1921
Volume 100, Issue 1
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract.

Matrix-assisted desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a clinical microbiology tool for the systematic identification of microorganisms. It has recently been presented as an innovative tool for the rapid and accurate identification of mosquitoes and their blood meal. To evaluate the capacity of this tool to identify mosquitoes collected in a tropical environment and preserved with silica gel, we analyzed 188 mosquitoes of different species collected in Chad, which were preserved with silica gel for 2 months. The MALDI-TOF MS analysis correctly identified 96% of the mosquitoes and 37.5% of their blood meals. Using MALDI-TOF MS and molecular biology, eight mosquito species were identified, including s.l., , , , , , , and . Blood meal identification revealed that mosquitoes fed mainly on humans, birds, and cows. Matrix-assisted desorption/ionization time-of-flight mass spectrometry appears to be a promising, fast, and reliable tool to identify mosquitoes and the origin of their blood meal for samples stored with silica gel.

Loading

Article metrics loading...

The graphs shown below represent data from March 2017
/content/journals/10.4269/ajtmh.18-0657
2018-12-03
2020-01-25
Loading full text...

Full text loading...

/deliver/fulltext/14761645/100/1/tpmd180657.html?itemId=/content/journals/10.4269/ajtmh.18-0657&mimeType=html&fmt=ahah

