Database resources of the National Center for Biotechnology Information

An update on clinical presentation and responses to therapy of patients with hereditary hypophosphatemic rickets with hypercalciuria (HHRH)

Pathogenic variants in solute carrier family 34, member 3 (SLC34A3), the gene encoding the sodium-dependent phosphate cotransporter 2c (NPT2c), cause hereditary hypophosphatemic rickets with hypercalciuria (HHRH). Here, we report a pooled analysis of clinical and laboratory records of 304 individuals from 145 kindreds, including 20 previously unreported HHRH kindreds, in which two novel SLC34A3 pathogenic variants were identified. Compound heterozygous/homozygous carriers show above 90% penetrance for kidney and bone phenotypes. The biochemical phenotype for heterozygous carriers is intermediate with decreased serum phosphate, tubular reabsorption of phosphate (TRP (%)), fibroblast growth factor 23, and intact parathyroid hormone, but increased serum 1,25-dihydroxy vitamin D, and urine calcium excretion causing idiopathic hypercalciuria in 38%, with bone phenotypes still observed in 23% of patients. Oral phosphate supplementation is the current standard of care, which typically normalizes serum phosphate. However, although in more than half of individuals this therapy achieves correction of hypophosphatemia it fails to resolve the other outcomes. The American College of Medical Genetics and Genomics score correlated with functional analysis of frequent SLC34A3 pathogenic variants in vitro and baseline disease severity. The number of mutant alleles and baseline TRP (%) were identified as predictors for kidney and bone phenotypes, baseline TRP (%) furthermore predicted response to therapy. Certain SLC34A3/NPT2c pathogenic variants can be identified with partial responses to therapy, whereas with some overlap, others present only with kidney phenotypes and a third group present only with bone phenotypes. Thus, our report highlights important novel clinical aspects of HHRH and heterozygous carriers, raises awareness to this rare group of disorders and can be a foundation for future studies urgently needed to guide therapy of HHRH.

Convergent evolution and horizontal gene transfer in Arctic Ocean microalgae

Microbial communities in the world ocean are affected strongly by oceanic circulation, creating characteristic marine biomes. The high connectivity of most of the ocean makes it difficult to disentangle selective retention of colonizing genotypes (with traits suited to biome specific conditions) from evolutionary selection, which would act on founder genotypes over time. The Arctic Ocean is exceptional with limited exchange with other oceans and ice covered since the last ice age. To test whether Arctic microalgal lineages evolved apart from algae in the global ocean, we sequenced four lineages of microalgae isolated from Arctic waters and sea ice. Here we show convergent evolution and highlight geographically limited HGT as an ecological adaptive force in the form of PFAM complements and horizontal acquisition of key adaptive genes. Notably, ice-binding proteins were acquired and horizontally transferred among Arctic strains. A comparison with Tara Oceans metagenomes and metatranscriptomes confirmed mostly Arctic distributions of these IBPs. The phylogeny of Arctic-specific genes indicated that these events were independent of bacterial-sourced HGTs in Antarctic Southern Ocean microalgae.

Peptide Utility (PU) search server: A new tool for peptide sequence search from multiple databases

Proteins are essential building blocks in humans that have garnered huge attention from researchers worldwide due to their numerous therapeutic applications. To date, different computational tools have been developed to extract pre-existing information on these biological molecules, but most of these tools suffer from limitations such as non-user friendly interface, redundancy of data, etc. To overcome these limitations, a user-friendly interface, the Peptide Utility (PU) webserver (https://chain-searching.herokuapp.com/) has been developed for searching and analyzing homologous and identical protein/peptide sequences that can be searched from approximately 0.4 million sequences (structural and sequence information) in both online and offline modes. The PU web server can also be used to study different types of interactions in PDBSum, identifying the most dominating interface residues, the most prevalent interactions, and the interaction preferences of different residues. The webserver would also pave way for the design of novel therapeutic peptides and folds by identifying conserved residues in the three-dimensional structure space of proteins.

Identification of novel inhibitors of high affinity iron permease (FTR1) through implementing pharmacokinetics index to fight against black fungus: An in silico approach

Mucormycosis is a life-threatening fungal infection, particularly in immunocompromised patients. Mucormycosis has been reported to show resistance to available antifungal drugs and was recently found in COVID-19 as a co-morbidity that demands new classes of drugs. In an attempt to find novel inhibitors against the high-affinity iron permease (FTR1), a novel target having fundamental importance on the pathogenesis of mucormycosis, 11,000 natural compounds were investigated in this study. Virtual screening and molecular docking identified two potent natural compounds [6',7,7,10',10',13'-hexamethylspiro[1,8-dihydropyrano[2,3-g]indole-3,11'-3,13-diazatetracyclo[5.5.2.01,9.03,7]tetradecane]-2,9,14'-trione and 5,7-dihydroxy-3-(2,2,8,8-tetramethylpyrano[2,3-f]chromen-6-yl)chromen-4-one] that effectively bind to the active cavity of FTR1 with a binding affinity of -9.9 kcal/mol. Multiple non-covalent interactions between the compounds and the active residues of this cavity were noticed, which is required for FTR1 inhibition. These compounds were found to have inhibitory nature and meet essential requirements to be drug-like compounds with a considerable absorption, distribution, metabolism, and excretion (ADME) profile with no toxicity probabilities. Molecular dynamics simulation confirms the structural compactness and less conformational variation of the drug-protein complexes maintaining structural stability and rigidity. MM-PBSA and post-simulation analysis predict binding stability of these compounds in the active cavity. This study hypothesizing that these compounds could be a potential inhibitor of FTR1 and will broaden the clinical prospects of mucormycosis.

HGD: an integrated homologous gene database across multiple species

Homology is fundamental to infer genes' evolutionary processes and relationships with shared ancestry. Existing homolog gene resources vary in terms of inferring methods, homologous relationship and identifiers, posing inevitable difficulties for choosing and mapping homology results from one to another. Here, we present HGD (Homologous Gene Database, https://ngdc.cncb.ac.cn/hgd), a comprehensive homologs resource integrating multi-species, multi-resources and multi-omics, as a complement to existing resources providing public and one-stop data service. Currently, HGD houses a total of 112 383 644 homologous pairs for 37 species, including 19 animals, 16 plants and 2 microorganisms. Meanwhile, HGD integrates various annotations from public resources, including 16 909 homologs with traits, 276 670 homologs with variants, 398 573 homologs with expression and 536 852 homologs with gene ontology (GO) annotations. HGD provides a wide range of omics gene function annotations to help users gain a deeper understanding of gene function.

