HCGene: a software tool to support the hierarchical classification of genes

SUMMARY: The R package HCGene (Hierarchical Classification of Genes) implements methods to process and analyze the Gene Ontology and the FunCat taxonomy in order to support the functional classification of genes. HCGene allows the extraction of subgraphs and subtrees related to specific biological problems, the labeling of genes and gene products with multiple and hierarchical functional classes, and the association of different types of bio-molecular data to genes for learning to predict their functions. AVAILABILITY: http://homes.dsi.unimi.it/~valenti/SW/hcgene/download/hcgene_1.0.tar.gz.     

MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence

The web server MetalDetector classifies histidine residues in proteins into one of two states (free or metal bound) and cysteines into one of three states (free, metal bound or disulfide bridged). A decision tree integrates predictions from two previously developed methods (DISULFIND and Metal Ligand Predictor). Cross-validated performance assessment indicates that our server predicts disulfide bonding state at 88.6% precision and 85.1% recall, while it identifies cysteines and histidines in transition metal-binding sites at 79.9% precision and 76.8% recall, and at 60.8% precision and 40.7% recall, respectively. AVAILABILITY: Freely available at http://metaldetector.dsi.unifi.it. SUPPLEMENTARY INFORMATION: Details and data can be found at http://metaldetector.dsi.unifi.it/help.php.     

Classification of small molecules by two- and three-dimensional decomposition kernels

MOTIVATION: Several kernel-based methods have been recently introduced for the classification of small molecules. Most available kernels on molecules are based on 2D representations obtained from chemical structures, but far less work has focused so far on the definition of effective kernels that can also exploit 3D information. RESULTS: We introduce new ideas for building kernels on small molecules that can effectively use and combine 2D and 3D information. We tested these kernels in conjunction with support vector machines for binary classification on the 60 NCI cancer screening datasets as well as on the NCI HIV data set. Our results show that 3D information leveraged by these kernels can consistently improve prediction accuracy in all datasets. AVAILABILITY: An implementation of the small molecule classifier is available from http://www.dsi.unifi.it/neural/src/3DDK.     

Disulfide connectivity prediction using recursive neural networks and evolutionary information

MOTIVATION: We focus on the prediction of disulfide bridges in proteins starting from their amino acid sequence and from the knowledge of the disulfide bonding state of each cysteine. The location of disulfide bridges is a structural feature that conveys important information about the protein main chain conformation and can therefore help towards the solution of the folding problem. Existing approaches based on weighted graph matching algorithms do not take advantage of evolutionary information. Recursive neural networks (RNN), on the other hand, can handle in a natural way complex data structures such as graphs whose vertices are labeled by real vectors, allowing us to incorporate multiple alignment profiles in the graphical representation of disulfide connectivity patterns. RESULTS: The core of the method is the use of machine learning tools to rank alternative disulfide connectivity patterns. We develop an ad-hoc RNN architecture for scoring labeled undirected graphs that represent connectivity patterns. In order to compare our algorithm with previous methods, we report experimental results on the SWISS-PROT 39 dataset. We find that using multiple alignment profiles allows us to obtain significant prediction accuracy improvements, clearly demonstrating the important role played by evolutionary information. AVAILABILITY: The Web interface of the predictor is available at http://neural.dsi.unifi.it/cysteines     

ULIXES, unravelling and exploiting Mediterranean Sea microbial diversity and ecology for xenobiotics’ and pollutants’ clean up

