Differential Gene Expression in Erlotinib-Treated Fibroblasts.

BACKGROUND: Therapies targeting the epidermal growth factor receptor (EGFR) result in a painful rash, the most common and debilitating toxicity among patients with non-small cell lung cancer (NSCLC) who take EGFR tyrosine kinase inhibitor (TKI) therapy; however, predicting the development and the severity of the rash is difficult. OBJECTIVE: The aim of this study was to examine how erlotinib-an EGFR TKI that NSCLC patients take to stop or slow tumor growth-altered the transcriptome of dermal fibroblasts. METHODS: Dermal fibroblasts (ATCC PCS-201-012) were seeded in cell culture flasks, grown under standard conditions, and transferred to cell culture dishes. Cells were treated once daily for 3 days with erlotinib 100 nM (n = 5), erlotinib 1 µM (n = 5), vehicle 1 µM (dimethyl sulfoxide) (n = 5), or no treatment (n = 5). Total RNA was extracted using a standard TRIzol method and hybridized using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Raw intensities generated from the arrays were normalized using a Robust Multiarray Average method and analyzed using analysis of variance in Limma R software. Differentially expressed genes were analyzed using Ingenuity Pathway Analysis to identify canonical or noncanonical signaling pathways enriched in this dataset. RESULTS: We selected genes for investigation based on their potential role in wound healing (AQP3), rash development (CCL2), fibroblast activation (PALLD), cancer and cancer progression (GDF-15, SLC7A11, MMP12, and DIRAS3), and cell cycle control (CDC6). We were able to validate four of these genes by both Western blot analysis and quantitative polymerase chain reaction (MMP12, CCL2, CDC6, and SLC7A11). DISCUSSION: If found predictive of rash in future studies using patient samples, our findings may help to identify those at risk for severe rash so that (a) the dose of EGFR TKI therapy may be adjusted; (b) additional treatments for the rash can be developed; and/or (c) precise, patient-centered interventions can be developed so that patients with cancer can better self-manage their rash and adhere to EGFR TKI treatment.

The effective population size of malaria mosquitoes: large impact of vector control.

Malaria vectors in sub-Saharan Africa have proven themselves very difficult adversaries in the global struggle against malaria. Decades of anti-vector interventions have yielded mixed results--with successful reductions in transmission in some areas and limited impacts in others. These varying successes can be ascribed to a lack of universally effective vector control tools, as well as the development of insecticide resistance in mosquito populations. Understanding the impact of vector control on mosquito populations is crucial for planning new interventions and evaluating existing ones. However, estimates of population size changes in response to control efforts are often inaccurate because of limitations and biases in collection methods. Attempts to evaluate the impact of vector control on mosquito effective population size (N(e)) have produced inconclusive results thus far. Therefore, we obtained data for 13-15 microsatellite markers for more than 1,500 mosquitoes representing multiple time points for seven populations of three important vector species--Anopheles gambiae, An. melas, and An. moucheti--in Equatorial Guinea. These populations were exposed to indoor residual spraying or long-lasting insecticidal nets in recent years. For comparison, we also analyzed data from two populations that have no history of organized vector control. We used Approximate Bayesian Computation to reconstruct their demographic history, allowing us to evaluate the impact of these interventions on the effective population size. In six of the seven study populations, vector control had a dramatic impact on the effective population size, reducing N(e) between 55%-87%, the exception being a single An. melas population. In contrast, the two negative control populations did not experience a reduction in effective population size. This study is the first to conclusively link anti-vector intervention programs in Africa to sharply reduced effective population sizes of malaria vectors.

Species-specific chemosensory gene expression in the olfactory organs of the malaria vector Anopheles gambiae.

