Waters Acquity UPLC M-Class System

The Waters Acquity UPLC M-Class System is a nano- to microscale ultra performance LC (UPLC) system rated for 15,000 psi operation. Coupled to Waters’ mass spectrometers, the system delivers the sensitivity to quantify and identify vanishingly small concentrations of key molecules.

The system is suited for a broad range of applications including proteomics, metabolic profiling, metabolite identification and pharmacokinetic studies. Its 15k psi-capable columns tap the potential of sub-2-µm particle technology, yielding fast separations, high peak capacities and good sensitivity.

The system’s internal low-volume design and redesigned fluidics minimise dispersive and adsorptive losses during a chromatographic separation. The non-reactive materials for its internal fluid pathways ensure the integrity of samples and maximise the recovery of biologically important molecules.

In order to preserve peak capacity, the system has a micro ESI probe optimised for microscale separations, along with low-dispersion flow cells that retain chromatographic resolution into the detector. The increased pressure envelope enables the system to exploit fully sub-2-µm particles in longer columns - up to 25 cm in length - resulting in fast separations and good resolution of individual chromatographic peaks.

Owing to its increased operating pressure range, the system can rapidly separate peptic peptides for MS analysis. The automated hydrogen deuterium exchange mass spectrometry (HDX-MS) system integrates all the steps of HDX-MS, from sample preparation to actual sequence determination, deuterium uptake curves and comparison plots with the company’s DynamX HDX data analysis software.

Two-dimensional LC is a strategy for dealing with sample complexity and the dynamic range of the sample’s proteins or peptides. The product streamlines 2D-LC separations with an intuitive menu-driven method set-up, standardised separation chemistries and reproducible chromatography. Innovative valving strategies increase sample throughput while maximising data quality.