Figures
Abstract
Paraoxonases (PON) are a family of proteins (PON1, 2 and 3) with multiple enzymatic activities. PON1 interferes with homoserine lactone-mediated quorum sensing in bacteria and with reactive oxygen species (ROS) in humans and mice. PON1 gene mutations have been linked to multiple traits, including aging, and diseases of the cardiovascular, nervous and gastrointestinal system. The overlapping enzymatic activities in the PON family members and high linkage disequilibrium rates within their polymorphisms confound animal and human studies of PON1 function. In contrast, arthropods such as Drosophila melanogaster have no PON homologs, resulting in an ideal model to study interactions between PON genotype and host phenotypes. We hypothesized that expression of PON1 in D. melanogaster would alter ROS. We found that PON1 alters expression of multiple oxidative stress genes and decreases superoxide anion levels in normal and germ-free D. melanogaster. We also found differences in the composition of the gut microbiota, with a remarkable increase in levels of Lactobacillus plantarum and associated changes in expression of antimicrobial and cuticle-related genes. PON1 expression directly decreased superoxide anion levels and altered bacterial colonization of the gut and its gene expression profile, highlighting the complex nature of the interaction between host genotype and gut microbiota. We speculate that the interaction between some genotypes and human diseases may be mediated by the presence of certain gut bacteria that can induce specific immune responses in the gut and other host tissues.
Citation: Pezzulo AA, Hornick EE, Rector MV, Estin M, Reisetter AC, Taft PJ, et al. (2012) Expression of Human Paraoxonase 1 Decreases Superoxide Levels and Alters Bacterial Colonization in the Gut of Drosophila melanogaster. PLoS ONE 7(8): e43777. https://doi.org/10.1371/journal.pone.0043777
Editor: Fanis Missirlis, Queen Mary University of London, United Kingdom
Received: June 22, 2012; Accepted: July 25, 2012; Published: August 30, 2012
Copyright: © Pezzulo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Funding from the National Institute of Health and Insitutional Commitment to JZ. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work was supported by the National Institutes of Health, NIHLPPG HL091842-02 (JZ) and ES015981 and ES014871 (ABC).
Competing interests: The authors have declared that no competing interests exist.
Introduction
The human paraoxonases (PON1, PON2 and PON3) are proteins with promiscuous enzymatic activities and with distinct tissue expression profiles [1]–[6]. Members of this gene family exhibit phosphotriesterase, esterase and lactonase activity to varying degrees [1], [7]–[9]; of these, PON1 has been the most extensively studied. PON1 was originally named for its capacity to hydrolyze paraoxon and other organophosphates [10], and has since been associated to an astounding number of traits and diseases affecting multiple organ systems [2]. While the phosphotriesterase function of PON1 is responsible for its organophosphate-degrading capacity, structure-activity studies suggest that lactonase activity is its native function [9].
Mutations in the human PON1 gene have been associated with aging and diseases of the cardiovascular, nervous, endocrine and gastrointestinal systems [2], [11], [12]. A possible mechanism for these phenotypes may be related to HDL-dependent and independent antioxidant properties of PON1 [13], [14] and its effects on levels of hydroperoxides and platelet activating factor, which may also affect oxidative stress in tissues [15]–[18]. PON1 can also hydrolyze acyl-homoserine lactones used by quorum-sensing bacteria to regulate multiple virulence factors during colonization of new environments [19]–[22]. This could at least indirectly explain the association of mutations in PON1 with Crohn's disease and ulcerative colitis, or perhaps other phenotypes associated with the gut microbiota such as obesity and cardiovascular disease [23]–[29].
Describing how mutations in PON1 result in the associated phenotypes remains an elusive goal for multiple reasons. Mutations in each of the three PON family members are in strong linkage disequilibrium with mutations in other PON genes or with different genes [30]–[32]. A phenotype associated to genetic variation in PON1 may therefore be caused by a mutation in another gene. Moreover, the close proximity of the genomic loci for PON1, PON2 and PON3 results in recombination rates that makes generation of triple KO mice difficult and, in single knockout mice, lack of one PON member may be compensated by the remaining two members [21].
Although paraoxonases are conserved across a wide range of species, arthropods (including the versatile Drosophila melanogaster) lack a homolog [20], [22]. Therefore, we have previously used D. melanogaster as a model to study paraoxonases in the absence of proteins with overlapping enzymatic activity that can confound analyses of genotype-phenotype interactions [22].
In the Drosophila midgut, reactive oxygen species generated and controlled by the duox system [33]–[37] control intestinal bacterial populations and suppress virulent pathogens such as Erwinia carotovora and Pseudomonas entomophila from invading the host. Activation of the Toll and Imd pathways to regulate multiple antimicrobial peptides provides an additional mechanism allowing a pathogen class-specific immune response [35]–[37]. Whether and how these mechanisms directly regulate symbiotic bacteria in the normal gut remains a less clear but distinct possibility [38]–[41].
Here, we hypothesized that expression of human PON1 in D. melanogaster would directly result in altered levels of reactive oxygen species in the gut. Moreover, we hypothesized that abnormal reactive oxygen species levels would affect the composition of gut symbionts.
