16S rDNA-based metagenomic analysis of bacterial diversity associated with two populations of the Kleptoplastic sea slug Elysia chlorotica and its algal prey Vaucheria litorea.
With more than [10.sup.30] microbial cells, prokaryotes are the dominant life form on Earth (Whitman et al., 1998; Simon and Daniel, 2011). Bacteria are ubiquitous, inhabiting typical soil and water environments as well as extreme environments such as deep-sea hydrothermal vents, glacier ice, and waters with high salt content (Jannasch and Mottl, 1985; Satyanarayana et al., 2005; Oren, 2008; Simon et al., 2009). Bacteria are key players in nutrient sequestration and recycling, providing the largest reservoir of carbon, nitrogen, and phosphorus on the planet (Whitman et al., 1998). The diversity of microbial metabolisms, ranging from photoautotrophic to chemoheterotrophic, has allowed bacteria to succeed as both free-living and symbiotic organisms. Despite their prolific nature, it is estimated that less than 1% of all known bacteria are cultivable, leading to a significant underestimation of bacterial diversity due to an inability to accurately mimic specific environmental niches, such as complex symbiotic partnerships (Handelsman, 2004; Kennedy et al., 2010; Simon and Daniel, 2011).
With the advent of metagenomics, particularly next-generation sequencing (NGS), a greater number of bacterial symbiotic relationships are being discovered as more systems (from marine invertebrates to the human gut) are characterized (Handelsman, 2004; Kennedy et al., 2007; Dubilier et al., 2008; Ley et al., 2008; Simon and Daniel, 2011). The use of 16S rDNA, first proposed by Carl Woese (Woese and Fox, 1977; Woese et al., 1990), has become the default tool for the molecular identification and characterization of microbes (Gill et al., 2006; Sogin et al., 2006; Dethlefsen et al., 2008; McInerney et al., 2008; Tringe and Hugenholtz, 2008; Sunagawa et al., 2009; Webster et al., 2010). The 16S rDNA gene is highly conserved in prokaryotes, but the sequence is hypervariable between species, allowing it to be used as a marker of evolutionary relatedness by comparing sequence polymorphisms. When metagenomic analysis first became common practice, bacterial diversity was studied using 16S rDNA clone libraries and automated Sanger sequencing. This produced long, high-quality reads (generally 700-900 bp) but was limited by the number of samples that could be sequenced in a single run and by cost (Goldberg et al., 2006). The emergence of NGS technologies over the past 5 years has greatly benefited metagenomics by allowing for large amounts of data to be produced at a low cost thanks to sequencing runs performed in parallel (Metzker, 2010).
Marine environments in particular have been the focus of various metagenomic studies, allowing for a better understanding of the diversity of both free-living and symbiotic bacteria and how these bacteria benefit the organisms they are associated with, especially in terms of providing nutrients and chemical defenses to their hosts. For marine animals with reduced digestive systems (e.g., sponges, corals, tube worms, and clams), obtaining nutrients from food and the surrounding environment can be difficult. To overcome this limitation, many marine invertebrates harbor chemosynthetic symbionts that provide them with organic carbon derived primarily from carbon dioxide and methane (Vacelet and Boury-Esnault, 2002; Bright and Giere, 2005; Taylor and Glover, 2006; Dubilier et al., 2008). Symbionts harbored in the gut of marine invertebrates as well as terrestrial animals, such as termites and humans, can also provide usable carbon by degrading complex polysaccharides using enzymes provided by a symbiont (e.g., cellulases and chitinases) that their hosts lack (Savage, 1986; Sawabe et al., 1995; Erasmus et al., 1997; Distel et al., 2002; Brune and Ohkuma, 2011).
In addition to organic carbon, nitrogen is an essential, yet often limiting, factor for marine invertebrate growth. Nitrogen exists as either fixed nitrogen (nitrate, nitrite, ammonium, and dissolved organic nitrogen) or atmospheric nitrogen (N2), and is continually cycled in marine environments (Brandes et al., 2007; Fiore et al., 2010). Most animals obtain fixed nitrogen from a food source, but if food is unavailable or fails to supply sufficient nitrogen, it must be acquired from the environment. Many corals, sponges, and shipworms harbor symbiotic microbes capable of nitrogen fixation or of nitrogen transformations such as nitrification and denitrification (Chimetto et al., 2008; Mohamed et al., 2008; Fiore a al., 2010). Additionally, marine invertebrates may obtain their nitrogen from passive uptake, including the uptake of free amino acids found in dissolved organic matter (Stephens, 1981; heckle and Manahan, 1989; Soylemez a al., 2010). The marine ecosystem also harbors numerous free-living bacteria capable of nitrogen cycling and generating usable forms of nitrogen in the local environment (Capone, 2008; Stal and Zehr, 2008; Kraft et al., 2011).
Symbiotic microbes are also important for maintaining the health of their host. Many marine invertebrates, especially corals and sponges, harbor various microbial symbionts that are capable of producing natural products or secondary metabolites, such as antibiotics and antimicrobials, that protect the host (e.g., by regulating the number of other microorganisms associated with the animal; Hentschel et al., 2001; Ritchie, 2006; Shnit-Orland and Kushmaro, 2009; Sacristan-Soriano et al., 2011). Interestingly, these bacterial products can also be beneficial to humans because many have anti-cancer, antifungal, and antimicrobial properties (Proksch et al., 2002; Wagner-Dobler et al., 2002; Piel et al., 2004).
In this study, 16S rDNA metagenomic approaches were used to identify bacteria associated with the sea slug Elysia chlorotica Gould, 1870, and its algal prey Vaucheria litorea C. Agardh CCMP2940, 1823. The sacoglossan mollusc E. chlorotica (class Gastropoda, suborder Placobranchea) is found in salt marshes along the eastern coast of North America, ranging from Nova Scotia to Florida, and is best known for forming an obligate endosymbiosis with chloroplasts obtained from its algal prey V. litorea, a filamentous heterokont (class Xanthophyceae; Trench, 1975; West, 1979; Pierce et al., 1996; Rumpho et al., 2000). This symbiosis is characterized by the ability of adult E. chlorotica to shift their metabolism between heterotrophism and photoautotrophism. The sea slugs are able to photosynthesize like plants by fixing CO2, provided that light and air are supplied. In the laboratory, animals are sustained photoautotrophically for months with no additional input of nutrients via heterotrophy. Although this endosymbiosis has been well investigated (Pierce et at, 1996; Rumpho et al., 2000, 2008, 2011; Pelletreau et al., 2011), no study has yet characterized and compared the bacterial community associated with both sea slug and alga to determine what species are present in the two organisms and whether these microbes perform any metabolic functions that help sustain the symbiosis. It is known, however, that E. ornata (a tropical relative of E. chlorotica) harbors the gammaproteobacterium Endozoicomonas elysicola in its gut (Kurahashi and Yokota, 2007). Additionally, an unclassified gram-negative endosymbiont was identified in the cytoplasm of three Vaucheria spp. (Ott, 1979). The presence of these endobiotic bacteria suggests that both E. chlorotica and V. litorea harbor bacteria, perhaps of a symbiotic nature.