Molecular Characterization of Probiotics and Their Influence on Children with Autism Spectrum Disorder

Children with autism spectrum disorder (ASD) are usually unable to express abdominal discomfort properly, and thus gastrointestinal symptoms (GIS) are sometimes shadowed by aggression, which is sometimes misunderstood as a behavioral characteristic of ASD. Several studies have reported interesting correlations between the severity of behavioral and gastrointestinal symptoms in ASD children. The present study aimed to investigate the potential effects of probiotics as an adjuvant therapy to modulate the clinical status of ASD children. This study included 40 children with ASD aged 2-5 years. The feeding product was prepared from whey powder (without casein) and some minced cooked yellow vegetables in adequate ratios fortified with the studied probiotic strains (Bifidobacterium spp. and Lactobacillus spp.). Bifidobacterium strains were assessed from stool samples of children with ASD. Bifidobacterium strains were analyzed in the stools of ASD children. Recruited ASD patients received 10 g of the nutritional supplement once a day for 3 months. Childhood Autism Rating Scale (CARS) and Autism Diagnostic Interview-Revised (ADIR) were reevaluated clinically. Questionnaire on Pediatric Gastrointestinal Symptoms-Rome III Version was used for all children with ASD before and after. There is a significant increase in the colony counts of both Bifidobacterium spp. and Lactobacillus spp., which present in the stool of ASD children after probiotic supplementation for 3 months. It was highly significant in the case of Bifidobacterium spp. (p value 0.000) and a significant increase in Lactobacillus spp. (p value 0.015). The present study showed reduced anxiety and observation of deep sleep for children with ASD (80%) after taking the supplementation. This indicates that probiotics may have a potential effect in reducing symptoms and severity of ASD and in correcting dysbiosis.

Physiological, Agronomical, and Proteomic Studies Reveal Crucial Players in Rice Nitrogen Use Efficiency under Low Nitrogen Supply

Excessive use of nitrogenous fertilizers to enhance rice productivity has become a significant source of nitrogen (N) pollution and reduced sustainable agriculture. However, little information about the physiology of different growth stages, agronomic traits, and associated genetic bases of N use efficiency (NUE) are available at low-N supply. Two rice (Oryza sativa L.) cultivars were grown with optimum N (120 kg ha⁻¹) and low N (60 kg ha⁻¹) supply. Six growth stages were analyzed to measure the growth and physiological traits, as well as the differential proteomic profiles, of the rice cultivars. Cultivar Panvel outclassed Nagina 22 at low-N supply and exhibited improved growth and physiology at most of the growth stages and agronomic efficiency due to higher N uptake and utilization at low-N supply. On average, photosynthetic rate, chlorophyll content, plant biomass, leaf N content, and grain yield were decreased in cultivar Nagina 22 than Panvel was 8%, 11%, 21%, 19%, and 22%, respectively, under low-N supply. Furthermore, proteome analyses revealed that many proteins were upregulated and downregulated at the different growth stages under low-N supply. These proteins are associated with N and carbon metabolism and other physiological processes. This supports the genotypic differences in photosynthesis, N assimilation, energy stabilization, and rice-protein yield. Our study suggests that enhancing NUE at low-N supply demands distinct modifications in N metabolism and physiological assimilation. The NUE may be regulated by key identified differentially expressed proteins. These proteins might be the targets for improving crop NUE at low-N supply.

Author-sourced capture of pathway knowledge in computable form using Biofactoid

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

PCMDB: a curated and comprehensive resource of plant cell markers

The advent of single-cell sequencing opened a new era in transcriptomic and genomic research. To understand cell composition using single-cell studies, a variety of cell markers have been widely used to label individual cell types. However, the specific database of cell markers for use by the plant research community remains very limited. To overcome this problem, we developed the Plant Cell Marker DataBase (PCMDB, http://www.tobaccodb.org/pcmdb/), which is based on a uniform annotation pipeline. By manually curating over 130 000 research publications, we collected a total of 81 117 cell marker genes of 263 cell types in 22 tissues across six plant species. Tissue- and cell-specific expression patterns can be visualized using multiple tools: eFP Browser, Bar, and UMAP/TSNE graph. The PCMDB also supports several analysis tools, including SCSA and SingleR, which allows for user annotation of cell types. To provide information about plant species currently unsupported in PCMDB, potential marker genes for other plant species can be searched based on homology with the supported species. PCMDB is a user-friendly hierarchical platform that contains five built-in search engines. We believe PCMDB will constitute a useful resource for researchers working on cell type annotation and the prediction of the biological function of individual cells.

Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance

The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action.

ARGEOS: A New Bioinformatic Tool for Detailed Systematics Search in GEO and ArrayExpress

Simple Summary

A systematic search for datasets of transcriptome data is a hefty task. Therefore, we developed the ARGEOS web tool, which simplifies the search and selection of datasets from various public databases. In addition, the service carries out an advanced analysis of a dataset, including collecting detailed protocols, information on the number of datasets, and providing additional reference information. An example of a cell polarization study exemplifies the effectiveness of the tool.

Abstract

Conduct a reanalysis of transcriptome data for studying intracellular signaling or solving other experimental problems is becoming increasingly popular. Gene expression data are archived as microarray or RNA-seq datasets mainly in two public databases: Gene Expression Omnibus (GEO) and ArrayExpress (AE). These databases were not initially intended to systematically search datasets, making it challenging to conduct a secondary study. Therefore, we have created the ARGEOS service, which has the following advantages that facilitate the search: (1) Users can simultaneously send several requests that are supposed to be used for systematic searches, and it is possible to correct the requests; (2) advanced analysis of information about the dataset is available. The service collects detailed protocols, information on the number of datasets, analyzes the availability of raw data, and provides other reference information. All this contributes to both rapid data analysis with the search for the most relevant datasets and to the systematic search with detailed analysis of the information of the datasets. The efficiency of the service is shown in the example of analyzing transcriptome data of activated (polarized) cells. We have performed a systematic search of studies of cell polarization (when cells are exposed to different immune stimuli). The web interface for ARGEOS is user-friendly and straightforward. It can be used by a person who is not familiar with database searching.

Will the chemical probes please stand up?

In 2005, the NIH Molecular Libraries Program (MLP) undertook the identification of tool compounds to expand biological insights, now termed small-molecule chemical probes. This inspired other organisations to initiate similar efforts from 2010 onwards. As a central focus of the Probes & Drugs portal (P&D), we have standardised, integrated and compared sets of declared probe compounds harvested from 12 different sources. This turned out to be challenging and revealed unexpected anomalies. Results in this work address key questions including; a) individual and total structure counts, b) overlaps between sources, c) comparisons with selected PubChem sources and d) investigating the probe coverage of druggable targets. In addition, we developed new high-level scoring schemes to filter collections down to probes of higher quality. This generated 548 high-quality chemical probes (HQCP) covering 447 distinct protein targets. This HQCP collection has been added to the P&D portal and will be regularly updated as established sources expand and new ones release data.

