Project PXD000756

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Summary

Title

Comparative analysis of the secretome from a model filarial nematode (Litomosoides sigmodontis) reveals maximal diversity in gravid female parasites

Description

Filarial nematodes (superfamily Filarioidea) are responsible for an annual global health burden of approximately 6.3 million disability-adjusted life-years, which represents the greatest single component of morbidity attributable to helminths affecting humans. No vaccine exists for the major filarial diseases, lymphatic filariasis and onchocerciasis; in part because research on protective immunity against filariae has been constrained because the human-parasitic species cannot complete their lifecycles in laboratory mice. However, the rodent filaria Litomosoides sigmodontis has become a popular experimental model, as BALB/c mice are fully permissive for its development and reproduction. Here, we provide a comprehensive analysis of excretory-secretory products from L. sigmodontis across five lifecycle stages. Applying intensity-based quantification, we determined the abundance of 302 unique excretory-secretory proteins, of which 64.6% were present in quantifiable amounts only from gravid adult female nematodes. This lifecycle stage, together with immature first-stage larvae (microfilariae), released four proteins that have not previously been evaluated as vaccine candidates: a predicted 28.5 kDa filaria-specific protein, a zonadhesin and SCO-spondin-like protein, a vitellogenin, and a protein containing six metridin-like ShK toxin domains. Female nematodes also released two proteins derived from the obligate Wolbachia symbiont. Notably, excretory-secretory products from all parasite stages contained several uncharacterised members of the transthyretin-like protein family. Furthermore, biotin labelling revealed that redox proteins and enzymes involved in purinergic signalling were enriched on the adult nematode cuticle. Comparison of the L. sigmodontis adult secretome with that of the human–infective filarial nematode Brugia malayi (reported previously in three independent published studies) identified differences that suggest a considerable underlying diversity of potential immunomodulators. The molecules identified in L. sigmodontis excretory-secretory products show promise not only for vaccination against filarial infections, but for the amelioration of allergy and autoimmune diseases.

Sample Processing Protocol

Sample preparation for proteomics StrataClean Resin containing bound ESP was washed twice with 25 mM ammonium bicarbonate before suspension in 0.1% RapiGest SF, 25 mM ammonium bicarbonate. The resin samples were heated at 80°C for 10 min, reduced with 3 mM DTT at 60°C for 10 min, cooled, then alkylated with 9 mM iodoacetamide (Sigma) for 30 min (room temperature) protected from light; all steps were performed with intermittent vortex-mixing. The samples were then digested using 0.2 µg proteomic-grade trypsin at 37°C overnight with rotation, centrifuged at 13,000 g for 5 min, and the supernatant removed. The resin was washed twice with 0.1% RapiGest SF, 25 mM ammonium bicarbonate and the supernatants pooled. To remove RapiGest SF, the samples were precipitated using 1% TFA at 37°C for 2 h and centrifuged at 12,000 g for 1 hr (4°C). The peptide supernatant was concentrated using C18 reverse-phase spin filters according to the manufacturer’s instructions. The WBE samples were reduced and alkylated as above, digested with trypsin at a protein:trypsin ratio of 50:1 at 37°C overnight, and precipitated to remove RapiGest SF as for the ESP preparations. NanoLC MS ESI MS/MS analysis Peptide solutions (2 µl) were analysed by on-line nanoflow LC using the nanoACQUITY-nLC system (Waters) coupled to an LTQ-Orbitrap Velos (Thermo Scientific) MS equipped with the manufacturer’s nanospray ion source. The analytical column (nanoACQUITY UPLC BEH130 C18 1.7 µm particle size, 15 cm x 75 µm capillary column) was maintained at 35°C and a flow-rate of 300 nl/min. The gradient consisted of 3 - 40% ACN, 0.1% formic acid for 45 or 90 min, then a ramp of 40 - 85% ACN, 0.1% formic acid for 3 min in positive ionisation mode. Full scan MS spectra (m/z range 300 - 2000) were acquired by the Orbitrap at a resolution of 30,000, and analysis was performed in data-dependent mode. The top 20 most intense ions from MS1 scan (full MS) were selected for tandem MS by CID and all product spectra were acquired in the LTQ ion trap. Ion trap and Orbitrap maximal injection times were set to 50 ms and 500 ms, respectively.

