28 resultados para High-throughput assay method
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
New fast liquid chromatographic and capillary zone electrophoresis methods were developed and validated for simultaneous determination of atenolol and chlortalidone in combined dose tablets. The reversed phase HPLC method was carried out on a CN LiChrosorb (R) (125 x 4 mm, 5 mu m) column. The CZE method was carried out on an uncoated fused-silica capillary of 30 cm x 75 mu m i.d. with 25 mmol L(-1) sodium tetraborate, pH 9.4. The total analysis time was <6 and <2.5 min for HPLC and CZE methods, respectively. Both methods can be used for stability studies as well.
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Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results: We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions: This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity >= 2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.
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A simple and rapid development of a stability-indicating LC method for determination of chloroquine diphosphate in the presence of its hydrolysis, oxidative and photolysis degradation products is described. Stress testing showed that chloroquine diphosphate was degraded under basic conditions and by photolytic treatment but was stable under the other stress conditions investigated. Separation of the drug from its degradation products was achieved with a Nova Pack C18 column, 0.01 M PIC B7 and acetonitrile (40:60 v/v) pH 3.6, as mobile phase. Response was linear over the range 0.08-5.70 mu g mL(-1) (r = 0.996), with limits of detection and quantification (LOD and LOQ) of 0.17 and 0.35 mu g mL(-1), respectively.
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Background: Mutations in TP53 are common events during carcinogenesis. In addition to gene mutations, several reports have focused on TP53 polymorphisms as risk factors for malignant disease. Many studies have highlighted that the status of the TP53 codon 72 polymorphism could influence cancer susceptibility. However, the results have been inconsistent and various methodological features can contribute to departures from Hardy-Weinberg equilibrium, a condition that may influence the disease risk estimates. The most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or via a separate method. Results: We developed two new genotyping methods for TP53 codon 72 polymorphism detection: Denaturing High Performance Liquid Chromatography (DHPLC) and Dot Blot hybridization. These methods were compared with Restriction Fragment Length Polymorphism (RFLP) using two different restriction enzymes. We observed high agreement among all methodologies assayed. Dot-blot hybridization and DHPLC results were more highly concordant with each other than when either of these methods was compared with RFLP. Conclusions: Although variations may occur, our results indicate that DHPLC and Dot Blot hybridization can be used as reliable screening methods for TP53 codon 72 polymorphism detection, especially in molecular epidemiologic studies, where high throughput methodologies are required.
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Conjugated linoleic acids (CLAs) are a group of linoleic acid isomers that are naturally found in food products originating from ruminants (meat and dairy). These acids have received special attention in recent years due to their potential human health benefits. Research efforts have been proposed to increase the CLA content in beef to improve public health. However, because there are more than 30 million beef cattle used each year by the American food industry, it will be necessary to ensure their content in a large number of samples. Therefore, it is important to have an inexpensive and rapid analytical method to measure CLA content in food products. Because gas chromatography (GC), a current popular method for measuring CLAs, is slow, this paper describes a nuclear magnetic resonance spectroscopy ((1)H NMR) method that is potentially >10 times faster than the GC method. Analyses show a correlation coefficient of 0.97, indicating the capacity of NMR to quantify the CLA content in beef samples. Furthermore, the method proposed herein is simple and does not require sophisticated sample preparation.
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Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.
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Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.
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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.
