Meta-All: a system for managing metabolic pathway information

BACKGROUND: Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. RESULTS: We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. CONCLUSION: META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at and can be downloaded free of charge and installed locally

Feasibility of an in situ measurement device for bubble size and distribution

The feasibility of in situ measurement device for bubble size and distribution was explored. A novel in situ probe measurement system, the EnviroCam™, was developed. Where possible, this probe incorporated strengths, and minimized weaknesses of historical and currently available real-time measurement methods for bubbles. The system was based on a digital, high-speed, high resolution, modular camera system, attached to a stainless steel shroud, compatible with standard Ingold ports on fermenters. Still frames and/or video were produced, capturing bubbles passing through the notch of the shroud. An LED light source was integral with the shroud. Bubbles were analyzed using customized commercially available image analysis software and standard statistical methods. Using this system, bubble sizes were measured as a function of various operating parameters (e.g., agitation rate, aeration rate) and as a function of media properties (e.g., viscosity, antifoam, cottonseed flour, and microbial/animal cell broths) to demonstrate system performance and its limitations. For selected conditions, mean bubble size changes qualitatively compared favorably with published relationships. Current instrument measurement capabilities were limited primarily to clear solutions that did not contain large numbers of overlapping bubbles

An Introductory Guide to Aligning Networks Using SANA, the Simulated Annealing Network Aligner.

Sequence alignment has had an enormous impact on our understanding of biology, evolution, and disease. The alignment of biological networks holds similar promise. Biological networks generally model interactions between biomolecules such as proteins, genes, metabolites, or mRNAs. There is strong evidence that the network topology-the "structure" of the network-is correlated with the functions performed, so that network topology can be used to help predict or understand function. However, unlike sequence comparison and alignment-which is an essentially solved problem-network comparison and alignment is an NP-complete problem for which heuristic algorithms must be used.Here we introduce SANA, the Simulated Annealing Network Aligner. SANA is one of many algorithms proposed for the arena of biological network alignment. In the context of global network alignment, SANA stands out for its speed, memory efficiency, ease-of-use, and flexibility in the arena of producing alignments between two or more networks. SANA produces better alignments in minutes on a laptop than most other algorithms can produce in hours or days of CPU time on large server-class machines. We walk the user through how to use SANA for several types of biomolecular networks

A next generation, pilot-scale continuous sterilization system for fermentation media

A new continuous sterilization system was designed, constructed, started up, and qualified for media sterilization for secondary metabolite cultivations, bioconversions, and enzyme production. An existing Honeywell Total Distributed Control 3000-based control system was extended using redundant High performance Process Manager controllers for 98 I/O (input/output) points. This new equipment was retrofitted into an industrial research fermentation pilot plant, designed and constructed in the early 1980s. Design strategies of this new continuous sterilizer system and the expanded control system are described and compared with the literature (including dairy and bio-waste inactivation applications) and the weaknesses of the prior installation for expected effectiveness. In addition, the reasoning behind selection of some of these improved features has been incorporated. Examples of enhancements adopted include sanitary heat exchanger (HEX) design, incorporation of a “flash” cooling HEX, on-line calculation of F(o) and R(o), and use of field I/O modules located near the vessel to permit low-cost addition of new instrumentation. Sterilizer performance also was characterized over the expected range of operating conditions. Differences between design and observed temperature, pressure, and other profiles were quantified and investigated

An integrated network visualization framework towards metabolic engineering applications

Background Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. Results In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. Conclusions The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.This work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project ref. COMPETE FCOMP-01-0124-FEDER-015079 and the FCT Strategic Project PEst-OE/EQB/LA0023/2013. The work of PV is funded by PhD grant ref. SFRH/BDE/51442/2011

Linking Proteins to Signaling Pathways for Experiment Design and Evaluation

Biomedical experimental work often focuses on altering the functions of selected proteins. These changes can hit signaling pathways, and can therefore unexpectedly and non-specifically affect cellular processes. We propose PathwayLinker, an online tool that can provide a first estimate of the possible signaling effects of such changes, e.g., drug or microRNA treatments. PathwayLinker minimizes the users' efforts by integrating protein-protein interaction and signaling pathway data from several sources with statistical significance tests and clear visualization. We demonstrate through three case studies that the developed tool can point out unexpected signaling bias in normal laboratory experiments and identify likely novel signaling proteins among the interactors of known drug targets. In our first case study we show that knockdown of the Caenorhabditis elegans gene cdc-25.1 (meant to avoid progeny) may globally affect the signaling system and unexpectedly bias experiments. In the second case study we evaluate the loss-of-function phenotypes of a less known C. elegans gene to predict its function. In the third case study we analyze GJA1, an anti-cancer drug target protein in human, and predict for this protein novel signaling pathway memberships, which may be sources of side effects. Compared to similar services, a major advantage of PathwayLinker is that it drastically reduces the necessary amount of manual literature searches and can be used without a computational background. PathwayLinker is available at http://PathwayLinker.org. Detailed documentation and source code are available at the website

PageMan: An interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments

BACKGROUND: Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. RESULTS: Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs. PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis. PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at . CONCLUSION: PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

Sharp bounds and normalization of Wiener-type indices

10.1371/journal.pone.0078448PLoS ONE811-POLN

Neoadjuvant concurrent chemoradiation with weekly paclitaxel and carboplatin for patients with oesophageal cancer: a phase II study

This study was performed to assess the efficacy and safety of preoperative chemoradiation consisting of carboplatin and paclitaxel and concurrent radiotherapy for patients with resectable (T2-3N0-1M0) oesophageal cancer. Treatment consisted of paclitaxel 50 mg m−2 and carboplatin AUC=2 on days 1, 8, 15, 22 and 29 and concurrent radiotherapy (41.4 Gy in 23 fractions, 5 days per week), followed by oesophagectomy. All 54 entered patients completed the chemoradiation without delay or dose-reduction. Grade 3–4 toxicities were: neutropaenia 15%, thrombocytopaenia 2%, and oesophagitis 7.5%. After completion of the chemoradiotherapy 63% had a major endoscopical response. Fifty-two patients (96%) underwent a resection. The postoperative mortality rate was 7.7%. All patients had an R0-resection. The pathological complete response rate was 25%, and an additional 36.5% had less than 10% vital residual tumour cells. At a median follow-up of 23.2 months, the median survival time has not yet been reached. The probability of disease-free survival after 30 months was 60%. In conclusion, weekly neoadjuvant paclitaxel and carboplatin with concurrent radiotherapy is a very tolerable regimen and can be given on an outpatient basis. It achieves considerable down staging and a subsequent 100% radical resection rate in this series. A phase III trial with this regimen is now ongoing