Fungi of the murine gut episodic variation and proliferation during antibiotic treatment, ARTYKUŁY NAUKOWE ...
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//-->Fungi of the Murine Gut: Episodic Variation andProliferation during Antibiotic TreatmentSerena Dollive, Ying-Yu Chen, Stephanie Grunberg, Kyle Bittinger, Christian Hoffmann, Lee Vandivier,Christopher Cuff, James D. Lewis, Gary D. Wu*, Frederic D. Bushman*University of Pennsylvania School of Medicine, Department of Microbiology, Philadelphia, Pennsylvania, United States of AmericaAbstractAntibiotic use in humans has been associated with outgrowth of fungi. Here we used a murine model to investigate the gutmicrobiome over 76 days of treatment with vancomycin, ampicillin, neomycin, and metronidazole and subsequent recovery.Mouse stool was studied as a surrogate for the microbiota of the lower gastrointestinal tract. The abundance of fungi andbacteria was measured using quantitative PCR, and the proportional composition of the communities quantified using 454/Roche pyrosequencing of rRNA gene tags. Prior to treatment, bacteria outnumbered fungi by.3orders of magnitude.Upon antibiotic treatment, bacteria dropped in abundance.3orders of magnitude, so that the predominant 16Ssequences detected became transients derived from food. Upon cessation of treatment, bacterial communities mostlyreturned to their previous numbers and types after 8 weeks, though communities remained detectably different fromuntreated controls. Fungal communities varied substantially over time, even in the untreated controls. Separate cageswithin the same treatment group showed radical differences, but mice within a cage generally behaved similarly. Fungiincreased,40-foldin abundance upon antibiotic treatment but declined back to their original abundance after cessation oftreatment. At the last time point,Candidaremained more abundant than prior to treatment. These data show that 1) gutfungal populations change radically during normal mouse husbandry, 2) fungi grow out in the gut upon suppression ofbacterial communities with antibiotics, and 3) perturbations due to antibiotics persist long term in both the fungal andbacterial microbiota.Citation:Dollive S, Chen Y-Y, Grunberg S, Bittinger K, Hoffmann C, et al. (2013) Fungi of the Murine Gut: Episodic Variation and Proliferation during AntibioticTreatment. PLoS ONE 8(8): e71806. doi:10.1371/journal.pone.0071806Editor:Ilse D. Jacobsen, Leibniz Institute for Natural Products Research and Infection Biology- Hans Knoell Institute, GermanyReceivedMarch 18, 2013;AcceptedJuly 3, 2013;PublishedAugust 19, 2013Copyright:ß2013 Dollive et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Funding:This work was supported by Project UH2DK083981, the Penn Genome Frontiers Institute; National Institutes of Health (NIH) AI39368 (GDW); PennDigestive Disease Center (P30 DK050306); The Joint Penn-CHOP Center for Digestive, Liver, and Pancreatic Medicine; S10RR024525; UL1RR024134, and K24-DK078228; and the University of Pennsylvania Center for AIDS Research (CFAR). The funders had no role in study design, data collection and analysis, decision topublish, or preparation of the manuscript.Competing Interests:The authors have declared that no competing interests exist.* E-mail: bushman@mail.med.upenn.edu (FDB); gdwu@mail.med.upenn.edu (GDW)IntroductionThe effects of antibiotic use on the human microbiome can bechallenging to study–confounding factors include complications ofthe underlying diseases states and concomitant use of additionalforms of therapy [1]. Despite these difficulties, outgrowth of fungihas been repeatedly linked to antibiotic treatment at multiple bodysites [2–8]. Fungal infection associated with antibiotic use is ofparticular concern in immunocompromised states such as HIV/AIDS [9–11], some cancers [8,12,13], and transplantation [14–18]. Many of these conditions necessitate the use of corticosteroids,which further predisposes the host to fungal infection [19].Invasive fungal infections have been increasing in recent decades[1,12], and the rise of azole-resistant species ofCandida[7,20],Aspergillus[21,22], andCryptococcus[9,23] brings further urgency tounderstanding the interaction between commensal fungi andbacteria during antibiotic treatment.Rodent models have been used to study the effects of antibioticson the mammalian gut, using culture based [24,25], metagenomic[26], and immunologic [26,27] methods. Antibiotic treatment canpredispose the host to infection by pathogens [28,29] and altermicrobial communities long term [29]. Induced exposure toCandida albicansshapes the bacterial composition of the murine gutPLOS ONE | www.plosone.org1during antibiotic recovery [25] and can cause gastritis [30], whileCandida tropicalishas been associated with increased severity inulcerative colitis [31]. Phenotypic effects have been found evenafter treatment with subclinical doses of antibiotics [32]. In studiesof the role of the vertebrate microbiome