquiring beneficial adaptations that allow for the compensation of the fitness costs associated with the PC\* mutation. Bacteria have the ability to rapidly evolve compensatory mechanisms to mitigate the fitness costs associated with antibiotic resistance, and compensatory mechanisms can reverse fitness costs without any loss of resistance (Andersson and Hughes, 2010). The *exoU*-PC\* strains that had been 'aged' through a primary competition experiment for 7 days have increased fitness compared to the un-aged strains, while aged *exoS*-PC\* strains have decreased fitness. The results suggest that the compensatory mechanisms in *exoU* strains most likely are acting as a repressor of the negative fitness effects of the *parC* mutation, as opposed to just conferring a general gain in fitness, based on the observation that the aged parent strains did not show as much of an increase in fitness as the PC\* mutants. The observed ability of *exoU* strains to compensate for the costs of FQ-resistance has many clinically negative consequences. Compensation in clinical populations leads to the stabilization of resistant populations without the presence of drug (Andersson and Hughes, 2010). Increased fitness after acquisition of FQ-resistance adds to the already complicated problem of treating infections caused by highly virulent *exoU* strains.

The inability of *exoS*-PC\* strains to regulate supercoiling suggests that the compensatory mechanisms in *exoU* strains are acting to maintain wild-type supercoiling levels in the PC\* mutants, as has been reported in other studies of compensation

of the costs of FQ-resistance (Kugelberg et al., 2005; Marcusson et al., 2009). Although, we did not identify the exact mechanisms responsible for the compensatory effects, we have shown that they are stable since strains were frozen and grown before testing for compensation in secondary competition experiments, and the results were reproducible in repeated experiments. Sequencing of the quinolone-resistance determining regions of *gyrA/B* and *parC/E* revealed no additional mutations had occurred during competition; however, beneficial mutations may have occurred elsewhere. For both *exoU* strains tested, the mutation frequencies correlated with the increase in fitness observed during competition experiments, suggesting that higher mutation frequency may facilitate the acquisition of beneficial mutations that mitigate the fitness costs of the *parC* mutation.

A dramatic increase in fitness occurred in the aged *exoU*-PC\* strains taken from a primary competition experiment in which sub-inhibitory levels (1/8 the MIC) of levofloxacin were added to culture. Although this low level of drug did not affect the growth of strains in the primary competition experiment, when the aged *exoU*-PC\* strains were re-competed under the same concentration of levofloxacin, they were 20–100 times more fit than before aging. In contrast, *exoS*-PC\* strains were dramatically less fit under these circumstances. However, none of the aged PC\* strains had an increase in MIC, nor any additional FQ-resistance mutations in target site genes. These results suggest that although the level of levofloxacin was much below the MIC, highly fit strains were selected for rapidly, more so than in conditions without drug. Also, the highly fit strains were not more resistant, suggesting that perhaps the presence of levofloxacin accelerated the process of compensation for the already present resistance mutations. As sub-inhibitory concentrations of antibiotics are routinely present during treatment due to insufficient dosing or inadequate penetration to certain areas of the body (Baquero and Negri, 1997; Andersson and Hughes, 2014), the implications of our results are alarming and suggest that low levels of antibiotic can rapidly select for highly fit strains, preferentially the highly virulent *exoU*-containing strains. Furthermore, when these highly fit, highly virulent strains are re-introduced to the antibiotic, they will rapidly outcompete all other strains. The sub-inhibitory concentration was also able to select for a *parC* mutation in an *exoU* parent strain, emphasizing the known phenomenon that selection for resistance mutations can occur at sub-inhibitory levels of antibiotic (Baquero et al., 1998; Andersson and Levin, 1999; Gullberg et al., 2011; Andersson and Hughes, 2014).

Overall, these results suggest a potentially lower fitness burden associated with FQ-resistance for *exoU* strains than for *exoS* strains, which in part provides an initial biological explanation for *exoU* strains' greater tendency to acquire FQ-resistance in the clinical setting. Although, we have yet to identify the specific genetic components underlying the fitness differences, we suspect that genes unique to strains with the *exoU* genetic background may contribute to the fitness benefits seen in this study. The *P. aeruginosa* genome consists of a highly conserved core genome, but variability is introduced in the form of genomic islands, which make up the accessory genome. Genes within the islands usually encode accessory activities such as specific
pathogenicity or symbiosis factors (Harrison et al., 2010). The *exoU* gene, along with its chaperone *spcU*, is located on a pathogenicity island, a specialized genomic island. *exoU* has been identified as part of a few different pathogenicity islands. The most highly studied is from the reference strain PA14, in which the *exoU* gene is on an island named PAPI-2 (Kulasekara et al., 2006). Studies with PA14 have shown that virulence is dependent on the presence of the entire island and not just the *exoU* gene alone; therefore, other as yet unknown genes contained on the pathogenicity islands contribute combinatorially to the increased virulence of *exoU* strains (Harrison et al., 2010). Furthermore, pathogenicity in strain PA14 requires the coordinated action of multiple virulence factors, associated with both the core and accessory genomes (Lee et al., 2006). Therefore, it is possible that other genes in the accessory genome in combination with *exoU* may provide fitness benefits to *exoU* strains that allow for increased ability to adapt to the fitness costs of FQ-resistance. Genomic islands have been shown to confer fitness benefits, and the accessory genome of *P. aeruginosa* is an important driver of the ability of strains to persist in a particular environment (Hacker and Carniel, 2001; Ozer et al., 2014).

This study has several limitations. We acknowledge that a limited number of clinical strains and their isogenic mutants were evaluated in the study. Despite having access to a large collection of clinical strains, the selection of strains to create isogenic target site mutants to study the effect of FQ-resistance on fitness proved challenging, as most of the isolates in our collection were found to already contain the resistance-conferring mutation that, we are investigating, due to the high prevalence of FQ resistance in clinical isolates of *P. aeruginosa*. Therefore, we were not able to use those to create isogenic pairs. Furthermore, genetic manipulation of these clinical isolates proved to be difficult, as these strains were not universally amenable to the creation of isogenic mutants via oligonucleotide recombination. Nonetheless, it is worth nothing that the strains evaluated in this study were carefully selected to represent a broad range of characteristics such as varying degrees of FQ resistance, virulence, and clinical outcomes. While the limited

number of strains evaluated in this study may not necessarily represent the genetic variability present among all *exoU* and *exoS* clinical strains, strain-specific differences in fitness effects were observed even among strains with the same *exoU* or *exoS* genetic background, though the trend observed appears to follow similar pattern for strains with the same *exoU* or *exoS* genetic background.

Understanding the fitness costs of antibiotic resistance and possibilities of compensation for these costs is essential for rationally combating the problem of antibiotic resistance. Importantly, this study outlines a useful model with the creation of isogenic clinical strains for investigating the biological costs of resistance in a medically important pathogen and can be applied to other drug-organism pairs.

## AUTHOR CONTRIBUTIONS

MA, AW-B, and SF designed the experiments. MA and AW-B wrote the manuscript. SF edited and provided critical review of the manuscript.

## FUNDING

This work was supported by award number TL1TR000132 from NIH/NCRR/NCATS to MA and award number R21AI073467 from the National Institute of Allergy and Infectious Diseases to AWB. SF was supported in part by U.S. Army Research Office grants W911NF1010444 and W911NF1210321.

## ACKNOWLEDGMENTS

The authors thank Dr. Herbert Schweizer and Dr. Donald Moir for generously sharing plasmids and strains, and Juliana Brondani and Nicole Schrad for assistance with growth and competition experiments.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Agnello, Finkel and Wong-Beringer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# Virulence and Genomic Feature of Multidrug Resistant *Campylobacter jejuni* Isolated from Broiler Chicken

Haihong Hao¹,²,³†, Ni Ren²,³†, Jing Han⁴, Steven L. Foley⁴, Zahid Iqbal², Guyue Cheng¹,
Xiuhua Kuang², Jie Liu², Zhenli Liu², Menghong Dai²*, Yulian Wang¹* and
Zonghui Yuan¹,²,³*

¹ National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China, ² MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Wuhan, China, ³ Hubei Collaborative Innovation Center for Animal Nutrition and Feed Safety, Huazhong Agricultural University, Wuhan, China, ⁴ Division of Microbiology, FDA, National Center for Toxicological Research, Jefferson, AR, USA

## OPEN ACCESS

**Edited by:**
Axel Cloeckaert,
French National Institute for
Agricultural Research (INRA), France

**Reviewed by:**
Elaine Allan,
University College London, UK
Xian-Zhi Li,
Health Canada, Canada

*Correspondence:
Zonghui Yuan
yuan5802@mail.hzau.edu.cn
Yulian Wang
wangyulian@mail.hzau.edu.cn
Menghong Dai
daimenghong@mail.hzau.edu.cn

† These authors have contributed
equally to this work.

