Microbial and Functional Diversity within the Phyllosphere ofEspeletia Species in an Andean High-Mountain Ecosystem

Carlos A. Ruiz-Pérez,a,b,c Silvia Restrepo,b,c María Mercedes Zambranoa,b

Molecular Genetics, Corporación CorpoGen, Bogotá DC, Colombiaa; Colombian Center for Genomics and Bioinformatics of Extreme Environments, Bogotá DC,Colombiab; Universidad de Los Andes, Bogotá DC, Colombiac

Microbial populations residing in close contact with plants can be found in the rhizosphere, in the phyllosphere as epiphytes onthe surface, or inside plants as endophytes. Here, we analyzed the microbiota associated with Espeletia plants, endemic to thePáramo environment of the Andes Mountains and a unique model for studying microbial populations and their adaptations tothe adverse conditions of high-mountain neotropical ecosystems. Communities were analyzed using samples from the rhizo-sphere, necromass, and young and mature leaves, the last two analyzed separately as endophytes and epiphytes. The taxonomiccomposition determined by performing sequencing of the V5-V6 region of the 16S rRNA gene indicated differences among pop-ulations of the leaf phyllosphere, the necromass, and the rhizosphere, with predominance of some phyla but only few sharedoperational taxonomic units (OTUs). Functional profiles predicted on the basis of taxonomic affiliations differed from thoseobtained by GeoChip microarray analysis, which separated community functional capacities based on plant microenvironment.The identified metabolic pathways provided insight regarding microbial strategies for colonization and survival in these ecosys-tems. This study of novel plant phyllosphere microbiomes and their putative functional ecology is also the first step for futurebioprospecting studies in search of enzymes, compounds, or microorganisms relevant to industry or for remediation efforts.

Andean high-mountain environments have been reported asdiversity hot spots, mainly because of their endemic species

(1). The Paramos ecosystems within the Neotropical Andes con-sist of isolated, high-elevation areas that are reported to be theworld’s fastest-evolving biodiversity hot spot (2). These ecosys-tems are exposed to harsh environmental conditions, such as highincidence of UV radiation (3) and daily shifts in temperatures thatimpose selective pressure on native plants and their associatedmicrobiota (4). In particular, the phyllosphere of endemic plantsfrom Paramos represents a unique ecosystem for microbial com-munities with diverse and distinctive abilities to survive underconditions considered extreme for other forms of life.

The phyllosphere refers to all aboveground surfaces of anyplant, including leaves, stems, buds, flowers, and fruits (5). It actsas a landing stage where spores or other propagules can developand multiply (6) and has been reported as probably the largestecosystem on earth colonized by microorganisms, mainly bacteriaand fungi (7). Interest in studying the phyllosphere microbiota isgrowing due to its potential in terms of microbial interactions,survival under harsh environmental, nutrient or humidity condi-tions, and bioprospecting. The most emblematic plant in the Co-lombian Paramos is known as “frailejón,” a plant endemic to theregion and belonging to the genus Espeletia (8, 9). These plantshave unique adaptations that enable them to resist exposure to UVlight and daily temperature changes; they are in close relation withmore than 125 animal species (10) and are important for soilhealth and the capacity of these ecosystems to retain and regulatewater availability and to store carbon (11). Based on the develop-mental stage, these plants can be separated into different “tiers”(12). The upper tier is composed of young leaves somewhat pro-tected from the environment, the middle tier (midtier) is com-posed of fully mature leaves exposed to environmental conditions,and the necromass tier is composed of senescent leaves (Fig. 1).Finally, the root soil environment, which is humid, tends to have

an acidic pH, and is rich in carbon (11), can be very different fromthat of the plant phyllosphere.

Both environmental conditions and the host must influencethe functional ecology of plant microbial communities (13), driv-ing their composition and interactions. Microbial communitiesassociated with plants such as Espeletia (i.e., epiphytes and endo-phytes) should therefore reflect the adaptations to the environ-mental conditions to which they are exposed and have the meta-bolic plasticity required for them to thrive. The different planttiers also represent various microenvironments in which micro-bial communities should be taxonomically diverse or at least met-abolically differentiated. Thus, the ecology and molecular andfunctional diversity of microbial populations associated with Es-peletia plants may present key insights into understanding howmicroorganisms interact with and adapt to these extreme habitats.Based on these hypotheses, we analyzed Espeletia plant-associatedmicrobial communities, which remain largely unknown. Somestudies done by culturing bacteria and fungi, including mycorrhi-zae, indicate that many microorganisms are commonly associatedwith these plants and are probably important for nutrient avail-ability and decomposition of biomass (14–16). Other work hasfocused on endophytic fungi and their biocontrol and biotechno-

Received 28 August 2015 Accepted 30 December 2015

Accepted manuscript posted online 8 January 2016

Citation Ruiz-Pérez CA, Restrepo S, Zambrano MM. 2016. Microbial and functionaldiversity within the phyllosphere of Espeletia species in an Andean high-mountainecosystem. Appl Environ Microbiol 82:1807–1817. doi:10.1128/AEM.02781-15.

