<p> This thesis focused on the development of comprehensive, rapid and simple methodologies for the analysis of fatty acids by gas chromatography mass spectrometry (GC/MS) and intact lipids by electrospray ionization tandem mass spectrometry (ESIIMS/MS). The methodologies were applied as a tool for functional genomics in the soil bacterium Sinorhizobium meliloti. The effects of inorganic phosphate (Pi)-starvation and acidity on lipid composition were studied. </p> <p> A micro-scale, one-vial method for the analysis of fatty acids as their fatty acid methyl esters by GC/MS was developed. The method required small sample sizes, involved minimum handling and avoided tedious extraction steps, which increased sample throughput. A series of quality controls were included to measure losses due to handling, derivatization efficiencies and the extent of side reactions. The method was suitable for the analysis of sensitive bacterial fatty acids such as cyclopropane fatty acids. </p> <p> A shotgun lipidomics approach was developed for the analysis of intact lipids by ESIIMS/MS. Fatty acid distributions were obtained for eight lipid classes and up to 58 individual lipids were identified in crude lipid extracts without sample cleanup or chromatography. For the first time, fatty acid distributions were provided for non-phosphorus containing lipids using shotgun lipidomics. Fatty acid distributions within lipid classes suggested that phospholipids and 1,2-diacylglyceryl-3-O-4'-(N,N,N-trimethyl)-homoserine lipids (TMHSs) were both synthesized from phosphatidic acid while sulfoquinovosyldiacylglycerol (SLs) had a different biosynthetic origin. </p> <p> The methodologies were applied to study knockout mutants of five genes thought to participate in lipid metabolism in S. meliloti. It was demonstrated that: (1) cfa2 gene coded for the main cyclopropane fatty acyl synthase; (2) the plsC gene coded for a fatty acy 1 transferase specific for C 16 fatty acids in the sn-2 position of phospholipids; (3) a metabolic phenotype was revealed for knockout mutants of dme and tme genes (DME and TME, malic enzymes) when succinate was the carbon source. </p> / Thesis / Doctor of Philosophy (PhD)

Terpenes are secondary metabolites produced by plants and they have promising roles in plant defense and pharmaceuticals. They are synthesized by terpene synthases and these enzymes are part of a complex plant metabolic pathway. Diterpene biosynthesis requires co-expression of class II and class I diterpene synthases (diTPSs) to convert geranylgeranyl diphosphate (GGPP), the common precursor, into a C20 intermediate substrate. These substrates then use cytochrome p450s (CYPs) as their final steps to form diterpene scaffolds. CYPs are monooxygenases that change the redox status of their substrates into final diterpene products. Medicago truncatula was used as my model organism to investigate how legumes synthesize these secondary metabolites to contribute to crop defense improvement in the future. Seven diTPSs - MtTPS17, MtTPS18, MtTPS19, MtTPS37, MtTPS38, MtTPS39, and MtTPS40 - in M. truncatula have been identified. MtTPS38 was found to produce ent-CPP and MtTPS37 used ent-CPP to yield ent-kaurene. Combinatorial expression showed that MtTPS38 and MtTPS37 react together to produce ent-kaurene, a precursor for an important plant hormone gibberellin (GA). CYPs have also been discovered to be clustered around MtTPS19, suggesting the possibility of MtTPS19 utilizing these CYPs for downstream reactions.

