@article{wu_wong_chiles_mellinger_bae_jung_peterson_wang_negrete_huang_et al._2022, title={Glycerate from intestinal fructose metabolism induces islet cell damage and glucose intolerance}, volume={34}, ISSN={["1932-7420"]}, DOI={10.1016/j.cmet.2022.05.007}, abstractNote={Dietary fructose, especially in the context of a high-fat western diet, has been linked to type 2 diabetes. Although the effect of fructose on liver metabolism has been extensively studied, a significant portion of the fructose is first metabolized in the small intestine. Here, we report that dietary fat enhances intestinal fructose metabolism, which releases glycerate into the blood. Chronic high systemic glycerate levels induce glucose intolerance by slowly damaging pancreatic islet cells and reducing islet sizes. Our findings provide a link between dietary fructose and diabetes that is modulated by dietary fat.}, number={7}, journal={CELL METABOLISM}, author={Wu, Yanru and Wong, Chi Wut and Chiles, Eric N. and Mellinger, Allyson L. and Bae, Hosung and Jung, Sunhee and Peterson, Ted and Wang, Jamie and Negrete, Marcos and Huang, Qiang and et al.}, year={2022}, month={Jul}, pages={1042-+} }
 @article{mellinger_muddiman_gamcsik_2022, title={Highlighting Functional Mass Spectrometry Imaging Methods in Bioanalysis}, volume={6}, ISSN={["1535-3907"]}, DOI={10.1021/acs.jproteome.2c00220}, abstractNote={Most mass spectrometry imaging (MSI) methods provide a molecular map of tissue content but little information on tissue function. Mapping tissue function is possible using several well-known examples of "functional imaging" such as positron emission tomography and functional magnetic resonance imaging that can provide the spatial distribution of time-dependent biological processes. These functional imaging methods represent the net output of molecular networks influenced by local tissue environments that are difficult to predict from molecular/cellular content alone. However, for decades, MSI methods have also been demonstrated to provide functional imaging data on a variety of biological processes. In fact, MSI exceeds some of the classic functional imaging methods, demonstrating the ability to provide functional data from the nanoscale (subcellular) to whole tissue or organ level. This Perspective highlights several examples of how different MSI ionization and detection technologies can provide unprecedented detailed spatial maps of time-dependent biological processes, namely, nucleic acid synthesis, lipid metabolism, bioenergetics, and protein metabolism. By classifying various MSI methods under the umbrella of "functional MSI", we hope to draw attention to both the unique capabilities and accessibility with the aim of expanding this underappreciated field to include new approaches and applications.}, journal={JOURNAL OF PROTEOME RESEARCH}, author={Mellinger, Allyson L. and Muddiman, David C. and Gamcsik, Michael P.}, year={2022}, month={Jun} }
 @article{mellinger_kibbe_rabbani_meritet_muddiman_gamcsik_2022, title={Mapping glycine uptake and its metabolic conversion to glutathione in mouse mammary tumors using functional mass spectrometry imaging}, volume={193}, ISSN={["1873-4596"]}, DOI={10.1016/j.freeradbiomed.2022.11.010}, abstractNote={Although glutathione plays a key role in cancer cell viability and therapy response there is no clear trend in relating the level of this antioxidant to clinical stage, histological grade, or therapy response in patient tumors. The likely reason is that static levels of glutathione are not a good indicator of how a tissue deals with oxidative stress. A better indicator is the functional capacity of the tissue to maintain glutathione levels in response to this stress. However, there are few methods to assess glutathione metabolic function in tissue. We have developed a novel functional mass spectrometry imaging (fMSI) method that can map the variations in the conversion of glycine to glutathione metabolic activity across tumor tissue sections by tracking the fate of three glycine isotopologues administered in a timed sequence to tumor-bearing anesthetized mice. This fMSI method generates multiple time point kinetic data for substrate uptake and glutathione production from each spatial location in the tissue. As expected, the fMSI data shows glutathione metabolic activity varies across the murine 4T1 mammary tumor. Although glutathione levels are highest at the tumor periphery there are regions of high content but low metabolic activity. The timed infusion method also detects variations in delivery of the glycine isotopologues thereby providing a measure of tissue perfusion, including evidence of intermittent perfusion, that contributes to the observed differences in metabolic activity. We believe this new approach will be an asset to linking molecular content to tissue function.