Chancellery Research - Research Publications
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ItemGenome sequence of the pathogenic intestinal spirochete brachyspira hyodysenteriae reveals adaptations to its lifestyle in the porcine large intestine.(Public Library of Science (PLoS), 2009)Brachyspira hyodysenteriae is an anaerobic intestinal spirochete that colonizes the large intestine of pigs and causes swine dysentery, a disease of significant economic importance. The genome sequence of B. hyodysenteriae strain WA1 was determined, making it the first representative of the genus Brachyspira to be sequenced, and the seventeenth spirochete genome to be reported. The genome consisted of a circular 3,000,694 base pair (bp) chromosome, and a 35,940 bp circular plasmid that has not previously been described. The spirochete had 2,122 protein-coding sequences. Of the predicted proteins, more had similarities to proteins of the enteric Escherichia coli and Clostridium species than they did to proteins of other spirochetes. Many of these genes were associated with transport and metabolism, and they may have been gradually acquired through horizontal gene transfer in the environment of the large intestine. A reconstruction of central metabolic pathways identified a complete set of coding sequences for glycolysis, gluconeogenesis, a non-oxidative pentose phosphate pathway, nucleotide metabolism, lipooligosaccharide biosynthesis, and a respiratory electron transport chain. A notable finding was the presence on the plasmid of the genes involved in rhamnose biosynthesis. Potential virulence genes included those for 15 proteases and six hemolysins. Other adaptations to an enteric lifestyle included the presence of large numbers of genes associated with chemotaxis and motility. B. hyodysenteriae has diverged from other spirochetes in the process of accommodating to its habitat in the porcine large intestine.
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ItemBoolean versus ranked querying for biomedical systematic reviews(BMC, 2010-10-12)BACKGROUND: The process of constructing a systematic review, a document that compiles the published evidence pertaining to a specified medical topic, is intensely time-consuming, often taking a team of researchers over a year, with the identification of relevant published research comprising a substantial portion of the effort. The standard paradigm for this information-seeking task is to use Boolean search; however, this leaves the user(s) the requirement of examining every returned result. Further, our experience is that effective Boolean queries for this specific task are extremely difficult to formulate and typically require multiple iterations of refinement before being finalized. METHODS: We explore the effectiveness of using ranked retrieval as compared to Boolean querying for the purpose of constructing a systematic review. We conduct a series of experiments involving ranked retrieval, using queries defined methodologically, in an effort to understand the practicalities of incorporating ranked retrieval into the systematic search task. RESULTS: Our results show that ranked retrieval by itself is not viable for this search task requiring high recall. However, we describe a refinement of the standard Boolean search process and show that ranking within a Boolean result set can improve the overall search performance by providing early indication of the quality of the results, thereby speeding up the iterative query-refinement process. CONCLUSIONS: Outcomes of experiments suggest that an interactive query-development process using a hybrid ranked and Boolean retrieval system has the potential for significant time-savings over the current search process in the systematic reviewing.
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ItemPrediction of breast cancer prognosis using gene set statistics provides signature stability and biological context(BMC, 2010-05-25)BACKGROUND: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little overlap, indicating that the results from any one study are unstable. It has been suggested that the underlying pathways are essentially identical, and that the expression of gene sets, rather than that of individual genes, may be more informative with respect to prognosis and understanding of the underlying biological process. RESULTS: We sought to examine the stability of prognostic signatures based on gene sets rather than individual genes. We classified breast cancer cases from five microarray studies according to the risk of metastasis, using features derived from predefined gene sets. The expression levels of genes in the sets are aggregated, using what we call a set statistic. The resulting prognostic gene sets were as predictive as the lists of individual genes, but displayed more consistent rankings via bootstrap replications within datasets, produced more stable classifiers across different datasets, and are potentially more interpretable in the biological context since they examine gene expression in the context of their neighbouring genes in the pathway. In addition, we performed this analysis in each breast cancer molecular subtype, based on ER/HER2 status. The prognostic gene sets found in each subtype were consistent with the biology based on previous analysis of individual genes. CONCLUSIONS: To date, most analyses of gene expression data have focused at the level of the individual genes. We show that a complementary approach of examining the data using predefined gene sets can reduce the noise and could provide increased insight into the underlying biological pathways.
