Genomic survey of candidate stress-response genes in the estuarine anemone Nematostella vectensis.
To survive and reproduce, organisms must deploy an array of molecular, physiological, and behavioral responses to avoid or counteract detrimental environmental conditions. These responses to environmental stress are often complex, involving many genes and integrating events at cellular and organismal levels. Except in cases where it is possible to simply flee stressful environmental conditions, an organism's response to most environmental stressors--both natural and anthropogenic stressors--will typically involve changes in baseline gene expression that alter physiology, development, or behavior. Therefore, to study organismal stress responses, we must integrate environmental data, gene expression data, and organismal data (Ankley et al., 2006; Lee and Mitchell-Olds, 2006). The ongoing proliferation of genomic data is enabling comparative stress-response studies on a phylogenetically wider sampling of taxa occupying a broader range of habitat types (Lettieri, 2006). It is now possible to compare evolved differences between species occupying diverse environments at both shallow and deep evolutionary divergences.
Nematostella vectensis as an estuarine sentinel species
Nematostella vectensis Stephenson, the starlet sea anemons, is one of the relativety small number of macroscopic animals that are year-round residents in estuarine environments. It is a small infaunal anemone (typically <1 cm) inhabiting salt marshes, saline lagoons, and other sheltered brackish environments. The species' range includes the eastern Pacific, western Atlantic, northern English Channel, and western North Sea (Hand and Uhlinger, 1994).
In recent years, Nematostella has emerged as a model system for developmental (Finnerty et al., 2004; Matus et al., 2006) and genomic studies (Sullivan et al., 2006; Putnam et al., 2007), and it has proven particularly informative for reconstructing the functional evolution of developmental regulatory genes whose origins can be traced to the cnidarian-triploblast common ancestor. It is useful for such studies because (1) it is an outgroup to the superphylum Triploblastica (=Bilateria; Fig. 1), (2) it is easy to culture in the laboratory through its entire sexual and asexual life history, and (3) its genome appears to have evolved in a relatively conservative fashion. A general finding of comparative genomic studies involving Nematostella is that the sea anemone exhibits remarkable genomic complexity and a surprising degree of genomic conservation relative to vertebrates, despite its extreme evolutionary distance from vertebrates (Technau et al., 2005; Sullivan et al., 2006; Putnam et al., 2007; Sullivan and Finnerty, 2007).
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Nematostella is also useful for studying organismal responses to environmental stress because, in addition to extensive genomic resources, (1) it lives in a spatially and temporally variable habitat that is easily accessible, (2) it is easily subjected to laboratory stress studies, and (3) it is widely distributed (Hand and Uhlinger, 1994). Importantly, Nematostella has been collected in both pristine and anthropogenically impacted, degraded salt marsh habitats (Harter and Matthews, 2005), so it must be tolerant of a wide range of natural and anthropogenic stressors.
A first step in understanding how organisms sense and respond to stressors from the environment is to identify the genetic components of stress-response pathways. In this study, we searched the Nematostella genome to identify homologs of proteins known to be involved in sensing stress, counteracting particular stressors, and repairing damaged tissue. We divided the stress-response genes into three broad functional categories: (1) those that mediate chemical stresses, (2) those that counteract pathogens, (3) and those that underlie wound healing.
Materials and Methods
Identifying proteins implicated in stress response in other taxa
We compiled a list of proteins known to be involved in (1) chemical stress response, (2) innate immunity, and (3) wound healing. To identify genes involved in chemical stress response, we utilized a collection of "defensome" motifs compiled by Goldstone et al. (2006), with the following additions: zinc transporter (Pfam identifier PF02535); Ctr copper transporter family (PF04145); Cation efflux family (PF01545). To identify candidate genes involved in pathogen defense, we consulted the Innate Immunity Phyiogenomic Explorer, ver. 2.0 (Krishnamurthy et al., 2006). We first eliminated those protein families whose functional connection to innate immunity is relatively tenuous--i.e., proteins annotated as "related to" innate immunity or that might "putatively" play a role in innate immunity. This left 128 protein families to which we could ascribe a role in innate immunity with higher confidence. To identify candidate genes involved in wound healing, we culled the recent literature on wound healing and regeneration (Kiritsy et al., 1993; Galko and Krasnow, 2004; Alvarado and Tsonis, 2006; Huxley-Jones et al., 2007).
Identifying homologous proteins in Nematostella
After assembling a list of stress-response query genes from other taxa (Fig. 2a), we sought to identify putative homologs in Nematostella. Our principal search strategy utilized conserved protein domains cataloged in the Pfam database, release 17 (Finn et al., 2006). For innate immune genes and chemical defense genes, lists of conserved Pfam domains had already been compiled (Goldstone et al., 2006; Krishnamurthy et al., 2006). For wound-healing genes, we identified conserved domains in the query proteins using the conserved domain search function at Pfam (Fig. 2b). We then identified all Nematostella proteins that contained one of these conserved Pfam domains (Finn et al., 2006) by searching a database of predicted proteins at StellaBase 1.0 (Sullivan et al., 2008) using a Hidden Markoff Model search algorithm (Fig. 2c; Durbin et al., 1998). Nematostella proteins were scored as possessing a particular Pfam domain if the match to a query sequence received an Expect value [less than or equal to] 1e-6. These proteins predicted by using StellaBase were then cross-referenced with predicted Nematostella proteins at NCBI using BLASTp (Fig. 2d). Since this search identifies all proteins matching a particular domain, even those that are not implicated in stress response, the proteins identified in our search were compared against the human Ref Seq database (downloaded 1 Oct. 2007, containing 24306 proteins) using BLASTp to determine whether a known stress-response gene is the best match (Fig. 2e-f).
In cases where no discernible Pfam domain could be located or where only certain members of large gene families are involved in stress response, human homologs of the query sequences were identified in the non-redundant database at NCBI (Fig. 2g-h) and compared against StellaBase using BLASTp (Fig. 2i), again specifying an Expect value cut-off of e -6 to identify putative Nematostella homologs. These StellaBase-predicted proteins were then cross-referenced with predicted Nematostella proteins at NCBI using BLASTp (Fig. 2j). Each Nematostella protein identified as a best match in this search was then compared against the human genome, using tBLASTn to determine whether a known stress-response gene is the best match (Fig. 2k-1).
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Comparison of protein motifs counts across seven species
We used the Genome Comparison tool in StellaBase to compare the occurrence of each conserved Pfam motif in the sequenced genomes of seven different taxa. The taxa compared were Escherichia coli, Arabidopsis thaliana, Saccharomyces cerevisiae, Nematostella vectensis, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. Using the Pfam database (release 17), we identified Pfam domains in each genome by using a hidden Markov model search algorithm on the NCBI dataset for each of these species. For these searches, we queried all Pfam motifs for which we recovered at least one matching Nematostella protein. When we tallied the results across species, we included all proteins that matched a Pfam motif at an Expect value cut-off of le -6 (Suppl. Table 1; http://www.biolbull.org/supplemental/). To facilitate comparisons among taxa, we calculated the ratio of the number of each Pfam motif found in each taxon divided by the number found in human (Fig. 3).
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Overall, we screened the Nematostella genome with 137 different Pfam motifs that are known to be associated with stress-response genes in other taxa. We identified over 2400 Nematostella proteins that were significant matches to 123 different Pfam motifs (Suppl. Table 1; http://www.biolbull.org/supplemental/). Below, we discuss individual stress-response proteins that we identified or failed to identify, categorized according to the type of stressor.
Chemical stress response
The chemical stressors that impact biodiversity in aquatic ecosystems include a diverse array of naturally and anthropogenically produced compounds (Goldstone et al., 2006). Naturally produced chemical compounds, generated by organisms or by solar radiation, include reactive oxygen species, phytotoxins, and microbial metabolites. Anthropogenic chemical insults include toxic pollutants such as heavy metals, polychlorinated biphenyls (PCBs), pesticides, herbicides, pharmaceuticals, polycyclic aromatic hydrocarbons, flame retardants (polybrominated diphenyl ethers), and organochlorine compounds (DDT, endosulfan). Estuaries are particularly susceptible to anthropogenic chemical contaminants since they are often located in the vicinity of dense coastal population centers, and their freshwater inputs tend to concentrate runoff and point sources of pollution from upstream sources. At the same time, chemical stressors generated by organisms or by solar radiation can often achieve extremely high levels in shallow estuarine pools that are only infrequently flushed by the tides.
The combination of natural and anthropogenic chemical stressors can have considerable consequences for the biodiversity in estuaries (Pennings and Bertness, 2001; Weis et al., 2004, 2005). Two biotic metrics that reveal much about the health of estuarine ecosystems are (1) the community composition--in particular, the presence and abundance of key indicator species, and (2) the physiological status of resident organisms. Increasingly, molecular and genomic methods are being employed to assay both the community composition of estuaries, particularly the microbial communities, and the physiological status of resident organisms. For example, gene expression assays have recently been employed to characterize the chemical stress response of Fundulus heteroclitus, the mummichog, an estuarine fish (Meyer et al., 2005; Schulte, 2007). The mummichog is a highly mobile animal, living in the surface waters of estuarine pools and creeks. It can migrate extensively throughout an estuary to avoid locally unfavorable conditions. However, many animals commonly found in estuaries are sessile, benthic species with limited ability to escape locally stressful conditions. Due to their lack of mobility and their habit of living in or on sediments that tend to accumulate toxicants, the gene expression profiles of such species (e.g., Nematostella) are likely to more accurately reflect the recent history of chemical stressors at a particular geographic locale.
