Introduction {#s1}
============

Similar selective pressures in geographically distant habitats can cause unrelated organisms to converge in both morphological and functional traits. Pitchers of carnivorous plants have evolved repeatedly and independently to have the same shapes and insect-trapping functions in Southeast Asia, North America, and Australia ([@bib3]). Similar selective pressures can also cause the independent emergence of multispecies interactions with parallel physiological or ecological functions, defined as 'convergent interactions' ([@bib14]). The concept of convergent interactions was developed in detail in [@bib14], and can be used as a tool to better understand forces influencing interspecific relationships. Here, we investigate whether convergent interactions can be identified between different, independently evolved pitcher plant genera and the arthropods and microbes housed within their pitchers. We hypothesize that the microbial communities formed within the fluids of distantly-related pitcher plant species possess similar community structures and functions, and we test this hypothesis by comparing the bacterial and eukaryotic communities living within the plant-held waters (phytotelmata) of pitcher plants from two genera in different plant orders, *Nepenthes* (family Nepenthaceae, order Caryophyllales) native to Southeast Asia and *Sarracenia* (family Sarraceniaceae, order Ericales) native to North America.

Microbial communities are complex, and even apparently simple habitats house orders of magnitude more microbial species than plant or animal species ([@bib36]). Parsing the principles shaping microbial community structure and function remains a challenge. But virtually all plants and animals interact with microbes ([@bib67]; [@bib50]), and host morphology and ecology are likely to shape associated microbial communities. Convergent plant or animal forms, chemistry, or habitats may control the communities within them ([@bib14]), analogous to a kind of 'extended phenotype.' Convergently evolved organisms are ideal systems for understanding how different aspects of form or ecology influence microbial communities because they enable distinctions among the effects of evolutionary history, geography, and host morphology or physiology.

A nascent understanding of how microbial communities assemble in association with highly specialized, convergently evolved hosts is emerging. Interactions between animals and their gut microbiomes are frequently mediated by diet. For example, animals with fermenting foreguts as distantly related as the hoatzin bird and cow are colonized by microbial communities with similar structures ([@bib34]), and the gut bacteria of disparate animals whose diets consist of ants also possess a convergent community composition ([@bib27]). In turn, the herbivorous, arboreal ants of different taxonomic groups are associated with specific bacteria likely to supplement their low-nitrogen diets ([@bib62]; [@bib37]). And convergent shifts in bacterial communities are observed in different cichlid fishes as diets change from herbivory to carnivory ([@bib10]). Similar convergent dynamics are observed in sea urchin larvae ([@bib23]). Animals\' microbial associates are likely to impact fitness. The pitchers of carnivorous pitcher plants are the plant analog of an animal gut, and may function in digestion of animal prey. Convergently evolved genera of pitcher plants provide a tractable model and opportunity to explore the assembly and functional potentials of host-associated microbial communities.

In fact, pitcher microcosms have long served as elegant models for investigating metacommunities and community assembly ([@bib43]; [@bib19]; [@bib66]; [@bib7]; [@bib15]); each pitcher pool is a discrete but similar habitat with a unique history. In our study, we take advantage of the pitcher system to focus primarily on comparisons of the communities of convergently evolved plants, testing how unrelated hosts with similar morphologies and functions shape their associated communities. Implicit within our comparisons are myriad community assembly mechanisms and processes, including dispersal and environmental filtering caused by characteristics of the host.

Two genera of carnivorous pitcher plants, *Sarracenia* and *Nepenthes*, evolved independently in North America and Southeast Asia, respectively ([@bib3]). Pitchers are highly modified leaves, and both genera grow pitchers to attract, trap, and digest insects---primarily ants. Pitcher microcosms also house communities of bacteria, fungi, protozoa, and arthropods ([@bib11]; [@bib17]; [@bib42]). Pitchers of both genera have characteristic shapes, although forms can vary greatly in color and size among different species. Pitchers of both genera also offer extra-floral nectar to attract prey, possess slippery interiors to trap prey, and secrete digestive enzymes to break down prey tissues ([@bib38]; [@bib2]; [@bib46]). *Nepenthes* species produce more different kinds, and a greater abundance, of enzymes compared to *Sarracenia* species, and *Sarracenia* species may rely more on their bacterial communities for prey degradation ([@bib20]; [@bib53]; [@bib9]). Pitchers actively absorb nitrogen, phosphorus, and other elements from prey; these nutrients are otherwise scarce in the soils where the plants grow ([@bib25]; [@bib64]; [@bib29]). While the plants are perennial, individual pitchers can last from a few weeks to two years, depending on the species, and are generally most active for the first few weeks to months after opening ([@bib35]; [@bib59]). Pitcher interiors appear to be sterile before opening ([@bib60]; [@bib18]) (but see \[[@bib26]\]), and once open, a complex community forms within ([@bib11]; [@bib42]; [@bib44]; [@bib45]; [@bib24]). Many pitcher-associated organisms are specialists, and are restricted to the pitcher habitat for at least part of their lives ([@bib32]; [@bib11]). Various arthropods have co-diversified with their pitcher plant host, suggesting ecological dependence and a shared evolutionary history ([@bib63]). In fact, even though the species *S. purpurea* was introduced to Europe over 100 years ago, it houses very few insect inquilines as compared with pitchers in native habitats ([@bib68]); the close associations of pitchers and arthropods may be slow to evolve.

To test for convergence between the microcosms of North American *Sarracenia* and Southeast Asian *Nepenthes*, we collected fluids from over 330 pitchers of six species of *Sarracenia* and eight species of *Nepenthes* from native habitats in the United States, Singapore, and Borneo ([Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S1), and used next generation sequencing to characterize the biodiversity housed in each pitcher. To the best of our knowledge, ours are the first comparisons of the entire communities, encompassing bacteria, microbial eukaryotes, and arthropods, associated with convergently evolved organisms; our sampling is also more intensive than any sampling previously published for pitcher plants. We tested for convergence between communities by comparing species richness, community composition, phylogenetic structure, and functional potential. We hypothesized the living communities housed in unrelated pitchers would converge, both structurally and functionally: tests of the hypothesis would result in similar species richness, phylogenetic structure, and functional potential between the *Sarracenia* and *Nepenthes*, as compared to the same parameters measured from surrounding bog water and soil communities. In addition to describing the bacterial and eukaryotic communities of each of the 14 different species of pitcher plants, we explored which features of host species appear to drive patterns of biodiversity. Finally, in a field manipulation, we experimentally tested whether North American insects and microbes would colonize Southeast Asian *Nepenthes* pitchers when *Nepenthes* plants were placed in a North American *Sarracenia* habitat; the experiment tests whether the pitchers of different genera function as similar selective environments when exposed to the same microbial pool. In the aggregate, data provide evidence for the convergence of pitcher microcosms between independently evolved host genera, and identify aspects of pitcher form and physiology underpinning the similarities.

Results {#s2}
=======

The species richness and evenness of North American and Southeast Asian pitcher plant microcosms converge {#s2-1}
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To compare the microbial communities within *Sarracenia* and *Nepenthes* pitchers, we analyzed DNA samples from pitchers and their surrounding environments using an amplicon sequencing approach, separately characterizing bacteria and eukaryotes ([Figure 1A](#fig1){ref-type="fig"}, [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S2, [Supplementary file 2](#supp2){ref-type="supplementary-material"} Dataset S1). Communities from Southeast Asian and North American pitchers were defined as converging if the communities were more similar to each other than to the communities of the environments immediately surrounding the plants, even despite the vast geographic distance between them. In fact, the *Nepenthes* and *Sarracenia* pitcher communities were distinct from and had fewer Operational Taxonomic Units (OTUs, clustered at 97% sequence similarity; a proxy for species) than communities in surrounding bog water or soil ([Figure 1B and C](#fig1){ref-type="fig"}, and [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S3). The pattern held for both bacteria and eukaryotes, and was unaffected by sample volume (no correlation of observed OTUs with sample volume; for bacteria: R = −0.003, p=0.984, and for eukaryotes: R = −0.003, p=0.812). Pitcher samples also had significantly lower Shannon diversities (Mann-Whitney U Test, p\<0.001 in all comparisons) than surrounding environments ([Figure 1B](#fig1){ref-type="fig"}), and this pattern also held when we controlled for extraction volume (by analyzing a subset of 155 samples, each extracted from the same volume; [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S3). Overall, pitcher communities were characterized by both decreased richness and evenness as compared to communities from their immediate environments.

![Pitcher microcosms are more similar to each other than they are to communities of surrounding habitats.\
(**A**) Geography of sampled *Sarracenia* and *Nepenthes* and experimental approach. (**B**) The species richness (displayed as rarefaction plots) and Shannon diversity (inset beanplots) of both bacterial (i, top) and eukaryotic (ii, bottom) communities was lower in pitchers than in surrounding soil and bog water. Error bars are standard deviations. (**C**) Community composition using the unweighted UniFrac metric for bacteria (i, top) and eukaryotes (ii, bottom). NMDS stress and dimensions (k) are listed, and the center of each cluster is the category's median value.](elife-36741-fig1){#fig1}

The composition of pitcher communities was also significantly different from the community composition of surrounding bog water or soil ([Figure 1C](#fig1){ref-type="fig"}, [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S4. Bacteria: *envfit*: R^2^ = 0.31, p\<0.001, *adonis*: R^2^ = 0.08, p\<0.001; Eukaryota: *envfit*: R^2^ = 0.38, p\<0.001, *adonis*: R^2^ = 0.08, p\<0.001). To understand differences in community composition across just one region, we separately tested and analyzed Southeast Asian samples from pitchers, bog water, soil, plastic tubes, or cupped, dead leaves filled with water and sitting on the ground. The communities in water from leaves or from plastic tubes were more similar to pitcher fluid communities than bog water or soil communities ([Figure 1---figure supplement 1](#fig1s1){ref-type="fig"}).

