Identification of functional differences in metabolic networks using comparative genomics and constraint-based models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here.     

Relevance of transgenic mouse models to human Alzheimer disease

During the past 2 decades, the elucidation of susceptibility and causative genes for Alzheimer disease as well as proteins involved in the pathogenic process has greatly facilitated the development of genetically altered mouse models. These models have played a major role in defining critical disease-related mechanisms and in evaluating novel therapeutic approaches, with many treatments currently in clinical trial owing their origins to studies initially performed in mice. This review discusses the utility of transgenic mice as a research tool and their contributions to our understanding of Alzheimer disease.     

Curation is forever: comparative genomics approaches to functional annotation

The process of deriving accurate annotations for genes in newly sequenced genomes has up to now been based largely on projection of results in one organism to genes in other organisms based on sequence similarity. We are now entering a period in which metabolic reconstructions will play an increasingly significant role. These reconstructions will support a gradual refinement of estimates of function, leading to more consistent and precise understanding. They will become key components in establishing which functional roles have not yet been connected to genes and which aspects of an organism's physiology can be understood in terms of existing functional assignments. As each refinement is made, we incrementally approach the goal of establishing a qualitative understanding of an organism in terms of its inventory of genes.     

Plenty more fish in the sea: comparative and functional genomics using teleost models.

Biology has collaborated with evolution to create an enormous repertoire of animal variation. This in turn has provided experimental biologists with models that can be used in the lab to simulate more complex systems. Amongst the organisms that have been used in this way are fish, where a large number of species have been utilised in a variety of different ways. Fish possess the smallest genomes of any vertebrate, making them ideal as models for genome analysis and gene discovery. Fish are also easy to maintain in a laboratory environment and can be bred easily. Fish often have well-defined physiology and respond well to many experimental procedures. Finally, fish are of great economic importance in their own right, as one of the world's largest sources of protein. In this review, the relationship between fish species is examined along with the role of different fish models in a wide range of biological disciplines.     

Small membrane proteins found by comparative genomics and ribosome binding site models

The correct annotation of genes encoding the smallest proteins is one of the biggest challenges of genome annotation, and perhaps more importantly, few annotated short open reading frames have been confirmed to correspond to synthesized proteins. We used sequence conservation and ribosome binding site models to predict genes encoding small proteins, defined as having 16–50 amino acids, in the intergenic regions of the Escherichia coli genome. We tested expression of these predicted as well as previously annotated genes by integrating the sequential peptide affinity tag directly upstream of the stop codon on the chromosome and assaying for synthesis using immunoblot assays. This approach confirmed that 20 previously annotated and 18 newly discovered proteins of 16–50 amino acids are synthesized. We summarize the properties of these small proteins; remarkably more than half of the proteins are predicted to be single‐transmembrane proteins, nine of which we show co‐fractionate with cell membranes.     

Microarray detection of food-borne pathogens using specific probes prepared by comparative genomics

In order to design a method for the accurate detection and identification of food-borne pathogens, we used comparative genomics to select 70-mer oligonucleotide probes specific for 11 major food-borne pathogens (10 overlapping probes per pathogen) for use in microarray analysis. We analyzed the hybridization pattern of this constructed microarray with the Cy3-labeled genomic DNA of various food-borne pathogens and other bacteria. Our microarray showed a highly specific hybridization pattern with the genomic DNA of each food-borne pathogen; little unexpected cross-hybridization was observed. Microarray data were analyzed and clustered using the GenePix Pro 6.0 and GeneSpring GX 7.3.1 programs. The analyzed dendrogram revealed the discriminating power of constructed microarray. Each food-borne pathogen clustered according to its hybridization specificity and non-pathogenic species were discriminated from pathogenic species. Our method can be applied to the rapid and accurate detection and identification of food-borne pathogens in the food industry. In addition, this study demonstrates that genome sequence comparison and DNA microarray analysis have a powerful application in epidemiologic and taxonomic studies, as well as in the food safety and biodefense fields.     

