Mosquito colony

A. albopictus eggs were obtained from the Malaria Research and Reference Reagent Resource Center (MR4) as part of BEI Resources Repository, NIAID, NIH (ALBOPICTUS, MRA-804, deposited by Sandra Allan). Eggs were raised to adults using a protocol similar to that described for A. aegypti [21] with the exception that larvae were fed pulverized TetraMin flakes (Melle, Germany). Adult females between 5 to 10 days post-eclosion were used for the present study.

Design of the study

The experimental design consisted of two treatments, blood fed (BF) and non-blood fed (NBF) females at three different time points. In brief, the BF mosquitoes were fed on heparinized rabbit blood for 30 minutes (see details below) and collected at 3 h, 12 h, or 24 h after feeding. These time points occur after the post-prandial diuresis, which ends within 2 h after feeding [8]. Moreover, one or more of these time points has been commonly used in other studies examining the effects of blood feeding on gene expression in mosquitoes [13], [14], [15], [16], [17], [18], [19], [20], [22]. NBF females were only offered a 10% sucrose solution and dissected at similar time points to serve as controls. Each treatment/time point was replicated three times using females from different cohorts (i.e., 3 biological replicates per time point).

Blood feeding and isolation of Malpighian tubules

For each experimental treatment, 90 adult female mosquitoes were transferred to two small 32 oz. cages (45 females per cage) without access to a sucrose solution for 24 h prior to offering them blood or sucrose. To one cage, a membrane feeder (Hemotek, Blackburn, UK) was used to feed the mosquitoes warmed blood (37°C), which consisted of heparinized rabbit blood (purchased from Hemostat Laboratories, Dixon, CA) supplemented with adenosine 5′-triphosphoric acid (disodium salt; Sigma, St. Louis, MO) at a concentration of 0.01 g/ml. A solution of 10% lactic acid was applied to the membrane surface as an attractant. Females were given access to the blood for a period of 30 min before the feeder was removed from the cage. In the other cage, the mosquitoes were given access to cotton balls soaked with 10% sucrose for 30 min. At 3 h, 12 h, or 24 h after removing the feeder or cotton balls, the cage was refrigerated on ice to immobilize the mosquitoes.

Before dissecting the mosquitoes that were offered blood, their abdomens were visually examined to confirm their engorgement. The alimentary canal of each mosquito was then extracted by tugging on the last segment of the abdomen with fine forceps under Ringer solution. The Ringer solution consisted of (in mM): 150 NaCl, 3.4 KCl, 1.7 CaCl₂, 1.8 NaHCO₃, 1.0 MgCl₂, 5 glucose, and 25 HEPES (pH 7.1). The Malpighian tubules were isolated from their attachment to the alimentary canal and immediately immersed in 50 µL of TRIzol Reagent (Life Technologies, Carlsbad, BA) in a sterile 1.5 ml microcentrifuge tube on ice. A total of 200 Malpighian tubules (from 40 females) were pooled for a given replicate.

Altogether, Malpighian tubules were isolated from 1) mosquitoes fed a blood meal at 3 different time points (3 h, 12 h, 24 h; 40 mosquitoes at each time point) and 2) mosquitoes not fed a blood meal at similar time points (40 mosquitoes each). A total of 3 biological replicates was obtained for each time point in both the BF and NBF groups, resulting in 18 sets of tubules for RNA isolation and cDNA library preparation (triplicates each of 3 h BF, 12 h BF, 24 h BF, 3 h NBF, 12 h NBF, and 24 h NBF).

Isolation and purification of total RNA and assessment of its quantity and quality

Total RNA was extracted from each set of Malpighian tubules immediately after they were isolated from the mosquitoes using the method of Chomczynski and Sacchi [23]. The resulting RNA was treated with TURBO DNA-free (Life Technologies) to remove genomic DNA and then purified with a RNA Clean & Concentrator-5 kit (Zymo Research, Irvine, CA), according to the manufacturer's protocol.

The purified RNA was initially measured for quantity and quality using a NanoDrop 2000c Spectrophotometer (Thermo Fisher Scientific, Waltham, MA). Samples with a concentration <20 ng/µl or poor absorbance ratios (i.e., 260/280 value <1.6; 260/230 value <1.6 or >3.0) were discarded. RNA quality was further assessed using the Experion Automated Electrophoresis System (Bio-Rad, Hercules, CA). Only samples with RNA Quality indicator values of 7.5 or higher were used. The concentration of RNA was determined with a Qubit 2.0 Fluorometer (Life Technologies).

Synthesis and sequencing of cDNA libraries

Total RNA (565 ng) was used to synthesize adaptor-indexed double-stranded cDNA libraries using the TruSeq DNA Sample Prep Kit V2, Set A and B (Illumina, San Diego, CA). The size chosen for libraries was ∼270 bp. The quality of the synthesized libraries was evaluated using the Agilent 2100 Bioanalyzer High Sensitive DNA Chip (Agilent Technologies, Santa Clara, CA) and the quantity determined using the Qubit 2.0 Fluorometer (Life Technologies).

