Microbs are well knows infectious entities which are the keen interest for researcher and scientist for the many pathogenic diseases. The development of the microbs in host -pathogen infection are being analysed by the many microbiological methods and experiments. Insilico approaches and computational methods are also now added to explore these infection and metabolic pathways identifications. Enzymes and chemical compounds are the part of these metabolic pathways, which interconnected to other molecules in formation of various proteins, leading to diseases development. The Bioinfor matics has given new way and approaches to pathologist to detect and enquire about the host pathogen interaction by these metabolic pathway databases.
Major diseases in Public health problem are caused due to various pathogenic bacteria globally. These pathogens are being have been reported to challenge the existing treatment by developing drug resistance and in several cases effective vaccines are yet to be developed.
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Efforts are continuously made by scientist and researchers for the effective drugs and vaccines development but the target achievable are not yet successful due to the dynamic adaptability. This result due to pathogens is having frequent phase and antigenic modifications, variations in major virulence factors, and adoptive mutations. The advent of several microbial complete genome sequences along with development of various bioinformatics tools, made it faceable for in silico analysis of the genomes and subsequent drug discovery against deadly human pathogen, NCBI genome database has listed approximately 1549 fully sequenced microbial genomes including pathogenic bacteria till now (2011). In addition, the amount of subsequent data generated by utilizing genome sequences and related information, including transcriptome, proteome, metabolic, and regulatory networks, is also rapidly increasing. various combinations of computational methods, mathematics, statistics, and modeling knowledge together with traditional and advanced biological methods has become indispensable to obtain biologically meaningful data from such a flood of information (Lee. et al., 2005).Identification of drug targets in many pathogenic bacteria done by many Computational approaches based on subtractive genomics have successfully achieved (Sakharkar et al., 2004; Dutta et al., 2006; Sharma et al., 2008.). The functional and structural characterisation of enzymes belonging to microbial metabolic pathways is very important for structure-based drug design (Jacobson M., 2004).There are various web resources which can be use to identify the pathogen pathways and their mode of actions in different diseases. The chapter is describing the major microbial pathways and interactions with Bio-molecules.
1. Useful Internet Resources for Microbial Biotechnology
The list will provide the various tools and softwares for Microbs. This can be use to identify the basic information about microbs. These can be classified in following categories.
Enzymes and their Genes
Scientific Literature and Related Information
Biodegradation and Biotechnology in General
1a. Chemical Compounds
EPAÂ PBT Profiler: Persistent, Bioaccumulative, and Toxic Profiles Estimated for Organic Chemicals On-Line
Extension Toxicology NetworkÂ at Oregon State University
National Pesticide Information Center, Oregon State University
Agricultural Research Service (ARS)Â Pesticide Properties Database
JINNO Laboratory, Toyohasi University of Technology, Japan
Polycyclic Aromatic Hydrocarbons (PAHs) Database
Polycyclic Aromatic Hydrocarbon Structure IndexÂ from the National Institute of Standards and Technology
Search theÂ EPA Envirofacts Master Chemical IntegratorÂ (EMCI)
EPAÂ Office of Pollution Prevention and Toxics
Pesticide Fact Sheets
IPCSÂ INCHEM: Chemical Safety Information from Intergovernmental Organizations
National Toxicology Program
SearchÂ NTP Databases
National Library of Medicine'sÂ TOXNET: Toxicology Data Network
Agency for Toxic Substances and Disease Registry (ATSDR)Â ToxFAQs
Environment WriterÂ Chemical Backgrounders
Hazardous Substances Information SystemÂ from the Australian Safety and Compensation Council
Environmental Fate DatabaseÂ from SRC
Scorecard: The Pollution Information Site
Scorecard Chemical Profiles
Compendium of Pesticide Common NamesÂ by Alan Wood
UKÂ Pesticides Safety Directorate
OSHAÂ Chemical Sampling Information
Chemical Entities of Biological Interest (ChEBI)Â at EBI, UK
PubChem, NCBI, NLM, NIH
ChemSpider: Building a Structure Centric Community for Chemists
Molecular ModelsÂ by Dr. Dave Woodcock
Organic Compounds DatabaseÂ at Colby College, Maine
IUPAC Goldbook: Compendium of Chemical Terminology
ChemFinderÂ from CambridgeSoft Corporation.
