An optimized gossypol high-performance liquid chromatography assay and its application in evaluation of different gland genotypes of cotton

A comparative study on gossypol content of various genetic types of pigment glands of cotton varieties was conducted through an optimized high-performance liquid chromatography (HPLC) on a C18 column (4.6 mm x 250 mm, 5 Μm particle) with methanol-0.5% acetic acid aqueous solution, 90 : 10 (v/v), as mobile phase, at a flow rate of 0.8 ml/min and UV detection at 254 nm. The method was shown to be highly reproducible, with precision [as relative standard deviation (RSD)] and accuracy [as relative mean error (RME)] < 10%, both intra-day and inter-day. Absolute recoveries were > 94%. The results revealed major differences among the different gland varieties or species of cotton, including the special and ordinary glandless and glandedGossypium hirsutum, G. barbadense, and displayed the precious resources of different glands of extraordinary cotton     

Genomic DNA extraction from<Emphasis Type="Italic">Victoria amazonica</Emphasis>

DNA extraction is difficult in many plants because of metabolites that interfere with DNA isolation procedures and subsequent applications such as DNA restriction, amplification, and cloning. We developed the first reliable and efficient method for isolatingVictoria amazonica genomic DNA that is free from polysaccharides and polyphenols. This protocol uses 1.5 M NaCl, 2% polyvinylpyrrolidone (PVP) (Mr 1000), 5% mercaptoethanol, 0.12% sodium sulfite, and an incubation at 65°C for 4 h. The purity of isolated genomic DNA was confirmed by means of high-performance liquid chromatography (HPLC) profile and spectrophotometric analyses (A_260/230 ratio of 1.836, A_260/280 of 1.842). DNA was obtained in the amount of 387 μg per gram of leaf material, and it proved amenable to restriction digestion.     

ProteomeGRID: towards a high-throughput proteomics pipeline through opportunistic cluster image computing for two-dimensional gel electrophoresis

The quest for high-throughput proteomics has revealed a number of critical issues. Whilst improved two-dimensional gel electrophoresis (2-DE) sample preparation, staining and imaging issues are being actively pursued by industry, reliable high-throughput spot matching and quantification remains a significant bottleneck in the bioinformatics pipeline, thus restricting the flow of data to mass spectrometry through robotic spot excision and protein digestion. To this end, it is important to establish a full multi-site Grid infrastructure for the processing, archival, standardisation and retrieval of proteomic data and metadata. Particular emphasis needs to be placed on large-scale image mining and statistical cross-validation for reliable, fully automated differential expression analysis, and the development of a statistical 2-DE object model and ontology that underpins the emerging HUPO PSI GPS (Human Proteome Organization Proteomics Standards Initiative General Proteomics Standards). The first step towards this goal is to overcome the computational and communications burden entailed by the image analysis of 2-DE gels with Grid enabled cluster computing. This paper presents the proTurbo framework as part of the ProteomeGRID, which utilises Condor cluster management combined with CORBA communications and JPEG-LS lossless image compression for task farming. A novel probabilistic eager scheduler has been developed to minimise make-span, where tasks are duplicated in response to the likelihood of the Condor machines' owners evicting them. A 60 gel experiment was pair-wise image registered (3540 tasks) on a 40 machine Linux cluster. Real-world performance and network overhead was gauged, and Poisson distributed worker evictions were simulated. Our results show a 4:1 lossless and 9:1 near lossless image compression ratio and so network overhead did not affect other users. With 40 workers a 32x speed-up was seen (80% resource efficiency), and the eager scheduler reduced the impact of evictions by 58%.     

A peptide preconcentration approach for nano-high-performance liquid chromatography to diminish memory effects

An advanced method has been developed for the analysis of proteolytic digests of complex protein mixtures by reversed phase high-performance liquid chromatography coupled to mass spectrometry. The occurrence of memory effects was prevented by a parallel set of two precolumns employed for simultaneous separation and washing procedures. The system was tested extensively, and tryptic digests of three single proteins were analyzed. In addition, different solvent systems were evaluated for effective washing of the employed precolumns. Using the analytical strategy presented, a reliable identification of proteins in complex mixtures was obtained and not hampered by the occurrence of memory effects.     

Photo-irradiated titanium dioxide catalyzes site specific DNA damage via generation of hydrogen peroxide

Titanium dioxide (TiO₂) is a potential photosensitizer for photodynamic therapy. In this study, the mechanism of DNA damage catalyzed by photo-irradiated TiO₂ was examined using [₃₂P]-5'-end-labeled DNA fragments obtained from human genes. Photo-irradiated TiO₂ (anatase and rutile) caused DNA cleavage frequently at the guanine residue in the presence of Cu(II) after E. coli formamidopyrimidine-DNA glycosylase treatment, and the thymine residue was also cleaved after piperidine treatment. Catalase, SOD and bathocuproine, a chelator of Cu(I), inhibited the DNA damage, suggesting the involvement of hydrogen peroxide, superoxide and Cu(I). The photocatalytic generation of Cu(I) from Cu(II) was decreased by the addition of SOD. These findings suggest that the inhibitory effect of SOD on DNA damage is due to the inhibition of the reduction of Cu(II) by superoxide. We also measured the formation of 8-oxo-7,8-dihydro-2' -deoxyguanosine, an indicator of oxidative DNA damage, and showed that anatase is more active than rutile. On the other hand, high concentration of anatase caused DNA damage in the absence of Cu(II). Typical free hydroxyl radical scavengers, such as ethanol, mannnitol, sodium formate and DMSO, inhibited the copper-independent DNA photodamage by anatase. In conclusion, photo-irradiated TiO₂ particles catalyze the copper-mediated site-specific DNA damage via the formation of hydrogen peroxide rather than that of a free hydroxyl radical. This DNA-damaging mechanism may participate in the phototoxicity of TiO₂.     

