To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response. Systems biology is an approach to develop comprehensive and ultimately predictive models of how components of a biological system give rise to its observed behavior Most current high-throughput technologies only provide data for a single molecule type, and the underlying regulatory structure of the cell must be inferred from their qualitative or quantitative relationships. Data describing only a single level of biological regulation is unlikely to fully explain the behavior of complex biological systems. Thus, there is a need for integrating data from multiple sources representing different hierarchical levels of regulation to reconstruct more complete cellular networks. For example, studies comparing mRNA and protein expression profiles have indicated that mRNA changes are unreliable predictors of protein abundance The necessity for integrated data analysis across ‘omics platforms is further driven by the desire to identify fundamental properties of biological networks, such as redundancy, modularity, robustness, and feedback control To explore the practicality of integrating different types of high-throughput data to understand complex cellular functions, we have conducted a multidimensional analysis of the temporal response of human mammary epithelial cells (HMEC) to epidermal growth factor receptor (EGFR) activation. EGFR signaling plays an important role in regulating proliferation and motility in many epithelial cells and can integrate signals from diverse pathways through receptor crosstalk In this study, we examined time-dependent changes in gene and protein expression patterns following EGF treatment of synchronized HMEC to determine how data from each platform qualitatively contributed to pathway and network analysis. While the cell processes identified by each data type varied significantly, integration of the multiple datasets recapitulated most of the known mitogenic pathways mediated through EGFR. Furthermore, networks derived from the combined datasets exhibited more highly connected signaling nodes with an appropriate hierarchical structure than networks derived from any individual dataset. This study demonstrates that integration of multiple data types provides complementary, not redundant, information necessary to reconstruct complex cellular response networks.0/G1 of the cell cycle 1-S-G2/M transitions by flow cytometry , and mass spectrometry-based proteomics. The experimental strategy  used takytometry  also yie18–22 hr .A complete listing of the significant RNA and protein changes identified by each platform is provided in the supplementary information . Among 32/M measured by flow cytometry.Categorically, RNAs that changed represented a wide variety of cell processes including immediate early genes, cell cycle regulatory genes, anti-apoptotic genes, matrix remodeling and proteolytic genes. The most highly-induced genes identified across all time points examined were extracellular proteases, including interstitial collagenase , and stromelysin 2 . We also observed early gene induction patterns, including activating transcription factor 3 (ATF3) and prostaglandin-endoperoxide synthase 2 (PTGS2), which were transiently up-regulated at 1 hr and returned to basal levels by 4 hr. A dramatic change in gene expression at the 24 hr time point was observed, reflecting the shift in cell population to G16O or 18O at the site of trypsin digestion was also used to estimate protein abundances 18O/16O), and using a significance threshold of 1.5-fold change, 511 proteins (with ≥2 peptide identifications each) were found to change in abundance in response to EGFR activation  tag strategy tivation . The 1.5The antibody-based proteomic analysis by Western blots from triplicate analyses indicated that 83 out of 612 detected proteins showed a ≥1.5 fold difference in abundance in response to EGF treatment (at any time point) compared to 0 hr controls . These aTo estimate the degree of concordance between RNA and protein expression changes, the subset of proteins observed to change by LC-FTICR analysis (511) was merged with the corresponding gene expression values measured on the microarray platform. By cross-referencing platform-specific identifiers to common gene symbols Because multiple time points were measured in this study, multivariate correlation analysis was also used to assess the global correlation between RNA expression and protein abundance changes over time. Canonical correlation analysis was used to identify a linear combination of time points that maximizes the correlation between RNA and protein expression profiles The overall smoothed shapes of the temporal RNA and protein expression patterns derived by regression were also compared and ranked using a test F-statistic in order to identify some of the most concordant and discordant RNA/protein pairs . An impoRNA/protein pairs in the biological process “protein metabolism” displayed more positive concordance than predicted by chance. Examples include proteins involved in protein processing and translational regulation of protein synthesis, such as eukaryotic translation initiation factor 4E (EIF4E) and ribosomal binding protein 1 homolog (RRBP1). In contrast, RNA/protein pairs in the “primary metabolism” category showed more anti-correlated patterns of expression than predicted by chance. These included proteins involved in fatty acid and carbohydrate metabolism, such as acetyl-coenzyme A acetyltransferase 1 (ACAT1) and pyruvate dehydrogenase alpha 1 (PDHA1). RNA/protein pairs whose annotation involved “signal transduction”, “stress response”, or “intracellular transport” processes, however, showed no statistically significant trend toward either concordant or discordant abundance changes based on the Wilcoxon rank sum test. These results provide strong support for previous assertions that the concordance between RNA and protein expression varies between specific functional classes of proteins To determine the extent to which we could reconstruct the known EGFR regulatory networks from our datasets, we used the MetaCore software suite , which uses a curated, literature-based database of interaction and regulatory relationships to generate network maps from sets of differentially expressed genes or proteins. This approach was necessary because the limited number of conditions represented by the proteomic and microarray data in this study is insufficient to computationally infer connectivity between gene expression and protein expression nodes. We first evaluated whether similar biological processes regulated by EGFR activation are captured by each high-dimensional data platform by conducting gene set enrichment analysis on each dataset separately. The results  demonstrate that each data type emphasizes a specific pattern of cellular processes . The mosTo determine whether the pathway analyses of our integrated datasets made biological sense given our current understanding of EGFR signaling, we also analyzed how the major cell processes evolved over time. For these analyses, the major cell processes represented by the combined data were statistically ranked according to early (0–4 hr), intermediate (8–13 hr) and late (18–24 hr) time domains after EGFR activation . SignifiThe results in EGFR node from the LC-FTICR data increasing dramatically to 16 edges. When the microarray, LC-FTICR and PowerBlot data were all combined, the largest network cluster grew only modestly to 169 nodes. However, the connectivity of the highly linked nodes increased to 21 edges for EGFR and 28 edges for FOS , which emerged from the protein phosphorylation data obtained from the antibody analysis . Other wEach data type also contributed to different types of edges in the overall inferred network. For example, from the microarray data alone, 63% of the edges were inferred to be transcriptional regulatory relationships whereas only 17% were inferred to be direct protein interaction events. In contrast, 60% of the edges from the LC-FTICR data were inferred to represent protein interaction events and only 4% to represent direct transcriptional regulation. These findings are not unanticipated, but they provide an indicator of the added value of each data type in the reconstruction of cell response networks.Since the primary goal of our study was to quantify the benefits of data integration across different measurement platforms for network and pathway analysis, the EGFR system was a valuable system due to the extensive knowledge of signaling networks it is coupled to. However, a surprising observation from our combined results was that the most robust response to mitogenic concentrations of EGF was not cell cycle regulation, but induction of matrix metalloproteinase cascades. Indeed, RNA levels for interstitial collagenase (MMP1), and stromelysin 2 (MMP10) were among the largest changes observed in the study, increasing 24- and 8-fold, respectively. To validate these high-throughput measurements, additional experiments were conducted using orthogonal techniques to measure the secretion of MMP1 and MMP10 protein. ELISA analysis of conditioned medium collected from HMEC during mitogenic stimulation confirmed that high levels of both MMP1 and MMP10 protein are secreted in a manner that is dependent on EGFR kinase activity .The concept that integration of data derived from multiple levels of biological regulation will improve our understanding of signaling networks is generally accepted, yet is rarely practiced in biological research. To our knowledge, this study is the first systematic analysis of the practical benefits of merging heterogeneous temporal data for purposes of network and pathway interrogation in human cells. We focused on the EGFR pathway because it plays an important role in epithelial cell regulation and cancer biology, and there is mounting evidence that EGFR transactivation is coupled to wide variety of external stimuli An important reason for integrated data analysis is that RNA abundance changes are not always a good predictor of protein abundance changes, especially over a time scale of several hours. The canonical correlation analysis we describe here has advantages over simple correlation analysis, since it can conceptually capture RNA and protein expression