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EP1230383A2 - Bioanalyse quantitative d'expression de genes dans des microechantillons - Google Patents

Bioanalyse quantitative d'expression de genes dans des microechantillons

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Publication number
EP1230383A2
EP1230383A2 EP00921995A EP00921995A EP1230383A2 EP 1230383 A2 EP1230383 A2 EP 1230383A2 EP 00921995 A EP00921995 A EP 00921995A EP 00921995 A EP00921995 A EP 00921995A EP 1230383 A2 EP1230383 A2 EP 1230383A2
Authority
EP
European Patent Office
Prior art keywords
spots
genes
hybridization
nucleic acid
dna
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP00921995A
Other languages
German (de)
English (en)
Inventor
Eugenia Wang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jewish General Hospital
Original Assignee
Jewish General Hospital
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from CA002268695A external-priority patent/CA2268695A1/fr
Priority claimed from US09/299,193 external-priority patent/US6511849B1/en
Application filed by Jewish General Hospital filed Critical Jewish General Hospital
Publication of EP1230383A2 publication Critical patent/EP1230383A2/fr
Withdrawn legal-status Critical Current

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6813—Hybridisation assays
    • C12Q1/6834—Enzymatic or biochemical coupling of nucleic acids to a solid phase
    • C12Q1/6837—Enzymatic or biochemical coupling of nucleic acids to a solid phase using probe arrays or probe chips
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/00583—Features relative to the processes being carried out
    • B01J2219/00596—Solid-phase processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/00583—Features relative to the processes being carried out
    • B01J2219/00603—Making arrays on substantially continuous surfaces
    • B01J2219/00605—Making arrays on substantially continuous surfaces the compounds being directly bound or immobilised to solid supports
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/00583—Features relative to the processes being carried out
    • B01J2219/00603—Making arrays on substantially continuous surfaces
    • B01J2219/00605—Making arrays on substantially continuous surfaces the compounds being directly bound or immobilised to solid supports
    • B01J2219/0061—The surface being organic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/00583—Features relative to the processes being carried out
    • B01J2219/00603—Making arrays on substantially continuous surfaces
    • B01J2219/00659—Two-dimensional arrays
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/0068—Means for controlling the apparatus of the process
    • B01J2219/00686—Automatic
    • B01J2219/00689—Automatic using computers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/0068—Means for controlling the apparatus of the process
    • B01J2219/00702—Processes involving means for analysing and characterising the products
    • B01J2219/00707—Processes involving means for analysing and characterising the products separated from the reactor apparatus
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
    • B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
    • B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
    • B01J2219/00718—Type of compounds synthesised
    • B01J2219/0072—Organic compounds
    • B01J2219/00722—Nucleotides
    • C—CHEMISTRY; METALLURGY
    • C40—COMBINATORIAL TECHNOLOGY
    • C40B—COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES
    • C40B40/00—Libraries per se, e.g. arrays, mixtures
    • C40B40/04—Libraries containing only organic compounds
    • C40B40/06—Libraries containing nucleotides or polynucleotides, or derivatives thereof

Definitions

  • the present invention is in the area of a method for detecting quantitative as well as qualitative levels of expression of genes in a microarray, for example, in combinatorial libraries.
  • Microarray techniques offer biologists a systematic way to survey DNA and RNA variation. Until recently, the only tools available to scientists were Northern blot analysis, RNase protection or RT-PCR to assay differential expression. These techniques are limited to use with a few genes at a time. In contrast, microarray techniques provide a means of generating a global view of huge numbers of gene expressions simultaneously which has attracted great interest, and they are becoming standard tools of both molecular biology research and clinical diagnostics. As the first step of expression profiling experiments, the analysis and quantification of the array images exert an important impact on the accuracy of the subsequent data mining and exploration.
  • Microarrays typically contain at separate sites nanomolar (less than picogram) quantities of individual genes, cDNAs, or Expressed Sequence Tags ("ESTs") (partial gene sequences) on a substrate such as a nitrocellulose or silicon plate, or photolithographically prepared glass substrate.
  • ESTs Expressed Sequence Tags
  • Microarrays containing approximately a thousand ESTs are commercially available from Affymatrix. Clontech sells arrays of gene- specific cDNA fragments, with approximately half the number of Affymatrix' s ESTs, designed for specific research areas such as tumor research or broad applications. Once fabricated, the arrays are hybridized to cDNA probes using standard techniques with gene-specific primer mixes.
  • the nucleic acid to be analyzed — the target — is isolated, amplified and labeled, typically with a fluorescent reporter group, radiolabel or phosphorous label probe.
  • the array is inserted into the scanner, where patterns of hybridization are detected.
  • the hybridization data are collected as light emitted from the reporter groups already incorporated into the target, which is now bound to the probe array. Probes that perfectly match the target generally produce stronger signals than those that have mismatches. Since the sequence and position of each probe on the array are known, by complementarity, the identity of the target nucleic acid applied to the probe array can be determined.
  • cDNAs and ESTs can be detected by autoradiography or phosphorimaging ( P). Fluorescent dyes are also used, and are commercially available from suppliers such as Clontech.
  • the mapping and sequencing phase of the human genome project is well ahead of schedule. So far, complete genomic sequences of 17 model organisms, including the eukaryotes S. cerevisiae and C. elegans, have been finished. The complete human genome sequence is expected to be available this year. However, of the genes already sequenced, currently the function of only approximately 20% of 53,000 human genes, or 25% of 6,200 yeast open reading frames, are known. The next phase of the human genome project will be dealing with understanding the functions of the remaining 80% of the genes. The main approach to studying a new gene's function is by determining its pattern of expression - when, where and how strongly it is expressed.
  • TIBS 24, 168-173 (1999) are probably not optimal hybridization probes, because clone inserts can be of very different lengths (0.3 -3.0 kb) and GC content, and therefore have different melting temperatures. This means that the efficacy of hybridization of different probes in microarrays under particular hybridization conditions can differ very significantly, making expression profiles dependent on experimental conditions. Finally, if cDNA targets for hybridization on arrays on glass are fluorescently labeled, while this approach allows direct comparison between control and test samples in one experiment (Cheung, et al. Nature Genetics 21, suppl., 15-19 (1999)), the sensitivity of fluorescent probes is lower than that of radioactive or enzyme-coupled probes.