}, journal={FREE RADICAL BIOLOGY AND MEDICINE}, author={Mellinger, Allyson L. and Kibbe, Russell R. and Rabbani, Zahid N. and Meritet, Danielle and Muddiman, David C. and Gamcsik, Michael P.}, year={2022}, month={Nov}, pages={677–684} }
 @article{mellinger_garrard_khodjaniyazova_rabbani_gamcsik_muddiman_2022, title={Multiple Infusion Start Time Mass Spectrometry Imaging of Dynamic SIL-Glutathione Biosynthesis Using Infrared Matrix-Assisted Laser Desorption Electrospray Ionization}, volume={21}, ISSN={["1535-3907"]}, DOI={10.1021/acs.jproteome.1c00636}, abstractNote={Due to the high association of glutathione metabolism perturbation with a variety of disease states, there is a dire need for analytical techniques to study glutathione kinetics. Additionally, the elucidation of microenvironmental effects on changes in glutathione metabolism would significantly improve our understanding of the role of glutathione in disease. We therefore present a study combining a multiple infusion start time protocol, stable isotope labeling technology, infrared matrix-assisted laser desorption electrospray ionization, and high-resolution accurate mass-mass spectrometry imaging to study spatial changes in glutathione kinetics across in sectioned mouse liver tissues. After injecting a mouse with the isotopologues [2-13C,15N]-glycine, [1,2-13C2]-glycine, and [1,2-13C2,15N]-glycine at three different time points, we were able to fully resolve and spatially map their metabolism into three isotopologues of glutathione and calculate their isotopic enrichment in glutathione. We created a tool in the open-source mass spectrometry imaging software MSiReader to accurately compute the percent isotope enrichment (PIE) of these labels in glutathione and visualize them in heat-maps of the tissue sections. In areas of high flux, we found that each label enriched an approximate median of 1.6%, 1.8%, and 1.5%, respectively, of the glutathione product pool measured in each voxel. This method may be adapted to study the heterogeneity of glutathione flux in diseased versus healthy tissues.}, number={3}, journal={JOURNAL OF PROTEOME RESEARCH}, author={Mellinger, Allyson L. and Garrard, Kenneth P. and Khodjaniyazova, Sitora and Rabbani, Zahid N. and Gamcsik, Michael P. and Muddiman, David C.}, year={2022}, month={Mar}, pages={747–757} }
 @article{kibbe_mellinger_muddiman_2022, title={Novel matrix strategies for improved ionization and spatial resolution using IR-MALDESI mass spectrometry imaging}, volume={57}, ISSN={["1096-9888"]}, DOI={10.1002/jms.4875}, abstractNote={Abstract}, number={8}, journal={JOURNAL OF MASS SPECTROMETRY}, author={Kibbe, Russell R. and Mellinger, Allyson L. and Muddiman, David C.}, year={2022}, month={Aug} }
 @article{mellinger_mccoy_minior_williams_2021, title={Discovery proteomics of human placental tissue}, volume={9}, ISSN={["1097-0231"]}, url={https://doi.org/10.1002/rcm.9189}, DOI={10.1002/rcm.9189}, abstractNote={We describe a label‐free proteomics protocol for the interrogation of the placental proteome. Step‐by‐step directions, including tissue cleanup and preparation, proteolytic digestion, nanoLC–MS/MS data collection and data analysis, are provided. The workflow has been applied toward exploring differential protein expression patterns in placentas from women who have been exposed to drugs during pregnancy relative to those who have not. We collected 20 tissue specimens, each representing a combination of spatially diverse sections across the placenta. These specimens were analyzed in the work described here, to survey information across the entire organ. This protocol can be scaled up or down as needed.}, journal={RAPID COMMUNICATIONS IN MASS SPECTROMETRY}, publisher={Wiley}, author={Mellinger, Allyson L. and McCoy, Krista and Minior, Duy An T. and Williams, Taufika Islam}, year={2021}, month={Dec} }
