Derek D N Smith

Arvin Nickzad

Eric Déziel

John Stavrinides

A Novel Glycolipid Biosurfactant Confers Grazing Resistance upon Pantoea ananatis BRT175 against the Social Amoeba Dictyostelium discoideum

Pantoea is a versatile genus of bacteria with both plant-and animalpathogenic strains, some of which have been suggested to cause human infections. There is, however, limited knowledge on the potential determinants used for host association and pathogenesis in animal systems. In this study, we used the model host Dictyostelium discoideum to show that isolates of Pantoea ananatis exhibit differential grazing susceptibility, with some being resistant to grazing by the amoebae. We carried out a high-throughput genetic screen of one grazing-resistant isolate, P. ananatis BRT175, using the D. discoideum pathosystem to identify genes responsible for the resistance phenotype. Among the 26 candidate genes involved in grazing resistance, we identified rhlA and rhlB, which we show are involved in the biosynthesis of a biosurfactant that enables swarming motility in P. ananatis BRT175. Using liquid chromatography-mass spectrometry (LC-MS), the biosurfactant was shown to be a glycolipid with monohexose-C 10 -C 10 as the primary congener. We show that this novel glycolipid biosurfactant is cytotoxic to the amoebae and is capable of compromising cellular integrity, leading to cell lysis. The production of this biosurfactant may be important for bacterial survival in the environment and could contribute to the establishment of opportunistic infections.

IMPORTANCE

The genetic factors used for host interaction by the opportunistic human pathogen Pantoea ananatis are largely unknown. We identified two genes that are important for the production of a biosurfactant that confers grazing resistance against the social amoeba Dictyostelium discoideum. We show that the biosurfactant, which exhibits cytotoxicity toward the amoebae, is a glycolipid that incorporates a hexose rather than rhamnose. The production of this biosurfactant may confer a competitive advantage in the environment and could potentially contribute to the establishment of opportunistic infections. KEYWORDS: biosurfactants, Pantoea, Dictyostelium, opportunistic infections P antoea is a genus of Gram-negative bacilli in the Enterobacteriaceae and a close relative of human-pathogenic genera Klebsiella and Enterobacter. Pantoea includes epiphytic and pathogenic members that have been identified throughout the environment, including clinical settings. Infections caused by members of Pantoea are known to occur primarily in immunocompromised individuals with preexisting conditions and can result in abscesses, pneumonia, or bacteremia [START_REF] Bergman | Pantoea agglomerans septicemia in three newborn infants[END_REF][START_REF] Shubov | Pantoea agglomerans pneumonia in a heart-lung transplant recipient: case report and a review of an emerging pathogen in immunocompromised hosts[END_REF][START_REF] De Baere | Bacteremic infection with Pantoea ananatis[END_REF][START_REF] Lalas | Sporadic Pantoea agglomerans bacteremia in a near-term female: case report and review of literature[END_REF][START_REF] Cheng | Bacteremia caused by Pantoea agglomerans at a medical center in Taiwan, 2000 -2010[END_REF][START_REF] Cruz | Pantoea agglomerans, a plant pathogen causing human disease[END_REF]; however, healthy individuals may be infected through penetrative injury by plant vegetation, which can result in cutaneous infections or develop into septic arthritis [START_REF] Cruz | Pantoea agglomerans, a plant pathogen causing human disease[END_REF][START_REF] De Champs | Isolation of Pantoea agglomerans in two cases of septic monoarthritis after plant thorn and wood sliver injuries[END_REF]. More concerning are the clinical cases of fatal bacteremia in neonates caused by contaminated parenteral nutrition as well as bacteremia in immunocompromised adults [START_REF] Bergman | Pantoea agglomerans septicemia in three newborn infants[END_REF][START_REF] De Baere | Bacteremic infection with Pantoea ananatis[END_REF][START_REF] Lalas | Sporadic Pantoea agglomerans bacteremia in a near-term female: case report and review of literature[END_REF][START_REF] Cheng | Bacteremia caused by Pantoea agglomerans at a medical center in Taiwan, 2000 -2010[END_REF][START_REF] Cruz | Pantoea agglomerans, a plant pathogen causing human disease[END_REF][START_REF] Habsah | An outbreak of Pantoea spp. in a neonatal intensive care unit secondary to contaminated parenteral nutrition[END_REF]. Many members of Pantoea, such as Pantoea ananatis, while considered common environ-mental microbes, have been suggested to be opportunists with human-pathogenic potential [START_REF] Coutinho | Pantoea ananatis: an unconventional plant pathogen[END_REF][START_REF] Walterson | Pantoea: insights into a highly versatile and diverse genus within the Enterobacteriaceae[END_REF].

P. ananatis was originally isolated from pineapple as the causative agent of fruitlet brown rot [START_REF] Serrano | Bacterial fruitlet brown rot on pineapple in the Philippines[END_REF]. Many isolates have also been found to cause disease in a wide range of plant species but are also reported to colonize humans opportunistically [START_REF] Coutinho | Pantoea ananatis: an unconventional plant pathogen[END_REF]. A study examining virulence potential showed that a P. ananatis pineapple isolate was especially virulent in an embryonated hen egg model compared to five clinical Pantoea agglomerans isolates [START_REF] Völksch | Polyphasic study of plant-and clinic-associated Pantoea agglomerans strains reveals indistinguishable virulence potential[END_REF]. Similarly, quantitative growth assays have shown that closely related isolates of P. ananatis can vary greatly in their growth potential in plant and insect model hosts [START_REF] Nadarasah | Quantitative evaluation of the hostcolonizing capabilities of the enteric bacterium Pantoea using plant and insect hosts[END_REF], suggesting the presence of specific genetic factors that mediate host association [START_REF] Kirzinger | Insights into crosskingdom plant pathogenic bacteria[END_REF][START_REF] Nadarasah | Insects as alternative hosts for phytopathogenic bacteria[END_REF][START_REF] Stavrinides | A single genetic locus in the phytopathogen Pantoea stewartii enables gut colonization and pathogenicity in an insect host[END_REF]. This has been explored further in a comparative genomics analysis of eight P. ananatis genomes, which determined that isolates readily exchange genetic factors involved in host-and niche-specific colonization [START_REF] De Maayer | Analysis of the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and interact with plant, insect and vertebrate hosts[END_REF]. Candidate disease factors were suggested to include a putative adhesin, multiple type VI secretion systems, and even type I fimbriae [START_REF] De Maayer | Analysis of the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and interact with plant, insect and vertebrate hosts[END_REF][START_REF] Shyntum | Comparative genomics of type VI secretion systems in strains of Pantoea ananatis from different environments[END_REF]. The presence of animal cell-specific type III secretion systems has also been noted in several strains, although their involvement in host association and specificity is still unclear [START_REF] Kirzinger | Host specificity determinants as a genetic continuum[END_REF][START_REF] Kirzinger | Inheritance of Pantoea type III secretion systems through both vertical and horizontal transfer[END_REF]. There is currently limited functional information on these and other genetic factors in this species that may contribute to opportunism and human pathogenicity.

Model pathosystems are excellent tools for identifying candidate disease factors in pathogenic bacteria. Dictyostelium discoideum has been used as a model host for host-pathogen interactions due to its tractability, its similarities to mammalian cells in its cellular response to virulence factors, and its ability to phagocytose bacteria [START_REF] Cosson | Eat, kill or die: when amoeba meets bacteria[END_REF][START_REF] Hasselbring | Dictyostelium discoideum as a model system for identification of Burkholderia pseudomallei viru-lence factors[END_REF][START_REF] Pan | Use of a Dictyostelium model for isolation of genetic loci associated with phagocytosis and virulence in Klebsiella pneumoniae[END_REF][START_REF] Lelong | Evolution of Pseudomonas aeruginosa virulence in infected patients revealed in a Dictyostelium discoideum host model[END_REF][START_REF] Alibaud | Pseudomonas aeruginosa virulence genes identified in a Dictyostelium host model[END_REF]. Resistance to D. discoideum grazing can be used to identify isolates with possible virulence potential [START_REF] Froquet | Dictyostelium discoideum: a model host to measure bacterial virulence[END_REF]. Pseudomonas aeruginosa and Burkholderia pseudomallei mutants that are attenuated for virulence in the D. discoideum model are also attenuated in more complex model hosts like fruit flies and mice [START_REF] Hasselbring | Dictyostelium discoideum as a model system for identification of Burkholderia pseudomallei viru-lence factors[END_REF][START_REF] Alibaud | Pseudomonas aeruginosa virulence genes identified in a Dictyostelium host model[END_REF]. The D. discoideum pathosystem has been used to identify and assess the involvement of a variety of animal-specific virulence factors in host association, including the type VI secretion system, the type III secretion system, and various cytotoxins [START_REF] Alibaud | Pseudomonas aeruginosa virulence genes identified in a Dictyostelium host model[END_REF][START_REF] Pukatzki | The human pathogen Pseudomonas aeruginosa utilizes conserved virulence pathways to infect the social amoeba Dictyostelium discoideum[END_REF][START_REF] Macintyre | The Vibrio cholerae type VI secretion system displays antimicrobial properties[END_REF][START_REF] Sperandio | Virulence of the Pseudomonas fluorescens clinical strain MFN1032 towards Dictyostelium discoideum and macrophages in relation with type III secretion system[END_REF][START_REF] Cosson | Pseudomonas aeruginosa virulence analyzed in a Dictyostelium discoideum host system[END_REF]. In this study, we used D. discoideum as a model host to screen for genetic factors that may enable P. ananatis to exploit animal hosts. One strain, P. ananatis BRT175, which was shown to have a grazing-resistant phenotype, was subjected to a genetic screen to identify the genetic determinants involved in resisting D. discoideum feeding. We show that two genes, rhlA and rhlB, are involved in producing a novel biosurfactant that is cytotoxic to D. discoideum.