The 18 resulting cDNA libraries were diluted to 18 nM and pooled to generate a multiplexed cDNA library (using 18 unique indexed adapters) of 36 fM. The pooled library was sequenced using the Illumina HiSeq 2000 platform at the Ohio State University Comprehensive Cancer Center (Columbus, OH). Demultiplexing was performed with CASAVA 1.8.2. FASTQ files were generated from the ‘basecall’ files. All single-end reads were submitted to the NCBI sequence read archive (accession number SRP034701). The sequencing of all 18 libraries generated over 232 million single-end raw reads (∼13 million reads per sample) (Table S1).

Filtering data, alignment, and read counting

The MCIC-Galaxy pipeline was implemented for preprocessing, filtering, and data analysis [24]. The raw reads were first analyzed with the “FASTQC” tool (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to assess quality. Adapters were removed using CUTADAPT [25] with an error rate of 0.1 and a minimum overlap length of 6. Reads were trimmed for length and quality using the “Trim the reads” tool, version 1.2.2, (Phred threshold score <20; read length <20 bp), discarding all miscalled bases, but not duplicates or polyA tails, because reads were aligned on a reference transcriptome. The number of reads retained after removing adapters, low quality, and short reads was >194 million, which is ∼84% of the total number of original 232 million reads.

After the preprocessing and filtering, reads were aligned to the following two reference transcriptomes using “Burrow-Wheeler Aligner”, version 1.2.3 [26]: 1) A. aegypti (www.vectorbase.org; AaegL1.4, v1.00; 18,769 sequences) [27] and 2) A. albopictus (www.ncbi.nlm.nih.gov;transcript shotgun archive accession numbers JO845359-JO913491, 68,413 sequences) [28]. The number of reads that aligned to unique and redundant transcripts in the reference transcriptome was determined for each sample using “Count Features” tool, version 0.91. The dataset was filtered to contain only transcripts with a minimum of five mapped reads for any two replicates in at least one treatment/time combination. Only the subset of transcripts meeting this criterion was used in subsequent analyses.

Considerably more reads mapped onto the A. albopictus transcriptome (∼9.6 million reads/sample; 75% reads mapped) compared to the A. aegypti transcriptome (∼2.4 million reads/sample; 18.5% reads mapped). However, the A. albopictus transcriptome assembly and annotation is incomplete and contains redundancies (i.e., there are several transcript identification numbers corresponding to the same transcript), which limited our ability to accurately identify and quantify specific individual transcripts of interest (e.g., aquaporins, NH₃ detoxification enzymes). Moreover, mapping onto the A. aegypti transcriptome resulted in the detection of 9,813 non-redundant transcripts, which is within the range of ∼7,000–18,000 transcripts detected in RNA-seq studies of A. aegypti isolated tissues or whole animals [12], [17], [29], [30]. Thus, we use the A. aegypti transcriptome and its transcript nomenclature for our downstream analyses.

For quality assessment, “Count Features” output was implemented to examine the dispersion of the biological replicates (libraries per treatment). Counting reads were normalized calculating the RPKM (reads per kilobase per million reads). Pearson's correlation and Principal Component Analysis graphics were generated to assess the similarity of the replications for each condition.

Transcriptome analysis

The read counts generated using “Count Features” output were submitted to the “DESeq” pipeline, version 1.0.0 [31], to identify transcripts with a significant differential expression between treatments/time points. This tool is based on the negative binomial distribution, with normalized libraries by size factor (developing an estimate effective library size) [31]. The comparisons made were a NBF treatment against BF treatments at three time points (3 h, 12 h and 24 h). All of the transcripts with a significant expression change were filtered by a FDR-adjusted P value threshold of 0.05, and their log₂ fold-change value was recorded.

The DAVID v6.7 annotation clustering module [32] was used to classify differentially expressed transcripts into functional groups. Clustering analysis was carried out for the subset of transcripts that had showed sustained up- or down-regulation (i.e., at least two consecutive time points of differential expression). The DAVID is currently not compatible with A. aegypti transcript IDs. Thus, the differentially-expressed transcripts were first converted to A. gambiae transcript IDs using tBLASTx (E-value <10⁻²⁰). Then, enrichment of GO and other annotation terms in candidate sub-lists were explored using the functional annotation clustering tool. This clustering method condenses the input transcript list into functionally related transcripts (annotation clusters), taking into account the similarity of their annotation profiles based on multiple annotation sources (e.g. GO terms and Interpro keywords).

