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We propose a useful system for remote sharing of transmission electron microscope (TEM) images by connecting three computers: a computer connected to a TEM, a computer distributing images and a computer receiving images. Then, we confirmed the performance of three web conferencing systems, Microsoft Teams, Zoom and Google Meet, to evaluate the usefulness of their remote use based on the clarity of images, smoothness of movement and time lag in images on each computer in the system. Display image of operation computer for TEM can be captured using the following two methods: a virtual camera of a video distribution software that provided a good reaction speed to transfer images and the screen sharing by conference system software that could share high-quality images.

Phytophagous insect larvae feed on plants containing secondary metabolic products with biological activity against other predatory organisms. Phytophagous insects can use their specialised metabolic systems to covert these secondary metabolic products into compounds with therapeutic properties useful to mankind. Some Asians drink tea decoctions made from phytophagous insect frass which is believed to be effective against inflammatory diseases. However, insects that can convert plant-derived secondary metabolic products into useful human therapeutic agents remain poorly studied. Here, we constructed the TUATinsecta database by integrating publicly plant/insect datasets for the purpose of selecting insect species. Using TUAT-insecta we selected the Asian swallowtail butterfly, Papilio xuthus larvae fed on several species of Rutaceous plants and examined whether the plant-derived secondary metabolites, especially those present in frass, were chemically altered or not. We extracted metabolic products from frass using three organic solvents with different polarities, and evaluated solvent fractions for their cytotoxic effects against several human cell lines. We found that chloroform frass extracts from P. xuthus larvae fed on Poncirus trifoliata leaves contained significant cytotoxic activity. Our findings demonstrate that screening of insect species using the ‘TUATinsecta’ database provides an important pipeline for discovering novel therapeutic agents that might be useful for mankind.

DNA barcoding and environmental DNA (eDNA) are increasing the need for the utilization of gene sequences in the field of biodiversity. GBIF (Global Biodiversity Information Facility) and GGBN (Global Genome Biodiversity Network) are taking action on the treatment of gene sequences in the field of biodiversity (Finstad et al. 2020). Gene sequences have been collected and published by INSDC (International Nucleotide Sequence Database Collaboration) for over 30 years (Arita et al. 2020). Biodiversity information has been collected using standards such as Darwin Core (Wieczorek et al. 2012), but INSDC gene sequences are stored in their own format. In the field of bioinformatics, researchers are also organizing the BioHackathon series, notably the NBDC/DBCLS BioHackathon and the spin-off Biohackathon Europe, to standardize data through the Semantic Web (Garcia Castro et al. 2021, Vos et al. 2020), but the linkage with biodiversity information has just begun. In this study, as an example of linking gene sequence information with biodiversity information, I attempted to construct an infrastructure for knowledge extraction by utilising gene sequence entries derived from museum specimens from GenBank (Sayers et al. 2020). I have previously surveyed the BOLD (The Barcode of Life Data System) (Ratnasingham and Hebert 2007) IDs listed in GenBank (Nakazato 2020). I downloaded the fish and insect data from the GenBank FTP (file transfer protocol) site. Then I extracted the descriptions in the "specimen_voucher" field and obtained 749,627 (28% of the fish entries in GenBank) and 1,621,890 (13%) specimen IDs, respectively. I also extracted from the "note" field approximately 1000 entries describing the type of the specimen, such as "holotype", "lectotype", and "paratype". These extracts include descriptions written in natural language. NCBI (National Center for Biotechnology Information) publishes the BioCollections database (Sharma et al. 2019), and these data may be able to refine the description. In the future, I plan to map these extracted IDs to the collection IDs in the biodiversity information database. This will enable us to enrich the biodiversity information with GenBank descriptions, for example, by adding articles listed in GenBank as references to the specimen data.

