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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).


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).


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; 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).



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; 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

            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

            Rxr           SB_14472      gi|5902068     e-58

Metal &     Mtf           SB_8762       1127901963     e-65

            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).

Efflux pumps

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).

Oxidative biotransformation

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;, 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

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

Oxidative damage     Sod_Cu          Superoxide        PF00080

                     Sob_Fe_N        Superoxide        PF00081

                     An_peroxidase   Peroxidase        PF03098

                     Catalase        Catalase          PF00199

                     GSHPx           Glutathione       PF00255

                     Thioredoxin     Thioredoxin       PF00085

Metal complexing     Metallothio     Metallothionein   PF00131

                     Cu-oxidase      Multicopper       PF00394

                     Transferrin     Transferrin       PF00405

                     Ferritin        Ferritin          PF00210

                     Heme_oxygenase  Heme_oxygenase    PF01126

                     Phytochelatin   Phytochelatin     PF05023

Glutathione cycling  GCS             Glutamate         PF03074
                                     cysteine ligase

                     GSH_synthase    Eukaryotic        PF03199

                     Glutaredoxin    Glutathione       PF00462

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).

Heat-shock proteins

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

BIR             Inhibitor of Apoptosis     PF00653

BTB             BTB/POZ doamin             PF00651

bZIP_1          bZIP transcription factor  PF00170

bZIP_2          Basic region leucine       PF07716

C_tripleX       Cysteine rich repeat       PF02363

CARD            Caspase recruitment        PF00619

cNMP_binding    Cyclic nucleotide-binding  PF00027

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

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
Glycolytic      Fructose-bisphosphate      PF00274
                aldolase class-I

HMG_box         HMG (high mibility group)  PF00505

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

NACHT           NACHT domain               PF05729

NMT             Myristoyl-CoA:protein      PF01233

NMT_C           Myristoyl-CoA: protein     PF02799

Paml16          Pam16                      PF03656

PAZ             PAZ domain                 PF02170

Pentapeptide    Pentapeptide repeats (8    PF00805

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

Ribonuclease_3  RNase3 domain              PF00636

SAM_1           SAM domain (Sterile alpha  PF00536

SAM_2           SAM domain (Sterile alpha  PF07647

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

WAP             WAP-type (Whey Acidic      PF00095
                Protein) 'four-disulfide

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: (e.g., 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.

Wound healing

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; 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

Extracellular   Collagen         Collagen triple helix      PF01391

                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

                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

                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:
(e.g., 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

  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

  JNKI-B1              NM_139046    XM_001637538    3e-133

SLRPs (small

  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

  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


  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

  Biglycan             AY166584      5e-25   Vasorin

  Chondroadherin       AY166584      5e-25   Vasorin

  Decorin              AC104667.5    6e-44   BAC clone

  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

  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

  Syndecan 2           AF163151      1e-22   Dentin

  Syndecan 3           HSU78181      3e-25   Human sodium channel

  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

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

  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

  Asporin                 CAI16697   XM_967172     2e-28

  Dermatan Sulf.          AAC50945   XM_001650288  9e-14

  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

  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

  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

  Biglycan             1e-44   SLITI

  Chondroadherin       2e-39   Similar to platelet

  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

  Fibronectin 1        3e-145  Prot. tyrosine phosphatase
  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; 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.


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).


(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:

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
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Date:Jun 1, 2008
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