profiles that are “concordant” yet out of sync due to temporal delays. The canonical correlation of 0.44 found in this study is greater than correlations previously reported in which the slopes of RNA and protein temporal profiles were used for comparison Beyond general correlations, our results also suggest that some functional classes of proteins show a greater tendency toward tight coupling to transcriptional control than others. Most studies reporting global measurements of gene and protein expression levels have used single time point designs and rely on steady-state measurements that do not discriminate between synthesis and degradation processes that underlie changes in abundance . However, rates of protein degradation and turnover can vary by orders of magnitude, even with highly abundant proteins The major cell processes found to be modulated by EGFR were qualitatively very different with respect to each measurement platform . The empAn important advantage of data integration observed here is that the networks derived from heterogeneous datasets show a more connected topology than networks derived from a single dataset. Cellular signaling networks are thought to approximate a scale-free topology, characterized by fewer nodes with a higher degree of connectivity SRC as a signaling intermediate In contrast to the microarray results, 60% of the node-edge relationships identified from the LC-FTICR data infer direct protein interactions as regulatory mechanisms. The bias of LC-FTICR results towards protein interactions is further implied from network statistics showing that there were nearly 3-fold more nodes with multiple edges (multiple effectors) than nodes with single edges (binary interactions). This also contrasts the microarray data, where the fraction of inferred nodes with multiple edges was only 1.6-fold greater than nodes with single edges. It is noteworthy that based on microarray data alone, EGFR would not have been identified as a major node in the pathway analysis. However, the largest network clusters identified from the LC-FTICR data alone included EGFR itself and β1-integrin as the most connected nodes. Previous studies have reported that EGFR and β1-integrin associate as a complex, providing a mechanism for bidirectional coupling of EGFR signaling to the extracellular matrix and other receptor pathways A limitation of pathway analysis using computational tools based on literature-curated databases is that relationships involving non-annotated molecules cannot be identified. However, such tools are highly useful for weighting abundance changes for specific gene products identified experimentally and inferring signaling linkages that are not always intuitive. By using curated databases for comparison, our study illustrates some of the strengths and biases inherent in different measurement platforms. Despite platform-specific strengths and weaknesses, integration of heterogeneous datasets not only enhances the connectivity of the derived networks, but also qualitatively influences the regulatory relationships inferred from high-dimensional data. Computational inference of signaling networks would be a preferable strategy to utilize all of the data, however inference utilizing multiple data types is challenging due to differences in quantitative range and sheer volume of data required for robust calculations The human mammary epithelial cell line HMEC (strain 184A1), obtained from Martha Stampfer , 4 cells were seeded in 150-mm dishes and allowed 24 hr in complete medium for attachment and growth. Growth arrest was induced by replacing the medium with medium lacking serum, EGF and other growth factors for 48 hr. A mitogenic response was then initiated by treating cells with 10 ng/ml EGF in minimal medium. Samples were collected at 0, 0.25, 1, 4, 8, 13, 18 and 24 hr and processed for RNA expression profiling and proteomic analyses as described below. The fraction of cells in G0/G1, S and G2/M phases of the cell cycle was measured in parallel samples by flow cytometry analysis  after fixation in cold 70% ethanol and labeling with propidium iodide.For the experiments shown, 7.5×10Total RNA was prepared using a Qiagen RNeasy Mini kit  and the integrity and purity evaluated by gel electrophoresis and absorption spectroscopy. RNA expression profiles were analyzed using NimbleGen whole genome 60-mer oligonucleotide arrays (Design Version 2003_10_27) which contains 38,108 array elements . Briefly, 0.5 µg of total RNA for each sample was used for cRNA synthesis using oligo-dT primers and T7 RNA polymerase through the NimbleGen Microarray Service facility. Each biological sample was hybridized against 3 independent arrays , and quality control assessment determined that the arrays for the 15 minute time point failed to hybridize according to manufacturer specifications. Raw intensity data for the remaining arrays were quantile normalized 3, 10 mM NaF, and protease inhibitor cocktail, pH 7.4) using intermittent sonication on ice. The lysates were centrifuged for 20 min at 4°C at 14000 g to pellet any residual debris. Protein concentrations were determined using the BCA assay . Parallel Western blot analyses were performed by BD Biosciences  through their PowerBlot™ custom service using the complete array of available antibodies . This approach employs co-hybridization of panels of antibodies that recognize distinctly migrating proteins on denaturing gradient gels, followed by detection with secondary antibody and quantification by gel image analysis. Samples were analyzed in triplicate, and gel image analysis of expression ratios were determined using a 3×3 matrix comparison method to determine the ratio of treated∶control (0 hr) for each of the triplicate analyses. Only proteins which passed visual inspection of the image quality and showed a ≥1.5-fold change compared to control (0 hr) were considered significant. The raw microarray data files are publicly available in GEO (GSE15668), and significant gene lists used in the bioinformatics analyses are included as For analysis of protein abundance changes, cell pellets collected at different time points were separately washed three times with ice-cold phosphate-buffered saline. The cells were lysed in buffer  tag approach 16O-to-18O exchange as previously described 16O and all the other samples  were labeled with 18O. Supernatants were collected by centrifuging the samples for 5 min at 15000 g, and equal amounts of the 16O-labeled control sample were combined with each of the 18O-labeled time point samples, and dried.For quantitative analysis by LC-FTICR, proteins from each of the eight lysates were digested with trypsin separately and cysteinyl and non-cysteinyl peptides was prepared from the tryptic digests and were differentially labeled separately using post-digestion trypsin-catalyzed 16O∶18O), normalizing LC elution times, and matching the accurate measured masses (±5 ppm) and NET (±2%) values of each feature to the corresponding mass and time tag in the database to identify peptide sequences. All identified peptides were assigned an identical probability of 1.0 and entered into ProteinProphet software http://omics.pnl.gov, and final datasets used in the bioinformatics analyses are submitted as Samples were analyzed using an in-house 11.5-T FTICR mass spectrometer. The same LC system and gradient was applied for LC-MS/MS and LC-FTICR analysis. The LC-FTICR data analysis was conducted as previously described 10 expression ratio values. Biological process enrichment statistics were calculated using the pathway mapping tool, MetaCore  based upon a hypergeometric distribution where the p-value represents the probability of particular mapping arising by chance, given the number of significantly regulated genes/proteins in the dataset, the total number of genes assigned to a process, and the background genes/proteins experimentally identified by the platform. Networks were reconstructed using MetaCore's direct interaction algorithm, where the only edges allowed are those between two root nodes  using their proprietary database of curated interactions from the literature. The resulting integrated network was redrawn using Cytoscape Data were integrated across platforms using the Bioinformatics Resource Manager software cancor function in R) was used to assess the overall  concordance of RNA and protein temporal expression profiles. The significance of the observed canonical correlations was evaluated by permuting protein labels (but keeping time profiles intact), and computing the canonical correlations for each of 1000 permutations. Genes were ranked according to the concordance of their individual RNA and protein expression profiles. Rankings were made by reference to a smoothing model. Let t for gene g for RNA and protein, respectively. The respective time profiles were fit to the models (using the lm function in R)a>0 and b<0.Canonical correlation analyses of time profile microarray and proteomic data were conducted using the freely available R software . Prior to analysis all time profiles were individually transformed to have mean 0 and standard deviation 1, so that subsequent comparisons emphasize the shapes of the profiles. Canonical correlation analysis  and anti-correlated (B) temporal patterns. The x-axis is time in hours. The left-hand y-axis is the RNA scale, and the right-hand y-axis is the protein abundance scale. The RNA profile is shown in red and protein profile is in blue. The dashed line indicates the regression-based fit for temporal concordance. Values are expressed as log2 expression ratios.(TIF)Click here for additional data file.Figure S2EGFR-Regulated Secretion of Matrix Metalloproteases. HMEC were treated with EGF (10 ng/ml), alone or in the presence of the selective EGFR kinase inhibitor PD153035 (200 nm). MMP-1 and MMP-10 protein levels were measured in conditioned medium at 24 hr using ELISA . Values are the mean ± s.d. of biological triplicates.(TIF)Click here for additional data file.Table S1Significant gene and protein lists measured by microarrays, FTICR proteomics and western blot analysis in the time course study. The file includes gene/protein identifiers from each platform and values listed are log10 expression ratios relative to time 0 hr controls.(XLS)Click here for additional data file.


