Covalent binding of reactive estrogen metabolites to microtubular protein as a possible mechanism of aneuploidy induction and neoplastic cell transformation.

Neoplastic cell transformation induced by estrogens and some other carcinogens such as benzene appears to involve the induction of mitotic aneuploidy rather than DNA damage and point mutations. As metabolic activation may also play an important role in the mechanism of carcinogenesis of these nongenotoxic compounds, we have studied the interaction of reactive quinone metabolites of various estrogens and of benzene with the major microtubular protein, tubulin, in a cell-free system. Covalent binding of the radioactively labeled metabolites to the alpha- and beta-subunit of tubulin was found to depend on the structure of the metabolite. When the adducted tubulins were tested in vitro for their ability to polymerize to microtubules, inhibition of microtubule assembly was observed in every case, although to varying extents. It is proposed that the formation of covalent tubulin adducts may impair the formation of mitotic spindles and thus contribute to chromosomal nondisjunction and aneuploidy induction

Challenges of molecular nutrition research 6: the nutritional phenotype database to store, share and evaluate nutritional systems biology studies

The challenge of modern nutrition and health research is to identify food-based strategies promoting life-long optimal health and well-being. This research is complex because it exploits a multitude of bioactive compounds acting on an extensive network of interacting processes. Whereas nutrition research can profit enormously from the revolution in ‘omics’ technologies, it has discipline-specific requirements for analytical and bioinformatic procedures. In addition to measurements of the parameters of interest (measures of health), extensive description of the subjects of study and foods or diets consumed is central for describing the nutritional phenotype. We propose and pursue an infrastructural activity of constructing the “Nutritional Phenotype database” (dbNP). When fully developed, dbNP will be a research and collaboration tool and a publicly available data and knowledge repository. Creation and implementation of the dbNP will maximize benefits to the research community by enabling integration and interrogation of data from multiple studies, from different research groups, different countries and different—omics levels. The dbNP is designed to facilitate storage of biologically relevant, pre-processed—omics data, as well as study descriptive and study participant phenotype data. It is also important to enable the combination of this information at different levels (e.g. to facilitate linkage of data describing participant phenotype, genotype and food intake with information on study design and—omics measurements, and to combine all of this with existing knowledge). The biological information stored in the database (i.e. genetics, transcriptomics, proteomics, biomarkers, metabolomics, functional assays, food intake and food composition) is tailored to nutrition research and embedded in an environment of standard procedures and protocols, annotations, modular data-basing, networking and integrated bioinformatics. The dbNP is an evolving enterprise, which is only sustainable if it is accepted and adopted by the wider nutrition and health research community as an open source, pre-competitive and publicly available resource where many partners both can contribute and profit from its developments. We introduce the Nutrigenomics Organisation (NuGO, http://www.nugo.org) as a membership association responsible for establishing and curating the dbNP. Within NuGO, all efforts related to dbNP (i.e. usage, coordination, integration, facilitation and maintenance) will be directed towards a sustainable and federated infrastructure

Interaktion chinoider Metaboliten mit Proteinen Ein moeglicher Mechanismus fuer die Aneuploidie-Induktion durch das kanzerogene Oestrogen Diethylstilbestrol

Available from TIB Hannover: DW 5605 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

An approach to quality management in structural biology: Biophysical selection of proteins for successful crystallization

Aggregation, incorrect folding and low stability are common obstacles for protein structure determination, and are often discovered at a very late state of protein production. In many cases, however, the reasons for failure to obtain diffracting crystals remain entirely unknown. We report on the contribution of systematic biophysical characterization to the success in structural determination of human proteins of unknown fold. Routine analysis using dynamic light scattering (DLS), differential scanning calorimetry (DSC) and Fourier-transform infrared spectroscopy (FTIR) was employed to evaluate fold and stability of 263 purified protein samples (98 different human proteins). We found that FTIR-monitored temperature scanning may be used to detect incorrect folding and discovered a positive correlation between unfolding enthalpy measured with DSC and the size of small, globular proteins that may be used to estimate the quality of protein preparations. Furthermore, our work establishes that the risk of aggregation during concentration of proteins may be reduced through DLS monitoring. In summary, our study demonstrates that biophysical characterization provides an ideal tool to facilitate quality management for structural biology and many other areas of biological research

Development and evaluation of a short 24-h food list as part of a blended dietary assessment strategy in large-scale cohort studies

Background/Objectives:The validity of dietary assessment in large-scale cohort studies has been questioned. Combining data sources for the estimation of usual intake in a blended approach may enhance the validity of dietary measurement. Our objective was to develop a web-based 24-h food list for Germany to identify foods consumed during the previous 24 h and to evaluate the performance of the new questionnaire in a feasibility study.Subjects/Methods:Available data from the German National Nutrition Survey II were used to develop a finite list of food items. A total of 508 individuals were invited to fill in the 24-h food list via the Internet up to three times during a 3-6-month time period. In addition, participants were asked to evaluate the questionnaire using a brief online evaluation form.Results:In total, 246 food items were identified for the 24-h food list, reflecting >75% variation in intake of 27 nutrients and four major food groups. Among the individuals invited, 64% participated in the feasibility study. Of these, 100%, 85% and 68% of participants completed the 24-h food list one, two or three times, respectively. The average time needed to complete the questionnaire was 9 min, and its acceptability by participants was rated as high.Conclusions:The 24-h food list represents a promising new dietary assessment tool that can be used as part of a blended approach combining multiple data sources for valid estimation of usual dietary intake in large-scale cohort studies