The clusters are assigned an enrichment score, which represents the minus log-transformed geometric mean of the modified Fisher Exact (EASE) Scores within the cluster. Significantly enriched annotation clusters were defined as those containing a minimum enrichment score of 1.3, because the –log (0.05)  = 1.3. Thus, an enrichment score of >1.3 corresponds to a P<0.05. The enrichment score is based on the following parameters: Similarity Term Overlap  =  3; Similarity Threshold  =  0.7; Initial Group Membership  =  3; Final Group Membership  =  5; Multiple Linkage Threshold  =  0.3. Once the significantly-enriched functional clusters were identified, the A. gambiae transcript IDs within them were converted back to their respective A. aegypti transcript IDs.

We also performed a preliminary DAVID clustering analysis using reads mapped to the existing A. albopictus reference transcriptome, despite its incomplete assembly and annotation. Notably, there was a good correlation between the enriched functional clusters identified using this reference and those using the A. aegypti reference. For example, the thioredoxin, glutathione S-transferase, vitamin binding, cofactor metabolic process, oxidative phosphorylation/ATP synthesis, protein biosynthesis, glycoylsis, and ATPase activity clusters were enriched in both DAVID analyses. Thus, our decision to use the A. aegypti transcriptome, which allows for better identification and quantification of specific transcripts (see above), does not compromise our ability to identify enriched functional pathways.

Differential expression in Malpighian tubules after blood feeding

DESeq was used to search for transcripts differentially expressed between the 24 h NBF control and the BF treatments at each time point. Using the A. aegypti transcriptome as a reference, a total of 1,857 non-redundant transcripts was found to be differentially expressed over all of the time points (∼10% of the A. aegypti transcriptome). Table 1 shows that the Malpighian tubules from the BF mosquitoes were characterized by progressive increases in differential expression throughout the time series. At each time point, the differentially expressed transcripts consist of similar numbers of up- and down-regulated transcripts.

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Table 1. Total number of transcripts whose abundance is significantly affected by blood feeding at each time point compared to non-blood fed controls.

https://doi.org/10.1371/journal.pntd.0002929.t001

We next aimed to identify enriched, functional pathways within the differentially expressed transcripts using a DAVID functional clustering analysis [32], [33]. We focused our analysis on transcripts that exhibited ‘sustained’ changes in differential expression after blood feeding, which we defined as those significantly up- or down-regulated for at least two consecutive time periods. Based on the A. aegypti transcriptome, a total of 669 transcripts met our ‘sustained’ criterion, consisting of 340 up-regulated transcripts and 329 down-regulated transcripts. As shown in Table 2, the DAVID analysis revealed a significant enrichment (enrichment score > 1.3) of 1) nine functional groups among the sustained, up-regulated transcripts and 2) six functional groups among the sustained, down-regulated transcripts. The identities of the transcripts that comprise the functional groups of Table 2 and their respective heat maps of differential expression are shown in Figures S1–S15.

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Table 2. DAVID functional clusters that are significantly enriched among the transcripts in Malpighian tubules exhibiting a sustained, up-regulation or down-regulation after blood feeding.

https://doi.org/10.1371/journal.pntd.0002929.t002

Cursory interpretations of the changes to these broad functional groups and the transcripts within them suggests that blood feeding promotes the expression of transcripts associated with 1) antioxidants and detoxification, 2) proteolytic activity, 3) amino acid metabolism, and 4) cytoskeletal dynamics. On the other hand, blood feeding appears to suppress the expression of transcripts associated with 1) oxidative metabolism, 2) active transport, and 3) mRNA translation. Below, we discuss these interpretations in more detail with the caveat that transcript levels may not necessarily reflect protein abundance, biochemical activity, or physiological function. Thus, we consider our interpretations as the building of hypotheses that will require testing in future studies using functional genetic, biochemical, and physiological techniques.

Down-regulation of transcripts associated with oxidative metabolism and active transport—Potential implications for diuretic fluid secretion

The mosquito Malpighian tubule epithelium is well-studied, because of its remarkable capacity for active transepithelial fluid secretion, which mediates the post-prandial diuresis. The vacuolar (V-type) H⁺-ATPase is the ultimate energizer of transepithelial fluid secretion in the epithelium [34]. This proton pump resides in the luminal brush border of principal cells where it is situated in close proximity to mitochondria that fuel the pump with ATP [35], [36]; the pump is a multisubunit protein consisting of two sectors: 1) a catalytic, cytosolic V₁ sector and 2) a H⁺-translocating, membrane-bound V₀ sector [37]. Inhibiting the pump or the production of ATP in the epithelium effectively inhibits fluid secretion [34], [38]. Thus, the enrichment of the ‘oxidative phosphorylation/ATP synthesis’, ‘ATPase activity’, ‘glycolysis’, and ‘sugar/inositol transporter’ functional clusters among the transcripts that exhibited a sustained down-regulation (Table 2) caught our attention.