**Specialty section:**
This article was submitted to
Antimicrobials, Resistance and
Chemotherapy,
a section of the journal
Frontiers in Microbiology

**Received:** 14 May 2016
**Accepted:** 26 September 2016

**Published:** 14 October 2016

**Citation:**
Hao H, Ren N, Han J, Foley SL, Iqbal Z, Cheng G, Kuang X, Liu J, Liu Z, Dai M, Wang Y and Yuan Z (2016) Virulence and Genomic Feature of Multidrug Resistant Campylobacter jejuni Isolated from Broiler Chicken. *Front. Microbiol.* 7:1605. doi: 10.3389/fmicb.2016.01605

The aim of this study was to reveal the molecular mechanism involved in multidrug resistance and virulence of *Campylobacter jejuni* isolated from broiler chickens. The virulence of six multidrug resistant *C. jejuni* was determined by *in vitro* and *in vivo* methods. The *de novo* whole genome sequencing technology and molecular biology methods were used to analyze the genomic features associated with the multidrug resistance and virulence of a selected isolate (*C. jejuni* 1655). The comparative genomic analyses revealed a large number of single nucleotide polymorphisms, deletions, rearrangements, and inversions in *C. jejuni* 1655 compared to reference *C. jejuni* genomes. The co-emergence of Thr-86-Ile mutation in *gyrA* gene, A2075G mutation in 23S rRNA gene, *tetO*, *aphA* and *aadE* genes and pTet plasmid in *C. jejuni* 1655 contributed its multidrug resistance to fluoroquinolones, macrolides, tetracycline, and aminoglycosides. The combination of multiple virulence genes may work together to confer the relative higher virulence in *C. jejuni* 1655. The co-existence of mobile gene elements (e.g., pTet) and CRISPR-Cas system in *C. jejuni* 1655 may play an important role in the gene transfer and immune defense. The present study provides basic information of phenotypic and genomic features of *C. jejuni* 1655, a strain recently isolated from a chicken displaying multidrug resistance and relatively high level of virulence.

**Keywords:** *Campylobacter jejuni*, broiler chicken, multidrug resistance, virulence, *de novo* genome sequencing

## INTRODUCTION

*Campylobacter jejuni* is one of the most important foodborne pathogens worldwide (Abril et al., 2010). The macrolides (mainly erythromycin and azithromycin) and fluoroquinolones are the empirical drugs of choice for treatment of campylobacteriosis (Allos, 2001). Other antimicrobial agents, including gentamicin, meropenem, and clindamycin are alternative therapies (Iovine et al., 2008).

The National Antimicrobial Resistance Monitoring System (NARMS) in the USA and Danish Integrated Antimicrobial Resistance Monitoring and Research Program (DANMAP) data showed that multidrug resistance in *C. jejuni* has been very rare (0.3-0.7%) from retail chicken meat (DANMAP, 2014; NARMS, 2015). Multidrug resistant *C. jejuni* have been isolated from chicken
farms in China recently (Chen et al., 2010; Hao et al., 2015; Wang et al., 2016). The multidrug resistant C. jejuni in chicken may greatly threaten food safety and human public health, therefore it is important to investigate the virulence potential and mechanism involved in multidrug resistance and virulence of C. jejuni.

Although genomes of many human-source C. jejuni (e.g., NCTC11168, 81-176, 260.94, HB93-13, CF93-6, and 269.97) have been sequenced, only three genomes of C. jejuni (305, RM1221, and 81-176-DRH212) from poultry have been obtained (Parkhill et al., 2000; Fouts et al., 2005; Hofreuter et al., 2006). C. jejuni RM1221 (ATCC BAA-1032) is a chicken isolate with unique lipoolgosaccharide and ability to colonize chicken skin (Fouts et al., 2005). C. jejuni 305 is a turkey isolate with stress tolerance (Takamiya et al., 2011). C. jejuni 81-176-DRH212 is a C. jejuni 81-176 variant with enhanced fitness in the chicken gastrointestinal tract (Johnson et al., 2014). The genome sequences of broiler C. jejuni isolates with multidrug resistance and high virulence have not been published previously. In order to investigate the mechanisms involved in the multidrug resistance and increased virulence in C. jejuni isolated from broiler chickens in China, the genomic profile of a C. jejuni isolate with relative higher virulence and multidrug resistance was determined by the de novo sequencing technology in the present study.

# MATERIALS AND METHODS

## Isolation and Identification of Chicken

### C. jejuni

Six strains (1442, 1447, 1614, 1622, 1655, and 1685) were isolated from caecum of healthy broiler chicken in the chicken farms located in the center of China in 2013. These farms have a long history of usage of different antimicrobial drug for prevention and treatment chicken disease. These strains were confirmed as C. jejuni by classic biochemical test and PCR amplification of the 16S rRNA, mapA and vs1 genes (Stucki et al., 1995; Hao et al., 2013, 2015). The C. jejuni isolates were grown on Mueller-Hinton (MH) agar supplemented with 5% sheep blood at 42°C under microaerobic conditions (5% O₂, 10% CO₂, and 85% N₂) for 24-48 h.

## Antimicrobial Susceptibility Test

The minimum inhibitory concentrations (MICs) of erythromycin (ERY), tylosin (TYL), ciprofloxacin (CIP), enrofloxacin (ENR), doxycycline (DOX), tetracycline (TET), amikacin (AMK), and gentamicin (GEN) were determined using the agar dilution method as recommended by the Clinical and Laboratory Standards Institute (CLSI) M31-A3 guidelines (CLSI., 2008). The C. jejuni ATCC33560 was used as quality control for the MIC determination.

## Preliminary Pathogenicity Test

Newly hatched broiler chickens were purchased from Zhengda Limited Company (Wuhan, China). Prior to the experiment, all the chickens tested negative for C. jejuni strains by C. jejuni isolation and identification methods. The chickens were randomly divided into 8 groups with 7 chickens in each group.

The chickens in groups 1-7 were administrated once with $5 \times 10^5$ CFU of each C. jejuni strain (1442, 1447, 1614, 1622, 1655, 1685, and RM1221) by oral injection, respectively. The eight group served as the negative control with no bacterial infection. The clinical symptoms and mortality of the chickens in each group was observed daily. The colonization rate of each C. jejuni strain was determined using selective medium containing 32 µg/mL erythromycin.

## Cytotoxin Assay

The murine macrophage RAW264.7 cell line was used to evaluate the cytotoxic effects of the six C. jejuni isolates. The tissue culture cytotoxin assay was carried out as previously described (Guerrant et al., 1987) with some modification. Briefly, C. jejuni was treated by 2000 µg/ml polymyxin B for 1 h at 37°C (Ashkenazi and Cleary, 1990) and centrifuged at 8000 rpm for 20 min. The supernatant were filtered through 0.22 µm filter. Purified shiga toxin (Chinese Center for Disease Control and Prevention) and 0.3% Triton X-100-PBS were used as positive controls, and polymyxin B-treated broth and polymyxin B-PBS (phosphate-buffered saline) were used as negative controls. Suspensions of murine macrophage RAW264.7 cells (100 µl; $5 \times 10^5$ cells) were placed in 96-well flat-bottom microtiter plates and allowed to adhere for 1 to 3 h to form the tissue culture monolayers. Serial twofold dilutions of the prepared C. jejuni filtrates were added to the tissue culture monolayers in 100 µl volumes. The monolayers were incubated with the filtrates at 37°C in 5% CO₂ for 24 h. The monolayers were then examined by phase-contrast microscopy for the percentage of cells rounded. Cell death was determined by trypan blue dye uptake (A540 value) and correlated with cell morphology after Giemsa staining. The index of cytotoxin effect was calculated by the formula.

$$100 \times \left[ 1 - \frac{A_{540}(\text{test}) - A_{540}(\text{positive})}{A_{540}(\text{negative}) - A_{540}(\text{positive})} \right].$$

## Biofilm Assays

To measure the biofilm formation of the six C. jejuni strains, crystal violet staining was used as described previously for C. jejuni and other bacteria (Asakura et al., 2007; Fields and Thompson, 2008; McLennan et al., 2008; Reuter et al., 2010) with some modification. Briefly, the 200 µl of C. jejuni fresh culture (OD₆₀₀ = 0.05) was added to 96-well flat-bottom microtiter plates. Plates were incubated without shaking at 42°C under microaerobic conditions for 24, 48, and 72 h. For crystal violet staining, each well was washed with PBS three times to remove the planktonic cells. The 200 µl of methanol were added and incubated for 15 min and then dried at room temperature. Then 200 µl of 0.1% Zucker crystal violet solution were added, and the plates were incubated at room temperature for 5 min. Unbound crystal violet was washed off with PBS, and the plates were dried at 60°C. Bound crystal violet was dissolved in 30% glacial acetic acid for 10 min. The absorbance was determined using a plate reader at 570 nm. The wells with sterile medium were used as blank control. The blank corrected absorbance values of C. jejuni strains were used for reporting biofilm production. Assays were repeated at least three times with three technical replicates.
## LD₅₀ Determination

Based on the results from the preliminary pathogenicity experiments with chickens, cytotoxin testing and biofilm assays, three *C. jejuni* isolates (1442, 1622, and 1655) were selected to further determine their median lethal dose (LD₅₀) using 2 days old chicken orally or intraperitoneally infected with a range of concentration (10⁵–10⁷ CFU) of each *C. jejuni* isolate. All the chickens tested negative for *C. jejuni* prior to inoculation using the *C. jejuni* isolation and identification methods described above. The chickens were randomly divided into six groups with 35 chickens in each group. The chickens in each group were orally or intraperitoneally administrated with 0, 10⁵, 10⁶, or 10⁷ CFU of the *C. jejuni* isolates, respectively. Seven chickens were inoculated with each of the dilution of the test strains.