RESULTS

Qualitative assay identifies grazing-resistant P. ananatis isolates. The grazing resistance of 10 phylogenetically characterized P. ananatis isolates (13) was evaluated using a qualitative assay in which the plaque formation and sporulation on Escherichia coli B/r, the standard food source for D. discoideum, were used as a reference (Table 1). Grazing resistance was variable between the P. ananatis isolates and ranged from minimal plaque formation to full plaque formation and sporulation. P. ananatis BRT175 was the most resistant isolate, with minimal plaque formation and no sporulation when challenged with 10,000, 1,000, or 100 D. discoideum cells on modified SM (MSM) agar (Fig. 1). Similarly, P. ananatis M232A, LMG20103, and 15320 also showed a grazing-resistant phenotype with no sporulation. P. ananatis B7, BRT98, and 26SR6 showed an intermediate phenotype with large plaque formation occurring even when only 100 D. discoideum cells were applied. P. ananatis Cit30-11, LMG5342, and 17671 were completely susceptible to D. discoideum grazing, with large plaques forming and sporulation occurring in all treatments. Interestingly, the sister taxon isolate to P. ananatis BRT175, P. ananatis 17671, was one of the least grazing-resistant isolates, with plaque and spore formation being evident throughout the lawn. Grazing resistance and susceptibility did not appear correlated with phylogenetic relatedness within the P. ananatis species group [START_REF] Nadarasah | Quantitative evaluation of the hostcolonizing capabilities of the enteric bacterium Pantoea using plant and insect hosts[END_REF], as isolates at both extremes of grazing resistance are closely related.

Transposon mutagenesis identifies multiple genetic factors linked to grazing resistance.

To identify the genetic factors involved in grazing resistance, the grazing-resistant P. ananatis BRT175 was selected for mutagenesis and a highthroughput genetic screen was initiated for D. discoideum grazing susceptibility. A total of 3,789 mutants of P. ananatis BRT175 were screened, and 36 wells were identified as containing a grazing-susceptible mutant, as indicated by large plaque formation and/or sporulation. These 36 mutants were shown to represent 26 candidate genes that influence bacterial grazing resistance. Representative mutants from each of the 26 candidate genes were tested for growth deficiencies, with many of the mutants showing little or no defect in growth rate or growth density relative to the wild type (see Fig. S1 in the supplemental material). These 26 genes included quorum-sensingrelated autoinducer synthase homologs of phzI and eanI, as well as purine and pyrimidine biosynthesis genes guaB and pyrC, pyrD, and carB (Table 2). Also identified was the dsbB gene, which is involved in a two-component system that forms disulfide bonds in periplasmic proteins [START_REF] Totsika | Characterization of two homologous disulfide bond systems involved in virulence factor biogenesis in uropathogenic Escherichia coli CFT073[END_REF][START_REF] Qin | Francisella tularensis subsp. tularensis Schu S4 disulfide bond formation protein B, but not an RND-type efflux pump, is required for virulence[END_REF][START_REF] Denoncin | Disulfide bond formation in the bacterial periplasm: major achievements and challenges ahead[END_REF], as well as the thioredoxin system component trxB, which plays an important role in replication during intracellular growth [START_REF] Bjur | Thioredoxin 1 promotes intracellular replication and virulence of Salmonella enterica serovar Typhimurium[END_REF].

The screen also identified rhlA and rhlB as being important for grazing resistance. The rhlA and rhlB genes, which were recovered once and four times, respectively (Table 2), are adjacent genes in the P. ananatis BRT175 genome. Homologs of these rhlA and rhlB genes encode enzymes responsible for the biosynthesis of rhamnolipids in Pseudomonas aeruginosa and a few Burkholderia species [START_REF] Hausmann | Rhamnolipids: detection, analysis, biosynthesis, genetic regulation, and bioengineering of production[END_REF]. The transposon insertion in the rhlA::Tn5 mutant (mutant 28C8) occurred near nucleotide 385 of the 837-bp open reading frame, which would induce a polar mutation if the genes are coregulated and in a putative operon [START_REF] Alexeyev | Improved antibiotic-resistance gene cassettes and omega elements for Escherichia coli vector construction and in vitro deletion/insertion mutagenesis[END_REF][START_REF] Alexeyev | New mini-Tn5 derivatives for insertion mutagenesis and genetic engineering in gramnegative bacteria[END_REF]. The transposon insertion in the rhlB::Tn5 mutant (mutant 32C5) occurred near nucleotide 531 of the 1,173-bp open reading frame. Both rhl mutants had severe impairment in grazing resistance, with amoebal sporulation being evident after 7 days of grazing compared to no sporulation and minimal plaque formation on wild-type P. ananatis BRT175. The rhlA::Tn5 mutant was even more susceptible, showing complete grazing susceptibility with as few as 500 amoebae being sufficient for sporulation, whereas 2,000 or more amoebae were necessary for sporulation on the rhlB::Tn5 mutant (Fig. 2A).

rhlA is involved in biosynthesis of a glycolipid biosurfactant. To establish the involvement of a biosurfactant, we measured and compared surface tension and emulsification activities of culture extracts from P. ananatis BRT175 and the rhlA::Tn5 mutant. Wild-type culture extracts were found to reduce the surface tension of water from 72 to 40 mN/m, whereas the rhlA::Tn5 culture extracts could reduce the water surface tension only to 62 mN/m. Accordingly, the mutant extracts had almost no emulsification activity compared to the wild type (Fig. 3). These results suggested the production of an extracellular biosurfactant and the involvement of the rhlA product in its synthesis.

To determine if the biosurfactant was a rhamnolipid, we analyzed the extracts from the wild type and the rhlA::Tn5 cultures using liquid chromatography-mass spectrometry (LC-MS) protocols developed for rhamnolipids. Wild-type extracts had three peaks with m/z values of 519, 547, and 575, which were absent from the rhlA::Tn5 culture extracts (Fig. 4), but none of these corresponded to any of the approximately 60 different known rhamnolipid congeners [START_REF] Lépine | Rhamnolipids: diversity of structures, microbial origins and roles[END_REF]. To investigate this unexpected result, we used tandem mass spectrometry (MS/MS) fragmentation to further analyze the m/z 519 pseudomolecular ion, the most abundant molecule requiring rhlA for its biosynthesis. This biosurfactant was determined to be a monohexose-C 10 -C 10 , although the exact nature of the sugar moiety is still undetermined (Fig. 5). The two other identified masses (m/z 547 and m/z 575) appear to correspond to congeners containing hydroxydodecanoic (C 12 ) and hydroxytetradecanoic (C 14 ) acid moieties as side chain fatty acids. Further investigation will be required to fully identify the exact nature of these new biosurfactants. rhlA but not rhlB is essential for full swarming motility. Because rhamnolipids can aid in swarming motility in some species [START_REF] Caiazza | Rhamnolipids modulate swarming motility patterns of Pseudomonas aeruginosa[END_REF][START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF][START_REF] Nickzad | Quorum sensing controls swarming motility of Burkholderia glumae through regulation of rhamnolipids[END_REF], we compared the swarming proficiency of the rhl mutants relative to that of the wild type. Wild-type P. ananatis BRT175 exhibits a characteristic dendritic pattern on 0.5% modified SM agar (Fig. 2B andC), whereas the rhlA::Tn5 mutant is deficient in swarming on 0.5% modified SM agar and 0.5% modified M9 agar (Fig. 2B andC). The rhlB::Tn5 mutant was still capable of swarming on both medium types (Fig. 2B andC). The three other rhlB::Tn5 mutants (25E4, 24H12, and 40C2), each of which appeared to have a unique transposon insertion site, also retained swarming activity on 0.5% modified SM agar. To determine whether swarming motility was an indicator for grazing resistance, all isolates in the P. ananatis group were tested for swarming proficiency. Grazing-susceptible P. ananatis Cit30-11 and LMG5342 and E. coli B/r showed no motility (Fig. 6), whereas P. ananatis 17671, a grazing-susceptible isolate, had a different motility phenotype, as it appeared to move mostly linearly from the point of inoculation. P. ananatis 17671 did not form dendrites, nor did it form what is commonly referred to as a "featureless mat" [START_REF] Kearns | A field guide to bacterial swarming motility[END_REF], which is one of the motility patterns formed by some swarming bacteria. P. ananatis LMG20103, M232A, B7, 15320, BRT98, and 26SR6, which represent both grazing- resistant and intermediate strains, formed primarily a "featureless mat" phenotype with some dendrite-like protrusions visible in B7, LMG20103, M232A, and BRT98 trials (Fig. 6).

The biosurfactant produced by P. ananatis BRT175 is cytotoxic to D. discoideum. To evaluate whether the new biosurfactant produced by P. ananatis BRT175 has a cytotoxic or inhibitory effect at concentrations produced within culture media, D. discoideum cells were exposed to cell-free culture medium conditioned with either wild-type P. ananatis BRT175, the rhlA::Tn5 mutant, or the rhlB::Tn5 mutant (Kruskal-Wallis test, significant P ϭ 0.02). In three independent plaque assay experiments, no plaques formed on plates seeded with amoebae that had been exposed to wild-typeconditioned culture medium (P ϭ 0.0305) (Fig. 7A). Amoebae exposed to rhlA::Tn5 strain-conditioned medium formed plaques similar to the number seen in the control (P ϭ 0.2728). Interestingly, the rhlB::Tn5 strain-conditioned medium also did not allow for plaque formation (P ϭ 0.0305). Amoeba cell viability assays using trypan blue staining were consistent with these results (Kruskal-Wallis test, P ϭ 0.04), with exposure to the wild-type-conditioned culture medium leaving mostly cellular debris (P ϭ 0.0064) (Fig. 7B). Cells exposed to the rhlB::Tn5 strain-conditioned medium were still largely intact, but many cells showed trypan blue uptake, indicating loss of membrane integrity (P ϭ 0.1065); there was also no significant difference between the rhlA::Tn5 strain-conditioned medium and the control (P ϭ 0.4549).

rhlA and rhlB are distributed among isolates of P. ananatis. A survey of the distribution of the P. ananatis BRT175 rhlA and rhlB genes using BLAST identified the closest homologs in several other sequenced isolates of P. ananatis, including P. ananatis LMG20103 (43), LMG5342 (44), AJ13355, and PA13, as well as in unpublished draft genomes of P. ananatis 15320, BRT98, 26SR6, Cit30-11, and 17671. Homologs were also identified in Pantoea stewartii subsp. stewartii DC283, which is a sister species to P. ananatis [START_REF] Nadarasah | Quantitative evaluation of the hostcolonizing capabilities of the enteric bacterium Pantoea using plant and insect hosts[END_REF]. Independent genealogies of the two genes constructed using representative sequences from a variety of species show partial congruence of the major clades, with monophyly of the P. ananatis-P. stewartii homologs; however, the most recent common ancestor of the P. ananatis rhlA gene is shared with Lonsdalea quercina, whereas the P. ananatis rhlB gene is more closely related to the Serratia marcescens homolog (Fig. 8). In the Serratia and Dickeya lineages, the rhlA and rhlB genes are not adjacent to each other as in the P. ananatis isolates.

