Web-accessible Database Research Articles

DSCI: a database of synthetic biology components for innate immunity and cell engineering decision-making processes

Although significant progress of clinical strategy has been made in gene editing and cell engineering in immunotherapy, it is now apparent that design and modification in terms of complex signaling pathways and motifs on medical synthetic biology are still full of challenges. Innate immunity, the first line of host defense against pathogens, is critical for anti-pathogens immune response as well as regulating durable and protective T cell-mediated anti-tumor responses. Here, we introduce DSCI (Database of Synthetic Biology Components for Innate Immunity, https://dsci.renlab.cn/), a web-accessible and integrative database that provides better insights and strategies for innate immune signaling circuit design in biosynthesis. Users can interactively navigate comprehensive and carefully curated components resources that presented as visualized signaling motifs that participate in innate immunity. The current release of DSCI incorporates 1240 independent components and more than 4000 specific entries contextually annotated from public literature with experimental verification. The data integrated into DSCI includes the components of pathways, relationships between regulators, signal motifs based on regulatory cascades, and loop graphs, all of which have been comprehensively annotated to help guide modifications to gene circuits. With the support of DSCI, users can easily obtain guidance of gene circuits construction to make decision of cell engineering based on innate immunity. DSCI not only provides comprehensive and specialized resource on the biological components of innate immune synthesis, but also serves as a useful tool to offer modification or generation strategies for medical synthetic biology.

Bioinformatics Methods for Constructing Metabolic Networks

Metabolic pathway prediction and reconstruction play crucial roles in solving fundamental and applied biomedical problems. In the case of fundamental research, annotation of metabolic pathways allows one to study human health in normal, stressed, and diseased conditions. In applied research, it allows one to identify novel drugs and drug targets and to design mimetics (biomolecules with tailored properties), as well as contributes to the development of such disciplines as toxicology and nutrigenomics. It is important to understand the role of a metabolite as a substrate (the product or intermediate participant of an enzymatic reaction) in cellular signaling and phenotype implementation according to the pivotal paradigm of biology: “one gene–one protein–one function (one trait)”. Due to the development of omics technologies, a vast body of data on the metabolome composition of living organisms has been accumulated over the past two decades. Systematization of the information on the roles played by metabolites in implementation of cellular signaling, as well as metabolic pathway reconstruction and refinement, have necessitated the development of bioinformatic tools for performing large-scale omics data mining. This paper reviews web-accessible databases relevant to metabolic pathways and considers the applications of the three types of bioinformatics methods for constructing metabolic networks (graphs for substrate–enzyme–product transformation; stoichiometric analysis of substrate–product transformation; and product retrosynthesis). It describes, step by step, a generalized algorithm for constructing biological pathway maps which explains to the researcher the workflow implemented in available bioinformatics tools and can be used to create new tools in projects requiring pathway reconstruction.

Trends in Dietary Micronutrient Adequacy in Young Adults Over the Latest 25 Years in Japan.

It has been assumed that economically developed countries are well nourished compared to developing countries, but little is known about how economic status affects dietary micronutrient intake in the future childbearing generation. We analyzed the trend of dietary micronutrient adequacy in young adults in Japan, as one of the representative countries with advanced dietary habits and economic progress. We conducted a retrospective analysis using 2 web-accessible databases, namely the Japanese National Health and Nutrition Survey and the World Development Indicators. Japan has been facing a progressive insufficiency of dietary vitamins A and C and iron, especially among young adults, over the past 25 years. The hidden progression of silent malnutrition has become more apparent since the 2010s, coinciding with a series of economic recessions and natural disasters. Given that parental dietary habits play a critical role in ensuring a balanced diet for their children, our findings underscore the importance of proactive nutrition counseling and education, especially for young adults of childbearing age who have been identified as vulnerable to micronutrient deficiencies. In line with this policy, we would like to suggest the use of digital transformation platforms as a potential solution in the future, especially for the digital native population.

CfOmics: a cell-free multi-Omics database for diseases.

