Investigating macromolecules inside cultured and injected cells by in-cell NMR spectroscopy

The noninvasive character of NMR spectroscopy, combined with the sensitivity of the chemical shift, makes it ideally suited to investigate the conformation, binding events and dynamics of macromolecules inside living cells. These 'in-cell NMR' experiments involve labeling the macromolecule of interest with a nonradioactive but NMR-active isotope (15N or 13C). Cellular samples are prepared either by selectively overexpressing the protein in suitable cells (e.g., bacterial cells grown on isotopically labeled media), or by injecting isotopically labeled proteins directly into either cells or cell extracts. Here we provide detailed protocols for in-cell NMR experiments in the prokaryotic organism Escherichia coli, as well as eukaryotic cells and extracts employing Xenopus laevis oocytes or egg extracts. In-cell NMR samples with proteins overexpressed in E. coli can be produced within 13-14 h. Preparing Xenopus oocyte samples for in-cell NMR experiments takes 6-14 h depending on the oocyte preparation scheme and the injection method used.     

Determination of 4-amino-m-cresol and 5-amino-o-cresol by high performance liquid chromatography and fluorescence derivatization using fluorescamine

For the determination of two oxidation hair dyes, 4-amino-m-cresol (4-AC) and 5-amino-o-cresol (5-AC), a sensitive isocratic high performance liquid chromatography (HPLC) method using the reversed phase mode was developed. The hair dyes were pre-column derivatized with fluorescamine prior to injection. Sensitivity could be improved 10-fold for 4-AC and 50-fold for 5-AC by fluorescence detection compared to UV detection. The limit of detection was 1 ng/injection for 4-AC and 100 pg/injection for 5-AC, respectively. For the determination of both compounds in aqueous biological matrices in order to simulate conditions for penetration studies with pig skin, a solid phase extraction procedure using C18 cartridges and acetonitrile (ACN) for elution could be developed. Average recovery was 83.4% with a coefficient of variation (CV) of 2.64% for intra-day assay and 3.20% for inter-day assay for 5-AC and 2.89% and 3.41% for 4-AC, respectively.     

MetNet: Software to Build and Model the Biogenetic Lattice of Arabidopsis

MetNet (http://www.botany.iastate.edu/ approximately mash/metnetex/metabolicnetex.html) is publicly available software in development for analysis of genome-wide RNA, protein and metabolite profiling data. The software is designed to enable the biologist to visualize, statistically analyse and model a metabolic and regulatory network map of Arabidopsis, combined with gene expression profiling data. It contains a JAVA interface to an interactions database (MetNetDB) containing information on regulatory and metabolic interactions derived from a combination of web databases (TAIR, KEGG, BRENDA) and input from biologists in their area of expertise. FCModeler captures input from MetNetDB in a graphical form. Sub-networks can be identified and interpreted using simple fuzzy cognitive maps. FCModeler is intended to develop and evaluate hypotheses, and provide a modelling framework for assessing the large amounts of data captured by high-throughput gene expression experiments. FCModeler and MetNetDB are currently being extended to three-dimensional virtual reality display. The MetNet map, together with gene expression data, can be viewed using multivariate graphics tools in GGobi linked with the data analytic tools in R. Users can highlight different parts of the metabolic network and see the relevant expression data highlighted in other data plots. Multi-dimensional expression data can be rotated through different dimensions. Statistical analysis can be computed alongside the visual. MetNet is designed to provide a framework for the formulation of testable hypotheses regarding the function of specific genes, and in the long term provide the basis for identification of metabolic and regulatory networks that control plant composition and development.     

A panel of 20 highly variable microsatellite polymorphisms in rhesus macaques (Macaca mulatta) selected for pedigree or population genetic analysis

This paper reports 20 new microsatellite loci that are highly polymorphic in rhesus macaques (Macaca mulatta). We screened known human microsatellite loci to identify markers that are polymorphic in rhesus macaques, and then selected specific loci that show substantial levels of heterozygosity and robust, reliable amplification. The 20 loci reported here were chosen to include one highly informative microsatellite from each rhesus monkey autosomal chromosome. Fourteen of the 20 polymorphisms are tetranucleotide repeats, and all can be analyzed using standard PCR and electrophoresis procedures. These new rhesus markers have an average of 15.5 alleles per locus and average heterozygosity of 0.83. This panel of DNA polymorphisms will be useful for a variety of different genetic analyses, including pedigree testing, paternity analysis, and population genetic studies. Many of these loci are also likely to be informative in other closely related Old World monkey species.     

Flower proteome: changes in protein spectrum during the advanced stages of rose petal development

Flowering is a unique and highly programmed process, but hardly anything is known about the developmentally regulated proteome changes in petals. Here, we employed proteomic technologies to study petal development in rose (Rosa hybrida). Using two-dimensional polyacrylamide gel electrophoresis, we generated stage-specific (closed bud, mature flower and flower at anthesis) petal protein maps with ca. 1,000 unique protein spots. Expression analyses of all resolved protein spots revealed that almost 30% of them were stage-specific, with ca. 90 protein spots for each stage. Most of the proteins exhibited differential expression during petal development, whereas only ca. 6% were constitutively expressed. Eighty-two of the resolved proteins were identified by mass spectrometry and annotated. Classification of the annotated proteins into functional groups revealed energy, cell rescue, unknown function (including novel sequences) and metabolism to be the largest classes, together comprising ca. 90% of all identified proteins. Interestingly, a large number of stress-related proteins were identified in developing petals. Analyses of the expression patterns of annotated proteins and their corresponding RNAs confirmed the importance of proteome characterization.Electronic Supplementary Material Supplementary material is available for this article at