DISCUSSION

This work explored the genetic factors responsible for grazing resistance and/or virulence of P. ananatis in a D. discoideum pathosystem. The qualitative grazing assay identified four out of 10 isolates as having a resistant phenotype (limited plaque formation), three as having intermediate phenotypes (plaque formation but no sporulation), and three as having a susceptible phenotype (plaque and spore formation) (Fig. 1). Sister isolates P. ananatis BRT175 and P. ananatis 17671 showed phenotypes on the two extremes of the grazing resistance spectrum, supporting the presence of specific genetic factors that contribute to this phenotype. It has been shown that there are differences in the flexible genomic complement of P. ananatis isolates, such that the species appears to have an open genome [START_REF] De Maayer | Analysis of the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and interact with plant, insect and vertebrate hosts[END_REF], which facilitates the introduction of substantial genetic variability and the acquisition of isolate-specific virulence traits. In the case of grazing resistance, the method by which such factors confer the grazingresistant phenotype may be through one of several mechanisms. The plaque formation with no sporulation, for example, may suggest that the bacteria interfere with the D. discoideum life cycle, as shown with Salmonella enterica subsp. Typhimurium [START_REF] Sillo | Salmonella typhimurium is pathogenic for Dictyostelium cells and subverts the starvation response[END_REF]. S. enterica inhibits the D. discoideum starvation response through the type III secretion system [START_REF] Sillo | Salmonella typhimurium is pathogenic for Dictyostelium cells and subverts the starvation response[END_REF], thereby preventing sporulation. We were unable to identify any type III secretion system in P. ananatis BRT175 that might function analogously [START_REF] Smith | Draft genome sequence of the antibiotic-producing epiphytic isolate Pantoea ananatis BRT175[END_REF]. However, isolates within the P. ananatis group may use other secretion systems, which are known to be responsible for producing cytotoxic factors by some bacteria [START_REF] Shyntum | Comparative genomics of type VI secretion systems in strains of Pantoea ananatis from different environments[END_REF][START_REF] Pukatzki | Identification of a conserved bacterial protein secretion system in Vibrio cholerae using the Dictyostelium host model system[END_REF]. It is also possible that bacteria produce antifeeding factors, such that the amoebae starve to death. Serratia marcescens produces serrawettin W2, a surfactant that causes Caenorhabditis elegans to avoid feeding on the bacteria [START_REF] Pradel | Detection and avoidance of a natural product from the pathogenic bacterium Serratia marcescens by Caenorhabditis elegans[END_REF]. Another mechanism to explain the grazing phenotype is the direct killing of the predatory amoebae. A wide variety of toxins and virulence factors are activated in a density-dependent manner through quorum sensing regulation in a number of pathogenic bacteria [START_REF] Antunes | Quorum sensing in bacterial virulence[END_REF][START_REF] Pearson | Roles of Pseudomonas aeruginosa las and rhl quorum-sensing systems in control of elastase and rhamnolipid biosynthesis genes[END_REF][START_REF] Deep | Quorum sensing and bacterial pathogenicity: from molecules to disease[END_REF], which may directly target the amoebae. Several of the 26 candidate loci implicated in grazing resistance were genes involved in biosynthetic pathways that had been shown previously to be involved in virulence in humans and animal model systems (Table 2).

Of the candidate genes identified, the rhamnolipid biosynthesis genes rhlA and rhlB were of particular interest due to their involvement in the production of rhamnolipids and their importance in the virulence of the opportunistic human pathogens P. aeruginosa and Burkholderia spp. [START_REF] Zulianello | Rhamnolipids are virulence factors that promote early infiltration of primary human airway epithelia by Pseudomonas aeruginosa[END_REF][START_REF] Jensen | Rapid necrotic killing of polymorphonuclear leukocytes is caused by quorum-sensing-controlled production of rhamnolipid by Pseudomonas aeruginosa[END_REF][START_REF] Häussler | Structural and functional cellular changes induced by Burkholderia pseudomallei rhamnolipid[END_REF]. Typically, rhlA and rhlB are in an operon [START_REF] Ochsner | Isolation, characterization, and expression in Escherichia coli of the Pseudomonas aeruginosa rhlAB genes encoding a rhamnosyltransferase involved in rhamnolipid biosurfactant synthesis[END_REF][START_REF] Dubeau | Burkholderia thailandensis harbors two identical rhl gene clusters responsible for the biosynthesis of rhamnolipids[END_REF], and this may be the case for P. ananatis BRT175 based on the collinearity and close proximity of the two coding regions in the genome sequence [START_REF] Smith | Draft genome sequence of the antibiotic-producing epiphytic isolate Pantoea ananatis BRT175[END_REF]. In other systems, these genes direct the production of rhamnolipids, which act as wetting agents that enable swarming motility but which also have cytotoxic properties [START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF][START_REF] Jensen | Rapid necrotic killing of polymorphonuclear leukocytes is caused by quorum-sensing-controlled production of rhamnolipid by Pseudomonas aeruginosa[END_REF]. RhlA is necessary for the synthesis of 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAA) [START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF]. RhlB is the rhamnosyltransferase that transfers a dTDP-L-rhamnose to HAA to form a monorhamnolipid, while RhlC can transfer an additional rhamnose sugar to create a dirhamnolipid [START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF][START_REF] Ochsner | Isolation, characterization, and expression in Escherichia coli of the Pseudomonas aeruginosa rhlAB genes encoding a rhamnosyltransferase involved in rhamnolipid biosurfactant synthesis[END_REF][START_REF] Rahim | Cloning and functional characterization of the Pseudomonas aeruginosa rhlC gene that encodes rhamnosyltransferase 2, an enzyme responsible for di-rhamnolipid biosynthesis[END_REF]. Interestingly, these glycolipidic biosurfactants have been reported only anecdotally in cultures of Enterobacteriaceae [START_REF] Lépine | Rhamnolipids: diversity of structures, microbial origins and roles[END_REF]. In P. ananatis BRT175, the products of rhlA and rhlB are responsible for the biosynthesis of a novel, hexose-based surfactant. The lipid moieties primarily consist of hydroxydecanoic (C 10 ) acid, much like the rhamnolipids produced by P. aeruginosa [START_REF] Déziel | Mass spectrometry monitoring of rhamnolipids from a growing culture of Pseudomonas aeruginosa strain 57rp[END_REF], but other congeners that likely consisted of hydroxydodecanoic (C 12 ) or hydroxytetradecanoic (C 14 ) acid were detected. This glycolipid also exhibits emulsification and surface tension reduction properties, which are known characteristics of rhamnolipid biosurfactants [START_REF] Lépine | Rhamnolipids: diversity of structures, microbial origins and roles[END_REF].

The culture medium conditioned by the growth of P. ananatis BRT175 was cytotoxic based on our observations in a plaque assay and trypan blue staining of exposed cells. The cytotoxicity of the wild-type-conditioned medium is consistent with previous work in P. aeruginosa that showed rapid lysis of D. discoideum cells (30) and polymorphonuclear leukocytes (53) after exposure to rhamnolipid extracts. While we did not observe plaque formation after exposure to rhlB::Tn5 strain supernatant, trypan blue staining revealed compromised cells, suggesting the retention of some level of cytotoxicity likely due to the production of the fatty acid component of the biosurfactant by RhlA (Fig. 2A). In P. aeruginosa, the HAA precursor still possesses some surfactant properties [START_REF] Caiazza | Rhamnolipids modulate swarming motility patterns of Pseudomonas aeruginosa[END_REF][START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF], which also explains the capacity of the rhlB::Tn5 strain to still swarm, albeit differentially from wild type (Fig. 2B andC). Rhamnolipid-free and HAAdependent P. aeruginosa swarming can lead to a reduced swarming zone [START_REF] Déziel | rhlA is required for the production of a novel biosurfactant promoting swarming motility in Pseudomonas aeruginosa: 3-(3-hydroxyalkanoyloxy)alkanoic acids (HAAs), the precursors of rhamnolipids[END_REF] and altered motility patterns [START_REF] Caiazza | Rhamnolipids modulate swarming motility patterns of Pseudomonas aeruginosa[END_REF]. Another study examining the influence of rhamnolipids and HAA on swarming motility patterns found that HAA can inhibit dendritic tendril formation and can cause repulsion of cells away from concentrations of HAA [START_REF] Tremblay | Self-produced extracellular stimuli modulate the Pseudomonas aeruginosa swarming motility behaviour[END_REF].

Our analysis of the distribution of the rhlA and rhlB homologs revealed that these two genes are common to all P. ananatis strains analyzed. The qualitative differences in the grazing resistance phenotypes between P. ananatis BRT175, P. ananatis BRT98, P. ananatis LMG20103, P. ananatis LMG5342, P. ananatis Cit30-11, P. ananatis 26SR6, P. ananatis 17671, and P. ananatis 15320 are not attributable solely to the presence of rhlA-rhlB genes, as all 8 genomes carry the genes (Fig. 8). This suggests that differences in regulation, other unidentified genetic factors, or combinations thereof are involved in the P. ananatis-D. discoideum interaction. Nonetheless, the persistence of these genes in the P. ananatis lineage suggests that they play an important role in the biology of this species. Furthermore, the presence of these genes in the sister species P. stewartii could suggest acquisition by the P. ananatis-P. stewartii common ancestor, although additional P. stewartii isolates will need to be surveyed to test this hypothesis. The origin of acquisition is not entirely clear, particularly given that the closest homolog of the P. ananatis-P. stewartii rhlA gene is that from the enteric bacterium L. quercina, whereas the P. ananatis-P. stewartii rhlB gene is closest to the homolog from a different enteric bacterium, S. marcescens (Fig. 8). Because the homologs are not adjacent in the Serratia genome, this could indicate that P. ananatis rhlA and rhlB have come from different sources. Alternatively, the Pantoea homologs may have been transferred to some of the other enteric organisms individually, although there are insufficient representative sequences from this group to determine whether this is the case.

