- Research article
- Open Access
Exploring the midgut transcriptome of Phlebotomus papatasi: comparative analysis of expression profiles of sugar-fed, blood-fed and Leishmania major-infected sandflies
- Marcelo Ramalho-Ortigão†1, 2,
- Ryan C Jochim†1, 3,
- Jennifer M Anderson1,
- Phillip G Lawyer4,
- Van-My Pham1,
- Shaden Kamhawi1 and
- Jesus G Valenzuela1Email author
© Ramalho-Ortigão et al; licensee BioMed Central Ltd. 2007
- Received: 24 April 2007
- Accepted: 30 August 2007
- Published: 30 August 2007
In sandflies, the blood meal is responsible for the induction of several physiologic processes that culminate in egg development and maturation. During blood feeding, infected sandflies are also able to transmit the parasite Leishmania to a suitable host. Many blood-induced molecules play significant roles during Leishmania development in the sandfly midgut, including parasite killing within the endoperitrophic space. In this work, we randomly sequenced transcripts from three distinct high quality full-length female Phlebotomus papatasi midgut-specific cDNA libraries from sugar-fed, blood-fed and Leishmania major-infected sandflies. Furthermore, we compared the transcript expression profiles from the three different cDNA libraries by customized bioinformatics analysis and validated these findings by semi-quantitative PCR and real-time PCR.
Transcriptome analysis of 4010 cDNA clones resulted in the identification of the most abundant P. papatasi midgut-specific transcripts. The identified molecules included those with putative roles in digestion and peritrophic matrix formation, among others. Moreover, we identified sandfly midgut transcripts that are expressed only after a blood meal, such as microvilli associated-like protein (PpMVP1, PpMVP2 and PpMVP3), a peritrophin (PpPer1), trypsin 4 (PpTryp4), chymotrypsin PpChym2, and two unknown proteins. Of interest, many of these overabundant transcripts such as PpChym2, PpMVP1, PpMVP2, PpPer1 and PpPer2 were of lower abundance when the sandfly was given a blood meal in the presence of L. major.
This tissue-specific transcriptome analysis provides a comprehensive look at the repertoire of transcripts present in the midgut of the sandfly P. papatasi. Furthermore, the customized bioinformatic analysis allowed us to compare and identify the overall transcript abundance from sugar-fed, blood-fed and Leishmania-infected sandflies. The suggested upregulation of specific transcripts in a blood-fed cDNA library were validated by real-time PCR, suggesting that this customized bioinformatic analysis is a powerful and accurate tool useful in analysing expression profiles from different cDNA libraries. Additionally, the findings presented in this work suggest that the Leishmania parasite is modulating key enzymes or proteins in the gut of the sandfly that may be beneficial for its establishment and survival.
- cDNA Library
- Blood Meal
- Peritrophic Matrix
- Post Blood Meal
Cutaneous leishmaniasis due to L. major is found throughout the Old World, including the Middle East and West Africa. Phlebotomus papatasi is the principal vector for this parasite and is refractory to the development of other species of Leishmania.
Upon taking a blood meal, hematophagous arthropods express a large number of molecules that participate in various physiologic processes ranging from blood digestion to egg development. Furthermore, many insects can either obtain or transmit pathogens during the acquisition of a blood meal. In blood-feeding arthropods, the midgut plays a crucial role as the primary organ involved in processing the blood meal and, in some instances, molecules expressed in the midgut of an insect vector have been shown to directly influence pathogen establishment [1, 2]. Certain pathogens, such as Leishmania, appear able to modulate the activity of sandfly midgut proteases for their own benefit or survival [3, 4].
Sequenced data sets containing information regarding expression profiles of anopheline and culicine mosquitoes, such as Anopheles gambiae and Aedes aegypti, following a blood meal have become available [5, 6]. Other datasets now encompass insects such as Pedicullus humanus  and Cullicoides sonorensis . In comparison, transcriptome information regarding sandflies is limited. Previous work has focused mainly on the sandfly salivary gland [9–11], whereas only a small number of sandfly-specific midgut cDNA have been identified [12–16]. Recently, a large set of cDNA transcripts from the whole sandfly Lutzomyia longipalpis has been sequenced, providing greater information regarding molecules present in sandflies . However, the information regarding sandfly midgut-specific transcripts remains poor.
In this work, we embarked on a comprehensive study of P. papatasi midgut-specific transcripts and compared the expression profile of these transcripts by directly comparing those obtained from midguts of females fed on sugar only, on blood or on blood containing L. major. With this approach, we have identified several P. papatasi midgut-specific transcripts that are differentially expressed after a blood meal and in the presence of L. major.