Two populations of E. chlorotica (from near Nova Scotia [NS1, Canada, and Martha's Vineyard [MV}, MA, USA) were collected directly from their wild salt marsh habitats and analyzed to identify the microbes present and whether differences exist between the populations as a reflection of the two environments. In addition, the metabolic signatures of those microbes were compared to determine whether the two populations had distinctive signatures. An additional study compared the microbiomes of both wild populations to those that had been starved for 6 months in laboratory-controlled aquaria to determine changes in microbial diversity as a factor of both the environment and starvation. It was hypothesized that depriving the laboratory sea slugs of V. litorea would facilitate detection of metabolically necessary bacteria (e.g., those involved in N2 fixation). Finally, we analyzed the microbiomes of second-generation (F2) adult NS and MV sea slugs that were raised entirely in the laboratory. We compared their bacterial diversity to both the wild and laboratory-starved sea slugs as well as to the microbiome of the laboratory-cultured V. litorea that the F2 sea slugs had been fed throughout their development. Here we hypothesized that bacteria seen in association with both the wild and laboratory-bred sea slugs were likely to be obligate symbionts (genetically inherited) in nature and that E. chlorotica may obtain some of its bacterial diversity from its algal prey V. litorea.
Materials and Methods
Animal collections and maintenance
Adult, "wild" (W) specimens of Elysia chlorotica were collected from salt marshes near Halifax, Nova Scotia, Canada (NS-W) in May 2010 and from Martha's Vineyard, Massachusetts, USA (MV-W) in June 2010 (see Table 1 for a list of sample designations). Animals were stored in 50-ml conical tubes, which also contained the associated water and minimal sediment from the site of collection, for transport back to the laboratory on ice. Within 24 h of collection or arrival in the laboratory, 5-10 individual sea slugs from each population were flash-frozen by immersion in liquid nitrogen without washing (to preserve all associated external bacteria) and stored at--80 [degrees]C.
Table 1 Sample designation, population, treatment, and organism for metagenomic data Organism Sample Population Sample Treatment1 designation Elysia chlorotica (sea slug) NS-W Nova Scotia Wild NS-L Nova Scotia Lab-starved NS-F2 Nova Scotia Lab-bred MV-W Martha's Wild Vineyard MV-L Martha's Lab-starved Vineyard MV-F2 Martha's Lab-bred Vineyard Vaucheria litorea V. litorea Martha's Maintained under (alga) Vineyard laboratory culturing conditions for >10 years (1) Wild, collected from native salt marsh environment; Lab-starved, starved and maintained under laboratory euituring conditions for 6 mon in the absence of any algal food; Lab-bred (F2), second-generation adults bred in laboratory.
For "laboratory" (L) E. chlorotica, animals were collected from the wild (August 2009 for NS sea slugs and December 2009 for MV sea slugs) and then maintained for 6 mon in separate aquaria for each population in aerated 32 practical salinity units (PSU) artificial seawater (ASW; 925 mosmol [kg.sup.-1] Instant Ocean, Aquarium Systems, OH) at 10 [degrees]C on a 12-h light/dark cycle. During this 6-mon laboratory period, sea slugs from both populations (NS-L and MV-L) were starved (provided light and air but no algal food). The animals were transferred to new aquaria with fresh ASW every 1-2 wk. After 6 mon, unwashed sea slugs from each population were flash-frozen in liquid nitrogen and stored at--80 [degrees]C.
Laboratory-bred individuals of E. chlorotica (F2) were cultured from adults collected in the wild in the spring of 2009 for both populations. Briefly, adult sea slugs were maintained in 1 liter of ASW at 24 [degrees]C with filaments. of Vaucheria litorea to induce egg production. For each population, egg ribbons were removed from the breeding chamber, aspirated, rinsed with autoclaved 0.2-pm-filtered ASW (afASW), and maintained in afASW supplemented with 2.5 mg [1.sup.-1] of chloramphenicol (CAM) to minimize bacterial growth and help ensure further development to the veliger stage. Once hatched, the veligers were fed the unicellular haptophyte alga Isochrysis galbana daily and cultures were transferred to new afASW + CAM twice weekly. When veligers appeared metamorphically competent, they were transferred to afASW--CAM, and V. litorea was added to induce settlement and metamorphosis of veliger larvae to juveniles of E. chlorotica. F2 juveniles were allowed to mature to adulthood and free-feed on V. litorea in aquaria as described above. At the time of collection, the adult F2 sea slugs ([greater than or equal to]6$ mon old [NS] and [greater than or equal to]4 mon old [MV]) were not washed before being flash-frozen in liquid nitrogen and stored at--80 [degrees]C.
Laboratory culturing of Vaucheria litorea
The V. litorea culture used in this study has been maintained in the laboratory for more than 10 years in a modified f/2 medium in 32 PSU ASW at 18 [degrees]C with a 12-h light/dark cycle and sub-cultured every 2 wk. The alga was sampled 1 wk after being transferred in April 2009 and June 2011. A sample of O.25 g wet weight was cut from tive different algal cultures, pooled, frozen in liquid nitrogen, and stored at -80 [degrees]C.
Total DNA extraction
DNA was extracted from the sea slugs individually (five total for each sample) before pooling the final DNA. For the alga, the five individual algal samples for each sampling date (2009 and 2011) were pooled prior to DNA extraction. Total DNA for both the animals and the alga was extracted using the Plant DNA extraction buffer following the manufacturer's (Invitrogen, CA) instructions. An additional chloroform extraction was performed on all pooled DNA to improve purity. Quality and quantity of extracted DNA was assessed by gel electrophoresis and NanoDrop spectrophotornetry (NanoDrop Technologies, Inc., DE), before being stored at -20 [degrees]C.
Amplification of bacterial 16S rDNA
Bacterial-specific rDNA was amplified using a primer designed to exclude chloroplast 16S rDNA (7991) in conjunction with the universal bacterial primer 1492r (Lane, 1991; Chelius and Triplett, 2001). The 799f primer was designed by compiling bacterial 16S rDNA to identify conserved regions and excluding sequences shared only by plastids and cyanobacteria while still amplifying most bacterial 16S rDNA (Chelius and Triplett, 2001). This primer set amplified a 735-bp fragment of bacterial 16S rDNA (from V5-V9) from the total DNA of all samples of E. chlorotica and V. litorea. PCR reactions containing 1X NEB Standard Tag reaction buffer (New England Biolabs, MA), 0.2 mmol [1.sup.-1] each dNTP, 0.2 [micro]mol [1.sup.-1] each primer, 0.0625 U NEB Tag polymerase, and 10 ng of template DNA were performed following the conditions outlined by Chelius and Triplett (2001) using an MJ Mini thermal cycler (BioRad). PCR products were assessed following separation in a 1% (w:v) agarose gel in 0.5X Tris-acetate-EDTA (TAE) buffer. The 16S rDNA band (presumed based on size of the PCR product of approximately 735 bp) was gelexcised using the Qiagen QlAquick gel extraction kit (Qiagen, CA). DNA was eluted in 30 [micro]l of elution buffer (10 mmol [1.sup.-1] Tris-C1, pH 8.5), assessed using the NanoDrop spectrophotometer, and stored at--20 [degrees]C.
