(NYG) medium (5 g peptone, 3 g yeast extract, and 20 g glycerol, pH 7.0–7.2, in 1 L of distilled water) at 28◦C (Atlas, 1997). X. campestris pv.campestris FE58, Xanthomonas oryzae pv. oryzae PXO99A, X. oryzae pv. oryzae RS105, X. oryzae pv. oryzae KACC10331, X. campestris pv. campestris 8004, Xanthomonas axonopodis pv. glycines 12-2, P. syringae pv. glycinea PG4180, A. citrulli DSM17060, P. syringae pv. lachrymans 814/98, and E. amylovora ATCC15580 were also grown in nutrient broth (NB) medium at 28◦C. All solid media contained 1.5% agar, and antibiotics were added at the following concentrations: 20 µg/ml rifampicin and 8 µg/ml gentamicin for L. brunescens, 50 µg/ml rifampicin, and 10 µg/ml tetracycline for X. campestris pv. campestris FE58, and 20 µg/ml gentamicin for E. coli. Sucrose was added at a final concentration of 4% for the counter-selection of in-frame deletion strains.

### Generation of In-Frame Deletion Mutants

In-frame deletion plasmids were constructed by amplifying the flanking regions of specific genes by polymerase chain reaction (PCR) using Tks Gflex DNA Polymerase (TaKaRa Bio Inc., Kusatsu, Japan) and OH23 genomic DNA as the template according to the manufacturer's instructions. Briefly, PCR amplification was performed using 30 PCR cycles consisting of denaturation at 98◦C for 10 s, annealing at 55◦C for 15 s, and elongation at 68◦C for 1 min on a Bio-Red S1000 thermal cycler. The suicide vector pJQ200SK was digested with XbaI and BamHI (Thermo Fisher Scientific), and the target PCR fragments were ligated into the suicide vector using In-Fusion HD Cloning Plus (TaKaRa Bio Inc.). The recombinant vectors were transformed into E. coli DH5αλpir and confirmed using the universal primers M13F/M13R. The resulting plasmids were introduced into L. brunescens by conjugation. The deletion mutants 1rpfF, 1rpfC, and 1rpfG were selected for double homologous recombination events because the suicide vector contained a sacB counter-selectable marker (Quandt and Hynes, 1993). Finally, all mutants were confirmed by PCR using specific primers (**Table 2**).

### Growth Measurements

Lysobacter brunescens OH23 and the rpf mutants were cultured in NB medium at 28◦C with shaking at 180 rpm until the OD600 was approximately 1.0 [which corresponds to approximately 109 CFU/ml (Colony Forming Units/ml)]. Then, 1 ml of culture for each strain was transferred into 50 ml of new liquid NB medium. The cultures were then incubated at 28◦C with shaking at 180 rpm. To measure the growth, the OD600 value was determined every 12 h for each culture using a BioPhotometer Plus (Eppendorf, Germany) until each culture reached stationary stage. Three replicates were performed for each treatment, and the experiment was repeated three times.

### Bioassay for DSF Activities in a DSF Reporter Strain

The fermentation and isolation of LbDSF was assessed as previously described (Han et al., 2015). After extracting the DSF-dependent quorum-sensing signals in L. brunescens OH23,

#### TABLE 2 | Primers used in this study.

fmicb-10-01230 June 15, 2019 Time: 17:44 # 4

we performed a DSF bioassay, as described previously with modifications (Wang et al., 2004). Briefly, L. brunescens OH23 and the 1rpfF, 1rpfC, and 1rpfG mutants were grown in NB liquid medium (25 L liquid medium in a CRJ-50D fermenter, twice, for a total of 50 L) at 28◦C at 180 rpm until the culture reached 2 × 109 CFU/ml (OD600 = approximately 2.0). The culture broth was centrifuged at 12,000 rpm for 10 min, and the supernatant was extracted with the same volume of ethyl acetate. The extracted organic phase was evaporated at 47◦C, and the dry crude extract was partitioned using methanol and petroleum ether (100 ml each, three times). The petroleum ether phase was evaporated at 47◦C, and the resulting oil (2.1 g) was dissolved in 10 ml of dimethyl sulfoxide (DMSO). The DSFreporter strain, Xcc FE58, was grown in liquid NYG medium (5.0 g peptone, 3.0 g yeast extract, 20.0 g glycerol, and 1.0 L water, pH 7.2) for 2 days until the culture reached 3 × 109 CFU/ml (OD600 = approximately 3.0).

The bioassay plates were prepared using the following steps. First, 0.8 g agarose powder was added to 100 ml 0.5 × NYG liquid medium. The medium was heated until the agarose was resolved, at which point 60 µl of X-gluc (60 mg/ml) and 2 ml of the reporter strain Xcc FE58 culture (3 × 109 CFU/ml) were added into the NYG agarose medium (the medium was cooled to 42◦C before use). This medium was used to prepare the 90-mm bioassay plates. Then, 5 µl of the DSF crude extract (10 mg crude extract resuspended in 200 µl of DMSO) from L. brunescens OH23, 1rpfF, 1rpfC, or 1rpfG mutants was added to each well. The bioassay plates were incubated at 28◦C for 24 h. The quantification of LbDSF was assessed as previously described (Wang et al., 2004). In brief, DSF activity was confirmed by the presence of a blue halo around the well and measured using the formula DSF (unit/ml) = 0.134 × e (1.9919W) , where W is the diameter of the blue halo zone and the width of the blue halo zone was increased while adding more exogenous LbDSF (**Figure 2B**).

One unit of DSF is equivalent to a 1-cm-diameter blue halo zone formed by the addition of 0.18 ± 0.07 µg exogenous LbDSF. We also added DMSO to the bioassay plate as a negative control. Three replicates were performed for each treatment, and the experiment was repeated three times.

### Isolation and Identification of LbDSF

The crude DSF extract was purified using HPLC. The HPLC detection conditions were as follows: reverse-phase HPLC (Shimadzu MS-2020, Tokyo, Japan) at 210 nm using a C-18 column (250 × 4.6 mm, Phenomenex). The mobile phase was 80% methanol in H2O from 0 to 13 min, 100% methanol in H2O from 13 to 20 min, and 80% methanol in H2O from 20 to 30 min (H2O containing 0.04% trifluoroacetic acid). The fraction corresponding to LbDSF appeared at 11.5 min.

Fractions containing the desired compound were evaporated to dryness under reduced pressure. The purified compound (4.3 mg) was dissolved in chloroform and characterized by mass spectrometry and NMR. High-resolution ESI-MS of the purified compound was performed in an AB (QTRAP 6500) instrument. The samples were directly infused into a mass spectrometer and analyzed in negative ion mode using a Turbo Ion Spray source. The NMR spectra ( 1H NMR and 13C NMR) were recorded in CD3OD using an AVANCE 600 (Bruker Company, Germany) instrument with a standard pulse program.

1**H NMR (600 MHz, CDCl**3**):** δ 2.35 (t, 2H, J = 7.8 Hz), 1.63 (qt, 2H, J = 7.2 Hz), 1.51 (sept, 1 H, J = 6.6 Hz), 1.37–1.24 (m, 16 H), 1.15 (m, 2 H), and 0.86 (d, 6 H, J = 6.6 Hz).

13**C NMR (150 MHz, CDCl**3**):** 179.97, 39.05, 34.01, 29.93, 29.69, 29.63, 29.59, 29.42, 29.23, 29.05, 27.97, 27.41, 24.67, and 22.65.

**MS (ESI):** calculated for C15H29O2 [M-H]− 241.2173, found 241.2.

### Effect of the DSF-Dependent Quorum-Sensing System on XSAC Production

The ability of the wild-type and DSF mutants to produce XSAC was measured by an anti-Xanthomonas activity assay (diameter of inhibition zone) and analyzed using the agar diffusion method as described below. Pathogenic strains of Xanthomonas, including X. oryzae pv. oryzae PXO99A, X. oryzae pv. oryzae RS105, X. oryzae pv. oryzae KACC10331, X. campestris pv. campestris 8004, and X. axonopodis pv. glycines 12-2, were individually incubated in NB liquid medium until the culture OD600 was approximately 1.0. L. brunescens OH23, and its derived mutants (1rpfF, 1rpfC, and 1rpfG mutants) were incubated in NB liquid medium or NB liquid medium supplemented with 2 µM LbDSF until approximately 1.5–2.0 × 109 CFU/ml (OD600 = approximately 1.5–2.0). The cultures of L. brunescens OH23, 1rpfF, 1rpfC, and 1rpfG were centrifuged, and the supernatants were incubated at 85◦C for 30 min. For each pathogenic strain of Xanthomonas (**Table 1** and **Supplementary Table S1**), 100 ml of liquefied NB solid medium was incubated at 45◦C for 30 min, mixed with 108 cells, and then poured into plates. Then, 30 µl of supernatant from the cultures was spotted onto the selective plates. All plates were cultured at 28◦C, and the zones of inhibition on the plates were photographed and compared after 2 days. XSAC production was confirmed by the diameter of the inhibition zone, and all of the data regarding the inhibition zone were subtracted from the diameter of the oxford cup. Three replicates were performed for each treatment, and the experiment was repeated three times.

### Pathogenicity Assays in vivo

Oryza sativa ssp. indica rice cultivars IR24 and X. oryzae pv. oryzae PXO99A were used in the pathogenicity assay. O. sativa ssp. indica rice cultivars IR24 were grown under a 12-h light/dark cycle at 25◦C with approximately 70% relative humidity for 2 months. The preparation of the supernatants from cultures of L. brunescens OH23, 1rpfF, 1rpfC, and 1rpfG is described above. The leaves of IR24 plants were detached and dipped in the liquid culture of X. oryzae pv. oryzae PXO99A at a concentration of approximately 0.5 × 109 CFU/ml (OD600 = approximately 0.5) for 1 h. To determine the XSAC production and activity of wild-type OH23, 1rpfF, 1rpfC, and 1rpfG, and chemically complemented strains, X. oryzae pv. oryzae PXO99A-infected rice leaves were treated with the respective supernatants every 24 h. For the negative control, X. oryzae pv. oryzae PXO99Ainfected rice leaves were treated with NB medium. IR24 plants were grown in a glasshouse with the same conditions as above, and lesion lengths were measured and photographed at 7 dpi. Three replicates were performed for each treatment, and the experiment was repeated three times.

### Detection and Comparison of Colony Morphology in L. brunescens

Single colonies of wild-type OH23, 1rpfF, 1rpfC, and 1rpfG strains were inoculated on NYG plates or NYG plates containing 5 µM LbDSF for 3 days at 28◦C. Then, the colony morphology of each strain was photographed and compared. Three replicates were used for each treatment, and the experiment was repeated three times.

### Observation of Surface Motility

The surface motility assay of L. brunescens wild-type OH23, 1rpfF, 1rpfC, and 1rpfG strains was performed as previously described (Song et al., 2017). Briefly, NB semi-solid medium containing 0.3% agar was used for surface motility assays, and 2.5 µl of L. brunescens wild-type OH23 or the derived mutants (109 CFU/ml, OD600 was approximately 1.0 for all strains) was spotted onto the surface of NB semi-solid medium plates or NB semi-solid medium plates containing 5 µM LbDSF. The plates were incubated at 28◦C for 4 days, and then the surface motility of each strain was photographed, measured, and compared. Three replicates were performed for each treatment, and the experiment was repeated three times.

### RNA Extraction, Reverse Transcription PCR, and Real-Time-PCR

Lysobacter brunescens OH23, 1rpfF, 1rpfC, and 1rpfG mutants were each grown in 5 ml of NA medium to an OD600 of approximately 1.0. Three milliliters of cells was transferred into a sterile centrifuge tube and centrifuged for 3 min at 12,000 rpm. RNA was extracted from the strains using TRIzol solution (TaKaRa Biocompany) following the manufacturer's instructions. For DNA removal and reverse transcription PCR, the PrimerScript RT Reagent Kit with the gDNA Eraser Kit (TaKaRa Biocompany) was used in this study. For the realtime PCR assay, a QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific) was used to detect gene expression. The gene expression was calculated by the 2−11CT method. The primers for real-time PCR are listed in **Supplementary Table S2**. Three replicates were performed for each treatment, and the experiment was repeated three times.

### Data Analysis

Statistical analyses were calculated using SPSS (Statistical Package, Version 21.0). The variables were subjected to Student's t-test and tested for significance at P < 0.05 (∗ ), P < 0.01 (∗∗), P < 0.001 (∗∗∗), and P < 0.0001 (∗∗∗∗).

### RESULTS AND DISCUSSION

### Identification of the Small Signaling Molecule LbDSF in L. brunescens

To identify the structure of the DSF signal in L. brunescens OH23, we harvested the L. brunescens culture from a 50-L fermenter system (CRJ-50D), collecting 25 L each time for a total of 50 L, and we extracted the crude DSF from the supernatant using the same method as previously described (Han et al., 2015). The methods of separation and identification of the DSF from OH23 were described previously (Wang et al., 2004). Briefly, we collected samples every 2 min from HPLC, concentrated every fraction by evaporation, and added 1 µg of every sample

into the DSF bioassay plates containing Xcc FE58 and X-gluc. The formation of a blue halo in the plates indicated the induction ability of each fraction. The results showed that the samples from 10.01 to 12.00 min induced gusA expression (**Figures 1A,B**). The DSF activity from 10.01 to 12.00 min was 0.53 ± 0.20 units. Furthermore, PengXCA-gusA was minimally induced by the addition of the samples from 0.01–10.00 or 12.01–16.00 min, and blue halo zones were not observed. To further confirm these results, we purified 1 µg of compound from these four fractions and detected the induction abilities of each fraction using the DSF bioassay system. The results of this assay revealed that PengXCA-gusA activation was induced only by adding the purified compound from fraction c, which exhibited a DSF activity of 1.98 ± 0.69 units.

We also examined whether the compound from these fractions enhanced the anti-Xanthomonas activity in L. brunescens OH23. We collected, dried, and dissolved every fraction in DMSO. The supernatant from strain OH23 formed a zone of inhibition in the growth of X. oryzae pv. oryzae RS105 that was 2.15 ± 0.09 cm in diameter. The zone of inhibition increased to 2.77 ± 0.12 cm after the addition of 2.0 µM purified fraction c (**Supplementary Figure S3**). Moreover, the zone of inhibition did not significantly increase when the purified compounds from fraction a, fraction b, fraction d, or the DMSO control were added (**Supplementary Figure S3**). These results demonstrated that only the compounds from fraction c, collected at 11.5 min, enhanced the inhibition activities in strain OH23 (**Supplementary Figure S3**).