Indiana University-Purdue University Indianapolis (IUPUI) / Canines can detect different diseases simply by smelling different biological sample types, including urine, breath and sweat. This has led researchers to try and discovery unique volatile organic compound (VOC) biomarkers. The power of VOC biomarkers lies in the fact that one day they may be able to be utilized for noninvasive, rapid and accurate diagnostics at a point of care using miniaturized biosensors. However, the identity of the specific VOC biomarkers must be demonstrated before designing and fabricating sensing systems. Through an extensive series of experiments, VOCs in urine are profiled by solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) to identify biomarkers for breast cancer using murine models. The results from these experiments indicated that unique classes of urinary VOCs, primarily terpene/terpenoids and carbonyls, are potential biomarkers of breast cancer. Through implementing chemometric approaches, unique panels of VOCs were identified for breast cancer detection, identifying tumor location, determining the efficacy of dopaminergic antitumor treatments, and tracking cancer progression. Other diseases, including COVID-19 and hypoglycemia (low blood sugar) were also probed to identify volatile biomarkers present in breath samples. VOC biomarker identification is an important step toward developing portable gas sensors, but another hurdle that exists is that current sensors lack selectivity toward specific VOCs of interest. Furthermore, testing sensors for sensitivity and selectivity is an extensive process as VOCs must be tested individually because the sensors do not have modes of chromatographic separation or compound identification. Another set of experiments is presented to demonstrate that SPME fibers can be coated with materials, used to extract standard solutions of VOCs, and analyzed by GC-MS to determine the performance of various gas sensing layers. In the first of these experiments, polyetherimide (PEI) was coated onto a SPME fiber and compared to commercial polyacrylate (PAA) fibers. The second experiment tuned the extraction efficiency of polyvinylidene fluoride (PVDF) - carbon black (CB) composites and showed that they had higher sensitivity for urinary VOC extraction relative to a polydimethylsiloxane (PDMS) SPME fiber. These results demonstrate SPME GC-MS can rapidly characterize and tune the VOC adsorption capabilities of gas sensing layers.

The purpose of this study was to find an alternative instrumental method to sensory analysis and to further investigate the aroma properties of spoiling blue crab meat. This was accomplished by use of a Cyranose 320™ Electronic Nose, Draeger-Tubes®, and solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS). These techniques were compared to the more established techniques for determining quality of blue crab meat of sensory and microbiological analysis. Three different electronic nose methods were used to evaluate five sequentially spoiled groups of crab meat. The manufacturer's recommended setup only resulted in a 30 % correct separation of the known groups, and only 10 % of the samples were correctly identified when coded unknown samples were used to validate the electronic nose training results. The compressed air method which utilized compressed tank breathing air, filtered through activated carbon and moisture traps resulted in 100 % separation of the known groups, but only correctly identified 20 % of the coded unknown samples. Draeger-Tubes® were found to be more accurate and precise compared with the electronic nose. All 5 groups of samples analyzed using Draeger-Tubes® were found to be significantly different at α = 0.05 using a Tukey-Kramer ANOVA statistical procedure. The coded unknown samples were correctly identified at a rate of 83 %. The simplicity and rapidness of this procedure allows it to possibly be an alternative for the crab industry as an alternative to sensory analysis. SPME-GC-MS found trimethylamine (TMA), ammonia, and indole to best correlate with spoilage of blue crab meat. TMA was found to be sensitive to the minor changes in the early stages (0 - 4 days of refrigerated storage) of spoilage for blue crab meat. Indole corresponded well with sensory results, which suggests that indole may be a promising indicator for detecting early, mid, and highly spoiled samples. It is feasible that these methods can be applied to other crustaceans to determine spoilage level. / Master of Science in Life Sciences

