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Dev Comp Immunol. 2007; 31(8): 763–782.
PMCID: PMC1871615

Biomphalaria glabrata transcriptome: Identification of cell-signalling, transcriptional control and immune-related genes from open reading frame expressed sequence tags (ORESTES)


Biomphalaria glabrata is the major intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. Much remains to be discovered concerning specific molecules mediating the defence events in these intermediate hosts, triggered by invading schistosomes. An expressed sequence tag (EST) gene discovery strategy known as ORESTES has been employed to identify transcripts that might be involved in snail–schistosome interactions in order to examine gene expression patterns in infected B. glabrata. Over 3930 ESTs were sequenced from cDNA libraries made from both schistosome-exposed and unexposed snails using different tissue types, producing a database of 1843 non-redundant clones. The non-redundant set has been assessed for gene ontology and KEGG pathway assignments. This approach has revealed a number of signalling, antioxidant and immune-related gene homologues that, based on current understanding of molluscan and other comparative systems, might play an important role in the molluscan defence response towards infection.

Keywords: Expressed sequence tag, EST, ORESTES, Molluscan defence, Biomphalaria glabrata, Schistosoma mansoni

1. Introduction

The freshwater snail Biomphalaria glabrata is an intermediate host for Schistosoma mansoni, the digenean parasite that causes human intestinal schistosomiasis. This host–parasite relationship has become a model system for examination of snail–schistosome interactions, and as such, recent molecular work has focused on B. glabrata. Now with the continued significance of genome research, the B. glabrata genome initiative ( aims to increase the available genetic data for this snail species, with the final goal of a complete genome sequence. Such sequence data will complement that available for the schistosome parasite from the schistosome genome/transcriptome sequencing initiatives [1–5] and for the definitive host from the human genome project [6]. In addition to genome sequencing, the generation of expressed sequence tags (ESTs), short stretches of sequence obtained from cDNA libraries [7], is valuable in a number of ways: in identifying snail homologues of genes previously described in other species; for identifying transcribed regions of the genome, useful for genome annotation and analysis; for the detection of splice variants and alternative polyadenylation gene isoforms; in the discovery of single nucleotide polymorphisms (SNPs) and finally for expression studies, such as those involving microarrays. The EST project described here was initiated with the ultimate aim of manufacturing a cDNA microarray for B. glabrata, which required a large number of sequenced cDNA clones to be available.

EST projects in other molluscs, such as oysters, have revealed a wealth of useful sequence data including signalling, antioxidant and immune-related gene homologues [8,9], demonstrating that molluscs express many of the same genes, and may therefore carry out the same processes, which have previously been described in vertebrates. A recent EST project from Lymnaea stagnalis [10] identified a number of genes that had not previously been identified in the Lophotrochozoa. Therefore initiating an EST sequencing project in B. glabrata has the potential to identify other novel molluscan genes including those that might be associated with the snail's response to infection. At the start of this project (January 2003) only 1427 B. glabrata EST sequences were available on GenBank from earlier studies [11–15]. During the course of this project several other laboratories have also developed gene discovery programmes for B. glabrata [16,17] (see also unpublished EST programmes).

Previous EST projects in B. glabrata [11,15] used traditional library construction and sequencing approaches to obtain sequence data. A complimentary EST approach called open reading frame ESTs (ORESTES) [18] has been used successfully to obtain large numbers of sequences for both human [18–20] and schistosome [4,5] transcriptome projects. The ORESTES approach preferentially targets the middle section of mRNAs [18], making it more likely coding regions will be sequenced, than in other EST methodologies where sequencing commences at the end of the cDNA, often only obtaining untranslated sequence. This alternative method has two advantages for snail ESTs; firstly, it is more likely that gene similarity to other organisms can be ascertained if coding regions are sequenced, and secondly, the data generated are likely to be complementary to, rather than redundant with, sequence data from traditional approaches. The ORESTES approach also allows the construction of a number of mini-libraries using small quantities of RNA [21], making it suitable for investigating gene expression in small amounts of tissue such as those present in B. glabrata. Producing a large number of smaller libraries also facilitates a more extensive analysis of gene expression; thus in the EST project described here, different snail strains (both resistant and susceptible to S. mansoni infection) were used and different tissue types from both parasite-exposed and unexposed material were examined. Based on gene ontology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway assignments a number of antioxidant, signalling and immune-related gene homologues have been identified and are presented here; the potential involvement of these genes in molluscan defence is considered, particularly within the framework of comparative immunobiology.