DNA barcoding technology has become employed widely for biodiversity and molecular biology researchers to identify species and analyze their phylogeny. Recently, DNA metabarcoding and environmental DNA (eDNA) technology have developed by expanding the concept of DNA barcoding. These techniques analyze the diversity and quantity of organisms within an environment by detecting biogenic DNA in water and soil. It is particularly popular for monitoring fish species living in rivers and lakes (Takahara et al. 2012). BOLD Systems (Barcode of Life Database systems, Ratnasingham and Hebert 2007) is a database for DNA barcoding, archiving 8.5 million of barcodes (as of August 2020) along with the voucher specimen, from which the DNA barcode sequence is derived, including taxonomy, collected country, and museum vouchered as metadata (e.g. https://www.boldsystems.org/index.php/Public_RecordView?processid=TRIBS054-16). Also, many barcoding data are submitted to GenBank (Sayers et al. 2020), which is a database for DNA sequences managed by NCBI (National Center for Biotechnology Information, US). The number of the records of DNA barcodes, i.e. COI (cytochrome c oxidase I) gene for animal, has grown significantly (Porter and Hajibabaei 2018). BOLD imports DNA barcoding data from GenBank, and lots of DNA barcoding data in GenBank are also assigned BOLD IDs. However, we have to refer to both BOLD and GenBank data when performing DNA barcoding. I have previously investigated the registration of DNA barcoding data in GenBank, especially the association with BOLD, using insects and flowering plants as examples (Nakazato 2019). Here, I surveyed the number of species covered by BOLD and GenBank. I used fish data as an example because eDNA research is particularly focused on fish. I downloaded all GenBank files for vertebrates from NCBI FTP (File Transfer Protocol) sites (as of November 2019). Of the GenBank fish entries, 86,958 (7.3%) were assigned BOLD identifiers (IDs). The NCBI taxonomy database has registrations for 39,127 species of fish, and 20,987 scientific names at the species level (i.e., excluding names that included sp., cf. or aff.). GenBank entries with BOLD IDs covered 11,784 species (30.1%) and 8,665 species-level names (41.3%). I also obtained whole "specimens and sequences combined data" for fish from BOLD systems (as of November 2019). In the BOLD, there are 273,426 entries that are registered as fish. Of these entries, 211,589 BOLD entries were assigned GenBank IDs, i.e. with values in “genbank_accession” column, and 121,748 entries were imported from GenBank, i.e. with "Mined from GenBank, NCBI" description in "institution_storing" column. The BOLD data covered 18,952 fish species and 15,063 species-level names, but 35,500 entries were assigned no species-level names and 22,123 entries were not even filled with family-level names. At the species level, 8,067 names co-occurred in GenBank and BOLD, with 6,997 BOLD-specific names and 599 GenBank-specific names. GenBank has 425,732 fish entries with voucher IDs, of which 340,386 were not assigned a BOLD ID. Of these 340,386 entries, 43,872 entries are registrations for COI genes, which could be candidates for DNA barcodes. These candidates include 4,201 species that are not included in BOLD, thus adding these data will enable us to identify 19,863 fish to the species level. For researchers, it would be very useful if both BOLD and GenBank DNA barcoding data could be searched in one place. For this purpose, it is necessary to integrate data from the two databases. A lot of biodiversity data are recorded based on the Darwin Core standard while DNA sequencing data are sometimes integrated or cross-linked by RDF (Resource Description Framework). It may not be technically difficult to integrate these data, but the species data referenced differ from the EoL (The Encyclopedia of Life) for BOLD and the NCBI taxonomy for GenBank, and the differences in taxonomic systems make it difficult to match by scientific name description. GenBank has fields for the latitude and longitude of the specimens sampled, and Porter and Hajibabaei 2018 argue that this information should be enhanced. However, this information may be better described in the specimen and occurrence databases. The integration of barcoding data with the specimen and occurrence data will solve these problems. Most importantly, it will save the researcher from having to register the same information in multiple databases. In the field of biodiversity, only DNA barcode sequences may have been focused on and used as gene sequences. The museomics community regards museum-preserved specimens as rich resources for DNA studies because their biodiversity information can accompany the extraction and analysis of their DNA (Nakazato 2018). GenBank is useful for biodiversity studies due to its low rate of mislabelling (Leray et al. 2019). In the future, we will be working with a variety of DNA, including genomes from museum specimens as well as DNA barcoding. This will require more integrated use of biodiversity information and DNA sequence data. This integration is also of interest to molecular biologists and bioinformaticians.

