Citations

While the life cycles of hepatitis viruses (A, B, C, D, and E) have been modestly characterized, recent intensive studies have provided new insights. Because these viruses “hijack” the membrane trafficking of the host cell machinery during replicative propagation, it is essential to determine and understand these specific cellular pathways. Hepatitis B virus (HBV) and hepatitis C virus are well known as leading causes of liver cirrhosis and hepatocellular carcinoma. While substantial inroads toward treating hepatitis C virus patients have recently been made, patients with HBV continue to require lifelong treatment, which makes a thorough understanding of the HBV life cycle essential. Importantly, these viruses have been observed to “hijack” the secretory and endocytic membrane trafficking machineries of the hepatocyte. These can include the canonical clathrin‐mediated endocytic process that internalizes virus through cell surface receptors. While these receptors are encoded by the host genome for normal hepatocellular functions, they also exhibit virus‐specific recognition. Further, functions provided by the multivesicular body, which include endosomal sorting complexes required for transport, are now known to envelope a variety of different hepatitis viruses. In this review, we summarize the recent findings regarding the cellular membrane trafficking machineries used by HBV in the context of other hepatitis viruses. (Hepatology2018; 00:000‐000).

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero inflation remain largely undeveloped. Here we propose GMPR - a simple but effective normalization method - for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero inflation remain largely undeveloped. Here we propose GMPR - a simple but effective normalization method - for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

The clinical utility of microbiome biomarkers depends on the reliable and reproducible nature of comparative results. Underappreciation of the variation associated with common demographic, health, and behavioral factors may confound associations of interest and generate false positives. Here, we present the Midwestern Reference Panel (MWRP), a resource for comparative gut microbiome studies conducted in the Midwestern United States. We analyzed the relationships between demographic and health behavior–related factors and the microbiota in this cohort, and estimated their effect sizes. Most variables investigated were associated with the gut microbiota. Specifically, body mass index (BMI), race, sex, and alcohol use were significantly associated with microbial β-diversity (P < 0.05, unweighted UniFrac). BMI, race and alcohol use were also significantly associated with microbial α-diversity (P < 0.05, species richness). Tobacco use showed a trend toward association with the microbiota (P < 0.1, unweighted UniFrac). The effect sizes of the associations, as quantified by adjusted R 2 values based on unweighted UniFrac distances, were small (< 1% for all variables), indicating that these factors explain only a small percentage of overall microbiota variability. Nevertheless, the significant associations between these variables and the gut microbiota suggest that they could still be potential confounders in comparative studies and that controlling for these variables in study design, which is the main objective of the MWRP, is important for increasing reproducibility in comparative microbiome studies.

Abstract Motivation Recent studies have revealed a complex interplay between environment, the human microbiome and health and disease. Mediation analysis of the human microbiome in these complex relationships could potentially provide insights into the role of the microbiome in the etiology of disease and, more importantly, lead to novel clinical interventions by modulating the microbiome. However, due to the high dimensionality, sparsity, non-normality and phylogenetic structure of microbiome data, none of the existing methods are suitable for testing such clinically important mediation effect. Results We propose a distance-based approach for testing the mediation effect of the human microbiome. In the framework, the nonlinear relationship between the human microbiome and independent/dependent variables is captured implicitly through the use of sample-wise ecological distances, and the phylogenetic tree information is conveniently incorporated by using phylogeny-based distance metrics. Multiple distance metrics are utilized to maximize the power to detect various types of mediation effect. Simulation studies demonstrate that our method has correct Type I error control, and is robust and powerful under various mediation models. Application to a real gut microbiome dataset revealed that the association between the dietary fiber intake and body mass index was mediated by the gut microbiome. Availability and implementation An R package ‘MedTest’ is freely available at https://github.com/jchen1981/MedTest. Supplementary information Supplementary data are available at Bioinformatics online.

ABSTRACT Microglia as immune cells of the central nervous system (CNS) play significant roles not only in pathology but also in physiology, such as shaping of the CNS during development and its proper maintenance in maturity. Emerging research is showing a close association between microglia and the neurovasculature that is critical for brain energy supply. In this review, we summarize the current literature on microglial interaction with the vascular system in the normal and diseased brain. First, we highlight data that indicate interesting potential involvement of microglia in developmental angiogenesis. Then we discuss the evidence for microglial participation with the vasculature in neuropathologies from brain tumors to acute injuries such as ischemic stroke to chronic neurodegenerative conditions. We conclude by suggesting future areas of research to advance the field in light of current technical progress and outstanding questions. © 2018 Wiley Periodicals, Inc. Develop Neurobiol 78: 604–617, 2018

Tumor tissues are chronically exposed to hypoxia owing to aberrant vascularity. Lipid droplet (LD) accumulation is a hallmark of hypoxic cancer cells, yet how LDs form and function during hypoxia remains poorly understood. Herein, we report that in various cancer cells upon oxygen deprivation, HIF-1 activation down-modulates LD catabolism mediated by adipose triglyceride lipase (ATGL), the key enzyme for intracellular lipolysis. Proteomics and functional analyses identified hypoxia-inducible gene 2 (HIG2), a HIF-1 target, as a new inhibitor of ATGL. Knockout of HIG2 enhanced LD breakdown and fatty acid (FA) oxidation, leading to increased ROS production and apoptosis in hypoxic cancer cells as well as impaired growth of tumor xenografts. All of these effects were reversed by co-ablation of ATGL. Thus, by inhibiting ATGL, HIG2 acts downstream of HIF-1 to sequester FAs in LDs away from the mitochondrial pathways for oxidation and ROS generation, thereby sustaining cancer cell survival in hypoxia.