Dynamic Geographic Personal Data – New Opportunity and Challenge Introduced by the Location-Aware Mobile Networks

A new generation of mobile terminals, communicators and smartphones, designed for general public, are emerging from the mobile phone revolution. Their distinctive features include enhanced data capabilities and the ability to locate the user. These features make these new types of applications, location-based and location-aware services, suitable for mobile users. In addition to location-based information access they also provide excellent means for data collection about the mobile users themselves, yielding valuable dynamic and geographic personal data. This type of data has never been available to such an extent before. Availability of such data would result in new opportunities for potential users: in commerce, in the public sector and even for private use. It is also a great challenge to the information systems: in data collection, management and analysis. Privacy protection is maybe the most serious problem to be found in this context. The objective of this paper is to present the opportunities and challenges provided by dynamic geographic personal data in the context of emerging location-aware mobile networks. Here a new service is outlined in parallel with existing and planned location-based services. The new service, designed for collecting, managing and releasing dynamic geographic population data, is called Dynamic Geographic Data Service (DGDS).     

Automated search of natively folded protein fragments for high-throughput structure determination in structural genomics

Structural genomic projects envision almost routine protein structure determinations, which are currently imaginable only for small proteins with molecular weights below 25,000 Da. For larger proteins, structural insight can be obtained by breaking them into small segments of amino acid sequences that can fold into native structures, even when isolated from the rest of the protein. Such segments are autonomously folding units (AFU) and have sizes suitable for fast structural analyses. Here, we propose to expand an intuitive procedure often employed for identifying biologically important domains to an automatic method for detecting putative folded protein fragments. The procedure is based on the recognition that large proteins can be regarded as a combination of independent domains conserved among diverse organisms. We thus have developed a program that reorganizes the output of BLAST searches and detects regions with a large number of similar sequences. To automate the detection process, it is reduced to a simple geometrical problem of recognizing rectangular shaped elevations in a graph that plots the number of similar sequences at each residue of a query sequence. We used our program to quantitatively corroborate the premise that segments with conserved sequences correspond to domains that fold into native structures. We applied our program to a test data set composed of 99 amino acid sequences containing 150 segments with structures listed in the Protein Data Bank, and thus known to fold into native structures. Overall, the fragments identified by our program have an almost 50% probability of forming a native structure, and comparable results are observed with sequences containing domain linkers classified in SCOP. Furthermore, we verified that our program identifies AFU in libraries from various organisms, and we found a significant number of AFU candidates for structural analysis, covering an estimated 5 to 20% of the genomic databases. Altogether, these results argue that methods based on sequence similarity can be useful for dissecting large proteins into small autonomously folding domains, and such methods may provide an efficient support to structural genomics projects.     

Evaluation of 18F-labeled exendin(9-39) derivatives targeting glucagon-like peptide-1 receptor for pancreatic β-cell imaging

β-cell mass (BCM) is known to be decreased in subjects with type-2 diabetes (T2D). Quantitative analysis for BCM would be useful for understanding how T2D progresses and how BCM affects treatment efficacy and for earlier diagnosis of T2D and development of new therapeutic strategies. However, a noninvasive method to measure BCM has not yet been developed.We developed four ¹⁸F-labeled exendin(9-39) derivatives for β-cell imaging by PET: [¹⁸F]FB9-Ex(9-39), [¹⁸F]FB12-Ex(9-39), [¹⁸F]FB27-Ex(9-39), and [¹⁸F]FB40-Ex(9-39). Affinity to the glucagon-like peptide-1 receptor (GLP-1R) was evaluated with dispersed islet cells of ddY mice. Uptake of exendin(9-39) derivatives in the pancreas as well as in other organs was evaluated by a biodistribution study. Small-animal PET study was performed after injecting [¹⁸F]FB40-Ex(9-39).FB40-Ex(9-39) showed moderate affinity to the GLP-1R. Among all of the derivatives, [¹⁸F]FB40-Ex(9-39) resulted in the highest uptake of radioactivity in the pancreas 30?min after injection. Moreover, it showed significantly less radioactivity accumulated in the liver and kidney, resulting in an overall increase in the pancreas-to-organ ratio. In the PET imaging study, pancreas was visualized at 30?min after injection of [¹⁸F]FB40-Ex(9-39).[¹⁸F]FB40-Ex(9-39) met the basic requirements for an imaging probe for GLP-1R in pancreatic β-cells. Further enhancement of pancreatic uptake and specific binding to GLP-1R will lead to a clear visualization of pancreatic β-cells.