Human intestinal absorption is estimated using a human colon carcinoma cell line (Caco-2) cells from human colorectal adenocarcinoma, intestinal perfusion, or a mammalian model. These current evaluation systems are limited in their ability to estimate human intestinal absorption. In addition, in vivo evaluation systems using laboratory animals such as mice and rats entail animal ethics problems, and it is difficult to screen compounds on a large scale at the drug discovery stage. Thus, we propose the use of Bombyx mori larvae for evaluation of intestinal absorption of compounds as an alternative system in this study. First, to compare the characteristics among Caco-2 cells, human intestine, and B. mori larval midgut, we analyzed their RNA-seq data, and we found 26 drug transporters common to humans and B. mori. Next, we quantitatively developed an oral administration technique in B. mori and established a method using silkworm B. mori larvae that can easily estimate the intestinal permeability of compounds. Consequently, we could determine the dose and technique for oral administration in B. mori larvae. We also developed a B. mori model to evaluate the intestinal permeability of orally administered. Our constructed evaluation system will be useful for evaluating intestinal permeability in medical drug development.

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

BackgroundPolyembryony is defined as the formation of several embryos from a single egg. This phenomenon can occur in humans, armadillo, and some endoparasitoid insects. However, the mechanism underlying polyembryogenesis in animals remains to be elucidated. The polyembryonic parasitoid waspCopidosoma floridanumoviposits its egg into an egg of the host insect; eventually, over 2000 individuals will arise from one egg. Previously, we reported that polyembryogenesis is enhanced when the juvenile hormone (JH) added to the culture medium in the embryo culture. Hence, in the present study, we performed RNA sequencing (RNA-Seq) analysis to investigate the molecular mechanisms controlling polyembryogenesis ofC. floridanum. Functional annotation of genes is not fully available forC.floridanum; however, whole genome assembly has been archived. Hence, we constructed a pipeline for gene functional annotation inC. floridanumand performed molecular network analysis. We analyzed differentially expressed genes between control and JH-treated molura after 48 h of culture, then used the tblastx program to assign wholeC. floridanumtranscripts to human gene.ResultsWe obtained 11,117 transcripts in the JH treatment group and identified 217 differentially expressed genes compared with the control group. As a result, 76% ofC. floridanumtranscripts were assigned to human genes. Gene enrichment analysis revealed genes associated with platelet degranulation, fatty acid biosynthesis, cell morphogenesis in the differentiation and integrin signaling pathways were fluctuated following JH treatment. Furthermore, Cytoscape analysis revealed a molecular interaction that was possibly associated with polyembryogenesis .ConclusionsWe have constructed a pipeline for gene functional annotation ofC. floridanum, and identified transcripts with high similarity to human genes during early embryo developmental. Additionally, this study reveals new molecular interactions associated with polyembryogenesis; these interactions could indicate the molecular mechanisms underlying polyembryony. Our results highlight the potential utility of molecular interaction analysis in human twins.