Organisms found in *Nepenthes* and *Sarracenia* pitcher microcosms are typically from the same phylogenetic clades {#s2-2}
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To compare the phylogenetic structures among pitcher communities, we mapped OTUs present in at least 10% of our field (not experimental) *Nepenthes* or *Sarracenia* samples onto bacterial and eukaryotic phylogenetic trees, together with all OTUs found in bog water and soil ([Figure 2](#fig2){ref-type="fig"} and associated [Figure 2---figure supplement 1](#fig2s1){ref-type="fig"}). Organisms repeatedly colonizing *Nepenthes* or *Sarracenia* pitchers in North America and Southeast Asia tended to be from similar clades of bacteria or eukaryotes ([Figure 2](#fig2){ref-type="fig"}). The pattern was most pronounced in bacteria, and shared families included Microbacteriaceae, Gordoniaceae, Chitinophagaceae, Sphingobacteriaceae, Bradyrhizobiaceae, Rhizobiaceae, Sphingomonadaceae, Burkholderiaceae, Comamonadaceae, Oxalobacteriaceae, Neisseriaceae, Enterobacteriaceae, Moraxellaceae, and Xanthomonadaceae. Across eukaryotes shared clades included dipteran insects, mites, and rotifers.

![*Nepenthes* and *Sarracenia* pitchers are colonized by related organisms.\
Phylogeny of bacterial and eukaryotic OTUs found in soil and bog samples (brown); and OTUs present in at least 10% of field collected *Nepenthes* (red) or *Sarracenia* (blue) samples. The height of the colored bars surrounding each tree corresponds to the natural log of the relative abundance of reads from each OTU, normalized across the samples in each category. Labels designate monophyletic clades where high proportions of OTUs are shared between *Nepenthes* and *Sarracenia* samples. Gray dots mark branches leading to nodes with bootstrap support of 0.7 or higher. The bacterial tree is rooted in Archaea and the eukaryotic tree is rooted in Streptophyta.](elife-36741-fig2){#fig2}

Within each genus, pitcher species, acidity, form, and volume correlate with community composition {#s2-3}
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To investigate drivers of community composition among pitchers of each genus, we had recorded species identity and measured the pH and total volume of pitcher fluid associated with each sample. As we extracted DNA from each sample, we recorded DNA concentrations; a proxy for the living biomass within a pitcher ([@bib49]). In both the *Sarracenia* and *Nepenthes* systems, pitcher communities differed significantly among host species ([Figure 3](#fig3){ref-type="fig"}, [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S4). For bacteria, the effect of host species was similar in *Sarracenia* (*envfit* R^2^ = 0.40, p\<0.001; *adonis* R^2^ = 0.14, p\<0.001) and *Nepenthes* (*envfit* R^2^ = 0.38, p\<0.001; *adonis* R^2^ = 0.18, p\<0.001) species; however, for eukaryotes, pitcher host species explained more of the observed variation in *Sarracenia* species (*envfit* R^2^ = 0.42, p\<0.001; *adonis* R^2^ = 0.20, p\<0.001) as compared to *Nepenthes* species (*envfit* R^2^ = 0.22, p\<0.001; *adonis* R^2^ = 0.15, p\<0.001).

Pitchers of different species maintain different levels of acidity, although these differences are more pronounced in the genus *Nepenthes* than in the genus *Sarracenia*. Certain *Nepenthes* species can actively raise or lower the acidity of individual pitchers by pumping protons into or out of pitcher fluid ([@bib5]; [@bib54]). In our sampling of natural populations, we measured values below pH 4 in *N. rafflesiana*, *N. gracilis*, and *N. stenophylla*. But low-pH pitcher fluid does not seem to correlate with the *Nepenthes* phylogeny: low-pH species are in different clades, separated by species with higher average pH levels ([@bib52]). Furthermore, each species with low pH pitchers also had pitchers with higher pH levels. The large pH gradient across the *Nepenthes* fluids in our samples was strongly correlated with bacterial community composition, and explained most of the observed variation ([Figure 3A](#fig3){ref-type="fig"}. *ordisurf* R^2^ = 0.74, p\<0.001; *mantel* r = 0.63, p\<0.001). This result supports a recent study that also noted a correlation between pitcher fluid pH and *Nepenthes* bacteria ([@bib40]). But the strong effect of pH on bacterial community composition is not driven by *Nepenthes* species differences per se; significant, high correlations between pH and bacterial community composition are also found within each of the three species with very low pH values when the data of each species are analyzed alone (Mantel tests: *N. gracilis* r = 0.46, p\<0.001; *N. rafflesiana* r = 0.68, p\<0.001; *N. stenophylla* r = 0.85, p\<0.001). Eukaryotic community composition in *Nepenthes* was more weakly correlated with pH, and pH explained a smaller portion of the variation (*ordisurf* R^2^ = 0.20, p\<0.001; *mantel* r = 0.14, p\<0.001). In the genus *Sarracenia*, bacterial (but not eukaryotic) community composition correlated with pH (bacteria: *ordisurf* R^2^ = 0.15, p\<0.001, *mantel* r = 0.11, p=0.010). For both the *Nepenthes* and *Sarracenia* bacterial communities, the relationship of pH with Shannon alpha diversity appeared to be quadratic: Shannon diversity peaked around pH 5.5 and was lower at both lower and higher pH levels ([Figure 3---figure supplement 1](#fig3s1){ref-type="fig"}). The correlation was much stronger for *Nepenthes* samples (R^2^ = 0.67, p\<0.001), but still significant for *Sarracenia* samples (R^2^ = 0.07, p=0.002).

![Community compositions differ by host species within both *Nepenthes* and *Sarracenia* pitchers.\
NMDS ordinations of pitcher samples, colored by host species. Ordisurf vectors with correlations greater than 0.3 are mapped onto the ordinations: pH in (Ai) and volume in (Bi).](elife-36741-fig3){#fig3}

Shape emerges as a potential strong influence among the *Sarracenia* species, but is confounded with species identity: *S. purpurea* and *S. rosea* pitchers grow with a shorter, more cylindrical shape, while pitchers of *S. alata*, *S. flava*, *S. leucophylla* and *S. rubra* grow to a taller, more tapered shape. Although our samples of *S. purpurea* and *S. rosea* were collected in Massachusetts and Florida, respectively, the two species are very closely related ([@bib28]). The taller, tapered *Sarracenia* pitchers have an aspect ratio of width to height below 0.2; while the shorter, more cylindrical *Sarracenia* have an aspect ratio above 0.2, as do the *Nepenthes* pitchers from this study. Because growth form is confounded with *Sarracenia* host species identity and phylogeny, we could not analyze it as a separate variable. But pitchers from species of *Sarracenia* with shorter, wider pitchers tended to have a larger volume of fluid than the taller pitchers, and volume was strongly correlated with *Sarracenia* bacterial community composition (*ordisurf* R^2^ = 0.31, p\<0.001, *mantel* r = 0.15, p=0.006) and eukaryotic community composition (*ordisurf* R^2^ = 0.18, p\<0.001, *mantel* r = 0.17, p\<0.001).

Collection site also significantly influenced *Sarracenia* communities; however, the effect was weaker when we controlled for the fact that not all species grow at all sites ([Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S4). DNA concentration was significantly correlated with *Sarracenia* bacterial community composition (*ordisurf* R^2^ = 0.22, p\<0.001, *mantel* r = 0.11, p=0.035). There was also a weak, but marginally significant correlation between DNA concentration and the Shannon diversity of *Sarracenia* bacterial communities, which was driven by a few *Sarracenia* samples with very cloudy fluid and high relative abundances of Enterobacteriaceae OTUs ([Figure 3---figure supplement 2](#fig3s2){ref-type="fig"}).

Relocated *Nepenthes* converge on *Sarracenia*-like communities {#s2-4}
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In a manipulative experiment, we relocated *Nepenthes* pitcher plants (propagated in Southeast Asia and purchased through a commercial U.S. nursery) to a *Sarracenia* bog in North America to test whether relocated *Nepenthes* pitchers would acquire communities similar in community structure and phylogenetic composition to those of local *Sarracenia*. All *Nepenthes* placed into the *Sarracenia* habitat were maintained in pots with soil material purchased in the U.S., and the plants were removed after experiments concluded. We included potted *S. purpurea* as a control to explore whether growth in a pot influenced community assembly. Target pitchers approaching maturity were manually opened in the bog on Day 1 of each experiment. The experiment also included cylindrical, round-bottomed 50 mL sterile glass tubes, either with or without sterilized insect material ('prey') added as a nutrient control ([Figure 4A](#fig4){ref-type="fig"}). During the experiment, we also recorded whether pitchers contained larvae of the pitcher plant mosquito, *Wyeomyia smithii*, a specialized insect that completes its lifecycle only within *Sarracenia purpurea* pitchers ([Figure 4B](#fig4){ref-type="fig"}). *W. smithii* larvae regularly colonized their native *S. purpurea* pitchers (whether they were growing in the ground or in a pot). Surprisingly, they also colonized pitchers of *Nepenthes bicalcarata* and *N. ampullaria*, albeit in lower proportions ([Figure 4B](#fig4){ref-type="fig"}). The mosquitoes never colonized the more acidic *N. gracilis* and *N. rafflesiana* species, nor the experimental glass-tube pitchers.

![A manipulative field experiment demonstrates that *Nepenthes* pitchers in a *Sarracenia* habitat assemble *Sarracenia*-like microcosms.\
(**A**) Experimental treatments: Spb = *Sarracenia purpurea* bog; Spp = *S. purpurea* pot; Na = *Nepenthes ampullaria*; Nb = *N. bicalcarata*; Ng = *N. gracilis*; Nr = *N. rafflesiana*; Gt = glass tube; Gtp = glass tube with sterilized prey. (**B**) *Wyeomyia smithii* (pitcher plant mosquito) larvae colonized their native *S. purpurea* hosts, as well as foreign *Nepenthes* species with average pH \> 4, but not pitcher-shaped glass tubes. Numbers of samples are listed above each category, and average pH values are listed below. (**C**) Natural microcosms of *Nepenthes* and *Sarracenia* pitchers sampled in SE Asia or North America house different organisms (Ci and Cii). (**D**) However, experimentally-relocated *Nepenthes* converge on *Sarracenia*-like communities and differ from those of natural *Nepenthes* (Di and Dii), except for bacterial communities sampled from *Nepenthes* in which pH \< 4 (Di). Glass tubes (with or without added prey) of a pitcher-like form assemble communities that are similar to those of experimental pitchers (Di and Dii).](elife-36741-fig4){#fig4}

To compare the biodiversity of entire communities, we first re-plotted our beta-diversity results from natural *Nepenthes* versus natural *Sarracenia* pitchers ([Figure 4C](#fig4){ref-type="fig"}), and found that community composition was significantly different for the two genera. Bacterial assemblages were more similar between the two genera than eukaryotic assemblages, and correspondingly, host genus explained less variation in bacterial than in eukaryotic community composition (Bacteria: *envfit* R^2^ = 0.33, p\<0.001, *adonis* R^2^ = 0.09, p\<0.001; Eukaryota: *envfit* R^2^ = 0.55, p\<0.001, *adonis* R^2^ = 0.14, p\<0.001).