Clone libraries of 16S rDNA were created for the NS and MV wild and laboratory samples of E. chlorotica and for the V. litorea sampled in 2009. PCR products were ligated into pGEM-T Easy vectors following the manufacturer's (Promega, WI) protocol and using 5 ng of each PCR product. The ligations were incubated on blue ice and shipped overnight to the Genome Sequencing Center at Washington University (St. Louis, MO) for transformation and single-pass Sanger sequencing using the 1492r primer.
FLX amplicon pyrosequencing
The 16S rDNA products amplified from NS and MV wild, laboratory, and F2 samples of E. chlorotica DNA and V. litorea DNA were gel-excised and shipped to Research and Testing Laboratories LLC (Lubbock, TX). There, the samples were amplified with primers Yellow939F and Yellow 1492R (V6-V9 region) for bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP) as described by Sun et al. (2011).
Sequence analysis and phylogenetic classification
Clone library sequences were aligned and trimmed using Molecular Evolutionary Genetic Analysis (MEGA5; Tamura et al., 2011). Pyrosequencing amplicons were assessed for quality by Researching and Testing Laboratories LLC as described by Dowd et al. (2008). Amplicons with tags that did not have 100% homology to the sample designator and those less than 150 by long were removed from the analysis. Trimmed clone library and amplicon sequences for duplicate E. chlorotica samples, as well as the V. litorea samples from 2009 and 2011, were combined and then analyzed together using the Ribosomal Database Project (RDP) pyrosequencing pipeline (Cole et al., 2009). Sequences for each sample were aligned using Infernal ver. 1.1 rc 1 (Nawrocki and Eddy, 2007), clustered using the complete-linkage clustering method, and operational taxonomic units (OTUs) were determined by multiple pairwise distances (Cole et al., 2009) using a cutoff of [greater than or equal to]97% similarity ([much less than]3% divergence). RDP software was used to determine rarefaction curves.
The OTUs (representing pooled clone library and ampli-con sequence data) for each E. chlorotica and V. litorea sample were phylogenetically classified using the RDP classifier. Taxonomic designations were dependent on the confidence threshold percentage, a bootstrap-like confidence estimation, as described in Table 2. Any OTU sequence that fell below the required identity at any taxonomic level was grouped with other sequences at the next highest level, so that for each sequence the "most certain" taxonomy is reported. Classification of OTUs was visualized using Sig-maPlot 2000 (Systat Software, Inc., San Diego, CA). MEGA5 was used to build a maximum likelihood phylogenetic tree (bootstrap 1000) of all E. chlorotica and V. litorea OTUs. Fast UniFrac release 1.3 (Hamady et al., 2010) was used to perform unweighted and normalized weighted principal coordinate analyses (PCoA) of UniFrac values for all E. chlorotica and V. litorea samples. For the weighted PCoA, branch lengths in the phylogenetic tree were normalized in UniFrac to account for different rates of evolution between sequences so that each sequence contributed equally to the root-to-tip distance, preventing the analysis from emphasizing samples containing taxa that have evolved more quickly.
Table 2 Taxonomic designations based on confidence threshold cutoff's, a bootstrap-like confidence estimate Taxonomic designation Confidence threshold culoff (%) Phylum >77 Class >80 Order >85 Family >89 Genus >94 Operational taxonomic units (OTUs) were classified from phylum to genus using the Ribosomal Database Project (Cole et al., 2009)
I6S rDNA sequence accessibility
All assembled sequence data have been deposited on the public MG-RAST server (http://metagenomics.anl.gov). Sequences for each sample can be downloaded using the following MG-RAST IDs: NS-W (4488663.3), NS-L (4488654.3), NS-F2 (4488655.3), MV-W (4488658.3), MV-L (4488659.3), MV-F2 (4489049.3), and V. litorea (4489048.3).
Results and Discussion
It has been known since the late-1960s that Elysia chlo-rotica harbors chloroplasts from Vaucheria litorea in an endosymbiotic association, enabling the sea slug to live photosynthetically for several months under laboratory culture conditions (reviewed by Rumpho et al., 2000, 2011). However, no one has examined other symbionts (used here to describe associated bacteria, though the nature of the symbiosis remains to be defined) living on or within this photosynthetic metazoan and their potential roles in supporting the long-term survival of E. chlorotica. We examined bacterial diversity in two populations of adult E. chlo-rotica found in vastly different marine environments. In addition to the apparent climatological differences, the habitat of the Nova Scotia (NS) population is characterized by an extensive salt marsh with long, slow tidal exchanges, numerous deep trenches, and shallow pannes, all with hy-poxic silt/mud sediment and abundant plant growth, including large mats of various algae. In contrast, the Martha's Vineyard (MV) site is bracketed by marsh habitat but is subject to rapid tidal inundations, and is composed of mainly aerobic, coarse sandy sediment (K. Pelletreau, pers. obs.).
Characterization of bacterial communities using PCR amplification of 16S rDNA can be negatively biased by a number of factors including multiple copies of the 16S rDNA gene (rrn) in a genome (Farrelly et at, 1995; Klap-penbach et al., 2001; Crosby and Criddle, 2003) and variability in amplification targets (Dethlefsen et al., 2008; Liu a al., 2008; Wu et al., 2010), as well as amplification of extracellular, environmental DNA fragments (Klein, 2011). Thus, the presence of a gene signature does not guarantee the presence of an intact, active microbe, making it difficult to claim without further investigation that specific bacteria are present and performing certain metabolic tasks. Despite these limitations to using 16S rDNA, it is a robust tool and the most commonly used molecular method for identifying prokaryotes in varied environments.
The primers used to amplify the 16S rDNA product (799f-1492r; Chelius and Triplett, 2001) were chosen specifically because they excluded chloroplast 16S rDNA. Preliminary sequencing results for wild NS and MV sea slugs using universal 16S rDNA primers (63f and 1387r; Marchesi a al., 1998) resulted in clone libraries that were dominated by plastid 16S rDNA (90% for NS and 98% for MV; S. Devine, unpubl. data; H. Mattsson, unpubl. data). A side effect of this primer choice was the concurrent elimination of cyanobacterial sequences from our metagenomic libraries. Therefore, any diversity or metabolic benefits (e.g., nitrogen fixation and natural products; Burja a al., 2001; Lesser a at, 2007; Usher, 2008; Fiore et al., 2010) derived from the presence of cyanobacteria were not considered here.
