New pattern-based method for identifying recent HIV-1 infections from the viral env sequence

The study investigates a pattern-based method for measuring intra-patient viral genetic diversity for determination of recent infections and estimation of population incidence. Pattern-based diversities of recent infections are significantly lower than that of chronic ones. With larger window periods varying from 200 to 350 days, a higher accuracy (90%95%) not affected by advanced disease nor antiretroviral therapy (ART) treatment could be obtained. The pattern-based genetic method is supplementary to existing serology-based assays, both suitable for use in low and high epidemic regions respectively. The envelope (env) gene of HIV/SIV is the most variable of viral genes

Insulin resistance and white adipose tissue inflammation are uncoupled in energetically challenged Fsp27-deficient mice.

Fsp27 is a lipid droplet-associated protein almost exclusively expressed in adipocytes where it facilitates unilocular lipid droplet formation. In mice, Fsp27 deficiency is associated with increased basal lipolysis, 'browning' of white fat and a healthy metabolic profile, whereas a patient with congenital CIDEC deficiency manifested an adverse lipodystrophic phenotype. Here we reconcile these data by showing that exposing Fsp27-null mice to a substantial energetic stress by crossing them with ob/ob mice or BATless mice, or feeding them a high-fat diet, results in hepatic steatosis and insulin resistance. We also observe a striking reduction in adipose inflammation and increase in adiponectin levels in all three models. This appears to reflect reduced activation of the inflammasome and less adipocyte death. These findings highlight the importance of Fsp27 in facilitating optimal energy storage in adipocytes and represent a rare example where adipose inflammation and hepatic insulin resistance are disassociated.This work was supported by grants from the National Basic Research Program (2013CB530602 and 2011CB910801 to P.L.), from the National Natural Science Foundation of China (31430040, 31321003 and 31030038), from the China Postdoctoral Science Foundation (2012M520249 and 2013T60103 to L.Z.) and from the Wellcome Trust (091551 to D.S.). This work was also supported by the Bio and Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013M3A9D5072563 to C.C.) and Korea Healthcare Technology R&D Project, Ministry for Health, Welfare and Family Affairs, Korea (A102060 to C.C.).This is the final published version. It first appeared at http://www.nature.com/ncomms/2015/150107/ncomms6949/full/ncomms6949.html?WT.ec_id=NCOMMS-20150114

Gene expression profile in the fat tissue of Fsp27 deficient mice

Fsp27 is a lipid droplet-associated protein almost exclusively expressed in adipocytes where it facilitates unilocular lipid droplet formation. In mice, Fsp27 deficiency is associated with increased basal lipolysis, browning of white fat and a healthy metabolic profile, whereas energetically challenged Fsp27 deficient mice (ob/ob/Fsp27−/−) show dramatically reduced fat mass, hepatic steatosis and insulin resistance which represents a typical lipodystrophy phenotype. Here, we investigate the effect of Fsp27 depletion on the gene expression of gonadal white adipose tissue (GWAT) under normal or energetically challenged condition (Fsp27−/− vs Wild type; ob/ob/Fsp27−/− vs ob/ob). We systematically analyzed the change in signaling pathway in Fsp27 deficient mice. The raw data have been deposited into Gene Expression Omnibus (GEO): GSE59807 and GSE22693

Cross-Species Analysis of Gene Expression and Function in Prefrontal Cortex, Hippocampus and Striatum.

BACKGROUND:Mouse has been extensively used as a tool for investigating the onset and development of human neurological disorders. As a first step to construct a transgenic mouse model of human brain lesions, it is of fundamental importance to clarify the similarity and divergence of genetic background between non-diseased human and mouse brain tissues. METHODS:We systematically compared, based on large scale integrated microarray data, the transcriptomes of three anatomically distinct brain regions; prefrontal cortex (PFC), hippocampus (HIP) and striatum (STR), across human and mouse. The widely used DAVID web server was used to decipher the biological functions of the highly expressed genes that were identified using a previously reported approach. Venn analysis was used to depict the overlapping ratios of the notably enriched biological process (BP) terms (one-tailed Fisher's exact test and Benjamini correction; adjusted p < 0.01) between two brain tissues. GOSemSim, an R package, was selected to perform GO semantic similarity analysis. Next, we adjusted signal intensities of orthologous genes by the total signals in all samples within species, and used one minus Pearson's correlation coefficient to assess the expression distance. Hierarchical clustering and principal component analysis (PCA) were selected for expression pattern analysis. Lineage specific expressed orthologous genes were identified by comparison of the most extreme sub-datasets across species and further verified using reverse transcription PCR (RT-PCR) and quantitative real-time PCR (qRT-PCR). RESULTS:We found that the number of the significantly enriched BP terms of the highly expressed genes in human brain regions is larger than that in mouse corresponding brain regions. The mainly involved BP terms in human brain tissues associated with protein-membrane targeting and selenium metabolism are species-specific. The overlapping ratios of all the significantly enriched BP terms between any two brain tissues across species are lower than that within species, but the pairwise semantic similarities are very high between any two brain tissues from either human or mouse. Hierarchical clustering analysis shows the biological functions of the highly expressed genes in brain tissues are more consistent within species than interspecies; whereas it shows the expression patterns of orthologous genes are evidently conserved between human and mouse equivalent brain tissues. In addition, we identified four orthologous genes (COX5B, WIF1, SLC4A10 and PLA2G7) that are species-specific, which have been widely studied and confirmed to be closely linked with neuro- physiological and pathological functions. CONCLUSION:Our study highlights the similarities and divergences in gene function and expression between human and mouse corresponding brain regions, including PFC, HIP and STR

Function of the c-Met receptor tyrosine kinase in carcinogenesis and associated therapeutic opportunities

Abstract c-Met is a receptor tyrosine kinase belonging to the MET (MNNG HOS transforming gene) family, and is expressed on the surfaces of various cells. Hepatocyte growth factor (HGF) is the ligand for this receptor. The binding of HGF to c-Met initiates a series of intracellular signals that mediate embryogenesis and wound healing in normal cells. However, in cancer cells, aberrant HGF/c-Met axis activation, which is closely related to c-Met gene mutations, overexpression, and amplification, promotes tumor development and progression by stimulating the PI3K/AKT, Ras/MAPK, JAK/STAT, SRC, Wnt/β-catenin, and other signaling pathways. Thus, c-Met and its associated signaling pathways are clinically important therapeutic targets. In this review, we elaborate on the molecular structure of c-Met and HGF and the mechanism through which their interaction activates the PI3K/AKT, Ras/MAPK, and Wnt signaling pathways. We also summarize the connection between c-Met and RON and EGFR, which are also receptor tyrosine kinases. Finally, we introduce the current therapeutic drugs that target c-Met in primary tumors, and their use in clinical research

Confirmation of Affymetrix microarray data by RT-PCR.

<p><i>GAPDH</i>, a housekeeping gene, was used to normalize gene expression in human and mouse (a) PFC, (b) HIP and (c) STR. Genes that are predicted by miacroarray data but not verified by RT-PCR are highlighted using dashed boxes. The background and band colors were reversed. The average relative densitometry values were analyzed using Image J software. Data are expressed as mean ± SD. Red bars represent human and green bars mouse.</p

Confirmation of Affymetrix chip data by qRT-PCR.

<p>GAPDH was used to normalize gene expression. The relative expression of each gene was calculated as log2 of 2^-△Ct values. Data are expressed as mean ± SD. Red bars represent human and green bars mouse.</p