High-resolution peptide separations using nano-LC at ultra-high pressure
We report on the optimization of nano‐LC gradient separations of proteomic samples that vary in complexity. The gradient performance limits were visualized by kinetic plots depicting the gradient time needed to achieve a certain peak capacity, while using the maximum system pressure of 80 MPa. The s...
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Published in | Journal of separation science Vol. 36; no. 7; pp. 1192 - 1199 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Weinheim
Blackwell Publishing Ltd
01.04.2013
Wiley Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | We report on the optimization of nano‐LC gradient separations of proteomic samples that vary in complexity. The gradient performance limits were visualized by kinetic plots depicting the gradient time needed to achieve a certain peak capacity, while using the maximum system pressure of 80 MPa. The selection of the optimal particle size/column length combination and corresponding gradient steepness was based on scouting the performance of 75 μm id capillary columns packed with 2, 3, and 5 μm fully porous silica C18 particles. At optimal gradient conditions, peak capacities up to 500 can be obtained within a 120 min gradient using 2 μm particle‐packed capillary columns. Separations of proteomic samples including a cytochrome c tryptic digest, a bovine serum albumin tryptic digest, a six protein mix digest, and an Escherichia coli digest are demonstrated while operating at the kinetic‐performance limit, i.e. using 2‐μm packed columns, adjusting the column length and scaling the gradient steepness according to sample complexity. Finally, good run‐to‐run retention time stability (RSD values below 0.18%) was demonstrated applying ultra‐high pressure conditions. |
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Bibliography: | istex:74D5B3171265453C19693A4B963477C238A67E4B Research Foundation Flanders - No. G.0919.09 ark:/67375/WNG-X93JS5Q4-9 ArticleID:JSSC3201 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1615-9306 1615-9314 |
DOI: | 10.1002/jssc.201201087 |