Diversity, Specificity, and Phylogenetic Relationships of Endohyphal Bacteria in Fungi That Inhabit Tropical Seeds and Leaves

Interactions between fungi and tropical trees help shape some of the most biodiverse communities on earth. These interactions occur in the presence of additional microbes that can modify fungal phenotypes, such as endohyphal bacteria (EHB). Here we examine the occurrence, diversity, and taxonomic composition of EHB in fungi that colonize seeds and leaves of plants in tropical forests. We use PCR and fluorescence microscopy to detect EHB in fungi, and a phylogenetic approach to explore evolutionary relationships among seed- and leaf-inhabiting fungi and their bacterial partners. Analyses focusing on two prevalent orders of fungi (Hypocreales and Xylariales) revealed that seed- and leaf-inhabiting fungi have a shared evolutionary history, yet differ in the prevalence, richness, and composition of their endohyphal symbionts. Phylogenetic analyses detected that the endohyphal habit is widespread, here encompassing members of seven phyla of bacteria (including three classes of Proteobacteria). Occurring in seed- vs. leaf-associated fungi has not resulted in detectable structure in the evolution of EHB, and no congruence was observed in the phylogenetic relationships of these apparently facultative, horizontally transmitted symbionts and their fungal hosts. Our results are consistent with multiple origins of fungus-bacterium associations and argue for evaluating focal pairs to determine how particular EHB affect the establishment or maintenance of fungal symbioses in seeds and leaves.


INTRODUCTION
Interactions between fungi and tropical trees contribute directly to shaping some of the most biodiverse communities on earth Zimmerman and Vitousek, 2012;Peay et al., 2013;Bagchi et al., 2014). Fungi that recruit to seeds in soil can alter seed fate by influencing secondary dispersal, dormancy, germination, and survival (Knoch et al., 1993;Gallery et al., 2007a,b;Dalling et al., 2011;Sarmiento et al., 2015). Fungi in sapwood and roots can change nutrient acquisition or transport, water transport, and tissue integrity (Blanchette, 1991;Agrios, 1997;Bonfante and Genre, 2010;Oliva et al., 2014). In leaves, fungi can alter photosynthetic rates, gas exchange, interactions with natural enemies, and growth (Pinto et al., 2000;Gilbert, 2002;Rodriguez et al., 2009;Grimmer et al., 2012). Together these interactions underlie a major component of forest dynamics and the maintenance of biological diversity in tropical plant communities (Gilbert, 2002).
Interactions of plants and fungi are influenced both by environmental factors and by the intricate processes of hostsymbiont recognition (see Agrios, 1997;Schafer and Kotanen, 2003;Jones and Dangl, 2006;Kluger et al., 2008;Gallery et al., 2010). They also can be shaped by additional microbes that modify fungal phenotypes (Frey-Klett et al., 2007;Márquez et al., 2007). Plant-fungus interactions in complex, heterogeneous environments such as tropical forests may be especially subject to influence from other microbes (Frey-Klett et al., 2007;Bonfante and Anca, 2009). Such "symbio-modulatory" microbes may occur in the same microenvironments as the primary interactors, on their surfaces, or within their tissues, influencing the outcome of interactions through substrate modification, regulation of gene expression, or metabolite production (Partida-Martinez and Hertweck, 2005;Bonfante and Anca, 2009;Salvioli et al., 2010Salvioli et al., , 2016Hoffman et al., 2013).
Together these studies indicate that EHB can shape the phenotypes of plant-associated fungi with downstream effects on the fungus-plant interactions that contribute in turn to forest ecology. As a first step toward elucidating such interactions, we examined the occurrence, diversity, distribution, taxonomic placement, and evolutionary history of EHB in fungi associated with plants from lowland tropical forests. We focused specifically on seed-associated and foliar endophytic fungi, which are highly diverse functional groups that each encompass a gradient of beneficial to antagonistic interactions with seeds or leaves, respectively (Arnold et al., 2003;Arnold and Engelbrecht, 2007;Gallery et al., 2007a;Kluger et al., 2008). Here, we first determine the phylogenetic placement of these fungi and evaluate whether their use of distinctive host tissues (seeds vs. leaves) reflects divergent evolutionary histories. Upon establishing that they do not appear to be evolutionarily distinct, we next determine the frequency and diversity of EHB in representative fungal lineages. We infer the phylogenetic relationships of EHB to place these symbionts taxonomically, and then use measures of phylogenetic diversity and signal to inform their evolutionary history. Finally, we compare relationships among EHB with the phylogenetic relationships and ecological modes of their hosts.