The evolutionary arms race between microorganisms competing for the same environmental niche is thought to be an evolutionary driver for opportunistic pathogens [START_REF] Brüssow | Bacteria between protists and phages: from antipredation strategies to the evolution of pathogenicity[END_REF][START_REF] Matz | Off the hook-how bacteria survive protozoan grazing[END_REF][START_REF] Brown | Evolution of virulence in opportunistic pathogens: generalism, plasticity, and control[END_REF]. This predatory relationship of environmental amoebae with bacteria, for example, may select for traits in prey that confer resistance to phagocytosis but which have the potential for exaptation as virulence factors that function against the cells of the innate immune system [START_REF] Cosson | Pseudomonas aeruginosa virulence analyzed in a Dictyostelium discoideum host system[END_REF][START_REF] Jensen | Rapid necrotic killing of polymorphonuclear leukocytes is caused by quorum-sensing-controlled production of rhamnolipid by Pseudomonas aeruginosa[END_REF][START_REF] Matz | Off the hook-how bacteria survive protozoan grazing[END_REF][START_REF] Adiba | From grazing resistance to pathogenesis: the coincidental evolution of virulence factors[END_REF]. Such determinants may enable those same isolates to exploit additional hosts, effectively expanding their host range to include animals and humans. Unraveling the key genetic factors that enable strains of Pantoea spp. to colonize different hosts will provide important insight into the pathogenic capabilities of this highly versatile group.

MATERIALS AND METHODS

Cell growth and culturing. Overnight cultures of Pantoea and Escherichia coli were grown at 30°C and 37°C, respectively, in Miller LB broth (BD, Franklin Lakes, NJ) with shaking at 220 rpm under appropriate antibiotic selection and conditions (Table 1) (50 g/ml kanamycin, 150 g/ml ampicillin, 50 g/ml rifampin, 38 g/ml chloramphenicol). Dictyostelium discoideum AX2-214 cultures were incubated at 21°C and maintained in petri dishes containing 10 ml HLF1 (Formedium, Hunstanton, United Kingdom) HL5 medium with vitamins and microelements, supplemented with 13.5 g/liter glucose, 300 g/ml streptomycin, and 150 g/ml ampicillin. Cells were passaged every 4 to 6 days following a 100-fold dilution, and fresh stocks were prepared axenically from spores after 3 to 4 weeks of passaging [START_REF] Fey | Protocols for growth and development of Dictyostelium discoideum[END_REF]. Spores were harvested from SM/5 plates (2 g/liter glucose, 2 g/liter Bacto peptone [BD], 0.2 g/liter yeast extract [BD], 0.2 g/liter MgSO 4 •7H 2 O, 1.9 g/liter KH 2 PO 4 , 1.0 g/liter K 2 HPO 4 , 1.5% agar [BD], pH 6.5) with E. coli B/r as a food source [START_REF] Fey | Protocols for growth and development of Dictyostelium discoideum[END_REF]. Cultures for downstream assays were prepared via a 100-to 200-fold dilution of confluent cells in Erlenmeyer flasks containing HL5 at no more than 20% of the maximum volume. The cells were incubated at room temperature and shaken at 180 rpm. Cells were harvested during log-phase growth (typically 3 ϫ 10 6 to 6 ϫ 10 6 cells/ml) by centrifuging 15 to 50 ml of cell culture three times at 500 ϫ g for 5 min and resuspending the pellet each time in Sorensen's buffer with calcium (SorC) (2 g/liter KH 2 HPO 4 , 0.29 g/liter Na 2 HPO 4 , 50 M CaCl 2 , pH 6.0). The final pellet was resuspended in 1 ml of SorC. Cells were enumerated in a hemocytometer and diluted to appropriate concentrations for downstream applications.

Qualitative screen for grazing-resistant isolates. A collection of Pantoea isolates (13) was evaluated for grazing resistance using a modified qualitative D. discoideum assay [START_REF] Froquet | Dictyostelium discoideum: a model host to measure bacterial virulence[END_REF]. Cells from an overnight Pantoea culture were centrifuged at 10,000 ϫ g for 5 min and resuspended in an equal volume of SorC twice. To ensure consistency of inoculations across qualitative grazing plates, bacterial cell densities were standardized to a final optical density at 600 nm (OD 600 ) of 1.0 in SorC by taking absorbance readings from 200-l samples using a BioTek Epoch microplate spectrophotometer (BioTek, Winooski, VT) in 96-well plates (Greiner Bio-One, model 655180; Monroe, NC). Fifty microliters of each bacterial suspension was spotted and allowed to dry onto 24-well plates containing 1.5 ml modified SM agar per well (65) (10 g/liter glucose, 10 g/liter Bacto peptone [BD], 1 g/liter yeast extract [BD], 1 g/liter MgSO 4 •7H 2 O, 1.9 g/liter KH 2 PO 4 , 0.6 g/liter K 2 HPO 4 , 1.5% agar [BD], pH 6.5). Suspensions of D. discoideum were pipetted in 5-l aliquots onto the center of each well at 10,000, 1,000, and 100 total cells. Escherichia coli B/r, which is used as the food source for D. discoideum, served as a control. Isolates were identified as grazing resistant if plaque formation was reduced or absent and sporulation did not occur after exposure to 10,000 D. discoideum cells after 7 days of incubation at 21°C (in darkness). The experiment consisted of two replicates, and experiments were repeated twice with similar results.

Genetic screening and mutant characterization. Mutagenesis was carried out using a triparental mating approach, whereby the RK600 helper plasmid was used to introduce the pBSL118 plasmid, carrying a mini-Tn5 transposon (kanamycin resistance), into P. ananatis BRT175 (rifampin resistance) (Table 1). Aliquots of each overnight culture (1 ml) were pelleted and resuspended in 100 l LB and mixed in a 1:1:1 ratio. This triparental mixture (100 l) was spotted on LB agar plates and incubated overnight at 30°C. A portion of the bacterial lawn was then scraped from the plate with the edge of a sterile spreader and spread on an LB plate containing rifampin and kanamycin. Following incubation for 24 to 48 h at 30°C, individual transposon mutants were picked and grown overnight at 30°C with shaking at 150 rpm in 96-well plates containing 100 l modified SM broth (recipe as described above, without agar, pH 6.0 to 6.4) per well. The following day, 5 l from each well was plated on a corresponding 96-well modified SM agar plate, allowed to dry, and overlaid with 2 l of D. discoideum at 500 cells/l. Plates were monitored for up to 7 days for wells containing susceptible mutants, which were characterized by enhanced plaque formation and/or sporulation. Susceptible mutants were retested in replicates of 8 for confirmation of the phenotype (Table 2).

The location of the transposon insertion in each mutant was determined by inverse PCR [START_REF] Ochman | Genetic applications of an inverse polymerase chain reaction[END_REF]. Briefly, DNA was extracted from each mutant using the E.Z.N.A bacterial DNA kit (Omega Bio-Tek, Norcross, GA) per the manufacturer's directions. About 1 to 2 g of genomic DNA was digested for 2 h at 37°C using HincII or PstI (New England Biolabs, Whitby, Ontario, Canada) in a 20-l reaction volume using 20 units of enzyme and according to the manufacturer's instructions. Ten microliters of heat-inactivated digest was added to 3 l T4 DNA ligase (New England Biolabs), 167 l double-distilled water (ddH 2 O), and 20 l 10ϫ T4 buffer to be incubated for 16 h at 16°C. Ligations were purified using the E.Z.N.A Cycle Pure kit (Omega Bio-Tek) and eluted into a 30-l volume. Typically, 5 l of purified ligation had sufficient template to be amplified in a 25-to 50-l PCR mixture using EconoTaq DNA polymerase (Lucigen Corp., Middleton, WI) per the manufacturer's instructions, using the primers NPTϩ772 (5=-TTCGCAGCGCATCG CCTTCTATC-3=) and NPT-41 (5=-AGCCGAATAGCCTCTCCACCCAAG-3=). Cycling conditions were one denaturation cycle of 94°C for 120 s, followed by 40 cycles of 94°C for 30 s, 63°C for 30 s, and 72°C for 240 s, and one polymerization cycle of 72°C for 300 s. Amplification was verified by gel electrophoresis, and single amplicons were excised and gel purified from any reactions with multiple amplicons using the E.Z.N.A gel extraction kit (Omega Bio-Tek) per the manufacturer's instructions. Amplicons were sequenced by Génome Québec (Montréal, Québec, Canada). Insertion sites were confirmed by BLAST analysis against the annotated P. ananatis BRT175 genome [START_REF] Smith | Draft genome sequence of the antibiotic-producing epiphytic isolate Pantoea ananatis BRT175[END_REF].

rhlA-rhlB mutant phenotypic characterization assays. To determine the relative differences in grazing susceptibility caused by the interruption of rhlA and rhlB, cultures of P. ananatis BRT175, the rhlA::Tn5 strain (mutant 28C8), and the rhlB::Tn5 strain (mutant 32C5) were grown overnight at 30°C in modified SM broth. An 0.5-ml sample of each strain culture was added to 5 ml of fresh modified SM broth and incubated for another 40 min at 30°C to dilute the cultures and increase the proportion of live cells. Cell densities were standardized to an OD 600 of ~0.125 from 200-l samples using the plate spectrophotometer in 96-well plates (as described above). D. discoideum cells were diluted half-fold eight times starting at 1,600 cells/l. A 12.5-l volume of bacteria was spotted on modified SM agar and allowed to dry. Five microliters of each of the dilution series of D. discoideum cells was then placed on separate spots in order of decreasing concentration. Experiments were performed twice with two replicates each.