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The museomics activity regards museum-preserved specimens as rich resources for DNA studies by extracting and analyzing DNA from these specimens in conjunction with their biodiversity information. Also in biodiversity field, DNA sequence data such as DNA barcoding has become essential as evidence for species identification and phylogenetic analysis as well as occurrence and morphological information. To accelerate biodiversity informatics, it is important to utilize both biodiversity occurrence and morphology data, and bioinformatics sequencing data. There are many databases for biodiversity domain such as GBIF (The Global Biodiversity Information Facility) for species occurrence records, EoL (The Encyclopedia of Life) as a knowledge base of all species, and BOLD (The Barcode of Life Data) for DNA barcoding data. In genomics science, molecular data involving DNA and protein sequences have been captured by the DNA Data Bank in Japan (DDBJ), the European Bioinformatics Institute (EBI, UK), and the National Center for Biotechnology Information (NCBI, US) under the International Nucleotide Sequence Database Collaboration (INSDC) for more than 30 years. Recently, NCBI launched a new database called BioCollections, including 7,930 culture collections, museums, herbaria, and other natural history collections. In addition, we can submit biodiversity information such as specimen voucher IDs, BOLD IDs, and latitude/longitude with DNA sequences. To find out the current situation, I downloaded GenBank (Nucleotide) files (updated at 22 Feb 2019) from the NCBI FTP (file transfer protocol) site and extracted biodiversity features including specimen voucher IDs and BOLD IDs. For Insecta, there are 2,427,343 sequence entries with specimen voucher ID and 1,766,142 entries with BOLD ID of 3,389,495 total entries. The most abundant species with voucher IDs is “Cecidomyiidae sp. BOLD−2016” (Diptera) (35,861 sequence entries). The most frequently referred voucher ID is “USNMENT00921257” (1510 sequence entries), indicating Stenamma megamanni (Hymenoptera, Formicidae, Myrmicinae). For flowering plants (Magnoliophyta), of 3,094,140 total entries, 1,109,420 sequence entries are assigned with voucher IDs and 73,409 entries with BOLD IDs. Additionally, 79,891 matK entries and 63,821 rbcL entries are submitted with voucher IDs, without BOLD IDs. I also retrieved BOLD data for Insecta and flowering plants. The 2,368,801 GenBank entries are referred from 4,176,481 BOLD total entries for Insecta, and the 259,245 GenBank entries from 345,706 BOLD entries for flowering plants. Some DNA barcoding data exist redundantly in BOLD database because BOLD imports sequences from NCBI submitted as DNA barcoding data in BOLD. These entries have different BOLD IDs but same BIN_URL is assigned. Recently, high-throughput sequencing technology, also called next-generation sequencing technology (NGS), has made a great impact in genomic science. Biodiversity researchers became to perform not only DNA barcoding but also RNA-Seq with NGS. NGS also accelerates museomics activity. NGS data are archived to the Sequence Read Archive (SRA) database, and sample information is described in BioSample database in INSDC. To utilize NGS data for biodiversity field, we will need to integrate such databases and other biodiversity databases. We, Database Center for Life Science, tackle to integrate life science data with Semantic Web technology. We held annual meetings to integrate life science data, called BioHackathons, in which researchers from all over the world participated. We began to RDFize BioSample data, but we should import existing schemes used in the biodiversity field including Darwin Core.

