1,523 research outputs found

    Multi-Snapshot Imaging for Chromatographic Peak Analysis

    Get PDF

    Characterization of Transport and Adsorption Mechanisms in Chromatographic Media

    Get PDF
    This work deals with experimentally determined binding orientations of lysozyme on different chromatographic adsorber materials at varying mobile phase compositions (ionic strength and pH). Findings were correlated with molecular dynamics simulations and used to obtain a model approach to predict protein retention times in ion-exchange chromatography. The second part of this work deals with confocal laser-scanning microscopy as a tool to visualize protein transpiort in chromatographic media

    To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

    Get PDF
    Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies

    Computational studies of origins of life scenarios

    Get PDF
    Understanding the origins of life on Earth is one of the most intriguing problems facing science today. In the research presented here, we apply computational methods to explore origins of life scenarios. In particular, we focus on the origins of the genetic code and the intersection between geochemistry and a primordial ``biochemistry" in which mononucleotides could form short oligoucleotide chains. We also apply quantum chemical methods to a modern biochemical reaction, the charging of tRNA by an aminoacyl-tRNA synthetase, in order to shed light on the possible chemistry one may want to consider in problems relating to the origins of life. The question of how codons came to be associated with specific amino acids in the present form of the genetic code is one fundamental part of gaining insight into the origins of life. Carl Woese and coworkers designed a series of experiments to test associations between amino acids and nucleobases that may have played a role in establishing the genetic code. Through these experiments it was found that a property of amino acids called the polar requirement (PR) is correlated to the organization of the codon table. No other property of amino acids has been found that correlates with the codon table as well as PR, indicating that PR is uniquely related to the modern genetic code. Using molecular dynamics simulations of amino acids in solutions of water and dimethylpyridine used to experimentally measure PR, we show that variations in the partitioning between the two phases as described by radial distribution functions correlate well with the measured PRs. Partition coefficients based on probability densities of the amino acids in each phase have the linear behavior with base concentration as suggested by the PR experiments. We also investigate the possible roles of inorganic mineral surfaces in catalysis and stabilization of reactions essential for early forms of replicating systems that could have evolved into biochemical processes we know today. We study a proposed origins of life scenario involving the clay montmorillonite, as well as a generalized form of a charged surface, and their catalytic role in forming oligonucleotides from activated mononucleotides. Clay and mineral surfaces are important for concentrating the reactants and for promoting nucleotide polymerization reactions. Using classical molecular dynamics methods we provide atomic details of reactant conformations prior to polynucleotide formation, lending insight into previously reported experimental observations of this phenomenon. The simulations clarify the catalytic role of metal ions, demonstrate that reactions leading to correct linkages take place primarily in the interlayer, and explain the observed sequence selectivity in the elongation of the chain. The study comparing reaction probabilities involving L- and D- chiral forms of the reactants has found enhancement of homochiral over heterochiral products when catalyzed by montmorillonite. Finally, we shift our perspective on the problem of the origins of life, by considering a modern biological reaction which is essential to all forms of life today: the charging of tRNA with correct amino acids according to their anticodons. These reactions are performed by amino-acyl tRNA synthetases (AARSs), and are essential for enforcing the genetic code. While studies involving the PR and code optimality apply to a more error-prone epoch of early biology, possibly forming ``statistical proteins" whose sequence is determined probabilistically by a loose mechanism of assignment of amino acids based on (possibly) PR, the mechanisms that charge tRNA today are highly refined to charge only the correct amino acid to a tRNA, and are thus essential for the high-fidelity translation mechanism present in all living cells. To gain some insight into how the charging reaction may have come about, we apply quantum chemical methods to a problem of modern biology to gain a further understanding of the mechanisms behind biochemical reactions

    A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

    Get PDF
    In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s)

    OmicsVis: an interactive tool for visually analyzing metabolomics data

    Get PDF
    When analyzing metabolomics data, cancer care researchers are searching for differences between known healthy samples and unhealthy samples. By analyzing and understanding these differences, researchers hope to identify cancer biomarkers. Due to the size and complexity of the data produced, however, analysis can still be very slow and time consuming. This is further complicated by the fact that datasets obtained will exhibit incidental differences in intensity and retention time, not related to actual chemical differences in the samples being evaluated. Additionally, automated tools to correct these errors do not always produce reliable results. This work presents a new analytics system that enables interactive comparative visualization and analytics of metabolomics data obtained by two-dimensional gas chromatography-mass spectrometry (GC × GC-MS). The key features of this system are the ability to produce visualizations of multiple GC × GC-MS data sets, and to explore those data sets interactively, allowing a user to discover differences and features in real time. The system provides statistical support in the form of difference, standard deviation, and kernel density estimation calculations to aid users in identifying meaningful differences between samples. These are combined with novel transfer functions and multiform, linked visualizations in order to provide researchers with a powerful new tool for GC × GC-MS exploration and bio-marker discovery

    A system-wide stable isotope labeling approach for connecting natural products to their biosynthetic gene clusters