Listed prominently among the down-regulated transcripts in the ‘oxidative phosphorylation/ATP synthesis’ (Figure S1) and ‘ATPase activity’ (Figure S2) functional clusters are those encoding subunits of the V-type H⁺-ATPase. Remarkably, as shown in Figure 2, fourteen transcripts encoding subunits of the V-type H⁺-ATPase exhibit a sustained down-regulation after blood feeding, while only one shows a sustained up-regulation (AAEL003743-RA). Furthermore, a manual search of all the differentially-expressed transcripts (including those not considered ‘sustained’) revealed three other transcripts associated with the V-type H⁺-ATPase that are down-regulated transiently at one or two non-consecutive time points (i.e., AAEL002464-RA, AAEL010819-RA, AAEL010819-RB in Figure 2). Among all of these down-regulated transcripts, nine encode subunits of the V₁ sector of the V-type H⁺-ATPase, seven encode subunits of the V₀ sector, and one encodes an accessory protein (Figure 2). The only up-regulated transcript encodes subunit ‘a’ of the V₀ sector (a.k.a. vha100-1).

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Figure 2. Differential expression after blood feeding of transcripts encoding subunits of the V-type H⁺-ATPase.

Blue shading indicates significant down-regulation compared to NBF controls, whereas yellow shading indicates significant up-regulation compared to NBF controls. Lack of shading indicates no significant difference relative to NBF controls. Degree of shading is based on value of Log₂ fold change as indicated by the scale below on the right.

https://doi.org/10.1371/journal.pntd.0002929.g002

The above changes to transcripts of the V-type H⁺-ATPase in the Malpighian tubules of A. albopictus contrast with those previously reported in the midgut of A. aegypti after blood feeding [19]. In our study, nearly all subunits of the V-type H⁺-ATPase exhibited a down-regulation in Malpighian tubules after blood feeding (Figure 2), whereas Sanders et al. found that transcripts encoding V-type H⁺-ATPase subunits exhibited an up-regulation in the midgut of A. aegypti at 12 h and 24 h after blood feeding [19]. These contrasting results suggest that the regulation of V-type H⁺-ATPase expression in response to blood feeding is tissue dependent in mosquitoes.

Notable among the transcripts that exhibited a sustained down-regulation after blood feeding in the ‘oxidative phosphorylation/ATP synthesis’ (Figure S1) and ‘glycolysis’ (Figure S3) functional clusters are those encoding enzymes associated with glycolysis, the citric acid cycle, and ATP synthesis, such as phosphofructokinase, pyruvate kinase, enolase, 2-oxoglutarate dehydrogenase, glycerol-3-phosphate dehydrogenase, and acetyl-CoA synthetase. In addition, within the ‘oxidative phosphorylation/ATP synthesis’ (Figure S1) and ‘sugar/inositol transporter’ (Figure S4) functional clusters are transcripts encoding putative SLC2-like sugar transporters, which import glucose into cells for use as a fuel to generate ATP. Thus, in Malpighian tubules, blood-feeding leads to a decrease in the abundance of transcripts encoding enzymes associated with the catabolism of glucose and synthesis of ATP, which is consistent with the aforementioned decrease in abundance of transcripts encoding subunits of the V-type H⁺-ATPase subunits.

Also notable among the transcripts listed in the ‘oxidative phosphorylation/ATP synthesis’ (Figure S1) functional cluster are those encoding ion transport mechanisms that are known or hypothesized to play a role in the transepithelial secretion of ions by mosquito Malpighian tubules. We discuss these mechanisms below.

Mechanisms of K⁺ uptake.

Both barium-sensitive inward-rectifying K⁺ (Kir) channels and bumetanide-sensitive Na,K,2Cl-cotransporters (NKCCs) are considered the major mechanisms for the uptake of K⁺ from the hemolymph across the basolateral membranes of mosquito Malpighian tubules [39], [40], [41], where they presumably localize to principal cells. As shown in Figure 3, blood-feeding elicits a sustained down-regulation of two transcripts encoding Kir channel subunits (AAEL008931-RA, AAEL013373-RA) and one transcript encoding a putative NKCC (AAEL006180-RA). We recently cloned and characterized AAEL008931-RA (Kir2B) from the Malpighian tubules of A. aegypti and have confirmed that it encodes a barium-sensitive Kir channel [41]. The NKCC is an ortholog of Drosophila melanogaster Ncc69, which has been shown to a play a key role in fluid and K⁺ secretion in fruit fly Malpighian tubules [42]. These changes in Kir and NKCC transcript abundance suggest that blood-feeding leads to a decrease in the capacity of the tubules to uptake K⁺ across the basolateral membrane, which is expected to reduce the diuretic capacity of the tubules.

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Figure 3. Differential expression after blood feeding of transcripts encoding known and putative ion and water transport mechanisms.