The midgut is the tissue where Leishmania development takes place while within its sand fly vector. Within the midgut environment, Leishmania possibly interacts with various secreted molecules and cell types lining the midgut epithelia. In order to gain greater insight into the repertoire of the proteins present in the midgut of P. papatasi, we constructed and sequenced three high quality full-length cDNA libraries from the midgut of sandflies fed either on sugar only (unfed), blood or blood containing L. major. 4010 high quality sequenced clones obtained from the three cDNA libraries were combined and analysed resulting in the formation of 1382 clusters. Each cluster may contain a large number of transcripts which creates a contig (high quality consensus sequence) or may have a single transcript that can be defined as a singleton. Therefore, we will utilise the nomenclature of "cluster" in the remainder of the manuscript to define either a consensus sequence from various transcripts or a singleton.
List of Phlebotomus papatasi midgut-specific sequences, clusters, and sequences per cluster of cDNA libraries made from flies sugar-fed, blood-fed, and blood fed with Leishmania major parasites
Number of Clusters
Number of Sequences
protein synthesis machinery
protein modification machinery
protein export machinery
nuclear metabolism and regulation
metabolism, amino acid
metabolism, nucleic acid and nucleotides
conserved of unknown function
Clusters of combined P. papatasi midgut cDNA libraries (sugar-fed, blood-fed and Leishmania major -infected) of transcripts with high quality sequences
NCBI best match to NR database
microvilli membrane protein [A. aegypti ]
microvilli membrane protein [A. aegypti ]
microvilli membrane protein [A. aegypti]
LP07759p [D. melanogaster ]
hypothetical protein 17 [L. obliqua ]
40S ribosomal S30 protein
ENSANGP00000028746 [A. gambiae ]
similar to CG4778-PA [T. castaneum ]
similar to CG4778-PA [T. castaneum ]
chymotrypsin [P. papatasi]
carboxypeptidase B [A. aegypti ]
ribosomal protein S20 [B. mori ]
40S ribosomal protein S20
trypsin 1 [P. papatasi ]
CG32276-PB, isoform B [D. melanogaster ]
Ribosome associated membrane protein
Ribosomal protein L19 [D. melanogaster ]
60s ribosomal protein L19
trypsin 2 [P. papatasi ]
RE59709p [D. melanogaster ]
60S ribosomal protein L32
similar to D. melanogaster CG3203 [D. yakuba ]
60S ribosomal protein L17
peritrophin-like protein 1 [C. felis ]
Ribosomal protein L29 [D. melanogaster ]
60S ribosomal protein L29
CG13551 [D. melanogaster ]
LD17235p [D. melanogaster ]
60S ribosomal protein L11
similar to D. melanogaster RpL14 [D. yakuba ]
60S ribosomal protein L14
60S acidic ribosomal protein P1 [S. frugiperda ]
60s Acidic ribosomal protein P1
ENSANGP00000019623 [A. gambiae ]
S7 ribosomal protein [C. pipiens quinquefasciatus ]
40S ribosomal protein S7
unknown [C. sonorensis ]
similar to D. melanogaster qm [D. yakuba ]
60s ribosomal protein L10
trypsin 4 [P. papatasi ]
microvilli membrane protein [A. aegypti ]
Cr-PII [P. americana ]
ENSANGP00000017713 [A. gambiae ]
hypothetical protein [T. castaneum ]
GA13179-PA [D. pseudoobscura ]
TPA_inf: HDC07203 [D. melanogaster ]
GA16408-PA [D. pseudoobscura ]
Kazal type serine protease inhibitor
carboxypeptidase A [A. aegypti ]
midgut specific galectin [P. papatasi ]
GA15307-PA [D. pseudoobscura ]
Glutathione S-transferase [M. domestica]
10 kDa salivary protein [P. ariasi ]
ribosomal protein S8 [A. albopictus ]
40S ribosomal protein S8
60S acidic ribosomal protein P2 [A. aegypti ]
60S acidic ribosomal protein P2
ENSANGP00000016569 [A. gambiae ]
membrane LPS inducible TNF protein
similar to D. melanogaster RpS18 [D. yakuba ]
40S ribosomal protein S18
trypsin 3 [P. papatasi ]
CG30415-PB, isoform B [D. melanogaster ]
similar to CG2998-PA [T. castaneum ]
40S ribosomal protein S28
Ribosomal protein L23 [D. melanogaster ]
60S ribosomal protein L23
similar to D. melanogaster RpS12 [D. yakuba ]
40S ribosomal protein S12
ENSANGP00000021011 [A. gambiae ]
similar to D. melanogaster CG2033 [D. yakuba ]
40S ribosomal protein S15
ENSANGP00000013724 [A. gambiae ]
cyclophylin isoform [A. aegypti ]
60S ribosomal protein L40 [A. albopictus ]
Ubiquitin/ribosomal L40 fusion
similar to ENSANGP00000002356 [A. mellifera ]
chymotrypsin [P. papatasi ]
GA16582-PA [D. pseudoobscura ]
60S ribosomal protein L12
similar to D. melanogaster CG2099 [D. yakuba ]
60S ribosomal protein L35A
