Discovery Metabolomics and Lipidomics 

Discovery metabolomics, or an untargeted metabolomics approach, has been applied to many areas of science and has contributed to the understanding of mammalian and plant metabolism, identification of new natural products and detection of environmental contaminants. A common theme across these research endeavours are the analytical challenges faced – namely, that of the detection and identification of small molecules, which have subtly changed in defined experimental groups. The number and breadth of chemical compound types being measured necessitates separation prior to mass spectrometry. Long shallow gradients obtained by liquid chromatography provide excellent peak capacity. However, efficient sample throughput is also required as many samples need to be analysed to add statistical significance to the results. 

Ion mobility spectrometry (IMS) provides an orthogonal method of separation for detection and identification of components along with access to an additional measurable, physiochemical property in the form of collision cross section (CCS). Separation in the gas phase by IMS has been combined with rapid chromatography and mass spectrometry to deliver metabolomics and lipidomics with exceptional combined peak capacity, while maintaining productivity in sample to sample throughput for large phenotypic studies.

The advantage of Rapid Metabolic Microbore Profiling (RAMMP) methods is that they deliver a CCS measurement for all components detected1,2. This has been repeatably shown to aid in the identification of the compounds differentially expressed when compared to libraries of empirical or predicted values.

References

  1. A.M. King, L.G Mullin, I.D. Wilson, M. Coan, P.D. Rainville, R.S. Plumb, L.A. Gethings, G. Maker and R. Trengove. Development of a rapid profiling method for the analysis of polar analytes in urine using HILIC-MS and ion mobility enable HILIC-MS. (2019) Metabolomics. 15(2); 17.
  2. A.M. King, R.D. Trengove, L.G. Mullin, P.D. Rainville, G. Isaac, R.S. Plumb, L.A. Gethings and I.D. Wilson. Rapid profiling method for the analysis of lipids in human plasma using ion mobility enabled-reversed phase-ultra high performance liquid chromatography/mass spectrometry. (2020) J Chomatogr A. Jan 25;1611:460597.

Metabolic Profiling of Urine Samples with the SYNAPT XS High Definition (HDMS)

Discovery Proteomics

Proteomics is a field of research which looks to study the complete set of expressed proteins in an organism and how their structure, function and interactions relate to biological processes. It offers an insight to the “functional” Genome, aiming to measure the composition, modification and expression changes of the proteins produced by an organism’s genetic material. Several technologies have been developed to investigate the proteome in-depth, including gel-based approaches such as differential in-gel electrophoresis (DIGE). However, the most commonly utilized are mass spectrometry based techniques, enabling the collection of fragmentation data to provide qualitative and quantitative information. This can be a highly complex analysis which truly pushes the boundaries of liquid chromatography, high-resolution mass spectrometry and has led to important technological advances which have benefited many other applications. Traditionally, MS/MS data were collected using data directed analysis (DDA) whereby, the mass spectrometer switched on individual peptides. Limitations associated with DDA (duty cycle considerations and dynamic range) lead to the development of alternative, new methods of collecting peptide fragment data, termed data independent analysis (DIA)1-3. Integration of ion mobility into the DIA workflow has become an established method and helps overcome the limitations of DDA based methods, providing additional selectivity in addition to increasing the confidence and depth of peptide/protein identifications. 

References 

  1. E. Rodriguez-Suarez, C. Hughes, L. Gethings, K. Giles, J. Wildgoose, M. Stapels, K. E. Fadgen, S. J. Geromanos, J. P.C. Vissers, F. Elortza and J. I. Langridge. An Ion Mobility Assisted Data Independent LC-MS Strategy for the Analysis of Complex Biological Samples. (2013) Current Analytical Chemistry. 9: 199.
  2. S. J. Geromanos, C. Hughes, S. Ciavarini,  et al., Using ion purity scores for enhancing quantitative accuracy and precision in complex proteomics samples. (2012) Anal. Bioanal. Chem. 404, 1127–1139.
  3. U. Distler, J. Kuharev, P. Navarro, et al., Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics. (2014) Nat. Methods 11, 167–170.

Further reading

  1. U. Distler, J. Kuharev and S. Tenzer. Biomedical applications of ion mobility-enhanced data-independent acquisition-based label-free quantitative proteomics. (2014) Expert Review of Proteomics. 11:6, 675-684.
  2. U. Distler, J. Kuharev, P. Navarro, et al., Label-free quantification in ion mobility–enhanced data-independent acquisition proteomics. (2016) Nat. Protoc. 11, 795–812.

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