Identification of disease-related alterations in molecular and cellular mechanisms may reveal useful biomarkers for human diseases including cancers. High-throughput omic technologies for identifying and quantifying multi-level biological molecules (e.g., proteins, glycans, and metabolites) have facilitated the advances in biological research in recent years. Liquid (or gas) chromatography coupled with mass spectrometry (LC/GC-MS) has become an essential tool in such large-scale omic studies. Appropriate LC/GC-MS data preprocessing pipelines are needed to detect true differences between biological groups. Challenges exist in several aspects of MS data analysis. Specifically for biomarker discovery, one fundamental challenge in quantitation of biomolecules is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based omic studies. Purification of mass spectometric data is highly desired prior to subsequent differential analysis. In this research dissertation, we majorly target at addressing the purification problem through probabilistic modeling. We propose an intensity-level purification model (IPM) to computationally purify LC/GC-MS based cancerous data in biomarker discovery studies. We further extend IPM to scan-level purification model (SPM) by considering information from extracted ion chromatogram (EIC, scan-level feature). Both IPM and SPM belong to the category of topic modeling approach, which aims to identify the underlying "topics" (sources) and their mixture proportions in composing the heterogeneous data. Additionally, denoise deconvolution model (DMM) is proposed to capture the noise signals in samples based on purified profiles. Variational expectation-maximization (VEM) and Markov chain Monte Carlo (MCMC) methods are used to draw inference on the latent variables and estimate the model parameters. Before we come to purification, other research topics in related to mass spectrometric data analysis for cancer biomarker discovery are also investigated in this dissertation. Chapter 3 discusses the developed methods in the differential analysis of LC/GC-MS based omic data, specifically for the preprocessing in data of LC-MS profiled glycans. Chapter 4 presents the assumptions and inference details of IPM, SPM, and DDM. A latent Dirichlet allocation (LDA) core is used to model the heterogeneous cancerous data as mixtures of topics consisting of sample-specific pure cancerous source and non-cancerous contaminants. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum and tissue proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis. Chapter 5 elaborates these applications in cancer biomarker discovery, where typical single omic and integrative analysis of multi-omic studies are included. / Ph. D. / This dissertation documents the methodology and outputs for computational deconvolution of heterogeneous omics data generated from biospecimens of interest. These omics data convey qualitative and quantitative information of biomolecules (e.g., glycans, proteins, metabolites, etc.) which are profiled by instruments named liquid (or gas) chromatography and mass spectrometer (LC/GC-MS). In the scenarios of biomarker discovery, we aim to find out the significant difference on intensities of biomolecules with respect to two specific phenotype groups so that the biomarkers can be used as clinical indicators for early stage diagnose. However, the purity of collected samples constitutes the fundamental challenge to the process of differential analysis. Instead of experimental methods that are costly and time-consuming, we treat the purification task as one of the topic modeling procedures, where we assume each observed biomolecular profile is a mixture of hidden pure source together with unwanted contaminants. The developed models output the estimated mixture proportion as well as the underlying “topics”. With different level’s purification applied, improved discrimination power of candidate biomarkers and more biologically meaningful pathways were discovered in LC/GC-MS based multi-omic studies for liver cancer. This research work originates from a broader scope of probabilistic generative modeling, where rational assumptions are made to characterize the generation process of the observations. Therefore, the developed models in this dissertation have great potential in applications other than heterogeneous data purification discussed in this dissertation. A good example is to uncover the relationship of human gut microbiome with the host’s phenotypes of interest (e.g., disease like type-II diabetes). Similar challenges exist in how to infer the underlying intestinal flora distribution and estimate their mixture proportions. This dissertation also covers topics of related data preprocessing and integration, but with a consistent goal in improving the performance of biomarker discovery. In summary, the research help address sample heterogeneity issue observed in LC/GC-MS based cancer biomarker discovery studies and shed light on computational deconvolution of the mixtures, which can be generalized to other domains of interest.

No / There is increasing evidence for complexity in mortuary practices in Britain during the Roman period. One class of burials demonstrates an association between inhumation in stone sarcophagi or lead-lined coffins, 'plaster' coatings, textile shrouds and natural resins. It has been suggested that this 'package' represents a deliberate attempt at body preservation. Fragments with a resinous appearance found in one such burial from Arrington, Cambridgeshire, UK were analysed using gas-chromatography-mass spectrometry. The triterpenic compounds identified are biomarkers for the genus Pistacia and provide the first chemical evidence for an exotic resin in a mortuary context in Roman Britain. / AHRC