The civilizations in the Mediterranean Sea have deeply changed the local environment, especially with the extraction of subsurface oil and gas, their refinery and transportation. Major environmental impacts are affecting all the sides of the basin with actual and potential natural and socio-economic problems. Events like the recent BP??s oil disaster in the Gulf of Mexico would have a tremendous impact on a close basin like the Mediterranean Sea. The recently EU-funded project ULIXES (http://www.ulixes.unimi.it/) aims to unravel, categorize, catalogue, exploit and manage the microbial diversity available in the Mediterranean Sea for addressing bioremediation of polluted marine sites. The rationale of the project is based on the multiple diverse environmental niches of the Mediterranean Sea and the huge range of microorganisms inhabiting therein. Microbial consortia and their ecology, their components or products are used for designing novel pollutant- and site-tailored bioremediation approaches. ULIXES exploits microbial resource mining by the isolation of novel microorganisms as well as by novel advanced ??meta-omics?? technologies for solving pollution of three major high priority pollutant classes, petroleum hydrocarbons, chlorinated compounds and heavy metals. A network of twelve European and Southern Mediterranean partners is exploring the microbial diversity and ecology associated to a large set of polluted environmental matrices including seashore sands, lagoons, harbors and deep-sea sediments, oil tanker shipwreck sites, as well as coastal and deep sea natural sites where hydrocarbon seepages occur. The mined collections are exploited for developing novel bioremediation processes to be tested in ex situ and in situ field bioremediation trials.     

Effect of different concentrations of oxygen on expression of sigma 1 receptor and superoxide dismutases in human colon adenocarcinoma cell lines

Context: Tumor cells due to distance from capillary vessels exist in different oxygenation conditions (anoxia, hypoxia, normoxia). Changes in cell oxygenation lead to reactive oxygen species production and oxidative stress. Sigma 1 receptor (Sig1R) is postulated to be stress responding agent and superoxide dismutases (SOD1 and SOD2) are key antioxidant enzymes. It is possible that they participate in tumor cells adaptation to different concentrations of oxygen.

Objective: Evaluation of Sig1R, SOD1, and SOD2 expression in different concentrations of oxygen (1%, 10%, 21%) in colon adenocarcinoma cell lines.

Materials and methods: SW480 (primary adenocarcinoma) and SW620 (metastatic) cell lines were cultured in standard conditions in Dulbecco’s modified Eagle’s medium for 5 days, and next cultured in Hypoxic Chamber in 1% O₂, 10% O₂, 21% O₂. Number of living cells was determined by trypan blue assay. Level of mRNA for Sig1R, SOD1, and SOD2 was determined by standard PCR method. Statistical analysis was conducted using Statistica 10.1 software.

Results: We observed significant changes in expression of Sig1R, SOD1, SOD2 due to different oxygen concentrations. ANOVA analysis revealed significant interactions between studied parameters mainly in hypoxia conditions in SW480 cells and between Sig1R and SOD2 in SW620 cells. It also showed that changes in expression of studied proteins depend significantly on type of the cell line.

Conclusion: Changes of Sig1R and SOD2 expression point to mitochondria as main organelle responsible for survival of tumor cells exposed to hypoxia or oxidative stress. Studied proteins are involved in intracellular response to stress related with different concentrations of oxygen.     

A combination of bioactive and nonbioactive alkyl-peptides form a more stable nanofiber structure for differentiating neural stem cells: a molecular dynamics simulation survey

Self-assembling alkyl-peptides are important molecules due to their ability to construct nano-level structures such as nanofibers to be utilized as tissue engineering scaffolds. The bioactive epitope of FAQRVPP which acts as neural stem cells (NSCs) outgrowth inducing factor is used in nanofiber structures. Based on previous experimental studies the density and distribution pattern of the epitopes on the surface of the nanofibers plays an important role in the differentiation function efficiency. We decided to survey and compare the stability of two pre-constructed fiber structures in the forms of all-functionalized nanofiber (containing only bioactive alkyl-peptides) and distributed functionalized nanofiber (a combination of nonbioactive and bioactive alkyl-peptides with ratio 2:1). Our findings reveal that the all-functionalized fiber shows an unstable structure and is split into intermediate micelle-like structures to reduce compactness and steric hindrance of functional epitopes whereas the distributed functionalized fiber shows an integrated stable nanofiber with a more amount of beta sheets that are well-organized and oriented around the hydrophobic core. The hydrogen bonds and energy profiles of the structures indicate the role of hydrophobic interactions during the alkyl-chain core formation and the important role of electrostatic interactions and hydrogen bond network in the stability of the final structures. Finally, it seems that the possibility of the presence of intermediate structure is increased in the all-functionalized nanofiber environment, and it can reduce functional efficiency of the scaffolds. These findings can help to design more efficient nanofiber structures with different goals in scaffolds for tissue engineering. Abbreviations MD Molecular Dynamics