Editor: V. Müller, Goethe University Frankfurt am Main

Address correspondence to María Mercedes Zambrano,mzambrano@corpogen.org.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/AEM.02781-15.

Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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logical potential (12, 17). In this work, we used culture-indepen-dent means, 16S rRNA gene sequencing and GeoChip 5.0 func-tional microarrays, to address community structure, diversity,and functional potential using samples from different plant tiers.The description of bacterial communities allowed us to comparemicrobial structures across the plant and to highlight microbialcontributions to particular geobiological processes and the poten-tial of these communities in terms of metabolic plasticity and ad-aptation.

MATERIALS AND METHODSStudy site and sampling. Sampling was performed at El Coquito hotspring (04°52=27�N, 75°15=51.4�W) in the Natural National Park Los Ne-vados in Colombia (http://www.parquesnacionales.gov.co). Leaves weresampled from Espeletia hartwegiana according to reported methodologies(6, 18) with some modifications. Briefly, leaves (50 to 100 g) from threeindividuals were taken from three different tiers: (i) upper tier, youngleaves; (ii) midtier, mature and fully developed leaves; and (iii) lower tier,senescent leaves or necromass. Because of their ecological importance,only three individuals were sampled, in close proximity (within 10 m), to

avoid possible environmental effects. Two sets of leaves were taken fromeach individual, one for the epiphyte community analysis and one for theendophyte community. Roots (1 to 5 g) were taken from two differentplants with a sterile scalpel (Fig. 1).

DNA extraction. Endophyte DNA was isolated according to previ-ously reported methodologies, with some modifications (12, 19). Briefly,the plant tissue was surface sterilized by washing with sterile H2O to re-move dirt, placed in NAP buffer (124 mM Na2HPO4), and vortexed for 1min to dislodge epiphytes. Leaves were then shaved to remove the pubes-cence on their surface, which facilitates the subsequent sterilization pro-cess (12), washed with sterile H2O, submerged in 90% ethanol (60 s),5.25% sodium hypochlorite solution (6 min), and 70% ethanol (30 s), andfinally rinsed with sterile distilled H2O. Sterilization was checked by takingan imprint of the leaf on malt extract medium (12) and incubating at25°C. One gram of the previously treated material was cut into 0.1- to0.5-mm sections, placed in a 1.5-ml Eppendorf tube containing 1 g ofsterile 0.1-mm-diameter glass beads and 1 ml TE (10 mM Tris, 10 mMEDTA, pH 8.0), and homogenized in a Mini-BeadBeater (BioSpec Prod-ucts) for 5 min. DNA was extracted using the PowerSoil DNA isolation kit(Mobio Laboratories, Carlsbad, CA, USA), according to the manufactur-er’s instructions.

FIG 1 Overview of sampling site and Espeletia sp. morphology. (A) Sampling site (El Coquito Hot Spring, 04°52=27�N, 75°15=51.4�W). (Adapted from GoogleEarth [copyright 2015 DigitalGlobe and Google, Image Landsat].) (B) Espeletia sp. morphology. (C) Sampling distribution per individual collected. Y, youngleaves; M, mature leaves; N, necromass; R, roots; EP, epiphyte; ED, endophyte.

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We obtained epiphyte DNA by first releasing bacteria from the surfaceof leaves by submerging 10 to 20 g of healthy plant tissue in 100 ml ofrelease buffer (0.1 M potassium phosphate, 0.1% glycerol, 0.15% Tween80, pH 7.0) and vortexing for 7 min (13, 20). The remaining bacteria weredislodged from the leaves with the help of a sterile swab, and the buffer wasthen filtered through a 0.2-�m-pore filter. DNA was extracted using thePowerSoil DNA isolation kit.

Combined epiphyte and endophyte DNA was extracted from root andnecromass samples by cutting the tissue into 0.5- to 1-cm fragments,which were placed in 25 ml of release buffer in a 50-ml tube and homog-enized by vortexing for 10 min. The buffer was filtered through a 0.2-�m-pore filter, and the filters were used for DNA extraction using the Power-Soil DNA isolation kit. All DNA extractions were quantified using a Qubit2.0 fluorometer (Life Technologies Corporation, Carlsbad, CA, USA). Intotal, we obtained six epiphyte and six endophyte DNA extractions, cor-responding to the upper and middle tiers from three plant replicates, threeDNA extractions for the necromass tier, one for each replicate, and two forthe roots.