Insects are well adapted to changing environmental conditions. They have unique systems for eliminating reactive oxygen species (ROS). Superoxide dismutase (SOD) is a key enzyme that plays a primary role in removing ROS. Bombyx mori is a lepidopteran insect, whose body size is larger than the model insect Drosophila melanogaster, which enabled us to more easily examine gene expression at the tissue level. We searched B. mori SOD (BmSOD) genes using genome database, and we analyzed their function under different type of oxidative stress. Consequently, we identified four new types of BmSODs in addition to the three types already known. Two of the seven types had a unique domain architecture that has not been discovered previously in the SOD family, and they were expressed in different tissues and developmental stages. Furthermore, these BmSODs responded differently to several kinds of stressors. Our results showed that the seven types of BmSODs are likely to play different roles in B. mori; therefore, B. mori could be used to distinguish the functions of each SOD for resistance to oxidative stress that changes with the environmental conditions.

Museum-preserved samples are attracting attention as a rich resource for DNA studies. Museomics aims to link DNA sequence data back to the museum collection. Molecular biologists are interested in morphological information including body size, pattern, and colors, and sequence data have also become essential for biodiversity research as evidence for species identification and phylogenetic analysis. For more than 30 years, molecular data, such as DNA and protein sequences, have been captured by the DNA Data Bank of Japan (DDBJ), the European Bioinformatics Institute (EBI, UK), and the National Center for Biotechnology Information (NCBI, US) under the International Nucleotide Sequence Database Collaboration (INSDC). INSDC provides collected molecular data to researchers as public databases including GenBank for DNA sequences and Gene Expression Omnibus (GEO) for gene expression. These three institutes synchronize archived data and publish all data on an FTP (File Transfer Protocol) site so that it is available for big data analysis. In recent years, high-throughput sequencing technology, also called next-generation sequencing (NGS) technology, has been widely utilized for molecular biology including genomics, transcriptomics, and metagenomics. Biodiversity researchers also focus on NGS data for DNA barcoding and phylogenetic analysis as well as molecular biology. Additionally, a portable NGS platform, MinION (Oxford Nanopore Technologies), has been launched, enabling biodiversity researchers to perform DNA sequencing in the field. Along with GenBank and GEO data, INSDC accepts NGS data and provides a public primary database, called the Sequence Read Archive (SRA). As of March 2018, 6.4 Peta Bases of NGS data is freely available under more than 130,000 projects in SRA. The Database Center for Life Science (DBCLS) provides a search engine for public NGS data, called DBCLS SRA (http://sra.dbcls.jp/) in collaboration with DDBJ. SRA contains not only raw sequence reads or processed data mapped to genome, but also information on the experimental design, including project types, sequencing platforms, and sample species. Researchers can use this data to refine their search results. We also linked publications referring to NGS data to the corresponding SRA entries. The mission of DBCLS is to accelerate the accessibility of life science data. Collected data used to be described in the Excel-readable tabular format, but these formats are difficult to merge with other databases because of the ambiguity of labels. To overcome this difficulty, we recently integrated life science data with Semantic Web technology. We held annual meetings to integrate life science data, called BioHackathons, in which researchers from all over the world participated. UniProt and Ensembl databases currently provide an RDF (Resource Description Framework) version of curated genome and protein data, respectively. In the biodiversity domain, there are many databases such as GBIF (The Global Biodiversity Information Facility) for species occurrence records, EoL (The Encyclopedia of Life) as a knowledge base of all species, and BoL (The Barcode of Life) for DNA barcoding data. RDF is utilized to describe Darwin Core based data so that bioinformatics and biodiversity informatics researchers can technically merge both types of data. Currently, specimen data and DNA sequence data are not linked. Museomics starts with cross-referencing specimen and sequence IDs and by making data sources comply with an existing standard.

Human intestinal absorption is estimated using a human colon carcinoma cell line (Caco-2) cells from human colorectal adenocarcinoma, intestinal perfusion, or a mammalian model. These current evaluation systems are limited in their ability to estimate human intestinal absorption. In addition, in vivo evaluation systems using laboratory animals such as mice and rats entail animal ethics problems, and it is difficult to screen compounds on a large scale at the drug discovery stage. Thus, we propose the use of Bombyx mori larvae for evaluation of intestinal absorption of compounds as an alternative system in this study. First, to compare the characteristics among Caco-2 cells, human intestine, and B. mori larval midgut, we analyzed their RNA-seq data, and we found 26 drug transporters common to humans and B. mori. Next, we quantitatively developed an oral administration technique in B. mori and established a method using silkworm B. mori larvae that can easily estimate the intestinal permeability of compounds. Consequently, we could determine the dose and technique for oral administration in B. mori larvae. We also developed a B. mori model to evaluate the intestinal permeability of orally administered. Our constructed evaluation system will be useful for evaluating intestinal permeability in medical drug development.

Although host-plant selection is a central topic in ecology, its general underpinnings are poorly understood. Here, we performed a case study focusing on the publicly available data on Japanese butterflies. A combined statistical analysis of plant–herbivore relationships and taxonomy revealed that some butterfly subfamilies in different families feed on the same plant families, and the occurrence of this phenomenon more than just by chance, thus indicating the independent acquisition of adaptive phenotypes to the same hosts. We consequently integrated plant–herbivore and plant–compound relationship data and conducted a statistical analysis to identify compounds unique to host plants of specific butterfly families. Some of the identified plant compounds are known to attract certain butterfly groups while repelling others. The additional incorporation of insect–compound relationship data revealed potential metabolic processes that are related to host plant selection. Our results demonstrate that data integration enables the computational detection of compounds putatively involved in particular interspecies interactions and that further data enrichment and integration of genomic and transcriptomic data facilitates the unveiling of the molecular mechanisms involved in host plant selection.