2. Materials and methods

2.1. Snail material

B. glabrata strains used were: resistant BS90 [22] (NHM3017) or susceptible NHM1742 or BB02 (NHM3032), the strain currently being used for the genome sequencing project (see Snails were held overnight in autoclaved snail water with 100 μg/ml ampicillin prior to killing by decapitation. The exuded haemolymph was collected, pooled and the haemocytes isolated by centrifugation at 4 °C, 10,000g for 20 min. Each snail was preserved in 800 μl RNAlater (Ambion Inc., Texas, USA) and stored at −20 °C until dissection. Haemopoietic organ, ovotestis, head/foot and brain tissue was dissected. For the exposed material, 60 snails were individually exposed to 10 S. mansoni miracidia (Belo Horizonte strain) each and 2, 4, 6, 8 and 24 h after infection, 12 of the snails were swiftly killed as above. Tissue was pooled from each time period; the extended sampling was designed to include all transcripts expressed over the first 24 h of infection.

2.2. RNA extraction

Total RNA was extracted from each dissected tissue using SV RNA extraction kit (Promega UK Ltd, Southampton, UK) according to the manufacturer's protocol. This kit includes DNAse treatment to eliminate genomic DNA contamination. Pigment from the head/foot tissue was found to block the spin columns supplied with this extraction kit, so RNA was extracted from this tissue using Trizol (Invitrogen Ltd, Paisley, UK). Briefly, 30 mg tissue was ground in 1 ml Trizol and centrifuged at 12,000g for 10 min at 4 °C. The supernatant was incubated at room temperature for 5 min then 0.2 ml chloroform added, mixed vigorously and left at room temperature for 3 min. The samples were spun at 12,000g, 4 °C for 15 min and the RNA precipitated from the supernatant using 0.5 ml propan-2-ol and centrifugation at 12,000g for 10 min at 4 °C. The pellet was washed using 75% ethanol and dissolved in 50–100 μl water. RNA extracted using Trizol was DNAse treated (Promega), according to the manufacturer's instructions prior to mRNA extraction. mRNA was extracted from the total RNA from both extraction methods using the Micro-fastTrack 2.0 mRNA extraction kit (Invitrogen) according to the manufacturer's instructions. The mRNA was eluted in 200 μl elution buffer and precipitated overnight at −70 °C using 600 μl ethanol. The mRNA was dissolved in 10 μl water and tested using specific B. glabrata actin primers [12] to check there was no DNA contamination.

2.3. cDNA synthesis and amplification

For each library, a 27 μl mastermix containing 800 U Reverse Transcriptase (MMLV-RT) (Promega), 4 μl RNAsin (Promega), 4 μl dNTPs at 2 mM, 8 μl 5× buffer (Promega) and 7 μl mRNA (70–240 ng) was prepared and 2 μl aliquoted into 12 tubes prepared with 12 different arbitrary primers (1.5 μl of 15 mM) (for primer sequences see supplementary material). The tubes were incubated at 42 °C for 1 h then heated to 70 °C for 10 min.

Amplification was carried out using Ready-to-go beads (Amersham Biosience, Amersham, UK). The 3.5 μl cDNA reactions (including primers) and 25 μl water were each added to a tube containing a single bead and amplified using the following cycling conditions: 75 °C for 5 min followed by 15 cycles at 94 °C, 52–45 °C for 1 min (touchdown PCR, dropping 0.5 °C each cycle) and 1 min 72 °C, then 26 cycles of 94 °C for 30 s, 48 °C for 1 min and 72 °C for 1 min, then 7 min at 72 °C. A negative control (no DNA) was carried out simultaneously for each primer (dissolving 2 ready-to-go beads in 50 μl water and aliquoting 3 μl into a tube containing 0.3 μl primer (at 15 mM)). Three μl of each synthesis reaction was examined by gel electrophoresis alongside the control amplification and reactions chosen for inclusion in the mini-library only if the control amplification showed no contamination and a smear without single prominent bands in the reaction profile. This ensured that a mix of products would be obtained from each library.