16S rRNA gene amplification and sequencing. The V5-V6 hypervari-able region of the 16S rRNA gene of Bacteria and Archaea was amplifiedwith primer 799F (5=-AACMGGATTAGATACCCKG-3=), which mini-mizes contamination from chloroplast DNA and amplifies a mitochon-drial product that is larger and thus easier to separate and differentiatefrom the microbial amplified products (21), and the reverse primer 1050R(5=-AGYTGDCGACRRCCRTGCA-3=) (22). DNA concentration was ad-justed as previously reported (13) and used in 25-�l PCR mixtures con-taining DNA (10 ng for endophytic fraction or 1 ng for epiphytic frac-tion), 2.5 �l 10� AccuBuffer [600 mM Tris-HCl, 60 mM (NH4)2SO4, 100mM KCl, 20 mM MgSO4, pH 8.3], 2 �l 10 mM deoxynucleoside triphos-phate (dNTP) mix, 0.5 �M of each primer, and 5 units of Accuzyme DNApolymerase (Bioline USA Inc., Taunton, MA, USA). Cycling conditionswere 94°C for 2 min, followed by 30 cycles of 94°C for 30 s, 55°C for 30 s,and 72°C for 45 s and a final extension of 72°C for 10 min. PCR productswere separated on a 3% agarose gel and purified based on amplicon sizedifference using the QIAquick gel extraction kit (Qiagen, Valencia, CA,USA) when necessary. The remaining samples were purified using theQIAquick PCR purification kit (Qiagen, Valencia, CA, USA). DNA wasquantified using a Qubit 2.0 fluorometer (Life Technologies Corporation,Carlsbad, CA, USA), and amplicons were sequenced on an IlluminaMiSeq machine with a paired-end protocol (PE-250; Molecular ResearchMR DNA, Shallowater, TX, USA).

Sequence analysis. Forward and reverse Illumina paired-end se-quence reads were assembled using the FastqJoin software (23) to obtainlonger sequences, using a minimum overlap of 150 bp, given the averagelength of our reads (�250 bp) and the total length of the V5-V6 region(�300 bp). Assembled reads were then analyzed using UPARSE (24) andQIIME 1.8 (25). The reads were first filtered by quality at a mean qualitylevel of �25 and then based on the maximum expected error (�0.5) (24)and separated according to the barcodes, and sequences with mismatchesin the primer or barcode or with ambiguous bases were excluded. Oper-ational taxonomic units (OTUs) were picked at 97% sequence similaritylevel using the UPARSE-OTUref algorithm, which includes a de novo andreference-based chimera-checking step. In this step, singletons were re-moved to avoid including sequencing errors as recommended in theUPARSE pipeline. Taxonomy assignment was performed with QIIME1.8, using the Greengenes reference database and taxonomy (version13_8) (26). The phylogenetic overlap of 97% between samples was com-puted using the core microbiome script in QIIME 1.8. Sequences assignedto “chloroplast” or “mitochondria” were removed from the data set (ap-proximately 2.8%). For tree-based analysis, representative sequences foreach OTU were aligned against the Greengenes core data set (27) usingPyNAST (28). The approximately maximum likelihood phylogenetic treewas built using FastTree (29).

Diversity analysis. Alpha and beta diversity analyses were performedusing both QIIME 1.8 (25) and the R package Phyloseq (30). We assessed

the richness in the different samples using the Chao1 index. For diversityestimates, we computed Shannon entropy and Gini-Simpson indices,which take into account richness and abundance. These indices are sen-sitive to abundant species and to abundant and rare species, respectively(31). They were transformed into effective numbers of species for com-parison among samples (32). In order to measure and compare diversityindices (i.e., beta diversity), we normalized the OTU tables using the vari-ance stabilization function from DESeq2 to account for different librarysizes and sequencing depth (33) wrapped in Phyloseq (30), as reportedearlier (34). Normalized tables were then used to estimate the differentialabundance of OTUs between microbial populations using DESeq2 (33).Principal coordinates analysis (PCoA) and hierarchical clustering werecomputed based on UniFrac distances. Alpha and beta diversity plots weremade using Phyloseq and SPSS Statistics 22 (IBM, New York, NY, USA).

Functional analysis. Metabolic pathways were predicted using thesoftware PICRUSt (35) after performing an additional closed-referenceOTU picking pipeline using QIIME 1.8. The resulting KEGG orthologieswere further processed using HUMAnN (36), which transforms 16SrRNA-based predictions into gene and pathway summaries. This sum-mary was then visualized using the Galaxy web-based applicationGraPhlAn (37–39). Total metagenomic DNA was also analyzed using theGeoChip 5.0 functional microarray (40, 41) (Glomics, Norman, OK,USA). The normalization was performed as previously described (42).Briefly, (i) spots with a signal-to-noise ratio of �2 were removed, (ii) thenormalized intensity of each spot was calculated by dividing the signalintensity of each sport by the mean intensity of all the spots of the array,and (iii) at least two of three spots were required for a gene to be positive(singleton removal). The normalized hybridization output was organizedbased on functional categories, singletons were removed, and data wereanalyzed using the multivariate statistical software package PRIMER-Ev6 (Plymouth Marine Laboratory). Principal coordinate ordinationswere used to visualize Bray-Curtis similarities. Analysis of similarity(ANOSIM) was used to assess the confidence in the similarities observed.Functional categories in each sample were compared using analysis ofvariance (ANOVA) (F statistic) and plotted using SigmaPlot v12 (SystatSoftware, Inc., San Jose, CA, USA).

