Application of Predicted Collisional Cross Section to Metabolome Databases to Probabilistically Describe the Current and Future Ion Mobility Mass Spectrometry

Metabolomics is a
powerful phenotyping platform with potential
for high-throughput analyses. The primary technology for metabolite
profiling is mass spectrometry. In recent years, the coupling of mass
spectrometry with ion mobility spectrometry (IMS) has offered the
promise of faster analysis time and greater resolving power. Our understanding
of the potential impact of IMS on the field of metabolomics is limited
by availability of comprehensive experimental data. In this analysis,
we use a probabilistic approach to enumerate the strengths and limitations,
the present and future, of this technology. This is accomplished through
use of “model” metabolomes, predicted physicochemical
properties, and probabilistic descriptions of resolving power. This
analysis advances our understanding of the importance of orthogonality
in resolving (separation) dimensions, describes the impact of the
metabolome composition on resolution demands, and offers a system
resolution landscape that may serve to guide practitioners in the
coming years.