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Annotated Differentially Expressed Salivary Proteins of Susceptible and Insecticide-Resistant Mosquitoes of Anopheles stephensi

  • Sonam Vijay,

    Affiliation Protein Biochemistry and Structural Biology Laboratory, National Institute of Malaria Research (ICMR), Sector-8, Dwarka, New Delhi, India

  • Ritu Rawal,

    Affiliation Protein Biochemistry and Structural Biology Laboratory, National Institute of Malaria Research (ICMR), Sector-8, Dwarka, New Delhi, India

  • Kavita Kadian,

    Affiliation Protein Biochemistry and Structural Biology Laboratory, National Institute of Malaria Research (ICMR), Sector-8, Dwarka, New Delhi, India

  • Kamaraju Raghavendra,

    Affiliation Insecticide Resistance Laboratory, National Institute of Malaria Research (ICMR), Sector-8, Dwarka, New Delhi, India

  • Arun Sharma

    arushar@gmail.com

    Affiliation Protein Biochemistry and Structural Biology Laboratory, National Institute of Malaria Research (ICMR), Sector-8, Dwarka, New Delhi, India

Annotated Differentially Expressed Salivary Proteins of Susceptible and Insecticide-Resistant Mosquitoes of Anopheles stephensi

  • Sonam Vijay, 
  • Ritu Rawal, 
  • Kavita Kadian, 
  • Kamaraju Raghavendra, 
  • Arun Sharma
PLOS
x

Abstract

Vector control is one of the major global strategies for control of malaria. However, the major obstacle for vector control is the development of multiple resistances to organochlorine, organophosphorus insecticides and pyrethroids that are currently being used in public health for spraying and in bednets. Salivary glands of vectors are the first target organ for human-vector contact during biting and parasite-vector contact prior to parasite development in the mosquito midguts. The salivary glands secrete anti-haemostatic, anti-inflammatory biologically active molecules to facilitate blood feeding from the host and also inadvertently inject malaria parasites into the vertebrate host. The Anopheles stephensi mosquito, an urban vector of malaria to both human and rodent species has been identified as a reference laboratory model to study mosquito—parasite interactions. In this study, we adopted a conventional proteomic approach of 2D-electrophoresis coupled with MALDI-TOF mass spectrometry and bioinformatics to identify putative differentially expressed annotated functional salivary proteins between An. stephensi susceptible and multiresistant strains with same genetic background. Our results show 2D gel profile and MALDI-TOF comparisons that identified 31 differentially expressed putative modulated proteins in deltamethrin/DDT resistant strains of An. stephensi. Among these 15 proteins were found to be upregulated and 16 proteins were downregulated. Our studies interpret that An. stephensi (multiresistant) caused an upregulated expression of proteins and enzymes like cytochrome 450, short chain dehyrdogenase reductase, phosphodiesterase etc that may have an impact in insecticide resistance and xenobiotic detoxification. Our study elucidates a proteomic response of salivary glands differentially regulated proteins in response to insecticide resistance development which include structural, redox and regulatory enzymes of several pathways. These identified proteins may play a role in regulating mosquito biting behavior patterns and may have implications in the development of malaria parasites in resistant mosquitoes during parasite transmission.

Introduction

In developing countries, malaria is one of the serious arthropod borne disease causing mortality and morbidity. An. stephensi Liston (Diptera:Culicidae), a major urban malaria vector spans throughout the Middle East and South East Asia, contributes to 12% of malaria cases annually [1,2]. In spite of the various efforts to control malaria transmission, still this fatal disease is responsible for millions of deaths. Absence of an effective vaccine, emergence of multi drug resistance in Plasmodium parasite [3,4] and multiple insecticide resistance in mosquitoes [5,6] accentuates the need for novel effective malaria control strategies.

In spite of the development of resistance, various insecticides and insecticide treated nets (ITNs) are being used as malaria control measures in public health system. Therefore, the threat of insecticide resistance and its implications is now a greater challenge. Genetic and proteomic factors and over use of all major groups of insecticides are responsible for rapid development of resistance among malaria vectors [7]. There are various known proteins/enzymes e.g. esterases, monooxogenases and glutathione S-transferases that known to be involved in the development of resistance against various insecticides in the Anopheles vectors [8]. Previous studies have reported effect of DDT on parasite development and showed blood fed insecticide resistant mosquitoes showed low survival rate after exposure of insecticides [9]. Other studies also showed impact of insecticide resistance on expression of salivary gland proteins in resistant acetylcholine allele of Culex sp [10]. Therefore, in order to understand the plausible role of expressed functional proteins of insecticide resistance mosquitoes in the development of parasite, physiological changes in the mosquito and various important enzymes of metabolic pathways, further knowledge of various proteins is required.

