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Identification of cryptic Anopheles mosquito species by molecular protein profiling.

Müller P, Pflüger V, Wittwer M, Ziegler D, Chandre F, Simard F, Lengeler C - PLoS ONE (2013)

Bottom Line: The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies.While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time.As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Services and Diagnostic, Swiss Tropical and Public Health Institute, Basel, Switzerland. pie.mueller@unibas.ch

ABSTRACT
Vector control is the mainstay of malaria control programmes. Successful vector control profoundly relies on accurate information on the target mosquito populations in order to choose the most appropriate intervention for a given mosquito species and to monitor its impact. An impediment to identify mosquito species is the existence of morphologically identical sibling species that play different roles in the transmission of pathogens and parasites. Currently PCR diagnostics are used to distinguish between sibling species. PCR based methods are, however, expensive, time-consuming and their development requires a priori DNA sequence information. Here, we evaluated an inexpensive molecular proteomics approach for Anopheles species: matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS is a well developed protein profiling tool for the identification of microorganisms but so far has received little attention as a diagnostic tool in entomology. We measured MS spectra from specimens of 32 laboratory colonies and 2 field populations representing 12 Anopheles species including the A. gambiae species complex. An important step in the study was the advancement and implementation of a bioinformatics approach improving the resolution over previously applied cluster analysis. Borrowing tools for linear discriminant analysis from genomics, MALDI-TOF MS accurately identified taxonomically closely related mosquito species, including the separation between the M and S molecular forms of A. gambiae sensu stricto. The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies. While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time. As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

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Model selection and cross-validation for colony authentication in Anopheles arabiensis (Model 3).(A) Error rate as a function of the number of peaks included in the SDA model for five A. arabiensis colonies and the total error rate over all colonies. The peaks were ranked according to the correlation-adjusted t-scores (CAT scores). The vertical, red line shows the 23 peaks chosen for the SDA model (Table S4). (B) Top 23 peaks included in SDA model after they were ranked according to CAT scores (i.e. peak with highest CAT score appears at the top of the list). The length and direction of the horizontal blue bars represents the CAT scores of the centroid versus the pooled mean and shows the influence of a particular peak in differentiating between the colonies.
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pone-0057486-g006: Model selection and cross-validation for colony authentication in Anopheles arabiensis (Model 3).(A) Error rate as a function of the number of peaks included in the SDA model for five A. arabiensis colonies and the total error rate over all colonies. The peaks were ranked according to the correlation-adjusted t-scores (CAT scores). The vertical, red line shows the 23 peaks chosen for the SDA model (Table S4). (B) Top 23 peaks included in SDA model after they were ranked according to CAT scores (i.e. peak with highest CAT score appears at the top of the list). The length and direction of the horizontal blue bars represents the CAT scores of the centroid versus the pooled mean and shows the influence of a particular peak in differentiating between the colonies.

Mentions: The SDA Model 3 (Figure 6 and Table S4), classifying specimens of the same species into their colonies of origin, accurately scored 20 out of 25 specimens (80%) among the five A. arabiensis laboratory colonies (Table S1). Though 80% accuracy may seem low this is still quite remarkable given that the model is based on only 5 randomly picked individuals per colony. Including more features than the minimum 21 peaks yielded by our inclusion criteria would actually increase accuracy even more. For example, including an additional 7 peaks into the model provides an accuracy of 88% (i.e. 22 correctly identified out of 25 individuals). Including more specimens in the training set would also reduce the classification error (data not shown).


Identification of cryptic Anopheles mosquito species by molecular protein profiling.

Müller P, Pflüger V, Wittwer M, Ziegler D, Chandre F, Simard F, Lengeler C - PLoS ONE (2013)

Model selection and cross-validation for colony authentication in Anopheles arabiensis (Model 3).(A) Error rate as a function of the number of peaks included in the SDA model for five A. arabiensis colonies and the total error rate over all colonies. The peaks were ranked according to the correlation-adjusted t-scores (CAT scores). The vertical, red line shows the 23 peaks chosen for the SDA model (Table S4). (B) Top 23 peaks included in SDA model after they were ranked according to CAT scores (i.e. peak with highest CAT score appears at the top of the list). The length and direction of the horizontal blue bars represents the CAT scores of the centroid versus the pooled mean and shows the influence of a particular peak in differentiating between the colonies.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585343&req=5

pone-0057486-g006: Model selection and cross-validation for colony authentication in Anopheles arabiensis (Model 3).(A) Error rate as a function of the number of peaks included in the SDA model for five A. arabiensis colonies and the total error rate over all colonies. The peaks were ranked according to the correlation-adjusted t-scores (CAT scores). The vertical, red line shows the 23 peaks chosen for the SDA model (Table S4). (B) Top 23 peaks included in SDA model after they were ranked according to CAT scores (i.e. peak with highest CAT score appears at the top of the list). The length and direction of the horizontal blue bars represents the CAT scores of the centroid versus the pooled mean and shows the influence of a particular peak in differentiating between the colonies.
Mentions: The SDA Model 3 (Figure 6 and Table S4), classifying specimens of the same species into their colonies of origin, accurately scored 20 out of 25 specimens (80%) among the five A. arabiensis laboratory colonies (Table S1). Though 80% accuracy may seem low this is still quite remarkable given that the model is based on only 5 randomly picked individuals per colony. Including more features than the minimum 21 peaks yielded by our inclusion criteria would actually increase accuracy even more. For example, including an additional 7 peaks into the model provides an accuracy of 88% (i.e. 22 correctly identified out of 25 individuals). Including more specimens in the training set would also reduce the classification error (data not shown).

Bottom Line: The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies.While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time.As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Services and Diagnostic, Swiss Tropical and Public Health Institute, Basel, Switzerland. pie.mueller@unibas.ch

ABSTRACT
Vector control is the mainstay of malaria control programmes. Successful vector control profoundly relies on accurate information on the target mosquito populations in order to choose the most appropriate intervention for a given mosquito species and to monitor its impact. An impediment to identify mosquito species is the existence of morphologically identical sibling species that play different roles in the transmission of pathogens and parasites. Currently PCR diagnostics are used to distinguish between sibling species. PCR based methods are, however, expensive, time-consuming and their development requires a priori DNA sequence information. Here, we evaluated an inexpensive molecular proteomics approach for Anopheles species: matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS is a well developed protein profiling tool for the identification of microorganisms but so far has received little attention as a diagnostic tool in entomology. We measured MS spectra from specimens of 32 laboratory colonies and 2 field populations representing 12 Anopheles species including the A. gambiae species complex. An important step in the study was the advancement and implementation of a bioinformatics approach improving the resolution over previously applied cluster analysis. Borrowing tools for linear discriminant analysis from genomics, MALDI-TOF MS accurately identified taxonomically closely related mosquito species, including the separation between the M and S molecular forms of A. gambiae sensu stricto. The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies. While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time. As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

Show MeSH
Related in: MedlinePlus