Nematostella is an ideal estuarine sentinel species for genomic studies on chemical stress. As a sessile benthic animal and a basal metazoan, it can provide results to complement the ongoing work on Fundulus, a motile vertebrate. It is an easily collected and common inhabitant of estuaries all along the east coast of North America from Nova Scotia to Georgia and along the Gulf coast. Introduced populations can also be found in England and on the Pacific coast of North America, from central California to British Columbia (Reitzel et al., 2008). It occupies both pristine and highly contaminated habitats. For example, Nematostella has been collected in the Hackensack Meadowlands, a restored marsh located along the Hackensack River in northeastern New Jersey. This well-studied site is known to be contaminated with heavy metals (Weis et al., 2004, 2005; Barrett and McBrien, 2007), chlorinated hydrocarbons (Bopp et al., 1998), and pesticides (Barrett and McBrien, 2007).
As Nematostella's apparently low dispersal ability probably renders it unable to escape toxic contamination in the sediment through migration, it is likely that some populations have evolved greater tolerance to some chemical contaminants. Population genetic surveys conducted throughout the animal's extensive range have identified sharp genetic breaks between neighboring estuaries, and even between adjacent pools within single estuaries (Darling et al., 2004; Reitzel et al., 2008). Although the swimming larva represents a potential dispersal vehicle, these genetic studies suggest that the effective dispersal potential for this animal may be quite low. We have observed that larvae in culture exhibit positive geotaxis, a behavioral tendency that would contribute to their apparently limited dispersal (Reitzel, Darling, Sullivan, and Finnerty, unpubl. data).
Goldstone et al. (2006) characterized the chemical "defensome" of the sea urchin. Their classification, which we follow here, included (1) stress-activated receptors, signal transduction proteins, and transcription factors; (2) efflux pumps; (3) oxidizing enzymes; (4) reducing and conjugating enzymes; (5) antioxidant proteins; (6) metal detoxicants; and (7) heat-shock proteins. The first stage in chemical defense is environmental sensing, which involves two principal groups of genes, the PAS (Per-ARNT-SIM) family of transcription factors that respond to oxygen and small molecules, and the nuclear receptor superfamily that bind a variety of ligands, some involved in stress. Both these classes of genes regulate transcription of a variety of effector genes including cytochrome p450s (CYPs), conjugating enzymes, and transporters. Some chemical compounds that breech the cell membrane are removed by efflux proteins such as the ATP Binding Cassette (ABC) and other ion transporters such as the organic anion and cation transporters (OAT and OCT, respectively). Other chemical stressors are biotransformed to inactivate and eliminate them. Biotransformation involves two phases: oxidation, then reduction or conjugation. Oxidation is typically carried out by two families of genes, the flavoprotein monooxygenases (FMO) and the CYPs. After oxidation, compounds are reduced or conjugated by a large suite of gene families including glutathione-S-transferases (GSTs), sulfotransferases (SULTs), and aldo-keto reductases (AKRs). The final group of genes in chemical defense summarized by Goldstone et al. (2006) is antioxidant defenses. Reactive oxygen species (ROS), including superoxide, [H.sub.2][O.sub.2], and hydroxyl radical, are a product of both metabolism and exogenous processes (pollutants, ultraviolet radiation, hypoxia). Regardless of their source, ROS affect signal transduction cascades, transcription factors, DNA integrity, and lipids, to name a few, resulting in effects on differentiation, apoptosis, stress-responsive genes, and aging (Adler et al., 1999). A variety of antioxidant proteins including superoxide dismutase (SOD), catalases (CATs), and peroxidases have been identified in diverse metazoans that regulate ROS in the cell.
Stress-activated receptors, signal transduction pathways, and transcription factors
Nematostella possesses a number of receptor and transduction genes involved in chemical defense in sea urchin and human (Table 1). For example, a recent phylogenetic study revealed that most of the gene families in the basic helix-loop-helix (bHLH) superfamily had evolved prior to the cnidarian-triploblast divergence. Nematostella was found to possess 68 genes representing 29-32 families, including two proteins that also possess a second domain, the Per-Arnt-Sim, or PAS, domain: (1) the hypoxia inducible factor l[alpha] HIF-1 [alpha]) and (2) the aryl hydrocarbon receptor nuclear translocator (ARNT; Simionato et al., 2007). In our search of the Nematostella genome, we identified three PAS proteins--ARNT, HIF-1[alpha], and the ary1-hydrocarbon receptor (AHR). AHR was not identified in the earlier study, and given its presence in Hydra, its apparent absence in Nematostella was ascribed to a lineage-specific loss in the sea anemone (Simionato et al., 2007). The putative AHR homolog we identified (SB_56923; gil56394392), whose expression has been confirmed through an expressed sequence tag (EST) (JGI_CAGN20098.fwd), was not represented in the bHLH proteins culled from Nematostella in this previous study. However, a single "AHR related" gene, presumably the same protein, was identified in the publication of the Nematostella genome (Putnam et al., 2007). Both AHR and HIF-1[alpha] form complexes with ARNT and then regulate transcription of downstream targets through recognition of xenobiotic-responsive elements (XREs) or hypoxia-responsive elements (HREs), respectively. Further bioinformatic searches for these elements in upstream regions of potential effector genes would provide a fruitful avenue of research in constructing gene networks.
Our search recovered likely homologs to the bZIP transcription factors NF-E2 and Maf, which heterodimerize and activate gene expression in response to oxidative and xenobiotic stress. Both were recently identified in a number of cnidarians including Nematostella (Amoutzias et al., 2007). We also identified a KEAP1, an oxidative stress and electrophile sensor protein that binds NF-E2 in the cytoplasm, preventing NF-E2 translocation to the nucleus when the cell is not under stress (Jaiswal, 2004).
Table 1 Xenobiotic receptors and conditional transcription factors in Nematostella genome Gene Gene name Nematostella Human gene ID E value Family homolog bHLH-PAS AHR SB_50387 gi|4502003 e-33 ARNT SB_15721 gi|2702319 e-35 Hif-1[alpha] SB_27525 gi|4504385 e-32 CNC-bZIP & Cnc/NEF2 SB_56664 gi|5453774 e-7 related Keap SB_8385 gi|32425813 e-53 Maf SB_34218 gi|3068761 e-14 SB_16005 e-12 Nuclear Hnf(4) SB_4250 gi|31077207 e-34 receptors Rxr SB_14472 gi|5902068 e-58 Metal & Mtf SB_8762 1127901963 e-65 heat response Hsf SB_766 gi|5031767 e-45 SB_49214 e-34
Predicted Nematostella proteins also exhibit strong matches to the metal-responsive transcription factor (MTF1) and the heat-shock factor HSF1. Because each of these transcription factors regulates gene expression by binding to well-characterized recognition motifs in target genes--metal-responsive elements for MTF: TGCRCNC (Saydam et al., 2001; Zhang et al., 2001); heat-shock elements for HSF: repeats of AGAAN and its complement recognized by trimers of HSF1 (Orosz et al., 1996)--it will be possible to screen the Nematostella genome for candidate target genes.
Nematostella, like other cnidarians surveyed (Grasso et al., 2001; Thornton, 2003; Bertrand et al., 2004), lacks many of the nuclear receptors traditionally studied in organismal stress (e.g., estrogen receptors, NR1 family). However, the receptors most relevant to environmental perturbation, hepatocyte nuclear factor 4 (Hnf4) and the retinoid X receptor (RXR), both members of the ancestral nuclear receptor subfamily 2, appear to be present in Nematostella (Reitzel and Tarrant, unpubl. data) and other cnidarians (e.g., Grasso et al., 2001). The functional role of these genes awaits further study, but some evidence suggests that cnidarians may be susceptible to a condition resembling endocrine disruption (Tarrant, 2005). Furthermore, understanding the interaction of nuclear receptors and other genes involved in endocrine-like function in Nematostella may reveal how the endocrine system evolved (Tarrant, 2007).
ATP-binding cassette (ABC) superfamily proteins are efflux transporters that pump compounds across cellular membranes against their concentration gradient (Dean and Annilo, 2005). ABC transporters are grouped into eight subfamilies (A-H) of which B, C, and G are known to expel toxic substances (Goldstone et al., 2006). Our search recovered 42 candidate ABC transporters. The ABC transporter complement from Nematostella is similar to that of human (n = 48), greater than Ciona (n = 31), and less than urchin (n = 65). Phylogenetic studies of these genes are ongoing and will allow a comparison of the ABC gene distribution in each subfamily.
Nematostella also has strong matches to other toxicant efflux proteins involved in removal of herbicides and toxic metals such as mercury and cadmium. We observed significant matches to the organic anion transporter polypeptide (OATP) family (n = 4, SB_12293, 7514, 12005, and 47307), the organic cation transporter (OCT) family (n = 1, SB_18740), and zinc transporters (n = 4, SB_34021, 4313, 28001, and 34688).
Nematostella has putative homologs for all but one of the gene families involved in oxidative biotransformation (Table 2). The Nematostella genome encodes 48 predicted cytochrome p450s (Table 2, Supp. Table 1; http://www.biolbull.org/supplemental/), a gene family involved in oxidation of xenobiotic compounds including polycyclic aromatic hydrocarbons. Two other enzymes involved in oxidation of exogenous compounds--flavin-containing monooxygenase (FMO) and aldehyde dehydrogenase (ALDH)--are also present in Nematostella's genome. We did not identify a clear homolog for the prostaglandin-endoperoxide synthase (PTGS/COX) in Nematostella. This result is surprising given that PTGS genes have been identified in corals (Varvas et al., 1999; Jarving et al., 2004). Although the PTGS protein of the coral Gersemia fruticosa is 50% identical to the human version, the best Nematostella match is only 23% identical to human PTGS and exhibits equivalent similarity to human peroxidases. Overall, for those gene families known to be involved in oxidative biotransformation, Nematostella appears to have fewer genes than human or urchin (Table 2).