Results
Expression of human PON1 alters expression of oxidative stress genes in D. melanogaster
PON1 has been associated to decreased oxidative stress in human tissues [13]–[18]. As an initial screen to determine whether PON1 decreases oxidative stress in D. melanogaster, we analyzed data from gene expression microarrays of +/Tub and PON1/Tub flies (Gene Expression Omnibus accession #GSE29534 in http://www.ncbi.nlm.nih.gov/geo/) (Figure S1). We used RMA expression values in an ANOVA model to determine fold change and false discovery rate (FDR) of gene expression between +/Tub and PON1/Tub flies. We then extracted the data from genes included in the Gene Ontology term “Response to oxidative stress” (GO:0006979; http://amigo.geneontology.org/cgi-bin/amigo/go.cgi). The heatmap in Figure 1 shows that 26 out of 45 genes in our dataset that are associated with the “Response to oxidative stress” GO Term were differentially expressed between +/Tub and PON1/Tub flies (FDR<0.01) but not between +/Tub and +/+flies (See also table S1). These data suggest that PON1 alters oxidative stress in D. melanogaster.
Heatmap of expression values of genes in the Gene Ontology term “Response to oxidative stress” in PON1/Tub, +/Tub and +/+ D. melanogaster. Columns represent samples and rows correspond to genes. Color scale corresponds to RMA expression value. * = genes differentially expressed between +/Tub and PON1/Tub (FDR<0.01). n = 4 aliquots of 20 flies per genotype.
Expression of human PON1 decreases superoxide levels in the gut of D. melanogaster
Regulation of ROS and the oxidative state in organisms is a complex and incompletely understood process. Screening for expression level changes of genes associated to oxidative stress in microarray data revealed that some genes are upregulated and others downregulated when PON1 is expressed in D. melanogaster. In order to perform mechanistic studies, we focused on the effect of PON1 expression on superoxide anion (O2.−) levels, which have been shown to play an important role in gut immunity in D. melanogaster [33], [34]. We hypothesized that PON1 would decrease the levels of O2.− in D. melanogaster.
We used two different methods to quantify O2.− levels in D. melanogaster more accurately [42]. First, we measured O2.− levels in whole +/Tub and PON1/Tub flies using a lucigenin-based assay (Figure 2). We found that O2.− levels were significantly lower in PON1/Tub compared to +/Tub flies. Second, we used dihydroethidium staining to directly determine O2.− levels in the midgut of +/Tub and PON1/Tub flies. To investigate the location of O2.−, we used confocal microscopy. Figure 3 A and B shows that O2.− can be detected with dihydroethidium in the midgut of both +/Tub and PON1/Tub flies. In order to quantitate O2.− levels, we used epifluorescence microscopy to assess many midguts. Figure 3C shows that the intensity of dihydroethidium staining is significantly decreased in the midgut of PON1/Tub flies.
Lucigenin staining of whole +/Tub and PON1/Tub flies. Data shown are rate of luminescence mean ± s.e.m. n = 5 pools of 3 flies per genotype. * = p<0.05, unpaired t-test.
(A and B) Dihydroethidium (DHE) staining and confocal microscopy were used to detect superoxide in dissected midguts from +/Tub and PON1/Tub flies. (C) Dihydroethidium staining epifluorescence intensity in midguts of +/Tub and PON1/Tub flies (P-element system insertion). Controls are PON1/Tub and PON2/Tub insertions using the phiC31 system. Data are mean ± s.e.m. n = 10 to 40 midguts per genotype. * = p<0.05 vs. +/Tub, unpaired t-test.
The method (P-element system) used to insert the PON1 transgene into a random site of the D. melanogaster genome can potentially result in secondary effects due to disruption of the insertion site. We therefore included analysis of a different D. melanogaster line with PON1 insertion in a different but known genomic site (phiC31 system) as a control to exclude transgene insertion site effects in PON1/Tub flies. We found that expression of PON1 by insertion of the transgene in the alternative site also resulted in decreased O2.− levels. Moreover, insertion of PON2, which is another member of the paraoxonase family, in this same alternative site, did not result in decreased O2.− levels (Figure 3C). Additionally, flies expressing PON1 do not have decreased longevity under standard rearing conditions (Figure S2). This results show that PON1 decreases O2.− levels in the midgut of D. melanogaster and suggest that this effect is not caused by insertion site disruption or by indirect health-impairing mechanisms.
Expression of human PON1 alters the gut microbiome of D. melanogaster
Generation of ROS by the Duox system is one of the primary mechanisms that controls gut microbial populations in D. melanogaster [33]–[37]. We therefore hypothesized that decreased O2.− levels in the midgut could result in a secondary phenotype of altered colonization by midgut bacteria. We extracted genomic DNA from pools of 20 guts from +/Tub and PON1/Tub flies in triplicate and amplified a portion of the V2 region of the 16 s rRNA gene of bacteria using barcoded primers, followed by high-throughput sequencing of amplicons. We generated approximately 20,000 high quality sequences per sample. Sequences were demultiplexed and analyzed using QIIME virtual box [43]. OTU's were generated using sequences with >97% similarity, and the RDP classification method was used to assign a taxonomic identity based on the most current RDP database, to a representative sequence from each OTU. A taxonomy summary chart at the Order level was generated and the average of 3 samples per group is shown in Figure 4. 99% of the detected sequences corresponded to the orders Rhodospirillales, Rickettsiales, and Lactobacillales (with the most common species for each order being Acetobacter aceti, Wolbachia endosymbiont of Drosophila melanogaster, and Lactobacillus plantarum, respectively). Other Orders detected (<1% of total combined frequency) include Rhizobiales, Bacillales, Clostridiales, Sphingomonadales, Flavobacteriales and Bacteroidales and are shown in Table S2. Interestingly, while the relative abundance of Wolbachia was dramatically decreased by PON1, the proportion of Acetobacter and Lactobacillus were increased. These data show that expression of PON1 alters the composition of the gut microbiome of D. melanogaster and suggest that a PON1-mediated decrease in midgut O2.− may preferentially affect specific types of bacteria.