We next compared the beta-diversity results of wild *Nepenthes* to our experimental data of relocated *Nepenthes*, native *Sarracenia*, and experimental glass tubes ([Figure 4D](#fig4){ref-type="fig"}). When *Nepenthes* microcosms assembled in a *Sarracenia* habitat, the assemblages of both bacteria and eukaryotes converged on compositions similar to those of the local *Sarracenia* and not wild *Nepenthes* ([Figure 4D](#fig4){ref-type="fig"}). The exception to convergence was in *Nepenthes* pitchers with pH below 4. The bacterial assemblages in highly acidic pitcher fluids (generally *N. gracilis* and *N. rafflesiana*) separated from other *Nepenthes* and *Sarracenia* pitchers in the same manner as acidic pitcher bacterial assemblages shifted in natural *Nepenthes* populations, and were instead more similar in structure and phylogenetic composition to wild, acidic *Nepenthes* ([Figure 4D](#fig4){ref-type="fig"} and [Figure 3](#fig3){ref-type="fig"}). Acidity explained most of the variation in bacterial community composition from the experiments (pH: *ordisurf* R^2^ = 0.67, p\<0.001, *mantel* r = 0.50, p\<0.001) and was also a significant predictor of eukaryotic community composition (pH: *ordisurf* R^2^ = 0.21, p\<0.001, *mantel* r = 0.11, p\<0.001). Region---whether the pitchers were in Harvard Forest, Singapore or Malaysia---explained only a small portion of bacterial variation (*envfit* R^2^ = 0.19, p\<0.001, *adonis* R^2^ = 0.07, p\<0.001), but a larger portion of the eukaryotic variation (*envfit* R^2^ = 0.41, p\<0.001, *adonis* R^2^ = 0.10, p\<0.001).

Communities of bacteria and eukaryotes in our experimental pitchers were different from bog water communities (not shown), but partially clustered with the organisms colonizing the glass tube pitchers ([Figure 4D](#fig4){ref-type="fig"}). NMDS plots indicate glass tubes with added prey did not assemble communities more similar to the experimental pitcher communities than glass tubes without added prey. Only a very small portion of the variation in community composition was explained in analyses of pitchers vs. glass tubes; however, the differences were highly significant (bacteria: *envfit* R^2^ = 0.05, p\<0.001, *adonis* R^2^ = 0.02, p\<0.001; eukaryotes: *envfit* R^2^ = 0.09, p\<0.001, *adonis* R^2^ = 0.03, p\<0.001). The analysis suggests a sterile, pitcher-shaped form is almost, but not quite entirely, sufficient for acquiring a pitcher plant-like microcosm ([Figure 4D](#fig4){ref-type="fig"}).

*Nepenthes* and *Sarracenia* microbiomes are enriched in gene pathways for degradation; both have high relative abundances of chitinases and key nitrogen mineralization enzymes {#s2-5}
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To investigate the functional potential of pitcher microbiomes, we generated metagenomes from 24 field-collected (not experimentally relocated) pitcher samples (16 *Nepenthes* and 8 *Sarracenia*). When compared with other published metagenomes for soil, lake, and phyllosphere samples ([Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S5), pitcher plant community metagenomes were more enriched in gene pathways for fatty acid degradation, fermentation, and the biosynthesis of cell wall materials and non-proteinogenic amino acids, while non-pitcher metagenomes were more enriched in gene pathways for metabolic precursors (the biosynthesis of proteinogenic amino acids, tRNA charging, glycolysis, Calvin cycle and folate transformations) ([Figure 5A](#fig5){ref-type="fig"}).

![Pitcher plant microbiomes are enriched in degradation genes.\
(**A**) Gene pathways enriched in pitcher plant *versus* other environmental metagenomes. (**B**) NMDS plot of functional gene families comparing pitcher plant and environmental metagenomes. (**C**) Relative abundance of gene families in metagenomes. Abbreviations: pepN = aminopeptidase N; ODC = ornithine decarboxylase; LDC = lysine decarboxylase; and GLDH = glutamate dehydrogenase.](elife-36741-fig5){#fig5}

In terms of overall functional potential as measured by Kegg Orthology (KO) groups using the Bray-Curtis dissimilarity metric in an NMDS plot, pitcher metagenomes were highly variable and were most similar to other phyllosphere communities ([Figure 5B](#fig5){ref-type="fig"}). Among *Nepenthes* and *Sarracenia* metagenomes, KO gene families in *Sarracenia purpurea* clustered close to *Nepenthes ampullaria*, *N. gracilis* and *N. reintwardiana*. Other *Sarracenia* (those with a tapered shape) and other *Nepenthes* (those with more acidic fluid) appeared to be more dissimilar in terms of functional potential.

To probe the functional similarities of *Nepenthes* and *Sarracenia* communities more deeply, we chose to compare abundances of enzymes involved in the degradation of complex polysaccharides and proteins. We specifically chose to focus on chitinases (K01183, GH families 18 and 19) because chitin is the main component of insect exoskeletons and can be used as both a carbon and nitrogen source. Because pitchers evolved to trap insect prey, we hypothesized pitcher plant microbiomes would have the genes to digest chitin. We also chose to focus on key enzymes involved in proteins and amino acid degradation (aminopeptidase N, lysine decarboxylase, ornithine decarboxylase, and glutamate dehydrogenase), because nitrogen mineralization via the microbiome may assist pitcher plants in nitrogen acquisition from prey. Finally, we chose to compare cellulases across the metagenomes, as we hypothesized microbiomes of pitcher plants would be less involved in breaking down plant material, compared to microbiomes of other habitats. Although individual pitcher samples showed considerable variability, *Nepenthes* and *Sarracenia* microbiome metagenomes did in fact have high relative abundances of chitinase, lysine decaboxylase, and ornithine decarboxylase genes compared to metagenomes of bacterial communities collected from other habitats ([Figure 5C](#fig5){ref-type="fig"}). But aminopeptidase N levels were not significantly higher in pitcher plants than in other habitats, and surprisingly, glutamate dehydrogenases were, in fact, significantly lower in pitcher plants. The glutamate dehydrogenase pathway can be either catabolic or anabolic, and this dual activity might explain our result. Cellulases were significantly lower in pitcher plant microbiomes, as hypothesized. Our results are consistent with recent proteomics data documenting high levels of amino acid and carbohydrate metabolism pathways in *Sarracenia pupurea* ([@bib56]). As the specific functions of the microbial communities within pitchers become better understood, we anticipate our data will be used to more explicitly measure and compare the functions of these different microbiomes.

Discussion {#s3}
==========

Evidence for the convergence of communities within the carnivorous pitchers of *Nepenthes* and *Sarracenia* is strong and pitcher characteristics appear to regulate fundamental aspects of community biodiversity. First, in nature, the bacterial and eukaryotic communities inside both *Nepenthes* and *Sarracenia* pitchers are less species rich and less even than communities in surrounding soil or bog water; pitcher habitats favor a subset of available species ([Figures 1](#fig1){ref-type="fig"} and [2](#fig2){ref-type="fig"}). Second, although the communities within the two genera of pitchers are made up of different species, organisms tend to be closely related and from the same phylogenetic clades ([Figure 2](#fig2){ref-type="fig"}). This pattern was especially pronounced among bacteria. Third, both *Nepenthes* and *Sarracenia* pitcher microbiomes are depleted in pathways for metabolic precursors and enriched in pathways involved in fatty acid degradation and cell wall biosynthesis; pitcher microbiomes also possess a high relative abundance of both chitinases and genes involved in amino acid degradation ([Figure 5](#fig5){ref-type="fig"}). Results suggest the pitcher microbiomes of both genera function as decomposers of insect prey. Finally, *Nepenthes* pitchers experimentally placed into a *Sarracenia* habitat assembled *Sarracenia*-like communities ([Figure 4](#fig4){ref-type="fig"}). Convergently evolved pitchers appear to cause convergent interactions ([@bib14]) between the two genera and their associated pitcher microcosms.

Among species within a genus, fluid acidity was the strongest driver of beta-diversity, specifically for *Nepenthes* bacterial communities; this same characteristic explains aspects of our manipulative experiment. When microcosms of *Nepenthes* and *Sarracenia* pitchers assembled in parallel in a common environment, pitchers with similar fluid acidity held communities more alike in composition ([Figure 4](#fig4){ref-type="fig"}). Furthermore, while the communities formed in sterile glass tubes with or without sterilized insect 'prey' appeared somewhat similar to plant pitcher communities, communities were still statistically different---suggesting that a general tube-like form that drowns insects in rainwater is almost, but not completely, sufficient for generating a pitcher-like microcosm. Other unmeasured characteristics of real *Nepenthes* and *Sarracenia* pitchers, including for example the production or abundance of plant-produced digestive enzymes or nectar, oxygen levels, and temperature, are also likely to cause these plant-formed pitcher microcosms to be more similar to each other than they are to glass tube microcosms.

The pitcher environment appears to be the dominant selective force shaping community composition in pitchers. Fewer eukaryotes consistently colonize *Nepenthes* or *Sarracenia* pitchers, as compared to bacteria ([Figure 2](#fig2){ref-type="fig"}); the pattern is consistent with stronger habitat filtering with increasing body size, as observed in bromeliad phytotelmata ([@bib31]). Within each pitcher plant genus, collection site explained less of the observed variation than characteristics of the pitcher itself, suggesting that environmental filtering has a larger influence than dispersal. At a broad scale, comparisons between Southeast Asia and North America reveal that the regional pools of microbial organisms are distinct, and dispersal likely plays a stronger role in differentiating the microbial communities of these two continents. However, despite the differences in regional pools, organisms from the same phylogenetic groups colonize the pitcher microcosms found on opposite sides of the globe.

