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Tracking the sources of blood meals of parasitic arthropods using shotgun proteomics and unidentified tandem mass spectral libraries


Identifying the species on which hematophagous arthropods feed is crucial for studying the factors that affect pathogen distributions and that can aid public health. Here we describe a protocol to identify the species a parasitic arthropod has previously fed upon by identifying the source of the remnants of a previous blood meal via shotgun proteomics and spectral matching. The protocol is a nontargeted approach that uses the entire detected blood proteome for source identification; it does not require a priori knowledge of genome or protein sequences. Instead, reference spectral libraries are compiled from the blood of multiple host species by using SpectraST, which takes 4 d; the identification of the species from which a previous blood meal of a hematophagous arthropod was taken is achieved with spectral matching against the reference spectral libraries, which takes approximately another 4 d. This method is robust against random degradation of the blood meal and can identify unknown blood remnants months after the feeding event.

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Figure 1: Data analysis workflow as described in Steps 15–18.
Figure 2: Screenshots of running msconvert (ProteoWizard) to convert vendor-specific formats to open XML data formats.
Figure 3: A snapshot illustrating the anticipated fingerprinting summary file.

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  1. Taylor, L.H., Latham, S.M. & Woolhouse, M.E. Risk factors for human disease emergence. Philos. Trans. Royal Soc. Lond. B Biol. Sci. 356, 983–989 (2001).

    Article  CAS  Google Scholar 

  2. Leibold, M.A. A graphical model of keystone predators in food webs: trophic regulation of abundance, incidence, and diversity patterns in communities. Am. Naturalist 147, 784–812 (1996).

    Article  Google Scholar 

  3. Rose, M.D. & Polis, G.A. The distribution and abundance of coyotes: the effects of allochthonous food subsidies from the sea. Ecology 79, 998–1007 (1998).

    Article  Google Scholar 

  4. LoGiudice, K., Ostfeld, R.S., Schmidt, K.A. & Keesing, F. The ecology of infectious disease: effects of host diversity and community composition on Lyme disease risk. Proc. Natl. Acad. Sci. USA 100, 567–571 (2003).

    Article  CAS  Google Scholar 

  5. Lord, R.D., Lord, V.R., Humphreys, J.G. & McLean, R.G. Distribution of Borrelia burgdorferi in host mice in Pennsylvania. J. Clin. Microbiol. 32, 2501–2504 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Matuschka, F.R., Fischer, P., Musgrave, K., Richter, D. & Spielman, A. Hosts on which nymphal Ixodes ricinus most abundantly feed. Am. J. Trop. Med. Hyg. 44, 100–107 (1991).

    Article  CAS  Google Scholar 

  7. Brisson, D., Dykhuizen, D.E. & Ostfeld, R.S. Conspicuous impacts of inconspicuous hosts on the Lyme disease epidemic. Proc. Roy. Soc. Biol. Sci. 275, 227–235 (2008).

    Article  Google Scholar 

  8. Allan, B.F., Goessling, L.S., Storch, G.A. & Thach, R.E. Blood meal analysis to identify reservoir hosts for Amblyomma americanum ticks. Emerg. Infect. Dis. 16, 433–440 (2010).

    Article  CAS  Google Scholar 

  9. Arnold, E.H., Simmons, S.W. & Fawcett, D.G. Precipitin technique for determining mosquito blood meals. Public Health Rep. 61, 1244–1249 (1946).

    Article  CAS  Google Scholar 

  10. Burkot, T.R., Goodman, W.G. & DeFoliart, G.R. Identification of mosquito blood meals by enzyme-linked immunosorbent assay. Am. J. Trop. Med. Hyg. 30, 1336–1341 (1981).

    Article  CAS  Google Scholar 

  11. Kent, R.J. Molecular methods for arthropod bloodmeal identification and applications to ecological and vector-borne disease studies. Mol. Ecol. Resour. 9, 4–18 (2009).

    Article  CAS  Google Scholar 

  12. Tempelis, C.H. & Rodrick, M.L. Passive hemagglutination inhibition technique for the identification of arthropod blood meals. Am. J. Trop. Med. Hyg. 21, 238–245 (1972).

    Article  CAS  Google Scholar 

  13. Wickramasekara, S., Bunikis, J., Wysocki, V. & Barbour, A.G. Identification of residual blood proteins in ticks by mass spectrometry proteomics. Emerg. Infect. Dis. 14, 1273–1275 (2008).

    Article  CAS  Google Scholar 

  14. Schubert, J.H. & Holdeman, L.V. A modified precipitin technique for determining the source of mosquito blood-meals. Am. J. Trop. Med. Hyg. 5, 272–273 (1956).

    Article  CAS  Google Scholar 

  15. Onder, O., Shao, W., Kemps, B., Lam, H. & Brisson, D. Blood meal source tracking through genome-free proteomics technology using unidentified tandem mass spectral libraries. Nat. Commun. 4, 1746 (2013).

