Peptidomics: bridging the gap between proteome and metabolome

Studies of naturally occurring peptides and protein profiling by 'classical' proteomics are linked by common analytical objectives and methodologies. The first international workshop "Peptidomics: methods and applications" held on 6-7th September 2005 at Royal Holloway University of London confirmed that the science of peptidomics is a rapidly developing activity of high interest to both academia and industry. This meeting featured talks by over 20 leading international scientists detailing methods and typical applications, including newly-developed capabilities for protein and peptide analyses. It provided a definition of the scope of the subject in terms of current and future technologies together with applications ranging from studies of defined biological extracts to complete ecosystems. The proceedings of this meeting, speakers' contact details and other relevant information can be accessed at: www.rhul.ac.uk/biosci/meetings.     

Biodiversity: bridging the gap between condition and conservation

The aim of this study is to create a two-tiered assessment combining restoration and conservation, both needed for biodiversity management. The first tier of this approach assesses the condition of a site using a standard bioassessment method, AUSRIVAS, to determine whether significant loss of biodiversity has occurred because of human activity. The second tier assesses the conservation value of sites that were determined to be unimpacted in the first step against a reference database. This ensures maximum complementarity without having to set a priori target areas. Using the reference database, we assign site-specific and comparable coefficients for both restoration (Observed/Expected taxa with >50% probability of occurrence) and conservation values (O/E taxa with <50%, rare taxa). In a trial on 75 sites on rivers around Sydney, NSW, Australia we were able to identify three regions: (1) an area that may need restoration; (2) an area that had a high conservation value and; (3) a region that was identified as having significant biodiversity loss but with high potential to respond to rehabilitation and become a biodiversity hotspot. These examples highlight the use of the new framework as a comprehensive system for biodiversity assessment.     

Exploring the gap between dynamic and constraint-based models of metabolism

Systems biology provides new approaches for metabolic engineering through the development of models and methods for simulation and optimization of microbial metabolism. Here we explore the relationship between two modeling frameworks in common use namely, dynamic models with kinetic rate laws and constraint-based flux models. We compare and analyze dynamic and constraint-based formulations of the same model of the central carbon metabolism of Escherichia coli. Our results show that, if unconstrained, the space of steady states described by both formulations is the same. However, the imposition of parameter-range constraints can be mapped into kinetically feasible regions of the solution space for the dynamic formulation that is not readily transferable to the constraint-based formulation. Therefore, with partial kinetic parameter knowledge, dynamic models can be used to generate constraints that reduce the solution space below that identified by constraint-based models, eliminating infeasible solutions and increasing the accuracy of simulation and optimization methods.     

Livestock genomics: bridging the gap between mice and men

Dissecting the genetic control of variation in complex traits, such as disease resistance and agricultural-product quality, remains very challenging. Farm animals are now well placed to bridge the gap between human biology and traditional model species. Livestock species share with model species the benefits of controlled breeding, and their biology is often much closer to that of humans. Genetic research in model species focuses on differences between homogenous lines, whereas genetic research in humans focuses on genetic variation within populations. Livestock genetics has the strengths of both human and model-species genetics because researchers can exploit both the abundant genetic variation between divergent breeds and the variation that is segregating within breeds. Therefore, livestock genomics fills the void where the genetics of model species proves intractable or where model species are not a good proxy for human biology.     

Toward bridging the gap between life and physics

Examination of the scale properties of living organisms and the electronic configuration of crystalline structures suggests that related modeling may be used for both. This paper comments on individual and common properties of the two systems and draws a comparison between them. Both exhibit multiple ‘scales’ separated by complex or forbidden regions and a global ‘overview’ of their scale properties. We conclude that the analogy may provide a fruitful route toward extension of the modeling of both living organisms and electronic materials, by permitting bootstrapping cross-modeling between them.     

Tissue microarrays: bridging the gap between research and the clinic

Tissue microarrays are a high-throughput method for the investigation of biomarkers in multiple tissue specimens at once. This technique allows for the analysis of up to 500 tissue samples in a single experiment using immunohistochemistry and in situ hybridization. Recently, cell lines and xenografts have been reduced to a tissue microarray format and are being applied to preclinical drug development. In clinical research, tissue microarrays are applied at multiple levels: comprehensive analysis of samples in the context of a clinical trial or across a population. Tissue microarrays play a central role in translational research, facilitating the discovery of molecules that have potential roles in the diagnosis, prognosis and prediction of response to therapy.     

