Characterization and Tissue-specific Expression of bHLH Genes in Dimocarpus longan

In plants, the basic helix-loop-helix (bHLH) transcription factors (TFs) play pivotal roles in many biological processes including growth, stress response, and secondary metabolite synthesis. To date, many bHLH genes have been identified and characterized in diverse plant species. However, little is known regarding the bHLH genes in Dimocarpus longan Lour. (D. longan). Based on RNA-seq data, we identified 42 putative bHLH genes from D. longan and determined their putative functions using the NCBI Conserved Domain Search Tool and Pfam databases. The physicochemical properties, phylogenetic relationships, conserved motifs, gene ontology (GO) annotations, protein-protein interactions, and tissue-specific expression patterns of these bHLH genes were systematically explored. In total, ten motifs were found in DlbHLH proteins using MEME, among which two were highly conserved. Phylogenetic tree analysis found that DlbHLH proteins can be divided into nine groups, with group 2 being the largest. GO annotation results showed that the DlHLH genes were involved in various molecular functions. RNA-seq and qRT-PCR results revealed important differences in the expression patterns of 17 of the DlbHLH genes. In particular, DlbHLH-9, DlbHLH-19, DlbHLH-25, DlbHLH-26, and DlbHLH-35 were found to show significantly different expression patterns in root and leaf tissues. The results of this study will further enrich our knowledge regarding bHLH transcription factor genes and lay a foundation for enhancing the production of active secondary metabolites by genetic engineering in D. longan

Genome-wide association tests by using block information in family data

Abstract By applying an association test to analyze the data sets from Genetic Analysis Workshop 15 Problem 3, we compare power using different haplotype-block information. The results from using both of the two different coding schemes show that the test using tight blocks with limited haplotype diversity within each block is more powerful than that using evenly spaced blocks, and the latter is more powerful than that using single-marker blocks. By using carefully chosen haplotype blocks, the power of association tests may be enhanced.http://deepblue.lib.umich.edu/bitstream/2027.42/117371/1/12919_2007_Article_2513.pd

Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes

BACKGROUND: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very few common identified marker genes among different studies involving patients with the same disease. Therefore, it is of great interest and challenge to merge data sets from multiple studies to increase the sample size, which may in turn increase the power of statistical inferences. In this study, we combined two lung cancer studies using micorarray GeneChip(®), employed two gene shaving methods and a two-step survival test to identify genes with expression patterns that can distinguish diseased from normal samples, and to indicate patient survival, respectively. RESULTS: In addition to common data transformation and normalization procedures, we applied a distribution transformation method to integrate the two data sets. Gene shaving (GS) methods based on Random Forests (RF) and Fisher's Linear Discrimination (FLD) were then applied separately to the joint data set for cancer gene selection. The two methods discovered 13 and 10 marker genes (5 in common), respectively, with expression patterns differentiating diseased from normal samples. Among these marker genes, 8 and 7 were found to be cancer-related in other published reports. Furthermore, based on these marker genes, the classifiers we built from one data set predicted the other data set with more than 98% accuracy. Using the univariate Cox proportional hazard regression model, the expression patterns of 36 genes were found to be significantly correlated with patient survival (p < 0.05). Twenty-six of these 36 genes were reported as survival-related genes from the literature, including 7 known tumor-suppressor genes and 9 oncogenes. Additional principal component regression analysis further reduced the gene list from 36 to 16. CONCLUSION: This study provided a valuable method of integrating microarray data sets with different origins, and new methods of selecting a minimum number of marker genes to aid in cancer diagnosis. After careful data integration, the classification method developed from one data set can be applied to the other with high prediction accuracy

Untargeted Plasma Metabolite Profiling Reveals the Broad Systemic Consequences of Xanthine Oxidoreductase Inactivation in Mice

A major challenge in systems biology is integration of molecular findings for individual enzyme activities into a cohesive high-level understanding of cellular metabolism and physiology/pathophysiology. However, meaningful prediction for how a perturbed enzyme activity will globally impact metabolism in a cell, tissue or intact organisms is precluded by multiple unknowns, including in vivo enzymatic rates, subcellular distribution and pathway interactions. To address this challenge, metabolomics offers the potential to simultaneously survey changes in thousands of structurally diverse metabolites within complex biological matrices. The present study assessed the capability of untargeted plasma metabolite profiling to discover systemic changes arising from inactivation of xanthine oxidoreductase (XOR), an enzyme that catalyzes the final steps in purine degradation. Using LC-MS coupled with a multivariate statistical data analysis platform, we confidently surveyed >3,700 plasma metabolites (50–1,000 Da) for differential expression in XOR wildtype vs. mice with inactivated XOR, arising from gene deletion or pharmacological inhibition. Results confirmed the predicted derangements in purine metabolism, but also revealed unanticipated perturbations in metabolism of pyrimidines, nicotinamides, tryptophan, phospholipids, Krebs and urea cycles, and revealed kidney dysfunction biomarkers. Histochemical studies confirmed and characterized kidney failure in xor-nullizygous mice. These findings provide new insight into XOR functions and demonstrate the power of untargeted metabolite profiling for systemic discovery of direct and indirect consequences of gene mutations and drug treatments

Spred2 controls the severity of Concanavalin A-induced liver damage by limiting interferon-gamma production by CD4(+) and CD8(+) T cells