Liquid biopsy has emerged as a promising non-invasive approach for detecting, monitoring diseases, and predicting their recurrence. However, the effective utilization of liquid biopsy data to identify reliable biomarkers for various cancers and other diseases requires further exploration. Here, we present cfOmics, a web-accessible database (https://cfomics.ncRNAlab.org/) that integrates comprehensive multi-omics liquid biopsy data, including cfDNA, cfRNA based on next-generation sequencing, and proteome, metabolome based on mass-spectrometry data. As the first multi-omics database in the field, cfOmics encompasses a total of 17 distinct data types and 13 specimen variations across 69 disease conditions, with a collection of 11345 samples. Moreover, cfOmics includes reported potential biomarkers for reference. To facilitate effective analysis and visualization of multi-omics data, cfOmics offers powerful functionalities to its users. These functionalities include browsing, profile visualization, the Integrative Genomic Viewer, and correlation analysis, all centered around genes, microbes, or end-motifs. The primary objective of cfOmics is to assist researchers in the field of liquid biopsy by providing comprehensive multi-omics data. This enables them to explore cell-free data and extract profound insights that can significantly impact disease diagnosis, treatment monitoring, and management.

Acropora CervicornisData Coordination Hub, an Open Access Database for Evaluating Genet Performance

Once one of the predominant reef-building corals in the region,Acropora cervicornisis now a focal species of coral restoration efforts in Florida and the western Caribbean. Scientists and restoration practitioners have been independently collecting phenotypic data on genets ofA. cervicornisgrown in restoration nurseries. While these data are important for understanding the intraspecific response to varying environmental conditions, and thus the potential genetic contribution to phenotypic variation, in isolation these observations are of limited use for large-scale, multi- institution restoration efforts that are becoming increasingly necessary. Here, we present theAcropora cervicornisData Coordination Hub, a web-accessible relational database to align disparate datasets to compare genet-specific performance. In this data descriptor, we release data for 248 genets evaluated across 38 separate traits. We present a framework to align datasets with the ultimate goal of facilitating informed, data-driven restoration throughout the Caribbean.

BarleyExpDB: an integrative gene expression database for barley

BackgroundRNA-sequencing (RNA-seq) has been widely used to study the dynamic expression patterns of transcribed genes, which can lead to new biological insights. However, processing and analyzing these huge amounts of histological data remains a great challenge for wet labs and field researchers who lack bioinformatics experience and computational resources.ResultsWe present BarleyExpDB, an easy-to-operate, free, and web-accessible database that integrates transcriptional profiles of barley at different growth and developmental stages, tissues, and stress conditions, as well as differential expression of mutants and populations to build a platform for barley expression and visualization. The expression of a gene of interest can be easily queried by searching by known gene ID or sequence similarity. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Proteins Families Database, and Simple Modular Architecture Research Tool annotations.ConclusionsBarleyExpDB will serve as a valuable resource for the barley research community to leverage the vast publicly available RNA-seq datasets for functional genomics research and crop molecular breeding.

CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides.

Recently, cyclic peptides have been considered breakthrough drugs because they can interact with "undruggable" targets such as intracellular protein-protein interactions. Membrane permeability is an essential indicator of oral bioavailability and intracellular targeting, and the development of membrane-permeable peptides is a bottleneck in cyclic peptide drug discovery. Although many experimental data on membrane permeability of cyclic peptides have been reported, a comprehensive database is not yet available. A comprehensive membrane permeability database is essential for developing computational methods for cyclic peptide drug design. In this study, we constructed CycPeptMPDB, the first web-accessible database of cyclic peptide membrane permeability. We collected information on a total of 7334 cyclic peptides, including the structure and experimentally measured membrane permeability, from 45 published papers and 2 patents from pharmaceutical companies. To unambiguously represent cyclic peptides larger than small molecules, we used the hierarchical editing language for macromolecules notation to generate a uniform sequence representation of peptides. In addition to data storage, CycPeptMPDB provides several supporting functions such as online data visualization, data analysis, and downloading. CycPeptMPDB is expected to be a valuable platform to support membrane permeability research on cyclic peptides. CycPeptMPDB can be freely accessed at http://cycpeptmpdb.com.

Semi-Empirical Astronomical Light Pollution Evaluation of Satellite Constellations

Several commercial organizations have recently launched or plan to launch constellations containing thousands of satellites. Such large constellations potentially adversely affect astronomical observations. This study formulates a set of indicators that assess the impact of light pollution from different constellations on ground-based visible band astronomy. These include the statistically expected number of visible and sunlit satellites above ground-based observers, as well as the number that are also expected to be brighter than the currently recommended limit for constellation satellites. The latter indicator provides a consolidated means to evaluate the potential for a constellation to affect ground-based astronomy too severely, by simultaneously accounting for the effects of constellation population, orbital distribution as well as brightness magnitude and variability. For existing constellations, the evaluation process incorporates actual satellite photometric brightness measurements, which are becoming increasingly available in web-accessible databases and repositories. For proposed constellations, a semi-empirical method allows rough approximations of pre-launch light pollution levels, based on observed brightness distributions observed of currently orbiting analog satellites.