Tissue microarrays: bridging the gap between research and the clinic

Tissue microarrays are a high-throughput method for the investigation of biomarkers in multiple tissue specimens at once. This technique allows for the analysis of up to 500 tissue samples in a single experiment using immunohistochemistry and in situ hybridization. Recently, cell lines and xenografts have been reduced to a tissue microarray format and are being applied to preclinical drug development. In clinical research, tissue microarrays are applied at multiple levels: comprehensive analysis of samples in the context of a clinical trial or across a population. Tissue microarrays play a central role in translational research, facilitating the discovery of molecules that have potential roles in the diagnosis, prognosis and prediction of response to therapy.     

Relations as patterns: bridging the gap between OBO and OWL

Background  

Most biomedical ontologies are represented in the OBO Flatfile Format, which is an easy-to-use graph-based ontology language. The semantics of the OBO Flatfile Format 1.2 enforces a strict predetermined interpretation of relationship statements between classes. It does not allow flexible specifications that provide better approximations of the intuitive understanding of the considered relations. If relations cannot be accurately expressed then ontologies built upon them may contain false assertions and hence lead to false inferences. Ontologies in the OBO Foundry must formalize the semantics of relations according to the OBO Relationship Ontology (RO). Therefore, being able to accurately express the intended meaning of relations is of crucial importance. Since the Web Ontology Language (OWL) is an expressive language with a formal semantics, it is suitable to de ne the meaning of relations accurately.     

Self-complementarity within proteins: bridging the gap between binding and folding

Complementarity, in terms of both shape and electrostatic potential, has been quantitatively estimated at protein-protein interfaces and used extensively to predict the specific geometry of association between interacting proteins. In this work, we attempted to place both binding and folding on a common conceptual platform based on complementarity. To that end, we estimated (for the first time to our knowledge) electrostatic complementarity (Em) for residues buried within proteins. Em measures the correlation of surface electrostatic potential at protein interiors. The results show fairly uniform and significant values for all amino acids. Interestingly, hydrophobic side chains also attain appreciable complementarity primarily due to the trajectory of the main chain. Previous work from our laboratory characterized the surface (or shape) complementarity (Sm) of interior residues, and both of these measures have now been combined to derive two scoring functions to identify the native fold amid a set of decoys. These scoring functions are somewhat similar to functions that discriminate among multiple solutions in a protein-protein docking exercise. The performances of both of these functions on state-of-the-art databases were comparable if not better than most currently available scoring functions. Thus, analogously to interfacial residues of protein chains associated (docked) with specific geometry, amino acids found in the native interior have to satisfy fairly stringent constraints in terms of both Sm and Em. The functions were also found to be useful for correctly identifying the same fold for two sequences with low sequence identity. Finally, inspired by the Ramachandran plot, we developed a plot of Sm versus Em (referred to as the complementarity plot) that identifies residues with suboptimal packing and electrostatics which appear to be correlated to coordinate errors.     

Online homology modelling as a means of bridging the sequence-structure gap

For even the best-studied species, there is a large gap in their representation in the protein databank (PDB) compared to within sequence databases. Typically, less than 2% of sequences are represented in the PDB. This is partly due to the considerable experimental challenge and manual inputs required to solve three dimensional structures by methods such as X-ray diffraction and multi-dimensional nuclear magnetic resonance (NMR) spectroscopy in comparison to high-throughput sequencing. This gap is made even wider by the high level of redundancy within the PDB and under-representation of some protein categories such as membrane-associated proteins which comprise approximately 25% of proteins encoded in genomes. A traditional route to closing the sequence-structure gap is offered by homology modelling whereby the sequence of a target protein is modelled on a template represented in the PDB using in silico energy minimisation approaches. More recently, online homology servers have become available which automatically generate models from proffered sequences. However, many online servers give little indication of the structural plausibility of the generated model. In this paper, the online homology server Geno3D will be described. This server uses similar software to that used in modelling structures during structure determination and thus generates data allowing determination of the structural plausibility of models. For illustration, modelling of a chemotaxis protein (CheY) from Pseudomononas entomophila L48 (accession YP_609298) on a template (PDB id. 1mvo), the phosphorylation domain of an outer membrane protein PhoP from Bacillus subtilis, will be described.     