## Adhesion and Invasion Assay

The adhesion and invasion of these three *C. jejuni* strains (1442, 1622, and 1655) was determined as previously described (Almofti et al., 2011a). Briefly, 5.0 × 10⁷ CFU/mL of the *C. jejuni* strain was used to inoculated the monolayers of macrophage RAW264.7 cells at multiplicity of infection (MOI) of 100. The infected monolayers were incubated for 3 h to allow the occurrence of adhesion and invasion. For determination of the total number of adherent and internalized bacteria, the monolayers were washed three times with Dulbecco's Modified Eagle's Medium (DMEM) without antibiotic to remove the extracellular unbound bacteria. The monolayers were then lysed to release the intracellular bacteria. For determination of the invading bacteria, the monolayers were washed twice with aspirated DMEM medium and 100 mg/ml gentamicin was added for 1 h to kill the extracellular and bound bacteria. The monolayers were then washed three times and lysed to release intracellular bacteria. The number of adherent bacteria was obtained by subtraction of the internalized bacteria number from total number of adherent and internalized bacteria.

## Intracellular Survivability Assay

To determine the intracellular survivability of *C. jejuni* within macrophage RAW264.7, the invasion period of each *C. jejuni* strain (1442, 1622, and 1655) was extended to 3, 6, 10, 16, 24, 48, and 72 h post-infection. Cells were washed and lysed as previously described in the adhesion and invasion assay. The surviving intracellular bacteria were enumerated by plating serial dilutions on blood agar and counting the resultant colonies.

## Motility Test

To determine the migration of the three selected strains (1442, 1622, and 1655), a fresh culture of *C. jejuni* strain was inoculated into MH broth and cultured to their logarithmic growth phase. Then 3 µl of bacteria with consistent concentration were stabbed into 0.4 % MH agar. Plates were incubated at 42°C under microaerophilic conditions for 24 h and the motility was scored by measuring the diameter of the growth in each plate. The experiment was performed in triplicate.

## De Novo Whole-Genome Sequencing Of
*C. jejuni* 1655

Total genomic DNA of *C. jejuni* 1655 was extracted using the TIANamp Bacteria DNA kit according to the manufacturer's protocol. The genomic DNA was sent to Shanghai Biotechnology Corporation for the *de novo* whole genome sequencing performed in a HiSeq 2500 platform using a multiplexed, 2 × 100 nucleotide paired end approach (Illumina). The sequence analysis and assembly were carried out using CLC Genomics Workbench (ver. 6.0., Qiagen). Prediction and identification of the main components of the genome, including open reading frames (ORFs), tRNA, rRNA, ncRNA, CRISPR-Cas system, and repeat elements, were conducted using software of Glimmer 3.02 and some other online tools.

The nucleotides and predicted proteins of 1655 were compared with previously sequenced *C. jejuni* genomes in GenBank using updated nt and nr databases with BLAST software. The genomes used as reference sequences for the comparative genomic analysis were *C. jejuni* 81–176, *C. jejuni* NCTC11168, *C. jejuni* RM1221. The comparative genomic analysis was performed using BLASTN, BLASTX, Mummer and Quast. The sequence data from *C. jejuni* 1655 was compared to the results of antimicrobial resistance and virulence to identify genetic factors that correspond to the observed mechanisms.

## Nucleotide Sequence Accession Numbers

The whole genome sequence of *C. jejuni* 1655 has been deposited at DDBJ/ENA/GenBank under the accession MDDM00000000.

## Ethics Statement

All the experimental procedure in this study was performed according to the guidelines of the committee on the use and care of the laboratory animals in Hubei province China. The study was approved by Animal Ethics Committee of Huazhong Agricultural University (hzauch 2014-002) and the Animal Care Center, Hubei Science and Technology Agency in China (SYXK 2013-0044). These experiments were in line with national regulations about animal welfare ethics. All the animals were monitored throughout the study for any adverse effect signs. All efforts were made to minimize suffering of animals.

## RESULTS

### Minimum Inhibitory Concentration (MIC)

The minimum inhibitory concentrations (MICs) of different antimicrobial agents against the 6 *C. jejuni* isolates (1442, 1447, 1614, 1622, 1655, and 1685) were presented in **Table 1**. Each isolate exhibited resistance to all the tested drugs, while three (1622, 1655, and 1685) showed higher-level MICs to erythromycin and gentamicin than the others.

### Pathogenicity of *C. jejuni* Isolates on
Chicken

After oral infection with 10⁵ CFU of the *C. jejuni* isolates, no clinical change was observed in two groups infected with 1442 or 1447, while the other four isolates (1614, 1622, 1655, and 1685) and RM1221 caused different degrees of diarrhea and bloody
<table><caption>TABLE 1 | MICs of different antimicrobial agents against six *C. jejuni* isolates (µg/mL).</caption><thead><tr><th rowspan="2">Strains</th><th colspan="8">MICs of different antimicrobial agents</th></tr><tr><th>ERY</th><th>TYL</th><th>ENR</th><th>CIP</th><th>TET</th><th>DOX</th><th>GEN</th><th>AMK</th></tr></thead><tbody><tr><td>1442</td><td>128</td><td>&gt;256</td><td>64</td><td>128</td><td>128</td><td>32</td><td>64</td><td>16</td></tr><tr><td>1447</td><td>64</td><td>&gt;256</td><td>32</td><td>8</td><td>128</td><td>32</td><td>1</td><td>8</td></tr><tr><td>1614</td><td>256</td><td>&gt;256</td><td>0.25</td><td>16</td><td>64</td><td>64</td><td>&gt;256</td><td>4</td></tr><tr><td>1622</td><td>512</td><td>&gt;256</td><td>256</td><td>128</td><td>&gt;256</td><td>32</td><td>&gt;256</td><td>64</td></tr><tr><td>1655</td><td>512</td><td>&gt;256</td><td>32</td><td>64</td><td>256</td><td>32</td><td>&gt;256</td><td>8</td></tr><tr><td>1685</td><td>512</td><td>&gt;256</td><td>16</td><td>32</td><td>64</td><td>32</td><td>&gt;256</td><td>16</td></tr><tr><td>RM1221</td><td>0.5</td><td>2.0</td><td>0.5</td><td>0.125</td><td>0.5</td><td>0.25</td><td>0.5</td><td>0.5</td></tr></tbody></table>

ERY, Erythromycin; TYL, Tylosin; ENR, Enrofloxacin; CIP, Ciprofloxacin; TET, tetracycline; DOX, Doxycycline; GEN, Gentamicin; AMK, Amikacin.

<figure><img src="image_58.png" /><figcaption>FIGURE 1 | Colonization change of *C. jejuni* isolates in chicken after inoculation. The Y-axis is the number (Log₁₀ CFU/kg feces) of each strain colonizing the birds at different days. The asterisk (*) and (**) represent statistical significant difference with *P* ≤ 0.05 and *P* ≤ 0.01 comparing with *C. jejuni* RM1221, respectively.</figcaption></figure>

stools, respectively. The clinical signs of three strains (1614, 1685, and RM 1221) were recovered at day 4, while serious diarrhea caused by 1622 and 1655 was sustained for over 8 and 10 days, respectively (Table S1). Therefore, 1655 exhibited relative higher pathogenicity on chickens than RM1221 and other five *C. jejuni* isolates. Within 15 days, the mortality of all the strains was 0% following oral inoculation of 2 days-old chicken.

## Colonization of *C. jejuni* Isolates in Chicken

After oral administration with 5 × 10⁵ CFU of the *C. jejuni* isolates to 2-days old chickens, all the strains could colonize chickens' intestinal tract. Fecal samples were obtained at different time points (2, 4, 6, 8, and 10 days). RM1221 colonized at

concentration of 10⁵–10⁷ CFU/kg feces at day 2 and day 4, but the concentration was reduced to less than 10⁴ CFU/feces at day 10 (Figure 1). The concentrations of five isolates (1442, 1447, 1622, 1655, and 1685) were higher than 10⁴ CFU/kg feces within the ten days (Figure 1). Comparing with the colonization of RM1221, three isolates (1622, 1655, and 1685) exhibited significantly stronger colonization (Figure 1).

