Post-genomic Virology The impact of bioinformatics, microarrays and proteomics on investigating host and pathogen interactions Steven Masson

Introduction Post-genomic research encompasses many diverse aspects of modern science Includes –Bioinformatics –Microarrays –Proteomics Methods recently applied to the study of host and pathogen interactions for bacteria and viruses

Purpose To give a basic overview of current post-genomic research Illustrate approaches to data analysis Explore some of the areas of virology on which the research should have a marked impact

–Is the study of the application of computer and statistical techniques to the management of biological information. –In genome projects,bioinformatics includes the development of methods to search databases quickly, to analyze DNA sequence information, and to predict protein sequence and structure from DNA sequence data.

Microarrays Tool for studying how large numbers of genes interact with each other and how a cell’s regulatory networks control vast batteries of genes simultaneously An array of DNA or protein samples can be hybridized with probes to study patterns of gene expression.

Proteomics The study of entire protein systems –what are the component proteins –how they interact with each other –what kinds of metabolic networks or signaling networks they form

Genome Analysis (Genomics) Traditionally, species phylogenies have been based on comparisons of a single gene or only a few genes Results: Inconsistent comparisons –Differential rates of evolution of genes within an organism –Confounding effect of horizontal gene transfers which gives genes independent evolutionary histories

Bioinformatics Gives New Techniques Assess how many genes in one completely sequenced genome are also present in other completely sequenced genomes Allows building of phylogenetic trees based on: – defining the functional content of organisms –conservation, gain or loss of gene function It is hoped that sequence similarity will be found between proteins with functional information associated with them and unknown proteins, thereby inferring a function for the unknown proteins

Methods for searching sequence databases

Threading – functionally related proteins have similar overall 3-D structure even though extensive amino acid sequence may have been lost during evolution Not easily applied to viral proteins because they often rapidly diverge from ancestral sequence at AA level – however – such diversity can help define structural boundaries for a protein required to perform a defined function

Viral proteins have effectively sampled many AA combinations to produce such a structure Viruses able to move to other AA combinations when drug resistant mutants are selected while maintaining overall protein structure and function Therefore, viral proteins may serve as excellent models in comparative structural genomics studies of the future

Gene Expression Studies (Transcriptomics) Based on Central Dogma –Information flows from genome of organism to RNA intermediates (mRNA) to the effector molecules (proteins) Determining which mRNAs are expressed in a cell gives an idea of which proteins are present Large-scale gene expression mapping accomplished by using gene arrays

Array Procedure Synthesize oligonucleotide probe Oligonucleotides are spotted onto a glass slide Target DNA is extracted from experimental sample and labeled with two different fluorescent nucleotides –Cy3 for the control (reference) sample –Cy5 for the experimental sample Samples mixed and hybridized to a single array allowing competitive hybridization for common probe spots

Construction of a HSV-1 DNA Microarray

Analysis The ratio of each labeled cDNA hybridized is proportional to the relative amounts of the mRNA in the two samples It provides a measure of the relative abundance of the mRNA in each sample

Normalization Following image analysis, it is necessary to apply a normalization factor to the set of results from each individual experiment to account for differences in RNA quality, labeling, and hybridization efficiencies and array vibrations

Pathogen Arrays Arrays have been used to observe the effects of different culture conditions on the pathogenic bacterial gene expression patterns –They have been used in classical herpesvirus gene expression to identify patterns of immediate early, early, or late gene expression –And to determine pattern of gene expression of viral genes following the reaction of virus lytic replication from latently infected cells

Results The results confirmed earlier work on subsets of viruses’ genes, but more importantly extended such analysis to a whole genome scale encompassing most virally encoded genes In the future, replication profile studies using viral mutants will help to reveal some of the complexities of viral gene expression control, gene interaction networks and gene function

Host Arrays The effect of microbe gene expression on the biology of the microbe is intimately linked to the effect of the host Preliminary array work has been undertaken to determine how bacteria and viruses remodel the host transcriptome (the full complement of activated genes at a particular time) during the infection process

Host-Pathogen Interactions: Bacteria The effects of exposure of eukaryotic cells to different bacteria have been investigated using DNA arrays Results confirmed many previous studies, highlighting the fact that bacteria that cause acute pathogenic extracellular infections induce many genes of pro- inflammatory pathways

Bacterial infection Two host response strategies observed 1.Host cell developed an immune response to hinder parasitic development 2.The bacterial pathogen induced host metabolic processes to counteract such antibacterial responses Arrays revealed previously unrecognized effects such as the induction of interferon regulatory factor-1 (IRF- 1), which is known to be a key factor in the interferon- mediated antiviral response –However, cellular responses to viral infection also require an interferon stimulated gene factor Authors suggest that this indicates an adjustable host- defense mechanism that can discriminate between viral and bacterial infection and bring out a different outcome

Host-Pathogen Interaction: Viruses Microarrays have demonstrated the close association of virus replication with host cell machinery by the induction of host transcription, translation factors, and protein synthesis genes Some studies used defined mutant viruses that were unable to enter lytic replication –Has been used to dissect the infection process into component parts

Proteomics Proteomics represents the effort to establish the identities, quantities, structures, and biochemical and cellular functions of all proteins in an organism, organ, or organelle, and how these properties vary in space, time, or physiological state. As it is possible to determine transcriptional differences between microbes, it is possible to determine protein differences

Protein-protein Interaction Maps Many cellular processes involve protein-protein interactions, either to create active enzymes or use one protein to bind to and modify others Much information is lost by simply counting proteins or transcripts Example: Map of 2,358 protein- protein-protein interactions in yeast

Infectious Disease Proteomics So far, this has been applied to bacteria and was used successfully to compare the proteome of the non-virulent vaccine strain Mycobacterium bovis BCG with that of the virulent Mycobacterium tuberculosis They have identified 25 different proteins from the 2600 resolved proteins of both strains This technology is most hopeful to investigate the very early events in virus infection of cells

The Near Future Protein and antibody arrays –Recombinant proteins can be arrayed in a variety of formats to study protein-protein and protein-ligand interactions Tissue arrrays –Particular use in cancer biology for profiling of tissue and cell samples

Conclusion of Review The authors suggest that the combination of such interaction data with array based assessment of gene transcription will tell “when, where, and which” viral proteins are important Insight and a greater understanding of pathogenesis has been already been achieved in the short existence of post-genomic virology Ultimately, this will allow the development of new diagnostics and therapeutics translating this type of research into the improved management of infectious diseases

Obstacles Research community needs to make all the functional genomic data publicly available and in a format that facilitates cross comparisons between different groups Currently, much of the work is impossible to cross compare to find common patterns due to the use of different array methods, types and standardization of array experiments However, this will undoubtedly change in the future with the establishment of agreed scientific standards