Sequence and microarray data accession numbers. Sequence datawere deposited in the NCBI Sequence Read Archive (SRA) under acces-sion no. SRP060388 (see also the OTU sequences in the supplementalmaterial). GeoChip data were deposited in NCBI GEO under accessionno. GSE70539.

RESULTSMicrobial community composition and structure. The phyloge-netic composition of microbial communities associated with Es-peletia sp. was analyzed using 17 DNA samples, isolated from fourdifferent plant tiers, by amplifying and sequencing the V5-V6 re-gion of the 16S rRNA gene (Fig. 1). A total of 3,041,094 16S rRNApaired-end sequences were obtained, assembled into single se-quences, demultiplexed, and quality filtered, yielding a total of1,762,044 high-quality sequences. After the OTU clustering andchimera-checking steps, we obtained 6,744 to 102,266 sequencereads per sample and a total of 1,548 OTUs. Samples had an ap-proximate coverage in terms of OTUs of 79.8%, calculated usingobserved OTUs and Chao1 richness, estimates that ranged from656 to 1,165 (see Table S1 in the supplemental material). OTUaccumulation curves showed that most samples were well charac-terized with our sequencing efforts, in particular the epiphyte leafcommunities and the necromass and root samples (see Fig. S1 inthe supplemental material), the last two including combined en-dophyte and epiphyte communities. The endophyte leaf commu-nities were less well characterized, even though coverage was good(Good’s coverage, �96%) (see Table S1 in the supplemental ma-terial). Shannon and Simpson diversity indices (see Table S1 in the

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supplemental material) were transformed into effective numbersof species to compare samples (32). Both transformations showedthat diversity was significantly higher for the necromass and rootfractions (P � 0.05) than even the combined leaf endophyte andepiphyte fractions (Fig. 2).

Taxonomic affiliation was examined using the uclust-basedconsensus taxonomy classifier. There were few Archaea (0.1 to16%) in our data set, i.e., Crenarchaeota (marine benthic group A[MBGA]), Euryarchaeota (Thermoplasmata), and Thaumar-chaeota, and a low percentage of unclassified OTUs (�4% acrosssamples) that might represent new microorganisms. There wasalso a marked difference in OTU abundances across samples (seeFig. S2 in the supplemental material), and of the 1,548 OTUsidentified, only 174 were shared by all samples (see Fig. S3 in thesupplemental material). Among these core community OTUs, themost common corresponded to Acinetobacter sp., “CandidatusBaumannia” species, Burkholderia sp., Erwinia sp., Hymenobactersp., Klebsiella sp., Pseudomonas sp., Propionibacterium sp., andSphingomonas sp. The most abundant phyla in all plant sampleswere Acidobacteria, Actinobacteria, Bacteroidetes, Crenarchaeota,Firmicutes, and Proteobacteria even when subsampling at the low-est number of reads obtained, 6,700 sequences per sample (datanot shown) (Fig. 3). The phylum Proteobacteria was more abun-dant in endophyte and epiphyte communities of both young andmature leaves (71.38% to 85.83%) than in the necromass and rootfractions (51.94% and 45.40%, respectively). Within this phylum,there were marked differences in relative abundances across sam-ples at the class level, such as the higher abundance of Gammapro-

teobacteria in young and mature leaves (both endophytes and ep-iphytes) than in the root or necromass tiers (Fig. 3). However, thenecromass and root fractions had a higher relative abundance ofthe phylum Acidobacteria (11.81% and 20.28%, respectively) thandid the leaf habitat (2.40% to 3.66%), and there were more Bacte-roidetes and Alphaproteobacteria in the necromass fraction(21.05%) and Crenarchaeota in the root fraction (13.93%). Acti-nobacteria showed a relative abundance ranging from 4.07% to12.02% across samples.

A PCoA using weighted UniFrac distances was used to assess ifmicrobial communities clustered according to their plant mi-croenvironment (Fig. 4). The root fraction was separated from thephyllosphere (leaf endophyte and epiphyte) and necromass sam-ples. All leaf samples clustered together, indicating that they weresimilar and differed from the necromass and root fractions, asconfirmed by hierarchical clustering (see Fig. S4 in the supple-mental material). The similarity between epiphyte and endophyteleaf communities was also evident by the fact that the only differ-ences found corresponded to changes in abundance of few OTUsbelonging to Acidobacteria, Bacteroidetes, and Proteobacteria (seeFig. S5 in the supplemental material). Despite being part of thephyllosphere, the necromass had increased abundance of someOTUs from the phyla Acidobacteria, Actinobacteria, Bacteroidetes,Firmicutes, Proteobacteria, and candidate divisions FBP and TM7that distinguished this fraction from leaf epiphyte and endophytecommunities (see Fig. S5 in the supplemental material). The dif-ferences observed for the root fraction were driven by OTUsmainly from the phyla Acidobacteria, Actinobacteria, AD3, Arma-