## Cytotoxin of the Six *C. jejuni* Isolates in Macrophage Cells

Figure 2 showed the killing effect (index) of cytotoxin released by six strains (1442, 1447, 1614, 1622, 1655, and 1685) on murine
## Cytotoxin production of C. jejuni

<figure><img src="image_59.png" /></figure>

**FIGURE 2** | Cytotoxic production of C. jejuni isolates in murine macrophage RAW264.7 cell. The Y-axis is the index of cytotoxic production of each strain. The results were obtained from three independent repeats. The asterisk (*) and (**) represent statistical significant difference with *P* ≤ 0.05 and *P* ≤ 0.01 comparing with C. jejuni RM1221, respectively.

## Biofilm formation of C. jejuni strains

<figure><img src="image_60.png" /></figure>

**FIGURE 3** | Biofilm formation of C. jejuni isolates at different time points under ordinary conditions. The Y-axis is the OD<sub>570</sub> value of crystal violet in biofilm. The results were obtained from three independent experiments. The asterisk (*) and (**) represent statistical significant difference with *P* ≤ 0.05 and *P* ≤ 0.01 comparing with C. jejuni RM1221, respectively.

macrophage RAW264.7. The killing effect of cytotoxin from all the strains was lower than 80%. However, compared to RM 1221, significant differences of the index of cytotoxin were observed in these C. jejuni strains. Among them, 1442, 1622, and 1655 seemed to release more cytotoxin and therefore exhibited higher killing effect on murine macrophage RAW264.7.

## Biofilm Formation of the Six C. jejuni Isolates

Different level of biofilm formation was observed in each C. jejuni strain (Figure 3). It seemed that the level of biofilm formation had positive correlation with the incubation time. The highest

level of biofilm formation was occurred after 72 h incubation (Figure 3). Compared to RM1221, a significant difference of biofilm formation was observed in three isolates (1614, 1655, and 1685) after each incubation time, indicating that these three strains may have stronger ability to form biofilm (Figure 3).

## LD₅₀ of the Three Selected C. jejuni Isolates on Chicken

From the preliminary pathogenicity testing on chicken, cytotoxin testing and biofilm assays, three isolates (1442, 1622, and 1655) were selected for LD₅₀ determination. As the result shown in Table 2, different fatality rates were observed in different groups.
After oral infection, the highest concentration (3.70 × 10⁷ CFU) of 1442 and 1622 could cause mortality rate of 0% (0/7) and 28.6% (2/7) respectively, while 3.7 × 10⁷ CFU of 1655 cause fatality rate of 55.6% (4/7). For intraperitoneal infection, 3.7 × 10⁶ CFU of 1442 and 1622 only leaded to one chicken death, while the lowest concentration (3.7 × 10⁵ CFU) of 1655 leaded to 100% death of chickens. The 1655 exhibited highest pathogenicity on chicken with the calculated LD₅₀ of 8.45 × 10⁷ CFU for oral infection and LD₅₀ of less than 3.7 × 10⁵ CFU for Intraperitoneal infection (Table 2).

## Adhesion and Invasion of C. jejuni on Macrophage RAW264.7

The three isolates (1442, 1622, and 1655) exhibited remarkable higher adhesion and invasion to macrophage cell RAW264.7 than RM1221 (Figure 4). The significant change of adhesion to macrophage cells (P < 0.01) was observed in 1622 and 1655. However, there was no significant difference in the adhesion and invasion between three selected isolates (1442, 1622, and 1655).

## Intracellular Survivability of C. jejuni in Macrophage RAW264.7

The intracellular survivability of the three strains (1442, 1622, and 1655) was shown in Figure 5. Comparing with RM1221, three selected strains showed remarkable advantage in intracellular survivability in murine macrophage RAW 264.7. RM1221 had short survival time (24 h), while three strains were able to survive for more than 48 h, although a considerable decrease in the number of all internalized was observed. Among them, 1622 and 1655 exhibited highest survivability at 72 h. At each time point, the post-infection number of surviving 1655 was higher than 1622, suggesting that 1655 strain had strongest survivability.

## Motility of the Three Selected C. jejuni

As shown in Figure 6, there was apparent difference between diameter growth rings of the three strains (1442, 1622, and 1655) on 0.4% MH agar plate. RM1221 and 1622 were not motile, while 1655 and 1442 had a strong motility.

## Whole-Genome Features of C. jejuni 1655

Based on the above in vitro and in vivo studies, 1655 was selected for subsequent whole genome sequencing to analyze the potential genetic mechanisms involved in the multidrug resistance and high virulence.

The basic genome information of 1655 and other three reference strains (RM1221, 81–176, and NCTC11168) are summarized into Table 3. The 1655 genome was comprised of a chromosome and a tetracycline resistance plasmid pTet. The pTet plasmid of 1655 had 98% homology with pTet plasmid in 81176. The genome of 1655 was 1720, 061 bp long and contained 1733 predicted coding regions. The genomes of two chicken original strains (1655 and RM1221) were significantly larger than that of two human isolates (C. 81–176 and NCTC11168). The GC content of 1655 was 31.36%, consistent with the reference genome sequences.

<table><caption>TABLE 2 | LD₅₀ of the three multidrug resistant strains on 2 days old chickens.</caption><thead><tr><th>Infection route</th><th>Strains</th><th>Infection dose of (CFU)</th><th>Number of chickens</th><th>Number of Dead chicken</th><th>LD<sub>50</sub></th></tr></thead><tbody><tr><td rowspan="5">Oral infection</td><td rowspan="4">1442</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>0</td><td rowspan="4">NA</td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>0</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>0</td></tr><tr><td>0</td><td>7</td><td>0</td></tr><tr><td rowspan="4">1622</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>2</td><td rowspan="4">NA</td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>0</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>0</td></tr><tr><td>0</td><td>7</td><td>0</td></tr><tr><td rowspan="4">1655</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>4</td><td rowspan="4">8.45 × 10<sup>7</sup></td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>1</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>1</td></tr><tr><td>0</td><td>7</td><td>0</td></tr><tr><td rowspan="10">Intraperitoneal infection</td><td rowspan="4">1442</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>2</td><td rowspan="4">NA</td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>1</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>0</td></tr><tr><td>0</td><td>7</td><td>0</td></tr><tr><td rowspan="4">1622</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>1</td><td rowspan="4">NA</td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>1</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>0</td></tr><tr><td>0</td><td>7</td><td>0</td></tr><tr><td rowspan="4">1655</td><td>3.70 × 10<sup>7</sup></td><td>7</td><td>7</td><td rowspan="4">&lt;3.70 × 10<sup>5</sup></td></tr><tr><td>3.70 × 10<sup>6</sup></td><td>7</td><td>7</td></tr><tr><td>3.70 × 10<sup>5</sup></td><td>7</td><td>7</td></tr><tr><td>0</td><td>7</td><td>0</td></tr></tbody></table>

The genome sequence of 1655 was composed by 35 large contigs (Figure 7). The cluster of orthologous groups (COG) assignment for predicted gene products were shown in the third circle from the outside in Figure 7. A total of 1733 putative gene products were assigned to COG identifications classified into 19 COG categories. Three copies of rRNA gene cluster (5s rRNA, 16s rRNA, and 23s rRNA) and 40 tRNA genes were identified on the C. jejuni 1655 chromosome.

The global alignment of four genomes (RM1221, 81–176, NCTC11168, and 1655) is shown in Figure 8. High similarity was observed in the genome of three reference strains (RM1221, 81–176, and NCTC11168). However, disordered distribution, deletions and rearrangements were observed in the genome of 1655 when compared with genome of three reference strains.

## Resistance Determinants in C. jejuni 1655

The genome sequencing data showed that 1655 contained T86I mutation in the gyrA gene. Some mutations (e.g., A2075G mutation, C2113T, position 1732–1791 mutations) were found in the 23S rRNA of C. jejuni 1655. The ribosomal L4 contained V196A mutation and ribosomal L22 had A74G mutation. The tetracycline resistant gene tetO was located in pTet plasmid. The C. jejuni 1655 also contained aphA and aadE exogenous genes
## Adhesion and Invasion of *C. jejuni* strains

<figure><img src="image_61.png" /></figure>

**FIGURE 4** | Adhesion (left) and invasion (right) of *C. jejuni* strains in macrophage RAW264.7 cell. The Y-axis is the mean of log10 CFU/mL of each strain in the cells. The results were obtained from three independent experiments. The asterisk (*) and (**) represent statistical significant difference with *P* ≤ 0.05 and *P* ≤ 0.01 comparing with *C. jejuni* RM1221, respectively.

## Intracellular survivability of *C. jejuni* strains

<figure><img src="image_62.png" /></figure>

**FIGURE 5** | Intra-macrophage survival assay of three selected *C. jejuni* strains in macrophage RAW264.7 cell. The Y-axis is the mean of log10 CFU/mL of each strain in the cell. The asterisk (*) and (**) represent statistical significant difference with *P* ≤ 0.05 and *P* ≤ 0.01 comparing with *C. jejuni* RM1221, respectively.

which mediated resistance to aminoglycosides. No mutation was found in the regulators (CmeR and CosR) of CmeABC efflux pumps.