Publishing databases in the Resource Description Framework (RDF) model is becoming widely accepted to maximize the syntactic and semantic interoperability of open data in life sciences. Here we report advancements made in the 6th and 7th annual BioHackathons which were held in Tokyo and Miyagi respectively. This review consists of two major sections covering: 1) improvement and utilization of RDF data in various domains of the life sciences and 2) meta-data about these RDF data, the resources that store them, and the service quality of SPARQL Protocol and RDF Query Language (SPARQL) endpoints. The first section describes how we developed RDF data, ontologies and tools in genomics, proteomics, metabolomics, glycomics and by literature text mining. The second section describes how we defined descriptions of datasets, the provenance of data, and quality assessment of services and service discovery. By enhancing the harmonization of these two layers of machine-readable data and knowledge, we improve the way community wide resources are developed and published. Moreover, we outline best practices for the future, and prepare ourselves for an exciting and unanticipatable variety of real world applications in coming years.

It is important for public data repositories to promote the reuse of archived data. In the growing field of omics science, however, the increasing number of submissions of high-throughput sequencing (HTSeq) data to public repositories prevents users from choosing a suitable data set from among the large number of search results. Repository users need to be able to set a threshold to reduce the number of results to obtain a suitable subset of high-quality data for reanalysis. We calculated the quality of sequencing data archived in a public data repository, the Sequence Read Archive (SRA), by using the quality control software FastQC. We obtained quality values for 1 171 313 experiments, which can be used to evaluate the suitability of data for reuse. We also visualized the data distribution in SRA by integrating the quality information and metadata of experiments and samples. We provide quality information of all of the archived sequencing data, which enable users to obtain sufficient quality sequencing data for reanalyses. The calculated quality data are available to the public in various formats. Our data also provide an example of enhancing the reuse of public data by adding metadata to published research data by a third party.

Background Various insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases. Results Enolase is an important glycolytic enzyme in all organisms. We used a combination of dry and wet bench processes to identify functional enolases in the silkworm Bombyx mori (BmEno). First, we detected five annotated enolases from public databases using a Hidden Markov Model (HMM) search, and then through cDNA cloning, Northern blotting, and RNA-seq analysis, we revealed three functional enolases in B. mori: BmEno1, BmEno2, and BmEnoC. BmEno1 contained a conserved key amino acid residue for metal binding and substrate binding in other species. However, BmEno2 and BmEnoC showed a change in this key amino acid. Phylogenetic analysis showed that BmEno2 and BmEnoC were distinct from BmEno1 and other enolases, and were distributed only in lepidopteran clusters. BmEno1 was expressed in all of the tissues used in our study. In contrast, BmEno2 was mainly expressed in the testis with some expression in the ovary and suboesophageal ganglion. BmEnoC was weakly expressed in the testis. Quantitative RT-PCR showed that the mRNA expression of BmEno2 and BmEnoC correlated with testis development; thus, BmEno2 and BmEnoC may be related to lepidopteran-specific spermiogenesis. Conclusions We identified and characterized three functional enolases from public databases with a combination of dry and wet bench processes in the silkworm B. mori. In addition, we determined that BmEno2 and BmEnoC had species-specific functions. Our strategy could be helpful for the detection of minor genes and functional genes in non-model organisms from public databases. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3455-y) contains supplementary material, which is available to authorized users.

Background In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons. Results In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr. Conclusions Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0453-z) contains supplementary material, which is available to authorized users.