Integrative taxonomy resolves species identities within the Macrobiotus pallarii complex (Eutardigrada: Macrobiotidae)

The taxonomy of many groups of meiofauna is challenging due to their low number of diagnostic morphological characters and their small body size. Therefore, with the advent of molecular techniques that provide a new source of traits, many cryptic species have started to be discovered. Tardigrades are not an exception, and many once thought to be cosmopolitan taxa are being found to be complexes of phenotypically similar species. Macrobiotus pallarii Maucci, 1954 was originally described in South Italy and has been subsequently recorded in Europe, America, and Asia. This allegedly wide geographic range suggests that multiple species may be hidden under this name. Moreover, recently, genetic evidence to support this was put forward, and the Macrobiotus pallarii complex has been proposed to accommodate putative species related to M. pallarii. Here, we describe three new pseudocryptic species based on populations that would have been all classified as Macrobiotus pallarii if molecular methods were not employed. Using an integrative taxonomy approach, we analyzed animals and eggs from the topotypic population of Macrobiotus pallarii, together with four other populations of the complex. We recovered four distinct phylogenetic lineages that, despite the overlap of morphometric traits, can be separated phenotypically by subtle but discrete morphological characters. One lineage corresponds to Macrobiotus pallarii, whereas the other three are newly described as Macrobiotus margoae Stec, Vecchi & Bartels, sp. nov. from the USA, Macrobiotus ripperi Stec, Vecchi & Michalczyk, sp. nov. from Poland and Finland, and Macrobiotus pseudopallarii Stec, Vecchi & Michalczyk, sp. nov. from Montenegro. To facilitate species identification, we provide a dichotomous key for species of the M. pallarii complex. Delimitation of these pseudocryptic taxa highlights the need for an integrative approach to uncover the phylum's diversity in full.

Microalgae with artificial intelligence: A digitalized perspective on genetics, systems and products

With recent advances in novel gene-editing tools such as RNAi, ZFNs, TALENs, and CRISPR-Cas9, the possibility of altering microalgae toward designed properties for various application is becoming a reality. Alteration of microalgae genomes can modify metabolic pathways to give elevated yields in lipids, biomass, and other components. The potential of such genetically optimized microalgae can give a "domino effect" in further providing optimization leverages down the supply chain, in aspects such as cultivation, processing, system design, process integration, and revolutionary products. However, the current level of understanding the functional information of various microalgae gene sequences is still primitive and insufficient as microalgae genome sequences are long and complex. From this perspective, this work proposes to link up this knowledge gap between microalgae genetic information and optimized bioproducts using Artificial Intelligence (AI). With the recent acceleration of AI research, large and complex data from microalgae research can be properly analyzed by combining the cutting-edge of both fields. In this work, the most suitable class of AI algorithms (such as active learning, semi-supervised learning, and meta-learning) are discussed for different cases of microalgae applications. This work concisely reviews the current state of the research milestones and highlight some of the state-of-art that has been carried out, providing insightful future pathways. The utilization of AI algorithms in microalgae cultivation, system optimization, and other aspects of the supply chain is also discussed. This work opens the pathway to a digitalized future for microalgae research and applications.

CRISPRCasdb a successor of CRISPRdb containing CRISPR arrays and cas genes from complete genome sequences, and tools to download and query lists of repeats and spacers

In Archaea and Bacteria, the arrays called CRISPRs for 'clustered regularly interspaced short palindromic repeats' and the CRISPR associated genes or cas provide adaptive immunity against viruses, plasmids and transposable elements. Short sequences called spacers, corresponding to fragments of invading DNA, are stored in-between repeated sequences. The CRISPR-Cas systems target sequences homologous to spacers leading to their degradation. To facilitate investigations of CRISPRs, we developed 12 years ago a website holding the CRISPRdb. We now propose CRISPRCasdb, a completely new version giving access to both CRISPRs and cas genes. We used CRISPRCasFinder, a program that identifies CRISPR arrays and cas genes and determine the system's type and subtype, to process public whole genome assemblies. Strains are displayed either in an alphabetic list or in taxonomic order. The database is part of the CRISPR-Cas++ website which also offers the possibility to analyse submitted sequences and to download programs. A BLAST search against lists of repeats and spacers extracted from the database is proposed. To date, 16 990 complete prokaryote genomes (16 650 bacteria from 2973 species and 340 archaea from 300 species) are included. CRISPR-Cas systems were found in 36% of Bacteria and 75% of Archaea strains. CRISPRCasdb is freely accessible at https://crisprcas.i2bc.paris-saclay.fr/.

CRISPRCasdb a successor of CRISPRdb containing CRISPR arrays and cas genes from complete genome sequences, and tools to download and query lists of repeats and spacers

In Archaea and Bacteria, the arrays called CRISPRs for 'clustered regularly interspaced short palindromic repeats' and the CRISPR associated genes or cas provide adaptive immunity against viruses, plasmids and transposable elements. Short sequences called spacers, corresponding to fragments of invading DNA, are stored in-between repeated sequences. The CRISPR-Cas systems target sequences homologous to spacers leading to their degradation. To facilitate investigations of CRISPRs, we developed 12 years ago a website holding the CRISPRdb. We now propose CRISPRCasdb, a completely new version giving access to both CRISPRs and cas genes. We used CRISPRCasFinder, a program that identifies CRISPR arrays and cas genes and determine the system's type and subtype, to process public whole genome assemblies. Strains are displayed either in an alphabetic list or in taxonomic order. The database is part of the CRISPR-Cas++ website which also offers the possibility to analyse submitted sequences and to download programs. A BLAST search against lists of repeats and spacers extracted from the database is proposed. To date, 16 990 complete prokaryote genomes (16 650 bacteria from 2973 species and 340 archaea from 300 species) are included. CRISPR-Cas systems were found in 36% of Bacteria and 75% of Archaea strains. CRISPRCasdb is freely accessible at https://crisprcas.i2bc.paris-saclay.fr/.

PhaeoNet: A Holistic RNAseq-Based Portrait of Transcriptional Coordination in the Model Diatom Phaeodactylum tricornutum

Transcriptional coordination is a fundamental component of prokaryotic and eukaryotic cell biology, underpinning the cell cycle, physiological transitions, and facilitating holistic responses to environmental stress, but its overall dynamics in eukaryotic algae remain poorly understood. Better understanding of transcriptional partitioning may provide key insights into the primary metabolism pathways of eukaryotic algae, which frequently depend on intricate metabolic associations between the chloroplasts and mitochondria that are not found in plants. Here, we exploit 187 publically available RNAseq datasets generated under varying nitrogen, iron and phosphate growth conditions to understand the co-regulatory principles underpinning transcription in the model diatom Phaeodactylum tricornutum. Using WGCNA (Weighted Gene Correlation Network Analysis), we identify 28 merged modules of co-expressed genes in the P. tricornutum genome, which show high connectivity and correlate well with previous microarray-based surveys of gene co-regulation in this species. We use combined functional, subcellular localization and evolutionary annotations to reveal the fundamental principles underpinning the transcriptional co-regulation of genes implicated in P. tricornutum chloroplast and mitochondrial metabolism, as well as the functions of diverse transcription factors underpinning this co-regulation. The resource is publically available as PhaeoNet, an advanced tool to understand diatom gene co-regulation.

