A rational design of synthetic peptide vaccine with a built-in adjuvant. A modular approach for unambiguity.

We describe a peptide vaccine model containing a built-in adjuvant. This model used a multiple antigen peptide system (MAPS) to amplify peptide antigens and a lipoamino acid, tripalmitoyl glyceryl cysteine (P3C), as a built-in adjuvant. An 18-residue peptide antigen (B2) derived from the third variable domain (amino acid 312-329) of the glycoprotein gp120 of type I human immunodeficiency virus (HIV-1) was used in this model. This peptide antigen is a suitable target since it consists of neutralizing, T-helper, and T-cytotoxic epitopes. The peptide antigen in a tetravalent MAPS format (B2M-P3C) with a lipophilic attachment was synthesized by two routes for comparison: a direct stepwise approach and an indirect modular approach. In the stepwise approach, each residue was sequentially added to the peptide resin to give B2M-P3C and the P3C was incorporated to the side chain of a carboxyl terminal lysine as Fmoc-Lys(P3C). In the modular approach, a module containing a chloroacetylated core matrix of MAPS (M-P3C) with a carboxyl tetrapeptide bearing Lys(P3C) and a second module containing the peptide antigen B2 with a cysteine at its terminus were synthesized and purified separately, and then coupled to each other to form B2M-P3C. In the modular approach, the molecular ion of B2M-P3C was unambiguously identified by ion-spray mass spectrometry. B2M-P3C, administered in liposomes without any adjuvant such as Freund's complete adjuvant, was used to immunize mice and found to induce gp120-specific antibodies in vitro, and prime cytotoxic T lymphocytes in vivo.(ABSTRACT TRUNCATED AT 250 WORDS)     

Estimating mutual information using B-spline functions – an improved similarity measure for analysing gene expression data

Background

The information theoretic concept of mutual information provides a general framework to evaluate dependencies between variables. In the context of the clustering of genes with similar patterns of expression it has been suggested as a general quantity of similarity to extend commonly used linear measures. Since mutual information is defined in terms of discrete variables, its application to continuous data requires the use of binning procedures, which can lead to significant numerical errors for datasets of small or moderate size.

Results

In this work, we propose a method for the numerical estimation of mutual information from continuous data. We investigate the characteristic properties arising from the application of our algorithm and show that our approach outperforms commonly used algorithms: The significance, as a measure of the power of distinction from random correlation, is significantly increased. This concept is subsequently illustrated on two large-scale gene expression datasets and the results are compared to those obtained using other similarity measures.A C++ source code of our algorithm is available for non-commercial use from kloska@scienion.de upon request.

Conclusion

The utilisation of mutual information as similarity measure enables the detection of non-linear correlations in gene expression datasets. Frequently applied linear correlation measures, which are often used on an ad-hoc basis without further justification, are thereby extended.

     

Homonuclear three-dimensional NOE-NOE nuclear magnetic resonance/spectra for structure determination of proteins in solution.

The solution structures of two proteins (CMTI-I, a trypsin inhibitor from Cucurbita maxima, and hisactophilin, an actin binding protein of 118 amino acids) have been determined based on the NOE data derived solely from the homonuclear 3D NOE-NOE magnetic resonance spectroscopy. Two different approaches for extraction of the structural information from the 3D NOE-NOE experiment were tested. One approach was based on the transformation of the 3D intensities into distance constraints. In the second, and more robust approach, the 3D NOE intensities were used directly in structure calculations, without the need to transform them into distance constraints. A new 2D potential function representing the 3D NOE-NOE intensity was developed and used in the simulated annealing protocol. For CMTI-I, a comparison between structures determined with the 3D NOE-NOE method and various 2D NOE approaches was carried out. The 3D data set allowed better definition of the structures than was previously possible with the 2D NOE procedures that used the isolated two-spin approximation to derive distance information.     

Recovering ensembles of chromatin conformations from contact probabilities

The 3D higher order organization of chromatin within the nucleus of eukaryotic cells has so far remained elusive. A wealth of relevant information, however, is increasingly becoming available from chromosome conformation capture (3C) and related experimental techniques, which measure the probabilities of contact between large numbers of genomic sites in fixed cells. Such contact probabilities (CPs) can in principle be used to deduce the 3D spatial organization of chromatin. Here, we propose a computational method to recover an ensemble of chromatin conformations consistent with a set of given CPs. Compared with existing alternatives, this method does not require conversion of CPs to mean spatial distances. Instead, we estimate CPs by simulating a physically realistic, bead-chain polymer model of the 30-nm chromatin fiber. We then use an approach from adaptive filter theory to iteratively adjust the parameters of this polymer model until the estimated CPs match the given CPs. We have validated this method against reference data sets obtained from simulations of test systems with up to 45 beads and 4 loops. With additional testing against experiments and with further algorithmic refinements, our approach could become a valuable tool for researchers examining the higher order organization of chromatin.     