2.4. Cloning and sequencing

For each library, the selected amplified cDNA samples were pooled and cloned using pGEM-T easy cloning kit (Promega) according to the manufacturer's instructions. One hundred and ninety two clones (2×96), selected at random from the cloning plates were picked into 0.5 ml LB and grown up overnight. Ten μl PCRs with M13 forward and reverse primers were carried out to check insert size and the presence of a single insert and, from these, 96 colonies were chosen for 100 μl PCRs. PCRs contained 1×NH4 reaction buffer (Bioline, London, UK), 2.5 mM MgCl2, 0.2 mM dNTP, 0.2 μM each M13 Forward and Reverse primers and 0.025 U/μl PCR Taq polymerase (Bioline, London, UK). Cycling conditions were: 94 °C for 2 min, then 35 cycles of 94 °C for 30 s, 58 °C for 30 s and 72 °C for 1 min 30 s, then 10 min at 72 °C. Glycerol stocks for the selected colonies were stored at −80 °C.

PCR products were purified using Multiscreen PCR filter plates (Millipore, Billerica, USA) then cycle-sequenced directly using BigDye kit (Applied Biosystems, Foster City, USA) and T7 primer and run on ABI 377 or capillary sequencers. Vector, primer and poor quality sequences were removed using Sequencher 3.1.1 (GeneCodes Corp., Ann Arbor, USA).

2.5. Bioinformatics

Cluster analysis was performed in SeqTools ( using BlastN score values (cut-off value 0.5) and used to calculate percentage redundancy. For each library BlastN and BlastX [23] searches were run and any ribosomal sequences and sequences shorter then 80 bp removed. Duplicate sequences were also removed, although overlapping sequences were retained. Since each library represented different tissues, strains or infected/uninfected material, duplicate sequences between libraries were retained.

2.6. Clone nomenclature

Each clone had a unique ZB number assigned during sequencing. In addition to this the clones were also assigned a code based on strain (see Section 2.1), tissue type (B—brain, HO—haemopoietic organ, HAEM—haemocytes, HF—head/foot and OT—ovotestis), infection status (EX—parasite exposed, UN—unexposed) and plate number and position. The sequences were submitted to GenBank (accession numbers CK149151-CK149590, CK656591-CK656938, CO870183-CO870449, CV548035-CV548805, EG030731-EG030747).

2.7. Gene function

Gene ontology functions were assigned using GOblet ( KEGG pathway analysis was carried out using the KEGG automatic annotation server (KAAS) for ortholog assignment and pathway mapping (

3. Results

3.1. ORESTES libraries

A total of 41 ORESTES libraries were made from five tissue types (head–foot, brain, ovotestis, haemocytes and haemopoietic organ) from the three B. glabrata strains, one resistant (NHM3017) and two susceptible (NHM1742 and BB02 (NHM3032)), using material that had either remained unexposed or had been exposed to S. mansoni (Table 1). Some of the libraries were made from the same snail strain and tissue type but were separately made with different primers, using new experimental material, so have been treated independently. Libraries were prepared from each of the two susceptible strains for each tissue, with the exception of exposed ovotestis from NHM1742 where two libraries were made. Two or three libraries were prepared per tissue and exposure type for the resistant strain, with the exception of brain tissue where material was limiting. A single plate of 96 clones was sequenced for each library and in total, 3936 clones were sequenced from 41 libraries.

Table 1
Biomphalaria glabrata ORESTES libraries. The number of non-redundant (NR) sequences was determined after cluster and Blast analyses to remove duplicate and ribosomal sequences from within each library