  • Fluorescent probes can also bleach during analysis, making it impossible to rescan an array; and last but not least, the price of laser scanners and other equipment necessary to analyze fluorescence still remains too high for broader implementation of cDNA microarrays.
  • Microarrays provide a simple and comprehensive way to describe huge numbers of genes simultaneously. While array preparation techniques have matured in recent years, as reported by Cheung, et al, Nature Genet. 21, 15-19 (1999) and Brown and Botstein N ⁇ twre Genet. 21, 33-37 (1999), the techniques for quantifying and analyzing the array data are still in an evolving stage. As noted above, arrays in general have found a wide range of applications, such as investigating normal biological and disease processes, and profiling differential gene expression.
  • Bleeding due to an overabundance of a specific gene's presence or expression is a problem with some commercially available filters, with bleeding from one spot to adjacent spots, obscuring the results for the adjacent spots. Fluorescent labels fade, so that permanent records must be made by alternative techniques. Sensitivity of detection is low.
  • a cDNA probe generated by random priming distributes the isotropic label among nearly all RNA species. Many labeled species will contribute only to non-specific background hybridization, or will cross- hybridize to many different cDNA fragments. The proportion of label that is in sequences complementary to genes represented on the array is minimal. Label can be concentrated into poly A+ RNA using oligo(dT) primers. However, most cells contain mRNA from many thousands of genes at any given time, so the probe primarily consists of sequences not represented on the array that can contribute to undesirable cross-hybridization. Selection of probes to exclude common sequences helps. Another approach to address these problems is to decrease the number of genes on the array. Still another approach is to apply multiple samples to each array, so that results can be averaged, and anomalous results readily identified.
  • a method for detection of gene expression or hybridization in microarrays for example, in combinatorial libraries where quantities are very small and spots located very closely, resulting in uncomfortable situations where intense reaction can spill over into the adjacent spots, and therefore obscure the accuracy of the reaction of the neighboring sites.
  • the assay uses a digoxigenin enzyme assay for detection.
  • the examples demonstrate the utility of the enzymatic detection system.
  • the transcriptionally regulated profile of E-box-related genes specific to a given cultured cell sample was determined by unique digoxigenin (DIG)- labeled cDNAs produced from RNAs isolated from the culture of interest.
  • DIG digoxigenin
  • This specific enzymatic labeling probe allows the end result of detecting hybridization reaction intensity by colorimetric evaluation of alkaline phosphatase-coupled antibody to DIG.
  • the enzymatic deposit on each locus of the E-box microarray is readily analyzed by an upright microscope attached to a CCD camera, without the problem of the long delay needed for exposure time with radioactive probes, or the photobleaching and high background reaction problem associated with the fluorescent probe approach.
  • the enzymatic approach provides a user-friendly designer approach to custom-adapt the gene screening task to analyze a subgroup of gene expressions controlled by the same molecular modality.
  • the assay is very sensitive, enabling detection of as little as 0.02
  • a method for enhancing the reliability of analysis of expression of DNA in microarray formats has also been developed, using software analysis that normalizes the spots.
  • This process uses deformable template techniques to quantify large-scale array data automatically, despite possible spatial distortion of the arrays.
  • Each node in the deformable template represents a gene spot, and iterates according to the gradient descent rule, which minimizes an energy function combining data mismatch energy and template deformation energy .
  • Figures la, lb, lc, Id and le show an apparatus for making microarrays.
  • Figure 2a-e demonstrates all the steps of template definition, iteration, unreliable region detection and spot labeling. It is easy to distinguish the over-expressed spots, labeled as '*', and those distorted by the shadow of over-expressed spots, labeled as '?'. The labels of the spots are confirmed by visual inspection on the original image, where arrows indicate the positions of spots in the shadow of the over-expressed ones.
  • Figure 2a is a raw image of part of a ClonTech cDNA array. The array quantification method was tested by analyzing ClonTech AtlasTM cDNA Filter Arrays, which comprise 588 cDNA elements spotted in duplicate.
  • an autoradiograph was obtained after the procedures of radioactivity labeling, array hybridization and rinsing.
  • the digital images are obtained by scanning the autoradiographs upright at 300 DPI, with 8-bit gray scale and gamma correction disabled.
  • a 3*3 out- range pixel smoothing filter was applied to reduce salt-and-pepper noise.
  • the initial position overlays a grid template on the original image, which is one block of a ClonTech filter. Users are required to provide the position of spots in the left-top and right-bottom corners via a graphical user interface.
  • Figure 2b is the initial alignment with a prototype template.
  • Figure 2c is the fine alignment by automatic iteration of a deformable template.
  • Figure 2d shows the unreliable regions (yellow) detected by mathematical morphology.
  • the structuring element is chosen as a disk with the same size as an ideal sample spot.
  • Figure 2e shows automatic labeling of the spots, corresponding to the unreliable regions ('*' over-expressed spots; '?' - spots distorted by the shadow; V - normal spots).
  • Figures 3a-3d show the qualitative and quantitative evaluation of repeatability and reliability. Two blocks (transcription factors and general DNA-binding proteins) of ClonTech AtlasTM mouse cDNA arrays were quantified using the same deformable template method. The imaging conditions are the same as in Figure 2a.
  • the normalization procedure can be understood as rotating the coordinate space by angle ⁇ (L2, 13) .
  • the reliability of normalization can be evaluated by the angles ⁇ (Ll,L3) and ⁇ (L2,L3) ( Figure 3d).
  • Figure 4 shows cDNA microarray hybridization for evaluation of E-box binding-related gene expression.
  • the matrix position, with each gene's abbreviation, is written underneath each locus of three repeats of dots with identical amounts deposited; the X-coordinates denote the number 1, 2, 3, 4, and 5 positions, and Y-coordinates denote the "a" through "o" positions.