Convergent interactions, albeit on a much smaller scale, mirror the biome concept ([@bib57]): the same functional groups of plants and animals are found in different regions of the world when those regions possess similar climate and soil conditions. For example, clumped grasses, crustose lichens, and jumping rodents are found in xeric shrublands globally, including in Australia and Arizona, just as Chitinophagaceae bacteria, Sphingomonadaceae bacteria, and Histiostomatidae mites are found in the unrelated pitcher microcosms of Southeast Asia and North America. However, beyond scale, there is a second fundamental difference between the two concepts: convergent interactions are, by definition, *interactions* among different living organisms, and thus there is a potential for reciprocal feedback, and potentially coevolution.

The concept of convergent interactions can be used to better understand the selective pressures structuring microbial biodiversity elsewhere, outside of the pitcher plant system. In addition to diet ([@bib34]; [@bib27]; [@bib10]; [@bib62]; [@bib37]), many other features of convergently evolved organisms appear to cause associations with similar microbial communities. For example, bacterial communities associated with fungus-growing ants, beetles, and termites in different regions of the world have dominant community members from the same genera, with convergent functional potential ([@bib8]), and microbial symbionts of sponges are functionally equivalent across phylogenetically divergent hosts ([@bib30]). Convergent interactions can provide predictions about community structure and function, which can be tested across systems. The framework provides a tool to explore compositional and functional similarities of whole ecosystems, potentially enabling an understanding of the fundamental evolutionary and environmental drivers structuring microbial communities.

Materials and methods {#s4}
=====================

  Reagent type (species) or resource   Designation                                 Source or reference       Identifiers   Additional information
  ------------------------------------ ------------------------------------------- ------------------------- ------------- ------------------------
  Commercial assay or kit              MoBio PowerClean kit                        Qiagen/MoBio                            
  Commercial assay or kit              Quant-iT High-Sensitivity dsDNA Assay Kit   Invitrogen/ThermoFisher                 
  Commercial assay or kit              TruSeq DNA PCR Free HT Kit                  Illumina                                
  Commercial assay or kit              KAPA LTP Library Prep Kit                   Roche                                   
  Commercial assay or kit              KAPA Library Quantification Kit             Roche                                   
  Commercial assay or kit              PerfeCta NGS Library Quantification Kit     Quanta Biosciences/VWR                  

Collections and experiments took place from 2012 to 2014 at field sites along the U.S. Gulf Coast, at Harvard Forest in Massachusetts, in Singapore, and in the Maliau Basin of Borneo ([Figure 1A](#fig1){ref-type="fig"}). In total, we sampled and sequenced communities collected in the field from more than 330 pitchers from 8 species of *Nepenthes* and 6 species of *Sarracenia* (for more details about the species, see [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S1), and 70 environmental samples. The experimental data included samples from 60 experimental pitchers of natural and potted *S. purpurea* and 4 species of potted *Nepenthes*, and 16 glass tubes. R code and data for our analyses are available via the Harvard Dataverse: <https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QYUBN2>.

Field collections and background information {#s4-1}
--------------------------------------------

*Nepenthes* pitchers from three co-occurring species (*N. ampullaria*, *N. gracilis* and *N. rafflesiana*) were sampled from three sites in Singapore (Kent Ridge Park, Bukit Timah Nature Preserve, and between Lower and Upper Peirce Reservoir Park) in January 2012. Additional pitchers from the same species and sites were sampled in March 2013 and March 2014. Pitchers from an additional five co-occurring species (*N. veitchii, N. tentaculata, N. stenophylla, N. reinwardtiana,* and *N. hirsuta*) were sampled from the Maliau Basin, Borneo in March 2014.

*Sarracenia* pitchers from five species (*S. alata, S. flava, S. leucophylla, S. rosea* and *S. rubra*) were sampled from thirteen sites from Mississippi to Florida along the U.S. Gulf Coast in June 2014 and a sixth species (*S. purpurea*) was sampled from Harvard Forest in Massachusetts in July 2014. For details of which species were sampled from which sites see [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S1. Sites were considered different if separated by more than 0.1 degree of latitude or longitude.

Sampling pitcher fluid {#s4-2}
----------------------

Contents of each pitcher were collected with sterile, single-use plastic transfer pipettes and placed into empty, sterile plastic tubes. Fluids were mixed within each pitcher using the pipette before collecting to homogenize any differences by depth. Volumes and pH levels of all pitcher fluids were recorded, except for our first collection in Singapore in 2012 (for more detail on Singapore sampling see \[[@bib13]\]). The pitchers of some species can have large volumes (e.g. 100--500 mLs); for higher volume samples, we estimated total volume and collected a well-mixed subsample from the pitcher. We measured pH with colorpHast strips (EMD Millipore) by removing small amounts of fluid with additional sterile pipettes. To preserve DNA, we added cetyltrimethylammonium bromide and salt solution (hereafter 'CTAB'; final concentrations: 2% CTAB, 1.4 M NaCl, 20 mM EDTA, 100 mM Tris pH 8) to each sample in the same volume as the collected fluid. All samples were processed the same day as collection, except for Maliau Basin samples that were refrigerated overnight and processed the next morning, due to time constraints. After CTAB addition, samples were transported at room temperature to Harvard University, and subsequently frozen.

Sampling the surrounding environment {#s4-3}
------------------------------------

Protocols reflected pitcher plant habitats ([Figure 1A](#fig1){ref-type="fig"}). When wet, we collected bog samples from the surrounding environment, and when dry, we collected soil samples and water either from fallen leaves or from sterile tubes placed in the environment, as follows: Singapore, March 2013---soil, Gulf Coast, June 2014---soil and bog water; Massachusetts, July 2014---bog water; Singapore, February 2014---sampling from plastic tubes left out for one month to collect rainwater and acquire microbial communities; Maliau Basin, January 2014---sampling from soil and water held in fallen leaves. All soil samples were collected from the surface organic layer in approximately 7 mL volumes. See Dataset S1 for sample details.

Experimental relocation of *Nepenthes spp*. to a New England bog {#s4-4}
----------------------------------------------------------------

In summer 2013 we set up experiments to manipulate *Nepenthes* within a *Sarracenia* habitat, the Tom Swamp bog at Harvard Forest in Petersham, MA (USA). Four different species of *Nepenthes* (*N. ampullaria*, *N. bicalcarata*, *N. gracilis* and *N. rafflesiana*) were purchased from Borneo Exotics via the ExoticPlantsPlus nursery in New York. *Nepenthes* plants were maintained in a greenhouse for two months after arriving from Southeast Asia, and then a growth chamber for a few weeks while pitchers were maturing for use in the field. *Sarracenia purpurea* plants were purchased from Meadowview Biological Research Station in Virginia, potted using purchased sphagnum peat and perlite, maintained in a greenhouse for three months, and used in the experiments as a control for whether growth in a pot influenced community assembly.

Experiment I had six treatments: *S. purpurea* growing naturally in the bog, *S. purpurea* in pots, *N. ampullaria*, *N. gracilis* and *N. rafflesiana* in pots, and empty, 50 mL sterile glass tubes used as a rough mimic of the pitcher shape. There were eight stations, and the experiment ran from June 26 -- July 17. Pitchers were sampled for subsequent sequencing on days 14 and 21. Experiment II had five treatments: *S. purpurea* in the bog, *S. purpurea* in pots, *N. ampullaria* in pots, sterile glass tubes, and sterile glass tubes each filled with 30 mg of autoclaved, ground wasps as a nutrient and prey control. There were five stations, and the experiment ran from July 17 -- September 4. Pitchers were sampled for subsequent sequencing on days 14, 35, and 49. Experiment III had six treatments: *S. purpurea* in the bog, *N. ampullaria*, *N. rafflesiana* and *N. bicalcarata* in pots, sterile glass tubes, and sterile glass tubes with prey. There were five stations, and the experiment ran from July 24 -- September 10. Pitchers were sampled for subsequent sequencing on days 15, 35, and 48.

To sample, we collected 750 uL of fluid from experimental pitchers and tubes using sterile transfer pipettes, as described above. At sampling, we also noted the presence or absence of pitcher plant mosquito larvae (*Wyeomyia smithii*) in pitchers. On the last day of each experiment, we collected entire pitcher contents. On the last days of Experiments II and III, we collected samples of bog water. All samples were stored in small tubes in a cooler with ice, and brought back to the laboratory, where they were frozen the same day. Subsequent analyses target only the last day's sample from each pitcher or tube, so that no pitcher or tube is included more than once in the dataset.

Sample processing, DNA extraction, amplification and sequencing {#s4-5}
---------------------------------------------------------------

Once we had collected samples, we turned our attention to DNA extraction and sequencing. When removing fluid for DNA extraction, we took care to avoid macroscopic organisms. We concentrated sample fluid by filtration or isopropanol precipitation and centrifugation. Concentration protocol did not affect community composition (samples processed by different techniques clustered together).

We extracted DNA by bead-beating concentrated materials with buffer and phenol-chloroform, and then proceeding with a standard phenol-chloroform extraction ([@bib61]). We included a negative control with each set of extractions, and discarded the samples from one extraction set found to have measurable amounts of DNA in the negative control. We measured DNA quantity, and then re-extracted DNA from a few samples with very low DNA amounts, using a larger initial volume. DNA extracts with dark coloration (suggesting high levels of polyphenols) were cleaned using a MoBio Powerclean kit. DNA concentrations of successful extractions were fluorometrically quantified a final time using a Quant-iT High-Sensitivity dsDNA Assay Kit (Invitrogen). Samples were sent to Argonne National Laboratories for Illumina MiSeq next-generation amplicon sequencing. The Earth Microbiome Project's barcoded 16S and 18S primers ([@bib4]; [@bib22]) were used to amplify DNA in separate runs, with PCR amplification and sequencing executed according to the Earth Microbiome Project protocols (<http://www.earthmicrobiome.org/emp-standard-protocols>). The 16S primers target the V4 region of the ribosomal RNA gene and are used to characterize prokaryotic communities, while the 18S primers target the V9 region and are used to characterize eukaryotes. The amplicon sequencing datasets can be accessed from the Sequence Read Archive as NCBI BioProject PRJNA448553.