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ItemGli1 Is an Inducing Factor in Generating Floor Plate Progenitor Cells from Human Embryonic Stem Cells(WILEY-BLACKWELL, 2010-10)Generation of mesencephalic dopamine (mesDA) neurons from human embryonic stem cells (hESCs) requires several stages of signaling from various extrinsic and intrinsic factors. To date, most methods incorporate exogenous treatment of Sonic hedgehog (SHH) to derive mesDA neurons. However, we and others have shown that this approach is inefficient for generating FOXA2+ cells, the precursors of mesDA neurons. As mesDA neurons are derived from the ventral floor plate (FP) regions of the embryonic neural tube, we sought to develop a system to derive FP cells from hESC. We show that forced expression of the transcription factor GLI1 in hESC at the earliest stage of neural induction, resulted in their commitment to FP lineage. The GLI1+ cells coexpressed FP markers, FOXA2 and Corin, and displayed exocrine SHH activity by ventrally patterning the surrounding neural progenitors. This system results in 63% FOXA2+ cells at the neural progenitor stage of hESC differentiation. The GLI1-transduced cells were also able to differentiate to neurons expressing tyrosine hydroxylase. This study demonstrates that GLI1 is a determinant of FP specification in hESC and describes a highly robust and efficient in vitro model system that mimics the ventral neural tube organizer.
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ItemBIOADI: a machine learning approach to identifying abbreviations and definitions in biological literature(BMC, 2009)BACKGROUND: To automatically process large quantities of biological literature for knowledge discovery and information curation, text mining tools are becoming essential. Abbreviation recognition is related to NER and can be considered as a pair recognition task of a terminology and its corresponding abbreviation from free text. The successful identification of abbreviation and its corresponding definition is not only a prerequisite to index terms of text databases to produce articles of related interests, but also a building block to improve existing gene mention tagging and gene normalization tools. RESULTS: Our approach to abbreviation recognition (AR) is based on machine-learning, which exploits a novel set of rich features to learn rules from training data. Tested on the AB3P corpus, our system demonstrated a F-score of 89.90% with 95.86% precision at 84.64% recall, higher than the result achieved by the existing best AR performance system. We also annotated a new corpus of 1200 PubMed abstracts which was derived from BioCreative II gene normalization corpus. On our annotated corpus, our system achieved a F-score of 86.20% with 93.52% precision at 79.95% recall, which also outperforms all tested systems. CONCLUSION: By applying our system to extract all short form-long form pairs from all available PubMed abstracts, we have constructed BIOADI. Mining BIOADI reveals many interesting trends of bio-medical research. Besides, we also provide an off-line AR software in the download section on http://bioagent.iis.sinica.edu.tw/BIOADI/.
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ItemNatural micropolymorphism in human leukocyte antigens provides a basis for genetic control of antigen recognition(ROCKEFELLER UNIV PRESS, 2009-01-16)Human leukocyte antigen (HLA) gene polymorphism plays a critical role in protective immunity, disease susceptibility, autoimmunity, and drug hypersensitivity, yet the basis of how HLA polymorphism influences T cell receptor (TCR) recognition is unclear. We examined how a natural micropolymorphism in HLA-B44, an important and large HLA allelic family, affected antigen recognition. T cell-mediated immunity to an Epstein-Barr virus determinant (EENLLDFVRF) is enhanced when HLA-B*4405 was the presenting allotype compared with HLA-B*4402 or HLA-B*4403, each of which differ by just one amino acid. The micropolymorphism in these HLA-B44 allotypes altered the mode of binding and dynamics of the bound viral epitope. The structure of the TCR-HLA-B*4405(EENLLDFVRF) complex revealed that peptide flexibility was a critical parameter in enabling preferential engagement with HLA-B*4405 in comparison to HLA-B*4402/03. Accordingly, major histocompatibility complex (MHC) polymorphism can alter the dynamics of the peptide-MHC landscape, resulting in fine-tuning of T cell responses between closely related allotypes.
