High prevalence of quorum-sensing and quorum-quenching activity among cultivable bacteria and metagenomic sequences in the Mediterranean sea

genes G C A T T A C G G C A T Article High Prevalence of Quorum-Sensing and Quorum-Quenching Activity among Cultivable Bacteria and Metagenomic Sequences in the Mediterranean Sea Andrea Muras 1ID , Mario López-Pérez 2, Celia Mayer 1, Ana Parga 1, Jaime Amaro-Blanco 1and Ana Otero 1,*ID 1Departamento de Microbioloxía e Parasitoloxía, Facultade de Bioloxía-CIBUS, Universidade de Santiago de Compostela, Santiago de Compostela 15782, Spain; [email protected] (A.M.); [email protected] (C.M.); anapar[email protected] (A.P.); [email protected] (J.A.-B.) 2Evolutionary Genomics Group, División de Microbiología, Universidad Miguel Hernández, San Juan de Alicante 03202, Spain; [email protected] *Correspondence: [email protected]; Tel.: +34-881-816-913 Received: 12 December 2017; Accepted: 12 February 2018; Published: 16 February 2018 Abstract: There is increasing evidence being accumulated regarding the importance of N-acyl homoserine lactones (AHL)-mediated quorum-sensing (QS) and quorum-quenching (QQ) processes in the marine environment, but in most cases, data has been obtained from specific microhabitats, and subsequently little is known regarding these activities in free-living marine bacteria. The QS and QQ activities among 605 bacterial isolates obtained at 90 and 2000 m depths in the Mediterranean Sea were analyzed. Additionally, putative QS and QQ sequences were searched in metagenomic data obtained at different depths (15–2000 m) at the same sampling site. The number of AHL producers was higher in the 90 m sample (37.66%) than in the 2000 m sample (4.01%). However, the presence of QQ enzymatic activity was 1.63-fold higher in the 2000 m sample. The analysis of putative QQ enzymes in the metagenomes supports the relevance of QQ processes in the deepest samples, found in cultivable bacteria. Despite the unavoidable biases in the cultivation methods and biosensor assays and the possible promiscuous activity of the QQ enzymes retrieved in the metagenomic analysis, the results indicate that AHL-related QS and QQ processes could be common activity in the marine environment. Keywords: quorum sensing; quorum quenching; AHL; lactonase; acylase; marine bacteria 1. Introduction Quorum sensing (QS) is a bacterial communication system based on the production and secretion of small signal molecules called autoinducers that accumulate in the extracellular environment when high cell densities are reached [ 1 ]. Once a threshold intracellular concentration is achieved, the signaling molecule triggers the synchronous expression of multiple genes in the population, initiating a coordinated action. Although different types of signal molecules have been described [ 2 ], the best characterized QS signals are the N-acyl homoserine lactones (AHLs). These QS signal molecules are constituted by a homoserine lactone ring (HSL) linked by an amide bond to a fatty acid (between 4 and 18 carbons). AHLs are QS signals that are considered typical of Gram-negative bacteria [ 3 ], although they are also produced by different clades of bacteria [ 4 , 5 ], including the Gram-positive Exiguobacterium sp. [ 6 ]. The most common AHL-based QS system comprises a LuxI-type signal synthase and a LuxR-type receptor [ 7 ]. Other AHL synthases belonging to the families Genes 2018,9, 100; doi:10.3390/genes9020100 www.mdpi.com/journal/genes Genes 2018,9, 100 2 of 20 LuxM/AinS and HdtS have been described, not sharing homology with the LuxI synthase family [ 8 , 9 ]. Some bacteria do not produce AHLs or have a recognizable LuxI autoinducer synthase but possess LuxR homologs, called LuxR orphans, that can interact with the autoinducers synthetized by other bacteria [ 10 ]. Recently, LuxR homologues have been described to act as sensors for QS signals different from AHLs, making the picture more complex [ 11 ]. Despite being more infrequently reported, LuxI orphans are also present in some bacteria [12]. In spite of the low bacterial population in the open sea and the low chemical stability of AHLs at the high pH of seawater, new evidence reinforces the idea of the importance of AHL-mediated QS mechanisms in marine environments [ 3 , 5 , 13 , 14 ]. More recently, numerous studies have reported the isolation of AHL-producing bacterial strains from marine samples [ 15 – 20 ]. The presence of bacteria with the ability to produce AHLs in these marine microhabitats was reported in subtidal biofilms [ 21 ], sponges [ 16 , 22 ], cnidarians [ 23 , 24 ], and marine snow [ 15 , 19 , 25 ]. It is now generally accepted that the AHL-mediated QS systems play an important role in relevant marine ecology processes including the settlement of invertebrate larvae [ 26 , 27 ] and of macroalgae zoospores [ 28 ]. The AHLs produced by bacteria associated with the cyanobacteria Trichodesmium are proposed to mediate and coordinate the processing and acquisition of phosphorus [ 29 ], a limiting nutrient in oligotrophic open ocean environments. Furthermore, symbiotic and pathogenic interactions with a eukaryotic host also act as examples of these ecologically relevant niches [ 28 , 30 ]. In addition, the expression of important virulence genes in marine fish pathogenic bacteria is commonly controlled through AHL-mediated processes [31]. The presence of AHLs in open marine environments has been also reported using direct, non-cultivation-dependent measurements [ 25 , 32 ]. A large phylogenetic diversity of the AHLs synthases was observed in the Global Ocean Sampling (GOS) metagenomic database [ 33 ], suggesting that AHL production is a widespread mechanism in marine environments. The AHLs are proposed to participate in the marine carbon cycle by increasing the activity of certain key hydrolytic enzymes for the degradation of particulate organic carbon in seawater, playing an important role in the remineralisation depth distribution of sinking particulate organic carbon (POC) [ 25 , 34 ]. QS-mediated processes have been suggested to be even more ecologically relevant in specific marine microhabitats in which the bacterial population is more concentrated, forming cell clusters [13,14]. Since QS systems have important effects in the interactions between prokaryotes and also with eukaryotes, it makes sense that competitors have evolved mechanisms for silencing other bacterial QS systems. The ability to disrupt bacterial communication is a widespread strategy used by different kinds of organisms: marine algae [ 35 ], terrestrial plants [ 36 ], mammalian cells [ 37 ], and bacteria [4,38,39] . The term quorum quenching (QQ) was coined to describe the enzymatic inactivation of AHL QS signals [ 40 ], although at present this term is often used in a general sense to describe any type of QS disruption [ 41 ]. Enzymatic QQ is the best studied QS inhibitory strategy [ 40 ]. The genes that codify this type of enzymes are classified in two main groups: lactonases and acylases, although other types of QQ enzymes have also been