High-throughput sequencing analysis of the V2 region of the bacterial 16 s rRNA gene in DNA extracted from guts of +/Tub and PON1/Tub flies. Figure shows taxonomy summary chart of order abundance as an average of 3 samples of 20 guts.
Expression of human PON1 increases the gut load of Lactobacillus in D. melanogaster
Abundance data refer to proportions so observed changes in one bacterial group could be caused by changes in abundance of another group. We therefore studied the total load of Wolbachia and Lactobacillus independently. We hypothesized that expression of PON1 would result in alterations in the load of specific bacteria in the gut of D. melanogaster. We first homogenized guts of PON/Tub and +/Tub flies and used the homogenates to quantify the intracellular endosymbiont Wolbachia using qPCR [44]. We found that levels of Wolbachia, normalized to the single-copy Drosophila gene su(F), were almost identical, with a +/Tub to PON/Tub expression ratio of 1.06 (95% CI = 0.005–53.71). Second, we cultured the homogenates on Chromagar™ orientation plates which allow classification of colonies according to color produced. On Chromagar™ plates, β-glucosidase-producing Lactobacillus should generate blue colonies. Although other bacteria were expected according to the high-throughput sequencing results, this simple scheme would allow us to discern Lactobacillus, the predominant β-glucosidase-producing species detected, from other bacteria. Interestingly, whereas the total load of culturable bacteria was similar in both genotypes (Figure 5), load of blue colonies (predominantly Lactobacillus plantarum as confirmed by 16 s rRNA gene sequencing) was significantly elevated in PON1 flies. Interestingly, a global gene ontology-based reanalysis of our gene expression microarray data using GOrilla (http://cbl-gorilla.cs.technion.ac.il/) [45], [46] revealed altered expression of cuticle and Imd pathway antimicrobial peptide genes (Figure S3), which are important in maintaining normal gut homeostasis and control of the intraluminal bacterial population [35], [47]–[49]. These data show that expression of PON1 alters the gut microbiome of D. melanogaster.
Guts of +/Tub and PON1/Tub flies 3–5 days post eclosion were homogenized and plated on Chromagar™ Orientation plates. Number of white, blue, purple and total colonies per gut are shown, data is log average ± s.e.m . n = 15 guts. * = p<0.05, unpaired t-test.
PON1-mediated decrease in gut superoxide levels in D. melanogaster is independent of altered bacterial colonization
Expression of PON1 both decreased O2.− levels and altered the microbiome in the midgut of D. melanogaster. Decreased O2.− levels could be directly caused by PON1 or could be secondary to the abnormal midgut microbiome of PON1/Tub flies. In order to determine whether PON1 directly decreases O2.− levels, we generated lines of axenic (germ-free) D. melanogaster using the method described in [50] and compared the levels of O2.− in +/Tub and PON/Tub flies. We predicted that in germ-free PON/Tub flies, levels of O2.− would be decreased compared to +/Tub. Figure 6 shows that in both conventionally reared and germ-free D. melanogaster, PON1 expression decreases levels of O2.−. These results show that PON1 directly decreases O2.− levels independent of changes in the midgut microbiome of D. melanogaster.
Lucigenin staining using pools of germ-free whole +/Tub and PON1/Tub flies. Data shown are rate of luminescence mean ± s.e.m. n = 5 pools of 3 flies per genotype. * = p<0.05, unpaired t-test.
Discussion
We have previously shown that human PON1 can protect D. melanogaster from quorum-sensing pathogens such as P. aeruginosa in a physical injury model [22]. Here, we found that, even in the absence of gut bacteria, PON1 can dramatically decrease levels of O2.− in the midgut. Expression of PON1 and the resultant decrease in correlated with marked changes in the composition of the gut microbiome, including an increased load of the symbiont L. plantarum.
The levels of O2.− in the midgut of Drosophila affected the composition of the gut microbiome, but it is also possible that direct interference with bacterial quorum sensing may directly or indirectly affect the colonizing capacity of some bacterial species [51]. Interestingly, this abnormal gut microbiota composition correlated with increased expression of antimicrobial peptides, perhaps, though not proven here, because the increased load of L. plantarum resulted in compensatory PGRP-LC-mediated activation of the Imd pathway [52], [53]. It has previously been proposed that both the Toll and Imd pathways are not only responsive to pathogens but also to symbionts that can constitute a threat under certain circumstances [38]. Thus, an abnormal deficit in function in a mechanism of midgut bacterial control in D. melanogaster (ROS) may result in compensatory activation of another antimicrobial mechanism (Imd).
The pattern observed in this study highlights the bidirectional and complex nature of the interaction between host genotype and composition of the gut microbiome. Some studies have suggested that genetic and physiologic factors of the host [26], [28], [29], [54] can induce changes in the abundance of some bacterial phylotypes, while other studies have shown that specific compositions of gut bacterial communities [23], [24], [27], [55] or specific symbionts [56] can affect the immune status and metabolism of the host. Here, we show that expression of a single gene can affect the composition of gut bacteria and result in an altered immune status in the host. This suggests that a single mutation in the gene of a human host can affect host physiology in unexpected ways when this mutation affects the composition of the gut microbiome. Some potential conditions in which this effect may be observed include human gastrointestinal, cardiovascular, and metabolic diseases such as inflammatory bowel disease, atherosclerosis, and diabetes mellitus. Interestingly, mutations in PON1 have been associated with all of these conditions, and the possibility of microbiome-mediated effects in these phenotypes is intriguing.
How does PON1 affect the levels of ROS and the composition of the gut microbiome in Drosophila? Our study suggests that PON1 may directly affect components of the system that generates and clears ROS in the midgut, but determining which components are affected and how this results in altered gut bacterial colonization will require further characterization.