No / Gas chromatography–mass spectrometry (GC–MS) and bulk carbon isotope determinations have been performed on samples (‘cemented organic residues’, charcoal, sediment and fire-cracked rock) excavated from 12 slab-lined pits from various locations in Arctic Norway to test the premise that these archaeological features were used for the extraction of oil from the blubber of marine mammals, such as seal, whale and walrus. A wide range of lipid compound classes were detected especially in the cemented organic residues and in the charcoal samples. The presence of long-chain unsaturated and isoprenoid fatty acids together with oxidation and thermal alteration products of unsaturated acids such as dicarboxylic acids, dihydroxyfatty acids and ω-(o-alkylphenyl)alkanoic acids suggests that these features were used for marine oil extraction at elevated temperatures. Notably the location of the hydroxyl groups in the dihydroxyfatty acids provides a record of the positional isomer of the precursor fatty acid and allows confirmation that 11-docosenoic (cetoleic) acid, the most abundant C22:1 isomer in marine oil, was a major component of the original lipid. Further information was provided by the presence of long-chain fatty acyl moieties in surviving triacylglycerols and the presence of cholesterol. A fungal metabolite, mycose (trehalose), was found in all samples apart from a fire-cracked rock and points to microbiological activity in the pits. Bulk isotope analysis conducted on the ‘cemented organic residues’ is consistent with modern reference samples of blubber and oil from seal and whale. These data provide clear analytical evidence of the function of slab-lined pits in the archaeological record and suggest widespread exploitation of marine mammals for producing oil for heating, lighting and myriad other uses in the past.

This investigation examines the effects of load, speed, exhaust gas recirculation (EGR) level and hydrogen addition level on the exhaust gas emissions, particulate matter size distribution and chemical composition. The experiments were performed on a 2.0 litre, 4 cylinder, direct injection engine. EGR levels were then varied from 0% to 40%. Hydrogen induction was varied between 0 and 10% vol. of the inlet charge. In the case of using hydrogen and EGR, the hydrogen replaced air. The load was varied from 0 to 5.4 bar BMEP at two engine speeds, 1500 rpm and 2500 rpm. For this investigation the carbon monoxide (CO), total unburnt hydrocarbons (THC), nitrogen oxides (NOX) and the filter smoke number (FSN) were all measured. The in-cylinder pressure was also captured to allow the heat release rate to be calculated and, therefore, the combustion to be analysed. A gravimetric analysis of the particulate matter size distribution was conducted using a nano-MOUDI. Finally, a GC-MS was used to determine the chemical composition of the THC emissions. The experimental data showed that although CO, FSN and THC increase with EGR, NOX emissions decrease. Inversely, CO, FSN and THC emissions decrease with hydrogen, but NOX increases. When hydrogen was introduced the peak cylinder pressure was increased, as was the maximum rate of in-cylinder pressure rise. The position of the peak cylinder pressure was delayed as hydrogen addition increased. This together with the obtained heat release patterns shows an increase in ignition delay, and a higher proportion of premixed combustion. The experimental work showed that the particulate matter size distribution was not dramatically altered by the addition of EGR, but the main peak was slightly shifted towards the nucleation mode with the addition of hydrogen. Hydrogen addition does not appear to have a large effect on the chemical composition of the THC, but does dramatically decrease the emissions.