Databases, models, and algorithms for functional genomics

A variety of patterns have been observed on the DNA and protein sequences that serve as control points for gene expression and cellular functions. Owing to the vital role of such patterns discovered on biological sequences, they are generally cataloged and maintained within internationally shared databases. Furthermore,the variability in a family of observed patterns is often represented using computational models in order to facilitate their search within an uncharacterized biological sequence. As the biological data is comprised of a mosaic of sequence-levels motifs, it is significant to unravel the synergies of macromolecular coordination utilized in cell-specific differential synthesis of proteins. This article provides an overview of the various pattern representation methodologies and the surveys the pattern databases available for use to the molecular biologists. Our aim is to describe the principles behind the computational modeling and analysis techniques utilized in bioinformatics research, with the objective of providing insight necessary to better understand and effectively utilize the available databases and analysis tools. We also provide a detailed review of DNA sequence level patterns responsible for structural conformations within the Scaffold or Matrix Attachment Regions (S/MARs).     

Decoding the differential biomarkers of Rheumatoid arthritis and Osteoarthritis: A functional genomics paradigm to design disease specific therapeutics

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease of unidentified aetiology, chiefly affecting the synovial membranes of joints, cartilage, bone, bursa and tendon sheath. Osteoarthritis (OA) is a degenerative disorder and encompass different sets of pathogenic pathways than RA; however, it shows a medley of clinical manifestations or symptoms resembling RA. Hence, we intend to identify more disease specific biomarkers through the meta-analysis of microarray datasets that can be crucial in the differential diagnosis, disease specific treatment as well as management of both RA and OA in a typical clinical setting.     

Technical approaches for mouse models of human disease

The mouse is the leading organism for disease research. A rich resource of genetic variation occurs naturally in inbred and special strains owing to spontaneous mutations. However, one can also obtain desired gene mutations by using the following processes: targeted mutations that eliminate function in the whole organism or in a specific tissue; forward genetic screens using chemicals or transposons; or the introduction of exogenous transgenes as DNAs, bacterial artificial chromosomes (BACs) or reporter constructs. The mouse is the only mammal that provides such a rich resource of genetic diversity coupled with the potential for extensive genome manipulation, and is therefore a powerful application for modeling human disease. This poster review outlines the major genome manipulations available in the mouse that are used to understand human disease: natural variation, reverse genetics, forward genetics, transgenics and transposons. Each of these applications will be essential for understanding the diversity that is being discovered within the human population.     

Trends in large-scale mouse mutagenesis: from genetics to functional genomics

The primary goal of mouse mutagenesis programmes is to develop a fundamental research infrastructure for mammalian functional genomics and to produce human disease models. Many large-scale programmes have been ongoing since 1997; these culminated in the International Knockout Mouse Consortium (IKMC) in 2007 with the aim to establish knockout and conditional mouse strains for all mouse genes. This article traces the origins and rationale of these large-scale mouse mutagenesis programmes.     

Genome sequencing and comparative genomics of tropical disease pathogens

The sequencing of eukaryotic genomes has lagged behind sequencing of organisms in the other domains of life, archae and bacteria, primarily due to their greater size and complexity. With recent advances in high-throughput technologies such as robotics and improved computational resources, the number of eukaryotic genome sequencing projects has increased significantly. Among these are a number of sequencing projects of tropical pathogens of medical and veterinary importance, many of which are responsible for causing widespread morbidity and mortality in peoples of developing countries. Uncovering the complete gene complement of these organisms is proving to be of immense value in the development of novel methods of parasite control, such as antiparasitic drugs and vaccines, as well as the development of new diagnostic tools. Combining pathogen genome sequences with the host and vector genome sequences is promising to be a robust method for the identification of host-pathogen interactions. Finally, comparative sequencing of related species, especially of organisms used as model systems in the study of the disease, is beginning to realize its potential in the identification of genes, and the evolutionary forces that shape the genes, that are involved in evasion of the host immune response.     

