The Center for Innovative Technology (CIT) at Vanderbilt University

A state-of-the-art small molecule omics shared resource center and collaborative analytical facility specializing in a range of mass spectrometry and confocal screening techniques.

The CIT focuses on metabolomics and lipidomics analyses using a range of mass spectrometry instrumentation and provides the infrastructure and expertise to measure both untargeted (discovery) and targeted (validation, quantification) small molecules.  The Center places an emphasis on the use and development of numerous separation technologies coupled to MS including hydrophobic/hydrophilic liquid chromatography (RPLC and HILIC) and ion mobility-mass spectrometry (IM-MS). As a result, the CIT houses an array of cutting-edge instrumentation and technologies that are supported by current state-of-the-art informatics and data analysis software.

The combination of these capabilities forms the basis for the analyses of diverse biospecimen sample matrices ranging from cells, tissues, and biofluids to advanced systems such as organ-on-chip microfluidics and other 3-dimensional cell culture devices.

Further, the CIT provides several routine and advanced services that can be tailored to the goals of individual research projects. If needed, new workflows can be established for method development, targeted biomolecule measurement acquisition, and/or metabolite validation.

The goal of metabolomics is to measure the complex collection of small molecule metabolites present within a fluid, cell, or tissue. Unlike an organism’s genome, metabolomic measurements are dynamic and thus the analysis results are context dependent. Consequently, either reproducible steady state or temporal changes associated with disease state, toxicant exposure, or drug administration can be identified.

Metabolite identifications are assigned based on high mass accuracy measurements, isotope distributions, tandem mass spectrometry (MS) fragmentation patterns, and comparisons with spectral libraries and standards. Data analysis results can reveal unique biochemical fingerprints of cellular processes or responses. For this reason, results can be exploited as a 1) discovery-based approach for generating novel hypotheses or 2) used for a better understanding of physiological processes mediated by genetic or environmental perturbations.