described [ 39 ]. The pioneer studies on the ecological relevance of QQ processes carried out with bacteria isolated from soil and rhizosphere indicated that 2–4.8% of these strains had the ability to interfere with AHLs [ 42 – 44 ]. More recent studies revealed a high prevalence of QQ enzymes in the marine environment: enzymatic QQ activity was observed in bacterial strains isolated from corals [ 23 , 45 ], sponges [ 46 ], marine biofilms [ 47 ], estuarine and open ocean superficial seawater [ 48 , 49 ], and fish and bivalve hatcheries [ 50 , 51 ], presenting higher frequencies of bacteria with this capability (2–46%) in comparison to terrestrial samples [ 46 , 48 , 52 – 54 ]. The importance of QQ processes in the marine environment was further supported by metagenomic studies showing a high frequency of QQ enzymes in marine metagenomic collections including the Global Ocean Sampling collection [ 48 ]. Despite the relevance of QS and QQ in niche marine environments seems clear and all the available data points to a high prevalence of QS and QQ activities in the seawater, there is no study in which a metagenomic analysis is combined with the analysis of the QS and QQ activities among cultivable isolates for the same sample. This double approach would allow Genes 2018,9, 100 3 of 20 us to avoid the handicaps of both methods and to assess the relevance of these processes in free-living bacteria. Therefore, the aim of this work was to study the AHL production and degradation activity in free-living bacteria from the Mediterranean Sea using two different but complementary approaches, such as functional screening in bacteria able to grow in standard culture conditions and metagenomic analysis in order to improve our understanding of the ecologic relevance of AHL-mediated processes in the marine environment. The metagenomic analysis was carried out from seawater samples collected from six depths in the photic zone at 15 m intervals (15, 30, 45, 60, 75, and 90 m) and from two depths in the aphotic zone (1000 and 2000 m) at the same time, while cultivable bacteria were obtained from the 90 and 2000 m samples in order to assess the spatial distribution of the QS and QQ processes. 2. Materials and Methods 2.1. Sample Collection, Bacterial Quantification, and Strain Isolation Eight seawater samples from different depths were collected for metagenomic analyses as described previously [ 55 , 56 ] on October 15, 2015 at a single point in the Mediterranean Sea (37.35361 ◦ N, 0.286194 ◦ W) by the research vessel ‘García del Cid’. Samples from 90 and 2000 m depth were also used for bacterial isolation and functional screening. The 90 m sample is considered the limit of the photic zone, with a chlorophyll-a (Chl-a) value of 0.13 mg/m 3 , a total organic carbon (TOC) of 1.35 mgC/L, total N of 6.9 µ M, total P of 0.25 µ M, and 1.37 × 10 5 heterotrophic bacteria counts. The 2000 m sample was characterized by an almost undetectable Chl-a concentration (0.01 mg/m3), lower TOC (0.94 mg C/L), higher total N and p-values (8.62 and 0.5 µ M, respectively), and lower heterotrophic bacteria counts (4.5 × 10 4 ) [ 55 , 56 ]. Both rich and oligotrophic culture media were used for bacterial isolation as previously described [ 47 ]. The rich media included tryptone soy agar 1% NaCl (TSA-1) and marine agar (MA) suitable for eutrophic bacteria, and the low organic formulations included MA diluted 1/100 with seawater (salinity 35 g/L) and filtered autoclaved seawater medium (FAS) supplemented with 0.5 g/L of each of the following polymers: agarose, chitin, and starch (FAS-POL). Five series of 10-fold dilutions were prepared in sterilized natural seawater for each sample and plated in the above-mentioned culture media. The plates were incubated at 22 ◦ C for 15 days. For the estimation of colony forming units (CFUs), plates with 30–300 colonies were selected. A total of 605 strains were randomly picked up and isolated to be used for QS and QQ functional screening (Table S1). All the marine isolates obtained were able to grow on MA at 22 ◦ C, hence these culture conditions were selected as standard for laboratory maintenance and assays. 2.2. 16S-Based Bacterial Identification The identification of the collection of 605 cultivable marine bacteria was carried out using 200 µ L of cultures obtained in marine broth and pooled in groups of 65–80 strains. These pools were centrifuged, and the DNA was extracted with DNeasy PowerSoil Kit (Qiagen ® , Hilden, Germany). The amplification of 16S rRNA genes was performed using a diversity assay illumine inhouse bTEFAP ® (Lubbock, TX, USA). PCR were carried out under the following standard conditions: initial step of 94 ◦ C for 3 min followed by 28 cycles at 94 ◦ C for 30 s, 53 ◦ C for 40 s, and 72 ◦ C for 1 min. Sequencing (Miseq, Illumina, San Diego, CA, USA) and data processing were performed using BLASTn against a curated database from RDPII and NCBI (MR DNA, Shallowater, TX, USA). In order to analyze the bacterial diversity of the cultivable bacteria, the 16S rDNA sequences were clustered to operational taxonomic units (OTUs) defined at 95% identity using CD-HIT [ 57 ]. The sequences were assigned a taxonomic identity using the RDP database [58]. For the isolated strains showing wide-spectrum QQ activity, genomic DNA was extracted using a Wizard DNA purification Kit (Promega, Madison, WI, USA), and the bacterial 16S rRNA gene was amplified using the universal primers 96 bfm (5 0 -GAGTTTGATYHTGGCTCAG-3 0 ) and 1152 uR (5 0 -ACGGHTACCTTGTTACGACTT-3 0 ) [ 59 ]. PCR were carried out under the following standard Genes 2018,9, 100 4 of 20 conditions: initial step of 96 ◦ C for 2 min followed by 35 cycles at 95 ◦ C for 1 min, 53 ◦ C for 30 s, and 72 ◦C for 2 min. The 16S rRNA sequences were identified using the web-based tool EzTaxon [60]. 2.3. Quorum-Sensing Activity Assay The marine bacterial collection (605 strains) was screened for the strains ' capability to activate the AHL biosensor Agrobacterium tumefaciens NTL4 [ 61 , 62 ]. The strains were cultured in microtiter plates in 200 µ L of Marine Broth (MB) for 48 h. The plates were centrifuged, and the supernatants were transferred to a new plate. The pH of the supernatants was checked to be less than pH 8 in order to avoid lactonolysis of the AHLs produced at high pH values [ 63 ]. The presence of AHLs after the incubation period was detected by adding 50 µ L of a mixture of soft Agrobacterium (AB) medium [ 61 ] (0.2% agar) with 5-bromo-4-chloro-3-indolylβ -D-galactopyroside (X-GAL, 80 µ g/mL) and an overnight culture of A. tumefaciens NTL4 (1:5) on top of the supernatants in microtiter wells. The plates were incubated for 6–8 h at 30 ◦ C, and the production of blue colour on the surface of the wells was checked. AB medium pH 6.5 plus the C6-HSL (10 µ M) was used as control. A. tumefaciens NTL4 was cultured at 22 ◦C in LB or AB medium supplemented with 30 µg gentamycin/mL. The capacity of the strains presenting wide-spectrum QQ activity to activate the sensor A. tumefaciens NTL4 was confirmed with a disk-diffusion agar plate assay [modified from 50] at different times. One mL of an overnight shaken culture of the biosensor was mixed with 4 mL of soft AB medium (0.8%) with X-GAL (80 µ g/mL) to cover the AB agar plates. Once the plates had solidified, 10 µ L of supernatant from the 24 h and 48 h cultures of the 12 wide-spectrum QQ strains was loaded in antibiogram disks and deposited on the plates. The plates were incubated at 22 ◦ C for 24 h. PBS pH 6.5 plus C6-HSL was used as a control, and the presence of a blue induction halo around the disks was checked. The stock of C6-HSL was prepared in acetonitrile at a concentration 1 mg/mL. This stock solution was diluted in PBS to a final concentration of 10 µM and added to the disks. 