Metabolic profiling on 2D NMR TOCSY spectra using machine learning

Due to the dynamicity of biological cells, the role of metabolic profiling in discovering biological fingerprints of diseases, and their evolution, as well as the cellular pathway of different biological or chemical stimuli is most significant. Two-dimensional nuclear magnetic resonance (2D NMR) is one of the fundamental and strong analytical instruments for metabolic profiling. Though, total correlation spectroscopy (2D NMR 1H -1H TOCSY) can be used to improve spectral overlap of 1D NMR, strong peak shift, signal overlap, spectral crowding and matrix effects in complex biological mixtures are extremely challenging in 2D NMR analysis. In this work, we introduce an automated metabolic deconvolution and assignment based on the deconvolution of 2D TOCSY of real breast cancer tissue, in addition to different differentiation pathways of adipose tissue-derived human Mesenchymal Stem cells. A major alternative to the common approaches in NMR based machine learning where images of the spectra are used as an input, our metabolic assignment is based only on the vertical and horizontal frequencies of metabolites in the 1H-1H TOCSY. One- and multi-class Kernel null foley–Sammon transform, support vector machines, polynomial classifier kernel density estimation, and support vector data description classifiers were tested in semi-supervised learning and novelty detection settings. The classifiers’ performance was evaluated by comparing the conventional human-based methodology and automatic assignments under different initial training sizes settings. The results of our novel metabolic profiling methods demonstrate its suitability, robustness, and speed in automated nontargeted NMR metabolic analysis

Analytical and computational methods towards a metabolic model of ageing in Caenorhabditis elegans

Human life expectancy is increasing globally. This has major socioeconomic implications, but also raises scientific questions about the biological bases of ageing and longevity. Research on appropriate model organisms, such as the nematode worm Caenorhabditis elegans, is a key component of answering these questions. Ageing is a complex phenomenon, with both environmental and genetic influences. Metabolomics, the analysis of all small molecules within a biological system, offers the ability to integrate these complex factors to help understand the role of metabolism in ageing. This thesis addresses the current lack of methods for C. elegans metabolite analysis, with a particular focus on combining analytical and computational approaches. As a first essential step, C. elegans metabolite extraction protocols for NMR, GC-MS and LC-MS based analysis were optimized. Several methods to improve the coverage, automatic annotation and data analysis steps of NMR and GC-MS are proposed. Next, stable isotope labelling was explored as a tool for C. elegans metabolomics. An automated stable isotope based workflow was developed, which identifies all biological, non-redundant features within a LC-MS acquisition and annotates them with molecular compositions. This demonstrated that the vast majority (> 99.5%) of detected features inside LC-MS metabolomics experiments are not of biological origin or redundant. This stable isotope workflow was then used to compare the metabolism of 24 different C. elegans mutant strains from different pathways (e.g. insulin signalling, TOR pathway, neuronal signalling), with differing levels of lifespan extension compared to wild-type worms. The biologically relevant features (metabolites) were detected and annotated, and compared across the mutants. Some metabolites were correlated with longevity across the mutant set, in particular, glycerophospholipids. This led to the formulation of a hypothesis, that lifespan extension in C. elegans requires increased activity of common downstream longevity effector mechanisms (autophagy, and mitochondrial biogenesis), that also involve subcellular compartmentation and hence membrane formation. This results in the alterations in lipid metabolism detected here.Open Acces

Computational Tools for the Processing and Analysis of Time-course Metabolomic Data

Modern, high-throughput techniques for the acquisition of metabolomic data, combined with an increase in computational power, have provided not only the need for, but also the means to develop and use, methods for the interpretation of large and complex datasets. This thesis investigates the methods by which pertinent information can be extracted from nontargeted metabolomic data and reviews the current state of chemometric methods. The analysis of real-world data and research questions relevant to the agri-food industry reveals several problems for which novel solutions are proposed. Three LC-MS datasets are studied: Medicago, Alopecurus and aged Beef, covering stress resistance, herbicide resistance and product misbranding. The new methods include preprocessing (batch correction, data-filtering), processing (clustering, classification) and visualisation and their use facilitated within a flexible data-to-results pipeline. The resulting software suite with a user-friendly graphical interface is presented, providing a pragmatic realisation of these methods in an easy to access workflow

Actinobacterial diversity in Atacama Desert habitats as a road map to biodiscovery