Fungi Examined
We selected fungi isolated during previous studies from a living culture collection at the Robert L. Gilbertson Mycological Herbarium, University of Arizona, Tucson, USA (ARIZ) (Gallery et al., 2007a,b;Del Olmo-Ruiz and Arnold, 2014;Zalamea et al., 2015). We focused on two functional groups dominated by the species-rich Ascomycota: seed-associated fungi and foliar endophytic fungi. Both groups are highly diverse in lowland tropical forests, but are generally understudied with regard to their phylogenetic affinity, taxonomy, and ecological modes.
All fungi used in this study were isolated originally at Barro Colorado Island, Panama (BCI: 9 • 10 ′ N, 79 • 51 ′ W; 86 m.a.s.l.) or La Selva Biological Station, Heredia, Costa Rica (LS: 10 • 26 ′ N, 83 • 59 ′ W; 35 m.a.s.l.). Barro Colorado Island is located in a seasonally moist tropical forest (Holdridge, 1947) with an average rainfall of 2600 mm/y and a pronounced dry season from January to April (Leigh, 1999). The flora and vegetation of BCI have been described previously (Croat, 1978;Foster and Brokaw, 1982). La Selva is located in a wet tropical forest (Holdridge, 1947) with an average rainfall of 3962 mm/y (Sanford et al., 1994). The flora and vegetation of LS are described by La Flora Digital de La Selva 1 .
Seed-associated fungi were isolated originally from surfacesterilized seeds of trees following burial and incubation in soil in the forest understory at BCI (Supplementary Table 1). Seeds were retrieved from the soil at intervals (1-6 months following burial) and surface sterilized by sequential immersion in 95% ethanol (10 s), 0.7% sodium hypochlorite (NaClO; 2 min), and 70% ethanol (2 min). Each seed was allowed to surface-dry and cut in half under sterile conditions, and then plated on 2% malt extract agar (MEA), prepared without antibiotics, to isolate fungi from the seed interior (Gallery et al., 2007a;Sarmiento et al., 2015;Zalamea et al., 2015).
Foliar endophytic fungi were isolated originally from surfacesterilized, healthy leaves of diverse vascular plants at BCI and LS (Supplementary Table 1). Leaf pieces were washed with deionized water, patted dry, cut into small fragments (ca. 2-mm 2 ), surface sterilized as above but using 0.525% NaClO, allowed to dry under sterile conditions, and plated on 2% MEA prepared without antibiotics (U'Ren et al., 2009;Del Olmo-Ruiz and Arnold, 2014;Del Olmo-Ruiz and Arnold, in revision;Arnold, unpublished data).
Emergent hyphae were isolated into pure culture and deposited as living vouchers at ARIZ. These vouchers were used in the present study. A diversity of fungi was obtained in culture (Gallery et al., 2007a,b;U'Ren et al., 2009;Del Olmo-Ruiz and Arnold, 2014;Del Olmo-Ruiz and Arnold, in revision;Sarmiento et al., 2015;Zalamea et al., 2015), but two genera were particularly common among isolates from seeds and leaves (putative Fusarium, Hypocreales; putative Xylaria, Xylariales). We therefore focused our work on these taxa, first using phylogenetic methods (below) to confirm the taxonomic placement and ecological diversity of isolates in each group.

DNA Extraction and PCR
Total genomic DNA was extracted from axenic fungal cultures following  or with the Extract-N-Amp Plant Mini Kit (Sigma-Aldrich, St. Louis, MO, USA) following the manufacturer's instructions. The former is a phenol:chloroform based extraction and the latter a more rapid two-step kit that was adopted for convenience. Both methods provide comparable results (Sandberg et al., 2014). We used the forward primers ITS1F or ITS5 and reverse primers LR3 or ITS4 (10 µM) to amplify the nuclear ribosomal internal transcribed spacers and the 5.8S gene (ITS ribosomal DNA [rDNA]), and when possible, the first 600 base pairs (bp) of the large subunit (partial LSU rDNA). Fragment sizes ranged from ca. 600 (ITS rDNA) to 1200 bp (ITS rDNA-partial LSU rDNA). PCR methods followed  unless genomic DNA was obtained using the Extract-N-Amp kit, in which case methods followed the manufacturer's instructions.
Reactions were run on PTC-200 thermal cyclers (Bio-Rad, Hercules, CA, USA) with the following cycling parameters: 1 http://sura.ots.ac.cr/florula4/ 94 • C for 3 min; 35 cycles of 94 • C for 30 s, 55 • C for 30 s, and 72 • C for 2 min; and 72 • C for 10 min. PCR products were evaluated by visualizing with SYBR Green I (Molecular Probes, Invitrogen, Carlsbad CA, USA) after electrophoresis on 1% agarose gels. Positive PCR products producing single bands were sequenced directly (see below). Negative controls included water instead of template and were always blank, indicating no contamination during the DNA extraction or amplification process.
Products producing multiple bands or displaying weak amplification were cloned with StrataClone cloning kits (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer's instructions, except that we used one-half the recommended reagent volumes for each reaction. Following blue/white screening, successful transformants were transferred to fresh plates and allowed to grow an additional 24 h to increase colony size. Eight positive clones per isolate were amplified using primers M13F(−20) and M13R(−27; numbers indicate specific primer variants) (10 µM) (Hoffman and Arnold, 2010). The cycling parameters were 94 • C for 10 min; 35 cycles of 94 • C for 1 min, 54 • C for 1 min, and 72 • C for 2 min; and 72 • C for 10 min. Up to eight positive PCR products per isolate were selected for sequencing.
Positive PCR products showing one band of the appropriate length were cleaned with ExoSAP-IT (Affymetrix, Santa Clara, CA, USA) following the manufacturer's instructions. Cleaned products were diluted 1:2 with sterile water prior to sequencing.