3.2. Analysis of total ESTs and selection of non-redundant ESTs

A total of 3809 sequences were obtained (127 reactions did not work or the sequenced clones contained no insert or had mixed sequences so these were not analysed further) and were compared to the non-redundant section of GenBank. The Blast results (Table 2) showed that 28.5% (n=1087) of the gene fragments identified proteins on the database, including 35 previously characterized B. glabrata proteins and 127 proteins with no assigned function. Including some other non-coding gene fragment matches, less than 2% (n=76) of the sequences matched characterized B. glabrata genes or proteins in the non-redundant section of GenBank. Nearly 35% (n=1317) could not be assigned any function, either having no Blast matches, or having homology to a nucleotide or protein sequence on GenBank with no function described. Unfortunately, 39% of the sequences (n=1482) matched B. glabrata ribosomal sequences. Other workers [16] have also found a large ribosomal content in polyA selected RNA from B. glabrata, and concluded that the high A content in B. glabrata ribosomal sequences meant that polyA selection did not efficiently remove it. In the present study it was found that some 18mer primers chosen for ORESTES library construction tended to target ribosomal regions, so they were not used again. However, it was impossible to predict in advance which primers would be problematic. The ‘other’ sequences (n=8) had database matches but do not necessarily code for proteins, for example retrotransposon sequences. For each library, duplicate and ribosomal sequences were removed and the % redundancy per plate ranged from 9.6% to 71.9% (Table 1).

Table 2
Blast results summary. Breakdown of the types of sequences obtained from the B. glabrata ORESTES libraries identified with Blast searches of GenBank

After removal of duplicate and ribosomal sequences, a total of 1843 non-redundant sequences were submitted to GenBank, ranging in size from 80 bp (shorter sequences were discarded) to 1068 bp, with a mean length of 518 bp. Cluster analysis between libraries (since the data were previously sifted to remove duplicate clones from each library) revealed 456 sequences in 163 clusters and 1387 singletons (Fig. 1). This resulted in 1550 unique sequences, with 15.9% redundancy. The most common sequence (in 12 of the libraries) was tropomyosin 2 (SwissProt accession number P43689), previously sequenced from B. glabrata [24], while two other common sequences (in 11 libraries) were a hypothetical integral membrane transporter protein (accession number XP_135742) and a sequence with no Blast match. Examining the Blast results from the 1843 non-redundant sequences (Table 2), 42% showed significant BlastX similarity to known proteins (including mitochondrial, ribosomal and Biomphalaria proteins) in the non-redundant databases, while 52.9% were of unknown function, 3.4% Biomphalaria sequences, 0.4% ‘other’ sequences (e.g. retrotransposons) and the remainder were ribosomal sequences (2.4%).

Fig. 1
Histogram showing EST clusters in the non-redundant EST set, after removal of duplicates within libraries.

3.3. Cluster analysis with other B. glabrata ESTs

Sequences from the 1843 ORESTES clones were used for BlastN searches of the other 10,791 B. glabrata EST sequences available on dbEST (September 2006) including many added since the sequences presented here. Four hundred and thirty-nine of the ESTs identified B. glabrata sequences with a match greater than 1e-20. Cluster analysis of these revealed 293 clusters or unique ESTs matched sequences on dbEST. Closer examination of a subset of 1613 sequences from a B. glabrata haemocyte cDNA library [17], created in the conventional way (not from ORESTES mini-libraries) showed only 31 ORESTES sequences clustered with transcripts sequenced from that library.

3.4. Functional classification based on gene ontology assignments

The functions of the non-redundant 1843 sequences were assessed using gene ontology, based on Blast matches with genes whose functions have been previously assessed (Fig. 2). Of the 1843 ESTs, 587 were assigned a function, in three categories, biological process, molecular function and cellular component. In the biological process categories, the largest proportion (44%) was assigned to physiological processes (Fig. 2a). The most prevalent molecular functions (Fig. 2b) were binding (36%) and catalytic activity (23%). Other molecular function assignments were signal transducers (8%) and transcription regulators (4%), and five antioxidant genes (0.4%) were also identified. Over 80% of the cellular component assignments were for genes coding for cellular proteins including 50% intracellular and 25% membrane proteins (Fig. 2c). Gene ontologies were examined to identify genes that were homologous to antioxidant molecules, signalling molecules, transcriptional regulators, immune response genes and stress response genes (Table 3), since many of these might be significant in the snail's response to parasite infection. A total of 117 homologues of genes that code for proteins involved in cell signalling or transcriptional regulation were identified; these genes were categorised as follows: signal transducers (54), cell–cell signalling (19), transcription regulator activity (28), signal transducers and transcription factor regulators (10) (Table 3). Although not the original purpose of generating these ESTs, gene ontologies were also assessed by tissue type, strain, parasite susceptibility and whether parasite exposed or unexposed, for both biological process and molecular function (see supplementary material).

