Proteomic changes occurring in the malaria mosquitoes Anopheles gambiae and Anopheles stephensi during aging

Sikulu-Lord, Maggy T.; Monkman, James; Dave, Keyur A.; Hastie, Marcus L.; Dale, Patricia Ellen; Kitching, R. L.; Killeen, Gerry F.; Kay, Brian H.; Gorman, Jeffery J.; Hugo, Leon E.

doi:10.1016/j.jprot.2015.06.008

Cited by 33 publications

(24 citation statements)

References 44 publications

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“…Here, visible and NIR light (wavelength 400-2500 nanometers) is passed through the whole or part of a mosquito specimen and an absorbance spectrum is collected instantly without destroying the sample. Changes in spectral peaks at different wavelengths represent how intensely different molecules absorb light, and thus NIR spectra of mosquitoes are determined by the biochemical composition of their tissues, which are known to differ according to age [14, 15], species [16, 17], microbiome [18], physiological stage [19, 20], and by pathogen infection [20, 21]. Differences in NIR spectra have been used to distinguish young (e.g.…”

Section: Introductionmentioning

confidence: 99%

Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

Maia

Kapulu

Muthui

et al. 2019

Preprint

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23Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne 24 disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-25 effective and high-throughput tools for mass-screening of vectors. This study demonstrates proof-of-26 concept that near-infrared spectroscopy (NIRS) is capable of rapidly identifying laboratory strains of 27 human malaria infection in African mosquito vectors. By using partial least square regression models 28 based on malaria-infected and uninfected Anopheles gambiae mosquitoes, we showed that NIRS can 29 detect oocyst-and sporozoite-stage Plasmodium falciparum infections with 88% and 95% accuracy, 30 respectively. Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS 31 could revolutionize surveillance and elimination strategies for the most important human malaria 32 parasite in its primary African vector species. Further research is needed to evaluate how the method 33 performs in the field following adjustments in the training datasets to include data from wild-caught 34 infected and uninfected mosquitoes. 35 36 Introduction 37 Malaria is holding back development in endemic countries and remains one of the leading causes of 38 death in children under 5 years-old in sub-Saharan Africa [1-3]. During the past decade, the large-scale 39 roll-out of long-lasting insecticide treated nets and indoor residual spraying across Africa has resulted in 40 a substantial reduction in malaria cases [4]. The WHO's Global Technical Strategy for Malaria 2016-41 2030 seeks to reduce malaria incidence and related mortality by at least 90% and to eliminate the 42 disease in a minimum of 35 countries [1]. These bold goals will require new interventions that can 43 address residual malaria transmission as well as new tools to better monitor their impact on vector-44 borne disease transmission. Mosquito surveillance is a cornerstone of the control of malaria and other 45vector-borne diseases [5]. However, presently, there is no high-throughput, cost-efficient method to 46 identify Plasmodium infection and infectiousness in mosquitoes. Molecular methods such as ELISA and 47PCR are used to determine parasite infection, but these are expensive and laborious [6][7][8], challenging 48 resource-poor countries with few funds and limited access to reagents and equipment, and thus are 49 unsuitable for large-scale surveillance. A further complication is that typically only 1-2% of mosquitoes 50 may be infected with transmission stage parasites (sporozoites), meaning that very large sample sizes 51 must be tested to accurately quantify site and time-specific estimates of mosquito infection rates as will 52 be required to assess progress towards malaria elimination [9]. 54Recent advances indicate several mosquito traits can be accurately identified through analysis of their 55 tissues with near infrared spectroscopy (NIRS) [10][11][12][13] . Here, visible and NIR light (wavelength 400-56 2500 nanometers) ...

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Section: Introductionmentioning

confidence: 99%

Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

Maia

Kapulu

Muthui

et al. 2019

Preprint

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“…Ion selector resolution was set at 0.5% of the mass of the precursor ion [6] . All protein spots identified by MALDI-TOF/TOF mass spectrometry are reported in our accompanying manuscript [1] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…For public access, mass spectrometry raw data are available via ProteomeXchange with identifier PXD002153. A detailed description of this study has been described elsewhere [1] .…”

mentioning

confidence: 99%

Mass spectrometry identification of age-associated proteins from the malaria mosquitoes Anopheles gambiae s.s. and Anopheles stephensi

et al. 2015

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This study investigated proteomic changes occurring in Anopheles gambiae and Anopheles stephensi during adult mosquito aging. These changes were evaluated using two-dimensional difference gel electrophoresis (2D-DIGE) and the identities of aging related proteins were determined using capillary high-pressure liquid chromatography (capHPLC) coupled with a linear ion-trap (LTQ)-Orbitrap XL hybrid mass spectrometry (MS). Here, we have described the techniques used to determine age associated proteomic changes occurring in heads and thoraces across three age groups; 1, 9 and 17 d old A. gambiae and 4 age groups; 1, 9, 17 and 34 d old A. stephensi. We have provided normalised spot volume raw data for all protein spots that were visible on 2D-DIGE images for both species and processed Orbitrap mass spectrometry data. For public access, mass spectrometry raw data are available via ProteomeXchange with identifier PXD002153. A detailed description of this study has been described elsewhere [1].

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“…For example, age-related changes in protein concentrations are seen in mosquitoes [84], honeybees [85], sea urchins [86], and macaque hearts [87], and age-related longitudinal changes in metabolites have been measured in the common marmoset [88]. In addition, metabolite concentrations are correlated with longevity across 26 mammalian species [89], leading to new insights into how metabolite concentrations change across species with highly variable lifespans.…”

Section: Proteomics and Metabolomics As Ageing Biomarkersmentioning

confidence: 99%

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

Hoffman

Lyu

Pletcher

et al. 2017

Essays in Biochemistry

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Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible ‘biomarkers’, which are predictors of one’s biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying ‘endophenotypes’ in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

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Proteomic changes occurring in the malaria mosquitoes Anopheles gambiae and Anopheles stephensi during aging

Cited by 33 publications

References 44 publications

Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

Mass spectrometry identification of age-associated proteins from the malaria mosquitoes Anopheles gambiae s.s. and Anopheles stephensi

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

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