Xianwen Ren

Virome Analysis for Identification of Novel Mammalian Viruses in Bat Species from Chinese Provinces

ABSTRACT Bats are natural hosts for a large variety of zoonotic viruses. This study aimed to describe the range of bat viromes, including viruses from mammals, insects, fungi, plants, and phages, in 11 insectivorous bat species (216 bats in total) common in six provinces of China. To analyze viromes, we used sequence-independent PCR amplification and next-generation sequencing technology (Solexa Genome Analyzer II; Illumina). The viromes were identified by sequence similarity comparisons to known viruses. The mammalian viruses included those of the Adenoviridae, Herpesviridae, Papillomaviridae, Retroviridae, Circoviridae, Rhabdoviridae, Astroviridae, Flaviridae, Coronaviridae, Picornaviridae, and Parvovirinae; insect viruses included those of the Baculoviridae, Iflaviridae, Dicistroviridae, Tetraviridae, and Densovirinae; fungal viruses included those of the Chrysoviridae, Hypoviridae, Partitiviridae, and Totiviridae; and phages included those of the Caudovirales, Inoviridae, and Microviridae and unclassified phages. In addition to the viruses and phages associated with the insects, plants, and bacterial flora related to the diet and habitation of bats, we identified the complete or partial genome sequences of 13 novel mammalian viruses. These included herpesviruses, papillomaviruses, a circovirus, a bocavirus, picornaviruses, a pestivirus, and a foamy virus. Pairwise alignments and phylogenetic analyses indicated that these novel viruses showed little genetic similarity with previously reported viruses. This study also revealed a high prevalence and diversity of bat astroviruses and coronaviruses in some provinces. These findings have expanded our understanding of the viromes of bats in China and hinted at the presence of a large variety of unknown mammalian viruses in many common bat species of mainland China.

Binary matrix factorization for analyzing gene expression data

The advent of microarray technology enables us to monitor an entire genome in a single chip using a systematic approach. Clustering, as a widely used data mining approach, has been used to discover phenotypes from the raw expression data. However traditional clustering algorithms have limitations since they can not identify the substructures of samples and features hidden behind the data. Different from clustering, biclustering is a new methodology for discovering genes that are highly related to a subset of samples. Several biclustering models/methods have been presented and used for tumor clinical diagnosis and pathological research. In this paper, we present a new biclustering model using Binary Matrix Factorization (BMF). BMF is a new variant rooted from non-negative matrix factorization (NMF). We begin by proving a new boundedness property of NMF. Two different algorithms to implement the model and their comparison are then presented. We show that the microarray data biclustering problem can be formulated as a BMF problem and can be solved effectively using our proposed algorithms. Unlike the greedy strategy-based algorithms, our proposed algorithms for BMF are more likely to find the global optima. Experimental results on synthetic and real datasets demonstrate the advantages of BMF over existing biclustering methods. Besides the attractive clustering performance, BMF can generate sparse results (i.e., the number of genes/features involved in each biclustering structure is very small related to the total number of genes/features) that are in accordance with the common practice in molecular biology.

Deciphering the bat virome catalog to better understand the ecological diversity of bat viruses and the bat origin of emerging infectious diseases

Studies have demonstrated that ~60%–80% of emerging infectious diseases (EIDs) in humans originated from wild life. Bats are natural reservoirs of a large variety of viruses, including many important zoonotic viruses that cause severe diseases in humans and domestic animals. However, the understanding of the viral population and the ecological diversity residing in bat populations is unclear, which complicates the determination of the origins of certain EIDs. Here, using bats as a typical wildlife reservoir model, virome analysis was conducted based on pharyngeal and anal swab samples of 4440 bat individuals of 40 major bat species throughout China. The purpose of this study was to survey the ecological and biological diversities of viruses residing in these bat species, to investigate the presence of potential bat-borne zoonotic viruses and to evaluate the impacts of these viruses on public health. The data obtained in this study revealed an overview of the viral community present in these bat samples. Many novel bat viruses were reported for the first time and some bat viruses closely related to known human or animal pathogens were identified. This genetic evidence provides new clues in the search for the origin or evolution pattern of certain viruses, such as coronaviruses and noroviruses. These data offer meaningful ecological information for predicting and tracing wildlife-originated EIDs.