Fig. 2
Gene ontologies. Percentage representation of gene ontology (GO) mappings for B. glabrata ESTs. (a) Biological processes, (b) molecular function and (c) cellular component. Note that individual GO categories can have multiple mappings and that the charts ...
Table 3
Transcripts selected by gene ontology. Individual B. glabrata ESTs that identified antioxidant proteins, signal transducers, transcription regulators and immune or stress response proteins

3.5. Functional classification based on KEGG pathway analysis

As an alternative method of categorising ESTs by biochemical function, clones were assigned to biochemical pathways using the KEGG website. Four hundred and thirteen ESTs were assigned to metabolic, genetic information processing, environmental information processing and cellular pathways (Tables 4 and 5). Thirty-one enzymes (38 clones) from 7 out of a possible 11 signal transduction pathways were identified as well as 25 enzymes (31 clones) from 7 out of a possible 9 immune-related pathways.

4. Discussion

Use of the ORESTES approach generated 1843 ESTs from different tissues and strains of B. glabrata. Only 3.4% of these had been previously characterized in B. glabrata and cluster analysis with other B. glabrata ESTs identified less than 300 clusters of overlapping sequences. Over half of the sequences showed no matches to previously sequenced genes in the non-redundant section of GenBank. Functional analysis of those with sequence similarity to previously characterized genes, using gene ontologies and KEGG assignments identified a number of antioxidant, signalling and transcriptional regulatory genes, molecules that may potentially be involved in snail/parasite interactions, as well as several immune and stress response proteins.

4.1. Antioxidant proteins

Four different genes were identified that were similar to molecules that demonstrate antioxidant functions in other organisms. Peroxinectin (CV548486) is a cell adhesion protein with peroxidase activity, which has been identified in other invertebrates including the crayfish Pacifastacus leniusculus [25], the black tiger shrimp Penaeus monodon [26], Drosophila melanogaster [27] and the white shrimp Litopenaeus vannamei [28], and is a functional equivalent of the vertebrate myeloperoxidase [25,29]. Peroxidasin (CV548777) is a similar protein with peroxidase activity associated with developmental processes in both Drosophila [30] and Xenopus tropicalis [31]. Dual oxidase 1 (Duox1) (CK149203), possesses a peroxidase domain and is thus categorized with antioxidant function; interestingly though, these transmembrane proteins also have a superoxide-generating subunit homologous to glycoprotein p91phox [32], a host defence molecule that generates reactive oxygen species (ROS) [33,34]. Another Duox1 sequence has been identified in B. glabrata [17] but our sequence (CK149203) seems to be a paralog of this gene as it shows no similarity at the nucleotide level with the other sequences (CK989379, CK990069) and did not identify these sequences in BlastN searches, despite all matching the same section of translated protein in tBlastX searches.

4.2. Signalling molecules and transcriptional regulators

Based on our knowledge of other, well-characterised, biological systems, some of the identified signalling molecules and transcriptional regulators play a part in pathways that are likely to be involved in the innate immune response of snails. In a few cases (as described below), functional studies have shown that such signalling pathways contribute to the regulation of molluscan defence reactions.