ChemSpy.com: Internet Navigator for the Chemical Industry
ChemSpyÂ Environment News
Always on Time
Marked to Standard
ZINC: a free database of commercially-available compounds, from UCSF
Online Chemical Database
NIST Chemical WebBookÂ from the National Institute of Standards and Technology
Chemical Information PageÂ at the National Library of Medicine
1b. Enzymes and their Genes
IntEnz: Integrated Enzyme Database at EBI
Ligand Chemical DatabaseÂ at Kyoto University
ExPASy ENZYME DatabaseÂ at the University of Geneva
BRENDA: The Comprehensive Enzyme Information System
The Enzyme Database, Trinity College, Dublin
Enzyme NomenclatureÂ from the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology.
E-zyme: for prediction of enzymatic reactions, at Kyoto University
Thermodynamics of Enzyme-Catalyzed ReactionsÂ from the National Institute of Standards and Technology
Sequence Retrieval SystemÂ at the European Bioinformatics Institute
a/b hydrolase fold families databaseÂ at the University of Stuttgart
Catalytic Site AtlasÂ at EMBL-EBI
EzCatDB: Enzyme Catalytic Mechanism Database from AIST, Japan
BiocatCollection: International Collection of Biocatalysts
GenBankÂ at the National Center for Biotechnology Information
Microbial Genomics GatewayÂ by the US Department of Engergy
MBGD: Microbial Genome DatabaseÂ for Comparative Analysis at the University of Tokyo
The Enhanced Microbial Genomes LibraryÂ at Pole Bio-Informatique Lyonnais, France
PGD: The Plasmid Genome Database from the Centre of Ecology and Hydrology-Oxford, UK
GenProtEC:Â E. coliÂ genes and proteins at the Woods Hole Marine Biological Laboratory
1c. Metabolic Pathways
KEGG:Â Kyoto Encyclopedia of Genes and Genomes
PathPred: Biodegradation/biosynthesis pathway prediction
Boehringer Mannheim Biochemical PathwaysÂ on the ExPASy server, Geneva, Switzerland
IUBMB-Nicholson Metabolic Maps, Minimaps and Animaps
International Society for the Study of Xenobiotics
BioCyc:Â Knowledge Library of Pathway/Genome Databases
MetaCycÂ Biodegradation Pathways
Yeast Genome PathwaysÂ at MIPS, Germany
GREP: Generator of Reaction Equations and Pathways at Trinity College Dublin, Ireland
Biodegradative Strain DatabaseÂ at Michigan State University
American Type Culture Collection
DSMZ: German Collection of Microorganisms and Cell Cultures
SearchÂ Bacterial Nomenclature Up-To-Date
List of bacterial names with standing in nomenclature
Centraalbureau voor Schimmelcultures (CBS)Â SearchÂ the NCCB Bacteria/Plasmids Database
WFCC-MIRCENÂ World Data Centre for Microorganisms
Microbes.info: The Microbiology Information Portal
MicrobeWikiÂ at Kenyon College
Taxonomy BrowserÂ at the National Center for Biotechnology Information
Toxic Waste SiteÂ in theÂ Microbe ZooÂ at Michigan State University
Microbial WorldÂ at University of Edinburgh
American Society for Microbiology
Society for Industrial Microbiology
1e. Scientific Literature and Related Information
Entrez PubMedÂ at the National Center for Biotechnology Information
Entrez cross-database search page
Journal of Biological Chemistry Online
Journal of Biochemistry Online
Nucleic Acids Research Online
Journal of Chemical Information and Modeling
American Society for Microbiology Journals
Genamics JournalSeek: Molecular Biology, Biochemistry and Science Journals
National Academy Press
SearchÂ text of NAP books for "biodegradation"
Natural Attenuation for Groundwater Remediation (2000)
In Situ Bioremediation: When Does It Work? (1993)
U.S. EPAÂ A Citizen's Guide to BioremediationÂ PDF File
U.S. EPAÂ Hazardous Waste Clean-Up Information (CLU-IN)
PublicationsÂ from the Canadian Network of Toxicology Centers
1f. Biodegradation and Biotechnology in General
U.S. Geological SurveyÂ BioremediationÂ andÂ Toxic Substances Hydrology Program
Biodegradation, from Environmental Inquiry, Cornell University
U.S. Department of Energy,Â Office of Biology and Environmental ResearchÂ Program
Google Directory of Biotechnology
The microbs pathways, enzymes and targets can be also search by these web resources the details of web resources have been provided to explore the related information.
