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

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field

Proteomic Shifts in Embryonic Stem Cells with Gene Dose Modifications Suggest the Presence of Balancer Proteins in Protein Regulatory Networks

Large numbers of protein expression changes are usually observed in mouse models for neurodegenerative diseases, even when only a single gene was mutated in each case. To study the effect of gene dose alterations on the cellular proteome, we carried out a proteomic investigation on murine embryonic stem cells that either overexpressed individual genes or displayed aneuploidy over a genomic region encompassing 14 genes. The number of variant proteins detected per cell line ranged between 70 and 110, and did not correlate with the number of modified genes. In cell lines with single gene mutations, up and down-regulated proteins were always in balance in comparison to parental cell lines regarding number as well as concentration of differentially expressed proteins. In contrast, dose alteration of 14 genes resulted in an unequal number of up and down-regulated proteins, though the balance was kept at the level of protein concentration. We propose that the observed protein changes might partially be explained by a proteomic network response. Hence, we hypothesize the existence of a class of “balancer” proteins within the proteomic network, defined as proteins that buffer or cushion a system, and thus oppose multiple system disturbances. Through database queries and resilience analysis of the protein interaction network, we found that potential balancer proteins are of high cellular abundance, possess a low number of direct interaction partners, and show great allelic variation. Moreover, balancer proteins contribute more heavily to the network entropy, and thus are of high importance in terms of system resilience. We propose that the “elasticity” of the proteomic regulatory network mediated by balancer proteins may compensate for changes that occur under diseased conditions

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

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

Proteome comparison of helicobacter pylori isolates associated with four disease groups

The Gram-negative bacterium Helicobacter pylori is found in human gastric mucosa. H. pylori, one of the most common chronic bacterial infections of humans, is present in almost half of the world population. It is associated with chronic gastritis, non-ulcer dyspepsia, gastric and duodenal ulcers, and malignant neoplasms. The aim of this study was to detect microbial candidate protein markers whose presence might be correlated with the development of four different clinical consequences of H. pylori infection, gastric ulceration [GU], duodenal ulceration [DU], non-ulcer dyspepsia [NUD] and gastritis [GI]. Eleven H. pylori isolates associated with these outcomes were analysed. The total complement of protein from these H. pylori isolates were resolved by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and compared using PDQUEST pattern analysis software. Relationships between the isolates associated with specific disease outcomes were determined by cluster analysis.Fifty six disease specific proteins were then characterised by tryptic peptide-mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Up to 1165 protein species were resolved from each H. pylori strain. Proteome analysis revealed that only 470 (40%) of the proteins detected were common to all eleven isolates. Twenty six of the 56 disease specific proteins that were selected for identification consisted of spots whose expression is altered in response to stress conditions or those that can affect H. pylori cell division and the cell membrane. The remaining 30 proteins had no known function. This study has provided further confirmation of the extensive variation that the bacterium H. pylori exhibits at the proteome level. Most significantly this study has found, through the application of cluster analysis and protein matching, that isolates do form disease groups. Comparative proteome analysis is a useful method for highlighting the extensive strain variation that H. pylori exhibits and to determine if any disease specific proteins exist

Molecular and phenotypic profiling from base to the crown in maritime pine wood-forming tissue

Research• Environmental, developmental and genetic factors affect variation in wood properties at the chemical, anatomical and physical levels. Here, the phenotypic variation observed along the tree stem was explored and the hypothesis tested that this variation could be the result of the differential expression of genes/proteins during wood formation. • Differentiating xylem samples of maritime pine (Pinus pinaster) were collected from the top (crown wood, CW) to the bottom (base wood, BW) of adult trees. These samples were characterized by Fourier transform infrared spectroscopy (FTIR) and analytical pyrolysis. Two main groups of samples, corresponding to CW and BW, could be distinguished from cell wall chemical composition. • A genomic approach, combining large-scale production of expressed sequence tags (ESTs), gene expression profiling and quantitative proteomics analysis, allowed identification of 262 unigenes (out of 3512) and 231 proteins (out of 1372 spots) that were differentially expressed along the stem. • A good relationship was found between functional categories from transcriptomic and proteomic data. A good fit between the molecular mechanisms involved in CW–BW formation and these two types of wood phenotypic differences was also observed. This work provides a list of candidate genes for wood properties that will be tested in forward genetic

An integrated proteomic and metabolomic approach to investigate cerebral ischemic preconditioning

The molecular mechanism that leads to ischemic preconditioning and hence to ischemic tolerance, are not completely understood although it is clear that multiple effectors and pathways contribute to the instauration of this neuroprotective profile. To study the mechanism/pathway involved in the ischemic tolerance, brain proteins, plasma proteins and plasma metabolites were analyzed in preconditioning stimulus (7'Middle Cerebral Artery occlusion or 7'MCAo), in severe stroke and (permanent Middle Cerebral Artery occlusion or pMCAo) and in preconditioned (7'MCAo/pMCAo) mouse model. A conventional 2-DE approach was used to study technical replicates of pooled brain proteins revealing an involvement of energy metabolism, mitochondrial electron transport, synaptic vesicle transport and antioxidant processes; moreover network analysis suggested an involvement of the androgen receptor that was validated on technical replicates of pooled brain proteins by western blot analysis revealing an increased expression in preconditioned stimulus animals (7'MCAo). Plasma proteins were analyzed using a i-DE LC-MS/MS approach on technical replicates of pooled plasma proteins revealing decreased levels of epidermal growth factor receptor (EGFR) and increased levels of insuline like growth factor acid labile subunit (IGFALS), which expression was paralleled by increased insulin like growth factor 1 (IGFi) plasma concentration, as validated by ELISA on biological replicates, in preconditioning stimulus animals (7'MCAo). Finally an untarget metabolomics analysis was applied to technical replicates of pooled plasma proteins revealing fatty acid oxidation and branched-chain aminoacid metabolism as the main biological processes modulated in ischemic tolerance and highlighted an involvement of the aminoacid leucine, carnitine esters and adenosine. The results described in this thesis represents the first application of both proteomic and metabolomic approaches in cerebral ischemic sets, highlighting the androgen receptor as an important mediator between proteins and metabolites and adding new evidence to the current knowledge on ischemic preconditioning that may represent a starting point for future experiments on investigating candidate pathways that relate to the Androgen receptor