One way that aerobic biological systems counteract the generation of reactive oxygen species (ROS) is with superoxide dismutase proteins SOD1 and SOD2 that metabolize superoxide radicals to molecular oxygen and hydrogen peroxide or scavenge oxygen radicals produced by the extensive oxidation-reduction and electron-transport reactions that occur in mitochondria. We characterized SOD1 and SOD2 of Bombyx mori isolated from the fat body of larvae. Immunological analysis demonstrated the presence of BmSOD1 and BmSOD2 in the silk gland, midgut, fat body, Malpighian tubules, testis and ovary from larvae to adults. We found that BmSOD2 had a unique expression pattern in the fat body through the fifth instar larval developmental stage. The anti-oxidative functions of BmSOD1 and BmSOD2 were assessed by exposing larvae to insecticide rotenone or vasodilator isosorbide dinitrate, which is an ROS generator in BmN4 cells; however, exposure to these compounds had no effect on the expression levels of either BmSOD protein. Next, we investigated the physiological role of BmSOD1 and BmSOD2 under environmental oxidative stress, applied through whole-body UV irradiation and assayed using quantitative RT-PCR, immunoblotting and microarray analysis. The mRNA expression level of both BmSOD1 and BmSOD2 was markedly increased but protein expression level was increased only slightly. To examine the differences in mRNA and protein level due to UV irradiation intensity, we performed microarray analysis. Gene set enrichment analysis revealed that genes in the insulin signaling pathway and PPAR signaling pathway were significantly up-regulated after 6 and 12 hours of UV irradiation. Taken together, the activities of BmSOD1 and BmSOD2 may be related to the response to UV irradiation stress in B. mori. These results suggest that BmSOD1 and BmSOD2 modulate environmental oxidative stress in the cell and have a specific role in fat body of B. mori during pupation.

One of the major aims of molecular biology and medical science is to understand disease mechanisms. A genetic disorder is a disease caused by abnormalities in genes and chromosomes, and researchers often report the identification of disease-relevant genes and correlations between phenotypes and genotypes (Butte & Kohane 2006; Lamb 2007; PerezIratxeta et al. 2002, 2005, 2007). Omics analysis using microarray, new generation sequencing (NGS) technology, and mass spectrometry is widely employed for determining genome sequences and profiling gene expression. Changes in gene expression on a genome-wide scale can be detected by omics analysis, which provides various types of huge datasets. These data are often archived in public databases; nucleotide sequences in the DDBJ/EMBL/GenBank International Nucleotide Sequence Database (INSD) (Cochrane et al. 2011), gene expression in Gene Expression Omnibus (GEO) (Barrett et al. 2011), and journal articles in MEDLINE. Currently, research cannot continue without the use of these databases. In Japan, the Database Center for Life Science (DBCLS) has developed infrastructure for researchers to access and easily reuse these data by providing index sites such as INSD and GEO yellow pages and by constructing a portal site for life science databases and tools. Researchers can easily analyze public data in conjunction with their own omics data. Here we present an analytical method to clarify the associations between genes and diseases. We characterized genes and diseases by assigning a MeSH-controlled vocabulary (Nakazato et al. 2008, 2009). Our objective was to help interpret omics data from molecular and clinical aspects by comparing these feature profiles.

Sulfate (SO42−) is the second most abundant anion in seawater (SW), and excretion of excess SO42−from ingested SW is essential for marine fish to survive. Marine teleosts excrete SO42−via the urine produced in the kidney. The SO42−transporter that secretes and concentrates SO42−in the urine has not previously been identified. Here, we have identified and characterized candidates for the long-sought transporters. Using sequences from the fugu database, we have cloned cDNA fragments of all transporters belonging to the Slc13 and Slc26 families from mefugu ( Takifugu obscurus ). We compared Slc13 and Slc26 mRNA expression in the kidney between freshwater (FW) and SW mefugu. Among 14 clones examined, the expression of a Slc26a6 paralog (mfSlc26a6A) was the most upregulated (30-fold) in the kidney of SW mefugu. Electrophysiological analyses of Xenopus oocytes expressing mfSlc26a6A, mfSlc26a6B, and mouse Slc26a6 (mSlc26a6) demonstrated that all transporters mediate electrogenic Cl−/SO42−, Cl−/oxalate2−, and Cl−/ nHCO3−exchanges and electroneutral Cl−/formate−exchange. Two-electrode voltage-clamp experiments demonstrated that the SO42−-elicited currents of mfSlc26a6A is quite large (∼35 μA at +60 mV) and 50- to 200-fold higher than those of mfSlc26a6B and mSlc26a6. Conversely, the currents elicited by oxalate and HCO3−are almost identical among mfSlc26a6A, mfSlc26a6B, and mSlc26a6. Kinetic analysis revealed that mfSlc26a6A has the highest SO42−affinity as well as capacity. Immunohistochemical analyses demonstrated that mfSlc26a6A localizes to the apical (brush-border) region of the proximal tubules. Together, these findings suggest that mfSlc26a6A is the most likely candidate for the major apical SO42−transporter that mediates SO42−secretion in the kidney of marine teleosts.

