Browsing by Subject "metabolomics"

Now showing 1 - 8 of 8
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    1H-NMR Metabolomics Characterizes Transition From Ebb To Flow In A Porcine Model Of Smoke Inhalation And Severe Burn Injury
    (2018-06) Hendrickson, Cole
    Burn injury initiates a metabolic response that, even when treated, causes muscle wasting and organ dysfunction in burn patients as long as two years following injury. This increased metabolic rate, termed “flow” phase in burn physiology, is initially masked by low blood pressure and inadequate oxygen supply in burn shock, known as “ebb” phase. Our study examined the metabolic transition between the “ebb” and “flow” phases of burn recovery using proton nuclear magnetic resonance (1H-NMR) spectroscopy in a porcine model of severe burn injury with additional smoke inhalation. We hypothesized the serum metabolomes of porcine subjects would be distinguishable by time point, and the changes in individual metabolite concentrations would characterize the shift from “ebb” to “flow” in burn physiology. Fifteen pigs received 40% total body surface area (TBSA) thermal burns with additional pine bark smoke inhalation treatment. Subjects were resuscitated and kept anesthetized until 72 hours post-burn or death. Arterial blood samples were drawn at baseline (pre-burn) and every 24 hours until 72 hours post-injury or death. The aqueous portion of each sample was analyzed in a 700MHz spectrometer and metabolite peaks were fit to spectra using Chenomx software. Thirty-eight metabolites were detected in 39 samples, and principal component analysis (PCA) was conducted to separate samples by time point. 51.6% of metabolite variability was captured in the first two principal components. We found post-burn metabolomes of porcine subjects to be distinguishable by time point using 1H-NMR and principal component analysis. We also constructed a framework for non-lactic acidosis in resuscitated burn subjects that emphasized oxidative stress and increased fatty acid catabolism as root causes of organic acid accumulation. Further studies will be required to confirm and elaborate on the post-burn metabolic pathways suggested by this analysis.
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    Data for Detection of Exchangeable Protons in NMR Metabolomic Analysis using AI-Designed Water Irradiation Devoid Pulses
    (2025-02-06) Veliparambil Subrahmanian, Manu; Veglia, Gianluigi; Vuckovic, Ivan; Macura, Slobodan; mvelipar@umn.edu; Manu, Veliparambil Subrahmanian; Veglia Lab
    1H NMR spectroscopy has enabled the quantitative profiling of metabolites in various biofluids, emerging as a possible di-agnostic tool for metabolic disorders and other diseases. To boost the signal-to-noise ratio and detect proton resonances near the water signal, current 1H NMR experiments require solvent suppression schemes (e.g., presaturation, jump-and-return, WATERGATE, excitation sculpting, etc.). Unfortunately, these techniques affect the quantitative assessment of analytes containing exchangeable protons. To address this issue, we introduce two new1D 1H NMR techniques that eliminates the water signal, preserving the intensities of exchangeable protons. Using GENETICS-AI, a software that combines an evolutionary algorithm and artificial intelligence, we tailored new WAter irradiation DEvoid (WADE) pulses and optimized 1D 1H NOESY sequence for metabolomics analysis. When applied to human urine samples, kidney tissue extract, and plasma, the WADE technique allowed for accurate measurement of typical metabolites and direct quantification of urea, which is usually challenging to measure using standard NMR experiments. We anticipate that these new NMR techniques will significantly improve the accuracy and reliability of metabolite quantitative assessment for a wide range of biological fluids.
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    Development and Deployment of Untargeted Metabolomics Pipelines to Reveal Molecular Signatures of Wellness
    (2022-08) Nelson, Alisa
    Metabolomics technologies hold significant potential for aiding research in the underlying drivers of metabolic disease. However, the complexity of metabolomics data sets can limit their impact. This thesis combines computational biology with analytical chemistry and metabolic physiology to deploy metabolomics pipelines directed toward two significant research problems: (i) distinguishing the serum metabolome of normal weight and overweight or obese trained runners; (ii) developing bioinformatic pipelines using stable isotopes to improve feature selection and elucidate metabolite-metabolite relationships.Previously, metabolomics tools have been applied to measure the differences between metabolically healthy (MHO) and metabolically unhealthy obesity (MUO), or untrained versus trained groups. However, how well-trained MHO groups respond to acute exercise is yet unknown. Using liquid chromatography-high resolution mass spectrometry- based untargeted metabolomics, multidimensional mass spectrometry-based shotgun lipidomics, correlation analysis and machine learning models, the effect of increased adiposity and acute exercise on trained runners are evaluated. Fatty acid esters of hydroxy fatty acids (FAHFAs), an anti-diabetic and anti-inflammatory lipid class, distinguish normal weight (NWT) and overweight/obese trained (OWT) runners who differ in body composition but have similar levels of cardiovascular fitness. Many diverse FAHFA species are elevated at baseline and decrease with acute running in NWT, but not OWT. These exercise-induced changes are inversely associated with changes in IL-6, a known myokine involved in inflammatory pathways, and are influenced by visceral fat mass. Baseline concentrations of FAHFAs are negatively associated with visceral fat mass and together with free fatty acids and purine nucleosides account for 53% of the variation in VO2max in this cohort. Finally, the formation of isobaric FA dimers in untargeted metabolomics pipelines when fatty acids are abundant necessitate the use of targeted measurement of FAHFAs in serum for accurate quantitation. This work reveals a novel role of FAHFAs in acute exercise adaptation that is affected by increased adiposity. These results may direct future research in the treatment of obesity and its related complications. Moreover, this thesis provides a rigorous approach to validating biologically significant features the broader metabolomics community can mimic in future untargeted studies.