Viral load monitoring (VLM) to identify individuals failing antiretroviral therapy (ART) is not widely available in resource-limited settings. We compared the genotypic resistance patterns between clients with VLM versus immunological monitoring (IM).Between 2004–2008, 559 ART naïve clients were enrolled in a prospective cohort, initiated on ART, and monitored with viral load (VL) and CD4+ cell counts every 6 months (VLM group). From February 2008 through June 2009, 998 clients on ART for 36–40 months (corresponding to the follow-up time of the VLM group) at the same clinic and monitored with CD4+ cell counts every 6 months were recruited into a cross sectional study (IM group). Samples from VLM clients at 12, 24 and 36 months and IM clients at 36–40 months with VL > 2000 copies/ml underwent genotypic drug resistance testing.P < 0.0001) had at least 1 non-nucleoside reverse transcriptase mutation. 19/39 (49%) of VLM clients had an M184V mutation compared to 61/70 (87%) in the IM group (P < 0.0001). Only 2/39 (5%) of VLM clients developed thymidine analogue mutations compared to 34/70 (49%) of IM clients (P < 0.0001).Baseline characteristics were similar. Virologic failure (VL > 400 copies/ml) at 12, 24 and 36 months in the VLM group were 12%, 6% and 8% respectively, and in the IM group 10% at 36–40 months. Samples from 39 VLM and 70 IM clients were genotyped. 23/39 (59%) clients in the VLM group  compared to 63/70 (90%) in the IM group, (Routine VL monitoring reduced the rate of accumulated genotypic resistance to commonly used ART in Uganda. Antiretroviral treatment (ART) programs have scaled up to reach over 5.2 million HIV-infected individuals in need of life-saving treatment in low and middle income countries by the end of 2009 . Most ofFailure to achieve or maintain virologic suppression for prolonged periods of time may lead to the sequential development of thymidine analogue mutations (TAMs) in clients taking nucleoside reverse transcriptase inhibitors (NRTIs) such as zidovudine (ZDV) or stavudine (d4T) as part of their ART regimens -12. The The objective of our study was to compare genotypic resistance patterns (with particular attention to TAMs) among a group of clients on first-line ART at an urban clinic in Kampala, Uganda, who were monitored both clinically, immunologically and virologically as part of a research cohort study to a similar group of clients attending the same clinic who were monitored only clinically and immunologically.The Infectious Diseases Institute (IDI) of Makerere University College of Health Sciences  is a center of excellence in the delivery of HIV clinical care, research and training, with over 10,000 active clients registered including over 6,500 receiving ART. Eligibility criteria for ART at the time of this study (February 2008 through June 2009) were CD4 < =200 cells/ul or WHO stage IV disease; first-line regimens included stavudine or zidovudine plus lamivudine and nevirapine or efavirenz.Clients attending the routine care clinic who become eligible for ART are offered adherence counseling prior to ART and also during follow-up if deemed necessary by clinicians. Clients are seen monthly for follow-up assessments, drug refills and monitored through prospective CD4+ cell counts every 6 months. Treatment failure was assessed according to the WHO immunologic or clinical criteria for treatment failure . A more A nested research cohort within the routine care clinic was established in 2004, with a consecutive prospective enrollment of 559 ART-naïve clients who initiated ART from April 2004 through April 2005; clients enrolled in this cohort are monitored through both CD4+ counts and viral load measurement , every 6 months; plasma is also stored for future investigations. A more detailed description of the study procedures and data collection has been presented elsewhere . In brieFrom February 2008 through June 2009, a cross sectional study was conducted in the IDI routine care clinic population recruiting a convenience sample of clients who were on first-line ART regimens for 36–40 months (corresponding to the length of follow-up time reached by IDI research cohort clients). Clients still on first-line ART were consecutively recruited during their monthly follow-up visits. After providing written informed consent, blood was drawn for HIV viral load (VL), CD4+ cell count and plasma was stored for genotyping. Genotyping was done on all clients found to have an HIV VL > 2,000 copies/ml (corresponding to the sensitivity threshold of the assay). Results of the viral load and genotyping test were made available to the physicians for clinic management of their clients.In the research cohort clients, those alive and in care at 12 months were considered eligible for this analysis. We included any research cohort client having a HIV VL of >2000 copies/ml while still on first-line at months 12, 24 or 36 of follow-up; however, clients who had a detectable VL above 2,000 copies/ml up to month 12 but subsequently (months 24 or beyond) became virologically suppressed without regimen change were not included in the genotyping analysis as these were considered to have early adherence problems rather than drug resistance . All cliP values are two-sided. All analyses were performed using SAS version 9.2  or Stata version 11.1 .Baseline characteristics for both monitoring groups were compared using the Fisher exact test for categorical variables  and Mann–Whitney U test for continuous variables . We used the Mann–Whitney U test to compare median CD4+ count increase at follow-up. We used the t-test for proportions to assess differences in mutation rates across monitoring groups. All Plasma was separated within 2 hours from blood draw and stored immediately at −80°C. HIV-1 RNA was tested with the Roche Amplicor MONITOR v1.5 assay . HIV-1 RNA was extracted from plasma samples using a Qiagen RNA extraction method . Polymerase gene-specific primers were used for reverse transcriptase, followed by 750 base pair pol gene encompassing amino acids 1–242 of reverse transcriptase. The PCR products was then purified using the QIAquick PCR purification kit  and sequenced using Beckman Coulter sequencing kit . The obtained sequences were then edited using BioEdit sequence editor version 7.0.4. The cleaned sequences were then uploaded into the Stanford University HIV Drug resistance database to obtain the drug resistance profile. Genotyping assays were performed at the Joint Clinical Research Center laboratory in Kampala. For genotype analysis, mutations were generally categorized according to the International AIDS Society-USA recommendations .All study participants from the IDI routine care clinic provided written informed consent, while the participants from the IDI research cohort had already provided consent at study enrollment for future use of stored plasma. The study was approved by the National AIDS Research Council Ethics Board, the Uganda National Council for Science and Technology, and the National Institute of Allergy and Infectious Diseases Intramural Institutional Review Board.Genbank accession numbers: KC008609 to KC008711.Four hundred forty one of the 559 research cohort clients (VLM group) were alive and in care at 12 months and included in this analysis. Nine hundred ninety-eight clients on ART for 36–40 months were recruited from the routine clinic population (IM group). Table Samples from 39 VLM and 70 IM clients were successfully amplified and genotyped Figure  &1b. SomComparing the 39 first genotypes from VLM clients to the 70 IM clients, 23/39 (59%) of VLM clients as opposed to 63/70 (90%) in the IM group had at least 1 NNRTI mutation (p < 0.0001)  of VLM clients as opposed to 63/70 (90%) in the IM group had at least 1 NNRTI mutation (p = 0.1034). Four out of ten (40%) of VLM clients had an M184V mutation compared to 61/70 (87%) of IM clients (P = 0.0185). None of the VLM clients developed TAMS whereas 34/70 (49%) of IM clients developed TAMS (p < 0.0001).A total of 26 clients in the VLM cohort were switched from first to second-line ART in the first 36 months of follow-up, while all patients in the IM group reached 36 months on first-line ART without clinicians suspecting treatment failure. The median number of VL measurements before switch was 4 and median VL prior to switch was 21,773 .Although the proportion of clients failing ART at 36 months was comparable between those monitored with VL and compared to those monitored with CD4+ cell counts only, the proportion of the clients with multiple resistance mutations especially TAMS was significantly higher in the IM clients. This is the first observational study directly comparing genotypic resistance profiles to commonly used antiretroviral drugs between individuals monitored with virologic compared to immunologic monitoring alone. Several studies have documented the lack of sensitivity of immunologic and clinical criteria to identify individuals failing ART raising concern regarding the potential for increased genotypic resistance to ART, which could result ,11,18. IThe participants enrolled in the IM cohort in this study were clients who had not been identified as having any evidence of