Sequencing and Assembly
Positive products were sequenced bidirectionally with the original PCR primers (5 µM) at the University of Arizona Genetics Core (Applied Biosystems BigDye Terminator v3.1 cycle sequencing kits; Applied Biosystems AB3730XL DNA Analyzer; Foster City, CA, USA). An assembly pipeline consisting of phred and phrap  driven by Chromaseq (Maddison and Maddison, 2005) in Mesquite v.2.75 ) was used to call bases and assemble reads into contigs. Base calls were verified by manual inspection of chromatograms in Sequencher v.5.1 (Gene Codes Corp., Ann Arbor, MI, USA). ITS rDNA-partial LSU rDNA sequences were submitted to GenBank (accessions KU977534-KU978121, KU978403-KU978448, and KX530755-KX530763).
We used BLASTn comparisons with GenBank (nucleotide collection [nr/nt]) (Altschul et al., 1990) and the Ribosomal Database Project (RDP) Fungal ITS Classifier (Deshpande et al., 2015) to select 223 strains for further study. These were isolates that were tentatively identified as Fusarium, Xylaria, or close relatives of those genera. Together these fungi represented isolates from 29 species of vascular plants from BCI and LS (three species of ferns, foliage only; 26 woody angiosperms, foliage and/or seeds) (Supplementary Table 1).
Top matches in database searches are not always closest phylogenetic neighbors and consequently may be inappropriate for identification (see U'Ren et al., 2009;Koski and Golding, 2012;Porter and Golding, 2012;U'Ren et al., 2016). Therefore, we used phylogenetic analyses to clarify the taxonomic placement of these strains and the resulting phylogenies to inform the distribution of seed-associated vs. foliar endophytic habits in each focal group.

Phylogenetic Analyses of Fungal Strains
Phylogenetic Reconstructions Using ITS rDNA and ITS rDNA-Partial LSU rDNA BLASTn-and RDP classification with parallel examination of preliminary sequence alignments led us to assemble 19 data sets that encompassed Fusarium and close relatives in the Hypocreales, and Xylaria and close relatives in the Xylariales (Supplementary Table 1). Care was taken to match the phylogenetic information provided by ITS rDNA or ITS rDNA-partial LSU rDNA with the appropriate breadth of taxon sampling in each focal data set. We delimited our taxon sampling in part by reviewing existing phylogenetic hypotheses for each group, and by evaluating the limitations imposed by ambiguous alignments of ITS rDNA at broad taxonomic levels (see Schroers, 2001;Zhang et al., 2006;O'Donnell et al., 2008;Hsieh et al., 2010;Lombard et al., 2010;Chaverri et al., 2011;Short et al., 2013;U'Ren et al., 2016).
For each dataset, we first used Muscle v3.7 (Edgar, 2004) to align sequences with well-curated references from GenBank (i.e., those from type specimens and/or published species descriptions, and with information on host, substrate, and geographic origin, if available; Supplementary Table 2). We then edited each alignment by eye in Mesquite v2.75 ). Ambiguously aligned characters were excluded. Matrix details are listed in Supplementary Table 3 and alignments submitted were to TreeBASE 2 .
Maximum likelihood analyses were conducted in RAxML v.8.2.4 (Stamatakis, 2014) with bootstrap support determined on the basis of 1000 pseudoreplicates. Bayesian analyses were conducted in MrBayes v.3.2.6 (Huelsenbeck and Ronquist, 2001;Ronquist and Huelsenbeck, 2003) with six million generations, initiated with random trees, four chains, sampling every 1000th tree, and a burn-in of all trees with a standard deviation of split frequencies ≥ 0.01. Bayesian analyses did not converge after six million generations for the Fusarium solani species complex, so the run was extended to 30 million generations. For both ML and Bayesian analyses, we used jModelTest2 (Posada, 2008;Darriba et al., 2012) to select the appropriate model of sequence evolution. Models for each alignment are listed in Supplementary  Table 3. Muscle, RAxML, Mr. Bayes, and jModelTest2 were implemented using the CIPRES Science Gateway (Miller et al., 2010).