2.4. Quorum-Quenching Activity Assay The QQ activity of the strains was tested using a solid microtiter plate assays carried out with the AHL biosensors Chromobacterium violaceum VIR07 [ 64 ] for C12-HSL and C. violaceum CV026 [ 65 ] for C6-HSL. Two hundred microliters of the 48 h cultures carried out in microtiter plates in MB were centrifuged, and the pellets were washed with phosphate buffered saline (PBS) pH 6.5 and resuspended in another 200 µ L of the same buffer. These cell suspensions were used for live-cell AHL degradation assay by adding either C6-HSL or C12-HSL (10 µ M in PBS, prepared from a concentrated stock—1 mg/mL in acetonitrile) and incubating for 24 h at 22 ◦ C. The presence of AHLs after the incubation period was detected by adding 50 µ L of a mixture of soft Luria–Bertani (LB) (0.2% agar) and an overnight culture of the corresponding C. violaceum biosensor on top of the cell suspension in microtiter wells. The plates were incubated for 24 h at 30 ◦ C, and the production of violacein was observed. PBS pH 6.5 plus the corresponding AHL (10 µ M) was used as a control [ 66 ]. The same assay was used to check the capacity to degrade the oxo-substituted AHLs OC6-HSL and OC12-HSL. In order to detect false positives derived from the inhibition of the growth of the C. violaceum biosensors, all positive strains were re-isolated, and their activity confirmed with a Petri dish solid bioassay as described previously [ 47 ]. The Petri dish bioassays allow distinguishing growth inhibition (presence of a transparent halo around the well) from QS inhibition. In the C. violaceum assay, because of the high concentration of added exogenous AHL (10 µ M), the absence or reduction of the violacein halo was considered indicative of enzymatic degradation. In this assay, the presence of an inhibitory substance is generally visualized as a clear, not transparent, halo around the well, surrounded by an external halo of violacein. Nevertheless, the presence of a very high amount of a QS inhibitor counteracting the action of the exogenous AHL could not be fully excluded. The biosensor strains were maintained in LB plates supplemented with kanamycin (30 µg/mL). Genes 2018,9, 100 5 of 20 2.5. Characterization of AHL-Degradation Activity Crude cell extracts (CCE) were obtained as previously reported [ 67 ]. Briefly, the cell biomass was obtained by centrifugation, resuspended in PBS, sonicated on ice, and centrifuged again. The cell extract obtained was filtered through a 0.20 µ m filter and stored at 4 ◦ C. To determine the minimal active concentration (MAC) of the CCEs, C6-HSL (10 µ M) was exposed to different dilutions of CCEs, in PBS pH 6.5. The mixture was incubated for 24 h at 22 ◦ C, and the presence of a signal was detected using the C. violaceum CV026 Petri dish bioassay. The control wells were filled with sterile PBS pH 6.5 plus AHL (10 µM). 2.6. Metagenomic Samples Eight samples (Med-OCT2015-15 m, Med-OCT2015-30 m, Med-OCT2015-45 m, Med-OCT2015-60 m, Med-OCT2015-75 m, Med-OCT2015-90 m, Med-OCT2015-1000 m, and Med-OCT2015-2000 m) [55,56] from different depths were taken for metagenomic analyses on October 15, 2015 at a single sampling site in the Western Mediterranean (37.35361 ◦ N, 0.286194 ◦ W). Six samples were obtained from the uppermost 100 m at 15 m intervals using a hose attached to a CTD (Seabird). Another two samples from the depths of 1000 m and 2000 m, were taken the next day (October 16) in two casts (100 L each) using the CTD rosette. All seawater samples were sequentially filtered on board through 20, 5, and 0.22 µ m pore size polycarbonate filters (Millipore, Billerica, MA, USA). All filters were immediately frozen on dry ice and stored at − 80 ◦ C until processing. DNA extraction was performed from the 0.22 and 5 µ m filters, as previously described [ 68 ]. The metagenomes were sequenced using Illumina Hiseq-4000 (150 bp, paired-end read) (Macrogen, Seoul, Korea). 2.7. Metagenomic Analysis The metagenomic analysis (read pre-processing, assembly and gene prediction and annotation) was carried out as previously described [ 56 ]. In brief, each metagenome was assembled independently using IDBA-UD [ 69 ]. The genes obtained on the assembled contigs were predicted using Prodigal [ 70 ] transfer RNA (tRNA), and the rRNA genes were predicted using tRNAscan-LE [ 71 ], ssu-align [ 72 ], and meta-rna [ 73 ]. A taxonomic and functional annotation was performed comparing the predicted protein sequences against NCBI NR, COG [ 74 ], and TIGFRAM [ 75 ] databases were performed using USEARCH6 [ 76 ]. USEARCH6 with an e-value <1e-5 was also used to identify potential 16S sequences from a subset of 10 million reads for each metagenome against RDP database [ 77 ]. These candidates were then aligned to archaeal, bacterial, and eukaryal 16S/18S rRNA HMM models [ 78 ], using ssu-align to identify true sequences [ 72 ], using a threshold of sequence identity ≥ 80% and alignment length ≥ 90 bp. In order to analyze the 16S rDNA diversity, identical sequences (99.9% of identity) from both datasets were removed using CD-HIT software [57]. The rest of the sequences were clustered to operational taxonomic units (OTUs) defined at 95% identity. Taxonomic affiliations of these clusters were assigned using the assigned Ribosomal Database Project (RDP) database [58]. Only AHL lactonase and AHL acylase genes with demonstrated activity were used within the QQ enzymes (Supplementary Material). The analysis of other QS-related genes, such as those for AHL synthases (LuxI,AinS, and HdtS) and AHL receptors (LuxR and AinR) as well as the gene for the synthase responsible for producing the AI-2 signal (LuxS), was carried out by aligning the metagenomic reads against the NR database using DIAMOND [ 79 ] (blastx option, top hit, ≥ 50% identity, ≥ 50% alignment length, e-value < 10 −5 ). The abundance of these genes was normalized by the number of reads matching recA + radA sequences for each metagenome. The reads that gave hit to viral or eukaryal proteins were not taken into account. In order to analyse the relative abundance of the QQ enzymes in the water column, we applied the same sequence search for genes involved in the normal metabolism derived from marine bacteria, such as nitrogen (amoC,amt), phosphate, (pstA), sulfur (dsrA, soxB), and general oxidative metabolism (dmdA) [48,80]. Genes 2018,9, 100 6 of 20 2.8. Data Availability The metagenomic datasets used in this study were submitted to NCBI SRA and are available under BioProjects accession number PRJNA352798 (Med-OCT2015-15 m, Med-OCT2015-30 m, Med-OCT2015-45 m, Med-OCT2015-60 m, Med-OCT2015-75 m, Med-OCT2015-90 m, Med-OCT2015-1000 m and MedOCT2015-2000 m). 