translation factor SUI1-like protein [A. aegypti ]
Translation initiation factor 1
GA10714-PA [D. pseudoobscura ]
ADP ribosylation factor
similar to D. melanogaster CG10423 [D. yakuba ]
40s ribosomal protein S27
ENSANGP00000026718 [A. gambiae ]
Cytochrome C oxidase subunit IV
unknown [C. sonorensis ]
cytochrome b [P. papatasi ]
similar to CG9916-PA isoform 1 [T. castaneum ]
ribosomal protein S17e [Eucinetus sp. ]
40S ribosomal protein S17
10 kDa salivary protein [P. ariasi ]
larval chymotrypsin-like protein [A. aegypti ]
peroxiredoxin-like protein [A. aegypti ]
glutathione S-transferase [A. aegypti ]
midgut chitinase [P. papatasi ]
Microvilli-associated like proteins
Astacin-like zinc metalloprotease
Kazal-type serine protease inhibitor
Glutathione S-transferase (GST)
From clusters 125 and 232, two transcripts were identified to encode putative GSTs with homology to other dipteran GSTs in the Sigma and Delta/Epsilon classes, respectively. The predicted molecular weights of the two putative proteins are similar at 23.2 kDa for cluster 125 and 24.5 kDa for cluster 232. Within the midgut, these proteins may play an important role in the regulation of reactive oxygen species which occur as a by-product of hemoglobin digestion. Cluster 125 and 232 share high protein sequence similarity with L. longipalpis ESTs NSFM-105e10 and NSFM-74c11, respectively.
A large number of clusters produced by the three cDNA libraries have no sequence similarity to other known proteins. This has also been observed in the analysis of the Chironomus tentans midgut with good evidence that the unknown transcripts contained coding sequences . It is also possible that the abundance of unidentifiable sequences may be caused by the sequence quality of the transcripts or that the captured sequences are 3' untranslated regions, non-coding small nuclear RNA, or sequences of uncharacterised organisms such as bacteria and yeast present in the sandfly midgut. A number of clusters with unknown functions were identified as coding sequences which exhibited signal peptides, such as clusters 11 and 126.
Functionally characterised proteins
From the three cDNA libraries, we identified chitinase transcripts which were then expressed as recombinant proteins for the demonstration of activity in the midgut of P. papatasi sandflies . Another product of the cDNA libraries was the identification and characterisation of a galectin protein as the first arthropod receptor for a parasite; specifically, L. major within the P. papatasi sandfly midgut .
Comparative analysis of transcripts that significantly differ from the sugar-fed and blood-fed midgut cDNA libraries
To investigate the effects of blood feeding on the midgut expression profile in P. papatasi, we compared the abundance of transcripts in sugar and blood-fed cDNA libraries. We hypothesized that a blood meal will have an effect on the expression of sandfly midgut transcripts that will be reflected in the relative abundance of sequences forming a cluster in the two libraries. Chi-square statistical analysis was used to evaluate the significance of the differences in the abundance of midgut transcripts from unfed and blood-fed cDNA libraries thereby identifying different expression profiles of selected midgut transcripts in each cDNA library.
We observed a significant difference (P value ≤ 0.05) in the abundance of a number of midgut transcripts when we compared the sugar-fed and blood-fed sandfly midgut cDNA library. Table 3 shows a list of selected transcripts that were either more abundantly or less abundantly expressed in these two cDNA libraries.
Clusters overrepresented in the sugar-fed and blood-fed midgut cDNA libraries as determined by X2 statistical analysis
Microvilli protein (PpMVP1)
Microvilli protein (PpMVP2)
Microvilli protein (PpMVP3)
Microvilli protein (PpMVP4)
Ferritin light chain (PpFLC)
Unknown (Cluster 73)
Unknown (Cluster 99)
Validation of transcript abundance of selected sequences by real-time PCR
In order to validate the results observed by the chi-square analysis, we further characterised several transcripts by semi-quantitative end-point reverse-transcriptase PCR as well as by real-time PCR. These were utilised to assess the relative abundance of transcripts in the midgut tissue under sugar-fed and blood-fed conditions. The investigated transcripts included peritrophins PpPer1 and PpPer2, as well as microvilli proteins PpMVP1, PpMVP2, and PpMVP4.