  • the matrix location for each gene triplet is then identified as XN coordinates. For example, 5k denotes the position of N-Myc, and 3d denotes the position of Mad. The same coordinates are also included in Table 4.
  • Figures 5a and b show the expression profiles of E-box binding-related gene expressions in Hela cells.
  • Figure 5a - total RNA was labeled with digoxigenin in RT reaction with gene specific primers;
  • Figure 5b - mRNA was labeled with digoxigenin in RT reaction with oligo(dT) primers.
  • Arrows within the matrix show positions of: /- Hela DNA (positive control); II- lambda DNA (negative control); Z/7-UBC; IV- RPL-13A; V- MBP-1; VI- HPRT1. The distance between dots can be measured by the bar of 1mm.
  • Figure 6 shows the hybridization of products of multiplex PCR with 5 pairs of primers with a cDNA microarray. Arrows within the matrix point to: I -Mrdb; //- c-Myc p64; III- TFII-1 ; IV- ODC1 ; V- cdc25A; VI- Hela genomic DNA.
  • Figure 7 shows the relationship between concentrations of 5 genes including Mrdb, c-Myc, TFII-1, ODC1, and cdc25a, and intensity of hybridization signals. Logarithmic approximation is shown. Dot intensity is represented by the arbitrary units on the Y-axis; concentration is measured as ng/ml on the X-axis.
  • Figures 8a and 8b show the expression profiles of E-box-related genes in Hela cells ( Figure 8a), and normal human lymphocytes ( Figure 8b). Arrows within the matrix show positions of: I- Aldolase C; II- Mad4; III- MBP-1.
  • Figures 9a, b and c depict a pairwise comparison of E-box gene expression in Hela cells and human lymphocytes. Two independent hybridizations are averaged for each type of cell.
  • Figure 9a Three- dimensional, and Figure 9b - two-dimensional, representations of differences in gene expression. Each panel corresponds to one column in Figure 8a, and each bar represents an individual gene.
  • Figure 9c Distribution of genes with common gain or loss of expression in dependence on relative ratio value. The relative fold ratio between samples S 1 and S2 is computed as
  • the first is a chromophore detection assay to facilitate determination of the amount of expression in microarrays, Northern blots, Southern blots, and other techniques for determination of DNA hybridization; the second is a fast and reliable approach to analyzing generic arrays using a deformable template to extract the expression spots in the array, which is capable of identifying the unreliable expressions automatically.
  • This automated iteration reduces the human error in quantification to a large extent, and optimizes the processing time in comparing arrays ten-fold compared to the existing packages.
  • Figures la-le show an apparatus for forming microarrays of biological materials.
  • the base of the apparatus is a vibration isolation table 1.
  • a platform 14 Mounted on the table 1 by means of a first horizontal linear guide 2, is a platform 14.
  • the platform 14 is connected through a carriage (not shown) to a drive mechanism (not shown) such as a lead screw in the guide 2.
  • the horizontal linear guide 2 carries a computer controlled motor 5 a connected to the drive mechanism, which effects movement of the platform 14 back and forth along the first linear guide 2.
  • the motor 5 a is linked to a computer 13 via an amplifier 15 and a motion control board 28.
  • the platform 14 is designed to hold detachable sample reservoirs 11 in predetermined positions 18. As shown in Figure lb, a sample reservoir 11 is a 96-well microtiter plate. The platform 14 also holds a series of substrates 12 which are held in place by means of suction, created by drawing a vacuum through the holes 21 on the platform underneath the substrate.
  • the table 1 At opposite sides of the table 1 are vertical risers 6, having upper ends that carry a second horizontal linear guide 3 mounted substantially transversely, above and straddling the platform 14 and the first linear guide 2.
  • the second horizontal linear guide 3 carries a computer controlled motor 5b connected to a drive mechanism (not shown) such as a lead screw which is in threaded engagement with a carriage (not shown) which can be moved along the guide 3 by operation of the motor 5b, linked to the computer 13 via an amplifier 16 and the motion control board 28.
  • a drive mechanism such as a lead screw which is in threaded engagement with a carriage (not shown) which can be moved along the guide 3 by operation of the motor 5b, linked to the computer 13 via an amplifier 16 and the motion control board 28.
  • a third guide 4 is attached to the second linear guide 3 by means of the carriage such that the third linear guide 4 is substantially pe ⁇ endicular to the first linear guide 2 and the second linear guide 3.
  • the third linear guide 4 can be moved back and forth by the carriage along the axis of the second linear guide 3.
  • a drive mechanism within the third linear guide 4 e.g. a lead screw that is meshed with the carriage, enables the third linear guide 4 to be moved vertically by a further computer controlled motor 5c and positioned in any desired vertical location within the range of movement.
  • Computer control is achieved by connection of motor 5a to an amplifier 17 which is connected to the motion control board 28.
  • a sampling manifold 9 which contains four sampling needles 8 spaced linearly along the manifold at intervals to allow for simultaneous sample pick-up by all four sampling needles 8 from four sample locations in sample reservoirs 11.
  • the sampling manifold 98 can be moved between two positions by activation of a pneumatic cylinder 10 connected between the sampling manifold 9 and third linear guide 4.
  • the sampling manifold 9 is in the "down" position, for sampling and cleaning.
  • the sampling manifold is pivoted to the "up" position, as shown by the broken lines.
  • the base of the third linear guide 4 has piezoelectric inkjets 7 mounted thereon, the sampling needles 8 being connected to the piezoelectric inkjets 7 by microline tubing conduits 34 ( Figure lc).
  • Each sampling needle 8 is connected through a conduit 34 to a micropump 35 and thence to a microvalve 36.
  • Each microvalve 36 is adjustable so that the fluid delivered from the pump 35 can be directed selectively to the corresponding piezoelectric inkjet 7 or to the waste.
  • overflow reservoirs 24, 25 there are two gravity overflow reservoirs 24, 25, positioned on opposite sides of the first linear guide 2 at the rear of the platform, on isolation table 1.