NSCs Neural Stem Cells

PME Particle mesh Ewald

RDF Radial Distribution Function

RG Radius of gyration

RASA Relative Accessible Surface Area

RMSD Root Mean Square Deviations

SASA Solvent Accessible Surface Area.

Communicated by Ramaswamy H. Sarma     

A proposal for a standard CORBA interface for genome maps

MOTIVATION: The scientific community urgently needs to standardize the exchange of biological data. This is helped by the use of a common protocol and the definition of shared data structures. We have based our standardization work on CORBA, a technology that has become a standard in the past years and allows interoperability between distributed objects. RESULTS: We have defined an IDL specification for genome maps and present it to the scientific community. We have implemented CORBA servers based on this IDL to distribute RHdb and HuGeMap maps. The IDL will co-evolve with the needs of the mapping community. AVAILABILITY: The standard IDL for genome maps is available at http:// corba.ebi.ac.uk/RHdb/EUCORBA/MapIDL.htm l. The IORs to browse maps from Infobiogen and EBI are at http://www.infobiogen.fr/services/Hugemap/IOR and http://corba.ebi.ac.uk/RHdb/EUCORBA/IOR CONTACT: manu@infobiogen.fr, tome@ebi.ac.uk     

MathSBML: a package for manipulating SBML-based biological models

MathSBML is a Mathematica package designed for manipulating Systems Biology Markup Language (SBML) models. It converts SBML models into Mathematica data structures and provides a platform for manipulating and evaluating these models. Once a model is read by MathSBML, it is fully compatible with standard Mathematica functions such as NDSolve (a differential-algebraic equations solver). MathSBML also provides an application programming interface for viewing, manipulating, running numerical simulations; exporting SBML models; and converting SBML models in to other formats, such as XPP, HTML and FORTRAN. By accessing the full breadth of Mathematica functionality, MathSBML is fully extensible to SBML models of any size or complexity. AVAILABILITY: Open Source (LGPL) at http://www.sbml.org and http://www.sf.net/projects/sbml     

Compression of next-generation sequencing reads aided by highly efficient de novo assembly

We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data structure is used to dramatically reduce the memory required by traditional de Bruijn graph assemblers, allowing millions of reads to be assembled very efficiently. Read sequences are then stored as positions within the assembled contigs. This is combined with statistical compression of read identifiers, quality scores, alignment information and sequences, effectively collapsing very large data sets to <15% of their original size with no loss of information. Availability: Quip is freely available under the 3-clause BSD license from http://cs.washington.edu/homes/dcjones/quip.     

The lipocalin website

We introduce a website devoted to the lipocalins. The website contains data on lipocalin structures and sequences, as well as reviewing lipocalin biology and biochemistry. Our hope is that it can act as a focus for future research into the lipocalin protein family. The website can be accessed at the following URL: http://www. jenner.ac.uk/lipocalin.htm.     