Determination of the three-dimensional structure of oligosaccharides in the solid state from experimental 13C NMR data and ab initio chemical shift surfaces

A novel method for the determination of the three-dimensional (3D) structure of oligosaccharides in the solid state using experimental 13C NMR data is presented. The approach employs this information, combined with 13C chemical shift surfaces (CSSs) for the glycosidic bond carbons in the generation of NMR pseudopotential energy functions suitable for use as constraints in molecular modeling simulations. Application of the method to trehalose, cellobiose, and cellotetraose produces 3D models that agree remarkably well with the reported X-ray structures, with phi and psi dihedral angles that are within 10 degrees from the ones observed in the crystals. The usefulness of the approach is further demonstrated in the determination of the 3D structure of the cellohexaose, an hexasaccharide for which no X-ray data has been reported, as well as in the generation of accurate structural models for cellulose II and amylose V6.     

Influence of statistical estimators of mutual information and data heterogeneity on the inference of gene regulatory networks

The inference of gene regulatory networks from gene expression data is a difficult problem because the performance of the inference algorithms depends on a multitude of different factors. In this paper we study two of these. First, we investigate the influence of discrete mutual information (MI) estimators on the global and local network inference performance of the C3NET algorithm. More precisely, we study 4 different MI estimators (Empirical, Miller-Madow, Shrink and Schürmann-Grassberger) in combination with 3 discretization methods (equal frequency, equal width and global equal width discretization). We observe the best global and local inference performance of C3NET for the Miller-Madow estimator with an equal width discretization. Second, our numerical analysis can be considered as a systems approach because we simulate gene expression data from an underlying gene regulatory network, instead of making a distributional assumption to sample thereof. We demonstrate that despite the popularity of the latter approach, which is the traditional way of studying MI estimators, this is in fact not supported by simulated and biological expression data because of their heterogeneity. Hence, our study provides guidance for an efficient design of a simulation study in the context of network inference, supporting a systems approach.     

Molecular identification and functional characterization of the vitamin C transporters expressed by Sertoli cells

Vitamin C is an essential micronutrient for the development of male germ cells. In the gonad, the germ cells are isolated from the systemic circulation by the blood-testis barrier, which consists of a basal layer of Sertoli cells that communicate through an extensive array of tight junction complexes. To study the behavior of Sertoli cells as a first approach to the molecular and functional characterization of the vitamin C transporters in this barrier, we used the 42GPA9 cell line immortalized from mouse Sertoli cells. To date, there is no available information on the mechanism of vitamin C transport across the blood-testis barrier. This work describe the molecular identity of the transporters involved in vitamin C transport in these cells, which we hope will improve our understanding of how germ cells obtain vitamin C, transported from the plasma into the adluminal compartment of the seminiferous tubules. RT-PCR analyses revealed that 42GPA9 cells express both vitamin C transport systems, a finding that was confirmed by immunocytochemical and immunoblotting analysis. The kinetic assays using radioactive vitamin C revealed that both ascorbic acid (AA) transporters, SVCT1 and SVCT2, are functionally active. Moreover, the kinetic characteristics of dehydroascorbic acid (DHA) and 3-methylglucose (OMG) transport by 42GPA9 Sertoli cells correspond to facilitative hexose transporters GLUT1, GLUT2 and GLUT3 expressed in these cells. This data is consistent with the concept that Sertoli cells have the ability to take up vitamin C. It is an important finding and contributes to our knowledge of the physiology of male germ cells.     

Isotopomer analysis using GC-MS

Knowledge of the complete isotopomer distribution represents the ultimate amount of information on the labeling pattern of a metabolite. One technique for measuring the isotopomer distributions is the analysis of the multiplet intensities arising from the 13C-13C couplings in NMR spectroscopy. While this technique has proven to be very valuable in the elucidation of labeling patterns of C2 and C3 units of various amino acids, fragments larger than C3 are very difficult to measure. Another technique, GC-MS, offers a unique possibility of analyzing fragments larger than C3 and GC-MS is therefore able to give information which is complementary to the information that can be obtained from NMR spectroscopy. In this work we have developed fast, simple, and robust GC-MS methods that can be used to gain information on the labeling patterns of the amino acids in a crude biomass hydrolysate. It is shown that a combination of information obtained from these analyses and information from the NMR spectroscopy is able to yield a much more complete picture of the isotopomer distributions of the amino acids than any of the two techniques alone. The GC-MS method was used for analyzing the labeling patterns of amino acids from a batch cultivation of Penicillium chrysogenum grown on fully labeled glucose. The data from this analysis showed no signs of any significant carbon isotope effects, and the measurements can therefore be used without corrections for metabolic flux analysis.     