2.9. Statistical Analysis The effects of depth and culture media on the number of CFUs/mL was analysed with the non-parametric Mann–Whitney test at significance level p< 0.05, with IBM SPSS statisticsV20 program. 3. Results 3.1. Bacterial Growth and Isolation The number of CFUs/mL was significantly higher in the 2000 m (0.8–5.8 × 10 3 CFUs/mL) than in the 90 m water sample (0.2–0.6 × 10 3 CFU/mL) for the different culture media tested (Mann–Whitney Test, p< 0.05), despite the isolation conditions excluded the retrieval of barophilic or psychrophilic strains from the deep-sea sample. The culture media did not affect the number of CFUs/mL obtained in the 90 m, photic sample (Figure 1, Mann–Whitney Test, p> 0.05). On the contrary, the CFUs obtained in MA and FAS-POL culture media were significantly higher in the sample from 2000 m, yielding three times more CFUs than the other media (Figure 1, Mann Whitney Test, p< 0.05). Genes2018,9,100 6of20 Med‐OCT2015‐45m,Med‐OCT2015‐60m,Med‐OCT2015‐75m,Med‐OCT2015‐90m,Med‐OCT2015‐ 1000mandMedOCT2015‐2000m). 2.9.StatisticalAnalysis TheeffectsofdepthandculturemediaonthenumberofCFUs/mLwasanalysedwiththe non‐parametricMann–Whitneytestatsignificancelevelp<0.05,withIBMSPSSstatisticsV20program. 3.Results 3.1.BacterialGrowthandIsolation ThenumberofCFUs/mLwassignificantlyhigherinthe2000m(0.8–5.8×103CFUs/mL)thanin the90mwatersample(0.2–0.6×103CFU/mL)forthedifferentculturemediatested(Mann–Whitney Test,p<0.05),despitetheisolationconditionsexcludedtheretrievalofbarophilicorpsychrophilic strainsfromthedeep‐seasample.TheculturemediadidnotaffectthenumberofCFUs/mLobtained inthe90m,photicsample(Figure1,Mann–WhitneyTest,p>0.05).Onthecontrary,theCFUs obtainedinMAandFAS‐POLculturemediaweresignificantlyhigherinthesamplefrom2000m, yieldingthreetimesmoreCFUsthantheothermedia(Figure1,MannWhitneyTest,p<0.05).  Figure1.Cultivablebacteriaconcentration(colonyformingunits(CFU)/mL,average±s.d.,n=5) obtainedinthephotic(90m,whitebars)andaphotic(2000m,blackbars)samplesfortheculture mediaTSA‐1%NaCl(TSA‐1),MarineAgar(MA),Marineagardiluted1:100inseawater(MA1/100), andFilteredautoclavedsea‐waterenrichedwithpolymers(FAS‐POL). 3.2.TaxonomicDiversityoftheCultivableStrains Atotalof605isolates,231fromthe90mand374fromthe2000msample,werecollectedand screenedfortheircapacitytoactivateaQSbiosensorandfortheirQQactivityagainstAHLs (SupplementaryTableS1).ThemostcultivablestrainsbelongedtoGammaproteobacteria(34.88%), Firmicutes(30.95%),andAlphaproteobacteria(17.44%).MembersoftheActinobacteria(6.84%)and Bacteroidetes(7.14%)werelessrepresented(Figure2A).Firmicuteswerehighlyrepresentedinthe cultivablecollection(30%inbothsamples),incomparisonwiththedataobtainedfromthe metagenomicanalysisatthesamedepth(<1%)[56].Gammaproteobacteria(35%)werealso overrepresentedinthe90msampleincomparisonwiththemetagenomicdata(13.56%).Therelative abundanceatthefamilylevelshowedsimilarprofilesatbothdepths,exceptforVibrionaceaeand Rhodobacteraceaewhichwereonlyidentifiedat2000m(Figure2A).However,whentheOTUswere clusteredat95%ofidentityfrombothdatasetstoseparatethematgenuslevel,56and82generacould beidentifiedat90and2000m,respectively,showingthattherewasagreatergeneticdiversityat2000 mthatcouldnotbeappreciatedathighertaxomoniclevels.Inthefuture,thegenomesequencingof theseorganismscouldclarifyandshedlightonmanyofthedifferencesbetweenthesetwodepths. Despiteofthis,thetwocollectionsofcultivablebacteriashared11ofthe13mostabundantgenera Figure 1. Cultivable bacteria concentration (colony forming units (CFU)/mL, average ± s.d., n= 5) obtained in the photic (90 m, white bars) and aphotic (2000 m, black bars) samples for the culture media TSA-1%NaCl (TSA-1), Marine Agar (MA), Marine agar diluted 1:100 in seawater (MA 1/100), and Filtered autoclaved sea-water enriched with polymers (FAS-POL). 3.2. Taxonomic Diversity of the Cultivable Strains A total of 605 isolates, 231 from the 90 m and 374 from the 2000 m sample, were collected and screened for their capacity to activate a QS biosensor and for their QQ activity against AHLs (Supplementary Table S1). The most cultivable strains belonged to Gammaproteobacteria (34.88%), Firmicutes (30.95%), and Alphaproteobacteria (17.44%). Members of the Actinobacteria (6.84%) and Bacteroidetes (7.14%) were less represented (Figure 2A). Firmicutes were highly represented in the cultivable collection (30% in both samples), in comparison with the data obtained from the metagenomic analysis at the same depth (<1%) [ 56 ]. Gammaproteobacteria (35%) were also overrepresented in the 90 m sample in comparison with the metagenomic data (13.56%). The relative abundance at the family level showed similar profiles at both depths, except for Vibrionaceae and Rhodobacteraceae which were only identified at 2000 m (Figure 2A). However, when the OTUs were clustered at 95% of identity from both datasets to separate them at genus level, 56 and 82 genera could be identified at 90 and 2000 m, respectively, showing that there was a greater genetic diversity at 2000 m Genes 2018,9, 100 7 of 20 that could not be appreciated at higher taxomonic levels. In the future, the genome sequencing of these organisms could clarify and shed light on many of the differences between these two depths. Despite of this, the two collections of cultivable bacteria shared 11 of the 13 most abundant genera (Figure 2B). Surprisingly, Bacillus was the most abundant group among the cultivable bacteria, representing 15.74% and 16.6%, in the 90 and 2000 m samples, respectively. The genera Microbacterium (2.38%) and Sphingomonas (2.38%) were exclusively identified in the sample from the 90 m depth, meanwhile the genus Pantoea and Vibrio appeared only in the sample from 2000 m (Figure 2B). Genes2018,9,100 7of20 (Figure2B).Surprisingly,Bacilluswasthemostabundantgroupamongthecultivablebacteria, representing15.74%and16.6%,inthe90and2000msamples,respectively.ThegeneraMicrobacterium (2.38%)andSphingomonas(2.38%)wereexclusivelyidentifiedinthesamplefromthe90mdepth, meanwhilethegenusPantoeaandVibrioappearedonlyinthesamplefrom2000m(Figure2B).   Figure2.(A)Bacterialdiversityincultivablebacteriaisolatedfromphotic(90mdepth,n=231)and aphotic(2000mdepth,n=374)samples;(B)relativeabundanceofthe13mostabundantgenerain90 and2000mdepthsamples.Thegenerarepresentedbyasingleisolatearegroupedas“other”. 3.3.Quorum‐SensingandQuorum‐QuenchingActivitiesamongCultivableBacteria Theactivationofthebeta‐galactosidasegeneofthesensor,whichsuggeststhepresenceofAHLs intheculturemedia,wasrelativelyfrequentamongthe605marineisolates(20.84%).Thenumberof positiveswashigherinthesamplesfrom90m(37.66%)thaninonesfrom2000m(4.01%)(Figure 3A).TheoligotrophicMA1/100culturemediumallowedtheisolationofthehigherpercentageof strainswithputativeQSactivityatboth90(60%)and(12.67%)2000m.Onthecontrary,thestrains isolatedfromTSA‐Ipresentedalowercapacitytoactivatethereporter(4.76and2.52%for90and 2000msamplesrespectively). Figure 2. ( A ) Bacterial diversity in cultivable bacteria isolated from photic (90 m depth, n= 231) and aphotic (2000 m depth, n= 374) samples; ( B ) relative abundance of the 13 most abundant genera in 90 and 2000 m depth samples. The genera represented by a single isolate are grouped as “other”. 