agarwal moa lecture 103113

Discovery and Mechanistic Investigation of AntifungalsAmeeta AgarwalSenior ScientistNational Center for Natural Products ResearchUniversity of MississippiOctober 31, 2013

OverviewFirst Half: Introduction to DNA microarray technology

Experimental considerations for using DNA microarray technologySecond Half:Example of how DNA microarray technology has been used in investigating the mechanism of action of an antifungal natural product compound

Limitations and future directions

How to Study the Effect of an Antifungal Agent at a Whole-Genome Level?Treatment of a cell with a antifungal agentGene expression changes in response to the agentMonitor gene expression changes using DNA microarraysBy Using DNA Microarray Technology

What is a DNA Microarray?A solid support (glass microscope slide, nylon membrane, plastic slide) on which small DNA spots are deposited robotically and chemically fixed in place. The identity of the DNA spot (i.e., gene information) is pre-determined. The entire set of genes of an organism can be placed on a microarray.

What is a DNA Microarray? (contd.)Types of DNA Microarrays

Control CellsIsolate RNAIsolate RNALabelLabelCy5Cy3Hybridize target samples to DNA probes on a microarray slideAcquire fluorescent imageQuantitate dataIdentify differentially expressed genesSample Cells(drug-treated)Prepare cDNAPrepare cDNAMicroarray Experiment Overview (Spotted Arrays)(solvent-treated)

Raw Image of Cy3 Fluorescence (Control Cells)Raw Image of Cy5 Fluorescence (Compound-Treated Cells)Example of a Microarray Image (Spotted Arrays)

Is the signal real?

Is the data comparable across arrays (normalization)?

Comparison between untreated and treated classes (modified t-tests)

Data filtering (is useful data being compared?)- Remove genes with missing signal values- Remove genes with very low signal values- Remove genes with similar signal values across the arrays (unchanged genes)

Final result:Gene expression change = Signal in treated sample Signal in untreated sample

These parameters apply to both Spotted arrays and Affymetrix arraysData Analysis

Normalization: Correcting Differences Between Cy3 and Cy5 HybsNormalization corrects for hybridization differences between Cy3 and Cy5 samples (majority of genes should give equal hybridization) Global normalization (total intensity normalization) Use of house-keeping genes Lowess normalization (based on linear regression)

Example: Microarray DataMajority of genes will have a Cy5:Cy3 ratio of 1.0

Sheet1

Gene DescriptionCy3 SignalCy5 SignalCy5:Cy3 Ratio

YGR226C:N/A:unknown694.78711.581.02

YGR226C:N/A:unknown733.35680.260.93

YJR035W:RAD26:putative helicase495.80436.990.88


YJL196C:ELO1:fatty acid elongation protein941.062444.752.60


YJL132W:N/A:unknown; similar to phospholipase D337.75435.661.29


YJL068C:N/A:unknown; similar to human esterase D1218.571112.030.91


YJL007C:N/A:unknown348.14344.730.99

YJL007C:N/A:unknown320.10374.781.17

YIL164C:NIT1:nitrilase2319.782693.641.16


YIL100W:N/A:unknown226.69367.391.62

YIL100W:N/A:unknown297.08236.890.80

YIL036W:N/A:unknown; similar to Mei4p and to cAMP response element1078.211225.871.14


YHR194W:N/A:unknown1192.481280.031.07

YHR194W:N/A:unknown1163.261367.751.18

YHR132C:ECM14:unknown2402.312385.960.99

YHR132C:ECM14:unknown2446.352124.380.87

YKL127W:PGM1:phosphoglucomutase2663.072334.900.88


YKL064W:MNR2:unknown7763.886444.800.83

YKL064W:MNR2:unknown7305.946060.510.83

Sheet2

Sheet3

Example: Microarray Data (Contd.)Statistical Analysis of Data:Class comparison between untreated class and treated class (probability test for difference between the two classes, i.e., deviation from 1.0)