Constructing the metagenomic libraries
Clone library sequencing and bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP) data were combined and collectively used to analyze bacterial diversity (Table 3). All sequences were assessed for quality by read length ([greater than or equal to]150 bp) and for classification as bacteria by a confidence threshold greater than 50% using the RDP Classifier. The total number of reads ranged from 4,601 (NS-F2) to 18,728 (V. litorea), with the MV sea slug samples consistently having a higher number of reads than the corresponding NS samples.
Table 3 Characteristics of 16S rDNA metagenomic libraries Sample designation (1) Characteristic NS-W NS-L NS-F2 MV-W MV-L MV-F2 Amplicon 5897 5887 4601 10,395 11,220 7038 sequences Clone library 91 160 n/a 71 154 n/a sequences Total reads 5988 6047 4601 10,466 11,374 7038 OTUs (2) 199 889 409 216 346 558 # of 91 399 171 70 142 165 single-read OTUs (Percent of (45.7) (44.9) (41.8) (32.4) (41.0) (29.6) total) Characteristic Vaucheria litorea Amplicon 18,493 sequences Clone library 235 sequences Total reads 18,728 OTUs (2) 1574 # of 567 single-read OTUs (Percent of (36.0) total) (1) NS = Nova Scotia, MV = Martha's Vineyard, W = wild, L = laboratory-starved, F2 = laboratory-bred. (2) Operational taxonomic units (OTUs) were defined by a pairwise similarity cutoff of 97% using the Ribosomal Database Project (Cole et ai, 2009) pyrosequencing pipeline.
Operational taxonomic unit identification and sequence depth
To overcome bacterial species ambiguity, which horizontal gene transfer, asexual reproduction, and high sequence homology (i.e., <3% sequence divergence between similar species) can complicate (Cohan, 2002; Bent and Forney, 2008; Wooley a al., 2010), OTUs for each E. chlorotica and V. litorea sample were identified by grouping bacteria on the basis of 16S rDNA sequence identity greater than or equal to 97% (Table 3). Microbial diversity thus reflects the number and relative abundance of OTUs in the environment, not necessarily the number of defined species. NS-L and V. litorea samples had the highest number of OTUs, 889 and 1574, respectively. This is likely a result of these samples exhibiting the highest number of single-read OTUs (OTUs with only one sequence associated with them [399 and 567, respectively]).
Rarefaction curves for each sample were constructed to measure the fraction of OTUs sequenced and indicated that the sequence data from NS-W and all MV samples were approaching completeness, as indicated by the graphic curve plateaus (Fig. 1). Thus, any further sequencing of these samples would yield very few new OTUs. In contrast, the rarefaction curves for NS-L and V. litorea indicate that further sequencing is necessary to be confident that the bacterial profile is complete. The high number of single-read OTUs from these samples (Table 3) indicates a large proportion of unique bacterial signatures in these samples, likely contributing to the shape of the rarefaction curves.
Taxonomic diversity: Phyla
The phylogeny of OTUs from each sample was identified using the RDP Classifier with the confidence threshold for each taxonomic level as described in Table 2. At most, 3% of OTUs (V. litorea) were unclassifiable at the phylum level. All samples were dominated by Proteobacteria ([greater than or equal to] 71%, Table 4)--the largest and most phenotypically diverse phylum, accounting for at least 40% of all known genera (Kersters et al., 2006). Like the Proteobacteria, other phyla in common to all E. chlorotica and V. litorea samples (Actinobacteria, Bacteroidetes, and Firmicutes; Table 4) can be found in a variety of aquatic environments, and their abundance can also be influenced by salinity (Kirchman et al., 2005; Mesbah et al., 2007; Dillon et al., 2009; Tamames a al., 2010). However, these latter phyla were far less dominant than the Proteobacteria. For example, Actinobac-teria and Firmicutes are more prevalent in freshwater, which corresponds to the low overall numbers (0.03%-1.9% and 0.04%-13.3%, respectively; Table 4) observed in this study. Firmicutes were more common in the laboratory-starved and laboratory-bred samples (13.3% in NS-F2), which may reflect an introduction of new laboratory-derived flora, particularly from human interaction since the most common Firmicutes sequenced were Staphylococcus and Streptococcus. In contrast to the Actinobacteria and Firmicutes, Bacteroidetes are abundant in all aquatic environments. However, Bacteroidetes, along with Proteobacteria, usually dominate marine environments and are important for nutrient cycling (Cottrell and Kirchman, 2000; Kirchman, 2002). In this study, Bacteroidetes accounted for 1.4% (NS-W) to 14.5% (NS-L) of the total OTUs (Table 4) and were typically the second most abundant phylum.
Table 4 Percentage of bacterial phyla associated with Elysia chlorotica populations and Vaucheria litorea Sample designation (1) Phyla (2) NS-W NS-L NS-F2 MV-W MV-L MV-F2 V, Iitorea Proteobacteria 97.0 79.0 71.0 97.9 97.2 88.6 88.4 Bacteroidetes 1.35 14.5 1.96 1.42 2.13 2.22 7.32 Firmicutes 0.100 2.78 13.3 0.0382 0.22 5.19 0.0427 Unclassitied 1.45 2.32 2.11 0.277 0.317 0.739 2.93 bacteria Actinobacteria 0.134 0.628 1.93 0.0287 0.0528 1.1.8 1.01 Fusobacteria 0 0.562 9.02 0 0 1.35 0 Tenericutes 0 0.198 0.522 0.344 0 0.767 0.267 Acidobacteria 0 0.0165 0.0217 0.0287 0.0176 0 0.117 Chlamydiae 0 0 0.130 0.00955 0.0176 0 0.0107 Chlorollexi 0 0 0 0 0 0 0.0587 OP10 0 0 0 0 0 0 0.0267 Planctomycetes 0 0 0 0 0 0 0.0160 Verrumierobia 0 0 0 0 0 0 0.0107 TM7 0 0 0 0 0 0 0.00534 (1) NS = Nova Scotia, MV = Martha's Vineyard, W = wild, L = laboratory-starved, F2 = laboratory-bred. (2) Phylum taxonomy and abundance were classified based on a confidence threshold cutoff of >77% using the RDP Classifier (RDP release 10 update 29). Values are given as a percentage.
The alga exhibited more diversity at the phylum level in comparison to the two sea slug populations, as indicated by several phyla (Chloroflexi, OP10, Planctomycetes, TM7, and Verrumicrobia) appearing only in association with V. litorea (Table 4). Due to the low resolution of diversity at the phylum level for all samples, microbial diversity was further analyzed at the class and order levels (Fig. 2).