3.3. Quorum-Sensing and Quorum-Quenching Activities among Cultivable Bacteria The activation of the beta-galactosidase gene of the sensor, which suggests the presence of AHLs in the culture media, was relatively frequent among the 605 marine isolates (20.84%). The number of positives was higher in the samples from 90 m (37.66%) than in ones from 2000 m (4.01%) (Figure 3A). The oligotrophic MA 1/100 culture medium allowed the isolation of the higher percentage of strains with putative QS activity at both 90 (60%) and (12.67%) 2000 m. On the contrary, the strains isolated from TSA-I presented a lower capacity to activate the reporter (4.76 and 2.52% for 90 and 2000 m samples respectively). Genes 2018,9, 100 8 of 20 Genes2018,9,100 8of20  Figure3.(A)PercentageoftheisolatedstrainswiththeabilitytoactivatetheN‐acylhomoserine lactone(AHL)sensorAgrobacteriumtumefaciensNTL4inthe90m(whitebars)and2000m(blackbars) samples;(B)percentageofisolateswithquorum‐quenching(QQ)activityagainstC6andC12‐HSL isolatedfromeachculturemediainthe90m(whitebars)and2000m(blackbars)samples,as confirmedbyusingthePetridishsolidassaywithChromobacteriumviolaceumCV026andVIR07. Mediaused:tryptonesoyagar1%NaCl(TSA‐1),marineagar(MA),dilutedmarineagar(MA1/100), andfilteredautoclavedseawatermedium(FAS)supplementedwith0.5g/Lpolymers:agarose,chitin andstarch(FAS‐POL). Thecapacityofthemarinebacterialcollectiontointerferewithbothlong‐ (C12‐HSL)and short‐chain(C6‐HSL)AHLswasfirsttestedusingaC.violaceum‐basedbioassayin96‐wellmicrotiter plates.NoneoftheQQpositivesinthepreliminaryassayshowedinterferencewiththegrowthofthe biosensors.TheabilitytoquenchtheQSsignalC12‐HSLwasobservedinalargenumberofcultivable bacteria(38.24%).Theaverageactivitywashigherinthe2000m,aphoticsample(47.05%)thaninthe 90mphoticone(29.43%,Figure3B).Amongthe68strainsisolatedfromthe90mdepthwiththe capacitytoquenchC12‐HSL,fourstrains,representing1.73%ofthetotalstrains,werealsoableto eliminatetheC6‐HSLQSsignal,andasimilarpercentagewasobtainedfortheisolatesfromthe2000 msample(2.12%).AlltheisolateswiththeabilitytointerferewithC6‐HSLcouldalsodegrade C12‐HSL,butnoisolatewasfoundthatcouldonlyeliminatetheactivityoftheshort‐chainAHL.The oligotrophicMA1/100culturemediumallowedtheisolationofthehighestpercentageofstrainswith QQactivityagainstC12‐HSL(84.5%)inthe2000msample.Onthecontrary,inthe90msample,the richculturemedia(TSA‐IandMA)presentedthehighestpercentagesofQQactivity(50–52%).The mosteffectiveculturemediumtoisolatestrainswithQQactivityagainsttheshort‐chainsignal Figure 3. ( A ) Percentage of the isolated strains with the ability to activate the N-acyl homoserine lactone (AHL) sensor Agrobacterium tumefaciens NTL4 in the 90 m (white bars) and 2000 m (black bars) samples; ( B ) percentage of isolates with quorum-quenching (QQ) activity against C6 and C12-HSL isolated from each culture media in the 90 m (white bars) and 2000 m (black bars) samples, as confirmed by using the Petri dish solid assay with Chromobacterium violaceum CV026 and VIR07. Media used: tryptone soy agar 1% NaCl (TSA-1), marine agar (MA), diluted marine agar (MA 1/100), and filtered autoclaved seawater medium (FAS) supplemented with 0.5 g/L polymers: agarose, chitin and starch (FAS-POL). The capacity of the marine bacterial collection to interfere with both long- (C12-HSL) and short-chain (C6-HSL) AHLs was first tested using a C. violaceum-based bioassay in 96-well microtiter plates. None of the QQ positives in the preliminary assay showed interference with the growth of the biosensors. The ability to quench the QS signal C12-HSL was observed in a large number of cultivable bacteria (38.24%). The average activity was higher in the 2000 m, aphotic sample (47.05%) than in the 90 m photic one (29.43%, Figure 3B). Among the 68 strains isolated from the 90 m depth with the capacity to quench C12-HSL, four strains, representing 1.73% of the total strains, were also able to eliminate the C6-HSL QS signal, and a similar percentage was obtained for the isolates from the 2000 m sample (2.12%). All the isolates with the ability to interfere with C6-HSL could also degrade C12-HSL, but no isolate was found that could only eliminate the activity of the short-chain AHL. The oligotrophic MA 1/100 culture medium allowed the isolation of the highest percentage of strains with QQ activity against C12-HSL (84.5%) in the 2000 m sample. On the contrary, in the 90 m sample, the rich culture media (TSA-I and MA) presented the highest percentages of QQ activity (50–52%). The most effective culture medium to isolate strains with QQ activity against the short-chain signalC6-HSL were the oligotrophic FAS-POL (3.22%) and MA 1/100 (9.85%) for the samples from 90 and 2000 m, respectively. Genes 2018,9, 100 9 of 20 3.4. Identification of the Wide-Spectrum Quorum-Quenching Strains and Characterization of Quorum-Quenching Activity The taxonomic label of the best hit is shown in Table 1for the 12 strains presenting wide-spectrum QQ activity. The four marine strains selected from the 90 m sample belonged to Firmicutes (Planomicrobium chinense), Alphaproteobacteria (Sphingopyxis alaskensis,Erythrobacter citreus), and Actinobacteria (Microbacterium schleiferi). Among the eight strains from the deepest sample, one of them belonged to Betaproteobacteria (Ralstonia pickettii), six to Alphaproteobacteria (5 Erythrobacter flavus strains, Citomicrobium sp.), and one to Gammaproteobacteria (Pantoea sp.). Despite the high number of Bacillus sp. strains present in the collections, no Bacillus strain with wide-spectrum QQ activity was identified. Table 1. Identification and characterization of the marine isolates showing wide Quorum-Quenching (QQ) activity. The presence of QQ activity in the cell extracts and the minimal active concentration of extract (MAC, µ g protein/mL cell extract) needed to fully eliminate the activity of 10 µ M of C6-HSL was also investigated. Live Cell Cell Extract MAC C6-HSL (µg Protein/mL Cell Extract) Strain Closest Cultivated Bacteria % ID at 16S rRNA Gene Locus C6-HSL OC6-HSLC12-HSL OC12-HSL C6-HSL C12-HSL 90 m 1F1 Planomicrobium chinense 99.93 + + + + + + 104.7 2E12 Sphingopyxis alaskensis 99.93 + + + + + + 18.67 2G12 Erythrobacter citreus 99.04 + + + + + + 1918 3A3 Microbacterium schleiferi 99.71 + + + + - + nd 2000 m 2F1 Ralstonia pickettii 95.79 + + ±+ + + 17.6 3G7 Erythrobacter flavus 99.34 + + + + + + 786 4B4 Erythrobacter flavus 99.34 + + + + + + 216 4B7 Pantoea sp. 96.01 + - + - - - nd 4B9 Erythrobacter flavus 99.71 + + + + + + 961 4B10 Erythrobacter flavus 99.49 + + + + + + 223.9 4B12 Erythrobacter flavus 99.49 + + + + + + 965 4C3 Citromicrobium sp. 98.33 + + + + - + nd Nd: Not determined. The