To identify the structure of the unidentified DSF compounds, we first collected approximately 2.6 mg of the compounds exhibiting the highest DSF activity (fraction c, 11.5 min) from 50 L of crude supernatant and resuspended it in chloroform for NMR analysis. After purification of the compounds from fraction c, mass spectrometry analysis of the purified compound revealed a main m/z fraction at 241.2 Da, which was consistent with the expected molecular weight of LeDSF3, [M-H]− = 241.2173 Da (**Figure 1C**). In contrast with most DSFs, the structure of LeDSF3 consisted of a saturated aliphatic chain, which was formed by a tetradecanoic acid structure with a methyl group linked to carbon 13. To confirm the presence of LeDSF3, 1H and 13C NMR spectra were collected, and all signals were assigned (**Supplementary Figures S2A,B**). In agreement with the expected structure, no signal was detected between 7 and 5 ppm in the 1H NMR spectrum, indicating that the purified compound was not an unsaturated aliphatic chain. A doublet with a 6.6-Hz coupling constant appeared at 0.86 ppm in the 1H NMR spectrum, corresponding to the methyl groups. The protons in the alpha and beta position to the carboxylic acid were observed at 2.35 and 1.63 ppm as a triple and a quintuplet, respectively, whereas the proton of carbon **13** appeared at 1.51 ppm as a septuplet. 13C NMR revealed a signal at 179.97 ppm, corresponding to the carboxylic acid. Carbon **2** was detected at 34.01 ppm, whereas the methyl groups appeared at 22.65 ppm in the 13C NMR spectrum. In agreement with the 1H NMR spectrum, no signal was detected between 180 and 120 ppm in the 13C NMR spectrum, discarding the possibility of an unsaturated chain. Therefore, the primary compound from fraction c, named LbDSF, was determined to be 13-methyltetradecanoic acid (**Figure 1C**), which was originally reported in L. enzymogenes (Han et al., 2015).

### Identification of the rpf Gene Cluster in L. brunescens

As mentioned above, DSF family signals have been reported in different Xanthomonas bacteria. As a result, we compared and sequenced the genome of OH23 to identify genes potentially related to the LbDSF biosynthesis pathway. By blasting all rpf operon protein sequences1 , we found that rpf proteins were highly conserved in Lysobacter spp. NCBI BLASTp analysis revealed that the Rpf proteins from L. brunescens had the highest homology to those of L. enzymogenes (taxid: 69), and the levels of protein identity were 72% (rpfF), 61% (rpfC), and 89% (rpfG). According to our BLASTp results, RpfF is an enoyl-CoA hydratase involved in the biosynthesis of DSF (**Figure 2A**). Accordingly, the DSF activity by wild-type OH23 was 0.88 ± 0.28 units, and the mutation of the rpfF gene abolished DSF production in L. brunescens (**Figure 2B**). RpfC is the hybrid histidine sensor kinase of the Rpf two-component regulatory system, which negatively regulates DSF production. Therefore, DSF accumulated in the 1rpfC mutant (**Figures 2A,B**), and DSF production of 1rpfC was 5.91 ± 2.29 units. RpfG is the response regulator of the Rpf two-component regulatory system and is responsible for signal transduction. Compared to wild-type OH23, DSF production was not altered in the 1rpfG mutant (**Figures 2A,B**), and the DSF activity of the 1rpfG was 0.63 ± 0.14 units.

Mutation of rpfF abolished the ability to produce DSFs in X. campestris pv campestris, which suggested that rpfF were essential for DSF production (Deng et al., 2011). In X. oryzae pv oryzae, the DSF production increased in the mutant of rpfC, and the DSF sensor kinase RpfC negatively regulated the biosynthesis of DSF (He et al., 2010; Deng et al., 2011). Taken together, these results indicate that the model for DSF production and signal transduction in L. brunescens is highly similar to that of L. enzymogenes and X. oryzae pv oryzae (He et al., 2010; Qian et al., 2013). In addition, the growth of wild-type OH23 and the rpf mutants was measured. The results demonstrated that the rpf mutants had growth similar to that of the wild-type strain under the tested conditions (**Figure 2C**).

### DSF-Dependent Quorum-Sensing System Positively Regulates Antibiotic Biosynthesis Through the Small Signaling Molecule LbDSF and the RpfC/RpfG Two-Component System

In previous findings, the genus Xanthomonas and several Gram-negative bacteria used the DSF-dependent quorumsensing system to mediate a diverse range of physiological activities related to virulence, motility, biofilm, and extracellular enzyme, and the DSF-dependent quorum-sensing system was also required for the biosynthesis of HSAF in L. enzymogenes (Qian et al., 2013; Guo et al., 2019). To investigate the

1https://blast.ncbi.nlm.nih.gov/Blast.cgi

function of the DSF-dependent quorum-sensing system in the biosynthesis of XSAC, we tested the anti-Xanthomonas abilities of the OH23 wild-type, 1rpfF,1rpfG, 1rpfC, and chemically complemented strains (mutants supplemented with LbDSF). As shown in **Figures 3A,B** and **Supplementary Figures S4–S7**, wild-type OH23 inhibited the growth of X. oryzae pv. oryzae

OH23 and its corresponding rpf mutants.

FIGURE 3 | Anti-Xanthomonas activity of L. brunescens OH23 and its corresponding rpf mutants with or without LbDSF addition. (A) Supernatants from L. brunescens OH23 or rpf mutant cultures with or without exogenous LbDSF supplementation were tested for their antimicrobial activity against X. oryzae pv. oryzae PXO99A . (B) The analysis of the images of X. oryzae pv. oryzae PXO99A growth inhibition zones shown in A. (C) Representative images of IR24 leaves infected with X. oryzae pv. oryzae PXO99A and treated with test supernatants. CK is the control, which was treated with water every 24 h. Images were taken 7 days post-inoculation (dpi). (D) Analysis of the lesion lengths on IR24 rice leaves caused by X. oryzae pv. oryzae PXO99A infection with or without treatment with test supernatants, as shown in C. Different numbers of star (∗ ) above the bars indicate a significant difference between the wild-type strain OH23 and mutant strains (ns: not sigificant, ∗∗∗P < 0.001; ∗∗∗∗P < 0.001, t-test).

PXO99A (Xoo PXO99A), X. oryzae pv. oryzae RS105 (Xoo RS105), X. oryzae pv. oryzae KACC 10331 (Xoo KACC 10331), X. campestris pv. campestris 8004 (Xcc 8004), and X. axonopodis pv. glycines 12-2 (Xag 12-2). The diameters of the inhibition zones were 1.22 ± 0.10 cm, 1.75 ± 0.15 cm, 1.95 ± 0.24 cm, 0.29 ± 0.09 cm, and 1.50 ± 0.14 cm, respectively. The 1rpfF,1rpfG, and 1rpfC mutants lost the ability to inhibit all tested Xanthomonas strains, demonstrating that these mutants were impaired in the biosynthesis of XSAC (**Figure 3A** and **Supplementary Figures S4–S7**). To determine the genes relevant to the XSAC biosynthesis, we analyzed the putative operon that related to the biosynthesis of XSAC (data not shown), and 8 genes of 13 genes were indispensable for the biosynthesis of XSAC (**Supplementary Figures S8A,B**). Furthermore, the q-PCR results shown that the expression of all 13 genes, the genes for XSAC biosynthesis, were dramatically reduced in the 1rpfF mutant (**Supplementary Figure S8C**).

In L. enzymogenes, HSAF biosynthesis gene pks-nrps expression was reduced ∼10 times, and HSAF production was also dramatically reduced in the 1rpfFOH11 mutant (Qian et al., 2013). Taken together, the DSF quorum-sensing XSAC biosynthesis regulation model in L. brunescens OH23 was similar to the DSF quorum-sensing HSAF biosynthesis regulation model in L. enzymogenes OH11, and the DSF quorum-sensing system positively regulated the biosynthesis of XSAC (Qian et al., 2013; Han et al., 2015).

To further address whether the small signaling molecule LbDSF restored XSAC biosynthesis in the rpf mutants, we added LbDSF (2 µM) to the mutant culture in liquid NB medium, incubated the culture at 28◦C at 180 rpm, and then tested the anti-Xanthomonas activity of the supernatant. When LbDSF was added into the cultures, the growth inhibitory ability of wild-type OH23 increased 35.01, 19.54, 8.97, 16.86, and 27.15% against Xoo PXO99A, Xoo RS105, Xoo KACC 10331, Xcc 8004, and Xag 12- 2, respectively (**Figure 3A** and **Supplementary Figures S4–S7**). LbDSF addition restored the anti-Xanthomonas activity in the 1rpfF, and the diameter of the zones of inhibition were 0.84 ± 0.22 cm, 1.71 ± 0.16 cm, 0.36 ± 0.10 cm, 0.25 ± 0.11 cm, and 1.18 ± 0.16 cm against Xoo PXO99A, Xoo RS105, Xoo KACC 10331, Xcc 8004, and Xag 12-2, respectively (**Figure 3A** and **Supplementary Figures S4–S7**). Additionally, exogenous LbDSF had no effect on the anti-Xanthomonas activity in 1rpfC and 1rpfG (**Figure 3A**). These results were consistent with the fact that the small signaling molecule LbDSF is a transduction signal in the L. brunescens rpf system, where RpfF is involved in DSF biosynthesis, and RpfC/RpfG is the two-component system involved in signal transduction.

We then investigated whether all of the supernatants mentioned above had inhibitory activities in vivo. Xoo PXO99Ainfected IR24 rice leaves were treated with the supernatants every 24 h, and lesion lengths were measured at 7 dpi. As shown in **Figures 3C,D**, the negative control was only treated with NB medium, and the lesion length was 2.92 ± 0.41 cm. However, the wild-type OH23 treatment group showed significantly decreased lesion lengths (0.70 ± 0.21 cm). The addition of exogenous LbDSF or DMSO to the culture of wild-type OH23 was shown to significantly influence the lesion length relative to the negative control. For the 1rpfF treatment group, exogenous LbDSF restored the anti-Xanthomonas activity, and the lesion length was 0.83 ± 0.23 cm. However, both the 1rpfG and 1rpfC treatment

groups exhibited similar lesion lengths as the negative control. The results from the in vivo plant assays were consistent with the results from the anti-Xanthomonas ability on plates.

In L. enzymogenes, LeDSF3 was 13-methyltetradecanoic acid, and acted as an extracellular signal to positively regulate the biosynthesis of HSAF; the two-component regulatory system RpfC/RpfG sensed and transduced LeDSF3; and the global regulator Clp was downstream of the LeDSF quorumsensing system and also played a positive role in regulating the biosynthesis of HSAF and WAP-8294A2 (Han et al., 2015; Xu et al., 2016). To further investigate the function of clp in L. brunescens OH23, the ClpOH11 amino acid sequence was compared with the draft genome sequence of L. brunescens OH23, and Peg.2300 (Clp) shared 83% similarity to that of ClpOH11 at the amino acid level (**Supplementary Figure S9A**). Next, the anti-Xanthomonas abilities of 1clp and its complementary strain were tested, and clp had no significant effect on biosynthesis of XSAC (**Supplementary Figure S9B**), which revealed that Clp was not involved in the regulation of XSAC biosynthesis. Taken together, these findings indicate that the structure of LbDSF and the regulation of RpfC/RpfG L. brunescens were similar to the LeDSF quorum-sensing HSAF biosynthesis regulation model in L. enzymogenes and a potential novel transcription regulator in the DSF-dependent quorum-sensing system that regulated XSAC biosynthesis in L. brunescens.

### DSF-Dependent Quorum-Sensing System Affects Colony Morphology in L. brunescens

The DSF quorum-sensing system was shown to influence colony morphology in L. enzymogenes (Qian et al., 2013). To investigate the function of the DSF-dependent quorum-sensing system in modulating colony morphology in L. brunescens, we tested the wild-type OH23 strain and the 1rpfF, 1rpfC, and 1rpfG mutants. As shown in **Figure 4**, the wild-type OH23 displayed round colonies with lobular and spiculated boundaries on NYG plates with an average diameter size of 1.87 ± 0.05 cm. However, the 1rpfF, 1rpfC, and 1rpfG mutants showed smooth colony appearance with an average diameter size of 0.64 ± 0.08 cm under the same growth conditions.

Exogenous LbDSF (2 µM) restored the colony morphology in the 1rpfF when compared to the wild-type OH23 with an average diameter size of 1.32 ± 0.08 cm, whereas the addition of exogenous LbDSF did not influence the colony morphology of the 1rpfC and 1rpfG (**Figure 4**). These results indicate that the DSFdependent quorum-sensing system is involved in the regulation of colony morphology in L. brunescens.

### DSF Signaling Controls Surface Motility Through Type IV Pili (T4P) in L. brunescens

The DSF-dependent quorum-sensing system was also shown to affect cell motility in L. enzymogenes (Qian et al., 2013). To investigate the function of the DSF-dependent quorumsensing system in regulating motility in L. brunescens, we tested

the motility of the wild-type OH23, 1rpfF, 1rpfC, and 1rpfG strains. Since OH23, unlike L. enzymogenes OH11, does not exhibit twitching motility (data not shown), we analyzed the surface motility of wild-type OH23 and its derivative mutants on NB semi-solid (0.3% agar) motility medium plates for 4 days incubated at 28◦C.

NYG plates contained 5 µM LbDSF. Each treatment was completed in

triplicate, and the experiment was repeated three times.

As shown in **Figure 5A**, the wild-type OH23 strain was motile in motility medium plates with a typical circular dissemination pattern from the point of inoculation that was 2.78 ± 0.33 cm in size. However, the surface motility of 1rpfF, 1rpfC, or 1rpfG was substantially reduced. These mutants only reached an average surface motility diameter of approximately 0.82 ± 0.11 cm in 4 days, indicating that the mutants had a 73.72% reduction in the diameter of their surface motility zone compared to the wildtype OH23. Exogenous LbDSF (2 µM) restored surface motility in the 1rpfF strain compared to the wild-type OH23 strain with an average surface motility diameter of 2.42 ± 0.10 cm. However, exogenous LbDSF did not exhibit any effect on the surface motility in the 1rpfC and 1rpfG mutants. These results indicate that the DSF-dependent quorum-sensing system is involved in the regulation of surface motility in L. brunescens.

Type IV Pili has been shown to be important for surface motility in diverse bacteria. Since the pilA gene encodes the major pilin subunit of T4P (Mattick, 2002; Burdman et al., 2011; Wang et al., 2014), we measured pilA1 expression in the wild-type OH23, 1rpfF, 1rpfC, and 1rpfG. As shown

in **Figure 5B**, pilA1 expression was dramatically decreased in 1rpfF, 1rpfC, and 1rpfG. The addition of exogenous LbDSF (2 µM) partially restored pilA1 expression in the 1rpfF compared to wild-type OH23, while exogenous LbDSF did not influence pilA1 expression in the 1rpfC and 1rpfG. These results indicate that the DSF-dependent quorum-sensing system is involved in the regulation of pilA1 expression in L. brunescens.

biosynthesis, surface motility, and cell morphology.

