Transcription profiling by array of honey bee brains from bees that show Varroa Sensitive Hygiene (VSH) behavior
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ABSTRACT: Expression profiling of bees that have been selected for their high tendency to perform VSH behavior (VSH+) versus control bees, who performs normal VSH behavior (VSH-)
Project description:Brain expression profiling of bees perfroming consistently vibration signal (modulatory signal that stimulates the performance of several different activities in the hive).
Project description:We analyzed the changes in brain gene expression after alarm pheromone exposure. Bees from single-drone inseminated colonies were exposed to alarm pheromone at the hive entrance and collected 1h after exposure for analysis.
Project description:Expression profiling of honey bee brains exposed to brood pheromone. Exposure was performed in colonies and young (5 days-old) and old bees (15 days-old) were analyzed .
Project description:Apis mellifera workers in temperate climates display two castes; short lived summer bees that engage in nursing, hive maintenance and foraging, and long lived winter bees (diutinus bees) which remain within the hive and are essential for thermoregulation. Label free quantitative proteomic analysis was conducted on A. mellifera workers sampled in June and December to compare the proteomes of summer and winter bees. Proteomic analysis was completed on head, abdominal and venom sac samples which revealed an elevated level of protein abundance in summer bees but and a decrease in protein abundance in winter bees. Head and abdominal samples displayed an increase in cuticular proteins in summer samples whereas an increase in xenobiotic proteins was observed in winter samples. Several carbohydrate metabolism pathways which have been linked to energy production and longevity in insects were observed to be increased in abundance in winter samples in comparison to summer samples. Proteomic analysis of the venom sacs an increased abundance and expression of bee venom associated proteins in comparison to winter workers. These data provides an insight into the adaptions of A. mellifera workers in summer and winter and may aid in future treatment and disease studies on honeybee colonies.
Project description:Apis mellifera workers in temperate climates display two castes; short lived summer bees that engage in nursing, hive maintenance and foraging, and long lived winter bees (diutinus bees) which remain within the hive and are essential for thermoregulation. Label free quantitative proteomic analysis was conducted on A. mellifera workers sampled in June and December to compare the proteomes of summer and winter bees. Proteomic analysis was completed on head, abdominal and venom sac samples which revealed an elevated level of protein abundance in summer bees but and a decrease in protein abundance in winter bees. Head and abdominal samples displayed an increase in cuticular proteins in summer samples whereas an increase in xenobiotic proteins was observed in winter samples. Several carbohydrate metabolism pathways which have been linked to energy production and longevity in insects were observed to be increased in abundance in winter samples in comparison to summer samples. Proteomic analysis of the venom sacs an increased abundance and expression of bee venom associated proteins in comparison to winter workers. These data provides an insight into the adaptions of A. mellifera workers in summer and winter and may aid in future treatment and disease studies on honeybee colonies.
Project description:Apis mellifera workers in temperate climates display two castes; short lived summer bees that engage in nursing, hive maintenance and foraging, and long lived winter bees (diutinus bees) which remain within the hive and are essential for thermoregulation. Label free quantitative proteomic analysis was conducted on A. mellifera workers sampled from July to October 2019 to compare the proteomes of workers as the colony progresses through the year. Proteomic analysis revealed a shift in protein expression in workers in September and October in comparison to July and August samples. Workers samples in September and October had a higher abundance of proteins associated with oxidative phosphorylation and storage proteins such as hexamerin. Interestingly, a shift in protein expression was detected in newly emerged bees between July to October, providing evidence that workers have adapted to emerge with a different protein profile in preparation for the winter months.