To create conditioned culture medium for the cytotoxicity assays, P. ananatis BRT175, P. ananatis BRT175 rhlA::Tn5 (mutant 28C8), and P. ananatis BRT175 rhlB::Tn5 (mutant 32C5) were each grown at 21°C for 6 days with shaking at 220 rpm in modified M9 medium (2 mM MgSO 4 , 20 g/liter glucose, 0.1 mM CaCl 2 , 1/5 dilution of 5ϫ M9 salts [64 g/liter Na 2 HPO 4 , 15 g/liter KH 2 PO 4 , 2.5 g/liter NaCl, 13.78 g/liter NaNO 3 ]). Sodium nitrate was substituted for ammonium chloride as it has been shown to be a preferred nitrogen source in Pseudomonas aeruginosa for surfactant production [START_REF] Guerra-Santos | Pseudomonas aeruginosa biosurfactant production in continuous culture with glucose as carbon source[END_REF]. Filtration was performed to retain products exported by the bacteria while excluding bacterial cells. Cultures were centrifuged, the bacterial pellet was discarded, and supernatants were filter sterilized using 0.2-to 0.22-m polyether sulfone (PES) bottle top filters. The supernatants and control media were adjusted to pH 6.52 Ϯ 0.02 and resterilized using 0.2-to 0.22-m PES syringe filters to standardize pH values for downstream assays. Supernatants were kept at 4°C between experiments.

These supernatants were then used in PFU assays to assess D. discoideum cell viability after exposure to conditioned culture medium. Overnight cultures of E. coli B/r were centrifuged twice for 2 min at 12,000 ϫ g and resuspended in 1 ml SorC each time. The final E. coli suspension was then diluted to an OD 600 of ~0.1 (200 l, 96-well plate). The D. discoideum cells (harvested as described above) were diluted to 15 cells/l in SorC. Aliquots of 90 l of modified M9 culture medium conditioned by P. ananatis BRT175, P. ananatis BRT175 rhlA::Tn5 (mutant 28C8), or P. ananatis BRT175 rhlB::Tn5 (mutant 32C5) or unconditioned culture medium as the control were prepared. Ten microliters of amoebae was then added to the 90 l of medium and incubated for 25 min at 21°C. Three hundred microliters of the prepared E. coli suspension was added after incubation. The entire volume was pipetted on a 60-mm petri dish containing SM/5 medium and dried while on a rotary shaker to help evenly distribute the liquid. The plates were incubated at 21°C, and plaque counts were taken after 3 to 4 days. Statistical comparisons were performed using the Kruskal-Wallis test and Dunn's test [START_REF] Dinno | Test: Dunn's test of multiple comparisons using rank sums[END_REF] for pairwise comparisons

FIG 1

 1 FIG 1 Qualitative assay of resistance of P. ananatis isolates to D. discoideum grazing. Ten thousand, 1,000, and 100 Dictyostelium discoideum AX2-214 cells were applied to dried bacterial lawns and monitored for 7 days for plaque formation and sporulation. E. coli B/r is used as the food source for D. discoideum and was included as a reference. The buffer SorC was used for the no-amoeba control.

FIG 2 FIG 3

 23 FIG 2 Grazing and swarming phenotypes of Pantoea ananatis BRT175 biosurfactant mutants. The predicted operon is shown at the top for each strain, with a red "X" indicating the disrupted gene. (A) Grazing of P. ananatis BRT175 at different cell densities (250 to 8,000 cells) of D. discoideum AX2-214 after a 7-day incubation. WT, wild type. (B) Swarming after a 24-h incubation on 0.5% modified SM agar. (C) Swarming after 48 h on 0.5% modified M9 agar.

FIG 4 FIG 5

 45 FIG 4 Triple-quadrupole ESI-MS spectra of P. ananatis BRT175 culture extracts obtained in negative ionization mode. Pseudomolecular ions [M-H] ؊ are observed at m/z 519, 547, and 575 for the wild-type strain (a), which are absent in culture extracts of the rhlA::Tn5 strain (mutant 28C8) (b). The y axis shows relative abundance considering the highest ion as 100%; the x axis shows m/z for each ion. The pseudomolecular ion at m/z 271 corresponds to 16hydroxyhexadecanoic acid, which was added as an internal standard.

FIG 6 FIG 7

 67 FIG 6 Swarming motility patterns of wild-type P. ananatis strains and E. coli B/r. All images represent the motility patterns observed after incubation for 24 h at 21°C following a single point inoculation on 0.5% modified SM agar. B7-A and B7-B represent two different swarming phenotypes of P. ananatis B7.

FIG 8

 8 FIG 8 Phylogenetic trees of RhlA and RhlB homologs. Radial (unrooted) neighbor-joining phylogenies of representative RhlA (A) and RhlB (B) homologs, constructed using the Jones-Taylor-Thornton amino acid model, with complete gap deletion. Only bootstrap values greater than 70% are shown. In addition to the P. ananatis strains used in this study, other representative taxa included Burkholderia cenocepacia H111 (CDN64069), Burkholderia glumae BGR1 (ACR31008), Burkholderia pseudomallei 1106a (ABN94800), Dickeya dadantii 3937 (YP_003882762), Lonsdalea quercina (WP_026742016), Pantoea stewartii subsp. stewartii DC283 (EHU02365), Pseudomonas aeruginosa PAO1 (NP_252169), and Serratia marcescens FGI94 (AGB82844).

TABLE 1 Bacterial and eukaryotic strains used in this study Species and strain Selection Source or reference

 1

	Pantoea ananatis
	15320

a International Collection of Microorganisms from Plants. b Steven Lindow, University of California, Berkeley. c Gwyn Beattie, Iowa State University. d Teresa Coutinho, University of Pretoria.

TABLE 2

 2 Locations of Tn5 transposon gene insertions in grazing-susceptible mutants d

Grazing phenotype and locus a Gene Predicted function Swarming Mutant designation(s)

	Grazing susceptible
	L585_12500	ompR	Transcriptional regulator	Y	28H12
	L585_05285	cpxA	Histidine kinase	Y	35D8, 18A11
	L585_21390	phzR/luxR sdiA	[Intergenic space-upstream]	Y	10E5
			transcriptional regulator
	L585_04860	ptsN	PTS sugar transporter subunit IIA	Y	19E7
	L585_22810	nagC/nagD	Transcriptional regulator (polar	Y	26A5
			mutation of nagC)
	L585_16630	dsbB	Disulfide bond formation protein	Y	26H9
	L585_21750	serC	3-Phosphoserine/	Y	28G12
			phosphohydroxythreonine
			aminotransferase
	L585_20040	srmB	RNA helicase	N	36D8
	L585_10945	yagG	[Intergenic space-upstream]	Y	31C1
			uncharacterized member of the
			GPH family of galactose-pentose-
			hexuronide transporters
			(symporter)
	L585_00065	motA	Flagellar motor protein	N	36E1
	L585_00075	flhD	[Intergenic space-upstream]	N	42A7, 42H1 b
			transcriptional regulator and
			flagellar apparatus operon
	L585_10950	eanI	Acylhomoserine lactone synthase	Y	22A12
	Enhanced grazing susceptible
	L585_10305		Hypothetical protein (rrf2 domain,	Y	16A5, 16A2, b 16A1, b 16H12 b
			badM-like transcriptional
			regulator)
	L585_04880	arcB	[Intergenic space-downstream]	Y	24A2, 24A5 c
			aerobic respiration control sensor
			protein
	L585_16795	prc	Carboxy-terminal protease	Y	14G9
	L585_21810	trxB	Thioredoxin reductase	Y	39D5
	L585_03130	rhlB	Rhamnosyltransferase I, subunit B	Y	32C5, 24H12, 25E4, 40C2
	L585_21385	phzI	Autoinducer synthase	Y	25E1, 26F4 b
	L585_03125	rhlA	Rhamnosyltransferase I, subunit A	N	28C8
	L585_04515	pyrB	Aspartate carbamoyltransferase	Y	36A4
			catalytic subunit
	L585_03535	carB	Carbamoyl phosphate synthase	Y	24G12
			large subunit
	L585_19770	guaB	IMP dehydrogenase	Y	4H11
	L585_21595	pyrD	Dihydroorotate dehydrogenase	Y	28H8
	L585_04660	pnp	Polynucleotide phosphorylase/	N	30D8
			polyadenylase
	L585_15360	prfC	Peptide chain release factor 3	N	8F6
	L585_21170	pyrC	Dihydroorotase	Y	35F10

a Mutants exhibiting plaque formation were scored as grazing susceptible, whereas mutants in which 4 out of 8 test wells exhibited spore formation were classified as enhanced grazing susceptible. The NCBI accession number for the draft annotated whole-genome shotgun sequence is ASJH01000000. b Mutant not tested for swarming capability. c Mutant did not swarm. d Abbreviations: PTS, phosphotransferase; Y, yes; N, no.

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The wild-type (WT) extract exhibits emulsifying activity, whereas the extract from the rhlA::Tn5 (mutant 28C8) culture lacks any emulsifying activity, with the height of the hydrophobic phase being identical to the negative control (reagent-grade water). Smith et al. Volume 1 Issue 1 e00075-15 msphere.asm.org 6 on August 25, 2016 by guest http://msphere.asm.org/ Downloaded from

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ACKNOWLEDGMENTS

We acknowledge the kind contributions of Steven Lindow, Teresa Coutinho, Gwyn Beattie, and the International Collection of Microorganisms from Plants. We thank Andrew Cameron, Tzu-Chiao Chao, Dae-Yeon Suh, Lucas Robinson, Alyssa Walterson, and Morgan Kirzinger for their valuable input and feedback on the manuscript. We thank the dictyBase organization for being an invaluable resource and for providing the D. discoideum strain used in this work. This work was funded by Discovery Grants from the Natural Sciences and Engineering Research Council of Canada to J.S. and E.D., a Leaders Opportunity Fund (no. 28591) from the Canada Foundation for Innovation to J.S., and the University of Regina Faculty of Science. D.D.N.S. was supported by a Canadian Institutes of Health Research Master's Award and University of Regina Faculty of Graduate Studies and Research scholarships. E.D. holds the Canada Research Chair in Sociomicrobiology.

of the mean plaque counts from three independent experiments between the control and each treatment.

