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Mwanga EP, Siria DJ, Mshani IH, Mwinyi SH, Abbasi S, Jimenez MG, Wynne K, Baldini F, Babayan SA, Okumu FO. Rapid classification of epidemiologically relevant age categories of the malaria vector, Anopheles funestus. Parasit Vectors 2024; 17:143. [PMID: 38500231 PMCID: PMC10949582 DOI: 10.1186/s13071-024-06209-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 02/21/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Accurately determining the age and survival probabilities of adult mosquitoes is crucial for understanding parasite transmission, evaluating the effectiveness of control interventions and assessing disease risk in communities. This study was aimed at demonstrating the rapid identification of epidemiologically relevant age categories of Anopheles funestus, a major Afro-tropical malaria vector, through the innovative combination of infrared spectroscopy and machine learning, instead of the cumbersome practice of dissecting mosquito ovaries to estimate age based on parity status. METHODS Anopheles funestus larvae were collected in rural south-eastern Tanzania and reared in an insectary. Emerging adult females were sorted by age (1-16 days old) and preserved using silica gel. Polymerase chain reaction (PCR) confirmation was conducted using DNA extracted from mosquito legs to verify the presence of An. funestus and to eliminate undesired mosquitoes. Mid-infrared spectra were obtained by scanning the heads and thoraces of the mosquitoes using an attenuated total reflection-Fourier transform infrared (ATR-FT-IR) spectrometer. The spectra (N = 2084) were divided into two epidemiologically relevant age groups: 1-9 days (young, non-infectious) and 10-16 days (old, potentially infectious). The dimensionality of the spectra was reduced using principal component analysis, and then a set of machine learning and multi-layer perceptron (MLP) models were trained using the spectra to predict the mosquito age categories. RESULTS The best-performing model, XGBoost, achieved overall accuracy of 87%, with classification accuracy of 89% for young and 84% for old An. funestus. When the most important spectral features influencing the model performance were selected to train a new model, the overall accuracy increased slightly to 89%. The MLP model, utilizing the significant spectral features, achieved higher classification accuracy of 95% and 94% for the young and old An. funestus, respectively. After dimensionality reduction, the MLP achieved 93% accuracy for both age categories. CONCLUSIONS This study shows how machine learning can quickly classify epidemiologically relevant age groups of An. funestus based on their mid-infrared spectra. Having been previously applied to An. gambiae, An. arabiensis and An. coluzzii, this demonstration on An. funestus underscores the potential of this low-cost, reagent-free technique for widespread use on all the major Afro-tropical malaria vectors. Future research should demonstrate how such machine-derived age classifications in field-collected mosquitoes correlate with malaria in human populations.
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Affiliation(s)
- Emmanuel P Mwanga
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania.
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK.
| | - Doreen J Siria
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Issa H Mshani
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Sophia H Mwinyi
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Said Abbasi
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania
| | - Mario Gonzalez Jimenez
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Klaas Wynne
- School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Francesco Baldini
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Simon A Babayan
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Fredros O Okumu
- Environmental Health and Ecological Sciences Department, Ifakara Health Institute, P.O. Box 53, Morogoro, Tanzania
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Life Science and Bioengineering, The Nelson Mandela African Institution of Science and Technology, P. O. Box 447, Arusha, Tanzania
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Ferreira TN, Santos LMB, Valladares V, Flanley CM, McDowell MA, Garcia GA, Mello-Silva CC, Maciel-de-Freitas R, Genta FA. Age, sex, and mating status discrimination in the sand fly Lutzomyia longipalpis using near infra-red spectroscopy (NIRS). Parasit Vectors 2024; 17:19. [PMID: 38217054 PMCID: PMC10787389 DOI: 10.1186/s13071-023-06097-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 12/13/2023] [Indexed: 01/14/2024] Open
Abstract
BACKGROUND Understanding aspects related to the physiology and capacity of vectors is essential for effectively controlling vector-borne diseases. The sand fly Lutzomyia longipalpis has great importance in medical entomology for disseminating Leishmania parasites, the causative agent of Leishmaniasis, one of the main neglected diseases listed by the World Health Organization (WHO). In this respect, it is necessary to evaluate the transmission potential of this species and the success of vector control interventions. Near-infrared spectroscopy (NIRS) has been used to estimate the age of mosquitoes in different conditions (laboratory, semi-field, and conservation), taxonomic analysis, and infection detection. However, no studies are using NIRS for sand flies. METHODS In this study, we developed analytic models to estimate the age of L. longipalpis adults under laboratory conditions, identify their copulation state, and evaluate their gonotrophic cycle and diet. RESULTS Sand flies were classified with an accuracy of 58-82% in 3 age groups and 82-92% when separating them into young (<8 days) or old (>8 days) insects. The classification between mated and non-mated sandflies was 98-100% accurate, while the percentage of hits of females that had already passed the first gonotrophic cycle was only 59%. CONCLUSIONS We consider the age and copula estimation results very promising, as they provide essential aspects of vector capacity assessment, which can be obtained quickly and at a lower cost with NIRS.
