Challenges in integrating Escherichia coli molecular biology data

One key challenge in Systems Biology is to provide mechanisms to collect and integrate the necessary data to be able to meet multiple analysis requirements. Typically, biological contents are scattered over multiple data sources and there is no easy way of comparing heterogeneous data contents. This work discusses ongoing standardisation and interoperability efforts and exposes integration challenges for the model organism Escherichia coli K-12. The goal is to analyse the major obstacles faced by integration processes, suggest ways to systematically identify them, and whenever possible, propose solutions or means to assist manual curation. Integration of gene, protein and compound data was evaluated by performing comparisons over EcoCyc, KEGG, BRENDA, ChEBI, Entrez Gene and UniProt contents. Cross-links, a number of standard nomenclatures and name information supported the comparisons. Except for the gene integration scenario, in no other scenario an element of integration performed well enough to support the process by itself. Indeed, both the integration of enzyme and compound records imply considerable curation. Results evidenced that, even for a well-studied model organism, source contents are still far from being as standardized as it would be desired and metadata varies considerably from source to source. Before designing any data integration pipeline, researchers should decide on the sources that best fit the purpose of analysis and be aware of existing conflicts/inconsistencies to be able to intervene in their resolution. Moreover, they should be aware of the limits of automatic integration such that they can define the extent of necessary manual curation for each application.     

New tools and new biology: Recent miniaturized systems for molecular and cellular biology

Recent advances in applied physics and chemistry have led to the development of novel microfluidic systems. Microfluidic systems allow minute amounts of reagents to be processed using μm-scale channels and offer several advantages over conventional analytical devices for use in biological sciences: faster, more accurate and more reproducible analytical performance, reduced cell and reagent consumption, portability, and integration of functional components in a single chip. In this review, we introduce how microfluidics has been applied to biological sciences. We first present an overview of the fabrication of microfluidic systems and describe the distinct technologies available for biological research. We then present examples of microsystems used in biological sciences, focusing on applications in molecular and cellular biology.     

The evolution of molecular biology into systems biology

Systems analysis has historically been performed in many areas of biology, including ecology, developmental biology and immunology. More recently, the genomics revolution has catapulted molecular biology into the realm of systems biology. In unicellular organisms and well-defined cell lines of higher organisms, systems approaches are making definitive strides toward scientific understanding and biotechnological applications. We argue here that two distinct lines of inquiry in molecular biology have converged to form contemporary systems biology.     

The intelligence in developing systems for molecular biology

A report on the 14th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), Fortaleza, Brazil, 6-10 August 2006.     

Prospects of yeast systems biology for human health: integrating lipid, protein and energy metabolism

The yeast Saccharomyces cerevisiae is a widely used model organism for studying cell biology, metabolism, cell cycle and signal transduction. Many regulatory pathways are conserved between this yeast and humans, and it is therefore possible to study pathways that are involved in disease development in a model organism that is easy to manipulate and that allows for detailed molecular studies. Here, we briefly review pathways involved in lipid metabolism and its regulation, the regulatory network of general metabolic regulator Snf1 (and its human homologue AMPK) and the proteostasis network with its link to stress and cell death. All the mentioned pathways can be used as model systems for the study of homologous pathways in human cells and a failure in these pathways is directly linked to several human diseases such as the metabolic syndrome and neurodegeneration. We demonstrate how different yeast pathways are conserved in humans, and we discuss the possibilities of using the systems biology approach to study and compare the pathways of relevance with the objective to generate hypotheses and gain new insights.     

GTC: A web server for integrating systems biology data with web tools and desktop applications

Gaggle Tool Creator (GTC) is a web application which provides access to public annotation, interaction, orthology, and genomic data for hundreds of organisms, and enables instant analysis of the data using many popular web-based and desktop applications.     

Molecular interaction maps of bioregulatory networks: a general rubric for systems biology

A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the molecular interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the molecular interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.     

Synthetic biology: a foundation for multi-scale molecular biology

The field of synthetic biology has made rapid progress in a number of areas including method development, novel applications and community building. In seeking to make biology "engineerable," synthetic biology is increasing the accessibility of biological research to researchers of all experience levels and backgrounds. One of the underlying strengths of synthetic biology is that it may establish the framework for a rigorous bottom-up approach to studying biology starting at the DNA level. Building upon the existing framework established largely by the Registry of Standard Biological Parts, careful consideration of future goals may lead to integrated multi- scale approaches to biology. Here we describe some of the current challenges that need to be addressed or considered in detail to continue the development of synthetic biology. Specifically, discussion on the areas of elucidating biological principles, computational methods and experimental construction methodologies are presented.     

The value of high quality protein-protein interaction networks for systems biology

Protein-protein interaction (PPI) networks contain a large amount of useful information for the functional characterization of proteins and promote the understanding of the complex molecular relationships that determine the phenotype of a cell. Recently, large human interaction maps have been generated with high throughput technologies such as the yeast two-hybrid system. However, they are static and incomplete and do not provide immediate clues about the cellular processes that convert genetic information into complex phenotypes. Refined multiple-aspect PPI screening and confirmation strategies will have to be put in place to increase the validity of interaction maps. Integration of interaction data with other qualitative and quantitative information (e.g. protein expression or localization data), will be required to construct networks of protein function that reflect dynamic processes in the cell. In this way, combined PPI networks can become valuable resources for a systems-level understanding of cellular processes and complex phenotypes.     

Plant gene expression in the age of systems biology: integrating transcriptional and post-transcriptional events

The extensive mechanistic and regulatory interconnections between the various events of mRNA biogenesis are now recognized as a fundamental principle of eukaryotic gene expression, yet the specific details of the coupling between the various steps of mRNA biogenesis do differ, and sometimes dramatically, between the different kingdoms. In this review, we emphasize examples where plants must differ in this respect from other eukaryotes, and highlight a recurring trend of recruiting the conserved, versatile functional modules, which have evolved to support the general mRNA biogenesis reactions, for plant-specific functions. We also argue that elucidating the inner workings of the plant 'mRNA factory' is essential for accomplishing the ambitious goal of building the 'virtual plant'.     

Modeling molecular networks: a systems biology approach to gene function

A report on the European Science Foundation Workshop on Modeling of Molecular Networks, Granada, Spain, 11-14 June 2002.