A Point of Inflection and Reflection on Systems Chemical Biology

For the past several decades, chemical biologists have been leveraging chemical principles for understanding biology, tackling disease, and biomanufacturing, while systems biologists have holistically applied computation and genome-scale experimental tools to the same problems. About a decade ago, the benefit of combining the philosophies of chemical biology with systems biology into systems chemical biology was advocated, with the potential to systematically understand the way small molecules affect biological systems. Recently, there has been an explosion in new technologies that permit massive expansion in the scale of biological experimentation, increase access to more diverse chemical space, and enable powerful computational interpretation of large datasets. Fueled by these rapidly increasing capabilities, systems chemical biology is now at an inflection point, poised to enter a new era of more holistic and integrated scientific discovery. Systems chemical biology is primed to reveal an integrated understanding of fundamental biology and to discover new chemical probes to comprehensively dissect and systematically understand that biology, thereby providing a path to novel strategies for discovering therapeutics, designing drug combinations, avoiding toxicity, and harnessing beneficial polypharmacology. In this Review, we examine the emergence of new capabilities driving us to this inflection point in systems chemical biology, and highlight holistic approaches and opportunities that are arising from integrating chemical biology with a systems-level understanding of the intersection of biology and chemistry.

Lipid Related Genes Altered in NASH Connect Inflammation in Liver Pathogenesis Progression to HCC: A Canonical Pathway

Nonalcoholic steatohepatitis (NASH) is becoming a public health problem worldwide. While the number of research studies on NASH progression rises every year, sometime their findings are controversial. To identify the most important and commonly described findings related to NASH progression, we used an original bioinformatics, integrative, text-mining approach that combines PubMed database querying and available gene expression omnibus dataset. We have identified a signature of 25 genes that are commonly found to be dysregulated during steatosis progression to NASH and cancer. These genes are implicated in lipid metabolism, insulin resistance, inflammation, and cancer. They are functionally connected, forming the basis necessary for steatosis progression to NASH and further progression to hepatocellular carcinoma (HCC). We also show that five of the identified genes have genome alterations present in HCC patients. The patients with these genes associated to genome alteration are associated with a poor prognosis. In conclusion, using an integrative literature- and data-mining approach, we have identified and described a canonical pathway underlying progression of NASH. Other parameters (e.g., polymorphisms) can be added to this pathway that also contribute to the progression of the disease to cancer. This work improved our understanding of the molecular basis of NASH progression and will help to develop new therapeutic approaches.

Molecular characterization of a new vitivirus discovered in a blueberry plant with green mosaic symptoms

A new virus belonging to the genus Vitivirus in the family Betaflexiviridae was identified by next-generation sequencing of a blueberry plant showing green mosaic symptoms. The genome organization of the virus, which is tentatively named "blueberry green mosaic-associated virus" (BGMaV), is typical of vitiviruses, with five open reading frames (ORFs) and a polyadenylated 3' terminus. The ORFs code for the viral replicase, a 16K protein of unknown function, a movement protein, a coat protein (CP), and a nucleic acid binding protein. Phylogenetic analyses based on the deduced amino acid sequence of the CP and conserved motifs of the RNA-dependent RNA polymerase confirmed the taxonomic placement of BGMaV in the genus Vitivirus.

Protein interactions and consensus clustering analysis uncover insights into herpesvirus virion structure and function relationships

Infections with human herpesviruses are ubiquitous and a public health concern worldwide. Current treatments reduce the severity of some symptoms associated to herpetic infections but neither remove the viral reservoir from the infected host nor protect from the recurrent symptom outbreaks that characterise herpetic infections. The difficulty in therapeutically tackling these viral systems stems in part from their remarkably large proteomes and the complex networks of physical and functional associations that they tailor. This study presents our efforts to unravel the complexity of the interactome of herpes simplex virus type 1 (HSV1), the prototypical herpesvirus species. Inspired by our previous work, we present an improved and more integrative computational pipeline for the protein–protein interaction (PPI) network reconstruction in HSV1, together with a newly developed consensus clustering framework, which allowed us to extend the analysis beyond binary physical interactions and revealed a system-level layout of higher-order functional associations in the virion proteome. Additionally, the analysis provided new functional annotation for the currently undercharacterised protein pUS10. In-depth bioinformatics sequence analysis unravelled structural features in pUS10 reminiscent of those observed in some capsid-associated proteins in tailed bacteriophages, with which herpesviruses are believed to share a common ancestry. Using immunoaffinity purification (IP)–mass spectrometry (MS), we obtained additional support for our bioinformatically predicted interaction between pUS10 and the inner tegument protein pUL37, which binds cytosolic capsids, contributing to initial tegumentation and eventually virion maturation. In summary, this study unveils new, to our knowledge, insights at both the system and molecular levels that can help us better understand the complexity behind herpesvirus infections.

Consensus clustering of protein-protein interaction networks provides insights into the assembly mechanism of herpes simplex virus type 1 (HSV1) virions and structure-function relationships underlying herpesvirus infection.

Metabolism, Nutrition, and Redox Signaling of Hydroxyproline

SIGNIFICANCE

Hydroxyproline is a structurally and physiologically important imino acid in animals. It is provided from diets and endogenous synthesis, and its conversion into glycine enhances the production of glutathione, DNA, heme, and protein. Furthermore, oxidation of hydroxyproline by hydroxyproline oxidase (OH-POX) plays an important role in cell antioxidative reactions, survival, and homeostasis. Understanding the mechanisms whereby hydroxyproline participates in metabolism and cell signaling can improve the nutrition and health of animals and humans. Recent Advances: Hydroxyproline is highly abundant in milk and is utilized for renal synthesis of glycine to support neonatal growth, development, and survival. The oxidation of hydroxyproline by mitochondrial OH-POX generates reactive oxygen species (ROS). Enhanced ROS production contributes to the regulation of oxidative defense, apoptosis, angiogenesis, tumorigenesis, hypoxic responses, and cell survival in animals.

CRITICAL ISSUES

Although dietary hydroxyproline enters the portal circulation, its utilization by the portal-drained viscera is unknown. Pathways for hydroxyproline metabolism and their regulation at the molecular, cellular, and whole-body levels remain to be defined. Furthermore, the mechanisms responsible for hydroxyproline-derived ROS and related metabolites to induce cell survival or apoptosis are unknown.