Shotgun metagenomics {#s4-6}
--------------------

To explore functional gene diversity in pitcher plant microbiomes, we conducted shotgun metagenomic sequencing with 24 of our pitcher samples. Sixteen samples were sequenced at the High Impact Research Institute in Malaysia (HIR) at the University of Malaya, and eight at the Bauer Core Facility (RRID:[SCR:001031](https://scicrunch.org/resolver/SCR:001031)) at Harvard University. The HIR set targeted two samples from each of four different species of both *Nepenthes* and *Sarracenia*. DNA was extracted as described above, but 2--4 extractions were done for each sample and resulting DNA was pooled to increase the amount available for sequencing. DNA was sheared with a Covaris at settings aiming for average lengths of 350 base pairs (bp), and libraries were prepared using a TruSeq DNA PCR Free HT Kit. DNA library concentrations were measured using a KAPA Library Quantification Kit, and the qualities were tested with a Bioanalyzer. DNA libraries were then pooled in equal concentrations and sequenced on the Illumina HiSeq 2500 platform in four Rapid Run, paired-end,100 bp lanes.

The Bauer Core Facility set included eight additional *Nepenthes* samples (two samples from each of four different species). Here, we used the same DNA extractions as previously used for metabarcoding. DNA samples were sheared with a Covaris at 500 bp, and prepared with a KAPA LTP Library Prep Kit. Due to lower initial DNA quantities, the samples were subject to 2--9 cycles of PCR before final quantification using a PerfeCta NGS Library Quantification Kit, quality testing with a Bioanalyzer, and pooling of samples in equal concentrations. These libraries were sequenced in one-third of an Illumina HiSeq 150 bp paired-end Rapid Run lane. Shotgun metagenomic data can be accessed via the Argonne National Laboratory metagenomics server MG-RAST (RRID:[SCR:004814](https://scicrunch.org/resolver/SCR:004814)): <http://www.mg-rast.org/linkin.cgi?project=mgp15454>.

Analyses of 16S and 18S diversity {#s4-7}
---------------------------------

To generate Operational Taxonomic Units (OTUs), amplicon data were clustered using QIIME (Quantitative Insights Into Microbial Ecology, RRID:[SCR:001905](https://scicrunch.org/resolver/SCR:001905)) versions 1.8 and 1.9 ([@bib21]) on Harvard University's Odyssey computing cluster. We joined forward and reverse reads using fastq-join, then split libraries with a PHRED quality cut-off of 20 to remove low-quality sequences, and used UCLUST (version 1.2.21q) open-reference clustering to form groups of sequences into OTUs with 97% similarity. Resulting numbers of sequences and OTUs are summarized in [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S2. Phylogenetic trees were generated using QIIME default settings for 16S; when generating the18S alignment and tree we set the allowed gap fraction to 0.8 and the entropy threshold to 0.0005. We assigned taxonomy with the greengenes version 13_8 (Greengenes Database Consortium) and SILVA version 111 databases for 16S and 18S, respectively. For 18S, we used the BLAST method to assign taxonomy, as UCLUST assignment was poor. For subsequent analyses of 18S sequences, we used only OTUs assigned to Eukaryota.

To calculate alpha diversity of our samples, we first discarded any samples with fewer than 6500 or 4300 sequences for the 16S and 18S datasets, respectively. We then built rarefaction plots of soil, bog, *Nepenthes*, and *Sarracenia* samples using the observed species metric in QIIME and standard deviations across each category ([Figure 1B](#fig1){ref-type="fig"}). We also calculated the Shannon diversity index and standard deviations across the same categories ([Figure 1B](#fig1){ref-type="fig"}, [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S3). To ensure that sample volume was not driving differences in alpha diversity between environmental and pitcher plant samples, we used a linear model to test for a correlation between sample volume and observed OTUs. We also re-calculated Shannon diversity and standard deviations using a subset of 155 samples where DNA was extracted from the same volume for all samples ([Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S3).

To explore beta diversity among samples, we first removed any observation of an OTU with less than 10 sequences per sample in order to minimize the probability of including sequencing errors, including barcode misassignments ([@bib16]; [@bib55]). We accounted for uneven sequencing across the samples by subsampling our OTU tables to 4000 sequences per sample. We calculated dissimilarity matrices with the unweighted Unifrac metric ([@bib48]) and Bray-Curtis using R packages *picante* and *phyloseq* ([@bib41]; [@bib51]; RRID:[SCR:013080](https://scicrunch.org/resolver/SCR:013080)), and ran non-metric multidimensional scaling (NMDS) analyses using the *vegan* R package ([@bib58]; RRID:[SCR:011950](https://scicrunch.org/resolver/SCR:011950)) ([Figures 1C](#fig1){ref-type="fig"}, [3](#fig3){ref-type="fig"}, [4](#fig4){ref-type="fig"} and [5](#fig5){ref-type="fig"} and [Figure S1](#supp1){ref-type="supplementary-material"}). We used the functions *envfit* and *ordisurf* to fit environmental factors or vectors (respectively) to our ordinations and to analyze main effects. We also calculated dissimilarity matrices using the Bray-Curtis metric, to take into account how relative abundances among OTUs might influence beta-diversity analyses. For both the unweighted Unifrac and Bray-Curtis measures, we used mantel tests to test for correlations of the dissimilarity matrices with pH and volume, and permutational multivariate analyses of variance (PERMANOVAs, function *adonis* in *vegan*) ([@bib6]) to test the explanatory power of factors including plant species and collection site ([Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S4). We adjusted P-values within each group to account for multiple comparisons using the Benjamini-Hochberg procedure ([@bib12]).

To examine phylogenetic patterns among *Nepenthes* pitchers, *Sarracenia* pitchers, and environmental samples, we chose to focus on relatively common OTUs, removing OTUs containing fewer than 100 sequences across all our samples as well as those not present in at least 10% of either *Nepenthes* or *Sarracenia* microbiome samples. We then subsampled the OTU table for each category to 2000 sequences per sample, combined all observations of the OTUs by category (e.g. *Nepenthes*, *Sarracenia* or environment), and normalized by the number of samples in each category. We filtered our previously generated 16S and 18S phylogenetic trees using the resulting OTU tables and plotted them with the Interactive Tree of Life (iToL) program([@bib47]) ([Figure 2](#fig2){ref-type="fig"}). The bacterial tree was rooted with Archaea, and the eukaryotic tree was rooted in Streptophyta (land plants and most green algae). We added barcharts along the outer edge of the trees, displaying the natural log of the abundance for each OTU in each category, and gray dots to each branch with bootstrap support of 0.7 or higher ([Figure 2](#fig2){ref-type="fig"}). The same trees, with branch lengths and tree scales included, are shown in [Figure 2---figure supplement 1](#fig2s1){ref-type="fig"}. The branches of the figure supplement trees were colored by either phylum (for bacteria) or by broad taxon levels (for eukaryotes).

Functional analyses {#s4-8}
-------------------

For the shotgun metagenomic data, we combined forward and reverse reads from all lanes for each sample, and used Trimmomatic to remove barcodes and low-quality sequences. We used HUMAnN2 (HMP Unified Metabolic Analysis Network 2, \[[@bib1]\]) on Harvard University's Odyssey computing cluster to identify individual reads by comparing and annotating reads to reads of known function, build profiles of identified functional genes for each sample, and normalize numbers of sequences across samples. We next compared our metagenomes to publicly available metagenomes from soil, lake, and phyllosphere habitats using MG-RAST ([@bib33]; RRID:[SCR:004814](https://scicrunch.org/resolver/SCR:004814)) and the NCBI's Sequence Read Archive (SRA; RRID:[SCR:004891](https://scicrunch.org/resolver/SCR:004891); accession numbers are listed in [Supplementary file 1](#supp1){ref-type="supplementary-material"} Table S5). We analyzed these metagenomes in the same way as our own data, also using HUMAnN2. To detect differentially abundant gene pathways in pitcher plants vs. the other metagenomes, we subset gene pathways to those with abundances and variances in the top 50% of the dataset, and used LEfSe (Linear Discriminant Analysis Effect Size, [@bib65]) to identify statistically significant features. We reported the pathways with the five largest linear discriminant values for each group ([Figure 5](#fig5){ref-type="fig"}). We made NMDS plots of KO functional matrices with Bray-Curtis distances and a beanplot of chitinases using the *vegan* and *beanplot* ([@bib39]) packages in R. We tested for differences in gene family abundances between pitcher plant and comparison metagenomes using Mann-Whitney U tests (function *wilcox.test* in R) and we adjusted P-values to control for false discoveries using the Benjamini-Hochberg procedure ([@bib12]) ([Figure 5](#fig5){ref-type="fig"}).

Funding Information
===================

This paper was supported by the following grants:

-   http://dx.doi.org/10.13039/100000001National Science Foundation NSF Graduate Fellowship and Doctoral Dissertation Improvement Grant DEB-1400982 to Leonora S Bittleston.

-   http://dx.doi.org/10.13039/100000925John Templeton Foundation Foundational Questions In Evolutionary Biology to Naomi E Pierce, Anne Pringle.

-   Harvard University Museum of Comparative Zoology Putnam Expedition Grant to Leonora S Bittleston.

-   http://dx.doi.org/10.13039/100006363National Geographic Society to Naomi E Pierce.

-   http://dx.doi.org/10.13039/501100004386Universiti Malaya High Impact Research Grant, UM-MOHE HIR Grant UM.C/625/1/HIR/MOHE/CHAN/14/1 to Kok Gan Chan.

-   http://dx.doi.org/10.13039/100000001National Science Foundation SES-0750480 to Naomi E Pierce.

-   http://dx.doi.org/10.13039/501100004386Universiti Malaya High Impact Research Grant, H-50001-A000027 to Kok Gan Chan.

-   http://dx.doi.org/10.13039/501100004386Universiti Malaya High Impact Research Grant, A-000001-50001 to Kok Gan Chan.

Collecting permits were issued to LSB by Singapore National Parks (NP/RP11-096), the Sabah Biodiversity Centre (Collecting permit: JKM/MBS.1000-2/2 (112); Export permit: JKM/MBS.1000-2/3 (97)), and the Maliau Basin Management Committee (MBMC 2012/10). Permission to collect in North America was granted by Harvard Forest, the Nature Conservancy, Eglin Air Force Base, Nokuse Plantation, and local National and State Forests. We are grateful for collecting help from Dan Sternof Beyer and Kadeem Gilbert, and for expedition support and use of lab space from the Institute for Tropical Biology and Conservation at the University of Malaysia Sabah. Thanks to Drs. Li Daiquin and Gregory Jedd for use of lab space in Singapore, and to Dr. Shawn Lum, Dr. Stuart Davies, Kang Min Ngo, and Su Shiyu for help locating *Nepenthes*. We deeply appreciate Dr. Tom Miller's invaluable suggestions and field support during Florida collecting trips, and the three reviewers whose helpful comments improved our manuscript.