Blue shading indicates significant down-regulation compared to NBF controls, whereas yellow shading indicates significant up-regulation compared to NBF controls. Lack of shading indicates no significant difference relative to NBF controls. Degree of shading is based on value of Log₂ fold change as indicated on the right.

https://doi.org/10.1371/journal.pntd.0002929.g003

Down-regulation of transcripts associated with the translation of mRNA

The other functional clusters enriched among the transcripts that exhibited a sustained down-regulation are related to the translation of mRNA (i.e., protein biosynthesis and translational elongation; Table 2). These transcripts consist primarily of ribosomal protein subunits and translation/elongation factors that exhibit a down-regulation at 12 h and 24 h after a blood meal (Figure S5 and Figure S6), which suggests that most newly-translated proteins in the tubules in response to blood feeding are synthesized within 12 h. Furthermore, the data suggest that during the chronic processing of blood meals (24–48 h after blood feeding) the capacity of the tubules for de novo protein synthesis may decrease. These observations in the Malpighian tubules of A. albopictus are similar to results of previous studies in the midgut and fat body of A. aegypti, where blood feeding led to a down-regulation of transcripts encoding ribosomal protein subunits and/or translation factors within 12 h to 24 h after a blood meal [17], [19], [52].

Up-regulation of transcripts associated with antioxidants and detoxification—Implications for heme metabolism/detoxification and metabolite excretion

Hemoglobin is the most abundant protein in mammalian blood, and its digestion leads to the production of heme, a highly toxic metabolite that causes cell and tissue damage via oxidative stress and/or the disruption of plasma membranes [53]. Mosquitoes utilize a variety of mechanisms to detoxify heme and limit its absorption into the hemolymph. The first line of defense is found in the midgut, which secretes a peritrophic matrix that encapsulates the ingested blood cells and may sequester more than half of the amount of heme in a typical blood meal [54], [55]. Additional mechanisms for heme detoxification include the 1) enzymatic degradation of heme by heme oxygenase (HO) to produce biliverdin, Fe²⁺, and carbon monoxide [56], 2) chelation of heme by xanthurenic acid (XA), which is a product of the kynurenine pathway of tryptophan catabolism [57], [58], and 3) binding and/or catabolism of heme by glutathione S-transferases (GSTs) [59], [60]. Furthermore, protection against heme-induced, free-radical damage in mosquitoes can be mediated by: 1) antioxidant enzymes, such as glutathione peroxidase (GP), thioredoxin peroxidase (THP), thioredoxin reductase (THR), superoxide dismutase (SOD), and catalase (CAT); 2) antioxidant proteins, such as thioredoxin (TH); and 3) small molecule antioxidants, such as glutathione and uric acid [53].

Thus, we were intrigued by the enrichment of the ‘thioredoxin’ and ‘glutathione S-transferase’ functional clusters among the transcripts that exhibited a sustained up-regulation after blood feeding (Table 2; Figures S7–S8). Furthermore, we noticed that the ‘cofactor metabolic process’ (Figure S9) and ‘vitamin biosynthetic process’ (Figure S10) functional clusters contained several transcripts associated with putative antioxidant and detoxification mechanisms, and that the ‘ATPase/AAA+ type’ (Figure S11) functional cluster contained several transcripts encoding putative ATP-binding cassette (ABC) transporters, which play key roles in insect metabolite/xenobiotic excretion [61]. Below, we discuss the up-regulation of transcripts after a blood meal within the aforementioned functional clusters in the context of 1) the prevention of heme-induced oxidative cell and tissue damage and 2) the detoxification/excretion of heme and heme-related metabolites.

Heme detoxification and antioxidant production mechanisms.

As shown in Figure 4, we find a remarkable, sustained up-regulation after blood feeding of several transcripts encoding putative heme-detoxification mechanisms, including 4 transcripts that encode enzymes associated with XA production (kynurenine 3-monoxygenases and a tryptophan dioxygenase) and 8 transcripts encoding GSTs (Delta, Sigma, Epsilon, and Rho classes). A manual search for other GSTs among the transcripts that were differentially expressed (non-sustained) revealed 3 others: 1) a putative microsomal GST (AAEL006829-RA), which was up-regulated, albeit transiently, at 3 h and 24 h after blood feeding, 2) the heme-binding GSTX2 (AAEL010500-RA), which was up-regulated transiently at 3 h, and 3) a Zeta class GST (AAEL011934-RA), which was down-regulated by 24 h after blood feeding (Figure 4). Interestingly, two of the up-regulated GST transcripts (AAEL007962-RA, GSTe4; AAEL010500-RA, GSTX2) were also found to be up-regulated in pyrethroid-resistant lines of A. aegypti [62], [63], which suggests putative roles of these GSTs in both heme and insecticide detoxification in mosquitoes.

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Figure 4. Differential expression after blood feeding of transcripts associated with heme detoxification and antioxidant mechanisms.