FIG 2 Community diversity indices. Shapes indicate the means for the transformed Shannon (A) and Simpson (B) indices for each community (YED, youngendophyte; MED, mature endophyte; YEP, young epiphyte; MEP, mature epiphyte; N, necromass; R, root), and of the combined tiers YED � YEP (upper tier)and MED � MEP (middle tier). Variations among communities were tested with one-way ANOVA. Pairwise testing was corrected using Tukey’s post hoc test;letters (a, b) represent statistically significant differences (P � 0.05). The error bars show the standard errors (SE) for the replicates after the transformation toeffective number of species.

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timonadetes, Bacteroidetes, Chlamydiae, Chloroflexi, Crenar-chaeota, Firmicutes, Proteobacteria, TM6, TM7, and Verrucomicro-bia. These phyla were significantly more abundant in the rootfraction than in the phyllosphere communities (i.e., leaves and

necromass; P � 0.01) (see Fig. S5 in the supplemental material), afinding consistent with the aforementioned higher diversity mea-surements for the root fraction. Interestingly, Corynebacteriumsp., Pseudomonas sp., and Rothia sp. were more abundant in both

FIG 3 Relative abundance of bacterial phyla associated with Espeletia sp. YED, young endophyte; MED, mature endophyte; YEP, young epiphyte; MEP, matureepiphyte; N, necromass; R, root. The Proteobacteria phylum has been replaced by the corresponding classes (Alphaproteobacteria, Betaproteobacteria, Gamma-proteobacteria, and Deltaproteobacteria).

FIG 4 Principal coordinate analysis (PCoA) plot based on weighted UniFrac distances. The two axes represent 51.9% of the variation in the samples. Individual pointsrepresent the replicates for each sample. YED, young endophyte; MED, mature endophyte; YEP, young epiphyte; MEP, mature epiphyte; N, necromass; R, root.

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the epiphyte and endophyte fractions than in the necromass androot fractions.

Metabolic profiles vary according to plant microenviron-ment. To further understand how Espeletia plant microhabitatsaffect microbial communities, we analyzed the samples using abioinformatics 16S rRNA-based prediction approach and a func-tional microarray. We predicted the metabolic potential of each ofthe communities using PICRUSt (35). Based on this information,we constructed a tree depicting the main metabolic pathways, cat-egorized by the KEGG database (43), combined with a heat map ofgene “abundances” for each category in every sample (see Fig. S6in the supplemental material). The predicted functional categoriesshowed genes involved in xenobiotic degradation, in carbohy-drate, lipid, amino acid, and cofactor metabolism, in biosynthesisof secondary metabolites, and in energy metabolism. Interest-ingly, genes involved in replication and repair pathways, includingbase excision repair (alkB), DNA replication, homologous recom-bination (radA, radB, radC, recF, recO, recN), mismatch repair(mutS, mutS2, mutL, mutH, vsr), and nucleotide excision repair(mfd) systems, were also predicted to be present in the samples. Allthese mechanisms are involved in repair of DNA damage causedby UV (44). The degradation of xenobiotics and the biosynthesisof secondary metabolites such as antibiotics, alkaloids, polyketides,and terpenoids were also a relevant feature of this prediction (seeFig. S6 in the supplemental material). Although the 16S rRNA-based predictions did not show any clear separation between thecommunities, we found statistically significant differences be-tween the endophyte community and the root and necromasscommunities (ANOSIM, global R 0.359, P � 0.05, n 17,permutation 9,999) (Fig. 5A).

To obtain information regarding the actual functional profilesof these microbial communities, we used the GeoChip 5.0 func-tional microarray, which contains over 167,000 probes coveringmore than 395,000 coding sequences from approximately 1,500functional gene families involved in several biogeochemical, cel-lular, and ecological processes. All microbial communities hadgenes involved in carbon fixation and degradation pathways, ni-trogen, phosphorus, and sulfur metabolism, organic remediation,secondary metabolism, virulence-related genes, and environmen-tal stress responses. Protection against high UV exposure, whichcan occur in the exposed microenvironment of the leaves, wasevident by the presence of genes involved in pigment production(acsF, bacteriorhodopsin gene, bchG, blh, ctrW, pebB, among oth-ers) and in repair of DNA damage, as mentioned above, causeddirectly by UV or by UV-induced production of agents such areactive oxygen species (ROS) (44). There were statistically signif-icant differences among the communities analyzed (ANOSIM,global R 0.524, P � 0.05, n 16, permutation 9,999). Pair-wise comparisons showed that the epiphyte, root, and necromasscommunities shared greater similarity, while the endophyte com-munities were significantly different from the rest of the commu-nities (P � 0.05). Compared to the ordination analysis performedusing the 16S rRNA-based predictions, the GeoChip analysis sep-arated the endophyte communities from the rest (Fig. 5B).