Archaeal primase: bridging the gap between RNA and DNA polymerases

In the evolution of life, DNA replication is a fundamental process, by which species transfer their genetic information to their offspring. DNA polymerases, including bacterial and eukaryotic replicases, are incapable of de novo DNA synthesis. DNA primases are required for this function, which is sine qua non to DNA replication. In Escherichia coli, the DNA primase (DnaG) exists as a monomer and synthesizes a short RNA primer. In Eukarya, however, the primase activity resides within the DNA polymerase alpha-primase complex (Pol alpha-pri) on the p48 subunit, which synthesizes the short RNA segment of a hybrid RNA-DNA primer. To date, very little information is available regarding the priming of DNA replication in organisms in Archaea. Available sequenced genomes indicate that the archaeal DNA primase is a homolog of the eukaryotic p48 subunit. Here, we report investigations of a p48-like DNA primase from Pyrococcus furiosus, a hyperthermophilic euryarchaeote. P. furiosus p48-like protein (Pfup41), unlike hitherto-reported primases, does not catalyze by itself the synthesis of short RNA primers but preferentially utilizes deoxynucleotides to synthesize DNA fragments up to several kilobases in length. Pfup41 is the first DNA polymerase that does not require primers for the synthesis of long DNA strands.     

Manufacturing flexibility and performance: bridging the gap between theory and practice

How firms scan and interpret their environments has implications for the flexibility strategy that they choose, as well as for the performance of that strategy. We extend Daft and Weick’s (Acad Manage Rev 9(2):284–295, 1984) model of firms as interpretation systems into a theoretical model of flexibility performance through extended iterations between observations of a failed flexibility initiative and relevant literature. We test the model using well-known teaching cases. We argue that the use of an iterative process that involves cases and theory both stimulates creativity in integrating theory and lays an initial foundation for evidence-based practice.     

Correlative microscopy: bridging the gap between fluorescence light microscopy and cryo-electron tomography

Cryo-electron tomography of frozen-hydrated biological samples offers a means of studying large and complex cellular structures in three-dimensions and with nanometer-scale resolution. The low contrast of unstained biological material embedded in amorphous ice and the need to minimise the exposure of these radiation-sensitive samples to the electron beam result in a poor signal-to-noise ratio. This poses problems not only in the visualisation and interpretation of such tomograms, it is also a problem in surveying the sample and in finding regions which contain the features of interest and which are suitable for recording tomograms. To address this problem, we have developed a correlative fluorescence light microscopy-electron microscopy approach, which guides the search for the structures of interest and allows electron microscopy to zoom in on them. With our approach, the total dose spent on locating regions of interest is negligible. A newly designed cryo-holder allows imaging of fluorescently labelled samples after vitrification. The absolute coordinates of structures identified and located by cryo-light microscopy are transferred to the electron microscope via a Matlab-based user interface. We have successfully tested the experimental setup and the whole procedure with two types of adherent fluorescently labelled cells, a neuronal cell line and keratinocytes, both grown directly on EM grids.     

Bio-Ontology and text: bridging the modeling gap

MOTIVATION: Natural language processing (NLP) techniques are increasingly being used in biology to automate the capture of new biological discoveries in text, which are being reported at a rapid rate. Yet, information represented in NLP data structures is classically very different from information organized with ontologies as found in model organisms or genetic databases. To facilitate the computational reuse and integration of information buried in unstructured text with that of genetic databases, we propose and evaluate a translational schema that represents a comprehensive set of phenotypic and genetic entities, as well as their closely related biomedical entities and relations as expressed in natural language. In addition, the schema connects different scales of biological information, and provides mappings from the textual information to existing ontologies, which are essential in biology for integration, organization, dissemination and knowledge management of heterogeneous phenotypic information. A common comprehensive representation for otherwise heterogeneous phenotypic and genetic datasets, such as the one proposed, is critical for advancing systems biology because it enables acquisition and reuse of unprecedented volumes of diverse types of knowledge and information from text. RESULTS: A novel representational schema, PGschema, was developed that enables translation of phenotypic, genetic and their closely related information found in textual narratives to a well-defined data structure comprising phenotypic and genetic concepts from established ontologies along with modifiers and relationships. Evaluation for coverage of a selected set of entities showed that 90% of the information could be represented (95% confidence interval: 86-93%; n = 268). Moreover, PGschema can be expressed automatically in an XML format using natural language techniques to process the text. To our knowledge, we are providing the first evaluation of a translational schema for NLP that contains declarative knowledge about genes and their associated biomedical data (e.g. phenotypes). AVAILABILITY: http://zellig.cpmc.columbia.edu/PGschema