In summary, expression of PON1directly leads to a decrease in midgut O2.− levels and abnormal oxidative stress gene expression with an associated alteration in the gut microbiome in D. melanogaster. These changes may then lead to an altered innate antimicrobial peptide expression profile. Mutations in PON1 or other ROS modulating genes may result in an altered gut microbiome as an intermediate mechanism for diseases such as atherosclerosis and diabetes mellitus, and may also affect important traits such as longevity. Exploring the mechanisms that link genotypes in PON and other genes to bacterial homeostasis in the gut and other organs and health in the host will likely reveal important new findings.
Methods
Transgenic D. melanogaster Lines
Drosophila stocks were reared on standard cornmeal-agar-molasses medium at room temperature (21–25°C). The tubulin-Gal4 transgenic line (y1 w*; P{tubP-GAL4}LL7/TM3, Sb1) was obtained from the Bloomington stock center. We used the P-element system (random insertion site) to generate the hPON1/Tub flies used in most experiments [57] and the PhiC31 system (site-specific integration) for insertion site control experiments [58], [59]. Human PON1 cDNA was cloned into the pUAST (P-element) vector or the pUASTattB (PhiC31) vector and subsequently injected into corresponding y w1118 (P-element) or 51D (PhiC31) D. melanogaster embryos using standard techniques (Rainbow Transgenic Flies, Inc. Camarillo, CA). The binary GAL4-UAS system and tubulin (tub) promoter were used for the ubiquitous transgenic expression of PON1. y w1118; ; tub-GAL4/TM3,Sb virgin females were crossed to the corresponding P-element or PhiC31UAS-hPON1 transgenic males to obtain flies heterozygous for both PON1 and Tub. Male w1118 were used for +/Tub controls. F1 progeny were tested for expression of PON1 by performing western blots using an antibody to PON1 (Abcam, Cambridge, MA).
Axenic D. melanogaster
Axenic fly stocks were generated according to the method described by Bakula [50]. Approximately 20 adult males and 30 virgin females were allowed to acclimatize on orange juice plates with yeast for 24 h. at 29°C. After acclimation, embryos were collected every 12 h. Embryos were then dechorionated in sodium hypochlorite (2-fold diluted bleach) for 2 min., washed twice with 70% ethanol, and then washed twice with sterile, distilled water in a sterile tissue culture hood. Control embryos were only washed with water. Embryos were then transferred to autoclaved sterile food vials. Absence of bacteria was confirmed by culture and 16 s rRNA PCR. Flies were collected for experiments 3 days after eclosion.
Gut dissections
The entire gastrointestinal tract was removed intact from females for staining and further processing by grasping below the head and at the tip of the abdomen with fine forceps and gently pulling.
Dihydroethidium-based superoxide quantification
Female adult fly guts (3–5 days post-eclosion, from same parents and bottle) were dissected as previously described under 1× Schneider's Drosophila Media (Gibco, Invitrogen, Carlsbad, CA). The guts were then stained with DHE using a previously described method (http://www.nature.com/protocolexchange/protocols/414) [42], [60]. Epifluorescence imaging was performed using an Olympus IX71 epifluorescence microscope. Confocal imaging was performed with an Olympus FV1000 confocal microscope. Quantification of fluorescence was performed in ImageJ [61] v1.42 (http://rsbweb.nih.gov/ij/index.html) using mean gray area measurements of outlined whole midguts.
Lucigenin-based superoxide quantification
To assess O2.− levels in whole flies, a lucigenin based ROS assay was performed on fly lysate as described in [62], [63]. Fly lysates were prepared using 3-day old male whole flies. For each sample 3 flies were homogenized with a pestle in mitochondria buffer (1 mM Tris pH 7.5, 20 µM EDTA, Aprotinin 2 ng/mL, Leupeptin 2 ng/mL, Pepstatin 2 ng/mL). After sonication, lysates were centrifuged and supernatant collected. A Bradford assay was completed on all samples prior to conducting the experiment. 50 µg of protein were diluted in 1× PBS to a final volume of 1 ml. Lucigenin (5 µM) and NADPH (100 µM) (Sigma-Aldrich, St. Louis, MO) were added to each sample, and luminescence was recorded every 30 s for 10 min. Initial rate was defined as the linear slope of the data points from 30 s to 150 s.
D. melanogaster Gut DNA extractions
3-day old female flies were mixed with 3-day old males and allowed to incubate on sterile corn meal food prior to dissection. Females were anesthetized with CO2 and decapitated. The males were discarded. Female bodies were submerged under 1× PBS +/+ and the midgut, excluding the crop, was dissected. Forceps were sterilized frequently throughout. 20 guts were dissected per sample, triplicate samples were used for each genotype. Guts were homogenized with a bead beater for 30 s in 750 µL RLT buffer, using Matrix E bead tubes (MP Biomedical, Solon, OH). DNA was extracted using a DNeasy Blood & Tissue Kit (Qiagen, Valencia, CA) and eluted into 50 µL TE buffer.