Sheet1


YGR226C:N/A:unknown694.78711.581.02

YGR226C:N/A:unknown733.35680.260.93









YJL007C:N/A:unknown348.14344.730.99

YJL007C:N/A:unknown320.10374.781.17



YIL100W:N/A:unknown226.69367.391.62

YIL100W:N/A:unknown297.08236.890.80



YHR194W:N/A:unknown1192.481280.031.07

YHR194W:N/A:unknown1163.261367.751.18

YHR132C:ECM14:unknown2402.312385.960.99

YHR132C:ECM14:unknown2446.352124.380.87



YKL064W:MNR2:unknown7763.886444.800.83

YKL064W:MNR2:unknown7305.946060.510.83

Sheet4

YGR226C:N/A:unknown431.472046510.69163503861.1836030625

YGR226C:N/A:unknown417.045288551.48081915821.322352356









YJL007C:N/A:unknown234.220428305.62282693311.3048512871

YJL007C:N/A:unknown211.589294235.36591946211.1123715903



YIL100W:N/A:unknown151.065903169.69477415181.1233161871

YIL100W:N/A:unknown152.848862175.49471049191.148158437



YHR194W:N/A:unknown775.854065824.07272140411.0621491316

YHR194W:N/A:unknown788.362183799.59291736711.0142456533

YHR132C:ECM14:unknown1666.0115971262.58943386560.7578515276

YHR132C:ECM14:unknown1698.323121435.58426362090.8452951307



YKL064W:MNR2:unknown5128.1010744178.33542411390.8147919403

YKL064W:MNR2:unknown4541.7705083753.51852964880.8264438996

Sheet2


YGR226C:N/A:unknown781.2171900556802.5974731.0273679115

YGR226C:N/A:unknown1014.0691468331904.6999510.8921481872









YJL007C:N/A:unknown692.0079367394477.3717650.6898356791

YJL007C:N/A:unknown681.4587446555464.6478880.6818430193



YIL100W:N/A:unknown492.0697355672330.04480.670727696

YIL100W:N/A:unknown403.7893164504327.6997380.8115611896



YHR194W:N/A:unknown1996.0534299181985.2426760.9945839356

YHR194W:N/A:unknown2063.45304169611946.4624020.943303464

YHR132C:ECM14:unknown5312.09714992224425.4003910.8330797171

YHR132C:ECM14:unknown5542.52657618084392.4511720.7924997944



YKL064W:MNR2:unknown7952.62685358437393.1914060.9296540052

YKL064W:MNR2:unknown8340.96363046286702.1777340.8035255914

Sheet3

Expt #1Expt#2Expt#3

Gene DescriptionCy5:Cy3 RatioCy5:Cy3 RatioCy5:Cy3 Ratio

YGR226C:N/A:unknown694.8711.61.0781.2802.61.0431.5510.71.2

YGR226C:N/A:unknown733.4680.30.91014.1904.70.9417.0551.51.3

YJR035W:RAD26:putative helicase495.8437.00.9607.2491.10.8316.2407.31.3

YJR035W:RAD26:putative helicase388.8492.71.3652.0540.40.8325.6348.51.1

YJL196C:ELO1:fatty acid elongation protein941.12444.82.61151.23447.73.0634.31695.42.7

YJL196C:ELO1:fatty acid elongation protein839.02504.23.0953.43723.43.9525.11597.13.0

YJL132W:N/A:unknown; similar to phospholipase D337.7435.71.3420.2552.51.3173.8342.72.0

YJL132W:N/A:unknown; similar to phospholipase D237.5373.81.6352.1326.10.9176.8216.91.2

YJL068C:N/A:unknown; similar to human esterase D1218.61112.00.92025.51442.80.7892.0880.91.0

YJL068C:N/A:unknown; similar to human esterase D978.5866.70.91853.41765.41.0753.7587.40.8

YJL007C:N/A:unknown348.1344.71.0692.0477.40.7234.2305.61.3

YJL007C:N/A:unknown320.1374.81.2681.5464.60.7211.6235.41.1

YIL164C:NIT1:nitrilase2319.82693.61.24195.64817.71.11516.21718.01.1

YIL164C:NIT1:nitrilase2212.62515.31.14330.24769.11.11330.51614.91.2

YIL100W:N/A:unknown226.7367.41.6492.1330.00.7151.1169.71.1

YIL100W:N/A:unknown297.1236.90.8403.8327.70.8152.8175.51.1

YIL036W:N/A:unknown; similar to Mei4p and to cAMP response element1078.21225.91.12129.11809.30.8803.8732.20.9

YIL036W:N/A:unknown; similar to Mei4p and to cAMP response element1207.41139.10.92082.22127.31.0879.3908.41.0

YHR194W:N/A:unknown1192.51280.01.11996.11985.21.0775.9824.11.1

YHR194W:N/A:unknown1163.31367.81.22063.51946.50.9788.4799.61.0

YHR132C:ECM14:unknown2402.32386.01.05312.14425.40.81666.01262.60.8

YHR132C:ECM14:unknown2446.42124.40.95542.54392.50.81698.31435.60.8

YKL127W:PGM1:phosphoglucomutase2663.12334.90.93311.22835.10.91619.41529.20.9

YKL127W:PGM1:phosphoglucomutase2895.32843.31.03830.72711.40.72070.11679.50.8

YKL064W:MNR2:unknown7763.96444.80.87952.67393.20.95128.14178.30.8

YKL064W:MNR2:unknown7305.96060.50.88341.06702.20.84541.83753.50.8

Microarray Experiment Overview (Affymetrix GeneChips)Control CellsIsolate RNAIsolate RNASample Cells(compound-treated)Prepare cDNAPrepare cDNABiotin-labeled cRNABiotin-labeled cRNA Wash chip Stain with fluorescent antibody Detect fluorescence signal Quantitate signals Identify differentially expressed genes(solvent-treated)Hybridize target samples to DNA probes on a GeneChipHybridize target samples to DNA probes on a GeneChip