Genome-wide data enables us to clarify the underlying molecular mechanisms of complex phenotypes. The Online Mendelian Inheritance in Man (OMIM) is a widely employed knowledge base of human genes and genetic disorders for biological researchers. However, OMIM has not been fully exploited for omics analysis because its bibliographic data structure is not suitable for computer automation. Here, we characterized diseases and genes by generating feature profiles of associated drugs, biological phenomena and anatomy with the MeSH (Medical Subject Headings) vocabulary. We obtained 1 760 054 pairs of OMIM entries and MeSH terms by utilizing the full set of MEDLINE articles. We developed a web-based application called Gendoo (gene, disease features ontology-based overview system) to visualize these profiles. By comparing feature profiles of types 1 and 2 diabetes, we clearly illustrated their differences: type 1 diabetes is an autoimmune disease (P-value = 4.55 x 10(-5)) and type 2 diabetes is related to obesity (P-value = 1.18 x 10(-15)). Gendoo and the developed feature profiles should be useful for omics analysis from molecular and clinical viewpoints. Gendoo is available at http://gendoo.dbcls.jp/.

Microarray technology has become employed widely for biological researchers to identify genes associated with conditions such as diseases and drugs. To date, many methods have been developed to analyze data covering a large number of genes, but they focus only on statistical significance and cannot decipher the data with biological concepts. Gene Ontology (GO) is utilized to understand the data with biological interpretation; however, it is restricted to specific ontology such as biological process, molecular function, and cellular component. Here, we attempted to apply MeSH (Medical Subject Headings) to interpret groups of genes from biological viewpoint. To assign MeSH terms to genes, in this study, contexts associated with genes are retrieved from full set of MEDLINE data using machine learning, and then extracted MeSH terms from retrieved articles. Utilizing the developed method, we implemented a software called BioCompass. It generates high-scoring lists and hierarchical lists for diseases MeSH terms associated with groups of genes to utilize MeSH and GO tree, and illustrated a wiring diagram by linking genes with extracted association from articles. Researchers can easily retrieve genes and keywords of interest, such as diseases and drugs, associated with groups of genes. Using retrieved MeSH terms and OMIM in conjunction with, we could obtain more disease information associated with target gene. BioCompass helps researchers to interpret groups of genes such as microarray data from a biological viewpoint.

Despite unfavorable conditions, a single species of fish, Osorezan dace, lives in an extremely acidic lake (pH 3.5) in Osorezan, Aomori, Japan. Physiological studies have established that this fish is able to prevent acidification of its plasma and loss of Na+. Here we show that these abilities are mainly attributable to the chloride cells of the gill, which are arranged in a follicular structure and contain high concentrations of Na+-K+-ATPase, carbonic anhydrase II, type 3 Na+/H+exchanger (NHE3), type 1 Na+-HCO[Formula: see text] cotransporter, and aquaporin-3, all of which are upregulated on acidification. Immunohistochemistry established their chloride cell localization, with NHE3 at the apical surface and the others localized to the basolateral membrane. These results suggest a mechanism by which Osorezan dace adapts to its acidic environment. Most likely, NHE3 on the apical side excretes H+in exchange for Na+, whereas the electrogenic type 1 Na+-HCO[Formula: see text]cotransporter in the basolateral membrane provides HCO[Formula: see text] for neutralization of plasma using the driving force generated by Na+-K+-ATPase and carbonic anhydrase II. Increased expression of glutamate dehydrogenase was also observed in various tissues of acid-adapted dace, suggesting a significant role of ammonia and bicarbonate generated by glutamine catabolism.