Topology models for 37 Saccharomyces cerevisiae membrane proteins based on C-terminal reporter fusions and predictions

We provide experimentally based topology models for 37 integral membrane proteins from Saccharomyces cerevisiae. A C-terminal fusion to a dual Suc2/His4C topology reporter has been used to determine the location of the C terminus of each protein relative to the endoplasmic reticulum membrane, and this information is used in conjunction with theoretical topology prediction methods to arrive at a final topology model. We propose that this approach may be used to produce reliable topology models on a proteome-wide scale.     

An Approach for Incorporating Information on Chemical Availability in Soils into Risk Assessment and Risk-Based Decision Making,Prepared by: The New England Environmentally Acceptable Endpoints Workgroup

A regional workgroup comprised of individuals from regulatory agencies, uni versities, and consulting companies was formed to develop an approach for incor porating information on chemical availability in soils into risk assessment and risk based decision making. The approach consists of the following decision framework for including information on chemical availability: (1) Determine the usefulness of incorporating information on bioavailability; (2) Identify information needs from a conceptual model of exposure for the site and from exposure pathways judged critical to the assessment; (3) Identify soil factors that affect bioavailability; (4) Determine the type or form of information (measures and/or models) that can be used within the risk assessment and risk management process; (5) Select methods (measures and/or models) based on the “weight of evidence” or strength of the bioavailability information they will provide and how that information will be used for risk assessment and risk based decision making; (6) Incorporate information into the risk assessment and risk based decision making. These fac tors can be integrated into existing risk based approaches for site management such as Superfund, state approaches, and the ASTM Risk Based Corrective Action Process (RBCA). Consistent with risk assessment guidance, an assessment of chemical availability in soils must consider current as well as reasonably foresee able conditions. The approach recognizes that information on chemical availabil ity is contextual and depends on the receptor and pathway. Further, the value of information depends on how well it is accepted and/or validated for use in regulatory decision making. The workgroup identified four principles for select ing methods (measures and/or models) for obtaining information on chemical availability and for evaluating information on chemical availability for use in risk assessments: (1) soil chemical relevance, (2) pathway relevance, (3) receptor relevance, and (4) acceptance of the method.     

The prediction of protein structural class using averaged chemical shifts

Knowledge of protein structural class can provide important information about its folding patterns. Many approaches have been developed for the prediction of protein structural classes. However, the information used by these approaches is primarily based on amino acid sequences. In this study, a novel method is presented to predict protein structural classes by use of chemical shift (CS) information derived from nuclear magnetic resonance spectra. Firstly, 399 non-homologue (about 15% identity) proteins were constructed to investigate the distribution of averaged CS values of six nuclei ((13)CO, (13)Cα, (13)Cβ, (1)HN, (1)Hα and (15)N) in three protein structural classes. Subsequently, support vector machine was proposed to predict three protein structural classes by using averaged CS information of six nuclei. Overall accuracy of jackknife cross-validation achieves 87.0%. Finally, the feature selection technique is applied to exclude redundant information and find out an optimized feature set. Results show that the overall accuracy increased to 88.0% by using the averaged CSs of (13)CO, (1)Hα and (15)N. The proposed approach outperformed other state-of-the-art methods in terms of predictive accuracy in particular for low-similarity protein data. We expect that our proposed approach will be an excellent alternative to traditional methods for protein structural class prediction.     

Strategy tool trial for office furniture

Purpose

A strategic product development tool combining REACH and environmental and financial factors was previously developed for a coatings company. This paper presents results from refining this tool for an office furniture company, using life cycle assessment (LCA)-based environmental information, addressing the research questions: ? Is it possible to combine information from REACH with the LCA approach to provide useful information for a furniture producer in their environmental product development process? ? Does the approach developed for substances in mixtures need to be adapted for articles? ? Is there a correlation between energy consumption and the environmental impacts analysed? ? Will product designers get the same information independent of the environmental impact category used? ?C Will the strategy tool indicate the same ranking of products for all environmental impacts? ?C Does REACH information indicate the same set of priorities as those arising from LCA environmental data alone? (Do they agree, or is there a conflict?) ? Will strategic decisions differ if different environmental indicators are in focus? The strategy tool??s purpose is to analyse company product portfolios, identifying products that need redevelopment or redesign because of issues concerning hazardous substances, or environmental performance.