Blue shading indicates significant down-regulation compared to NBF controls, whereas yellow shading indicates significant up-regulation compared to NBF controls. Lack of shading indicates no significant difference relative to NBF controls. Degree of shading is based on value of Log₂ fold change as indicated by the scale below on the right.

https://doi.org/10.1371/journal.pntd.0002929.g004

Transcripts encoding putative antioxidant mechanisms for protection against heme-induced oxidative stress are also in general up-regulated in Malpighian tubules after blood feeding. Namely, transcripts encoding CAT, GP, TH, THP, and THR exhibited a sustained up-regulation after a blood meal (Figure 4). A manual search for additional differentially-expressed transcripts (non-sustained) encoding THR revealed two others (AAEL002886-RA,-RB), which were transiently up-regulated at 3 h (Figure 4); a similar search for transcripts encoding THPs found one (AAEL004112-RA) that is up-regulated by 24 h and another (AAEL013528-RA) that is down-regulated by 24 h (Figure 4). Similar patterns in the expression of CAT and THR have been observed in the midgut of A. aegypti after a blood meal [19].

The consensus of the above results suggests that the molecular capacity of the Malpighian tubules to detoxify heme and protect against heme-induced free radical damage increases after mosquitoes ingest a blood meal. Thus, the data may point towards a putative new role of the tubule epithelium after a blood meal in the detoxification of heme that enters the hemolymph.

Heme and heme-metabolite excretion.

In addition to direct heme detoxification, the up-regulation of GSTs can be interpreted as serving a potential role in improving the clearance of heme metabolites, such as biliverdin (derived from HO activity), from the hemolymph. Mammalian GSTs possess binding-sites for various organic molecules, including biliverdin, bilirubin, and even heme [64], [65], [66]. In the mammalian liver, the binding of bilirubin by intracellular GSTs provides a favorable diffusional gradient for bilirubin uptake by liver cells [65]. Moreover, GSTs are known to conjugate reduced glutathione onto large organic molecules thereby increasing their solubility, decreasing their toxicity, and enhancing their transport by ABC transporters [67]. Thus, it is reasonable to hypothesize that one or more of the up-regulated GSTs in Malpighian tubules may contribute towards 1) maintaining a favorable chemical gradient for the uptake of heme and/or biliverdin from the hemolymph, and/or 2) chemically modifying heme and/or biliverdin to improve their excretion.

In regards to the potential excretion of heme and heme-derived metabolites by Malpighian tubules, putative ABC transporters are among those in the ‘ATPase/AAA+ type’ functional cluster (Figure S11). In general, ABC transporters are promiscuous in their transport substrates, which include heme, bilirubin, glutathione-conjugated organic compounds, uric acid, xenobiotics (including insecticides), ions (e.g., cytstic-fibrosis transmembrane regulator), and lipids [68], [69], [70], [71], [72]. As shown in Figure 5, five transcripts encoding ABC transporters (of the ‘A’, ‘B’, and ‘C’ types) exhibit a sustained up-regulation after blood feeding. Furthermore, a manual search of all the differentially-expressed transcripts (non-sustained) revealed eight others (of the ‘A’, ‘B’, ‘C’, and ‘G’ types) that exhibited a transient up-regulation at one or two discontinuous time points (Figure 5). Only one transcript (AAEL005929-RA) exhibited a down-regulation and another (AAEL005937-RA) exhibited an up-regulation at 3 h followed by a down-regulation at 12 h. Thus, there is a general up-regulation of transcripts encoding ABC transporters, which suggests that blood feeding leads to an increased capacity of the tubule epithelium for the excretion of metabolites and xenobiotics derived from the blood meal.

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Figure 5. Differential expression after blood feeding of transcripts encoding putative ABC transporters.

Blue shading indicates significant down-regulation compared to NBF controls, whereas yellow shading indicates significant up-regulation compared to NBF controls. Lack of shading indicates no significant difference relative to NBF controls. Degree of shading is based on value of Log₂ fold change as indicated by the scale below on the right.

https://doi.org/10.1371/journal.pntd.0002929.g005

Up-regulation of transcripts associated with proteasomes—Implications for proteolytic activity

Another functional cluster enriched among the transcripts that exhibited a sustained up-regulation is the ‘proteasome complex’ (Table 2), which is related to the degradation of protein. These transcripts consist entirely of those encoding proteasome or protease regulatory subunits and most exhibit an up-regulation at 3 h and 12 h after a blood meal (Figure S12), which suggests that the tubules enhance their molecular capacity for proteolytic activity early after a blood meal. Enhanced proteolytic activity within the tubule epithelium may lead to the degradation of 1) proteins encoded by the transcripts that are down-regulated after blood feeding, and/or 2) proteins that may experience oxidative damage from heme. An increase of proteasome activity would also be expected to result in an increase of free amino-acids available for the synthesis of new proteins [73]—perhaps those associated with the ‘thioredoxin’ and ‘glutathione S-transferase’ functional clusters mentioned above.