Salivary glands are an important organ of Anopheles mosquito, because of its main role in the transmission of the infective stage of the malaria parasite and in parasite vector interactions. Mosquito salivary proteins are important because they contain various bioactive factors like anti-coagulation factors, platelet aggregation inhibition proteins and immunosuppressive proteins that help the mosquito to overcome homeostasis and blood feeding [10,11]. It is known that insecticide resistance may also impact on the feeding habit of mosquito and vector competence [12]. Therefore, it is important to elucidate the role of functional proteins that are directly annotated in the insecticide resistant species in the development of parasites.

In this study, we adopted a conventional proteomic approach of 2D-electrophoresis coupled with MALDI-TOF mass spectrometry and bioinformatics to identify putative differentially expressed annotated functional salivary proteins between An. stephensi (susceptible) and An. stephensi (multi-resistant) strains. Expressed annotated functional salivary proteins or peptides that are upregulated/downregulated in insecticide resistant An. stephensi mosquitoes may have some role in various parasite development studies of the malaria parasite. These annotated proteins may be helpful in explaining the behavior of resistant mosquitoes toward the development of resistance and may lead to a search for a diagnostic protective antigen for novel malaria control strategies.

Materials and Methods

Mosquitoes

The two strains of An. stephensi namely An. stephensi susceptible (S) and An. stephensi multi-resistant (R) used in this study were reared and maintained in our insectary. These strains were maintained at 27°C ± 2°C with 70% ± 10% relative humidity with photoperiods of 12:12 (light/dark) hours. Adult mosquitoes were maintained on a resin and 10% sucrose solution.

Development of insecticide resistant strain

A multi-insecticide resistant strain of Anopheles stephensi was used for proteomics studies. Briefly, the wild mosquitoes were collected from field sites. After collection they were identified and checked for insecticide resistance using WHO prescribed methods (adult susceptibility test). After test, DDT/Deltamethrin/malathion resistance strain of An. stephensi and susceptible strain were maintained separately. This resistant strain was established in the laboratory by selection to deltamethrin at every generation to WHO diagnostic doses and carried out according to WHO procedure [13]. These strains are being tested quarterly against all 3 insecticides and respectively cyclic colonies are being maintained.

To maintain these susceptible and resistant strains properly, insecticide susceptibility test was executed on 3–4 day old adult sugar fed mosquitoes according to WHO recommended doses. This multiple insecticide resistant strain is found resistant to DDT 4% (79%), malathion 5% (54.5%) and deltamethrin 0.05% (21.6%). The resistant ratio (RR) of multiresistant strain of An. stephensi was against DDT (1.91), Malathion (2.17) and deltamethrin (0.93). An. stephensi susceptibility strain was taken as a control. Only those strains were selected as susceptible that found to be 100% mortality after exposed to WHO recommended diagnostic doses.

Preparation of salivary gland extracts (SGE) for 2D gel-electrophoresis

Salivary glands were dissected from 200 adult sugar fed (3–4 days old) female An. stephensi mosquitoes each (susceptible and resistant) using fine needles. Dissected salivary glands were ultrasonicated in lysis buffer (Tris 50mM, 150mM NaCl, 1% NP40 with protease inhibitors pH 7.4) for 3 pulses of 20 sec each on ice and homogenized sample were centrifuged at 5000 rpm for 10 min at 4°C (Complete, Roche Diagnostics, Germany). Debris were removed and supernatant was stored at -20°C. The protein concentrations of the SGEs were quantified with the Bradford reagent (Sigma Aldrich). For 2D electrophoresis firstly the SGE samples were desalted and cleaned using the ReadyPrep 2D Cleanup Kit (Bio-Rad), as per the manufacturers’ protocol. Thereafter, cleaned SGE samples were resuspended in 2D ReadyPrep rehydration buffer (8M urea, 2M thiourea, 2% CHAPS, 50 mM Dithiotheritol (DTT), 0.2% Bio-Lyte 3/10 ampholyte, and Bromophenol blue (trace).

2D electrophoresis

Salivary gland protein samples were immobilized on IPG strips (17 cm) of pH 3–10 (Linear, Bio-Rad) using a Protean IEF Cell (Bio-Rad) and kept for isoelectric focusing with a default cell temperature of 20°C and a maximum current of 50 mA/strip. Briefly, 300 μl sample in rehydration buffer were thawed and each of them were pipetted as a line along the edge of a channel. IPG strips were gently placed (gel side up) on to the sample and finally layered with 2–3 ml of mineral oil. The sample supernatants were rehydrated on IPG strips at 20°C overnight after which IEF was run in three steps: 1. 250V for 20 min Linear; 2. 10000V for 2.5 hrs Linear; 3. 10000V for 5–7 hrs and 40000 V-hrs in Rapid mode. After IEF run the strips were equilibrated in equilibration buffer I (6M urea, 0.375M Tris-HCl, pH 8.8, 2% SDS, 20% glycerol and 2% DTT) and equilibration buffer II (6M urea, 0.375M Tris-HCl, pH 8.8, 2% SDS, 20% glycerol and 2.5% iodoacetamide for 10 min. The second dimension was carried out on 12% SDS-PAGE on Mini Protean cell (Bio-Rad). The 2D gels were silver stained with FOCUS-FAST silverTM stain (G-Biosciences) after the run to visualize the spots. Stained gels of both the susceptible and resistant strains were scanned and analyzed using ImageMaster 2D Platinum 7.0 software (GE Healthcare Life Sciences).

