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

Utility of MALDI-TOF MS for determination of species identity and blood meal sources of primary malaria vectors on the Kenyan coast

Background

Protein analysis using matrix-assisted laser desorption/ionisation time-of-flight mass-spectrometry (MALDI-TOF MS) represents a promising tool for entomological surveillance. In this study we tested the discriminative power of this tool for measuring species and blood meal source of main Afrotropical malaria vectors on the Kenyan coast.

Methods

Mosquito collections were conducted along the coastal region of Kenya. MALDI-TOF MS spectra were obtained from each individual mosquito's cephalothorax as well as the abdomens of blood-engorged mosquitoes. The same mosquitoes were also processed using gold standard tests: polymerase chain reaction (PCR) for species identification and enzyme linked immunosorbent assay (ELISA) for blood meal source identification.

Results

Of the 2,332 mosquitoes subjected to MALDI-TOF MS, 85% (1,971/2,332) were considered for database creation and validation. There was an overall accuracy of 97.5% in the identification of members of the An. gambiae ( An. gambiae, 100%; An. arabiensis, 91.9%; An. merus, 97.5%; and An. quadriannulatus, 90.2%) and An. funestus ( An. funestus, 94.2%; An. rivulorum, 99.4%; and An. leesoni, 94.1%) complexes. Furthermore, MALDI-TOF MS also provided accurate (94.5% accuracy) identification of blood host sources across all mosquito species.

Conclusions

This study provides further evidence of the discriminative power of MALDI-TOF MS to identify sibling species and blood meal source of Afrotropical malaria vectors, further supporting its utility in entomological surveillance. The low cost per sample (<0.2USD) and high throughput nature of the method represents a cost-effective alternative to molecular methods and could enable programs to increase the number of samples analysed and therefore improve the data generated from surveillance activities.

Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

Utility of MALDI-TOF MS for determination of species identity and blood meal sources of primary malaria vectors on the Kenyan coast

Background: Protein analysis using matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) represents a promising tool for entomological surveillance. In this study we tested the discriminative power of this tool for measuring species and blood meal source of main Afrotropical malaria vectors on the Kenyan coast. Methods: Mosquito collections were conducted along the coastal region of Kenya. MALDI-TOF MS spectra were obtained from each individual mosquito’s cephalothorax as well as the abdomens of blood-engorged mosquitoes. The same mosquitoes were also processed using gold standard tests: polymerase chain reaction (PCR) for species identification and enzyme linked immunosorbent assay (ELISA) for blood meal source identification. Results: Of the 2,332 mosquitoes subjected to MALDI-TOF MS, 85% (1,971/2,332) were considered for database creation and validation. There was an overall accuracy of 97.5% in the identification of members of the An. gambiae (An. gambiae, 100%; An. arabiensis, 91.9%; An. merus, 97.5%; and An. quadriannulatus, 90.2%) and An. funestus (An. funestus, 94.2%; An. rivulorum, 99.4%; and An. leesoni, 94.1%) complexes. Furthermore, MALDI-TOF MS also provided accurate (94.5% accuracy) identification of blood host sources across all mosquito species. Conclusions: This study provides further evidence of the discriminative power of MALDI-TOF MS to identify sibling species and blood meal source of Afrotropical malaria vectors, further supporting its utility in entomological surveillance. The low cost per sample (<0.2USD) and high throughput nature of the method represents a cost-effective alternative to molecular methods and could enable programs to increase the number of samples analysed and therefore improve the data generated from surveillance activities.

Rapid identification of mosquito species and age by mass spectrometric analysis

BACKGROUND

A rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.

RESULTS

The accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5-6 days, 14-15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.

CONCLUSIONS

The accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.

