IU Indianapolis ScholarWorks :: Browsing by Subject "mass spectrometry"

Browsing by Subject "mass spectrometry"

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Advances in Gas Chromatography, Thermolysis, Mass Spectrometry, and Vacuum Ultraviolet Spectrometry
(2021-05) Rael, Ashur; Goodpaster, John V.; Manicke, Nicholas E.; Naumann, Christoph A.; Minto, Robert E.
In the area of forensic chemistry, improved or new analysis methods are continually being investigated. One common and powerful technique used in forensic chemistry is wall-coated open-tubular column (WCOT) gas chromatography with electron ionization single quadrupole mass spectrometry (GC-MS). Improvements to and effectiveness of alternatives to this instrumental platform were explored in an array of parallel inquiries. The areas studied included the column for the chromatographic separation, the universal detection method employed, and the fragmentation method used to enhance molecular identification. Superfine-micropacked capillary (SFµPC) columns may provide an alternative to commercial packed GC columns and WCOT GC columns that combines the benefits of the larger sample capacity of packed columns and the benefits of the excellent separation capabilities and mass spectrometry (MS) flow rate compatibility of WCOT columns. SFµPC columns suffer from high inlet pressure requirements and prior reported work has required specialized instrumentation for their use. Fabrication of and chromatography with SFµPC GC columns was successfully achieved with typical GC-MS instrumentation and within the flow rate limit of a MS. Additionally, the use of higher viscosity carrier gasses was demonstrated to reduce the required inlet pressure for SFµPC GC columns. Recently, a new vacuum ultraviolet spectrometer (VUV) universal detector has been commercialized for GC. The ability of VUV detectors to acquire absorbance spectra from 125 nm to 430 nm poses a potential alternative to MS. As such, GC-VUV provides an exciting potential alternative approach to achieving excellent quantitative and qualitative analysis across a wide range of analytes. The performance of VUV and MS detectors for forensic analysis in terms of quantitative and qualitative analysis was compared. Analysis of alkylbenzenes in ignitable liquids was explored, which can be important evidence from suspected arson fires and are difficult to differentiate with MS. The VUV detector was found to have superior specificity and comparable sensitivity to the MS detector in scan mode. Addition of thermolysis (Th) as an orthogonal fragmentation pathway provides the opportunity to increase the differences between MS fragmentation patterns. Fragmentation has been widely established to aid in identification of molecules with MS by providing characteristic fragments at characteristic relative abundances. However, molecules with very similar structures do not result in sizable spectral differences in all cases with typical MS fragmentation techniques. A series of Th units were fabricated and integrated into GC-Th-MS instruments. Th-MS was conducted with the thermally labile nitrate esters across a range of instrumentation and thermal conditions.
Automated derivatization and identification of controlled substances via total vaporization solid phase microextraction (Tv-Spme) and gas chromatography-mass spectrometry (Gc-Ms)
(2018) Hickey, Logan D.; Goodpaster, John
Gas chromatography-mass spectrometry (GC-MS) is one of the most widely used instrumental techniques for chemical analyses in forensic science laboratories around the world due to its versatility and robustness. The most common type of chemical evidence submitted to forensic science laboratories is seized drug evidence, the analysis of which is largely dominated by GC-MS. Despite this, some drugs are difficult or impossible to analyze by GC-MS under normal circumstances. For these drugs, derivatization can be employed to make them more suitable for GC-MS. In Chapter 1, the derivatization of primary amino and zwitterionic drugs with three different derivatization agents, trifluoroacetic anhydride (TFAA); N,O-bis(trimethylsilyl)trifluoroacetamide + 1% trimethylchlorosilane (BSTFA + 1% TMCS); and dimethylformamide dimethylacetal (DMF-DMA), is discussed. The chromatographic performance was quantified for comparison between the derivatives and their parent drugs. Peak symmetry was compared using the asymmetry factor (As), separation efficiency was measured by the number of theoretical plates (N), and sensitivity was compared by measuring the peak areas. In Chapter 2, derivatization techniques were adapted for an automated on-fiber derivatization procedure using a technique called total vaporization solid phase microextraction (TV-SPME). TV-SPME is a variation of SPME in which a small volume of sample solution is used which can be