Microbiome pipeline/analysis
DNA was processed for sequencing in a Roche GS FLX 454 Titanium Series (454 Life Sciences, Branford, CT) at the University of Iowa DNA facility. The V2 region of bacterial 16S rDNA was amplified using a FastStart High Fidelity PCR System (Roche Applied Science, Indianapolis, IN). Each 25 µL reaction contained 25 ng of column purified DNA (DNeasy Blood and Tissue Kit, Qiagen, Valencia, CA), 2.5 µL FastStart 10× Buffer, 0.25 FastStart HiFi Polymerase, 0.4 µM of a modified primer 8F (also referred to as in some publications) [5′-CCTATCCCCTGTGTGCCTTGGCAGTC-TCAG-AGAGTTTGATCCTGGCTCAG-3′; composite of GS FLX Titanium Primer B (underlined), four-base library key (TCAG), and the universal bacterial primer 8F (italics)], and 0.4 µM of a modified primer 338R [5′-CCATCTCATCCCTGCGTGTCTCCGAC-TCAG-NNNNNNNNNN-TGCTGCCTCCCGTAGGAGT-3′; GS FLX Titanium Primer A (underlined), a unique 10-base Extended Multiplex Identifier (Ns), four-base library key (TCAG), and the broad-range bacterial primer 338R (italics)] [28]. Primers were HPLC purified and acquired from Integrated DNA Technologies (Coralville, IA). Cycling conditions were 94°C for 3 min., followed by 30 cycles of 94°C for 1 sec., 60°C for 45 sec., and 72°C for 1 min. Size and quality of the resulting PCR products was confirmed by agarose gel electrophoresis. Replicate PCRs were pooled and amplicons purified using Ampure magnetic purification beads (Agencourt Beckman Coulter, Danvers, MA). Subsequent steps for sequencing were performed following manufacturer recommended protocols.
Culturable microbiome of D. melanogaster
Male and female flies of each genotype, from the same set of parents were kept in bottles on standard cornmeal agar. At designated days post-eclosion, twenty male flies were taken from the bottles, anesthetized with CO2 and surface sterilized by rinsing sequentially in 70% ethanol and two fresh aliquots of 1× PBS (Gibco, Invitrogen, Carlsbad, CA). Flies were then placed in fresh refrigerated 1× PBS −/−, and ground with a pestle until thoroughly homogenized (2–3 min.). Serial dilutions were made and plated on ChromAgar™ Orientation plates (BD Biosciences, San Jose, CA) and incubated at 37°C until visible colonies grew. Colonies were counted and categorized by color. Colony PCR using 27F and 1492R primers for the 16 s rRNA gene followed by standard Sanger sequencing was used to confirm identity of blue ChromAgar colonies.
D. melanogaster RNA extraction
Twenty male flies age 3–5 days and cultured in the same bottle of each genotype were selected and homogenized in TRIzol reagent (Invitrogen, Carlsbad, CA) using Lysis Matrix E tubes (MP Biomedical, Solon, OH). Samples were bead-beated for 45 sec. RNA extraction was done with the Invitrogen PureLink RNA Mini kit (Invitrogen, Carlsbad, CA), per instruction manual for extractions using the TRIzol reagent.
Microarray hybridizations
Roche NimbleGen 12plex HD2 gene expression microarrays (Design number 080813_Dmel_exp_HX12, Roche Nimblegen, Madison, WI) were used to analyze D. melanogaster gene expression across 3 genotypes (+/+, +/Tub and PON1/Tub), providing four technical replicate hybridizations per sample. Oligo dT primers (Invitrogen, Carlsbad, CA) were used to generate double-stranded cDNA from total RNA isolated. The cDNA was then amplified/labeled using Cy3-coupled random nonamers and hybridizations were performed using 4 ug of labeled cDNA per subarray as directed by the Roche NimbleGen Gene Expression Protocol (see http://www.nimblegen.com/products/lit/expression_userguide_v5p0.pdf for specific labeling and processing details). After hybridization for 16–20 h., the arrays were washed, dried, and then scanned on an Axon GenePix 4000B microarray scanner from Molecular Devices (Sunnyvale, CA).
Microarray analysis
Raw data .pair files passing standard quality control criteria were imported into Partek Genomics Suite v6.4 for computation of RMA expression values [64]. The gene expression calls from each of the four technical replicates per sample had R-squared values of greater than 0.97.
The data was deposited in the Gene Expression Omnibus site (http://www.ncbi.nlm.nih.gov/geo/) under GEO Accession #GSE29534 using MIAME standards. Hierarchical clustering analysis was performed in Gene Pattern (http://www.broadinstitute.org/cancer/software/genepattern/) [65]. RMA values generated in Partek were used to generate a .gct format file. The .gct file was used as the input file for the “HierarchicalClustering” module in Gene Pattern with Pearson correlation used as distance measure and Pairwise complete-linkage as clustering method. The resulting output files were used in the “HierarchicalClusteringViewer” module of Gene Pattern, and a .txt Sample Information File was used to label each sample with sample genotype. The resulting file was edited in the GNU Image Manipulation Program GIMP v 2.6 (http://www.gimp.org/) for further annotation.
ANOVA analysis was performed in Partek Genomics Suite comparing +/+, +/Tub and PON1/Tub samples. Data in the resulting spreadsheet containing p-values and log2 transformed fold changes was used in Prism v5.0 for Mac to generate volcano plots. Probes differentially expressed between +/+ and +/Tub samples were considered to be affected by the Tub driver insertion and were excluded from further analysis. To perform gene ontology analysis, Partek Genomics Suite was used to generate a list containing probes that pass a threshold of false discovery rate of 0.01 (1%) between +/Tub and PON/Tub samples. Probes in this spreadsheet were ranked according to fold change magnitude from highest to lowest. The list was used in GOrilla (http://cbl-gorilla.cs.technion.ac.il/) [45], [46] to generate directed acyclic graphs of the Gene Ontology terms enriched in the submitted gene list. The generated GO Term lists were filtered to include only those with at least 4 genes enriched in the GO Term. The AmiGO browser (GO database release 2012-05-05 in http://amigo.geneontology.org/cgi-bin/amigo/go.cgi) was used to obtain the list of genes in the GO term “Response to oxidative stress” (GO:0006979) and this list was crossmatched to the ANOVA spreadsheet in Partek to generate heatmaps (as described above) of oxidative stress-related genes.