Multilocus Analyses
Relationships remained unresolved in the analyses outlined above for two taxonomic groups: the Fusarium solani species complex (FSSC) and Gliocladiopsis. We therefore used multilocus data to improve our inferences. For FSSC we used ITS rDNA-partial LSU rDNA, the RNA polymerase II second largest subunit gene (RPB2; 1500-1800 bp in length), and the translation elongation factor 1-alpha gene (TEF; 600-900 bp in length) following Short et al. (2014). For Gliocladiopsis we used ITS rDNA, the RNA polymerase II largest subunit gene (RPB1; 400 2 http://purl.org/phylo/treebase/phylows/study/TB2:S19714 to 600 bp in length), and TEF following Castlebury et al. (2004) and Hirooka et al. (2013). PCR primers and cycling conditions are detailed in the Supplementary Materials and Methods. These sequences were submitted to GenBank (accessions KU978449- For each taxon, we aligned sequences with references, separately assembled and manually edited alignments, and conducted preliminary ML analyses for each gene as above. We explored topological congruence among the best ML gene trees for each taxon with the Wilcoxon signed-rank Templeton test (WT), implemented in PAUP * v.4.0a150 (Swofford, 2002). Following the exclusion of 13 isolates due to missing data (see Supplementary Table 1), we detected conflict among single-locus datasets for the FSSC (WT, p ≤ 0.05 for 2/3 comparisons). However, because the multilocus framework adopted here has been used to classify phylogenetically diverse and clinically relevant fusaria and members of the FSSC in recent studies, our dataset includes many of these previously described isolates, and ITS data did not yield well-resolved or well-supported topologies in this group, we proceeded with using all of the data in a combined analysis (see Chang et al., 2006;Zhang et al., 2006;O'Donnell et al., 2008;Short et al., 2013). For Gliocladiopsis, we included all isolates and detected no conflict among the three single-locus datasets (WT, p > 0.1 for all comparisons). Singlelocus alignments and trees for the FSSC and Gliocladiopsis were submitted to TreeBASE 2 .
Following assessment of congruence of individual gene trees, we concatenated single-locus alignments for each taxon into a supermatrix, and carried out phylogenetic reconstructions as above while allowing for independent evolution of individual loci by specifying partitions in each analysis. Bayesian analyses did not converge after six million generations for the FSSC, so the run was extended to 30 million generations. Matrix details are listed in Supplementary Table 3, and final concatenated alignments were submitted to TreeBASE 2 .
Together these analyses clarified the phylogenetic placement of seed-associated fungi and foliar endophytic fungi, and showed that these functional groups have a shared evolutionary history (see below). Using this information we then structured our screening of EHB to evaluate whether bacterial endosymbionts differed in prevalence, diversity, or composition in seed-associated vs. foliar endophytic strains.

Detection of EHB
The presence or absence of bacteria in living hyphae was investigated initially using light microscopy for all fungi for which viable cultures were available. Once visual examination ruled out extrahyphal bacteria (i.e., contaminants in the medium or microbes on hyphal surfaces), we screened total genomic DNA from the fungal cultures for the bacterial 16S ribosomal RNA gene (16S rRNA).

PCR Screen for EHB
DNA extracted directly from apparently axenic fungal cultures (above) was screened for bacterial 16S rRNA through PCR using the primers 27F and 1492R following Hoffman and Arnold (2010). PCR products were visualized using gel electrophoresis as above. Positive PCR products producing single bands were prepared and sequenced directly as above. Positive products producing multiple bands or displaying weak or no amplification were cloned, and positive transformants were amplified and sequenced as above. All reads were processed as above. 16S rRNA gene sequences were submitted to GenBank (accessions KU978122-KU978402).

Live/Dead Visual Screen
Fungal cultures that were positive for bacterial 16S rRNA were examined by microscopy with the LIVE/DEAD BacLight TM Bacterial Viability Kit (Invitrogen, Carlsbad, CA, USA) following Hoffman and Arnold (2010). We examined exemplar fungi representing at least three unique bacterial 16S sequences for each of the major taxonomic groups of EHB recovered here (Supplementary Table 1).
We prepared fungal samples for visualization by removing a small piece of mycelium (≤2-mm 2 ) from the growing edge of single colonies growing on 2% MEA. Fragments were aseptically transferred to glass slides containing 20 µL of 1:1:18 LIVE/DEAD stain (component A: component B: diH 2 O), teased apart using sterile insect mounting needles (size 00; BioQuip, Rancho Dominguez, CA, USA), covered with a coverslip, and incubated in darkness for 15 min. After incubation, we washed the mycelium by pulling sterile distilled water through the slide mounts with bibulous paper, and sealed the slides with two coats of nail polish. We used a Leica DM400B compound microscope with a 100-W mercury arc lamp for fluorescent imaging. Samples were viewed at room temperature with a Chroma Technology 35,002 filter set (480-nm excitation/520-nm emission) and 100 × APO oil objective.
Visible fluorescence of nucleic acids distinct from fungal mitochondrial or nuclear DNA, combined with the absence of extrahyphal bacteria and successful amplification of the bacterial 16S rRNA gene from fungal genomic DNA, provided evidence for the presence of viable EHB (Hoffman and Arnold, 2010;Arendt et al., 2016). We next evaluated the richness, phylogenetic placement, and composition of these EHB.

