JP2008518587A - Detection and quantification of subcellular components - Google Patents

Abstract

A method for the detection and quantification of multiple and unique fluorescent signals from a cell sample is provided.
The method combines immunohistochemistry and fluorescent labeling in situ hybridization techniques. The method is useful for identifying specific subcellular components of cells such as chromosomes and proteins.
[Selection] Figure 1

Description

  The present invention relates to a method for detecting and quantifying subcellular (subcellular) components of cells using immunostaining and fluorescence-labeled in situ hybridization, and in particular, between immunostaining and in situ hybridization. The combination allows for the detection of subcellular components in cells such as fetal hemoglobin in maternal blood samples. The method is useful for prenatal and / or preimplantation diagnosis of genetic diseases.

There are many ways to stain and analyze cells and their components. The ability to apply many such methods simultaneously has been of particular interest and has been of particular interest for detailed study of samples in the diagnosis of genetic diseases. However, the combination of the prior art methods has not provided any advantage over the single method applied alone. The ability to simultaneously apply immunostaining and fluorescence in situ hybridization (FISH) analysis to biological samples of particular interest, for example, can provide quantitative raindrop data for specific protein and nucleic acid components of the same cell at the same time, for example Give sex. However, conventional or standard immunostaining and FISH protocols are mutually exclusive. The harsh conditions required for satisfactory FISH analysis are generally incompatible with the retention of important identifiable antigens or stable antibodies based on appropriate detection signals for cellular components. Therefore, there is a need to develop better methods in genetic disease diagnosis using genetic objects in visualization and quantification methods.
U.S. Patent No. 5,225,326; U.S. Patent Application No. 07 / 668,751; PCT WO94 / 02646; U.S. Patent Application No. 08 / 132,804. None

  A single continuous method of preparing biological samples for immunostaining and fluorescent in situ hybridization (FISH) analysis is provided.

  In one embodiment, reacting the cell sample with at least one antibody, causing each antibody to bind to a particular cellular component and generate a unique fluorescent signal; using one or more nucleic acid probes Processing the cells by hybridization in situ, each nucleic acid probe hybridizes with a target nucleic acid sequence to generate a unique fluorescent signal; generates one or more images of the reaction and processed cell sample And a method for identifying a multicellular component in a cell, comprising: detecting and analyzing the fluorescent signal of the image corresponding to both the antibody and the nucleic acid probe.

  In the embodiments described herein, methods are provided for detecting and quantifying subcellular components of cells in a cell sample. The method can be applied to a variety of biological samples, for example, a blood sample, particularly a variety of biological samples containing cells for genetic disease diagnosis in maternal blood.

  In one embodiment, the method comprises a fluorescence signal generated from one or more antibodies from immunostaining, the signal being specific to each antibody used and subsequent to a cell sample for fluorescence in situ hybridization (FISH) analysis. The process of generating a continuous In one embodiment, the methods consist of selecting those that support the necessary or intrinsic fluorescence for the FISH probe utilized, which includes both fluorescent immunohistochemistry and FISH signals from cell samples. Allows individual visualization and quantification of each and every fluorescent signal generated.

  In one embodiment, a method of operating a computer system that detects whether a genetic condition defined by at least one target nucleic acid is present in a sample is provided. The method involves the use of digitized images of the probe hybridized to the probe and sample, along with an analysis of the object to be counted and statistical predictions to detect whether a genetic condition exists. The count includes, for example, a count of the number of times a genetic abnormality is detected and a comparison with a statistical prediction of the abnormality in a particular tissue type, cell type or sample. The count includes a count of the number of times that a genetic abnormality occurs and a comparison of the number of times that a cell type occurs in the same sample with the number of times that a normal nucleic acid occurs in the same sample. The counting includes counting the number of times that one or more genetic abnormalities occur in a single cell. The computer system is used for identifying cell types, counting cells, examining cell morphology, etc., and can also be used to compare and correlate this information with a count of genetic abnormalities.

  In one embodiment, a method is provided for operating a computer system that detects whether a genetic condition defined by at least one target nucleic acid is present in a fixed sample. The method comprises a digitized image, preferably a color image of a fixed sample, a fluorescence in situ hybridization under conditions that specifically hybridize a labeled probe with fluorescence to the target nucleic acid and fluorescence to detect the first object of interest. Receiving a digitized image that has been subjected to immunostaining; processing the image on a first object, eg, a computer, to separate cellular components; interest associated with a target nucleic acid within a predetermined predetermined characteristic; Determining a first subject for the indicated probe; and analyzing the count of the first subject, eg, cells, for statistical predictions to detect whether a genetic condition exists. This method is applicable to many genetic conditions, including whether the genetic condition is human trisomy 21 or not. Further, it can be appreciated that the statistical prediction is based on, for example, tissue type. A calculator can be used to identify the tissue type of the cell being examined, but the tissue type is also known.

  In one embodiment, receiving the digitized image further includes creating red, green, and blue pixels that indicate red, green, and blue intensities at respective pixel locations in the received color image. In one embodiment, the processing step further includes manually selecting a plurality of pixels in the background; determining a range of color intensity values corresponding to a portion of the background; and a color intensity value within the determined range Identifying as a background region of an image having. In one embodiment, prior to the measurement step, there is a computer process for filtering the color image to weaken the dark pixel color intensity values in the color image and to darken the weak pixel color intensity values in the color image. The filtering step further passes the color image through a hole filling filter; filters the other color image through an erosion filter; and performs another operation on the loaded filling color image to delineate the area around the contour. Defining; selecting a pixel within the contour by performing a logical NOT operation; and performing a logical AND operation between the selected pixel and the filled color image.