Statistical analysis
All experiments were performed at least 3 times separately. Statistical analyses were performed in Graphpad Prism 5 for MacOS X. A p-value<0.05 in unpaired t-tests was considered statistically significant [66].
Supporting Information
Figure S1.
Expression of PON1 alters the gene expression profile of D. melanogaster. Total RNA from +/+, +/Tub and PON1/Tub flies was extracted and analyzed on D. melanogaster gene expression arrays. (A) Unsupervised hierarchical clustering and (B) volcano plot. Heatmap of the 25 most highly differentially (C) downregulated and (D) upregulated genes in PON1/Tub compared to +/Tub and +/+ flies. Color key shows corresponding normalized RMA expression values.
https://doi.org/10.1371/journal.pone.0043777.s001
(TIFF)
Figure S2.
Expression of PON1 does not affect longevity of D. melanogaster. Survival of +/Tub and PON1/Tub flies was followed over 60 days. Data shown are % flies alive. n = 200 flies per genotype. Curves are not statistically different using the log-rank test.
https://doi.org/10.1371/journal.pone.0043777.s002
(TIFF)
Figure S3.
Expression of PON1 alters the gene expression profile of immune system-related genes in D. melanogaster. Total RNA from +/+, +/Tub and PON1/Tub flies was extracted and analyzed on D. melanogaster gene expression arrays. Global gene ontology analysis in GOrilla revealed PON1-induced differential expression of groups of genes associated to gene ontology terms (A) sensory perception of chemical stimulus, (B) chitin metabolic process, (C) antibacterial humoral response and (D) structural constituent of cuticle, shown as heatmaps. Color key shows corresponding normalized expression values.
https://doi.org/10.1371/journal.pone.0043777.s003
(TIFF)
Table S1.
Expression of genes associated with gene ontology term “Response to oxidative stress” in PON1/Tub and +/Tub flies. Bold columns correspond to genes differentially express between PON1/Tub and +/Tub flies but not between control genotypes +/Tub vs. +/+.
https://doi.org/10.1371/journal.pone.0043777.s004
(PDF)
Table S2.
Taxonomy summary table (order level) of gut microbiota of PON1/Tub and +/Tub flies. Each column shows relative abundance results from a pool of 20 guts. 3 replicates per genotype are shown.
https://doi.org/10.1371/journal.pone.0043777.s005
(PDF)
Acknowledgments
We thank Michael J. Welsh for insightful discussion, and Einat Snir, Jennifer Bair, Thomas Bair and Kevin Knudtson at The University of Iowa DNA facility for excellent technical support.
Author Contributions
Conceived and designed the experiments: AAP EEH MVR ME ACR PJT SCB ABC JRM DAS JZ. Performed the experiments: AAP EEH MVR ME ACR PJT SCB. Analyzed the data: AAP EEH MVR JRM DAS JZ. Wrote the paper: AAP JZ.
References
- 1. Draganov DI, Teiber JF, Speelman A, Osawa Y, Sunahara R, et al. (2005) Human paraoxonases (PON1, PON2, and PON3) are lactonases with overlapping and distinct substrate specificities. J Lipid Res 46: 1239–1247.
- 2. Goswami B, Tayal D, Gupta N, Mallika V (2009) Paraoxonase: a multifaceted biomolecule. Clin Chim Acta 410: 1–12.
- 3. Ng CJ, Wadleigh DJ, Gangopadhyay A, Hama S, Grijalva VR, et al. (2001) Paraoxonase-2 is a ubiquitously expressed protein with antioxidant properties and is capable of preventing cell-mediated oxidative modification of low density lipoprotein. J Biol Chem 276: 44444–44449.
- 4. Primo-Parmo SL, Sorenson RC, Teiber J, La Du BN (1996) The human serum paraoxonase/arylesterase gene (PON1) is one member of a multigene family. Genomics 33: 498–507.
- 5. Reddy ST, Wadleigh DJ, Grijalva V, Ng C, Hama S, et al. (2001) Human paraoxonase-3 is an HDL-associated enzyme with biological activity similar to paraoxonase-1 protein but is not regulated by oxidized lipids. Arterioscler Thromb Vasc Biol 21: 542–547.
- 6. Shih DM, Xia YR, Yu JM, Lusis AJ (2010) Temporal and Tissue-Specific Patterns of Pon3 Expression in Mouse: In situ Hybridization Analysis. Adv Exp Med Biol 660: 73–87.
- 7. Billecke S, Draganov D, Counsell R, Stetson P, Watson C, et al. (2000) Human serum paraoxonase (PON1) isozymes Q and R hydrolyze lactones and cyclic carbonate esters. Drug Metab Dispos 28: 1335–1342.
- 8. Jakubowski H (2010) The role of paraoxonase 1 in the detoxification of homocysteine thiolactone. Adv Exp Med Biol 660: 113–127.
- 9. Khersonsky O, Tawfik DS (2005) Structure-reactivity studies of serum paraoxonase PON1 suggest that its native activity is lactonase. Biochemistry (Mosc) 44: 6371–6382.
- 10. Aldridge W (1953) Serum esterases. 2. An enzyme hydrolysing diethyl p-nitrophenyl phosphate (E 600) and its identity with the A-esterase of mammalian sera. Biochem J 53: 117–124.
- 11. Boehm D, Krzystek-Korpacka M, Neubauer K, Matusiewicz M, Berdowska I, et al. (2009) Paraoxonase-1 status in Crohn's disease and ulcerative colitis. Inflamm Bowel Dis 15: 93–99.
- 12. Rothem L, Hartman C, Dahan A, Lachter J, Eliakim R, et al. (2007) Paraoxonases are associated with intestinal inflammatory diseases and intracellularly localized to the endoplasmic reticulum. Free Radic Biol Med 43: 730–739.
