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Nanocapillaries for open tubular chromatographic separations of proteins in femtoliter to picoliter samples.

ABSTRACT: We have recently examined the potential of bare nanocapillaries for free solution DNA separations and demonstrated efficiencies exceeding 10(6) theoretical plates/m. In the present work, we demonstrate the use of bare and hydroxypropylcellulose (HPC) coated open tubular nanocapillaries for protein separations. Using 1.5 microm inner diameter (i.d.) capillary columns, hydrodynamically injecting femto- to picoliter volumes of fluorescent or fluorescent dye labeled protein samples, utilizing a pneumatically pressurized chamber containing 1.0 mM sodium tetraborate solution eluent (typically 200 psi) as the pump, and performing on-column detection using a simple laser-induced fluorescence detector, we demonstrate efficiencies of close to a million theoretical plates/m while generating single digit microliter volumes of waste for a complete chromatographic run. We achieve baseline resolution for a protein mixture consisting of transferrin, alpha-lactalbumin, insulin, and alpha-2-macroglobulin.

SUBMITTER: Wang X

PROVIDER: S-EPMC2802834 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Nanocapillaries for open tubular chromatographic separations of proteins in femtoliter to picoliter samples.

Wang Xiayan X Cheng Chang C Wang Shili S Zhao Meiping M Dasgupta Purnendu K PK Liu Shaorong S

Analytical chemistry 20090901 17

We have recently examined the potential of bare nanocapillaries for free solution DNA separations and demonstrated efficiencies exceeding 10(6) theoretical plates/m. In the present work, we demonstrate the use of bare and hydroxypropylcellulose (HPC) coated open tubular nanocapillaries for protein separations. Using 1.5 microm inner diameter (i.d.) capillary columns, hydrodynamically injecting femto- to picoliter volumes of fluorescent or fluorescent dye labeled protein samples, utilizing a pneu ...[more]

PMID: 19663450

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Project description:BackgroundHigh-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination with database searching algorithms. A major problem with existing methods lies within the significant number of false positive and false negative annotations. So far, standard algorithms for protein identification do not use the information gained from separation processes usually involved in peptide analysis, such as retention time information, which are readily available from chromatographic separation of the sample. Identification can thus be improved by comparing measured retention times to predicted retention times. Current prediction models are derived from a set of measured test analytes but they usually require large amounts of training data.ResultsWe introduce a new kernel function which can be applied in combination with support vector machines to a wide range of computational proteomics problems. We show the performance of this new approach by applying it to the prediction of peptide adsorption/elution behavior in strong anion-exchange solid-phase extraction (SAX-SPE) and ion-pair reversed-phase high-performance liquid chromatography (IP-RP-HPLC). Furthermore, the predicted retention times are used to improve spectrum identifications by a p-value-based filtering approach. The approach was tested on a number of different datasets and shows excellent performance while requiring only very small training sets (about 40 peptides instead of thousands). Using the retention time predictor in our retention time filter improves the fraction of correctly identified peptide mass spectra significantly.ConclusionThe proposed kernel function is well-suited for the prediction of chromatographic separation in computational proteomics and requires only a limited amount of training data. The performance of this new method is demonstrated by applying it to peptide retention time prediction in IP-RP-HPLC and prediction of peptide sample fractionation in SAX-SPE. Finally, we incorporate the predicted chromatographic behavior in a p-value based filter to improve peptide identifications based on liquid chromatography-tandem mass spectrometry.

Dataset Information

Nanocapillaries for open tubular chromatographic separations of proteins in femtoliter to picoliter samples.

Publications

Nanocapillaries for open tubular chromatographic separations of proteins in femtoliter to picoliter samples.

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