The results of semi-quantitative PCR can be seen in Figures 10B and 10D where the induction of PpPer1 is clearly evident. The differences in PpPer2 expression between the two midguts conditions is less clear using this technique (Figure 10D). Figure 10A shows the transcript abundance of PpPer1 as fold change over the control gene in non blood-fed and post blood-meal ingestion as measured by real-time PCR. Figure 10C shows the same real-time PCR analysis of the PpPer2 transcript. The profile of the peritrophin transcripts by real-time PCR strongly correlates with the profile found in the libraries based on the number of sequences.
Pptryp1 low and Pptryp4 high transcript abundance, were in accordance with the results of previously published endpoint reverse-transcriptase PCR . Additionally, the previously characterised chitinase molecule, PpChit1, was identified in cluster 243 and produced by three sequences contributed by the blood-fed cDNA library with none present in the sugar-fed cDNA library. The mRNA expression levels of PpChit1 peak at 72 hours post blood-meal ingestion .
Comparative analysis of transcripts significantly differs from the blood-fed and L. major-infected midgut cDNA libraries
During its development within the midgut of the sandfly, Leishmania is faced with various potential barriers that may prevent the establishment of the infection. Among such potential barriers are digestive proteases (trypsins and chymotrypsins), the peritrophic matrix and the requirement for parasite attachment to the midgut epithelia to prevent excretion of parasites with remnants of the digested blood. Previous data suggested that Leishmania is able to downregulate proteolytic activity in the sandfly midgut . Also, chitinases produced either by the sandfly  or by the Leishmania  facilitates parasites in the escape from the peritrophic matrix. Attachment to the midgut epithelia occurs via the presence of L. major lipophosphoglycan receptors, such as PpGalec  or, in the case of permissive sandflies, via the presence of midgut glycoproteins bearing terminal N-acetyl-galactosamine .
Clusters overrepresented in the blood-fed and Leishmania major-infected sand fly midgut cDNA libraries as determined by X2 statistical analysis
Microvilli protein (PpMVP1)
Microvilli protein (PpMVP2)
Ferritin light chain (PpFLC)
Unknown (Cluster 73)
Unknown (Cluster 99)
Development of Leishmania within its sand fly host is largely restricted to the vector midgut. Within the midgut Leishmania begins its development confined within a peritrophic matrix and is subjected to the onslaught of digestive enzymes. Later, they attach to the epithelia to prevent excretion with remnants of the blood meal and detach as they develop into the infective metacyclic form before being transmitted to a suitable host during a subsequent blood meal. The sandfly midgut presents a number of biological barriers the Leishmania parasite must circumnavigate or defeat to proliferate and develop inside the insect vector. Acquiring a better understanding of the molecules present in this organ will illuminate the potential molecular interactions occurring between the Leishmania parasite and the sandfly vector. Comparative transcriptome analysis provides a powerful global approach as demonstrated by the repertoire of molecules identified from a whole organism or from a specific tissue and the generation of new hypotheses from these data. Large scale genome analyses benefit from data generated from transcriptome analyses, for example, by aiding in the annotation of exons and introns.
The results of the present work provide insights into the repertoire of the molecules present in the midgut of the sandfly P. papatasi, the natural vector of L. major. We identified a variety of molecules and obtained high quality, full-length sequences from many of them. The high quality sequences were deposited at NCBI, significantly augmenting the available midgut-specific coding sequences. A large number of non-annotated sequences were deposited in the EST database for the scientific communities to access these transcripts.
The global changes in sandfly midgut expression profile were assessed by comparing data generated from randomly sequenced midgut cDNA clones obtained from cDNA libraries of adult females fed on sugar only, blood or blood with the addition of L. major. Our approach allowed for the identification of transcripts that are induced by blood feeding and likely participate in the digestion of the blood meal and events leading to egg production. Digestion of blood as a nutritional source is complicated by the cellular and molecular response and components of the blood itself, once ingested by the insect vector. Transcripts identified in the P. papatasi midgut, such as ferritin, Kazal-type serine protease inhibitors, and GST, are examples of the molecules identified on the gut of this insect. Additionally, the inclusion of a L. major-infected midgut cDNA library provides insight into genes potentially regulated by this parasite during its development within the sandfly midgut. The random sequencing approach followed by the in silico analysis of the transcript abundance was supported by experimental analyses obtained via real-time PCR.
Overall, this analysis will contribute to the understanding of the molecular interactions between Leishmania and the sandfly vector and may open new avenues for basic research towards the control of this neglected vector-borne disease.
Phlebotomus papatasi sandflies (Saudi Arabia strain) were obtained from colonies maintained at Walter Reed Army Institute for Research (WRAIR) and at NIAID-NIH. Three to 5-day old female sandflies were fed either on 20% sucrose solution (sugar fed) or on BALB/c mouse whole blood, via artificial meals , with or without the addition of 2 × 10 6L. major (V1 strain) amastigotes per ml.