 @article{bereman_kirkwood_sabaretnam_furlong_rowe_guillemin_mellinger_muddiman_2020, title={Metabolite Profiling Reveals Predictive Biomarkers and the Absence of beta-Methyl Amino-L-alanine in Plasma from Individuals Diagnosed with Amyotrophic Lateral Sclerosis}, volume={19}, ISSN={["1535-3907"]}, DOI={10.1021/acs.jproteome.0c00216}, abstractNote={By employing chip-based capillary zone electrophoresis coupled to high resolution mass spectrometry, we profiled the plasma metabolome of 134 patients diagnosed with sporadic amyotrophic lateral sclerosis (81 males and 53 females) and 118 individuals deemed healthy (49 males; 69 females). The most significant markers (p﹤0.01) were creatine, which was 49% elevated, and creatinine and methylhistidine which were decreased by 20% and 24%, respectively, in ALS patients. The ratio of creatine versus creatinine increased 370% and 200% for male and female ALS patients, respectively. In addition, male ALS patients on average had 5-13% lower amounts of 7 essential amino acids while females did not significantly differ from healthy controls. We developed two models using the metabolite abundances: 1) A classification model for the separation of ALS and healthy samples; and 2) A classification model for the prediction of disease progression based on the ALS functional rating score. Utilizing a Monte Carlo cross-validation approach, a linear discriminant analysis model achieved a mean area under the receiver operating characteristic curve (AUC) of 0.85 (0.06) with a mean sensitivity of 80% (9%) and specificity of 78% (10%), for the separation of ALS and controls, respectively. A support vector machine classifier predicted progression categories with an AUC of 0.90 (0.06) with a mean sensitivity 73% (10%) and specificity 86% (5%). Lastly, using a previously reported assay with a stable isotope labeled (13C315N2) spike-in standard, we were unable to detect the exogenous neurotoxic metabolite, β-methylamino-L-alanine (BMAA), in the free or protein bound fraction of any of the 252 plasma samples.}, number={8}, journal={JOURNAL OF PROTEOME RESEARCH}, author={Bereman, Michael S. and Kirkwood, Kaylie I and Sabaretnam, Tharani and Furlong, Sarah and Rowe, Dominic B. and Guillemin, Gilles J. and Mellinger, Allyson L. and Muddiman, David C.}, year={2020}, month={Aug}, pages={3276–3285} }
 @article{mellinger_griffith_bereman_2020, title={Peptide variability and signatures associated with disease progression in CSF collected longitudinally from ALS patients}, volume={412}, ISSN={["1618-2650"]}, DOI={10.1007/s00216-020-02765-8}, abstractNote={We employ shotgun proteomics and data-independent acquisition (DIA) mass spectrometry to analyze cerebrospinal fluid longitudinally collected from 14 amyotrophic lateral sclerosis (ALS) patients (8 males and 6 females). We perform three main analyses of these data: (1) examine the intra- and inter-patient protein variability in CSF; (2) explore the association of inflammation with rate of disease progression; and (3) develop a mixed-effects model to best explain the decrease in ALS-Functional Rating Scale (ALS-FRS) score. Overall, the CSF protein abundances are tightly regulated with the intra-individual variability contributing just 4% to the overall variance. In four patients, a moderately significant correlation (p < 0.1) was observed between inflammation and rate of disease progression. Using a least absolute shrinkage and selection operator (LASSO) variable selection, we selected 55 viable peptides for mathematical modeling via a linear mixed-effects regression. We then employed forward selection to generate a final model by minimizing Akaike's information criterion (AIC). The final model utilized changes in abundance from 28 peptides as fixed effects to model progression of the disease in these patients. These peptides were from proteins involved in stress response and innate immunity. Graphical abstract.}, number={22}, journal={ANALYTICAL AND BIOANALYTICAL CHEMISTRY}, author={Mellinger, Allyson L. and Griffith, Emily H. and Bereman, Michael S.}, year={2020}, month={Sep}, pages={5465–5475} }