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Glycosylphosphatidylinositol (GPI) anchoring is a common, relevant posttranslational modification of eukaryotic surface proteins. Here, we developed a fast, simple, and highly sensitive (high attomole-low femtomole range) method that uses liquid chromatography-tandem mass spectrometry (LC-MS(n)) for the first large-scale analysis of GPI-anchored molecules (i.e., the GPIome) of a eukaryote, Trypanosoma cruzi, the etiologic agent of Chagas disease. Our genome-wise prediction analysis revealed that approximately 12% of T. cruzi genes possibly encode GPI-anchored proteins. By analyzing the GPIome of T. cruzi insect-dwelling epimastigote stage using LC-MS(n), we identified 90 GPI species, of which 79 were novel. Moreover, we determined that mucins coded by the T. cruzi small mucin-like gene (TcSMUG S) family are the major GPI-anchored proteins expressed on the epimastigote cell surface. TcSMUG S mucin mature sequences are short (56-85 amino acids) and highly O-glycosylated, and contain few proteolytic sites, therefore, less likely susceptible to proteases of the midgut of the insect vector. We propose that our approach could be used for the high throughput GPIomic analysis of other lower and higher eukaryotes. Molecular Systems Biology 7 April 2009; doi:10.1038/msb.2009.13
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Background: The incidence of venous lesions following transvenous cardiac device implantation is high. Previous implantation of temporary leads ipsilateral to the permanent devices, and a depressed left ventricular ejection fraction have been associated with an increased risk of venous lesions, though the effects of preventive strategies remain controversial. This randomized trial examined the effects of warfarin in the prevention of these complications in high-risk patients. Method: Between February 2004 and September 2007, we studied 101 adults who underwent a first cardiac device implantation, and who had a left ventricular ejection fraction <= 0.40, or a temporary pacing system ipsilateral to the permanent implant, or both. After device implantation, the patients were randomly assigned to warfarin to a target international normalized ratio of 2.0-3.5, or to placebo. Clinical and laboratory evaluations were performed regularly up to 6 months postimplant. Venous lesions were detected at 6 months by digital subtraction venography. Results: Venous obstructions of various degrees were observed in 46 of the 92 patients (50.0%) who underwent venography. The frequency of venous obstructions was 60.4% in the placebo, versus 38.6% in the warfarin group (P = 0.018), corresponding to an absolute risk reduction of 22% (relative risk = 0.63; 95% confidence interval = 0.013-0.42). Conclusions: Warfarin prophylaxis lowered the frequency of venous lesions after transvenous devices implantation in high-risk patients. (PACE 2009; 32:S247-S251)
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The gene SNRNP200 is composed of 45 exons and encodes a protein essential for pre-mRNA splicing, the 200 kDa helicase hBrr2. Two mutations in SNRNP200 have recently been associated with autosomal dominant retinitis pigmentosa (adRP), a retinal degenerative disease, in two families from China. In this work we analyzed the entire 35-Kb SNRNP200 genomic region in a cohort of 96 unrelated North American patients with adRP. To complete this large-scale sequencing project, we performed ultra high-throughput sequencing of pooled, untagged PCR products. We then validated the detected DNA changes by Sanger sequencing of individual samples from this cohort and from an additional one of 95 patients. One of the two previously known mutations (p.S1087L) was identified in 3 patients, while 4 new missense changes (p.R681C, p.R681H, p.V683L, p.Y689C) affecting highly conserved codons were identified in 6 unrelated individuals, indicating that the prevalence of SNRNP200-associated adRP is relatively high. We also took advantage of this research to evaluate the pool-and-sequence method, especially with respect to the generation of false positive and negative results. We conclude that, although this strategy can be adopted for rapid discovery of new disease-associated variants, it still requires extensive validation to be used in routine DNA screenings. (C) 2011 Wiley-Liss, Inc.
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Introduction - A large number of natural and synthetic compounds having butenolides as a core unit have been described and many of them display a wide range of biological activities. Butenolides from P. malacophyllum have presented potential antifungal activities but no specific, fast, and precise method has been developed for their determination. Objective - To develop a methodology based on micellar electrokinetic chromatography to determine butenolides in Piper species. Methodology - The extracts were analysed in an uncoated fused-silica capillaries and for the micellar system 20 mmol/L SDS, 20% (v/v) acetonitrile (ACN) and 10 mmol/L STB aqueous buffer at pH 9.2 were used. The method was validated for precision, linearity, limit of detection (LOD) and limit of quantitation (LOQ) and the standard deviations were determined from the standard errors estimated by the regression line. Results - A micellar electrokinetic chromatography (MEKC) method for determination of butenolides in extracts gave full resolution for 1 and 2. The analytical curve in the range 10.0-50.0 mu g/mL (r(2) = 0.999) provided LOD and LOQ for 1 and 2 of 2.1/6.3 and 1.1/3.5 mu g/mL, respectively. The RSD for migration times were 0.12 and 1.0% for peak area ratios with 100.0 +/- 1.4% of recovery. Conclusions - A novel high-performance MEKC method developed for the analysis of butenolides 1 and 2 in leaf extracts of P. malacophyllum allowed their quantitative determined within an analysis time shorter than 5 min and the results indicated CE to be a feasible analytical technique for the quantitative determination of butenolides in Piper extracts. Copyright (C) 2010 John Wiley & Sons, Ltd.