    Get PDF
    Although the first bacterial genome sequence was published almost 20 years ago, there is still no generalizable method for automatically assigning natural products to their cognate biosynthetic gene clusters (BGCs). This thesis describes the development of a mass spectrometry-based parallel stable isotope labeling (SIL) platform, termed IsoAnalyst, which automatically associates metabolite stable isotope labeling patterns with BGC structure prediction in order to connect natural products to their cognate BGCs. The parallel SIL experiments were optimized for small scale and a custom tool written in Python was developed for the untargeted detection and interpretation of SIL labeling patterns. This approach was validated in the industrial production strains Saccharopolyspora erythraea and Amycolatopsis mediterranei demonstrating that the compounds erythromycin A and rifamycin SV respectively, could be associated with the proper BGCs based on the distribution of isotopomer labeling patterns. The method was further validated by connecting known biosynthetic intermediates of these compounds to their associated BGCs and the identification of various siderophores through a combination of SIL labeling patterns and MS/MS fragmentation data. Extension to environmental organisms using a sequenced Micromonospora sp. from our Actinobacterial isolate library led to the discovery of lobosamide D, a new member of the lobosamide family of natural products, and an update to the lobosamide BGC to include relevant tailoring enzymes. This discovery illustrates the power of the IsoAnalyst platform for identifying new compounds, linking molecules to BGCs, and generating new knowledge about biosynthesis

    Metabolic profiling and pathway mapping of cardiovascular disease

    Get PDF
    In this thesis, metabolic profiling (MP) platforms were utilised to interrogate the manifestation of cardiovascular disease and provide candidate biomarkers. A number of LC-MS and NMR methodologies were employed. Data processing was followed by assessment using multivariate (MVDA) and univariate (UV) statistics. MP is applied under three cardiovascular disease themes: 1) plaque rupture, 2) plaque formation, and 3) arterial ectopic calcification. Statistically significant features were structurally assigned. Identified metabolites were mapped to their corresponding biochemical pathways. For MP of ruptured plaque, tissue from symptomatic and asymptomatic patients for stroke was used. After detection of statistically significant features and structural assignment, two biochemical pathways showed dysregulations: the arachidonic acid pathway, indicating increased levels of inflammation, and the β-oxidation pathway with increased levels of three acyl-carnitines. Tissue extracts were used to investigate plaque formation. Arterial intima tissue, incorporating plaque lesions (carotid and femoral), was compared to intimal thickening tissue. Intima thickening demonstrated distinct MP compared to plaques. Plaques from different anatomical locations also demonstrated altered MP. After metabolite assignment, pathway mapping revealed dysregulations common to both anatomical locations. These were cholesterol, ceramide, purine, pyrimidine and β-oxidation pathways. These pathways are related to inflammation and apoptosis. A metabolite previously unassociated to atherogenesis was detected with strong statistical significance (t-test; p≥9.8x10-12), namely phosphatidylethanolamine-ceramide. It also demonstrated high correlations to cholesterol, a well-established risk-factor of atherosclerosis. The third theme of the project explores ectopic cardiovascular calcification. Experiments were conducted on blood serum. Patients with coronary artery and aortic valve calcification were compared with non-calcified controls. Phosphatidylcholine moieties and sphingomyelins were the major discriminating metabolites between cases and controls. These are involved in inflammation and apoptosis. The two diseases manifested different profiles with only three commonly dysregulated metabolites. A number of experiments using additional samples and bottom-up approaches will follow to provide validation of results.Open Acces

    Identification and Quantification of Black Carbon Particulates in Urban River Sediments Involving a Multi-tiered Analytical Approach

    Get PDF
    Black Carbon (‘BC’) is routinely defined as the residual carbon fraction resulting from the incomplete combustion of biomass and/or biofuels (Agarwal et al. 2011). BC is best described as spectrum of carbonaceous combustion by-products, encompassing partially combusted, charred plant tissues, to highly graphitized soot (Shrestha et al. 2010). The highly condensed aromatic structures which exist in the BC matrix are largely responsible for its resistance to further biological or chemical degradation, as well as, its efficient sorption properties in soils and sediments (Forbes et al., 2006; Shrestha et al., 2010). Using a multi-tiered geochemical approach, quantification of BC was coupled with environmental forensics of other contaminants of concern in a highly urbanized/industrialized, tidally influenced river (Lower Hackensack River, New Jersey, USA). This approach allowed for further understanding involving the accumulation and mobility of BC particles in relation to other contaminants of concern and the sedimentation fluxes and hydrodynamic processes which influence them. Review of BC as a potential index parameter for other hydrophobic organic compounds, such as the ever-persistent polycyclic aromatic hydrocarbons (PAHs), was included as part of this research due to their synchronous co-emission inputs and complimentary high sorption capabilities. Analytical quantitative efforts included an array of chemical, thermal and oxidative isolation/extraction techniques including: the Lloyd Kahn method for total organic carbon (TOC) analysis, modified TOC analysis for BC determination, EPA Method 8270 for priority PAHs, loss on ignition (LOI), pyrolysis-gas chromatography mass spectrometry (Py-GC/MS) for evaluation of parent and alkylated PAH assemblages, chemothermal oxidation at 375oC (CTO-375), and major and minor elemental analysis involving scanning electron microscopy (SEM). PAH ratios of various principal masses (m/z 178, 202, 228, etc.,) were also utilized in conjunction with alkyl PAH series ratios to infer potential BC source inputs and to allow for a comprehensive analysis of the chemical characteristics of the historically impacted Lower Hackensack River sediment. Lastly, routine ecological and risk assessment analytical techniques, such as grain size distribution and percent moisture (of sediments) were included as part of this comprehensive sediment study. Historical river-sediment data provided by several federal and state agencies were also evaluated to allow for elucidation of spatial trends relative to heavy metal concentrations, PAHs and other contaminants of concern. Ultimately, the results indicate relatively low concentrations of BC (in comparison to TOC) throughout the lower river sediments, with a general increasing trend observed further downstream adjacent to various petroleum related industries. Qualitative and quantitative analysis of BC particles via SEM further revealed the likely presence of coal fly ash, and various amorphous pyrolytic BC particles. The results of this study also demonstrate the importance of considering different analytical approaches when attempting to quantify BC stocks in an urbanized waterway such as the Lower Hackensack River
    • …
    corecore