In-gel extraction and trypsin digestion of proteins for MALDI analysis

Differential annotated protein spots among 2 strains of An. stephensi (susceptible and resistant) were excised automatically using a computer assisted ProPic work station (Genomic Solutions). These spots were digested automatically using a Pro Prep protein digestion station (Genomic Solutions). Briefly, all spots were destained using destaining solution for 10 minute intervals (3–4 times) until the gel pieces become translucent white. The gels were dehydrated using acetonitrile. Dried gel pieces were rehydrated with 10 mM dithiotreitol DTT in 100 mM ammonium bicarbonate and alkylated with 55mM iodoacetamide. After 45 min incubation with occasional vortexing, the gel pieces were incubated with 50mM ammonium bicarbonate and rehydrated with acetonitrile for 10 mins and dried the gel pieces using speed vac concentrator. Digestion buffer (50mM NH4HCO3 (pH: 8.5), 5 mM CaCl2, and trypsin (proteomic grade, Roche diagnostics) was added to dried gel pieces and incubated overnight at 37°C. Finally, peptides were extracted thrice by one change of 20 mM NH4HCO3 and three changes of 5% formic acid in 50% acetonitrile (20 min for each change). The dried pepmix was suspended in TA buffer and spotted onto the MALDI plate after mixing it with matrix solution.

MALDI-TOF MS analysis

Above digested premix samples were first desalted and concentrated on C18 Zip Tips (Millipore, USA). Desalted peptides samples were mixed with α-cyano-4-hydroxycinnamic acid matrix (50% aqueous acetonitrile and 0.2% trifluoroacetic acid) prepared in 1:1 ratio and the resulting 2 μl was spotted onto the MALDI plate. After air drying the samples, it was analyzed on MALDI TOF/TOF UltraFlex III mass spectrometer (Bruker Daltonics, Bremen, Germany). Maldi TOF analysis was carried out in positive-ion reflectron mode of 500–3000m/z detection range using FLEX control software. Further analysis was performed on FlexAnalysis TM software for obtaining the peptide mass fingerprint (Bruker-Daltonics). For peptide selection, a parameter of mass range was set to 900–3000 Da. Further spectra analysis and peak detection was done using MASCOT Wizard Program (Matrix Science UK).

Database search

MALDI-MS and computational analysis of differentially expressed proteins was carried out using Mascot software (Matrix Science). Briefly, the peaks obtained in the peptide mass fingerprint were analyzed by MASCOT peptide mass fingerprinting search using NCBInr, Swiss prot database for identification of the proteins. Raw data were analyzed in mascot peptide mass fingerprinting (PMF) using parameters: fixed modification (carbamidomethyl), variable modification (Methionine oxidation), trypsin as an enzyme, peptide tolerance: variable from 50 ppm to 500ppm, Missed Cleavages: 1 or 2. All the searches were performed against different Anopheles species, Aedes and Culex mosquito databases (NCBInr/Swiss prot) and also against An. stephensi databases submitted in VectorBase (https://www.vectorbase.org/organisms/anopheles-stephensi/). Proteins analyzed by PMF were manually validated on basis of scores, % sequence coverage and peptides match. Further, all the significant proteins/peptides were analyzed using various bioinformatics programme includes SMART programme (http://smart.embl-heidelberg.de/) [14], SIGNAL P 4.1, (http://www.cbs.dtu.dk/services/SignalP/) [15], BLAST P and GO analysis (http://www.geneontology.org/) to find out their probable function.

Results

Comparative 2D gel electrophoresis of An. stephensi (susceptible and resistant) SGE

The salivary proteins expression profile between susceptible (S) and multi-resistant strain (R) of an urban malaria vector An. stephensi sugar fed mosquitoes was analyzed using comparative 2D- electrophoresis coupled with MALDI-TOF mass spectrometry. SGE samples of An. stephensi susceptible (S) and multi-resistant strain (R) were separated on 17cm IPG strips (pH range 3–10) and 12% polyacrylamide in 2D gels. A total 168 spots between a pI range of 3–9 and MW 25–110 kDa were detected by ImageMaster 2D Platinum software. Depiction of the gel picture of total protein identified in An. stephensi susceptible (S) and multi-resistant strain (R) by 2D-electrophoresis is shown (Fig. 1A and 1B). Among 168 spots, 44 spots were validated in An. stephensi susceptible species and 36 spots were validated in An. stephensi resistant species during differential expression analysis. Further among PMF of 44 major spots, 28 spots were found to be similar and 16 annotated spots were found to be different in both susceptible and resistant strain of An. stephensi. These comparisons of differential spots in susceptible and resistant species were on the basis of pixel volume of each spot. In Fig. 2, volume of spots of both species is shown as a scatter plot which was calculated on the basis of spot area and intensity. Here, it showed the linear distribution between the spot volumes. The correlation coefficient between susceptible and resistant species of An. stephensi was >0.81 (Fig. 2).