Messenger RNA extraction and cDNA library construction
Phlebotomus papatasi female midguts (10 midguts) were dissected from sugar fed only, from blood fed at 6 h (6 midguts), 24 h, 48 h and 72 h post blood meal PBM (5 midguts each) and from L. major-infected at 16 h (3 midguts), 22 h and 96 h (5 midguts each) post infection (p.i.). For blood-fed and for L. major-infected, groups of midguts were pooled for RNA extraction. Pooling was done for the sugar-fed group as well. Messenger RNA was purified with the Micro-FastTrack mRNA isolation kit (Invitrogen-Life Technologies, Carlsbad, CA) and 100 ng of mRNA was used to produce a first strand cDNA. A cDNA library, enriched for full-length cDNA, was synthesized using the SMART cDNA library construction kit (Clontech Laboratories, Mountain View, CA). One microgram of double stranded DNA for each original library (sugar-fed, blood-fed, L. major-infected) was fractionated using a Chromaspin 1000 column (Clontech Laboratories, Mountain View, CA) into small (S), medium (M) and large (L) transcripts based upon their electrophoresis profile on a 1.1% agarose gel. Pooled fractions were ligated into Lambda TriplEx2 vector (Clontech, Mountain View, CA) and packaged into lambda phage (Stratagene, La Jolla, CA). Individual libraries were plated on LB agar plates in order to achieve roughly 200–300 plaques per 182 mm plates.
Unidirectional sequencing of randomly selected clones was completed as previously described . Single, isolated plaques were picked from the plate using sterile wooden sticks and placed into 70 μl of water. Amplification of the cDNA was performed using Platinum PCR SuperMix (Invitrogen), 4 μl template, and primers PT2F1 (AAG TAC TCT AGC AAT TGT GAG C) and PT2R1 (CTC TTC GCT ATT ACG CCA GCT G). PCR amplification products were cleaned using either. Multiscreen PCR cleaning plates (Millipore) or Edge Biosystems PCR cleaning plates and three washes with ultra pure water. The cleaned PCR product was resuspended in 25 μl of water of which 4 μl were used for cycle sequencing with PT2F3 primer (TCT CGG GAA GCG CGC CAT TGT) and either DTCS reaction kit (Beckman) or Big Dye 3.1 (Applied Biosystems). Sequencing reaction products were cleaned using Sephadex G-50 (GE Healthcare) in a multiscreen cleaning plate (Millipore) and analysed using either CEQ8000 (Beckman Coulter) or ABI3700 (Applied Biosystems) DNA sequencing instrument.
Detailed description of the bioinformatic analysis of the data appear in [10, 29]. Briefly, prior to analysis the vector sequence was removed from the cDNA nucleotide sequences. Sequence data from the three libraries were grouped together and aligned to generate clusters of contiguous sequences or contigs based on 90% homology over 90 nucleotides, after sequences with more than 5% Ns were discarded. Three frame translations of the consensus sequence of each contig were subjected to comparison using the appropriate BLAST algorithm to the NCBI non-redundant protein database, conserved domain database  which contains the eukaryotic clusters of orthologous groups (COG), Simple Modular Architecture Tool (SMART) and Protein Family Database (Pfam), and the Gene Ontology database . Nucleotide sequences were directly compared with two customised databases, mitochondrial and ribosomal RNA (rRNA) nucleotide databases using BlastN. Determination of the presence of a signal secretion peptide or transmembrane helices was accomplished by the submission of sequence peptides to the SignalP server  or TMHMM server , respectively. The L. longipalpis BLAST server was utilized to determine homology between the P. papatasi clusters and L. longipalpis ESTs . The number of transcripts each library contributed to a particular contig was derived using a custom program, Count Libraries (JMC Ribeiro, personal communication). Comparisons between the sugar-fed and blood-fed midgut cDNA sequences and comparisons between blood-fed and L. major-infected midgut cDNA sequences were based on separate Chi-square analysis . The grouped and assembled sequences, BLAST results and signal peptide results were combined in an Excel spreadsheet and the putative function, if any was manually verified and annotated. Sequences were aligned using Clustal X, version 1.83, and converted to graphical aligned sequences using BioEdit, version 184.108.40.206 . Phylogenetic analysis was conducted on amino acid alignments using TREE-PUZZLE, version 5.2, generating trees by maximum likelihood using quartet puzzling to calculate node support .