Affymetrix Image File: Example

Is the Signal Real? (Affymetrix Arrays)Each gene is represented ~32 times on the array

Some gene elements are designed to give greater specificity

Some gene elements are designed to give weaker specificity

The Affymetrix software (AGCC) performs a modified t-test to determine if the signal is specific

Result: One computed signal value per geneP-value to indicate significanceDetection call P=Present (very strong specific signal)M=Marginal (weaker signal)A=Absent (very weak non-specific signal)

Genes with P calls, strong signal values and low p-values are considered useful

Statistical Analysis of Data: Class ComparisonGene 1Gene 2Gene 3Gene 4Gene 5Gene 6Gene 7Gene 8Gene 9Gene 10Gene 11Gene 12Gene 13Gene 14Gene 15Gene 16Gene 17Gene 18Gene 19Gene 20Gene 21Signal Un-B(Chip 2)Signal Un-C(Chip 3)Signal Tr-A(Chip 4)Signal Tr-B(Chip 5)Signal Tr-C(Chip 6)Signal Un-A(Chip 1)Mean Signal (Un)Mean Signal (Tr)Ratio (Tr/Un)p-valueData Analysis:Class comparison between untreated & treated classes (probability test for difference between the two classes)Software used at NCNPR for statistical analysis of microarray data: BRBArrayTools

What is the Final Outcome of a DNA Microarray Experiment?Advanced data analysis involves comparing the data to previously described genomic profiles (searching databases, cluster analysis), and network analysis (is there cross-talk between the identified pathways).Initial data analysis identifies a list of genes that are differentially expressed under a given experimental condition, i.e., which genes are induced and which genes are repressed by a compound.Further data analysis involves identifying the genes (gene annotation), determining what biochemical pathways they belong to, determining which biochemical pathways are over-represented in the data set, and interpreting the data.

Identification of MOA Using DNA Microarrays - Example

Classification of CompoundsCompound ACompound BKnown MOAUnknown MOACompound XCompound YCompound Z(DNA-damager)(Membrane-disrupter)DNA-damager

Experimental Considerations for using DNA Microarray Technology Is DNA microarray technology the appropriate technology for my project?- Does my project require the study of whole-genome effects?- Does my project require the study of a few genes? Are the appropriate tools available or accessible to me for DNA microarray studies? - Are DNA microarrays available for my target organism? Is a model organism more suitable?- Is the appropriate instrumentation available to me? Can I find a collaborator who has the instruments?- Do I have the funding to conduct DNA microarray studies? Statistical considerations - At least triplicates- Do I have access to appropriate statistical analysis software? Do I need training? Collaborator?- Are there appropriate databases available for downstream analyses?Cost of a drug MOA study with DNA microarraysGeneChip Cost: $1,380 (One chip = $230, need 6 chips)Reagents for target preparation: $600 (One target = $100, need 6 targets)Reagents for hybridization, staining, etc : $600 ($100 per chip)Miscellaneous supplies: $300(media, plasticware, RNA isolation kits) Total: ~$3,000

Example of how DNA microarray technology has been used by our group to identify the MOA of the antifungal compound sampangineAgarwal AK, Xu T, Jacob MR, Feng Q, Lorenz MC, Walker LA, Clark AM (2008) Role of heme in the antifungal activity of the azaoxoaporphine alkaloid sampangine. Eukaryot Cell. 7:387-400.Huang Z, Chen K, Xu T, Zhang J, Li Y, Li W, Agarwal AK, Clark AM, Phillips JD, Pan X (2011) Sampangine inhibits heme biosynthesis in both yeast and human. Eukaryot Cell. 10:1536-1544.References:

DNA Microarray Experiment with Sampangine using the Model Yeast Saccharomyces cerevisiaeDMSO (0.25%)SMP (IC50 conc., 1.2 g/mL)Expose for 1.5 doublings (~ 4.5 h)Isolate RNAHybridize to Affymetrix ArraysPrepare biotinylated targets