Taxonomic diversity: Class
At the class level, Actinobacteria, Alphaproteobacteria, Bacilli, Betaproteobacteria, Flavoproteobacteria, and Gammaproteobacteria were found in all of the sea slug and algal samples at varying abundances (Fig. 2). Again, more taxonomic classes were associated with V. litorea than with E. chlorotica, although most of these classes were 1% or less of the total algal OTUs, limiting their resolution (see top bar in Fig. 2G). For all samples, [alpha]-, [BETA]-, and [gamma]-proteobacteria were the most dominant classes; [alpha]-and [gamma]-proteobacteria are known to be most abundant in marine environments (Crump et al., 1999; Rappe et al., 2000; Dillon et al., 2009). The [gamma]-proteobacteria are the largest proteobacterial class (and most dominant in this study with the exception of NS-W; Fig. 2) with many diverse metabolisms and less sensitivity to changes in salinity (Glockner et at, 1999). In contrast, (3-proteobacteria are affected by salinity and are typically more abundant in freshwater than in marine environments (Glockner et al., 1999; Schweitzer a al., 2001; Kirchman et al., 2005). In this study, the [BETA]-proteobacteria was the dominant class only in the NS-W sample (Fig. 2), corresponding with an environment subject to large fluctuations in salinity (from 10-27 PSU; Scott, 1977; pers. obs.). In addition to the proteobacteria, dominant classes included Bacilli (up to 5% in MV-F2), Flavobacteria (6.6% in V. litorea), and Sphingohacteria (12% in NS-L).
Taxonomic diversity: Order
To further reveal microbial diversity, each class of [gamma]-,[BETA] and [alpha]-proteobacteria was characterized to the order level, and all remaining orders were grouped as "other" (Fig. 2). At the order level, percentage of abundance for all orders is dependent on only those OTUs that were classifiable below class level (>85% similarity to the RDP reference sequence) and always in relation to the percentage at the class level, not to total OTUs. This was done to more clearly present those orders that are at a relatively low abundance (many represent [less than or equal to] 1 %) when considering the total number of OTUs per sample. For example, 57% of the NS-L sample (at the class level) was composed of [gamma]-proteobacteria, which could be further classified to several orders. However, the percentage of the total OTUs will always be smaller than the percentage represented at the order--level for example, the Thiotrichales represent 7% of the total [gamma]-proteobacteria (Fig. 2B), but since the [gamma]-proteobacteria represent only 57% of the total OTUs, the Thiotrichales constitute only 3.6% of the total OTUs for that sample. In contrast, Thiotrichales constitute 47% of [gamma]-proteobacteria in the NS-W sample, but [gamma]-proteobacteria account for only 0.8% of the total OTUs. Thus, Thiotrichales actually represent only 0.1% of the total OTUs for NS-W (Fig. 2A).
When compared to the other class designations, the [gamma]-proteobacteria had the highest number of orders, includ-ing Alteromonadales, Chromatiales, Enterobacteriales, Pseudornonadales, and Vibrionales. However, in MV-W and MV-L (Fig. 2D, E), [gamma]-proteobacteria were composed primarily of Thiotrichales of the genus Francisella. The i3-proteobacteria in all samples were dominated by Burk-holderiales, most of which were of the family Coma-monadaceae. The [alpha]-proteobacteria were composed primarily of Rhizobiales, Rhodobacterales, and Rickettsiales. Since the remaining classes consisted of 28% or less of the total class diversity, the orders associated with these classes were combined in each panel of Figure 2. Of these orders, Bacillales, Flavobacteriales, Fusobacteriales, and Sphingo-bacteriales were most common among the samples. Flavo-bacteriales and Sphingobacteriales are both members of the phylum Bacteroidetes, which was often a dominant phylum after Proteobacteria (Table 4).
The two wild populations (Fig. 2A, D) exhibited key differences at the class level, with NS-W dominated by [gamma]-proteobacteria (Fig. 2A) and MV-W dominated by [BETA]-pro-teobacteria (Fig. 2D). Differences persisted at the order level, particularly for the [gamma]-proteobacteria and [alpha]-proteobac-teria, which showed varying abundances of Thiotrichales ([gamma]-proteobacteria) and Rickettsiales ([alpha]-proteobacteria) for the two samples. The W samples also differed at the order level for the "other" classes, although both were dominated by Flavobacteriales. These trends suggest that the differences in the environment between the NS and MV sampling sites are important selectors for bacterial diversity.
In comparing the classes and orders associated with animals maintained in the laboratory for 6 mon, these samples began to look more similar to one another in terms of diversity, but varying abundances revealed differences (compare Fig. 2B and 2E). For example, the [gamma]-proteobac-teria class was dominated by Alteromonadales in NS-L, whereas Thiotrichales dominated this class in MV-L. Similarly, orders of a-proteobacteria differed in the two samples, with Rickettsiales and Rhodobacterales dominating in NS-L while Rhodobacterales was most abundant in MV-L. As expected, based on changes in environment and lifestyle (i.e., starvation), laboratory-maintained sea slugs harbored different bacteria than wild sea slugs. Interestingly, these differences in the microbiomes were most obvious in the NS-L sample, whereas MV-L still looked similar to MV-W, particularly in terms of class diversity and the high number of Thiotrichales.
A comparison of the wild animals maintained in the laboratory for 6 mon to those that had been bred and raised entirely under laboratory conditions (L vs. F2; Fig. 2B, E vs. Fig. 2C, F) further supports a change in the microbiome as a product of maintenance in the laboratory environment. The L and F2 samples were more similar to one another in bacterial diversity and abundance than to the W samples, especially the NS-L and-F2 sea slugs (Fig. 2B, C). The NS-and MV-F2 sea slugs were most similar to one another at both the class and order levels (Fig. 2C, F). Additionally, V. litorea exhibited a unique class/order profile in comparison to both F2 samples as well as to any other sea slug samples (Fig. 20).
Principal coordinate analysis
To better understand what effect these differences in diversity had on the relatedness of each of the samples, unweighted and weighted UniFrac analyses were performed (Fig. 3A and 3B, respectively). When the two wild populations were compared, the NS-W and MV-W samples clustered more closely in the unweighted PCoA (Fig. 3A) than they did in the weighted PCoA (Fig. 3B), suggesting that community diversity between the wild samples is more similar when looking at who is present in each environment (unweighted) than when abundance is taken into account (weighted). However, these two samples do not cluster very tightly (i.e., in comparison to the F2 E. chlorotica samples), indicating that the environmental differences between the two collection sites played a key role in determining the bacterial communities. Although both the NS-W and MV-W samples were collected during the late spring/early summer (May for NS and June for MV), the marsh topography and environmental conditions are markedly different between the two sites. Salinity of the NS marsh can range from 10-21 PSU (Scott, 1977) (though data from August 2010 showed a high salinity of 27 PSU), whereas MV marsh salinity has been shown to be much higher, typically around 32 PSU (Carman et al., 2010). In addition, water temperatures vary between the two locations; at the time of collection the temperatures were approximately 6 [degrees]C in Nova Scotia (El Dorado Weather, buoy 44258) and 16 [degrees]C in Martha's Vineyard (Martha's Vineyard Coastal Observatory). Additional variables (e.g., nutrient load, air temperature) likely contribute to shaping the natural bacterial populations from which E. chlorotica could recruit.