totally vaporized, removing the need to consider the equilibrium between analytes in the solution and analytes in the headspace. By allowing derivatization agent to adsorb to the SPME fiber prior to introduction to the sample vial, the entire derivatization process can take place on the fiber or in the headspace surrounding it. The use of a robotic sampler made the derivatization procedure completely automated. In Chapter 3, this on-fiber derivatization technique was tested on standards of 14 controlled substances as well as on realistic samples including simulated “street meth”, gamma-hydroxybutyric acid (GHB) in mixed drinks, and hallucinogenic mushrooms, and was also tested on several controlled substances as solid powders. Future work in this area is discussed in Chapter 4, including adapting the method to toxicological analyses both in biological fluids and in hair. Some of the expected difficulties in doing so are discussed, including the endogenous nature of GHB in the human body. The presence of natural GHB in beverages is also discussed, which highlights the need for a quantitative addition to the method. Additional method improvements are also discussed, including proposed solutions for complete derivatization of more of the analytes, and for decreasing analysis time.
Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time
(MDPI, 2022-07) Grocki, Paul; Woollam, Mark; Wang, Luqi; Liu, Shengzhi; Kalra, Maitri; Siegel, Amanda P.; Li, Bai-Yan; Yokota, Hiroki; Agarwal, Mangilal; Chemistry and Chemical Biology, School of Science
Volatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.
EnvCNN: A Convolutional Neural Network Model for Evaluating Isotopic Envelopes in Top-Down Mass-Spectral Deconvolution
(ACS, 2020-06) Basharat, Abdul Rehman; Ning, Xia; Liu, Xiaowen; BioHealth Informatics, School of Informatics and Computing
Top-down mass spectrometry has become the main method for intact proteoform identification, characterization, and quantitation. Because of the complexity of top-down mass spectrometry data, spectral deconvolution is an indispensable step in spectral data analysis, which groups spectral peaks into isotopic envelopes and extracts monoisotopic masses of precursor or fragment ions. The performance of spectral deconvolution methods relies heavily on their scoring functions, which distinguish correct envelopes from incorrect ones. A good scoring function increases the accuracy of deconvoluted masses reported from mass spectra. In this paper, we present EnvCNN, a convolutional neural network-based model for evaluating isotopic envelopes. We show that the model outperforms other scoring functions in distinguishing correct envelopes from incorrect ones and that it increases the number of identifications and improves the statistical significance of identifications in top-down spectral interpretation.
Feasibility of Desorption Electrospray Ionization Mass Spectrometry for Diagnosis of Oral Tongue Squamous Cell Carcinoma
(Wiley, 2017) D'Hue, Cedric; Moore, Michael; Summerlin, Don-John; Jarmusch, Alan; Alfaro, Clint; Mantravadi, Avinash; Bewley, Arnaud; Farwell, D. Gregory; Cooks, R. Graham; Pathology and Laboratory Medicine, School of Medicine
Rationale Desorption electrospray ionization mass spectrometry (DESI-MS) has demonstrated utility in differentiating tumor from adjacent normal tissue in both urologic and neurosurgical specimens. We sought to evaluate if this technique had similar accuracy in differentiating oral tongue squamous cell carcinoma (SCC) from adjacent normal epithelium due to current issues with late diagnosis of SCC in advanced stages. Methods Fresh frozen samples of SCC and adjacent normal tissue were obtained by surgical resection. Resections were analyzed using DESI-MS sometimes by a blinded technologist. Normative spectra were obtained for separate regions containing SCC or adjacent normal epithelium. Principal Component Analysis and Linear Discriminant Analysis (PCA-LDA) of spectra were used to predict SCC versus normal tongue epithelium. Predictions were compared with pathology to assess accuracy in differentiating oral SCC from adjacent normal tissue. Results Initial PCA score and loading plots showed clear separation of SCC and normal epithelial tissue using DESI-MS. PCA-LDA resulted in accuracy rates of 95% for SCC versus normal and 93% for SCC, adjacent normal and normal. Additional samples were blindly analyzed with PCA-LDA pixel-by-pixel predicted classifications as SCC or normal tongue epithelial tissue and compared against histopathology. The m/z 700–900 prediction model showed a 91% accuracy rate. Conclusions DESI-MS accurately differentiated oral SCC from adjacent normal epithelium. Classification of all typical tissue types and pixel predictions with additional classifications should increase confidence in the validation model.