Up-regulation of transcripts associated with amino acid metabolism—Potential insights into ammonia detoxification

Consistent with the enrichment of the ‘proteasome complex’ functional cluster among up-regulated transcripts, which is expected to increase the abundance of free amino acids (see above), there is a corresponding enrichment in the ‘amine biosynthetic process’ cluster (Table 2). The transcripts within this cluster consist primarily of those encoding enzymes associated with amino-acid catabolism and/or biosynthesis, such as cysteine dioxygenase, 2-amino-3-ketobutyrate coenzyme A ligase, glutamine synthetase, phosphoserine phosphatase, ornithine decarboxylase, and phosphoserine aminotransferase (Figure S13). Similar (as well as redundant) transcripts are also found in the ‘vitamin binding’ functional cluster, such as alanine-glyoxylate aminotransferase and alanine aminotransferase (Figure S14). Notably, the up-regulation of these transcripts occurs at 12 h and 24 h, appearing to follow the up-regulation of transcripts associated with the proteasome (Figure S12). Thus, the potential increase in the availability of amino acids derived from proteasome activity in the tubules may be followed by an increased molecular capacity to breakdown and/or convert amino acids into other products.

The aforementioned up-regulation of glutamine synthetase and alanine aminotransferase drew our attention to a potential role of the Malpighian tubules in the handling of ammonia. As mosquitoes metabolize a protein-rich blood meal, they face a potentially toxic accumulation of ammonia in their hemolymph and tissues from the catabolism of proteins and amino acids in the blood meal. Glutamine synthetase and alanine aminotransferase play prominent roles in detoxifying the ammonia (see below and Figure 6).

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Figure 6. Biochemical pathways for ammonia detoxification in mosquitoes.

Redrawn from Isoe and Scaraffia [9]. Yellow and blue text indicates an enzyme encoded by a transcript that is up-regulated and down-regulated, respectively, after blood feeding.

https://doi.org/10.1371/journal.pntd.0002929.g006

In brief, to prevent the build-up of toxic ammonia, mosquitoes have a remarkable capacity to fix and assimilate it into free amino acids (e.g., alanine, proline, glutamine) via a series of biochemical reactions catalyzed by enzymes, such as glutamine synthetase (GS), glutamate dehydrogenase (GDH), glutamate synthase (GltS), alanine aminotransferase (ALAT), and pyrrolidine-5-carboxylate synthase (P5CS) and reductase (P5CR) (Figure 6) [9], [74], [75], [76]. Moreover, glutamine can serve as a substrate for the production of uric acid through a pathway that includes xanthine dehydrogenase (XDH) among other enzymes [9], [76]. Once uric acid is produced, it can be excreted directly or further converted into allantoin, allantoic acid, and urea through a series of biochemical reactions catalyzed by urate oxidase (UO), allantoinase (ALLN), and allantoicase (AALC), respectively (Figure 6) [9], [76].

Figure 7 shows the transcripts associated with this pathway in Malpighian tubules that are differentially expressed after blood feeding. Namely, two transcripts encoding GS, one transcript encoding ALAT, and one transcript encoding XDH exhibit a sustained up-regulation after blood feeding. Three transcripts encoding a GDH and two transcripts encoding ALAT are each transiently up-regulated at 12 h, whereas one transcript encoding GltS is transiently down-regulated at 12 h (Figure 7). The up-regulation of these transcripts occurs at 12 h and/or 24 h after blood feeding, which coincides with the putative availability of amino acids from increased proteasome activity in the tubule (see above), as well as a period of intense protein digestion of the blood meal in the midgut [10], [11].

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Figure 7. Differential expression after blood feeding of transcripts associated with ammonia detoxification.

Blue shading indicates significant down-regulation compared to NBF controls, whereas yellow shading indicates significant up-regulation compared to NBF controls. Lack of shading indicates no significant difference relative to NBF controls. Degree of shading is based on value of Log₂ fold change as indicated by the scale below on the right.

https://doi.org/10.1371/journal.pntd.0002929.g007

Interpreting these molecular findings in the context of the ammonia detoxification pathway suggests that the Malpighian tubules detoxify ammonia by converting it to glutamate via GDH and/or glutamine via GS (Figure 6). Given the up-regulation of ALAT, it is reasonable to propose that any newly-formed glutamate is converted into alanine (Figure 6). This putative handling of ammonia is similar to that reported for the midgut of A. aegypti, which fixes and assimilates ammonia into glutamine and alanine, as opposed to the fat body which fixes and assimilates ammonia into glutamine and proline [77]. The fate of the alanine in Malpighian tubules is unknown, but it is possible that it is shuttled to the fat body for conversion into proline, which can then be shuttled to the flight muscle for use as an energy source [78].