FUTURE DIRECTIONS

Interorgan metabolism of hydroxyproline (including synthesis, catabolism, and flux) in animals must be quantified using isotope technologies. Efforts should also be directed toward studying dietary, hormonal, and epigenetic regulation of OH-POX expression at transcriptional and translational levels. Another emerging research need is to understand the roles of cellular redox and signaling networks involving both ROS and Δ¹-pyrroline-3-hydroxy-5-carboxylate in nutrition, health, and disease.

Characterization of indole-3-pyruvic acid pathway-mediated biosynthesis of auxin in Neurospora crassa

Plants, bacteria and some fungi are known to produce indole-3-acetic acid (IAA) by employing various pathways. Among these pathways, the indole-3-pyruvic acid (IPA) pathway is the best studied in green plants and plant-associated beneficial microbes. While IAA production circuitry in plants has been studied for decades, little is known regarding the IAA biosynthesis pathway in fungal species. Here, we present the first data for IAA-producing genes and the associated biosynthesis pathway in a non-pathogenic fungus, Neurospora crassa. For this purpose, we used a computational approach to determine the genes and outlined the IAA production circuitry in N. crassa. We then validated these data with experimental evidence. Here, we describe the homologous genes that are present in the IPA pathway of IAA production in N. crassa. High-performance liquid chromatography and thin-layer chromatography unambiguously identified IAA, indole-3-lactic acid (ILA) and tryptophol (TOL) from cultures supplemented with tryptophan. Deletion of the gene (cfp) that encodes the enzyme indole-3-pyruvate decarboxylase, which converts IPA to indole-3-acetaldehyde (IAAld), results in an accumulation of higher levels of ILA in the N. crassa culture medium. A double knock-out strain (Δcbs-3;Δahd-2) for the enzyme IAAld dehydrogenase, which converts IAAld to IAA, shows a many fold decrease in IAA production compared with the wild type strain. The Δcbs-3;Δahd-2 strain also displays slower conidiation and produces many fewer conidiospores than the wild type strain.

Preferential selection of Arginine at the lipid-water-interface of TRPV1 during vertebrate evolution correlates with its snorkeling behaviour and cholesterol interaction

TRPV1 is a thermo-sensitive ion channel involved in neurosensory and other physiological functions. The trans-membrane helices of TRPV1 undergo quick and complex conformational changes governed by thermodynamic parameters and membrane components leading to channel opening. However, the molecular mechanisms underlying such events are poorly understood. Here we analysed the molecular evolution of TRPV1 at the lipid-water-interface region (LWI), typically defined as a layer of 6 Å thickness on each side of the membrane with less availability of free water. Amino acids demarcating the end of the trans-membrane helices are highly conserved. Residues present in the inner leaflet are more conserved and have been preferentially selected over others. Amino acids with snorkeling properties (Arginine and Tyrosine) undergo specific selection during the vertebrate evolution in a cholesterol-dependent and/or body temperature manner. Results suggest that H-bond formation between the OH- group of cholesterol and side chain of Arg557 or Arg575 at the inner leaflet is a critical parameter that can regulate channel functions. Different LWI mutants of TRPV1 have altered membrane localization and deficient colocalization with lipid raft markers. These findings may help to understand the lipid-protein interactions, and molecular basis of different neuronal functions. Such findings may have broad importance in the context of differential sensory responses, pathophysiologies, and application of pharmacological drugs such as anaesthetics acting on TRPVs.

Genomic and Molecular Characterization of Clinical Isolates of Enterobacteriaceae Harboring mcr-1 in Colombia, 2002 to 2016

Polymyxins are last-resort antimicrobial agents used to treat infections caused by carbapenem-resistant Enterobacteriaceae Due to the worldwide dissemination of polymyxin resistance in animal and human isolates, we aimed to characterize polymyxin resistance associated with the presence of mcr-1 in Enterobacteriaceae and nonfermenter Gram-negative bacilli, using isolates collected retrospectively in Colombia from 2002 to 2016. A total of 5,887 Gram-negative clinical isolates were studied, and 513 were found to be resistant to the polymyxins. Susceptibility to colistin was confirmed by broth microdilution for all mcr-1-positive isolates, and these were further subjected to whole-genome sequencing (WGS). The localization of mcr-1 was confirmed by S1 pulsed-field gel electrophoresis (S1-PFGE) and CeuI-PFGE hybridization. Transferability was evaluated by mating assays. A total of 12 colistin-resistant isolates recovered after 2013 harbored mcr-1, including 8 Escherichia coli, 3 Salmonella enterica serovar Typhimurium, and 1 Klebsiella pneumoniae isolate. E. coli isolates were unrelated by PFGE and belonged to 7 different sequence types (STs) and phylogroups. S Typhimurium and K. pneumoniae isolates belonged to ST34 and ST307, respectively. The mcr-1 gene was plasmid borne in all isolates but two E. coli isolates which harbored it on the chromosome. Conjugation of mcr-1 was successful in 8 of 10 isolates (8.2 × 10^-5 to 2.07 × 10^-1 cell per recipient). Plasmid sequences showed that the mcr-1 plasmids belonged to four different Inc groups (a new IncP-1 variant and the IncFII, IncHI1, and IncH families). Our results indicate that mcr-1 is circulating in clinical isolates of colistin-resistant Enterobacteriaceae in Colombia and is mainly harbored in transferable plasmids.

The Plasma Proteome Is Associated with Anthropometric Status of Undernourished Nepalese School-Aged Children

Background: Malnutrition affects body growth, size, and composition of children. Yet, few functional biomarkers are known to be associated with childhood morphology.

Objective: This cross-sectional study examined associations of anthropometric indicators of height, musculature, and fat mass with plasma proteins by using proteomics in a population cohort of school-aged Nepalese children.

Methods: Height, weight, midupper arm circumference (MUAC), triceps and subscapular skinfolds, upper arm muscle area (AMA), and arm fat area (AFA) were assessed in 500 children 6–8 y of age. Height-for-age z scores (HAZs), weight-for-age z scores (WAZs), and body mass index–for-age z scores (BAZs) were derived from the WHO growth reference. Relative protein abundance was quantified by using tandem mass spectrometry. Protein-anthropometry associations were evaluated by linear mixed-effects models and identified as having a false discovery rate (q) <5%.