References

  1. Fernandes JN, Moise IK, Maranto GL, Beier JC, , 2018. Revamping mosquito-borne disease control to tackle future threats. Trends Parasitol 34: 359368. [Google Scholar]
  2. Moise IK, Riegel C, Muturi EJ, , 2018. Environmental and social-demographic predictors of the southern house mosquito Culex quinquefasciatus in New Orleans, Louisiana. Parasit Vectors 11: 249. [Google Scholar]
  3. Brasil P, 2017. Outbreak of human malaria caused by Plasmodium simium in the Atlantic Forest in Rio de Janeiro: a molecular epidemiological investigation. Lancet Glob Health 5: e1038e1046. [Google Scholar]
  4. WHO, 2016. World Malaria Report 2016. Geneva, Switzerland: World Health Organization. [Google Scholar]
  5. WHO, 2017. World Malaria Report 2017. Geneva, Switzerland: World Health Organization. [Google Scholar]
  6. Pluess B, Tanser FC, Lengeler C, Sharp BL, , 2010. Indoor residual spraying for preventing malaria. Cochrane Database Syst Rev 4: CD006657. [Google Scholar]
  7. Medzihradsky OF, 2018. Study protocol for a cluster randomised controlled factorial design trial to assess the effectiveness and feasibility of reactive focal mass drug administration and vector control to reduce malaria transmission in the low endemic setting of Namibia. BMJ Open 8: e019294. [Google Scholar]
  8. Bass C, Williamson MS, Wilding CS, Donnelly MJ, Field LM, , 2007. Identification of the main malaria vectors in the Anopheles gambiae species complex using a TaqMan real-time PCR assay. Malar J 6: 155. [Google Scholar]
  9. Muturi EJ, Mwangangi JM, Beier JC, Blackshear M, Wauna J, Sang R, Mukabana WR, , 2013. Ecology and behavior of Anopheles arabiensis in relation to agricultural practices in central Kenya. J Am Mosq Control Assoc 29: 222230. [Google Scholar]
  10. Yssouf A, Almeras L, Raoult D, Parola P, , 2016. Emerging tools for identification of arthropod vectors. Future Microbiol 11: 549566. [Google Scholar]
  11. Fyodorova MV, Savage HM, Lopatina JV, Bulgakova TA, Ivanitsky AV, Platonova OV, Platonov AE, , 2006. Evaluation of potential west Nile virus vectors in Volgograd region, Russia, 2003 (Diptera: Culicidae): species composition, bloodmeal host utilization, and virus infection rates of mosquitoes. J Med Entomol 43: 552563. [Google Scholar]
  12. Ngo KA, Kramer LD, , 2003. Identification of mosquito bloodmeals using polymerase chain reaction (PCR) with order-specific primers. J Med Entomol 40: 215222. [Google Scholar]
  13. Kent RJ, , 2009. Molecular methods for arthropod bloodmeal identification and applications to ecological and vector-borne disease studies. Mol Ecol Resour 9: 418. [Google Scholar]
  14. Martinez-de la Puente J, Ruiz S, Soriguer R, Figuerola J, , 2013. Effect of blood meal digestion and DNA extraction protocol on the success of blood meal source determination in the malaria vector Anopheles atroparvus. Malar J 12: 109. [Google Scholar]
  15. Bizzini A, Greub G, , 2010. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry, a revolution in clinical microbial identification. Clin Microbiol Infect 16: 16141619. [Google Scholar]
  16. Seng P, Drancourt M, Gouriet F, La Scola B, Fournier PE, Rolain JM, Raoult D, , 2009 . Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Infect Dis 49: 543551. [Google Scholar]
  17. Dridi B, Raoult D, Drancourt M, , 2012. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification of Archaea: towards the universal identification of living organisms. APMIS 120: 8591. [Google Scholar]
  18. Murugaiyan J, Roesler U, , 2017. MALDI-TOF MS profiling-advances in species identification of pests, parasites, and vectors. Front Cell Infect Microbiol 7: 184. [Google Scholar]
  19. Halada P, Hlavackova K, Dvorak V, Volf P, , 2018. Identification of immature stages of phlebotomine sand flies using MALDI-TOF MS and mapping of mass spectra during sand fly life cycle. Insect Biochem Mol Biol 93: 4756. [Google Scholar]
  20. Hoppenheit A, Murugaiyan J, Bauer B, Steuber S, Clausen PH, Roesler U, , 2013. Identification of tsetse (Glossina spp.) using matrix-assisted laser desorption/ionisation time of flight mass spectrometry. PLoS Negl Trop Dis 7: e2305. [Google Scholar]
