To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of “in-culture” experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (e.g., cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell’s metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform’s capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional “in-culture” UPLC-ESI-IM-MS experiment, further demonstrating this platform’s capabilities.
Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Chemistry, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Chemistry, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee, United States of America;Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, United States of America;Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Recommended Citation:
Christina C. Marasco,Jeffrey R. Enders,Kevin T. Seale,et al. Real-Time Cellular Exometabolome Analysis with a Microfluidic-Mass Spectrometry Platform[J]. PLOS ONE,2015-01-01,10(2)