Table 2 Comparison of the number of proteins in the Nematostella, urchin (Strongylocentrotus purpuratus), and human genomes that exhibit significant matches to Pfam domains found in biotransformative genes Classification Description Pfam Version accession Oxidative CYP PF00067 11 FMO PF00743 8 ALDH PF00171 10 PTGS/COX PF01124 7 Conjugative GST PF00043/02798 5/8 MGST PF01124 7 SULT PF00685 14 UGT PF00201 8 NAT PF00797 7 Reductive AKR-like PF00248 10 EPHX PF06441 1 Classification Nematostella Urchin * Human * Oxidative 48 120 57 2 16 6 13 20 19 0 0 2 Conjugative 8 38 21 1 [dagger] 12 3 5 36 13 1 49 13 0 1 2(10) Reductive 2 10 8 0 5 2 * Data for urchin and human from Goldstone et al., 2006. [dagger] A search of Nematostella expressed sequence tags using BLAST at NCBI resulted in a significant match (GI: 156227921).
Nematostella also has a diverse set of genes involved in reductive and conjugative biotransformation. We identified Nematostella homologs for the conjugative gene families that transfer glutathione (GSTs, n = 8), that metabolize xenobiotics (SULTs, n = 5), and that detoxify contaminants by addition of a glycosyl group to form hydrophobic molecules (UGTs, n = 1). A larger number of proteins in each of these families was detected with BLASTp searches of the Nematostella genome (footnotes in Table 2). We did not detect a Nematostella homolog of the NQO-like aldo-keto reductase superfamily or the NATs, which detoxify compounds by acetylation of amines. NQO-like AKRs have only been reported in vertebrates and appear to be a vertebrate-specific gene family (Vasiliou et al., 2006). Our Pfam-based search of predicted proteins at StellaBase failed to identify a microsomal-membrane-bound glutathione transferase (MGST) or a microsomal epoxide hydrolase (EPHX). However, using BLASTp queries against the assembled Nematostella genome and ESTs produced by the Joint Genome Institute (Putnam et al., 2007), we identified one significant MGST also represented among the Nematostella ESTs (GI: 156227921) and one EPHX (GI: XP_001622323). The presence of only a single MGST in Nematostella may reflect the condition found in the cnidarian-triploblast ancestor; if so, this gene family appears to have undergone a significant expansion in the Triploblastica. Overall, for the shared reductive and conjugative genes, Nematostella seems to possess fewer representatives than sea urchin or human, suggesting potential expansion after the cnidarian triploblast split (Table 2).
Antioxidants and metal complexing
The Nematostella genome appears to encode a number of proteins involved in responding to ROS, including superoxide dismutase (SOD), various peroxidases, and the glutathione pathway (Table 3). Previous research with cnidarians, primarily anthozoans, has characterized the expression of SODs and catalase (CAT) in response to environmental stress (Richier et al., 2003, 2005; Yakovleva et al., 2004; Dash et al., 2006, 2007; Merle et al., 2007).
We also identified putative homologs to the iron-storage protein ferritin, the heme-detoxification enzyme heme oxygenase 1 (HMOX1), and the metal-binding phytochelatins. Interestingly, Nematostella appears to lack any member of the evolutionarily conserved metal-binding genes, the class I and II metallothioneins, which are found in diverse eukaryotes (Hamer, 1986) including sponges (Schroder et al., 2000). Metallothioneins are also reported to be absent from Hydra (Andersen et al., 1988), suggesting that these proteins may be absent in all cnidarians. Although cnidarians seemingly lack metallothioneins, a few studies have shown that various species accumulate metals in tissue and that species exhibit differential sensitivity to particular metals (Karntanut and Pascoe, 2000, 2002, 2007; Mitchelmore et al., 2003a). Studies on the anemone Anthopleura elegantissima have suggested that the accumulation of metals may be influenced by glutathione, a metal-binding antioxidant, as well as by endosymbionts (Mitchelmore et al., 2003a, b). Nematostella has a number of glutathione peroxidases (Table 3), enzymes that use glutathione as a cofactor, and glutathione S-transferases (Table 2) that catalyze conjugation and reduction reactions with glutathione as a substrate. Nematostella is not known to harbor endosymbionts.
Table 3 Pfam domains found in proteins that respond to oxidative damage and metal toxicity that are represented in the Nematostella genome Classification Pfam Name Description Pfam Accession Oxidative damage Sod_Cu Superoxide PF00080 dismutase Sob_Fe_N Superoxide PF00081 dismutase An_peroxidase Peroxidase PF03098 Catalase Catalase PF00199 GSHPx Glutathione PF00255 peroxidase Thioredoxin Thioredoxin PF00085 Metal complexing Metallothio Metallothionein PF00131 Cu-oxidase Multicopper PF00394 oxidase Transferrin Transferrin PF00405 Ferritin Ferritin PF00210 Heme_oxygenase Heme_oxygenase PF01126 Phytochelatin Phytochelatin PF05023 synthase Glutathione cycling GCS Glutamate PF03074 cysteine ligase GSH_synthase Eukaryotic PF03199 glutathione synthase Glutaredoxin Glutathione PF00462 reductase Classification Version Count Oxidative damage 8 1 11 1 5 4 8 1 (1) 9 6 8 13 Metal complexing 8 0 11 1 7 1 11 1 10 1 4 2 Glutathione cycling 5 1 5 1 10 4 (1) Significant BLAST match to Nematostella predicted protein in GenBank (GI: 156386091).
HSF, identified above, is a transcription factor that regulates expression of the heat-shock proteins (HSPs), which are involved in responses to temperature fluctuations and a wide variety of other stressors. HSPs are categorized into families on the basis of the molecular weight of the protein. Nematostella has multiple representatives in the hsp20 (7), hsp70 (6), and hsp90 (3) families. HSPs from various cnidarians have been studied in a variety of stress responses including temperature (Hayes and King, 1995; Kingsley et al., 2003; Schroth et al., 2005), coral bleaching (Downs et al., 2002), and aggression (Rossi and Snyder, 2001).
Innate immunity and biological stress
Broadly, the immune system of vertebrates with jaws can be divided into adaptive and innate immunity. Through the adaptive immune system, jawed vertebrates are capable of mounting a "learned response" against infectious agents via the generation of pathogen-specific antibodies. This complex, acquired response relies on B-cells (humoral system) and T-cells (cell-mediated systems), other lymphocytes, and an ability to model an extensive number of unique antibodies via light-chain variability of immunoglobulin proteins.
However, even in those organisms that possess an adaptive immune response, an important component of organismal health is the innate immune system. The innate immune system comprises a number of disparate host-defense mechanisms that interfere with the efficacy of infection by pathogens. The first line of defense, and an integral part of the innate immune system, is a physical barrier that impedes the entrance of infectious agents. Epithelium, mucous membranes, waxy cuticles, shells, and chitinous skeletons perform such a function in phylogenetically diverse organisms. Once an infectious agent gains access, vertebrate hosts may deploy numerous components of the innate immune system, including an inflammatory response, activation of the complement system, deployment of nonspecific macrophages and other leukocytes, production of free radicals and peroxide, and the production of antimicrobial peptides. Although such antimicrobial peptides lack the degree of specificity exhibited by immunoglobulins, they bind cell structural elements or macromolecules that are specific to major clades of infectious organisms.
A comparison of nonvertebrate deuterostomes (e.g., sea urchin) and basal vertebrates (lamprey, hagfish) reveals that the adaptive immune system is a vertebrate invention (Sodergren et al., 2006). In contrast, the evolutionary origin of the innate immune system remains obscure. Its presence in both deuterostomes (e.g., human and sea urchin) and protostomes (e.g., Drosophila sp. and Limulus polyphemus) indicates that this system originated prior to the radiation of triploblasts. We found that 63 of the 128 Pfam motifs specifically implicated in innate immune function appear to have homologs in the genome of Nematostella. These 63 Pfam motifs identify 1039 unique predicted proteins housed in StellaBase that may be involved in innate immune function (Table 4).