The change in the microbial community as a function of the culture environment was best demonstrated by the transition from wild-captured to laboratory-maintained animals, In the NS samples, both the unweighted and weighted PCoA showed unique clustering of the NS-W relative to NS-L sample (Fig. 3). While NS-W clustered more closely to MV-W and MV-L, NS-L clustered with both F2 E. chlorotica populations but not with NS-W or MV-L. The bacterial profiles from animals collected in the wild from Martha's Vineyard (MV-W) versus those maintained in the laboratory (MV-L) showed tighter clustering in the weighted analysis and less clustering in the unweighted analysis (Fig. 3). Both of these MV samples had high numbers of Francisella (64% and 85% of total OTUs of the W and L samples, respectively), which is taken into account in the weighted PCoA, and the partial dominance of one bacterial group may explain part of the tight clustering. It was expected that the bacterial profiles of NS-L and MV-L would look more similar to each other than they do because of the same culture conditions in the laboratory. While the NS-L animals did exhibit a shift toward the bacterial profile observed in the F2 populations, the MV-L sample remained distinct, possibly due to the Francisella dominanace. The bacteria associated with NS-L E. chlorotica may be more advanced in their transition from a wild signature to a bacterial community that is representative of laboratory culturing and maintenance, whereas the MV-L population may still be transitioning toward the "laboratory" bacterial population. These observed differences in bacterial composition are likely a result of maintenance in a simple (no plants, sediment, or other animals) laboratory environment for 6 mon prior to sampling. A study by Kooperman a-al. (2007) comparing bacteria associated with wild and aquaria-raised coral showed shifts in diversity between the two environments, likely a result of a change in coral physiology in response to the artificial environment. Thus, by altering their bacterial symbionts, animals such as E. chlorotica (present study) and corals (Reshef et al., 2006) are able to adapt to changing environments. Overall, the data show that the wild E. chlorotica samples associate with specific bacterial communities that change over time and are directly and uniquely influenced by their immediate environment.
The strongest association was observed between the two populations of laboratory-bred F2 E. chlorotica, which clustered very closely together in both the unweighted (Fig. 3A) and weighted (Fig. 3B) UniFrac analyses, corresponding to the similarities seen in their bacterial profiles (Fig. 2C, F). These animals were subjected to identical selection pressures throughout their development, including the application of chloramphenicol to minimize bacterial growth during initial planktonic phases. Use of the antibiotic, in theory, should minimize and normalize the bacteria associated with the eggs and developing veligers, allowing the two sea slug populations to develop with similar bacterial (at least ecto-bacterial) profiles. In this case, the F2 sea slugs could select from bacteria in the artificial seawater (although this was autoclaved and filtered to minimize bacterial contamination), the laboratory environment (i.e., air and human interaction), and the V. litorea filaments provided as a food source. Since the NS-L and F2 E. chlorotica samples clustered together, this suggests that the laboratory culturing environment played an important role in the selection and maintenance of the bacterial communities.
Many of the bacteria associated with laboratory-cultured V. litorea, particularly members of the Chloroflexi, OP1O, Planctomycetes, TM7, and Verrumicrobia, were unique to V. litorea (Table 4), resulting in V. litorea clustering independently in both the unweighted (Fig. 3A) and weighted (Fig. 3B) UniFrac analyses. The unweighted PCoA plotted the alga closer to the F2 sea slugs than did the weighted analysis, reflecting the bacteria in common between the three samples without taking abundance into account. However, even though the F2 sea slugs preyed on the laboratory-cultured V. litorea, the organisms maintained separate terial communities, as indicated by the lack of clustering in UniFrac analyses. Although the alga could serve as a source of bacteria in the wild, the V. litorea in this study was from a long-term (>10 years) laboratory-maintained culture. Its normal flora has most likely transitioned over time, much like what is seen between the NS-W and NS-L samples, making a direct comparison between the wild E. chlorotica samples and V. litorea difficult. Interestingly, the NS population (NS-W and NS-L) clustered more closely with V. litorea than the MV population did, even though the V. litorea was originally collected from Martha's Vineyard.
Shared bacterial communities and putative metabolic functions
While comparisons of the total bacteria at the class and order levels illustrated the effect of varied environments and selection pressures on bacterial community profiles (Fig. 2), comparisons of the shared bacterial families (Fig. 4) were used to identify potential symbionts or metabolic partners Table 5). Bacteria common to all samples within a population, regardless of environmental conditions, may be symbiotically maintained by the sea slug or alga because of metabolic benefits provided by these bacteria.
Table 5 Characteristics of shared bacterial families Samples Family (Class) Typical shared by habitats (1) NS-W, L, Propionibacteriace Cutaneous, F2 MV-W, (Actinobacteria) intestinal, L, F2 V. soil, litorea wastewater NS-W, L, Rhodobacteraceae Aquatic F2 MV-W, ([alpha]-proteobacteria) environments, L, F2 V. marine litorea sediments, algae, marine invertebrates NS-W, L, Burkholderiales incertac Aquatic F2 MV-W, sedis ([beta]-proteobacter environments U F2 ia) with organic material NS-W, L, Comamonadaceae Aquatic F2 MV-W, ([beta]-proteobacteria) environments, U F2 soil NS-W, L, Francisellaceae Aquatic F2 MV-W, ([gamma]-proteobacteria) environments, L, F2 soil, marine and terrestrial animals NS-W, L, Micrococcaceae Soil, normal F2 (Actinobacteria) human flora NS-W, L, Moraxellaceae Aquatic F2 ([gamma]-proteobacteria) environments, soil, human tissues NS-W, L, Staphylococcaceae Animals and F2 (Bacilli) humans, soil, freshwater MV-W, L, Alteromonadaceae Marine F2 ([gamma]-proteobacteria) environments, sediments, deep-sea vents, marine invertebrates MV-W, L, Streptococcaceac Animals and F2 (Bacilli) humans, soil MV-W, L, Vibrionaceae Marine F2 ([gamma]-proteobacteri environments, a) marine invertebrates and vertebrates NS-L. Colwelliaceae Marine waters, MV-L ([gamma]-proteobacteria) sediments, deep-sea vents, marine invertebrates, organic materials NS-L, Flammeovirigaceae (Sphi Marine sediment, MV-L ngobacteria) marine invertebrates NS-F2, Cytophagaceae Marine MV-F2, V. (Sphingobacteria) environments litorea near shore and associated with algae, organic matter, or marine