BIOCHEMICAL PATHWAYSÂ -Â
a searchable database of metabolic pathways, enzymes, substrates and products. Has links toÂ ENZYMEÂ (see below). Constructed in conjunction withÂ Boehringer Mannheim Corp.Produces a graphic representation of the metabolic pathways resulting from the search within the context of an enormous metabolic map - neighboring metabolic reactions can be viewed.
The data base is implemented in a relational data base and covers some 40 data fields with information about nomenclature, reaction and specificity, enzyme structure, isolation/preparation, stability, literature references and cross references to sequence and 3D-structure data banks. The data base is made available via the Internet through cooperation with the European Bioinformatics Institute. The enzyme information contained in this database is comprehensive and useful covering many aspects including substrates, inhibitors, optimal conditions for activity, locations and sources. Searching the database requires the EC number for the target enzyme - seeÂ EC Enzyme orÂ ENZYMEÂ in this database. Links are provided to several other enzyme and metabolic pathways databases. Brenda is one of several databases nested within the metabolic pathway database set of theÂ SRS5Â sequence retrieval system at EBI. To find the database follow these links fromÂ SRS entrance page -Â START, expand theÂ Metabolic PathwaysÂ menu (click on), click onÂ BRENDA. link to go to theÂ BRENDAÂ front page and the final link to the search page.
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Enzyme commission database: this Web version of EC Enzyme has hot links among its own entries and to the following Databases.Â
SWISSPROTÂ - The Swiss Protein Database EC Enzyme comes with a users manual that gives an extensive description of the database.
Â Encyclopedia ofÂ E.coliÂ Genes and Metabolism - needs a password but free registration for non-profit organisations.
Enzyme nomenclature database - a repository of information relative to the nomenclature of enzymes. It is primarily based on the recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (IUBMB) and it describes each type of characterized enzyme for which an EC (Enzyme Commission) number has been provided.
Ligand Chemical Database for Enzyme Reactions at Kyoto, Japan. TheÂ ENZYMEÂ section is a collection of all known enzymatic reactions classified according to the nomenclature of the International Union of Biochemistry and Molecular Biology (IUBMB). TheÂ COMPOUNDÂ section is a collection of metabolic compounds including substrates, products, and inhibitors.
Metabolic DatabaseÂ -Â
The metabolic component ofÂ SoyBase, a soybean genetic database, contains reaction and pathway descriptions and diagrams for a number of basic metabolicpathways.Â SoybaseÂ is anÂ ACEDBÂ database; the metabolic data has been made available on the Web via a translation program that is still under development, and has some bugs. AGISÂ = Agricultural Genome Information Service, an integrated system for agricultural genome analysis. (See entry inÂ Plant CornerÂ andÂ AGIS genome siteÂ ).
a protease and protease inhibitor Web server at the University of Tours, France. PROLYSISÂ is intended as a Web resource for those interested in proteases and their natural or synthetic inhibitors. This page contains informations of general interest as well as useful links to other Internet resources.
All enzymes are given an Enzyme Commission (E.C.) number allowing it to be uniquely identified.
All E.C. numbers have four fields separated by periods:e.g. "184.108.40.206".