Table 4 Pfam domains associated with innate immunity that are present in Nematostella vectensis Pfam name (1) Description Accession AMP-binding AMP-binding enzyme PF00501 Ank Ankyrin repeat PF00023 Asp Eukaryotic aspartyl PF00026 protease BIR Inhibitor of Apoptosis PF00653 domain BTB BTB/POZ doamin PF00651 bZIP_1 bZIP transcription factor PF00170 bZIP_2 Basic region leucine PF07716 zipper C_tripleX Cysteine rich repeat PF02363 CARD Caspase recruitment PF00619 domain cNMP_binding Cyclic nucleotide-binding PF00027 domain DEAD_2 DEAD_2 PF06733 Death Death domain PF00531 DSL Delta serrate ligand PF01414 Dsarm Double-stranded RNA PF00035 binding motif EGF EGF-like domain PF00008 EGF_2 EGF-like domain PF07974 EGF_CA Calcium binding EGF PF07645 domain F-box F-box domain PF00646 FYVE FYVE zinc finger PF01363 Gln-synt_C Glutamine synthetase, PF00120 catalytic domain Glyco_hydro_1 Glycosyl hydrolase family PF00232 1 956 Glycolytic Fructose-bisphosphate PF00274 aldolase class-I HMG_box HMG (high mibility group) PF00505 box Ig Immunoglobulin domain PF00047 Ion_trans Ion transport protein PF00520 Laminin_EGF Laminin EGF-like (Domains PF00053 III and V) LEA_4 Late embryogenesis PF02987 abundant protein Lipozygenase Lipoxygenase PF00305 LRR_1 Leucine Rich Repeat PF00560 MATH MATH domain PF00917 MMR_HSRI GTPase of unknown PF01926 function NACHT NACHT domain PF05729 NMT Myristoyl-CoA:protein PF01233 N-myristoyltransferase, N-terminal NMT_C Myristoyl-CoA: protein PF02799 N-myristoyItransferase, C-terminal Paml16 Pam16 PF03656 PAZ PAZ domain PF02170 Pentapeptide Pentapeptide repeats (8 PF00805 copies) Piwi Piwi domain PF02171 Pkinase Protein kinase domain PF00069 Pkinase_Tyr Protein tyrosine kinase PF07714 PLAT PLAT/LH2 domain PF01477 PP2C Protein phosphatase 2C PF00481 PSI Plexin repeat PF01437 RCCI Regulator of chromosome PF00415 condensation (RCCI) RdRP RNA dependent RNA PF05183 polymerase Ribonuclease_3 RNase3 domain PF00636 SAM_1 SAM domain (Sterile alpha PF00536 motif) SAM_2 SAM domain (Sterile alpha PF07647 motif) SapB_1 Saposin-like type B, PF05184 region 1 SapB_2 Saposin-like type B, PF03489 region 2 TIR TIR domain PF01582 TPR_1 Tetratricopeptide repeat PF00515 TPR_2 Tetratricopeptide repeat PF07719 TPR_4 Tetratricopeptide repeat PF07721 Tsg101 Tumor susceptibility gene PF05743 101 protein (TSG101) Ubiquitin Ubiquitin family PF00240 UCH Ubiquitin PF00443 carboxyl-terminal hydrolase WAP WAP-type (Whey Acidic PF00095 Protein) 'four-disulfide core' WD40 WD domain, G-beta repeat PF00400 zf-C2H2 Zinc finger, C2H2 type PF00096 zf-C3HC4 Zinc finger, C3HC4 type PF00097 (RING finger) zf-TRAF TRAF-type zinc finger PF02176 zf-UBP Zn-finger in PF02148 ubiquitin-hydrolases and other protein Pfam name (1) Version (2) Count (3) AMP-binding 14 16 Ank 16 104 Asp 13 1 BIR 10 3 BTB 18 42 bZIP_1 10 1 bZIP_2 3 5 C_tripleX 8 1 CARD 10 7 cNMP_binding 16 11 DEAD_2 5 1 Death 11 6 DSL 8 9 Dsarm 11 8 EGF 14 121 EGF_2 1 44 EGF_CA 4 91 F-box 19 3 FYVE 11 9 Gln-synt_C 12 1 Glyco_hydro_1 8 2 Glycolytic 8 2 HMG_box 8 14 Ig 14 76 Ion_trans 17 53 Laminin_EGF 12 17 LEA_4 6 1 Lipozygenase 7 2 LRR_1 19 35 MATH 14 6 MMR_HSRI 9 5 NACHT 2 2 NMT 8 3 NMT_C 4 1 Paml16 3 2 PAZ 10 1 Pentapeptide 11 2 Piwi 7 4 Pkinase 13 85 Pkinase_Tyr 3 88 PLAT 9 17 PP2C 10 5 PSI 12 2 RCCI 8 8 RdRP 2 4 Ribonuclease_3 12 2 SAM_1 16 12 SAM_2 4 13 SapB_1 4 1 SapB_2 4 2 TIR 8 2 TPR_1 14 74 TPR_2 3 74 TPR_4 2 2 Tsg101 2 1 Ubiquitin 12 5 UCH 16 9 WAP 10 3 WD40 18 83 zf-C2H2 14 111 zf-C3HC4 11 11 zf-TRAF 7 5 zf-UBP 7 1 (1) Pfam motifs may be retrieved by placing the accession after the following URL: http://www.sanger.ac.uk/cgi-bin/Pfam/getacc? (e.g., http://www.sanger.ac.uk/cgi-bin/Pfam/getacc?PF00501 will retrieve information for Pfam motif 'AMP-binding.' (2) 'Version' refers to the version / update of the Pfam motif utilized in the hidden Markoff model search. (3) 'Count' refers to the number of predicted proteins in StellaBase, ver. 1.0, which match the hidden Markoff model of each domain with an E-value less than or equal to le-6.
Toll-receptor-mediated innate immunity
The Toll-Receptor pathway is a central signaling pathway in the innate immune system. Originally identified in Drosophila, Toll receptors, and their nine vertebrate homologs, the Toll-like receptors, respond to numerous bacterial cell-wall constituents and the presence of viruses by initiating a signaling cascade that culminates in the activation of the transcription factors NF-kB, AP-1, and/or interferon regulatory factors. These transcription factors then upregulate the expression of effector genes required for the innate response (Armant and Fenton, 2002).
Five Toll-like domains (Pfam motif: TIR) have been identified in the Nematostella genome (Miller et al., 2007; Sullivan et al., 2007). Four of these domains are present in transmembrane proteins, suggesting a role in extracellular signaling. Three of these four transmembrane proteins are associated with two or more immunoglobulin motifs, suggesting a structure reminiscent of vertebrate interleukin receptors. The remaining transmembrane-linked TIR motif is associated with numerous leucine-rich motifs, which, when combined with phylogenetic analyses, suggests a structure conserved with true Toll- and Toll-like receptors in fly and vertebrates. The final TIR domain is not associated with a transmembrane motif, but rather with a DEATH domain, indicating that this protein may act as the first step in the intracellular signaling cascade (e.g., it may be a MyD88 homolog). Like Nematostella, Hydra magnipapillata was also found to possess predicted proteins combining Toll-like receptor domains in association with transmembrane motifs (Zheng et al., 2005).
Other key elements of the innate immune system have also been identified in Nematostella, including several members of the Toll and interleukin signaling cascades such as IRAK, TRAF, ECSIT, IKK, MKK, JNK, IKB, p38, and the transcription factors NF-kB and AP-1 (Table 4; Miller et al., 2007; Sullivan et al., 2007). Additionally, the transcription Interferon-regulatory factor, also inducible by the Toll-like signaling cascade, may have a homolog in this basal animal (SB 44157, Genbank Accession gill56396757|ref|XP_001637559.1; BLASTp E-value versus human interferon regulatory factor 2 [gill53082752|ref|NP_002 190.2] = [5e.sup.-40]). Interestingly, although Nematostella was found to possess a complex repertoire of innate immune genes, a relatively reduced complement of innate immune genes was identified in the freshwater hydrozoan Hydra magnipapillata (Miller et al., 2007).
In enidarians, it has been suggested that Toll-like receptors might be performing an ancestral function unrelated to innate immunity (Kanzok et al., 2004; Zheng et al., 2005). Kanzok et al. (2004) argued that animals lacking a coelom, including all diploblastic animals such as cnidarians, would not benefit from production of anti-microbial peptides--a hallmark of Toll-receptor-mediated innate immunity--because diploblasts lack an internal body compartment (namely, the coelom) into which these proteins could be secreted. For a time, this hypothesis was bolstered by an inability to recover an NF-kB or other Rel-homology domain containing transcription factor from any basal animal.
Now that many of the components of innate immunity have been identified in cnidarians, we can begin to assess whether they are performing a role homologous to the role in triploblastic animals. If functional Toll-and Interleukin-signaling cascades are indeed present in Nematostella, downstream targets of the cascade may be conserved between cnidarians and bilaterians (e.g., canonical targets of NF-kB). Homologs of known targets of NF-kB in vertebrates have been identified in Nematostella through sequence homology (Table 4; Sullivan et al., 2007). Downstream components present in Nematostella include numerous apoptosis regulators (i.e., caspases [Eckhart et al., 2007], p53, and p63), domains associated with antimicrobial peptides, antioxidant enzymes, and a putative homolog of a complement component protein (Table 4). We are currently searching the 5' regions of these putative targets to identify loci that are enriched for kB sites, and therefore potentially regulated by NF-kB, perhaps via the Toll-signaling cascade.
C3-related complement system proteins
Among cnidarians, a homolog for the complement system protein C3 was first identified in the gorgonian Swiftia exserta (Dishaw et al., 2005). In Nematostella, a systematic search of the genome for components of the complement pathway identified a C3 protein in addition to integrins, suggesting that a simplified complement system may be present (Nonaka and Kimura, 2006). Such a system, however, would have to be extremely simplified relative to the complement system of vertebrates, whose complexity required a number of gene and genome duplications over the course of vertebrate evolution. Interestingly, Hydra magnipapillata appears to lack a C3 protein (Miller et al., 2007), although evolutionarily related A2M-domain-containing proteins are expressed in the endoderm of Hydra with an expression pattern similar to that of a C3 protein of the coral Acropora millepora.
Along with chemical insults and infection by pathogens, physical wounding is a major source of organismal stress. Indeed, different categories of stressors interact to threaten the well-being of organisms: for example, pathogens may be introduced upon wounding, and the inability to recover from wounds may be the proximate cause of death in animals that are already stressed by chemical insults or pathogens. All animal phyla exhibit some ability to recover from wounds. In those animals where it has been studied in detail, wound healing is a complex and dynamic process that requires the interaction of many factors including cytokines, intracellular signaling pathways, transcription factors, and extracellular matrix (ECM) proteins. The extent to which the wound-healing process of "basal animals" might be homologous to the wound healing of triploblastic animals is not yet known.
We expect that some genes in the wound-healing repertoire of cnidarians may be unique to this phylum and thus identifiable only through empirical studies on cnidarians. However, as the "epithelial level of organization" exhibited by Nematostella is an extremely ancient invention that dates to the common ancestor of the Eumetazoa (if not earlier), it is likely that epithelial repair mechanisms are similarly ancient, and core elements of these pathways may be deeply conserved across animals. If so, searching for homologs of known wound-healing genes should be useful to identify candidate wound-healing genes in Nematostella.