Defining 3D residue environment in protein structures using SCORPION and FORMIGA

SUMMARY: Two web-based applications to analyze amino acids three-dimensional (3D) local environment within protein structures-SCORPION and FORMIGA-are presented. SCORPION and FORMIGA produce a graphical presentation for simple statistical data showing the frequency of residue occurrence within a given sphere (defined here as the 3D contacts). The center of that sphere is placed at the Calpha and at the last heavy atom in the side chain of the selected amino acid. Further depth of detail is given in terms of a secondary structure to which the profiled amino acid belongs. Results obtained with those two applications are relevant for estimating the importance of the amino acid 3D local environment for protein folding and stability. Effectively, SCORPION and FORMIGA construct knowledge-based force fields. The difference between SCORPION and FORMIGA is in that the latter operates on protein interfaces, while the former only functions for a single protein chain. Both applications are implemented as stand-alone components of STING Millennium Suite. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS, http://trantor.bioc.columbia.edu/SMS, http://mirrors.rcsb.org/SMS, http://www.es.embnet.org/SMS and http://www.ar.embnet.org/SMS. [options: Scorpion, Formiga]     

The effects of the muscular contraction on the abdominal biomechanics: a numerical investigation

Abdominal wall biomechanics is strongly affected by muscular contraction and intra-abdominal pressure (IAP) which characterize different physiological functions and daily tasks. However, the active muscular behavior is generally not considered in current computational models of the abdominal wall. The aim of this study is to develop a numerical model mimicking muscular activation and IAP.

A three dimensional Finite Element model of a healthy abdominal wall is developed detailing the principal abdomen components reconstructed upon anatomical data and medical images. Fascial tissues, aponeuroses and linea alba are modelled as hyperelastic fiber-reinforced materials, while a three-element Hill’s model is assumed for muscles. Numerical analyses are performed increasing the IAP up to 100?mmHg and simultaneously activating the muscular structures.

The obtained abdominal behavior is compared to a similar model with same IAPs, but passive muscles conditions. Abdomen stiffness and strength are computed in regions in which hernias can potentially occur. A global stiffening of the abdominal wall is found corresponding to a low abdomen deformation and the membrane force on fascial structures is reduced by muscular contraction.

Representing active muscular contraction leads to advanced findings, otherwise membrane force results overestimated considering a purely passive behavior for the abdominal wall.     

Characterization of organophosphate pesticides in urine and home environment dust in an agricultural community

Context: Organophosphorus insecticides (OPs) have been used to control agricultural pests found in Washington state. Farmworkers (FW) have higher exposure to OP pesticides than non-farmworkers (NFW), and FW children may in turn have higher exposure than NFW children.

Objective: To examine the association between the concentration in house dust of five OPs used commonly in pome fruit orchards and the concentration in urine of dialkylphosphate metabolites (DAP), in a cohort of Hispanic FW and NFW and their children.

Methods: Parents and children participated in three data collection periods over the course of one year. Urine samples were evaluated for the DAPs characteristic of OP exposure, and dust from homes and vehicles was evaluated for intact OP residues.

Results: Geometric mean (GM) concentrations of OPs in house and vehicle dust were higher in FW households than NFW households in all agricultural seasons. GM concentration of urinary DAPs was higher for children in FW households than NFW households.

Discussion: Regression analysis found a positive association between OP residues in house dust and the children’s urinary DAPs.

Conclusions: To our knowledge, this study is the first to report an association between pesticides in house dust and their biological metabolites in urine.     

Best practice of identification and proteomic analysis of extracellular vesicles in human health and disease

Introduction: Extracellular vesicles are emerging sources of biomarkers for modern preventive and precision medicine. Extracellular vesicles in body fluids offer a unique opportunity for integrative biomarker approaches due to their complex biocargo that includes proteins, lipids, nucleic acids and metabolites. Mass spectrometry-based proteomics data suggest that a significant portion of human proteins are sorted into extracellular vesicles and amenable for biomarker discovery schemes.

Areas covered: this review focuses on key aspects of isolation, quality control and subsequent analysis of blood plasma- and conditioned medium-derived extracellular vesicle proteins, and summarizes the current state-of-the-art in the field. Furthermore, it provides introduction and guidelines for mass spectrometry-based proteomic analysis of extracellular vesicles.

