Computational Methods on Study of Differentially Expressed Proteins in Maize Proteomes Associated with Resistance to Aflatoxin Accumulation

Plant breeders have focused on improving maize resistance to Aspergillus flavus infection and aflatoxin accumulation by breeding with genotypes having the desirable traits. Various maize inbred lines have been developed for the breeding of resistance. Identification of differentially expressed proteins among such maize inbred lines will facilitate the development of gene markers and expedite the breeding process. Computational biology and proteomics approaches on the investigation of differentially expressed proteins were explored in this research. The major research objectives included 1) application of computational methods in homology and comparative modeling to study 3D protein structures and identify single nucleotide polymorphisms (SNPs) involved in changes of protein structures and functions, which can in turn increase the efficiency of the development of DNA markers; 2) investigation of methods on total protein profiling including purification, separation, visualization, and computational analysis at the proteome level. Special research goals were set on the development of open source computational methods using Matlab image processing tools to quantify and compare protein expression levels visualized by 2D protein electrophoresis gel techniques

Power and limitations of electrophoretic separations in proteomics strategies

Proteomics can be defined as the large-scale analysis of proteins. Due to the complexity of biological systems, it is required to concatenate various separation techniques prior to mass spectrometry. These techniques, dealing with proteins or peptides, can rely on chromatography or electrophoresis. In this review, the electrophoretic techniques are under scrutiny. Their principles are recalled, and their applications for peptide and protein separations are presented and critically discussed. In addition, the features that are specific to gel electrophoresis and that interplay with mass spectrometry (i.e., protein detection after electrophoresis, and the process leading from a gel piece to a solution of peptides) are also discussed

Microfluidics for the Analysis of Integral Membrane Proteins: A Top-down Approach

The development of fully automated and high-throughput systems for proteomics is now in demand because of the need to generate new protein-based disease biomarkers. Unfortunately, it is difficult to identify protein biomarkers that are low abundant when in the presence of highly abundant proteins, especially in complex biological samples like serum, cell lysates, and other biological fluids. Membrane proteins, which are in many cases of low abundance compared to cytosolic proteins, have various functions and can provide insight into the state of disease and serve as targets for new drugs making them attractive biomarker candidates. Traditionally, proteins are identified through the use of gel electrophoretic techniques and two-dimensional protein profile patterns have been used as potential diagnostic tools for biomarker discovery and the profiles from protein content of body fluids or cells are available in databases. However, gel electrophoretic methods are not always suitable for particular protein samples. Microfluidics offers the potential as a fully automated platform for the efficient analysis of complex samples, such as membrane proteins and do so with performance metrics that exceed their bench top counterparts. In recent years, there have been various applications and improvements to microfluidics and their use for proteomic analysis reported in the literature. In addition, microfluidics offers the potential of a disposable, low cost, and easily fabricated method to perform analysis on complex samples. In this work through the use of microfluidic devices, we demonstrate the ability to effectively extract and purify biotinylated cell surface membrane proteins from the cell lysate of MCF-7 human breast carcinoma. In addition, we also attempt to separate membrane proteins from MCF-7 cells. Our on-chip assay (µ-solid-phase extraction, µSPE) allows us to extract membrane proteins and rid the sample of contaminating cytosolic proteins (purification) in order to do further analysis on the membrane proteins. We also attempted to separate a complex biological sample using a microchip that is suitable for multidimensional techniques that employed sodium dodecyl sulfate micro-capillary gel electrophoresis (SDS µ-CGE) in the 1st dimension and micro-micellar electrokinetic capillary chromatography (µ-MEKC) in the 2nd dimension. Proteins were detected by laser-induced fluorescence following their labeling with dyes. Because our overall goal of this work is the development of a completely integrated system for the analysis of complex protein samples, we also discuss the integration of the extraction module with the separation module along with fabrication steps toward the integration of modules for the digestion of proteins on chip and interfacing the device with MALDI-MS

High-throughput isolation and characterization of untagged membrane protein complexes: outer membrane complexes of Desulfovibrio vulgaris.

Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein-protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms

ESTIMATING AUTOANTIBODY SIGNATURES TO DETECT AUTOIMMUNE DISEASE PATIENT SUBSETS

Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune responses, making autoantibodies useful for diagnosis and prediction. In many diseases, the targets of autoantibodies are incompletely defined. Although the technologies for autoantibody discovery have advanced dramatically over the past decade, each of these techniques generates hundreds of possibilities, which are onerous and expensive to validate. We set out to establish a method to greatly simplify autoantibody discovery, using a pre-filtering step to define subgroups with similar specificities based on migration of labeled, immunoprecipitated proteins on sodium dodecyl sulfate (SDS) gels and autoradiography [Gel Electrophoresis and band detection on Autoradiograms (GEA)]. Human recognition of patterns is not optimal when the patterns are complex or scattered across many samples. Multiple sources of errors - including irrelevant intensity differences and warping of gels - have challenged automation of pattern discovery from autoradiograms. In this paper, we address these limitations using a Bayesian hierarchical model with shrinkage priors for pattern alignment and spatial dewarping. The Bayesian model combines information from multiple gel sets and corrects spatial warping for coherent estimation of autoantibody signatures defined by presence or absence of a grid of landmark proteins. We show the preprocessing creates better separated clusters and improves the accuracy of autoantibody subset detection via hierarchical clustering. Finally, we demonstrate the utility of the proposed methods with GEA data from scleroderma patients