Wound healing in vertebrates
Traditionally in vertebrate models, the process of wound healing has been broken down into three distinct but overlapping phases (Singer and Clark, 1999): (1) inflammation, (2) proliferation, and (3) matrix rebuilding and remodeling. During the inflammatory stage, the coagulation pathway is activated and platelets appear at the wound site (Kiritsy et al., 1993). Under the influence of cytokines such as platelet-derived growth factor (PDGF) and transforming growth factor beta (TGF-beta), these platelets form a plug at the site of injury (Franchini and Ottaviani, 2000). This phase is characterized by the activation of neutrophils, macrophages, and mast cells, which help to remove debris and bacteria from the wound site. Simultaneously, cytokines stimulate circulating cells to express integrins, and the integrins enable these cells to interact with the ECM. The proliferative phase is marked by the presence of fibroblasts, which produce a number of ECM components including collagen, proteoglycans, and fibronectin. Keratinocytes proliferate and migrate out to the edge of the wound site, creating a natural defense barrier. Additional cytokines are produced from fibroblasts, keratinocytes, and macrophages, and these intercellular signaling factors help to coordinate this complicated series of events. Lastly, the ECM is remodeled by the modification of collagen fibers, which results in the contraction of the wound. Collagen reorganization appears to be a very ancient component of metazoan wound healing shared among protostomes and deuterostomes (Tettamanti et al., 2005).
Wound healing in cnidarians
In cnidarians, wound healing is often followed by regeneration, and these two processes tend to be conflated in the cnidarian literature (Henry and Hart, 2005). However, two lines of evidence reveal that would healing and regeneration are evolutionarily and mechanistically separable processes. First, there are many animal species whose regenerative abilities are limited but whose wound-healing abilities are quite well developed--for example, if the tail of a mouse is surgically removed, the wound will heal, but the tail will not regenerate. Second, even in animals with extensive regenerative ability, such as cnidarians, wounds that do not result in the loss of a body region or structure do not necessarily trigger regeneration. In Nematostella, for example, complete bisection through the body column always results in the regeneration of a missing oral crown or a missing physa (Reitzel et al., 2007). However, incomplete bisection of the body column only rarely triggers the development of an ectopic oral crown or physa. Far more often, it triggers wound healing without regeneration. Here, we focus on wound healing and not regeneration, because the former is clearly a response to acute stress.
In cnidarians, the cellular events underlying wound healing have not been characterized at the same level of detail as in vertebrates, but at least one potential parallel has been noted. In vertebrates, the inflammatory stage is characterized by the influx of specialized cells to the wound site, including phagocytes (Gillitzer and Goebeler, 2001). Similarly, in some cnidarians, including gorgonians, scleractinian corals, and sea anemones, amoebocytes are recruited from the mesoglea to the wound site, and these cells engage in phagocytosis (Hutton and Smith, 1996; Meszaros and Bigger, 1999; Olano and Bigger, 2000; Henry and Hart, 2005; Mydlarz et al., 2006). These amoebocytes that migrate to the wound site also produce ROS (Hutton and Smith, 1996), as occurs in the circulating amoebocytes of other invertebrates (Nakamura et al., 1985; Coteur et al., 2002), suggesting that these cells are playing a role in an inflammatory response.
Identifying homologs of known wound-healing genes in Nematostella
In a first step toward determining whether the wound healing process in cnidarians is homologous to that of vertebrates, we can determine whether the same genes are involved in coordinating and regulating the process. Although a complex network of genes underlies the process of wound healing in vertebrates, none of the genes so far identified appears to be uniquely involved in wound healing. Thus, it is not possible to strictly categorize any gene as a "wound healing gene." However, we can determine which genes from the entire complement of genes active during wound healing in vertebrates are present in Nematostella, and subsequent investigations can determine whether these putative homologs are deployed in a homologous fashion during wound healing in the anemone.
The genes involved in vertebrate wound healing can be broken down into the following broad functional categories: (1) intercellular signaling molecules; (2) cell surface receptors and intracellular signaling molecules, (3) transcription factors, and (4) ECM components. On the basis of a survey of the literature, we identified 31 Pfam domains in proteins associated with wound healing, including signaling molecules, cell surface receptors, intracellular signaling factors, transcription factors, and ECM components. Every one of these Pfam domains scored a significant match to at least one predicted protein in StellaBase (Table 5, Suppl. Table 1; http://www.biolbull.org/supplemental/). Overall, the 31 domains scored significant matches to 485 different anemone proteins.
Table 5 Pfam domains associated with wound healing that are represented in the Nematostella genome Classification Pfam name (1) Pfam description Pfam number Extracellular Collagen Collagen triple helix PF01391 matrix components Fn2 Fibronectin type II PF00040 Fn3 Fibronectin type III PF00041 TB TB domain PF00683 glypican glypican PF01153 Laminin_EGF Laminin EGF-like PF00053 Laminin_G_1 Laminin G domain PF00054 Laminin_G_2 Laminin G domain PF02210 Laminin_B Laminin B (Domain IV) PF00052 Laminin_N Laminin N-terminal PF00055 NIDO Nidogen-like PF06119 LRR_1 Leucine Rich Repeat PF00560 LRRNT Leucine Rich Repeat N PF01462 TSP_1 Thrombospondin type 1 PF00090 TSP_3 Thrombospondin type 3 PF02412 TSP_C Thrombospondin C- PF05735 hemopexin Hemopexin PF00045 Somatomedin_B Somatomedin B domain PF01033 VWA von Willebrand factor PF00092 VWC von Willebrand factor PF00093 VWD von Willebrand factor PF00094 Signaling TGF_beta Transforming growth PF00019 molecules and receptors Activin_recp Activin type I and II PF01064 FGF Fibroblast growth factor PF00167 Lectin_leg_like Legume-like lectin PF03388 Gal_lectin Galactose binding lectin PF02140 Lectin_C Lectin C-type domain PF00059 TNF TNF (Tumor Necrosis) PF00229 Intergrin_beta Integrin, beta chain PF00362 FG-GAP FG-GAP repeat PF01839 Intergin_B_tail Integrin beta tail domain PF07965 Transcription CP2 CP2 domain PF04516 factors MH2 MH2 domain PF03166 MH1 MH1 domain PF03165 Classification Count (2) Version (3) Extracellular matrix components 25 7 9 8 107 10 1 7 1 9 17 12 14 12 17 10 1 8 5 7 1 2 55 19 1 8 54 8 6 7 4 1 3 8 3 7 98 14 1 7 2 13 Signaling molecules and receptors 5 8 3 11 3 8 1 3 25 7 24 9 1 8 3 7 7 11 2 7 Transcription factors 1 4 1 4 4 6 (1) Pfam motifs may be retrieved by placing the accession number after the following URL: http://www.sanger.ac.uk/cgi-bin/Pfam/getacc? (e.g., http://www.sanger.ac.uk/egi-bin/Pfam/getacc?PF00501 will retrieve information for Pfam motif 'AMP-binding.' (2) 'Count' refers to the number of predicted proteins in StellaBase, ver. 1.0, which match the hidden Markoff model of each domain with an E value less than or equal to 1e-6. (3) Version' refers to the version / update of the Pfam motif utilized in the hidden Markoff model search.
Another 26 genes involved in vertebrate wound healing could not be associated with particular Pfam domains. The human homolog for each of these genes was retrieved from NCBI and a BLAST search was conducted against predicted Nematostella genes at NCBI to identify putative homologs in the sea anemone (Table 6). These human proteins included 22 ECM components in addition to TGF-beta receptor and Jun N-terminal kinase (JNK). Most of these human genes matched one or more Nematostella sequences with an Expect value at or below the threshold of e -6, and in 10 cases, a reciprocal tBLASTn search, back against the human genome, provided evidence of genuine orthology between the human and sea anemone proteins (Table 6). Below, we discuss particular wound-healing genes that appear to have homologs in Nematostella.
Intercellular signaling proteins involved in wound healing--the cytokines
In vertebrates, cytokines function in a number of important biological processes including chemostasis and cell proliferation (Faler et al., 2006), and they play key roles during both the inflammatory and proliferative stages of wound healing. Our search of the Nematostella genome using a "transforming growth factor beta-like" domain (PF 00019) identified five TGF-beta ligands. Two TGF-beta factors were previously reported in this species, including a GDF5-like gene and a DPP-like gene; on the basis of their developmental expression, they are thought to be involved in axial patterning (Finnerty et al, 2004). Both of these genes were found in our Pfam domain search, as well as other TGF-beta factors identified previously (Matus et al., 2006).
There are two types of TGF-beta receptors: type I and type II. In the absence of a ligand, these receptors exist as homodimers on the surface of the cell, but they typically bind to ligands as heterotetramers (Derynck and Zhang, 2003). Activation of this signaling cascade by the binding of a TGF-beta ligand to a receptor complex can result in the nuclear translocation of SMAD proteins, which can impact cell proliferation and migration. Also, the TGF-beta signaling pathway can be Smad-independent and result in the activation of MAPK pathways, some of which have a role in the Smad activation (Derynck and Zhang, 2003). In Nema-tostella, we identified a single TGF-beta receptor that best matches human TGB-beta receptor I.