    Article  Google Scholar 

  16. Laskay, U.A. et al. Development of a host blood meal database: de novo sequencing of hemoglobin from nine small mammals using mass spectrometry. Biol. Chem. 393, 195–201 (2012).

    Article  CAS  Google Scholar 

  17. Gariepy, T.D., Lindsay, R., Ogden, N. & Gregory, T.R. Identifying the last supper: utility of the DNA barcode library for bloodmeal identification in ticks. Mol. Ecol. Resour. 12, 646–652 (2012).

    Article  CAS  Google Scholar 

  18. Mukabana, W.R., Takken, W. & Knols, B.G. Analysis of arthropod bloodmeals using molecular genetic markers. Trends Parasitol. 18, 505–509 (2002).

    Article  CAS  Google Scholar 

  19. Humair, P.F. et al. Molecular identification of bloodmeal source in Ixodes ricinus ticks using 12S rDNA as a genetic marker. J. Med. Entomol. 44, 869–880 (2007).

    Article  CAS  Google Scholar 

  20. Pizarro, J.C. & Stevens, L. A new method for forensic DNA analysis of the blood meal in Chagas disease vectors demonstrated using Triatoma infestans from Chuquisaca, Bolivia. PLoS ONE 3, e3585 (2008).

    Article  Google Scholar 

  21. Mota, J. et al. Identification of blood meal source and infection with Trypanosoma cruzi of Chagas disease vectors using a multiplex cytochrome b polymerase chain reaction assay. Vector Borne Zoonotic Dis. 7, 617–627 (2007).

    Article  Google Scholar 

  22. Moran Cadenas, F. et al. Identification of host bloodmeal source and Borrelia burgdorferi sensu lato in field-collected Ixodes ricinus ticks in Chaumont (Switzerland). J. Med. Entomol. 44, 1109–1117 (2007).

    Article  Google Scholar 

  23. Dasari, S. et al. Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment. J. Proteome Res. 11, 1686–1695 (2012).

    Article  CAS  Google Scholar 

  24. Lam, H. & Aebersold, R. Building and searching tandem mass (MS/MS) spectral libraries for peptide identification in proteomics. Methods 54, 424–431 (2011).

    Article  CAS  Google Scholar 

  25. Lam, H. et al. Building consensus spectral libraries for peptide identification in proteomics. Nat. Methods 5, 873–875 (2008).

    Article  CAS  Google Scholar 

  26. Craig, R., Cortens, J.C., Fenyo, D. & Beavis, R.C. Using annotated peptide mass spectrum libraries for protein identification. J. Proteome Res. 5, 1843–1849 (2006).

    Article  CAS  Google Scholar 

  27. Frewen, B.E., Merrihew, G.E., Wu, C.C., Noble, W.S. & MacCoss, M.J. Analysis of peptide MS/MS spectra from large-scale proteomics experiments using spectrum libraries. Anal. Chem. 78, 5678–5684 (2006).

    Article  CAS  Google Scholar 

  28. Stein, S.E. & Scott, D.R. Optimization and testing of mass-spectral library search algorithms for compound identification. J. Am. Soc. Mass Spectr. 5, 859–866 (1994).

    Article  CAS  Google Scholar 

  29. Onder, O., Turkarslan, S., Sun, D. & Daldal, F. Overproduction or absence of the periplasmic protease DegP severely compromises bacterial growth in the absence of the dithiol: disulfide oxidoreductase DsbA. Mol. Cell Proteomics 7, 875–890 (2008).

    Article  CAS  Google Scholar 

  30. Onder, O. et al. Modifications of the lipoamide-containing mitochondrial subproteome in a yeast mutant defective in cysteine desulfurase. Mol. Cell Proteomics 5, 1426–1436 (2006).

    Article  CAS  Google Scholar 

  31. Chambers, M.C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat. Biotechnol. 30, 918–920 (2012).

    Article  CAS  Google Scholar 

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This work was supported by a grant from the US National Institutes of Health (AI076342); the US Center for Disease Control and Prevention (U01CK000170); and the University Grant Council, Hong Kong Special Administrative Region Government (HKUST RPC10EG08, DAG12EG01S).

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Authors and Affiliations



D.B., H.L. and Ö.Ö. conceived the study and formulated the experimental and computational strategy. Ö.Ö. optimized all the experimental protocols. H.L. and W.S. adapted SpectraST to build spectral libraries from unidentified spectra. Ö.Ö., H.L. and D.B. co-wrote the manuscript, with input from all authors.

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Correspondence to Özlem Önder or Henry Lam.

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The authors declare no competing financial interests.

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Önder, Ö., Shao, W., Lam, H. et al. Tracking the sources of blood meals of parasitic arthropods using shotgun proteomics and unidentified tandem mass spectral libraries. Nat Protoc 9, 842–850 (2014).

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