The left-hand-most field represents the most broad classification for the enzyme. The next field represents a finer division of that broad category. The third field is adds more detailed information and the fourth field defines the specific enzyme. The E.C. Classification Page has three columns representing the first three fields of the E.C. number of an enzyme. Clicking on an item in the 1st column alters the second column to show the subclassifications for that major heading. Clicking on an item in the 2nd column alters the third column to show the appropriate subclassifications. Clicking on the third column opens another window that will contain all possible full E.C. numbers that conform to your first three choices. Clicking on a specific number will take you to the E.C. database entry for that enzyme, in that window.
an Integration of Biological Data to Support the Interpretation of Genomes. PUMA is a web-based system that offers integrated access to biological data. It is intended as an environment to support the interpretation and presentation of genomes.Â PUMAÂ is a system that attempts to integrate access to the emerging body of biological sequence data from within a functional context; it is an integration based on a functional overview of an organism and offers access through structured presentations of the data -- most notably, metabolic pathways, alignments, and phylogenetic trees. (See also new site onreconstructed metabolism).
TheÂ RestrictionÂ Enzyme DatabaseÂ - a collection of information about restriction enzymes, methylases, and the microorganisms from which they have been isolated - isoschizomers, recognition sequences, cleavage sites, methylation specificity, commercial availability, and references - both published and unpublished. Maintained by Dr Richard J. Roberts and Dana Macelis.
Metabolic pathwaysÂ -Â
Metabolic pathways of the diseased potato and disease resistance-related proteins in potato at Scottish Crop Reseach Institute (SCRI). Poster-sized representation of the extensive metabolic events taking place in the potato challenged by pathogens or wounding. Proteins included in the Metabolic pathways of the diseased potato are listedÂ here. Many of these proteins have enzyme activity, exist as multiple isozymes, and may be involved in the biosynthesis of either signalling molecules or antimicrobial compounds. Enzyme activity, subcellular localization and function can be controlled by post-translational modification involving addition of phosphates, methyl groups, carbohydrates or lipids to the proteins. Isozymes can be differentially regulated with some up-regulated by wounding whilst others are up-regulated by pathogens. Many enzymes are able to act on a number of substrates and 'enzyme reactions'listed below are only examples rather than being an exhaustive listing. Many more proteins are associated with resistance of potato to bacterial and fungal diseases but have not been included in the table because they have either not been well characterised or are not yet included in the metabolic pathways chart.
Cell signalling pathways
(What Is There)Â The WIT system helps users create metabolic reconstructions, which is made possible by the recent abundance of complete bacterial genomic sequences. Such reconstructions will for the first time set the stage for meaningful simulations of the basic behaviour of microbes, and may thus significantly advance microbial biology.
2. Online Web Portals for Pathogenic
This is well known that pathogen causing severe disease epidemics and lower economic yields. In human health, there is growing concern over fungal infections in immunocompromised patients. Over the last 15 years, the number of genes conï¬rmed by gene and/or transcript disruption experiments to be required for the disease causing ability of a microbe has gradually increased. These genes are termed pathogenicity genes if the effect on the phenotype is qualitative, or virulence/aggressiveness genes if the effect is quantitative (Shaner et al.,1992).the following resources are also helpfull to trace the pathogenic genes role and their functions.
2a. BRITE- Biomolecular Relations in Information Transmission and Expression
Molecular interactions and pathways database, part of the KEGG system
2b. MiST - Microbial Signal Transduction database
Signal transduction systems link environmental stimuli with adaptive cellular responses and enable an organism to survive and adapt to changing conditions. This communication network of signaling pathways regulates critical cellular activities in all organisms from bacteria to humans. The MiST (Microbial Signal Transduction) database is a comprehensive catalog of the signal transduction proteins (two- and one-component systems) within completely sequenced bacterial and archaeal genomes. These are identified with various domain profiles that directly or indirectly implicate a particular protein as participating in signal transduction. MiST currently contains information on the signal transduction proteins within more than 365 genomes and newly, available genomes are added on a monthly basis. We have designed a user-friendly interface to facilitate the comparison and analysis of bacterial signal transduction repertoires.
A knowledgebase of virus-host molecular interaction networks
2d.CPA - Comparative Pathway Analyzer
The Comparative Pathway Analyzer (CPA) is a web tool for comparative metabolic network analysis. The differences in metabolic reaction content between two sets of organisms are computed and displayed on KEGG pathway maps.
