Browsing by Author "Ferreira, Christina R."

Now showing 1 - 4 of 4
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    Multiple Reaction Monitoring Profiling (MRM-Profiling) of Lipids To Distinguish Strain-Level Differences in Microbial Resistance in Escherichia coli
    (ACS, 2019-09) Xie, Zhuoer; Gonzalez, L. Edwin; Ferreira, Christina R.; Vorsilak, Anna; Frabutt, Dylan; Sobreira, Tiago J. P.; Pugia, Michael; Cooks, R. Graham; Chemistry and Chemical Biology, School of Science
    The worldwide increase in antimicrobial resistance is due to antibiotic overuse in agriculture and overprescription in medicine. For appropriate and timely patient support, faster diagnosis of antimicrobial resistance is required. Current methods for bacterial identification rely on genomics and proteomics and use comparisons with databases of known strains, but the diagnostic value of metabolites and lipids has not been explored significantly. Standard mass spectrometry/chromatography methods involve multiple dilutions during sample preparation and separation. To increase the amount of chemical information acquired and the speed of analysis of lipids, multiple reaction monitoring profiling (MRM-Profiling) has been applied. The MRM-Profiling workflow includes a discovery stage and a screening stage. The discovery stage employs precursor (PREC) ion and neutral loss (NL) scans to screen representative pooled samples for functional groups associated with particular lipid classes. The information from the first stage is organized in precursor/product ion pairs, or MRMs, and the screening stage rapidly interrogates individual samples for these MRMs. In this study, we performed MRM-Profiling of lipid extracts from four different strains of Escherichia coli cultured with amoxicillin or amoxicillin/clavulanate, a β-lactam and β-lactamase inhibitor, respectively. t tests, analysis of variance and receiver operating characteristic (ROC) curves were used to determine the significance of each MRM. Principal component analysis was applied to distinguish different strains cultured under conditions that allowed or disallowed development of bacterial resistance. The results demonstrate that MRM-Profiling distinguishes the lipid profiles of resistant and nonresistant E. coli strains.
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    Multiple reaction monitoring profiling as an analytical strategy to investigate lipids in extracellular vesicles
    (Wiley, 2021) Edwards, Madison E.; De Luca, Thomas; Ferreira, Christina R.; Collins, Kimberly S.; Eadon, Michael T.; Benson, Eric A.; Sobreira, Tiago J.P.; Cooks, R. Graham; Medicine, School of Medicine
    Extracellular vesicles (EVs) convey information used in cell-to-cell interactions. Lipid analysis of EVs remains challenging because of small sample amounts available. Lipid discovery using traditional mass spectrometry platforms based on liquid chromatography and high mass resolution typically employs milligram sample amounts. We report a simple workflow for lipid profiling of EVs based on multiple reaction monitoring (MRM) profiling that uses microgram amounts of sample. After liquid-liquid extraction, individual EV samples were injected directly into the electrospray ionization (ESI) ion source at low flow rates (10 μl/min) and screened for 197 MRM transitions chosen to be a characteristic of several classes of lipids. This choice was based on a discovery experiment, which applied 1,419 MRMs associated with multiple lipid classes to a representative pooled sample. EVs isolated from 12 samples of human lymphocytes and 16 replicates from six different rat cells lines contained an estimated amount of total lipids of 326 to 805 μg. Samples showed profiles that included phosphatidylcholine (PC), sphingomyelin (SM), cholesteryl ester (CE), and ceramide (Cer) lipids, as well as acylcarnitines. The lipid profiles of human lymphocyte EVs were distinguishable using principal component and cluster analysis in terms of prior antibody and drug exposure. Lipid profiles of rat cell lines EV's were distinguishable by their tissue of origin.
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    Novel Quantification of Extracellular Vesicles with Unaltered Surface Membranes Using an Internalized Oligonucleotide Tracer and Applied Pharmacokinetic Multiple Compartment Modeling
    (Springer, 2021-10) De Luca, Thomas; Stratford, Robert E., Jr.; Edwards, Madison E.; Ferreira, Christina R.; Benson, Eric A.; Medicine, School of Medicine
    Purpose: We developed an accessible method for labeling small extracellular vesicles (sEVs) without disrupting endogenous ligands. Using labeled sEVs administered to conscious rats, we developed a multiple compartment pharmacokinetic model to identify potential differences in the disposition of sEVs from three different cell types. Methods: Crude sEVs were labeled with a non-homologous oligonucleotide and isolated from cell culture media using a commercial reagent. Jugular vein catheters were used to introduce EVs to conscious rats (n = 30) and to collect blood samples. Digital PCR was leveraged to allow for quantification over a wide dynamic range. Non-linear mixed effects analysis with first order conditional estimation - extended least squares (FOCE ELS) was used to estimate population-level parameters with associated intra-animal variability. Results: 86.5% ± 1.5% (mean ± S.E.) of EV particles were in the 45-195 nm size range and demonstrated protein and lipid markers of endosomal origin. Incorporated oligonucleotide was stable in blood and detectable over five half-lives. Data were best described by a three-compartment model with one elimination from the central compartment. We performed an observation-based simulated posterior predictive evaluation with prediction-corrected visual predictive check. Covariate and bootstrap analyses identified cell type having an influence on peripheral volumes (V2 and V3) and clearance (Cl3). Conclusions: Our method relies upon established laboratory techniques, can be tailored to a variety of biological questions regarding the pharmacokinetic disposition of extracellular vesicles, and will provide a complementary approach for the of study EV ligand-receptor interactions in the context of EV uptake and targeted therapeutics.
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    Suspect Screening of Exogenous Compounds Using Multiple Reaction Screening (MRM) Profiling in Human Urine Samples
    (Elsevier, 2022) Marasco, César A., Jr.; Edwards, Madison E.; Lamarca, Rafaela S.; Sobreira, Tiago J. P.; Caterino, Jeffrey M.; Hains, David S.; Schwaderer, Andrew L.; de Lima Gomes, Paulo C. F.; Ferreira, Christina R.; Pediatrics, School of Medicine
    Thousands of chemical compounds produced by industry are dispersed in the human environment widely enough to reach the world population, and the introduction of new chemicals constantly occurs. As new synthetic molecules emerge, rapid analytical workflows for screening possible presence of exogenous compounds in biofluids can be useful as a first pass analysis to detect chemical exposure and guide the development and application of more elaborate LC-MS/MS methods for quantification. In this study, a suspect screening workflow using the multiple reaction monitoring (MRM) profiling method is proposed as a first pass exploratory technique to survey selected exogenous molecules in human urine samples. The workflow was applied to investigate 12 human urine samples using 310 MRMs related to the chemical functionalities of 87 exogenous compounds present in the METLIN database and reported in the literature. A total of 11 MRMs associated with five different compounds were detected in the samples. Product ion scans for the precursor ions of the selected MRMs were acquired as a further identification step for these chemicals. The suspect screening results suggested the presence of five exogenous compounds in the human urine samples analyzed, namely metformin, metoprolol, acetaminophen, paraxanthine and acrylamide. LC-MS/MS was applied as a last step to confirm these results, and the presence of four out of the five targets selected by MRM profiling were corroborated, indicating that this workflow can support the selection of suspect compounds to screen complex samples and guide more time-consuming and specific quantification analyses.