Results: Among 982 proteins, 1, 10, 14, and 17 proteins were associated with BAZ, HAZ, MUAC, and AMA, respectively (q < 0.05). Insulin-like growth factor (IGF)-I, 2 IGF-binding proteins, and carnosinase-1 were associated with both HAZ and AMA. Proteins involved in nutrient transport, activation of innate immunity, and bone mineralization were associated with HAZ. Several extracellular matrix proteins were positively associated with AMA alone. The proteomes of MUAC and AMA substantially overlapped, whereas no proteins were associated with AFA or triceps and subscapular skinfolds. Myosin light-chain kinase, possibly reflecting leakage from muscle, was inversely associated with BAZ. The proteome of WAZ was the largest (n = 33) and most comprehensive, including proteins involved in neural development and oxidative stress response, among others.

Conclusions: Plasma proteomics confirmed known biomarkers of childhood growth and revealed novel proteins associated with lean mass in chronically undernourished children. Identified proteins may serve as candidates for assessing growth and nutritional status of children in similar undernourished settings. The antenatal micronutrient supplementation trial yielding the study cohort of children was registered at clinicaltrials.gov as NCT00115271.

Complete genome anatomy of the emerging potato pathogen Dickeya solani type strain IPO 2222T

Several species of the genus Dickeya provoke soft rot and blackleg diseases on a wide range of plants and crops. Dickeya solani has been identified as the causative agent of diseases outbreaks on potato culture in Europe for the last decade. Here, we report the complete genome of the D. solani IPO 2222^T. Using PacBio and Illumina technologies, a unique circular chromosome of 4,919,833 bp was assembled. The G + C content reaches 56% and the genomic sequence contains 4,059 predicted proteins. The ANI values calculated for D. solani IPO 2222^T vs. other available D. solani genomes was over 99.9% indicating a high genetic homogeneity within D. solani species.

Using DrugBank for In Silico Drug Exploration and Discovery

DrugBank is a fully curated drug and drug target database that contains 8174 drug entries including 1944 FDA approved small-molecule drugs, 198 FDA-approved biotech (protein/peptide) drugs, 93 nutraceuticals, and over 6000 experimental drugs. Additionally, 4300 non-redundant protein (i.e., drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. DrugBank is primarily focused on providing both the query/search tools and biophysical data needed to facilitate drug discovery and drug development. This unit provides readers with a detailed description of how to effectively use the DrugBank database and how to navigate through the DrugBank Web site. It also provides specific examples of how to find chemical homologs of potential drug leads and how to identify potential drug targets from newly sequenced tumor samples. The intent of this unit is to give readers an introduction to the field of Web-based drug discovery and to show how cheminformatics can be seamlessly integrated into the field of bioinformatics. © 2016 by John Wiley & Sons, Inc.

Characterisation of the Porphyromonas gingivalis Manganese Transport Regulator Orthologue

PgMntR is a predicted member of the DtxR family of transcriptional repressors responsive to manganese in the anaerobic periodontal pathogen Porphyromonas gingivalis. Our bioinformatic analyses predicted that PgMntR had divalent metal binding site(s) with elements of both manganous and ferrous ion specificity and that PgMntR has unusual twin C-terminal FeoA domains. We produced recombinant PgMntR and four variants to probe the specificity of metal binding and its impact on protein structure and DNA binding. PgMntR dimerised in the absence of a divalent transition metal cation. PgMntR bound three Mn(II) per monomer with an overall dissociation constant Kd 2.0 x 10(-11) M at pH 7.5. PgMntR also bound two Fe(II) with distinct binding affinities, Kd1 2.5 x 10(-10) M and Kd2 ≤ 6.0 x 10(-8) M at pH 6.8. Two of the metal binding sites may form a binuclear centre with two bound Mn2+ being bridged by Cys108 but this centre provided only one site for Fe2+. Binding of Fe2+ or Mn2+ did not have a marked effect on the PgMntR secondary structure. Apo-PgMntR had a distinct affinity for the promoter region of the gene encoding the only known P. gingivalis manganese transporter, FB2. Mn2+ increased the DNA binding affinity of PgMntR whilst Fe2+ destabilised the protein-DNA complex in vitro. PgMntR did not bind the promoter DNA of the gene encoding the characterised iron transporter FB1. The C-terminal FeoA domain was shown to be essential for PgMntR structure/function, as its removal caused the introduction of an intramolecular disulfide bond and abolished the binding of Mn2+ and DNA. These data indicate that PgMntR is a novel member of the DtxR family that may function as a transcriptional repressor switch to specifically regulate manganese transport and homeostasis in an iron-dependent manner.

Molecular Cloning of cpcU and Heterodimeric Bilin Lyase Activity Analysis of CpcU and CpcS for Attachment of Phycocyanobilin to Cys-82 on the β-Subunit of Phycocyanin in Arthrospira platensis FACHB314

A new bilin lyase gene cpcU was cloned from Arthrospira platensis FACHB314 to study the assembly of the phycocyanin β-Subunit. Two recombinant plasmids, one contained the phycocyanobilin (PCB) producing genes (hoxI and pcyA), while the other contained the gene of the β-Subunit of phycobiliprotein (cpcB) and the lyase gene (cpcU, cpcS, or cpcU/S) were constructed and separately transferred into Escherichia coli in order to test the activities of relevant lyases for catalyzing PCB addition to CpcB during synthesizing fluorescent β-PC of A. platensis FACHB314. The fluorescence intensity examination showed that Cys-82 maybe the active site for the β-Subunit binding to PCBs and the attachment could be carried out by CpcU, CpcS, or co-expressed cpcU/S in A. platensis FACHB314.

Why individual thermo sensation and pain perception varies? Clue of disruptive mutations in TRPVs from 2504 human genome data

Every individual varies in character and so do their sensory functions and perceptions. The molecular mechanism and the molecular candidates involved in these processes are assumed to be similar if not same. So far several molecular factors have been identified which are fairly conserved across the phylogenetic tree and are involved in these complex sensory functions. Among all, members belonging to Transient Receptor Potential (TRP) channels have been widely characterized for their involvement in thermo-sensation. These include TRPV1 to TRPV4 channels which reveal complex thermo-gating behavior in response to changes in temperature. The molecular evolution of these channels is highly correlative with the thermal response of different species. However, recent 2504 human genome data suggest that these thermo-sensitive TRPV channels are highly variable and carry possible deleterious mutations in human population. These unexpected findings may explain the individual differences in terms of complex sensory functions.

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality

BACKGROUND

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function.

RESULTS

Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions.

CONCLUSIONS

The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .

Expression of temperature-sensitive ion channel TRPM8 in sperm cells correlates with vertebrate evolution

Transient Receptor Potential cation channel, subfamily Melastatin, member 8 (TRPM8) is involved in detection of cold temperature, different noxious compounds and in execution of thermo- as well as chemo-sensitive responses at cellular levels. Here we explored the molecular evolution of TRPM8 by analyzing sequences from various species. We elucidate that several regions of TRPM8 had different levels of selection pressure but the 4th-5th transmembrane regions remain highly conserved. Analysis of synteny suggests that since vertebrate origin, TRPM8 gene is linked with SPP2, a bone morphogen. TRPM8, especially the N-terminal region of it, seems to be highly variable in human population. We found 16,656 TRPM8 variants in 1092 human genomes with top variations being SNPs, insertions and deletions. A total of 692 missense mutations are also mapped to human TRPM8 protein of which 509 seem to be delateroiours in nature as supported by Polyphen V2, SIFT and Grantham deviation score. Using a highly specific antibody, we demonstrate that TRPM8 is expressed endogenously in the testis of rat and sperm cells of different vertebrates ranging from fish to higher mammals. We hypothesize that TRPM8 had emerged during vertebrate evolution (ca 450 MYA). We propose that expression of TRPM8 in sperm cell and its role in regulating sperm function are important factors that have guided its molecular evolution, and that these understandings may have medical importance.

The microbiome of otitis media with effusion in Indigenous Australian children

INTRODUCTION

Indigenous Australian children have a high prevalence of otitis media with effusion (OME) and associated conductive hearing loss. Only three microbiological studies of middle ear fluid (MEF) from Indigenous Australian children with OME have been reported. All of these were reliant on culture or species-specific PCR assays. The aim of this study was to characterise the middle ear fluid (MEF), adenoid and nasopharyngeal (NP) microbiomes of Indigenous Australian children, using culture-independent 16S rRNA gene sequencing.

METHODS

MEF, NP swabs and adenoid specimens were collected from 11 children in the Alice Springs region of Central Australia. Bacterial communities in these specimens were characterised using 16S rRNA gene sequencing.

RESULTS

The microbiota in MEF samples were dominated (>50% relative abundance) by operational taxonomic units (OTUs) consistent with Alloiococcus otitidis (6/11), Haemophilus influenzae (3/11) or Streptococcus sp. (specifically, Mitis group streptococci which includes Streptococcus pneumoniae) (1/11). Anatomical site selectivity was indicated by the presence of a single conserved Haemophilus OTU in 7/11 MEF samples. In comparison, there were ten distinct Haemophilus OTUs observed across the NP and adenoid samples. Despite significant differences between the MEF and NP/adenoid microbiomes, Streptococcus sp., H. influenzae and Moraxella catarrhalis OTUs were common to all sample types. Co-occurrence of classical otopathogens in paired MEF and NP/Adenoid samples is consistent with earlier culture-based studies.

CONCLUSION

These data highlight the need to further assess H. influenzae traits important in otitis media and to understand the role of canal flora, especially A. otitidis, in populations with a high prevalence of tympanic membrane perforation.

Andrographolide: A potent antituberculosis compound that targets Aminoglycoside 2'-N-acetyltransferase in Mycobacterium tuberculosis

Tuberculosis (TB) still remains a major challenging infectious disease. The increased rate of emergence of multi-drug resistant and extensively-drug resistant strains of the organism has further complicated the situation, resulting in an urgent need for new anti-TB drugs. Antimycobacterial activity of Andrographis paniculata was evaluated using a rapid LRP assay and the probable targets were identified by docking analysis. The methanolic extract of A. paniculata showed maximum antimycobacterial activity at 250μg/ml against all the tested strains of M. tuberculosis (H37Rv, MDR, and drug sensitive). Based on bioassay guided fractionation, andrographolide was identified as the potent molecule. With the docking analysis, both ICDH (Isocitrate Dehydrogenase) and AAC (Aminoglycoside 2'-N-acetyltransferase) were predicted as targets of andrographolide in M. tuberculosis. Molecular simulation revealed that, ICDH showed low binding affinity to andrographolide. However, for AAC, the andrographolide was observed to be well within the active site after 10ns of molecular simulation. This suggests that ACC (PDB ID 1M4I) could be the probable target for andrographolide.

Improving compound-protein interaction prediction by building up highly credible negative samples

MOTIVATION

Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods.

RESULTS

This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein-protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans. We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new interactions by training an support vector machine classifier on the positive interactions annotated in DrugBank and our screened negative interactions. The screened negative samples and the predicted interactions provide the research community with a useful resource for identifying new drug targets and a helpful supplement to the current curated compound-protein databases.

AVAILABILITY

Supplementary files are available at: http://admis.fudan.edu.cn/negative-cpi/.

Mining for viral fragments in methylation enriched sequencing data

Most next generation sequencing experiments generate more data than is usable for the experimental set up. For example, methyl-CpG binding domain (MBD) affinity purification based sequencing is often used for DNA-methylation profiling, but up to 30% of the sequenced fragments cannot be mapped uniquely to the reference genome. Here we present and evaluate a methodology for the identification of viruses in these otherwise unused paired-end MBD-seq data. Viral detection is accomplished by mapping non-reference alignable reads to a comprehensive set of viral genomes. As viruses play an important role in epigenetics and cancer development, 92 (pre)malignant and benign samples, originating from two different collections of cervical samples and related cell lines, were used in this study. These samples include primary carcinomas (n = 22), low- and high-grade cervical intraepithelial neoplasia (CIN1 and CIN2/3 - n = 2/n = 30) and normal tissue (n = 20), as well as control samples (n = 17). Viruses that were detected include phages, adenoviruses, herpesviridae and HPV. HPV, which causes virtually all cervical cancers, was identified in 95% of the carcinomas, 100% of the CIN2/3 samples, both CIN1 samples and in 55% of the normal samples. Comparing the amount of mapped fragments on HPV for each HPV-infected sample yielded a significant difference between normal samples and carcinomas or CIN2/3 samples (adjusted p-values resp. <10(-5), <10(-5)), reflecting different viral loads and/or methylation degrees in non-normal samples. Fragments originating from different HPV types could be distinguished and were independently validated by PCR-based assays in 71% of the detections. In conclusion, although limited by the a priori knowledge of viral reference genome sequences, the proposed methodology can provide a first confined but substantial insight into the presence, concentration and types of methylated viral sequences in MBD-seq data at low additional cost.

Complete genome sequence of the fish pathogen Flavobacterium psychrophilum ATCC 49418(T.)

Flavobacterium psychrophilum is the causative agent of bacterial cold water disease and rainbow trout fry mortality syndrome in salmonid fishes and is associated with significant losses in the aquaculture industry. The virulence factors and molecular mechanisms of pathogenesis of F. psychrophilum are poorly understood. Moreover, at the present time, there are no effective vaccines and control using antimicrobial agents is problematic due to growing antimicrobial resistance and the fact that sick fish don't eat. In the hopes of identifying vaccine and therapeutic targets, we sequenced the genome of the type strain ATCC 49418 which was isolated from the kidney of a Coho salmon (Oncorhychus kisutch) in Washington State (U.S.A.) in 1989. The genome is 2,715,909 bp with a G+C content of 32.75%. It contains 6 rRNA operons, 49 tRNA genes, and is predicted to encode 2,329 proteins.