Integrins are a superfamily of integral membrane proteins that function in cell migration, cell-cell adhesion, cell-ECM adhesion, and signal transduction (Takada et al, 2007). In the cell, integrins are found as heterodimers, consisting of different alpha and beta subunits. The extracellular domains of integrins interact with a variety of ligands depending on the combination of receptor units. The cytoplasmic domain can interact with signaling proteins, focal adhesions, and cytoskeletal proteins, and it is through this interaction that integrin-initiated intracellular signaling occurs (Takada et al., 2007). It has been proposed that integrins can play a role in the nuclear translocation of the transcription factor NF-kB, as well as in activation of the Jun-N-terminal Protein Kinase (JNK) (Nikolopoulos et al., 2005). The JNK pathway is activated during the proliferative phase of wound healing in vertebrates and during epidermal wound repair in Drosophila (Ramet et al., 2002; Galko and Krasnow, 2004).
Both alpha and beta subunits of integrins were previously cloned in the jellyfish Podocoryne carnea (Reber-Muller et al., 2001). The beta subunit has also been cloned from sponge and coral (Brower et al., 1997). A search of the Nematostella genome using the "integrin, beta chain" and "integrin beta tail domain" identifies two integrin beta loci. A tBLASTn search using human integrin alpha proteins identifies two integrin alpha loci in Nematostella.
The transcription factor, grainyhead
Grainyhead plays a role in maintaining the tension of the cuticle in Drosophila, and similarly, it is implicated in the epithelial integrity of mammals, where a mutation in this gene causes defects in wound healing and epithelial barrier formation (Uv et al., 1994; Kudryavtseva et al., 2003; Mace et al., 2005; Ting et al., 2005). Grainyhead can be recognized by the possession of a highly conserved CP2 domain, and this transcription factor has been identified in a wide range of triploblastic animals (Moussian and Uv, 2005). A search of the Nematostella domain using the "CP2" domain identified a single significant match. Reciprocal tBLASTn searches between the human genome and the sea anemone genome identifies this predicted protein as the Nematostella ortholog of human grainyhead.
Smads are transcription factors that are downstream of TGF-beta signaling. They are implicated in cell proliferation and migration. In general, all smads share sequence similarity in the amino-terminal and carboxy-terminal domains, MH1 and MH2 respectively (Xu, 2006). Searching the Nematostella genome for the MH1 and MH2 domains identifies four significant matches to MH1 and one to MH2. According to a BLASTp search, four of the five MH1-containing proteins and the single MH2-containing protein are matches to human Smads. The remaining MH1-containing protein matches a human BMP.
Extracellular matrix proteins important in wound healing
During the proliferative stage of wound healing, an epithelium begins to form over the wound site, and the ECM is deposited. The ECM is a complex netting of glycoproteins, collagens, and proteoglycans. It is important for cellular remodeling during wound healing, and it is implicated in cell attachment and growth, cellular differentiation, and structural support of tissues (Huxley-Jones et al., 2007). Many ECM proteins exhibit strong evolutionary conservation across the animal kingdom. This high degree of conservation is thought to show the importance of collagen-based extracellular matrices in animals (Tettamanti et al., 2005; Aouacheria et al., 2006; Huxley-Jones et al., 2007).
The "collagen triple helix repeat" motif was a significant match for 19 predicted proteins in the Nematostella genome. When a BLAST search was performed against the human genome, these candidate Nematostella collagens exhibited best matches to multiple human collagen genes, including alpha 1 collagens (types V, XIII, XV, XXV), an alpha 2 collagen (type V), and an alpha 5 collagen (type IV). The BLAST searches also identified matches to a human contactin 4 (also known as BIG-2) and contactin 1 associated protein. The contactins are neuronal cell adhesion molecules that belong to the immunoglobulin superfamily (Yoshihara et al., 1995).
Searches using the "fibronectin type II domain" identified nine matches in the Nematostella genome, though none of these identified a fibronectin as a best match in the human genome. For example, three Nematostella hits to "fibronectin type II" were best matches to human matrix metalloproteinases (MMP-2 and MMP-9), enzymes involved in the breakdown of extracellular matrix proteins. MMP-2 and MMP-9 are unique among metalloproteinases in harboring three repeats homologous to fibronectin II (Steffensen et al., 2001). The six additional Nematostella loci that exhibit significant similarity to the "fibronectin type II" domain are best matches to human notch 2 preprotein, relaxin, vitrin, neuronal pentaxin, neuropilin, and semaphorin.
Searches using the "fibronectin type III domain" identified 101 significant matches in the Nematostella genome. Two of the genes identified are best matches to the same human fibronectin type III domain containing 3B gene, but none of the best matches are to human fibronectins. A large fraction of the Nematostella genes that were identified in the search for fibronectin type III domains are best matches to human protein tyrosine phosphatase receptors.
In an attempt to identify a bona fide fibronectin protein in Nematostella, we used tBLASTn to query the genome with the human fibronectin 1. When the best hit in the Nematostella genome was used to search the human genome, the best human match proved to be a sidekick protein (SDK2), not fibronectin 1 (Table 6).
Table 6 Reciprocal tBLASTn searches (human vs. anemone) using human proteins implicated in wound healing as the initial query Human query ID Nematostella E hit value Signaling Integrin, alpha 8 NM_003638 XM_001641385 1e-79 Integrin, alpha 4 NM_000885 XM_001641385 1e-74 TGF-beta type I AAD02042 XM_001622484 7e-138 receptor JNKI-B1 NM_139046 XM_001637538 3e-133 SLRPs (small leucine-rich-repeat proteins) Biglycan AAA52287 XM_001639122 9e-17 Chondroadherin AAK51556 XM_001639122 4e-22 Decorin AAB60901 XM_001633690 2.7 Fibromodulin CAA53233 XM_001631425 7e-14 Keratocan NP_008966 XM_001625510 0.0 Lumican AAA91639 XM_001640230 1e-16 Opticin CAB53459 XM_001623719 4e-08 Osteoglycin CAI16695 XM_001638871 0.15 PRELP CAG47066 XM_001630052 2e-15 Other extracellular matrix proteins Agrin CAI15575 XM_001632399 3e-75 Asporin CAI16697 XM_001638871.1 3e-19 Dermatan Sulf. AAC50945 XM_001623719.1 1e-09 Proteoglycan Dystroglycan AAH12740 XM_001621519.1 8e-25 Fibromodulin CAA51418 XM_001629115 2e-15 Fibronectin 1 NM_212476 XM_001635202.1 1e-26 Hemicentin NP_114141.2 XM_001625345.1 4e-116 Matrilin 1 NP_002370 XM_001618434 1e-42 Matrilin 2 AAH10444 XM_001636411 2e-91 Netrin 1 NP_004813 XM_001628849 3e-158 Netrin G1 NP_055732 XM_001628514 1e-145 Osteomodulin NP_005005 XM_001638987 4e-10 Osteonectin AAA60993 XM_001626392 1e-09 Podocan AAP79898 XM_001631425 6e-16 Reelin AAC51105 XM_001635471 2e-04 Syndecan 1 EAX00831 XM_001629466 0.24 Syndecan 2 NM_002998 XM_001637329 1.8 Syndecan 3 NP_055469 XM_001629466 1.9 Syndecan 4 NM_002999 XM_001641418 0.12 Tenascin CAA39628 XM_001638256 6e-64 Vitronectin EAW51082 XM_001633180 1e-13 von Willebrand fac. NM_000552 XM_001636212 1e-118 Human query Reciprocal E Human gene name human hit value Signaling Integrin, alpha 8 NM_003638 1e-74 integrin, alpha 8 Integrin, alpha 4 NM_003638 1e-74 integrin, alpha 8 TGF-beta type I NM_004612 9e-136 TGF-beta type I receptor receptor JNKI-B1 HSU35004 4e-131 JNK1-B1 SLRPs (small leucine-rich-repeat proteins) Biglycan AY166584 5e-25 Vasorin Chondroadherin AY166584 5e-25 Vasorin Decorin AC104667.5 6e-44 BAC clone RP11-810D14 Fibromodulin NM_020873 le-25 leucine rich repeat neuronal 1 Keratocan NP_002009 0.0 Flightless I Lumican NM_017768 8e-34 leucine rich repeat cont. 40 Opticin NM_012293 6e-32 peroxidasin homolog Osteoglycin AY280614 2e-19 synleurin mRNA PRELP NM_018214 3e-43 leucine rich repeat cont. 1 Other extracellular matrix proteins Agrin NM_198576 1e-71 agrin Asporin AY280614 2e-19 synleurin Dermatan Sulf. XM_001127072 6e-32 Peroxidasin homolog Proteoglycan Dystroglycan AK291692 5e-21 similar to Dystroglycan I Fibromodulin BC117180 3e-166 Leucine-rich repeat kinase 2 Fibronectin 1 NM_019064.3 2e-61 Sidekick 2 Hemicentin NM_031935 1e-99 Hemicentin 1 Matrilin 1 BC131710 2e-40 Matrilin 1 Matrilin 2 AB209735 3e-107 Fibrillin 2 Netrin 1 NM_004822 4e-160 Netrin 1 Netrin G1 BC113455 7e-119 Laminin, beta 1 Osteomodulin BC128989.1 2e-118 Leucine rich repeat cont. 7 Osteonectin NM_003118 2e-08 Osteonectin Podocan NM_130830.2 1e-25 Leucine rich repeat cont. 15 Reelin NM_001410 0.0 multiple EGF-like-domains 8 Syndecan 1 HSU78181 3e-25 Human sodium channel 2 Syndecan 2 AF163151 1e-22 Dentin sialophosphoprotein Syndecan 3 HSU78181 3e-25 Human sodium channel 2 Syndecan 4 BC020057 2e-160 Integrin, beta 1 Tenascin XM_001133349 0.0 Notch homolog 2 Vitronectin BC064803 7e-62 matrix metallopeptidase 14 von Willebrand fac. XM_001130382 2e-152 similar to Mucin-5AC
Small leucine-rich-repeat protein family
The small leucine rich repeat proteins (SLRPs) are a family of proteoglycans that are known to play important roles in organizing structural elements in the ECM, thereby impacting cell adhesion, wound healing, and the ability to withstand mechanical stress (Matsushima et al., 2000). The proteins are grouped into four classes based on the number and type of repeats and super-repeats they possess. Class I (e.g., decorin and biglycan) and class II (e.g., fibromodulin, lumican, keratocan, and PRELP) have 12 LRRs. Class III SLRPs (e.g., opticin and osteoglycin) have 7 LRRs. Class IV consists of chondroadherin. In vertebrates, specific LRR proteins are involved in distinct extracellular matrix types. For example, biglycan and decorin (class I) act in synergy to promote skin and bone integrity in mice (Corsi et al., 2002), while the class II protein lumican plays a role in wound healing in the cornea (Kao et al., 2006).