Introduction: Mitogen-activated protein kinases (MAPKs) are involved in T cell-mediated liver damage. However, the inhibitory mechanism(s) that controls T cell-mediated liver damage remains unknown. Objectives: We investigated whether Spred2 (Sprouty-related, EVH1 domain-containing protein 2) that negatively regulates ERK-MAPK pathway has a biological impact on T cell-mediated liver damage by using a murine model. Methods: We induced hepatotoxicity in genetically engineered mice by intravenously injecting Concanavalin A (Con A) and analyzed the mechanisms using serum chemistry, histology, ELISA, qRT-PCR, Western blotting and flow cytometry. Results: Spred2-deficient mice (Spred2(-/-)) developed more sever liver damage than wild-type (WT) mice with increased interferon-gamma (IFNy) production. Hepatic ERK phosphorylation was enhanced in Spred2(-/-) mice, and pretreatment of Spred2(-/-) mice with the MAPK/ERK inhibitor U0126 markedly inhibited the liver damage and reduced IFN gamma production. Neutralization of IFNy abolished the damage with decreased hepatic Stat1 activation in Spred2(-/-) mice. IFN gamma was mainly produced from CD4(+) and CD8(+) T cells, and their depletion decreased liver damage and IFN gamma production. Transplantation of CD4(+) and/or CD8(+) T cells from Spred2(-/-) mice into RAG1(-/-) mice deficient in both T and B cells caused more severe liver damage than those from WT mice. Hepatic expression of T cell attractants, CXCL9 and CXCL10, was augmented in Spred2(-/-) mice as compared to WT mice. Conversely, liver damage, IFN gamma production and the recruitment of CD4(+) and CD8(+) T cells in livers after Con A challenge were lower in Spred2 transgenic mice, and Spred2-overexpressing CD4(+) and CD8(+) T cells produced lower levels of IFN gamma than WT cells upon stimulation with Con A in vitro. Conclusion: We demonstrated, for the first time, that Spred2 functions as an endogenous regulator of T cell IFNy production and Spred2-mediated inhibition of ERK-MAPK pathway may be an effective remedy for T cell-dependent liver damage

Prenatal disruption of blood–brain barrier formation via cyclooxygenase activation leads to lifelong brain inflammation

Gestational maternal immune activation (MIA) in mice induces persistent brain microglial activation and a range of neuropathologies in the adult offspring. Although long-term phenotypes are well documented, how MIA in utero leads to persistent brain inflammation is not well understood. Here, we found that offspring of mothers treated with polyriboinosinic–polyribocytidylic acid [poly(I:C)] to induce MIA at gestational day 13 exhibit blood–brain barrier (BBB) dysfunction throughout life. Live MRI in utero revealed fetal BBB hyperpermeability 2 d after MIA. Decreased pericyte–endothelium coupling in cerebral blood vessels and increased microglial activation were found in fetal and 1- and 6-mo-old offspring brains. The long-lasting disruptions result from abnormal prenatal BBB formation, driven by increased proliferation of cyclooxygenase-2 (COX2; Ptgs2)-expressing microglia in fetal brain parenchyma and perivascular spaces. Targeted deletion of the Ptgs2 gene in fetal myeloid cells or treatment with the inhibitor celecoxib 24 h after immune activation prevented microglial proliferation and disruption of BBB formation and function, showing that prenatal COX2 activation is a causal pathway of MIA effects. Thus, gestational MIA disrupts fetal BBB formation, inducing persistent BBB dysfunction, which promotes microglial overactivation and behavioral alterations across the offspring life span. Taken together, the data suggest that gestational MIA disruption of BBB formation could be an etiological contributor to neuropsychiatric disorders

Mortality and Attrition Rates within the First Year of Antiretroviral Therapy Initiation among People Living with HIV in Guangxi, China: An Observational Cohort Study

Objective. To assess the mortality and attrition rates within the first year of antiretroviral therapy (ART) initiation among people living with human immunodeficiency virus (PLHIV) in rural Guangxi, China. Design. Observational cohort study. Setting. The core treatment indicators and data were collected with standard and essential procedures as per the Free ART Manual guidelines across all the rural health care centers of Guangxi. Participants. 58,115 PLHIV who were under ART were included in the study. Interventions. The data collected included sociodemographic characteristics that consist of age, sex, marital status, route of HIV transmission, CD4 cell count before ART, initial ART regimen, level of ART site, and year of ART initiation. Primary and Secondary Outcome Measures. Mortality and attrition rate following ART initiation. Results. The average mortality rate was 5.94 deaths, and 17.52 attritions per 100 person-years within the first year of ART initiation among PLHIV. The mortality rate was higher among intravenous drug users (Adjusted Hazard Ratio (AHR) 1.27, 95% Confidence Interval (CI) 1.14-1.43), prefecture as a level of ART site (AHR 1.14, 95% CI 1.02-1.28), and county as the level of ART site (AHR 2.12, 95% CI 1.90-2.37). Attrition was higher among intravenous drug users (AHR 1.87, 95% CI 1.75-2.00), the first-line ART containing AZT (AHR 1.09, 95% CI 1.03-1.16), and first-line ART containing LVP/r (AHR 1.34, 95% CI 1.23-1.46). Conclusion. The mortality and attrition rates were both at the highest level in the first year of post-ART; continued improvement in the quality of HIV treatment and care is needed