PhD ThesisThe Atacama Desert of Northern Chile, the oldest and driest nonpolar desert on the planet, is known to harbour previously undiscovered actinobacterial taxa with the capacity to synthesize novel natural products. In the present study, culture-dependent and culture-independent methods were used to further our understanding of the extent of actinobacterial diversity in Atacama Desert habitats. The culture-dependent studies focused on the selective isolation, screening and dereplication of actinobacteria from high altitude soils from Cerro Chajnantor. Several strains, notably isolates designated H9 and H45, were found to produce new specialized metabolites. Isolate H45 synthesized six novel metabolites, lentzeosides A-F, some of which inhibited HIV-1 integrase activity. Polyphasic taxonomic studies on isolates H45 and H9 showed that they represented new species of the genera Lentzea and Streptomyces, respectively; it is proposed that these strains be designated as Lentzea chajnantorensis sp. nov. and Streptomyces aridus sp. nov.. Additional isolates from sampling sites on Cerro Chajnantor were considered to be nuclei of novel species of Actinomadura, Amycolatopsis, Cryptosporangium and Pseudonocardia. A majority of the isolates produced bioactive compounds that inhibited the growth of one or more strains from a panel of six wild type microorganisms while those screened against Bacillus subtilis reporter strains inhibited sporulation and cell envelope, cell wall, DNA and fatty acid synthesis. Initial culture-independent studies were carried out to establish the extent of actinobacterial diversity in a range of hyper- and extreme hyper-arid Atacama Desert soils. Community DNA extracted from soil collected from the sampling sites was surveyed for actinobacteria by 454 pyrosequencing; rarefaction analyses indicated good coverage at most of the sites. The results revealed an amazing and unexpected taxonomic diversity at the ranks of order, family and genus, much of it novel. The total number of genera, for instance, is 328, of which around 40% could not be assigned to validly published genera. Rank abundancy profiles indicated that much of this diversity can be attributed to low abundancy taxa. Similar results were obtained from community DNA extracted from surface and subsurface soil samples collected at three different altitudes on Cerro Chajnantor. Actinobacterial community structure at these sampling sites was influenced by altitude and sampling depth, as well as several environmental variables that included conductivity, pH, redox potential and organic matter content. It is evident from these studies that the Atacama Desert landscape abounds in novel actinobacterial taxa that synthesize a broad range of specialized metabolites that can be developed as drug leads.Ministry of Higher Education Malaysia for a scholarship and my employer, Universiti Pendidikan Sultan Idris, Malaysi

Novel biomarkers of renal transplant failure/dysfunction via spectroscopic phenotyping

Successful renal transplantation not only improves patients’ quality and duration of life, but also confers a substantial economic healthcare cost saving. With the growing burden of end-stage renal disease and the requirement for renal replacement therapy, strategies to augment transplant success and subsequent graft survival become more vital than ever. Herein, an objective means of characterising renal function across the transplant journey, and appropriately stratifying in accordance to individual contingencies/factors (including the early detection of renal dysfunction), based on metabolism is explored. Patient pairs, recipients and donors, were metabolically phenotyped prior to (24 h) and post (days 1–5) transplantation using a multi-platform analytical approach (i.e., Nuclear Magnetic Resonance Spectroscopy (NMR) and Mass Spectrometry (MS)) of urine and plasma (n = 50). Using advanced statistics, the resulting metabolic profiles were subsequently modelled, and related to multiple clinical phenotypes (and outcomes), to increase the understanding of molecular changes/signatures across transplantation, capturing valuable information pertinent to transplant type, cause, co-morbidity, modality, immunology and complication (p-value < 0.05) – over donors as well as recipients. An attempt to then develop predictive algorithms for the early detection of renal dysfunction was preliminary defined within the confines of the study design, where integrated NMR and MS metabolic data improved patient stratification for complications over clinical measures (receiver operator characteristic area under curve over 0.900) and potentially replace current measures. While prospective/multicentre studies are imperative for subsequent real-world adoption (qualification/validation), the work conducted herein encompassed much of the first stage of marker development – discovery – where metabolic phenotyping renal transplantation has provided a deeper characterisation of patient journeys with new insights into multiple contingencies/factors (including complication). Such findings infer the value of metabolic phenotyping to augment and potentially replace current measures and methods to better inform decision making in the clinic on the individual/precision level.Open Acces

Control of Dynamic Supramolecular Systems

This thesis explores the control and application of complex dynamic system chemistry in the nanoscale by (1) manipulating interactions across lipid membranes and on the molecular level (2) through the manipulation of shapeshifting molecules. (1) This project involves the design and development of a library of artificial molecular carriers to be tested for successful bicarbonate targeting. These molecules are designed to instigate the active transport of ions across lipid membranes, 'pumping' ions from areas of low concentration to areas of higher concentration. These carriers can do this by consuming a fuel–redox energy supplied by the charge separation already present in photosynthetic apparatus. The preliminary data of our molecular artificial devices in the presence of plant cells suggest that these transporters have an influence on cell morphology due to possible cell membrane incorporation. Furthermore, emission studies revealed that molecular devices have an impact on the photosynthetic apparatus of the cell which is desired. These results are encouraging for the incorporation of molecular devices in plants. (2) In dynamic covalent chemistry, dynamic covalent rearrangements of fluxional carbon cages, such as bullvalenes and barbaralanes, impart shapeshifting molecular properties which have sparingly been studied. This research project focuses on developing methodologies to concretely control these dynamic fluxional carbon cages to simplify and analyse their structural complexity. Non-covalent control was achieved through the encapsulation of these fluxional molecules. This host-guest chemistry can control the dynamic regioisomerism & stereochemistry through molecular metal-organic cages and chiral macrocycles. For covalent control, the configuration of the cage is controlled by covalently tethered functional moieties. These methodologies involve incorporating phosphine-based ligands to control shapeshifting molecules through metal coordination. The development of such techniques will allow routine access to shapeshifting systems to explore their properties and application beyond synthetic, physical organic chemistry, and at the interfaces with materials chemistry and biolog