Leucine-rich repeats are found in a wide range of proteins, including bacterial virulence factors, cell adhesion molecules, enzymes, hormone receptors, and tyrosine kinase receptors, in addition to extracellular matrix-binding glycoproteins. A search of the Nematostella genome using the "leucine-rich-repeat" domain identified 54 matching genes, but none of these genes appears to be orthologous to any of the vertebrate SLRPs. When the human genome was queried using these 54 anemone sequences, the top BLAST hits included a number of predicted "leucine rich repeat containing" proteins but no members of the SLRP family. Using tBLASTn, we queried the Nematostella genome with human SLRP proteins (decorin, biglycan, fibromodulin, lu-mican, keratocan, PRELP, opticin, osteoglycin, and chon-droadherin). We then queried the human genome with the top BLAST hits from Nematostella, and not one of these reciprocal BLAST searches identified the human SLRP protein originally used to query Nematostella as the top hit. In all cases, other human LRR-containing proteins were identified (Table 6). These same SLRPs also seem to be lacking in protostome animals (Table 7), suggesting that they are deuterostome or vertebrate inventions (Huxley-Jones et al, 2007). The complexity of this gene family in vertebrates may be correlated with the diversity of vertebrate ECM types (cartilage, bone, tendon, cornea, tooth, etc.)
Other extracellular matrix genes
On the basis of reciprocal tBLASTn searches (Table 6), we were able to identify Nematostella orthologs of the human ECM proteins matrilin 1, netrin 1, osteonectin, and von Willebrand factor, but not reelin, syndecan-1, synde-can-2, syndecan-3, syndecan-4, tenascin, or vitronectin. A syndecan was previously reported in Nematostella (Chakra-varti and Adams, 2006). A single predicted protein in Stel-laBase (SB_50645) does exhibit greater resemblance to syndecan than to any other protein family represented in Pfam. However, the resemblance is weak (E-value = 0.02), and it is based primarily upon similarities in the short "cytoplasmic domain 1" (CI). Within this domain, the predicted Nematostella protein (RLRKRDEGSY) is identical to human syndecans (RMK/RKKDEGSY) at 7 or 8 of 10 residues (Chakravarti and Adams, 2006). However, a tBLASTn search of human genome using the anemone protein as a query did not return any hits. This suggests that the C1 domain may have predated the cnidarian-triploblast ancestor, but the ancestral syndecan may be a triploblast invention.
To determine whether the ECM proteins apparently missing from Nematostella might be exclusive to deuterostomes or vertebrates, we used tBLASTn to search for them in protostome genomes (Table 7). We then used tBLASTn to compare the top protostome hits back against the human genome to determine whether the best match would correspond to the original human query sequence. These reciprocal tBLASTn searches produced clear evidence for protostome syndecan and tenascin, suggesting that these ECM proteins may have evolved on the triploblastic stem lineage. However, we failed to identify asporin, fibronectin, matrilin, osteomodulin, podocan, reelin, or vitronectin in any protostome animals, suggesting that these ECM proteins may have originated within the Deuterostomia.
Table 7 Reciprocal tBLASTn searches (human vs. protostome) using human genes implicated in wound healing in the initial query Extracellular matrix ID Protostome E proteins hit value Human query SLRPs (small leucine-rich-repeal proteins) Biglycan AAA52287 XM_001649763 3e-21 Chondroadherin AAK51556 XM_970227 3e-26 Decorin AAB60901 No match n/a Fibrinidulin CAA53233 AJ549813 9e-21 Keratocan NP_008966 XM_001650288 8e-16 Lumican AAA91639 XM_395331 3e-17 Opticin CAB53459 XM_001606218 4e-11 Osteoglyein CAI16695 NM_206253 4e-04 PRELP CAG47066 XM_001360484 2e-15 Other extraceluar matrix proteins Asporin CAI16697 XM_967172 2e-28 Dermatan Sulf. AAC50945 XM_001650288 9e-14 Proteoglycan Fibronectin 1 NM_212476 XM_001601320 3e-33 Matrilin 2 NP_002370 AB159149 2e-26 Netrin G1 NP_055732 EF384215 6e-40 Osteomodulin NP_005005 XM_001658446 2e-16 Podocan AAP79898 XM_001650288 5e-29 Reelin AAC51105 XM_320234 9e-04 Syndecan 1 EAX00831 XM_001361667 1e-06 Syndecan 2 NM_002998 XM_966400 5e-6 Syndecan 3 NP_055469 XM_001664162 5e-3 Syndecan 4 NM_002999 XM_001361667 4e-10 Tenascin CAA39628 XM_310633 8e-62 Vitronectin EAW51082 XM_308849 9e-30 von Willebrand fac. NM_000552 XM_001606600 2e-168 Extracellular matrix ID Protostome E Reciprocal proteins hit value human hit Human query SLRPs (small leucine-rich-repeal proteins) Biglycan AAA52287 XM_001649763 3e-21 NM_003061 Chondroadherin AAK51556 XM_970227 3e-26 AK125112 Decorin AAB60901 No match n/a n/a Fibrinidulin CAA53233 AJ549813 9e-21 NM_018490 Keratocan NP_008966 XM_001650288 8e-16 BC101065 Lumican AAA91639 XM_395331 3e-17 BC094737 Opticin CAB53459 XM_001606218 4e-11 BC094737 Osteoglyein CAI16695 NM_206253 4e-04 EF090903 PRELP CAG47066 XM_001360484 2e-15 BC126169 Other extraceluar matrix proteins Asporin CAI16697 XM_967172 2e-28 AF055585 Dermatan Sulf. AAC50945 XM_001650288 9e-14 BC101065 Proteoglycan Fibronectin 1 NM_212476 XM_001601320 3e-33 X54131 Matrilin 2 NP_002370 AB159149 2e-26 EU085556 Netrin G1 NP_055732 EF384215 6e-40 HSU75586 Osteomodulin NP_005005 XM_001658446 2e-16 AK292182 Podocan AAP79898 XM_001650288 5e-29 BC101065 Reelin AAC51105 XM_320234 9e-04 AB051390 Syndecan 1 EAX00831 XM_001361667 1e-06 NM_001006946 Syndecan 2 NM_002998 XM_966400 5e-6 AK130131 Syndecan 3 NP_055469 XM_001664162 5e-3 NM_002998 Syndecan 4 NM_002999 XM_001361667 4e-10 NM_001006946 Tenascin CAA39628 XM_310633 8e-62 XM_945786 Vitronectin EAW51082 XM_308849 9e-30 X90925 von Willebrand fac. NM_000552 XM_001606600 2e-168 NM_198445.2 Extracellular matrix E Human gene name proteins value Human query SLRPs (small leucine-rich-repeal proteins) Biglycan 1e-44 SLITI Chondroadherin 2e-39 Similar to platelet glycoptoyrin Decorin n/a V precursor n/a Fibrinidulin 1e-121 Leucine-rich-repeat-containing G protein-coupled receptor 4 Keratocan 1e-40 Leucine-rich-repeat cont. 15 Lumican 9e-31 Toll-like receptor 3 Opticin 1e-28 Toll-like receptor 3 Osteoglyein 0 VPO mRNA PRELP 1e-105 Leucine-rich repeats & immunoglobulin-like domains Other extraceluar matrix proteins Asporin 0.0 Slit 2 Dermatan Sulf. 1e-40 Leucine-rich-repeat cont. 15 Proteoglycan Fibronectin 1 3e-145 Prot. tyrosine phosphatase beta Matrilin 2 1e-34 Collagen XXIX alpha 1 Netrin G1 0 Human netrin-1 Osteomodulin 3e-27 Similar to insulin-like growth factor binding protein, acid labiles subunit (IGFALS) Podocan 1e-40 Leucine-rich-repeat cont. 15 Reelin 0 VSGP/F-spondin Syndecan 1 1e-10 Syndecan 1 Syndecan 2 2e-15 Syndecan 2 Syndecan 3 3e-25 Syndecan 2 (SDC2) Syndecan 4 1e-10 Syndecan 1 Tenascin 0 Odd Oz/ten-m homolog 2s Vitronectin 1e-78 Matrix metalloproteinase von Willebrand fac. 0 SCO-spondin homolog Entries in bold type indicate human proteins that appear, on the basis of tBLASTn searches, to have orthologs in Nematostella.
Comparison of protein counts among seven diverse species
We compared the number of predicted proteins bearing Pfam motifs associated with chemical stress, innate immunity, or wound healing in seven diverse taxa (Fig. 3, Suppl. Table 1; http://www.biolbull.org/supplemental/). As expected, E. coli encodes the fewest proteins in all three categories. For motifs associated with chemical stress response, Saccharomyces cerevisiae, Nematostella, and Caenorhabditis elegans encode fewer proteins than human, while Drosophila melanogaster and Arabidopsis thaliana encode more. A. thaliana outnumbered human for proteins containing motifs associated with chemical stress by more than 3 to 1 due to extremely abundant representation of some Pfam motifs (e.g., p450s), despite lacking representatives for four of the assessed motifs.