Comparing four methods to estimate usual intake distributions

Background/Objectives: The aim of this paper was to compare methods to estimate usual intake distributions of nutrients and foods. As ‘true’ usual intake distributions are not known in practice, the comparison was carried out through a simulation study, as well as empirically, by application to data from the European Food Consumption Validation (EFCOVAL) Study in which two 24-h dietary recalls (24-HDRs) and food frequency data were collected. The methods being compared were the Iowa State University Method (ISU), National Cancer Institute Method (NCI), Multiple Source Method (MSM) and Statistical Program for Age-adjusted Dietary Assessment (SPADE). Subjects/Methods: Simulation data were constructed with varying numbers of subjects (n), different values for the Box–Cox transformation parameter (¿BC) and different values for the ratio of the within- and between-person variance (rvar). All data were analyzed with the four different methods and the estimated usual mean intake and selected percentiles were obtained. Moreover, the 2-day within-person mean was estimated as an additional ‘method’. These five methods were compared in terms of the mean bias, which was calculated as the mean of the differences between the estimated value and the known true value. The application of data from the EFCOVAL Project included calculations of nutrients (that is, protein, potassium, protein density) and foods (that is, vegetables, fruit and fish). Results: Overall, the mean bias of the ISU, NCI, MSM and SPADE Methods was small. However, for all methods, the mean bias and the variation of the bias increased with smaller sample size, higher variance ratios and with more pronounced departures from normality. Serious mean bias (especially in the 95th percentile) was seen using the NCI Method when rvar=9, ¿BC=0 and n=1000. The ISU Method and MSM showed a somewhat higher s.d. of the bias compared with NCI and SPADE Methods, indicating a larger method uncertainty. Furthermore, whereas the ISU, NCI and SPADE Methods produced unimodal density functions by definition, MSM produced distributions with ‘peaks’, when sample size was small, because of the fact that the population's usual intake distribution was based on estimated individual usual intakes. The application to the EFCOVAL data showed that all estimates of the percentiles and mean were within 5% of each other for the three nutrients analyzed. For vegetables, fruit and fish, the differences were larger than that for nutrients, but overall the sample mean was estimated reasonably. Conclusions: The four methods that were compared seem to provide good estimates of the usual intake distribution of nutrients. Nevertheless, care needs to be taken when a nutrient has a high within-person variation or has a highly skewed distribution, and when the sample size is small. As the methods offer different features, practical reasons may exist to prefer one method over the other

Comparing four methods to estimate usual intake distributions

Background/Objectives: The aim of this paper was to compare methods to estimate usual intake distributions of nutrients and foods. As ‘true’ usual intake distributions are not known in practice, the comparison was carried out through a simulation study, as well as empirically, by application to data from the European Food Consumption Validation (EFCOVAL) Study in which two 24-h dietary recalls (24-HDRs) and food frequency data were collected. The methods being compared were the Iowa State University Method (ISU), National Cancer Institute Method (NCI), Multiple Source Method (MSM) and Statistical Program for Age-adjusted Dietary Assessment (SPADE). Subjects/Methods: Simulation data were constructed with varying numbers of subjects (n), different values for the Box–Cox transformation parameter (¿BC) and different values for the ratio of the within- and between-person variance (rvar). All data were analyzed with the four different methods and the estimated usual mean intake and selected percentiles were obtained. Moreover, the 2-day within-person mean was estimated as an additional ‘method’. These five methods were compared in terms of the mean bias, which was calculated as the mean of the differences between the estimated value and the known true value. The application of data from the EFCOVAL Project included calculations of nutrients (that is, protein, potassium, protein density) and foods (that is, vegetables, fruit and fish). Results: Overall, the mean bias of the ISU, NCI, MSM and SPADE Methods was small. However, for all methods, the mean bias and the variation of the bias increased with smaller sample size, higher variance ratios and with more pronounced departures from normality. Serious mean bias (especially in the 95th percentile) was seen using the NCI Method when rvar=9, ¿BC=0 and n=1000. The ISU Method and MSM showed a somewhat higher s.d. of the bias compared with NCI and SPADE Methods, indicating a larger method uncertainty. Furthermore, whereas the ISU, NCI and SPADE Methods produced unimodal density functions by definition, MSM produced distributions with ‘peaks’, when sample size was small, because of the fact that the population's usual intake distribution was based on estimated individual usual intakes. The application to the EFCOVAL data showed that all estimates of the percentiles and mean were within 5% of each other for the three nutrients analyzed. For vegetables, fruit and fish, the differences were larger than that for nutrients, but overall the sample mean was estimated reasonably. Conclusions: The four methods that were compared seem to provide good estimates of the usual intake distribution of nutrients. Nevertheless, care needs to be taken when a nutrient has a high within-person variation or has a highly skewed distribution, and when the sample size is small. As the methods offer different features, practical reasons may exist to prefer one method over the other