Experiment Planning for Protein Structure Elucidation and Site-Directed Protein Recombination

In order to most effectively investigate protein structure and improve protein function, it is necessary to carefully plan appropriate experiments. The combinatorial number of possible experiment plans demands effective criteria and efficient algorithms to choose the one that is in some sense optimal. This thesis addresses experiment planning challenges in two significant applications. The first part of this thesis develops an integrated computational-experimental approach for rapid discrimination of predicted protein structure models by quantifying their consistency with relatively cheap and easy experiments (cross-linking and site-directed mutagenesis followed by stability measurement). In order to obtain the most information from noisy and sparse experimental data, rigorous Bayesian frameworks have been developed to analyze the information content. Efficient algorithms have been developed to choose the most informative, least expensive, and most robust experiments. The effectiveness of this approach has been demonstrated using existing experimental data as well as simulations, and it has been applied to discriminate predicted structure models of the pTfa chaperone protein from bacteriophage lambda. The second part of this thesis seeks to choose optimal breakpoint locations for protein engineering by site-directed recombination. In order to increase the possibility of obtaining folded and functional hybrids in protein recombination, it is necessary to retain the evolutionary relationships among amino acids that determine protein stability and functionality. A probabilistic hypergraph model has been developed to model these relationships, with edge weights representing their statistical significance derived from database and a protein family. The effectiveness of this model has been validated by showing its ability to distinguish functional hybrids from non-functional ones in existing experimental data. It has been proved to be NP-hard in general to choose the optimal breakpoint locations for recombination that minimize the total perturbation to these relationships, but exact and approximate algorithms have been developed for a number of important cases

The function of NaV1.8 clusters in lipid rafts

NaV1.8 is a voltage gated sodium channel mainly expressed on the membrane of thin diameter c-fibre neurons involved in the transmission of pain signals. In these neurons NaV1.8 is essential for the propagation of action potentials. NaV1.8 is located in lipid rafts along the axons of sensory neurons and disruption of these lipid rafts leads to NaV1.8 dependant conduction failure. Using computational modelling, I show that the clustering of NaV1.8 channels in lipid rafts along the axon of thin diameter neurons is energetically advantageous and requires fewer channels to conduct action potentials. During an action potential NaV1.8 currents across the membrane in these thin axons are large enough to dramatically change the sodium ion concentration gradient and thereby void the assumptions upon which the cable equation is based. Using scanning electron microscopy NaV1.8 is seen to be clustered, as are lipid raft marker proteins, on neurites at scales below 200nm. FRET signals show that the lipid raft marker protein Flotillin is densely packed on the membrane however disruption of rafts does not reduce the FRET signal from dense protein packing. Using mass spectrometry I investigated the population of proteins found in the lipid rafts of sensory neurons. I found that the membrane pump NaK-ATPase, which restores the ion concentrations across the membrane, is also contained in lipid rafts. NaK-ATPase may help to offset concentration changes due to NaV1.8 currents enabling the repeated firing of c-fibres, which is associated with spontaneous pain in chronic pain disorders.Open Acces

Markov chain Monte Carlo analyses of longitudinal biomedical magnetic resonance data

Markov chain Monte Carlo simulation was used in an analysis of the data acquired in three longitudinal biomedical magnetic resonance studies. The first of these investigations uses a Bayesian nonlinear hierarchical random coefficients model to examine the longitudinal extracellular direct current (DC) potential and apparent diffusion coefficient (ADC) responses to focal ischaemia in the rat. The purpose is to perform a formal analysis of the temporal relationship between the two responses, and thus to examine the data for compatibility with a common latent (driving) process and, alternatively, the existence of an ADC threshold for anoxic depolarisation. The DC-potential and ADC transition parameter posterior probability distributions were generated, paying particular attention to the within-subject differences between the DC-potential and ADC transition characteristics. The results indicate that the DC-potential and ADC changes are not driven by a common latent process and, in addition, provide no evidence for a consistent ADC threshold associated with anoxic depolarisation. The second analysis uses data acquired in a nuclear magnetic resonance spectroscopic study into the effects of intestinal ischaemia and subsequent reperfusion on liver metabolism in the rat. The purpose of the analysis is to examine the temporal relationship between energy status [inorganic phosphate to adenosine triphosphate ratio (PAR)] and the pH response, the former of which is an indicator of liver energy failure. The posterior distribution obtained for the PAR-pH onset time difference indicates that the pH response precedes the change in PAR, suggesting that intracellular acidosis cannot be ruled out as a contributing factor to the observed liver failure. The third dataset was acquired in an electron spin resonance study of the Arrhenius behaviour of the rabbit muscle sarcoplasmic reticulum membrane. An MCMC Arrhenius plot changepoint analysis is used to estimate the order parameter 'transition' temperature

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement

Predicting Flavonoid UGT Regioselectivity with Graphical Residue Models and Machine Learning.