  • the reservoirs 24, 25 contain cleaning solutions that can, when desired, be pumped through the interior of the apparatus.
  • such overflow reservoirs 24, 25 are provided with a fluid in-feed aperture 40 in the lower portion of the overflow reservoir, into which is pumped the solution of interest from a fluid reservoir 41 , through a pump 44.
  • a fluid overflow aperture 42 In the upper portion of the overflow reservoir is a fluid overflow aperture 42 out of which the liquid in the overflow reservoir returns to the fluid reservoir 41.
  • the overflow reservoir is further provided with openings 43 on the top to allow for insertion of the sampling needles 8.
  • each box 26, 27 is mounted to the vibration isolation table 1 .
  • the top of each box is provided with openings 51, 52 to accommodate the sampling needles 8 and the piezoelectric inkjets 7, respectively.
  • Each box 26, 27 is provided with nozzles 50 on the interior sides thereof for the delivery of wash fluid from a wash fluid reservoir (not shown) onto the exterior surfaces of the sampling needles 8 and the piezoelectric inkjets 7.
  • the lower part of the boxes are provided with an exit port 53 through which the waste wash fluid is sucked off into a vacuum trap.
  • a number of substrates 12 are placed on the platform 14 and selected samples are loaded into the sample reservoirs 11.
  • the platform 14 mounted on the first linear guide 2 is moved into position such that the sampling manifold 9 is in position for sampling.
  • the sampling manifold 9 is lowered by actuation of the pneumatic cylinder 10, and the third linear guide 4 is lowered, to place the sampling needles 8 into the sample reservoirs 11.
  • the quantities of sample to be placed on the microarray are taken up through the sampling needles 8 by way of the micropumps 35 and delivered through the conduits 34 to the piezoelectric inkjets 7, and the sampling manifold 9 retracted.
  • the piezoelectric inkjets 7 are positioned over the substrate 12 and the piezoelectric inkjets 7 deliver the samples onto the substrate 12. This process is repeated such that multiple samples are delivered to the selected substrates 12 at the predetermined locations to form a microarray.
  • the sampling needles 8, the conduit 34, the micropump 35, the microvalves 36, and the piezoelectric inkjets 7 are cleaned between take-up of different samples. This is done using the two gravity overflow reservoirs, one 24 containing saline and the other 25 containing water. Saline or water is taken up by sampling needle 8 and delivered through the conduit 34 to the piezoelectric inkjets 7 to flush the system. Following this the cleaning boxes 26, 27, are used to spray water and/or air on the exterior surfaces of the sampling needles 8 and the piezoelectric inkjets 7.
  • the whole of the process may be automatized. Motion control, digital actuation, sample processing, and micropumping can all be controlled by means of a computer using specialized computer programs designed therefor. Certain functions such as the recirculation of fluid through the gravity overflow reservoirs can be run continuously during operation and do not require computer control.
  • liquid reagents can be dispensed using the described apparatus.
  • the liquids may contain DNA, RNA, modified nucleic acids and nucleic acid analogues, peptides, antibodies, antigens, enzymes, or cells.
  • the apparatus can also dispense activator or inhibitor fluids.
  • An activator fluid is one which makes possible coupling to the substrate, or causes a synthesis reaction with a previously deposited reagent.
  • An inhibitor fluid protects an area on the substrate to prevent the material in the area from reacting.
  • Piezoelectric inkjets 7 preferably are drop-on-demand printer heads which are able to deliver small metered amounts of liquids quickly and accurately.
  • the amount of material delivered will depend on the specific use, and may be, for example, 10 to 1000 picolitres (pi), preferably 20 to 100 pi, and most preferred 35 pi.
  • sample reservoirs include 96-well and 384-well microtiter plates and EppendorfTM tubes.
  • sampling devices include sampling needles, which may be made of stainless steel bore tubing and may include syringe tips.
  • the gravity overflow reservoirs and the cleaning boxes may be located in any suitable position.
  • the micropumps 35 may be activated intermittently or continuously. Intermittent activation may be achieved using an AC - DC relay under the control of the motion control board. Components of the apparatus may be provided separately for assembly, together with instructions for assembly and use of the apparatus. Digoxigenin Enzymatic Detection Assay
  • the assay utilizes digoxigenin (DIG) to label target nucleic acid molecules, such as cDNA produced from gene-specific primers, with subsequent incubation with anti-digoxigenin antibody conjugated with an enzyme such as alkaline phosphatase (AP), and colorimetric or chemiluminescent detection.
  • DIG digoxigenin
  • AP alkaline phosphatase
  • the method includes the steps of labeling the nucleic acid molecules, typically cDNA, hybridizing the labelled molecules, rinsing to remove material that did not hybridize, incubating the hybridized material with enzyme conjugated anti-digoxigenin antibody, typically alkaline phosphatase, staining for revelation of bound enzyme, and scanning for data acquisition.
  • This method is fast, requiring a maximum of two days, and can detect samples of four micrograms or less.
  • the assay can be used to detect as little as 0.02 nanograms of nucleic acid.
  • the starting material i.e., the DNA or RNA isolated from the targeted tissues can be as little as one to two micrograms.
  • the starting materials can be labeled by the digoxigen method, then the labeled nucleic acid used for hybridization with the microarrays. Methods currently used by
  • the assay uses an enzyme that can cleave a chromogenic, chemiluminescent or colorimetric substrate.
  • the enzyme is alkaline phosphatase and the substrate is Disodium 3-(4- methoxyspiro ⁇ 1 ,2-dioxetane-3 ,2 ' -(5 ' -chloro)tricyclo [3.3 J J ] decan ⁇ -4-yl) phenyl phosphate - CSPD.
  • the reacted substrate is stained with 5-Bromo-4-chloro-3-indolyl- phosphate, toluidine salt (BCIP), and Nitro blue tetrazolium chloride (NBT) in detection buffer. Extraction of gene expression from array images
  • the gene expressions are represented as equally spaced spots of the same size.
  • the spots can be displaced from their ideal positions.
  • Simple grid templates are insufficient to extract the gene expressions.