Cell viability was assessed using a trypan blue viability assay. This was performed by resuspending pelleted D. discoideum cells in 125 l of filtered conditioned culture medium from either P. ananatis BRT175, P. ananatis BRT175 rhlA::Tn5, or P. ananatis BRT175 rhlB::Tn5, with unconditioned modified M9 medium as a control. A stock of D. discoideum cells was prepared at ~4,000 cells/l for creating 250-l aliquots for each replicate. The cells were centrifuged for 5 min at 500 ϫ g, and the supernatant was discarded. D. discoideum cells were resuspended and exposed to the conditioned culture medium and control for a minimum of 20 min at room temperature. One hundred twenty-five microliters of 0.4% trypan blue was added, and total and unstained cells were enumerated by counting 25 of the 0.040-mm 2 squares on a hemocytometer. Each treatment was performed in triplicate. Most cells in the wild-typeconditioned culture medium treatment could not be enumerated as they were reduced to cellular debris. Statistical comparisons were performed using the Kruskal-Wallis test and Dunn's test [START_REF] Dinno | Test: Dunn's test of multiple comparisons using rank sums[END_REF] for pairwise comparisons of the mean viability counts from three independent experiments between the control and each treatment.

Swarming trials were performed by inoculating a single colony in the center of a modified SM agar plate containing 0.5% (wt/vol) agar and incubating it at 21°C for 24 h. P. ananatis BRT175 mutants were monitored for up to 48 h for swarming. Swarming assays were also performed on modified M9 agar plates containing 0.5% (wt/vol) agar by centrifuging cultures grown at 30°C and resuspending the bacterial pellet in the medium to an OD 600 of ~0.4 (200 l, 96-well plate). Ten microliters of concentrated culture was applied to the center of the agar plates and incubated at 21°C for 48 h. All images in this study were captured using an Epson Perfection V330 photo scanner at 600 to 1,200 dots per inch (DPI).

Biosurfactant production and extraction. To characterize the structure of the biosurfactant, solvent extractions were performed on culture medium conditioned with either P. ananatis BRT175 or P. ananatis BRT175 rhlA::Tn5 (mutant 28C8). Cultures were grown in 200 ml MSM supplemented with 20 g/liter glucose and 2 g/liter NaNO 3 in 1-liter Erlenmeyer flasks and incubated at 30°C with shaking at 250 rpm. MSM had the following composition: 2.5 g/liter KH 2 PO 4 , 1.5 g/liter K 2 HPO 4 , 0. After 6 days of incubation, the cells were pelleted by centrifugation at 8,000 ϫ g for 15 min, and the resulting supernatant was acidified with 1 N HCl to a pH of 2 to 3. The supernatant was then extracted twice with equal volumes of ethyl acetate. The organic fractions were then pooled and rotary evaporated, which yielded a crude extract containing the biosurfactant product. The final crude extract from 200 ml of culture was dissolved in 25 ml of MilliQ water to give an 8-fold-concentrated extract solution, which was subsequently used for further analysis.

Liquid chromatography-mass spectrometry analyses. The culture extracts of P. ananatis BRT175 and P. ananatis BRT175 rhlA::Tn5 (mutant 28C8) were dissolved in methanol, and 16-hydroxyhexadecanoic acid was added as an internal standard. Samples were analyzed by high-performance liquid chromatography (HPLC; Waters 2795, Mississauga, Ontario, Canada) equipped with a 6.4-by 150-mm Agilent Zorbax Eclipse XDB-C 8 reverse-phase column (particle size, 5 mm) using a water-acetonitrile gradient with a constant 2 mmol • liter Ϫ1 concentration of ammonium acetate [START_REF] Dubeau | Burkholderia thailandensis harbors two identical rhl gene clusters responsible for the biosynthesis of rhamnolipids[END_REF]. The detector was a mass spectrometer (Quattro Premier XE; Waters). Analyses were performed in negative electrospray ionization (ESIϪ), supplemented by the multiple-reaction monitoring (MRM) mode [START_REF] Lépine | Liquid chromatography/ mass spectrometry for the identification and quantification of rhamnolipids[END_REF].

Surface tension and emulsification assays. The surface tension of the extract solutions of P. ananatis BRT175 and P. ananatis BRT175 rhlA::Tn5 (mutant 28C8) strains was measured by the du Noüy ring method using a Fisher tensiometer model 20 (Fisher Scientific, Pittsburgh, PA). The instrument was calibrated against water, and measurements were performed in triplicate at room temperature. The emulsifying activity of culture extracts was tested against n-hexadecane. Three-milliliter aliquots of extract solutions of P. ananatis BRT175 and P. ananatis BRT175 rhlA::Tn5 (mutant 28C8) were mixed with 2 ml of n-hexadecane and vortexed at high speed for 2 min. The emulsion was observed after letting the tubes stand at room temperature for 60 min. The lipophilic dye Sudan black was added to the n-hexadecane to increase contrast.

Phylogenetic analyses. Homologs of the P. ananatis BRT175 rhlA and rhlB genes were identified using BLAST against both complete and draft genome sequences available at NCBI. Alignments were made using ClustalX2 with default parameters using iteration after each alignment step. Neighborjoining phylogenies were constructed using MEGA6 (70) with the Jones-Taylor-Thornton amino acid model, complete gap deletion, and 500 bootstrap replicates.

Growth comparisons of P. ananatis BRT175 mutants. P. ananatis BRT175 and Tn5 mutants were inoculated into 10 ml of modified SM broth in a 15-ml conical tube, which was then tightly sealed and incubated overnight at 30°C without shaking [START_REF] Hall | Growth rates made easy[END_REF]. Overnight cultures were standardized to an OD 600 of ~0.2 (300 l, 96-well plate). Of the standardized culture, 50 l was added to 250 l of modified SM broth in a 96-well plate to be grown at 30°C for 18 h with continuous medium shaking, and OD 600 readings were taken every 20 min in a BioTek Synergy HT plate reader. Each experiment was performed three times independently with 6 replicates per strain. Nine mutants were tested per plate, with P. ananatis BRT175 being used as a reference control for each set of mutants. Only one mutant per affected gene was tested (Table 2). Figure S1 in the supplemental material was generated in R using ggplot2 [START_REF] Core | R: a language and environment for statistical computing[END_REF][START_REF] Wickham | ggplot2: elegant graphics for data analysis[END_REF].

Nucleotide sequence accession numbers. The rhlA and rhlB genes from P. ananatis 15320, BRT98, Cit30-11, 26SR6, and 17671 have been deposited in GenBank under accession numbers KM819089, KM819090, KM819091, KM819092, KT455465, KT455466, KT455467, KT455468, KT455469, and KT455470.

P. ananatis Grazing


Benjamin Baron
email: bbaron@npa.lip6.fr

Prométhée Spathis
email: spathis@npa.lip6.fr

Marcelo Dias De Amorim

Mostafa Ammar
email: ammar@cc.gatech.edu

Cloud Storage for Mobile Users Using Pre-Positioned Storage Facilities

Keywords: Vehicular cloud storage and sharing system, opportunistic networks, placement algorithm

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INTRODUCTION

Cloud storage services have shown their great potential given the popularity of services such as Dropbox or Google Drive. Mobile users accessing such services through wireless networks including cellular 4G LTE or Wi-Fi are often faced with high cost, low bandwidth, and limited coverage.

In this paper, we design a cloud-like file storage and sharing system specifically targeting mobile users. The system deploys a collection of strategically located pre-positioned data storage facilities acting as file repositories. Mobile users upload files that they would like to archive or share, * This author's work was supported in part by NSF grants NETS 1409589 and NETS 1161879.

or retrieve files uploaded by them or by other users from this set of repositories as they meet them. We leverage the existing mobility of the initial uploaders and subsequent users to limit the dependency of our system on conventional infrastructure-based networks.

We consider techniques that use the mobility of either the initial file uploader or subsequent users to replicate files. The distinctive feature of our approach lies in the opportunistic use of mobile users as data shuttles between the file repositories. Copies of the files are transferred to users when in the vicinity of a repository and transported to other repositories along user routes. To increase the likelihood of replication, copies of the user files can be loaded on multiple users traveling among the repositories.

One of the main challenges in implementing our system is handling user requests to either store a file or retrieve one in a timely fashion. A request is delayed depending on how close the user is from the nearest repository. Each request comes with a deadline indicating when it expires. Past the deadline, the request is considered as failed. Our goal in the design of the system is to bound the request deadline to minimize the failure rate of requests.

Two aspects of the system can have a significant effect on the request failure rate. The first is the degree of replication for files in the repository. The second is the number and placement of file repositories in the mobile environment. Our work considers both of these challenges.

We propose an algorithm to place the repositories at strategic locations where they can capture a maximum number of user requests before they expire. To enable the distribution strategy of the user files across the repositories, the placement algorithm also takes into account the flows of users traveling between the repositories. The placement of the repositories then faces two different objectives. On the one hand, the repositories must be spaced far enough from one another to avoid starving user requests and limit the overlap of user requests they serve. On the other hand, the repositories must be close enough and well connected to one another by the movements of the users to create a connected network that enables the distribution of user files in all repositories. We instantiate our system using bus stops as potential locations for repositories and buses as mobile users. Buses also behave as data shuttles between repositories.

The repositories we use to build our system are somehow similar to throwboxes [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] and offloading spots [START_REF] Baron | Offloading massive data onto passenger vehicles: Topology simplification and traffic assignment[END_REF]. Repositories also enable data transfers by combining the trajectories of multiple mobile users. The mobile users that we use to distribute the files across the repositories act as data MULEs [START_REF] Shah | Data mules: Modeling and analysis of a three-tier architecture for sparse sensor networks[END_REF]. In our system, the repositories store files in a distributed manner and help share them with mobile users. Content storage and retrieval was also an issue studied in the context of Delay-Tolerant Networking (DTN) [START_REF] Fall | A delay-tolerant network architecture for challenged internets[END_REF]. Examples include TierStore [START_REF] Demmer | Tierstore: A distributed filesystem for challenged networks in developing regions[END_REF] which is a Network File System that relies on very low latency links that intermittently connect the repositories. This makes TierStore well suited in the context of DTNs. Ott and Pitkänen [START_REF] Ott | Dtn-based content storage and retrieval[END_REF] proposed a system based on repositories to cache user content, thus decreasing the latency when retrieving content. However, both of these approaches do not study the impact of a placement of storage repositories that can guarantee the availability and distribution of files.

To summarize, our contributions are the following:

• File distribution. We leverage the users traveling between repositories to distribute files. With copies of the files available at multiple repositories, user requests are more likely to be successful.

• Repository placement. We design an algorithm that places a target number of repositories over a geographical area to satisfy a maximum number of user requests. The placement of the repositories depends on the mobility patterns of mobile nodes, the deadline for user requests, and the vehicle flows connecting the repositories together.

