dna arrays for early disease detection chem 395 bioanalytical chemistry instructor prof.james...
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DNA arrays for early disease DNA arrays for early disease detectiondetectionChem 395Chem 395
Bioanalytical chemistryBioanalytical chemistry
InstructorInstructorProf.James F.RuslingProf.James F.Rusling
Presented byPresented byVigneshwaran ManiVigneshwaran Mani
OutlineOutline
What is a Microarray?What is a Microarray? Types of MicroarrayTypes of Microarray Steps involved in Microarray Steps involved in Microarray
fabricationfabrication What happens to the Genes in What happens to the Genes in
disease state?disease state? Application of MicroarrayApplication of Microarray SummarySummary
Why Microarrays?????Why Microarrays?????
Small volume- miniaturizationSmall volume- miniaturization High throughput analysisHigh throughput analysis Large information generatedLarge information generated Less time required to analyzeLess time required to analyze
What is a Microarray?What is a Microarray?
A microarray is a A microarray is a spatially orderedspatially ordered, , minituarizedminituarized arrangement of arrangement of multitude of multitude of immobilizedimmobilized reagents reagents
Types of MicroarraysTypes of Microarrays
cDNA and Oligonucleotide cDNA and Oligonucleotide MicroarraysMicroarrays
Probe: Probe: ssDNA,OligonucleotidessDNA,Oligonucleotide
Target: ssDNA,ssRNATarget: ssDNA,ssRNA Principle: HybridizationPrinciple: Hybridization
Protein MicroarraysProtein Microarrays Probe: AntibodyProbe: Antibody Target: AntigenTarget: Antigen Principle: peptide chemistryPrinciple: peptide chemistry
OthersOthers Tissue arraysTissue arrays
Gene expressionGene expression
RNA POLYMERASE
RIBOSOMES
Nucleus
Cytoplasm
cDNA ARRAYScDNA ARRAYS
Marketed By: Agilent technologies
Steps Involved in MicroarraysSteps Involved in Microarrays
Microarray Microarray printingprinting
HybridizationHybridization
DetectionDetection
DNA-Microarray printingDNA-Microarray printing
100-10000 spots100-10000 spots Glass slide used as Glass slide used as
substratesubstrate DNA is attached covalently DNA is attached covalently
to glass slideto glass slide 96-384 well microtitre 96-384 well microtitre
plates usedplates used Spot Volume 0.25-1nl.Spot Volume 0.25-1nl. Spot size 100-150Spot size 100-150µm in µm in
diameterdiameter
• 1,2,3-X,Y,Z 1,2,3-X,Y,Z directiondirection
• 4-print head4-print head• 5-glass slide5-glass slide• 6-Microtitre 6-Microtitre
plateplate• 7-Distilled 7-Distilled
waterwater• 8- Drying8- Drying
A C U G
T G AC
A C U G
T G AC
mRNA Control mRNA Diseased
Reverse transcriptase Reverse transcriptase
Fluorescent labeling Fluorescent labeling
Cy3 Cy5
cDNA
T G AC T G A
C
Hybridize target to microarray
HybridizationHybridization
HybridizationHybridization
Detection:Detection:
The slide is scanned The slide is scanned twicetwice-Once to measure -Once to measure red red intensityintensity-Once to measure -Once to measure green green intensityintensity The images are The images are overlayed to produce overlayed to produce one imageone image
ScanningScanning
M = logM = logRR//GG = log = logRR – log – logGG
M<0M<0: gene is over-: gene is over-expressed in green-labeled expressed in green-labeled sample compared to red-sample compared to red-labeled sample.labeled sample.
M=0M=0: gene is equally : gene is equally expressed in both expressed in both samples.samples.
M>0M>0: gene is over-: gene is over-expressed in red-labeled expressed in red-labeled sample compared to sample compared to green-labeled sample.green-labeled sample.
What happens to Genes in What happens to Genes in (Cancer) Disease State(Cancer) Disease State
Certain genes undergo Certain genes undergo overexpression.overexpression.
No. of copies of particular genes may No. of copies of particular genes may increase.increase.
Gene mutation.Gene mutation.
Gene is overexpressed in a certain Gene is overexpressed in a certain disease state,disease state, More cDNA(target) will hybridizes to probe, as More cDNA(target) will hybridizes to probe, as
compared to control cDNA, compared to control cDNA,
In turn, the spot will fluorescence red with In turn, the spot will fluorescence red with greater intensity than it will be with green. greater intensity than it will be with green.