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    Effects Of Genetic Selection On Composition And Biosynthesis Of Milk Fats In Early Lactation Of Holstein Cows
    (2016-08) DING, FENG
    Genetic selection in dairy cattle has greatly improved the milk yield in the past decades. Contemporary Holsteins (CH) that were selected and maintained by the University of Minnesota produced more than 4,500 kg milk in 305 days than its counterpart unselected Holsteins (UH), which has stable milk yield since 1964. However, the influences of genetic selection on the chemical composition of cow milk were not well characterized. In this study, cows from UH and CH genotypes (CH) (n = 12/genotype) were co-housed and fed the same diet ad libitum 5 weeks prepartum. Weekly milk samples were obtained from the milking on each Tuesday night in the first 9 weeks of lactation. Analysis of macronutrients in milk indicated that CH and UH had comparable levels of lactose (4.75% vs. 4.69%, P=0.08). However, CH had a slight lower level of proteins (2.98% vs. 3.13%, P<0.05) and much higher level of fats than UH (4.33% vs. 3.55%, P<0.01). Lipidomic analysis through high-resolution liquid chromatography-mass spectrometry (LC-MS) analysis, multivariate data analysis (MDA), and MSMS fragmentation further revealed that the TAG profiles of UH and CH milk differed greatly in early weeks of lactation, but became more comparable by week 9. Hierarchical clustering analysis (HCA) of TAGs markers indicated that CH milk were more enriched with preformed fatty acids (FAs) while UH milk had higher abundance of FAs originated from de novo synthesis. This conclusion was further confirmed by quantitative analysis of FAs and organic acid precursors. Overall, these observations suggested that genetic selection increased the contribution of preformed FAs from blood lipids to the biosynthesis of milk TAGs, especially in the early phase of lactation.
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    Integrating Genomics and Metabolomics to Inform Breeding for Powdery Mildew Resistance in Grapevine
    (2018-08) Teh, Soon Li
    Two powdery mildew resistance loci have been identified using pedigree-connected F1 mapping families at the University of Minnesota grape breeding program. A consensus linkage map of the resistant parent (MN1264) was developed for genetic mapping. The resistance loci were mapped on chromosomes 2 and 15, with additive effects accounting for over 30% phenotypic variation. Marker haplotypes, hap+chr2 and hap+chr15, were constructed to trace the inheritance of resistance loci in grandparent-parent-progeny relationships. Both hap+chr2 and hap+chr15 in the resistant F1 progeny were inherited from parent MN1264, that originated from grandparent ‘Seyval blanc’. Additionally, two microsatellites markers (i.e., UDV-015b and VViv67) were identified to be associated with hap+chr15, and can be applied for marker-assisted selection. In a follow-up study to characterize metabolic changes attributed to hap+chr2 and hap+chr15, a metabolomic experiment was conducted on whole-plant propagated grapes in a time-course response to in vivo inoculation. The use of several multivariate analyses systematically identified 52 biomarkers that were associated with hap+chr2, and 12 biomarkers with hap+chr15. In a temporal assessment of biomarkers, the discriminating metabolic changes distinguishing resistant and susceptible individuals appeared to be occurring from 24 to 48 hours after inoculation.