BACKGROUND: The malaria mosquito Anopheles gambiae has a high preference for human hosts, a characteristic that contributes greatly to its capacity for transmitting human malaria. A sibling species, An. quadriannulatus, has a quite different host preference and feeds mostly on bovids. For this reason it does not contribute to human malaria transmission. Host seeking in mosquitoes is modulated by the olfactory system, which is primarily housed in the antennae and maxillary palps. Therefore, the detection of differing host odors by sibling species may be reflected in the expression level of the olfactory genes involved. Accordingly, we compared the transcriptomes of the antennae and maxillary palps of An. gambiae and An. quadriannulatus. RESULTS: We identified seven relatively abundant olfactory receptors, nine ionotropic receptors and three odorant binding proteins that are substantially up-regulated in An. gambiae antennae. Interestingly, we find that the maxillary palps of An. gambiae contain a species-specific olfactory receptor, Or52, and five An. gambiae-specific gustatory receptors (AgGr48-52) that are relatively abundant. These five gustatory receptors are also expressed in An. gambiae antennae, although at lower level, indicating a likely role in olfaction, rather than gustation. We also document an approximately three-fold higher overall expression of olfaction genes in the maxillary palps of An. quadriannulatus, indicating an important role of this organ in the olfaction system of this species. Finally, the expression of the CO2 receptor genes is five to six-fold higher in the zoophilic An. quadriannulatus, implying a much higher sensitivity for detecting CO2. CONCLUSIONS: These results identify potential human host preference genes in the malaria vector An. gambiae. Interestingly, species-specific expression of several gustatory receptors in the olfactory organs indicate a role in olfaction rather than gustation. Additionally, a more expansive role for maxillary palps in olfaction is implicated than previously thought, albeit more so in the zoophilic An. quadriannulatus.

Making Common Fund data more findable: catalyzing a data ecosystem.

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.

Successful Profiling of Plasmodium falciparum var Gene Expression in Clinical Samples via a Custom Capture Array.

var genes encode Plasmodium falciparum erythrocyte membrane protein-1 (PfEMP1) antigens. These highly diverse antigens are displayed on the surface of infected erythrocytes and play a critical role in immune evasion and sequestration of infected erythrocytes. Studies of var expression using non-leukocyte-depleted blood are challenging because of the predominance of host genetic material and lack of conserved var segments. Our goal was to enrich for parasite RNA, allowing de novo assembly of var genes and detection of expressed novel variants. We used two overall approaches: (i) enriching for total mRNA in the sequencing library preparations and (ii) enriching for parasite RNA with a custom capture array based on Roche's SeqCap EZ enrichment system. The capture array was designed with probes based on the whole 3D7 reference genome and an additional >4,000 full-length var gene sequences from other P. falciparum strains. We tested each method on RNA samples from Malian children with severe or uncomplicated malaria infections. All reads mapping to the human genome were removed, the remaining reads were assembled de novo into transcripts, and from these, var-like transcripts were identified and annotated. The capture array produced the longest maximum length and largest numbers of var gene transcripts in each sample, particularly in samples with low parasitemia. Identifying the most-expressed var gene sequences in whole-blood clinical samples without the need for extensive processing or generating sample-specific reference genome data is critical for understanding the role of PfEMP1s in malaria pathogenesis. IMPORTANCE Malaria parasites display antigens on the surface of infected red blood cells in the human host that facilitate attachment to blood vessels, contributing to the severity of infection. These antigens are highly variable, allowing the parasite to evade the immune system. Identifying these expressed antigens is critical to understanding the development of severe malarial disease. However, clinical samples contain limited amounts of parasite genetic material, a challenge for sequencing efforts further compounded by the extreme diversity of the parasite surface antigens. We present a method that enriches for these antigen sequences in clinical samples using a custom capture array, requiring minimal processing in the field. While our results are focused on the malaria parasite Plasmodium falciparum, this approach has broad applicability to other highly diverse antigens from other parasites and pathogens such as those that cause giardiasis and leishmaniasis.

Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments.

For optimal performance, machine learning methods for protein sequence/structural analysis typically require as input a large multiple sequence alignment (MSA), which is often created using query-based iterative programs, such as PSI-BLAST or JackHMMER. However, because these programs align database sequences using a query sequence as a template, they may fail to detect or may tend to misalign sequences distantly related to the query. More generally, automated MSA programs often fail to align sequences correctly due to the unpredictable nature of protein evolution. Addressing this problem typically requires manual curation in the light of structural data. However, curated MSAs tend to contain too few sequences to serve as input for statistically based methods. We address these shortcomings by making publicly available a set of 252 curated hierarchical MSAs (hiMSAs), containing a total of 26 212 066 sequences, along with programs for generating from these extremely large MSAs. Each hiMSA consists of a set of hierarchically arranged MSAs representing individual subgroups within a superfamily along with template MSAs specifying how to align each subgroup MSA against MSAs higher up the hierarchy. Central to this approach is the MAPGAPS search program, which uses a hiMSA as a query to align (potentially vast numbers of) matching database sequences with accuracy comparable to that of the curated hiMSA. We illustrate this process for the exonuclease-endonuclease-phosphatase superfamily and for pleckstrin homology domains. A set of extremely large MSAs generated from the hiMSAs in this way is available as input for deep learning, big data analyses. MAPGAPS, auxiliary programs CDD2MGS, AddPhylum, PurgeMSA and ConvertMSA and links to National Center for Biotechnology Information data files are available at https://www.igs.umaryland.edu/labs/neuwald/software/mapgaps/.