  • a deformable template with shape-varying ability, has been developed to keep track of the distortion of gene spots. Active shape models (Cootes, et al., Computer Vision and Image Understanding 61, 38-59 (1995); Ostu, N. IEEE Trans, on Syst. Man &
  • deformable template matching techniques integrate model- driven and data-driven analysis by an energy function and a set of regularization parameters.
  • Two factors are taken into account: data mismatch and template deformation.
  • criterion functions are defined to quantify these two factors: one measures how much the input pattern differs from the deformed template, and the other measures the degree to which the template is deformed.
  • optimal matching is achieved by minimizing a weighted sum of these two criteria.
  • the weighting factors are called regularization parameters, which provide a trade-off between template deformation and data mismatch.
  • Template representation As described in the example, a raw image is scanned from a ClonTech cDNA mouse array. Each sample spot in the three-dimensional view of the input image of the array corresponds to a local minimum in the gray level space. The following model is then used in order to extract pertinent information.
  • An array of gene samples is represented as a set of N circle spots of the same size.
  • the intensity of the spot is an average value 7 of pixel intensities inside the circle.
  • the radius of a microarray spot is determined by the printing and imaging conditions, and can be measured and set as a constant over the whole array. Therefore, the prototype template is based on prior knowledge about a generic array, which can be set as a grid of evenly spaced circles around the array.
  • the objective of using a deformable template is to find the optimal position of the centers of all spots regarding both data mismatch and template deformation factors.
  • Data mismatch energy measures the fitness of the deformed template to the input pattern. Since the input image is in gray level, and the gene expressions are represented by the integral intensities of local regions, data mismatch energy can be defined in term of the integral intensities:
  • ⁇ t is the weight of the z ' -th node
  • r is a predefined radius for the sample spots.
  • the potential function is an integration of gray level values over a local region, which has smoothing abilities. Experimental results exhibit its robustness to minor perturbation and noise. Template deformation energy
  • the template deformation energy measures the deviation of the deformed template from the prototype template.
  • the template deformation to translation happens due to wa ⁇ ing of membranes.
  • the deformation energy for each spot is defined as the
  • ⁇ is the flexibility of the -th node.
  • the minimization of the template deformation energy helps to prevent the nodes from being attracted by perturbations and noise in local backgrounds, and thus improves the robustness of the proposed algorithm.
  • the localization procedure of sample spots co ⁇ esponds to the minimization of the overall energy.
  • the flexibility and weight of each spot are set to be the same.
  • the positions of the target centers are regressed to minimize the energy defined by (4), which can be inte ⁇ reted as a set of nodes on a rubber band; the positions of the nodes tend to gravitate to the bottom of a local minimum of the energy field.
  • the nodes are moved one unit in each iteration, according to the sign of Ax and ⁇ y • For example, to extract gene expressions from one function group of an Atlas cD ⁇ A array, a 3*3 out-range pixel smoothing filter (Ekstrom, M. P.
  • the spots are mutually exclusive.
  • the change of intensity within each spot has a certain range.
  • a ® B ⁇ b + a I for some b _ B and a e A ⁇ Erosion of a binary image A by binary structuring element B,
  • a disk structuring element, C whose size is the upper limit of a spot on the a ⁇ ay being studied, was selected.
  • 0 ⁇ x ⁇ M, 0 ⁇ y ⁇ N ⁇ by global thresholding techniques, such as Ostu's thresholding method (Ostu, ⁇ .A. I ⁇ Trans, on Syst. Man & Cybern. 8, 62-66 (1978)) based on optimal discriminant analysis: G ⁇ g(x,y) ⁇ 0 ⁇ x ⁇ M, 0 ⁇ y ⁇ N ⁇ ,
  • the normalized volume is a real value within a range [0, 7 max ] , where I max is the upper limit of a pixel value.
  • 7 max equals 255 and 65535 respectively.
  • Performance Test Automatic Processing vs. Manual Operation
  • the system was trained based on 24 sub-images from two ClonTech filters.
  • the training stage includes selection of the optimal regularization parameter in the definition of energy.
  • the system was tested on 204 sub- images from 17 ClonTech filters, and 50 bio-chip microa ⁇ ay images printed in house. Testing results show that the proposed model can extract the spots satisfactorily, when they are mutually exclusive. However, some spots are attracted by the over-expressed ones, and thus cause distortion to the quantification procedure. Although the system is able to identify these e ⁇ oneous spots automatically, an ultimate solution requires improvement in the design of optimal probes and experimental conditions.
  • Table 1 lists the comparison among three systems in analyzing AtlasTM A ⁇ ays, including AtlaslmageTM 1.0 released by ClonTech (http://www.clontech.com), EstBlot (Adryan, et al., BioTech 26, 1174-1179 (1999)) developed by Johannes Gutenberg University, and Array Analyzer developed in our lab. Compared with the existing systems, our system performs several times faster. The system error is measured by repeating the quantification procedure on one a ⁇ ay six times. Two factors are considered in evaluating the system:
  • Table 2 lists the comparison of two systems on both ClonTech filters and the microa ⁇ ays printed in house, and it is clear that the system described herein outperforms the existing system.
  • R RI ⁇ 0.5 co ⁇ esponds to up- or down-regulation at two times.
  • genes with normalized abundance in [0, 0.33], (0.33, 0.67], (0.67, 1] as low, medium, and high abundance the maximum e ⁇ or in ratio for each category is 1.89%, 4.89% and 14.54%, respectively. It is clear that the ratios among low abundance genes are more sensitive to the initial positions of the prototype template in the quantification. Therefore, the system is more reliable in dealing with medium- and high- abundance spots.
  • Table 3 lists the relationship between the automatic evaluation (reliability labels) of the spots and the quantitative e ⁇ ors. Quantitative studies confirm that the automatically identified 'unreliable' loci suffer from more errors than the other two categories. Actually, the percentage of 'unreliable' spots can be used as an indicator of the quality of the hybridization procedure.