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Fig 1. Representative 2D gel picture of An. stephensi salivary gland proteins.

Molecular weight (kDa) is shown in the middle of gel. (A) Silver-stained gel of An. stephensi susceptible strain numbered from 1 to 43 using ImageMaster 2D Platinum 7.0 software (B) Silver-stained gel of An. stephensi multi resistant strain numbered from 1 to 43 using ImageMaster 2D Platinum 7.0 software.

https://doi.org/10.1371/journal.pone.0119666.g001

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Fig 2. Scatter plot showing volume of all protein spots of An. stephensi salivary gland.

Blue line shows linear regression. X axis represents the volumes of protein spots in An. stephensi susceptible species and Y axis represents volumes of protein spots in An. stephensi resistant species. Correlation coefficient was calculated and indicated at the bottom.

https://doi.org/10.1371/journal.pone.0119666.g002

Identification of An. stephensi salivary proteins by MALDI-TOF mass spectrometry

In the present study, only those spots which depicted the differential protein expression were explored for comparison between resistant species and susceptible species. Among 16 annotated spots, 9 major spots (spot numbers 4, 8, 9, 10, 11, 19, 36, 41 and 42) were shown to be up regulated in resistant species in comparison to susceptible species (Fig. 3A) and 7 spot (spot numbers 3, 13, 14, 21, 29, 35 and 39) were shown to be down regulated in resistant species (Fig. 3B). These annotated spots were majorly detected of molecular weight range 25–100 kDa and a pI range of 5–9. 2D spots of all upregulated and downregulated spots were further subjected to MALDI-TOF analysis and the peak list (xml) data obtained were analyzed by Mascot algorithm using peptide mass fingerprinting. PMF of all 16 annotated spots led to the identification of 31 different proteins using NCBInr and Swiss Prot database. All the identified proteins correspond to different spots with fold expression values are depicted (Table 1). A total of 15 proteins correspond to 9 differential upregulated spots were identified and their molecular weight, sequence coverage, functions with their respective spots are shown in table (Table 2). A total of 16 proteins correspond to 7 spots were identified as downregulated spots in resistant strain and all the information about each protein i.e. sequence coverage, molecular weight etc with spot numbers are summarized in Table 3.

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Fig 3. Differential spot selection of salivary gland protein in An. stephensi species.

Representation of the protein spots showing upregulated and downregulated expression in An. stephensi strains are marked by green line. Molecular weights (kDa) are shown in the middle of 2D gel. (A) Silver-stained gel of An. stephensi susceptible strain (B) Silver-stained gel of An. stephensi multi-resistant strain. Depiction of total 16 spots marked using ImageMaster 2D Platinum 7.0 software. Downregulated proteins: Match spot id (3,13,14,21,29,35,39); Upregulated proteins: Match spot id (4,8,9,10,11,19,36,41,42).

https://doi.org/10.1371/journal.pone.0119666.g003

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Table 1. Annotated total identified proteins spots with their fold expression values in An. stephensi multi resistant strain.

https://doi.org/10.1371/journal.pone.0119666.t001

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Table 2. Summary of upregulated salivary proteins identified in the SGE of An. stephensi multi resistant strain by MALDI-TOF MS/MS.

https://doi.org/10.1371/journal.pone.0119666.t002

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Table 3. Summary of down regulated salivary proteins identified in the SGE of An. stephensi multi resistant strain by MALDI-TOF MS.

https://doi.org/10.1371/journal.pone.0119666.t003

Differential protein in multi resistant strain of An. stepehensi

Detailed functional analysis of these 31 identified proteins was further explored using various bioinformatics algorithms. The most important upregulated protein identified was short chain dehydrogenase reductase (spot 4) with fold expression 7.21 and cytochrome P450 (spot 11) with fold expression 3.38. Peak spectrum of short chain dehydrogenase is shown with peptide sequence (Fig. 4A). Others upregulated protein identified are hamadarin, Sorting nexin-6, molybdenum cofactor synthesis protein 3, Cyclin-C, Piwi protein, phosphodiesterase, SG1 protein etc. Among the downregulated proteins expression, proteins identified were mostly hypothetical proteins, Yippee putative zinc-binding protein, 26S proteasome non-ATPase regulatory subunit, ND3 gene product (mitochondria), S-methyl-5′-thioadenosine phosphorylase, Mediator of RNA polymerase II transcription subunit 18, Ubiquitin carboxyl-terminal hydrolase x4 etc. Peak spectrum of 26S proteasome non-ATPase regulatory subunit is shown with peptide sequence (Fig. 4B). Mostly upregulated proteins are identified with putative function of oxido-reductase activity, catalytic activity, cell signaling, protein binding etc and mostly down regulated proteins found of unknown function, protein binding, transcription regulation, cell-cell recognition etc. These identified proteins could be depicted into biological function of each upregulated and downregulated protein with percentage as a pie chart was shown (Fig. 5A and 5B) and cellular location of each protein was also depicted (Fig. 5C). Peak spectrum of tryptic peptides of all upregulated spots and downregulated spots are shown respectively (S1 and S2 Figs.).