Imaging and 3D reconstruction of membrane protein complexes by cryo-electron microscopy and single particle analysis

Cryo-electron microscopy (cryo-EM) in combination with single particle image processing and volume reconstruction is a powerful technology to obtain medium-resolution structures of large protein complexes, which are extremely difficult to crystallize and not amenable to NMR studies due to size limitation. Depending on the stability and stiffness as well as on the symmetry of the complex, three-dimensional reconstructions at a resolution of 10-30 ˚ can be achieved. In this range of resolution, we may not be able to answer A chemical questions at the level of atomic interactions, but we can gain detailed insight into the macromolecular architecture of large multi-subunit complexes and their mechanisms of action. In this thesis, several prevalently large membrane protein complexes of great physiological importance were examined by various electron microscopy techniques and single particle image analysis. The core part of my work consists in the imaging of a mammalian V-ATPase, frozen-hydrated in amorphous ice and of the completion of the first volume reconstruction of this type of enzyme, derived from cryo-EM images. This ubiquitous rotary motor is essential in every eukaryotic cell and is of high medical importance due to its implication in various diseases such as osteoporosis, skeletal cancer and kidney disorders. My contribution to the second and third paper concerns the volume reconstruction of two bacterial outer membrane pore complexes from cryo-EM images recorded by my colleague Mohamed Chami. PulD from Klebsiella oxytoca constitutes a massive translocating pore capable of transporting a fully folded cell surface protein PulA through the membrane. It is part of the Type II secretion system, which is common for Gram-negative bacteria. The second volume regards ClyA, a pore-forming heamolytic toxin of virulent Escherichia coli and Salmonella enterica strains that kill target cells by inserting pores into their membranes. To the last two papers, I contributed with cryo-negative stain imaging of the cell division protein DivIVA from Bacillus subtilis and with image processing of the micrographs displaying the siderophore receptor FrpB from Neisseria meningitidis

A cooperative framework for molecular biology database integration using image object selection

The theme and the concept of 'Molecular Biology Database Integration' and the problems associated with this concept initiated the idea for this Ph.D research. The available technologies facilitate to analyse the data independently and discretely but it fails to integrate the data resources for more meaningful information. This along with the integration issues created the scope for this Ph.D research. The research has reviewed the 'database interoperability' problems and it has suggested a framework for integrating the molecular biology databases. The framework has proposed to develop a cooperative environment to share information on the basis of common purpose for the molecular biology databases. The research has also reviewed other implementation and interoperability issues for laboratory based, dedicated and target specific database. The research has addressed the following issues: diversity of molecular biology databases schemas, schema constructs and schema implementation multi-database query using image object keying, database integration technologies using context graph, automated navigation among these databases. This thesis has introduced a new approach for database implementation. It has introduced an interoperable component database concept to initiate multidatabase query on gene mutation data. A number of data models have been proposed for gene mutation data which is the basis for integrating the target specific component database to be integrated with the federated information system. The proposed data models are: data models for genetic trait analysis, classification of gene mutation data, pathological lesion data and laboratory data. The main feature of this component database is non-overlapping attributes and it will follow non-redundant integration approach as explained in the thesis. This will be achieved by storing attributes which will not have the union or intersection of any attributes that exist in public domain molecular biology databases. Unlike data warehousing technique, this feature is quite unique and novel. The component database will be integrated with other biological data sources for sharing information in a cooperative environment. This involves developing new tools. The thesis explains the role of these new tools which are: meta data extractor, mapping linker, query generator and result interpreter. These tools are used for a transparent integration without creating any global schema of the participating databases. The thesis has also established the concept of image object keying for multidatabase query and it has proposed a relevant algorithm for matching protein spot in gel electrophoresis image. An object spot in gel electrophoresis image will initiate the query when it is selected by the user. It matches the selected spot with other similar spots in other resource databases. This image object keying method is an alternative to conventional multidatabase query which requires writing complex SQL scripts. This method also resolve the semantic conflicts that exist among molecular biology databases. The research has proposed a new framework based on the context of the web data for interactions with different biological data resources. A formal description of the resource context is described in the thesis. The implementation of the context into Resource Document Framework (RDF) will be able to increase the interoperability by providing the description of the resources and the navigation plan for accessing the web based databases. A higher level construct is developed (has, provide and access) to implement the context into RDF for web interactions. The interactions within the resources are achieved by utilising an integration domain to extract the required information with a single instance and without writing any query scripts. The integration domain allows to navigate and to execute the query plan within the resource databases. An extractor module collects elements from different target webs and unify them as a whole object in a single page. The proposed framework is tested to find specific information e.g., information on Alzheimer's disease, from public domain biology resources, such as, Protein Data Bank, Genome Data Bank, Online Mendalian Inheritance in Man and local database. Finally, the thesis proposes further propositions and plans for future work

