Microbial Research Commons Including Viruses

1. Microbial Research Commons Including Viruses Prof. A.S. Kolaskar Bioinformatics Center University of Pune Pune, India

2. Introduction • Increasing research in life sciences and biotechnology in Indian Universities and national research institutions • Increased need for microbial and genetic resources • Establishment of microbial and other biological culture collections in universities and research institutions

3. Culture Collections In India • Microbial Type Culture Collection and Gene Bank (MTCC), Chandigarh – World Intellectual Property Organization (WIPO, recognized as International Depository Authority) • National Collection of Industrial Microorganisms (NCIM), Pune – Cultures are deposited for patenting • Virus cultures at National Institute of Virology (NIV) • National Facility for Animal Tissue and Cell Cuture, Pune

4. Culture Collections In India • Anaerobic Bacterial Resource Center (ABRC), Hyderabad • National Collection of Dairy Cultures, Karnal • National Fungal Culture Collection of India, Pune • University of Mumbai Food and Fermentation Technology Division 21 Culture Collections from India registered with WDCM

5. Thailand Network of Culture Collections • Biotech Culture Collection (BCC) – 3430 • Department of Medical Sciences Thailand (DMST) – 442 • Department of Agriculture (DOA) – 1163 • Thailand Institute of Scientific and Technological Research – 515

6. Issues • Limited characterization • Very few cultures characterized at DNA finger printing level • Data not fully computerized and information not available on the web • Duplication of cultures in the repository • Material Transfer Agreement similar to that in ATCC is followed by most repositories • No systems in place to detect or prevent misuse of MTA • Redistribution of cultures at informal level • Very few scientists conversant with taxonomic classification even at the national culture collections • Issues related to Biosafety and National security are not given due importance

7. PUMP-E: Salient Features • Dynamic Representation of pathways • Dynamically building the organism-specific pathways from genomic data • Development of Software for • Automated data updating (Perl scripts) • Reformatting and organization of relevant information from different databases • Drawing pathways diagrams • Comparison of pathways • Visualization of ligands, enzymes • Prediction of enzyme-substrate interactions • URL- http://202.41.70.51/mpe/

8. Approaches • Data acquisition & Integration • Dynamic Visualization of Metabolic Pathways • Query Interface • Molecular Visualization • Structure Prediction of Proteins • Simulation of 3D Structures of Enzymes and Metabolites

9. PUMP-E Homologymodels Compound Enzyme Database Organism Gene Reaction Pathway User-friendly Query interface Search by keywords Molecular viewer Dynamic generation of queried pathway

10. Source Databases for Data Acquisition  • Sequence databases: TIGR, NCBI, EBI • Metabolite databases: KEGG • Metabolic pathway database: KEGG • 3D Structure database: PDB • Enzyme Database: KEGG, EXPASY, IUBMB, BRENDA • Kinetics Data: NIST • Organism List : GOLD • Motifs, patterns & signatures : PROSITE

11. PUMP-E Front End and Query System • Web-based query interface • Supports complex advanced queries • Developed using ASP, HTML and java • Tested by various testing tools such as • Winrunner, Test Director etc.

12. PUMP-E :Front End and Query System

13. PUMP-E

15. Total number of pathways in bacteria under study as per BioCyc 9.1

16. Hamming Distance Calculations • Identical Pathways (0): • Start and end products are identical; intermediate steps are same. • Similar Pathways (1): • Start and end products are identical; intermediate steps are different • Pathways are absent (2): • Start or end products are not same

17. Metabolic pathway path profile Columns represents ‘n’ number of pathways and rows represent 15 bacteria under study. Each column corresponds to a particular type of pathway. 2 denote pathway follows same path, 1 denotes pathway follows different path while 0 denotes absence of pathway. This represents a part of the organism specific metabolic pathway path profile.