  21. Raharimalala FN, Andrianinarivomanana TM, Rakotondrasoa A, Collard JM, Boyer S, , , 2017. Usefulness and accuracy of MALDI-TOF mass spectrometry as a supplementary tool to identify mosquito vector species and to invest in development of international database. Med Vet Entomol 31: 289298. [Google Scholar]
  22. Rothen J, Githaka N, Kanduma EG, Olds C, Pflüger V, Mwaura S, Bishop RP, Daubenberger C, , 2016 . Matrix-assisted laser desorption/ionization time of flight mass spectrometry for comprehensive indexing of East African ixodid tick species. Parasit Vectors 9: 151. [Google Scholar]
  23. Niare S, Tandina F, Davoust B, Doumbo O, Raoult D, Parola P, Almeras L, , 2017 . Accurate identification of Anopheles gambiae Giles trophic preferences by MALDI-TOF MS. Infect Genet Evol 63: 410419. [Google Scholar]
  24. Tandina F, Niaré S, Laroche M, Koné AK, Diarra AZ, Ongoiba A, Berenger JM, Doumbo OK, Raoult D, Parola P, , 2018. Using MALDI-TOF MS to identify mosquitoes collected in Mali and their blood meals. Parasitology 145: 11701182. [Google Scholar]
  25. Diarra AZ, Almeras L, Laroche M, Berenger JM, Koné AK, Bocoum Z, Dabo A, Doumbo O, Raoult D, Parola P, , 2017 . Molecular and MALDI-TOF identification of ticks and tick-associated bacteria in Mali. PLoS Negl Trop Dis 11: e0005762. [Google Scholar]
  26. Yssouf A, , 2013. Matrix-assisted laser desorption ionization—time of flight mass spectrometry: an emerging tool for the rapid identification of mosquito vectors. PLoS One 8: e72380. [Google Scholar]
  27. Vogels CB, Möhlmann TW, Melsen D, Favia G, Wennergren U, Koenraadt CJ, , 2016. Latitudinal diversity of Culex pipiens biotypes and hybrids in farm, peri-urban, and wetland habitats in Europe. PLoS One 11: e0166959. [Google Scholar]
  28. Biteye B, Fall AG, Ciss M, Seck MT, Apolloni A, Fall M, Tran A, Gimonneau G, , 2018. Ecological distribution and population dynamics of Rift Valley fever virus mosquito vectors (Diptera, Culicidae) in Senegal. Parasit Vectors 11: 27. [Google Scholar]
  29. Diagne N, Fontenille D, Konate L, Faye O, Lamizana MT, Legros F, Molez JF, Trape JF, , 1994. Anopheles of Senegal. An annotated and illustrated list. Bull Soc Pathol Exot 87: 267277. [Google Scholar]
  30. Nebbak A, Willcox AC, Bitam I, Raoult D, Parola P, Almeras L, , 2016. Standardization of sample homogenization for mosquito identification using an innovative proteomic tool based on protein profiling. Proteomics 16: 31483160. [Google Scholar]
  31. Townzen JS, Brower AV, Judd DD, , 2008. Identification of mosquito bloodmeals using mitochondrial cytochrome oxidase subunit I and cytochrome b gene sequences. Med Vet Entomol 22: 386393. [Google Scholar]
  32. Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R, , 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol 3: 294299. [Google Scholar]
  33. Weeraratne TC, Surendran SN, Reimer LJ, Wondji CS, Perera MDB, Walton C, Parakrama Karunaratne SHP, , 2017. Molecular characterization of Anopheline (Diptera: Culicidae) mosquitoes from eight geographical locations of Sri Lanka. Malar J 16: 234. [Google Scholar]
  34. Carbonnelle E, Mesquita C, Bille E, Day N, Dauphin B, Beretti JL, Ferroni A, Gutmann L, Nassif X, , 2011. MALDI-TOF mass spectrometry tools for bacterial identification in clinical microbiology laboratory. Clin Biochem 44: 104109. [Google Scholar]
  35. Welker M, Moore ER, , 2011. Applications of whole-cell matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry in systematic microbiology. Syst Appl Microbiol 34: 211. [Google Scholar]
  36. Gregory D, Chaudet H, Lagier JC, Raoult D, , 2018. How mass spectrometric approaches applied to bacterial identification have revolutionized the study of human gut microbiota. Expert Rev Proteomics 15: 217229. [Google Scholar]
  37. El HB, Laroche M, Almeras L, Bérenger JM, Raoult D, Parola P, , 2018. Detection of Bartonella spp. in fleas by MALDI-TOF MS. PLoS Negl Trop Dis 12: e0006189. [Google Scholar]
  38. Laroche M, Almeras L, Pecchi E, Bechah Y, Raoult D, Viola A, Parola P, , 2017. MALDI-TOF MS as an innovative tool for detection of plasmodium parasites in Anopheles mosquitoes. Malar J 16: 5. [Google Scholar]