Methods

The LCA data used is cradle-to-gate data from type III environmental declarations for 11 seating solutions. REACH Complexity, health hazard and environmental class indicators (based on risk phrases) are combined with financial data and LCA-based indicators. Correlations between energy consumption and environmental impact factors for these specific furniture products are investigated. Establishing any such correlations serves to simplify subsequent analysis in the product development process, by effectively reducing the number of indicators that need to be taken into consideration.

Results

Correlations between energy consumption and the environmental impacts global warming, acidification, eutrophication and heavy metals are presented. Strategy tool figures are shown for energy consumption, ozone depletion potential and photochemical oxidation potential. The results for office chairs and conference/visitor chairs are presented separately, as the two types of chairs fulfil different functions.

Conclusions

The correlation between energy consumption and certain environmental impact indicators affords a simplification of the product development process, since energy consumption can be used as a reasonable proxy for these indicators in this specific case. The results support acknowledged principles of Ecodesign. Energy and materials minimization improves environmental performance??higher recycled material content and proportion of renewable energy resources are also beneficial. Designers have to consider multiple aspects in parallel and the strategy tool is useful for this purpose; the furniture producer has gained useful product development insight. The tool is applicable for strategic choice of products for development or redesign that can be useful across many business sectors.     

Quantitative milk proteomics – Host responses to lipopolysaccharide‐mediated inflammation of bovine mammary gland

Intramammary infusion of lipopolysaccharide (LPS) in cows induces udder inflammation that partly simulates mastitis caused by infection with Gram‐negative bacteria. We have used this animal model to characterize the quantitiative response in the milk proteome during the time course before and immediately after the LPS challenge. Milk samples from three healthy cows collected 3 h before the LPS challenge were compared with milk samples collected 4 and 7 h after the LPS challenge, making it possible to describe the inflammatory response of individual cows. Quantitative protein profiles were obtained for 80 milk proteins, of which 49 profiles changed significantly for the three cows during LPS challenge. New information obtained in this study includes the quantified increase of apolipoproteins and other anti‐inflammatory proteins in milk, which are important for the cow's ability to balance the immune response, and the upregulation of both complement C3 and C4 indicates that more than one complement pathway could be activated during LPS‐induced mastitis. In the future, this analytical approach may provide valuable information about the differences in the ability of individual cows to resist and recover from mastitis.     

Epistatic association mapping in homozygous crop cultivars

The genetic dissection of complex traits plays a crucial role in crop breeding. However, genetic analysis and crop breeding have heretofore been performed separately. In this study, we designed a new approach that integrates epistatic association analysis in crop cultivars with breeding by design. First, we proposed an epistatic association mapping (EAM) approach in homozygous crop cultivars. The phenotypic values of complex traits, along with molecular marker information, were used to perform EAM. In our EAM, all the main-effect quantitative trait loci (QTLs), environmental effects, QTL-by-environment interactions and QTL-by-QTL interactions were included in a full model and estimated by empirical Bayes approach. A series of Monte Carlo simulations was performed to confirm the reliability of the new method. Next, the information from all detected QTLs was used to mine novel alleles for each locus and to design elite cross combination. Finally, the new approach was adopted to dissect the genetic basis of seed length in 215 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 19 main-effect QTLs and 3 epistatic QTLs were identified, more than 10 novel alleles were mined and 3 elite parental combinations, such as Daqingdou and Zhengzhou790034, were predicted.     

Human Q and C chromosomal variations: distribution and incidence.

Chromosome preparations of 77 normal newborn babies from Grand Junction, Colorado, were stained first for G-band identification of each chromosome and subsequently stained for Q- and C-band localization. This approach permitted determination of the variation of the C region size in all chromosomes, and is the first such study reported. A total of 391 Q and C variants was described, an average of 5.08 +/- 0.23 per subject; 225 were Q varients, 166 were C variants. Q varients were distributed among seven chromosomes in the genome and among 76 of the 77 subjects. Chromosomes 3 and 4 had variable Q intensities at the centromere, and the acrocentric chromosomes, 13, 14, 15, 21, and 22, had variable Q intensities in their short arms and/or satellites. C variants, though fewer in number, were more widely distributed in the genome, with at least one variant described in each chromosome. C variants were identified in 65 of the 77 subjects. Most unique were the six pericentric inversions found in chromosome 9. Except for giant satellites, no correlations were found between Q and C variants. Q and C variants evaluated in 16 members of four families showed that in nearly every case each variant observed in a child could be demonstrated in one or both parents. It is evident from this study that the magnitude of chromosomal variation in human populations is far greater than heretofore believed. It has also been shown that the combination of Q- and C-banding procedures will yield much more information than either technique used alone and is therefore the preferred approach to many population and gene localization studies.     