18. Metabolic pathway path profile based tree

19. Bacillus anthracis Bacillus cereus 10987 Bacillus subtilis Bacillus cereus Zk Bacillus anthracis Sterne Bacillus halodurans C-125 Bacillus anthracis strain A2012 Bacillus licheniformis ATCC 14580 Bacillus cereus ATCC14579 Bacillus anthracis Ames Ancestor Comparison of Pathways from Genus Bacillus with E.Coli 198 Pathways of E.Coli are compared with pathways data from Biocyc for each of these organisms

20. Pathways absent in Genus Bacillus; Present in E.Coli • Electron transport (aerobic and anaerobic) • Phenyl ethyl amine degradation • L-lyxose degradation • Pyridoxal 5’-phosphate salvage pathway • Super pathway of pyridoxal 5’-phosphate biosynthesis and salvage • D-allose degradation • Fructose lysine degradation • Taurine degradation

21. Effect of pathways absent in genus Bacillus • Because of absence of L-lyxose degradation pathways in genus bacillus, it cannot utilize L-lyxose sugar as source of energy • D-Allose cannot be utilized as a sole carbon source by bacteria of genus bacillus as D-allose degradation pathway is absent • Under sulfate starvation conditions, bacteria from genus bacillus cannot utilizes taurine as a sulfur source owing to absence of Taurine degradation pathway. • Bacillus cannot grow on fructoselysine or psicoselysine as the sole carbon source because of absence of Fructose lysine degradation.

22. Pathways present in Genus Bacillus; Absent in E.Coli • 2 Nitro propane degradation • Denitrification pathway • Folate transformations • Formaldehyde assimilation • Methanogenesis from acetate • Octane oxidation • Spermine biosynthesis • Xylulose monophosphate cycle

23. Effect of pathways absent in E.coli • Xylulose monophosphate cycle and Methanogenesis from acetate are characteristic pathways of methanogenic bacteria and E.coli is not a methanogenic bacteria. Hence these pathways are absent in E.coli • E.coli cannot reduce nitrate to dinitrogen because of absence ofDenitrification pathway • Formaldehyde produced from the oxidation of methane and methanol by methanotrophic bacteria is assimilated by Formaldehyde assimilation pathway. This pathway is absent in E.coli as it is not methanogenic

24. Issues • Taxonomic classification as per NCBI and thus errors can creep in • No standard system to represent metabolic pathways • Errors in annotation at gene level translate into errors in metabolic pathways • Usefulness of metabolic pathways for characterization of microbes is not exploited

25. Animal Virus Information System

26. Family Genus Protein Peptide Togaviridae Alphavirus Structural polyprotein AYEHXXV/TXPN Filoviridae Filovirus Nucleocapsid protein PQLSAIALGVAT AHGSTLAGVNV GEQYQQLREAA Iridoviridae Lymphocystivirus Iridovirus Capsid protein TSXFIDXAT IEKXXYGG SRXGDYXL Papovaviridae Papillomavirus L1 protein CKYPDF/Y GHPLF/YNKV/L Polyomavirus Coat protein VP1 PDPXXNEN GVGPLCK QVEEVR Coat protein VP2 WXLPLXLGLYG Arenaviridae Arenavirus Surface glycoprotein MLXKEYXXRQXXTP PTHXHIXGXXCPXPHR LXLXGRSC Flaviviridae Flavivirus Non structural protein 1 CWYXMEIRP Envelope glycoprotein DRGWGNXCGXFGKG Adenoviridae Hexon protein FKPYSGTA GVLAGQ PNYCFPL ,NPFNHHRN Signature peptide sequences for animal virus families

27. Virus Peptide Unique upto - number of mismatches St. Louis encephalitis virus VNPFISTGGAN 3 EGRPAT 0 Murray valley encephalitis virus VTANPYVASSTA 3 Japanese encephalitis virus LDVRMINIEA[S/V]Q 3 West Nile virus TTKATGWIIQK 3 Kunjin virus STKATGRTILKE 3 Langat virus DGAEAWNEAGR 3 FTCEDKK 0 VGFSGTRP 0 Yellow fever virus MRVTKDTN[D/G][N/S]NL 3 Powassan virus KDNQDWNSVE 3 Dengue type 1 virus GTVLVQV 0 Dengue type 2 virus GTIVIRV 0 Dengue type 3 virus TEATQL 0 GTILIKV 0 Dengue type 4 virus TTAKEVA 0 GTTVVKV 0 Tick borne encephalitis virus GFLTSVGKA 0 Louping ill virus NPHWNNVER 0 Species specific peptidesFamily – Flaviviridae Protein – Envelope glycoproteins