isolate 2F1 may represent a new species within the genus Ralstonia because of the low identity with the known species of the genus (95.79%). The cell extracts of three isolates, 3A3 (Microbacterium schleiferi), 4B7 (Pantoea sp.), and 4C3 (Citromicrobium sp.) did not present QQ activity against C6-HSL. The ability to interfere with oxo-substituted AHLs was also tested for the 12 selected strains (Table 1). Most of the marine strains were able to inactivate the oxo-substituted AHL, except for strain 4B7 (Pantoea sp.) that did not show QQ activity against any of the substituted AHLs tested, namely OC6 and OC12-HSL. In order to check the relative activity of the strains, the minimal active concentration (MAC, µ g protein/mL) was calculated in the cell extracts. The marine isolates with the highest activity were 2E12 (Sphingopyxis alaskensis) and 2F1 (Ralstonia sp.), since their QQ activity was at least one order of magnitude higher than that of the other QQ strains (<20 µg/mL). Among the 12 strains, Sphingopyxis alaskensis 2E12 and Erythrobacter citreus 2G12 could activate the biosensor A. tumefaciens NTL4 using 24 h supernatants. This activity was maintained in 48 h supernatants only for Sphingopyxis alaskensis 2G12, but disappeared in Erythrobacter citreus 2G12. AHL-like activity was also detected in 48 h supernatants of Citromicrobium sp. 4C3. Genes 2018,9, 100 16 of 20 13. Cicirelli, E.M.; Williamson, H.; Tait, K.; Fuqua, C. Acylated homoserine lactone signalling in marine bacterial systems. In Chemical Communication among Bacteria; Winans, S.C., Bassler, B.L., Eds.; ASM Press: Washington, DC, USA, 2008; pp. 251–271. 14. Hmelo, L.R. Quorum sensing in marine microbial environments. Annu. Rev. Mar. Sci. 2017 ,9, 257–281. [CrossRef] [PubMed] 15. Gram, L.; Grossart, H.P.; Schlingloff, A.; Kiorboe, T. Possible quorum sensing in marine snow bacteria: Produtcion of acylated homoserine lactones by Roseobacter strains. Appl. Environ. Microbiol. 2002 ,68, 4111–4116. [CrossRef] [PubMed] 16. Taylor, M.W.; Shupp, P.J.; Baillie, H.J.; Charlton, T.S.; De Nys, R.; Kjelleberg, S.; Steinberg, P.D. Evidence for acyl homoserine lactone signal production in bacteria associated with marine sponges. Appl. Environ. Microbiol. 2004,70, 4387–4389. [CrossRef] [PubMed] 17. Wagner-Döbler, I.; Thiel, V.; Eberl, L.; Allgaier, M.; Bodor, A.; Meyer, S.; Ebner, S.; Henning, A.; Pukall, R.; Schulz, S. Discovery of complex mixtures of novel long-chain quorum sensing signals in free-living and host-associated marine Alphaproteobacteria. Chem. Biochem. 2005,6, 2195–2206. [CrossRef] [PubMed] 18. Romero, M.; Avendaño-Herrera, R.; Magariños, B.; Cámara, M.; Otero, A. Acylhomoserine-lactone production and degradation by the fish pathogen Tenacibaculum maritimum, a member of the Cytophaga–Flavobacterium–Bacteroides (CFB) group. FEMS Microbiol. Lett. 2010,304, 131–139. [CrossRef] [PubMed] 19. Jatt, A.N.; Tang, K.; Liu, J.; Zhang, Z.; Zhang, X.H. Quorum sensing in marine snow and its possible influence on production of extracellular hydrolytic enzymes in marine snow bacterium Pantoea anatatis. FEMS Microbiol. Ecol. 2015,91, 1–13. [CrossRef] [PubMed] 20. Rolland, J.L.; Stien, D.; Sanchez-Ferandin, S.; Lami, E. Quorum sensing and quorum quenching in the phycosphere of phytoplankton: A case of chemical interactions ecology. J. Chem. Ecol. 2016 ,42, 1201–1211. [CrossRef] [PubMed] 21. Huang, Y.L.; Ki, J.S.; Case, R.J.; Qian, P.Y. Diversity and acyl-homoserine lactone production among subtidal biofilm-forming bacteria. Aquat. Microb. Ecol. 2008,52, 185–193. [CrossRef] 22. Mohamed, N.M.; Cicirelli, E.M.; Kan, J.; Chen, F.; Fuqua, C.; Hill, R.T. Diversity and quorum-sensing signal production of Proteobacteria associated with marine sponges. Environ. Microbiol. 2008 ,10, 75–86. [CrossRef] [PubMed] 23. Tait, K.; Hutchinson, Z.; Thompson, F.L.; Munn, C.B. Quorum sensing signal production and inhibition by coral-associated Vibrios. Environ. Microbiol. Rep. 2010,2, 145–150. [CrossRef] [PubMed] 24. Ransome, E.; Munn, C.B.; Halliday, N.; Cámara, M.; Tait, K. Diverse profiles of N-acyl-homoserine lactone molecules found in cnidarians. FEMS Microbiol. Ecol. 2014,87, 315–329. [CrossRef] [PubMed] 25. Hmelo, L.R.; Tracy, J.M.; Van Mooy, B.A.S. Possible influence of bacterial quorum sensing on the hydrolisys of sinking particulate organic carbon in marine environments. Environ. Microbiol. Rep. 2011 ,3, 682–688. [CrossRef] [PubMed] 26. Joint, I.; Tait, K.; Callow, M.E.; Milton, D.; Williams, P.; Cámara, M. Cell-to-cell communication across the prokaryote-eukaryote boundary. Science 2002,298, 1207. [CrossRef] [PubMed] 27. Tait, K.; Joint, I.; Daykin, M.; Milton, D.L.; Williams, P.; Cámara, M. Disruption of quorum sensing in seawater abolishes attraction of zoospores of the green alga Ulva to bacterial biofilms. Environ. Microbiol. 2005 ,7, 229–240. [CrossRef] [PubMed] 28. Goecke, F.; Labes, A.; Wiese, J.; Imhoff, J.F. Chemical interactions between marine macroalgae and bacteria. Mar. Ecol. Prog. Ser. 2012,409, 267–300. [CrossRef] 29. Van Mooy, B.; Hmelo, L.; Sofe, L.E.; Campagna, S.R.; Mau, A.L.; Dhyrman, S.T.; Heithoff, A.; Webb, E.; Momper, L.; Mincer, T.J. Quorum sensing control of phosphorous acquisition in Trichodesmium consortia. ISME J. 2012,6, 422–429. [CrossRef] [PubMed] 30. Wahl, M.; Goecke, F.; Labes, A.; Sobretsov, S.; Weinberg, F. The second skin: Ecological role of epibiotic biofilms on marine organisms. Front. Microbiol. 2012,3, 292. [CrossRef] [PubMed] 31. Defoirdt, T.; Boon, N.; Sorgeloos, P.; Verstraete, W.; Bossier, P. Alternatives to antibiotics to control bacteria infections: Luminescent vibriosis in aquaculture as an example. Trends Biotechnol. 2007 ,25, 472–479. [CrossRef] [PubMed] Genes 2018,9, 100 17 of 20 32. Decho, A.; Visscher, P.T.; Ferry, J.; Kawaguchi, T.; He, L.; Przqkop, K.M.; Norman, R.S.; Reid, R.P. Autoinducers extracted from microbial mats reveals a surprising diversity of N-acylhomoserine lactones (AHLs) and abundance changes that may reltae to diel pH. Environ. Microbiol. 2009 ,11, 409–420. [CrossRef] [PubMed] 33. Doberva, M.; Sanchez-Ferandin, S.; Toulza, E.; Lebaron, P.; Lami, R. Diversity of quorum sensing autoinducer synthases in the Global Ocean Sampling Metagenomic Database. Aquat. Microb. Ecol. 2015 ,74, 107–119. [CrossRef] 34. Ziervogel, K.; Arnosti, C. Polysaccharide hydrolysis in aggregates and free enzyme activity in aggregate-free seawater from the northeastern Gulf of Mexico. Environ. Microbiol. 2008 ,10, 289–299. [CrossRef] [PubMed] 35. Givskov, M.; De Nys, R.; Manefield, M.; Gram, L.; Maiximilien, L.E.; Molin, S.; Steinberg, P.D.; Kjelleberg, S. Eukaryotic interference with homoserine lactone-mediated prokaryotic singalling. J. Bacteriol. 1996 ,178, 6618–6622. [CrossRef] [PubMed] 36. Gao, M.; Teplitski, M.; Robinson, J.B.; Bauer, W.D. Production of substances by Medicago truncatula that affect bacterial quorum sensing. Mol. Plant Microbe Interact. 2003,16, 827–834. [CrossRef] [PubMed] 37. Camps, J.; Pujol, I.; Ballester, F.; Joven, J.; Simó, J.M. Paraoxonases as potential antibiofilm agents: Their relationship with quorum-sensing signals in Gram-negative bacteria. Antimicrob. Agents Chemother. 