Large-scale essential gene identification in Candida albicans and applications to antifungal drug discovery

Candida albicans is the primary fungal pathogen of humans. Despite the need for novel drugs to combat fungal infections [Sobel, J.D. (2000) Clin Infectious Dis 30: 652], antifungal drug discovery is currently limited by both the availability of suitable drug targets and assays to screen corresponding targets. A functional genomics approach based on the diploid C. albicans genome sequence, termed GRACETM (gene replacement and conditional expression), was used to assess gene essentiality through a combination of gene replacement and conditional gene expression. In a systematic application of this approach, we identify 567 essential genes in C. albicans. Interestingly, evaluating the conditional phenotype of all identifiable C. albicans homologues of the Saccharomyces cerevisiae essential gene set [Giaever, G., Chu, A.M., Ni, L., Connelly, C., Riles, L., Veronneau, S., et al. (2002) Nature 418: 387-391] by GRACE revealed only 61% to be essential in C. albicans, emphasizing the importance of performing such studies directly within the pathogen. Construction of this conditional mutant strain collection facilitates large-scale examination of terminal phenotypes of essential genes. This information enables preferred drug targets to be selected from the C. albicans essential gene set by phenotypic information derived both in vitro, such as cidal versus static terminal phenotypes, as well as in vivo through virulence studies using conditional strains in an animal model of infection. In addition, the combination of phenotypic and bioinformatic analyses further improves drug target selection from the C. albicans essential gene set, and their respective conditional mutant strains may be directly used as sensitive whole-cell assays for drug screening.     

Advantages of using molecular coancestry in the removal of introgressed genetic material

Background

When introgression of undesired exogenous genetic material occurs in a population intended to remain pure, actions are necessary to recover the original background. It has been shown that genome-wide information can replace pedigree information for different objectives and is a valuable tool in the fields of genetic conservation and breeding. In this simulation study, molecular information provided by 50 000 SNP was used to minimise the molecular coancestry between individuals of an admixed population and the foreign individuals that originally introgressed a native population in order to remove the exogenous DNA.

Results

This management method, which detects the ‘purest’ individuals to be used as parents for the next generation, allowed recovery of the native genetic background to a great extent in all simulated scenarios. However, it also caused an increase in inbreeding larger than expected because of the lower number of individuals selected as parents and the higher coancestry between them. In scenarios involving several introgression events the method was more efficient than in those involving a single introgression event because part of the genetic information was mixed with the native genetic material for a shorter period.

Conclusions

Genome-wide information can be used to identify the purest individuals via the minimisation of molecular coancestry between individuals of the admixed and exogenous populations. Removal of the undesired genetic material is more efficient with a molecular-based approach than with a pedigree-based approach.     

Determination of metabolic fluxes in a non-steady-state system

Estimation of fluxes through metabolic networks from redistribution patterns of (13)C has become a well developed technique in recent years. However, the approach is currently limited to systems at metabolic steady-state; dynamic changes in metabolic fluxes cannot be assessed. This is a major impediment to understanding the behaviour of metabolic networks, because steady-state is not always experimentally achievable and a great deal of information about the control hierarchy of the network can be derived from the analysis of flux dynamics. To address this issue, we have developed a method for estimating non-steady-state fluxes based on the mass-balance of mass isotopomers. This approach allows multiple mass-balance equations to be written for the change in labelling of a given metabolite pool and thereby permits over-determination of fluxes. We demonstrate how linear regression methods can be used to estimate non-steady-state fluxes from these mass balance equations. The approach can be used to calculate fluxes from both mass isotopomer and positional isotopomer labelling information and thus has general applicability to data generated from common spectrometry- or NMR-based analytical platforms. The approach is applied to a GC-MS time-series dataset of (13)C-labelling of metabolites in a heterotrophic Arabidopsis cell suspension culture. Threonine biosynthesis is used to demonstrate that non-steady-state fluxes can be successfully estimated from such data while organic acid metabolism is used to highlight some common issues that can complicate flux estimation. These include multiple pools of the same metabolite that label at different rates and carbon skeleton rearrangements.