OTU Clustering and Diversity
We used Sequencher v.5.1 (Gene Codes Corp., Ann Arbor, MI) to cluster EHB sequences at ≥97% sequence similarity in order to estimate EHB operational taxonomic units (OTUs) and calculate richness (Stackebrandt and Göbel, 1994;Kembel et al., 2014). We treated each fungal isolate as a distinct sample unit (i.e., containing an EHB community), and used the R package vegan to calculate diversity of EHB OTUs as Fisher's alpha (R Core Team, 2015;Oksanen et al., 2016). OTUs were classified tentatively by taking into account BLASTn comparisons with GenBank (16S rRNA collection; Altschul et al., 1990), the RDP Bacterial 16S Classifier (Wang et al., 2007), and the SILVA Incremental Aligner ("Search and Classify"; Pruesse et al., 2012;Quast et al., 2013). We looked for agreement among the three methods and carefully considered cases of disagreement. Results were used to frame taxon sampling for subsequent phylogenetic analyses.
For each of the 22 datasets, we aligned 16S rRNA sequences with selected references from GenBank and inferred phylogenetic relationships as described above. Bayesian analyses did not converge after six million generations for Enterobacteriaceae, Pseudomonadales, and Pasteurellaceae (Gammaproteobacteria) such that these runs were extended to 20, 10, and 10 million generations, respectively. Matrix details are listed in Supplementary Table 3, and alignments were submitted to TreeBASE 2 .

Community Composition and Indicator Species
Treating each fungal isolate screened as a distinct sample, we evaluated whether communities of EHB differed as a function of the habit of the fungal strains from which they were isolated (i.e., seed-associated vs. foliar endophytic). We used Bray-Curtis dissimilarity, which was calculated using the relative abundances of all non-singleton EHB OTUs, and visualized results using non-metric multidimensional scaling (NMS, 999 runs). After finding a stable solution, we determined the proportion of variance explained by fungal functional group (seed-associated vs. foliar endophytic) with a post-hoc goodness-of-fit test and an independent analysis of similarity (ANOSIM, 999 permutations). Distance matrices, NMS, and ANOSIM were implemented using the R package vegan (R Core Team, 2015; Oksanen et al., 2016).
We used indicator species analysis (ISA) to explore whether certain taxa of EHB were strongly associated with the seedor leaf-associated habit of host fungi. We first coded all nonsingleton EHB OTUs by bacterial taxonomy (order or below except for the Bacteroidetes [phylum]) and the fungi in which they occur by habit (seed-associated or foliar endophytic), and then estimated the indicator value for each EHB taxon-host fungal habit combination. We assessed the significance of each indicator value by comparing with mean values obtained from a randomization test (999 permutations). Estimation of ISA parameters and indicator value significance were conducted using the R package indicspecies (De Cáceres and Legendre, 2009;R Core Team, 2015).

Analyses Based on Phylogenetic Inferences
Host Fungal Taxonomy, Host Plant Taxonomy, Geography, and the Identity of EHB We annotated tips on bacterial phylogenies with data from original collections, GenBank, and/or published work to visualize patterns regarding fungal habit (i.e., seed-associated vs. foliar endophytic), fungal taxonomy (genus level or below), host plant species, and geography ( Supplementary Tables 1, 2, 4, 5). We separately implemented multinomial logistic regression in JMP v.12.2 (SAS Institute, Cary, NC), combining those variables as predictors in an additive model to predict bacterial taxonomy at the level of phylum.
We measured congruence among the phylogenies of EHB, their fungal hosts, and the host plants from which the EHBfungal associations were isolated. To obtain the host plant phylogeny, we used the Phylomatic tool implemented in Phylocom v.4.2 (Webb et al., 2008) to trim the Angiosperm Phylogeny Group megatree (APG III., 2009) to include only those plant lineages examined here. Cophylogeny between host plants and fungi or bacteria was assessed manually for all pairs of trees.