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Affiliation(s)
- Tainá Neves Ferreira
- Laboratório de Bioquímica e Fisiologia de Insetos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Lilha M B Santos
- Laboratório de Transmissores de Hematozoários, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Vanessa Valladares
- Malacology Laboratory, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Catherine M Flanley
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - Mary Ann McDowell
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - Gabriela A Garcia
- Laboratório de Transmissores de Hematozoários, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | | | - Rafael Maciel-de-Freitas
- Laboratório de Transmissores de Hematozoários, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular, Rio de Janeiro, Brazil
| | - Fernando Ariel Genta
- Laboratório de Bioquímica e Fisiologia de Insetos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil.
- Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular, Rio de Janeiro, Brazil.
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Gao Z, Harrington LC, Zhu W, Barrientos LM, Alfonso-Parra C, Avila FW, Clark JM, He L. Accurate age-grading of field-aged mosquitoes reared under ambient conditions using surface-enhanced Raman spectroscopy and artificial neural networks. JOURNAL OF MEDICAL ENTOMOLOGY 2023; 60:917-923. [PMID: 37364175 DOI: 10.1093/jme/tjad067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/27/2023] [Accepted: 06/08/2023] [Indexed: 06/28/2023]
Abstract
Age-grading mosquitoes are significant because only older mosquitoes are competent to transmit pathogens to humans. However, we lack effective tools to do so, especially at the critical point where mosquitoes become a risk to humans. In this study, we demonstrated the capability of using surface-enhanced Raman spectroscopy and artificial neural networks to accurately age-grade field-aged low-generation (F2) female Aedes aegypti mosquitoes held under ambient conditions (error was 1.9 chronological days, in the range 0-22 days). When degree days were used for model calibration, the accuracy was further improved to 20.8 degree days (approximately equal to 1.4 chronological days), which indicates the impact of temperature fluctuation on prediction accuracy. This performance is a significant advancement over binary classification. The great accuracy of this method outperforms traditional age-grading methods and will facilitate effective epidemiological studies, risk assessment, vector intervention monitoring, and evaluation.