Additional information {#s5}
======================

No competing interests declared.

Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Visualization, Methodology, Writing---original draft.

Investigation, Methodology, Writing---review and editing.

Resources, Supervision, Writing---review and editing.

Resources, Data curation, Methodology, Writing---review and editing.

Resources, Supervision, Funding acquisition, Methodology, Writing---review and editing.

Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing---original draft, Project administration, Writing---review and editing.

Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing---original draft, Project administration, Writing---review and editing.

Additional files {#s6}
================

10.7554/eLife.36741.012

###### Tables S1-S5

10.7554/eLife.36741.013

###### Sample Metadata

10.7554/eLife.36741.014

Data availability {#s7}
-----------------

Amplicon sequencing data have been deposited as NCBI BioProject PRJNA448553: <https://www.ncbi.nlm.nih.gov/bioproject/PRJNA448553>. Metagenomic sequencing data have been deposited in MG-RAST: <http://www.mg-rast.org/linkin.cgi?project=mgp15454>. The source code and data for Figures 1-5 and for Tables S3 and S4 have been deposited in a Harvard Dataverse repository: <https://doi.org/10.7910/DVN/QYUBN2>.

The following datasets were generated:

Bittleston L2018Convergence between the microcosms of Southeast Asian and North American pitcher plants<https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA448553>Publicly available at NCBI BioProject (accession no. PRJNA448553)

Bittleston L2018Pitcher plant shotgun metagenomics<http://www.mg-rast.org/linkin.cgi?project=mgp15454>Publicly available at MG-RAST (accession no. mgp15454)

Leonora S Bittleston2018Data and code for: Convergence between the microcosms of Southeast Asian and North American pitcher plants<https://doi.org/10.7910/DVN/QYUBN2>Publicly available at the Harvard Dataverse website (DOI: 10.7910/DVN/QYUBN2)

10.7554/eLife.36741.022

Decision letter

Newman

Dianne K

Reviewing Editor

Howard Hughes Medical Institute, California Institute of Technology

United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article \"Convergence between the microcosms of Southeast Asian and North American pitcher plants\" for consideration by *eLife*. Your article has been reviewed by three peer reviewers, including Dianne Newman as Reviewing Editor, and the evaluation has been overseen by Detlef Weigel as Senior Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed their reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Though we find many aspects of your work to be positive, there are mixed opinions regarding whether it sufficiently advances the field.

Essential revisions:

We would like to give you an opportunity to respond to the reviewers\' concerns (paying particular attention to the issue of how sample volume was accounted for in your estimations of OTU curves, and providing metadata that would allow for more meaningful interpretations). We also encourage you to revise the Introduction/Discussion to more pointedly articulate how this study compares to previous ones that examine microbial community composition (including in animals), and how it raises new questions that move the field forward conceptually.

*Reviewer \#1:*

See summary comments

*Reviewer \#2:*

This paper presents a compelling combination of observational data and experiments to test the hypothesis that distantly-related families of pitcher plants share a common core microbiota independent of their geographic locations and evolutionary histories. The authors first present data supporting the hypothesis that the inquiline microbial communities of *Nepenthes* and *Sarracenia* species are more similar to one another than they are to their external environments. Such similarity across these huge geographic distances suggests that the plants\' leaf environments selectively enrich a similar suite of inquiline taxa and metabolic pathways. The authors then conduct a clever field experiment wherein *Nepenthes* host plants, which evolved in Asia, are brought into a *Sarracenia* habitat in New England and are allowed to naturally develop their microbiota. The authors found that *Nepenthes* pitcher community composition matched that of local *Sarracenia* pitchers, suggesting 1) that some shared features of these two families deterministically influenced the success of particular clades of micro-organisms, and 2) that differences between pitcher families\' microbiota are not evolutionarily conserved, and are instead products of their local source pools. In terms of novelty, a number of other studies have previously documented convergent interactions among hosts and their microbial symbionts (e.g., N-fixing and mycorrhizal associations in plants, diet-driven gut microbiota in animals), but this is among the first to identify shared communities that encompass such a wide taxonomic breadth (arthropods, micro-eukaryotes, bacteria). It is also one of the first to experimentally test how these communities form when placed well outside of their natural ranges (though analogous \'natural experiments\' have been conducted on *Sarracenia* introduced to Switzerland by Fragnière 2012 and Zander et al., 2016, which might be discussed). The inclusion of metagenomic data is another valuable contribution. Few studies have done so, and none as thoroughly as this one.

I outline a few concerns with the current draft below.

One major issue with the study design is that it appears pitcher leaves within each species were sampled at a single point in time from their respective locations. Given that pitcher environments and microbial communities have been observed to change markedly in response to season and prey deposition (e.g., Koopman et al., 2010; Sirota et al., 2013 PNAS) it would be very helpful to also have data on prey biomass (mg prey/ml), oxygen concentration, and (most importantly) living microbial and arthropod biomass in each pitcher. Were these data collected? How might differences in prey biomass influence the results?

Introduction, second paragraph: This paragraph draws some parallels between microbial diversity, global change, convergent interactions that are a bit of a stretch and are not covered in the design/Results/Discussion. If the goal is to justify the study, I think it\'s better to scrap the narratives of microbial diversity and global change, and instead introduce the question at hand -- how microbial communities assemble in highly-specialized, convergently-evolved structures. This could be done by introducing the concept of convergence in dietary structures among various clades (e.g. ruminants and the hoatzin, blood-feeding arthropods, wood-eating insects) and then introducing the potential importance of microbial digestive associates in these cases. The case can then be made that pitcher plants are uniquely situated for testing this concept.

Introduction, third paragraph: Citations here are misleading. Why not cite the studies that have actually used pitcher plants to investigate metacommunities and community assembly? (e.g.., Kneitel and Miller 2003; Buckley et al., 2003; Armitage 2017).

Introduction, third paragraph: It\'s not clear what these \'clear parallels\' are between these different communities. Here again, citations are somewhat misleading in that they do not address the aforementioned parallels between pitcher plant and phyllosphere/nectar/rhizosphere microbionts.

Introduction, last paragraph: Please explain how \'convergence\' is defined. As it stands, it is a nebulous enough term that it can be used to assign meaning to a huge variety of different patterns, such as:

-- many shared OTUs

-- some shared numerically-abundant OTUs

-- no shared OTUs but some shared genes conferring an implied function

-- no shared OTUs but many shared genes conferring no implied function

-- shared relative abundance of OTU families but no shared OTUs

-- shared network of OTU co-occurrences among hosts

Are there any commonly-used definitions? Is there a criterion for rejecting convergence?

Also, if the authors are truly searching for evidence of convergent interactions, then why aren\'t interactions being measured? The authors are making the tacit assumption that shared communities equates to shared interactions within those communities, which is not necessarily the case.

Subsection "Relocated *Nepenthes* converge on *Sarracenia*-like communities", last paragraph: Were pitcher leaves more similar to tubes with prey than they were to tubes without prey? These comparisons could identify how much variation prey capture accounts for, independent of the pitcher leaf.

Subsection "Relocated *Nepenthes* converge on *Sarracenia*-like communities", last paragraph: Given the differences in sample sizes, it\'s entirely conceivable that more tube samples would recapitulate the observed variation among pitchers and the \'reduced variation\' would vanish. Therefore, I suggest removing the statement that the glass communities were different from the experimental pitchers owing to their variation. Also, I couldn\'t find the PERMANOVA results for experimental pitchers vs. glass tubes. The negative results should also be included for the sake of transparency.

Discussion, second and fifth paragraphs: Without data on the actual contribution of microbes to host functioning (e.g., via prey decomposition/isotope uptake paired with fluid dilution/antibiotic treatment), calling these \'convergent interactions\' remains speculative, as the term \'interaction\' implies some type of reciprocal responses between the host organism and its microbiota. However, we already know that removing of many components of the pitcher food web (such as micro-arthropods) carries no perceptible consequences for their hosts (Butler, Gotelli and Ellison et al., 2008; Baiser, Ardeshiri and Ellison, et al. 2011). Again, a more formal introduction to \'convergent interactions\' would be welcome.

Subsection "Experimental relocation of *Nepenthes spp.* to a New England bog", second paragraph: I\'m not convinced that the control groups (bog water, soil) are appropriate references to use for detecting convergence among pitchers. For instance, bog and soil water are treated as \"null\" environments to which pitcher leaves are compared. However, since pitcher leaves are really being colonised by microbes derived primarily from the guts and bodies of trapped or resident arthropods, then wouldn\'t those organisms\' combined microbiota serve as a more meaningful source pool? That way, the resulting pitcher communities could be directly related to environmental filtering from the pool of colonists. What if the insect prey microbiota ended up being identical to the pitcher microbiota?

Subsection "Analyses of 16S and 18S diversity", third paragraph: Unweighted UniFrac is notoriously sensitive to rare members of the community. Please also include similar weighted UniFrac or Bray-Curtis based dissimilarity analysis in the supplement so that readers can assess the influence of rare vs. dominant taxa on beta-diversity.

Subsection "Analyses of 16S and 18S diversity", last paragraph: How were these trees generated? I can\'t assess their quality without more information such as the identification of major clades on the trees, some branch length scale, bootstrap values, rooting methodology, etc.

*Reviewer \#3:*

This study compared the eukaryotic and prokaryotic inhabitants of two phylogenetically and geographically distinct clades of pitcher plants. The authors ask if these inhabiting organisms show convergence in taxonomic and functional composition, defined here as being more similar to each other in composition than to other neighbouring habitats.

Overall, this is a very pleasing study. The breadth of organismal diversity studied -- from bacteria to insects -- is impressive and made possible by barcoding and metagenomics methods. The authors combine observational evidence (pitcher communities in native country) with experimental evidence (transplant of one pitcher genera to the other country) to build a case for convergence mediated by habitat filtering. Lastly, the authors delve into mechanistic details, examining the role of water chemistry (pH was key) and characterizing the prevalence of functional pathways.