  39. Tahir D, Almeras L, Varloud M, Raoult D, Davoust B, Parola P, , 2017. Assessment of MALDI-TOF mass spectrometry for filariae detection in Aedes aegypti mosquitoes. PLoS Negl Trop Dis 11: e0006093. [Google Scholar]
  40. Yssouf A, Flaudrops C, Drali R, Kernif T, Socolovschi C, Berenger JM, Raoult D, Parola P, , 2013. Matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid identification of tick vectors. J Clin Microbiol 51: 522528. [Google Scholar]
  41. Yssouf A, Socolovschi C, Leulmi H, Kernif T, Bitam I, Audoly G, Almeras L, Raoult D, Parola P, , 2014. Identification of flea species using MALDI-TOF/MS. Comp Immunol Microbiol Infect Dis 37: 153157. [Google Scholar]
  42. Mathis A, 2015. Identification of phlebotomine sand flies using one MALDI-TOF MS reference database and two mass spectrometer systems. Parasit Vectors 8: 266. [Google Scholar]
  43. Kerah-Hinzoumbe C, Péka M, Antonio-Nkondjio C, Donan-Gouni I, Awono-Ambene P, Samè-Ekobo A, Simard F, , 2009. Malaria vectors and transmission dynamics in Goulmoun, a rural city in south-western Chad. BMC Infect Dis 9: 71. [Google Scholar]
  44. Byrne K, Nichols RA, , 1999. Culex pipiens in London underground tunnels: differentiation between surface and subterranean populations. Heredity (Edinb.) 82: 715. [Google Scholar]
  45. Vinogradova EB, Shaikevich EV, , 2005. Differentiation between the urban mosquito Culex pipiens pipiens F. molestus and Culex torrentium (Diptera: Culicidae) by the molecular genetic methods. Parazitologiia 39: 574576. [Google Scholar]
  46. Kilpatrick AM, Kramer LD, Campbell SR, Alleyne EO, Dobson AP, Daszak P, , 2005. West Nile virus risk assessment and the bridge vector paradigm. Emerg Infect Dis 11: 425429. [Google Scholar]
  47. Hamon J, Burnett GF, Adam JP, Rickenbach A, Grjebine A, , 1967. Culex pipiens fatigans Wiedemann, Wuchereria bancrofti Cobbold and the economic development of tropical Africa. Bull World Health Organ 37: 217237. [Google Scholar]
  48. Chavasse DC, Lines JD, Ichimori K, , 1996. The relationship between mosquito density and mosquito coil sales in Dar es Salaam. Trans R Soc Trop Med Hyg 90: 493. [Google Scholar]
  49. Fofana D, Koné AB, Koné N, Konan YL, Doannio JM, N'goran KE, , 2012. Culex quinquefasciatus sensitivity to insecticides in relation to the urbanization level and sewage water in Yopougon, a township of Abidjan (Cote-d'Ivoire). Bull Soc Pathol Exot 105: 230236. [Google Scholar]
  50. Yadouleton A, Badirou K, Agbanrin R, Jöst H, Attolou R, Srinivasan R, Padonou G, Akogbéto M, , 2015. Insecticide resistance status in Culex quinquefasciatus in Benin. Parasit Vectors 8: 17. [Google Scholar]
  51. Rodhain F, Clerc Y, Albignac R, Ricklin B, Ranaivosata J, Coulanges P, , 1982. Arboviruses and lemurs in Madagascar: a preliminary note. Trans R Soc Trop Med Hyg 76: 227231. [Google Scholar]
  52. Rickenbach A, Eouzan JP, Ferrara L, Bailly-Choumara H, , 1976. Données Nouvelles sur la Présence, la Fréquence et la Répartition des Toxorhynchitinae et Culicinae (Diptera, Culicidae) au Cameroun2. Genres Eretrnapodites et Culex. Cah. O.R.S.T.O.M., sér. Ent. méd. et Parasitol., vol. XN, no 2, 1976: 93–10. [Google Scholar]
  53. Obame-Nkoghe J, 2017. Exploring the diversity of blood-sucking Diptera in caves of Central Africa. Sci Rep 7: 250. [Google Scholar]
  54. Peters W, , 1956. The Mosquitos of Liberia (Diptera: Culicidae), A General Survey. Bull Entomol Res 47: 525551. [Google Scholar]
  55. Erlank E, Koekemoer LL, Coetzee M, , 2018. The importance of morphological identification of African anopheline mosquitoes (Diptera: Culicidae) for malaria control programmes. Malar J 17: 43. [Google Scholar]
  56. Niare S, Berenger JM, Dieme C, Doumbo O, Raoult D, Parola P, Almeras L, , 2016. Identification of blood meal sources in the main African malaria mosquito vector by MALDI-TOF MS. Malar J 15: 87. [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.4269/ajtmh.18-0657
Loading
/content/journals/10.4269/ajtmh.18-0657
Loading

Data & Media loading...

  • Received : 10 Aug 2018
  • Accepted : 10 Sep 2018
  • Published online : 03 Dec 2018

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error