Expert commentary: Comparison of newly developed isolation and purification techniques with classical ultracentrifugation-based approaches are highly recommended. It is also essential to use multiple analytical approaches to characterize the isolated extracellular vesicles prior to characterization of their biocargo. Rigor in data reproducibility, critical data analysis, awareness of potential pitfalls, standardization and benchmarking are required for extracellular vesicle research to fulfil the current expectation that these subcellular structures can become a valid source of next generation biomarkers.     

ConSSeq: a web-based application for analysis of amino acid conservation based on HSSP database and within context of structure

SUMMARY: A web-based application to analyze protein amino acids conservation-Consensus Sequence (ConSSeq) is presented. ConSSeq graphically represents information about amino acid conservation based on sequence alignments reported in homology-derived structures of proteins. Beyond the relative entropy for each position in the alignment, ConSSeq also presents the consensus sequence and information about the amino acids, which are predominant at each position of the alignment. ConSSeq is part of the STING Millennium Suite and is implemented as a Java Applet. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/consseq/, http://trantor.bioc.columbia.edu/SMS/STINGm/consseq/, http://mirrors.rcsb.org//SMS/STINGm/consseq/, http://www.es.embnet.org/SMS/STINGm/consseq/ and http://www.ar.embnet.org/SMS/STINGm/consseq/     

SWEET-DB: an attempt to create annotated data collections for carbohydrates

Complex carbohydrates are known as mediators of complex cellular events. Concerning their structural diversity, their potential of information content is several orders of magnitude higher in a short sequence than any other biological macromolecule. SWEET-DB (http://www.dkfz.de/spec2/sweetdb/) is an attempt to use modern web techniques to annotate and/or cross-reference carbohydrate-related data collections which allow glycoscientists to find important data for compounds of interest in a compact and well-structured representation. Currently, reference data taken from three data sources can be retrieved for a given carbohydrate (sub)structure. The sources are CarbBank structures and literature references (linked to NCBI PubMed service), NMR data taken from SugaBase and 3D co-ordinates generated with SWEET-II. The main purpose of SWEET-DB is to enable an easy access to all data stored for one carbohydrate structure entering a complete sequence or parts thereof. Access to SWEET-DB contents is provided with the help of separate input spreadsheets for (sub)structures, bibliographic data, general structural data like molecular weight, NMR spectra and biological data. A detailed online tutorial is available at http://www.dkfz.de/spec2/sweetdb/nar/.     

Human disease glycomics: technology advances enabling protein glycosylation analysis – part 1

Introduction: Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories.

Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells.

Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.     

STING Millennium: A web-based suite of programs for comprehensive and simultaneous analysis of protein structure and sequence

STING Millennium Suite (SMS) is a new web-based suite of programs and databases providing visualization and a complex analysis of molecular sequence and structure for the data deposited at the Protein Data Bank (PDB). SMS operates with a collection of both publicly available data (PDB, HSSP, Prosite) and its own data (contacts, interface contacts, surface accessibility). Biologists find SMS useful because it provides a variety of algorithms and validated data, wrapped-up in a user friendly web interface. Using SMS it is now possible to analyze sequence to structure relationships, the quality of the structure, nature and volume of atomic contacts of intra and inter chain type, relative conservation of amino acids at the specific sequence position based on multiple sequence alignment, indications of folding essential residue (FER) based on the relationship of the residue conservation to the intra-chain contacts and Calpha-Calpha and Cbeta-Cbeta distance geometry. Specific emphasis in SMS is given to interface forming residues (IFR)-amino acids that define the interactive portion of the protein surfaces. SMS may simultaneously display and analyze previously superimposed structures. PDB updates trigger SMS updates in a synchronized fashion. SMS is freely accessible for public data at http://www.cbi.cnptia.embrapa.br, http://mirrors.rcsb.org/SMS and http://trantor.bioc.columbia.edu/SMS.