The DSF-dependent quorum-sensing system in the Xanthomonas genus differs substantially between species and has been shown to positively regulate virulence, biofilm formation, EPS biosynthesis, and adaption. Moreover, specific DSF molecules were related to specific antibiotic HSAF biosynthesis (He et al., 2010; Han et al., 2015). The Rpf system was shown to be activated by adding specific DSF molecules, and EPS production, extracellular xylanase activity, or antibiotic HSAF biosynthesis were restored (He et al., 2010; Han et al., 2015).

## CONCLUSION

In this study, we report the role of a quorum-sensing system in the production of a novel XSAC in the ubiquitous environmental bacterium L. brunescens (**Figure 6**). Our data revealed that L. brunescens OH23 uses a DSF-dependent quorum-sensing molecule to regulate XSAC production. We characterized this DSF compound as 13-methyltetradecanoic acid. This extracellular signal is produced by RpfF and transduced by the RpfC/RpfG two-component regulatory system. This molecule also regulates surface motility and colony morphology. Our findings will be useful in applied genetics and molecular biotechnology, thereby facilitating the improvement of antibiotic production in Lysobacter spp., which can potentially be used in the agricultural industry. Furthermore, the tight control that our identified DSF molecule exerts on XSAC expression suggests that Lysobacter spp. may produce other quorum-sensing signals that can induce the production of additional novel bioactive compounds.

### DATA AVAILABILITY

The datasets generated for this study can be found in Genbank, MK532476, MK532477, and MK532478.

## AUTHOR CONTRIBUTIONS

JL, RZ, PL, TJ, YJ, and YZ conducted the experiments. FL designed and conducted the experiments. JL, PL, and FL contributed to the writing of the manuscript. FL revised the manuscript.

### FUNDING

This study was supported by the Jiangsu Agricultural Science and Technology Innovation Funds [CX (16) 1049], the Jiangsu Provincial Key Technology Support Programme (BE2015354), the "948" Project of the Ministry of Agriculture (2014- Z24), the Earmarked Fund for China Agriculture Research System (CARS-28-16), and the China Postdoctoral Science Foundation (2017M610310).

### REFERENCES

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Abisado, R. G., Benomar, S., Klaus, J. R., Dandekar, A. A., and Chandler, J. R. (2018). Bacterial quorum sensing and microbial community interactions. mBio 9:e02331-17. doi: 10.1128/mBio.02331-17

Atlas, R. M. (1997). Handbook of microbiological media. Q. Rev. Biol. 2, 364–365.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2019.01230/full#supplementary-material

enzymogenes OH11. Biol. Control 120, 52–58. doi: 10.1016/j.biocontrol.2016. 08.006

**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 © 2019 Ling, Zhu, Laborda, Jiang, Jia, Zhao and Liu. 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) and the copyright owner(s) 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.

# AHLs Regulate Biofilm Formation and Swimming Motility of Hafnia alvei H4

Yao lei Zhu1,2, Hong man Hou1,2 \*, Gong liang Zhang1,2, Yi fang Wang1,2 and Hong shun Hao2

1 School of Food Science and Technology, Dalian Polytechnic University, Dalian, China, 2 Liaoning Key Lab for Aquatic Processing Quality and Safety, Dalian, China

The aim of this study was to evaluate the role of N-acyl homoserine lactones (AHLs) in the regulation of swimming motility of Hafnia alvei H4 and its biofilm formation on 96-well plate, glass and stainless-steel surfaces. The luxI gene, which codes for an enzyme involved in AHL synthesis, was deleted to generate a luxI mutant (1luxI). The mutant produced no AHL, and the relative expression of the luxR gene was significantly (P < 0.05) decreased. In addition, qRT-PCR analysis showed that the relative expression of the luxR gene in 1luxI was stimulated by the presence of exogenous AHLs (C4-HSL, C6-HSL, and 3-o-C8-HSL) added at concentrations ranging from of 50–250 µg/ml. Among the three AHLs, C6-HSL had the strongest effect. The ability of 1luxI to form biofilm on 96-well plate, glass and stainless-steel surfaces was significantly reduced (P < 0.05) compared with the wild type (WT), but was increased when provided with 150 µg/ml C4-HSL, whereas C6-HSL and 3-o-C8-HSL had no effect. Scanning electron microscopy analysis of the biofilm revealed less bacteria adhering to the surface of stainless-steel and fewer filaments were found binding to the cells compared with the WT. Furthermore, 1luxI also exhibited significant (P < 0.05) decrease in the expression of biofilm- and swimming motility-related genes, flgA, motA and cheA, consistent with the results observed for biofilm formation and swimming motility. Taken together, the results suggested that in H. alvei H4, C4-HSL may act as an important molecular signal through regulating the ability of the cells to form biofilm, as well as through regulating the swimming motility of the cell, and this could provide a new way to control these phenotypes of H. alvei in food processing.

Keywords: Hafnia alvei, AHLs, quorum sensing, biofilm, swimming motility

## INTRODUCTION

Quorum sensing (QS) is a cell-to-cell communication system used by bacteria, and it is widely by both Gram-negative and Gram-positive bacteria (Ammor et al., 2008). Bacteria secret several kinds of chemical compounds that can act as signaling molecules [autoinducers (AIs)]. N-acyl homoserine lactone (AHL), also known as AI-1, is secreted by Gram-negative bacteria, and the communication mechanism of this compound involves AHL synthase (LuxI) and the transcription factor LuxR, which is responsible for controlling gene expression in the presence of AHLs. The

#### Edited by:

Tom Defoirdt, Ghent University, Belgium

#### Reviewed by:

Maria Cristina D. Vanetti, Universidade Federal de Viçosa, Brazil Julia Van Kessel, Indiana University Bloomington, United States

> \*Correspondence: Hong man Hou<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

> Received: 29 November 2018 Accepted: 28 May 2019 Published: 19 June 2019

#### Citation:

Zhu Yl, Hou Hm, Zhang Gl, Wang Yf and Hao Hs (2019) AHLs Regulate Biofilm Formation and Swimming Motility of Hafnia alvei H4. Front. Microbiol. 10:1330. doi: 10.3389/fmicb.2019.01330

**121**

LuxI/LuxR system has become the model system of AHLsmediated quorum sensing, and the quorum-sensing system of Gram-negative is based on this system. LuxI synthesizes AHLs and it is encoded by the luxI gene. LuxR is encoded by the luxR gene, and it acts by binding to AHLs, thereby stimulating the expression of these genes in the presence of AHLs. The LuxI/LuxR complex is responsible for the up- or down-regulation of multiple target genes, such as those that code for pectinase, cellulase, and protease (Swift et al., 2001). Autoinducer-2 (AI-2) is synthesized from 4,5-dihydroxy-2,3-pentanedione (DPD) by LuxS, and it is used by Gram-negative and Gram-positive bacteria in interspecies communication. Peptides and derived peptides, generally serve as signaling molecules in Gram-positive bacteria (Bai and Rai, 2011).

Biofilm is a bacterial self-protection growth pattern and it is formed by the aggregation of bacterial cells within an extracellular matrix, which is mainly made of exopolimers (EPS) (Wang J. et al., 2016), and the adherence of bacterial cells to a solid surface depends on the EPS that the cells secret (Jung et al., 2013). In general, some pathogens and spoilage bacteria can adhere to the solid surfaces that can come into contact with food, such as the surfaces of food processing machines and packaging materials. These bacteria may then form biofilms, and the biofilms will allow the cells to become more resistant to cleaning treatments, and enable them to contaminate the food during subsequent processing (Gounadaki et al., 2008; Bai and Rai, 2011). This will effectively facilitate the transmission of the bacteria to the consumers via the contaminated food, eventually causing infections. Biofilms have been recognized as a frequent source of bacterial infections (Costerton et al., 1999). According to a report by Janssens et al. (2008), nearly 80% of persistent bacterial infections in the US were found to be related to biofilms. The formation of biofilm is a multi-step process, which consists of initial attachment, irreversible attachment, early development of biofilm architecture (microcolony formation), maturation and dispersion (Srey et al., 2013). Quorum sensing appears to be involved in all the steps of the process. Promotion and inhibition of biofilm formation by exogenous AHLs have been reported for Shewanella baltica (Zhao et al., 2016), Serratia A2 and Aeromonas B1 (Zhang et al., 2016), Vibrio parahaemolyticus (Bai and Rai, 2016), and Pseudomonas sp. HF-1 (Wang et al., 2012), suggesting that QS has a regulatory role in biofilm formation.

H. alvei is a Gram-negative, short-rod-shaped, flagellated bacterium that belongs to the family Enterobacteriaceae, which is considered as an opportunistic pathogen of humans and animals (Tan et al., 2014). However, despite being classified as a member of the Enterobacteriaceae family, H. alvei is still far from being virulent and pathogenic (Vivas et al., 2008). H. alvei is a common bacterial food contaminant (Liu et al., 2006), and it has been frequently isolated from spoiled food products, especially in chill-stored proteinaceous raw food, like refrigerated spherical fish paste (Tan et al., 2014), vacuumpacked beef (Bruhn et al., 2004) and raw milk (Viana et al., 2009). The strong tendency of H. alvei to adhere to solid surface and to form biofilm has been reported by Viana et al. (2009) and Hou et al. (2017), and it is considered to be a potentially important factor that causes food contamination and food spoilage. Therefore, it is necessary to look for effective ways to control biofilm formation. To our knowledge, fewer studies have studied the regulatory mechanism of quorum sensing of H. alvei with respect to biofilm formation and the motility of the cells in an artificial medium. Understanding more about the mechanism by which quorum sensing can impact biofilm formation will open up a new way to tackle the problem of food contamination by bacteria, and help safeguard better food quality and prevent food-poising.

In our previous study, we isolated a strain of H. alvei (H. alvei H4) from spoiled instant sea cucumber, and identified three kinds of AHLs secreted by this bacterium. These AHLs are C4-HSL, C6- HSL, and 3-o-C8-HSL. In addition, we also detected a significant influence of AHLs on the biofilm formation of H. alvei H4 (Hou et al., 2017). In this study, a luxI mutant of H. alvei H4 was constructed to conduct further research on the regulatory roles of C4-HSL, C6-HSL, and 3-o-C8-HSL in biofilm formation and swimming motility of H. alvei H4.

### MATERIALS AND METHODS

### Bacterial Strains and Culture Conditions

The bacterial strains used in this study are presented in **Table 1**. Chromobacterium violaceum CV026, and H. alvei H4 were routinely cultured at 30◦C, while Escherichia coli was grown at 37◦C. All strains were grown in LB medium (Luria Bertani, 10 g/l tryptone, 5 g/l yeast extract, 10 g/l NaCl) supplemented with antibiotics where appropriate (50 µg/ml ampicillin and 34 µg/ml chloramphenicol in the case of E. coli culture or 20 µg/ml chloramphenicol for the H. alvei H4 mutant).

### Construction of 1luxI Strain

To construct a luxI-deficient strain of H. alvei H4, a chloramphenicol resistance marker (CmR ) was inserted into the genomic DNA of H. alvei H4 at the luxI locus. Briefly, a 608-bp upstream homologous recombination arm and a 654-bp downstream homologous recombination arm of the luxI gene were amplified from the gDNA of H. alvei H4 and then cloned into the plasmid pUC19 to yield the construct pUC19-1luxI. The two DNA fragments were linked by a BamHI restriction

TABLE 1 | Strains and plasmids used in this study.

site. The chloramphenicol resistance maker (CmR ) was amplified from the plasmid pKD3, and then cloned into pUC19-1luxI at a site between the upstream and downstream homologous recombination arm fragments, yielding the construct pUC19- 1luxI::Cm. Target fragment in pUC19-1luxI::Cm was subcloned and ligated into the suicide plasmid pCVD442 to yield the construct pCVD442-1luxI::Cm, which was then introduced into E. coliβ2155 by electroplating. Conjugation between E. coliβ2155 harboring pCVD442-1luxI::Cm and H. alvei H4 was then performed. The mutant colonies obtained were verified by PCR and DNA sequencing. Primers used in this section see **Table 2**.

### AHLs Production

Chromobacterium violaceum CV026 was used as the biosensor strain to detect the production of AHLs by H. alvei H4 WT and 1luxI, since in the presence of AHLs, C. violaceum CV026 would produce a purple pigment that could be easily detected. This assay was performed as described by Viana et al. (2009). Briefly, AHLs were extracted from the corresponding bacterial culture. Aliquot (100 ml) of an overnight culture was centrifuged at 8000 × g for 15 min at 4◦C, and the supernatant was added to an equal volume of ethyl acetate containing 0.1% acetic acid (v/v) followed by thorough mixing. The mixture was then incubated at 25◦C for 2 h with shaking at 180 rpm. After that, the ethyl acetate layer was removed and freeze-dried under vacuum, and the residue was dissolved in 1 ml ultra-pure water. To prepare the plates for the assay, 80 ml LB agar medium was cooled to about 60◦C, mixed with 20 ml overnight culture of CV026, and then poured into sterile plates (20 ml per plate). Holes were punched into the solidified medium at the center of each plate using a sterile 1 ml pipette tip, and 60 µl of the AHL extract was dispensed into the hole. The plates was incubated at 30◦C until the purple zone appeared around the point of AHL application.

### Biofilm Formation on 96-Well-Plate

Biofilm formation was measured using the microplate assay as described by Hou et al. (2017), but with some modifications. Briefly, culture of H. alvei H4 WT and 1luxI were grown to an OD600 nm value of 1.0, and then diluted 100-fold in LB medium. The diluted culture was dispensed into a 96-well plate polypropylene microtiter plate (Corning, NY, United States) using 200 µl per well. After incubation at 30◦C for 24 h, the OD600 nm of the culture was measured. After that, the

TABLE 2 | Primers used for the construction of 1luxI.

culture medium was removed and washed off unattached cells by washing each well with 250 µl of 10 mM PBS (pH 7.2). A total of three washes were performed. This was followed by the addition of 250 µl anhydrous methanol and a 15-min incubation to fix the cells. Subsequently, 250 µl of 0.1% (v/v) crystal violet solution was added to each well and the plate was incubated at room temperature for 15 min and rinsed three times with deionized water (250 µl per rinse). The crystal violet was dissolved by the addition of 200 µl 33% glacial acetic acid followed by shaking at 300 rpm for 15 min. Biofilm formation was finally analyzed by measuring the absorbance of the plate at OD590 nm using a Spectra M2 spectrophotometer (Molecular Devices, United States). Biofilm formed by 1luxI in the presence of 150 µg/ml C4-HSL, 200 µg/ml C6-HSL, or 100 µg/ml 3-o-C8- HSL was detected essentially as described above.