invertebrates, freshwater, soil NS-F2, En tcrobacteri aceae Aquatic MV-F2, V. ([gamma]-proteobacteria) environments, litorea soil, gut flora NS-F2, Mycoplasmataceac Fish, MV-F2, V. (Mollicutes) arthropods, litorea humans, plants NS-F2, Oceanospirillaceae Marine MV-F2, V. ([gamma]-proteobacteria) environments, litorea decaying algae, marine invertebrates NS-F2, Pseudomonadaceae Aquatic MV-F2, V. ([gamma]-proteobacteria) environments, litorea soil, animals, plants NS-F2, Sphingomonadaceae Aquatic MV-F2, V. ([alpha]-protcobacteria) environments, litorea soil, plant roots NS-W, L, Flavobacteriaceae Aquatic F2 V. (Flavobacteria) environments, litorea marine sediments, algal surfaces, marine invertebrates and vertebrates MV-W, L, Hahellaceae Aquatic F2 V. ([gamma]-proteobacteria) environments and litorea sediment, marine invertebrate gut Samples Putative metabolic functions shared by (1) NS-W, L, Carbohydrate fermentation, some F2 MV-W, species produce vitamin [B.sub.12] L, F2 V. litorea NS-W, L, Aerobic anoxygenic phototrophs. some F2 MV-W, heterotrophs L, F2 V. litorea NS-W, L, Some are iron and manganese oxidizers F2 MV-W, or methanotrophs, important for U F2 bioremediation NS-W, L, Chemoorganotrophs. nitrate reduction, F2 MV-W, nitrogen fixation in some species U F2 NS-W, L, Can be fish and human pathogens F2 MV-W, L, F2 NS-W, L, Some are capable of nitrate reduction F2 and bioremediation NS-W, L, Degradation of aromatic compounds, F2 bioremediation, nitrate reduction NS-W, L, Facultative anaerobes, can be F2 halotolerant MV-W, L, Chemoheterotrophs, alginolytic F2 activity, amylase and lipase activity, can produce bioactive compounds MV-W, L, Carbohydrate fermentation to produce F2 lactic acid MV-W, L, Cycling of organic and inorganic F2 compounds, nitrogen fixation, putative kahalalide F production (Hill et a/., 2007) NS-L. Alteromonas-llkc. typically MV-L psychrophilic, degrade chitin and starch NS-L, CFB clade, carbon cycling, MV-L decomposition of organic material NS-F2, Cytophaga-Flavobacterium-Bacteroides MV-F2, V. (CFB) clade; degrade proteins, litorea cellulose, chitin, starch, and pectin; important in carbon cycling NS-F2, Sugar fermentation, nitrate reduction, MV-F2, V. some are capable of vitamin [B.sub.12] litorea production NS-F2, Some ferment glucose, can be MV-F2, V. pathogenic, often intracellular litorea NS-F2, Chemoorganotrophs, some can reduce MV-F2, V. nitrate, degrade oil, use litorea ammonia/urea NS-F2, Chemoorganotrophs with varied MV-F2, V. metabolisms, cellulase activity, litorea bioremediation, some species produce vitamin B,2 or fix nitrogen, some can produce natural products NS-F2, Chemoheterotrophs, important for MV-F2, V. nutrient recycling in oligotrophic litorea environments NS-W, L, CFB clade; degrade proteins, agars, F2 V. xylan, fucoidan, cellulose, and litorea chitin MV-W, L, Halophilic chemoorganotrophs, F2 V. Endozoicomonas sp. is endosymbiont of litorea Elysia ornata (Kurahashi and Yokota, 2007) (1) NS = Nova Scotia, MV = Martha's Vineyard, W = wild, L = laboratory-starved, F2 = laboratory-bred.
Looking at all of the bacteria from the NS samples (W, L, and F2), 58 bacterial families were identified (>89% similarity cutoff; Fig. 4A). Among all three samples, there were 9 common families. The NS-W and NS-L samples had 3 families in common that were not associated with NS-F2, while one family (Lactobacillaceae) was shared by only the NS-W and NS-F2 sea slugs. However, the two NS samples that were exposed to the laboratory environment (NS-L and NS-F2) had 15 families in common that were not associated with the NS-W sea slugs.
In the MV populations, 42 families were identified, and 9 families were common to all MV sea slug samples (Fig. 4B). In contrast to the NS populations, no families were solely shared by the MV-W and MV-L samples. Four families were exclusive to the MV-W and MV-F2 sea slugs and 10 were seen only in the laboratory-exposed MV samples (MV-L and MV-F2).
Fifty-seven families were identified in the comparison between NS-and MV-F2 sea slugs and laboratory-cultured V. litorea (Fig. 4C). Twelve families were shared by all three samples, suggesting that the F2 sea slugs may obtain some of these bacteria from feeding on V. litorea. Between the NS-F2 sea slugs and the alga, 7 families were shared while only 2 families were exclusive to the MV-F2 sea slugs and V. litorea. Eleven families were limited to only V. litorea, supporting its unique bacterial diversity profile.
In comparing all E. chlorotica and V. litorea samples, only two families (Propionibacteriaceae and Rhodobacter-aceae) were shared by both the sea slugs and alga (Table 5), suggesting that these families are either metabolically significant or widespread in various environments. Families common to only E. chlorotica were Burkholderiales incertae sedis, Comamonadace, and Francisellaceae. Two families, Colwelliaceae and Flammeovirgaceae, were exclusive to the laboratory-starved (L) sea slugs, suggesting a possible metabolic benefit to the starving sea slugs. However, no families were exclusive to both populations of wild (W) sea slugs or to only the laboratory-bred (F2) sea slugs.
On the basis of the hypothesis that evolution would drive the conservation of metabolically significant bacteria in E. chlorotica as possible symbionts regardless of culture environment, bacterial families that were shared between all NS or MV E. chlorotica or between F2 sea slugs and V. litorea were considered further for their putative metabolic functions (Table 5). Most of the bacteria identified are chemotrophs involved in nutrient cycling, especially carbon or nitrogen. However, phototrophic Rhodobacteraceae are shared among all E. chlorotica and V. litorea samples (Table 5) and are widely distributed and abundant in marine environments (Brinkhoff et al., 2008).
Members of the [gamma]-proteobacteria were the most commonly shared bacteria and were found in all samples; other shared bacteria included [alpha]-and [beta]-proteobacteria, Actino-bacteria, and Bacilli (Table 5; Fig. 4). Carbon cycling is a key metabolic feature of members of the [alpha]-and [gamma]-proteo-bacteria, including Alteromonadaceae, Pseudomonadaceae, Sphingomonadaceae, and Vibrionaceae as well as Cytopha-gaceae and Flavobacteriaceae, which are members of the Cytophaga-Flavobacteria-Bacteroides (CFB) Glade. These bacteria produce enzymes capable of degrading various polysaccharides, such as cellulose, chitin, and pectin (Ramaiah et al., 2000; Ivanova and Mikhailov, 2001; Kirchman, 2002; Kirchman et at, 2004; Mikhailov et al., 2006). Many of these bacteria form symbioses with marine organisms, such as shipworms, corals, and sea urchins, and transfer usable carbon to their hosts, which is especially important in environments with low nutrients (Ritchie and Smith, 1995; Sawabe et al., 1995; Distel et at, 2002; Luyten et al., 2006; Sharon and Rosenberg, 2008), Interestingly, most of the polysaccharide-degrading bacteria were shared between laboratory-bred E. chlorotica and V. litorea (Table 5; Fig. 4C).