  In certain embodiments, the genetic condition is further defined by the ratio of the target nucleic acid and the second nucleic acid. Accordingly, the method further comprises identifying a second subject having a particular predetermined characteristic associated with the second nucleic acid; counting the identified second subject, wherein the first Identification of the subject count includes finding a first subject / second subject count ratio. In some embodiments, the target nucleic acid defines a dominant trait and the second nucleic acid defines a corresponding inferior trait. The method in those embodiments comprises the steps of having a dominant trait, having a dominant trait, or having a dominant trait and having a dominant trait depending on the value of the ratio. . When the target nucleic acid is a rearrangement of a second nucleic acid, the method further comprises selecting a probe that hybridizes with the rearranged and non-rearranged nucleic acid. Finally, the method includes a step showing a stringent level of genetic conditions related to the ratio found.

  According to one embodiment of the present invention, in a sample containing cells that are being labeled with target-specific fluorescence, a sequence of computer instructions is instructed to instruct the computer system to count the occurrence of the target substance. A computer software product comprising a computer readable storage medium is provided, the instructions receiving a digitized color image of the fluorescently labeled sample; obtaining a color image of the fluorescently labeled sample Separating the object of interest from the background in the color image; measuring the parameters of the object of interest to enumerate objects having specific characteristics; and The enumeration is analyzed to direct the process of determining genetic abnormalities. The instruction can perform all the changes related to the above method.

  According to another embodiment of the present invention, an apparatus for analyzing an image of a sample containing cells labeled with target-specific fluorescence is provided, the apparatus comprising a computer system executed by image processing software; and Receiving a digitized color image of the fluorescently labeled sample; obtaining a color image of the fluorescently labeled sample; separating the object of interest from the background in the color image; Fixing an image processing instruction sequence comprising: measuring parameters of an object of interest to enumerate the objects having; and analyzing the enumeration of the objects with respect to a statistically expected enumeration to determine genetic anomalies Storage medium. Again, the instruction can perform all the changes related to the above method.

  In yet another embodiment, a computer-implemented method for processing image data of a bodily fluid or tissue sample is provided. The method creates a subset of a first image data set representing an image of a body fluid or tissue sample taken at a first magnification, the subset being a second representing an image of a candidate probe taken at a second magnification. Storing in the computer memory a subset of the second data set indicative of a subset of the second data set, indicating candidate probes containing rare cells that form a subset of the image data set, a target nucleic acid Measuring the size and color parameters of an object of interest to identify an object having a specific predetermined characteristic associated with the process, counting the object identified in the measurement process, and statistically counting the object Analysis of the statistical prediction count to detect whether genetic anomalies are present.

  In one embodiment, the measuring step includes filtering the color image in a computer to brighten the color intensity value of dark pixels in the color image and darkening the color intensity value of light pixels in the color image. Filtering passes the color image through a hole-filling filter; passes the filled color image through an erosion filter; performs another operation on the eroded and filled color image to define a perimeter region; logical NOT operation Selecting a pixel within the contour by performing a logical AND operation between the selected pixel and the filled color image.

  In one embodiment, a subset of the first image data set observes a monolayer optical field of cells from a body fluid or tissue sample using a computerized microscope vision system that detects signals indicative of the presence of rare cells. You can make it. In one embodiment, the method can further create an image file of red, green, and blue pixels that indicates the intensity of red, green, and blue at each pixel location in the received color image. In accordance with some aspects of the present invention, the process further manually selects a plurality of pixels in the background; determines a color intensity value range corresponding to the background; and determines a color intensity value within the determined range. Comprising identifying as a background region of an image having. In one embodiment, the signal can be measured to determine whether it is a significant signal level. The first and / or second image data subset can be converted into a suitable display by computer control and processing as described herein. The image data is, for example, converted from a red, green, blue (RGB) signal to a Hue Luminescence Saturation (HLS) signal, which uses filters and / or masks to distinguish cells that meet preselected criteria, Unfilled cells are eliminated, thus identifying, for example, rare cells.

  In another embodiment of the present invention, a method is provided for conducting a laboratory service, the method comprising receiving a body fluid or tissue sample, creating a smear of the body fluid or tissue sample, and subjecting the object in the smear to fluorescent staining. Immunostaining process, treating the smear with a fluorescent probe designed to hybridize with a nucleic acid sequence meaningful for diagnosis, immunological staining and hybridization meaningful for diagnosis based on the fluorescent signal generated by the nucleic acid probe And operating the computerized microscope so that the software program automatically identifies objects of interest having the defined nucleic acid sequence.

  In yet another embodiment of the present invention, a computer readable memory that fixes a series of instructions when performed by the computer direct performance of the process of detecting an object of interest having a diagnostic meaningful nucleic acid sequence A computer software product including the media is provided. The steps include creating a subset of a first image data set representing an image of a body fluid or tissue sample taken at a first magnification, the subset being cells or rare cells (less than 1 in 10,000 cells) Creating a subset of a second image dataset representing an image of a candidate probe taken at a second magnification, showing candidate probes containing objects of interest such as: showing candidate probes containing rare cells Storing the second subset of the data set in computer memory, directed to a nucleic acid sequence of diagnostic interest associated with the subject of interest to identify a subject having specific predetermined characteristics associated with the target nucleic acid. Measuring the fluorescence associated with the fluorescent nucleic acid probe, counting the objects identified in the measurement process, and Cement was analyzed counting the target with respect to the statistical expected count comprising the step of detecting whether there is a genetic abnormality.