  • a ⁇ ay Analyzer automates most of the quantification and comparison functions. It processes different function groups of an Atlas cDNA a ⁇ ay separately, and therefore enables the system to be readily generalized to the processing of all types of a ⁇ ays. Meanwhile, A ⁇ ay Analyzer is robust to variation among different users. The quantification of spots largely depends on the nature of the input image, rather than the subjective judgement of the users. While most commercial systems rely on human operators to evaluate the reliability of the results, A ⁇ ay Analyzer automatically identifies the potential e ⁇ or caused by over-expressed spots and their shadow. One of the unique features of this system is to discard unreliable quantification and exclude misleading results in advance.
  • Atlas data and any other a ⁇ ay data should be considered only semi-quantitative. It is always necessary to verify any interesting results of a ⁇ ay experiments with other assays to measure the level of RNA via Northern and/or semi-quantitative RT-PCR methods.
  • the process defined by the computer program presented here addresses some of the problems of unreliability inherent in indiscriminate microa ⁇ ay design.
  • a further solution is to design a microa ⁇ ay in a cluster pattern, in a "divide-and-conquer” fashion, to group the genes according to their intrinsic level of abundance, and then a ⁇ ay them in the template.
  • the "divide-and-conquer” approach also provides versatility, allowing follow-up study of a selected cluster of genes in a focused effort. Emerging reports show the power of the microa ⁇ ay analysis approach to determine gene expression changes in a template of 18,000 to 20,000 genes.
  • the method described herein allows the detection of areas where most changes occur, permitting an in-depth follow-up verification via other molecular methodologies such as Northern blotting analysis and/or semi- quantitative RT-PCR analysis. Furthermore, selected areas can also be used for in-depth analysis, to compare computer automated analysis versus manual densitometric tracing.
  • the computational work involved in any microa ⁇ ay analysis should document multigene changes with maximal reliability and repeatability, and minimal human e ⁇ or. This problem can be dealt with by high-powered mathematical modeling and computer programs, but more importantly it needs to be borne in mind when the microa ⁇ ays are designed.
  • Uninco ⁇ orated 32 P-labeled nucleotides were removed from the labeled cDNA probes by profiling with Chroma Spin spin columns (ClonTech), using gravity elution. Fractions containing the cDNA/R A probes were converted to single stranded cDNA at 68°C with 1 M NaOH, and neutralized with 1 M NaH 2 PO 4 [pH 7.0]. The probes were hybridized overnight at 68° C to prehybridized (68° C for 30 minutes) ClonTech mouse microa ⁇ ays, containing 588 PCR gene products, in the presence of C 0 t-1 DNA and sheared salmon sperm, using ExpressHyb hybridization solution (ClonTech).
  • the membranes were washed X4 with prewarmed 2X SSC, 1% SDS, followed by two additional washes with pre-warmed 0JX SSC, 0.5% SDS. The membranes were then wrapped wet in plastic wrap for autoradiography and phosphorimaging .
  • the autoradiograph film is scanned at 300DPI, 8 bit gray scale, by a typical commercially available flatbed scanner, Saphir Linotype-Hell.
  • the acquired image is enhanced and analyzed by a software package, Array Analyzer, developed in-house.
  • Array Analyzer developed in-house.
  • a deformable template is defined to quantify the gene expressions automatically.
  • Each node in the deformable template iterates according to the gradient descent rule, which minimizes an energy function combining data mismatch energy and template deformation energy.
  • An ideal gene spot is modeled as a circle with a predefined radius; thus the gene expressions can be quantified by integrated intensities.
  • a ⁇ ay Analyzer is also capable of identifying "bleeding" regions and thus alarm the user of potential e ⁇ ors in the quantification. In the later analysis, these regions are carefully checked, and are excluded from the discussion. To compare the gene expression of two samples, a relative fold ratio was defined instead of the conventional fold ratio; the relative fold ratio between samples show that, taking account of human e ⁇ ors in the operation, the pairwise comparison is more reliable in medium and high abundance genes.
  • the experimental results described in the text are based on the average of three repeats on each filter. In normalizing the two samples, Lambda DNA was selected as a negative control, and HPRT, MOD, and G3PDH were selected as positive controls. A linear normalization method is applied.
  • Customizing report 10 min M & A 0.5 min A 0.5 min A
  • Customizing report (graphical N/A N/A 5 min M & A data)
  • the processing time of AtlasImageTM 1.0 is that estimated in the manufacturer's instruction.
  • 'M' refers to manual operation
  • 'A' refers to automatic processing.
  • Operator '*' in measuring the processing time of Array Analyzer means the repeat times of the same procedure. Since A ⁇ ay Analyzer is designed for generic array analysis, each group of genes and housekeeping genes in ClonTech' s cDNA array is treated as an individual array. Thus, the quantification function is applied nine times for each array (6 times for functional groups and 3 times for control genes), and the comparison function is applied six times. Table 2 Comparison of system errors in quantification
  • Example 2 Digoxigenin Enzymatic Detection for Microarray Analysis of E-Box Binding Related Gene Expression.
  • E-box-binding proteins as well as c-Myc-regulating, -interacting and target genes, were chosen from different data bases - GeneAtlas (http://www.citi2.fr/GENATLAS), GeneCards (http://bioinfo.weizmann.ac.il/cards), GenBank (http://www.ncbi.nkm.nih.gov/Web/Genbank) and PubMed (http://www.ncbi.nlm.nih.gov/PubMed). Unigene (http://www.ncbi.nlm.nih.gov/UniGene/index.html) cluster numbers and sequences were used to identify genes and verify their uniqueness.
  • the program parameters were chosen in such a way that the melting temperature of the amplicon should be close to 80°C but not more than 88°C or less than 75°C, the length of the amplicon was to be generally around 450 bp (with a few outlyers between 300 and 700 bp), with primer annealing temperature about 60°C, and average length of primers 23 bp. Sequences of all amplicons have been carefully verified using proprietary software (BLASTN, FASTA), to avoid homology with repetitive elements and other related sequences, and also to distinguish between genes from the same family. A full list of all selected genes is represented in Table 4. DNA. RNA and mRNA isolation
  • RNA and DNA were isolated from approximately 10 HeLa cell cultures and human peripheral lymphocytes isolated from fresh blood aliquots using Trizol reagent (Gibco BRL, Burlington, ON). DNA and RNA concentrations and quality were determined by spectrophotometric and gel electrophoresis analysis in 0.8 or 2% agarose gels, respectively.