## Virulence Associated Genes in *C. jejuni* 1655

A large number of virulence associated genes were found in the genome of 1655 (Table 4). Among the selected genes involved in flagella synthesis and assembly (*flaA*, *flaC*, *flgA*,

*flgB*, *flhB*, *fliM*, and *fliY*), the *flaC* was found in the genome of 1655 and 11168. Two genes (*ciaB* and *nlpC*) associated with invasion and three genes (*cadF*, *galE*, and *peb2*) related to adhesion were present in 1655 but not in RM1221. Compared to the genes of CPS biosynthesis system in RM1221, the genome of 1655 contained a restriction modification enzyme, sugar nucleotidyltransferase, capsule polysaccharide protein, and alginate O-acetyltransferase. The genome of 1655 also contained some genes (*cfrA* and *ExbB-ExbD-TonB*) involved
<figure><img src="image_63.png" /></figure>

RM1221
0.5cm

<figure><img src="image_64.png" /></figure>

1622
0.5cm

<figure><img src="image_65.png" /></figure>

1442
2.9cm

<figure><img src="image_66.png" /></figure>

1655
4.6cm

**FIGURE 6** | Motility of the three selected *C. jejuni* strains on 0.4% MH plate. The motility is positively correlated to the diameter of growth ring of each strain. The diameter of spotted colonies was 0.5 cm.

in iron uptake system, while RM1221 lacked TonB and 81176 lacked *cfrA* and TonB13. The IS606 transposase, ISHa1675 transposase B and prophage Lp2 protein 6 were also found in the genome of 1655. ISHa1675 transposase B was not found in the genome of three reference strains. The sequence of prophage Lp2 protein in *C. jejuni* 1655 had 99% homology to that in 81-176. The pVir plasmid which previously found in 81-176, was not found in 1655. Three predicted genes of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated system were found in the genome of 1655. They may encode Csn1, Cas1, and Cas2 proteins respectively.

DISCUSSION

Compared to the genomes of reference strains (NCTC11168, 81-176, RM1221), the genome of 1655 contained some gene inversion, disordered distribution, deletions and rearrangements. The genome difference may be attributed to their different biological characteristics and different evolutional environment. NCTC11168 was originally isolated from a case of human enteritis (Parkhill et al., 2000). 81-176 was originally isolated from a diarrheal outbreak associated with raw milk consumption and exhibited high invasion and high pathogenicity for monkeys and humans (Korlath et al., 1985; Black et al., 1988; Tribble et al., 2010). *C. jejuni* RM1221 (ATCC BAA-1032) was isolated from chicken and showed low virulence (Fouts et al., 2005). 1655 was a multidrug resistant strain

<table><caption>TABLE 3 | Genomic information of target bacteria 1655 and reference strains.</caption><tr><td>Genomic contents</td><td>1655</td><td>NCTC11168</td><td>RM1221</td><td>81-176</td></tr><tr><td>Refseq number</td><td></td><td>NC_002163.1</td><td>NC_003912.7</td><td>NC_008787</td></tr><tr><td>Homology (%)</td><td>-</td><td>88.78</td><td>90</td><td>90.44</td></tr><tr><td>Genome size (bp)</td><td>1720061</td><td>1641481</td><td>1777831</td><td>1616554</td></tr><tr><td>G+C (%)</td><td>31.36</td><td>30.5</td><td>30.31</td><td>30.6</td></tr><tr><td>Predicted coding region</td><td>1733</td><td>-</td><td>1898</td><td>1770</td></tr><tr><td>CDS</td><td>1732</td><td>1668</td><td>1783</td><td>1680</td></tr><tr><td>Proteins</td><td>-</td><td>1572</td><td>1783</td><td>1449</td></tr><tr><td>Pseudo gene</td><td>323</td><td>40</td><td>58</td><td>35</td></tr><tr><td>rRNA</td><td>9</td><td>9</td><td>9</td><td>9</td></tr><tr><td>tRNA</td><td>40</td><td>43</td><td>44</td><td>44</td></tr><tr><td>Other RNA</td><td>326</td><td>4</td><td>4</td><td>2</td></tr></table>

isolated from chicken fecal samples that exhibited relative higher virulence, as evidence by its higher pathogenicity to chickens, colonization of the chicken intestinal tract, cytotoxin production, biofilm formation, adhesion/invasion/intracellular survivability to macrophage cell and higher motility.

1655 had multidrug resistance to fluoroquinolones, macrolides, tetracyclines and aminoglycosides. The single T86I mutation in *gyrA* gene contributed to its high-level resistance to FQs (Luangtongkum et al., 2009). High level macrolide resistance in *C. jejuni* 1655 was likely due to A2075G mutation in 23S rRNA (Hao et al., 2009; Luangtongkum et al., 2009; Hao et al., 2010). Although there were some other mutations and deletions in *gyrB*, 23S rRNA genes and ribosomal L4/L22, the function of these mutations on antimicrobial resistance was not evident. The high-level resistance to tetracycline was mediated by *tetO* gene which was located in pTet plasmid (Avrain et al., 2004). The pTet plasmid in 1655 was identical to the one found in 81-176 (Bacon et al., 2002). As a mobile gene element, pTet plasmid may act as a vehicle to pick up and spread multiple antibiotic resistance genes and virulence genes in *C. jejuni* (chen et al., 2013). The *aadE* and *aphA-3* genes in 1655 could explain its resistance to amikacin and gentamicin (Gibreel et al., 2004; Iovine, 2013).

Generally it has been through that multidrug resistance is often associated with higher fitness costs or less virulence (Luangtongkum et al., 2009). However, our study suggested that the multidrug resistant 1655 had higher virulence than the reference strain RM1221 that is not multidrug resistant. Previous studies indicated that T86I mutation in *gyrA* gene could affect DNA supercoiling to regulate the expression of genes associated with bacterial fitness, and therefore enhance the fitness of fluoroquinolone-resistant *Campylobacter* in chicken host and increase the severity and duration of *Campylobacteriosis* (Nelson et al., 2004; Luo et al., 2005; Helms et al., 2005; Evans et al., 2009; Han et al., 2012). However, mutations in 23S rRNA could lead to fitness cost and reduced virulence of
<figure><img src="image_67.png" /></figure>

macrolide resistant *Campylobacter* (Hao et al., 2009; Almofti et al., 2011a,b; Hao et al., 2013). Some of the clinical investigation data indicated the positive correlation between

virulence and resistance, but others indicated the negative correlation (Bagger-Skjøt et al., 2007; McGowan-Spicer et al., 2008). For example, two recent studies showed that prevalence
<figure><img src="image_68.png" /><figcaption>**FIGURE 8** | Global multiple alignment of *C. jejuni* genomes. From top to bottom are the genome structures of *C. jejuni* RM1221, 81–176, NCTC11168, and 1655, respectively. The color region and white region represented high and low similarity respectively. Above axis was the positive strand, below was the negative strand.</figcaption></figure>

of resistance to both erythromycin and ciprofloxacin was higher in isolates harboring *ciaB* and some virulence genes (e.g., *cdtA* and *dnaJ*) were associated with antimicrobial-resistant Campylobacter strains (Ghunaim et al., 2015; Lapierre et al., 2016). Our study revealed the relationship between multidrug-resistance and virulence of some *C. jejuni* chicken isolates, indicating that complex mechanisms may work together to cause multidrug resistance and the relative higher virulence in *C. jejuni* 1655.

Comparing to the genome of RM1221, 1655 contained some special virulence-associated genes and proteins, including *flaC*, *ciaB*, *nlpC*, *cadF*, *gelE*, *peb2*, restriction modification enzyme, sugar nucleotidyltransferase, capsule polysaccharide protein, alginate O-acetyltransferase and TonB iron uptake system. The *flaC* has been shown to modulate immune response in the intestinal tract and contribute to bacterial persistence of *C. jejuni* (Faber et al., 2015). The presence of *ciaB*, a Campylobacter invasion antigen, may contribute to the high invasion of *C. jejuni* 1655 (Rivera-Amill and Konkel, 1999). The *nlpC* may play a critical role in initial infection process, adherence to host cells (Padhi et al., 2016). The *cadF*, encoding fibronectin protein, may play an important role on the adhesion and colonization of 1655 in chicken (Konkel et al., 1997; Monteville et al., 2003). The *peb2* is a membrane associated protein which may contribute to the increased gastrointestinal virulence of *C. jejuni* (Cordwell et al., 2008). The capsule polysaccharide (CPS), lipooligosaccharide (LOS), and restriction-modification (R/M) systems may enhance the invasion and colonization of

1655 in reservoir hosts and mediate the virulence of 1655 by evading host immune response (Bacon et al., 2001; Suerbaum et al., 2001; Ahmed et al., 2002; Guerry et al., 2002; Klena et al., 2004; Poly et al., 2004; Fouts et al., 2005; Guerry and Szymanski, 2008). The outer membrane protein CfrA and energy transporter system TonB-ExbB-ExbD are associated with iron absorption and iron uptake in gram-negative bacteria (Krewulak and Vogel, 2011). The presence of CfrA and TonB-ExbB-ExbD system in 1655 may contribute to its stronger ability of nutrients uptake and higher intracellular survivability (Andrews et al., 2003; Hofreuter et al., 2006; Krewulak and Vogel, 2011).

