Preecha Patumcharoenpol

Methodological Review: Biomedical text mining and its applications in cancer research

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research.

Draft Genome Sequence of the Pathogenic Oomycete Pythium insidiosum Strain Pi-S, Isolated from a Patient with Pythiosis.

ABSTRACT Pythium insidiosum is an oomycete that causes a life-threatening infectious disease called pythiosis in humans and animals living in tropical and subtropical countries. Here, we report the first draft genome sequence of P. insidiosum. The genome of P. insidiosum is 53.2 Mb and contains 14,962 open reading frames.

Suggested mechanisms for Zika virus causing microcephaly: what do the genomes tell us?

BackgroundZika virus (ZIKV) is an emerging human pathogen. Since its arrival in the Western hemisphere, from Africa via Asia, it has become a serious threat to pregnant women, causing microcephaly and other neuropathies in developing fetuses. The mechanisms behind these teratogenic effects are unknown, although epidemiological evidence suggests that microcephaly is not associated with the original, African lineage of ZIKV. The sequences of 196 published ZIKV genomes were used to assess whether recently proposed mechanistic explanations for microcephaly are supported by molecular level changes that may have increased its virulence since the virus left Africa. For this we performed phylogenetic, recombination, adaptive evolution and tetramer frequency analyses, and compared protein sequences for the presence of protease cleavage sites, Pfam domains, glycosylation sites, signal peptides, trans-membrane protein domains, and phosphorylation sites.ResultsRecombination events within or between Asian and Brazilian lineages were not observed, and likewise there were no differences in protease cleavage, glycosylation sites, signal peptides or trans-membrane domains between African and Brazilian strains. The frequency of Retinoic Acid Response Element (RARE) sequences was increased in Brazilian strains. Genetic adaptation was also apparent by tetramer signatures that had undergone major changes in the past but has stabilized in the Brazilian lineage despite subsequent geographic spread, suggesting the viral population presently propagates in the same host species in various regions. Evidence for selection pressure was recognized for several amino acid sites in the Brazilian lineage compared to the African lineage, mainly in nonstructural proteins, especially protein NS4B. A number of these positively selected mutations resulted in an increased potential to be phosphorylated in the Brazilian lineage compared to the African linage, which may have increased their potential to interfere with neural fetal development.ConclusionsZIKV seems to have adapted to a limited number of hosts, including humans, during which its virulence increased. Its protein NS4B, together with NS4A, has recently been shown to inhibit Akt-mTOR signaling in human fetal neural stem cells, a key pathway for brain development. We hypothesize that positive selection of novel phosphorylation sites in the protein NS4B of the Brazilian lineage could interfere with phosphorylation of Akt and mTOR, impairing Akt-mTOR signaling and this may result in an increased risk for developmental neuropathies.

dBBQs: dataBase of Bacterial Quality scores

BackgroundIt is well-known that genome sequencing technologies are becoming significantly cheaper and faster. As a result of this, the exponential growth in sequencing data in public databases allows us to explore ever growing large collections of genome sequences. However, it is less known that the majority of available sequenced genome sequences in public databases are not complete, drafts of varying qualities. We have calculated quality scores for around 100,000 bacterial genomes from all major genome repositories and put them in a fast and easy-to-use database.ResultsProkaryotic genomic data from all sources were collected and combined to make a non-redundant set of bacterial genomes. The genome quality score for each was calculated by four different measurements: assembly quality, number of rRNA and tRNA genes, and the occurrence of conserved functional domains. The dataBase of Bacterial Quality scores (dBBQs) was designed to store and retrieve quality scores. It offers fast searching and download features which the result can be used for further analysis. In addition, the search results are shown in interactive JavaScript chart framework using DC.js. The analysis of quality scores across major public genome databases find that around 68% of the genomes are of acceptable quality for many uses.ConclusionsdBBQs (available at http://arc-gem.uams.edu/dbbqs) provides genome quality scores for all available prokaryotic genome sequences with a user-friendly Web-interface. These scores can be used as cut-offs to get a high-quality set of genomes for testing bioinformatics tools or improving the analysis. Moreover, all data of the four measurements that were combined to make the quality score for each genome, which can potentially be used for further analysis. dBBQs will be updated regularly and is freely use for non-commercial purpose.

Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D

Abstract Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of second-generation sequencing. Saccharomyces cerevisiae strain CEN.PK113-7D, widely used as a model organism and a cell factory, was selected for this study to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as the mitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C and strain CEN.PK113-7D identified chromosomal rearrangements against a background of similar gene content between the two strains. We identified full-length transcripts through ONT direct RNA sequencing technology. This allows for the identification of transcriptional landscapes, including untranslated regions (UTRs) (5′ UTR and 3′ UTR) as well as differential gene expression quantification. About 91% of the predicted transcripts could be consistently detected across biological replicates grown either on glucose or ethanol. Direct RNA sequencing identified many polyadenylated non-coding RNAs, rRNAs, telomere-RNA, long non-coding RNA and antisense RNA. This work demonstrates a strategy to obtain complete genome sequences and transcriptional landscapes that can be applied to other eukaryal organisms.