  • Poly(A) + RNA was isolated from 150 ⁇ g of total RNA using the Oligotex mRNA kit (Qiagen, Mississauga, ON), according to the manufacturer's instructions. Amplification and purification of probes 10 ⁇ g of total RNA was reverse-transcribed in 40 ⁇ l reaction, using 200
  • Each 50 ⁇ l reaction (10 mM Tris-HCl, pH 8.6, 50 mM KCl, 0.1% Triton X-100, 1.5 mM MgCl 2 , 0.5 mM of each dNTP, 20 pM of each primer, 1.25 U of Taq DNA polymerase (Amersham Pharmacia Biotech, Baie d'Urfe, QC) and 10 ⁇ l of RT reaction or 100 ng of genomic DNA) was thermal-cycled as follows: first cycle at 94°C for 5 min, 35 cycles at 94°C for 45 sec, at 60°C for 1 min and at 72°C for 30 sec, the last cycle at 72°C for 7 min.
  • Probes that could not be amplified in RT-PCR were extracted from genomic DNA, with the condition that the primers were selected in the 3' region of a gene. Size and yield of PCR products were determined by gel electrophoresis in 2% agarose. Then PCR products were purified from solution or agarose gel bands, following preparative agarose gel electrophoresis (if byproducts were determined), using GFX columns (Amersham Pharmacia Biotech, Baie d'Urfe, QC). After purification, concentrations of all probes were estimated by agarose gel electrophoresis, and adjusted to approximately lOO ng/ ⁇ l.
  • membranes were UV i ⁇ adiated at 50 mJ (GS Gene linker, Bio- Rad, Hercules, CA) to immobilize the DNA; then fragments of membranes containing arrays (approximately 1 x 1.5 cm) were cut off, denaturated in boiling water for 5 min, rinsed in 0.1 % SDS for 5 min, and used for prehybridization. After the UV i ⁇ adiation step, membranes can be stored attached to glass slides.
  • 50 mJ GS Gene linker, Bio- Rad, Hercules, CA
  • DIG-labeled cDNA for hybridization
  • GSP gene-specific primers
  • 1 nM of each primer that was used in RT-PCR reactions to prepare probes was mixed in a total volume of 250 ⁇ l.
  • Digoxigenin (DIG)-labeled targets were produced in RT reaction as follows: 1 ⁇ l of GSP, 4 ⁇ g of total RNA, and RNAse-free water in total volume of 14 ⁇ l were heated at 65°C for 15 min to denature the RNA, and then kept at room temperature for 5 min for primer annealing.
  • RNA and 400 ng of oligo(dT) 1 - ⁇ 8 primers were used.
  • the reaction mix containing 8 ⁇ l of 5x first strand buffer supplied by the enzyme's manufacturer, 2 ⁇ l of 10 mM mix of dATP, dCTP and dGTP (final concentration 500 ⁇ M each), 4 ⁇ l of 0.1 M DDT, 0.7 ⁇ l RNAguard, 31 U/ ⁇ l (Amersham Pharmacia Biotech, Baie d'Urfe, QC), 10 ⁇ l of a 2 mM mix of 19:1 dTTP:DIG-l 1-dUTP (Roche, Laval, QC) and 2 ⁇ l (200 U/ ⁇ l) of Moloney murine leukemia virus reverse transcriptase (MMLV RT) (Gibco BRL, Burlington, ON), was added.
  • MMLV RT Moloney murine leukemia virus reverse transcriptase
  • Reaction was carried out at 37°C for 1 h, followed by enzyme degradation at 94°C for 5 min in GeneAmp 9700.
  • Omniscript reverse transcriptase Qiagen, Mississauga, ON
  • Labeling reactions were purified on GFX columns; this step eliminates all labeled products shorter than 100 bp, as well as uninco ⁇ orated nucleotides, primers and protein.
  • hybridization membranes were rinsed (unless mentioned specially) twice with lxSSC, 0.1% SDS for 15 min at room temperature, and then with prewarmed OJxSSC, 0.1% SDS for 15 min at 68°C.
  • membranes were rinsed in more stringent conditions, i.e. twice in 2xSSC, 0.1% SDS at 68°C. for 30 min, and twice in OJxSSC, 0.1% SDS at 68°C for 30 min.
  • membranes were blocked for 1.5 h in 1 % blocking solution under slight agitation, and then treated for 30 min in 10 ml of alkaline phosphatase-conjugated sheep anti-digoxigenin antibody (Roche, Laval, QC), diluted 1 :1000 for colorimetric staining, or 1 :10000 for chemiluminescent detection.
  • membranes were rinsed three times for 15 min in rinsing buffer, equilibrated for 2 min in detection buffer (0.1 M Tris-HCl, 0.15 M NaCl, pH 9.5), and stained with 175 ⁇ g/ml 5-Bromo-4-chloro-3-indolyl-phosphate, toluidine salt (BCIP), and 330 ⁇ g/ml Nitro blue tetrazolium chloride (NBT) in detection buffer.
  • detection buffer 0.1 M Tris-HCl, 0.15 M NaCl, pH 9.5
  • detection buffer 0.1 M Tris-HCl, 0.15 M NaCl, pH 9.5
  • NBT Nitro blue tetrazolium chloride
  • 1 100 dilution of CSPD was applied, and chemiluminescence was detected according to the manufacturer's recommendations (Roche, Laval, QC) using BioMax MR Kodak film.
