DAPNe-IBA: A new system for sub micron scale molecular speciation and quantification.

Descriptions

The University of Surrey through its Department of Chemistry and Advanced Technology Institute has been funded to provide a system for Direct Analyte Probed Nano Extraction (DAPNe), housed within the EPSRC Ion Beam Centre National Facility. Funding exists for a high resolution mass spectrometer which will be used for analysis of a range of compounds extracted from surfaces through the DAPNe process, including (but not limited to) small proteins, peptides, drugs, metabolites, explosives, lipids and amino acids. Because we will remove only a few fg of material from the surface we will need a nano spray interface and an instrument with sensitivity in the fg range. For the various applications that we have been funded for, we need an instrument with a mass resolving power in excess of 130 000, mass accuracy < 1ppm RMS (internal) and mass range up to 6 000m/z. High resolution data must be achieved without compromising sensitivity performance. The system must not require cryogenic or water cooling. The system must be a bench top instrument so that it can be cited at the end of our Tandem Accelerator beam line. The system needs to be compatible with the only other system for DAPNe at University of North Texas, which is a Thermo Scientific Orbitrap instrument. The total spend for this project funded by EPSRC is 623 964 GBP. The amount is to include all taxes, Duties and Shipping.Direct Analyte Probed Nano Extraction Mass Spectrometry (DAPNe-MS) is a method of selecting and removing a small quantity of material from a surface, using a capillary tip attached to a nano-manipulator. The extracted material is then introduced into a mass spectrometer via nano-electrospray ionisation. The technique has achieved sensitivity at the at the attogram level and is particularly suited to picking up trace materials from surfaces. Unlike imaging mass spectrometry techniques, the process of sample removal and ionisation are decoupled and there is minimal fragmentation. This provides better selectivity and opportunities for superior quantification compared with other ambient MS methods.