DNA Microarray Experiment with Sampangine - ResultsBiological ProcessResponse to StimulusMetabolismCellular MetabolismCellular ProcessTransportHomeostasisResponse to Oxidative StressLipid MetabolismGeneration of Precursor Metabolites and EnergyIon TransportIron Ion TransportSterol TransportIon HomeostasisIron Ion HomeostasisCellular Respiration and Mitochondrial Electron TransportSRX1 (15.1) AAD4 (6.7)GPX2 (5.1)AAD6 (4.6)GTT2 (4.3)CCP1 (3.9)TSA2 (2.7)CTA1 (2.6)PRX1 (2.6)IZH4 (14.4)HES1 (11.4)IZH2 (2.9)ATF2 (2.9)UPC2 (2.7)SFK1 (2.7)ATF1 (2.7)ARE1 (2.0)YMR210W (-2.0)ERG20 (-2.1)MCR1 (-2.4)ERG28 (-2.6)ERG5 (-2.8)CYB5 (-3.0)NDI1 (-2.2)COX15 (-2.2)COX6 (-2.3)MCR1 (-2.4)COX5B (-2.4)COX12 (-2.5)QCR7 (-2.6)DLD1 (-2.8)QCR9 (-2.8)CYC7 (-3.0)RIP1 (-3.1)COX13 (-3.4)QCR2 (-3.4)PET10 (-4.0)COX5A (-4.4)QCR10 (-5.2)NDE1 (-5.2)COX4 (-13.2)CYC1 (-13.3)FRE1 (-2.2)ENB1 (-2.4) FRE4 (-2.6)FRE5 (-2.7)ARN1 (-3.3)SIT1 (-3.6)FIT3 (-5.2)FTR1 (-6.0)ARN2 (-9.0)FET3 (-11.0)FIT2 (-14.3)DAN1 (67.5)AUS1 (5.6)SUT2 (3.2)SUT1 (2.3)YLR126C (-3.3)SIT1 (-3.6)CCC2 (-5.0)HMX1 (-5.8)TIS11 (-8.6)ARN2 (-9.0)Cell Organization and BiogenesisOrganelle Organization and BiogenesisCell Wall OrganizationDAN1 (67.5)TIR1 (9.9)DAN2 (3.7)TIR4 (3.0)DAN4 (2.5)TIR3 (2.5)DAN3 (2.5)ANB1 (6.2)HEM13 (5.6)PAU1 (4.3)AAC3 (3.5)YLR413W (3.5)PAU6 (3.5)PAU4 (3.4)PAU3 (2.9)YGL039W (2.9)PAU7 (2.6)YJR116W (2.5)YGR131W (2.4)YLR437C (2.4)YMR002W (-2.0)YBR230C (-2.3)YOR215C (-2.5)YDL110C (-2.8)YHB1 (-3.7)Other Processes

Upregulated genesDAN1, DAN2, DAN4, TIR1, TIR3, TIR4Cell wall mannoproteinsInduced in anaerobic conditionsSome are involved in sterol uptakeAUS1, SUT1, SUT2Induced in anaerobic conditionsInvolved in sterol uptakeUPC2Transcription factorRegulates anaerobic genesANB1, PAU1, PAU3,PAU4, PAU5Induced in anaerobic conditionsHEM13Involved in heme biosynthesisDownregulated genesCOX12, COX13, COX15, COX4, COX5A, COX5B, COX6, CYC1, CYC7, QCR10, QCR2, QCR7, QCR9Cytochrome c oxidases/reductases (mitochondrial electron transport)ARN1, ARN2, FET3, FIT2, FIT3, FRE1, FRE4, FRE5, FTR1, HMX1, SIT1Iron uptake and homeostasisTranscript Profiling with Sampangine: Heme Deprivation Response in Yeast Cells

Heme Biosynthesis Pathway in YeastDoes SMP inhibit the heme synthesis pathway?

Does this inhibition cause accumulation of pathway intermediates?

Does this inhibition cause reduction in heme production?

Will exogenous heme rescue cells from SMP sensitivity?

Will mutants with deletions in the pathway genes show hypersensitivity to SMP?

Does SMP interfere with the activity of a specific enzyme in the pathway?

Wild-typehem1-SMP+SMPWild-typehem1Role of Heme in the Antifungal Activity of SampangineMutant AnalysisCheckerboard AssaysBiochemical Analysis

SMP Reduces Heme Levels in Yeast and Human CellsYeast cellsHuman cellsXuewen Pan, Baylor College of Medicine (now at Novartis)

Conclusion: SMP hyperactivates Hem4 resulting in disruption of heme synthesisEffect of SMP on Heme Synthesis Pathway Enzymes

Limitations and Future DirectionsDNA microarrays are a starting point in a MOA study. Followup studies are necessary to identify the precise MOA of a drug.

DNA microarrays only measure mRNA abundance, and dont account for changes in protein levels or metabolite levels

Use of proteomics and metabolomics technologies allow the measurement of proteins and metabolites respectively

Combining genomics, proteomics and metabolomics would be a powerful way of determining the global effects of drugs

**

agarwal moa lecture 103113

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