2011 ,55, 1325–1331. [CrossRef] [PubMed] 38. Dong, Y.H.; Zhang, L.H. Quorum sensing and quorum-quenching enzymes. J. Microbiol. 2005 ,43, 101–109. [PubMed] 39. Romero, M.; Mayer, C.; Muras, A.; Otero, A. Silencing bacterial communication through enzymatic quorum sensing inhibition. In Quorum Sensing vs Quorum Quenching: A Battle with No End in Sight; Kalia, V.C., Ed.; Springer: Delhi, India, 2015; pp. 219–236. 40. Dong, Y.H.; Wang, L.H.; Xu, J.L.; Zhang, H.B.; Zhang, X.F.; Zhang, H. Quenching quorum-sensing-dependent bacterial infection by an N-acyl homoserine lactonase. Nature 2001,411, 813–817. [CrossRef] [PubMed] 41. Kjelleberg, S.; McDougald, D.; Rasmussen, T.B.; Givskov, M. Quorum-sensing inhibition. In Chemical Communication among Bacteria; Winans, S.C., Bassler, B.L., Eds.; ASM Press: Washington, DC, USA, 2008; pp. 393–416. 42. Dong, Y.H.; Xu, J.L.; Li, X.Z.; Zhang, L.H. AiiA, an enzyme that inactivates the acylhomoserine lactone quorum-sensing signal and attenuates the virulence of Erwinia carotovora.Proc. Natl. Acad. Sci. USA 2000 ,97, 3526–3531. [CrossRef] 43. Dong, Y.H.; Gusti, A.R.; Zhang, Q.; Xu, J.L.; Zhang, L.H. Identification of quorum-quenching N-acyl homoserine lactoneses from Bacillus species. Appl. Environ. Microbiol. 2002 ,68, 1754–1759. [CrossRef] [PubMed] 44. D’Angelo-Picard, C.; Faure, D.; Penot, I.; Dessaux, Y. Diversity of N-acyl homoserine lactone-producing and–degrading bacteria in soil and tobacco rhizosphere. Environ. Microbiol. 2005 ,7, 1796–1808. [CrossRef] [PubMed] 45. Golberg, K.; Pavlov, V.; Marks, R.S.; Kushmaro, A. Coral-associated bacteria, quorum sensing disrupters, and the regulation of biofouling. Biofouling 2013,29, 669–682. [CrossRef] [PubMed] 46. Saurav, K.; Bar-Shalom, R.; Haber, M.; Burgsdorf, I.; Oliveiro, G.; Constantino, V.; Morgenstern, D.; Steindler, L. In search of alternative antibiotics drugs: Quorum-quenching activity in sponges and their bacterial isolates. Front. Microbiol. 2016,7, 1–18. [CrossRef] [PubMed] 47. Romero, M.; Martín-Cuadrado, A.M.; Roca-Rivada, A.; Cabello, A.M.; Otero, A. Quorum quenching in cultivable bacteria from dense marine coastal microbial communities. FEMS Microbiol. Ecol. 2011 ,75, 205–217. [CrossRef] [PubMed] 48. Romero, M.; Martín-Cuadrado, A.B.; Otero, A. Determination of whether quorum quenching is a common activity in marine bacteria by analysis of cultivable bacteria and metagenomic sequences. Appl. Environ. Microbiol. 2012,78, 6345–6348. [CrossRef] [PubMed] 49. Linthorne, J.S.; Chang, B.J.; Flematti, G.R.; Ghisalberti, E.L.; Sutton, D.C. A direct pre-screen for marine bacteria producing compounds inhibiting quorum sensing reveals diverse planktonic bacteria that are bioactive. Mar. Biotechol. 2014,17, 33–42. [CrossRef] [PubMed] 50. Torres, M.; Romero, M.; Prado, S.; Dubert, J.; Tahrioui, A.; Otero, A.; Llamas, I. N-acylhomoserine lactone-degrading bacteria isolated from hatchery bivalve cultures. Microbiol. Res. 2013 ,168, 547–554. [CrossRef] [PubMed] Genes 2018,9, 100 18 of 20 51. Torres, M.; Rubio-Portillo, E.; Antón, J.; Ramos-Esplá, A.A.; Quesada, E.; Llamas, I. Selection of the N-acylhomoserine lactone-degrading bacterium Alteromonas stellopolaris PQQ-42 and of its potential for biocontrol in aquaculture. Front. Microbiol. 2016,7, 646. [CrossRef] [PubMed] 52. Skindersoe, M.E.; Ettinger-Esptein, P.; Rasmussen, T.B.; Bjarnsholt, T.; De Nys, R.; Givskov, M. Quorum sensing antagonism from marine organisms. Mar. Biotechnol. 2008,10, 56–63. [CrossRef] [PubMed] 53. Hmelo, L.R.; Van Mooy, B.A.S. Kinetic constrainst on acylated homoserine lactone-based quorum sensing in marine environments. Aquat. Microb. Ecol. 2009,54, 127–133. [CrossRef] 54. Weiland-Bräuer, N.; Pinnow, N.; Schmitz, R.A. Novel reporter for identification of interference with acyl homoserine lactone and autoinducer-2 quorum sensing. Appl. Environ. Microbiol. 2015 ,81, 1477–1489. [CrossRef] [PubMed] 55. López-Pérez, M.; Haro-Moreno, J.M.; Gonzalez-Serrano, R.; Parras-Moltó, M.; Rodriguez-Valera, F. Genome diversity of marine phages recovered from Mediterranean metagenomes: Size matters. PLoS Genet. 2017 ,13, e1007018. [CrossRef] [PubMed] 56. Haro-Moreno, J.M.; López-Pérez, M.; de la Torre, J.; Picazo, A.; Camacho, A.; Rodriguez-Valera, F. Fine Stratification of Microbial Communities through A Metagenomic Profile of the Photic Zone. ISME J. 2017 . [CrossRef] 57. Fu, L.; Niu, B.; Zhu, Z.; Wu, S.; Li, W. CD-HIT: Accelerated for clustering the next generation sequencing data. Bioinformatics 2012,28, 3150–3152. [CrossRef] [PubMed] 58. Wang, Q.; Garrity, G.M.; Tiedje, J.M.; Cole, J.R. Naïve Bayesian classifier for rapid assignment of rRNA sequences into new bacterial taxonomiy. Appl. Environ. Microbiol. 2007 ,73, 5261–5627. [CrossRef] [PubMed] 59. Twigg, M.S.; Tait, K.; Williams, P.; Atkinson, S.; Cámara, M. Interference with the germination and growth of Ulva zoospores by quorum-sensing molecules from Ulva-associated epiphytic bacteria. Environ. Microbiol. 2014,16, 445–453. [CrossRef] [PubMed] 60. Chun, J.; Lee, J.H.; Jung, Y.; Kim, M.; Kim, S.; Kim, B.K.; Lim, Y.W.; Chun, J. EzTaxon: A web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences. Int. J. Syst. Evol. Microbiol. 2007,57, 2259–2261. [CrossRef] [PubMed] 61. Chilton, M.D.; Currier, T.C.; Farrand, S.K.; Bendich, A.J.; Gordon, M.P.; Nester, E.W. Agrobacterium tumefaciens DNA and PS8 bacteriophage DNA not detectedin crown gall tumors. Proc. Natl. Acad. Sci. USA 1974,71, 3672–3676. [CrossRef] [PubMed] 62. Shaw, P.D.; Ping, G.; Daly, S.L.; Cha, C.; Cronan, J.E., Jr.; Rinehart, K.L.; Farrand, S.K. Detecting and characterizing N-acyl-homoserine lactone signal molecules by thin-layer chromatography. Proc. Natl. Acad. Sci. USA 1997,94, 6036–6041. [CrossRef] [PubMed] 63. Yates, E.A.; Philipp, B.; Buckley, C.; Atkinson, S.; Chhabra, S.R.; Sockett, R.E.; Goldner, M.; Dessaux, Y.; Cámara, M.; Smith, H.; et al. N-acylhomoserine lactonase undergo lactonolysis in a pH-, temperature-, and acyl chain length-dependent manner during growth of Yersinia pseudotuberculosis NS Pseudomonas aeruginosa. Infect. Immun. 2002,70, 5635–5646. [CrossRef] [PubMed] 64. Morohoshi, T.; Kato, M.; Fukamachi, K.; Kato, N.; Ikeda, T. N-acylhomoserine lactone regulates violacein production in Chromobacterium violaceum type strain ATCC 12472. FEMS Microbiol. Lett. 2008 ,279, 124–130. [CrossRef] [PubMed] 65. McClean, K.H.; Winson, M.K.; Fish, L.; Taylor, A.; Chhabra, S.R.; Cámara, M.; Daykin, M.; Lamb, J.H.; Swift, S.; Bycroft, B.W.; et al. Quorum sensing and Chromobacterium violaceum: Exploitation of violacein production and inhibition for the detection of N-acylhomoserine lactones. Microbiology 1997 ,143, 3703–3711. [CrossRef] [PubMed] 66. Mayer, C.; Romero, M.; Muras, A.; Otero, A. Aii20J, a wide spectrum thermo-stable N-acylhomoserine lactonase from the marine bacterium Tenacibaculum sp. 20J can quench AHL-mediated acid resistance in Escherichia coli.Appl. Microbiol. Biotechnol. 