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ItemA mosaic genetic screen for novel mutations affecting Drosophila neuroblast divisions(BIOMED CENTRAL LTD, 2006-06-02)BACKGROUND: The asymmetric segregation of determinants during cell division is a fundamental mechanism for generating cell fate diversity during development. In Drosophila, neural precursors (neuroblasts) divide in a stem cell-like manner generating a larger apical neuroblast and a smaller basal ganglion mother cell. The cell fate determinant Prospero and its adapter protein Miranda are asymmetrically localized to the basal cortex of the dividing neuroblast and segregated into the GMC upon cytokinesis. Previous screens to identify components of the asymmetric division machinery have concentrated on embryonic phenotypes. However, such screens are reaching saturation and are limited in that the maternal contribution of many genes can mask the effects of zygotic loss of function, and other approaches will be necessary to identify further genes involved in neuroblast asymmetric division. RESULTS: We have performed a genetic screen in the third instar larval brain using the basal localization of Miranda as a marker for neuroblast asymmetry. In addition to the examination of pupal lethal mutations, we have employed the MARCM (Mosaic Analysis with a Repressible Cell Marker) system to generate postembryonic clones of mutations with an early lethal phase. We have screened a total of 2,300 mutagenized chromosomes and isolated alleles affecting cell fate, the localization of basal determinants or the orientation of the mitotic spindle. We have also identified a number of complementation groups exhibiting defects in cell cycle progression and cytokinesis, including both novel genes and new alleles of known components of these processes. CONCLUSION: We have identified four mutations which affect the process of neuroblast asymmetric division. One of these, mapping to the imaginal discs arrested locus, suggests a novel role for the anaphase promoting complex/cyclosome (APC/C) in the targeting of determinants to the basal cortex. The identification and analysis of the remaining mutations will further advance our understanding of the process of asymmetric cell division. We have also isolated a number of mutations affecting cell division which will complement the functional genomics approaches to this process being employed by other laboratories. Taken together, these results demonstrate the value of mosaic screens in the identification of genes involved in neuroblast division.
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ItemDrosophila neuroblast asymmetric divisions:: cell cycle regulators, asymmetric protein localization, and tumorigenesis(ROCKEFELLER UNIV PRESS, 2008-01-28)Over the past decade, many of the key components of the genetic machinery that regulate the asymmetric division of Drosophila melanogaster neural progenitors, neuroblasts, have been identified and their functions elucidated. Studies over the past two years have shown that many of these identified components act to regulate the self-renewal versus differentiation decision and appear to function as tumor suppressors during larval nervous system development. In this paper, we highlight the growing number of molecules that are normally considered to be key regulators of cell cycle events/progression that have recently been shown to impinge on the neuroblast asymmetric division machinery to control asymmetric protein localization and/or the decision to self-renew or differentiate.
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ItemProtein Folding Database (PFD 2.0): an online environment for the International Foldeomics Consortium(OXFORD UNIV PRESS, 2007-01)The Protein Folding Database (PFD) is a publicly accessible repository of thermodynamic and kinetic protein folding data. Here we describe the first major revision of this work, featuring extensive restructuring that conforms to standards set out by the recently formed International Foldeomics Consortium. The database now adopts standards for data acquisition, analysis and reporting proposed by the consortium, which will facilitate the comparison of folding rates, energies and structure across diverse sets of proteins. Data can now be easily deposited using a rich set of deposition tools. Enhanced search tools allow sophisticated searching and graphical data analysis affords simple data analysis online. PFD can be accessed freely at http://www.foldeomics.org/pfd/.