  In yet another embodiment of the invention, a method of preparing a cell sample for a diagnostic method is provided. The cell sample is obtained and fixed as a monolayer on the substrate. The cell sample contains rare cells present at 1 in 10,000 or less (ie, 0.01% or less). The monolayer is immunostained with fluorescent immunostaining directed at rare cells and treated with a fluorescent probe directed at a nucleic acid sequence associated with a disease state or abnormality. An optical field covering at least a portion of the cell sample is observed using a computerized microscope vision system for the presence of rare cells and a fluorescent signal indicative of the nucleic acid sequence of interest. Each signal is detected for a diagnostic operation and the coordinates at which the signal is detected are identified. Diagnosis is based on the count of rare cells that show nucleic acid sequences associated with disease states or abnormalities. The provisional diagnosis is made automatically by the computerized microscope vision system. In one embodiment, the rare cells are present in 0.01% or less cells. In another embodiment, rare cells are present at 0.0001%, 0.00001% or even 0.000001% or less.

  In yet another embodiment of the invention, the rare cells detected and diagnosed are cancer cells found in cells or tissues from animals or patients. The sample can be blood or other body fluid containing a cell or tissue biopsy. As an illustration of this embodiment, the cancer cell markers described in Section 5, such as GM4 protein, telomerase protein or nucleic acid, and p53 protein or nucleic acid, as determined by the particular application of the present invention Alternatively, it is used to generate the second signal.

  In one embodiment of the invention, the method detects the frequency of not less than 80% when a rare cell type is present in the sample. In other embodiments, the detection frequency is not less than 85%, 90%, 95% and 99%.

  According to one embodiment of the present invention, a method of preparing a blood sample is provided for a diagnostic procedure, the method of preparing a smear of a non-concentrated maternal blood sample containing a naturally occurring concentration of fetal cells; Treating the smear with a fluorescent nucleic acid probe directed to a nucleic acid sequence of; observing an optical field covering a portion of the smear using a computerized microscope vision system for a fluorescent signal indicative of the presence of fetal cells; and the nucleic acid Identifying a fetal cell having a nucleic acid sequence of interest by a fluorescent signal from the probe.

  In one embodiment, the signal is further processed to indicate morphological measurements of rare cells. In another embodiment, the cells are treated with a label that highlights the differences from other cells of the rare cell. In this embodiment, the signal can be, for example, from a label that selectively binds to rare cells. In another embodiment, the diagnostic method comprises the steps of moving to the identified coordinates and expanding the optical field of view to an isolated rare cell image.

  In certain embodiments, the optical field traverses an array of cell portions covering substantially all of the cells. This can be accomplished, for example, by moving cells on the substrate under the control of the computerized microscope vision system relative to the lens of the computerized microscope vision system. In another embodiment, the coordinates from which the first signal was obtained are identified, and then the rare cells at those coordinates are contacted after the coordinates are identified.

  In some embodiments, diagnostic signals can be used to identify rare cells. In other embodiments, the position signal can be used to identify a rare cell, and the diagnostic signal is obtained after the cell is placed.

  In one embodiment, rare cells are present in the sample at no more than 1 in 10,000 cells (ie, no more than 0.01% cells). In other embodiments, the rare cells are present at 0.001%, 0.00001% or 0.000001% or less. In certain important embodiments, the rare cells are fetal cells in a cell sample from maternal blood. The sample desirably contains only naturally occurring concentrations of fetal cells (which can be 0.001%, 0.00001% or 0.000001% or 0.0000001% or less).

  In any of the above embodiments, the cells can be prepared, for example, on a microscope slide, or the substrate can be calibrated to the substrate so that the coordinates of the rare cells identified in one step can be returned later in another step. Has a coordinate system that can be turned on. Similarly, the substrate in the embodiment has a length that is 10 times the width, and the substrate is elongated in one direction. Its length can be 20 times the width. The substrate can be a flexible film, and in one embodiment is a long flexible film that carries a relatively large volume of cells provided from a relatively large volume of smeared maternal blood. In any of the above embodiments, the fluorescence signal from the immunostaining and the fluorescence signal from the nucleic acid probe can be selected so that they do not interfere with each other when both are present.

  According to embodiments, such methods can use non-rich or enriched samples, such as maternal blood containing naturally occurring fetal cells.

  The present invention may be further understood by reading the following detailed description of the invention and various examples with reference to the accompanying drawings. The detailed description describes the invention with respect to fetal cells, rare cell types, and blood as body fluids or tissue samples, but the present invention has adhered to all cell types and body fluids or tissue samples, especially as a monolayer of cells on a substrate One skilled in the art will appreciate that it can be applied to sample-based diagnostics.

  Body fluids and tissue samples within the scope of the present invention include, but are not limited to, blood, tissue biopsy, spinal fluid, spinal cord fluid, urine, alveolar fluid, and the like. For those tissue samples, the cells do not naturally exist in a monolayer, so the cells are dissociated by standard techniques known to those skilled in the art. These techniques include, but are not limited to, trypsin, collagenase or disperse treatment of tissue.

