51 research outputs found

    Molecular Cloning and Characterization of the Human ErbB4 Gene: Identification of Novel Splice Isoforms in the Developing and Adult Brain

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    ErbB4 is a growth factor receptor tyrosine kinase essential for neurodevelopment. Genetic variation in ErbB4 is associated with schizophrenia and risk-associated polymorphisms predict overexpression of ErbB4 CYT-1 isoforms in the brain in the disorder. The molecular mechanism of association is unclear because the polymorphisms flank exon 3 of the gene and reside 700 kb distal to the CYT-1 defining exon. We hypothesized that the polymorphisms are indirectly associated with ErbB4 CYT-1 via splicing of exon 3 on the CYT-1 background. We report via cloning and sequencing of adult and fetal human brain cDNA libraries the identification of novel splice isoforms of ErbB4, whereby exon 3 is skipped (del.3). ErbB4 del.3 transcripts exist as CYT-2 isoforms and are predicted to produce truncated proteins. Furthermore, our data refine the structure of the human ErbB4 gene, clarify that juxtamembrane (JM) splice variants of ErbB4, JM-a and JM-b respectively, are characterized by the replacement of a 75 nucleotide (nt) sequence with a 45-nt insertion, and demonstrate that there are four alternative exons in the gene. Our analyses reveal that novel splice variants of ErbB4 exist in the developing and adult human brain and, given the failure to identify ErbB4 del.3 CYT-1 transcripts, suggest that the association of risk polymorphisms in the ErbB4 gene with CYT-1 transcript levels is not mediated via an exon 3 splicing event

    Ets-1 Regulates Energy Metabolism in Cancer Cells

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    Cancer cells predominantly utilize glycolysis for ATP production even in the presence of abundant oxygen, an environment that would normally result in energy production through oxidative phosphorylation. Although the molecular mechanism for this metabolic switch to aerobic glycolysis has not been fully elucidated, it is likely that mitochondrial damage to the electron transport chain and the resulting increased production of reactive oxygen species are significant driving forces. In this study, we have investigated the role of the transcription factor Ets-1 in the regulation of mitochondrial function and metabolism. Ets-1 was over-expressed using a stably-incorporated tetracycline-inducible expression vector in the ovarian cancer cell line 2008, which does not express detectable basal levels of Ets-1 protein. Microarray analysis of the effects of Ets-1 over-expression in these ovarian cancer cells shows that Ets-1 up-regulates key enzymes involved in glycolysis and associated feeder pathways, fatty acid metabolism, and antioxidant defense. In contrast, Ets-1 down-regulates genes involved in the citric acid cycle, electron transport chain, and mitochondrial proteins. At the functional level, we have found that Ets-1 expression is directly correlated with cellular oxygen consumption whereby increased expression causes decreased oxygen consumption. Ets-1 over-expression also caused increased sensitivity to glycolytic inhibitors, as well as growth inhibition in a glucose-depleted culture environment. Collectively our findings demonstrate that Ets-1 is involved in the regulation of cellular metabolism and response to oxidative stress in ovarian cancer cells

    P. falciparum Modulates Erythroblast Cell Gene Expression in Signaling and Erythrocyte Production Pathways

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    Global, genomic responses of erythrocytes to infectious agents have been difficult to measure because these cells are e-nucleated. We have previously demonstrated that in vitro matured, nucleated erythroblast cells at the orthochromatic stage can be efficiently infected by the human malaria parasite Plasmodium falciparum. We now show that infection of orthochromatic cells induces change in 609 host genes. 592 of these transcripts are up-regulated and associated with metabolic and chaperone pathways unique to P. falciparum infection, as well as a wide range of signaling pathways that are also induced in related apicomplexan infections of mouse hepatocytes or human fibroblast cells. Our data additionally show that polychromatophilic cells, which precede the orthochromatic stage and are not infected when co-cultured with P. falciparum, up-regulate a small set of genes, at least two of which are associated with pathways of hematopoiesis and/or erythroid cell development. These data support the idea that P. falciparum affects erythropoiesis at multiple stages during erythroblast differentiation. Further P. falciparum may modulate gene expression in bystander erythroblasts and thus influence pathways of erythrocyte development. This study provides a benchmark of the host erythroblast cell response to infection by P. falciparum