The fate of glutamine in Malpighian tubules is also unknown, but it is possible that it is converted into uric acid for excretion, as indicated by 1) the sustained up-regulation of XDH, and 2) the transient down-regulation of GltS, after blood feeding (Figure 7). Since transcripts encoding UO, ALLN, and ALLC were not differentially expressed after blood feeding (data not shown), the uric acid may be directly secreted by the tubules for excretion (perhaps by an ABC transporter in Figure 5), or it may be retained by the epithelium for use as an antioxidant to combat potential oxidative damage due to heme. Consistent with the former notion, uric acid is excreted by mosquitoes after a blood meal [79]. Likewise, uric acid is excreted by tsetse flies and reduviid bugs following a blood meal [80], [81], [82].

Up-regulation of transcripts associated with cytoskeletal dynamics

The remaining functional cluster enriched among the transcripts that exhibited a sustained up-regulation is related to cytoskeletal dynamics (i.e., ‘tubulin, GTPase domain’) (Table 2). The transcripts in this functional cluster consist primarily of those encoding components of microtubules, such as tubulin chains (alpha and beta), dynein light chains, and microtubule-associated proteins (Figure S15). Another related transcript populating this cluster is one encoding a putative Rab GTPase (AAEL006091-RA); Rab GTPases play important roles in regulating microtubule-mediated trafficking of vesicular cargo [83]. These changes suggest that blood feeding leads to a more dynamic microtubule-based cytoskeleton, which may be associated with the intracellular trafficking of vesicles and/or organelles. At least one study has found that the actin cytoskeleton of principal cells plays a key role in modulating diuretic fluid secretion in A. aegypti Malpighian tubules [84].

Putative changes in the microtubule-based cytoskeleton would also be consistent with a potential functional transition of the epithelium after blood feeding. For example, if the capacity of the tubule for diuresis indeed decreases, as expected by the down-regulation of transcripts associated with the V-type H⁺-ATPase and other ion/water transport mechanisms (Figures 2–3), then enhanced vesicular trafficking may play a key role in the endocytosis and degradation of these membrane-bound proteins. Likewise, if the capacity of the tubules for detoxification and metabolite excretion indeed increases, as expected by the up-regulation of transcripts associated with heme and ammonia detoxification/excretion (Figures 4–6), then the cytoskeletal dynamics may facilitate the movements of newly synthesized membrane-bound transporters that mediate the excretion of metabolites, such as ABC transporters.

It is also possible that a more dynamic microtubule cytoskeleton would facilitate the movements of organelles within the epithelial cells. For example, retraction of mitochrondria from the apical microvilli in principal cells is associated with a decrease of fluid secretion in Malpighian tubules isolated from pupal stages of mosquitoes [85]. Thus, similar microtubule-mediated movements of mitochondria may occur during the chronic processing of blood meals (24–48 h after blood feeding) to further contribute to a putative decreased capacity for diuresis.

Conclusions and significance

The present study provides the first transcriptomic analysis of the Malpighian tubules of a mosquito after a blood meal, and is also the first to be conducted in A. albopictus after blood feeding. The results reveal molecular changes in transcript accumulation in the tubule epithelium within the first 24 h after a blood meal that suggest a remarkable functional transition of the epithelium from one dedicated to electrolyte and fluid excretion to one dedicated to detoxification and metabolite processing (Figure 8). Moreover, the results uncover new putative roles of the Malpighian tubules in the chronic processing of blood meals after the post-prandial diuresis ends ∼2 h after a blood meal [8]. Thus, the tubule epithelium may represent an even more valuable target for the development of novel insecticides than has been previously appreciated. The next important step to complete is to validate the hypothesized functional transition of the epithelium after a blood meal using biochemical and physiological approaches.

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Figure 8. Summary of the molecular changes identified in the Malpighian tubule epithelium after blood feeding in the present study, with an emphasis on the mechanisms of transepithelial fluid secretion.

Blue-shaded items represent putative mechanisms or pathways that are down-regulated after blood feeding, whereas yellow-shaded text boxes represent putative pathways or functions that are up-regulated after blood feeding. See text for details. Gray-shaded items are ion transport mechanisms not examined in the present study. AE, anion exchanger [48]; AQP, aquaporin [22]; ATP, adenosine triphosphate [38]; ADP adenosine diphosphate; ClC, chloride channel [86]; Kir, inward-rectifying potassium channel [41]; KCC, potassium-chloride cotransporter [87]; PPK, pickpocket sodium channel (hypothesized, present study); NHA, sodium-hydrogen antiporter [88]; NHE, sodium-hydrogen exchanger [45]; NKCC, sodium-potassium-chloride cotransporter [89]; VHA, V-type H⁺-ATPase [35].

https://doi.org/10.1371/journal.pntd.0002929.g008