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Fig 4. Peak spectrum analyzed by MALDI-TOF in An. stephensi multi-resistant species.

(A) Representative PMF spectrum of over expressed protein i.e Short-chain dehydrogenase reductase (DNIKVTLISPGYINTALSLNALTGTGASYGK) (spot no. 4) (B) Representative PMF spectrum of down regulated protein i.e 26S proteasome non-ATPase regulatory subunit (VSQTAAAAAPADPIVDVEMESAEDAEAAK) (spot no.39).

https://doi.org/10.1371/journal.pone.0119666.g004

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Fig 5. Illustration of identified upregulated & downregulated salivary proteins analyzed by gene ontology tool.

(A) GO function of identified upregulated proteins. (B) GO function of identified downregulated proteins. (C) GO component of identified proteins.

https://doi.org/10.1371/journal.pone.0119666.g005

Network analysis of upregulated protein

Protein-protein interaction of most important upregulated protein i.e. short chain dehydrogenase reductase in multi-resistant strain of An. stephensi was analyzed using STRING 9.1 (http://string-db.org/) [16]. Evidence view of SDR protein was found to interact with other protein of An. gambiae i.e. AGAP005550, AGAP007493 (oxidoreductase activity), AGAP001883 (nucleotide binding), AGAP000965 (nucleotide binding), AGAP010129, AGAP000312 and AGAP000132 (Fig. 6A). Similarly evident view of another upregulated protein Tyrosyl DNA phosphodiesterase was shown (Fig. 6B). This was shown to interact with AGAP000623 (DNA ligase activity), AGAP009587 (DNA binding), AGAP004078 (DNA binding), AGAP009222 (DNA ligase activity), AGAP002805 (DNA binding), AGAP009632 (ATP binding), AGAP002605 (DNA repair), AGAP012174, AGAP009910 (Helicase activity).

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Fig 6. Evidence view of upregulated proteins in resistant strain showing interaction with other proteins.

(A) SDR protein (AGAP005532) (B) Tyrosyl DNA phosphodiesterase. Different line colors represent the types of evidence for the association. Green color depicts neighborhood; red color: gene fusion; pink color: experiments; light green color: text mining; blue color: co-occurrence; dark blue color: co-expression; purple color: homology. Circle nodes indicated different proteins.

https://doi.org/10.1371/journal.pone.0119666.g006

Discussion

Study of salivary gland proteins of malaria vector are of fundamental importance and a point of attraction because of their role in feeding, malaria parasite transmission and secretion of biologically active molecules [1719]. Recent An. stephensi genome analysis [20] and various other studies [21] that have been carried out in An. stephensi salivary glands represent amino terminal sequences and the proteins in relationship to the transcriptomic analysis [2223]; however none of these studies were able to assign a specific functional role to most of the gene products. Moreover, no study has directly explained the role of annotated proteins involved in function of parasite development/mechanism in insecticide resistant mosquitoes except the study on Culex [10]. In our earlier studies we have carried out An. stephensi salivary glands proteomics analysis which depicted the plausible role of various directly derived proteins [24]. Therefore, here in this study our main objective was to identify, compare and elucidate a plausible role of the annotated differentially expressed salivary proteins in insecticide resistant vectors using proteomic studies. To achieve this objective we analyzed role of putative functional annotated salivary gland proteins of susceptible An. stephensi mosquitoes and compared it with multi-resistant An. stephensi mosquitoes using 2D-electrophoresis, MALDI-TOF mass spectrometry and bioinformatics approaches for a plausible functional role in development of malaria parasites.

We have compared the expression profile of salivary gland proteins between susceptible and insecticide resistant strains of An. stephensi which have a same genetic background. Differential protein profiles of the SGEs of An. stephensi (susceptible) and of An. stephensi (Resistant) were examined based on the fold abundance values and the annotated spots. Our results showed identification of total 168 spots and among them 9 spots were identified as upregulated and 7 spots were identified as downregulated in multiresistant species of An. stephensi. This led to the identification of 31 proteins: 15 upregulated proteins and 16 downregulated proteins from the SGE of An. stephensi (resistant) which explain the alteration of expressed salivary gland protein by DDT/Deltamethrin resistance and that may play a role in parasite growth and development.