Smart networks of autonomous in-situ soil sensors

The article describes a modern system of control and communication integrated in an in-situ soil sensor to make it autonomous in operation, energy and data transfer at low cost. Network of such sensors can monitor continuously soil moisture over a catchment with low maintenance. A recent industrial standard of radio communication, Long Range Wide Area Network (LoRaWAN) is presented. It permits rapid deployment of a sensor in a remote observatory, and the transfer in real time of sensor data to a central web-accessed database, via a LoRaWAN receiver, or gateway, 12 km away. In this situation transmission loss can reach a rate of 30%. Good quality antenna can lower it below 5% without extensive cost. Double messaging and other transmission algorithms are a possibility, taking into account consumption. Currently, sensors measuring one point every ten minutes can last seven months with four cheap AA alkaline batteries. Further gains would increase lifetime in same conditions by 30%.

GroovDB: A Database of Ligand-Inducible Transcription Factors.

Genetic biosensors are integral to synthetic biology. In particular, ligand-inducible prokaryotic transcription factors are frequently used in high-throughput screening, for dynamic feedback regulation, as multilayer logic gates, and in diagnostic applications. In order to provide a curated source that users can rely on for engineering applications, we have developed GroovDB (available at https://groov.bio), a Web-accessible database of ligand-inducible transcription factors that contains all information necessary to build chemically responsive genetic circuits, including biosensor sequence, ligand, and operator data. Ligand and DNA interaction data have been verified against the literature, while an automated data curation pipeline is used to programmatically fetch metadata, structural information, and references for every entry. A custom tool to visualize the natural genetic context of biosensor entries provides potential insights into alternative ligands and systems biology.

ExRNAdisease: An extracellular RNA transcriptome atlas in human diseases

Extracellular RNAs (exRNAs) are types of RNAs that present outside of the cells with highly stable features. exRNAs have been shown to play important roles in aiding intercellular communication and regulating cellular processes. In clinical settings, exRNAs have the potential to serve as biomarkers indicating the presence of a disease.Recently, the high-throughput technologies such as RNA sequencing (RNAseq) and microarray have generated abundant exRNA expression data about various diseases. Thus, it is highly desirable to have a comprehensive database for disease-related exRNA transcriptome data detected in diverse body fluids. Here, a total of 88 previously published exRNA transcriptome datasets were collected. We developed a web-accessible database, exRNADisease, which is designed as a central repository for exRNAs from body fluids in human diseases and healthy controls. In the current version, a total of 18,265 samples were collected, which includes 10 body fluids and 78 human disease types. Six different types of RNAs were included (messenger RNAs, circular RNAs, long noncoding RNAs, microRNAs, transfer RNA fragments and PIWI-interacting RNA). Literature is also included to provide the robust evidence about the relationship between exRNAs and diseases. A user-friendly interface was constructed to conveniently search and browse disease-related exRNAs. exRNADisease will become a useful platform to provide genome-wide view of exRNA deregulation in human diseases and help to identify novel biomarkers.Availability and implementation: exRNAdisease can be freely accessible at http://www.origin-gene.cn/database/exRNAdisease/.

Comparative transcriptomic analysis unveils the deep phylogeny and secondary metabolite evolution of 116 Camellia plants.

Camellia plants include more than 200 species of great diversity and immense economic, ornamental, and cultural values. We sequenced the transcriptomes of 116 Camellia plants from almost all sections of the genus Camellia. We constructed a pan-transcriptome of Camellia plants with 89 394 gene families and then resolved the phylogeny of genus Camellia based on 405 high-quality low-copy core genes. Most of the inferred relationships are well supported by multiple nuclear gene trees and morphological traits. We provide strong evidence that Camellia plants shared a recent whole genome duplication event, followed by large expansions of transcription factor families associated with stress resistance and secondary metabolism. Secondary metabolites, particularly those associated with tea quality such as catechins and caffeine, were preferentially heavily accumulated in the Camellia plants from section Thea. We thoroughly examined the expression patterns of hundreds of genes associated with tea quality, and found that some of them exhibited significantly high expression and correlations with secondary metabolite accumulations in Thea species. We also released a web-accessible database for efficient retrieval of Camellia transcriptomes. The reported transcriptome sequences and obtained novel findings will facilitate the efficient conservation and utilization of Camellia germplasm towards a breeding program for cultivated tea, camellia, and oil-tea plants.