Nitrogen cycling is another key metabolic trait shared by different bacteria associated with all samples (Table 5; Fig. 4). Many of the bacteria, including members of the Coma-monadaceae, Enterobacteriaceae, Micrococcaceae, Oceano-spirillaceae, and Pseudomonadaceae, can reduce nitrate (Cole, 1996; Chou et al., 2008; Rajakumar et al., 2008). Denitrification is important in aquatic environments because a build-up of nitrate can lead to eutrophication and harmful algal blooms (Paerl et al., 2002; Rabalais et al., 2009). Although many of these bacteria are free-living, they can be associated with marine organisms, such as sponges, and are important in helping to balance out nutrient levels and prevent changes in the ecology and chemistry of the environment (Hoffmann et al., 2009; Fiore et al., 2010). Rho-dobacteraceae, which were found in common with all samples (Table 5), can also be denitrifiers and are known to associate with marine organisms and algae (Brinkhoff et al., 2008). Nitrogen fixation has also been reported among members of the Comamonadaceae, Pseudomonadaceae, and Vibrionaceae families (Jenni et al., 1989; Willems et al., 1991; Chimetto et al., 2008). While some bacteria in these families are free-living, Vibrio spp. can be prominent nitrogen-fixers in corals and sponges (Chimetto et al., 2008; Mohamed et al., 2008). How laboratory-starved sea slugs survive without nitrogen from a food source has been a long-standing question in understanding the stability of the Elysia-Vaucheria symbiosis. Although this study did not specifically analyze bacteria for nitrogen fixation, the data presented provide an initial description of potential microbial sources of nitrogen for use by E. chlorotica.
It is also feasible that the sea slugs obtain usable nitrogen that has been recycled from waste products. Members of the Comamonadaceae and CFB Glade are capable of degrading proteins to provide amino acids or ammonium ions that may be incorporated by the sea slugs (Schramm et al., 2003; Bernardet and Nakagawa, 2006; Bowman, 2006). In particular, Acidovorax-like symbionts of earthworms colonize the nephridia (excretory organs) and degrade peptides and amino acids, facilitating the reabsorption of nitrogen by the worms before it is excreted as waste (Schramm a al., 2003). In this study, Acidovorax spp. were associated with the NS population as well as with the MV-L and MV-F2 sea slugs.
Vitamin [B.sub.12] is a limiting nutrient for E. chlorotica when its algal prey is not available (e.g., during the 6-mon starved laboratory conditions). Some species of Enterobacteriaceae and Pseudomonadaceae (all laboratory-exposed sea slugs and V. litorea) as well as Propionibacteriaceae (all samples) (Table 5; Fig. 4) are capable of synthesizing vitamin [B.sub.12] (Martens et al., 2002; Stackebrandt et al., 2006) and, as such, serve as good candidates for further exploration into their potential metabolic role.
Natural products are beneficial to and ubiquitous in marine invertebrates, often serving as a means of chemical defense (Pawlik, 1993; Hay, 2009), but they are also beneficial to humans due to their various antimicrobial, antifungal, and anticancer properties (Monks et al., 2002; Blunt et al., 2009; Chakraborty et al., 2009). Alteromon-adaceae (Alteromonas, Pseudoalteromonas), Pseudomon-adaceae (Pseudomonas), Rhodobacteraceae (Roseobacter), and Vibrionaceae (Vibrio) appear repeatedly in the samples (Table 5; Fig. 4); they are families known to associate with various marine organisms, including corals, sponges, and algae, and represent known major secondary metabolite producers (Ivanova and Mikhailov, 2001; Wagner-Dobler et al., 2002; Thakur a al., 2005; Zheng et al., 2005; Mikhailov et al., 2006; Martens a al., 2007; Wietz et al., 2010; Mansson et al., 2011). Of particular interest are the Vibri-onaceae, which were found associated with all three MV E. chlorotica samples. One species, Vibrio mediterranei, has been shown to synthesize kahalalide F (KF), an anticancer depsipeptide, which is a secondary metabolite of several tropical Elysia spp. (Hamann and Scheuer, 1993; Ashour et al., 2006; Hill et al., 2007; Gao and Hamann, 2011). Also of interest are the Hahellaceae, especially members of the genus Endozoicomonas. These bacteria were associated with all MV samples as well as the NS-F2 sea slugs and V. litorea. Endozoicomonas elysicola is known to be an endo-symbiont of Elysia ornata, but it is not associated with any known specific metabolic traits. Although several putative metabolic functions can be assigned to the bacteria associated with E. chlorotica and V. litorea, further metatranscriptomic and biochemical studies are needed to confirm actual functions.
This study was the first to analyze the microbial diversity associated with the photosynthetic sea slug E. chlorotica and its algal prey Vaucheria litorea. Comparisons between two ecologically distinct populations of Elysia chlorotica indicated that these sea slugs maintain different bacterial communities and that diversity and abundance of these communities changes under different environmental conditions (i.e., wild vs. laboratory). Bacteria associated with laboratory-bred E. chlorotica also differ from those associated with their food source, laboratory-cultured V. litorea. However, bacteria in common to all samples within a population or between the laboratory-bred sea slugs and the alga may play key metabolic roles, particularly in polysac-charide digestion and nitrogen cycling. Future studies designed to identify and localize any permanent ecto-or endo-symbionts are needed to further elucidate specific metabolic functions the bacteria may be providing.
The authors thank Mr. Geoff Davis, Univ. of Maine, for his assistance with culturing of E. chlorotica, Ms. Katheryn Dutil for her assistance with culturing V. litorea, and Ms. Helen Mattsson for her Honors' Thesis research contributions to the early analysis of the microbiome. This research was supported by the National Science Foundation (grant #10S-0726178 to M.E.R.) and a Maine Sea Grant Project Development Grant (M.E.R.). This is Maine Agricultural and Forest Experiment Station Publication Number 3272, Hatch Project no. ME08361-08MRF (NC1168).
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Received 25 January 2012; accepted 31 May 2012.
* Current address: Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06069.
[dagger] To whom correspondence should be addressed. E-mail: email@example.com
Abbreviations: NS, Nova Scotia; MV, Martha's Vineyard; W, wild; L, laboratory; F2, laboratory-bred; OTU, operational taxonomic unit; PCoA, principal coordinate analysis.
SUSAN P. DEVINE *, KAREN N. PELLETREAU *, AND MARY E. RUMPHO * [dagger]
University of Maine, Department of Molecular and Biomedical Sciences, Orono, Maine 04469
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|Author:||Devine, Susan P.; Pelletreau, Karen N.; Rumpho, Mary E.|
|Publication:||The Biological Bulletin|
|Date:||Aug 1, 2012|
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