Quantitative PCR (qPCR) was performed in selected clones using the first-strand cDNA, obtained from 100 ng total RNA isolated from midguts dissected from P. papatasi females fed on sugar (unfed) or dissected after a blood meal (24–72 h post blood meal or PBM). cDNAs were synthesized using the 1st Strand cDNA Synthesis kit (Invitrogen, San Diego CA). Transcript levels were measured with SYBR green dye using a LightCycler 2.0 (Roche Diagnostics, Manheim, Germany). For qPCR reactions, samples were subjected to an initial holding step at 95°C for 15 minutes, followed by an amplification step consisting of 35 cycles of 95°C for 10 seconds, 54°C for 20 seconds and 72°C for 20 seconds with a single acquisition. The reaction continued with a single-cycle melting step of 95°C for 10 seconds, 67°C for 30 seconds and 95°C for 10 seconds, prior to cooling for 1 minute. Equal amounts of cDNA were amplified using gene-specific primer sets targeting individual transcripts as well as a P. papatasi alpha tubulin, as control or reference transcript. Reactions were routinely done in duplicate. The relative expression ratio of the target transcript and control or reference transcript (fold over control) was calculated using the LightCycler relative quantification software (Roche).
Semi quantitative RT-PCR reactions were performed with selected transcripts to further demonstrate the differential expression of these genes in P. papatasi midgut. In this case, 100 ng of total RNA isolated from midguts dissected from P. papatasi females fed on sugar (unfed) or dissected after a blood meal (48 h PBM) were used to synthesize a cDNA using the 1st Strand cDNA Synthesis kit (Invitrogen). PCR reactions were carried out by an initial hot start at 95°C for 5 minutes followed by 25 cycles of 95°C for 30 seconds, 54°C for 1 minute and 72°C for 1.5 minutes and a final extension cycle of 72°C for 5 minutes. PCR products were separated on 1.5% agarose.
We want to thank Dr. José M.C. Ribeiro for critical evaluation of this work and for the development and training of all custom bioinformatics programs used on this research, Dr. Robert Gwadz for his continuous support and Nancy Shulman for editorial assistance. This research was supported by The Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health.
- Kamhawi S, Ramalho-Ortigao M, Pham VM, Kumar S, Lawyer PG, Turco SJ, Barillas-Mury C, Sacks DL, Valenzuela JG: A role for insect galectins in parasite survival. Cell. 2004, 119 (3): 329-341. 10.1016/j.cell.2004.10.009.PubMedView ArticleGoogle Scholar
- Pal U, Li X, Wang T, Montgomery RR, Ramamoorthi N, Desilva AM, Bao F, Yang X, Pypaert M, Pradhan D: TROSPA, an Ixodes scapularis receptor for Borrelia burgdorferi. Cell. 2004, 119 (4): 457-468. 10.1016/j.cell.2004.10.027.PubMedView ArticleGoogle Scholar
- Borovsky D, Schlein Y: Trypsin and chymotrypsin-like enzymes of the sandfly Phlebotomus papatasi infected with Leishmania and their possible role in vector competence. Med Vet Entomol. 1987, 1 (3): 235-242.PubMedView ArticleGoogle Scholar
- Dillon RJ, Lane RP: Influence of Leishmania infection on blood-meal digestion in the sandflies Phlebotomus papatasi and P. langeroni. Parasitol Res. 1993, 79 (6): 492-496. 10.1007/BF00931590.PubMedView ArticleGoogle Scholar
- Ribeiro JM: A catalogue of Anopheles gambiae transcripts significantly more or less expressed following a blood meal. Insect Biochem Mol Biol. 2003, 33 (9): 865-882. 10.1016/S0965-1748(03)00080-8.PubMedView ArticleGoogle Scholar
- Dana AN, Hong YS, Kern MK, Hillenmeyer ME, Harker BW, Lobo NF, Hogan JR, Romans P, Collins FH: Gene expression patterns associated with blood-feeding in the malaria mosquito Anopheles gambiae. BMC Genomics. 2005, 6 (1): 5-10.1186/1471-2164-6-5.PubMed CentralPubMedView ArticleGoogle Scholar
- Pedra JH, Brandt A, Li HM, Westerman R, Romero-Severson J, Pollack RJ, Murdock LL, Pittendrigh BR: Transcriptome identification of putative genes involved in protein catabolism and innate immune response in human body louse (Pediculicidae: Pediculus humanus). Insect Biochem Mol Biol. 2003, 33 (11): 1135-1143. 10.1016/S0965-1748(03)00133-4.PubMedView ArticleGoogle Scholar