Nutrient utilization and survival. Even though gene familiesfor several metabolic pathways were detected with GeoChip (seeFig. S7 in the supplemental material), we focused on functionsrelevant to microbial growth and survival that could provide in-sight regarding strategies for adaptation to the harsh high-moun-tain plant environment of Espeletia sp. Pathways associated with

carbon cycling were abundant and present in all communitiesassociated with the plant. There was evidence of autotrophic ca-pacity due to genes involved in six carbon fixation pathways (seeFig. S8 in the supplemental material), of the capacity to formcarboxysomes (bacterial microcompartments that contain en-zymes involved in carbon fixation), and of the ability to carry outC1 metabolism such as methanogenesis, mainly in root and epi-phyte fractions, and methane oxidation (see Fig. S8 in the supple-mental material). Heterotrophic metabolism was also foundwithin our samples. The pathways involved in carbon degradationwere highly abundant in all samples, but more so in the epiphyte,necromass, and root fractions (P � 0.05) (Fig. 6). Functionsranged from the utilization of labile carbon sources such as starch,the most abundant pathway overall, to the metabolism of recalci-trant polymers such as lignin and other plant-derived compoundssuch as cellulose, hemicellulose, pectin, and terpenes. There werealso genes for the degradation of organic aromatic compoundsthat, in some cases, had a higher relative abundance than thoseinvolved in the metabolism of the more common cellulose, hemi-cellulose, and pectin plant components (see Fig. S9 in the supple-mental material). Taxa abundant in the necromass fraction,

FIG 5 Analysis of microbial metabolic potential. PCoA based on Bray-Curtissimilarities calculated for metabolic profiles predicted with PICRUSt (the twoaxes represent 85.5% of the variation) (A) and metabolic profiles derived fromthe GeoChip analysis (the two axes represent 65.6% of the variation) (B).Individual points represent the replicates for each sample. YED, young endo-phyte; MED, mature endophyte; YEP, young epiphyte; MEP, mature epiphyte;N, necromass; R, root.

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Methylobacterium sp., Pedobacter sp., Sphingomonas sp., and Spi-rosoma sp., and in roots, “Candidatus Koribacter” and “Candida-tus Solibacter,” were associated with increased carbon utilizationgenes. Nitrogen cycling pathways, such as assimilatory nitrate re-duction, denitrification, nitrification, nitrogen fixation, ammon-ification, and anammox pathways, were also present in all frac-tions, although at lower levels than pathways for carbon cycling(see Fig. S10 in the supplemental material). The root fraction hada higher abundance of genes for assimilatory and dissimilatorynitrate reduction, nitrification, and nitrogen fixation, while path-ways for ammonification, denitrification, and anammox weremore abundant in the necromass and epiphyte fractions.

The functional microarray analysis also detected genes indica-tive of microbial capacity to respond to adverse environmentalconditions. These include responses to acidic and alkaline shock,cold and heat shock, glucose, phosphate, and nitrogen limitation,osmotic stress, oxidative stress, oxygen limitation, and the strin-gent response (data not shown). Genes involved in the productionof bacterial pigments and of enzymes involved in the removal ofROS were also present (Fig. 7). Finally, genes involved in the pro-duction of antibiotics, associated mainly with Actinobacteria andProteobacteria, were also evident in all samples. Moreover, all sam-ples had a remarkable abundance of antibiotic resistance genesbelonging to several phyla, as well as the presence of plant hor-mone production genes.

DISCUSSION

The present study of the phylogenetic and functional profiles ofEspeletia sp.-associated microbial communities examines novelhost-associated microbiomes and reveals features of their func-tional ecology that can provide useful insight regarding strategiesfor microbial plant colonization and survival. The Espeletia sp.microbial communities showed the dominance of few bacterial

phyla, which also tend to dominate in phyllosphere microbiomesfrom Arabidopsis thaliana (13), Thlaspi geosingense (45), potato(46), soybean (47), almond drupes (48), and several tree species(18, 49), among others (50). In addition to this similarity at thephylum level, Espeletia communities also contained taxa, such asBacillus, Burkholderia, Methylobacterium, Pseudomonas, Sphin-gomonas, and Xanthomonas, that are an important fraction of thecore community in several plants (7, 13, 50). It is difficult to assess,

FIG 6 Mean normalized signal intensity of several carbon-degrading genes. Genes are clustered by major carbon sources: starch, hemicellulose, cellulose,camphor, chitin, cutin, inulin, lignin, pectin, terpenes. The signal intensity was normalized by the mean intensity of the microarray. Mean values of samples wereplotted with their respective SE. Variations among communities were tested with one-way ANOVA. Pairwise testing was corrected using Tukey’s post hoc test;letters (a, b, c) represent statistically significant differences (P � 0.05). YED, young endophyte; MED, mature endophyte; YEP, young epiphyte; MEP, matureepiphyte; N, necromass; R, root.