The identification of an upregulated protein cytochrome P450 (spot 11) similar to Culex mosquito was identified with 23% sequence similarity. It is known that cytochrome P450 allows insects to metabolize insecticides at a higher rate [25,26]. It is a kind of metabolic resistance which usually through the overproduction of detoxification enzymes. Earlier also its role was identified and validated by transcriptomics studies however in this study functional annotation of cytochrome P450 role was identified by proteomic studies directly [27,28]. This suggests that this upregulated expression of cytochrome P450 in resistant strain of An. stephensi may play a major role in insecticide resistance [8]. Another upregulated protein (spot 4) was identified as short chain dehydrogenase-reductase (SDR) that was found to be similar to An. gambiae with 19% sequence coverage. It has been reported that various roles of short chain dehydrogenase in lipid, amino acid, carbohydrate, hormone, and xenobiotic metabolism as well as in redox sensor mechanisms [29,30]. Surprisingly fold expression of this protein (7.21) was found the highest among all over expressed proteins. From these studies our result suggests that this upregulated protein in resistant strain may be associated with xenobiotic detoxification. Evidence view of SDR protein also shows interactions with the other associated proteins and such protein—protein interactions may further important for signaling studies. Next protein, the factor named hamadarin (spot 8) (fold expression: 2.17) that inhibits activation of the plasma contact system was also found to be upregulated in resistant strain [31]. Isawa proposed the function of this protein in biting of mosquitoes for efficiently sucking of the blood meal and this may be by attenuating the host’s acute inflammatory responses [31]. This protein was also demonstrated to be the part of D7 family, an odorant binding protein [31].

One cytoplasmic protein with 10% sequence similarity (AGAP011997) (spot 42) was found to be over expressed with 3.90 fold expression value. In this one conserved domain i.e. MR domain (multiple resistant domain) along with ATPases was found. Cyclin C (spot 11), was also found to be upregulated whose function is to control of cell cycle and regulation of gene transcription. Piwi protein (spot 11) that found to be upregulated in resistant species, its function is to control transposon and also helps to target genes through gene-drive systems based on transposons [32]. One hypothetical protein (spot 8) was found with RCC1 domain that have important role in regulation of gene expression. This protein was also identified with secreted function and its signal peptide was present at position 1 to 17. This over expressed protein may imply regulation of those genes that involved in resistance mechanism. Tyrosyl DNA Phosphodiesterase protein (spot 9) was next identified protein that was involved in DNA repair mechanism [33]. This upregulated protein with DNA repair function may have a role in some insecticide resistance mechanism. This may involve in repairing function of any alter gene in resistant species caused by any mutation. SG1 protein identified (spot 10) is found to be have secreted function with 4.0 fold expression. Signal peptide of this protein starts at position 1 and ends at position 20. Other upregulated proteins identified have various functions like protein degradation, nucleotide binding etc. This may imply that higher expression of these enzymes in multiresistant insecticide strain may suggest the higher metabolic activity of salivary glands cells and such over expressed proteins might have some role in regulation and in resistance mechanism.

Among downregulated proteins found in resistant species, many of them were of unknown function. Approx 7 proteins of unknown function corresponding to spot no. 13, 21, and 39 were identified. Next in list were various binding proteins that also shown to be down regulated in resistant species. One protein (spot 39) namely Yippee putative zinc-binding protein, its downregulated expression (0.39 fold expression) in resistant species reflected its lower binding capacity. This protein is found to be conserved among all eukaryotes [34]. One protein that role in regulation of transcription of nearly all RNA polymerase II-dependent genes is MED 18 found with 17% sequence similarity was also downregulated in resistant species.

Although this study showed various proteins that were found to be modulated by effect of DDT/Malathion/Deltamethrin insecticides but some important salivary proteins were not detectable in the An. stephensi strains like D7 protein, apyrase, enolase, transporters protein etc. However, this may be due to our failure to detect small transcripts for short forms of proteins using MALDI-TOF approach or also non detection of all the spots by 2D electrophoresis. Though in our earlier studies, these proteins were identified in An. stephensi salivary gland using in gel digestion approach [24].

These results emphasize the need of further experimentations to assess the effect of infected blood feeding on salivary gland protein expression profile in susceptible and resistant mosquitoes. We will also find such observations that may explain changes or delayed in oocyst development in resistant mosquitoes to uncover the mechanism of malaria control as a novel tool. Further studies on the role of these annotated proteins in involvement in probing time and biting behavior is required to assess the fitness of resistant mosquitoes for parasite development. Studies on the biting behavior patterns of susceptible and insecticide-resistant mosquitoes, its impact on parasite development and transmission are being carried out in our laboratory for novel control strategies.

Conclusion

In summary, our initial study constitutes the first study of MS based proteomic approach to identify and compare the protein profiles of An. stephensi salivary glands of susceptible and insecticide/ pyrethroid multiresistant strains. Through the use of 2D electrophoresis coupled with MALDI TOF, differential expression profile of SGEs annotated protein are examined and assessed by sequence coverage, peptide sequences and by fold expression. Our results depict the differentially regulated proteins in response to insecticide resistance in An. stephensi multiresistant strain and identified these proteins with major function like xenobiotic detoxification, insecticide resistance, DNA repair, regulation of gene transcription, control transposon etc. Mapping of putative upregulated/downregulated proteins in resistant strains of An. stephensi may have impact on the biting behavior of mosquitoes to adapt to environment and hence the transmission of malaria parasites. These studies may prove useful information in identification and annotation of genes to better understand the molecular mechanism for a diagnostic tool behind the resistance in An. stephensi multiresistant strain and furthermore contribute to the novel strategies to control the malaria pathogen transmission.