Machine learning is applied to a challenging and biologically significant protein classification problem: the prediction of flavonoid UGT acceptor regioselectivity from primary protein sequence. Novel indices characterizing graphical models of protein residues are introduced. The indices are compared with existing amino acid indices and found to cluster residues appropriately. A variety of models employing the indices are then investigated by examining their performance when analyzed using nearest neighbor, support vector machine, and Bayesian neural network classifiers. Improvements over nearest neighbor classifications relying on standard alignment similarity scores are reported

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Towards chemical profiling at the cellular level

Traditional methods for the analysis of cellular components have focused on 'grid and find' assays that provide quantitative information from a large population of cells, often as many as a million cells. The results of these studies are often presented only as the percentage of the dry weight of the cells and not the concentration within individual cells. The research presented in this thesis is concerned with the development and application of methods for single cell sampling and analysis (SiCSA) from fungal cells that overcomes this deficit. The methods developed offer the potential to investigate the intra-cellular concentration of biologically relevant molecules within selected cells of a heterogeneous population. The instruments and techniques for this work are described along with an overview of the fundamental principles behind this methodology. The model organism studied in this work was the filamentous fungi, Neurospora crassa, the orange bread mould. It is the best characterised of all the filamentous fungi, a group of organisms that are critically important to agriculture, medicine and the environment. Capillary electrophoresis electrospray mass spectrometry (CE-ESIMS) was used to measure the intra-cellular concentration of disaccharides, in particular trehalose. In Neurospora crassa this molecule is synthesised in response to environmental stress, and has been reported to accumulate at concentrations as high as 10 mM, based on measurements using bulk cell populations. The value of 1.3 mM for the intra-cellular concentration of disaccharide measured in the single cell sampling experiments described in this thesis is in good agreement with this previously published maximum concentration. Following topical application of a commercially relevant fungicide, azoxystrobin, to cell cultures of Neurospora crassa, the intra-cellular concentration of the fungicide was measured. For cells treated with azoxystrobin at a concentration of 14.8 pM (the saturation concentration of azoxystrobin in water), the intra-cellular concentration was shown to reach 9.9 μM within 5 minutes. It is likely that the high surface to volume ratio of the fungal hyphae facilitats the rapid diffusion of these large hydrophobic molecules across the cell membrane. The development of novel instrumentation applicable to the analysis of ultra-low volume samples is presented, encompassing microsampling, transfer, ionisation and detection. Their utility in comparison with competing techniques is discussed, along with suggestions as to the expected development of this technique and possible directions for future work

Exploring the Multifaceted Roles of Glycosaminoglycans (GAGs) - New Advances and Further Challenges

Glycosaminoglycans are linear, anionic polysaccharides (GAGs) consisting of repeating disaccharides. GAGs are ubiquitously localized throughout the extracellular matrix (ECM) and to the cell membranes of cells in all tissues. They are either conjugated to protein cores in the form of proteoglycans, e.g., chondroitin/dermatan sulfate (CS/DS), heparin/heparan sulfate (Hep/HS) and keratan sulfate (KS), as well as non-sulfated hyaluronan (HA). By modulating biological signaling GAGs participate in the regulation of homeostasis and also participate in disease progression. The book, entitled “Exploring the multifaceted roles of glycosaminoglycans (GAGs)—new advances and further challenges”, features original research and review articles. These articles cover several GAG-related timely topics in structural biology and imaging; morphogenesis, cancer, and other disease therapy and drug developments; tissue engineering; and metabolic engineering. This book also includes an article illustrating how metabolic engineering can be used to create the novel chondroitin-like polysaccharide.A prerequisite for communicating in any discipline and across disciplines is familiarity with the appropriate terminology. Several nomenclature rules exist in the field of biochemistry. The historical description of GAGs follows IUPAC and IUB nomenclature. New structural depictions such as the structural nomenclature for glycan and their translation into machine-readable formats have opened the route for cross-references with popular bioinformatics resources and further connections with other exciting “omics” fields

An automated fluorescence lifetime imaging multiwell plate reader: application to high content imaging of protein interactions and label free readouts of cellular metabolism

This thesis reports on work performed in the development and application of an automated plate reading microscope implementing wide field time gated fluorescence lifetime imaging technology. High content analysis (HCA) imaging assays enabled by automated microscopy platforms allow hundreds of conditions to be tested in a single experiment. Though fluorescence lifetime imaging (FLIM) is established in life sciences applications as a method whereby quantitative information may be extracted from time-resolved fluorescence signals, FLIM has not been widely adopted in an HCA context. The FLIM plate reader developed throughout this PhD has been designed to allow HCA-FLIM experiments to be performed and has been demonstrated to be capable of recording multispectral, FLIM and bright field data from 600 fields of view in less than four hours. FLIM is commonly used as a means of reading out Förster resonance energy transfer (FRET) between fluorescent fusion proteins in cells. Using the FLIM plate reader to investigate large populations of cells per experimental condition without significant user input has allowed statistically significant results to be obtained in FRET experiments that present relatively small changes in mean fluorescent lifetime. This capability has been applied to investigations of FOXM1 SUMOylation in response to anthracycline treatment, and to studies of the spatiotemporal activation profiles of small GTPases. Furthermore, the FLIM plate reader allows FLIM-FRET to be applied to protein-protein interaction screening. The application of the instrument to screening RASSF proteins for interaction with MST1 is discussed. The FLIM plate reader was also configured to utilise ultraviolet excitation radiation and optimised for the measurement of autofluorescence lifetime for label-free assays of biological samples. Experiments investigating the autofluorescence lifetime of live cells under the influence of metabolic modulators are presented alongside the design considerations necessary when using UV excitation for HCA-FLIM.Open Acces