### Biofilm Formation on Glass Surface

To examine the effect of quorum sensing on biofilms formed by H. alvei H4 on the glass surface, biofilm formation was investigated as described by Cai et al. (2018) with some modifications. Briefly, an overnight bacterial culture was diluted 100-fold in fresh LB medium, and 2 ml of the diluted culture was added to a glass tube (1 cm × 10 cm). As a control, 2 ml of LB was added to a separate glass tube. Both tubes were incubated at 30◦C for 24 h without shaking. After incubation, the culture medium was gently removed, and each tube was washed three times with 2.5 ml PBS, and then with 2.5 ml anhydrous methanol followed by drying at 60◦C for 15 min. The tube was then stained with 2.5 ml 0.1% CV (v/v) for 15 min at room temperature followed by three washes with 2.5 ml ultra-pure water and drying at 60◦C. The remaining CV on the inner surface of the tube was dissolved in 1.0 ml of 33% glacial acetic acid (v/v) with vortexing, and 200 µl of the sample was transferred to a new 96-well plate and the optical density of the sample at 590 nm was measured with a microplate reader (Spectra M2; Molecular Devices, Sunnyvale, CA, United States).

### Biofilm Formation on Stainless Steel

Stainless steels (type: 304) were cut into strips (1 cm × 3 cm × 0.2 mm) and processed as described by Tapia-Rodriguez et al. (2017). An overnight culture of H. alvei H4 WT and 1luxI were diluted 100-fold with LB medium to a cell density of about 106 CFU/ml. Aliquot (10 ml) of the diluted culture was placed in a test tube (1.5 cm × 10 cm) containing

a stainless-steel strip and incubated at 30◦C for 24 h without shaking. After incubation, the strip was transferred to a small test tube (1.5 cm × 5 cm) containing 5 ml PBS to wash off unattached cells. This washing step was repeated three times and the strip was then transferred to a 10 ml-tube and sonicated for 1.5 min in an ultrasonication bath (power, 300 W, 37 kHz 37; Elma; Elmasonic P; Germany) to disperse the biofilm as previously described (Jahid et al., 2015). Finally, the bacterial suspension was vortexed and serially diluted with 0.85% NaCl solution, and then spread onto an LB agar plate. The plate was incubated at 30◦C for 24 h and the colonies appearing on the plate were then counted.

### Biofilms Detected by SEM

H. alvei H4 WT and 1luxI were separately incubated in LB medium for 16 h at 30◦C with shaking at 150 rpm. The culture was then diluted to a final density of about 1.0 × 107 CFU/ml. First, 1 ml of the diluted culture was dispensed onto a sterile stainless steel (1 cm × 1 cm × 0.2 mm) placed inside a 24-well microtiter plate and cultured at 30◦C for 24 h. The biofilm deposited on the stainless steel was then was prepared for scanning electron microscopy (SEM) analysis according to the method described by Nithya et al. (2010). Briefly, the stainless steel was gently washed with sterile 0.1 M PBS, and the biofilm was fixed with 2.5% glutaraldehyde solution for 2 h followed by washing with 0.1 M PBS. The stainless steel was subjected to dehydration under a graded series of tert-butanol. This was followed by critical point drying, gold sputtering and SEM observation (Quanta 450, Waltham, MA, United States) performed at 3.0 kV under 5000 and 50000× magnifications as described previously (Hou et al., 2018).

### Swimming Motility Assay

To measure the swimming motility of H. alvei H4 and 1luxI, motility agar (2.6 g/l agar, 10 g/l tryptone, 5 g/l NaCl) (Zhu and Winans, 1998) was used. H. alvei H4 or 1luxI was incubated in LB medium at 30◦C until the OD600 nm of the cultures reached 1.0. Aliquot (3 µL) of the culture was spotted at the center of the motility agar plate followed by incubation at 30◦C. The extent of motility was assessed by measuring the diameter of the zone spread from the point of inoculation. To detect the effect of AHLs on the swimming motility of 1luxI, C4-HSL, C6-HSL, and 3-o-C8-HSL were added to separate motility agar plates. The final concentrations of C4-HSL, C6-HSL, and 3-o-C8-HSL in the plates were 150, 200, and 100 µg/ml, respectively. Swimming motility was determined as described above.

### Real-Time PCR Assay

H. alvei H4 WT and 1luxI was cultured in LB medium the absence or presence of AHLs (C4-HSL, C6-HSL, and 3-o-C8-HSL) at 30◦C with shaking at 150 rpm for 16 h. When the OD600 nm of the cultures reached 1.65, the cells were harvested and subjected to total RNA extraction using a RNAprep Pure Bacteria Kit (DP430, TIANGEN, Beijing). About 500 ng of total RNA was reversely transcribed into cDNA using a PrimeScriptTM Reagent kit (RR047, Takara, Japan). The reaction mixture consisted of 2 µL template cDNA, 12.5 µL SYBR Premix Ex TaqTM (RR420, Takara, Japan), 0.5 µL each of the forward and reverse primers (10 mM) (**Table 3**), and 9.5 µL RNA free water. Amplification was performed with a Step-One Thermal Cycler (Applied Biosystems, United States) and consisted of 40 cycles of denaturation at 95◦C for 15 s, annealing at 95◦C for 30 s, and extension at 60◦C for 45 s. The 16S rRNA gene was used as housekeeping control. The result was analyzed by 2−11CT method (Schmittgen and Livak, 2008).

### Statistical Analysis

Three replicate trials were carried out for each sample, and all the experiments were repeated three times. Data were analyzed by one-way analysis of variance (ANOVA) using SPSS18.0 software, and expressed as means ± standard deviations (SDs). Statistical significance was considered at the P < 0.05 level. All graphs were drawn with OriginPro 8.6 software.

## RESULTS

### AHLs Production by luxI Mutant

Pigment production assay showed a violet zone in the center of the plate when CV026 was incubated with the ethyl acetate extract prepared from the culture supernatant of H. alvei H4 but not from the culture supernatant of 1luxI (**Figure 1**), indicating the lack of AHLs production by 1luxI. The assay demonstrated the dependence of AHLs production on a functional luxI gene.

TABLE 3 | Primers used for RT-PCR.

CV026 was cultured in the absence of ethyl acetate extract prepared from LB medium (A), H. alvei H4 culture supernatant (B), and 1luxI culture supernatant (C).

### Response of luxR to AHLs

fmicb-10-01330 June 17, 2019 Time: 17:32 # 5

The effect of luxI mutation was further investigated by measuring the level of luxR mRNA in 1luxI and compared it with that of WT strain. 1luxI exhibited about fivefold reduction in the level of luxR mRNA relative the WT (**Figure 2A**), which clearly suggested that the expression of the luxR gene in the mutant was significantly (P < 0.05) inhibited. However, in the presence of exogenous AHLs, the level of luxR mRNA gradually increased with increasing concentrations of AHLs, suggesting that the expression of luxR could be stimulated by the presence of AHLs (**Figure 2B**). Maximum increase in luxR mRNA level stimulated by AHL ranged from 5.5-fold in the case of C4-HSL to 6.5-fold in the case of C6-HSL, while 3 o-C8-HSL yielded somewhat lower increase (4.5-fold). Thus, C6-HSL appeared to exert the strongest stimulatory effect on the expression of luxR.

### Biofilm Formation

Growth of H. alvei H4 was not affected by the deletion of the luxI gene, as shown by the similar growth curves between WT and 1luxI in the absence of AHLs (**Figure 3A**). Furthermore, the addition of AHLs to the culture of 1luxI also had not obvious effect on its growth. This suggested that growth of the bacterial cells was not dependent on the product of the luxI gene. However, deletion of the luxI gene had a significant effect on biofilm formation by H. alvei H4, as shown by the significantly higher level of biofilm formed by the wild type (WT) compared with 1luxI (**Figure 3B**). Addition of AHLs to the culture of 1luxI appeared to cause increase in biofilm formation. The extent of biofilm formation of 1luxI in the presence of C4-HSL was significantly (P < 0.05) enhanced and almost similar to that of the WT strain. However, C6-HSL seemed to

have no effect on the biofilm formation of 1luxI, causing no significant increase. Obvious promotion (P < 0.05) of biofilm formation on 1luxI were also achieved at the presence of 3-o-C8-HSL, but still far less than that of C4-HSL on 1luxI and WT strain. The result suggested that C4-HSL could be the AHL with major influence on biofilm formation.

### Biofilms on Glass

An intense zone of purple stain was found on the wall of the glass tube used to culture WT strain, indicating the presence of biofilm (**Figure 4A**). On the other hand, only very slight purple staining was found on the wall of the glass tube that was used to culture 1luxI, suggesting a lack of biofilm being formed by 1luxI. Addition of C4-HSL to the 1luxI culture resulted in obvious enhancement of the purple zone, but this did not occur when either C6-HSL or 3-o-C8-HSL was added to the culture. The result clearly suggested that the capacity of 1luxI to form biofilm was greatly reduced compared with its WT strain counterpart, and that only C4-HSL was able to restore its biofilm formation capacity.

### Biofilms on Stainless Steel

The mutant 1luxI was also compared with its WT counterpart in term of the ability to form biofilm on the surface of stainless steel. Significantly (P < 0.05) less colonies of 1luxI were found on the surface of the stainless steel compared with the WT strain, but when 1luxI was cultured in the presence of C4-HSL, the number of colonies found on the surface of the stainless steel was significantly (P < 0.05) increased, and being comparable with that of WT strain (**Figure 5**). However, as in the case of biofilm formed on glass surface, C6-HSL and 3-o-C8-HSL had no obvious effect on the ability of 1luxI to form biofilm on stainless steel surface.

### Biofilm by SEM

Biofilm formation of H. alvei H4 WT and 1luxI on stainless-steel surface was detected by SEM. Obvious reduction in the number of 1luxI cells on stainless-steel

FIGURE 4 | Biofilm formation by H. alvei strains. The image shows the biofilms formed on glass surface by WT and 1luxI with and without AHLs. The plot shows the extent of biofilm formed on the glass surface as quantitated by OD590 nm. NC, negative control. Data are the means ± SEMs (n = 3). Different letters above the columns indicate differences at the P < 0.05 level.

surface was observed, but the number of 1luxI cells was restored when supplied with 150 µg/ml C4-HSL (**Figure 6**). In addition, WT cells appeared to aggregate and adhered to the surface, and produced evident EPS filaments. In contrast, 1luxI tended to adhere to the surface as individual cells. When 1luxI was exposed to 150 µg/ml C4-HSL, the cells also formed aggregates and adhered to the surface of stainless steel, these cells also produced a lot of EPS.

### Swimming Motility

As shown in **Figures 2B–D**, the concentrations of AHLs, which induce the relative expression of luxR gene to the maximum respectively, were chosen for swimming motility assay, and swimming motility was determined by the expansion of the bacterial colony from the point of application to a greater diameter on the surface of an agar plate. Compared with WT, 1luxI suffered significant (P < 0.05) loss in swimming motility in the absence of exogenous AHLs (**Figure 7**). However, upon addition of C4-HSL, the swimming motility of 1luxI increased and became significantly higher than the level of WT. Addition of C6-HSL also had some enhancing effect on the swimming motility of 1luxI, but it remained obviously reduced compared with WT. In contrast, the addition of 3-o-C8-HSL appeared to have no real effect on the swimming motility of 1luxI.

### Expression of flgA, motA, and cheA

To further study the molecular mechanism of quorum sensing on biofilm formation, three biofilm formation and swimming motility related genes, flgA, motA and cheA, were chosen for analysis using qRT-PCR. The mRNA levels of all three genes in 1luxI in the absence of exogenous AHLs were significantly (P < 0.05) reduced compared with those of the WT, with motA being the most severely affected gene (**Figure 8**). Addition of C4-HSL (150 µg/ml) to the 1luxI culture restored the mRNA levels of the three genes to the levels comparable with those of the WT strain, except for the cheA gene, which showed lesser, but still significant increase. Similarly, the addition of C6-HSL (200 µg/ml) had some enhancing effect on the mRNA levels of motA and cheA, whereas the addition of 3-o-C8-HSL (100 µg/ml)

appeared to increase the mRNA levels of all three genes, but the increases still fell short of those achieved by C4-HSL. The result suggested that AHL could stimulate the expression of the motA and cheA genes, and to a lesser extent, the expression of the flgA gene.

### DISCUSSION

Mutant strain of H. alvei H4 with defective luxI gene was successfully constructed in this study, and the effect of this mutation on the quorum-sensing system was characterized with respect to AHL production, biofilm formation, and swimming motility. The luxI gene was generally recognized as AHL synthase gene, which controls the synthesis of AHLs (Waters and Bassler, 2005; Morohoshi et al., 2007). Indeed, the luxI mutant produced no detectable AHLs as assayed with the biosensor strain CV026 (**Figure 1**), consistent with the results reported for Aeromonas hydrophila and Acinetobacter nosocomialis (Khajanchi et al., 2009; Oh and Choi, 2015). The complementing strain of luxI was also constructed, and no differences in AHLs production, biofilm formation and swimming motility were found between comp-1luxI and WT strain (**Supplementary Figure 1**).

It is known to us that when local concentration of AHLs is high enough, AHLs would diffuse back into the cell, and induce the expression of luxR gene (Waters and Bassler, 2005; Bai and Rai, 2011). Expression of the luxR gene in the AHL-deficient strain of H. alvei H4 was found to decrease significantly, suggesting that expression of the luxR gene might require induction by AHLs. This hypothesis was confirmed by significant increase in luxR expression in the mutant when it was cultured in the presence of exogenous AHL (C4-HSL, C6-HSL, or 3-o-C8-HSL). The stimulating effect on luxR gene increased with the increase of AHLs concentration, causing the increase in luxR gene expression consequently. Similar result has also been obtained for Aliivibrio fischeri, whereby expression of the luxR gene was observed in the presence of 3-o-C6-HSL, with higher concentrations of the compound leading to more expression of the gene (Ramalho et al., 2016). In addition, there is also a threshold concentration of AHLs, and QS regulon is depressed when the concentration of AHLs exceeds this threshold, as a result of causing the reduction of luxR gene expression (Swift et al., 2001). Similar changes of sinR gene expression affected by AHLs were also obtained by Gao et al. (2012) in Sinorhizobium meliloti. Besides, response of CviR to autoinducer were found depressed when exposed to high concentration AHLs (Swem et al., 2009) in C. violaceum, consistent to the results achieved in the present study (**Figures 2B–D**).