Ecological Modes of Fungal Hosts and EHB
We used metadata for EHB in each bacterial phylogeny to compare phylogenetic diversity (PD) based on the habits (occurring in seeds vs. leaves) and geographic origins (temperate vs. tropical) of host fungi. We further compared EHB detected in this study to those known from root-associated Mucoromycotina, Mortierellomycotina, and Glomeromycota (MMG), as the latter represent ecologically and evolutionarily distinct groups in which EHB have been well-documented (Bianciotto et al., 2004;Partida-Martinez et al., 2007a;Naumann et al., 2010;Sato et al., 2010;Desirò et al., 2015). We calculated PD for each analysis as the sum of branch lengths spanning the minimum path connecting all taxa belonging to defined groups (Vane-Wright et al., 1991;Faith, 1992;Humphries et al., 1995;Faith and Baker, 2006;. Because PD typically increases with sampling effort and comparisons can be misinterpreted if sample sizes of groups are not standardized, we reduced the number of sequences in each focal group to that of the group with the smallest sample size prior to PD calculations (i.e., rarefied PD; Nipperess and Matsen, 2013). We randomly selected sequences for removal during rarefaction, and performed this process three times for each comparison to obtain mean PD and standard deviation for each group. We used the R package picante for trimming trees and inferring PD (Kembel et al., 2010;R Core Team, 2015). Rarefied PD was compared between groups using Welch two-sample t-tests.
To quantify the degree to which EHB among fungi of a particular habit form phylogenetically distinct groups, we grouped EHB in each bacterial phylogeny as for PD above and calculated phylogenetic signal (Blomberg et al., 2003). Although phylogenetic signal in continuous traits can be quantified in many ways (see Gilbert and Webb, 2007;Hardy and Pavoine, 2012;Münkemüller et al., 2012), few methods are available for estimating phylogenetic signal in binary traits. We quantified phylogenetic signal using the sum of sister-clade differences (character dispersion, D, where D ≥ 1 indicates weak signal or convergent evolution and D ≤ 0 indicates strong signal; Fritz and Purvis, 2010). Strong signal implies relative phylogenetic clumping, or monophyly, and would indicate phylogenetically distinct groups. For each bacterial phylogeny, we estimated D for each group, and tested values for significant departure from a model in which traits have a phylogenetically random distribution (D = 1; 1000 permutations), and a model in which traits are clumped as if evolved by Brownian motion (D = 0; 1000 simulated walks). Analyses were conducted using the R package caper (Orm et al., 2013;R Core Team, 2015).
These 13 topologies revealed that seed-associated and foliar endophytic fungi occurred together in many well-supported lineages (Figure 1 and Supplementary Figure 1). We initially treated these functional groups as distinct from one another based on their tissue of origin (seed vs. leaf; see below), but topologies in only 3 of 13 datasets suggested that they could be phylogenetically distinct (Allantonectria, Calonectria, and F. concolor, considering data for strains evaluated here and reference strains). In the remaining 10 topologies, there was no strong evidence for a distinctive evolutionary history of seed-vs. leaf-associated strains (Figure 1 and Supplementary Figure 1).

Occurrence and Diversity of EHB
EHB were detected in 167 of 223 fungal isolates (75%) (Figures 2, 3). Overall, EHB were detected in 17 of 19 fungal groups. Together these represented isolates from 27 host plant species from Panama and Costa Rica. We did not detect EHB in 46 strains (29.7%) of Hypocrealean fungi and 10 strains (14.7%) of Xylarialean fungi. Together these represented 49 strains (28.7%) of fungi isolated from seeds and seven strains (13.5%) of fungi isolated from leaves. In general, EHB were observed more frequently in fungi isolated from leaves vs. fungi isolated from seeds (Figure 3).