The genes encoding IS606 transposase, ISHa1675 transposase B and prophage Lp2 protein 6 were identified in the genome of 1655, suggesting that 1655 may contain transposons or phages. However, future experiments are needed to determine if these are associated with active mobile genetic elements in 1655. The ISHa1675 transposase B and prophage Lp2 protein 6 were not found in the genome of RM1221 and 11168, indicating that these two genes may play special role in the physiological characteristic of *C. jejuni* 1655.

Three proteins associated with CRISPR-Cas systems (CRISPR-Cas2, CRISPR-Cas1 and a hypothetical protein associated with the CRISPR) were found in 1655. The CRISPR-Cas system provides bacterial defense against foreign nucleic acids derived from bacteriophages or plasmids (Barrangou et al., 2007; Marraffini, 2013). It also plays an important role in gene regulation and bacterial pathogenicity (Mojica et al., 2005;
<table><caption>TABLE 4 | Virulence relative factors in C. jejuni 1655 and reference strains.</caption><thead><tr><th></th><th>1655</th><th>1221</th><th>11168</th><th>81176</th></tr></thead><tbody><tr><td>Virulence genes</td><td>Relative high</td><td>No</td><td>Low</td><td>Intermediate</td></tr><tr><td>Virulence</td><td>Relative high</td><td>No</td><td>Low</td><td>Intermediate</td></tr><tr><td>pVir Plasmid</td><td>—</td><td>—</td><td>—</td><td>+</td></tr><tr><td colspan="5"><strong>FLAGELLA SYNTHESIS GENES</strong></td></tr><tr><td>flaA</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>flaC</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>flhB</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>flgB</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>fltM</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>fltY</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td colspan="5"><strong>INVASION</strong></td></tr><tr><td>ciaB</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>nlpC</td><td>+</td><td>—</td><td>—</td><td>+</td></tr><tr><td colspan="5"><strong>ADHESION</strong></td></tr><tr><td>cadF</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>galE</td><td>+</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Peb1</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>Peb2</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td colspan="5"><strong>CHEMOTAXIS</strong></td></tr><tr><td>cheY</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>motB</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>dnaJ</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td colspan="5"><strong>CPS BIOSYNTHESIS SYSTEM</strong></td></tr><tr><td>Restriction modification enzyme</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>LPS biosynthesis protein</td><td>—</td><td>+</td><td>—</td><td>+</td></tr><tr><td>Sugar nucleotidyltransferase (CPS)</td><td>+</td><td>—</td><td>+</td><td>+</td></tr><tr><td>Capsule polysaccharide protein (KPS)</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>Alginate O-acetyltransferase AlgI</td><td>+</td><td>—</td><td>—</td><td>—</td></tr><tr><td colspan="5"><strong>IRON UPTAKE SYSTEM</strong></td></tr><tr><td>cfrA</td><td>+</td><td>+</td><td>+</td><td>—</td></tr><tr><td>TonB123</td><td>+</td><td>—</td><td>+</td><td>—</td></tr><tr><td>ExbB</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>ExbD</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td colspan="5"><strong>TRANSPOSASE AND PHAGES PROTEINS</strong></td></tr><tr><td>IS606 transposase</td><td>+</td><td>+</td><td>+</td><td>—</td></tr><tr><td>ISHa1675 transposase B</td><td>+</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Prophage Lp2 protein 6</td><td>+</td><td>—</td><td>—</td><td>+</td></tr><tr><td colspan="5"><strong>CRISPR-CAS SYSTEM</strong></td></tr><tr><td>CRISPR</td><td>csn1-cas1-cas2</td><td>csn1-cas1-cas2</td><td>csn1-cas1-cas2-CRISPR-cstIII</td><td>cstII</td></tr></tbody></table>

Louwen et al., 2013; Louwen and van Baarlen, 2013; Sampson and Weiss, 2014). Strains containing CRISPR-Cas system have a stronger ability of biofilm formation and colonization in mouse organs than those strains lack this system (Shimomura et al., 2011). Therefore, the presence of CRISPR-Cas system may contribute to the high virulence and biofilm formation capacity of C. jejuni 1655 strain.

CONCLUSION

1655 strain exhibited multidrug resistance to fluoroquinolone, macrolide, tetracycline, and aminoglycoside drugs and relative high *in vitro* and *in vivo* virulence. Comparing to the

genome of reference strains (NCTC11168, RM1221, and 81-176), there were large difference in the genome structure and genome content in 1655. The co-emergence of target gene mutations, resistance genes and pTet plasmid could explain its multidrug resistance. The virulence mechanism of *Campylobacter* may be mediated by a variety of virulence factors, including proteins involved in flagella biosynthesis, invasion, adhesion, CPS biosynthesis system, iron uptake system, transposase, phage proteins, and CRISPR-Cas system. Future experiments are needed to find the deeper molecular mechanisms and confirm the function of some important gene elements on multidrug resistance and relative higher virulence.
## FINANCIAL DISCLOSURE

This work was supported by National Basic Research Program of China (2013CB127200), National Key research and development program (2016YFD0501302), National Natural Science Foundation of China (31101856), National Key Technology R&D Program (2012BAK01B00), Morning program of Wuhan in China (2015070404010191), Fundamental Research Funds for the Central Universities (2662015PY035), and National Program for Risk Assessment of Quality and Safety of Livestock and Poultry Products (GJFP2016008). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The opinions expressed in this manuscript are solely the responsibility of the authors and do not necessarily represent the official views and policy of the US Food and Drug Administration or National Institutes of Health. Reference to any commercial materials, equipment, or process does not in any way constitute approval, endorsement, or recommendation by the Food and Drug Administration.

## AUTHOR CONTRIBUTIONS

Conceived and designed the experiments: HH, NR, MD, GC, ZY. Performed the experiments: NR, XK, JL, ZI, HH. Analyzed the data: HH, NR, JH, SF, YW, ZY. Contributed reagents/materials/analysis tools: YW, ZL, MD, YW, ZY. Wrote the paper: HH, NR, JH, SF, ZI, ZY.

## ACKNOWLEDGMENTS

Thanks the curious review by Dr. Huizhong Chen and Kidon Sung from FDA National Center for Toxicological Research.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb.2016.01605

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Hao, Ren, Han, Foley, Iqbal, Cheng, Kuang, Liu, Liu, Dai, Wang and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
# Is Quorum Sensing Interference a Viable Alternative to Treat *Pseudomonas aeruginosa* Infections?

Rodolfo García-Contreras *

Department of Microbiology and Parasitology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico

Quorum sensing (QS) coordinates the expression of multiple virulence factors in *Pseudomonas aeruginosa*; hence its inhibition has been postulated as a new alternative to treat its infections. In particular, QS interference approaches claim that they attenuate bacterial virulence without directly decreasing bacterial growth and suggest that *in vivo* the immune system would control the infections. Moreover, since *in vitro* experiments performed in rich medium demonstrate that interfering with QS decreases the production of virulence factors without affecting bacterial growth it was assumed than *in vivo* therapies will minimize the selection of resistant strains. Therefore, the underlying assumptions toward an effective implementation of a successful Quorum sensing interference (QSI) therapy for treating *P. aeruginosa* infections are that (i) QS only exerts important effects in the regulation of virulence genes but it does not affect metabolic processes linked to growth, (ii) the expression of virulence factors is only positively regulated by QS, (iii) inhibition of virulence factors *in vivo* do not affect bacterial growth, (iv) the immune system of the infected patients will be able to get rid of the infections, and (v) the therapy will be effective in the strains that are actively producing the infections. Nevertheless, for QSI in *P. aeruginosa*, substantial experimental evidence against the validity of most of these assumptions has accumulated during the past years, suggesting that a far better understanding of its virulence and its behavior during infections is needed in order to design truly solid QSI therapeutic alternatives to combat this remarkable pathogen.