Biofilm formation by the luxI mutant was inhibited, and since the mutant was deficient in AHL, this indicated that biofilm formation might be modulated by AHLs, and is associated with AHL-mediated QS. As reported by Ammor et al. (2008), bacterial phenotype such as resistance to antimicrobial compounds, biofilm formation, bioluminescence; pigment production, virulence gene expression, swimming motility and production of degradative extracellular proteases are regulated by the QS system. Furthermore, the addition of C4- HSL to the 1luxI culture restored the ability of the mutant cells to form biofilm, while the addition of C6-HSL and 3-o-C8-HSL appeared to have no significant effect, suggesting that the C4- HSL might play an important role in the regulation of biofilm formation in H. alvei H4. Similar result has been reported for A. hydrophila, in which biofilm formation and protease activity, which are inhibited in an AHL-deficient strain, can be stimulated by the addition of C4-HSL to the culture (Khajanchi et al., 2009). Niu et al. (2008) investigated the regulatory role of C12- HSL in the biofilm formation of Acinetobacter baumannii M2 and showed that biofilm formation is obviously inhibited in an

Zhu et al. Quorum Sensing of Hafnia alvei

abaI mutant, but can be restored by the addition of C12-HSL to the culture. Similarly, in Acinetobacter sp. strain DR1, C12- HSL was also found to play the same role as in A. baumannii M2 (Kang and Park, 2010). In P. aeruginosa, the LasR protein (a LuxR homologous protein) is soluble and stable only when it is produced in the presence of its cognate AHL ligand 3 o-C12-HSL, as the protein is becoming less soluble if it is produced in the presence of a different AHL, such as 3-o-C8- HSL or 3-o-C6-HSL, while soluble form is not produced in the presence of C4-HSL (Bottomley et al., 2007). Hence, C4- HSL might be the cognate ligand of LuxR in H. alvei H4, and it may possibly bind to the LuxR protein and play a regulatory role. In P. syringae and S. meliloti, the production of extracellular polysaccharide has been shown to be regulated by QS (Marketon et al., 2003; Quiñones et al., 2005). Therefore, the reduction in the numbers 1luxI cells adhering to polystyrene, glass and stainless-steel surfaces that we observed (**Figures 3–5**) might be caused by the reduction in biofilm formation and extracellular polysaccharide secretion. According to the results achieved in the present research and the studies reported by Nasser et al. (1998) and Andersson et al. (2000), different AHLs in bacteria may regulate different phenotypes, for H. alvei H4, C4-HSL seems to have a more important effect on regulating biofilm formation and swimming motility than C6- HSL and 3-o-C8-HSL, however, in other phenotypes regulated by quorum sensing system, C6-HSL and 3-o-C8-HSL might act as regulators.

Another important factor in the biofilm formation of bacteria is the extent of swimming motility, which contributes to the early development of the biofilm architecture (microcolony formation) (Srey et al., 2013). Bacterial motility depends mainly on the movement of flagella and Brownian motion (Li et al., 2008). Furthermore, some genes such as the flgA, motA, and cheA genes have been shown to be involved in biofilm formation and swimming motility (Lee et al., 2015). The data on swimming motility assay and qRT-PCR analysis of the expression of these three motility-related and biofilm-related genes, flgA, motA, and cheA (**Figure 8**), appeared to suggest that swimming motility might be regulated by regulating the expression of these genes. Since 1luxI exhibited significantly less swimming motility and lower expression of the flgA, motA, and cheA genes than WT strain in the absence of exogenous AHLs, these two factors might also be the cause of poor biofilm formation displayed by the mutant. Similar results have also been reported by Gurich and González (2009), whereby deletion of the sinI gene in

### REFERENCES

S. meliloti can result in significant reduction in the expression of the motility genes flaA and flaB, but such reduction can be reversed by the presence of AHLs. In contrast to our data, Wang T. et al. (2016) demonstrated that in Acidovorax citrulli, biofilm formation, motility and adherence of bacterial cells to a solid surface can be significantly promoted when the accR/I gene is defective. Furthermore, in A. nosocomialis, both biofilm formation and motility were found to be modulated by the luxR homologous gene anoR (Oh and Choi, 2015), and not the anoI gene. Therefore, the regulation of QS in biofilm formation their swimming motility might be different for different bacteria.

### CONCLUSION

In H. alvei, AHL-mediated QS system plays a key part in swimming motility and biofilm formation on different solid surfaces. We have shown here that among the different AHLs tested, C4-HSL appeared to exert a more significant impact on the modulation of these properties of the cells. Further study focusing on the regulation mechanism of the luxR/I gene, and the screening of effective QS inhibitors for H. alvei, and the application of these inhibitors to food production may bring about economic benefits as well as preventing the spread of food-related incident of infection among the public.

### AUTHOR CONTRIBUTIONS

HMH and GZ designed this study. YZ conducted the experiments. YZ, HMH, and YW performed the data analyses. HSH, GZ, and YZ drafted and revised the manuscript. All authors read and approved the final version of this manuscript.

### FUNDING

This work was supported financially by "The National Natural Science Foundation of China (Grant No. 31871895)."

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2019.01330/full#supplementary-material

of exogenous AHLs on bacterial phenotype. J. Gen. Appl. Microbiol. 62, 60–67. doi: 10.2323/jgam.62.60

**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 © 2019 Zhu, Hou, Zhang, Wang and Hao. 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) and the copyright owner(s) 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.

# Can Biofilm Be Reversed Through Quorum Sensing in Pseudomonas aeruginosa?

### Shaomin Yan and Guang Wu\*

State Key Laboratory of Non-Food Biomass and Enzyme Technology, National Engineering Research Center for Non-Food Biorefinery, Guangxi Key Laboratory of Biorefinery, Guangxi Biomass Engineering Technology Research Center, Guangxi Academy of Sciences, Nanning, China

Pseudomonas aeruginosa is a Gram-negative bacterium causing diseases in plants,

#### Edited by:

Cristina García-Aljaro, University of Barcelona, Spain

#### Reviewed by:

Rodolfo García-Contreras, National Autonomous University of Mexico, Mexico Akanksha Singh, Central Institute of Medicinal and Aromatic Plants (CIMAP), India

\*Correspondence:

Guang Wu<EMAIL_ADDRESS><EMAIL_ADDRESS>
#### Specialty section:

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

Received: 02 April 2019 Accepted: 25 June 2019 Published: 23 July 2019

#### Citation:

Yan S and Wu G (2019) Can Biofilm Be Reversed Through Quorum Sensing in Pseudomonas aeruginosa? Front. Microbiol. 10:1582. doi: 10.3389/fmicb.2019.01582 animals, and humans, and its drug resistance is a major concern in medical care. Biofilms play an important role in P. aeruginosa drug resistance. Three factors are most important to induce biofilm: quorum sensing (QS), bis-(30 -50 )-cyclic diguanosine monophosphate (c-di-GMP), and small RNAs (sRNAs). P. aeruginosa has its own specific QS system (PQS) besides two common QS systems, LasI–LasR and RhlI–RhlR, in bacteria. PQS is interesting not only because there is a negative regulation from RhlR to pqsR but also because the null mutation in PQS leads to a reduced biofilm formation. Furthermore, P. aeruginosa dispersed cells have physiological features that are distinct between the planktonic cells and biofilm cells. In response to a low concentration of c-di-GMP, P. aeruginosa cells can disperse from the biofilms to become planktonic cells. These raise an interesting hypothesis of whether biofilm can be reversed through the QS mechanism in P. aeruginosa. Although a single factor is certainly not sufficient to prevent the biofilm formation, it necessarily explores such possibility. In this hypothesis, the literature is analyzed to determine the negative regulation pathways, and then the transcriptomic data are analyzed to determine whether this hypothesis is workable or not. Unexpectedly, the transcriptomic data reveal a negative regulation between lasI and psqR. Also, the individual cases from transcriptomic data demonstrate the negative regulations of PQS with laslI, laslR, rhlI, and rhlR under different experiments. Based on our analyses, possible strategies to reverse biofilm formation are proposed and their clinic implications are addressed.

Keywords: biofilm, P. aeruginosa, quorum sensing, transcriptome, positive feedback, negative feedback

## INTRODUCTION

Pseudomonas aeruginosa is a Gram-negative bacterium living in soil and water.

Therefore, P. aeruginosa is a major concern in medical care because of its drug resistance against the traditional antibiotic therapy (Buhl et al., 2015; Oliver et al., 2015), that is particularly problematic for immunocompromised patients and the elderly in nosocomial environments (Xia et al., 2016). P. aeruginosa brings about its drug resistance through hydrolyzation of antibiotics with carbapenemases or extended-spectrum β-lactamases or ApmR (Vatcheva-Dobrevska et al., 2013; Fisher and Mobashery, 2014; Hakemi Vala et al., 2014), the low permeability of outer membrane (Eren et al., 2013; Zgurskaya et al., 2015), the multidrug efflux (Poole, 2004; Aghazadeh et al., 2014), etc. Also, the biofilm is an important player in P. aeruginosa drug resistance (Mah et al., 2003) because the dense extracellular matrix of biofilms reduces the efficacy of detergents and antibiotics (Mah et al., 2003). Such resistance could be increased a thousand times in some cases (Stewart and Costerton, 2001).

The dispersal of cells from the biofilm colony is a crucial and unique stage for biofilms to spread and colonize new surfaces (Monroe, 2007) and for the transition of dispersed cells from the biofilm to the planktonic growth phase. Could it be possible to stop the biofilm from happening, or reserve the biofilm back to the planktonic phenotype, or eradicate the biofilm in bacteria?

Theoretically, this hypothesis could be possible for P. aeruginosa, because its dispersed cells have physiological features that are distinct between the planktonic and the biofilm cells (Chua et al., 2014, 2015). In response to a low concentration of c-di-GMP, P. aeruginosa cells can disperse from the biofilm to become the planktonic cells. The drug resistance is not stronger in the biofilm cells than in the stationary-phase planktonic cells, but is stronger than in the logarithmic-phase planktonic cells (Spoering and Lewis, 2001). Additionally, P. aeruginosa produces cis-2-decenoic acid, which is a fatty acid messenger and induces dispersion and inhibits the growth of biofilm colonies (Davies and Marques, 2009). Furthermore, nitric oxide triggers the dispersal of biofilms in P. aeruginosa (Barraud et al., 2006), leading to the treatment of chronic infections in cystic fibrosis (Howlin et al., 2017).

The formation of biofilm is induced and regulated by numerous genes and environmental factors (Fazli et al., 2014), of which three are most important. The first one is the quorum sensing (QS), because QS controls about 10% genes in P. aeruginosa (Wagner et al., 2003), including many genes that are actively involved in the biofilm development and dispersal, although they are unlikely to be involved in the attachment and the initial of biofilm growth (Davies et al., 1998). The second one is the bis-(30 -50 )-cyclic diguanosine monophosphate (c-di-GMP), because its signaling network is the most complex secondary signaling system in bacteria (Hengge, 2009) and has the responsibility to decide whether bacteria adopt either planktonic or biofilm phenotype (Jenal and Malone, 2006). The third one is the small RNAs (sRNAs) although their role in biofilm is yet to be clear (Wolska et al., 2016).

Indeed, QS has a close relationship with biofilm (Wolska et al., 2016). It controls the synthesis of rhamnolipids that maintain the channels (Stoodley et al., 1994) for distributing nutrient and oxygen and removing waste products in mushroom-shaped structures (Davey and O'Toole, 2000). The channels can help in the release of a large amount of eDNA due to the autolysis of subpopulation of bacteria (Allesen-Holm et al., 2006) at the late stage of biofilm development. Various components of the biofilm matrix, such as extracellular DNA (eDNA), exopolysaccharides (EPS) and glucan, are closely related to biofilm matrix dynamics and bacterial virulence (Rainey et al., 2019). Also, there are other virulence factors, which play an important role in the QS regulation and biofilm formation. For example, pyocyanin promotes eDNA release and facilitates the biofilm formation (Klare et al., 2016).

It is worth reviewing literature to explore whether the biofilm is theoretically reversible through QS in P. aeruginosa, not only because P. aeruginosa is a causal organism of important health ailments but also because P. aeruginosa is a commonly used biofilm model organism (Rasamiravaka et al., 2015). More importantly, the synthesis of rhamnolipid in P. aeruginosa occurs at its late-exponential and stationary phases (Guerra-Santos et al., 1986). Rhamnolipid helps bacteria to utilize long-chain fatty acids as sources of carbon (Ochsner et al., 1994a) so it plays an important role in the biofilm formation (Stoodley et al., 1994; Davey and O'Toole, 2000; Allesen-Holm et al., 2006).

Reversing of biofilms could be plausible because QS is a target in many different circumstances such as attenuate virulence (Chan et al., 2015), bacterial metabolism (Goo et al., 2015), bacterial response to antibiotics (Rasamiravaka and El Jaziri, 2016), and therapy (LaSarre and Federle, 2013). Besides, the mechanism to form biofilms in P. aeruginosa is definitely different from other bacteria such as P. putida, P. fluorescens, Staphylococcus aureus, and Vibrio cholera (Wolska et al., 2016).

Needless to say, the reversing of biofilms is related to multiple factors, so a single factor such as QS could have very limited effects. However, we should theoretically explore those possibilities one by one at initial stage in view of the importance of biofilms in clinical meanings.

### POSITIVE AND NEGATIVE REGULATIONS IN QS

If we wish to reverse the biofilm through the QS, we need to find out whether the QS is reversible or not. So far overwhelmed evidence suggests that the QS is a positive feedback system, which implies that it is impossible to stop the QS once the QS is initiated. However, we have yet to know whether the ending point of QS is the biofilm formation? If this is the case, the stop of QS will either reverse the biofilm or stop the biofilm formation. To answer this issue, it is necessary to find out the negative regulation (feedback) in QS.

The QS is a cell-to-cell communication by means of production, detection, and response of chemical compounds, autoinducers, and thus the QS changes an individual or a population behavior upon the concentration of autoinducers, which are subject to the cell density (Fuqua et al., 1994).

Pseudomonas aeruginosa has three QS systems. (i) LasI– LasR that is related to the synthesis and the use of N-(3-oxododecanoyl)-L-homoserine lactone (3OC12-HL) (Passador et al., 1993; Pearson et al., 1994), whose concentration is ranged from

1 to 5 µM (Pearson et al., 1994, 1995) (brown color items in **Figure 1**). (ii) RhlI-RhlR that is related to the synthesis and the use of N-(butyryl)-L-homoserine lactone (BHL) (Pearson et al., 1995), whose concentration is about 10 µM (Pearson et al., 1995) (yellow color items in **Figure 1**). (iii) Pseudomonas quinolone signal (PQS)-based QS, PqsABCDH-PqsR that is related to the synthesis and the use of 2-heptyl-3-hydroxy-4-quinolone (HHQ) (Mashburn-Warren et al., 2008; Kulkarni and Jagannadham, 2014), whose concentration is about 6 µM (Pesci et al., 1999) (green color items in **Figure 1**). The first two QS systems essentially are N-acylated homoserine lactone (AHL)-based QS systems (Pesci et al., 1997) and exist in many bacteria.

