| Literature DB >> 27362709 |
Maggy T Sikulu-Lord1,2, Marta F Maia2, Masabho P Milali2, Michael Henry2, Gustav Mkandawile2, Elise A Kho1, Robert A Wirtz3, Leon E Hugo1, Floyd E Dowell4, Gregor J Devine1.
Abstract
The release of Wolbachia infected mosquitoes is likely to form a key component of disease control strategies in the near future. We investigated the potential of using near-infrared spectroscopy (NIRS) to simultaneously detect and identify two strains of Wolbachia pipientis (wMelPop and wMel) in male and female laboratory-reared Aedes aegypti mosquitoes. Our aim is to find faster, cheaper alternatives for monitoring those releases than the molecular diagnostic techniques that are currently in use. Our findings indicate that NIRS can differentiate females and males infected with wMelPop from uninfected wild type samples with an accuracy of 96% (N = 299) and 87.5% (N = 377), respectively. Similarly, females and males infected with wMel were differentiated from uninfected wild type samples with accuracies of 92% (N = 352) and 89% (N = 444). NIRS could differentiate wMelPop and wMel transinfected females with an accuracy of 96.6% (N = 442) and males with an accuracy of 84.5% (N = 443). This non-destructive technique is faster than the standard polymerase chain reaction diagnostic techniques. After the purchase of a NIRS spectrometer, the technique requires little sample processing and does not consume any reagents.Entities:
Mesh:
Year: 2016 PMID: 27362709 PMCID: PMC4928868 DOI: 10.1371/journal.pntd.0004759
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Examples of average spectra collected from heads and thoraces of Wolbachia infected and wild type male and female Ae. aegypti mosquitoes.
Fig 2Regression coefficient plots used to predict the presence or absence of infection.
They are based on 9 PLS regression factors. The plots show peaks that influenced the differentiation of female wMelPop from female wMel (panel A) and female wMel from female wild type Ae. aegypti (panel B).
Percentage accuracy of Wolbachia detection using cross validation and prediction analyses.
| Infection type | % Accuracy [N] Cross validation | % Accuracy [N] Validation set | % Accuracy [N] Test set |
|---|---|---|---|
| 92 [259] | 97 [200] | 95 [99] | |
| 89 [256] | 91 [248] | 93 [104] | |
| 85 [144] | 82 [301] | 93 [76] | |
| 91 [160] | 89 [346] | 88 [98] | |
| 95 [200] | 95 [337] | 98 [105] | |
| 89 [177] | 90 [335] | 79 [108] |
1 Accuracy of mosquitoes used to develop calibration models
2 Accuracy of cohort 1 mosquitoes that were used to validate calibration models
3 Accuracy of cohort 2 mosquitoes that were used to test calibration models
Fig 3NIRS differentiation of Wolbachia infected and wild type male and female Ae. aegypti mosquitoes using validation and test samples.
The dotted line indicates the classification cut off point as predicted by the NIRS.
Percentage accuracy with which pairs were differentiated at various ages (1–20 days), and the specific identification accuracy for the individual components of those pairs.
| Infection type | N | 1d | 5d | 10d | 15d | 19d | 20d | Specific [N] for first member of pair | Specific [N] for second member of pair |
|---|---|---|---|---|---|---|---|---|---|
| 299 | 87 | 98 | 100 | 97 | 100 | 96 | 95 [151] | 97 [148] | |
| 352 | 85 | 86 | 92 | 95 | 84 | 96 | 93 [208] | 87 [144] | |
| 377 | 70 | 87 | 87 | 89 | 80 | 92 | 89 [197] | 79 [180] | |
| 444 | 90 | 93 | 100 | 81 | 76 | 95 | 90 [262] | 89 [182] | |
| 442 | 95 | 99 | 98 | 95 | 92 | 97 | 95 [199] | 97 [243] | |
| 443 | 98 | 97 | 98 | 75 | 79 | 90 | 89 [197] | 86 [246] |