in mice, antibiotictreatment is often used to suppress the host bacteria, but the effectof this intervention on fungi is not commonly considered [28,33–35].Here we characterize the bacterial and fungal microbiota ofmice during antibiotic treatment and subsequent recovery aftercessation, analyzing both the amounts and types of microbespresent. We found that fungi indeed grew out upon antibiotictreatment. After cessation of antibiotic treatment, fungal andbacterial communities approached their pre-antibiotic states, butincreased abundance ofCandidapersisted in the gut at the last timepoint studied eight weeks later. To our surprise, we also found thatthe fungal communities changed radically over time in bothcontrol and treated mice. For each condition, specific fungicolonized multiple mice in the same cage, then gave way todifferent fungal colonists over time, and different patterns wereseen in different cages.August 2013 | Volume 8 | Issue 8 | e71806Fungi of the Gut MicrobiomeResultsLongitudinal Analysis of the Murine Gut during AntibioticTreatmentAn antibiotic cocktail containing vancomycin, ampicillin,neomycin, and metronidazole was given to twenty C57B6 micein water. After 2 weeks, antibiotic treatment was stopped for ten ofthe mice. These mice did not receive any antibiotics during theremaining nine weeks of the study (‘‘AbxShortTerm’’ mice). Theremaining ten mice under antibiotic treatment continued toreceive antibiotics for the duration of the study (‘‘AbxContinuous’’mice). Ten control mice received no antibiotics over the course ofthe study (‘‘Control’’ mice). Fecal samples were collected over oneweek prior to initiating the study, then at the indicated time pointsduring the study (Figure 1). DNA was purified from stool pelletsusing a procedure that included bead beating and a hightemperature incubation to facilitate lysis of fungal cells [36].Figure 2A). After initiation of antibiotic treatment, this fell as lowas,102apparent copies per ng DNA. Upon cessation oftreatment the community recovered to its former numbers. Forfungi, prior to antibiotic treatment,,105apparent 18S rRNAgene copies were detected per ng DNA (Figure 2B). Uponinitiation of antibiotic treatment the number climbed to between3–66108apparent copies per ng DNA. Upon cessation ofantibiotic treatment, the numbers dropped back to roughly theirformer levels The abundance of fungi in the Control groupshowed an unexpected increase at day 22. Further analysis showedthat the increase was in only one of the two cages housing thecontrol animals, and correlated with the appearance of a newfungal lineage at high levels in all animals in that cage (describedbelow).Additional information is required to relate these numbers ofrRNA gene copies to the numbers of organisms present. This issueis addressed in the next section.Analysis of the Numbers of Bacterial 16S and Eukaryotic18S Gene Copies Present after Antibiotic TreatmentWe first investigated the changes in abundance of bacteria andfungi, using stool specimens as a proxy for the lower intestinalmicrobiome. To assess changes in abundance, we first quantifiedthe relative abundance of bacterial and fungal genomes in thesamples per ng of DNA using quantitative PCR. For bacteria, aQPCR assay was used that detected the bacterial 16S rRNA gene,and for fungi, an assay was used detecting the 18S rRNA gene.The primers for the fungal assay were designed to suppressamplification of metazoan DNA originating from the host or foodmaterials [37]. The specificity was confirmed by pyrosequencingproducts of amplification with these primers (below and FigureS1).At the start of the study, fecal pellets contained high levels ofbacterial 16S rRNA genes per ng DNA (,106apparent copies;Assessing the Absolute Abundance of Bacteria and FungiSeveral corrections are required to link the QPCR data to thetotal number of organisms per stool pellet. One consideration isthat bacterial [38,39] and fungal [40,41] genomes typicallycontain multiple rRNA gene copies. From published data oncomplete genome sequences, we estimated the mean number of16S rRNA gene copies per bacteria at 5 [38], and 18S copies perfungal genome at 100 [41], though the number for fungi istentative due to the difficulty of accurately sequencing tandemdirect repeats and variability in copy number.Another concern in assessing possible fungal outgrowth duringantibiotic treatment is that the total number of microbes in pellets,and thus total DNA, may go down with treatment, so that fungicould falsely appear to proliferate only because total DNA contentwent down as bacterial numbers fell. Thus we sought to correct theabove assays, which were normalized to weight of DNA, to betterFigure 1. Diagram of the experiment.The time line for the 76 days of sample collection is shown along the top, and the periods of antibiotictreatment are shown at the bottom. Antibiotic treatment was initiated at time zero.doi:10.1371/journal.pone.0071806.g001PLOS ONE | www.plosone.org2August 