Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/174018
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- Title
- Multidimensional protein identification technology-selected reaction monitoring improving detection and quantification for protein biomarker studies
- Related
- Analytical chemistry, Vol. 84, No. 3, (2012), p.1592-1600
- DOI
- 10.1021/ac2028485
- Publisher
- American Chemical Society
- Date
- 2012
- Author/Creator
- Krisp, Christoph
- Author/Creator
- McKay, Matthew J
- Author/Creator
- Wolters, Dirk A
- Author/Creator
- Molloy, Mark P
- Description
- The targeted analysis of proteins in complex biological samples is best achieved using selected reaction monitoring (SRM). To maximize the sensitivity of this approach, sample fractionation or enrichment is still required, particularly to detect less abundant proteins in clinically relevant biofluids. Here, we report the development of multidimensional protein identification technology (MudPIT)-SRM, taking advantage of the robust online strong cation exchange chromatography for tryptic peptide fractionation and combining it with the multiplexed, quantitative attributes of SRM. The classical MudPIT method has been modified with an in-line strategy to introduce reference peptides onto the analytical column to enable quantitation at each salt step. Applying the MudPIT-SRM approach to profile abundant plasma proteins, we demonstrated mean increases in peak areas of almost 90% compared to conventional SRM. MudPIT-SRM analyses of low abundant proteins present in human wound fluid exudates similarly demonstrated increased peak areas and enabled the detection of proteins which were below the lower limit of detection when analyzed by conventional SRM. The MudPIT-SRM method is relatively facile to conduct and offers performance advantages to enhance sensitivity for biomarker studies.
- Description
- 9 page(s)
- Resource Type
- journal article
- Organisation
- Macquarie University. Dept. of Chemistry and Biomolecular Sciences
- Organisation
- Macquarie University. Australian Proteome Analysis Facility (APAF)
- Identifier
- http://hdl.handle.net/1959.14/174018
- Identifier
- ISSN:0003-2700
- Identifier
- mq_res-ext-2-s2.0-84856747041
- Language
- eng
- Reviewed
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