Assessment of diet-induced obese rats as an obesity model by comparative functional genomics

Objective: We applied a comparative functional genomics approach to evaluate whether diet‐induced obese (DIO) rats serve as an effective obesity model. Methods and Procedures: Gene‐expression profiles of epididymal fat from DIO and lean rats were generated using microarrays and compared with the published array data of obese and non‐obese human subcutaneous adipocytes. Results: Caloric intake and fuel efficiency were significantly higher in DIO rats, which resulted in increased body weight and adiposity. Circulating glucose, cholesterol, triglyceride, insulin, and leptin levels in DIO rats were significantly higher than those in the lean controls. DIO rats also exhibited impaired insulin sensitivity. A direct comparison of gene‐expression profiles from DIO and lean rats and those from obese and non‐obese humans revealed that global gene‐expression patterns in DIO rat fat resemble those of obese human adipocytes. Differentially expressed genes between obese and non‐obese subjects in both human and rat studies were identified and associated with biological pathways by mapping genes to Gene Ontology (GO) categories. Immune response–related genes and angiogenesis‐related genes exhibited significant upregulation in both obese humans and DIO rats when compared with non‐obese controls. However, genes in fatty acid metabolism and oxidation exhibited a broad downregulation only in obese human adipocytes but not in DIO rat epididymal fat. Discussion: Our study based on gene‐expression profiling suggested that DIO rats in general represent an appropriate obesity model. However, the discrepancies in gene‐expression alterations between DIO rats and obese humans, particularly in the metabolic pathways, may explain the limitations of using DIO rodent models in obesity research and drug discovery.     

Now and future of mouse mutagenesis for human disease models

One of the major objectives of the Human Genome Project is to understand the biological function of the gene and genome as well as to develop clinical applications for human diseases. For this purpose, the experimental validations and preclinical trails by using animal models are indispensable. The mouse (Mus musculus) is one of the best animal models because genetics is well established in the mouse and embryonic manipulation technologies are also well developed. Large-scale mouse mutagenesis projects have been conducted to de-velop various mouse models since 1997. Originally, the phenotype-driven mutagenesis with N-ethyl-N-nitrosourea (ENU) has been the major efforts internationally then knockout/conditional mouse projects and gene-driven mutagenesis have been following. At the beginning, simple monogenic traits in the experimental condition have been elucidated. Then, more complex traits with variety of environmental interactions and gene-to-gene interactions (epistasis) have been challenged with mutant mice. In addition, chromosomal substitution swains and collaborative cross strains are also available to elucidate the complex Waits in the mouse. Altogether, mouse models with mutagenesis and various laboratory strains will accelerate the studies of functional genomics in the mouse as well as in human.     

Zebrafish models for the functional genomics of neurogenetic disorders

In this review, we consider recent work using zebrafish to validate and study the functional consequences of mutations of human genes implicated in a broad range of degenerative and developmental disorders of the brain and spinal cord. Also we present technical considerations for those wishing to study their own genes of interest by taking advantage of this easily manipulated and clinically relevant model organism. Zebrafish permit mutational analyses of genetic function (gain or loss of function) and the rapid validation of human variants as pathological mutations. In particular, neural degeneration can be characterized at genetic, cellular, functional, and behavioral levels. Zebrafish have been used to knock down or express mutations in zebrafish homologs of human genes and to directly express human genes bearing mutations related to neurodegenerative disorders such as spinal muscular atrophy, ataxia, hereditary spastic paraplegia, amyotrophic lateral sclerosis (ALS), epilepsy, Huntington's disease, Parkinson's disease, fronto-temporal dementia, and Alzheimer's disease. More recently, we have been using zebrafish to validate mutations of synaptic genes discovered by large-scale genomic approaches in developmental disorders such as autism, schizophrenia, and non-syndromic mental retardation. Advances in zebrafish genetics such as multigenic analyses and chemical genetics now offer a unique potential for disease research. Thus, zebrafish hold much promise for advancing the functional genomics of human diseases, the understanding of the genetics and cell biology of degenerative and developmental disorders, and the discovery of therapeutics. This article is part of a Special Issue entitled Zebrafish Models of Neurological Diseases.