  • Arrays were scanned on an Olympus microscope equipped with a Multiscan-4 System (Applied Scientific Instrumentation, Eugene, OR) and a color CCD Sony 950 camera. Data acquisition and montage of different fields of view into one file were accomplished with the help of the Northern Eclipse Imaging System (EMPIX Imaging, Missisauga, ON). Quantitative measurements of intensity of enzymatic reaction at each dot, background subtraction, normalization to housekeeping genes, and comparison of paired hybridizations were all performed with an in-house software program. Results
  • This set of genes contains 38 E- box binding genes, together with the Myc (c-, N-, LI and L2) family, 5 c-Myc regulating factors (ZFP161, nm23-H2S, MBP-1, RBMS 1 and RBMS2), 5 c- Myc interacting genes (YY1, TFII-1, PAM, MM-1 and alpha-tubulin), and 4 c- Myc target genes (prothymosin alpha, MRDB, ODCl , and cdc25A).
  • Positive controls include 9 housekeeping genes with different levels of expression (UBC, beta-actin, GADPH, HPRT1, phospholipase 2, HLA-C, PRS9, aldolase C, and RPL13A), and also HeLa genomic DNA. Lambda DNA and 2xSSC (2x standard salt solution), which was used as solvent for all probes, were selected as negative controls.
  • Primers for all genes were selected with the help of Primer3 software, provided that they co ⁇ esponded to the same conditions for PCR reaction, and produced products of similar melting temperature. Most products were produced from HeLa or lymphocyte cDNA. In case PCR amplification failed from cDNA, primers were selected in the 3' region of these genes, and amplicons were produced from HeLa genomic DNA. The average annealing temperature of primers was 60J ⁇ 0.9°C, which allowed all PCR reactions to be in the 96-well format. Sizes and melting temperatures of products, and annealing temperatures of primers, are represented in Table 4. The average size of PCR products for a ⁇ aying, and their melting temperature, were 441 ⁇ 58 bp and 80 ⁇ 3°C, respectively. Selecting these parameters allowed hybridization and post-hybridization rinsing in stringent conditions, decreasing drastically the possibility of cross-hybridization and background level.
  • Scrupulous selection of primers may be used to distinguish in some cases between very close members of gene families (for example, USFl and 2, ID2, 3 and 4, members of the Myc family, and so on), or between two different transcripts of c-Myc.
  • genes for example, USFl and 2, ID2, 3 and 4, members of the Myc family, and so on
  • c-Myc there are several different transcription forms of c-Myc, transcribed from different promoters, with varying regulation properties (Bodescot and Brison Gene 174, 115-120 (1996)).
  • Selecting primers in the 1 st exon and the 2 nd -3 rd exons allowed discrimination between full-size and truncated forms of c-Myc.
  • Conditions influencing hybridization Several parameters which probably influence the results of hybridization with cDNA microarrays printed on nylon membranes were carefully tested.
  • MMLV Moloney murine leukemia virus
  • OmniScript OmniScript
  • DIG-labeled probes can be stored and reused several times. Reusing hybridization mixes 2-3 times, after storing at - 20° C for several months, gave results quite concordant with the original ones.
  • the arrays were scanned at a resolution of 3600 dpi, and results were compared with results of microscope scanning. In general, variability between replicated dots was higher in the case of the scanner, and linearity may be influenced by the scanner's software.
  • the scanner can be used for initial evaluation of hybridization results, especially when chemilumenescence detection is implemented.
  • HeLa cells HeLa cells (Figure 8a) and normal human lymphocytes (Figure 8b).
  • lymphocytes the most prominent alteration consisted of more than 2-fold up- regulation of E-box-related genes TCF4, MAD4 and Aldolase C.
  • down-regulation of c-Myc-regulating genes MBP1 and Nm23- H2S and small down-regulation of c-Myc and up-regulation of N-Myc, were registered in lymphocytes in comparison with HeLa cells.
  • Expression of some c-Myc interacting and target genes was down- (MM- 1 , ODC 1 ) or up-regulated (PAM, MrDb) in lymphocytes.
  • genes in the E-box microarray are all in the same category of abundance (intermediate or low abundant). Excluding highly abundant genes eliminates the problem of merging of strong signals. Merged signals in some circumstances substantially complicate the process of scanning, and create unreliable results during the data acquisition step.
  • Other advantages of using the enzymatic labeling approach, superceding both the radioactive and fluorescent probe approaches, are the time-saving and repeatability aspects.
  • this process from start to finish including the steps needed for labeling cDNA, hybridization, rinsing, incubation with the alkaline phosphatase conjugated anti-digoxigenin antibody, staining for revelation of bound alkaline phosphatase, and scanning for data acquisition, requires a maximum of two days. This is quite a time saving, compared with the up to eight days' exposure required for radioactive 32 P or 33 P labeled probes.
  • the advantage of the enzyme-labeled probes over fluorescent- labeled probes is the cost savings in the data evaluation step, where the method requires an inexpensive routine upright microscope, whereas the fluorescent- labeled probes require the use of an expensive laser detection system or a confocal microscope set-up. This, plus the notorious fact that fluorescence can be easily bleached after the scanning process, makes our enzymatic approach far superior, due to the ability to scan an array repeatedly with an inexpensive microscope, without losing the original signal intensity.

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Abstract

L'invention concerne une méthode mise au point pour la détection d'expression ou d'hybridation de gènes dans des microéchantillons, par exemple dans des bibliothèques combinatoires dans lesquelles les quantités sont minimes et les emplacements très rapprochés, pouvant provoquer des situations indésirables dans lesquelles une réaction intense peut déborder sur les emplacements adjacents et, par conséquent, fausser l'exactitude de la réaction des sites voisins. On utilise dans cette bioanalyse un test d'activité enzymatique de digoxigénine pour la détection. L'invention concerne également une méthode mise au point dans le but d'améliorer la fiabilité de l'analyse de l'expression d'ADN dans des microéchantillons, par analyse informatique destinée à normaliser les emplacements. Ce procédé fait appel à des techniques basées sur des modèles adaptables permettant de quantifier automatiquement des données d'échantillons à grande échelle, en dépit d'une possible distorsion spatiale des échantillons. Chaque noeud du modèle adaptable représente l'emplacement d'un gène, et se répète selon la règle de descente de gradient, minimisant une fonction énergie combinant l'énergie de désadaptation des données et l'énergie d'adaptation du modèle.
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