GenomeRxiv: a microbial whole-genome database and diagnostic marker design resource for classification, identification, and data sharing

genomeRxiv is a newly-funded US-UK collaboration to provide a public, web-accessible database of public genome sequences, accurately catalogued and classified by whole-genome similarity independent of their taxonomic affiliation. Our goal is to supply the basic and applied research community with rapid, precise and accurate identification of unknown isolates based on genome sequence alone, and with molecular tools for environmental analysis. The DNA sequencing revolution enabled the use of cultured and uncultured microorganism genomes for fast and precise identification. However, precise identification is impossible without 1. reference databases that precisely circumscribe classes of microorganisms, and label these with their uniquely-shared characteristics 2. fast algorithms that can handle the volumes of genome data Our approach integrates the highly-resolved classification framework of Life Identification Numbers (LINs) with the speed and computational efficiency of sourmash and k-mer hashing algorithms, and the precision and filtering of average nucleotide identity (ANI). We aim to construct a single genome-based indexing scheme that extends from phylum to strain, enabling the unique and consistent placement of any sequenced prokaryote genome. genomeRxiv includes protocols for confidentiality, allowing groups to identify and announce the identities of newly-sequenced organisms without sharing genome data directly. This protects communities working with commercially- and ethically-sensitive organisms (e.g. production engineering strains, potential bioweapons, and to enable benefit sharing with indigenous communities). genomeRxiv will also provide online capability to design molecular diagnostic tools for metabarcoding and qPCR, to enable tracking of specific groupings of bacteria directly in the environment.

DNA Sequence-Based Identification of Fusarium: A Work in Progress.

Accurate species-level identification of an etiological agent is crucial for disease diagnosis and management because knowing the agent's identity connects it with what is known about its host range, geographic distribution, and toxin production potential. This is particularly true in publishing peer-reviewed disease reports, where imprecise and/or incorrect identifications weaken the public knowledge base. This can be a daunting task for phytopathologists and other applied biologists that need to identify Fusarium in particular, because published and ongoing multilocus molecular systematic studies have highlighted several confounding issues. Paramount among these are: (i) this agriculturally and clinically important genus is currently estimated to comprise more than 400 phylogenetically distinct species (i.e., phylospecies), with more than 80% of these discovered within the past 25 years; (ii) approximately one-third of the phylospecies have not been formally described; (iii) morphology alone is inadequate to distinguish most of these species from one another; and (iv) the current rapid discovery of novel fusaria from pathogen surveys and accompanying impact on the taxonomic landscape is expected to continue well into the foreseeable future. To address the critical need for accurate pathogen identification, our research groups are focused on populating two web-accessible databases (FUSARIUM-ID v.3.0 and the nonredundant National Center for Biotechnology Information nucleotide collection that includes GenBank) with portions of three phylogenetically informative genes (i.e., TEF1, RPB1, and RPB2) that resolve at or near the species level in every Fusarium species. The objectives of this Special Report, and its companion in this issue (Torres-Cruz etal. 2022), are to provide a progress report on our efforts to populate these databases and to outline a set of best practices for DNA sequence-based identification of fusaria.

LLPSDB v2.0: an updated database of proteins undergoing liquid-liquid phase separation in vitro.

SummaryEmerging evidences have suggested that liquid–liquid phase separation (LLPS) of proteins plays a vital role both in a wide range of biological processes and in related diseases. Whether a protein undergoes phase separation not only is determined by the chemical and physical properties of biomolecule themselves, but also is regulated by environmental conditions such as temperature, ionic strength, pH, as well as volume excluded by other macromolecules. A web accessible database LLPSDB was developed recently by our group, in which all the proteins involved in LLPS in vitro as well as corresponding experimental conditions were curated comprehensively from published literatures. With the rapid increase of investigations in biomolecular LLPS and growing popularity of LLPSDB, we updated the database, and developed a new version LLPSDB v2.0. In comparison of the previously released version, more than double contents of data are curated, and a new class ‘Ambiguous system’ is added. In addition, the web interface is improved, such as that users can search the database by selecting option ‘phase separation status’ alone or combined with other options. We anticipate that this updated database will serve as a more comprehensive and helpful resource for users.Availability and implementationLLPSDB v2.0 is freely available at: http://bio-comp.org.cn/llpsdbv2.Supplementary information Supplementary data are available at Bioinformatics online.

AroCageDB: A Web-Based Resource for Aromatic Cage Binding Sites and Their Intrinsic Ligands.