The sophisticated QS systems in P. aeruginosa are described as follows. (i) LasI produces 3OC12-HL, which acts on LasR (Gambello and Iglewski, 1991; Pearson et al., 1994) (the upward brown arrow from lasR to LasR on the left side of **Figure 1**). (ii) LasR acts on aprA (Gambello et al., 1993), lasA (Toder et al., 1991) and toxA (Gambello and Iglewski, 1991; Gambello et al., 1993; Passador et al., 1993) (the downward brown arrow on the far left side in **Figure 1**). (iii) Both LasI and LasR act on lasB (Pearson et al., 1994, 1995) through 3OC12-HL, whose half-maximal expression needs 1.0 nM (Seed et al., 1995) (brown symbols on the left side of **Figure 1**). (iv) RhlI produces BHL, which acts on RhlR (Pearson et al., 1995, 1997) (the bright yellow arrow on the right side of **Figure 1**). (v) RhlR acts on pyocyanin synthesis (Meighen, 1991; Ochsner et al., 1994b; Brint and Ohman, 1995) (the long yellow arrow on the middle of **Figure 1**), lasA (Brint and Ohman, 1995) (the yellow arrow on the middle left of **Figure 1**), and rpoS (Latifi et al., 1996) (the yellow arrow on the upper right corner of **Figure 1**). (vi) Both RhlI and RhlR act on lasB through BHL (Brint and Ohman, 1995) (the yellow arrow on the upper right part of **Figure 1**), and rhlABR (Ochsner and Reiser, 1995) (the small yellow arrow on the middle of **Figure 1**), where rhlAB encodes rhamnosyltransferase (Ochsner et al., 1994a) (two yellow arrows on the upper middle part of **Figure 1**) together with rhlR positively regulate rhamnolipid synthesis (Ochsner et al., 1994b) (the yellow arrow on the middle upper part of **Figure 1**). (vii) LasR and RhlR positively regulate the synthesis of hydrogen cyanide (Pessi and Haas, 2000) (the downward yellow arrow on the lower middle part of **Figure 1**).

Still, **Figure 1** displays the effects of PQS-based QS on their targets. (i) PqsABCDH produces HHQ requiring phnA and phnB through anthranilate (Gallagher et al., 2002) (the green curly lines on the middle right part of **Figure 1**), then HHQ acts on PqsR (Cao et al., 2001), regulating the production of elastase, PA-IL lectin, pyocyanin and rhamnolipid (Pesci et al., 1999; McKnight et al., 2000; Gallagher et al., 2002; Lee and Zhang, 2015) (the green lines from the lower right corner in **Figure 1**). (ii) PqsE positively acts on biosynthesis of various virulent factors, which is independent of HHQ or any compounds produced related to the function of pqsABCDE operon although the expression of pqsE and PqsE are controlled by HHQ and PqsR (Farrow, et al., 2008) (dashed green line on the lower right part of **Figure 1**). (iii) PqsR– HHQ is involved in iron homeostasis (Bredenbruch et al., 2006; Oglesby et al., 2008) (the lowest green line in **Figure 1**).

A positive feedback can be found in each of three QS systems. (i) The first positive feedback goes from LasR–3OC12-HL to LasI through lasI, whose half-maximal expression needs 0.1 nM 3OC12-HL (Seed et al., 1995) (light gray ellipse on the left part of **Figure 1**). (ii) The second positive feedback goes from RhlR–HL to RhlI through rhlI (Ochsner and Reiser, 1995) (light gray ellipse on the upper right part of **Figure 1**). (iii) The third positive feedback goes from PqsR–HHQ to pqsABCDE and phnAB operons (Cao et al., 2001; Gallagher et al., 2002; Wade et al., 2005) (light gray ellipse on the middle right part of **Figure 1**).

The relationship among three QS systems in P. aeruginosa is positive in the following regulations. (i) LasR positively regulates HHQ through the complex LasR–3OC12-HL on pqsH (Pesci et al., 1999; Schertzer et al., 2009) (brown arrow on the right middle part of **Figure 1**). (ii) RhlR positively regulates HHQ through PqsE (Pesci et al., 1999) (two arrow-blue lines on the middle right part of **Figure 1**). (iii) LasR positively regulates rhlR through the complex LasR–3OC12-HL (Latifi et al., 1996; Pesci et al., 1997) and rhlI (Latifi et al., 1996) (the brown horizontal line with two arrows in **Figure 1**). (iv) HHQ strongly acts on rhlI with BHL (two arrow-blue lines in middle right part of **Figure 1**) but weakly acts on lasR and rhlR (McKnight et al., 2000). (v) RhlR positively regulates PqsE, whose overexpression leads to a high rhamnolipid production (Farrow, et al., 2008) (the yellow arrow on the right middle part of **Figure 1**). (vi) PqsE changes the function of RhlR rather than that of BHL (Farrow, et al., 2008) (two arrow-blue lines on the middle right part of **Figure 1**). (vii) LasR/3OC12-HL controls pqsR (Camilli and Bassler, 2006) (the end arrow of brown horizontal line in **Figure 1**).

In fact, there is a negative regulation among QS systems, namely, RhlR negatively regulates pqsR in P. aeruginosa (Pesci et al., 1997; Wade et al., 2005), or RhlR and BHL together negatively affect the production of HHQ and other quinolones through pqsR to pqsABCDE operon transcription (McGrath et al., 2004; Jensen et al., 2006; Xiao et al., 2006b) (the yellow arrow from RhlR–BHL to the yellow horizontal line to the right end with downward dash end in **Figure 1**). On the other hand, a negatively regulatory pathway is not so sure (the yellow end line highlighted with a red star on the middle of **Figure 1**).

### CAN THIS NEGATIVE REGULATION WORK?

As PQS-based QS is so particularly relevant to Pseudomonas, its significance should not be ignored. This is because the null mutation in PQS leads to a reduced biofilm formation and decreased the productions of pyocyanin, elastase, PA-IL lectin and rhamnolipids (Rahme et al., 1997, 2000; Cao et al., 2001; Diggle et al., 2003). Indeed, PQS directly or indirectly controls 92 or 143 genes as shown in two transcriptomic analyses (Deziel et al., 2005; Bredenbruch et al., 2006). By contrast, the other two QS systems together influence the expression in 200-plus genes (Whiteley et al., 1999).

For PQS, it does not reach its maximal production until the late stationary phase of growth (McKnight et al., 2000). This implies that HHQ is not involved in sensing the cell density, so the observation that the QS response is not reversed for

small decreases in population density in P. aeruginosa (Williams and Camara, 2009) is not the failure of PQS. An important time interval appears between QS systems, i.e., BHL is produced during the log phase of growth but HHQ is produced during late time in the stationary phase of growth (McKnight et al., 2000), so the positive regulation of HHQ on rhlI is more likely to be related to the second round of RhlI cycle. If HHQ would not function at this time interval, perhaps the QS would stop.

Another promising point is that the phenazine production requires HHQ in P. aeruginosa (McKnight et al., 2000; Mavrodi et al., 2001). In fact, phenazines may have a significant ecological impact on the biofilm formation in P. aeruginosa as well as other bacteria persisting in biofilms mixed with P. aeruginosa. Through affecting H2O2 generation, phenazines bring about the lysis of competing bacterial cells in mixed biofilms and the subsequent eDNA release (Das and Manefield, 2013).

Perhaps, one of the best ways to explore the possibility of whether the QS is reversible through PQS in P. aeruginosa is to analyze the transcriptomic data in order to find some common patterns. Accordingly, we analyzed the transcriptomic data on Affymetrix P. aeruginosa array with 5549 P. aeruginosa genes, platform GPL84, from Gene Expression Omnibus (GEO) (Edgar et al., 2002; Barrett et al., 2013), including all the data in 104 publications (**Supplementary Information**) with 274 datasets. Each dataset represents the response to a specifically experimental condition. With these all available transcriptomic data, we wish to determine if PQS could be depressed under different experimental conditions.

**Table 1** shows correlation coefficients between any two genes of three QS systems. The rationale is that there are up-regulations and down-regulations in transcriptomic data. The correlation between two genes, which are both up-regulated or both downregulated, would suggest a positive regulation with a positive correlation coefficient. By contrast, the correlation between two genes, which are regulated oppositely, would suggest a negative regulation with a negative correlation coefficient.

Based upon the correlations within a single QS system in **Table 1**, the correlations between lasI and lasR, and between rhlI and rhlR confirm their auto-induction relationships (Gambello and Iglewski, 1991; Pearson et al., 1994) within each QS system. No negative correlation is found between the QS genes in the same QS system. As pqsR is named mvfR in gene bank, the auto-induction relationship with the rest of PQS genes are not very evident as the paired correlations between pdsA, pqsB, pqsC, pqsD, pqsE, but all paired correlations suggest a positive regulation within PQS system (Gallagher et al., 2002). Based upon the correlations between two QS systems in **Table 1**, the results conform there is a positive regulation between lasI–lasR and rhlI–rhlR, and between rhlI-rhlR and pqsABCDE. However, an undocumented negative regulation is revealed between lasI

and pqsR/mvfR using these transcriptomic data. Could it be a potential pathway to reverse the biofilm formation?

Furthermore, the responses of QS systems are analyzed under different transcriptomic experiments, and classified as down-regulation, down-regulation/no response, no response, no response/up-regulation, up-regulation and mixed responses. **Figure 2** shows such analysis according to 94 transcriptomic experiments. No response on three QS systems was found in 30 transcriptomic experiments (the intersection of three circles in **Figure 2**). Both LasI-LasR and RhlI-RhlR have the same response in 29 transcriptomic experiments (the intersection of two upper circles in **Figure 2**), suggesting a good cooperation between them. By the contrast, only five and six transcriptomic experiments show the same response for PQS with LasI-LasR and RhlI-RhlR (the intersection of two upper and lower circles in **Figure 2**), respectively. The same response in both LasI-LasR and PQS systems includes no response in GSE24784, GSE26142, GSE35248, and GSE39044, and no response/up-regulation in GSE22684, indicating few positive impact of LasI-LasR on PQS. The same response in both RhlI-RhlR and PQS systems includes: down-regulation in GSE9255; down-regulation/no response in GSE5887; no response in GSE17179 and GSE61925; and no response/up-regulation in GSE65882 and GSE7402. Thus, the results from Venn diagram indicate that RhlI-RhlR has weak impacts on PQS. **Figure 2** demonstrates the responses of 30, 29, and 53 transcriptomic experiments solely in LasI-LasR, RhlI-RhlR, and PQS, respectively, of which their response ranges from down-regulation to mixed response.

Finally, the negative regulation between different QS systems is found in four transcriptomic experiments (GSE4152, GSE8408, GSE6122, and GSE17296). In the study on Australian clonal strain (AES-1) in patients with cystic fibrosis in GSE6122 (Manos et al., 2009), lasI, rhlI, and rhlR were down-regulated while pqsA, pqsB, pqsC, pqsD, and pqsE were up-regulated. This highlights the PQS remarkable effect on the biofilm formation and enhanced infectivity. Another three

transcriptomic experiments show that pqsA, pqsB, pqsC, pqsD, and pqsE were down-regulated whereas rhlI and rhlR were upregulated (Teitzel et al., 2006; Tralau et al., 2007; Kawakami et al., 2010), of which lasI was up-regulated in copper-stressed (Teitzel et al., 2006), and both lasI and lasR were up-regulated in sulfate limitation (Tralau et al., 2007). Therefore, RhlI-RhlR does have a negative regulation on PQS (McGrath et al., 2004; Wade et al., 2005; Xiao et al., 2006a).

### CONCLUSION

In this hypothesis, we apply the transcriptomic data to verify the hypothesis of whether the biofilm can be reversed in P. aeruginosa through QS because there are negative regulations between PQS and RhlI-RhlR. Interestingly, the transcriptomic data from 104 publications reveal a negative regulation between lasI and psqR, rendering a support to the hypothesis. Individual cases from transcriptomic data under different experiments demonstrate the negative regulations of PQS with laslI, laslR, rhlI, and rhlR.

In general, the relationships among different QS systems reveal positive regulations, which act together to promote the biofilm formation. However, the present analyses from literature and transcriptomic data provide the evidence that both LaslI-LaslR and RhlI-RhlR systems have negatively regulatory effects on PQS system. This is very important because these negative regulations lay the foundation for the biofilm reversion through QS. Although the exact pathways are still not fully discovered, the N-acylated homoserine lactone (AHL)-based QS systems can influence PQS-based QS system by inhibiting the expression of pqsABCDE operon and pqsR, resulting in the reduction of HHQ and PqsR synthesis. Consequently, the low concentration of PQS related products cannot maintain the biofilm, leading to its reversion. On the other hand, the down-regulated PQSbased QS system cannot perform well their function of positive regulations on LaslI-LaslR and RhlI-RhlR systems, which will further affect the biofilm formation, especially in the second round of RhlI cycle. Surely, there are other factors that play roles in the formation of drug-resistant multicellular biofilms, such as c-di-GMP. As mentioned in section "Introduction," this signal can govern bacterial cells to adopt either planktonic phenotype or biofilm formation (Hengge, 2009). Recent study demonstrates that high levels of cAMP lead to the decrease of c-di-GMP

### REFERENCES

content, which inhibits the biofilm formation in P. aeruginosa (Almblad et al., 2019).

In clinic therapeutics for infectious diseases, antibiotic resistance has been spreading widely and rapidly, which becomes a major challenge for modern medicine. The strategy of interfering the biofilm formation is effective through bacterial cell-to-cell communication, especially with QS system (Soheili et al., 2019). More recently, QS inhibitors are drawing great attention in blocking the pathogenicity from P. aeruginosa (Calvert et al., 2018; Schütz and Empting, 2018). The transcriptional regulator PqsR becomes an attractive object and is considered to be one of the most appropriate targets. Currently, QS regulation mechanism in P. aeruginosa is mainly related to positive and negative regulation between QS systems. Clearly, exploration of regulation beyond QS should get attention in future.

### DATA AVAILABILITY

All datasets generated or analyzed for this study are included in the manuscript and the **Supplementary Files**.

### AUTHOR CONTRIBUTIONS

GW designed the work. Both authors prepared and approved the manuscript.

### FUNDING

This work was partly supported by the National Natural Science Foundation of China (Nos. 31460296 and 31560315) and the Key Project of Guangxi Scientific Research and Technology Development Plan (AB17190534).

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2019.01582/full#supplementary-material

**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 © 2019 Yan and Wu. 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) and the copyright owner(s) 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.