One clone (EG030744) matched the transcription factor nuclear factor-κB1 (NF-κB1), a p105 NF-κB subunit that is proteolytically processed to yield NF-κB p50 [35]. The NF-κB/Rel transcription factors comprise a family of evolutionarily conserved and structurally related proteins identified in a variety of vertebrates and invertebrates including the beetle Allomyrina dichotoma [36], the sea squirt Ciona intestinalis [37] and the bivalve mollusc Crassostrea gigas [38]. Such transcription factors are central to the NF-κB pathway, a key intracellular pathway that co-ordinates the induction of defence genes in both mammals and Drosophila, and plays a pivotal role in vertebrate and invertebrate innate immunity [39,40]. IκB kinase (IKK) complex associated protein (IKAP) [41] was also identified (EG030742). This protein contains potential IKK association sites and was thus originally thought to play a role in NF-κB signalling by scaffolding the IKK signalsome [41]. Although this now seems unlikely (as discussed in [42]) IKAP seems to associate with stress-activated protein kinase/c-jun NH2-terminal kinase (SAPK/JNK) and regulate its activity in mammals [42]. Activation of SAPK/JNK occurs via the transmission of extracellular stress signals, and aside from the role that this protein plays in processes such as development, apoptosis, and proliferation, it can regulate immune responses in Drosophila [43,44]. Interestingly, SAPK/JNK is activated by recombinant human TNF-α in defence cells (haemocytes) of the bivalve mollusc Mytilus galloprovincialis [45] and, in the present study, we identified a homologue (clones CV548175, CV548723, CV548166, CV548685) of Drosophila JNK interacting protein 1 [46], a scaffold protein that aggregates specific components to form a functional SAPK/JNK signalling module in mammals [47].

Homologues of invertebrate integrin α3 [48] (CK149506), focal adhesion kinase (FAK) [49] (CK656717) and mammalian protein tyrosine kinase Src [50] (CK149232) were also identified. Integrins are a family of heterodimeric, transmembrane adhesion receptors whose ligand specificities are determined by the specific α and β subunits; integrins are crucial to cell adhesion and organisation of the actin cytoskeleton and they serve as important receptors in immune cell responses, cell migration and tissue integrity. Expressed in all metazoans, integrins have been characterized in several invertebrates [51], with β1 integrin subunits reported from haemocytes of the molluscs C. gigas [52] and B. glabrata [53]. Integrins nucleate the formation of focal adhesions and focal complexes and these events rely on the co-ordinated actions of signalling proteins that include FAK and Src. In mammals, integrin clustering is known to lead to autophosphorylation of FAK at Tyr397, FAK then associates with the SH2 domain of Src, which in turn phosphorylates FAK at Tyr925 [54]. In some cell types this can result in downstream signalling to the extracellular signal-regulated kinase (ERK) pathway [55], a signalling module that has been shown to regulate phagocytosis and nitric oxide production in haemocytes from L. stagnalis [56,57]. A recent study has demonstrated that integrin engagement results in increased phosphorylation of a FAK-like protein in L. stagnalis haemocytes and that integrin blockade inhibits phagocytosis and spreading by these cells [58]. Since integrins are also known to regulate cell spreading by haemocytes of B. glabrata [59] it appears that integrin binding is crucial to the defence responses of snails, particularly those involving actin remodelling. Thus, signalling through the identified FAK/Src proteins is likely to regulate such defence reactions, as has been shown in insects [60].

Protein kinase C (PKC) is known to play a role in regulating innate defences in mammals; this has also been documented for snails in which PKC seems to regulate nitric oxide (NO) and hydrogen peroxide (H2O2) production, phagocytosis and cell spreading by haemocytes [56,57,61,62]. In this context, it is interesting that we have now identified homologues of two proteins, activated protein kinase C receptor (RACK) (CK149425, CK149451) from Xenopus [63] and 14-3-3 γ (CO870195) from humans [64], which are known to interact with PKC. RACK has previously been characterized in B. glabrata by other workers [65], however, the nucleotide sequence fragment we identified differs significantly from that previously published, with only three short stretches being identified in a BlastN search with an E value of 3e-5. BlastX searches did identify (amongst other RACK sequences) the amino acid sequence of the previously sequenced B. glabrata RACK, with 89% similarity. Our nucleotide sequence also identified 12 other B. glabrata ESTs with close homology, so it seems likely that we have identified a second gene for RACK. 14-3-3 γ appears to be phosphorylated by PKC and might facilitate signalling to the ERK pathway via Raf [64]. Biomphalaria glabrata RACK might serve to direct the translocation of PKC isoforms to specific cellular compartments as it does in higher organisms [66].