**Keywords:** *Pseudomonas* infections, quorum sensing (QS), quorum quenching, resistance, clinical isolates

## INTRODUCTION

*Pseudomonas aeruginosa* is a remarkable opportunistic pathogen that infects patients that are immunocompromised, have severe burns, cancer, or AIDS, are intubated and with prosthetic devices, and also those suffering from chronic affections like cystic fibrosis (CF). This bacterium is a major health problem worldwide being responsible of 10% of nosocomial infections (Antunes et al., 2010; Castillo-Juárez et al., 2015), since it is intrinsically resistant to several antimicrobials (Poole, 2011) and able to develop resistance against new ones, has a high biofilm production and produces an arsenal of virulence factors. One of the main mechanisms that controls the production of its virulence factors is quorum sensing (QS) which coordinates the expression of such factors

**OPEN ACCESS**

**Edited by:**
Axel Cloeckaert,
French National Institute for
Agricultural Research (INRA), France

**Reviewed by:**
Pierre Cornelis,
Vrije Universiteit Brussel, Belgium
César De La Fuente-Núñez,
Massachusetts Institute of
Technology, USA

*Correspondence:
Rodolfo García-Contreras
rgarc@bq.unam.mx

**Specialty section:**
This article was submitted to
Antimicrobials, Resistance and
Chemotherapy,
a section of the journal
Frontiers in Microbiology

**Received:** 01 June 2016
**Accepted:** 31 August 2016
**Published:** 14 September 2016

**Citation:**
García-Contreras R (2016) Is Quorum Sensing Interference a Viable Alternative to Treat Pseudomonas aeruginosa Infections? *Front. Microbiol.* 7:1454. doi: 10.3389/fmicb.2016.01454
once bacteria have reached a high population density, thus maximizing their chances to overcome the host defenses and establish the infection.

QS systems are common in bacterial pathogens; among Gram negatives, in addition to *P. aeruginosa*, *Acinetobacter baumannii* (Bhargava et al., 2010), *Escherichia coli* (Sperandio et al., 2002) Salmonella strains (Choi et al., 2007), and Vibrio strains (Zhu et al., 2002; Yang and Defoirdt, 2015) use them to coordinate their virulence. Hence, QS interference (QSI) or quorum quenching (QQ) is a strategy proposed to inhibit virulence as an alternative to treat the infections of several important bacterial pathogens (Castillo-Juárez et al., 2015).

In this opinion piece I focus in *P. aeruginosa*, one of the most studied organisms regarding QS and QSI, nevertheless what is exposed here may be also applicable to other bacterial pathogens.

*P. aeruginosa* is one of the more complex known bacterial pathogens; it possesses an ample genome and a high percentage of its genes are devoted to gene regulation (Stover et al., 2000). Regarding QS systems, it has a hierarchical architecture governed by the LasRI module which produces and senses N-3-oxo-dodecanoyl-L-Homoserine lactone and activates the expression of multiple virulence genes such as those producing elastase A and B, pyocyanin, alkaline and protease, and activating a second homoserine lactone (HSL) QS module known as RhlRI, which produces and senses N-butyryl-L-Homoserine lactone. RhlR bound to its autoinducer also activates directly some virulence genes like those encoding rhamnolipids and pyocyanin (Smith and Iglewski, 2003; Jimenez et al., 2012). In addition, *P. aeruginosa* also has a quinolone dependent system known as PQS, which is positively regulated by LasR and negatively by RhlR, forming a complex and intricate network (Jimenez et al., 2012; Lee and Zhang, 2015). In addition to the QS intrinsic components, several regulators such as GacA/GacS, QscR, Vfr, RpoN, and RpoS, influence the expression of QS dependent factors (Lee and Zhang, 2015).

The complex relationship between QS and virulence in *P. aeruginosa* had been recently evidenced by the fact that *lasR* deficient mutants (including clinical strains) growing at slow rates or in the stationary phase, overproduce pyocyanin due a lack of repression of the phenazine genes by RsAL, a negative transcriptional regulator positively controlled by LasR (Cabeen, 2014). Moreover, in *lasR* mutants, the activity of the *rhl* system is only delayed but not abolished, allowing significant production of pyocyanin, rhamnolipids and N-butyryl-L-Homoserine lactone (which are RhlR dependent) and even the production of the LasR dependent QS signals N-3-oxo-dodecanoyl-L-Homoserine lactone and PQS (Dekimpe and Deziel, 2009). These findings suggest that the inhibition of a particular component of the QS network, even the pivotal factor LasR, may be counteracted by the activation of alternative components of the network. Indeed, some recent studies have identified novel QS inhibitors for which RhlR and not LasR as the relevant *in vivo* target (O'Loughlin et al., 2013; Welsh et al., 2015).

In addition, recently it was discovered that an environmental strain (148 isolated from dolphin gastric juice) produces significant amounts of the QS-controlled virulence factors rhamnolipids and pyocyanin. Critically, this strain is virulent

to mice, even without having a *lasR* gene and without producing N-3-oxo-dodecanoyl-L-Homoserine lactone. Hence, in this strain, the control of QS dependent virulence factors must be exerted by other regulators (Grosso-Becerra et al., 2014).

QS Interference could be achieved by the attenuation of the QS communication systems via: (i) the disruption of the QS receptors, (ii) the degradation of the autoinducers signals or (iii) the inhibition of the signal synthesis. Accordingly, several QS inhibitors or quorum quenchers (QQ) suitable for *P. aeruginosa* have been developed, under the assumptions that (i) the expression of virulence factors is only positively regulated by QS, (ii) the QQ will only exert significant effects in the regulation of virulence genes but not in metabolic processes linked to growth, hence avoiding or at least decreasing the generation of selective pressure that leads to resistance, (iii) the immune system of the infected patients will be able to get rid of the infections, and (iv) the therapy will be effective against the strains that are actively producing the infections. Nevertheless, substantial evidence against the validity of those assumptions has accumulated over the years.

## QUORUM SENSING INFLUENCES METABOLIC PROCESSES AND BACTERIAL GROWTH

Although the role of QS in *P. aeruginosa* virulence has been extensively studied, whether it influences global metabolism and cell growth is less explored. One possible reason for this bias is that at the transcriptomic level, few significant changes in metabolicrelated genes are found when QS proficient and deficient strains are compared or when QS inhibitors are administrated to QS proficient strains (Hentzer et al., 2003; Schuster et al., 2003; Wagner et al., 2003). Nevertheless, recently Davenport and coworkers found that the metabolome of a *lasI rhlI* double mutant (unable to produce HSL QS autoinducers) and that of its wild-type progenitor have a notorious divergence once the wild-type strain produced the highest levels of autoinducers; remarkably, around one third of all the metabolites identified changed (Davenport et al., 2015). This phenomenon is understandable since the wild-type strain devotes many of its resources to the production of costly virulence factors such as exoproteases, phenazines, and exopolysacharides, while, in contrast, the QS mutants uses the same resources for cell division. In agreement, the QS deficient mutants achieve higher growth yields than QS wild-type strains (Diggle et al., 2007).

Although the possible implications of the metabolic divergence in QS mutants on bacterial physiology and QS interference therapies is still unexplored, Davenport and coworkers demonstrated that important metabolic changes in the membrane metabolism of the wild-type strain are driven by QS upon entering the stationary phase. These modifications include increased fatty acid saturation, chain length, and cyclopropanation, which in turn, promote the generation of robust cell membranes. In contrast, the membranes of QS mutants do not have these modifications and are therefore more susceptible to stress.
In addition to these metabolic changes, several works have demonstrated that in *P. aeruginosa* and other bacteria, QS enhances the stress response (Bjarnsholt et al., 2005; Bhargava et al., 2014; de Oca-Mejia et al., 2015; García-Contreras et al., 2015a); for example, by upregulating antioxidant enzymes such as catalase, superoxide dismutase (Hassett et al., 1999) and NADPH-generating enzymes (García-Contreras et al., 2015a). This is important since during an infection, the immune system attacks bacteria by releasing reactive oxygen species, and at least *in vitro* oxidative stress is able to select functional QS systems as well as QS interference resistant mutants (García-Contreras et al., 2015a).

Moreover, growth of *P. aeruginosa* can be strongly dependent on QS either if adenosine or protein is used as sole carbon sources, since *nuh*, the gene encoding the nucleoside hydrolase, is under tight LasR control (Heurlier et al., 2005) and since the expression of exoproteases is under QS control (Diggle et al., 2007). During infections, adenosine utilization (Patel et al., 2007; Sheng et al., 2012) as well as the degradation of host proteins (Wretlind and Pavlovskis, 1983; Laarman et al., 2013) are important for bacterial virulence and survival.

All the above summarized facts demonstrate that QS is an important regulator of bacterial metabolism and physiology and suggest that QS interference will have the direct effect of decreasing bacterial growth and viability *in vivo*. In agreement, several *in vivo* infection studies have shown that when a QS interference therapy is able to increase animal survival (and decrease damage to the host), there is a significant decrease in bacterial counts in the infection sites (Wu et al., 2004; Christensen et al., 2007; Defoirdt et al., 2010; Jakobsen et al., 2011). The decrease in bacterial viability due QS interference may be an important potential source of *in vivo* selective pressure for the selection of bacterial resistance (García-Contreras et al., 2016).

## POTENTIAL INCREASE IN VIRULENCE UPON QUORUM SENSING INTERFERENCE

Although the production of multiple virulence factors in *P. aeruginosa* is positively regulated by QS, the virulence phenotype displayed by this organism is a complex combinatorial phenomenon that cannot be easily predicted with the identification of the presence or absence of a set of specific genes (Lee et al., 2006; Grosso-Becerra et al., 2014). In agreement, several studies had shown that clinical strains display a wide variety levels of virulence (Fenner et al., 2006; Lee et al., 2006; Garcia-Contreras et al., 2015b) and that environmental strains often conserve high virulence (Grosso-Becerra et al., 2014).