Back to the Future: Quantifying Wing Wear as a Method to Measure Mosquito Age

Vector biologists have long sought the ability to accurately quantify the age of wild mosquito populations, a metric used to measure vector control efficiency. This has proven difficult due to the difficulties of working in the field and the biological complexities of wild mosquitoes. Ideal age grading techniques must overcome both challenges while also providing epidemiologically relevant age measurements. Given these requirements, the Detinova parity technique, which estimates age from the mosquito ovary and tracheole skein morphology, has been most often used for mosquito age grading despite significant limitations, including being based solely on the physiology of ovarian development. Here, we have developed a modernized version of the original mosquito aging method that evaluated wing wear, expanding it to estimate mosquito chronological age from wing scale loss. We conducted laboratory experiments using adult Anopheles gambiae held in insectary cages or mesocosms, the latter of which also featured ivermectin bloodmeal treatments to change the population age structure. Mosquitoes were age graded by parity assessments and both human- and computational-based wing evaluations. Although the Detinova technique was not able to detect differences in age population structure between treated and control mesocosms, significant differences were apparent using the wing scale technique. Analysis of wing images using averaged left- and right-wing pixel intensity scores predicted mosquito age at high accuracy (overall test accuracy: 83.4%, average training accuracy: 89.7%). This suggests that this technique could be an accurate and practical tool for mosquito age grading though further evaluation in wild mosquito populations is required.

Time Flies-Age Grading of Adult Flies for the Estimation of the Post-Mortem Interval

The estimation of the minimum time since death is one of the main applications of forensic entomology. This can be done by calculating the age of the immature stage of necrophagous flies developing on the corpse, which is confined to approximately 2–4 weeks, depending on temperature and species of the first colonizing wave of flies. Adding the age of the adult flies developed on the dead body could extend this time frame up to several weeks when the body is in a building or closed premise. However, the techniques for accurately estimating the age of adult flies are still in their beginning stages or not sufficiently validated. Here we review the current state of the art of analysing the aging of flies by evaluating the ovarian development, the amount of pteridine in the eyes, the degree of wing damage, the modification of their cuticular hydrocarbon patterns, and the increasing number of growth layers in the cuticula. New approaches, including the use of age specific molecular profiles based on the levels of gene and protein expression and the application of near infrared spectroscopy, are introduced, and the forensic relevance of these methods is discussed.

Prediction of malaria transmission drivers in Anopheles mosquitoes using artificial intelligence coupled to MALDI-TOF mass spectrometry

Vector control programmes are a strategic priority in the fight against malaria. However, vector control interventions require rigorous monitoring. Entomological tools for characterizing malaria transmission drivers are limited and are difficult to establish in the field. To predict Anopheles drivers of malaria transmission, such as mosquito age, blood feeding and Plasmodium infection, we evaluated artificial neural networks (ANNs) coupled to matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) and analysed the impact on the proteome of laboratory-reared Anopheles stephensi mosquitoes. ANNs were sensitive to Anopheles proteome changes and specifically recognized spectral patterns associated with mosquito age (0–10 days, 11–20 days and 21–28 days), blood feeding and P. berghei infection, with best prediction accuracies of 73%, 89% and 78%, respectively. This study illustrates that MALDI-TOF MS coupled to ANNs can be used to predict entomological drivers of malaria transmission, providing potential new tools for vector control. Future studies must assess the field validity of this new approach in wild-caught adult Anopheles. A similar approach could be envisaged for the identification of blood meal source and the detection of insecticide resistance in Anopheles and to other arthropods and pathogens.

Mosquito Age Grading and Vector-Control Programmes

An ability to characterize the age of mosquito populations could provide cost-effective and compelling entomological evidence for the potential epidemiological impacts of vector control. The average age of a mosquito population is the most important determinant of vectorial capacity and the likelihood of disease transmission. Yet, despite decades of research, defining the age of a wild-caught mosquito remains a challenging, impractical, and unreliable process. Emerging chemometric and existing transcriptional approaches may overcome many of the limitations of current morphological techniques, but their utility in terms of field-based monitoring programmes remains largely untested. Herein, we review the potential advantages and disadvantages of new and existing age-grading tools in an operational context.

Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks

Background

Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier.

Methods and findings

We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers.

Conclusion

We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier.

Genome annotation improvements from cross-phyla proteogenomics and time-of-day differences in malaria mosquito proteins using untargeted quantitative proteomics

The malaria mosquito, Anopheles stephensi, and other mosquitoes modulate their biology to match the time-of-day. In the present work, we used a non-hypothesis driven approach (untargeted proteomics) to identify proteins in mosquito tissue, and then quantified the relative abundance of the identified proteins from An. stephensi bodies. Using these quantified protein levels, we then analyzed the data for proteins that were only detectable at certain times-of-the day, highlighting the need to consider time-of-day in experimental design. Further, we extended our time-of-day analysis to look for proteins which cycle in a rhythmic 24-hour ("circadian") manner, identifying 31 rhythmic proteins. Finally, to maximize the utility of our data, we performed a proteogenomic analysis to improve the genome annotation of An. stephensi. We compare peptides that were detected using mass spectrometry but are 'missing' from the An. stephensi predicted proteome, to reference proteomes from 38 other primarily human disease vector species. We found 239 such peptide matches and reveal that genome annotation can be improved using proteogenomic analysis from taxonomically diverse reference proteomes. Examination of 'missing' peptides revealed reading frame errors, errors in gene-calling, overlapping gene models, and suspected gaps in the genome assembly.

Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy

BACKGROUND

Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors.

METHODS

A total of 750 Anopheles gambiae (Keele strain) mosquitoes were fed Plasmodium falciparum NF54 gametocytes through standard membrane feeding assay (SMFA) and afterwards maintained in insectary conditions to allow for oocyst (8 days) and sporozoite development (14 days). Thereupon, each mosquito was scanned using near infra-red spectroscopy (NIRS) and processed by quantitative polymerase chain reaction (qPCR) to determine the presence of infection and infection load. The spectra collected were randomly assigned to either a training dataset, used to develop calibrations for predicting oocyst- or sporozoite-infection through partial least square regressions (PLS); or to a test dataset, used for validating the calibration's prediction accuracy.

RESULTS

NIRS detected oocyst- and sporozoite-stage P. falciparum infections with 88% and 95% accuracy, respectively. This study demonstrates proof-of-concept that NIRS is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors.

CONCLUSIONS

Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes.

Integrated proteome analyses of wheat glume and awn reveal central drought response proteins under water deficit conditions

Integrated proteome analyses revealed differentially accumulated proteins in the non-leaf green organs in wheat glume and awn that play important roles in photosynthesis and drought resistance. Two non-leaf green organs in wheat, glume and awn, have photosynthetic potential, contribute to grain yield, and also play roles in resistance to adverse conditions. We performed the first integrated proteome analysis of wheat glume and awn in response to water deficit. Water deficit caused a significant decrease in important agronomic traits and grain yield. A total of 120 and 77 differentially accumulated protein (DAP) spots, representing 100 and 67 unique proteins responsive to water deficit, were identified by two-dimensional difference gel electrophoresis (2D-DIGE) in glumes and awns, respectively, of the elite Chinese bread wheat cultivar Zhongmai 175. The DAPs of both organs showed similar functional classification and proportion and were mainly involved in photosynthesis, detoxification/defense, carbon/energy metabolism, and proteometabolism. Comparative proteome analyses revealed many more drought-responsive DAP spots in glumes than in awns, which indicate that glumes underwent more proteome changes in response to water deficit. The main DAPs involved in photosynthesis and carbon metabolism were significantly downregulated, whereas those related to detoxification/defense and energy metabolism were markedly upregulated under water deficit. The potential functions of the identified DAPs revealed an intricate interaction network that responds synergistically to drought stress during grain development. Our results from the proteome perspective illustrate the potential roles of wheat non-leaf green organs glume and awn in photosynthetic and defensive responses under drought stress.

2D-DIGE comparative proteomic analysis of developing wheat grains under high-nitrogen fertilization revealed key differentially accumulated proteins that promote storage protein and starch biosyntheses

Nitrogen (N) serves as a macronutrient that is essential to plant growth and development, and significantly influences storage protein and starch biosyntheses and, ultimately, grain yield and quality. In this study, we performed the first comparative proteomic analysis of developing wheat grains under high-N conditions using 2D-DIGE and tandem mass spectrometry. High-N fertilizer application caused significant increases in ear number, ear grain number, and grain yield. 2D-DIGE identified 142 differentially accumulated proteins (DAPs) during grain development in the elite Chinese bread wheat cultivar Zhongmai 175, of which 132 (93%) were identified by MALDI-TOF/TOF-MS, representing 92 unique proteins. These proteins are involved mainly in energy, N and protein metabolism, carbon metabolism, and starch biosynthesis. Subcellular localization prediction and fluorescence confocal microscopic analysis showed that the DAPs identified were localized mainly in the cytosol and chloroplast. Principal component analysis (PCA) revealed a greater proteomic difference among grain developmental periods than between the high-N and control groups. Protein-protein interaction analysis highlighted a complex network centered around enzymes involved in energy, N and protein metabolism, and starch biosynthesis. Six key DAP genes showed expression patterns consistent with their protein accumulation trends during grain development. A putative metabolic pathway was proposed, with synergistic regulatory networks of grain storage protein and starch biosyntheses in response to high-N application.