  In one embodiment, the present invention is used for fetal cell detection and diagnosis. Fluorescent immunostaining is used in the exemplary embodiment to show cell identity. For example, immunostaining is hemoglobin ε-linked, ie, a fluorescent dye conjugated to an antibody, eg, against embryonic hemoglobin. In addition, the identity of each cell is determined using a measure of the similarity of each cell to the characteristic morphology of nucleated red blood cells found using a cell recognition algorithm.

  Diagnosis can be based on nucleic acid probe signals (or a combination of immunostaining and nucleic acid probe signals).

  In an exemplary embodiment, the FISH consists of crossing a rare cell type, eg, fetal cell denatured test DNA, with a denatured dioxygenin (DIG) -labeled genomic probe. The sample containing the test DNA is washed and bound to anti-DIG antibody bound to the one carrying fluorescence. Optionally, a second layer of phosphor (eg, FITC) is added by low temperature standing with a phosphor-conjugated anti-Fab antibody. In one embodiment, FISH consists of crossing denatured cells of rare cells with a fluorescently labeled probe consisting of DNA that is cognate with a specific target DNA that is directly labeled with a specific fluorophore.

  Automated sample analysis is performed by an apparatus and method that distinguishes the optical field object of interest from other objects and backgrounding. An example of an automated system is disclosed in US Pat. No. 5,352,613 issued Oct. 4, 1994. In addition, once an object has been identified, the color, i.e. the combination of red, green and blue components for the pixel consisting of the object of interest or other parameters for that object can be measured and stored.

  Automated sample analysis and diagnosis of genetic conditions proceeds as follows: (i) Digitized color of a fixed sample that received fluorescence in situ hybridization under conditions that hybridize the fluorescently labeled probe to the target nucleic acid. Receiving the image; (ii) processing the color image in a computer to separate the object of interest from the background in the color image; (iii) measuring the parameters of the object of interest and identifying the object having certain characteristics (Iv) count the identified objects; and (v) analyze the object counts with respect to statistical prediction counts to determine genetic conditions. The method is useful for diagnosing genetic conditions associated with abnormalities in chromosome number and / or sequence. Thus, for example, the present invention can be used to detect chromosomal rearrangements by using a labeled probe that detects a rearranged chromosomal segment and the chromosome and combination in which the segment is translocated. More generally, in addition to trisomy, genetic amplification and rearrangements including translocations, deletions and insertions use methods that embody aspects of the invention for appropriately selected fluorescent probes. Can be detected.

  As used herein, the term “genetic abnormality” refers to the number and / or sequence of one or more chromosomes with respect to the corresponding number and / or sequence of chromosomes obtained from a healthy person, ie, an individual having normal chromosomal complement. Means an abnormality in Genetic abnormalities include, for example, chromosomal additions, deletions, amplifications, translocations and rearrangements that are typically characterized by as few as about 15 base pairs and as many nucleotide sequences as the prechromosome. Genetic abnormalities also include point mutations.

  The method preferably determines one or more genetic abnormalities in a fixed sample treated in a manner that preserves the structural integrity of the contained cellular and subcellular components, ie, a fixed sample attached to a solid support. Useful to do. As a method for fixing a sample containing cells to a solid support, for example, a glass slide is well known to those skilled in the art.

  The sample contains at least one target nucleic acid, and the distribution is indicative of a genetic abnormality. The term “distribution” means the presence, absence, relative amount and / or relative location of a target nucleic acid in one or more nucleic acids (eg, chromosomes) known to contain the target nucleic acid. In one embodiment, the target nucleic acid exhibits trisomy 21 and thus the method is useful for diagnosis of Down syndrome. In one embodiment, the sample intended for Down syndrome analysis is obtained from maternal peripheral blood. More particularly, the cells are isolated from peripheral blood according to standard methods, and the cells are attached to a solid support according to standard methods for detection of target nucleic acids (see, eg, Examples).

  Fluorescence in situ hybridization means a nucleic acid hybridization method that uses a fluorescently labeled probe to specifically hybridize to a target nucleic acid and thereby facilitate visualization of the nucleic acid. Such methods are well known to those skilled in the art and are incorporated, for example, in US Patent No. 5,225,326; US Patent Application No. 07 / 668,75. In general, in situ hybridization is useful, for example, in determining the distribution of nucleic acids in a sample containing nucleic acids such as those contained in tissues at the single cell level. Such techniques have been used for karyotyping and detection of the presence, absence and / or sequence of specific genes contained in cells. However, for karyotypes, the cells in the sample typically grow to metaphase (or interphase) before attaching the cells to the solid support for the performance of the in situ hybridization reaction. Get "diffusion".

Briefly, in situ hybridization preserves the structural integrity of the components contained therein by fixing the sample to a solid support and contacting the sample with a medium containing at least a precipitant and / or crosslinker. To do. Illustrative agents useful for fixing samples are described in the examples. Alternatively, fixatives are well known to those skilled in the art and are described, for example, in said patent.
In situ hybridization is carried out by denaturing the target nucleic acid so that it can be hybridized to the charged probe contained in the hybridization solution. The fixed sample is contacted with the denaturing agent and the hybridization solution simultaneously or sequentially. Thus, in one embodiment, the fixed sample is contacted with a hybridization solution containing a denaturant and at least one oligonucleotide probe. The probe has a nucleotide sequence that is at least substantially complementary to the nucleotide sequence of the target nucleic acid. The hybridization solution optionally contains one or more hybridization stabilizers, buffers and selective pore formers. Optimization of hybridization conditions to achieve hybridization of a specific probe to a specific target spread is well known to those skilled in the art.