Predicting target-ligand interactions using protein ligand-binding site and ligand substructures

Background

Cell proliferation, differentiation, Gene expression, metabolism, immunization and signal transduction require the participation of ligands and targets. It is a great challenge to identify rules governing molecular recognition between chemical topological substructures of ligands and the binding sites of the targets.

Methods

We suppose that the ligand-target interactions are determined by ligand substructures as well as the physical-chemical properties of the binding sites. Therefore, we propose a fragment interaction model (FIM) to describe the interactions between ligands and targets, with the purpose of facilitating the chemical interpretation of ligand-target binding. First we extract target-ligand complexes from sc-PDB database, based on which, we get the target binding sites and the ligands. Then we represent each binding site as a fragment vector based on a target fragment dictionary that is composed of 199 clusters (denoted as fragements in this work) obtained by clustering 4200 trimers according to their physical-chemical properties. And then, we represent each ligand as a substructure vector based on a dictionary containing 747 substructures. Finally, we build the FIM by generating the interaction matrix M (representing the fragment interaction network), and the FIM can later be used for predicting unknown ligand-target interactions as well as providing the binding details of the interactions.

Results

The five-fold cross validation results show that the proposed model can get higher AUC score (92%) than three prevalence algorithms CS-PD (80%), BLM-NII (85%) and RF (85%), demonstrating the remarkable predictive ability of FIM. We also show that the ligand binding sites (local information) overweight the sequence similarities (global information) in ligand-target binding, and introducing too much global information would be harmful to the predictive ability. Moreover, The derived fragment interaction network can provide the chemical insights on the interactions.

Conclusions

The target and ligand bindings are local events, and the local information dominate the binding ability. Though integrating of the global information can promote the predictive ability, the role is very limited. The fragment interaction network is helpful for understanding the mechanism of the ligand-target interaction.

Differences in carbon source utilisation distinguish Campylobacter jejuni from Campylobacter coli

Background

Campylobacter jejuni and C. coli are human intestinal pathogens that are the most frequent causes of bacterial foodborne gastroenteritis in humans in the UK. In this study, we aimed to characterise the metabolic diversity of both C. jejuni and C. coli using a diverse panel of clinical strains isolated from the UK, Pakistan and Thailand, thereby representing both the developed and developing world. Our aim was to apply multi genome analysis and Biolog phenotyping to determine differences in carbon source utilisation by C. jejuni and C. coli strains.

Results

We have identified a core set of carbon sources (utilised by all strains tested) and a set that are differentially utilised for a diverse panel of thirteen C. jejuni and two C. coli strains. This study used multi genome analysis to show that propionic acid is utilised only by C. coli strains tested. A broader PCR screen of 16 C. coli strains and 42 C. jejuni confirmed the absence of the genes needed for propanoate metabolism.

Conclusions

From our analysis we have identified a phenotypic method and two genotypic methods based on propionic utilisation that might be applicable for distinguishing between C. jejuni and C. coli.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-014-0262-y) contains supplementary material, which is available to authorized users.

Identification of important nodes in directed biological networks: a network motif approach

Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA), this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC) curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.

MIPS: a calmodulin-binding protein of Gracilaria lemaneiformis under heat shock

To study the Ca(2+)/Calmodulin (CaM) signal transduction pathway of Gracilaria lemaneiformis under heat stress, myo-inositol-1-phosphate synthase (MIPS), a calmodulin-binding protein, was isolated using the yeast two-hybrid system. cDNA and DNA sequences of mips were cloned from G. lemaneiformis by using 5'RACE and genome walking procedures. The MIPS DNA sequence was 2,067 nucleotides long, containing an open reading frame (ORF) of 1,623 nucleotides with no intron. The mips ORF was predicted to encode 540 amino acids, which included the conserved MIPS domain and was 61-67 % similar to that of other species. After analyzing the amino acid sequence of MIPS, the CaM-Binding Domain (CaMBD) was inferred to be at a site spanning from amino acid 212 to amino acid 236. The yeast two-hybrid results proved that MIPS can interact with CaM and that MIPS is a type of calmodulin-binding protein. Next, the expression of CaM and MIPS in wild-type G. lemaneiformis and a heat-tolerant G. lemaneiformis cultivar, "981," were analyzed using real-time PCR under a heat shock of 32 °C. The expression level displayed a cyclical upward trend. Compared with wild type, the CaM expression levels of cultivar 981 were higher, which might directly relate to its resistance to high temperatures. This paper indicates that MIPS and CaM may play important roles in the high-temperature resistance of G. lemaneiformis.

Overview and comparison of ortholog databases

Orthologs are an indispensable bridge to transfer biological knowledge between species, from protein annotations to sophisticated disease models. However, orthology assignment is not trivial. A large number of resources now exist, each with its own idiosyncrasies. The goal of this review is to compare their contents and clarify which database is most suited for a certain task.:

MOPED 2.5--an integrated multi-omics resource: multi-omics profiling expression database now includes transcriptomics data

Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org ) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org ) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding.

In silico identification of genetic variants in glucocerebrosidase (GBA) gene involved in Gaucher's disease using multiple software tools

Gaucher's disease (GD) is an autosomal recessive disorder caused by the deficiency of glucocerebrosidase, a lysosomal enzyme that catalyses the hydrolysis of the glycolipid glucocerebroside to ceramide and glucose. Polymorphisms in GBA gene have been associated with the development of Gaucher disease. We hypothesize that prediction of SNPs using multiple state of the art software tools will help in increasing the confidence in identification of SNPs involved in GD. Enzyme replacement therapy is the only option for GD. Our goal is to use several state of art SNP algorithms to predict/address harmful SNPs using comparative studies. In this study seven different algorithms (SIFT, MutPred, nsSNP Analyzer, PANTHER, PMUT, PROVEAN, and SNPs&GO) were used to predict the harmful polymorphisms. Among the seven programs, SIFT found 47 nsSNPs as deleterious, MutPred found 46 nsSNPs as harmful. nsSNP Analyzer program found 43 out of 47 nsSNPs are disease causing SNPs whereas PANTHER found 32 out of 47 as highly deleterious, 22 out of 47 are classified as pathological mutations by PMUT, 44 out of 47 were predicted to be deleterious by PROVEAN server, all 47 shows the disease related mutations by SNPs&GO. Twenty two nsSNPs were commonly predicted by all the seven different algorithms. The common 22 targeted mutations are F251L, C342G, W312C, P415R, R463C, D127V, A309V, G46E, G202E, P391L, Y363C, Y205C, W378C, I402T, S366R, F397S, Y418C, P401L, G195E, W184R, R48W, and T43R.