Identification of Novel Biomarker and Therapeutic Target Candidates for Diagnosis and Treatment of Follicular Adenoma
(International Institute of Anticancer Research, 2015-11) Lai, Xianyin; Chen, Shaoxiong; Department of Biochemistry and Molecular Biology, IU School of Medicine
ollicular adenoma is a type of benign and encapsulated nodule in the thyroid gland, but some adenomas have the potential to progress to follicular carcinoma. Therefore, it is important to monitor the state and progress of follicular adenoma in the clinic and discover drug development targets for the treatment of follicular adenoma to prevent its worsening to follicular carcinoma. Currently, the study of biomarkers and therapeutic targets lacks applications of up-to-date technologies, including proteomics and bioinformatics. To discover novel protein biomarker and therapeutic target candidates, a liquid chromatography-tandem mass spectrometry approach was applied to directly compare follicular adenoma with normal thyroid tissue samples. The proteomics analysis revealed 114 protein biomarker candidates out of 1,780 identified and quantified proteins. A comprehensive approach to prioritize the biomarker candidates by category and rank revealed CD63, DDB1, TYMP, VDAC2, and DCXR as the top five biomarker candidates. Upstream regulator analysis using the Ingenuity Pathway Analysis (IPA) software discovered four therapeutic target candidates for follicular adenoma, including TGFB1, MYC, ANGPT2, and NFE2L2. This study provided biomarker and therapeutic target candidates for a follow-up study, which will facilitate monitoring and treatment of follicular adenoma.
Investigation of Protein – Protein Interactors of Setmar Using Tandem Mass Tag Mass Spectrometry
(2022-03) Segizbayeva, Lana; Georgiadis, Millie M.; Mosley, Amber L.; Wells, Clark D.
The nuclear protein SETMAR has been reported to be involved in many processes such as non-homologous end joining (NHEJ), di-methylation (arguably) of K36 of histone H3, restart of stalled replication forks, chromosome decatenation, enhancing of TOPII inhibitors which results in resistance to chemotherapeutics in cancer patients, etc. All these purported functions are impossible to execute without interaction with other proteins. It is established that SETMAR binds specifically to DNA at terminal inverted repeat sequences and can loop DNA. This DNA sequence specific pull-down exploits this attribute to identify possible protein interactors of SETMAR. As a result of this experiment several proteins have been identified for further research: BAG2, c12orf45, PPIA, XRCC5/6, and ZBTB43, all of which are found in higher statistical abundances in full length SETMAR samples.
