Browsing by Subject "ion mobility spectrometry"

Now showing 1 - 3 of 3
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    Online protein unfolding characterized by ion mobility electron capture dissociation mass spectrometry: Cytochrome C from neutral and acidic solutions
    (Springer, 2023-02) Cain, Rebecca L.; Webb, Ian K.; Chemistry and Chemical Biology, School of Science
    Electrospray ionization mass spectrometry (ESI-MS) experiments, including ion mobility spectrometry mass spectrometry (ESI-IMS-MS) and electron capture dissociation (ECD) of proteins ionized from aqueous solutions, have been used for the study of solution-like structures of intact proteins. By mixing aqueous proteins with denaturants online before ESI, the amount of protein unfolding can be precisely controlled and rapidly analyzed, permitting the characterization of protein folding intermediates in protein folding pathways. Herein, we mixed various pH solutions online with aqueous cytochrome C for unfolding and characterizing its unfolding intermediates with ESI-MS charge state distribution measurements, IMS, and ECD. The presence of folding intermediates and unfolded cytochrome c structures were detected from changes in charge states, arrival time distributions (ATDs), and ECD. We also compared structures from nondenaturing and denaturing solution mixtures measured under “gentle” (i.e., low energy) ion transmission conditions with structures measured under “harsh” (i.e., higher energy) transmission. This work confirms that when using “gentle” instrument conditions, the gas-phase cytochrome c ions reflect attributes of the various solution-phase structures. However, “harsh” conditions that maximize ion transmission produce extended structures that no longer correlate with changes in solution structure.
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    Optimization of long range potential interaction parameters in ion mobility spectrometry
    (AIP, 2018) Wu, Tianyang; Derrick, Joseph; Nahin, Minal; Chen, Xi; Larriba-Andaluz, Carlos; Mechanical Engineering, School of Engineering and Technology
    The problem of optimizing Lennard-Jones (L-J) potential parameters to perform collision cross section (CCS) calculations in ion mobility spectrometry has been undertaken. The experimental CCS of 16 small organic molecules containing carbon, hydrogen, oxygen, nitrogen, and fluoride in N2 was compared to numerical calculations using Density Functional Theory (DFT). CCS calculations were performed using the momentum transfer algorithm IMoS and a 4-6-12 potential without incorporating the ion-quadrupole potential. A ceteris paribus optimization method was used to optimize the intercept σ and potential well-depth ϵ for the given atoms. This method yields important information that otherwise would remain concealed. Results show that the optimized L-J parameters are not necessarily unique with intercept and well-depth following an exponential relation at an existing line of minimums. Similarly, the method shows that some molecules containing atoms of interest may be ill-conditioned candidates to perform optimizations of the L-J parameters. The final calculated CCSs for the chosen parameters differ 1% on average from their experimental counterparts. This result conveys the notion that DFT calculations can indeed be used as potential candidates for CCS calculations and that effects, such as the ion-quadrupole potential or diffuse scattering, can be embedded into the L-J parameters without loss of accuracy but with a large increase in computational efficiency.
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    The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes
    (Taylor & Francis, 2019-06-24) Nakayasu, Ernesto S.; Qian, Wei-Jun; Evans-Molina, Carmella; Mirmira, Raghavendra G.; Eizirik, Decio L.; Metz, Thomas O.; Pediatrics, School of Medicine
    Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.