  With respect to a probe, the term “substantially enriched” means an enrichment sufficient to accomplish the present invention, ie, allows the nucleic acid target to specifically cross the probe, but is used to practice the present invention. The amount of loading that does not allow the probe to associate with the non-target nucleic acid sequence under conditions. Such conditions are known to those skilled in the art of in situ hybridization.

  Genetic abnormalities for which the present invention is useful include those in which the number and / or sequence of one or more chromosomes is abnormal with respect to a chromosome obtained from an individual having normal chromosomal complement. Exemplary chromosomes detected by the present invention include the human X chromosome, Y chromosome and chromosomes 13, 18 and 21. For example, the nucleic acid can be an entire chromosome, eg, chromosome 21, where the presence of three copies of the chromosome (the “distribution” of the target nucleic acid) indicates a genetic abnormality, Down's syndrome. Exemplary probes (eg, chromosomes) useful for specifically crossing to a target nucleic acid can be placed on a chromosome that is more than a genetic diagnosis. For example, Harrions's Principles of Internal Medicine, 12th edition, ed. Wilson et al. , MaGraw Hill, N .; Y. , N.M. Y. (1991).

  One embodiment of the present invention, for example, detects Down's syndrome by detecting trisomy 21 (discussed below) in fetal cells present in maternal peripheral blood, fusion device fluid, chorionic biliary, amniotic fluid, and embryonic tissue. Directed to prenatal diagnosis. However, the method of the present invention is not limited to the analysis of fetal cells. Thus, for example, the cell containing the target nucleic acid is a eukaryotic cell (eg, a human cell including cells obtained from blood, skin, lung and cells containing normal and tumor sources); prokaryotic cells (eg, bacteria 9) And plant cells. According to one embodiment, the present invention is used to distinguish different virus strains. According to this embodiment, the target nucleic acid is in a non-enveloped virus or an enveloped virus (having a non-enveloped membrane such as a lipid protein membrane) (see above). Exemplary viruses that can be detected by the present invention include human immunodeficiency virus, hepatitis virus and herpes virus.

  Oligonucleotide probes are labeled with a fluorophore (fluorescent “tag” or “label”) in a standard manner. The fluorophore can be attached directly to the probe (ie, covalently) or indirectly (eg, biotin can be attached to the probe and the fluorophore can be covalently attached to avidin; biotin-labeled probes and fluorescence The body-labeled avidin can form a complex that can function as a phosphor-labeled probe in the method of the present invention).

  Phosphors that can be used in accordance with the method and apparatus of the present invention are well known to those skilled in the art. This includes 4,6-diamino-2-phenylindole (DIPA), fluorescein isothiocyanate (FITC), and rhodamine. See, for example, the Examples. See also U.S. Pat. No. 4,373,932 issued to Gribnau et al. On Feb. 15, 1983, the contents of which are incorporated by reference into a list of exemplary phosphors that can be used in accordance with the method of the present invention. The presence of phosphors with different excitation and emission spectra makes simultaneous visualization better than one target nucleic acid in a single fixed sample.

  The distribution of the target nucleic acid indicates a genetic abnormality. Detected genetic abnormalities include mutations, deletions, additions, growths, translocations and rearrangements. For example, a deletion can be identified by detecting the absence of a fluorescent signal in the optical field. To detect genetic sequence deletions, a population of probes is prepared that is supplemented with a target nucleic acid that is present in normal cells but not in abnormal cells. If the probe hybridizes to nucleic acid in a fixed sample, the sequence is detected and the cell is called normal with respect to that sequence. However, if the probe does not cross the fixed sample, no signal is detected and the cell is called abnormal with respect to its sequence. Appropriate controls according to standard practices known to those skilled in the art are included in the in situ hybridization reaction.

  Genetic abnormalities associated with the addition of the target nucleic acid, for example, to detect the addition of a genetic sequence (trisomy) that can be identified by detecting the binding of a fluorophore labeled probe to a chromosomal polynucleotide repeat segment. First, a population of probes supplemented with the target nucleic acid is prepared. Hybridization of labeled probe to fixed cells containing three copies of chromosome 21 is shown as discussed in the Examples.

  Proliferation, mutation, translocation, and rearrangement is performed by selecting a probe that can specifically bind to a breakpoint in a nucleic acid target between a normal sequence and a sequence suspected of proliferation, mutation, translocation, and rearrangement. Identified by doing. Thus, the fluorescent signal results in the target nucleic acid, which is then used to indicate the presence or absence of a genetic abnormality in the sample being tested.

The probe is complementary to the nucleic acid sequence that crosses the breakpoint in normal individual DNA, but not in abnormal individual DNA. Probes for detecting genetic abnormalities are well known to those skilled in the art.

  An innovative feature of the computer control system embodiment utilized is an array of two or more objectives having identical optical properties. Since the lenses are arranged in rows and each of them has its own z-axis movement mechanism, they can be focused separately.

Each objective lens is connected to its own CCD camera. Each camera is connected to an image acquisition device. For each required optical field, the computer records its physical position on the microscope sample. This is accomplished through the use of a computer controlled xy mechanical stage. The image provided by the camera is digitized and stored in the host computer memory.