Lipidomic Analysis of Glioblastoma Multiforme Using Mass Spectrometry
(Bentham Science Publishers, 2014-04-01) Ha, Soo Jung; Showalter, Gordon; Cai, Shanbao; Wang, Haiyan; Liu, Wei Michael; Cohen-Gadol, Aaron A.; Sarkaria, Jann N.; Rickus, Jenna; Springer, John; Adamec, Jiri; Pollok, Karen E.; Clase, Kari L.; Department of Neurological Surgery, IU School of Medicine
Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors. It is highly invasive and current treatment options have not improved the survival rate over the past twenty years. Novel approaches and technologies from systems biology have the potential to identify biomarkers that could serve as new therapeutic targets for GBM. This study employed lipid profiling technology to investigate lipid biomarkers in ectopic and orthotopic human GBM xenograft models. Primary patient cell lines, GBM10 and GBM43, were injected into the flank and the right cerebral hemisphere of NOD/SCID mice. Tumors were harvested from the brain and flank and proteins, metabolites, and lipids extracted from each sample. Reverse phase based high performance liquid chromatography coupled with Fourier transform ion cyclotron resonance mass spectrometry (LC-FTMS) was used to analyze the lipid profiles of tumor samples. Statistical and clustering analyses were performed to detect differences. Over 500 lipids were identified in each tumor model and lipids with the greatest fold effect in the comparison of ectopic versus orthotopic tumor models fell predominantly into four main classes of lipids: glycosphingolipids, glycerophoshpoethanolamines, triradylglycerols, and glycerophosphoserines. Lipidomic analysis revealed differences in glycosphingolipid and triglyceride profiles when the same tumor was propagated in the flank versus the brain. These results underscore the importance of the surrounding physiological environment on tumor development and are consistent with the hypothesis that specific classes of lipids are critical for GBM tumor growth in different anatomical sites.
Metabolic and Molecular Regulation of Dietary Polyunsaturated Fatty Acids on Prostate Cancer
(Wiley, 2016-03) Zhao, Heng; Pflug, Beth R.; Lai, Xianyin; Wang, Mu; Department of Biochemistry & Molecular Biology, IU School of Medicine
Purpose The aim of this study is to investigate the role of n-3 and n-9 fatty acids in crucial processes involved in prostate cancer cell growth through a large-scale proteomic analysis. Experimental design We used a label-free protein quantification method to profile global protein expression of fish oil and oleic acid treated PCa cells and validated a panel of differentially expressed proteins by either Western blot or multiple reaction monitoring. Bioinformatic analysis was also performed to uncover the pathways involved in fatty acid metabolism. Results Fish oil, not oleic acid, suppresses prostate cancer cell viability. Assessment of fatty acid synthesis pathway activity also shows that oleic acid is a more potent inhibitor than fish oil on de novo fatty acid synthesis. Although fatty acid synthase activity decreases with fish oil treatment, the inhibition of its activity occurs over time while reduction in viability occurs within 24 h. Bioinformatic analysis revealed the pathways altered by these fatty acid treatments. Conclusions and clinical relevance This study suggests that suppression of cell viability by fish oil is independent of fatty acid synthase and fish oil regulates prostate cancer cells through activation of other pathways depending upon length of exposure to fish oil.
Native Proteomics in Discovery Mode Using Size-Exclusion Chromatography–Capillary Zone Electrophoresis–Tandem Mass Spectrometry
(ACS, 2018-09) Shen, Xiaojing; Kou, Ruiqiong; Yang, Zhichang; Chen, Daoyang; Liu, Xiaowen; Hong, Heedeok; Sun, Liangliang; BioHealth Informatics, School of Informatics and Computing
Native proteomics aims to characterize complex proteomes under native conditions and ultimately produces a full picture of endogenous protein complexes in cells. It requires novel analytical platforms for high-resolution and liquid-phase separation of protein complexes prior to native mass spectrometry (MS) and MS/MS. In this work, size exclusion chromatography (SEC)-capillary zone electrophoresis (CZE)-MS/MS was developed for native proteomics in discovery mode, resulting in the identification of 144 proteins, 672 proteoforms, and 23 protein complexes from the Escherichia coli proteome. The protein complexes include four protein homodimers, 16 protein-metal complexes, two protein-[2Fe-2S] complexes, and one protein-glutamine complex. Half of them have not been reported in the literature. This work represents the first example of online liquid-phase separation-MS/MS for characterization of a complex proteome under the native condition, offering the proteomics community an efficient and simple platform for native proteomics.

Browsing by Subject "mass spectrometry"

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