2015,99, 9523–9539. [CrossRef] [PubMed] 67. Romero, M.; Muras, A.; Mayer, C.; Buján, N.; Magariños, B.; Otero, A. In vitro quenching of fish pathogen Edwardsiella tarda AHL production using the marine bacterium Tenacibaculum sp. strain 20J cell extracts. Dis. Aquat. Organ. 2014,108, 217–225. [CrossRef] [PubMed] 68. Martín-Cuadrado, A.B.; Rodriguez-Valera, F.; Moreira, D.; Alba, J.C.; Ivars-Martinez, E.; Henn, M.R.; Talla, E.; López-García, P. Hindsight in the relative abundance, metabolic potential and genome dynamics of uncultivated marine archea from comparative metagenomic analyses of bathypelagic plankton of different oceanic regions. ISME J. 2008,2, 865–886. [CrossRef] [PubMed] Genes 2018,9, 100 19 of 20 69. Peng, Y.; Leung, H.C.; Yiu, S.M.; Chin, F.Y. IDBA-UD: A de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 2012,28, 1420. [CrossRef] [PubMed] 70. Hyatt, D.; Chen, G.L.; Locascio, P.F.; Land, M.L.; Larimer, F.W.; Hauser, L.J. Prodigal: Prokaryotic gene recognition and traslation initiation site identification. BMC Bioinform. 2010,11, 119. [CrossRef] [PubMed] 71. Lowe, T.T.; Eddy, S.R. tRNAscan-SE: A program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997,25, 955–964. [CrossRef] [PubMed] 72. Nawrocki, E. Structural RAN Homology Search and Alignment Using Covariance Models. Ph.D. Thesis, Arts and Sciences of Washington University, Saint Louis, MO, USA, December 2009. [CrossRef] 73. Huang, Y.; Gilna, P.; Li, W. Identification of ribosomal RNA genes in metagenomic fragments. Bioinformatics 2009,25, 1338–1340. [CrossRef] [PubMed] 74. Tatusov, R.L.; Natale, D.A.; Garkavtsev, I.V.; Tatusova, T.A.; Shankaaram, U.T.; Rao, B.S.; Kiryutin, B.; Galperin, M.Y.; Feodorova, N.D.; Koonin, E.V. The COG database: New developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res. 2001,28, 22–28. [CrossRef] 75. Haft, D.H.; Loftus, B.J.; Richardson, D.L.; Yang, F.; Eisen, J.A.; Paulsen, I.T.; White, O. TIGRFAMs: A protein family resources for the functional identification of proteins. Nucleic Acid Res. 2001 ,29, 41–43. [CrossRef] [PubMed] 76. Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010 ,26, 2460–2461. [CrossRef] [PubMed] 77. Cole, J.R.; Wang, Q.; Fish, J.A.; Chai, B.; McGarrell, D.M.; Sun, Y.; Brown, C.T.; Porras-Alfaro, A.; Kuske, C.R.; Tiedje, J.M. Ribosomal Database Project: Data and tools for high throughput rRNA analysis. Nucleic Acids Res. 2014,42, D633–D642. [CrossRef] [PubMed] 78. Eddy, S.R. Multiple alignment using hidden Markov models. In Proceedings of the International Conference on Intelligent Systems for Molecular Biology, Cambridge, UK, 16–19 July 1995; Volume 3, pp. 114–120. 79. Buchfink, B.; Xie, C.; Huson, D.H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 2015 , 12, 59–60. [CrossRef] [PubMed] 80. Ganesh, S.; Parris, D.J.; DeLong, E.F.; Stewart, F.J. Metagenomic analysis of size-fractionated picoplankton in a marine oxygen minimum zone. ISME J. 2014,8, 187–211. [CrossRef] [PubMed] 81. Cases, I.; de Lorenzo, V.; Ouzounis, C.A. Transcription regulation and environmental adaptation in bacteria. Trends Microbiol. 2003,11, 248–253. [CrossRef] 82. Nealson, K.H.; Platt, T.; Hastings, J.W. Cellular control of the synthesis and activity of the bacterial luminiscent system. J. Bacteriol. 1970,104, 313–322. [PubMed] 83. Amann, R.I.; Ludwig, W.; Scheleifer, K.H. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 1995,95, 143–169. 84. Acinas, S.G.; Antón, J.; Rodríguez-Valera, F. Diversity of Free-Living and attached bacteria in offshore western Mediterranean waters as depicted by analysis of genes encoding 16S rRNA. Appl. Environ. Microbiol. 1999,65, 514–522. [PubMed] 85. Diggle, S.P.; Griffin, A.S.; Campbell, G.S.; West, S.A. Cooperation and conflict in quorum sensing bacterial populations. Nature 2007,450, 411–414. [CrossRef] [PubMed] 86. Romero, M.; Diggle, S.P.; Heeb, S.; Cámara, M.; Otero, A. Quorum quenching activiy in Anabaena sp. PCC7120: Identification of AiiC, a novel AHL-acylase. FEMS Microbiol. Lett. 2008 ,280, 73–80. [CrossRef] [PubMed] 87. Pinardi, N.; Masetti, E. Variability of the large scale general circulation of the Mediterranean Sea from observations and modelling: A review. Palaerogeogr. Palaeoclimatol. Palaeoecol. 2000 ,158, 153–173. [CrossRef] 88. Lin, Y.H.; Xu, J.L.; Hu, J.; Wang, L.H.; Ong, S.L.; Leadbetter, J.R.; Zhang, L.H. Acyl-homoserine lactone acylase from Ralstonia strain XJ12B represents a novel potent class of quorum-quenching enzymes. Mol. Microbiol. 2003,47, 849–860. [CrossRef] [PubMed] 89. Decho, A.W.; Norman, R.S.; Visscher, P.T. Quorum sensing in natural environments: Emerging views from microbial mats. Trends Microbiol. 2010,18, 73–80. [CrossRef] [PubMed] 90. Chen, C.N.; Chen, C.J.; Liao, C.T.; Lee, C.Y. A probable aculeacin A Acylase from Ralstonia solanacearum GMI1000 is N-acyl homoserine lactone acylase with quorum-quenching activity. BMC Microbiol. 2009 ,9, 89. [CrossRef] [PubMed] Genes 2018,9, 100 20 of 20 91. Morohoshi, T.; Someya, N.; Ikeda, T. Novel N-acylhomoserine lactone-degrading bacteria from the leaf surface of Solanum tuberosum and their quorum-quenching properties. Biosci. Biotechnol. Biochem. 2009 ,73, 2124–2127. [CrossRef] [PubMed] 92. Wang, W.Z.; Morohoshi, T.; Ikenoya, M.; Someya, N.; Ikeda, T. AiiM, a novel class of N-acylhomoserine lactonase from the leaf-associated bacterium Microbacterium testaceum.Appl. Environ. Microbiol. 2010 ,76, 2524–2530. [CrossRef] [PubMed] 93. Last, D.; Krüger, G.H.; Dörr, M.; Bornscheuer, U.T. Fast, continuous, and high-throughput (bio)chemical activity assay for N-acyl-L-homoserine lactone quorum-quenching enzymes. Appl. Environ. Microbiol. 2016 , 82, 4145–4154. [CrossRef] [PubMed] 94. Ivanova, K.; Fernandes, M.M.; Francesko, A.; Mendoza, E.; Guezquez, J.; Burnet, M.; Tzanov, T. Quorum-Quenching and matrix-degrading enzymes in multilayer coatings synergistically prevent bacterial biofilm formation on urinary catheters. ACS Appl. Mater. Interfaces 2015 ,7, 27066–27077. [CrossRef] [PubMed] 95. Feugeas, J.P.; Tourret, J.; Launay, A.; Bouvet, O.; Hoede, C.; Denamur, E.; Tenaillon, O. Links between transcription, environmental adaptation and gene variability in Escherichia coli: Correlations between gene expression and gene variability reflect growth efficiencies. Mol. Biol. Evol. 2016 ,33, 2515–2529. [CrossRef] [PubMed] 96. Park, S.Y.; Kang, H.O.; Jang, H.S.; Lee, J.K.; Koo, B.T.; Yum, D.Y. Identification of extracellular N-acylhomoserine lactone acylase from a Streptomyces sp. and its application to quorum quenching. Appl. Environ. Microbiol. 2005,71, 2636–2641. [CrossRef] [PubMed] 97. Mukherji, R.; Varshney, N.K.; Panigrahi, P.; Suresh, C.G.; Prabhune, A. A new role for penicillin acylases: Degradation of acyl homoserine lactone quorum sensing signals by Kluyvera citrophila penicillin G acylase. Enzym. Microb. Technol. 2014,56, 1–7. [CrossRef] [PubMed] 98. Case, R.; Labbate, M.; Kjelleberg, S. AHL-driven quorum-sensing circuits: Their frequency and function among the Proteobacteria. ISME J. 2008,2, 345–349. [CrossRef] [PubMed] © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).