  The computer keeps track of the features of the objective-array in use and the position of the motorized stage. The stored features of each image can be used to match the image to the exact position in the virtual patchwork, or “assembled” image in the computer memory.

  The host computer system is driven by a software system that controls all mechanical elements of the system via appropriate drive devices. The software consists of an image composition algorithm that constructs a digitized image in computer memory and supplies the composition image to a further algorithm. Image decomposition, synthesis, and detection through specific image processing specific features for specific samples.

  In one embodiment, both immunostaining and probe signal are detected simultaneously. Those signals are processed separately (with separately processed immunostaining and signals from different chromosomes for the probe). In one embodiment, the simultaneous presence of both immunostaining and probe signals is used for diagnostic purposes, even in a single signal resulting from a coordinate signal or the interaction of two components (eg, signal hunting by a partner signal). The

  In general, the materials and techniques used to generate the immunostaining signal should not conflict with the materials and techniques used to generate the second probe, and vice versa. The immunostaining or probe must not damage or alter the characteristics of the cells sought to be measured to an unacceptable compromise. Finally, other desirable or necessary processing of cells should generally not interfere with the materials and techniques used to generate the first and second signals to an extent that compromises are unacceptable for diagnosis.

  In one embodiment of the invention, when no rare cell type is detected, the method of the invention detects the rare cell type with a frequency of 80% or less. In other embodiments, the frequency is no more than 85%, 90%, 95%, and 99%.

  A single chromosome for allelic tagging of an individual sets an upper bound on the number of mutations that can be tested simultaneously, but is used for the number of allele-specific mutations that can be tagged and detected simultaneously using combinatorial chemistry. Chromosomal abnormalities within the scope of the present invention include, but are not limited to, trisomy 21, 18, 13 and sex chromosomal abnormalities such as XXX, XXY, XYY. With the use of combinatorial chemistry, the methods of the invention can be used to diagnose a large number of rearrangements, including genetic irregularities and translocations observed in cancer. Mendelian irregularities within the scope of the present invention include, but are not limited to, cystic fibrosis, hemochromatosis high lipid plasma, Marfan syndrome and other connective tissue genetic irregularities, hemoglobin abnormalities, Includes other genetic irregularities with known sax syndrome or mutations. The use of combinatorial chemical dyes allows simultaneous tagging and detection of multiple alleles, and thus the presence of common disordered predispositions such as molecular markers specific for asthma and / or cancer, such as prostate, breast, Allows determination of colon, lung and leukemia cancers.

  One application of the present invention is in the field of cancer. Certain types of cancer cells are often morphologically recognizable against a background of non-cancerous cells. Therefore, the morphology of the cancer cell can be used as the first signal. Heat shock protein is also a marker expressed in most peripheral cancers. Labeled antibodies, such as fluorescently tagged antibodies specific for heat shock proteins, can be used to generate the first signal. Similarly, there is an antigen specific for a specific tissue such as a specific cancer or prostate, and an antibody specific for a cancer or tissue antigen such as prostate specific can be used to generate a first signal in a cancer cell or the like.

  Thus, rare cells in the context of other cells can be identified and confirmed according to the present invention. The confirmation includes determining the risk of cancer by confirming the diagnosis of the presence of cancer cells, determining the type of cancer, the risk of cancer, etc., and determining the presence of markers of genetic changes.

  Genetic change markers allow assessment of cancer risk. They provide information on exposure to carcinogens. They can detect early changes due to exposure to carcinogens, and identify individuals with a particularly high risk of cancer growth. Such markers include LOH of chromosome 9 in bladder cancer, and chromosome 1p deletion and gain / loss of chromosomes 7, 17 and 8 detected in colorectal carcinogenesis.

The development of lung cancer requires multiple genetic changes. Oncogene activation includes the K-ras and myc genes. Inactivation of tumor suppressor genes includes Rb, p53 and CDKN2. The identification of specific genes that are changing is useful for the initial detection of cells destined to become malignant and allows for the identification of potential targets for drug and gene-based therapies.
In determining trisomy, the present invention contemplates determining the presence of trisomy in a single cell and / or determining the frequency of trisomy single cells in a population of cells. The presence of trisomy and the risk of conditions related to trisomy is then assessed.

  In order to obtain relevant diagnostic information, it is important to be able to compare with other information that the signal can count (e.g., other signal counts for expected signal frequencies such as different tissue types, statistical information).

  The invention also relates to a pair of signals, one identifying a target rare cell such as a fetal cell, and the other useful for assessing the state of a cell such as a genetically defective fetal cell. Have been described. It should be understood that according to certain embodiments, only a single cell needs to be detected. For example, if the fetal cell has the Y chromosome and the diagnosis is abnormal on the Y chromosome, the signal identifying the genetic abnormality can be the same as the signal identifying the fetal cell. As another example, a single cell can be employed in an environment where the observed trait is an inferior trait. A pair of signals can be used to detect the presence of a condition diagnosed by the presence of two alleles or two or more in different genes. In these circumstances, a pair of signals (or even several signals) can identify a phenotype and cells having that phenotype. Such embodiments will be apparent to those skilled in the art.

Exemplary Embodiment
Example 1
The next method uses immunostaining techniques to analyze the blood sample for the presence of cells containing fetal hemoglobin and determine the presence of X and Y chromosomes in the same cells by fluorescent labeling in situ hybridization.