    Predicting Housekeeping Genes Based on Fourier Analysis

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    Housekeeping genes (HKGs) generally have fundamental functions in basic biochemical processes in organisms, and usually have relatively steady expression levels across various tissues. They play an important role in the normalization of microarray technology. Using Fourier analysis we transformed gene expression time-series from a Hela cell cycle gene expression dataset into Fourier spectra, and designed an effective computational method for discriminating between HKGs and non-HKGs using the support vector machine (SVM) supervised learning algorithm which can extract significant features of the spectra, providing a basis for identifying specific gene expression patterns. Using our method we identified 510 human HKGs, and then validated them by comparison with two independent sets of tissue expression profiles. Results showed that our predicted HKG set is more reliable than three previously identified sets of HKGs

    Expression of Regulatory Platelet MicroRNAs in Patients with Sickle Cell Disease

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    Background: Increased platelet activation in sickle cell disease (SCD) contributes to a state of hypercoagulability and confers a risk of thromboembolic complications. The role for post-transcriptional regulation of the platelet transcriptome by microRNAs (miRNAs) in SCD has not been previously explored. This is the first study to determine whether platelets from SCD exhibit an altered miRNA expression profile. Methods and Findings: We analyzed the expression of miRNAs isolated from platelets from a primary cohort (SCD = 19, controls = 10) and a validation cohort (SCD = 7, controls = 7) by hybridizing to the Agilent miRNA microarrays. A dramatic difference in miRNA expression profiles between patients and controls was noted in both cohorts separately. A total of 40 differentially expressed platelet miRNAs were identified as common in both cohorts (p-value 0.05, fold change>2) with 24 miRNAs downregulated. Interestingly, 14 of the 24 downregulated miRNAs were members of three families - miR-329, miR-376 and miR-154 - which localized to the epigenetically regulated, maternally imprinted chromosome 14q32 region. We validated the downregulated miRNAs, miR-376a and miR-409-3p, and an upregulated miR-1225-3p using qRT-PCR. Over-expression of the miR-1225-3p in the Meg01 cells was followed by mRNA expression profiling to identify mRNA targets. This resulted in significant transcriptional repression of 1605 transcripts. A combinatorial approach using Meg01 mRNA expression profiles following miR-1225-3p overexpression, a computational prediction analysis of miRNA target sequences and a previously published set of differentially expressed platelet transcripts from SCD patients, identified three novel platelet mRNA targets: PBXIP1, PLAGL2 and PHF20L1. Conclusions: We have identified significant differences in functionally active platelet miRNAs in patients with SCD as compared to controls. These data provide an important inventory of differentially expressed miRNAs in SCD patients and an experimental framework for future studies of miRNAs as regulators of biological pathways in platelets. Β© 2013 Jain et al

    Predicting a local recurrence after breast-conserving therapy by gene expression profiling

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    INTRODUCTION: To tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients. METHODS: By using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy. RESULTS: Validation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence. CONCLUSION: Our findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy

    Gene Expression Profiles of Colonic Mucosa in Healthy Young Adult and Senior Dogs

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    Background: We have previously reported the effects of age and diet on nutrient digestibility, intestinal morphology, and large intestinal fermentation patterns in healthy young adult and senior dogs. However, a genome-wide molecular analysis of colonic mucosa as a function of age and diet has not yet been performed in dogs. Methodology/Principal Findings: Colonic mucosa samples were collected from six senior (12-year old) and six young adult (1-year old) female beagles fed one of two diets (animal protein-based vs. plant protein-based) for 12 months. Total RNA in colonic mucosa was extracted and hybridized to Affymetrix GeneChipH Canine Genome Arrays. Results indicated that the majority of gene expression changes were due to age (212 genes) rather than diet (66 genes). In particular, the colonic mucosa of senior dogs had increased expression of genes associated with cell proliferation, inflammation, stress response, and cellular metabolism, whereas the expression of genes associated with apoptosis and defensive mechanisms were decreased in senior vs. young adult dogs. No consistent diet-induced alterations in gene expression existed in both age groups, with the effects of diet being more pronounced in senior dogs than in young adult dogs. Conclusion: Our results provide molecular insight pertaining to the aged canine colon and its predisposition to dysfunction and disease. Therefore, our data may aid in future research pertaining to age-associated gastrointestinal physiologica