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    Metabolomics study on Arabidopsis thaliana abiotic stress responses for priming, recovery, and stress combinations
    (2018-04) Xu, Yuan
    Temperature, water, and light are three stress factors that have major influences on plant growth, development, and reproduction. Plants can be primed to an acclimated state by a prior mild stress to enhance their resistance to future stress. ‘Priming’ is related to plant stress ‘memory’ during recovery. Plants may need to balance between keeping the memory for enhanced stress defense and resetting for maximum growth and development during recovery. In the field, plants are more often to encounter a combination of different abiotic stresses rather than a specific single stress condition. Plant responses to a combination of stresses may exhibit quite unique defense and acclimation responses as compared to the response elicited by each individual stress, which should not be simply considered as the sum of the two different stresses. However, the simultaneous occurrence of multiple stress events is rarely studied experimentally, especially by metabolomics methods. Metabolomics, the comprehensive, quantitative and qualitative analysis of small molecules, is an emerging 'omics' platform that is an important next-generation systems biology approach. By providing an instantaneous “snapshot” of metabolic processes that occur in an organism, metabolomics can potentially provide insightful molecular mechanism information to questions about physiological function in complex biological systems. The objective of this thesis research was to use both untargeted and targeted metabolomics approaches to investigate plant shared and unique metabolic features in responses to single as well as multiple abiotic stresses, the priming effect of temperature stresses, plant memory during recovery phase, and the relationships between combined stress with each of individual stresses. An ultra-high pressure liquid chromatography-high resolution mass spectrometry (UHPLC-HR-MS)-based metabolomics approach was utilized. In chapter two, a metabolomics study on Arabidopsis thaliana 11-day-old seedling’s abiotic stress responses including heat (basal and acquired), cold (basal and acquired), drought and high light with 2-day-recovery was performed using a standardized reference system. In chapter three, Arabidopsis thaliana 11-day-old seedlings that were induced by the combination of different abiotic stresses including heat, cold, drought, salinity, and high light, that mimics field environment was studied. From this thesis research, a number of potential stress signatures determined from the untargeted analysis were identified, quantified and clustered by stress response patterns. Central metabolism were found to undergo a complex regulatory process in response to stress. Shared and unique metabolic signatures were identified across different abiotic single and combined stresses. The majority of stress signatures clustered together and exhibited shared response patterns. However, cysteine, glutathione, and maltose showed unique and dramatic patterns, demonstrating large changes in glutathione biosynthesis, glutathione oxidation, and starch degradation. The results showed that only two combined stresses, including high light x cold and cold x salinity, had metabolic effects that reflected both of their constituent single stresses. Most combined stresses had one dominant stress that had a defining impact on the plant metabolic profile. Drought stress is the dominant stress for all of its stress combinations. Two combined stresses, including high light x heat and high light x salinity, showed unique metabolic stress response patterns that are not similar to any of their individual stresses. Most of these metabolic features were specifically changed only in the combined stress, which should thus be considered as novel stress conditions. In summary, this work utilized metabolomics to study plant priming effects, recovery processes, and combined stress responses. It led to an improved understanding of how plants respond to abiotic stresses and may support subsequent studies on plant abiotic stress metabolic flux analyses.
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    Optimizing Methods for Turfgrass Metabolomics
    (2023-11) Freund Saxhaug, Katrina; Hegeman, Adrian; Watkins, Eric
    Subtle differences in growing environment, harvesting methods, sample processing, and data analysis can lead to unintended variations in metabolomic data, so careful planning of metabolomic experiments is crucial.
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    Ploidy, Genetics, And Metabolomics Of Achillea, A Venerable And Variable Medicinal Plant
    (2022-09) Sammons, Katherine
    Humans have turned to plants for medicine since ancient times. In recent centuries technology has allowed isolation of pure compounds which largely replaced herbal medicines in the USA around the beginning of the 20th century. However, even in today’s world of modern medicine, some herbal medicines can offer support for health in ways that pharmaceutical drugs cannot. With the advent of high resolution analytical instruments it is now possible to reconsider herbal medicines in all of their chemical complexity. Using the ancient medicinal plant Achillea millefolium as a case study, I use high resolution accurate mass-mass spectrometry to chemically profile 115 publicly available accessions of Achillea spp. cultivated in a common garden.In Chapter 1 I describe a brief history of medicine and technology to understand how we arrived at the current reductionist single-active-constituent mindset, and why it is important to broaden our mental model. In Chapter 2 I use flow cytometry and karyology to describe the ploidy of each of the 115 Achillea accessions. I also use DArTseq, a SNP analysis technique, to describe the population structure among these accessions. Finally, in Chapter 3 I use high performance liquid chromatography tandem to a high resolution mass spectrometer to chemically profile the 115 accessions. Altogether, this study helps to better understand the role that ploidy and genotype play in the chemotype of Achillea spp. The high resolution chemical profiling also helps to re-envision plants with a higher level of chemical complexity. Additionally, it serves as a potential model for improving approaches to quality control in the herbal industry.