Data Processing Protocol

Thermo RAW files were imported into Progenesis LC–MS (version 4.1, Nonlinear Dynamics). Where necessary, technical replicate (repeat injection) runs were time-aligned using default settings and an auto-selected run as a reference. Peaks were picked by the software using default settings and filtered to include only peaks with a charge state between +2 and +6. Peptide intensities of technical replicates were normalised against the reference run by Progenesis LC-MS. Spectral data were transformed to MGF files with Progenesis LC–MS and exported for peptide identification using the Mascot (version 2.3.02, Matrix Science) search engine. Tandem MS data were searched against translated ORFs from the L. sigmodontis genome and its Wolbachia symbiont, wLs (obtained from http://nematodes.org/genomes/litomosoides_sigmodontis, release nLs 2.1.2, 10,246 protein sequences; and release wLs 2.0, 1,042 protein sequences), together with predicted proteomes for the rodent host (Mus musculus, Uniprot release 2012_08, 16,626 protein sequences; and Meriones unguiculatus, Uniprot release 2012_08, 223 protein sequences) and a general contaminant database (GPMDB, cRAP version 2012.01.01, 115 protein sequences). Search parameters included a precursor mass tolerance of 10 ppm, a fragment mass tolerance of 0.5 Da, and allowance for two missed tryptic cleavage. Carbamidomethylation (cysteine) was set as a fixed modification and oxidation (methionine) set as a variable modification. Mascot search results were further validated using the machine learning algorithm Percolator embedded within Mascot. The Mascot decoy database function was utilised and the false discovery rate was <1%, while individual percolator ion scores >13 indicated identity or extensive homology (p <0.05). Mascot search results were imported into Progenesis LC–MS as XML files and analysed according to the following criteria: at least two unique peptides were required for reporting protein identifications, and an individual protein had to be present in ≥2 biological replicates to be included in the ESP dataset. Protein abundance was calculated by the iBAQ method; that is, the sum of all peak intensities (from Progenesis output) divided by the number of theoretically observable tryptic peptides. Protein abundance was normalised by dividing the protein iBAQ value by the summed iBAQ values for the corresponding sample, and the reported abundance is the mean of the biological replicates

Contact

Stuart Armstrong, Infection Biology
Benjamin Makepeace, Department of Infection Biology Institute of Infection & Global Health University of Liverpool Liverpool Science Park IC2 146 Brownlow Hill Liverpool L3 5RF UK ( lab head )

Submission Date

13/02/2014

Publication Date

22/07/2014

Publication

    Armstrong SD, Babayan SA, Lhermitte-Vallarino N, Gray N, Xia D, Martin C, Kumar S, Taylor DW, Blaxter ML, Wastling JM, Makepeace BL. Comparative Analysis of the Secretome from a Model Filarial Nematode (Litomosoides sigmodontis) reveals Maximal Diversity in Gravid Female Parasites. Mol Cell Proteomics. 2014 Jun 23. pii: mcp.M114.038539 PubMed: 24958169

Assay

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# Accession Title Proteins Peptides Unique Peptides Spectra Identified Spectra View in Reactome
1 34835 surface proteomics 89 632 284 3878 383
2 34834 surface proteomics 75 318 166 4667 189
3 34779 surface proteomics 140 643 311 2892 396
4 34777 surface proteomics 88 447 207 3137 245
5 34778 surface proteomics 147 548 318 1637 393
6 34775 surface proteomics 86 435 207 2116 257
7 34776 surface proteomics 93 342 205 1739 253
8 34831 surface proteomics 149 602 352 2353 415
9 34773 surface proteomics 59 199 118 1151 131
10 34830 surface proteomics 78 282 183 1428 210