Evidence map›Paper›PMID 30902057›Full record

ArticleMalaria journal2019

Application of matrix-assisted laser desorption/ionization mass spectrometry to identify species of Neotropical Anopheles vectors of malaria.

Jose R Loaiza, Alejandro Almanza, Juan C Rojas, Luis Mejía, Norma D Cervantes, Javier E Sanchez-Galan, Fernando Merchán, Arnaud Grillet, Matthew J Miller, Luis F De León and 1 more

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 8 institutions in 3 countries.

Jose R LoaizaCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.ORCID http://orcid.org/0000-0001-5195-8540
Alejandro AlmanzaCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.
Juan C RojasCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.
Luis MejíaCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.
Norma D CervantesCollege of Health Sciences, The University of Texas at El Paso, El Paso, TX, USA.
Javier E Sanchez-GalanCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.
Fernando MerchánGrupo de Investigación en Sistemas de Comunicaciones Digitales Avanzados, Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Panamá, Panama, Republic of Panama.
Arnaud GrilletGrupo de Investigación en Sistemas de Comunicaciones Digitales Avanzados, Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Panamá, Panama, Republic of Panama.
Matthew J MillerSam Noble Oklahoma Museum of Natural History and Department of Biology, University of Oklahoma, Norman, OK, USA.
Luis F De LeónCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama.
Rolando A GittensCentro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama, 0843-01103, Republic of Panama. rgittens@indicasat.org.pa.ORCID http://orcid.org/0000-0002-0286-3956
Instituto de Investigaciones Científicas y Servicios de Alta Tecnología · PAUniversidad de Panamá · PAInstitut Polytechnique de Bordeaux · FRSmithsonian Tropical Research Institute · PAThe University of Texas at El Paso · USUniversidad Tecnológica de Panamá · PAUniversity of Massachusetts Boston · USUniversity of Oklahoma · US

Funding

U.S. Mexico Interdisciplinary Research Training ProgramT37MD001376 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI DUARTE-GARDEA, MARIA O. · 2005 to 2018
$3.2M
EPA EP-C-15-002EPA EP-D-15-016NIMHD NIH HHS T37 MD001376Secretaría Nacional de Ciencia, Tecnología e Innovación GRID15-002Secretaría Nacional de Ciencia, Tecnología e Innovación SNI 05-2016Secretaría Nacional de Ciencia, Tecnología e Innovación SNI 146-2017Secretaría Nacional de Ciencia, Tecnología e Innovación SNI 157-2017Secretaría Nacional de Ciencia, Tecnología e Innovación SNI 91-2015
6 · The paper itself

Abstract

backgroundMalaria control in Panama is problematic due to the high diversity of morphologically similar Anopheles mosquito species, which makes identification of vectors of human Plasmodium challenging. Strategies by Panamanian health authorities to bring malaria under control targeting Anopheles vectors could be ineffective if they tackle a misidentified species.

methodsA rapid mass spectrometry identification procedure was developed to accurately and timely sort out field-collected Neotropical Anopheles mosquitoes into vector and non-vector species. Matrix-assisted laser desorption/ionization (MALDI) mass spectra of highly-abundant proteins were generated from laboratory-reared mosquitoes using different extraction protocols, body parts, and sexes to minimize the amount of material from specimen vouchers needed and optimize the protocol for taxonomic identification. Subsequently, the mass spectra of field-collected Neotropical Anopheles mosquito species were classified using a combination of custom-made unsupervised (i.e., Principal component analysis-PCA) and supervised (i.e., Linear discriminant analysis-LDA) classification algorithms.

resultsRegardless of the protocol used or the mosquito species and sex, the legs contained the least intra-specific variability with enough well-preserved proteins to differentiate among distinct biological species, consistent with previous literature. After minimizing the amount of material needed from the voucher, one leg was enough to produce reliable spectra between specimens. Further, both PCA and LDA were able to classify up to 12 mosquito species, from different subgenera and seven geographically spread localities across Panama using mass spectra from one leg pair. LDA demonstrated high discriminatory power and consistency, with validation and cross-validation positive identification rates above 93% at the species level.

conclusionThe selected sample processing procedure can be used to identify field-collected Anopheles species, including vectors of Plasmodium, in a short period of time, with a minimal amount of tissue and without the need of an expert mosquito taxonomist. This strategy to analyse protein spectra overcomes the drawbacks of working without a reference library to classify unknown samples. Finally, this MALDI approach can aid ongoing malaria eradication efforts in Panama and other countries with large number of mosquito's species by improving vector surveillance in epidemic-prone sites such as indigenous Comarcas.

Indexed as

AnimalsAnophelesMalariaMosquito VectorsPanamaPlasmodiumSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationAnopheles mosquitoMalaria vectorMALDIMass spectrometryPanamaTaxonomic identification

Identifiers

PMID30902057
PMCPMC6431007
OpenAlexW2942450864

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.