- Campbell CL, Wilson WC: Differentially expressed midgut transcripts in Culicoides sonorensis (Diptera: ceratopogonidae) following Orbivirus (reoviridae) oral feeding. Insect Mol Biol. 2002, 11 (6): 595-604. 10.1046/j.1365-2583.2002.00370.x.PubMedView ArticleGoogle Scholar
- Valenzuela JG, Garfield M, Rowton ED, Pham VM: Identification of the most abundant secreted proteins from the salivary glands of the sand fly Lutzomyia longipalpis, vector of Leishmania chagasi. J Exp Biol. 2004, 207 (Pt 21): 3717-3729. 10.1242/jeb.01185.PubMedView ArticleGoogle Scholar
- Anderson JM, Oliveira F, Kamhawi S, Mans BJ, Reynoso D, Seitz AE, Lawyer P, Garfield M, Pham M, Valenzuela JG: Comparative salivary gland transcriptomics of sandfly vectors of visceral leishmaniasis. BMC Genomics. 2006, 7: 52-10.1186/1471-2164-7-52.PubMed CentralPubMedView ArticleGoogle Scholar
- Kato H, Anderson JM, Kamhawi S, Oliveira F, Lawyer PG, Pham VM, Sangare CS, Samake S, Sissoko I, Garfield M: High degree of conservancy among secreted salivary gland proteins from two geographically distant Phlebotomus duboscqi sandflies populations (Mali and Kenya). BMC Genomics. 2006, 7: 226-10.1186/1471-2164-7-226.PubMed CentralPubMedView ArticleGoogle Scholar
- Ramalho-Ortigao JM, Temporal P, de Oliveira SM, Barbosa AF, Vilela ML, Rangel EF, Brazil RP, Traub-Cseko YM: Characterization of constitutive and putative differentially expressed mRNAs by means of expressed sequence tags, differential display reverse transcriptase-PCR and randomly amplified polymorphic DNA-PCR from the sand fly vector Lutzomyia longipalpis. Mem Inst Oswaldo Cruz. 2001, 96 (1): 105-111. 10.1590/S0074-02762001000100012.PubMedView ArticleGoogle Scholar
- Ramalho-Ortigao JM, Traub-Cseko YM: Molecular characterization of Llchit1, a midgut chitinase cDNA from the leishmaniasis vector Lutzomyia longipalpis. Insect Biochem Mol Biol. 2003, 33 (3): 279-287. 10.1016/S0965-1748(02)00209-6.PubMedView ArticleGoogle Scholar
- Ramalho-Ortigao JM, Kamhawi S, Rowton ED, Ribeiro JM, Valenzuela JG: Cloning and characterization of trypsin- and chymotrypsin-like proteases from the midgut of the sand fly vector Phlebotomus papatasi. Insect Biochem Mol Biol. 2003, 33 (2): 163-171. 10.1016/S0965-1748(02)00187-X.PubMedView ArticleGoogle Scholar
- Ramalho-Ortigao JM, Kamhawi S, Joshi MB, Reynoso D, Lawyer PG, Dwyer DM, Sacks DL, Valenzuela JG: Characterization of a blood activated chitinolytic system in the midgut of the sand fly vectors Lutzomyia longipalpis and Phlebotomus papatasi. Insect Mol Biol. 2005, 14 (6): 703-712. 10.1111/j.1365-2583.2005.00601.x.PubMedView ArticleGoogle Scholar
- Boulanger N, Lowenberger C, Volf P, Ursic R, Sigutova L, Sabatier L, Svobodova M, Beverley SM, Spath G, Brun R: Characterization of a defensin from the sand fly Phlebotomus duboscqi induced by challenge with bacteria or the protozoan parasite Leishmania major. Infect Immun. 2004, 72 (12): 7140-7146. 10.1128/IAI.72.12.7140-7146.2004.PubMed CentralPubMedView ArticleGoogle Scholar
- Dillon RJ, Ivens AC, Churcher C, Holroyd N, Quail MA, Rogers ME, Soares MB, Bonaldo MF, Casavant TL, Lehane MJ: Analysis of ESTs from Lutzomyia longipalpis sand flies and their contribution toward understanding the insect-parasite relationship. Genomics. 2006, 88 (6): 831-840. 10.1016/j.ygeno.2006.06.011.PubMed CentralPubMedView ArticleGoogle Scholar
- Pomes A, Melen E, Vailes LD, Retief JD, Arruda LK, Chapman MD: Novel allergen structures with tandem amino acid repeats derived from German and American cockroach. J Biol Chem. 1998, 273 (46): 30801-30807. 10.1074/jbc.273.46.30801.PubMedView ArticleGoogle Scholar
- Wittstock U, Agerbirk N, Stauber EJ, Olsen CE, Hippler M, Mitchell-Olds T, Gershenzon J, Vogel H: Successful herbivore attack due to metabolic diversion of a plant chemical defense. Proc Natl Acad Sci USA. 2004, 101 (14): 4859-4864. 10.1073/pnas.0308007101.PubMed CentralPubMedView ArticleGoogle Scholar