Expression patterns of various genes is Expression patterns of various genes is characterized involved in many diseases,characterized involved in many diseases,
Compare expression pattern of the gene from the Compare expression pattern of the gene from the
individual with the expression pattern of a known individual with the expression pattern of a known disease.disease.
Changes in gene expression levelsChanges in gene expression levels
Number of copies of a particular target gene has Number of copies of a particular target gene has
increased.increased.
Large amount of (Disease) sample DNA will hybridize to Large amount of (Disease) sample DNA will hybridize to those spots on the microarray compared to (normal) those spots on the microarray compared to (normal) control DNA hybridizing to those same spots. control DNA hybridizing to those same spots.
Those spots containing the sample DNA will fluoresce Those spots containing the sample DNA will fluoresce red with greater intensity than they will fluoresce green, red with greater intensity than they will fluoresce green, indicating that the number of copies of the gene indicating that the number of copies of the gene involved in the disease has gone up. involved in the disease has gone up.
Genomic gains and lossesGenomic gains and losses
Gene Expression profile analysis in Gene Expression profile analysis in Human hepatocellular carcinoma by Human hepatocellular carcinoma by
cDNA microarraycDNA microarray
Eun Jung Chung,Young Kwan Eun Jung Chung,Young Kwan Sung,MohammadFarooq,Younghee Kim, Sanguk Sung,MohammadFarooq,Younghee Kim, Sanguk Im,Won Young Tak,Yoon Jin Hwang, Yang Il Kim, Im,Won Young Tak,Yoon Jin Hwang, Yang Il Kim, Hyung Soo Han, Jung-Chul Kim, and Moon Kyu Hyung Soo Han, Jung-Chul Kim, and Moon Kyu Kim.,Mol.Cells,Vol.14,pp382-387,2002Kim.,Mol.Cells,Vol.14,pp382-387,2002
HCC (Hepatocellular carcinoma)HCC (Hepatocellular carcinoma)
Primary liver cancer (HCC)Primary liver cancer (HCC) Somatic mutations and activation of certain Somatic mutations and activation of certain
oncogenes.oncogenes. These events Lead to expression changes in These events Lead to expression changes in
genes.genes. cDNA arrays are used to analyze expression cDNA arrays are used to analyze expression
patternspatterns
cDNA arrayscDNA arrays
3063 human cDNA8 different samples of HCC
Computer analysis
Gene expression patterns of 8 hepatocellular Gene expression patterns of 8 hepatocellular carcinomas.carcinomas.The genes were primarily classified into three The genes were primarily classified into three groups, based on their clustering pattern.groups, based on their clustering pattern.
Up-regulated genes in HCCUp-regulated genes in HCC Galectin-3Galectin-3 Serine/threonine kinase Serine/threonine kinase Fibroblast growth factor Fibroblast growth factor
receptorreceptor Ribosomal protein L35ARibosomal protein L35A
Down-regulated genes in Down-regulated genes in HCCHCC
mRNAs of Nip3mRNAs of Nip3 DecorinDecorin Insulin-like growth factor Insulin-like growth factor
binding protein-3binding protein-3
Application of MicroarraysApplication of Microarrays
ApplicationApplication
cDNA array.cDNA array. Tumor classification, risk Tumor classification, risk assessment, and prognosis assessment, and prognosis
prediction.prediction.
Expression Expression analysis.analysis.
Drug development, drug response, Drug development, drug response, and therapy developmentand therapy development
SummarySummary
Data can be generated in a high throughput, Data can be generated in a high throughput, parallel fashion.parallel fashion.
Less time required for analysis.Less time required for analysis. If gene expression data is already known for If gene expression data is already known for
a certain disease. Then we can compare the a certain disease. Then we can compare the gene expression data of the individual with gene expression data of the individual with the known, and predict the diseasethe known, and predict the disease
ReferencesReferences
David J. Duggan, Michael Bittner, Yidong Chen, Paul Meltzer & Jeffrey M. Trent, Nature genetics supplement, volume 21, january 1999.
Sunil R. Lakhani, Michael J.O’hare & Alan ashworth, Nature medicine,volume 7,number 4,april 2001.
Vivian G. Cheung, Michael Morley, Francisco Aguilar, Aldo Massimi,Raju Kucherlapati & Geoffrey Childs, Nature genetics supplement,volume 21,january 1999.
http://www.ncbi.nlm.nih.gov/
AcknowledgementAcknowledgement
Prof. James F. RuslingProf. James F. Rusling Chem 395 studentsChem 395 students