FIGURE 1 | continued
Frontiers in Ecology and Evolution | www.frontiersin.org Branches lacking support values have values <60 (MLBS) and <80 (BPP). Taxon labels for tropical seed-associated fungi examined here are bolded and preceded by black circles, and those for tropical foliar endophytic fungi are preceded by white circles. Taxon labels for all fungi examined here include host plant species names, geographic locations, and GenBank accession numbers for top BLAST matches based on ITS rDNA. Signs indicate if EHB were detected (+) or not (−) during screening. Filled circles to the right of taxon labels indicate the presence of one of eight most common 16S OTUs, and numbers indicate the total number of unique 16S OTUs detected in each fungal isolate. Names for reference strains include hosts/substrates and geographic origins (when available) as well as GenBank accession numbers. C = Cecropia. Double-and triple-hash marks indicate branches shortened to one-half and one-quarter of their length, respectively. Named clades provide examples of the diversity and distribution of EHB OTUs among host fungi varying in ecological mode (e.g., seed-associated Fusarium keratoplasticum, foliar endophytic Xylaria cubensis), host plant species (e.g., within X. cubensis example clade A: fungi from Chrysophyllum cainito vs. other host plants), geographic location (e.g., within X. cubensis: fungi from Costa Rica vs. Panama), and close relatives (e.g., within FSSC haplotype 25: only two pairs of fungi share EHB OTUs). In general, we detected similar and diverse EHB OTUs among fungi consistent-and varying in each of the above factors. We detected 122 OTUs among a total of 284 EHB sequences (Figure 3, Supplementary Table 5). Of these, 80 OTUs were found only once (65.6%). Among the 42 OTUs found more than once, the majority were found in multiple fungal genera or species complexes (66.7%), or in fungi from multiple host plant species (66.7%). Overall, 42.9% occurred in more than one study site. In contrast, a minority (14 OTUs, 33%) were found in both seed-associated and foliar endophytic fungi.
EHB were observed more frequently among Xylariales than Hypocreales, but the overall diversity of EHB was greater among Hypocreales in both seed-associated and foliar endophytic fungi (as inferred using Fisher's alpha, which is robust to differences in sample size; Figure 3). For both orders the diversity of EHB among fungi isolated from leaves exceeded that for fungi isolated from seeds (Figure 3).  (Figures 4, 5 Table 5). The bacterial lineages observed here included novel taxa with regard to previously recognized EHB, as well as taxa that were closely related to but distinct from those groups (Figure 5 and Supplementary Figure 2). In total, we recovered EHB representing seven bacterial phyla, 23 orders, and 37 families (Figures 4, 5, Supplementary Figure 2, and Supplementary Table 5).
EHB from seed-associated and foliar endophytic fungi often occurred together in well-supported lineages (Figure 5 and Supplementary Figure 2). However, at the OTU level, community composition of EHB differed significantly as a function of the habit of their host fungi (i.e., isolated from seed or leaf; Figure 6). Certain EHB OTU were significantly associated with either seed-associated (e.g., members of the Clostridiales) or foliar endophytic fungi (e.g., members of the Rhizobiales, Burkholderiaceae, and Bacillales) ( Table 1).

DISCUSSION
We investigated the prevalence, diversity, composition, and phylogenetic relationships of endohyphal bacteria in two major clades of fungi, focusing on representative Hypocreales and Xylariales that colonized seeds and leaves of diverse hosts in lowland tropical forests. Our study provides a first perspective on the EHB associated with functionally distinct but closely related fungi in two major orders, and explores their diversity and phylogenetic history with respect to their host fungi and the plants in which these bacterial-fungal associations occur.
Our results agree with previous work (U'Ren et al., 2009) in suggesting an evolutionary and ecological continuity between fungi that recruit to seeds in soil and those that occur in healthy leaves. Although certain fungal taxa were represented by isolates from only one ecological mode (e.g., F. liseola and Hypoxylon, seed-associated fungi; Calonectria, F. concolor, foliar endophytic fungi), nearly all phylogenetic analyses included seed-associated

Endohyphal Bacteria Are Common among Seed-Associated and Foliar Endophytic Fungi
Overall, ca. 67% of EHB discovered here were observed in fungi that represented multiple phylogenetic lineages and plant hosts, and close to half were found in fungi that represented multiple geographic origins. However, only one-third were found in both seed-associated and foliar endophytic fungi, even though these fungi came from the same sites and in some cases, from the same plant species.
We speculate that differences in EHB could be linked with functional traits associated with growing in leaves vs. seeds or soil. Such differences could reflect differential selection by host fungi or distinctive host-symbiont recognition in focal pairings, potentially resulting in phylogenetic signal. However, such differences do not appear to be stable in an evolutionary sense: the broad habit of occurring in fungi that colonize seeds vs. leaves (or other plant tissues) has not resulted in detectable Phylogenetic analyses and annotations of node support were carried out as for fungi. EHB from tropical seed-associated fungi are preceded by a black circle. EHB from tropical foliar endophytic fungi are preceded by a white circle. Taxon labels for all EHB observed in this study are bolded, show the host fungus, host plant, geographic origin, GenBank accession numbers for top BLAST matches, and letters indicating host fungal OTUs (95% ITS rDNA similarity). Reference EHB from temperate, foliar endophytic Ascomycota are preceded by white squares and taxon labels are as above but lack letters indicating host fungal OTUs. Reference EHB of root-associated Mucoromycotina, Mortierellomycotina, and Glomeromycota (MMG) are preceded by gray squares. Taxon labels for those latter sequences and for non-EHB references include hosts and geographic origins (when available) and GenBank accession numbers. C = Cecropia. FSSC = Fusarium solani species complex. Double-and triple-hash marks indicate branches shortened to one-half and one-quarter of their length, respectively. structure in the evolution of EHB. An exception is the EHB of root-associated Mucoromycotina, Mortierellomycotina, and Glomeromycota, which exhibited strong phylogenetic signal in all inclusive phylogenies ( Figure 5B and Supplementary Figure  2Q, Supplementary Table 8).
All fungi surveyed here were isolated with a standard growth medium (2% MEA) that was not amended by antibiotics. Whether EHB influence the cultivability of fungi on certain media, and whether this could bias the isolation of fungi that differ in EHB as a function of occurring in different tissue types or hosts, remains an open question for future work.

