Mass spectrometry (MS), with its low sample requirement and high sensitivity, has been the predominantly used methodology for characterization and elucidation of glycan structures. However, manual interpretation of MS data is complex and tedious due to large number of product ions observed and also due to the variation in their m/z values under various experimental conditions. We present an automated tool, SimGlycan, for this purpose, which accepts raw/standard MS data files as input and characterizes the associated glycan structure with high accuracy using database searching and scoring techniques. Not only does it predict the glycan structure using an MS/MS database searching technique, but it also facilitates predicting novel glycans by drawing a glycan and mapping it onto an experimental spectrum to check the degree of proximity between the theoretical and the experimental glycans. It serves as a platform for developing advanced tools that may be used for glycopeptide identification using MS data and 3D structural analysis of glycans with a few improvements in the existing features.

INTRODUCTIONThe objective of a polymerase chain reaction (PCR) is to amplify a specific DNA segment without any nonspecific by-products. In principle, each physical and chemical component of PCR can be modified to produce a potential increase in yield, specificity, or sensitivity. Yet the most critical parameter for successful PCR is optimal primer design. A poorly designed primer can result in little or no product, due to nonspecific amplification and/or primer-dimer formation leading to reaction failure, even when all the other parameters are properly optimized. This article provides general guidelines for PCR primer design, tips for development of primer pairs for more complex applications, and advice on the development of probes for real-time PCR.

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Efficient clinical diagnosis of pathogens is important for the management of infectious diseases. Conventional methods have longer turnaround time and, in most cases, lower sensitivity. Nucleic acid-based methods for the detection of microorganisms are rapid, sensitive and are generally successful even when the culturing of microorganisms fails. Sequence-based molecular methods such as real-time PCR, microarrays, and band biosensors provide high sensitivity, rapid diagnostics, and higher specificity allowing differentiation between related strains. Although numerous chemistries are available for the molecular level identification of pathogens, the most common are qPCR and DNA microarrays. Both of these techniques have a high accuracy when used with specific primers and probes. Manual design of these primer and probes is both tedious and results in lower quality of results because of the inability to simultaneously handle multiple criteria for design. Here, we describe a program AlleleID that designs qPCR and microarray assays to identify and detect pathogens.

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