Rapid and non-destructive identification of Anopheles gambiae and Anopheles arabiensis mosquito species using Raman spectroscopy via machine learning classification models.
Anopheles arabiensis
Anopheles gambiae
Discriminant Analysis
Logistic Regression
Machine learning
Melanin
Mosquito
Mosquito identification
Raman spectroscopy
Support Vector Machine
Journal
Malaria journal
ISSN: 1475-2875
Titre abrégé: Malar J
Pays: England
ID NLM: 101139802
Informations de publication
Date de publication:
08 Nov 2023
08 Nov 2023
Historique:
received:
26
07
2023
accepted:
31
10
2023
medline:
10
11
2023
pubmed:
9
11
2023
entrez:
8
11
2023
Statut:
epublish
Résumé
Identification of malaria vectors is an important exercise that can result in the deployment of targeted control measures and monitoring the susceptibility of the vectors to control strategies. Although known to possess distinct biting behaviours and habitats, the African malaria vectors Anopheles gambiae and Anopheles arabiensis are morphologically indistinguishable and are known to be discriminated by molecular techniques. In this paper, Raman spectroscopy is proposed to complement the tedious and time-consuming Polymerase Chain Reaction (PCR) method for the rapid screening of mosquito identity. A dispersive Raman microscope was used to record spectra from the legs (femurs and tibiae) of fresh anaesthetized laboratory-bred mosquitoes. The scattered Raman intensity signal peaks observed were predominantly centered at approximately 1400 cm PCA extracted twenty-one features accounting for 95% of the variation in the data. Using the twenty-one principal components, LDA, LR, QDA, and QSVM discriminated and classified the two cryptic species with 86%, 85%, 89%, and 93% accuracy, respectively on cross-validation and 79%, 82%, 81% and 93% respectively on the test data set. Raman spectroscopy in combination with machine learning tools is an effective, rapid and non-destructive method for discriminating and classifying two cryptic mosquito species, Anopheles gambiae and Anopheles arabiensis belonging to the Anopheles gambiae complex.
Sections du résumé
BACKGROUND
BACKGROUND
Identification of malaria vectors is an important exercise that can result in the deployment of targeted control measures and monitoring the susceptibility of the vectors to control strategies. Although known to possess distinct biting behaviours and habitats, the African malaria vectors Anopheles gambiae and Anopheles arabiensis are morphologically indistinguishable and are known to be discriminated by molecular techniques. In this paper, Raman spectroscopy is proposed to complement the tedious and time-consuming Polymerase Chain Reaction (PCR) method for the rapid screening of mosquito identity.
METHODS
METHODS
A dispersive Raman microscope was used to record spectra from the legs (femurs and tibiae) of fresh anaesthetized laboratory-bred mosquitoes. The scattered Raman intensity signal peaks observed were predominantly centered at approximately 1400 cm
RESULTS
RESULTS
PCA extracted twenty-one features accounting for 95% of the variation in the data. Using the twenty-one principal components, LDA, LR, QDA, and QSVM discriminated and classified the two cryptic species with 86%, 85%, 89%, and 93% accuracy, respectively on cross-validation and 79%, 82%, 81% and 93% respectively on the test data set.
CONCLUSION
CONCLUSIONS
Raman spectroscopy in combination with machine learning tools is an effective, rapid and non-destructive method for discriminating and classifying two cryptic mosquito species, Anopheles gambiae and Anopheles arabiensis belonging to the Anopheles gambiae complex.
Identifiants
pubmed: 37940964
doi: 10.1186/s12936-023-04777-y
pii: 10.1186/s12936-023-04777-y
pmc: PMC10634188
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
342Subventions
Organisme : Swedish International Development Cooperation Agency (SIDA), through the International Science Programme (ISP), Uppsala University.
ID : IPPS KEN:04
Organisme : Swedish International Development Cooperation Agency (SIDA), through the International Science Programme (ISP), Uppsala University.