    Single-Cell Analysis Reveals Distinct Gene Expression and Heterogeneity in Male and Female Plasmodium falciparum Gametocytes

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    Β© 2018 Walzer et al. Sexual reproduction is an obligate step in the Plasmodium falciparum life cycle, with mature gametocytes being the only form of the parasite capable of human-to-mosquito transmission. Development of male and female gametocytes takes 9 to 12 days, and although more than 300 genes are thought to be specific to gametocytes, only a few have been postulated to be male or female specific. Because these genes are often expressed during late gametocyte stages and for some, male- or female-specific transcript expression is debated, the separation of male and female populations is technically challenging. To overcome these challenges, we have developed an unbiased single-cell approach to determine which transcripts are expressed in male versus female gametocytes. Using microfluidic technology, we isolated single mid- to late-stage gametocytes to compare the expression of 91 genes, including 87 gametocyte-specific genes, in 90 cells. Such analysis identified distinct gene clusters whose expression was associated with male, female, or all gametocytes. In addition, a small number of male gametocytes clustered separately from female gametocytes based on sex-specific expression independent of stage. Many female-enriched genes also exhibited stage-specific expression. RNA fluorescent in situ hybridization of male and female markers validated the mutually exclusive expression pattern of male and female transcripts in gametocytes. These analyses uncovered novel male and female markers that are expressed as early as stage III gametocytogenesis, providing further insight into Plasmodium sex-specific differentiation previously masked in population analyses. Our single-cell approach reveals the most robust markers for sex-specific differentiation in Plasmodium gametocytes. Such single-cell expression assays can be generalized to all eukaryotic pathogens

    Automated Detection of <i>P</i>. <i>falciparum</i> Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells

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    <div><p>Malaria detection through microscopic examination of stained blood smears is a diagnostic challenge that heavily relies on the expertise of trained microscopists. This paper presents an automated analysis method for detection and staging of red blood cells infected by the malaria parasite <i>Plasmodium falciparum</i> at trophozoite or schizont stage. Unlike previous efforts in this area, this study uses quantitative phase images of unstained cells. Erythrocytes are automatically segmented using thresholds of optical phase and refocused to enable quantitative comparison of phase images. Refocused images are analyzed to extract 23 morphological descriptors based on the phase information. While all individual descriptors are highly statistically different between infected and uninfected cells, each descriptor does not enable separation of populations at a level satisfactory for clinical utility. To improve the diagnostic capacity, we applied various machine learning techniques, including linear discriminant classification (LDC), logistic regression (LR), and <i>k</i>-nearest neighbor classification (NNC), to formulate algorithms that combine all of the calculated physical parameters to distinguish cells more effectively. Results show that LDC provides the highest accuracy of up to 99.7% in detecting schizont stage infected cells compared to uninfected RBCs. NNC showed slightly better accuracy (99.5%) than either LDC (99.0%) or LR (99.1%) for discriminating late trophozoites from uninfected RBCs. However, for early trophozoites, LDC produced the best accuracy of 98%. Discrimination of infection stage was less accurate, producing high specificity (99.8%) but only 45.0%-66.8% sensitivity with early trophozoites most often mistaken for late trophozoite or schizont stage and late trophozoite and schizont stage most often confused for each other. Overall, this methodology points to a significant clinical potential of using quantitative phase imaging to detect and stage malaria infection without staining or expert analysis.</p></div
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