The cells are deposited on a solid support suitable for microscopic analysis and fixed with methanol. Following air drying, the cells are rinsed in phosphate buffered saline and then fixed with 2% formaldehyde in phosphate buffered saline. The cells are then washed successively in phosphate buffered saline and further washed with pH 7.6 Tris buffered saline containing Tween20. After removal of excess liquid, an inhibitor is added and the slide is incubated in a humidified chamber. After removing the inhibitor solution, a dilution of the primary antibody is added to the inhibitor, and the cells are cultured in a humidified chamber for 30-120 minutes. The antibody solution is then removed and the cells are washed several times in Tris-buffered saline pH 7.6 containing Tween20. Excess liquid is removed, a dilution of anti-mouse secondary antibody in inhibitor is added, and the cells are incubated for 30-120 minutes in a humidified chamber. The antibody solution is then removed and the cells are washed again several times in pH 7.6 Tris-buffered saline containing Tween20. After removal of excess liquid, the cell sample is incubated for 10 minutes with the addition of HNPP / fast red dye filtrate in alkaline phosphate buffer. The staining solution is removed and washed with pH 7.6 Tris-buffered saline containing Tween 20 and the cells are subsequently washed with a solution of DAPI in pH 7.6 Tris-buffered saline containing Tween 20. The cells are washed twice with pH 7.6 Tris-buffered saline containing Tween 20 and then with standard citrate water to remove excess liquid and the cells are air dried. The cells are then washed with 50 mM MgCl ₂ in phosphate buffered saline for 5 minutes, then washed twice with phosphate buffered saline to remove excess liquid and the cells are dried. A solution of fluorescently labeled FISH probes such as DNA and / or RNA in the cross is then added, a coverslip is placed on the slide containing the cells, and the cells are then incubated at 74 ° C. for 2.5 minutes. And then incubate at 37 ° C. for 4-16 hours in a humidified chamber The cover slip is removed and the cells are washed in 0.4X standard citrate water for 2 minutes at room temperature. Excess liquid is removed and the cells are air dried and mounted for microscopy for analysis.

Example 2
Apparatus The block diagram of FIG. 1 shows the basic components of an implementation system suitable for practicing this aspect of the invention. The basic elements of such a system are an XY stage 201, a mercury light source 203, a fluorescent microscope 205 equipped with a motorized objective lens / turret (base) 207, a color CCD camera 209, a personal computer (PC) system 211, and one or Two monitors 213 and 215 are included.

  Individual components of the system can be custom built or purchased as standard components. Each element is described in some more detail.

  A suitable motorized position stage for use with the selected microscope 205 can be provided. The XY stage 201 is preferably a motorized stage that is connected to a personal computer and can be electronically controlled using specially-supported software commands. When such an electronically controlled XY stage 201 is used, a stage control circuit inserted into the expansion bus of the PC 211 connects the stage 201 to the PC 211. The stage 201 can also be driven manually. Electronic control stages as described herein are manufactured by microscope manufacturers, including, for example, microscope manufacturers including Olympus (Tokyo, Japan), as well as other manufacturers (LUDL, USA, NY).

  The microscope 205 is, for example, a fluorescence microscope equipped with an objective lens with a motor that can provide up to 600 × with an oil immersion 60 × or 63 × objective lens in the reflected light fluorescent irradiators 203 and 20 ×. The motorized objective lens base 207 is preferably connected to the PC 211 to electronically switch between successive magnifications using special software commands. When such an objective lens base 207 with an electronic control motor is used, the objective lens base control circuit card inserted into the expansion bus of the PC 211 connects the stage 201 to the PC 211. The microscope 205 and stage 201 can be assembled to include a mercury light source 203 to provide substantially uniform illumination that does not change throughout the optical field of view.

  The microscope 205 generates an image viewed by the camera 209. The camera 209 can be a color 3-chip CCD camera or other camera connected to provide electronic output to provide high sensitivity and high resolution. The output of the camera 209 is supplied to an image processing circuit board attached to the frame grab and PC 211. A suitable camera is a Sony 930 (Sony, Japan).

  Various frame grab systems can be used in connection with the present invention. The frame grab can be, for example, a combination of a board MATROX IM-CLD (color image acquisition module) and MATROX IM-640 (image processing module) set available from MATROX (Montreal, Canada). The MATROX IM-640 module is characterized by hardware-supported image processing capabilities. These capabilities compliment the capabilities of the MATROX IMAGEINGLIBRARY (MIL) software package. It therefore provides a very quick execution of an algorithm based on MIL. The MATROX board supports display on a dedicated SVGA monitor. The dedicated monitor is provided in addition to the monitor generally used in the PC system 211.

Any suitable monitor SVGA can be used for use with the MATROX image processing board. One dedicated monitor that can be used in connection with the present invention is the ViewSonic4E / SVGA monitor. In order to have effective enough processing and storage capability, the PC system 211 can be a PC based on INTEL PENTIUM having at least 32 MB RAM and at least 2 GB hard disk drive storage space. It is desirable that the PC 211 further includes a monitor. Other than the features described herein, the PC 211 is conventional and may include a keyboard, printer, or other necessary device (not shown).