# Bacterial–Fungal Interactions in the Kelp Endomicrobiota Drive Autoinducer-2 Quorum Sensing

Anne Tourneroche1 , Raphaël Lami2 \*, Cédric Hubas3 , Elodie Blanchet2 , Marine Vallet1 , Karine Escoubeyrou4 , Alain Paris1 and Soizic Prado1 \*

1 Unité Molécules de Communication et Adaptation des Microorganismes (MCAM), Muséum National d'Histoire Naturelle (MNHN), Centre National de la Recherche Scientifique (CNRS), CP 54, Paris, France, 2 CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes (LBBM), USR3579, Observatoire Océanologique de Banyuls, Sorbonne Université, Banyuls-sur-Mer, France, 3 Muséum National d'Histoire Naturelle, UMR BOREA 7208 MNHN-Sorbonne Université-CNRS-UCN-UA-IRD, Station Marine de Concarneau, Paris, France, 4 CNRS, Observatoire Océanologique de Banyuls, Sorbonne Université, FR3724, Banyuls-sur-Mer, France

#### Edited by:

Tom Defoirdt, Ghent University, Belgium

### Reviewed by:

Qian Yang, Yellow Sea Fisheries Research Institute (CAFS), China Natrah Fatin Mohd Ikhsan, Putra Malaysia University, Malaysia

#### \*Correspondence:

Raphaël Lami<EMAIL_ADDRESS>Soizic Prado<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

> Received: 16 April 2019 Accepted: 09 July 2019 Published: 31 July 2019

#### Citation:

Tourneroche A, Lami R, Hubas C, Blanchet E, Vallet M, Escoubeyrou K, Paris A and Prado S (2019) Bacterial–Fungal Interactions in the Kelp Endomicrobiota Drive Autoinducer-2 Quorum Sensing. Front. Microbiol. 10:1693. doi: 10.3389/fmicb.2019.01693 Brown macroalgae are an essential component of temperate coastal ecosystems and a growing economic sector. They harbor diverse microbial communities that regulate algal development and health. This algal holobiont is dynamic and achieves equilibrium via a complex network of microbial and host interactions. We now report that bacterial and fungal endophytes associated with four brown algae (Ascophyllum nodosum, Pelvetia canaliculata, Laminaria digitata, and Saccharina latissima) produce metabolites that interfere with bacterial autoinducer-2 quorum sensing, a signaling system implicated in virulence and host colonization. Additionally, we performed co-culture experiments combined to a metabolomic approach and demonstrated that microbial interactions influence production of metabolites, including metabolites involved in quorum sensing. Collectively, the data highlight autoinducer-2 quorum sensing as a key metabolite in the complex network of interactions within the algal holobiont.

Keywords: quorum sensing (QS), AI-2, bacterial–fungal interaction, kelp microbiota, algal holobiont

### INTRODUCTION

Large marine brown algae, i.e., kelp, are an essential component of temperate coastal ecosystems. Indeed, these organisms are important primary producers that generate a specific habitat and thereby shape coastal marine life (Egan et al., 2013). In addition, kelp farming has been a growing economic sector over the last decades (FAO, 2018).

Like most eukaryotes, macroalgae are colonized by various microorganisms (the microbiota) that interact with them throughout the life cycle, and that modify their physiology (Wahl et al., 2012; Egan et al., 2013; Singh and Reddy, 2014). For example, commensal bacteria have profound effects on seaweed development, nutrition, and defense (Wahl et al., 2012; Singh and Reddy, 2014; Tapia et al., 2016). Algal tissues are also asymptomatically colonized by filamentous fungi (Debbab et al., 2012), although these fungi and their role are yet to be fully characterized (Fries, 1979; Zuccaro et al., 2003, 2008; Loque et al., 2010; Jones et al., 2012). Previously, we isolated and characterized the molecular diversity of cultivable fungi in different parts of the brown algae Ascophyllum nodosum, Pelvetia canaliculata, Laminaria digitata, and Saccharina latissima. We also found that metabolites produced by endophytic fungi are key mediators of interactions among macroalgae, their fungal microbiota, and protistan pathogens (Vallet et al., 2018).

Endophytic bacteria are likely to interact with fungi in the algal host to maintain the host-microbiota equilibrium and thus contribute to host health (Deveau et al., 2018; Hassani et al., 2018). Indeed, structural changes in the microbiota, i.e., dysbiosis, have been linked to disease in marine organisms and seaweeds (Fernandes et al., 2012; Zozaya-Valdes et al., 2015; Egan and Gardiner, 2016). However, the mechanisms underlying bacterial– fungal homeostasis remain unclear, although they appear crucial to macroalgal physiology not only in nature but also in farms, highlighting their importance in light of intensifying algal culture (Gachon et al., 2010).

Bacterial–fungal interactions consist of multiple and concomitant mechanisms ranging from nutrient competition to antibiosis, many of which depend on chemical signaling. Quorum sensing, which allows bacteria to coordinate gene expression based on the density of specific signaling molecules, is of particular interest, since it is essential for virulence, colonization, biofilm formation, and toxin production (Atkinson and Williams, 2009). Indeed, various types of quorum signals, also known as auto-inducers (AI), are already known. Some have been found in only one genus whereas others, such as type 1 (AI-1) or type 2 (AI-2), are present in various bacterial genera. Indeed, AI-2 molecules appear widespread among prokaryotes, and is produced by over 50% of sequenced bacterial species, including both Gram-positive and Gram-negative species (Hammer and Bassler, 2003; Federle, 2009). AI-2 molecules are derived from a common precursor, (S)-4,5 dihydroxypentane-2,3-dione (DPD), which is synthesized by the enzyme LuxS. By spontaneous cyclization, this precursor is transformed to 4-hydroxy-5-methyl-3(2H)furanone, (2R,4S)- 2-methyl-2,3,3,4-tetrahydroxytetrahydrofuran, and, especially in marine environments, to the furanosyl borate diester (Hardie and Heurlier, 2008).

Various marine bacteria were found to produce AI-2 (Bodor et al., 2008; Doberva et al., 2015; Pérez-Rodríguez et al., 2015), although it is considered in some species to be a metabolic by product and not a signaling molecule (Rezzonico and Duffy, 2008). Nevertheless, many studies showed that AI-2 regulates niche-specific behaviors in commensal and pathogenic bacteria, including biofilm formation or dispersion, cell division, virulence, bioluminescence, and motility (Hammer and Bassler, 2003; Hardie and Heurlier, 2008; Federle, 2009). Accordingly, secreted AI-2 is now recognized as a key signaling molecule that affects bacterial behavior at species and community level (Whiteley et al., 2017).

Strikingly, quorum sensing molecules are not exclusively produced by bacteria. Indeed, these compounds were also shown to regulate fungal morphogenesis, germination, apoptosis, biofilm development, or pathogenicity (Wongsuk et al., 2016). Importantly, some recent studies showed that both bacterial and fungal quorum sensing compounds mediate cross-kingdom signaling. For instance, eukaryotes may interfere with bacterial quorum sensing (Martín-Rodríguez et al., 2014; Ismail et al., 2016), while bacteria may react to fungal quorum signals (Cugini et al., 2007; Fourie et al., 2016). Cross-kingdom signaling is also modulated by quorum sensing inhibitors, i.e., quorum quenchers (Grandclément et al., 2016; Rolland et al., 2016). To date, halogenated furanones synthesized by the marine red algae Delisea pulchra are the best-studied naturally occurring quorum sensing inhibitors in eukaryotes. These compounds regulate bacterial colonization of algal surfaces by interfering with AI-1 and AI-2 (Defoirdt et al., 2007; Harder et al., 2012).

Despite these breakthroughs, the role of AI-2 quorum sensing in marine environments in general, and in holobionts in particular, remains poorly characterized (Doberva et al., 2015; Hmelo, 2017). One important shortcoming is the lack of quantitative measurements, since AI-2 itself is difficult to quantify (Wang et al., 2018). In this study, we hypothesized that AI-2 quorum sensing is involved in interspecies chemical signaling among endophytic fungi and bacteria in seaweeds. Accordingly, we first isolated and molecularly characterized the cultivable bacteria associated with the brown algae A. nodosum, P. canaliculata, L. digitata, and S. latissima. These bacteria were then investigated for their ability to produce or inhibit production of AI-2 along with fungi previously isolated from the same samples (Vallet et al., 2018). Co-cultures experiments, between several fungal and bacterial endophytic strains isolated from S. latissima microbiota combined with metabolomics approach pointed out that inter-species interactions involve metabolites production that modulates AI-2 production. Altogether these results suggest that dynamic interactions driven by microbial metabolites may occur within the microbiota and impact AI-2 QS signaling.

### MATERIALS AND METHODS

### Sampling and Endophyte Isolation

Fungi and bacteria were previously isolated from the brown algae L. digitata, S. latissima, A. nodosum, and P. canaliculata. L. digitata, and A. nodosum were collected in triplicate in Roscoff, France, in January 2013. Samples of all four species were also collected in triplicate in Oban, Scotland, in July 2013. Algae were surface-sterilized with 70% ethanol and 0.1% sodium hypochlorite, and cut into small pieces. Around 4,600 of these pieces were then aseptically transferred to different solid media, using at least 10 replicates from each algal part on each type of medium (**Supplementary Table S1**). Resulting cultures were then grown and preserved following previously described protocols (Vallet et al., 2018).

### Taxonomic Identification of Endophytic Bacteria

Genomic DNA was extracted with Wizard R Genomic DNA Purification Kit (Promega, Charbonnières-les-Bains, France) from single colonies of 209 bacterial isolates that were grown in marine broth. 16S rRNA genes were then amplified using 2× KAPA2G Ready Mix (Clinisciences, Nanterre, France), 1 µL bacterial DNA, and the universal primers 27F mod (50 -AGRGTTTGATCMTGGCTCAG-30 ) and 1492R mod (50 - TACGGYTACCTTGTTAYGACTT-30 ). Targets were amplified over one cycle of denaturation at 94◦C for 5 min, 35 cycles at 94◦C for 15 s, 50◦C for 15 s, and 72◦C for 20 s, and final extension at 72◦C for 10 min. PCR products were sequenced

by Sanger sequencing on the Bio2Mar platform (Observatoire Océanologique, Banyuls-sur-Mer, France), using primer 907R (Eurofins MWG Operon, Ebersberg, Germany).

The quality of each sequence was checked manually and the closest match in NCBI databases was determined by BLAST (Altschul et al., 1990). Further, sequences were aligned in Muscle, as implemented in MEGA 7.0 (Edgar, 2004; Kumar et al., 2016). Alignments were reviewed manually to verify mismatches, and a phylogenetic tree was constructed by maximum likelihood using the K2, G+I model. The reliability of each node in the tree was assessed by bootstrapping over 500 replicates.

### Screening for the Production of Quorum Sensing Mediators

The QS bioluminescent reporter strain Vibrio campbellii MM32 (**luxN**::Cm, **luxS**::Tn5Kan) was used to detect AI-2 in bacterial and fungal extracts, as previously described (Miller et al., 2004). The receptor luxN is mutated in this strain to abolish sensing of acyl homoserine lactones, while the synthase gene luxS is mutated to abolish AI-2 production but not sensing. It was previously constructed by introducing luxS::Tn5Kan onto the chromosome of strain JAF305 (luxN::Cm) (Bassler et al., 1993; Freeman and Bassler, 1999).

To obtain bacterial supernatants, 1 mL was collected from each of 209 bacterial cultures grown for 24 h at 22◦C in marine broth. Samples were then centrifuged at 17,000 × g for 10 min, and resulting supernatants were filtered at 0.22 µm. To obtain fungal extracts, 43 fungal isolates were grown for 3 weeks at 19◦C in MEA/ASW medium, and extracted three times with ethyl acetate. A detailed recipe of the medium is provided in **Supplementary Table S1**. Extracts were tested at a final concentration of 250 µg/mL, with final concentration of DMSO 2.5%.

Bacterial supernatants and fungal extracts were tested for the production of molecules interfering with AI-2 quorum sensing. Briefly, 20 µL of test samples and corresponding controls were mixed with 180 µL of V. campbellii MM32 diluted 1:5,000 and incubated at 30◦C and 100 rpm. Luminescence and cell density (OD620) were measured after 24 h. Data were collected in triplicate, and luminescence change was calculated as (lumiSN/E – lumiControl)/lumiControl, where lumiSN/E is bioluminescence (normalized to cell density) from the reporter strain in the presence of supernatant or extract, and lumiControl is bioluminescence (normalized to cell density) in the presence of either marine broth (when supernatants are tested) or DMSO (when extracts are tested).

### Quantification of AI-2 Precursor by LC–MS/MS

Due to low ionization potential and instability, AI-2 and DPD are not directly detectable by mass spectrometry (MS). However, quinoxaline derivatives of DPD, obtained by reaction with 4,5-dimethyl-1,2-phenylenediamine, are detectable by LC– MS/MS. DPD was thus quantified in bacterial supernatants after performing a derivatization reaction as described (Xu et al., 2017). Briefly, triplicate DPD standard solutions with concentration 2.6 nM–26 µM were obtained by diluting a stock solution of DPD (16.64 nM) in marine broth. To obtain quinoxaline derivatives, 250 µL of standard solution or supernatant was reacted with 250 µL of 0.1 mg/mL 4,5-dimethyl-1,2-phenylenediamine (Sigma, St. Louis, MO, United States) in 0.1M HCl. Samples were thoroughly mixed for 1 min, and incubated for 5 h at 25◦C with agitation. Samples were then desalted with two volumes of water using Sep-Pak C18 SPE cartridges (Waters, Beverly, MA, United States), and eluted with two volumes of acetonitrile. Subsequently, samples were analyzed by LC–MS/MS on a Dionex Ultimate 3000 HPLC system coupled to a Q ExactiveTM Focus mass spectrometer (Thermo Fisher Scientific, Waltham, MA, United States) and fitted with an electrospray ionization source and a Hypersil GOLD C18 column (2.1 mm × 150 mm, 1.9 µm particle size; Thermo Scientific, Waltham, MA, United States) operating at 20◦C. In this system, eluates are introduced directly into the mass spectrometer. LC– MS parameters are detailed in **Supplementary Table S1**. Data were collected using Xcalibur, in parallel reaction monitoring mode targeting the precursor ion at m/z 233.1285. The product ion at m/z 186.1140 was used for quantification.

### AI-2 Antagonist Activity in Fungal Extracts

To test AI-2 antagonist activity in fungal extracts, 20 µL samples were reacted as described with 180 µL of V. campbellii MM32 diluted 1:5,000 in marine broth and supplemented with 2 µM DPD (purchased from Rita Ventura's research group at ITQB, Oeiras, Portugal). To confirm that loss of luminescence, if any, was not due to cytotoxicity, 100 µL of culture was reacted with 30 µL of 0.01% resazurin (Graça et al., 2013) immediately after measurement of luminescence, and fluorescence (λex: 530 nm, λem: 590 nm) was measured after incubating for 4 h at 30◦C with agitation. As control, a 96-well plate containing 20 µL of fungal extract in marine broth was assayed in the same manner to assess background luminescence, fluorescence, and absorbance.

### Co-culture Experiment: Culture Conditions and Impact on Quorum Sensing

Fungal and bacterial isolates were co-cultured in triplicate in marine broth supplemented with 10% malt extract, 4% glucose, and 1.5% agar, adjusted to pH 7, and plated. Plates were inoculated with 2 mL of a mixture of 2 × 104 fungal spores and bacteria diluted to OD 0.1. Corresponding monocultures were prepared in triplicate in the same manner. Cultures were then incubated for 21 days at 19◦C and on a 12-h light/dark cycle. Petri dishes containing only culture medium (n = 3) were used as blank. Cultures and corresponding controls were extracted with ethyl acetate for 30 min, in a sonicator at room temperature. Samples were then filtered through a filter paper, and dried under vacuum using a centrifugal evaporator. Extracts were tested for their impact on quorum sensing at a final concentration of 250 µg/mL, with final concentration of DMSO 2.5%. Briefly, 20 µL of extract were mixed with 180 µL of V. campbellii MM32 diluted 1:5,000 and incubated at 30◦C and

100 rpm. Luminescence and cell density (OD620) were measured after 24 h. Data were collected in triplicate, and luminescence change was calculated as (lumiE – lumiControl)/lumiControl, where lumiE is bioluminescence (normalized to cell density) from the reporter strain in the presence of extract, and lumiControl is bioluminescence (normalized to cell density) in the presence of DMSO. To assess the viability of the biosensor, 100 µL of culture was reacted with 30 µL of 0.01% resazurin (Graça et al., 2013) immediately after measurement of luminescence, and fluorescence (λex: 530 nm, λem: 590 nm) was measured after incubating for 4 h at 30◦C with agitation.