Genomic profiling of plasmablastic lymphoma using array comparative genomic hybridization (aCGH): revealing significant overlapping genomic lesions with diffuse large B-cell lymphoma

BackgroundPlasmablastic lymphoma (PL) is a subtype of diffuse large B-cell lymphoma (DLBCL). Studies have suggested that tumors with PL morphology represent a group of neoplasms with clinopathologic characteristics corresponding to different entities including extramedullary plasmablastic tumors associated with plasma cell myeloma (PCM). The goal of the current study was to evaluate the genetic similarities and differences among PL, DLBCL (AIDS-related and non AIDS-related) and PCM using array-based comparative genomic hybridization.ResultsExamination of genomic data in PL revealed that the most frequent segmental gain (> 40%) include: 1p36.11-1p36.33, 1p34.1-1p36.13, 1q21.1-1q23.1, 7q11.2-7q11.23, 11q12-11q13.2 and 22q12.2-22q13.3. This correlated with segmental gains occurring in high frequency in DLBCL (AIDS-related and non AIDS-related) cases. There were some segmental gains and some segmental loss that occurred in PL but not in the other types of lymphoma suggesting that these foci may contain genes responsible for the differentiation of this lymphoma. Additionally, some segmental gains and some segmental loss occurred only in PL and AIDS associated DLBCL suggesting that these foci may be associated with HIV infection. Furthermore, some segmental gains and some segmental loss occurred only in PL and PCM suggesting that these lesions may be related to plasmacytic differentiation.ConclusionTo the best of our knowledge, the current study represents the first genomic exploration of PL. The genomic aberration pattern of PL appears to be more similar to that of DLBCL (AIDS-related or non AIDS-related) than to PCM. Our findings suggest that PL may remain best classified as a subtype of DLBCL at least at the genome level.

Comparative study of the cytokine/chemokine response in children with differing disease severity in enterovirus 71-induced hand, foot, and mouth disease.

Background Enterovirus 71 (EV71) infection can lead to a rapidly progressing, life-threatening, and severe neurological disease in young children, including the development of human hand, foot, and mouth disease (HFMD). This study aims to further characterize the specific immunological features in EV71–mediated HFMD patients presenting with differing degrees of disease severity. Methodology Comprehensive cytokine and chemokine expression were broadly evaluated by cytokine antibody array in EV71–infected patients hospitalized for HFMD compared to Coxsackievirus A16-infected patients and age-matched healthy controls. More detailed analysis using Luminex-based cytokine bead array was performed in EV71–infected patients stratified into diverse clinic outcomes. Additionally, immune cell frequencies in peripheral blood and EV71–specific antibodies in plasma were also examined. Principal Findings Expression of several cytokines and chemokines were significantly increased in plasma from EV71–infected patients compared to healthy controls, which further indicated that: (1) GM-CSF, MIP-1β, IL-2, IL-33, and IL-23 secretion was elevated in patients who rapidly developed disease and presented with uncomplicated neurological damage; (2) G-CSF and MCP-1 were distinguishably secreted in EV71 infected very severe patients presenting with acute respiratory failure; (3) IP-10, MCP-1, IL-6, IL-8, and G-CSF levels were much higher in cerebrospinal fluid than in plasma from patients with neurological damage; (4) FACS analysis revealed that the frequency of CD19+HLADR+ mature B cells dynamically changed over time during the course of hospitalization and was accompanied by dramatically increased EV71–specific antibodies. Our data provide a panoramic view of specific immune mediator and cellular immune responses of HFMD and may provide useful immunological profiles for monitoring the progress of EV71–induced fatal neurological symptoms with acute respiratory failure.

ellipsoidFN: a tool for identifying a heterogeneous set of cancer biomarkers based on gene expressions.