treatment failure by clinicians. In contrast to most studies looking at resistance among clients in RLS, this was not a selected group of individuals failing by immunologic or clinical criteria and would have been left on first-line ART if VL testing was not done as part of this study. The significant degree of resistance observed in this group raises concern about the need for periodic VL monitoring in settings where none is currently available in routine care. A moderate proportion of clients had multiple TAMS possibly resulting in compromised efficacy of commonly used second-line ART regimens available in RLS.Our study has limitations; it is not a randomized clinical trial and therefore unmeasured bias between the VLM and IM groups remains a possibility. Because the IM group was cross-sectional, we have no data on lost to follow-up or number of deaths before study enrollment; however, we would expect clients lost to care to do as poorly or worse with respect to rates of virologic failure. Clients enrolled in the VLM group followed certain inclusion criteria including living within 20 km of the clinic and willingness to attend to visit schedules which could also select for a more adherent population compared to the IM group. The use of stored specimens resulted in some amplification failures among the VLM group, which could possibly affect our overall results. Finally, we have no information on duration of virologic failure among the IM group to allow us to control for duration of failure which could influence the mutation patterns observed.Despite the limitations mentioned pertaining to study design, baseline characteristics, treatment setting and study staff were all similar. Virologic and immunologic characteristics at 36 months of follow-up were also similar between the two groups. . We believe the reduced rate of resistance, particularly to NRTIs, observed among VLM clients is explained by the frequent VL monitoring and ability to detect and allow caregivers to discuss adherence and possibly switch to second-line regimens prior to the development of extensive drug resistance. Our results support ongoing efforts to improve adherence counseling strategies as treatment programs continue to scale up access. Our study was not designed to look at longer term mortality benefits between our VLM and IM clients, however, a recent multi-country study conducted in Malawi, Zambia and South Africa suggested that the lower rate of mortality observed among South African ART programs could be explained in part by the presence of VL monitoring and timely switch to second-line regimens . As ART Access to viral load monitoring remains a priority for countries continuing to scale up ART in order to limit the emergence of drug resistance. Further studies are warranted to evaluate novel monitoring strategies that minimize resistance, maximize positive clinical outcomes, recognizing cost constraints faced by programs challenged by ever increasing numbers needing HIV treatment.The authors declared that they have no competing interests.SJR, HK, TCQ and AK contributed to study design, participant recruitment and follow-up, and final analysis. KN contributed to study conduct and statistical analysis. YCM, MK and BC contributed to participant recruitment, study conduct and analysis. In performed laboratory assays and contributed to analysis. All authors contributed to manuscript writing. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/12/381/prepub


Burkholderia pseudomallei is an important human pathogen whose infection biology is still poorly understood. The bacterium is endemic to tropical regions, including South East Asia and Northern Australia, where it causes melioidosis, a serious disease associated with both high mortality and antibiotic resistance. B. pseudomallei is a Gram-negative facultative intracellular pathogen that is able to replicate in macrophages. However despite the critical nature of its interaction with macrophages, few anti-macrophage factors have been characterized to date. Here we perform a genome-wide gain of function screen of B. pseudomallei strain K96243 to identify loci encoding factors with anti-macrophage activity. We identify a total of 113 such loci scattered across both chromosomes, with positive gene clusters encoding transporters and secretion systems, enzymes/toxins, secondary metabolite, biofilm, adhesion and signal response related factors. Further phenotypic analysis of four of these regions shows that the encoded factors cause striking cellular phenotypes relevant to infection biology, including apoptosis, formation of actin ‘tails’ and multi-nucleation within treated macrophages. The detailed analysis of the remaining host of loci will facilitate genetic dissection of the interaction of this important pathogen with host macrophages and thus further elucidate this critical part of its infection cycle. Burkholderia pseudomallei is a serious environmental pathogen of man and the causative agent of the often fatal disease melioidosis. Disease occurs following exposure to contaminated water or soil, usually through cuts in the skin or via inhalation, but the underlying mechanisms of pathogenicity of B. pseudomallei to humans remain poorly understood B. pseudomallei is endemic to S.E. Asia and N. Australia where infections are associated with both antibiotic resistance and high mortality rates (∼50%). The ability of this pathogen to infect via inhalation has necessitated its listing as a potential bio-warfare agent B. pseudomallei a high priority for research and vaccine development as no effective vaccine currently exists B. pseudomallei adheres to, survives and replicates within host epithelial cells and macrophages by somehow interfering with the cellular mechanisms which would otherwise destroy them. Known bacterial factors affecting the interaction with host cells include the bacterial capsule, and effectors delivered by the type III and type VI secretion systems (T3SS and T6SS) Burkholderia strains show a wide range of different interactions with human macrophages, ranging from no effect, to host cell apoptosis and capase-1-dependent lysis B. pseudomalleiB. pseudomallei the toxin remains to identified and encoding gene characterised Escherichia coli to identify the full list of loci potentially encoding toxins, or other factors, with anti-macrophage activity.The Gram-negative bacterium B. pseudomallei K96246, a clinical isolate, whose genome, of two chromosomes, has been fully sequenced B. pseudomallei genome which often contain genes encoding hypothetical virulence factors To perform the screen we chose the strain E. coli each carrying end-sequenced B. pseudomallei genomic fragments ) were used to identify loci encoding factors cytotoxic to the murine macrophage cell-line J774-2. The end-sequences of multiple positive clones recovered from the screens were aligned on to the sequenced genome in order to identify and confirm the precise configuration of the loci involved Photorhabdus bacteria does not dramatically decrease anti-insect virulence due to the remaining copy of a second toxin encoding gene Mcf2 and a host of other remaining virulence factor encoding genes that remain unaffected B. pseudomallei, here we use this gain of function screening technique to reveal over 100 loci encoding anti-macrophage factors scattered across the two different chromosomes of this bacterial genome. Such analyses will facilitate the identification and follow-up of effector proteins and small molecules that influence the potentially complex interaction between Burkholderia bacteria and host macrophages.Libraries of recombinant B. pseudomallei K96243 in BAC and fosmid clones for activity towards J774-2 macrophages. To identify and confirm anti-macrophage encoding loci in the B. pseudomallei genome the end-sequences from positive library clones (clones shown to reduce macrophage viability by >40 %) were re-assembled onto the sequenced genome. Each locus was defined by the minimum region of genetic overlap formed by a cluster of two or more positive clones. Using these criteria, a total of 59 anti-macrophage encoding loci were identified on chromosome 1 and 54 on chromosome 2. Details of the loci, the predicted open reading frames that they contain and associated BLAST matches are provided in detail in the supporting information . Regions associated with anti-macrophage activity also include CDSs relating to adhesion  and biofilm formation . However the largest predicted function categories associated with the anti-macrophage loci were either toxin/enzyme related  with 44 associated CDSs within loci, or proteins involved in transport/secretion  with 84 related CDSs within positive loci.Several broad functional classes were repeatedly predicted for the anti-macrophage loci identified : There aBacillus cereus hemolysin III (BPSS0803) and LasA elastase from Pseudomonas aeruginosa (BPSL0624). One locus also contains a gene (BPSS0067) encoding phospholipase – PLC-3 a putative non-hemolytic phospholipase C with an N-terminal twin-arginine translocation  which was transcriptionally up-regulated in a hamster model of infection and increases the LD50 of test animals dramatically