Transient absorption imaging of hemeprotein in fresh muscle fibers

2022 Summer.Includes bibliographical references.Mitochondrial diseases affect 1 in 4000 individuals in the U.S. among adults and children of all races and genders. Nevertheless, these diseases are hard to diagnose because they affect each person differently. Meanwhile the gold standard diagnosis methods are usually invasive and time- consuming. Therefore, a non-invasive and in-vivo diagnosis method is highly demanded in this area. Our goal is to develop a non-invasive diagnosis method based on the endogenous nonlinear optical effect of the live tissues. Mitochondrial disease is frequently the result of a defective electron transport chain (ETC). Our goal is to develop a non-invasive way to measure redox within the ETC, specifically, of cytochromes. Cytochromes are iron porphyrins that are essential to the ETC. Their redox states can indicate cellular oxygen consumption and mitochondrial ATP production. So being able to differentiate the redox states of cytochromes will offer us a method to characterize mitochondrial function. Meanwhile, Chergui's group found out that the two redox states of cytochrome c have different pump-probe spectroscopic responses, meaning that the transient absorption (TA) decay lifetime can be a potential molecular contrast for cytochrome redox state discrimination. Their research leads us to utilize the pump-probe spectroscopic idea to develop a time-resolved optical microscopic method to differentiate not only cytochromes from other chemical compounds but also reduced cytochromes from oxidized ones. This dissertation describes groundbreaking experiments where transient absorption is used to reveal excited-state lifetime differences between healthy controls and an animal model of mitochondrial disease, in addition to differences between reduced and oxidized ETC in isolated mitochondria and fresh preparations of muscle fibers. For our initial experiments, we built a pump-probe microscopic system with a fiber laser source, producing 530nm pump and 490nm probe using a 3.5kHz laser scanning rate. The pulse durations of pump and probe are both 800fs. For the preliminary results, we have successfully achieved TA decay contrast between reduced and oxidized cytochromes in solution form. Then we have achieved SNR enhanced pump-probe image of BGO crystal particles with the help of the software- based adaptive filter noise canceling method. We also have installed a FPGA-based adaptive filter to enhance the pump-probe signals of the electrophoresis gels that contain different mitochondrial respiratory chain supercomplexes. However, because the noise floor was still 30 dB higher than shot noise limit, cytochrome imaging in live tissues was still problematic. We then built another pump-probe microscope with a solid- state ultrafast laser source. In that way, we do not need to worry about laser relative intensity noise (RIN) anymore, since the noise floor of the solid-state laser source can reach the shot noise limit at MHz region. One other advantage of the new laser source is that it can provide one tunable laser output that can be directly converted to the probe pulse with tunable center wavelength. Its tunability can cover the entire visible spectrum. We realized a pump-probe microscopy with a 520nm pump pulse and a tunable probe pulse. The tunability on the probe arm allows us to explore better pump-probe contrast between two redox states. What's more, I will introduce my preliminary results of utilizing supercontinuum generation in a photonic crystal fiber (PCF) to realize tunability on pump wavelength. In that way, more possibilities will be unlocked. And the hyperspectral pump-probe microscope will be able to distinguish more molecules

Electron microscopy analysis of ATP-independent nucleosome unfolding by FACT

FACT is a histone chaperone that participates in nucleosome removal and reassembly during transcription and replication. We used electron microscopy to study FACT, FACT:Nhp6 and FACT:Nhp6:nucleosome complexes, and found that all complexes adopt broad ranges of configurations, indicating high flexibility. We found unexpectedly that the DNA binding protein Nhp6 also binds to the C-terminal tails of FACT subunits, inducing more open geometries of FACT even in the absence of nucleosomes. Nhp6 therefore supports nucleosome unfolding by altering both the structure of FACT and the properties of nucleosomes. Complexes formed with FACT, Nhp6, and nucleosomes also produced a broad range of structures, revealing a large number of potential intermediates along a proposed unfolding pathway. The data suggest that Nhp6 has multiple roles before and during nucleosome unfolding by FACT, and that the process proceeds through a series of energetically similar intermediate structures, ultimately leading to an extensively unfolded form