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A biomimetic sensor is proposed as a promising new analytical method for determination of captopril in different classes of samples. The sensor was prepared by modifying a carbon paste electrode with iron (II) phthalocyanine bis(pyridine) [FePe(dipy)] complex. Amperometric measurements in a batch analytical mode were first carried out in order to optimize the sensor response. An applied potential lower than 0.2 V vs Ag vertical bar AgCl in 0.1 mol L(-1) of TRIS buffer at pH 8.0 provided the best response, with a linear range of 2.5 x 10(-5) to 1.7 x 10(-4) mol L(-1). A detailed investigation of the selectivity of the sensor, employing seventeen other drugs, was also performed. Recovery studies were carried out using biological and environment samples in order to evaluate the sensor`s potential for use with these sample classes. Finally, the performance of the biomimetic sensor was optimized in a flow injection (FIA) system using a wall jet electrochemical cell. Under optimized flow conditions, a broad linear response range, from 5.0 x 10(-4) to 2.5 x 10(-2) mol L(-1), was obtained for captopril, with a sensitivity of 210 +/- 1 mu A L mol(-1).
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Background: The cultivar Micro-Tom (MT) is regarded as a model system for tomato genetics due to its short life cycle and miniature size. However, efforts to improve tomato genetic transformation have led to protocols dependent on the costly hormone zeatin, combined with an excessive number of steps. Results: Here we report the development of a MT near-isogenic genotype harboring the allele Rg1 (MT-Rg1), which greatly improves tomato in vitro regeneration. Regeneration was further improved in MT by including a two-day incubation of cotyledonary explants onto medium containing 0.4 mu M 1-naphthaleneacetic acid (NAA) before cytokinin treatment. Both strategies allowed the use of 5 mu M 6-benzylaminopurine (BAP), a cytokinin 100 times less expensive than zeatin. The use of MT-Rg1 and NAA pre-incubation, followed by BAP regeneration, resulted in high transformation frequencies (near 40%), in a shorter protocol with fewer steps, spanning approximately 40 days from Agrobacterium infection to transgenic plant acclimatization. Conclusions: The genetic resource and the protocol presented here represent invaluable tools for routine gene expression manipulation and high throughput functional genomics by insertional mutagenesis in tomato.
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Despite the valuable contributions of robotics and high-throughput approaches to protein crystallization, the role of an experienced crystallographer in the evaluation and rationalization of a crystallization process is still crucial to obtaining crystals suitable for X-ray diffraction measurements. In this work, the difficult task of crystallizing the flavoenzyme l-amino-acid oxidase purified from Bothrops atrox snake venom was overcome by the development of a protocol that first required the identification of a non-amorphous precipitate as a promising crystallization condition followed by the implementation of a methodology that combined crystallization in the presence of oil and seeding techniques. Crystals were obtained and a complete data set was collected to 2.3 A resolution. The crystals belonged to space group P2(1), with unit-cell parameters a = 73.64, b = 123.92, c = 105.08 A, beta = 96.03 degrees. There were four protein subunits in the asymmetric unit, which gave a Matthews coefficient V (M) of 2.12 A3 Da-1, corresponding to 42% solvent content. The structure has been solved by molecular-replacement techniques.