The Effects of Soil Texture on the Ability of Human Remains Detection Dogs to Detect Buried Human Remains.

Despite technological advances, human remains detection (HRD) dogs still remain one of the best tools for locating clandestine graves. However, soil texture may affect the escape of decomposition gases and therefore the effectiveness of HDR dogs. Six nationally credentialed HRD dogs (three HRD only and three cross-trained) were evaluated on novel buried human remains in contrasting soils, a clayey and a sandy soil. Search time and accuracy were compared for the clayey soil and sandy soil to assess odor location difficulty. Sandy soil (p < 0.001) yielded significantly faster trained response times, but no significant differences were found in performance accuracy between soil textures or training method. Results indicate soil texture may be significant factor in odor detection difficulty. Prior knowledge of soil texture and moisture may be useful for search management and planning. Appropriate adjustments to search segment sizes, sweep widths and search time allotment depending on soil texture may optimize successful detection.

Application of soil in forensic science: residual odor and HRD dogs.

Decomposing human remains alter the environment through deposition of various compounds comprised of a variety of chemical constituents. Human remains detection (HRD) dogs are trained to indicate the odor of human remains. Residual odor from previously decomposing human remains may remain in the soil and on surfaces long after the remains are gone. This study examined the ability of eight nationally certified HRD dogs (four dual purpose and four single purpose) to detect human remains odor in soil from under decomposing human remains as well as soils which no longer contained human remains, soils which had been cold water extracted and even the extraction fluid itself. The HRD dogs were able to detect the odor of human remains successfully above the level of chance for each soil ranging between 75% and 100% accurate up to 667 days post body removal from soil surface. No significant performance accuracy was found between the dual and single purpose dogs. This finding indicates that even though there may not be anything visually observable to the human eye, residual odor of human remains in soil can be very recalcitrant and therefore detectible by properly trained and credentialed HRD dogs. Further research is warranted to determine the parameters of the HRD dogs capabilities and in determining exactly what they are smelling.

Defense traits of larval Drosophila melanogaster exhibit genetically based trade-offs against different species of parasitoids.

Populations of Drosophila melanogaster face significant mortality risks from parasitoid wasps that use species-specific strategies to locate and survive in hosts. We tested the hypothesis that parasitoids with different strategies select for alternative host defense characteristics and in doing so contribute to the maintenance of fitness variation and produce trade-offs among traits. We characterized defense traits of Drosophila when exposed to parasitoids with different host searching behaviors (Aphaereta sp. and Leptopilina boulardi). We used host larvae with different natural alleles of the gene Dopa decarboxylase (Ddc), a gene controlling the production of dopamine and known to influence the immune response against parasitoids. Previous population genetic analyses indicate that our focal alleles are maintained by balancing selection. Genotypes exhibited a trade-off between the immune response against Aphaereta sp. and the ability to avoid parasitism by L. boulardi. We also identified a trade-off between the ability to avoid parasitism by L. boulardi and larval competitive ability as indicated by differences in foraging and feeding behavior. Genotypes differed in dopamine levels potentially explaining variation in these traits. Our results highlight the potential role of parasitoid biodiversity on host fitness variation and implicate Ddc as an antagonistic pleiotropic locus influencing larval fitness traits.

Large fluctuations in the effective population size of the malaria mosquito Anopheles gambiae s.s. during vector control cycle.

On Bioko Island, Equatorial Guinea, indoor residual spraying (IRS) has been part of the Bioko Island Malaria Control Project since early 2004. Despite success in reducing childhood infections, areas of high transmission remain on the island. We therefore examined fluctuations in the effective population size (N e ) of the malaria vector Anopheles gambiae in an area of persistent high transmission over two spray rounds. We analyzed data for 13 microsatellite loci from 791 An. gambiae specimens collected at six time points in 2009 and 2010 and reconstructed the demographic history of the population during this period using approximate Bayesian computation (ABC). Our analysis shows that IRS rounds have a large impact on N e , reducing it by 65%-92% from prespray round N e . More importantly, our analysis shows that after 3-5 months, the An. gambiae population rebounded by 2818% compared shortly following the spray round. Our study underscores the importance of adequate spray round frequency to provide continuous suppression of mosquito populations and that increased spray round frequency should substantially improve the efficacy of IRS campaigns. It also demonstrates the ability of ABC to reconstruct a detailed demographic history across only a few tens of generations in a large population.