28. VirGen Comparative genomics & data mining of viral genomes Browse VirGen at http://bioinfo.ernet.in/virgen/virgen.html

29. Salient Features of VirGen • Organizes genomic data in a structured fashion navigating from the family to an isolate • Full genomes of viruses • Compilation of representative genome entries for every viral species (Virus Taxonomy, 7th report of ICTV) • Complete annotation of every genomic entry  • Graphical representation of genome organization • Generation of alternative names of proteins • On-the-fly genome comparisons using BLAST2 • Multiple Sequence Alignment (MSA) of genomes, proteomes and individual proteins • Whole genome phylogeny • Prediction of B-cell epitopes

30. Genome analysis & Comparative genomics resources Menu to browse viral families Search using Keywords & Motifs Guided tour & Help Navigation bar VirGen Home

31. Genome Sample Record in VirGen Tabular display of genome annotation ‘Alternate names’ of proteins Retrieve sequence in FASTA format

32. Most parsimonious tree of genus Flavivirus Input data: Whole genome Method: DNA parsimony Bootstrapping: 1000 Browsing the Module of Whole Genome Phylogenetic Trees Most parsimonious tree of genus Flavivirus Input data: Whole genome Method: DNA parsimony Bootstrapping: 1000

33. 891-1787 bp region remains unannotated using representative strain What is the origin of the insert ??? BLAST with VirGen confirmed the non-viral origin of the insert BLAST with GenBank produced significant match with Bos taurus J-domain protein Case Study: Insertions in Pestivirus 1

34. Issues • ICTV classification and information available in published literature do not always match • No standard method to describe viral isolates/strains • Electron micrograph and other image data are not readily available making identification difficult and inaccurate • Recombination occurs much faster in viruses than in bacteria/other microbes • Host/vector information needs to be described in standard language • Minimal availability of Immunological properties and therapeutic options in the databases

35. Suggestions • Devise measures to build confidence amongst underdeveloped and developing nations that their resources will not be exploited • Networking and consortia among scientists, curators of culture collections, policy makers from developed and developing countries • Material transfer agreements should be standardized by taking into consideration national security and biosafety • Create awareness about open access and open educational resources • Lobbying to policy makers to make publicly available the outcomes of government funded research • Encouraging scientists to publish in open access journals • Organize training programs by international experts to improve quality of culture collections and databases • Improve access to specialized culture collections

36. National Knowledge Commission • The National Knowledge Commission (NKC) was constituted in 2005 as a high-level advisory body to the Prime Minister of India. The Commission has been given a mandate to guide policy and direct reforms, focusing on certain key areas such as education, science and technology, agriculture, industry, e-governance etc. Easy access to knowledge, creation and preservation of knowledge systems, dissemination of knowledge and better knowledge services are core concerns of the commission.

37. Access Creation Concepts Services Applications National Knowledge Commission

38. NKC Working Model • Identify focus areas/target groups • Consultations – formal and informal • Background research and analysis • Constitution of Working Groups • Internal deliberations of NKC • Finalization of recommendations • Submission to PM • Widespread dissemination • Implementation

39. Suggestions • Devise measures to build confidence amongst underdeveloped and developing nations that their resources will not be exploited • Networking and consortia among scientists, curators of culture collections, policy makers from developed and developing countries • Material transfer agreements should be standardized by taking into consideration national security and biosafety • Create awareness about open access and open educational resources • Lobbying to policy makers to make publicly available the outcomes of government funded research • Encouraging scientists to publish in open access journals • Organize training programs by international experts to improve quality of culture collections and databases • Improve access to specialized culture collections