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Affiliation(s)
- Zili Gao
- Department of Food Science, University of Massachusetts, Amherst, MA 01003, USA
- Raman, IR and XRF Core Facility, University of Massachusetts, Amherst, MA 01003, USA
| | - Laura C Harrington
- Department of Entomology, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, USA
| | - Wei Zhu
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003, USA
| | - Luisa M Barrientos
- Max Planck Tandem Group in Mosquito Reproductive Biology, Universidad de Antioquia, Medellin, Colombia
| | - Catalina Alfonso-Parra
- Max Planck Tandem Group in Mosquito Reproductive Biology, Universidad de Antioquia, Medellin, Colombia
- Instituto Colombiano de Medicina Tropical, Universidad CES, Sabaneta, Colombia
| | - Frank W Avila
- Max Planck Tandem Group in Mosquito Reproductive Biology, Universidad de Antioquia, Medellin, Colombia
| | - John M Clark
- Department of Veterinary and Animal Sciences, University of Massachusetts, Amherst, MA 01003, USA
| | - Lili He
- Department of Food Science, University of Massachusetts, Amherst, MA 01003, USA
- Raman, IR and XRF Core Facility, University of Massachusetts, Amherst, MA 01003, USA
- Department of Chemistry, University of Massachusetts, Amherst, MA 01003, USA
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Meireles ACA, Rios FGF, Feitoza LHM, da Silva LR, Julião GR. Nondestructive Methods of Pathogen Detection: Importance of Mosquito Integrity in Studies of Disease Transmission and Control. Pathogens 2023; 12:816. [PMID: 37375506 DOI: 10.3390/pathogens12060816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/26/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023] Open
Abstract
Mosquitoes are vectors of many pathogens, including viruses, protozoans, and helminths, spreading these pathogens to humans as well as to wild and domestic animals. As the identification of species and the biological characterization of mosquito vectors are cornerstones for understanding patterns of disease transmission, and the design of control strategies, we conducted a literature review on the current use of noninvasive and nondestructive techniques for pathogen detection in mosquitoes, highlighting the importance of their taxonomic status and systematics, and some gaps in the knowledge of their vectorial capacity. Here, we summarized the alternative techniques for pathogen detection in mosquitoes based on both laboratory and field studies. Parasite infection and dissemination by mosquitoes can also be obtained via analyses of saliva- and excreta-based techniques or of the whole mosquito body, using a near-infrared spectrometry (NIRS) approach. Further research should be encouraged to seek strategies for detecting target pathogens while preserving mosquito morphology, especially in biodiversity hotspot regions, thus enabling the discovery of cryptic or new species, and the determination of more accurate taxonomic, parasitological, and epidemiological patterns.
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Affiliation(s)
- Anne Caroline Alves Meireles
- Laboratory of Entomology, Oswaldo Cruz Foundation, Fiocruz Rondônia, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
- Postgraduate Program in Biodiversity and Health, PhD in Sciences-Fiocruz Rondônia/Oswaldo Cruz Institute, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
| | - Flávia Geovana Fontineles Rios
- Laboratory of Entomology, Oswaldo Cruz Foundation, Fiocruz Rondônia, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
- Postgraduate Program in Experimental Biology-PGBIOEXP, Fiocruz Rondônia-UNIR, BR-364, Km 9.5, Porto Velho 78900-550, RO, Brazil
| | - Luiz Henrique Maciel Feitoza
- Laboratory of Entomology, Oswaldo Cruz Foundation, Fiocruz Rondônia, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
- Postgraduate Program in Experimental Biology-PGBIOEXP, Fiocruz Rondônia-UNIR, BR-364, Km 9.5, Porto Velho 78900-550, RO, Brazil
| | - Lucas Rosendo da Silva
- Laboratory of Entomology, Oswaldo Cruz Foundation, Fiocruz Rondônia, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
- Postgraduate Program in Experimental Biology-PGBIOEXP, Fiocruz Rondônia-UNIR, BR-364, Km 9.5, Porto Velho 78900-550, RO, Brazil
| | - Genimar Rebouças Julião
- Laboratory of Entomology, Oswaldo Cruz Foundation, Fiocruz Rondônia, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
- Postgraduate Program in Experimental Biology-PGBIOEXP, Fiocruz Rondônia-UNIR, BR-364, Km 9.5, Porto Velho 78900-550, RO, Brazil
- National Institute of Epidemiology of Western Amazônia-INCT-EpiAmO, Rua da Beira 7671, Lagoa, Porto Velho 76812-245, RO, Brazil