Supporting Information

S1 Fig. Peak spectrums of upregulated proteins analyzed by MALDI-TOF.

Representative PMF spectrum of over expressed proteins of spot no. 8, 9, 10, 11, 19, 36, 41 and 42.

https://doi.org/10.1371/journal.pone.0119666.s001

(TIF)

S2 Fig. Peak spectrums of downregulated proteins analyzed by MALDI-TOF.

Representative PMF spectrum of under expressed proteins of spot no. 3, 13, 14, 21, 29 and 35.

https://doi.org/10.1371/journal.pone.0119666.s002

(TIF)

Acknowledgments

The authors would like to acknowledge to their technical staff Mr. Bhanu Arya (Technical Officer) and Mrs. Poonam Gupta (Technical assistant) for their excellent technical help in conduct of proteomics experiments. We will also like to thank all the technical staff of Insectary for providing us resistant mosquitoes. This paper bears the NIMR publication screening committee approval no. 059/2014.

Author Contributions

Conceived and designed the experiments: SV AS. Performed the experiments: SV RR. Analyzed the data: SV RR KK. Contributed reagents/materials/analysis tools: AS KR. Wrote the paper: SV AS. SV RR KK KR AS.

References

  1. 1. Dash AP, Adak T, Raghavendra K, Singh OP. The biology and control of malaria vectors in India. Cur Sci. 2007; 92: 1571–1578.
  2. 2. Sinka ME, Bangs MJ, Manguin S, Chareonviriyaphap T, Patil AP, Temperley WH, et al. The dominant anopheles vectors of human malaria in Asia-Pacific: occurrence data, distribution maps and bionomic précis. Parasite Vectors. 2011; 4: 89. pmid:21612587
  3. 3. Greenwood BM, Fidock DA, Kyle DE, Kappe SHI, Alonso PL, Collins FH, et al. Malaria: progress, perils, and prospects for eradication. J Clin Invest. 2008; 118: 1266–1276. pmid:18382739
  4. 4. World Health Organization (WHO). World malaria report. 2010; Geneva, Switzerland.
  5. 5. Ranson H, N’Guessan R, Lines J, Moiroux N, Nkuni Z, Corbel V. Pyrethroid resistance in African anopheline mosquitoes: what are the implications for malaria control? Trends Parasitol. 2011; 27: 91–98. pmid:20843745
  6. 6. Perera MDB, Hemingway J, Karunaratne SP. Multiple insecticide resistance mechanisms involving metabolic changes and insensitive target sites selected in anopheline vectors of malaria in Sri Lanka. Malar J. 2008; 7: 168. pmid:18755020
  7. 7. WHO-World Health Organization. World Malaria Report. Tech. Rep, 2013; WHO, Geneva, Switzerland.
  8. 8. Hemingway J, Ranson H. Insecticide resistance in insect vectors of human disease. Annu Rev Entomol. 2000; 45: 371–391. pmid:10761582
  9. 9. Alout H, Yameogo B, Djogbenou LS, Chandre F, Dabire RK, Corbel V, et al. Interplay between Plasmodium infection and resistance to insecticides in vector mosquitoes. J Infect Dis. 2014; 210 (9): 1464–1470. pmid:24829465
  10. 10. Djegbe I, Cornelie S, Rossignol M, Demettre E, Seveno M, Remoue F, et al. Differential Expression of Salivary Proteins between Susceptible and Insecticide- Resistant Mosquitoes of Culex quinquefasciatus. PLoS ONE. 2011; 6(3): e17496. pmid:21448269
  11. 11. Ribeiro JM, Francischetti IM. Role of arthropod saliva in blood feeding: sialome and post-sialome perspectives. Annu Rev Entomol. 2003; 48: 73–88. pmid:12194906
  12. 12. Rivero A, Vezilier J, Weill M, Read AF, Sylvain G. Insecticide Control of Vector-Borne Diseases: When Is Insecticide Resistance a Problem? PLoS Pathog. 2010; 6(8): e1001000. pmid:20700451
  13. 13. WHO. Test Procedures for Insecticide Resistance Monitoring in Malaria Vector Mosquitoes. 2013; Geneva: World Health Organization. https://doi.org/10.1186/1756-3305-6-337 pmid:24298981
  14. 14. Letunic I, Copley RR, Schmidt S, Ciccarelli FD, Doerks T, Schultz J, et al. SMART 4.0: towards genomic data integration. Nucleic Acids Res. 2004; 32: D142–D144. pmid:14681379
  15. 15. Petersen TN, Brunak S, Heijne GV, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Met. 2011; 10: 785–786.
  16. 16. Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 2013; 41: D808–D815. pmid:23203871