FIG 7 Mean normalized signal intensity of UV resistance-related genes.Genes are clustered by major functions: antioxidant enzymes, oxidativestress response, and pigment production. The signal intensity was normal-ized by the mean intensity of the microarray. Mean values of samples wereplotted with their respective SE. Variations among communities weretested with one-way ANOVA, and letters (a, b) indicate statistically signif-icant differences (P � 0.05). Pairwise testing was corrected using Tukey’spost hoc test; letters represent statistically significant groups. YED, youngendophyte; MED, mature endophyte; YEP, young epiphyte; MEP, matureepiphyte; N, necromass; R, root.

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however, if these bacterial communities are stable (51–53), andsampling at different months throughout the year could improveour capacity to discriminate between permanent and temporaryphyllosphere residents. Despite this difficulty, the fact that themost abundant phyla and bacterial species are shared across plantssuggests that there is a widespread “global” core communityadapted to life in the phyllosphere. In addition, the presence ofunclassified OTUs, both in this and previous studies, also suggeststhat there is still more diversity to be found in the plant phyllo-sphere (54–57).

Differences in plant-associated microbiomes are probably de-termined by changes in relative abundances or the presence of rarebacterial taxa with important ecological functions. Given the dif-ferent leaf microenvironment of endophytic and epiphytic micro-organisms, we expected the corresponding community structuresto vary. However, these two communities were very similar intaxonomy, they shared most OTUs, and were no different in rich-ness or diversity indices, in contrast to what has been reported forA. thaliana leaf endophyte and epiphyte communities (13). Theseinconsistent results could be attributed to the use of a small num-ber of plant samples or of a different plant species or to differencesin the protocols used for obtaining phyllosphere communityDNA. However, the differences in terms of diversity and relativeabundance of taxa between Espeletia leaf phyllosphere communi-ties and necromass and root communities suggest niche-selectiveproperties. Overall, the presence of shared taxa across plant tiersindicates that these communities are interconnected and that bac-teria can travel from the rhizosphere toward the leaves and viceversa, as has been reported previously (13, 58, 59). The high di-versity observed in terms of bacterial composition and functionalpotential for both the necromass and root fractions is consistentwith the fact that these communities are shaped by factors thatcontrast with those affecting phyllosphere communities. Whilethe leaf surface is considered a water- and nutrient-limited envi-ronment (6), both the necromass, which consists of senescentmaterial, and the more stable and exudate-rich root microen-vironment contain more readily available nutrients (13, 60). Inaddition, both the necromass and soils environments are moreprotected from environmental conditions such as UV exposureand desiccation (50).

The functional analysis of the various samples obtained fromEspeletia plants revealed metabolic capabilities relevant for micro-bial survival in these ecosystems. Both the 16S rRNA-based pre-diction and the GeoChip 5.0 analysis, which has been used toassess the metabolic pathways in other ecosystems (40, 42, 61–63),showed that these communities possess a diverse and versatilemetabolic potential. However, communities were separated basedon plant microenvironment only via GeoChip analysis, indicatingthat predictions can yield valuable global information but maynot be an adequate reflection of the community variations de-tected only when analyzing samples directly. The GeoChipanalysis also revealed differences between communities interms of the relative abundance of some functional groups.Epiphytes, for example, had a greater abundance of genes in-volved in utilization of carbon sources such as starch, hemicel-lulose, and cellulose, among others, and in nitrogen utilizationpathways, which were also abundant in the necromass fraction,such as ammonification, denitrification, and anammox. Thesedifferences could suggest adaptations to niches and nutrientavailability, particularly when comparing the necromass and

root samples with the leaf communities. However, differencescould also be due to variations in biomass recovery, particu-larly from the less abundant endophyte population.

Carbon cycling pathways, which were among the most abun-dant detected using GeoChip analysis (see Fig. S7 in the supple-mental material), revealed that plant-associated microbial com-munities can use diverse growth strategies. There was evidence ofautotrophy (mainly represented by Calvin cycle genes) and C1metabolism, but based on pathway abundances, microorganismsprobably use predominantly heterotrophic growth on plant- orinsect-derived carbon sources such hemicellulose, chitin, starch,pectin, and lignin. The pathways for carbon degradation weremore abundant in the epiphyte, necromass, and root fractions andcould reflect differences in nutrient availability. Many of the iden-tified genes were associated with taxa abundant in the necromasstier, which is characterized by senescent plant material, that havebeen reported in other plants to be important for carbon utiliza-tion, such as Bacillus sp. (64), Klebsiella sp. (65), Propionibacte-rium sp. (66, 67), and Pseudomonas sp. (68, 69). Interestingly, theroot community had increased abundance of “Candidatus Korib-acter” and “Candidatus Solibacter,” two Acidobacteria membersthat have been isolated from Arctic soils and are reported to havemetabolic versatility and many genes involved in breakdown ofstarch, hemicellulose, and pectin, among others (70). Genes in-volved in the degradation of aromatic compounds were also iden-tified in our samples, consistent with the presence of compoundsin Espeletia sp. plants, such as -pinene, �-pinene, -thujene, andlongipilin acetate, among others (71–73), that can shape thesepopulations, particularly in the necromass, where they may beused for the degradation of senescent leaves. Finally, the presenceof genes for degradation of organic contaminants suggests thatthese plants may be more influenced by human intervention thanpreviously thought and opens the possibility of exploiting thesecommunities for bioremediation purposes or in industrial pro-duction systems.