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Somé BM, Da DF, McCabe R, Djègbè NDC, Paré LIG, Wermé K, Mouline K, Lefèvre T, Ouédraogo AG, Churcher TS, Dabiré RK. Adapting field-mosquito collection techniques in a perspective of near-infrared spectroscopy implementation. Parasit Vectors 2022; 15:338. [PMID: 36163071 PMCID: PMC9513905 DOI: 10.1186/s13071-022-05458-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/27/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Near-infrared spectroscopy (NIRS) has the potential to be a useful tool for assessing key entomological parameters of malaria-transmitting mosquitoes, including age, infectious status and species identity. However, before NIRS can be reliably used in the field at scale, methods for killing mosquitoes and conserving samples prior to NIRS scanning need to be further optimized. Historically, mosquitoes used in studies have been killed with chloroform, although this approach is not without health hazards and should not be used in human dwellings. For the application of NIRS scanning it is also unclear which mosquito preservation method to use. The aim of the study reported here was to investigate the use of pyrethrum spray, a commercially available insecticide spray in Burkina Faso, for killing mosquitoes METHODS: Laboratory-reared Anopheles gambiae and Anopheles coluzzii were killed using either a pyrethrum insecticide spray routinely used in studies involving indoor mosquito collections (Kaltox Paalga®; Saphyto, Bobo-Dioulasso, Burkina Faso) or chloroform ("gold standard"). Preservative methods were also investigated to determine their impact on NIRS accuracy in predicting the species of laboratory-reared Anopheles and wild-caught mosquito species. After analysis of fresh samples, mosquitoes were stored in 80% ethanol or in silica gel for 2 weeks and re-analyzed by NIRS. In addition, experimentally infected An. coluzzii and wild-caught An. gambiae sensu lato (s.l.) were scanned as fresh samples to determine whether they contained sporozoites, then stored in the preservatives mentioned above for 2 weeks before being re-analyzed. RESULTS The difference in the accuracy of NIRS to differentiate between laboratory-reared An. gambiae mosquitoes and An. coluzzii mosquitoes killed with either insecticide (90%) or chloroform (92%) was not substantial. NIRS had an accuracy of 90% in determining mosquito species for mosquitoes killed with chloroform and preserved in ethanol or silica gel. The accuracy was the same when the pyrethrum spray was used to kill mosquitoes followed by preservation in silica gel, but was lower when ethanol was used as a preservative (80%). Regarding infection status, NIRS was able to differentiate between infected and uninfected mosquitoes, with a slightly lower accuracy for both laboratory and wild-caught mosquitoes preserved in silica gel or ethanol. CONCLUSIONS The results show that NIRS can be used to classify An. gambiae s.l. species killed by pyrethrum spray with no loss of accuracy. This insecticide may have practical advantages over chloroform for the killing of mosquitoes in NIRS analysis.
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Affiliation(s)
- Bernard Mouonniba Somé
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso ,grid.442667.50000 0004 0474 2212Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Dari F. Da
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso
| | - Ruth McCabe
- grid.7445.20000 0001 2113 8111MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, W2 1PG UK ,grid.4991.50000 0004 1936 8948Department of Statistics, University of Oxford, 24-29 St Giles, Oxford, OX1 3LB UK ,grid.10025.360000 0004 1936 8470NIHR Health Research Protection Unit in Emerging and Zoonotic Infections, University of Liverpool, The Ronald Ross Building, 8 West Derby Street, Liverpool, L69 7BE UK
| | - Nicaise Denis C. Djègbè
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso ,grid.442667.50000 0004 0474 2212Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Lawata Inès Géraldine Paré
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso ,grid.442667.50000 0004 0474 2212Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Kadidia Wermé
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso
| | - Karine Mouline
- grid.121334.60000 0001 2097 0141Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle (MIVEGEC), IRD, CNRS, Montpellier University, Montpellier, France
| | - Thierry Lefèvre
- grid.121334.60000 0001 2097 0141Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle (MIVEGEC), IRD, CNRS, Montpellier University, Montpellier, France
| | | | - Thomas S. Churcher
- grid.7445.20000 0001 2113 8111MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, W2 1PG UK
| | - Roch Kounbobr Dabiré
- grid.457337.10000 0004 0564 0509Institut de Recherche en Sciences de La Santé, Direction Régionale, 399 avenue de la liberté, 01 BP 545, Bobo-Dioulasso 01, Burkina Faso
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Highly Efficient Use of Infrared Spectroscopy (ATR-FTIR) to Identify Aphid Species. BIOLOGY 2022; 11:biology11081232. [PMID: 36009859 PMCID: PMC9404783 DOI: 10.3390/biology11081232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 08/09/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022]
Abstract
Aphids are commonly considered to be serious pests for trees, herbaceous and cultivated plants. Recognition and identification of individual species is very difficult and is based mainly on morphological features. The aims of the study were to suggest the possibility of identifying aphids through the use of Fourier-transform infrared (FTIR) spectroscopy, and to determine which absorption peaks are the most useful to separate aphid species. Using FTIR spectroscopy, based on the chemical composition of the body, we were able to distinguish 12 species of aphid. We have shown that using nine distinct peaks corresponding to the molecular vibrations from carbohydrates, lipids, amides I and II, it is possible to accurately identify aphid species with an efficiency of 98%.