1\) My most substantive comment is that I cannot find evidence in the Materials and methods or supplementary material that the authors standardized sample volume between the pitchers and the other environmental samples (soil and bog water). Since the authors use species accumulation curves (Figure 1B) to suggest that pitchers are more species depauperate than surrounding soil or bog water, standardizing sample volume is critical. Specifically, if there is any micro-scale spatial turnover in species composition, collecting a large sample, homogenizing it, and extracting 4000 sequences will result in capture of more OTUs that collecting a smaller sample, homogenizing it and extracting 4000 sequences.

2\) In the analysis of within-genera correlates of community structure (subsection "Within each genus, pitcher species, acidity, form, and volume correlate with community composition", third paragraph), it is not clear if you have controlled for species. If not, any community correlations with the physical and chemical properties of pitchers would be psuedoreplicated as these physical/chemical differences could simply stand in for species differences.

3\) In the gene pathways analysis, I couldn\'t determine if you were using samples from the same region (transplant experiment) or different regions (observation dataset). This matters in the interpretation of the results.

4\) There has been a fair amount of work comparing the strength of habitat filtering on macroscopic organisms vs. microbial, for example in lakes and bromeliads. Your study seems well positioned to follow up these ideas, in particular Figure 2 suggests that the pitcher habitat filters bacteria and eukaryotes to different degrees. Can you incorporate in your Discussion?

10.7554/eLife.36741.023

Author response

> Essential revisions:
>
> We would like to give you an opportunity to respond to the reviewers\' concerns (paying particular attention to the issue of how sample volume was accounted for in your estimations of OTU curves, and providing metadata that would allow for more meaningful interpretations). We also encourage you to revise the Introduction/Discussion to more pointedly articulate how this study compares to previous ones that examine microbial community composition (including in animals), and how it raises new questions that move the field forward conceptually.

We have included more detailed metadata in our revised manuscript, and updated our analyses to include both sample volumes and DNA concentrations. We have revised our Introduction and Discussion to more directly compare our study with other studies, targeting research investigating microbial community composition in animals and focusing on other convergently evolved organisms. We have carefully articulated how our study is a conceptual advance, relevant to the fields of evolution, ecology, and microbiology.

> Reviewer \#1:
>
> See summary comments
>
> Reviewer \#2:
>
> This paper presents a compelling combination of observational data and experiments to test the hypothesis that distantly-related families of pitcher plants share a common core microbiota independent of their geographic locations and evolutionary histories. The authors first present data supporting the hypothesis that the inquiline microbial communities of Nepenthes and Sarracenia species are more similar to one another than they are to their external environments. Such similarity across these huge geographic distances suggests that the plants\' leaf environments selectively enrich a similar suite of inquiline taxa and metabolic pathways. The authors then conduct a clever field experiment wherein Nepenthes host plants, which evolved in Asia, are brought into a Sarracenia habitat in New England and are allowed to naturally develop their microbiota. The authors found that Nepenthes pitcher community composition matched that of local Sarracenia pitchers, suggesting 1) that some shared features of these two families deterministically influenced the success of particular clades of micro-organisms, and 2) that differences between pitcher families\' microbiota are not evolutionarily conserved, and are instead products of their local source pools. In terms of novelty, a number of other studies have previously documented convergent interactions among hosts and their microbial symbionts (e.g., N-fixing and mycorrhizal associations in plants, diet-driven gut microbiota in animals), but this is among the first to identify shared communities that encompass such a wide taxonomic breadth (arthropods, micro-eukaryotes, bacteria). It is also one of the first to experimentally test how these communities form when placed well outside of their natural ranges (though analogous \'natural experiments\' have been conducted on Sarracenia introduced to Switzerland by Fragnière 2012 and Zander et al., 2016, which might be discussed). The inclusion of metagenomic data is another valuable contribution. Few studies have done so, and none as thoroughly as this one.

We appreciate your clear and concise summary; it highlights what we hoped readers would take from the manuscript.

We have added a sentence to the Introduction describing the Swiss *Sarracenia purpurea*: "Various arthropods have co-diversified with their pitcher plant hosts, suggesting ecological dependence and a shared evolutionary history (Satler et al. 2016). In fact, even though the species *S. purpurea* was introduced to Europe over 100 years ago, it houses very few insect inquilines, as compared to plants in native habitats (Zander et al. 2016); the close associations of pitchers and arthropods may be slow to evolve." We have not included the reference in our Discussion as the Swiss plants are growing in a place that does not have any native pitcher inquilines -- an aspect of natural history which translates to a very large difference between the Swiss circumstance and our manipulative experiment, in which the *Nepenthes* were placed into a *Sarracenia* habitat and exposed to the same pool of organisms already colonizing the convergently evolved Sarracenia.

> I outline a few concerns with the current draft below.
>
> One major issue with the study design is that it appears pitcher leaves within each species were sampled at a single point in time from their respective locations. Given that pitcher environments and microbial communities have been observed to change markedly in response to season and prey deposition (e.g., Koopman et al., 2010; Sirota et al., 2013 PNAS) it would be very helpful to also have data on prey biomass (mg prey/ml), oxygen concentration, and (most importantly) living microbial and arthropod biomass in each pitcher. Were these data collected? How might differences in prey biomass influence the results?

We agree that successional and seasonal dynamics can affect the communities within pitchers. But in Singapore, we sampled opportunistically at the same sites in different years (often traveling in different months of the different years), and saw almost no differences in our diversity measures among years (see our paper: Baker et al., 2016, Phil. Trans. B.). Much of our fieldwork took place in Southeast Asia. In remote locations, when it was impossible to specifically age pitchers or visit twice, sampling across pitchers was the best option: when we could only sample at one time point, we purposely sampled from pitchers at different successional stages in order to recover the greatest possible diversity. We recognize there can also be seasonal differences in diversity, but our data suggest successional stage and the randomness of prey capture have larger influences on microbiome diversity than season, and we are confident our sampling design reflects real differences between the biodiversity of different pitcher plant species across time and space.

We have included a discussion of oxygen concentrations in our Discussion (second paragraph). Oxygen is likely to be an unmeasured variable in our study; we did try to measure oxygen concentrations in the field, but our initial tests with a portable instrument proved the instrument was unreliable and we stopped collecting these data.

With regard to prey biomass and living microbial/other biomass, DNA concentration is the best and most appropriate measure for this study. Living biomass and DNA concentrations are strongly correlated (e.g. Marstorp, Guan and Gong, 2000), and in our samples it is a better measure than cell counts because some cells are lysed in the high-salt preservative we use to collect pitcher fluids in Borneo and other distant field sites. In fact our related study (Bittleston et al., 2016a) confirms that the great majority of the DNA sequences extracted from pitcher fluid samples came from living inquilines, and not from dead prey (in other words, DNA concentrations are not measuring dead biomass). DNA concentrations are also the most appropriate because some prey break down very quickly in pitcher plants, and measurements of prey biomass can result in an underestimation of resource availability (Heard, The American Midland Naturalist 1998; and personal observations).

We have added the DNA concentration of each sample to our metadata (Supplementary Dataset 1), and included DNA concentration as a variable in our analyses of *Nepenthes* and *Sarracenia* communities (see Supplementary file 1---table S4 in our revised manuscript).

> Introduction, second paragraph: This paragraph draws some parallels between microbial diversity, global change, convergent interactions that are a bit of a stretch and are not covered in the design/Results/Discussion. If the goal is to justify the study, I think it\'s better to scrap the narratives of microbial diversity and global change, and instead introduce the question at hand -- how microbial communities assemble in highly-specialized, convergently-evolved structures. This could be done by introducing the concept of convergence in dietary structures among various clades (e.g. ruminants and the hoatzin, blood-feeding arthropods, wood-eating insects) and then introducing the potential importance of microbial digestive associates in these cases. The case can then be made that pitcher plants are uniquely situated for testing this concept.

We appreciate your suggestions for improving our framing. We decided to delete the paragraph you reference, and rewrote the Introduction to 1) address microbial community assembly in convergent hosts across distinct animal/plant systems, and 2) explicitly articulate how pitcher plants are a model of microbial community dynamics.

> Introduction, third paragraph: Citations here are misleading. Why not cite the studies that have actually used pitcher plants to investigate metacommunities and community assembly? (e.g.., Kneitel and Miller 2003; Buckley et al., 2003; Armitage 2017).

We had chosen to cite general references to community assembly and metacommunity theory, but realize these citations were confusing. We have edited the citations to include your suggestions.

> Introduction, third paragraph: It\'s not clear what these \'clear parallels\' are between these different communities. Here again, citations are somewhat misleading in that they do not address the aforementioned parallels between pitcher plant and phyllosphere/nectar/rhizosphere microbionts.

Given our extensive editing, we don\'t feel this sentence is necessary any longer, and we have deleted it.

> Introduction, last paragraph: Please explain how \'convergence\' is defined. As it stands, it is a nebulous enough term that it can be used to assign meaning to a huge variety of different patterns, such as:
>
> -- many shared OTUs
>
> -- some shared numerically-abundant OTUs
>
> -- no shared OTUs but some shared genes conferring an implied function
>
> -- no shared OTUs but many shared genes conferring no implied function
>
> -- shared relative abundance of OTU families but no shared OTUs
>
> -- shared network of OTU co-occurrences among hosts
>
> Are there any commonly-used definitions? Is there a criterion for rejecting convergence?

Convergence is defined based on similarity, and similarity is a relative concept, making convergence inherently difficult to define precisely; nonetheless we seek precision and have written a sentence at the beginning of the results to clarify the definition we use to probe for the presence or absence of convergence: "Communities from Southeast Asian and North American pitchers were defined as converging if the communities were more similar to each other than to the communities of the environments immediately surrounding the plants, even despite the vast geographic distance between them." Much of the conceptual work behind this definition is described in our publication Bittleston et al. (2016b); in this publication we describe in detail our use of the word convergence. We have more explicitly referenced this publication in our revised manuscript. Using this definition, our study finds convergence as measured by alpha diversity (based on both observed OTUs and Shannon diversity), and as measured by the phylogenetic groups that are most common and relatively abundant within pitchers. Using this definition, tests of convergence can definitely fail. In terms of beta-diversity, our test of convergence is inconclusive, because in Figure 1Ci and Cii, the *Nepenthes* and *Sarracenia* communities do not cluster more closely with each other than they do with the communities from their surrounding environments. But the results of our manipulative field experiment suggest *Nepenthes* and *Sarracenia* pitchers function as similar selective environments, when exposed to the same microbial pool; the same kinds of communities assembled in each genus in the common habitat.