- 13. Mackness B, Hine D, Liu Y, Mastorikou M, Mackness M (2004) Paraoxonase-1 inhibits oxidised LDL-induced MCP-1 production by endothelial cells. Biochem Biophys Res Commun 318: 680–683.
- 14. Kabaroglu C, Mutaf I, Boydak B, Ozmen D, Habif S, et al. (2004) Association between serum paraoxonase activity and oxidative stress in acute coronary syndromes. Acta Cardiol 59: 606–611.
- 15. Aviram M, Billecke S, Sorenson R, Bisgaier C, Newton R, et al. (1998) Paraoxonase active site required for protection against LDL oxidation involves its free sulfhydryl group and is different from that required for its arylesterase/paraoxonase activities: selective action of human paraoxonase allozymes Q and R. Arterioscler Thromb Vasc Biol 18: 1617–1624.
- 16. Aviram M, Rosenblat M, Billecke S, Erogul J, Sorenson R, et al. (1999) Human serum paraoxonase (PON 1) is inactivated by oxidized low density lipoprotein and preserved by antioxidants. Free Radic Biol Med 26: 892–904.
- 17. Rodrigo L, Mackness B, Durrington PN, Hernandez A, Mackness MI (2001) Hydrolysis of platelet-activating factor by human serum paraoxonase. Biochem J 354: 1–7.
- 18. Watson AD, Berliner JA, Hama SY, La Du BN, Faull KF, et al. (1995) Protective effect of high density lipoprotein associated paraoxonase. Inhibition of the biological activity of minimally oxidized low density lipoprotein. J Clin Invest 96: 2882–2891.
- 19. Chun CK, Ozer EA, Welsh MJ, Zabner J, Greenberg EP (2004) Inactivation of a Pseudomonas aeruginosa quorum-sensing signal by human airway epithelia. Proc Natl Acad Sci U S A 101: 3587–3590.
- 20. Estin ML, Stoltz DA, Zabner J (2010) Paraoxonase 1, Quorum Sensing, and P. aeruginosa Infection: A Novel Model. Adv Exp Med Biol 660: 183–193.
- 21. Ozer EA, Pezzulo A, Shih DM, Chun C, Furlong C, et al. (2005) Human and murine paraoxonase 1 are host modulators of Pseudomonas aeruginosa quorum-sensing. FEMS Microbiol Lett 253: 29–37.
- 22. Stoltz D, Ozer E, Taft P, Barry M, Liu L, et al. (2008) Drosophila are protected from Pseudomonas aeruginosa lethality by transgenic expression of paraoxonase-1. J Clin Invest
- 23. Caesar R, Fak F, Backhed F (2010) Effects of gut microbiota on obesity and atherosclerosis via modulation of inflammation and lipid metabolism. J Intern Med 268: 320–328.
- 24. de La Serre CB, Ellis CL, Lee J, Hartman AL, Rutledge JC, et al. (2010) Propensity to high-fat diet-induced obesity in rats is associated with changes in the gut microbiota and gut inflammation. Am J Physiol Gastrointest Liver Physiol 299: G440–448.
- 25. Koren O, Spor A, Felin J, Fak F, Stombaugh J, et al. (2011) Human oral, gut, and plaque microbiota in patients with atherosclerosis. Proc Natl Acad Sci U S A 108 Suppl 1: 4592–4598.
- 26. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, et al. (2005) Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A 102: 11070–11075.
- 27. Murphy EF, Cotter PD, Healy S, Marques TM, O'Sullivan O, et al. (2010) Composition and energy harvesting capacity of the gut microbiota: relationship to diet, obesity and time in mouse models. Gut 59: 1635–1642.
- 28. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, et al. (2009) A core gut microbiome in obese and lean twins. Nature 457: 480–484.
- 29. Turnbaugh PJ, Ridaura VK, Faith JJ, Rey FE, Knight R, et al. (2009) The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med 1: 6ra14.
- 30. Erlich PM, Lunetta KL, Cupples LA, Huyck M, Green RC, et al. (2006) Polymorphisms in the PON gene cluster are associated with Alzheimer disease. Hum Mol Genet 15: 77–85.
- 31. Huen K, Barcellos L, Beckman K, Rose S, Eskenazi B, et al. (2011) Effects of PON polymorphisms and haplotypes on molecular phenotype in Mexican-American mothers and children. Environ Mol Mutagen 52: 105–116.
- 32. Jarvik GP, Hatsukami TS, Carlson C, Richter RJ, Jampsa R, et al. (2003) Paraoxonase activity, but not haplotype utilizing the linkage disequilibrium structure, predicts vascular disease. Arterioscler Thromb Vasc Biol 23: 1465–1471.
- 33. Ha E-M, Oh C-T, Bae YS, Lee W-J (2005) A direct role for dual oxidase in Drosophila gut immunity. Science 310: 847–850.
- 34. Ha E-M, Oh C-T, Ryu J-H, Bae Y-S, Kang S-W, et al. (2005) An antioxidant system required for host protection against gut infection in Drosophila. Dev Cell 8: 125–132.
- 35. Lemaitre B, Hoffmann J (2007) The host defense of Drosophila melanogaster. Annu Rev Immunol 25: 697–743.
- 36. Ryu JH, Ha EM, Lee WJ (2010) Innate immunity and gut-microbe mutualism in Drosophila. Dev Comp Immunol 34: 369–376.
- 37. Ryu JH, Kim SH, Lee HY, Bai JY, Nam YD, et al. (2008) Innate immune homeostasis by the homeobox gene caudal and commensal-gut mutualism in Drosophila. Science 319: 777–782.