First report on the application of near-infrared spectroscopy to predict the age of Aedes albopictus Skuse

To date, no methodology has been described for predicting the age of Aedes albopictus Skuse mosquitoes, commonly known as Asian tiger mosquitoes. In this study, we report the potential of near-infrared spectroscopy (NIRS) technique for characterizing the age of female laboratory reared Ae. albopictus. Using leave-one-out cross-validation analysis on a training set, laboratory reared mosquitoes preserved in RNAlater for up to a month were assessed at 1, 3, 7, 9, 13, 16, 20 and 25 days post emergence. Mosquitoes (N = 322) were differentiated into two age classes (< or ≥ 7 days) with 93% accuracy, into three age classes (<7, 7-13 and >13 days old) with 76% accuracy, and on a continuous age scale to within ±3 days of their actual average age. Similarly, models predicted mosquitoes (N = 146) excluded from the training model with 94% and 71% accuracy to the two and the three age groups, respectively. We show for the first time that NIRS, with an improved spectrometer and fibre configuration, can be used to predict the age of laboratory reared female Ae. albopictus. Characterization of the age of Ae. albopictus populations is crucial for determining the efficacy of vector control interventions that target their survival.

Monitoring the Age of Mosquito Populations Using Near-Infrared Spectroscopy

Mosquito control with bednets, residual sprays or fumigation remains the most effective tool for preventing vector-borne diseases such as malaria, dengue and Zika, though there are no widely used entomological methods for directly assessing its efficacy. Mosquito age is the most informative metric for evaluating interventions that kill adult mosquitoes but there is no simple or reliable way of measuring it in the field. Near-Infrared Spectroscopy (NIRS) has been shown to be a promising, high-throughput method that can estimate the age of mosquitoes. Currently the ability of NIRS to measure mosquito age is biased, and has relatively high individual mosquito measurement error, though its capacity to rigorously monitor mosquito populations in the field has never been assessed. In this study, we use machine learning methods from the chemometric literature to generate more accurate, unbiased estimates of individual mosquito age. These unbiased estimates produce precise population-level measurements, which are relatively insensitive to further increases in NIRS accuracy when feasible numbers of mosquitoes are sampled. The utility of NIRS to directly measure the impact of pyrethroid resistance on mosquito control is illustrated, showing how the technology has potential as a highly valuable tool for directly assessing the efficacy of mosquito control interventions.

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

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.

Differential proteomic screening and identification for non-traumatic necrotic femoral osseous tissue

Currently, there is a lack of effective early screening and detection methods for femoral head necrosis. Current research on most orthopedic diseases focuses on proteomics in the preliminary stage. The recent fluorescence differential in gel electrophoresis (DIGE) has advantages such as a high reproducibility, high sensitivity, high throughput, and high dynamic range. It is currently one of the most widely used quantitative proteomic research means. We conducted this study to investigate the pathogenesis of non-traumatic femoral head necrosis using the fluorescence DIGE to screen non-traumatic femoral head necrosis based on proteomics and provide a theoretical basis for screening possible biomarkers and molecular targeted treatment. The DIGE technique was used to separate the protein. An electrophoretogram was established on the basis of scanning and analysis. Identification and a bioinformatics analysis were conducted for the differential protein. The protein with differential expression of over 2-fold was excavated and ionized by means of substrate assisted laser desorption. The flight time was identified with a mass spectrometer (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, MALDI-TOF/TOF). The formation on sequences, structures and functions of these proteins were obtained through database retrieval. Western blot analysis was used to verify the differential protein expression and the reliability of the DIGE result was verified. DIGE was used to successfully separate 1,500±40 protein spots. There were 252 significant differential protein spots. The Ettan™ Spot Picker automatic work station was used to excavate 49 significant differential protein spots with expression difference over 2-fold. The MALDI-TOF/TOF mass spectrometer was used to identify these differential protein spots. Six proteins were identified in total, which include apolipoprotein A1 (APOA1), fibrous protein original chain, fibrous protein original chain, serum albumin, sulfur-oxygen protein peroxiredoxin 2 (PRDX2) and actin. APOA1 and PRDX2 were subject to western blot analysis detection; results were consistent with the DIGE result. Based on an analysis of the biological information, these proteins may be associated with the incidence and progression of femoral head necrosis.