While aromatic cages have extensively been investigated in the context of structural biology, molecular recognition, and drug discovery, there exist to date no comprehensive resource for proteins sharing this conserved structural motif. To this end, we parsed the Protein Data Bank and thus constructed the Aromatic Cage Database (AroCageDB), a database for investigating the binding pocket descriptors and ligand binding space of aromatic-cage-containing proteins (ACCPs). AroCageDB contains 487 unique ACCPs bound to 890 unique ligands, for a total of 1636 complexes. This web-accessible database provides a user-friendly interface for the interactive visualization of ligand-bound ACCP structures, with a variety of search options that will open up opportunities for structural analyses and drug discovery campaigns. AroCageDB is freely available at http://www.pharmbioinf.uni-freiburg.de/arocagedb/.

The new WEB-accessible online database of the M\xf6ssbauer effect data center

The web-accessible online database (WAD) of the Mössbauer Effect Data Center (MEDC) is one of the worldwide available information services provided by MEDC to the scientific community. It is based on the uniquely wide scope Mössbauer spectroscopy database that has been compiled and maintained by MEDC since the 1960’s. Following enhancements applied to the capabilities of the MEDC core database in connection with the development of a new database management software named “MEDC DBM”, the development of a new web-accessible online database (MEDC WAD) was started in 2019. Here we introduce the current state and the main features of the newly developed MEDC WAD system with emphasis put on its novel and rather unique attributes that can effectively aid the scientific research process in the field of Mössbauer spectroscopy.

Algebraic model selection and experimental design in biological data science

Design of experiments and model selection are essential steps in biological data-science pipelines and coupling them has the potential to improve computational efficiency. In particular approaches which can handle data from unspecified distributions and nonlinear models are of interest. We propose an algebra-based computational framework to unify experimental design and model selection for discrete data sets and minimal polynomial models. We use an affine transformation, called a linear shift, to identify data sets and bases of polynomial models simultaneously. We present the theoretical foundation for a web-accessible database. This framework enables us to address two illustrative questions that may arise when studying biological systems: finding the data which identifies a set of known interactions and finding identifiable interactions given a set of data. As an example, we apply the methodology to a previously constructed pharmacodynamic model of epidermal derived growth factor receptor (EGFR) signaling.

A Collection of Multimodal Melanoma Data

Computer-aided diagnosis, prognosis and therapy systems have been of great interest for a number of years. The availability of big volumes of data and of powerful computational resources have allowed artificial intelligence approaches to emerge in melanoma related studies. However, for such approaches to have good predictive performances data availability is of crucial importance. Melanoma related imaging, biological and clinical data can be found partially and scattered in various repositories. Thus, in this work, we assemble in a web accessible database, named ebioMelDB, the widest collection of clinical and dermoscopy images accompanied with patient clinical data and the widest collection of RNA-Seq gene expression data accompanied with patient clinical data. The database organization allows users to select the data that are appropriate for their application of interest (diagnosis, prognosis and therapy). Keywords: melanoma database, integrated data, dermoscopy, imaging, RNA-Seq, clinical data.

DbGENVOC: database of GENomic Variants of Oral Cancer, with special reference to India.

Oral cancer is highly prevalent in India and is the most frequent cancer type among Indian males. It is also very common in southeast Asia. India has participated in the International Cancer Genome Consortium (ICGC) and some national initiatives to generate large-scale genomic data on oral cancer patients and analyze to identify associations and systematically catalog the associated variants. We have now created an open, web-accessible database of these variants found significantly associated with Indian oral cancer patients, with a user-friendly interface to enable easy mining. We have value added to this database by including relevant data collated from various sources on other global populations, thereby providing opportunities of comparative geographical and/or ethnic analyses. Currently, no other database of similar nature is available on oral cancer. We have developed Database of GENomic Variants of Oral Cancer, a browsable online database framework for storage, retrieval and analysis of large-scale data on genomic variants and make it freely accessible to the scientific community. Presently, the web-accessible database allows potential users to mine data on ∼24 million clinically relevant somatic and germline variants derived from exomes (n = 100) and whole genomes (n = 5) of Indian oral cancer patients; all generated by us. Variant data from The Cancer Genome Atlas and data manually curated from peer-reviewed publications were also incorporated into the database for comparative analyses. It allows users to query the database by a single gene, multiple genes, multiple variant sites, genomic region, patient ID and pathway identities. Database URL: http://research.nibmg.ac.in/dbcares/dbgenvoc/