Several of the anti-macrophage loci encode putative toxins. For example, BPSS1993 encodes a metalloprotease A, termed MrpA, a 47 kDa protein negatively regulated by QS molecules, a putative hemolysin with homology to B. pseudomallei K96243 contains six gene clusters encoding putative T6SSs E. coli used in the library screens were not armed with any specific type III or type VI secretion systems, several positive loci encode putative VgrG-like T6SS-related proteins. Some VgrG effector proteins have been inferred to induce host cell toxicity by ADP-ribosylation of actin, as well as performing a role in formation of the secretion machinery itself B. pseudomallei T6SS-5 is induced upon exposure to macrophages and plays an important role in the intracellular survival of the pathogen E. coli used were absent.The genome of wzt ABC transporter, confirming the potential role of LPS in interaction with macrophages E. coli used for library construction. The second class I ABC system detected, BPSL3092-BPSL3094 is classified as involved in hemolysin export, however there are no identified hemolysins associated with this system in K96243 E. coli used in the screen. In summary, given that the host E. coli used in the screen (DH10B and EPI-300-T1R) lack the specific secretion machinery (e.g. T3SS or T6SS) necessary for delivery of many types of known effectors, the clusters of anti-macrophage loci uncovered here appear to be able to reconstitute toxicity in the recombinant E. coli either using systems still present (e.g. type 1 secretion) or by using transporters (e.g. ABC) or synthetic machinery (e.g. liposaccharide biosynthesis) also encoded within the positive clones/clusters.There are a total of 105 predicted functional ABC systems encoded within the genome of strain K96243 Pseudomonas syringaeIn order to begin to characterize the range of likely cellular phenotypes caused by this plethora of new candidate anti-macrophage factors we focused on the four positive clusters diagrammed in Photorhabdus luminescens insecticidal Toxin complex (Tc) component protein, specifically TcdB N and C terminal regions (7.87e-36 and 7.90e-29 respectively). The N-terminal region of BPSL590 has homology to the N-terminal of Salmonella enterica plasmid virulence associated protein SpvB (1.03e-09). The function of the N-terminus of SpvB remains unknown but shares sequence similarity to the N-terminal domain of P. luminescens toxin TcaC, the function of TcaC is largely unclear but is thought to act as a potentiator modifying other toxin components and it is required to reproduce full toxicity of the Toxin complexes via recombinant expression Thirty of the anti-macrophage loci contained ‘hypothetical proteins’ whose potential functions cannot be predicted from homology with known virulence factors. BPSL0590 and BPSL0591 are CDSs found in a positive locus on chromosome 1 which encode such hypothetical proteins. However closer examination of protein predictions from these two CDSs does reveal some limited homology to known toxins from other bacterial pathogens suggesting they may encode novel toxins. Position-specific-iterative blast (psi-BLAST) reveals that this putative membrane protein also has a central region similarity to the Rhs associated core sequence (1.98e-10) and to the middle N and C-terminal domains of a P. luminescens insecticidal Tc protein, specifically TccB. Macrophages treated with lysate from clones encompassing these toxin-like genes show both formation of multinucleated cells and apoptotic nuclei,  containing this region of interest show a dramatic decline in cell density, indicating a potent degree of cytotoxicity. Macrophages surviving such treatment become distended with little remaining cytoskeletal or nuclear structure  is an adhesin and facilitates attachment to the host cell during infection following secretion which is dependent on FhaC B. pseudomallei hemagglutinin-like gene display a very interesting phenotype with formation of dramatic actin projections or ‘tails’ extending towards neighboring cells from shrunken cell bodies containing condensed nuclei.The fourth cluster chosen for follow up analysis contains two CDSs encoding a putative hemagglutinin and with homology to the large filamentous hemagglutinin precursor, FhaB, (BPSS1727) and hemolysin activator-like protein precursor, FhaC (BPSS1728) of ertussis . The B. Burkholderia ‘SylA’ homolog, here termed BylA. The SylA gene product is a small molecule secreted into the supernatant of cultures of P. syringae bacteria E. coli clones carrying the Burkholderia BylA encoding cluster also show strong cytotoxic activity and remaining macrophages from treated monolayers display a shrunken and rounded phenotype . In this light we will now briefly discuss three aspects of the data and its generation. First, the overall distribution of the screening hits across the two chromosomes of B. pseudomallei. Second, the problems and pitfalls associated with the delivery of potential effectors from the recombinant E. coli and their uptake by the target macrophages. Third, and finally, we will spend some time discussing the likely nature of the positive clusters themselves and how they may inform our future understanding of Burkholderia infection biology.The bacterium B. pseudomallei many are specifically associated with genomic islands and/or regions of altered GC content. Genomic islands are often linked to symbiosis or pathogenicity E. coli, and therefore these regions may be more preferentially expressed in comparison to those with high %GC.The genomic locations of the gene clusters encoding anti-macrophage effectors and compounds are worthy of brief discussion before a detailed discussion of the clusters themselves and their potential role in infection biology. Thus although positive loci are distributed relatively uniformly across the two chromosomes of E. coli are not in any way secretion proficient or enhanced (e.g. via the addition of a T3SS), it is interesting to speculate how the anti-macrophage factors  are released from the host E. coli and indeed how they are taken up by (or contacted by in the context of ‘displayed’ molecules such as LPS) the target macrophages in cell culture. In this latter respect it is critical to note that the presence of some intact E. coli in the crude lysates applied to the macrophages appears necessary for toxicity in some cases, possibly by facilitating uptake of, or response to, recombinant factors. In contrast to much of the previous work on the three T3SSs in Burkholderia we would not expect T3SSs or their effectors to be recovered as positives in this system for a number of reasons. First, given that the size of the gene clusters encoding a complete T3SS can be extensive we were not expecting to recover T3SS related hits in the size range genomic fragments currently used (10–40 kb). More importantly we did not ‘arm’ the recombinant E. coli used in the library screening with a functional T3SS and we therefore also did not expect to identify any T3SS delivered effectors (in the absence of a clone encompassing an entire native T3SS). Finally, in relation to secretion, a number of positive clusters on chromosome 2 contain T6SS related CDSs. The precise role of T6SSs are largely uncharacterized but expression of one system has been shown to be induced upon invasion of macrophages. However mutation studies showed no alteration in invasion or intracellular survival suggesting a role in another area of pathogenesis Given the relatively crude and simple nature of the screen and given that the recombinant Burkholderia infection and may allow us to begin to answer how bacterial cells persist within and spread between infected macrophages. Several of these positive gene clusters are therefore worthy of further discussion here. The first such region contains homology to the B. pertussis filamentous hemagglutinin or FHA. FHA is an adhesin which facilitates attachment to host cells during infection. Alongside this role in attachment, FHA also has other accessory functions, including pro-apoptotic activity towards host macrophages B. pseudomallei region homologous to FHA, cause dramatic actin protrusions from macrophages and apoptotic nuclei. It should be noted that B. pseudomallei travel down actin protrusions in order to spread to neighboring cells via actin based motility B. pseudomallei to the host cell or perhaps act as an effector, like BimA, involved in the process of intracellular spread itself.In reference to the genetic composition of the clusters themselves, phenotypic analysis of four regions of interest detected by the screen begin to link activity of the gene products to some of the important phenotypes associated with B. pseudomallei is capable of invading and replicating within both phagocytic and epithelial cells either entering via cell mediated phagocytosis or via the combined effects of Bsa T3SS and its internally delivered effector, BopE B. pseudomallei cells exhibit actin based motility and induce host cell fusion, resulting in the formation of ‘multi-nucleated giant cells’ or MNGCs. Here we have described both a MNGC-like and pro-apoptotic phenotype linked to a novel toxin cluster