Computationally identifying effective biomarkers for cancers from gene expression profiles is an important and challenging task. The challenge lies in the complicated pathogenesis of cancers that often involve the dysfunction of many genes and regulatory interactions. Thus, sophisticated classification model is in pressing need. In this study, we proposed an efficient approach, called ellipsoidFN (ellipsoid Feature Net), to model the disease complexity by ellipsoids and seek a set of heterogeneous biomarkers. Our approach achieves a non-linear classification scheme for the mixed samples by the ellipsoid concept, and at the same time uses a linear programming framework to efficiently select biomarkers from high-dimensional space. ellipsoidFN reduces the redundancy and improves the complementariness between the identified biomarkers, thus significantly enhancing the distinctiveness between cancers and normal samples, and even between cancer types. Numerical evaluation on real prostate cancer, breast cancer and leukemia gene expression datasets suggested that ellipsoidFN outperforms the state-of-the-art biomarker identification methods, and it can serve as a useful tool for cancer biomarker identification in the future. The Matlab code of ellipsoidFN is freely available from http://doc.aporc.org/wiki/EllipsoidFN.

Novel SARS-like betacoronaviruses in bats, China, 2011.

To clarify the evolutionary relationships among betavoronaviruses that infect bats, we analyzed samples collected during 2010–2011 from 14 insectivorous bat species in China. We identified complete genomes of 2 novel betacoronaviruses in Rhinolophus pusillus and Chaerephon plicata bats, which showed close genetic relationships with severe acute respiratory syndrome coronaviruses.

Analysis of the Secretome and Identification of Novel Constituents from Culture Filtrate of Bacillus Calmette-Guérin Using High-resolution Mass Spectrometry

Tuberculosis (TB) is an infectious bacterial disease that causes morbidity and mortality, especially in developing countries. Although its efficacy against TB has displayed a high degree of variability (0%–80%) in different trials, Mycobacterium bovis bacillus Calmette-Guérin (BCG) has been recognized as an important weapon for preventing TB worldwide for over 80 years. Because secreted proteins often play vital roles in the interaction between bacteria and host cells, the secretome of mycobacteria is considered to be an attractive reservoir of potential candidate antigens for the development of novel vaccines and diagnostic reagents. In this study, we performed a proteomic analysis of BCG culture filtrate proteins using SDS-PAGE and high-resolution Fourier transform mass spectrometry. In total, 239 proteins (1555 unique peptides) were identified, including 185 secreted proteins or lipoproteins. Furthermore, 17 novel protein products not annotated in the BCG database were detected and validated by means of RT-PCR at the transcriptional level. Additionally, the translational start sites of 52 proteins were confirmed, and 22 proteins were validated through extension of the translational start sites based on N-terminus-derived peptides. There are 103 secreted proteins that have not been reported in previous studies on the mycobacterial secretome and are unique to our study. The physicochemical characteristics of the secreted proteins were determined. Major components from the culture supernatant, including low-molecular-weight antigens, lipoproteins, Pro-Glu and Pro-Pro-Glu family proteins, and Mce family proteins, are discussed; some components represent potential predominant antigens in the humoral and cellular immune responses.

Evaluating de Bruijn graph assemblers on 454 transcriptomic data.

Next generation sequencing (NGS) technologies have greatly changed the landscape of transcriptomic studies of non-model organisms. Since there is no reference genome available, de novo assembly methods play key roles in the analysis of these data sets. Because of the huge amount of data generated by NGS technologies for each run, many assemblers, e.g., ABySS, Velvet and Trinity, are developed based on a de Bruijn graph due to its time- and space-efficiency. However, most of these assemblers were developed initially for the Illumina/Solexa platform. The performance of these assemblers on 454 transcriptomic data is unknown. In this study, we evaluated and compared the relative performance of these de Bruijn graph based assemblers on both simulated and real 454 transcriptomic data. The results suggest that Trinity, the Illumina/Solexa-specialized transcriptomic assembler, performs the best among the multiple de Bruijn graph assemblers, comparable to or even outperforming the standard 454 assembler Newbler which is based on the overlap-layout-consensus algorithm. Our evaluation is expected to provide helpful guidance for researchers to choose assemblers when analyzing 454 transcriptomic data.

Full Genome of Influenza A (H7N9) Virus Derived by Direct Sequencing without Culture

An epidemic caused by influenza A (H7N9) virus was recently reported in China. Deep sequencing revealed the full genome of the virus obtained directly from a patient’s sputum without virus culture. The full genome showed substantial sequence heterogeneity and large differences compared with that from embryonated chicken eggs.