2e. PID (Pathway interaction database)
NCI-Nature Pathway Interaction Database
2f. Pathway Resource List
The Pathway Resource List (PRL) is a database of 150+ links to resources for protein-protein interactions, metabolic and signalling pathways, transcription factor and genetic interaction networks, pathway diagrams, protein sequences, and protein-compound interactions.
A web-based application for the mapping of prokaryotic genes and the corresponding proteins to common gene regulatory and metabolic networks. Users input a list of genes from which shared operons, co-expressed genes and shared regulators are detected. Common metabolic pathways are then viewed on KEGG maps.
Pathway and Literature Strainer (PaLS) highlights those members on a user inputted list that share descriptors from PubMed, GO, KEGG and Reactome.
2i.CPA -Comparative Pathway Analyzer
The Comparative Pathway Analyzer (CPA) is a web tool for comparative metabolic network analysis. The differences in metabolic reaction content between two sets of organisms are computed and displayed on KEGG pathway maps.
3. Israel Science and Technology Homepage
The Israelian government also providing the various resources for the pathogenic and non pathogenic microbs pathways and their target detection by online resources. The following mentioned web resources also helpful to explore the information of micorbs.
BioCarta Charts - Dynamic graphical models of biological pathways
Biocatalysis/Biodegradation Database - Microbial biocatalytic reactions and biodegradation pathways primarily for xenobiotic, chemical compounds
CellML Model Repository
Comprehensive Systems-Biology Database of transcriptional co-responses
E-Cell Project to model and reconstruct biological phenomena in silico
Golm Metabolome Database
Human Metabolome Database
IUBMB-Nicholson Metabolic Maps
JWS Online Cellular Systems Modelling
Metabolic Pathways of Biochemistry
MetaCyc database of metabolic pathways
Microbial biocatalytic reactions and biodegradation pathways
Molecule Pages: A comprehensive signaling database
NuGO - Nutritional Metabolomics Database
Pathcase Metabolic Pathway Database System
Reactome - a curated knowledgebase of biological pathways
Signaling and metabolic human biological pathway maps
UniPathway, metabolic pathways for the UniProtKB/Swiss-Prot
Despite rapid advances on certain aspects of plant pathogenic bacteria, many economically important pathosystems are largely unexplored and biologically relevant life stages of even familiar systems remain poorly understood. We know remarkably little about end-stage disease, latent infections, survival away from the host, interactions among multiple microbes in a plant, and the effects of quantitative virulence factors.
Biochemical reactions in a cell can be graphically represented as metabolic pathway mapsin the form of networks of interconnected molecules, depicting the relationships between enzymes and the chemical compounds they transform. The major challenge is that the metabolic network of even a simple bacterium is so complex that it is very difficult for a single scientist to grasp all the details (Karp., 2001). Computer databases for metabolic pathways and data on the participant enzymes and metabolites are therefore an indispensable tool for the analysis of biochemical networks of whole organisms. Metabolic pathways can be used to check the validity of the functional assignments by examining whether any given pathway is complete. If an enzyme is seemingly absent from an otherwise complete pathway, it may indicate that the gene coding for this enzyme was wrongly classified.Alternatively, if the gene for this enzyme is truly absent from the genome, the pathway may either have a different design or may not be operative in that particular species [Ogata et al,1996).
Metabolic pathways have attracted much interest, as they enable analysis of the functional capacities of organisms based on their genome sequences. Comparisons of metabolic pathways from different species facilitate delineation of their evolutionary relationships and identification of suitable targets for development of novel anti-microbial drugs. Integration of expression data for genes encoding metabolic enzymes with metabolic pathway maps enables understanding of how the metabolic processes of the organism are affected by different growth conditions and facilitates the determination of gene function. This knowledge is useful for the science of metabolic engineering, which aims at modifying the metabolic pathways of bacteria or plants in order to increase the production of certain compounds, or the degradation of toxic compounds (Sanford et al., 2002, Stephanopoulos, 2001).