containing genes predicting proteins with homology to the Salmonella enterica virulence associated protein SpvB and different components of the Toxin complexes (Tcs) of the insect pathogen Photorhabdus luminescens. Whilst we have not designated specific phenotypes to specific genes within this novel cluster we suggest that these genes are responsible for reorganization of the actin cytoskeleton possibly directly or via effects on the small Rho GTPases. Further, this suggests that the formation of MNGCs in Burkholderia infected hosts can be induced by a single factor, independently of the actin-based motility mechanism. Further work addressing the process of secretion and mechanism of action of this novel toxin cluster will be important in understanding the role this region plays in MNGC formation.Following attachment, Rickettsia prowazekiiRickettsia show attenuated virulence in guinea pigs, and animals immunized with the mutant strain are protected from subsequent challenge with the wild-type strain. Phospholipase D is also a major virulence determinant of Corynebacterium pseudotuberculosis and plays a key role in macrophage death Corynebacterium pseudotuberculosis and Rickettsia prowazekii have therefore shown promise as a strategy for development of attenuated strain vaccines Burkholderia with host macrophages therefore warrants further attention.Anti-macrophage activity is also seen in response to positive clones containing a phospholipase D domain protein. A PLD gene encoding a protein with phospholipase D activity is associated with phagosomal escape in B. pseudomallei which appears to encode a molecule similar to the proteome inhibitor SylA from P. syringae, which we term BylA here. SylA is of extreme interest as it shows good activity against carcinoma derived cell lines and BylA may therefore be similarly interesting and important. We have shown that gene clusters encoding BylA produce an active compound cytotoxic towards macrophages when expressed in recombinant E. coli. Moreover, this bioactivity can be localized to the supernatant of the recombinant E. coli culture suggesting that it does indeed correspond to a secreted small molecule similar to SylA.Finally, many of the positive gene clusters are associated with the production of NRPS/PKS systems which are predicted to make small molecules or peptides. Whilst it is often possible to predict the likely structure of the small molecules made via the unique combinations of PKS modules present, the role of these gene products in bacterial virulence is often less clear. We focused on one such positive region in B. pseudomallei virulence include gene knockout within the pathogen and subsequent testing for avirulence using in vivo models. However, B. pseudomallei has a large genome with high genomic plasticity between strains and subspecies, and is designed to survive in a diverse array of environmental settings. Different strains of B. pseudomallei possess very different genetic complements suggesting there may be a variety of mechanisms for producing the same disease outcome. These factors imply that functional redundancy is highly likely among the mechanics of infection and that other genes may compensate for those mutated, and therefore mask the loss of virulence associated with any single gene knock-out or knock-down. The gain-of-function screen described here allows us to look at the effects of single factors provided that their potency can be reconstituted in recombinant E. coli. Characterisation of such leads will allow us to understand poorly understood mechanisms behind the pathogenicity of this organism and also present us with putative targets for vaccine and drug development. For screening other bacteria, such as Gram-positives, and indeed other microbes, such as fungi, we can envisage that such gain of function screens could be conducted in alternative and more appropriate hosts such as Bacillus or indeed yeast. Such studies would then allow for the rapid and facile screening of other microbial genomes for virulence factors for which similar assays can be derived.Current models for studying the factors involved E. coli DH10B containing pBACe3.6 with an average B. pseudomallei DNA insert size of 20 kb originally employed for the Sanger genome sequencing project E. coli EPI-300-T1R (Epicentre) with an average insert size of 40 kb. BAC and fosmids libraries were arrayed into 96 well microplates to give ∼10X coverage of the genome. All clones in the libraries were then end-sequenced to facilitate location of their paired ends in the genome.A combination genomic BAC and fosmid libraries, were used in these experiments. The BAC library was constructed in −1 chloramphenicol as the selective antibiotic for both the BAC and Fosmid library clones. Replicate library plates were grown for 24 h at 350 rpm, 37°C and cultures were subsequently harvested by centrifugation at 4,000 rpm for 10 minutes. 80 µl of supernatant aspirated the remaining bacterial pellet and supernatant mixed thoroughly with 80 µl 1 mg ml−1 lysozyme in Phosphate Buffered Saline solution. Plates were then incubated at room temperature for a minimum of 1 h, followed by three freeze-thaw cycles before centrifugation at 3,000 rpm for 10 minutes. 80 µl of the crude lysates were removed and applied to 96 well plates containing confluent monolayers of the BALB/c monocyte macrophage cell line J774-2  in Dulbecco's Modified Eagles Medium (DMEM) supplemented with 10% foetal bovine serum, 5% non-essential amino-acids and 5 µg ml−1 chloramphenicol. Crude lysates and macrophages were co-incubated for 24 h . Media on the macrophages was then replaced with phenol red-free DMEM containing an antibiotic cocktail: ampicllin 100 µg ml−1, gentamicin 50 µg ml−1, penicillin 100 U ml−1, streptomycin 100 µg ml−1, kanamycin 100 µg ml−1 and tetracycline 5 µg ml−1 and incubated with the macrophages for 2 h  to destroy live bacteria which would otherwise affect the readout of the cell viability assay. Macrophage cell viability was assessed using the XTT assay Library plates were replicated into 96 well microplates containing 100 µl Luria Bertani medium plus 12.5 µg mlBurkholderia chromosomes using SSAHA2 version 2.5 Burkholderia GBrowse database, and the BAC and fosmid sequences were displayed as separate tracks in the GBrowse detail panel. This allows for the identification of ‘clusters’ of clones containing putative virulence factors. These positive ‘clusters’ form due to the multiplicity of genomic coverage within a fosmid library, for example, up to ten clones encoding an anti-macrophage toxin might be recovered from a library possessing 10X genomic coverage. The minimum region of genetic overlap within clusters was examined for candidate CDSs or operons using the annotated K96243 genome and BLASTX analysis BAC and fosmid end sequences were aligned to the −1 Hoechst 33258 (Sigma) to stain the nuclei. A final wash by brief immersion 2X in distilled water is then made and coverslips mounted onto slides using ProLong Gold Antifade  before visualization using fluorescence microscopy. For fraction screening of the SylA homolog a single colony of a BAC library clone containing the SylA region of homology was picked and grown for 24 h in LB plus 12.5 µg ml−1 chloramphenicol. Bacteria were harvested by centrifugation at 7,000 rpm for 5 minutes and the culture supernatant removed. Cell-free supernatant was prepared by filter-sterilising with a 0.22 µm syringe-driven filter unit (Millipore). The cytosolic fraction was prepared by re-suspending the bacterial pellet in 1X PBS and sonicating the mixture. The resultant sonicated product was centrifuged at 10,000 rpm for 15 min. to remove cell debris from the cytosol preparation. Supernatant and cytosol fractions were applied to J774 macrophage monolayers at 1∶5 (v/v) supernatant or cytosol: culture media and co-incubated for 24 h before fixing and staining as described.Confluent monolayers of J774-2 macrophages on glass coverslips were treated with equivalent volumes of crude lysates (prepared as described above) from clones identified as containing regions of interest and co-incubated for 24 h. Coverslips were then washed in sterile 1X PBS before fixing with 4% paraformaldehyde (w/v) in PBS for 15 min. Coverslips were then washed in 1 X PBS and immersed in a fresh solution of ammonium chloride in 1X PBS (13.3 mg/ml) for 15 minutes, at room temperature followed by washing in 1X PBS. Macrophages were permeabilised by covering with 0.2% Triton X-100 in 1X PBS for 15 minutes. Staining of the filamentous actin cytoskeleton was carried out with TRITC conjugated phalloidin (Sigma), at a 1/500 dilution in 1X PBS by inverting the coverslip onto a 60 µl drop of the staining solution and incubating at room temperature in the dark for 1 h. Following incubation the coverslips were washed 3×5 minutes in 1X PBS with the first wash containing 0.12 µg/µlTable S1B. pseudomallei K96243 chromosome 1Complete inventory of anti-macrophage associated loci identified on (DOC)Click here for additional data file.Table S2B. pseudomallei K96243 chromosome 2Complete inventory of anti-macrophage associated loci identified on (DOC)Click here for additional data file.


