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 proinflammatory pathways
Bacterial infection
•
Two host response strategies observed
1.
2.
•
Arrays revealed previously unrecognized effects such
as the induction of interferon regulatory factor-1 (IRF1), which is known to be a key factor in the interferonmediated antiviral response
–
•
Host cell developed an immune response to hinder parasitic
development
The bacterial pathogen induced host metabolic processes to
counteract such antibacterial responses
However, cellular responses to viral infection also require an
interferon stimulated gene factor
Authors suggest that this indicates an adjustable hostdefense 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 proteinprotein-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