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Tagging Strategies (tagging + strategy)
Selected AbstractsProtein adsorption drastically reduces surface-enhanced Raman signal of dye moleculesJOURNAL OF RAMAN SPECTROSCOPY, Issue 9 2010Dongmao Zhang Abstract There is an increasing interest in developing surface enhancement Raman spectroscopy methods for intracellular biomolecule and for in vitro protein detection that involve dye or protein,dye conjugates. In this work, we have demonstrated that protein adsorption on silver nanoparticle (AgNP) can significantly attenuate the surface-enhanced Raman spectroscopy (SERS) signal of dye molecules in both protein/dye mixtures and protein/dye conjugates. SERS spectra of 12 protein/dye mixtures were acquired using 4 proteins [bovine serum albumin (BSA), lysozyme, trypsin, and concanavalin A] and three dyes [Rhodamine 6G, adenine, and fluorescein isothiocyanate (FITC)]. Besides the protein/dye mixtures, spectra were also obtained for the free dyes and four FITC-conjugated proteins. While no SERS signal was observed in protein/FITC mixtures or conjugates, a significantly reduced SERS intensity (up to 3 orders of magnitude) was observed for both R6G and adenine in their respective protein mixtures. Quantitative estimation of the number of dye molecules absorbed onto AgNP implied that the degree of R6G SERS signal reduction in the R6G/BSA sample is 2 to 3 orders of magnitude higher than what could be accounted for by the difference in the amount of the absorbed dyes. This finding has significant implications for both intracellular SERS analyses and in vitro protein detection using SERS tagging strategies that rely on Raman dyes as reporter molecules. Copyright © 2009 John Wiley & Sons, Ltd. [source] Quantitative DY-maleimide-based proteomic 2-DE-labeling strategies using human skin proteinsPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 18 2009Lisa Dietz Abstract Sensitive differential proteomic analysis is challenging and often limited by distinct labeling or tagging strategies. In this study, we have examined the sensitivity, linearity, and photophysical properties of novel protein labeling DY-maleimide dyes (DY-505-MAL, DY-555-MAL and DY-635-MAL). All MS compatible DY-maleimide dyes exhibited excellent emission spectra, high sensitivity, and high linearity, when applied to standard 1-DE protein analysis. Correspondingly, 2-DE analysis of DY-635-MAL or DY-505-MAL maximal-labeled human keratinocyte proteins displayed remarkably high sensitivity. Compared with a standard fluorescent protein stain, DY-635-MAL or DY-505-MAL 2-DE analysis demonstrated equally high spot quality with an overall increase in the number of spots detectable (up to threefold higher;>1000 spots/gel). However, as determined with a FLA-5100 imaging system, comparative MultiGauge, and Delta2D analysis, not all DY-maleimide dyes possessed DIGE compatible fluorescent emission properties. However, DY-505-MAL and DY-635-MAL were found to be suitable for more complex, time and gel intensive, focused multiplexing analyses. Notably , as demonstrated with allergen-stimulated human skin proteins , defined, singular DY-maleimide dye protein labeling (SDPL) allows high quality, time saving, simple, and reliable differential proteomic examination. [source] A sparse marker extension tree algorithm for selecting the best set of haplotype tagging single nucleotide polymorphismsGENETIC EPIDEMIOLOGY, Issue 4 2005Ke Hao Abstract Single nucleotide polymorphisms (SNPs) play a central role in the identification of susceptibility genes for common diseases. Recent empirical studies on human genome have revealed block-like structures, and each block contains a set of haplotype tagging SNPs (htSNPs) that capture a large fraction of the haplotype diversity. Herein, we present an innovative sparse marker extension tree (SMET) algorithm to select optimal htSNP set(s). SMET reduces the search space considerably (compared to full enumeration strategy), and therefore improves computing efficiency. We tested this algorithm on several datasets at three different genomic scales: (1) gene-wide (NOS3, CRP, IL6 PPARA, and TNF), (2) region-wide (a Whitehead Institute inflammatory bowel disease dataset and a UK Graves' disease dataset), and (3) chromosome-wide (chromosome 22) levels. SMET offers geneticists with greater flexibilities in SNP tagging than lossless methods with adjustable haplotype diversity coverage (,). In simulation studies, we found that (1) an initial sample size of 50 individuals (100 chromosomes) or more is needed for htSNP selection; (2) the SNP tagging strategy is considerably more efficient when the underlying block structure is taken into account; and (3) htSNP sets at 80,90% , are more cost-effective than the lossless sets in term of relative power, relative risk ratio estimation, and genotyping efforts. Our study suggests that the novel SMET algorithm is a valuable tool for association tests. Genet. Epidemiol. 29:336,352, 2005. © 2005 Wiley-Liss, Inc. [source] UCHL-1 gene in multiple system atrophy: A haplotype tagging approachMOVEMENT DISORDERS, Issue 10 2005Daniel G. Healy MD Abstract To date, the etiology of multiple system atrophy (MSA) has proved impenetrable. We investigated the role of genetic variation in the UCHL-1 gene in MSA and looked for the presence of disease susceptibility alleles. We determined the linkage disequilibrium structure of the gene and employed a haplotype tagging strategy with power to represent 95% of the haplotype diversity. This approach was performed using a set of tagging single nucleotide polymorphisms (SNPs) that can infer the allelic state of all the common SNPs in UCHL-1 with a high coefficient of determination. This strategy enabled us to scan across the gene and maintain the power to detect signal(s) from any potential functional variant(s). In 257 Gilman-probable or -definite MSA subjects and 1,536 controls, we did not detect a case,control frequency difference for either the tagged haplotypes or for individual tagging SNPs. This search included the S18Y variant of UCHL-1, which has been reported to be protective in Parkinson's disease. © 2005 Movement Disorder Society [source] |