Stability and Strain in Hisactophilin and Mechanism of the Myristoyl Switch

Hisactophilin is a myristoylated, histidine-rich, pH-dependent actin- and membrane-binding protein. In response to cellular changes in pH, this β-trefoil protein reversibly switches between cytosolic and membrane- bound forms. A key feature of the reversible membrane-binding is the covalent acylation of the N-terminal glycine with a C14 myristoyl group. At pH > 6.9, the myristoyl group favours sequestration in the barrel of the β-trefoil, whereas at pH < 6.9, the myristoyl group favours increased solvent accessibility and eventually anchors hisactophilin to the inner leaflet of the cell membrane. In Dictyostelium discoideum, membrane-bound hisactophilin also binds and bundles actin, contributing to cell locomotion. Despite widespread myristoylation of eukaryotic proteins, its effects on protein folding, stability, and function are still poorly understood and limits our understanding of a broader set of switches and the ability to design them. Combining equilibrium denaturation, folding kinetics, variable temperature and variable pH nuclear magnetic resonance (NMR), chemical shift perturbations, and reverse micelle encapsulation, we use hisactophilin as a model for characterizing the determinants of finely tuned myristoyl switches. Equilibrium stability measurements identified hisactophilin mutants with broken switches—in which pH ceases influencing conformational switching—and switches with tuned sensitivities. In a few cases, stunningly small changes to amino acid side chains broke the pH-dependent myristoyl switch. Interestingly, a thermodynamic switch broken by one mutation may be repaired by making additional mutations, illustrating novel synergistic contributions to global stability and switching. Studying the mutants also revealed that a predominant effector of switching appears to be strain from an overpacked core when the myristoyl group is sequestered in the binding pocket. Altering strain through changing the geometry of the myristoyl binding pocket offers a new approach for tuning the sensitivity of hisactophilin and other switch proteins, as well as to inform future design efforts. The temperature dependence of amide proton chemical shifts localized myristoyl-induced strain to a set of residues in wild-type hisactophilin’s myristoyl-binding pocket. The mutants with broken switches (I85L, which favours the accessible state, and F6L/I85L/I93L, which favours the sequestered state), however, no longer show evidence of strain. Nonlinear temperature dependence of chemical shifts indicate that dynamics in residues that report on switching adjacent to the myristoyl group are also attenuated in broken-switch mutants. Thus, the strained residues in the protein core appear to form part of the communication network between the proton binding site(s) and the myristoyl group. Apparent pKas of backbone amide protons for I85L and LLL obtained by NMR-monitored pH titrations further support the decoupling of residues adjacent to the myristoyl group from switching. While we have achieved a high resolution and unrivalled look at the mechanism of hisactophilin’s pH-dependent myristoyl switch, we have also shown the validity and utility of chemical shift temperature dependences for characterizing small, functionally relevant local stability changes and gaining insight to the near-native energy landscape and its relation to protein function. Myristoyl switches participate in important cell signalling cascades by forming reversible protein- membrane or protein-protein interactions in response to environmental stimuli. Notwithstanding their prevalence, the high sensitivity and cooperativity of myristoyl switches complicates their study, resulting in poorly understood determinants and mechanisms. By employing thermodynamic measurements and developing a new, general application of an NMR technique, we have developed a detailed picture of the mechanism of a pH-dependent myristoyl switch

HSQC spectral based similarity matching of compounds using nearest neighbours and a fast discrete genetic algorithm

HSQC spectra are routinely acquired for chemical structure analysis based on hydrogen and carbon chemical environments. Two fast HSQC peak matching algorithms have been developed; a nearest neighbour approach and a probabilistic method based on an existing discrete genetic algorithm. Both of these techniques are intended to find HSQC spectra matches that supplement information generated by established molecular fingerprint methods. Our results are compared to those calculated using a specific implementation of molecular fingerprints. The nearest neighbour and genetic algorithm-based methods ranked highly particular structures missed by molecular fingerprints. Our analysis shows that by complementing molecular fingerprint matches with our findings, a comprehensive list of matches can be identified. The refined list of compounds could be used to improve the quality of compounds used in screening libraries in the pharmaceutical industry