New assessment of Anopheles vector species identification using MALDI-TOF MS

Nabet, Cécile; Koné, Abdoulaye K.; Dia, Abdoulaye Kane; Sylla, Moussa; Gautier, Magali; Yattara, Mohammed; Théra, Mahamadou A.; Faye, Ousmane; Braack, L.E.O.; Manguin, Sylvie; Béavogui, Abdoul Habib; Doumbo, Ogobara K.; Piarroux, Renaud

doi:10.1186/s12936-020-03557-2

Cited by 27 publications

(69 citation statements)

References 35 publications

(90 reference statements)

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“…Respectively, 30µL and 50 µL of mix buffer were used for legs and thoraxes, as previously described [32,33], and 30µL of mix buffer were used for heads based on our preliminary tests. For themanual homogenization, the samples were ground either with MP (with tips of 10µl) or PP until completed homogenization as previously described [24,41]. Automatic homogenization consisted of adding glass beads 0.1mm (BioSpec Products, Bartlesville, US) in each sample tube, followed by a homogenization cycle of 3 X 1 minute at 30 Hertz using a TissueLyser device, according to the standardized, automated setting described previously [29].…”

Section: Sample Homogenization For Maldi-tof Ms Analysismentioning

confidence: 99%

“…This proteomic tool, routinely used in microbiology diagnosis laboratories for bacteria or yeast identi cation [16][17][18], has been e ciently applied in several medical entomology studies for arthropods identi cation, such as ies [19,20], ticks [21,22] or eas [23]. This tool was also successfully used to identify mosquitoes from laboratory or eld origins [24][25][26]. Its performances for mosquito identi cation were highlighted in a recent study reporting the successful distinction of members from the Anopheles gambiae complex, An.…”

Section: Introductionmentioning

confidence: 99%

“…Concerning body parts, some studies reported the use of thoraxes and cephalothoraxes [34,35]. More recently, Nabet et al [24] emphasized that the mosquito head appeared to be the most appropriate body part for MS identi cation. In addition, methods for homogenizing the samples vary according to studies; some used automatic devices, such as TissueLyser (TL) and others ground samples manually with a micropipette (MP) [24] or pellet pestles (PP) [36].…”

Section: Introductionmentioning

confidence: 99%

“…More recently, Nabet et al [24] emphasized that the mosquito head appeared to be the most appropriate body part for MS identi cation. In addition, methods for homogenizing the samples vary according to studies; some used automatic devices, such as TissueLyser (TL) and others ground samples manually with a micropipette (MP) [24] or pellet pestles (PP) [36]. The sample homogenization mode and quantity of mix buffer could also in uence the quality of MS spectra, altering the spectral matching with reference MS spectra from the database [32,37].…”

Section: Introductionmentioning

confidence: 99%

“…The sample homogenization mode and quantity of mix buffer could also in uence the quality of MS spectra, altering the spectral matching with reference MS spectra from the database [32,37]. Other factors such as geographical origin [30,37,38] or engorgement status [24] were also reported to induce variations in the MS spectra, which could perturb species identi cation. The absence of a consensual strategy for mosquito identi cation using MALDI-TOF MS prejudice direct inter-studies comparisons, the sharing of reference MS spectra database (DB) and brings confusion to new users.…”

Section: Introductionmentioning

confidence: 99%

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Enhanced procedures for mosquito identification by MALDI-TOF MS

Bamou

Costa

Diarra

et al. 2022

Preprint

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Background. The increasing interest in arthropod identification by MALDI-TOF MS conducted to the emergence of heterogenic procedures, including sample preparation and selection of body parts to use. The absence of a consensual strategy hampers direct inter-studies comparisons and brings confusion to new users. Establishing optimized procedures and standardized protocols for mosquito identification by MALDI-TOF MS becomes compulsory, allowing notably the sharing of reference MS databases. Objective. Then, here, we propose to assess the optimal conditions for mosquito identification using MALDI-TOF MS profiling. Methods. Three homogenization methods, two manuals and one automatic, applied on three distinct body parts, legs, thorax and head, were evaluated on two mosquito laboratory strains, Anopheles coluzzii and Aedes aegypti. MS profiles reproducibility, identification rate with relevant scores and the suitable procedures for high-throughput analyses were the main criteria for establishing optimized guidelines. Additionally, the consequences of blood feeding and geographical origin were evaluated using both laboratory strain and field collected mosquitoes. Results. The three body parts exhibited relevant score values for mosquito identification using MALDI-TOF MS profiling; however, thorax and legs appeared the most suitable, independently of homogenization methods or species. Although manual grindings displayed high identification performance for the three body parts, this homogenization mode is not adapted to process a large number of samples. Then, the automatic procedure was selected as the reference homogenization method. Blood feeding status did not hamper the identification of mosquito species, despite the presence of MS peaks from blood origin in MS profiles from three body parts tested on both species. Finally, a significant improvement in identification scores was obtained for specimens from the field when MS spectra of species from the same geographical area were added to the database. Conclusion. The present work established guidelines concerning the selection of mosquito anatomic part and modality of sample preparation (e.g., homogenization) for future specimen identification by MALDI-TOF MS profiling. These standardized operational protocols could be used as references for creating an international MS database.

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Section: Sample Homogenization For Maldi-tof Ms Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Enhanced procedures for mosquito identification by MALDI-TOF MS

Bamou

Costa

Diarra

et al. 2022

Preprint

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Artificial Intelligence and Malaria

Nabet

Acherar

Huguenin

et al. 2022

Artificial Intelligence in Medicine

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Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species

Cannet,

Simon-Chane,

Akhoundi

et al. 2023

Sci Rep

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We present a new and innovative identification method based on deep learning of the wing interferential patterns carried by mosquitoes of the Anopheles genus to classify and assign 20 Anopheles species, including 13 malaria vectors. We provide additional evidence that this approach can identify Anopheles spp. with an accuracy of up to 100% for ten out of 20 species. Although, this accuracy was moderate (> 65%) or weak (50%) for three and seven species. The accuracy of the process to discriminate cryptic or sibling species is also assessed on three species belonging to the Gambiae complex. Strikingly, An. gambiae, An. arabiensis and An. coluzzii, morphologically indistinguishable species belonging to the Gambiae complex, were distinguished with 100%, 100%, and 88% accuracy respectively. Therefore, this tool would help entomological surveys of malaria vectors and vector control implementation. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

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New assessment of Anopheles vector species identification using MALDI-TOF MS

Cited by 27 publications

References 35 publications

Enhanced procedures for mosquito identification by MALDI-TOF MS

Enhanced procedures for mosquito identification by MALDI-TOF MS

Artificial Intelligence and Malaria

Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species

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