Gasoline is produced by distilling petroleum oil. This is done at a refinery, where a lot of other products are produced as well. With increasing interest in bio-fuels the fuel companies started to produce substances such as biodiesel as well as the petroleum-based fuels. These products are then transported to where they are going to be used or sold, there included both gasoline, which is a petroleum-based fuel, and biodiesel (FAME), which in Sweden is based on rapeseed oil. If the vessel for transporting gasoline, or pipeline/connections filling and emptying the tanks, has previously been used for biodiesel, there is a risk of contaminating the gasoline with biodiesel. This contamination can have a lot of different effects such as either clogging filters or injectors in both gasoline- and ethanol-based engines, or even change the properties and therefore quality of the fuel.  To ensure that the results from tests and research involving gasoline can be used and compared with each other, the quality of the fuel must have the same properties throughout all tests. This is controlled by taking samples on a regular basis and analyzing the quality and level of impurities in the fuel used in that specific test. Screening for FAME is therefore necessary which is where this thesis becomes relevant.  This thesis was carried out with the purpose to develop a new or verify an already developed method to quantify FAME in gasoline. To determine the FAME content, a standard gas chromatography method, IP 585, was used. It was changed to fit in this application, since it was originally made to determine FAME content in diesel, not gasoline. It was concluded that it was possible to determine the FAME content in gasoline when IP 585 was used as is. There were some possible alternatives to IP 585 and they will be discussed in the literature study. / Bensin framställs genom destillation av råolja. Detta görs på ett raffinaderi där ett flertal andra produkter också utvinns. På senare tid har ögonen öppnats för "biobränslen", bland annat biodiesel. Det händer därför att detta också framställs på samma plats som bensinen. Dessa produkter säljs sedan och brukar fraktas i stora tankar till företagen som köpt dem. Ifall tankarna vid transport eller rören bränslet går igenom till tankarna först använts till biodiesel och sedan används till bensin finns det stor risk att en del biodiesel hamnar i bensinen. Detta kan leda till en rad olika problem. Ett exempel är att biodieseln kan sätta igen och förstöra injektorer i bensin- och etanolmotorer. Det kan även påverka testresultat i olika testriggar, vilket är ett av fallen på Volvo. Ifall bränslet inte bibehåller samma kvalitet för varje test det används i leder det till svårigheter vid jämförelser och resultatens riktighet. Det blir därför nödvändigt att kontrollera bensinens innehåll, där inräknat screening av FAME. Detta arbete utfördes med syftet att utveckla en ny eller verifiera en redan beprövad metod för att bestämma koncentrationen FAME i bensin. För att mäta koncentrationen FAME användes en standardmetod till GC-MS, IP 585. Den modifierades något för att passa in i denna applikation då den från början var gjord för kvantifiering i diesel och inte bensin. Slutsatsen drogs att det är möjligt att mäta koncentrationen FAME i bensin med IP 585 använd som den är. Det fanns möjliga alternativ till metoden, dessa bemöts i litteraturstudien.

by Lai Wai Kai. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 70-74). / Acknowledgement --- p.iv / Abstract --- p.v / Figures and Tables --- p.vii / Abbreviations used in this study --- p.ix / Contents / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Biochemistry of cobalamin --- p.2 / Chapter 1.1.1 --- Biological functions of cobalamin --- p.2 / Chapter 1.1.2 --- Causes of cobalamin deficiency --- p.4 / Chapter 1.1.3 --- Significances of cobalamin deficiency --- p.7 / Chapter 1.1.4 --- Assessment of cobalamin deficiency --- p.8 / Chapter 1.2 --- Biochemistry of Methylmalonic acid (MMA) --- p.10 / Chapter 1.2.1 --- Elevation of MMA in biological fluids --- p.11 / Chapter 1.2.2 --- Significances of measurement of MMA --- p.11 / Chapter 1.2.3 --- Methods of measurement of urinary MMA --- p.13 / Chapter 2. --- Objectives of this project --- p.16 / Chapter 3. --- Materials and Methods / Chapter 3.1 --- Study subjects --- p.18 / Chapter 3.2 --- Sample collection --- p.18 / Chapter 3.3 --- Biochemical and haematological analysis --- p.18 / Chapter 3.4 --- Measurement of urinary creatinine concentration --- p.19 / Chapter 3.5 --- Measurement of serum cobalamin concentration --- p.20. / Chapter 3.6 --- GC-MS determination of urinary MMA --- p.21 / Chapter 3.7 --- Statistical analysis --- p.24 / Chapter 4. --- Results / Chapter 4.1 --- Clinical features of subjects --- p.28 / Chapter 4.2 --- General blood analysis --- p.28 / Chapter 4.3 --- Serum cobalamin analysis --- p.30 / Chapter 4.4 --- Urinary MMA analysis --- p.33 / Chapter 4.5 --- Relationship between urinary MMA excretion and age --- p.53 / Chapter 4.6 --- Relationship between urinary MMA excretion and serum cobalamin concentrations --- p.53 / Chapter 5. --- Discussions / Chapter 5.1 --- Serum cobalamin analysis --- p.62 / Chapter 5.2 --- Urinary MMA analysis --- p.62 / Chapter 5.3 --- Relationship between urinary MMA excretion and age --- p.66 / Chapter 5.4 --- Relationship between urinary MMA excretion and serum cobalamin concentration --- p.66 / Chapter 5.5 --- Relationship between urinary MMA excretion and diet --- p.68 / Chapter 6. --- Conclusions --- p.69 / Chapter 7. --- References --- p.70