Infection with Plasmodium berghei ookinetes alters protein expression in the brain of Anopheles albimanus mosquitoes

Background

The behaviour of Anopheles spp. mosquitoes, vectors for Plasmodium parasites, plays a crucial role in the propagation of malaria to humans. Consequently, it is important to understand how the behaviour of these mosquitoes is influenced by the interaction between the brain and immunological status. The nervous system is intimately linked to the immune and endocrine systems. There is evidence that the malaria parasite alters the function of these systems upon infecting the mosquito. Although there is a complex molecular interplay between the Plasmodium parasite and Anopheles mosquito, little is known about the neuronal alteration triggered by the parasite invasion. The aim of this study was to analyse the modification of the proteomic profile in the An. albimanus brain during the early phase of the Plasmodium berghei invasion.

Results

At 24 hours of the P. berghei invasion, the mosquito brain showed an increase in the concentration of proteins involved in the cellular metabolic pathway, such as ATP synthase complex alpha and beta, malate dehydrogenase, alanine transaminase, enolase and vacuolar ATP synthase. There was also a rise in the levels of proteins with neuronal function, such as calreticulin, mitofilin and creatine kinase. Concomitantly, the parasite invasion repressed the expression of synapse-associated proteins, including enolyl CoA hydratase, HSP70 and ribosomal S60 proteins.

Conclusions

Identification of upregulated and downregulated protein expression in the mosquito brain 24 hours after Plasmodium invaded the insect midgut paves the way to better understanding the regulation of the neuro-endocrine-immune system in an insect model during parasite infection.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1830-9) contains supplementary material, which is available to authorized users.

Comparative proteome analysis reveals that blood and sugar meals induce differential protein expression in Aedes aegypti female heads

Aedes aegypti females ingest sugar or blood to obtain the nutrients needed to maintain cellular homeostasis. During human blood ingestion, female mosquitoes may transmit different viruses such as dengue, yellow fever and, more recently, zika and chikungunya. Here, we report changes in protein expression in the heads of adult female Ae. aegypti mosquitoes in response to the ingestion of blood or sugar. Proteins extracted from the heads of Ae. aegypti fed exclusively on blood (BF) or sugar (SF) were trypsin hydrolyzed (off-gel) and analyzed by the reverse-phase nano-liquid chromatography coupled with hybrid mass spectrometry. A total of 1139 proteins were identified in female heads, representing 7.4% of the predicted proteins in Ae. aegypti genome (total = 15 419 active genes). Gene ontology annotation and categories showed that, in this insect, the head was rich in proteins involved in the metabolic process, proton transport, organelle, macromolecular complex, structural molecule activity, antioxidant activity, and catalytic activity. Our report is the first indicating that many of the annotated genes are translated into functional proteins in heads of adult female Ae. aegypti. Interestingly, we identified 8.7 times more exclusively expressed proteins involved in signal transduction, replication-transcription-translation (5.5 x), and transport (2.9 x) activity in BF than in SF groups. This paper discusses the protein profile of Ae. aegypti female heads and its implications for blood ingestion and carbohydrate intake.

Distinct metabolic changes between wheat embryo and endosperm during grain development revealed by 2D-DIGE-based integrative proteome analysis

Two Chinese bread wheat cultivars, Jinghua 9 and Zhongmai 175, distinct in grain weight and dough quality, were used to study proteome changes in the embryo and endosperm during grain development using a two-dimensional difference gel electrophoresis (2D-DIGE)-based proteomics approach. In total, 138 and 127 differentially expressed protein (DEP) spots representing 116 and 113 unique DEPs were identified in the embryo and endosperm, respectively. Among them, 54 (31%) DEPs were commonly present in both organs while 62 (35%) and 59 (34%) DEPs occurred only in the embryo and endosperm, respectively. Embryonic DEPs are primarily stress-related proteins and involved in carbohydrate and lipid metabolism, while those from the endosperm are related primarily to carbohydrate metabolism and storage. Principal component analysis (PCA) indicated that the proteome differences in the endosperm caused by different cultivars were greater than those by development stages, while the differences in the embryo showed the opposite pattern. Protein-protein interaction (PPI) analysis revealed a complex network centered primarily on enzymes involved in carbohydrate and protein metabolism. The transcriptional levels of fourteen important DEPs encoding genes showed high similarity between organs and cultivars. In particular, some key DEPs of the endosperm, such as phosphoglucomutase, ADP-glucose pyrophosphorylase (AGPase), and sucrose synthase (SUS), showed significantly upregulated expression, indicating their key roles in starch biosynthesis and grain yield. Moreover, upregulated expression of some storage proteins in the endosperm could improve wheat bread-making quality.