ID : IPPS KEN:04
Organisme : Swedish International Development Cooperation Agency (SIDA), through the International Science Programme (ISP), Uppsala University.
ID : IPPS KEN:04
Informations de copyright
© 2023. The Author(s).
Références
Parasitol Res. 2014 Jun;113(6):2375-8
pubmed: 24737398
Malar J. 2007 Feb 27;6:23
pubmed: 17326831
PLoS Negl Trop Dis. 2016 Jun 30;10(6):e0004759
pubmed: 27362709
Zootaxa. 2013;3619:246-74
pubmed: 26131476
Trans R Soc Trop Med Hyg. 1979;73(5):483-97
pubmed: 394408
Malar J. 2016 Apr 19;15:225
pubmed: 27093890
Malar J. 2020 Feb 24;19(1):89
pubmed: 32093677
Nat Rev Microbiol. 2020 Mar;18(3):177-189
pubmed: 31919479
Malar J. 2017 Sep 15;16(1):373
pubmed: 28915892
PeerJ. 2015 Sep 15;3:e991
pubmed: 26734510
Malar J. 2007 Nov 22;6:155
pubmed: 18034887
Am J Trop Med Hyg. 2009 Oct;81(4):622-30
pubmed: 19815877
PeerJ. 2017 May 24;5:e3300
pubmed: 28560094
Wellcome Open Res. 2019 May 1;4:76
pubmed: 31544155
Fly (Austin). 2012 Oct-Dec;6(4):284-9
pubmed: 22885252
Pigment Cell Melanoma Res. 2015 Sep;28(5):599-602
pubmed: 26176957
Proc Biol Sci. 1998 May 22;265(1399):847-54
pubmed: 9633110
Parasitol Today. 2000 Feb;16(2):74-7
pubmed: 10652493
BMC Bioinformatics. 2023 Jan 9;24(1):11
pubmed: 36624386
Nat Protoc. 2020 Jul;15(7):2143-2162
pubmed: 32555465
Science. 1980 Mar 7;207(4435):1089-91
pubmed: 7355276
Malar J. 2020 Jun 16;19(1):207
pubmed: 32546166
Malar J. 2023 Nov 8;22(1):342
pubmed: 37940964
Parasit Vectors. 2015 Jan 27;8:60
pubmed: 25623484
Appl Spectrosc. 2007 Nov;61(11):1225-32
pubmed: 18028702
Med Vet Entomol. 1987 Apr;1(2):127-36
pubmed: 2979526
J Biomed Opt. 2004 Nov-Dec;9(6):1198-205
pubmed: 15568940
Parasit Vectors. 2014 Dec 12;7:569
pubmed: 25498759
PLoS One. 2012;7(10):e47051
pubmed: 23071708
F1000Res. 2016 Aug 11;5:1949
pubmed: 27703667
Nat Commun. 2022 Mar 21;13(1):1501
pubmed: 35314683
Spectrochim Acta A Mol Biomol Spectrosc. 2013 Jun;110:55-9
pubmed: 23563634
Arthropod Struct Dev. 2016 Jul;45(4):311-9
pubmed: 27224206
PLoS One. 2013;8(2):e57486
pubmed: 23469000
J Exp Biol. 2015 Nov;218(Pt 22):3632-5
pubmed: 26449977
Sci Rep. 2015 Dec 16;5:18447
pubmed: 26669666
Med Vet Entomol. 1990 Oct;4(4):367-73
pubmed: 2133004
J Med Entomol. 1998 Jan;35(1):16-25
pubmed: 9542341
Malar J. 2012 Jul 16;11:232
pubmed: 22799568
Med Vet Entomol. 2002 Dec;16(4):461-4
pubmed: 12510902
Front Microbiol. 2019 May 29;10:1155
pubmed: 31191483
PLoS One. 2013 Aug 15;8(8):e72380
pubmed: 23977292
Malar J. 2016 Feb 09;15:76
pubmed: 26857915
J Biomol Tech. 2013 Apr;24(1):1-7
pubmed: 23543777