2013 | Volume 8 | Issue 8 | e71806Fungi of the Gut MicrobiomeFigure 2. Relative microbial abundance inferred from QPCR.A) Longitudinal analysis of 16S rRNA gene copies per ng of stool DNA. Thegroups of mice tested are shown by the color code (key at right). Error bars indicate standard error. B) Longitudinal analysis of 18S rRNA gene copiesper ng of stool DNA. The groups of mice tested are shown by the color code (key at right). Error bars indicate standard error. The amplicon used wasdesigned to suppress amplification of DNA from mouse or food materials.doi:10.1371/journal.pone.0071806.g002reflect the counts of individual organisms by putting the finalanalysis on a per pellet basis. Average wet weights of pellets were16.08 mg (SD = 3.329) in the presence of antibiotic (n = 20) and18.64 (SD = 2.685) in the control mice (n = 19), a slight butsignificant difference (p = 0.0129, Mann-Whitney U test). Acomparison of dry weights showed no significant differencebetweenantibiotictreated(n = 5,mean = 10.615 mg,SD = 1.635791) and control mice (n = 5, mean = 10.875 mg,SD = 0.781025). Thus in what follows we treated the startingweights as equal.DNA yields per pellet differed substantially (Table 1). Quanti-fication of yields after 15 or 76 days of antibiotic treatment showeddrops of 4.7 and 5.7 fold (p = 5.761025, Mann-Whitney U test).After withdrawal of antibiotic treatment (AbxShortTerm, Day 76),the total DNA yield returned to within a factor of two of thestarting value. Evidently bacterial DNA is the predominant sourceof DNA in mouse pellets, and the community mostly returned toPLOS ONE | www.plosone.org3its former size after cessation of antibiotic treatment. Thus theanalysis of the numbers of microbial genomes needs to take intoaccount the drop in total DNA. In addition, we also corrected forinefficiencies in the Taqman detection of 16S rRNA gene copies,which arise because some 16S rRNA gene sequences containmismatches within the probe binding sites (described in theMethods).Taking these factors into account, we found that in the absenceof antibiotic treatment, a typical stool pellet contained 56108–26109bacteria, and this dropped to,56104bacteria after15 days of antibiotic treatment (Figure 3A and Table 1). Below weshow that 56104is in fact an overestimate, because most of the16S DNA was in fact derived from bacterial DNA in sterile mousefood. Bacteria returned to their former numbers after cessation ofantibiotic treatment. Fungal genomes were much less abundantinitially, only in the range of 56105–26106per pellet (Figure 3Band Table 1). After 15 days of treatment with antibiotics, theAugust 2013 | Volume 8 | Issue 8 | e71806Fungi of the Gut MicrobiomeTable 1.DNA yields and numbers of genomes inferred from data on ribosomal gene copies.SampleControl (Baseline)Control (Day 15)Control (Day 76)AbxShortTerm(Baseline)AbxShortTerm(Day 15)AbxShortTerm(Day 76)AbxContinuous(Baseline)AbxContinuous(Day 15)AbxContinuous(Day 76)DNA yieldper pellet;average (ng)1.08E+036.27E+024.50E+024.51E+021.13E+023.94E+024.39E+021.48E+021.08E+02DNA yieldper pellet(ng); (SD)4.47E+024.02E+022.72E+021.56E+027.42E+011.88E+021.79E+027.32E+011.32E+01Number ofBacterialgenomes/pellet;average2.17E+096.03E+086.51E+085.79E+085.43E+043.85E+085.55E+089.43E+042.09E+05Number ofBacterialgenomes/pellet;(SD)1.18E+095.48E+084.97E+083.43E+084.92E+043.12E+083.68E+086.53E+041.86E+05Number of micro-eukaryotegenomes/pellet; average2.95E+061.98E+061.12E+067.11E+053.56E+075.35E+054.62E+057.86E+072.43E+07Number of micro-eukaryotegenomes/pellet; SD1.25E+061.30E+069.43E+054.43E+051.38E+074.16E+051.96E+053.85E+077.94E+06MicroeukaryoteProportion0.0010.0030.0020.0010.9980.0010.0010.9990.991doi:10.1371/journal.pone.0071806.t001numbers increased to,56107, or an increase of 25–50 fold.Fungal genome numbers remained high for the period ofantibiotic treatment. Eight weeks after cessation of antibiotictreatment, counts in the ABXShortTerm groups returned to thepretreatment level. Thus changes in fungal cell abundance weresubstantial, though less than suggested by the analysis in Figure 2B,which was normalized to the total weight of DNA, because totalDNA went down with antibiotic treatment.Analysis of Bacterial Lineages using 454/Roche DeepSequencingTo assess the representation of microbial lineages present andchanges with antibiotic therapy, we analyzed the longitudinalDNA samples using 454/Roche pyrosequencing. DNA waspurified from stool from 13 time points (Figure 1). Bacterialsequences were amplified using primers matching the 16S rRNAgene V1V2 region [36,42]. Sequencing yielded 239,867 reads,which were condensed into OTUs at 97% similarity andtaxonomy assigned using the RDP classifier [43].Prior to antibiotic treatment, communities were dominated bythe Firmicute lineageLachnospiraceaeand the Bacteriodetes lineageBacteroidales,along with a substantial number of less abundantlineages (Figure 4; Figure S2 A-I presents time points for eachmouse individually). After one day