The rest of this paper is organized as follows. We describe the problem statement in Section 2. In Section 3, we detail the algorithm to place the repositories. Finally, we evaluate our cloud storage system with traces of San Francisco buses in Section 4 and conclude in Section 5.

PROBLEM STATEMENT

We consider a geographical area with n mobile users that move according to a known mobility pattern and m fixed repositories placed over the geographical area according to a placement strategy. Both are equipped with wireless capabilities and with local storage to store user files. We enable communications only between mobile users and repositories through wireless interfaces (e.g., IEEE 802.11).

Repositories

The repositories are stationary and located at specific locations. They feature high availability, large storage and fast wireless transmission capabilities to handle large data rates in parallel with multiple mobile users. We assume a central controller is in charge of monitoring the files available at each repository. Whenever a repository receives a new file from a user, it notifies the controller of the availability of this file. Likewise, the mobile users can be notified of the availability of the files through the controller. We assume that the communications between the controller and the repositories and mobile users are handled by an inexpensive control channel (e.g., a cellular connection).

User requests

There are two types of user requests: put requests to store user files and get requests to retrieve them. All requests have an associated deadline. Once a mobile user generates a request, the request becomes pending for the user until they encounter a repository. When in the transmission range of the repository, the user seamlessly transfers all of its pending requests to the repository. put request. When a mobile user generates a put request, the user waits to be in the transmission range of the first repository it encounters. On an encounter with a repository, the user transfers the put request message along with the file. Once the file is received, the repository updates its local storage and notifies the availability of the file to the central controller. We define the two behaviors of mobile users when they have a put request to execute:

• "First" put policy: Mobile users immediately delete the request once they transferred it to the first repository they encounter or if its deadline expires, whichever occurs first.

• "All" put policy: Mobile users delete the request once the deadline associated with the request has expired. This allows the users to potentially replicate the files to all repositories they encounter from the moment the request is generated to the moment it expires.

get request. Users share the files they store on the repositories with other users. That is, any user can generate a get request to retrieve any available file. The user then transmits the get request to repositories it meets until the request is satisfied or until its deadline expires, whichever occurs first. In turn, the repository processes the request and transfers the requested file to the mobile user if the file is available in the repository's local storage. Otherwise, the repository notifies the mobile user that the requested file is not available. The mobile user will then try to retrieve the requested file from the next repository it will encounter. If the mobile user does not encounter any repository with a copy of the requested file before the request's deadline expires, the request fails.

File distribution with user mobility

We incorporate a file distribution strategy that exploits user mobility to move copy files among repositories. Increased file distribution will reduce get failure rates. To accomplish this, we introduce sync requests for the files that need distribution. Repositories generate sync requests once files are stored by their initial uploader, following put requests. A sync request results in transferring copies of a file from the repository to passing mobile users in charge of distributing these copies to repositories along their trajectories. A later encountered repository updates its local storage with the corresponding file and notifies the central controller of the new availability of the file. If the file is yet to be available in every repository, the new repository starts distribution the file it just received by generating corresponding sync requests. Otherwise, the central controller informs the repositories of the distribution completion.

The three types of requests put, get, and sync are shown in Figure 1. In this figure, the mobile nodes are buses that aggregate requests from the passengers riding the bus. The first mobile user on the left carries three requests: get for file A, sync for file B, and put for file C. The repository, which only has a local copy of file A, executes all the requests and adds files B and C to its local storage. When a subsequent mobile user encounters the repository, the repository generates sync requests and transfers them to the mobile node, along with the copies of the files. The mobile node then carries the sync requests to the next repository it encounters.

Performance objectives

We consider the following metrics to evaluate the performance of our storage and sharing system:

• Request success ratio. We aim to maximize the successes and minimize the failures of user requests. A put or get request is successful if it completes before its deadline expires. The success ratio is the number of successful requests divided by the number of all requests issued during the time period of interest.

• File distribution duration. File distribution relies on the movements of the mobile nodes to distribute copies of files across the repositories. The distribution duration of a file is the time it takes for it to be available in all the repositories of the system. The repository placement algorithm takes this metric into account when allocating the location of the repositories to minimize the distribution duration of the files.

REPOSITORY PLACEMENT

We detail the repository placement algorithm that determines the locations of a target number of repositories for a given user request deadline. The goals of the placement algorithm are twofold: (i) determine locations such that the allocated repositories serve the maximum number of user requests before they expire and (ii) connect the repositories together by the mobile users' movements to create the file distribution network. The goals of the placement algorithm are represented in Figure 2 in the case of a bus transit system. The bottom layer shows the trajectories of the buses in the Financial District of San Francisco, with allocated bus stops. Each bus trajectory is represented by a color and a width indicating the frequency of buses. The middle layer shows the discretized demands generated by the bus passengers. This layer shows the demands that are allocated to the repositories placed at the bus stops. Finally, the top layer shows a logical graph where nodes correspond to allocated repositories and edges to the flows of buses running between two repositories. As in the bottom layer, the width of the edges corresponds to the frequencies of buses.

We derive the placement of the repositories from a set cover problem, in particular, the Maximal Covering Location Problem [START_REF] Church | The maximal covering location problem[END_REF]. Given a set of candidate locations for the repositories, the placement problem consists of selecting the candidate locations that maximize the success ratio of the requests issued by the users. This problem was shown to be NP-Hard [START_REF] Megiddo | The maximum coverage location problem[END_REF], so we adapt known heuristics to solve it. To this end, we consider the Greedy Adding with Substitution (GAS) heuristic [START_REF] Church | The maximal covering location problem[END_REF] that determines the optimal locations for each iteration of the algorithm.

Candidate and demand locations

The placement algorithm takes both a set C of candidate locations where the repositories can be placed, as well as a set D of demand locations to be served by the allocated repositories. The candidate and demand locations refer to geographical places (typically circles and square cells) visited by the user trajectories. The algorithm outputs a set A of allocated candidate locations for the repositories.

Demands. Users can generate a request at any time. Each successive location visited by the trajectories of the users is a demand location with equal probability of being the starting location of a user request. To this end, we divide the geographical area into a grid of cells of a given size (e.g., 100 m × 100 m). Each cell aggregates the discretized user trajectories that go through the cell. The greater the number of trajectory aggregates, the higher the probability for a cell to be the starting location of user requests.

Candidates. Candidate locations for the repositories correspond to relevant locations the mobile users will often visit for long periods of time, allowing the transfer of significant amounts of data. For instance, candidate locations may be road intersections, or bus stops (e.g., in the case of a bus transit system). In the evaluation section, we use available data from bus transit systems and consider bus stops as candidates for the location allocation of the repositories.

To determine the locations of the repositories, we quantify the relations between two locations l1 and l2 (either a demand or candidate location) by computing the following spatial statistics:

• The mean visit frequency f (l1, l2) of mobile users that visited location l1, then location l2.

• The median inter-visit duration v(l1, l2) of two consecutive visits of mobile users at location l1 that visited location l2 later in during their trajectory.

• The median travel time t(l1, l2) of the time it takes for a mobile user to travel from location l1 to location l2.

We then measure the weight w(l1, l2) of a pair of locations (l1, l2) using the visit frequency f (l1, l2) and the median inter-visit duration v(l1, l2) as follows:

w(l1, l2) = f (l1, l2) v(l1, l2) •
In the following, we denote by {w l 1 l 2 } the weight matrix such that w l 1 l 2 = w(l1, and by {t l 1 l 2 } the travel time matrix such that t l 1 l 2 = t(l1, l2). Relations between demands and candidates. The deadline of the user requests imposes a bound δ on travel time t(d, c) between a demand location d a candidate location c. A demand location d is allocated to a candidate point c if the demand is within the bound δ and the w dc is not null (i.e., there are flows of mobile users that travel from the demand to each of the candidates). The goal is maximize the sum of the weights of the demands d ∈ D allocated to a candidate c:

d∈D {w dc | t dc ≤ dc }. Note that a single demand cell can allocated to multiple candidates, each within the given bound δ with non-null weights. Relations between pairs of candidates. We characterize the connectivity between two in terms of flows of mobile users travelling from c1 and c2 with both weights wc 1 c 2 and wc 2 c 1 . each candidate, we maximize the sum of the weights between this candidate c and the chosen candidates k ∈ A:

k∈A w kc + ck .

Location allocation

The algorithm derives from a greedy-adding with substitution (GAS) heuristic proposed to solve the Maximal Covering Location Problem [START_REF] Church | The maximal covering location problem[END_REF]. For each candidate location, we divide the iterations into two parts: selection and tion. Selection. We first pre-select the set of candidates from the set of remaining candidates such that candidate is connected to the chosen repositories by the flows of mobile users. This pre-selection is necessary, as it guarantees the creation of the distribution and increases the availability of files. From these pre-selected candidates, we choose the candidate that maximizes the sum of demand weights within the bound δ we defined previously. Substitution. The second part of the algorithm goes back on the previous iterations and examines each allocated candidate and tries to find a better candidate that maximizes the demand weights, while guaranteeing that the new candidate will be connected to the chosen candidates. If a better candidate is found, it replaces the candidate under examination. The substitution part allows to replace the candidates allocated in the early iterations that are not justified in the later iterations due to subsequent allocated candidates.

We adapt the algorithm for our system as follows. The first candidate is chosen such that it maximizes the sum of demand weights within the bound δ. Note that, since the demand weights are maximized for this candidate, the candidate is often visited by mobile users, making it a good intermediary node to be connected to the other candidates by the flows of mobile users. There is no substitution part, as no other candidate was already chosen. In our implementation, once a candidate is chosen, we remove all the candidates in the vicinity of the chosen candidate (in terms of travel time and distance from the chosen candidate, e.g., half the deadline and the distance corresponding to this duration with average speed). This allows us to better spread the repositories over the geographic area and avoids cluttering denser regions with too many repositories.