For motifs associated with wound repair, the Nematostella genome encodes more proteins than any other taxon except human (~50% as many as human), including representatives of every motif queried. However, although Nematostella harbors a large number of proteins containing motifs associated with wound healing, it actually lacks homologs for many of the vertebrate proteins specifically implicated in wound healing, including fibronectin, many ECM proteins, and SLRPs. However, all other taxa lack representatives of two or more of the Pfam motifs associated with wound-healing proteins. E. coli and S. cerevisiae contained the fewest matches for the wound-repair motifs, which is unsurprising given that they are single-celled organisms.
For pathogen response, the overall number of proteins is larger in A. thaliana and C. elegans than in humans. With respect to pathogen defense, Nematostella exhibits fewer hits than other metazoans, but the anemone is the only taxon to have at least one protein representing each of the Pfam motifs associated with pathogen defense. For example, human contained no matches for the PF05183 (RNA-dependent RNA polymerase), but Nematostella had four hits.
General Discussion and Conclusions
Characterizing the molecular stress-response repertoire of Nematostella can be informative at four levels: (1) comparisons to triploblastic animals and non-animal models will help us to reconstruct the early evolution of stress-response pathways; (2) comparisons to species with narrower environmental tolerances, especially closely related marine anemones, will help us to understand the genomic basis for Nematostella's hardiness and ability to survive in estuarine habitats; (3) comparisons among genetically and phenotypically distinct populations of the starlet sea anemone can reveal the microevolution of stress-response pathways; and (4) identifying molecular markers of stress will augment our ability to utilize Nematostella and other Cnidaria as environmental sentinels.
Early evolution of animal stress-response pathways
Nematostella is a member of the phylum Cnidaria, a closely related outgroup to the superphylum. Triploblastica (=Bilateria: Fig. 1). The Triploblastica encompasses the vast majority of animal phyla and species, and a great deal of research has been conducted in an attempt to explain the remarkable evolutionary radiation of this group (e.g., Peterson et al., 2000). Many human developmental regulatory genes and disease-related genes have clear orthologs in Nematostella, indicating that they must have originated prior to the cnidarian-triploblast split (Putnam et al., 2007; Sullivan and Finnerty, 2007). Comparing the genomic complement of stress genes in Nematostella and Triploblastica will help illuminate the stress-response system of early animals, perhaps revealing the importance of transcriptional control, a primary difference between stress-response pathways in triploblastic animals and other eukaryotes (e.g., Roelofs et al, 2008).
Evolution of stress tolerance
Nematostella occurs over a wide range of salinities (a range of practical salinity values from 2 to 54 (Sheader et al., 1997) and temperatures (-1[degrees]C to 28[degrees]C; Frank and Bleakney, 1978; Williams, 1983; Sheader et al., 1997), and its remarkable environmental tolerances appear to be recently evolved. Nematostella is the only known estuarine specialist in the family Edwardsiidae, a clade of coastal marine anemones mainly restricted to temperate and polar seas where neither temperature nor salinity vary much. By contrast, within a single estuary, Nematostella may occupy isolated high marsh pools or tidal streams that flush with each tide--habitats that can differ substantially in temperature, dissolved oxygen, and salinity (e.g. Smith and Able, 1994). The range of Nematostella also encompasses dramatic latitudinal variation in temperature, from Nova Scotia, where marsh waters undergo seasonal freezing, to the subtropical waters of the Gulf of Mexico (Hand and Uhlinger, 1994).
The basis for Nematostella's broad environmental tolerances is not known. It could be that Nematostella's genome encodes more stress-response genes than the genomes of related marine species do, and these loci might be expressed at different environmental thresholds. Our analysis suggests this is not the case, because the number of stress-response genes in Nematostella is comparable to or even fewer than those in other surveyed metazoans. However, as our search relied on known stress-response genes from other animals, we could have failed to identify "novel" stress-response genes that may be present in the Nematostella genome. Identification of such genes will require global analysis of gene expression in Nematostella while subjecting the animal to various stressors. Similar techniques for profiling gene expression have been employed in characterizing transcriptional responses to environmental stressors in marine animals, including other cnidarians (Edge et al., 2005; Auslander et al., 2008).
Alternatively, or in concert, Nematostella populations could harbor an unusual degree of functional polymorphism in stress-response genes. Such genetic diversity could be maintained by fluctuating selection pressures. We have begun to characterize the geographic distribution and functional significance of some evolutionarily unusual protein-coding polymorphisms that have been identified in stress-response genes (e.g., NF-kB and deiodinase; Sullivan, Reitzel, and Finnerty, unpubl. data).
Microevolution of stress response
Commensurate with the environmental variation it encounters, Nematostella is known to harbor extensive genetic variation (Putnam et al., 2007; Sullivan et al., 2008; Reitzel et al., 2008), evident even at fine spatial scales (Darling et al., 2004; Reitzel et al., 2007). This suggests that the natural dispersal ability of the animals may be quite limited, that local adaptation may be driving genetic differentiation, or a combination of both. At the phenotypic level, we have observed significant differences among clonal stocks in their tolerance to temperature variation and oxidative stress (unpubl. results). With the identification of numerous candidate stress-response genes, we can begin to investigate the genetic basis for Nematostella's remarkable stress tolerance.
Nematostella vectensis as a sentinel species
The need for estuarine sentinel species
While estuaries are highly variable with respect to key environmental variables, they are also extremely important to marine biodiversity and heavily threatened by increasing human encroachment. Many marine species, including commercially important fishes and crustaceans, utilize estuarine habitats during pre-adult stages, and several endangered shore birds depend upon estuaries for essential forage.
Over the past century, estuarine environments have been severely degraded by increasing human encroachment (Pennings and Bertness, 2001). Estuaries are heavily impacted by anthropogenic contaminants, including heavy metals and endocrine disruptors that are released from point sources of pollution. Estuaries have also become increasingly fragmented by extensive coastal development, some of which interrupts the natural hydrological circulation, rendering the habitat unsuitable for estuarine flora and fauna.
In addition, global climate change represents a particular threat to estuarine natives, which, like other species occupying "island" habitats, may be limited in their ability to disperse to more suitable habitat islands (Stocks and Grassle, 2003; Harley et al., 2006). Global warming will affect not only temperatures in the estuaries, but also the range of other key physiochemical variables (Harley et al., 2006). For example, increasing temperatures can indirectly alter the salinity of salt marshes by impacting the frequency and severity of storms, by melting polar ice caps and increasing sea levels, by altering ocean currents, and by increasing evaporation. The geographic range of estuarine species will respond differently depending upon their physiological tolerances and dispersal ability--some may expand, some may contract, and others will merely shift. This process will alter the membership of estuarine communities, including pathogens, which may increase the incidence of disease in many estuaries. The fate of estuarine communities may depend upon the ability of resident organisms to tolerate and adapt to this combination of physical, chemical, and biotic stressors and decreasing habitat availability. It is therefore urgent that we develop more sophisticated tools to monitor the health of estuarine ecosystems.
Collateral, benefits for other cnidarian sentinel species
Data on Nematostella will inform stress-response studies on other cnidarian species occupying different habitats (Fig. 4). The phylum Cnidaria is good source of environmental sentinel species because cnidarians are practically ubiquitous in aquatic habitats, and they are easily cultured via asexual propagation. Cnidarians occupy tropical, temperate, and polar latitudes, from the sea surface to the sea floor, in deep and shallow waters, and in freshwater, estuarine, ma-rine, and hypersaline environments. Their ability to reproduce asexually makes it possible to generate clonal stocks through regeneration--carefully controlled laboratory studies of organismal stress response can then eliminate genetic variation or exploit it, as desired. Repeated trials on the same genotypes (i.e., clonal lineages) exposed to the same environmental conditions can also be used to quantify stochastic variation in gene expression.
[FIGURE 4 OMITTED]
A number of cnidarian species are already being used for stress-response studies (Fig. 4), and Nematostella complements these models ecologically and phylogenetically. For example, sea anemones (class Anthozoa, subclass Hexacorallia order Actinaria) belong to the same subclass as the scleractinians, the main group of reef-building corals. Due to this relatively close evolutionary distance and the apparent similarity of coral and Nematostella genes (Miller et al., 2007), the identification of stress-response genes in the starlet sea anemone will inform ongoing genomic stress-response research on corals, which are more limited in experimental tractability (Fig. 4).
ADAM M. REITZEL (1), *, JAMES C. SULLIVAN (2), *, NIKKI TRAYLOR-KNOWLES (2), *, AND JOHN R. FINNERTY (2), [dagger]
(1) Biology Department, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543; and (2) Department of Biology, Boston University, 5 Cummington Street, Boston, Massachusetts 02215
Received 13 November 2007; accepted 14 February 2008.
* These authors contributed equally to this work.
[dagger] To whom correspondence should be addressed. E-mail: email@example.com
Abbreviations: ECM, extracellular matrix; EST, expressed sequence tag; ROS, reactive oxygen species.
AMR was supported by a Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, with funding provided by The Beacon Institute for Rivers and Estuaries, and the J. Seward Johnson Fund. NTK was supported by a graduate research training grant from the National Institutes of Health. This research was also supported by NSF grant FP-91656101-0 to JCS and JRF, EPA grant F5E11155 to AMR and JRF, and a grant from the Conservation International Marine Management Area Science Program to JRF.
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|Author:||Reitzel, Adam M.; Sullivan, James C.; Traylor-Knowles, Nikki; Finnerty, John R.|
|Publication:||The Biological Bulletin|
|Date:||Jun 1, 2008|
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