> Also, if the authors are truly searching for evidence of convergent interactions, then why aren\'t interactions being measured? The authors are making the tacit assumption that shared communities equates to shared interactions within those communities, which is not necessarily the case.

We would argue that we *are* measuring interactions: the interactions between the pitcher plants and the microcosms assembling within them. While exploring a subset of specific two-way interactions using more traditional ecological approaches emerges as a logical next step, it was not the focus of our paper, and could not be; we need the knowledge represented by the current manuscript to move forward. Focusing on a subset of interactions might also result in a different bias (how would we know the subset is representative?), and given that our aim was to work across the East Coast of North America, in Singapore, and in Borneo, high throughput molecular methods were definitely the first priority.

> Subsection "Relocated Nepenthes converge on Sarracenia-like communities", last paragraph: Were pitcher leaves more similar to tubes with prey than they were to tubes without prey? These comparisons could identify how much variation prey capture accounts for, independent of the pitcher leaf.

Thank you for this suggestion; you make a good point. We have now included the two types of tubes as different symbols in Figure 4Di and Dii. We also added text to the Results: "NMDS plots indicate glass tubes with added prey did not assemble communities more similar to the experimental pitcher communities than glass tubes without added prey."

> Subsection "Relocated Nepenthes converge on Sarracenia-like communities", last paragraph: Given the differences in sample sizes, it\'s entirely conceivable that more tube samples would recapitulate the observed variation among pitchers and the \'reduced variation\' would vanish. Therefore, I suggest removing the statement that the glass communities were different from the experimental pitchers owing to their variation. Also, I couldn\'t find the PERMANOVA results for experimental pitchers vs. glass tubes. The negative results should also be included for the sake of transparency.

We have removed the statement, and have included the analysis of pitchers vs. glass tubes in Supplementary file 1---table S4. We also added text to the Results: "Only a very small portion of the variation in community composition was explained in analyses of pitchers vs. glass tubes; however, the differences were highly significant (bacteria: *envfit* R^2^ = 0.05, P \< 0.001, *adonis* R^2^ = 0.02, P \< 0.001; eukaryotes: *envfit* R^2^ = 0.09, P \< 0.001, *adonis* R^2^ = 0.03, P \< 0.001). The analysis suggests a sterile, pitcher-shaped form is almost, but not quite entirely, sufficient for acquiring a pitcher plant-like microcosm (Figure 4D)."

> Discussion, second and fifth paragraphs: Without data on the actual contribution of microbes to host functioning (e.g., via prey decomposition/isotope uptake paired with fluid dilution/antibiotic treatment), calling these \'convergent interactions\' remains speculative, as the term \'interaction\' implies some type of reciprocal responses between the host organism and its microbiota. However, we already know that removing of many components of the pitcher food web (such as micro-arthropods) carries no perceptible consequences for their hosts (Butler, Gotelli and Ellison, 2008; Baiser, Ardeshiri and Ellison, 2011). Again, a more formal introduction to \'convergent interactions\' would be welcome.

Please also see our comments, above. We agree that direct evidence of reciprocal responses between the host organism and its microbiota would be strong evidence of convergent interactions. However, without our current data, the design of these manipulative experiments would be difficult to justify, and difficult to make happen in remote habitats: hopefully these kinds of experiments will take place in the near future. Meanwhile, our large dataset, collected from two continents, also builds a compelling case for convergent interactions: we have clearly demonstrated that two distantly related, convergently evolved genera of pitcher plants select for similar communities, with microbiomes with increased degradation capabilities compared to other habitats. However, to more appropriately reflect what we have learned, we have added "appear" to modify our updated statement: "Convergently evolved pitchers appear to cause convergent interactions (Bittleston et al., 2016b) between the two genera and their associated pitcher microcosms."

> Subsection "Experimental relocation of Nepenthes spp. to a New England bog", second paragraph: I\'m not convinced that the control groups (bog water, soil) are appropriate references to use for detecting convergence among pitchers. For instance, bog and soil water are treated as \"null\" environments to which pitcher leaves are compared. However, since pitcher leaves are really being colonised by microbes derived primarily from the guts and bodies of trapped or resident arthropods, then wouldn\'t those organisms\' combined microbiota serve as a more meaningful source pool? That way, the resulting pitcher communities could be directly related to environmental filtering from the pool of colonists. What if the insect prey microbiota ended up being identical to the pitcher microbiota?

Although insect gut microbes may be one source of pitcher microbiota, we do not agree they are the primary colonizers: the main bacterial groups we find in pitchers are ones that are generally soil-, water-, and plant surface-associated. Sirigusa et al. (2007) suggest that bacteria cultured from *Sarracenia* pitchers are of insect origins, however, the taxa referenced (e.g. *Serratia, Pantoea*, etc.) are also common soil and freshwater habitats. Takeuchi et al. (2015) found pitcher plant bacteria were more similar to phyllosphere bacteria than gut bacteria. In one of our own unpublished studies, we excluded insects (both prey and inquilines) from *Sarracenia purpurea* pitchers and still found common pitcher microbes colonizing the pitchers, even when insects were absent. Of course, ideally, we would have the entire spectrum of potential microbiota from all potential source environments as our "null" environments, but this kind of sampling simply wasn\'t feasible; based on what we knew, bog water and soil emerged as more relevant than insect guts. Because almost all of the microbes we found in our pitcher samples were also present (albeit at very low relative abundances, sometimes) in our environmental samples (see Figure 2), we feel that the sampled environments do represent good "null" comparisons for this study.

> Subsection "Analyses of 16S and 18S diversity", third paragraph: Unweighted UniFrac is notoriously sensitive to rare members of the community. Please also include similar weighted UniFrac or Bray-Curtis based dissimilarity analysis in the supplement so that readers can assess the influence of rare vs. dominant taxa on beta-diversity.

Thank you for your suggestion. We have run our beta-diversity analyses with Bray-Curtis as well and included the Results in our Supplementary file 1---table S4.

> Subsection "Analyses of 16S and 18S diversity", last paragraph: How were these trees generated? I can\'t assess their quality without more information such as the identification of major clades on the trees, some branch length scale, bootstrap values, rooting methodology, etc.

We did not include branch lengths in Figure 2 because visually, we find it easier to differentiate between clades when branch lengths are omitted. But to facilitate a more straightforward evaluation of the trees, we have added bootstrap value indicators in Figure 2, and have also included new trees as a figure supplement to Figure 2 with both branch lengths and branch length scales. We have also added text detailing rooting methodology to the Materials and methods section: "The bacterial tree was rooted with Archaea, and the eukaryotic tree was rooted in Streptophyta (land plants and most green algae)."

> Reviewer \#3:
>
> \[...\] 1) My most substantive comment is that I cannot find evidence in the Materials and methods or supplementary material that the authors standardized sample volume between the pitchers and the other environmental samples (soil and bog water). Since the authors use species accumulation curves (Figure 1B) to suggest that pitchers are more species depauperate than surrounding soil or bog water, standardizing sample volume is critical. Specifically, if there is any micro-scale spatial turnover in species composition, collecting a large sample, homogenizing it, and extracting 4000 sequences will result in capture of more OTUs that collecting a smaller sample, homogenizing it and extracting 4000 sequences.

Thank you for pointing this out: we have added sample volume metadata for our environmental samples to Supplementary file 1---table S3, and show that average sample volumes are similar across different types of samples (Supplementary file 1---table S3). We also tested for a relationship between sample volume and alpha diversity, using two different methods: we checked for a correlation between observed OTUs and volume (and found no correlation), and we re-ran our analysis of Shannon diversity using a subset of 155 samples that were all extracted around the same time, in exactly the same way, and with the same extraction volume. We see the same patterns of Shannon diversity in this subset as we see in our larger dataset. We are confident that sample volume is not driving the patterns of Figure 1Bi and Bii.

> 2\) In the analysis of within-genera correlates of community structure (subsection "Within each genus, pitcher species, acidity, form, and volume correlate with community composition", third paragraph), it is not clear if you have controlled for species. If not, any community correlations with the physical and chemical properties of pitchers would be psuedoreplicated as these physical/chemical differences could simply stand in for species differences.

Thank you for raising this issue. For the within-genus correlates that we examine, it would be difficult to control for host species within the multivariate analyses. For pH, the best way to control for host species is to examine the effect of pH within each of the three *Nepenthes* species that have broad pH ranges (*N. gracilis, N. rafflesiana* and *N. stenophylla*). We have added these analyses for these three host species, and for each we find that pH still has a very strong correlation with community diversity (Supplementary file 1---table S4). These new analyses clearly show that the strong correlation with pH is not simply a result of the different pH of different host species. Unfortunately, for the plant form analysis in *Sarracenia*, the different forms do not occur within a single species, and we cannot separate these factors. We have added a sentence to the manuscript explaining that plant form is confounded with host species and have removed plant form from our analyses.

> 3\) In the gene pathways analysis, I couldn\'t determine if you were using samples from the same region (transplant experiment) or different regions (observation dataset). This matters in the interpretation of the results.

We are using samples from different regions (the observation dataset), and definitely want this point to be clear to all readers. We have added text that says the metagenomes are from "field collected (not experimentally relocated)"pitchers.

> 4\) There has been a fair amount of work comparing the strength of habitat filtering on macroscopic organisms vs. microbial, for example in lakes and bromeliads. Your study seems well positioned to follow up these ideas, in particular Figure 2 suggests that the pitcher habitat filters bacteria and eukaryotes to different degrees. Can you incorporate in your Discussion?

Thank you for the interesting connection you make for us. We have added a sentence to our Discussion: "Fewer eukaryotes consistently colonize *Nepenthes* or *Sarracenia* pitchers, as compared to bacteria (Figure 2); the pattern is consistent with a stronger habitat filtering with increasing body size, as observed in bromeliad phytotelmata (Farjalla et al., 2012)."

[^1]: \*Corresponding author: Leonora S. Bittleston; current address: MIT Bldg 48-216, 15 Vassar Street, Cambridge, MA 02139; phone:1-831-212-1936; email: leobit\@gmail.com.