Endohyphal Bacteria Are Horizontally Transmitted
Given that up to one third of EHB discovered here occurred in both seed-associated and foliar endophytic fungi, the question arises: where in the fungal life cycle do these infections arise? Comparisons between the phylogenies of bacteria and those of their fungal and plant hosts revealed a lack of concordance, consistent with facultative associations and horizontal transmission proposed previously for EHB of endophytic Ascomycota (Hoffman and Arnold, 2010;Arendt et al., 2016). Many species of Fusarium, Xylaria, and related fungi have a saprotrophic life phase, permitting colonization by EHB in soil or leaf litter. A route of infection from these substrates into fungi that then colonize seeds or leaves is plausible, and merits further exploration. Alternatively, it is possible that EHB infect foliar endophytes in the phyllosphere, accounting at least in part for the differences in EHB communities observed here.
The potential for horizontal transmission by EHB in Ascomycota has been verified experimentally in vitro in members of two classes (Sordariomycetes and Dothideomycetes) (Arendt et al., 2016). This is in contrast to endohyphal Burkholderiaceae observed in Rhizopus spp. and certain Glomeromycota, which can be vertically transmitted (Bianciotto et al., 2004;Partida-Martinez et al., 2007a). That these Burkholderiaceae are phylogenetically distinct from EHB observed among Ascomycota to date ( Figure 5B) implies a diversity of ecological-or transmission modes in that bacterial family. More generally, whether fungi associate with bacteria prior to infecting plants or do so after co-infection may determine the degree to which EHB influence aspects of host specificity, pathogenicity, and/or ecological modes of the fungi they inhabit.
FIGURE 6 | EHB communities differ as a function of the habit of their host fungi (seed-associated vs. foliar endophytic). Non-metric multidimensional scaling (NMS) plot shows fungi that screened positive for EHB separated by differences in their EHB community composition. Relative abundances of non-singleton EHB OTUs were used to calculate Bray-Curtis dissimilarity values among all fungi. This best solution among 999 runs has two dimensions and a stress = 0.11. Independent analyses (goodness of fit test and analysis of similarity) show that host fungal habit (seed-associated vs. foliar endophytic) is associated with significant differences in EHB community composition.
In addition to contributing to the phylogenetic diversity of known groups, this work represents the first account of EHB belonging to the Rhodospirillaceae (Alphaproteobacteria), Chromatiales (Gammaproteobacteria), Microchaetaceae (Cyanobacteria), Streptomycetales, Micromonosporaceae, and Nocardiaceae (Actinobacteria), and Negativicutes, Clostridia, For clarity, EHB OTUs are represented by their phylogenetic group (EHB phylotype). Columns include specificity scores (proportion of EHB sequences in a given phylotype occurring in fungi of a given habit) and fidelity scores (proportion of EHB among a given fungal habit that represent a given phylotype). Indicator values are the products of specificities and fidelities, and are used as test statistics versus the distribution of indicator values produced by permuting the data 999 times. P-values are bolded for associations with indicator values that significantly differed from the permuted distribution. OTUs correspond directly to phylotypes in phylogenetic analyses of EHB (below). Values are calculated from 16S phylogenies in which each group is represented by more than one sequence. Values are means and standard deviations from three replicate runs in which sample sizes were rarefied (k). For each run, tips in each group were randomly selected for inclusion. The results of Welch t-tests comparing PD between seed-associated and foliar endophytic fungi are shown for each EHB phylotype. For comparisons with a significant difference, the greater of the two values and p-value are bolded.
and Lactobacillales (Firmicutes). This phylogenetic richness and novelty was discovered among only two orders of Sordariomycetes. We anticipate that more sensitive detection methods and sampling of additional Ascomycota will likely reveal an even greater diversity of EHB. Similarly, examination of entire genomes of EHB will provide further insight with regard to relationships with known bacteria, the evolution of their symbioses with fungi (Baltrus et al., in revision), and the potential for these bacterial endosymbionts to influence the phenotypes of the fungi that, through complex and intriguing symbioses, contribute to the dynamics of tropical forests.

AUTHOR CONTRIBUTIONS
JS characterized EHB and analyzed all data; CS, PZ, RG led isolation of fungi from seeds with collaboration from AD, AA; DB advised aspects of the bacterial analyses; JS, AA led the development of the manuscript, with contributions from all authors.

FUNDING
We thank the National Science Foundation (NSF DEB-1119758 to AA, NSF DEB-1120205 to James W. Dalling