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Introduction to Bioinformatics 6 of 25
Previous Identification Techniques
Similar gene amplification (degenerate PCR)
Antibody recognition (immunoscreening of cDNA Libraries)
Drawbacks: Limited candidates Biased Time consuming
Identification using microarray
Introduction to Bioinformatics 7 of 25
The DeRisi Lab Viral Microarray
Approx. 1,000 viruses Probes 70 nucleotide long 10 most conserved of each virus Amplification and hybridization
Objective: “create a microarray with the capability of detecting the widest possible range of both known and unknown viruses”
Identification using microarray
Introduction to Bioinformatics 8 of 25
The SARS Epidemic
SARS – Severe acute respiratory syndrome Flu-like symptoms Nov. 2002: first case in Gunangdong, China 15 Feb. 2003: Spreads to Hong-Kong 21 Feb.: 12 infections that will spread to
Hong Kong, Vietnam Singapore, Ireland, Germany and Canada
Identification using microarray
Introduction to Bioinformatics 9 of 25
The SARS Epidemic
Cases in: China, Hong Kong, Canada, Taiwan, Singapore, Vietnam, USA, Philippines, Germany, Mongloia, Thailand, France, Malaysia, Sweden, Italy, UK, India, Korea, Indonesia, South Africa, Kuwait, Ireland, Romania, Russia, Spain, Switzerland.
Total 8,096 known cases 774 deaths Mortality rate of 9.6% April 2004 –
last reported case
Identification using microarray
Introduction to Bioinformatics 10 of 25
The SARS Identification
March 15th - WHO generate global alert March 22th – samples obtained Amplified and Hybridized with microarray
(1,000 viruses, 10 probes of 70 nucleotides)
Following results in less then 24 hours
Identification using microarray
Introduction to Bioinformatics 11 of 25
SARS Identification
Identification using microarray
FamilyVirus
CoronaIBVAA
CoronaIBVAA
CoronaBovine corona
AA
CoronaHuman 229EAA
AstroTurkey astroAA
AstroOvine astroAA
AstroAvian nephritis
AA
AstroHuman astroAA
Introduction to Bioinformatics 12 of 25
SARS Identification
Identification using microarray
FamilyVirus
CoronaIBVAA
CoronaIBVAA
CoronaBovine corona
AA
CoronaHuman 229EAA
AstroTurkey astroAA
AstroOvine astroAA
AstroAvian nephritis
AA
AstroHuman astroAA
Introduction to Bioinformatics 13 of 25
Summary (round 1)
Microarray of conserved sequences from thousands of viruses
Hybridization enable identification
Rapid procedure
Limited homology suffice
Sequencing based on DNA recovered from microarray
The SARS proof
Identification using microarray
Introduction to Bioinformatics 15 of 25
E-Predict Algorithm Challenges
Complex hybridization pattern, still time consuming
Human interpretation might be biased
Separate closely related species
Unanticipated cross hybridization
Statistical significance
Signal from dozens or hundreds of species when pure samples impossible to obtain (metagenomics)
The E-Predict Algorithm
Introduction to Bioinformatics 17 of 25
Significance Estimation
Similarity ranking ≠ Probability that best profile corresponds to virus in sample
1,009 independent diverse microarray data
For every virus, most data – false positive
Used as null (H0) Distribution
The E-Predict Algorithm
Introduction to Bioinformatics 21 of 25
Serotype Discrimination
HRV – species of the Rhinovirus genus, part of the picornavirus family
HRV can be divided to: HRV group A HRV group B HRV87 (closely related to enteroviruses)
Energy profiles of HRV89 (group A) and HRV14 (group B)
The E-Predict Algorithm
Introduction to Bioinformatics 23 of 25
Summary
Results achieved very rapidly Minimal human interpretation: no bias Not sensitive to noise Handles complex hybridization pattern Valid Interfamily and intrafamily
separation Serotype separation
The E-Predict Algorithm
Introduction to Bioinformatics 24 of 25
Possible Application
Pathogen detection: clinical specimens
field isolates
Monitoring food/water contamination Characterization of microbial communities
from soil/water
The E-Predict Algorithm