Aedes aegypti, which regulate blood meal digestion and egg formation. In turn, hemocytes serve as the most important constitutive defense in mosquitoes against pathogens that enter the hemocoel. Prior studies indicated that blood feeding stimulates hemocytes to increase in abundance, but how this increase in abundance is regulated is unknown. Here, we determined that phagocytic granulocytes and oenocytoids express the A. aegypti insulin receptor (AaMIR). We then showed that: 1) decapitation of mosquitoes after blood feeding inhibited hemocyte proliferation, 2) a single dose of insulin-like peptide 3 (ILP3) sufficient to stimulate egg production rescued proliferation, and 3) knockdown of the AaMIR inhibited ILP3 rescue activity. Infection studies indicated that increased hemocyte abundance enhanced clearance of the bacterium Escherichia coli at lower levels of infection. Surprisingly, however, non-blood fed females better survived intermediate and high levels of E. coli infection than blood fed females. Taken together, our results reveal a previously unrecognized role for the insulin signaling pathway in regulating hemocyte proliferation. Our results also indicate that blood feeding enhances resistance to E. coli at lower levels of infection but reduces tolerance at higher levels of infection.All vector mosquito species must feed on the blood of a vertebrate host to produce eggs. Multiple cycles of blood feeding also promote frequent contacts with hosts, which enhance the risk of exposure to infectious agents and disease transmission. Blood feeding triggers the release of insulin-like peptides (ILPs) from the brain of the mosquito  Mosquitoes are vectors of several important diseases of humans and other mammals including Dengue fever, malaria and filariasis. These diseases adversely affect worldwide health by killing or debilitating millions of individuals. The key feature of mosquito biology that makes them such important disease vectors is that adult females must feed on the blood of their vertebrate host(s) to produce eggs. In turn, repeated bouts of blood feeding and egg development elevate the risk of mosquitoes feeding on an infected host and transmitting a given pathogen from one individual to another. A key regulator of egg development following blood feeding is the release of insulin-like peptides from the mosquito brain. We have found that insulin-like peptides enhance production of immune cells (hemocytes) that serve as the first line of defense against infection. Conversely, the molecular pathways that regulate egg development and hemocyte proliferation reduce the ability of mosquitoes to tolerate a persistent systemic infection. Taken together, our results indicate that trade-offs exist between reproduction and immune defense in mosquitoes, which is a subject of fundamental interest to evolutionary biologists and of applied importance in understanding disease transmission. Insects primarily rely on an innate immune system for defense against pathogens and other foreign invaders. Reciprocally, a number of insects including mosquitoes can be infected by and transmit certain pathogens that cause disease in humans and other vertebrate hosts. The key feature of mosquito biology that makes them important disease vectors is that adult females must feed on the blood of their vertebrate host(s) to produce eggs. Repeated bouts of blood feeding and egg development in turn increases the risk of mosquitoes feeding on an infected host and transmitting a given pathogen from one individual to another.Aedes aegypti triggers neurosecretory cells in the brain to release insulin-like peptides (ILPs) into circulation, which stimulate the ovaries to secrete ecdysteroid hormones (ECDs) At the physiological level, blood feeding by the mosquito A. aegypti produces three types of hemocytes named granulocytes, oenocytoids, and prohemocytes that are distinguished from one another by morphological, antigenic and functional characters Constitutive immune defenses in insects refer to factors like hemocytes that are always present and ready to act if an organism is infected, while inducible defenses refer to molecules like antimicrobial peptides that are produced in response to infection A. aegypti progressively declines with age, which in turn correlates with age-dependent increases in susceptibility to infection by bacteria like Escherichia coliPrior studies indicate that the number of hemocytes in adult This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, United States of America. The protocol was approved by The University of Georgia Institutional Animal Care and Use Committee (IACUC) , which oversees and provides veterinary care for all campus animal care facilities. IACUC is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC), is licensed by the US Department of Agriculture, and maintains an Assurance of Compliance with the US Public Health Service. IACUC technicians carried out all animal husbandry under strict guidelines to insure careful and consistent handling of animals.A. aegypti was used in all experiments. All life stages were maintained under a 12 h light/dark cycle at 28°C and 70–80% humidity. Larvae were fed with fish food, and adults were maintained in cages provided with 10% sucrose ad libitum.The UGAL strain of ILP3 used in the study was synthesized and purified as previously described Hemocytes were collected using the high injection/recovery method of Castillo et al. AaMIR  or actin (control)  0.2 mM of dNTPs and 2.5 Units Hotmaster Taq DNA polymerase  in 50-µl reaction mixtures. Cycling conditions were: 2 min of initial denaturation at 94°C, followed by 35 cycles of 20 sec denaturation step at 94°C, 30 sec annealing at 57°C, 45 sec extension at 72°C, and a final extension at 70°C for 10 min. Products were visualized on 0.5% agarose gels stained with ethidium bromide. Reactions for rqRT-PCR included iQ SYBR Green Supermix  and were run on a Rotor Gene Real Time-PCR cycler (Corbett) for 40 or 45 cycles under the following conditions: denaturation at 95° for 20 sec, annealing at 56° for 30 sec and extension at 72° for 30 sec. All reactions were run in quadruplicate with actin serving as the internal control . Data were analyzed by the ΔΔCt method as previously outlined Total RNA was extracted from hemocytes using Trizol reagent (Invitrogen). One µg of DNase-treated total RNA was used for cDNA synthesis using the Superscript III cDNA synthesis kit (Invitrogen). Hemocyte cDNA was diluted 10 fold and used 1 µl/20 µl for RT-PCR or 1 µl/10 µl for rqRT-PCR reactions with reaction mixtures containing specific primers for the AaMIR was PCR-amplified using the primers 5′ CCCCGGTTATGAAACAGTTC3′ (forward) and 5′TCTCGATGGACAAACTTCTT3′ reverse and cloned into the TOPO (pCR4.0) TA cloning dual promoter vector . Plasmid was then digested with NotI and KpnI (New England Biolabs), phenol/chloroform extracted and alcohol precipitated. Linearized plasmid was then used as template for synthesis of digoxigenin-labeled anti-sense and sense (negative control) AaMIR RNA probes using the DIG RNA labeling kit (SP6/T7) (Roche) following the manufacture's instructions. Probes were ethanol precipitated, resuspended in 25 µl of nuclease-free water and quantified by dot blot. In situ hybridization was then performed essentially as described by Lavine and Strand A 256 bp region of the -ΔΔCT values, differences in transcript abundance value between the dsMIR and dsEGFP treatments were analyzed by t-test.dsMIR and dsEGFP RNAs were produced using the T7 High Yield Transcription kit (Fermentas) The effects of decapitation on hemocyte abundance were conducted by decapitating females 1–12 h pbm followed by counting the total number of hemocytes recovered from females at 24 h pbm. The effects of ILP3 or 20E on hemocyte numbers at 24 h pbm were determined by decapitating females after feeding, injecting them with 0.5–50.0 pmol of ILP3 or 0.1–1.0 µg of 20E in 1 µl of PBS. Mosquitoes injected with PBS only served as a negative control. Decapitated females heal endogenously and visibly lose no hemolymph. Hemocyte abundance per mosquito was analyzed by ANOVA followed by the Tukey-Kramer multiple comparison procedure with treatment and/or sample time serving as the independent variable.Bromodioxyuridine (BrdU) incorporation was assessed by feeding day 2 females a sugar solution containing 1 mg BrdU per ml (Sigma). BrdU-fed females were then blood fed on day 4, and either left intact or decapitated. Hemocyte samples were then collected 24 h pbm and processed 3–1×105 colony forming units (CFUs) of the Migula strain of E. coli (ATCC# 25254), which are streptomycin-resistant. Third and fourth cohorts of mosquitoes were injected with dsEGFP or dsMIR RNA on day 1 followed by blood feeding on day 4 and injection with bacteria 24 h later as described above (BF-dsMIR). Mosquitoes were homogenized at 0, 3 or 24 h post-infection in 100 µl of BHI medium containing 50 µg/ml streptomycin, serially diluted and placed on BHI-streptomycin plates at 37°C for 18 h. The number of