of antibiotic treatment, thepreviously dominant lineages decreased sharply in abundance, andLactococcusbecame the dominant community member. At latertimes under antibiotic treatmentLactococcuswas the predominantor sole lineage detectable.Five aliquots of sterile mouse chow were analyzed byamplification with the V1V2 primers and 454/Roche pyrosequen-cing, revealing that a singleLactococcusOTU was the predominantphylotype in both stool from antibiotic treated animals and inchow (Figure S3). We thus conclude thatLactococcusDNA ispresent in sterile mouse food, and that the antibiotic treatmenteliminated the great majority of live bacteria, i. e. the 56104bacteria detected per pellet in Table 1 represents mostly bacterialDNA in food.After antibiotic treatment was stopped for the ABXShortTermgroup, major groups that were predominant before antibiotictreatment returned to their former levels, but at different rates. AnOTU classified asLachnospiraceaeand several OTUs classified asClostridiumreturned within one week. Several other clades,includingRuminococcaceaeand other Firmicutes increased inproportion by two weeks after cessation of treatment.Bacteroidalesdid not fully return until the end of the experiment at eight weeks.Enteroccocus, Escherichia,andPaenibacillus,which were not dominantmembers of the communities in the Control or antibiotic treatedgroups, had elevated proportions over the recovery period butdecreased in relative abundance after eight weeks off antibiotics.Table S1 presents a statistical analysis of the bacterial lineagesdetected and their behavior over the time course studied.Changes in the types of bacterial lineages were paralleled bychanges in the species richness (Figure 5). Prior to antibiotictreatment, 54.6 (SD = 6.9) phylotypes were detected after datafrom each mouse was normalized to 200 reads. After 2 days ofantibiotic treatment, this fell to 7 (SD = 2.0) and persisted for theremainder of the antibiotic treatment (p,2.2610216for compar-ison to the pretreatment group, Friedman test). Upon cessation ofantibiotic treatment, the community slowly returned to its formerrichness reaching 49.4 (SD = 5.6) lineages over 61 days, still lessthan the corresponding Control group which averaged 57.2(SD = 17) lineages on the same day (p = 0.02 Mann-Whitney Utest).Analysis of Microeukaryotes using 454/Roche DeepSequencingTo characterize microeukaryotes, we sequenced selectedsamples using 18S and ITS amplicons. To compare samples fromthe different treatment groups, 134,677 ITS sequences and 26,35518S sequences were generated, OTUs were formed, andtaxonomic attribution was preformed with BROCC [44]. The18S amplicon is more universal than the ITS amplicon [44], whilethe ITS amplicon provides greater resolution for some fungallineages [45], so both were used [37]. To check that the twoamplicons were yielding consistent information, we compared4August 2013 | Volume 8 | Issue 8 | e71806PLOS ONE | www.plosone.orgFungi of the Gut MicrobiomeFigure 3. Numbers of organisms per stool pellet.Values from QPCR were corrected to yield an estimate of the true numbers of organisms byaccounting for differential DNA yield, numbers of rRNA gene copies per genome, and efficiency of detection. A) Estimated numbers of bacterialgenomes per pellet. Note that during antibiotic treatment (Day 15), most of the 16S rRNA gene copies were derived from food and do notcorrespond to intact organisms. (B) Estimated numbers of fungal genomes per pellet. The x-axis shows the time point studied, and the y-axis showsthe inferred numbers of genomes. Each study group is indicated by the color code to the right of the figure panels.doi:10.1371/journal.pone.0071806.g003sequence samples from 15 mice amplified using both amplicons.Sequence samples were characterized by generating pairwiseUniFrac distances, then the distance matrices for each werecompared using Procrustes analysis. This showed high correlationbetween the two (p,0.0001, no better fits after 104permutations)and compositional comparison also showed similar profiles (FigureS1).The longitudinal behavior of fungal communities was exploredin detail using the ITS amplicon, which revealed strong effects ofboth antibiotic treatment and caging history of the animals(Figure 6; the full set of time points, with each animal shownindividually, is in Figure S4A-I). In the control animals (five micein each of two cages), although the composition of the bacterialcommunity remained relatively stable, the fungal communitychanged dramatically. For four samples taken over the first eightdays, most of the ten mice in the two cages showed colonization bydiverse fungal lineages, and no lineage predominated. By day 15,however, the situation had changed radically, with both cagesdominated by a phylotype annotated asWickerhamomyces.Thischanged by day 22, with cage 1 dominated byDebaryomyces,andPLOS ONE | www.plosone.org5August 2013 | Volume 8 | Issue 8 | e71806
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