### Co-culture Experiment: LC–MS-Based Metabolomic Analysis

Dried extracts were solubilized in methanol at 0.5 mg/mL, and analyzed by HPLC–MS in one batch and in a random sequence. Samples were loaded onto a Dionex Ultimate 3000 HPLC system fitted with a C18 AcclaimTM RSLC PolarAdvantage II column (2.1 mm × 100 mm, 2.2 µm pore size; Thermo Scientific, Waltham, MA, United States) operating at 40◦C, and coupled to a Maxis IITM QTOF mass spectrometer (Bruker, Bellerica, MA, United States) with an electrospray ionization source. Data were acquired with Data Analysis software. LC–MS parameters are listed in **Supplementary Table S1**. Raw LC–MS data were calibrated and converted to netCDF format using Data Analysis software (Bruker), and processed using the R package XCMS (Smith et al., 2006). Based on analytical conditions and raw data characteristics, final peak picking parameters were method = 'centWave,' ppm = 10, and peak width = c(5,20), while final grouping parameters were bw = 5, mzwid = 0.015, and retention time correction method = 'obiwarp.' Other parameters were set to default values. To limit noise from compounds already present in culture media, the dataset was filtered with an in-house script to retain only those features with intensity in at least one sample more than fivefold its average intensity in blank samples.

### Statistical Procedures

All analyses and graphs were performed using the R statistical framework (R Core Team, 2019). Van der Waerden tests followed by a post hoc test using the Fischer's Least Significant Difference (LSD) criterion was performed to test the contrasting effect of mono and co-culture on QS activity. Multivariate analyses were done using the R library mixOmics (Rohart et al., 2017).

### RESULTS

### Diversity of Cultivable Endophytic Bacteria From Brown Algae

A total of 209 bacterial isolates was obtained, and classified based according to 16S rRNA genes into 4 phyla, 12 orders, 19 families, 27 genera, and 88 taxonomically unique units (**Figures 1**, **2** and **Supplementary Table S2**). The most abundant phyla in L. digitata and S. latissima were Firmicutes (comprising 47 and 35% of all isolates, respectively) and Proteobacteria (39 and 53%). In P. canaliculata, Proteobacteria, and Actinobacteria were

predominant (44 and 38%), whereas Firmicutes accounted for 77% of bacteria isolated from A. nodosum. Gammaproteobacteria was between 50 and 100% of all Proteobacteria depending on algal species, although Alphaproteobacteria was occasionally present. On the other hand, Bacillus and Pseudoalteromonas were the most abundant genera in S. latissima (33 and 30%) and L. digitata (47 and 22%). Isolates from P. canaliculata were mostly Pseudoalteromonas, Rhodococcus, and Bacillus (19, 16, and 13%), whereas Bacillus was dominant in A. nodosum (63%). Rhodococcus, Bacillus, Cobetia, and Pseudoalteromonas were isolated from all four algal species.

### Production of AI-2 Compounds by Bacterial Endophytes

Most (86%) bacterial endophytes isolated from brown algae elicited an increase in luminescence from V. campbellii MM32, a quorum sensing reporter strain (**Table 1** and **Supplementary Data S1**). Strikingly, 10% of isolates boosted luminescence by over 50%, including a Kocuria isolate, six Bacillus isolates, and 13 Proteobacteria. Indeed, a Marinomonas isolate and five Cobetia isolates increased luminescence by at least 100%. In contrast, all but one Pseudoalteromonas isolate increased luminescence by less than 50%.

To confirm these results, DPD production by Marinomonas 424 and Cobetia 352b, two of the strongest inducers of luminescence, was quantified by LC–MS/MS. For comparison, DPD production was also quantified in Pseudoalteromonas 352a, which was co-isolated with Cobetia 352b and is a weak inducer of luminescence. Interestingly, culture supernatants from Marinomonas 424 and Cobetia 352b contained similar levels of DPD (692 and 585 nM, respectively), whereas a lower amount was found in the supernatant from Pseudoalteromonas 352a (66 nM). Thus, our results based on LC–MS/MS confirmed the quorum sensing patterns observed using the biosensor-based approach (**Figure 3**).

### Impact of Metabolites of Endophytic Fungi on Quorum Sensing

As presented in **Figure 4**, extracts from 13 fungi boosted the luminescence from the biosensor. Of these, eight (Verticillium biguttatum AN130T, Chaetomium globosum LD13H, Microsphaeropsis olivacea LD50H, Botryotinia fuckeliana LD535H, Leptosphaeria marina SL457T, and Diaporthe eres SL473T) increased the luminescence by over 50%. Conversely, extracts from 30 fungi strongly diminished the luminescence, as shown in **Figure 5**. For 14 of these extracts, the loss of luminescence was due to toxicity against the biosensor V. campbellii MM32. In contrast, the other 16 extracts evidently inhibited AI-2, blocking the effects of 2 µM DPD but with very limited impact on the biosensor V. campbellii MM32 metabolism (**Figure 5**).

### Impact of Bacterial–Fungal Interactions on Quorum Sensing

Metabolites produced in co-cultures of Cladosporium SL405T with Pseudoalteromonas 352a or Cobetia 352b reduced luminescence from V. campbellii MM32 by 44 and 20%, respectively. In contrast, metabolites from monocultures of Cladosporium SL405T decreased luminescence only slightly (12%), whereas metabolites from monocultures of either bacterium elicited a stronger decrease in luminescence (49%) (**Supplementary Data S3**). These results highlight the contrasting effects of co-cultures and monocultures on quorum sensing supported by a non-parametric test for independent

Numbers are bacterial isolates per genus.

samples (Van Der Waerden test), followed by a post hoc test using the Fischer's Least Significant Difference (LSD) criterion (**Figure 6**). Furthermore, the partial least squares discriminant analysis of samples covering the different co-culture conditions characterized through 4,221 metabolomic features collected by LC–MS showed that each monoculture or co-culture is characterized by a specific set of features corresponding to a unique set of metabolites (**Supplementary Data S2**). Sparse partial least squares discriminant analysis also identified four latent variables of 180 features (720 features in total) that discriminate a culture from all others (**Supplementary Data S2**). In a second round of partial least squares discriminant analysis based only on these 720 features (**Figure 7**), the co-cultures were differentiated in the third dimension both from each other and from every monoculture. Analysis of variance of scores get on the 3rd dimension confirmed that selected features significantly separate co-cultures from each other and from monocultures (F2,12 = 167.2, p < 1.7 × 10−9 ). This result implies that bacterial–fungal interactions impact very significantly metabolite production in specific ways.

Features that distinguish a culture and that are altered more than 10-fold over other cultures are listed in **Supplementary Table S3**. When compared to the corresponding monocultures, 28 and 5 of such features were identified in co-cultures of Cladosporium SL405T with Cobetia 352b and Pseudoalteromonas 352a, respectively. Conversely, 120 and 87 of such features were identified in Cobetia 352b and Pseudoalteromonas 352a monocultures when compared to the corresponding co-cultures with Cladosporium SL405T. Moreover, 93 features diminished by at least a factor of 10 in cocultures when compared to Cladosporium SL405T monocultures. Unfortunately, top-ranked metabolites were not identified by annotation against ISDB (Allard et al., 2016), GNPS, and MassBank. Similarly, identification against SIRIUS 4.0. (Böcker and Rasche, 2008) and Pubchem was inconclusive.

### Search of a Multivariate Link Between Luminescence Measurements and MS Metabolomic Variables

A link between the global response given by the luminescence representing an integrated measurement of the QS and the metabolome in the different mono or co-culture conditions was obtained thanks a PLS-based regression (**Figure 8**).

Complementary filters such as (i) VIP above 1.20 with a VIP standard error coming from repeated cross-validation calculus lower than the VIP value for the variable, and (ii) absolute value of the correlation between primary metabolomic variables and the predicted luminescence response above 0.75, were used to select from the initial set of 4221 variables a subset of 521 variables. The comprehensive heatmap obtained (**Figure 9**) showcased nine and one variables displaying a significantly higher mean

value for co-culture between Cla and Co and Cla and Ps, respectively (**Figure 10**). All these 10 significant variables are supposed to be induced in these co-culture conditions when compared to mono-culture conditions as revealed by the multiple comparison of means based on the Student-Newman-Keuls test. Indeed, these variables are of prime importance candidates that would be putatively involved in some metabolic pathways explaining the QS event.

### DISCUSSION

The data highlight the large diversity of cultivable bacterial endophytes associated with healthy L. digitata, S. latissima, A. nodosum, and P. canaliculata (**Figures 1**, **2**). The four phyla (Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes) and 27 genera that were identified are consistent with previous surveys of cultivable bacteria associated with macroalgae (Wiese et al., 2009; Hollants et al., 2013; KleinJan et al., 2017). Notably, the cultivable fraction of bacterial communities appears to vary depending on algal species, sampling site, and algal tissue. Nevertheless, bacteria classified as Cobetia and Pseudoalteromonas were isolated from every algal species, tissue, and sampling site. Moreover, these genera are the most frequently isolated from S. latissima, apart from Bacillus. Of note, Vibrio and Flavobacterium were not isolated from our samples, even though these are frequently isolated from brown algae (Hollants et al., 2013; Albakosh et al., 2016).

Among the isolated bacterial endophytes, 86% were found to produce AI-2, which triggers quorum sensing in the reporter strain V. campbellii MM32 (**Table 1**). Cobetia, Marinomonas, and Erwinia were the strongest inducers (>100% induction) of quorum sensing, whereas 93 and 73% of isolated Bacillus and Pseudoalteromonas induced quorum sensing only weakly (<50% induction). These results were confirmed by quantifying DPD, an AI-2 precursor, in bacterial supernatants using tandem mass spectrometry. As shown in **Figure 3**, Cobetia 352b and Marinomonas 424 produced around 700 nM of DPD, suggesting that these strains engage neighboring bacteria with AI-2 receptors. Pseudoalteromonas 352a also produced DPD but to a lesser extent (66 nM). Interestingly, fungal endophytes isolated along with these bacteria positively or negatively modulated AI-2 quorum sensing (**Figures 4**, **5**). These results provide more evidence that AI-2 quorum sensing is involved in interkingdom signaling.

While inhibitory activity against quorum sensing was previously detected in marine fungi (Martín-Rodríguez et al., 2014), this is the first demonstration, to the best of our

FIGURE 7 | Visualization of samples using the first four latent variables from partial least squares discriminant analysis of 720 selected features. Ps, Pseudoalteromonas monocultures (violet); Co, Cobetia monocultures (green); Cla, Cladosporium monocultures (blue); Cla-Ps, Cladosporium-Pseudoalteromonas co-cultures (gray); Cla-Co, Cladosporium-Cobetia co-cultures (orange). Ellipses represent 95% confidence intervals.

knowledge, that fungal metabolites may also enhance quorum sensing. However, such result is not surprising, as this effect was previously observed in metabolites from some other types of eukaryotes such as Chlamydomonas reinhardtii and Chlorella spp. microalgae (Rolland et al., 2016). Collectively, these findings suggest a key role for AI-2 signaling among endophytes of brown algae. On the other hand, we note that 14 fungal endophytes are strongly antimicrobial against the Vibrio biosensor (**Figure 5**),

and thus may be similarly active against V. harveyi, a prominent pathogen in aquaculture (Zhang and Li, 2016).

As the fungus Cladosporium SL405T and the bacteria Pseudoalteromonas 352a and Cobetia 352b were isolated from the same holobiont (S. latissima), they were characterized in monoculture and in co-culture, with a view to assess the impact of fungal–bacterial interactions on metabolite production and quorum sensing. The data indicate that these isolates produce quorum sensing or quorum sensing-modulating compounds. Of note, these genera are frequently isolated from macroalgae (Hollants et al., 2013; Hulikere et al., 2016; Li et al., 2017). Pseudoalteromonas is of particular interest, as it was shown to produce antimicrobials or bioactive molecules against algal spores, invertebrate larvae, fungi, and other bacteria. Such molecules may help the host against surface colonization by these organisms (Holmström et al., 2002; Richards et al., 2017). Also, Pseudoalteromonas was implicated in Hole-Rotten disease (Wang et al., 2007).

As shown in **Figures 6**, **7**, co-cultures of Cladosporium SL405T with two different bacteria produce different metabolites. These metabolites are also different from those produced by corresponding monocultures. For example, 28 and 5 metabolic features were at least 10-fold more abundant in co-cultures of Cladosporium SL405T with Cobetia 352b and Pseudoalteromonas 352a than in corresponding monocultures. This result implies that microbial interactions induce production of specific metabolites (**Supplementary Table S3**). Conversely, 120 and 87 features were at least 10-fold more abundant in Cobetia 352b monocultures and Pseudoalteromonas 352a monocultures than in co-cultures, suggesting either that production of these metabolites is inhibited by microbial interaction, or that these metabolites are degraded in co-cultures. Similarly, 105 and 108 features (of which 93 are common) were at least 10-fold more abundant in Cladosporium SL405T monocultures than in cocultures with Cobetia 352b and Pseudoalteromonas 352a.

Taken together, these results demonstrate that metabolomes in co-cultures fundamentally differ from metabolomes in monocultures due to microbial interactions. Unfortunately, chemical characterization of culture-specific metabolites was not possible since none matched known natural products. Identification of the source of metabolites in co-cultures also remains a major challenge, since the structure of such metabolites and other related biochemical information would be required (Xu et al., 2018). Nevertheless, we found that different cultures have variable impact on quorum sensing (**Figure 6**), such that metabolites obtained from co-cultures of the same fungus with two different bacteria clearly display contrasting effects on quorum sensing (**Figure 6**). For instance, metabolites from

a co-culture of Cladosporium SL405T and Pseudoalteromonas 352a diminish luminescence from the biosensor by 40%, while metabolites from a co-culture of Cladosporium SL405T and Cobetia 352b led to a loss of only 20%. The link between the impact on quorum sensing and the metabolites present in different culture conditions was strengthened by the PLSregression based analysis highlighting 10 variables, highly correlated with the predicted luminescence response (absolute value of the correlation above 0.75), and specially induced in the co-culture conditions when compared to mono-culture conditions (**Figure 10**).