Project description:To identify genes associated with lung cancer progression, we examined gene expression profiles of tumor cells from 20 patients with primary, untreated non-small cell lung cancer (10 adenocarcinomas (AC) and 10 squamous cell carcinomas (SCC)) in comparison to lung tissue of 23 patients with stage IIIB or stage IV non-small cell lung cancer (15 AC and 8 SCC). Bronchoscopical biopsies from patient with recurrent lung tumor were taken after initial treatment. Cancer cells were isolated using laser capture microdissection in order to obtain pure samples of tumor cells. For expression analysis, microarrays covering 8793 defined genes (Human HG Focus Array, Affymetrix) were used. Array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM), respectively. Genes were considered to be up- or down-regulated when the ratio between primary and recurrent tumor samples were at least 1.5-fold differentially expressed with an estimated false discovery rate: < 5%. Based on differentially expressed genes, primary cancer samples could be separated from recurrent tumor samples. We identified 115 and 124 significantly regulates genes in AC and SCC, respectively. For example, in recurrent AC we found increased expression of genes related to the wingless (FZD6, RYK, MYC) and calcium (CALM1, ATB2B1, S100A2) signalling pathways which might play a role in metastasis of tumor cells. Other differentially expressed genes were related to cell cycle (CCND1, CDK2), transcription factors (TTF1, TAF2, YY1), nuclear mRNA splicing and mRNA processing (SFRS1, HNRPL), protein-nucleus import (NUTF2, KPNB1, NUP50) and chromatin modification (HIST1H4C, SMARCC1). In SCC, we found an increased expression of CTNNB1, an important mediator in wingless signalling pathway. Among the down-regulated genes in SCC, the utmost fraction belonged to genes coding for ubiquitin mediated proteolysis (UCHL1, PSMA3, COPS6) and ribosomal proteins (RPS26, RPL7A, RPS15). Other down regulated genes were related to transcription factors (TCEA2, TAF10), nuclear mRNA splicing and mRNA processing (SNRPD2, HNRPM). In conclusion, a distinct pattern of gene expression is found during the progression from primary carcinoma to recurrent NSCLC. Our microarray-based expression profiling revealed interesting novel candidate genes and pathways that may contribute to lung cancer progression. Experiment Overall Design: - 20 patients with primary, untreated non-small cell lung cancer (10adenocarcinomas (AC) and 10 squamous cell carcinomas (SCC)) in comparison to lung tissue of 23 patients with stage IIIB or stage IV non-small cell lung cancer (15 AC and 8 SCC) Experiment Overall Design: - Human HG Focus Array, Affymetrix) were used Experiment Overall Design: - Array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM) Experiment Overall Design: - Genes were considered to be up- or down-regulated when the ratio between primary and recurrent tumor samples were at least 1.5-fold differentially expressed with an estimated false discovery rate: < 5%
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. So far, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. While SCLCs express properties of neuroendocrine cells, NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. A contamination of the tumor sample with normal epithelia, blood vessels, stromal cells, leucocytes and tumor necrosis may confound the true expression profile of the tumor. The use of laser capture microdissection (LCM) greatly improves the sample preparation for microarray expression analysis. Consequently, we used advanced technology including LCM and microarray analysis. In detail, we examined gene expression profiles of tumor cells from 29 previously untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), 9 small cell lung cancer (SCLC)) in comparison to normal lung tissue (LT) of 5 control patients without tumor. Bronchoscopical biopsies from the primary lung tumor were taken before treatment. Biopsies were cut into 8µm sections and from each section cancer cells were isolated using laser capture microdissection in order to obtain pure samples of tumor cells. Total RNA was extracted, reversely transcribed, in-vitro transcribed, labelled and hybridized to the array. For expression analysis, microarrays covering 8793 defined genes (Human HG Focus Array, Affymetrix) were used. Following quality control, array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM), respectively. Based on differentially expressed genes cancer samples could be clearly separated from non cancer samples using hierarchical clustering. Comparing AC, SCC and SCLC with normal lung tissue, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed with an estimated false discovery rate < 2.6%. Each histological subtype showed a distinct expression profile. Further, using a genetic programming approach we constructed a classificator to discriminate AC, SCC, NT and SCLC. To this end, the 50 genes with the greatest signal-to-noise ratio were selected to train the classificator. By leave-one-out cross validation all 34 samples were correctly classified in this training set. In order to validate the 50-gene-classificator on a test set, further 13 microdissected lung cancer samples were used and correctly classified in concordance to pathologic finding. In conclusion, the different lung cancer subtypes have distinct molecular phenotypes which reflect biological characteristics of the tumor cells and which might be the basis for development of targeted therapy. Moreover, gene expression profiling and genetic programming is a suitable tool for classification and discrimination of different histological subtypes in lung cancer in comparison to normal lung tissue. Experiment Overall Design: Comparison of gene expression profiles of normal lung tissues, adenocarcinomas, squamous cell carcinomas and small cell lung cancers.