An overlooked fact about the role of QS in *P. aeruginosa* virulence was discovered in 2005 by Bleves and coworkers, who that found that in contrast to several other virulence traits, the expression of the type III secretion system (TTSS) in *P. aeruginosa* is negatively regulated by QS, specifically by RhIR and PqsR (Bleves et al., 2005; Kong et al., 2009). An important factor in such negative regulation of virulence genes by QS is that

it requires low calcium levels, and hence several transcriptomics studies done in culture medium such as LB with relative high calcium levels fail to show this relationship. Since the TTSS is an important determinant of virulence in several animal infection models including pneumonia, peritonitis, bacteremia, burn infections, and keratitis (Hauser, 2009), the possibility that QS interfering therapies may be activating this system and therefore promoting virulence should not be ignored. Moreover, *P. aeruginosa* has five of the six known types of secretion systems present in Gram negative bacteria (all but type IV) and some of these systems, like type VI, are present in several copies in its genome (Bleves et al., 2010). The QS influence on the expression of these secretion systems is as of yet unknown, with the exceptions of the TTSS and the second type VI secretion system that are negatively regulated by QS (Sana et al., 2012).

More striking is the fact that QS interference using azithromycin selects the wild-type virulent phenotype against the less virulent *lasR* mutants in intubated patients colonized by *P. aeruginosa* (Kohler et al., 2010). This surprising fact is understandable since *lasR* mutants often appear and are selected in infections since they act as phenotypic cheaters that utilize the public goods such as exoproteases and siderophores produced by the cooperative wild-type individuals (Diggle et al., 2007; Sandoz et al., 2007). Hence, inhibiting QS removes the advantage of the *lasR* mutants and thereby selects the wild-type, thus a detrimental effect of QS interference in the long run could be to increase the prevalence of virulent genotypes in the nosocomial environment (Kohler et al., 2010).

Another key aspect of current QS inhibitors like furanones is that, depending on their concentration, they can activate rather than inhibit QS (Martinelli et al., 2004). Furthermore, related QS inhibitors such as synthetic HSLs can activate rather than inhibit some virulence factors (Welsh et al., 2015).

## LIMITATIONS OF THE CURRENT ANIMAL INFECTION MODELS FOR THE STUDY OF QUORUM SENSING INTERFERENCE

To date, several animal infection models have demonstrated that QS deficient mutants are much less virulent than their QS proficient parental strains; accordingly, QS interference promotes an increase in host survival and a decrease in damage and bacterial counts (Castillo-Juárez et al., 2015). The infection models used include arthropods like *Galleria mellonela*, nematodes such as *Caenorhabditis elegans*, fruit fly, and zebrafish which are valuable and informative but that do not accurately reflect human physiology. Moreover, when mice are used as a model, immune competent individuals are evaluated; hence, the fact that *P. aeruginosa* is a strict opportunistic pathogen that does not attack individuals with competent immune systems is overlooked, and so it is not clear if the immune systems of immunosuppressed patients will be able to clear the bacteria from infections upon QS interference treatments.

In addition to attacking immunosuppressed individuals, *P. aeruginosa* is the major cause of death of CF patients; accordingly, there are several mice models that incorporate
different mutations in the CF transmembrane conductance regulator (CTFR) protein and that are able to mimic some of the characteristics of the disease in humans. However, CF is a very complex disease and there are more than one thousand reported mutations in the *cftr* gene associated with the disease; hence, developing a murine model that closely resembles the human disease is challenging (Guilbault *et al.*, 2007).

Most of the current models are suitable to study acute infections and only a few like the one developed in 2005 by Hoffmann and coworkers are optimized to simulate chronic CF infections (Hoffmann *et al.*, 2005). Importantly, this model has been used to demonstrate that QS interference with azithromycin inhibits alginate production of the mucoid NH57388A strain *in vivo*, attenuating the damage produced to the host, but unfortunately it was not able to significantly increase mouse survival (Hoffmann *et al.*, 2007).

Clinical studies have demonstrated that AZM treatment improves lung function in CF patients (Saiman *et al.*, 2003); however, besides the QSI effect, azithromycin has bactericidal and anti-inflammatory effects; hence, the improvement of both mice and patients is likely due a combination of these effects rather than an exclusive consequence of the QSI properties of azithromycin. Therefore, testing of the effect of more specific QS interference molecules in these kind of models is needed in order to elucidate the potential of these therapies for CF patients.

Another kind of mouse model that more closely resembles the situation observed in humans is the thermally-induced injury model, which consists of producing a burn of second or third degree on the dorsal side of the mouse using hot water and subsequent inoculation of the burn. The utilization of this model has confirmed that QS-deficient mutants such as *lasR*, *lasI*, *rhlI*, *lasI rhlI*, and *pqsA* (Rumbaugh *et al.*, 1999a,b; Lesic *et al.*, 2007), have less virulence than the parental strains. Moreover, it has been used to test the effect of the halogenated anthranilic acid analogs 6FABA, 6CABA, and 4CABA which are inhibitors of the synthesis of quinolone QS signals. These compounds, at the doses administrated, decrease mouse mortality significantly. Nevertheless, they were tested at a single dose (Lesic *et al.*, 2007), so it is unknown if they exert dose response effects. This is not trivial since as mentioned before, QS inhibitors may act as QS activators depending on the used doses (Martinelli *et al.*, 2004).

## INSENSIBILITY OF SOME CLINICAL STAINS TO CURRENT QUORUM QUENCHERS

Before 2010 it was assumed than QS interference will be impervious or at least less susceptible to promote bacterial resistance than conventional antibiotic therapies (Defoirdt *et al.*, 2010). In 2011, it was demonstrated that *P. aeruginosa* acquires resistance easily against the canonical HSL-dependant quorum quencher furanone C-30, by activating the multidrug efflux pump MexAB-OprM (Maeda *et al.*, 2012). The activation of this pump is mediated by mutations disrupting the transcriptional repressors MexR and NaLC, and such mutations are common in

clinical isolates, presumably since they are selected by intense antibiotic treatments (Tomas *et al.*, 2010). As expected, these clinical isolates are resistant against C-30 (Maeda *et al.*, 2012).

Recent studies have demonstrated that C-30 resistance is common in multidrug resistant strains. Importantly, resistance against other QQ compounds like 5-fluorouracil is also present in some clinical isolates and some antibiotic sensitive strains are also resistant to C-30 by a decrease in the compound uptake. More strikingly, some of these strains produce higher amounts of the virulence factors in the presence of the furanone than in basal conditions (García-Contreras *et al.*, 2013a,b; García-Contreras *et al.*, 2015b).

This suggests that if eventually QSI therapies are implemented in the clinic, they likely would not be effective against all the strains present in infections (García-Contreras *et al.*, 2013a; Kalia *et al.*, 2013), and that crucially they may fail to inhibit those strains with active antibiotic efflux pumps. Indeed, it was recently proposed that bacteria resistant to several QS inhibitors may be selected by QSI treatments (Koul *et al.*, 2016).

## PERSPECTIVES

Since recent evidence has demonstrated that QS is linked to basal metabolism and growth, it will be important to evaluate QS interference and its effect in bacteria growing in medium that more closely simulates the composition of the environment during infection (Palmer *et al.*, 2007; García-Contreras *et al.*, 2015b), with attention on key metabolites that influence virulence and QS such as iron (Sokol and Woods, 1984; Mittal *et al.*, 2008; Hazan *et al.*, 2010), calcium (Sarkisova *et al.*, 2005), phosphate (Zaborin *et al.*, 2009), and adenosine (Patel *et al.*, 2007; Sheng *et al.*, 2012). Further, metabolomic and proteomic studies may shed light about the role of QS in bacterial physiology under *in vivo*-like conditions. In addition, the utilization of new technologies like microfluidics such as cell culture chips (organ-on-a-chip) would enable the interrogation of the roles of signaling, social cheating, mass transfer, and spatial organization in well-defined geometries, which is virtually impossible to asses at this moment using animal models.

Importantly, additional research about the ways *P. aeruginosa* may achieve resistance against QQ is needed in order to generate effective combination therapies less prone to the selection of resistance. One possibility is to exploit the fact that QS interference renders *P. aeruginosa* more sensitive to stress, including antibiotics and the effects of the immune system; hence, it is attractive to test if the combination of QS interference, antibiotic therapies and immunotherapy to improve the outcome of the therapies.

Another area of research that should be encouraged is the role of QS independent virulence factors and those negatively regulated by QS such as TTSS in infections and the effect of QS interference on these virulence determinants. Also, study of QS networks and the virulence of environmental and clinical strains is needed since current evidence indicates these are highly variable (Grosso-Becerra *et al.*, 2014; García-Contreras *et al.*,