- 38. Hultmark D (2003) Drosophila immunity: paths and patterns. Curr Opin Immunol 15: 12–19.
- 39. Leulier F, Royet J (2009) Maintaining immune homeostasis in fly gut. Nat Immunol 10: 936–938.
- 40. Royet J, Gupta D, Dziarski R (2011) Peptidoglycan recognition proteins: modulators of the microbiome and inflammation. Nat Rev Immunol 11: 837–851.
- 41. Vallet-Gely I, Lemaitre B, Boccard F (2008) Bacterial strategies to overcome insect defences. Nat Rev Microbiol 6: 302–313.
- 42. Peshavariya HM, Dusting GJ, Selemidis S (2007) Analysis of dihydroethidium fluorescence for the detection of intracellular and extracellular superoxide produced by NADPH oxidase. Free Radic Res 41: 699–712.
- 43. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, et al. (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7: 335–336.
- 44. Peng Y, Nielsen JE, Cunningham JP, McGraw EA (2008) Wolbachia infection alters olfactory-cued locomotion in Drosophila spp. Appl Environ Microbiol 74: 3943–3948.
- 45. Eden E, Lipson D, Yogev S, Yakhini Z (2007) Discovering motifs in ranked lists of DNA sequences. PLoS Comput Biol 3: e39.
- 46. Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z (2009) GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10: 48.
- 47. Apidianakis Y, Rahme LG (2011) Drosophila melanogaster as a model for human intestinal infection and pathology. Dis Model Mech 4: 21–30.
- 48. Kim YS, Ryu JH, Han SJ, Choi KH, Nam KB, et al. (2000) Gram-negative bacteria-binding protein, a pattern recognition receptor for lipopolysaccharide and beta-1,3-glucan that mediates the signaling for the induction of innate immune genes in Drosophila melanogaster cells. J Biol Chem 275: 32721–32727.
- 49. Kuraishi T, Binggeli O, Opota O, Buchon N, Lemaitre B (2011) Genetic evidence for a protective role of the peritrophic matrix against intestinal bacterial infection in Drosophila melanogaster. Proc Natl Acad Sci U S A 108: 15966–15971.
- 50. Bakula M (1969) The persistence of a microbial flora during postembryogenesis of Drosophila melanogaster. J Invertebr Pathol 14: 365–374.
- 51. Hughes DT, Terekhova DA, Liou L, Hovde CJ, Sahl JW, et al. (2010) Chemical sensing in mammalian host-bacterial commensal associations. Proc Natl Acad Sci U S A 107: 9831–9836.
- 52. Cox CR, Gilmore MS (2007) Native microbial colonization of Drosophila melanogaster and its use as a model of Enterococcus faecalis pathogenesis. Infect Immun 75: 1565–1576.
- 53. Takehana A, Katsuyama T, Yano T, Oshima Y, Takada H, et al. (2002) Overexpression of a pattern-recognition receptor, peptidoglycan-recognition protein-LE, activates imd/relish-mediated antibacterial defense and the prophenoloxidase cascade in Drosophila larvae. Proc Natl Acad Sci U S A 99: 13705–13710.
- 54. Kellermayer R, Dowd SE, Harris RA, Balasa A, Schaible TD, et al. (2011) Colonic mucosal DNA methylation, immune response, and microbiome patterns in Toll-like receptor 2-knockout mice. FASEB J 25: 1449–1460.
- 55. Kanther M, Sun X, Muhlbauer M, Mackey LC, Flynn EJ, et al. (2011) Microbial Colonization Induces Dynamic Temporal and Spatial Patterns of NF-kappaB Activation in the Zebrafish Digestive Tract. Gastroenterology 141: 197–207.
- 56. Altura MA, Stabb E, Goldman W, Apicella M, McFall-Ngai MJ (2011) Attenuation of host NO production by MAMPs potentiates development of the host in the squid-vibrio symbiosis. Cell Microbiol 13: 527–537.
- 57. Brand AH, Perrimon N (1993) Targeted gene expression as a means of altering cell fates and generating dominant phenotypes. Development 118: 401–415.
- 58. Bischof J, Maeda RK, Hediger M, Karch F, Basler K (2007) An optimized transgenesis system for Drosophila using germ-line-specific phiC31 integrases. Proc Natl Acad Sci U S A 104: 3312–3317.
- 59. Groth AC, Fish M, Nusse R, Calos MP (2004) Construction of transgenic Drosophila by using the site-specific integrase from phage phiC31. Genetics 166: 1775–1782.
- 60. Owusu-Ansah E, Yavari A, Mandal S, Banerjee U (2008) Distinct mitochondrial retrograde signals control the G1-S cell cycle checkpoint. Nat Genet 40: 356–361.
- 61. Abramoff MD, Magelhaes PJ, Ram SJ (2004) Image Processing with ImageJ. Biophotonics International 11: 36–42.
- 62. He C, Murthy S, McCormick ML, Spitz DR, Ryan AJ, et al. (2011) Mitochondrial Cu,Zn-Superoxide Dismutase Mediates Pulmonary Fibrosis by Augmenting H2O2 Generation. J Biol Chem 286: 15597–15607.
- 63. Tephly LA, Carter AB (2007) Constitutive NADPH oxidase and increased mitochondrial respiratory chain activity regulate chemokine gene expression. Am J Physiol Lung Cell Mol Physiol 293: L1143–1155.
- 64. Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, et al. (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15.
- 65. Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, et al. (2006) GenePattern 2.0. Nat Genet 38: 500–501.
- 66.
Motulsky H (1995) Intuitive Biostatistics. New York, New York, USA: Oxford University Press. 386 p.