  17. 17. Arca B, Lombardo F, Valenzuela JG, Francischetti IM, Marinotti O, Coluzzi M, et al. An updated catalogue of salivary gland transcripts in the adult female mosquito, Anopheles gambiae. J Exp Biol. 2005; 208: 3971–3986. pmid:16215223
  18. 18. Lanfrancotti A, Lombardo F, Santolamazza F, Veneri M, Castrignano T, Coluzzi M, et al. Novel cDNAs encoding salivary proteins from the malaria vector Anopheles gambiae. FEBS Lett. 2002; 517: 67–71. pmid:12062411
  19. 19. Monteiro RQ. Targeting exosites on blood coagulation proteases. An Acad Bras Cienc. 2005; 77: 275–280. pmid:15895163
  20. 20. Jiang X, Peery A, Hall AB, Sharma A, Chen XG, Waterhouse RM, et al. Genome analysis of a major urban malaria vector mosquito, Anopheles stephensi. Genome Biol. 2014; 15:459. pmid:25244985
  21. 21. Valenzuela JG, Francischetti IMB, Pham VM, Garfield MK, Ribeiro JMC. Exploring the salivary gland transcriptome and proteome of the Anopheles stephensi mosquito. Insect Biochem Mol Biol. 2003; 33 (7): 717–732. pmid:12826099
  22. 22. Dixit R, Sharma A, Mourya DT, Kamaraju R, Patole MS, Shouche YS, et al. Salivary gland transcriptome analysis during Plasmodium infection in malaria vector Anopheles stephensi. Int J Infect Dis. 2009; 13 (5): 636–646. pmid:19128996
  23. 23. Dixit R, Rawat M, Kumar S, Pandey KC, Adak T, Sharma A. Salivary gland transcriptome analysis in response to sugar feeding in malaria vector Anopheles stephensi. J Insect Physiol. 2011; 57 (10): 1399–1406. pmid:21787783
  24. 24. Vijay S, Rawat M, Sharma A. Mass Spectrometry Based Proteomic Analysis of Salivary Glands of Urban Malaria Vector Anopheles stephensi. BioMed Res Int. 2014; 686319: 12 pages. http://dx.doi.org/10.1155/2014/686319. pmid:25126571
  25. 25. Chandor-Proust A, Bibby J, Regent-Kloeckner M, Roux J, Guittard-Crilat E, Poupardin R, et al. The central role of mosquito cytochrome P450 CYP6Zs in insecticide detoxification revealed by functional expression and structural modeling. Biochem J. 2013; 455: 75–85. pmid:23844938
  26. 26. David JP, Ismail HM, Chandor-Proust A, Paine MJI. Role of cytochrome P450s in insecticide resistance: impact on the control of mosquito-borne diseases and use of insecticides on Earth. Phil Trans R Soc B. 2013; 368: 20120429. pmid:23297352
  27. 27. Strode C, Wondji CS, David JP, Hawkes NJ, Lumjuan N, Nelson DR, et al. Genomic analysis of detoxification genes in the mosquito Aedes aegypti. Insect Biochem Mol Biol. 2008; 38: 113–123. pmid:18070670
  28. 28. David JP, Strode C, Vontas J, Nikou D, Vaughan A, Pignatelli PM, et al. The Anopheles gambiae detoxification chip: a highly specific microarray to study metabolic-based insecticide. Proc Natl Acad Sci USA. 2005; 102(11): 4080–4084. pmid:15753317
  29. 29. Kavanagh KL, Jornvall H, Persson B, Opperman U. The SDR superfamily: functional and structural diversity within a family of metabolic and regulatory enzymes. Cell Mol Life Sci. 2008; 65: 3895–3906. pmid:19011750
  30. 30. Mayoral JG, Leonard KT, Defelipe LA, Turjansksi AG, Nouzova M, Noriegal FG. Functional Analysis of a Mosquito Short Chain Dehydrogenase Cluster. Arch Insect Biochem Physiol. 2013; 82(2): 96–115. pmid:23238893
  31. 31. Isawa H, Yuda M, Orito Y, Chinzei Y. A mosquito salivary protein inhibits activation of the plasma contact system by binding to factor XII and high molecular weight kininogen. J Biol Chem. 2002; 277(31): 27651–27658. pmid:12011093
  32. 32. Macias V, Coleman J, Bonizzoni M, James AA. piRNA pathway gene expression in the malaria vector mosquito Anopheles stephensi, Insect Mol Bio. 2014; pmid:24947897
  33. 33. Pouliot JJ, Yao KC, Robertson CA, Nash HA. Yeast gene for a Tyr-DNA phosphodiesterase that repairs topoisomerase I complexes. Sci. 1999; 286: 552–555. pmid:10521354
  34. 34. Roxstrom-Lindquist K, Faye I. The Drosophila gene Yippee reveals a novel family of putative zinc binding proteins highly conserved among eukaryotes. Insect Mol Biol. 2001. 10(1): 77–86. pmid:11240639