CFUs per individual was then determined , infection dose (1×103–1×105), and sample time  for a total of 180 individuals. We then compared the number of surviving bacteria per mosquito treatment and infection dose by Kruskal-Wallis tests. Other cohorts of BF and NBF mosquitoes treated as described above were maintained in cages  with sugar water for 6 days post-infection. The number of mosquitoes surviving each day was then determined by counting the number of mosquitoes that died during the intervening 24 h period. The survival experiments were replicated three times using cohorts of 20 females per treatment and infection dose. To assess the effect of infection on mortality rates, we used the proportional hazards model where treatment and infection dose were the independent variables and the number of dead mosquitoes on each day was the dependent variable. All analyses were conducted using the JMP 7.0 statistical platform .For infection assays, one cohort of adult females was blood fed (BF) on day 4 while a second cohort was left non-blood fed (NBF) followed 24 h later by injection of 1×10A. aegypti encodes a single receptor tyrosine kinase, designated the mosquito insulin receptor (AaMIR), that is structurally homologous to the vertebrate IR AaMIR. Using gene specific primers and total hemocyte cDNA as template, RT-PCR analysis detected AaMIR expression in hemocytes from both non-blood fed (NBF) females and blood-fed (BF) females sampled 2, 3, 9, and 24 h pbm  RNA into newly eclosed females, held them for 4 days with water, and then blood fed on day 4. rqRT-PCR analysis confirmed that dsMIR treatment reduced AaMIR transcript abundance in hemocytes relative to mosquitoes treated with dsEGFP . This resulted in the following treatments: BF, NBF, BF-dsEGFP injected, and BF-dsMIR injected. We then determined the number of surviving bacteria at 0, 3, and 24 h post-injection by homogenizing each mosquito and culturing the supernatant on streptomycin-containing BHI plates. Overall, the number of bacteria recovered per mosquito varied significantly among treatments, infection dose, and sample time  (3 CFUs) and 24 h sampling time, our results indicated that bacterial survival varied significantly among treatments   while clearance of bacteria by NBF and BF-dsMIR females also did not differ . In contrast, BF and BF-dsEGFP females cleared significantly more bacteria than NBF and BF-dsMIR females . Taken together, these results argued that increased production of hemocytes by BF and BF-dsEGFP females enhanced clearance of bacteria while pretreatment with dsMIR reduced hemocyte production and associated clearance of bacteria by BF females to similar levels as NBF females. These data also suggested that wounding at the time of dsRNA injection had no effect on the outcome of these assays. At the intermediate infection dose we tested (1×104 CFUs), the number of surviving bacteria after 24 h was also lower but no differences were detected among treatments  (5 CFUs) the number of surviving bacteria at 24 h had similarly increased in each treatment  (Given previous evidence showing that 1) granulocytes phagocytize several species of bacteria including  0.0001) . Focusin= 0.012) . Closer  = 0.88) , while a = 0.29) . InspectE. coli by BF and NBF females and survival by monitoring mosquito mortality for 6 days post-infection. 3 CFUs. However, analysis across all three levels of infection using the proportional hazards model revealed a strongly significant difference in the death rate of BF and NBF females  , but also showed that BF females died at higher rates than NBF females   . Effect <0.0001) . Thus, f after 6 . Since mA. aegypti, for example, bacterial infection of the hemocoel elicits a phagocytic response by hemocytes followed by inducible expression of antimicrobial peptides Anopheles gambiae, passage of Plasmodium to the hemolymph-bathed basal side of the midgut exposes the parasite to complement-like thioester-containing proteins from hemocytes that contribute to parasite killing Plasmodium infection also damages the peritrophic matrix that surrounds the blood meal, resulting in commensal bacteria interacting with the midgut, which in turn stimulates constitutive and inducible defense responses against both bacteria and PlasmodiumMost studies of the mosquito immune system focus on defense responses following systemic infection with bacteria or consumption of a pathogen-infected blood meal Far less is known about how mosquitoes invest in immune defenses in the absence of infection. We reasoned that the unique requirement of vector species to blood feed also creates a cyclical pattern of increased nutrient availability and infection risk that could favor cyclical investment in constitutive defenses like hemocytes. Our results support this hypothesis by showing that the number of hemocytes recovered from females increases 40% by 24 pbm. Our results further reveal a previously unrecognized role for the insulin signaling pathway in regulating the cellular arm of the mosquito immune system and synchronizing increased production of hemocytes with reproduction.A. gambiae. However, the average number of hemocytes per individual we and others recover from A. aegypti and A. gambiaeThe progressive, age-dependent decline in hemocyte abundance that occurs in the absence of blood feeding suggested to Hillyer and coworkers A. aegypti and other insects encode only a single receptor tyrosine kinase (IR) that functions as the receptor for multiple ILP family members Bombyx moriPacifastacus leniusculusAe. aegypti.Unlike mammals, which produce both insulin and insulin-like growth factors that preferentially interact with different receptors, A. aegypti hemocytes are labile in primary culture and we currently are unable to maintain them for a long enough period to evaluate whether ILP3 directly stimulates proliferation in vitro. However, we do note that injection of ILP3 (50 pmol) into NBF females stimulates a significant increase in hemocyte abundance relative to NBF controls after 24 h (data not presented). This increase is smaller than the increase observed in decapitated BF females  we tested. Our results showing that pretreatment of BF females with dsMIR reduces bacterial clearance to NBF levels also supports the conclusion that enhanced clearance by BF females is due to increased numbers of granulocytes. No difference in clearance of bacteria was detected among treatments at higher levels of infection. However, this outcome was not entirely unexpected given that hemocyte abundance after blood feeding increases less than 2-fold but females were injected with 10 or 100-fold more bacteria. In effect, infection by 104 or 105E. coli exceeded the phagocytic capacity of the granulocytes present in each treatment resulting in higher numbers of surviving bacteria after 24 h. Although Hillyer et al. A. aegypti granulocytes can phagocytize more than 1000 E. coli per cell, they also detected levels of surviving bacteria 24 h and 5 days post-infection that are very similar to our results with NBF females suggesting substantial numbers of bacteria evaded phagocytosis in vivo when mosquitoes were infected with 104 or more cells.We anticipated that blood feeding would elevate resistance to at least some potential pathogens through an increase in the number of phagocytic granulocytes. We examined this possibility using E. coli infection than BF females. When viewed together, the results presented in E. coli. However, at higher levels of initial infection blood feeding reduces tolerance to E. coli which is defined in the insect immunity literature as the ability to survive infection at a given pathogen load A. aegypti as a consequence of blood meal digestion and/or mobilization of resources for reproduction.In contrast, we did not anticipate that NBF females would better survive intermediate and high levels of E. coli in BF females remains unclear. In Drosophila, both bacterial infection and infection-independent activation of the Toll signaling pathway suppresses insulin signaling which reduces energy stores but enhances tolerance by potentially increasing investment in inducible defenses under Toll regulation A. aegyptiA. gambiae indicate that the presence of Vg diminishes killing of PlasmodiumPlasmodium infection also reduces Vg expression in A. gambiaeDrosophila could reflect an indirect response mediated by reduced insulin signaling. A second possibility for reduced tolerance is that metabolism of vertebrate blood is both energetically expensive and generates toxic compounds like heme or ammonia that must be inactivated A. aegypti, which normally regulates growth of gut microbiota but upon down regulation allows the gut microbiota to greatly increase in abundance. It is unlikely reduced ROS production in the midgut affected the systemic infection of the hemocoel we generated in our experiments. However, these results do suggest other processes related to tolerance could be adversely affected by processing the blood meal.The mechanism(s) underlying reduced tolerance to