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Joy T, Chen M, Arnbrister J, Williamson D, Li S, Nair S, Brophy M, Garcia VM, Walker K, Ernst K, Gouge DH, Carrière Y, Riehle MA. Assessing Near-Infrared Spectroscopy (NIRS) for Evaluation of Aedes aegypti Population Age Structure. INSECTS 2022; 13:insects13040360. [PMID: 35447802 PMCID: PMC9029691 DOI: 10.3390/insects13040360] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 04/03/2022] [Accepted: 04/05/2022] [Indexed: 02/04/2023]
Abstract
Given that older Aedes aegypti (L.) mosquitoes typically pose the greatest risk of pathogen transmission, the capacity to age grade wild Ae. aegypti mosquito populations would be a valuable tool in monitoring the potential risk of arboviral transmission. Here, we compared the effectiveness of near-infrared spectroscopy (NIRS) to age grade field-collected Ae. aegypti with two alternative techniques—parity analysis and transcript abundance of the age-associated gene SCP1. Using lab-reared mosquitoes of known ages from three distinct populations maintained as adults under laboratory or semi-field conditions, we developed and validated four NIRS models for predicting the age of field-collected Ae. aegypti. To assess the accuracy of these models, female Ae. aegypti mosquitoes were collected from Maricopa County, AZ, during the 2017 and 2018 monsoon season, and a subset were age graded using the three different age-grading techniques. For both years, each of the four NIRS models consistently graded parous mosquitoes as significantly older than nulliparous mosquitoes. Furthermore, a significant positive linear association occurred between SCP1 and NIRS age predictions in seven of the eight year/model combinations, although considerable variation in the predicted age of individual mosquitoes was observed. Our results suggest that although the NIRS models were not adequate in determining the age of individual field-collected mosquitoes, they have the potential to quickly and cost effectively track changes in the age structure of Ae. aegypti populations across locations and over time.
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Affiliation(s)
- Teresa Joy
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Minhao Chen
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Joshua Arnbrister
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Daniel Williamson
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Shujuan Li
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Shakunthala Nair
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Maureen Brophy
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Valerie Madera Garcia
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85724, USA; (V.M.G.); (K.E.)
| | - Kathleen Walker
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Kacey Ernst
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85724, USA; (V.M.G.); (K.E.)
| | - Dawn H. Gouge
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Yves Carrière
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
| | - Michael A. Riehle
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA; (T.J.); (M.C.); (J.A.); (D.W.); (S.L.); (S.N.); (M.B.); (K.W.); (D.H.G.); (Y.C.)
- Correspondence: ; Tel.: +1-520-626-8500
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Weeraratne TC, Karunaratne SHPP, Reimer L, de Silva WAPP, Wondji CS. Use of transcriptional age grading technique to determine the chronological age of Sri Lankan Aedes aegypti and Aedes albopictus females. Parasit Vectors 2021; 14:493. [PMID: 34565445 PMCID: PMC8474866 DOI: 10.1186/s13071-021-04994-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 09/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Aedes aegypti and Ae. albopictus are important vectors of human diseases such as dengue, chikungunya, and zika. In Sri Lanka, they have been responsible for transmitting dengue virus. One of the most important parameters influencing the likelihood of arbovirus transmission is the age structure of the mosquito population. However, mosquito age is difficult to measure with accuracy. This study aims to construct multivariate calibration models using the transcriptional abundance of three age-responsive genes: Ae15848 (calcium-binding protein), Ae8505 (structural component of cuticle), and Ae4274 (fizzy cell cycle/cell division cycle 20). METHODS The transcriptional age-grading technique was applied to determine the chronological age of Ae. aegypti and Ae. albopictus female mosquito populations from Sri Lanka using the age-responsive genes Ae15848, Ae8505, and Ae4274. Furthermore, Ae. aegypti samples obtained from colonies reared at two temperatures (23 and 27 °C) were used to investigate the influence of temperature on this age-grading technique. Expression levels of these three genes were quantified using reverse transcription qualitative PCR (qRT-PCR), and results were normalized against the housekeeping gene ribosomal gene S17 (RpS17). RESULTS The expression of Ae15848 and Ae8505 decreased with the age of mosquitoes and showed the most significant and consistent change while expression of Ae4274 increased with age. The multivariate calibration models showed > 80% correlation between expression of these age-responsive genes and the age of female mosquitoes at both temperatures. At 27 °C the accuracy of age predictions using the models was 2.19 (± 1.66) days and 2.58 (± 2.06) days for Ae. aegypti and Ae. albopictus females, respectively. The accuracy of the model for Ae. aegypti at 23 °C was 3.42 (± 2.74) days. CONCLUSIONS An adult rearing temperature difference of 4 °C (23-27 °C) did not significantly affect the age predictions. The calibration models created during this study could be successfully used to estimate the age of wild Ae. aegypti and Ae. albopictus mosquitoes from Sri Lanka.