- Shao L, Devenport M, Fujioka H, Ghosh A, Jacobs-Lorena M: Identification and characterization of a novel peritrophic matrix protein, Ae-Aper50, and the microvillar membrane protein, AEG12, from the mosquito, Aedes aegypti. Insect Biochem Mol Biol. 2005, 35 (9): 947-959. 10.1016/j.ibmb.2005.03.012.PubMedView ArticleGoogle Scholar
- Devenport M, Alvarenga PH, Shao L, Fujioka H, Bianconi ML, Oliveira PL, Jacobs-Lorena M: Identification of the Aedes aegypti peritrophic matrix protein AeIMUCI as a heme-binding protein. Biochemistry. 2006, 45 (31): 9540-9549. 10.1021/bi0605991.PubMedView ArticleGoogle Scholar
- Devenport M, Fujioka H, Jacobs-Lorena M: Storage and secretion of the peritrophic matrix protein Ag-Aper1 and trypsin in the midgut of Anopheles gambiae. Insect Mol Biol. 2004, 13 (4): 349-358. 10.1111/j.0962-1075.2004.00488.x.PubMedView ArticleGoogle Scholar
- Campos IT, Amino R, Sampaio CA, Auerswald EA, Friedrich T, Lemaire HG, Schenkman S, Tanaka AS: Infestin, a thrombin inhibitor presents in Triatoma infestans midgut, a Chagas' disease vector: gene cloning, expression and characterization of the inhibitor. Insect Biochem Mol Biol. 2002, 32 (9): 991-997. 10.1016/S0965-1748(02)00035-8.PubMedView ArticleGoogle Scholar
- Friedrich T, Kroger B, Bialojan S, Lemaire HG, Hoffken HW, Reuschenbach P, Otte M, Dodt J: A Kazal-type inhibitor with thrombin specificity from Rhodnius prolixus. J Biol Chem. 1993, 268 (22): 16216-16222.PubMedGoogle Scholar
- Geiser DL, Chavez CA, Flores-Munguia R, Winzerling JJ, Pham DQ: Aedes aegypti ferritin. Eur J Biochem. 2003, 270 (18): 3667-3674. 10.1046/j.1432-1033.2003.03709.x.PubMedView ArticleGoogle Scholar
- Arvestad L, Visa N, Lundeberg J, Wieslander L, Savolainen P: Expressed sequence tags from the midgut and an epithelial cell line of Chironomus tentans: annotation, bioinformatic classification of unknown transcripts and analysis of expression levels. Insect Mol Biol. 2005, 14 (6): 689-695. 10.1111/j.1365-2583.2005.00600.x.PubMedView ArticleGoogle Scholar
- Schlein Y, Romano H: Leishmania major and L. donovani: effects on proteolytic enzymes of Phlebotomus papatasi (Diptera, Psychodidae). Exp Parasitol. 1986, 62 (3): 376-380. 10.1016/0014-4894(86)90045-7.PubMedView ArticleGoogle Scholar
- Myskova J, Svobodova M, Beverley SM, Volf P: A lipophosphoglycan-independent development of Leishmania in permissive sand flies. Microbes Infect. 2007, 9 (3): 317-324. 10.1016/j.micinf.2006.12.010.PubMed CentralPubMedView ArticleGoogle Scholar
- Ribeiro JM, Arca B, Lombardo F, Calvo E, Phan VM, Chandra PK, Wikel SK: An annotated catalogue of salivary gland transcripts in the adult female mosquito, Aedes aegypti. BMC Genomics. 2007, 8: 6-10.1186/1471-2164-8-6.PubMed CentralPubMedView ArticleGoogle Scholar
- NCBI Conserved Domain Database (CDD). [http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml]
- Mappings of External Classification Systems to GO. [http://www.geneontology.org/GO.indices.shtml]
- SignalP 3.0 Server. [http://www.cbs.dtu.dk/services/SignalP/]
- TMHMM Server, v. 2.0. [http://www.cbs.dtu.dk/services/TMHMM/]
- L. longipalpis Blast Server. [http://www.sanger.ac.uk/cgi-bin/blast/submitblast/l_longipalpis]
- Ribeiro JM, Alarcon-Chaidez F, Francischetti IM, Mans BJ, Mather TN, Valenzuela JG, Wikel SK: An annotated catalog of salivary gland transcripts from Ixodes scapularis ticks. Insect Biochem Mol Biol. 2006, 36 (2): 111-129. 10.1016/j.ibmb.2005.11.005.PubMedView ArticleGoogle Scholar
- Tippmann HF: Analysis for free: comparing programs for sequence analysis. Brief Bioinform. 2004, 5 (1): 82-87. 10.1093/bib/5.1.82.PubMedView ArticleGoogle Scholar
- Schmidt HA, Strimmer K, Vingron M, von Haeseler A: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics. 2002, 18 (3): 502-504. 10.1093/bioinformatics/18.3.502.PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.