Candidate biomarkers for mosquito age-grading identified by label-free quantitative analysis of protein expression in Aedes albopictus females

We applied a "shotgun" approach based on nanoliquid chromatography-high resolution mass spectrometry associated to label free quantification (LFQ) to identify proteins varying with age, independently from the physiological state, in Aedes albopictus, a mosquito species which in the last decades invaded temperate regions in North America and Europe, creating concerns for associated high nuisance and risk of arbovirus transmission. The combined "shotgun" and LFQ approach was shown to be highly suitable to simultaneously compare several biological samples, as needed in a study aimed to analyze different age-groups and physiological states of adult mosquito females. The results obtained represent the first wide-scale analysis of protein expression in Ae. albopictus females: >1000 and 665 proteins were identified from few micrograms of crude protein extracts of mosquito heads and thoraxes, respectively. Six of these proteins were shown to significantly vary from 2- to 16-day-old females, independently from their physiological state (i.e. virgin, mated, host-seeking, blood-fed, and gravid).

BIOLOGICAL SIGNIFICANCE

Mosquito-borne diseases, such as malaria, dengue and other arboviroses, are a persistent cause of global mortality and morbidity, affecting hundreds of thousands of people. Billions of people living in tropical areas are at risk of being bitten every day by an infective mosquito female and the spread of tropical species such as Aedes albopictus to temperate areas is creating alarm in the northern hemisphere. Mosquito longevity is a critical factor affecting mosquito-borne pathogen transmission cycles and the mosquito capacity to transmit pathogens. However, large scale analyses of the age structure of mosquito field populations is hampered by the lack of optimal age-grading approaches. Our findings open new perspectives for the development of reliable, simple and cheap protein-based assays to age-grade Ae. albopictus females and, most likely, other mosquito species of higher medical relevance, such as the main dengue vector, Aedes aegypti, and the major Afrotropical malaria vectors. These assays would greatly contribute to epidemiological studies aimed at defining the actual vectorial capacity of a given mosquito species. Moreover, they would be very valuable in assessing the effectiveness of mosquito control interventions based on the relative ratio between young and old individuals before and after the intervention.

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

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].

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

The age of mosquitoes is a crucial determinant of their ability to transmit pathogens and their resistance to insecticides. We investigated changes to the abundance of proteins found in heads and thoraces of the malaria mosquitoes Anopheles gambiae and Anopheles stephensi as they aged. Protein expression changes were assessed using two-dimensional difference gel electrophoresis and the identity of differentially expressed proteins was determined by using either matrix-assisted laser desorption ionization tandem time-of-flight mass spectrometry or capillary high-pressure liquid chromatography coupled with a linear ion-trap (LTQ)-Orbitrap XL hybrid mass spectrometer. Protein biomarkers were validated by semi quantitative Western blot analysis. Nineteen and nine age dependent protein spots were identified for A. stephensi and A. gambiae, respectively. Among the proteins down-regulated with age were homologs of ADF/Cofilin, cytochome c1, heat shock protein-70 and eukaryotic translation initiation factor 5A (eIF5a). Proteins up-regulated with age included probable methylmalonate-semialdehyde dehydrogenase, voltage-dependent anion-selective channel and fructose bisphosphate aldolase. Semi quantitative Western blot analysis confirmed expression patterns observed by 2-D DIGE for eIF5a and ADF/Cofilin. Further work is recommended to determine whether these biomarkers are robust to infection, blood feeding and insecticide resistance. Robust biomarkers could then be incorporated into rapid diagnostic assays for ecological and epidemiological studies.

BIOLOGICAL SIGNIFICANCE

In this study, we have identified several proteins with characteristic changes in abundance in both A. gambiae and A. stephensi during their aging process. These changes may highlight underlying mechanisms beneath the relationship between mosquito age and factors affecting Plasmodium transmission and mosquito control. The similarity of changes in protein abundance between these species and the primary dengue vector Aedes aegypti, has revealed conserved patterns of aging-specific protein regulation.