We also identified a homologue of the B (regulatory) subunit of serine threonine protein phosphatase 2A (PP2A) [67] (CV548346), a heterotrimeric holoenzyme that either positively or negatively regulates the activities of wide variety of cellular signal transduction pathways including those involving IKK and ERK discussed above (for reviews see [68,69]). Also of interest are genes that were found to be homologous to those coding for proteins involved in protein kinase A and cAMP signalling, namely: adenylyl cyclase [70] (CV548064), the enzyme that generates the second messenger cAMP; cAMP-specific 3′,5′-cyclic phosphodiesterase (CV548523), an enzyme involved in cyclic nucleotide metabolism [71]; and the type N4 regulatory subunit of PKA [72] (CV548191). These proteins likely play a role in mollusc defence since the catecholamine noradrenaline modulates the phagocytic activity of C. gigas haemocytes via a β-adrenergic receptor-cAMP signalling pathway [73]. Finally, genes were found which matched to those of the transmembrane glycoprotein macrophage mannose receptor [74] (CO870241, CV548367), the Ras-related GTPase protein Rab 21 [75] (CK149518, CK149287) and hemolectin [76] (CV548237, CV548539, CV548566). The macrophage mannose receptor is a phagocytic receptor that targets pathogens such as bacteria and yeast which express mannose-rich glycoproteins [74] and Rab 21 has been recently found to interact with two LIM domain proteins in the slime mould Dictyostelium to collectively regulate phagocytosis [77]. The identified hemolectin showed homology to Drosophila hemolectin which is a major clot constituent in these flies [76].

4.3. Immune and stress response genes

Examination of the gene ontologies revealed 8 immune response genes and 10 response-to-stress genes. Of particular interest are α 2-macroglobulin (α2 M) and Rho-guanine nucleotide-exchange factor 4 (Rho-GEF 4). The identified α2 M (CV548690) is similar to that from the horseshoe crab Limulus polyphemus [78], a proteinase inhibitor similar to mammalian α2 M with broad reactivity towards proteinases; a similar inhibitor with activity towards serine, cysteine and metalloproteinase has been purified from B. glabrata plasma [79]. Such inhibitors could be important to defence, since they may be expressed during the humoral immune response in order to inactivate proteinases produced by invading pathogens [80]. The Rho-GEF 4 homologue (CO870295) was similar to that sequenced in humans [81]. This GEF is operational towards the small GTPases Rho A and Rac 1 and is thought to play a role in cell migration and cell–cell adhesion [82]. Given the universal nature of these cellular processes it is likely that Rho GEF 4 has a similar role in snails and thus may be important in the snail defence response towards pathogens.

5. Conclusions

The genes described above represent a set of those identified that might play important roles in molluscan defence. To eliminate pathogens such as parasites, the molluscan immune system must be able to mount a co-ordinated response to the invading organism, with processes such as cell adhesion and the production of reactive oxygen and nitrogen intermediates being crucial to the outcome of infection. Despite a parasite-mediated interference theory being proposed 25 years ago [83], the precise mechanism(s) by which schistosomes evade the defence response of their snail intermediate hosts remain largely unknown. A recent hypothesis paper has explored the idea that parasites might blunt the defence response of susceptible snails by interfering with key signal transduction pathways in their defence cells [84]; such a strategy could serve to alter gene expression and functional defence responses.

This EST gene discovery project has provided a significant number of genes for the first version of a custom B. glabrata cDNA microarray. A detailed investigation of the transcriptome in response to trematode infection in this snail intermediate host, in order to identify and understand the role of specific genes involved in the snail internal defence system can therefore now be carried out. Thus, we anticipate that through application of the microarray, we will move closer to gaining a comprehensive understanding of snail–schistosome interactions and the complex nature of the biological interplay that exists between snail and schistosome parasite.


This work was carried out with funding from the Wellcome Trust (068589/Z/02/Z). We would like to thank Jayne King and Mike Anderson, NHM, for snail and parasite culture and Julia Llewellyn-Hughes and Claire Griffin, NHM, for sequencing assistance. Emmanuel Dias-Neto thanks Associacao Beneficente Alzira Denise Hertzog Silva (ABADHS) for their support to the Laboratory of Neurosciences (LIM27). Cathy Jones was in receipt of a Royal Society of Edinburgh Sabbatical Fellowship whilst co-authoring this article.


Appendix ASupplementary data associated with this article can be found in the online version at doi:10.1016/j.dci.2006.11.004.

Appendix A. Supplementary Materials

Online Supplementary Materials

Online Supplementary Materials


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