Limits...
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.

Show MeSH

Related in: MedlinePlus

Dendrogram of hierarchical, unsupervised clustering of binary peaks (presence/absence).While the Anopheles species (complexes) are well separated by the cluster algorithm, the sibling species of the A. gambiae complex (coloured lines) do not segregate into well defined clusters. Specimens, both from the same species and colony, are split into different groups. The external branches represent each measured specimen. For each colony spectra from 10 specimens were recorded and included in the cluster analysis. The labels give the names of the colonies (Table 1). The length of the branches corresponds to the size of the Dice similarity coefficient.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3585343&req=5

pone-0057486-g002: Dendrogram of hierarchical, unsupervised clustering of binary peaks (presence/absence).While the Anopheles species (complexes) are well separated by the cluster algorithm, the sibling species of the A. gambiae complex (coloured lines) do not segregate into well defined clusters. Specimens, both from the same species and colony, are split into different groups. The external branches represent each measured specimen. For each colony spectra from 10 specimens were recorded and included in the cluster analysis. The labels give the names of the colonies (Table 1). The length of the branches corresponds to the size of the Dice similarity coefficient.

Mentions: Initially we also set out to use a cluster analysis approach. At first inspection, colonies from the same species (complex) that were reared in different laboratories over many years clustered well together into the same super cluster (Figure 2). A good example is A. stephensi. The individual specimens form the two colonies included in this study segregate into two clusters and yet aggregate into one single cluster for that species at the next higher level. This is in contrast to the A. gambiae species complex where hierarchical clustering failed to segregate the (four analysed) sibling species within the complex (Figure 2). Conceivably, the intermixture within the species complex mirrors the close relationship among the A. gambiae sibling species. In line with the lack of distinct hierarchical clusters there were no unique peaks that would serve as single biomarkers to separate the sibling species.


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)

Dendrogram of hierarchical, unsupervised clustering of binary peaks (presence/absence).While the Anopheles species (complexes) are well separated by the cluster algorithm, the sibling species of the A. gambiae complex (coloured lines) do not segregate into well defined clusters. Specimens, both from the same species and colony, are split into different groups. The external branches represent each measured specimen. For each colony spectra from 10 specimens were recorded and included in the cluster analysis. The labels give the names of the colonies (Table 1). The length of the branches corresponds to the size of the Dice similarity coefficient.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0057486-g002: Dendrogram of hierarchical, unsupervised clustering of binary peaks (presence/absence).While the Anopheles species (complexes) are well separated by the cluster algorithm, the sibling species of the A. gambiae complex (coloured lines) do not segregate into well defined clusters. Specimens, both from the same species and colony, are split into different groups. The external branches represent each measured specimen. For each colony spectra from 10 specimens were recorded and included in the cluster analysis. The labels give the names of the colonies (Table 1). The length of the branches corresponds to the size of the Dice similarity coefficient.
Mentions: Initially we also set out to use a cluster analysis approach. At first inspection, colonies from the same species (complex) that were reared in different laboratories over many years clustered well together into the same super cluster (Figure 2). A good example is A. stephensi. The individual specimens form the two colonies included in this study segregate into two clusters and yet aggregate into one single cluster for that species at the next higher level. This is in contrast to the A. gambiae species complex where hierarchical clustering failed to segregate the (four analysed) sibling species within the complex (Figure 2). Conceivably, the intermixture within the species complex mirrors the close relationship among the A. gambiae sibling species. In line with the lack of distinct hierarchical clusters there were no unique peaks that would serve as single biomarkers to separate the sibling species.

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