Draft genome and sequence variant data of the oomycete Pythium insidiosum strain Pi45 from the phylogenetically-distinct Clade-III

Pythium insidiosum is a unique oomycete microorganism, capable of infecting humans and animals. The organism can be phylogenetically categorized into three distinct clades: Clade-I (strains from the Americas); Clade-II (strains from Asia and Australia), and Clade–III (strains from Thailand and the United States). Two draft genomes of the P. insidiosum Clade-I strain CDC-B5653 and Clade-II strain Pi-S are available in the public domain. The genome of P. insidiosum from the distinct Clade-III, which is distantly-related to the other two clades, is lacking. Here, we report the draft genome sequence of the P. insidiosum strain Pi45 (also known as MCC13; isolated from a Thai patient with pythiosis; accession numbers BCFM01000001-BCFM01017277) as a representative strain of the phylogenetically-distinct Clade-III. We also report a genome-scale data set of sequence variants (i.e., SNPs and INDELs) found in P. insidiosum (accessible online at the Mendeley database: http://dx.doi.org/10.17632/r75799jy6c.1).

Comparative mitochondrial genome analysis of Pythium insidiosum and related oomycete species provides new insights into genetic variation and phylogenetic relationships.

Oomycetes are eukaryotic microorganisms, which are phylogenetically distinct from the true-fungi, which they resemble morphologically. While many oomycetes are pathogenic to plants, Pythium insidiosum is capable of infecting humans and animals. Mitochondrial (mt) genomes are valuable genetic resources for exploring the evolution of eukaryotes. During the course of 454-based nuclear genome sequencing, we identified a complete 54.9 kb mt genome sequence, containing 2 large inverted repeats, from P. insidiosum. It contains 65 different genes (including 2 ribosomal RNA genes, 25 transfer RNA genes and 38 genes encoding NADH dehydrogenases, cytochrome b, cytochrome c oxidases, ATP synthases, and ribosomal proteins). Thirty-nine of the 65 genes have two copies, giving a total of 104 genes. A set of 30 conserved protein-coding genes from the mt genomes of P. insidiosum, 11 other oomycetes, and 2 diatoms (outgroup) were used for phylogenetic analyses. The oomycetes can be classified into 2 phylogenetic groups, in relation to their taxonomic lineages: Saprolegnialean and Peronosporalean. P. insidiosum is more closely related to Pythium ultimum than other oomycetes. In conclusion, the complete mt genome of P. insidiosum was successfully sequenced, assembled, and annotated, providing a useful genetic resource for exploring the biology and evolution of P. insidiosum and other oomycetes.

Probing the Phylogenomics and Putative Pathogenicity Genes of Pythium insidiosum by Oomycete Genome Analyses

Pythium insidiosum is a human-pathogenic oomycete. Many patients infected with it lose organs or die. Toward the goal of developing improved treatment options, we want to understand how Py. insidiosum has evolved to become a successful human pathogen. Our approach here involved the use of comparative genomic and other analyses to identify genes with possible functions in the pathogenicity of Py. insidiosum. We generated an Oomycete Gene Table and used it to explore the genome contents and phylogenomic relationships of Py. insidiosum and 19 other oomycetes. Initial sequence analyses showed that Py. insidiosum is closely related to Pythium species that are not pathogenic to humans. Our analyses also indicated that the organism harbours secreted and adhesin-like proteins, which are absent from related species. Putative virulence proteins were identified by comparison to a set of known virulence genes. Among them is the urease Ure1, which is absent from humans and thus a potential diagnostic and therapeutic target. We used mass spectrometric data to successfully validate the expression of 30% of 14,962 predicted proteins and identify 15 body temperature (37u2009°C)-dependent proteins of Py. insidiosum. This work begins to unravel the determinants of pathogenicity of Py. insidiosum.

Draft genome sequences of the oomycete Pythium insidiosum strain CBS 573.85 from a horse with pythiosis and strain CR02 from the environment

Pythium insidiosum is an aquatic oomycete microorganism that causes the fatal infectious disease, pythiosis, in humans and animals. The organism has been successfully isolated from the environment worldwide. Diagnosis and treatment of pythiosis is difficult and challenging. Genome sequences of P. insidiosum, isolated from humans, are available and accessible in public databases. To further facilitate biology-, pathogenicity-, and evolution-related genomic and genetic studies of P. insidiosum, we report two additional draft genome sequences of the P. insidiosum strain CBS 573.85 (35.6 Mb in size; accession number, BCFO00000000.1) isolated from a horse with pythiosis, and strain CR02 (37.7 Mb in size; accession number, BCFR00000000.1) isolated from the environment.

Strategies for pathway-based analysis of genome-wide SNP data

Numerous genome-wide association studies (GWAS) have been performed in order to determine the susceptible loci of diseases. However, most diseases still cannot be explained by a single locus. Pathway-based methods address this problem by combining those small effects into groups of related genes or pathways. However, because pathway-based approaches consist of multiple steps, there is much room for improvement. This paper presents an improved method for translating list of SNPs from GWAS into list of genes. We incrementally adjusted and compared different modifications applied to Parkinsons disease (PD) genome-wide SNP data and then used GSEA-P to analyze the resulting list of genes. After careful adjustments, we are able to identify more relevant pathways that were not found previously.