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Affiliation(s)
| | | | - Lisa Reimer
- Vector Biology Department, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK
| | | | - Charles S Wondji
- Vector Biology Department, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.,Medical Entomology Department, Centre for Research in Infectious Diseases (CRID), Yaoundé, Cameroon
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Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy. Sci Rep 2021; 11:10289. [PMID: 33986416 PMCID: PMC8119679 DOI: 10.1038/s41598-021-89715-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 04/21/2021] [Indexed: 11/18/2022] Open
Abstract
There is an urgent need for high throughput, affordable methods of detecting pathogens inside insect vectors to facilitate surveillance. Near-infrared spectroscopy (NIRS) has shown promise to detect arbovirus and malaria in the laboratory but has not been evaluated in field conditions. Here we investigate the ability of NIRS to identify Plasmodium falciparum in Anopheles coluzzii mosquitoes. NIRS models trained on laboratory-reared mosquitoes infected with wild malaria parasites can detect the parasite in comparable mosquitoes with moderate accuracy though fails to detect oocysts or sporozoites in naturally infected field caught mosquitoes. Models trained on field mosquitoes were unable to predict the infection status of other field mosquitoes. Restricting analyses to mosquitoes of uninfectious and highly-infectious status did improve predictions suggesting sensitivity and specificity may be better in mosquitoes with higher numbers of parasites. Detection of infection appears restricted to homogenous groups of mosquitoes diminishing NIRS utility for detecting malaria within mosquitoes.
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10
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Goh B, Ching K, Soares Magalhães RJ, Ciocchetta S, Edstein MD, Maciel-de-Freitas R, Sikulu-Lord MT. The application of spectroscopy techniques for diagnosis of malaria parasites and arboviruses and surveillance of mosquito vectors: A systematic review and critical appraisal of evidence. PLoS Negl Trop Dis 2021; 15:e0009218. [PMID: 33886567 PMCID: PMC8061870 DOI: 10.1371/journal.pntd.0009218] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
CONCLUSIONS/SIGNIFICANCE The potential of RS as a surveillance tool for malaria and arbovirus vectors and MIRS for the diagnosis and surveillance of arboviruses is yet to be assessed. NIRS capacity as a surveillance tool for malaria and arbovirus vectors should be validated under field conditions, and its potential as a diagnostic tool for malaria and arboviruses needs to be evaluated. It is recommended that all 3 techniques evaluated simultaneously using multiple machine learning techniques in multiple epidemiological settings to determine the most accurate technique for each application. Prior to their field application, a standardised protocol for spectra collection and data analysis should be developed. This will harmonise their application in multiple field settings allowing easy and faster integration into existing disease control platforms. Ultimately, development of rapid and cost-effective point-of-care diagnostic tools for malaria and arboviruses based on spectroscopy techniques may help combat current and future outbreaks of these infectious diseases.
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Affiliation(s)
- Brendon Goh
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Koek Ching
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Ricardo J Soares Magalhães
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia
- Children's Health Research Centre, Children's Health and Environment Program, The University of Queensland, Brisbane, Australia
| | - Silvia Ciocchetta
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia
| | - Michael D Edstein
- Australian Defence Force, Malaria and Infectious Disease Institute, Brisbane, Australia
| | | | - Maggy T Sikulu-Lord
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
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