EVALUATION

We run our evaluation in two parts. The first part corresponds to the allocation of a given number of repositories for the given deadline. The second part is the simulation of the system with the repositories placed in the area. Mobility model for public transit vehicles. Firstly, we simulated the movements of the San Francisco MUNI buses 1 using the ONE simulator [START_REF] Keränen | The one simulator for dtn protocol evaluation[END_REF]. The ONE simulator is a time-discrete and event-based simulator of delay-tolerant networks. We used the MapRouteMovement mobility model implemented in ONE to simulate the movements of mobile nodes and their stops on a street map. This mobility model is particularly well suited to simulate the movement of buses that are part of a transit system. We derive the movements of the buses from GTFS (General Transit Feed Specification) 2 feeds given by the MUNI transit authority that gather the buses' schedules. We develop generic tools to convert the GTFS feeds into a collection of MapRouteMovement mobility models compatible with the ONE format. Repository placement. Secondly, we developed a framework to determine the locations of the repositories. The framework implements the algorithm described in Section 3. It takes the bus movements we derived from the GTFS feeds. We divide the geographical area into a grid of cells of size 100m × 100m. We take bus stops as candidates to host a repository, since the buses stop for a long enough duration to transfer large amounts of data. The framework then allocates the locations of the target number of repositories among the candidate locations, given user request deadline. We represented in Figure 3a the output allocation of 15 repositories' locations out of the 4,590 bus stops in San Francisco using the movements of the MUNI buses. In this figure, we show a Getis Ord-G hotspot analysis of the spatially significant bus stop candidates with regards to the visit frequencies of the buses in their vicinity [START_REF] Getis | The analysis of spatial association by use of distance statistics[END_REF].

After running the tools to convert the GTFS feed, we obtained the movements of 493 buses running on 130 different trajectories, which represents the traffic of buses running between 10am and 4pm on a typical weekday. Both the mobile users and the repositories are equipped with WiFi network interfaces with a range of 250m. We ignore wireless interference and assume enough wireless capacity to accommodate the full exchange of files between the repositories and the mobile users. The candidate locations are the bus stops given by the GTFS bus feed projected onto the street map. The wait time of the buses at the bus stops is picked at random between 10 seconds and 30 seconds. The mobile users send requests independently every 10 minutes following a Poisson distribution, without any assumptions on the popularity and geographical locality of the files. We assume the mobile users generate the put and get requests as follows: 10% of the requests are put requests and 90% of the requests are get requests. The simulation duration is 20,000 seconds. Success ratio. As a first step, we perform the simulations to evaluate the benefits of the put policies and the distribution network in the success ratio of the user requests. To (a) Allocation of the repositories. The color variations of the candidate locations represent hotspots resulting from the Getis Ord-G spatial analysis with regard to the bus visit frequencies locations [START_REF] Getis | The analysis of spatial association by use of distance statistics[END_REF]. 58 [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] 36 [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] 54 ( 12) 32 ( 5) 58 ( 8) 67 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 36 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 41 ( 12) 0 (0) 44 ( 7) 78 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 96 ( 20) 61 ( 6)

0 (0) 50 (11) 41 (8) 28 (6) 44 (12) 33 (4) 28 (12) 52 (6) 70 (20) 31 (4) 19 (3) 46 (5) 50 (6) 55 (7) 51 (7) 49 (11) 0 (0) 39 (6) 28 (9) 43 (11) 61 (8) 23 (8) 50 (7) 95 (11) 52 (12) 40 (6) 15 (4) 21 (5) 51 (8) 9 (3) 40 (8) 40 (6) 0 (0) 59 (6) 72 (9) 67 (6) 54 (6) 14 (4) 61 (13) 40 (8) 49 (5) 23 (5) 39 (6) 63 (9) 28 (5) 27 (5) 26 (9) 59 (6) 0 (0) 12 (9) 36 (7) 9 (7
19 [START_REF] Keränen | The one simulator for dtn protocol evaluation[END_REF] 46 ( 9) 50 ( 7) 69 ( 12) 52 ( 9) 28 ( 12) 24 ( 9) 55 (

53 [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] 38 ( 9) 50 ( 6) 98 ( 14) 45 ( 6) 33 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 16 ( 5)

0 (0) 57 (9) 9 (3)
60 ( 12) 50 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 63 [START_REF] Ott | Dtn-based content storage and retrieval[END_REF] 30 ( 12) 36 ( 12) 67 ( 12) 39 ( 12) 63 ( 12) 108 ( 17) 41 ( 13) 47 [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] 41 [START_REF] Zhao | Capacity enhancement using throwboxes in dtns[END_REF] 59 ( 9) 0 (0) 47 ( 8) 50 [START_REF] Megiddo | The maximum coverage location problem[END_REF] 12 ( 4) 30 ( 6) 39 [START_REF] Keränen | The one simulator for dtn protocol evaluation[END_REF] 52 [START_REF] Ott | Dtn-based content storage and retrieval[END_REF] 55 [START_REF] Ott | Dtn-based content storage and retrieval[END_REF] 35 ( 9) 41 ( 6) this end, we simulate the system under different assumptions regarding the put policy ("first" or "all") and the existence of the distribution network. We represent the average success ratio of the get user requests and the file availability in the repositories in Figure 4. In the scenario with the "first" put policy and no distribution network, we notice that the more repositories there are, the more user requests are satisfied. Some buses that have pending get requests are not able to reach any repository because of their routes and the few repositories available. Adding more repositories allows more buses to reach repositories, resulting in better success ratio of the get user requests. However, since the data is scattered across multiple repositories, the success ratio of the get requests still remains low for short deadlines. For long deadlines, the buses visit more repositories, which increases their chances to visit one with a copy of the requested file. Taking advantage of the "all" put policy helps increase the success ratio of the get requests by 9.98% on average for all the deadlines. With this policy, the buses distribute copies of the files to different repositories, thus increasing the availability of the files. Contrary to the "first" put policy where user files are available at only one repository, the "all" put policy increases the chance of a mobile user to find a repository with a local copy of the requested file.

90 (13) 50 (5) 33 (6) 7 (3) 10 (3
The distribution network led to increase the user request success ratio by 104.3%. Note that this improvement is greater for lower user request deadlines (e.g., the improvement for the user requests of 1200 seconds is of 201.4% on average). The distribution network distributes copies of the files in several repositories. Since the repository placement algorithm guarantees that all the repositories are connected together, the files can be distributed to each repository of the system. Hence, a mobile user with a pending get request is more likely to encounter a repository that has a local copy of the requested file, which increases the success ratio of the get requests. File availability. We compare the benefits of the distribution network with the "all" put policy using the "File availability" plots in Figure 4. The plots show the proportion of files available at the repositories, where "1.0" of file availability corresponds to all the files being available at each repository. We clearly see the benefits of the distribution network to distribute the files to the repositories. The "all" put policy also distributes the files to several repositories, however, it fails to distribute the files to repositories beyond those located on the routes of the mobile users that generated the put requests. The plot further shows that, even with the distribution network, the files are not available at every repository (only 85% of them). In fact, the data represented accounts for the files that were not fully distributed by the end of the simulation. Distribution duration. In the second step of our evaluations, we study the distribution duration of the copies of user files among the available repositories. In Figure 5, we show the average duration to distribute a file throughout the distribution network since the time the file was stored in the first repository (following a put request). We represent the distribution duration of the copies of user files as a function of the proportion of the file availability for different numbers of repositories. For example, with 10 repositories, 40% of file availability corresponds to the file being available in four repositories. The first repository where the file is stored can be any of the repositories available. We notice that the average time needed to distribute the user files to every repository, regardless of the number of repositories available, is 4000 seconds, or a little more than one hour. It takes more time to distribute the copies of the files to the repositories at the beginning and end of the file distribution. At the beginning of the file distribution, only one copy of the files is available at the first repository. It takes on average 700 seconds to distribute the first copy of the file to the second repository. As more repositories distribute copies of the files, the distribution of the copies becomes faster. By the end of the file distribution, copies of files are available at most repositories. It takes on average 500 seconds to reach the last repository, as it is the farthest away from the first repository where the original copy of the file was stored.

In Figure 3b, we give an origin-destination matrix that shows the average travel time in minutes between any pair of repositories. This translates to the time needed to distribute the file to different repositories from the time the file was stored in a first repository (following a put request). These values give the average duration for a file to be available in a repository. In the figure, the repositories are identified by the same numbers as the ones in Figure 3a. The connectivity between two repositories depends on the number and frequency of the buses going from one repository to another. For instance, repositories 1 and 15 are very well connected to the rest of the repositories. However, repository 9 is not as well connected since it is farther away from the rest of the repositories. This the longer time it takes to distribute copies of the user files from repository 9 to every other repository. This goes to show that the further away the repositories are, the more time it takes on average to reach them and distribute copies of the files to them.

CONCLUSION

In this paper, we presented a cloud-like file storage and sharing system. Users share files on the system by seamlessly storing and retrieving files on pre-positioned repositories within a bounded deadline. A challenge we identified in this paper is the processing of user requests in a timely fashion. To this end, we leverage the movements of the mobile users between the repositories to distribute copies of the user files throughout the system. Additionally, we designed an algorithm to place a given number of repositories such that they serve the maximum number of user requests. We evaluated the storage system with simulated movements of San Francisco buses. We showed how the number of storage nodes impacts the success of the user requests to retrieve user files. We also evaluated the distribution duration of the copies of the files with the movements of the users between the repositories. Regardless of the number of repositories available, it takes a little more than an hour to distribute a file to each repository placed in San Francisco using traces of the MUNI buses.

As future work, we plan to implement distribution strategies that replicate copies of the files to some of the repositories. We also intend to take into account the limited capacity of wireless transmissions between the mobile users and the repositories, as well as the contention when multiple nodes try to exchange files with a repository. This creates more challenges with regard to the scheduling of the requests executed at each repository.

Figure 1 :

 1 Figure 1: Requests and data exchanges between a repository and two mobile users when they encounter one another.

Figure 2 :

 2 Figure 2: Different layers to represent the goals of the placement algorithm in the case of a bus transit system.

  Origin-destination matrix of the repositories (identified by the numbers represented on the Figure3ashowing the mean travel time in minutes between each pair of repositories. The values in parentheses are the corresponding standard deviation. The simulations were done for 15 repositories placed as shown in Figure3a.

Figure 3 :Figure 4 :

 34 Figure3: Results for the allocation of 15 repositories in San Francisco using the bus movements of the MUNI bus transit system.

Figure 5 :

 5 Figure 5: Distribution duration as a function of the file availability for different numbers of repositories.