The presence of genes for methanogenesis, especially in theepiphyte and root fractions, suggests that this C1 metabolic path-way could occur in the plant environment, consistent with a re-cent report indicating that methanogenesis can take place inplants in the presence of oxygen by not-yet-identified mechanisms(74). In our work, these genes were associated mainly with ar-chaeal genes from members of the class Methanomicrobia, inwhich these pathways have been described (75, 76). It is possiblethat methanogenesis could occur in oxygen-limited biofilm struc-tures on leaves, consistent with the high abundance of Pseudomo-nas spp., microorganisms long recognized as plant colonizers andbiofilm formers (13, 53, 68). Finally, methane produced bymethanogenic microorganisms, besides being used by metha-notrophs as a carbon source, can be coupled to the nitrogen cycle,as has been reported recently (77, 78). Our GeoChip results alsoindicated that these plant microbial communities could performalmost every transformation of nitrogen, especially in the rootfraction, where these pathways were more abundant. The abun-dance of carbon and nitrogen functional groups in plant samplessuggests that microbial communities in the roots might be moreactive in providing nitrogen in a usable form whereas phyllo-sphere communities provide carbon sources as nutrients.

In addition to nutrient acquisition, plant microbial communi-ties must also be able to survive under the environmental condi-tions of the particular habitat and as part of a complex community

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of bacteria, fungi, insects, and nematodes, using strategies thatshould be revealed in the functional profiles obtained. Severalmechanisms for resistance to solar radiation were identified in oursamples, such as production of pigments and genes involved inprotection from ROS, consistent with the high exposure to UVradiation (3). The presence of genes involved in antibiotic produc-tion, particularly by Actinobacteria, can be indicative of microbialcompetition for nutrients and space. Although these metabolitescould be used as signaling molecules, as suggested previously (79),the widespread presence of genes involved in antibiotic resistanceacross several taxa could also indicate ongoing competition. Fi-nally, the production of plant hormones suggests an importantrole for these microorganisms in their association with the planthost. Microbial production of plant hormones has been reportedto promote growth and development (80) and to prevent the entryof plant pathogens by modulating the plant’s immune system (57,81). The relation between bacteria and host growth and mortalityhas been previously described (49), suggesting that microbialcommunities may indeed be important for plant development.The present study therefore represents a starting point for uncov-ering possible interactions between microbial communities andEspeletia sp. development and health that become particularly rel-evant given the importance of these plants to these strategic yetthreatened ecosystems and the recent reports of their increasedmortality from causes that are still unclear but related to the pres-ence of insects and/or fungi (82).

This study provides both taxonomic and functional informa-tion regarding Espeletia plant microbiomes. Taxonomic analysisindicated a continuum of microorganisms throughout the plantand communities with functional profiles shaped by specific nichecharacteristics. The presence of genes involved in growth and sur-vival and in interactions with other species indicates that theremight be both functional complementation and competitionamong microbial communities that, in addition, might also beimportant for host health. Although no new mechanisms for ad-aptation were identified, given the limitations of the meta-genomics approaches used, this survey of microbial communitiesand their encoded functions provides a starting point for futurestudies aimed at understanding adaptations of the Espeletia phyl-losphere microbiota, the roles played by these microorganisms,and their relevance in these ecosystems, which hopefully may leadto strategies for conservation of these plants. In addition, the datacan also be used for comparing microbiomes between locally re-stricted plants, such as Espeletia, with more globally distributedspecies. Lastly, this work also opens the possibility of bioprospect-ing for microbial processes such as nutrient utilization, remedia-tion, and antimicrobial compound production in the phyllo-sphere microbiome of plant species endemic to high Andeanmountains.

ACKNOWLEDGMENT

We declare that we have no competing interest in relation to the workpresented in this paper.

FUNDING INFORMATIONThis work was financed by Colciencias (contract no. 573-2012 and 649-2013) and was performed under MADS contract no. 76-2013 for access togenetic resources and UAESPNN Research permit no. PIDB DTAO 021-10. The funding agencies had no role in study design, data collection andinterpretation, or the decision to submit the work for publication.

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