  The PC 211 executes a smear analysis software program corresponding to MICROSOFT ++ using MATROX IMAGEINGLIBRARY (MIL). MIL is a software library of functions, including those that control the operation of the frame grab 211 and those that process images collected by the frame grab 211 for subsequent storage in the PC 211 as disk files. The MIL consists of a number of specialized image processing routines that are particularly suitable for performing image processing tasks as filtering, object selection and various measurement functions. The smear analysis software program runs as a WINDOWS 95 application. Program instruction messages and measurement results are displayed on the computer monitor 213, while images acquired through the imaging hardware 211 are displayed on a dedicated imaging monitor 215.

To process a microscope image using a smear analysis program, the system is first calibrated. Calibration compensates for daily variations in performance as well as changes from one microscope, camera, etc. to another. During this phase, look at the correction image and set the following correction parameters:
System color response;
The dimensions and boundaries of the area on the slide containing the smear to be scanned for fetal cells;
The actual dimensions of the optical field when using magnifications 20x and 60x (or 63x); and the minimum and maximum fetal nucleus area when using magnifications 20x and 60x (or 63x).

The detection algorithm for the object identification signal is calculated in two stages. The first stage is the pre-scan stage 1 shown in the flow diagram embodiment of FIG. 2, which identifies possible fetal cell locations using low magnification and high speed. For example, a 20x objective can be selected to initiate a fetal cell search:
The program moves the automation stage (FIG. 2, 201) to a preset starting point, for example one of the corners of the smear-containing slide.
-The xy position of the stage at the preset starting point is the recorded optical field (step 301).
An optical field of view is obtained using the CCD camera 209 (step 305) and transferred to the PC 211 as an RGB (red / green / blue) image.
The RGB image is converted into an ILLS (Hue / Luminance / Saturation) display.
Since the hue component is binary quantized as a black and white image (step 309), a pixel with a hue value in the range between 190 and 255 is 0 (black) indicating the region of interest (blob) While the other respective pixel values are set to 255 (white, background). Blobs indicate possible fetal cell nucleus regions.
• The area of each blob in the binary quantized image is measured. In the case of 20x, it is outside the range of about 20-200 pixels in size, blob pixels are set to a value of 255 (background); they are excluded from further processing (steps 311, 313, 315) And 317).
• Next, calculate the coordinates of the center of gravity of each blob using the custom-built MATROX function (step 319). The center of gravity of the blob is the point at which points cut from a thin, uniform density sheet of blob-shaped material are balanced. Since these coordinates are stored in a database along with the xy position of the latest optical field, the blob is repositioned in the next processing stage using higher magnification.
Additional optical fields are processed in the same way, recording the xy position of each subsequent optical field until the entire slide is covered (steps 321 and 323).

Stage II shown in the flowchart of the embodiment of FIGS. 3A and 3B includes a final fetal cell recognition process:
Select a magnification of 63x (step 401).
The program moves the automation stage so that the coordinates of the first location of the first found CG (which is a possible fetal cell nucleus region) is the center of the optical field (step 403).
The optical field of view is acquired using a CCD camera (FIG. 2, 209) and transferred to the computer as an RGB image (step 405).
Converted to the RGB image HLS model (step 407).
The program then creates a light emission column diagram by counting the number of pixels whose light emission values are equal to each possible value of light emission (step 409). The counts are stored in the array as a length array 256 containing a count of pixels having gray-level values corresponding to each index.
The program then analyzes the emission distribution curve represented by the values stored in the sequence (step 411) and places the last peak. This peak was found to contain pixels that represent the plasma region in the image. Its function is to analyze emission distribution curves; calculate 9-points that move smoothly on the curve; calculate tangents of lines defined by 10 gray-level value distances; slope of these lines Set the points as 1 if the curve finds successive points with zero slope and these points (gray level) indicate minimum (curve valley) or 1 if they are maximum (peak in the curve) Then find the peak or valley in the curve by finding the position of 1 or -1 in the array of gray level values.
The program then sets the gray level value of the pixel in the valley of the emission distribution that occurs before the final peak of the distribution as the cutoff value (step 413).
• Using this cutoff value, the program then issues a second binary quantized image. This is a black and white image, the pixel corresponding to the pixel in the luminescent image having a gray level value lower than the cut-off point is set to 255 (white), and the pixel in the luminescent image having a gray level value higher than the cut-off point is set. The corresponding pixel is set to 0 (black). The white blobs in this image are treated as cells, while the black areas are treated as non-cell areas.
A closing filter is applied to the second binary quantized image (step 417); thus the holes, ie the black dots in the white area, are closed.
• The program now measures the area of the cell. If the cell area is less than or equal to 200 pixels, these pixels are eliminated, i.e., the pixels comprising these cells are set to a pixel value of 255 (black) (step 419).
The hole filling function found in MIL is applied to the remaining blobs (step 412).
The binary quantized image obtained after processing is a mask whose white area shows only cells.
• Red blood cells are now distinguished from white blood cells based on the saturation component of the HLS image. The mask is used to limit the treatment to the cell area only.
The program now counts the number of pixels whose saturation values are each possible value of saturation. The counts are stored in the array as an array of length 256 containing a count of pixels having gray level values corresponding to each index (step 423).
The program now analyzes the saturation distribution curve indicated by the values stored in the array (step 25) and places the first peak. This peak includes a pixel value indicating an area included in white blood cells.
After the peak is set as the cutoff point, the gray level value coincides with the first minimum (valley).
• Using this cutoff value, the program creates a third binary quantized image. The pixel corresponding to the pixel in the saturated image having a gray level value higher than the cutoff point is set to 255 (white). They constitute the red blood cell region. Pixels corresponding to pixels in a saturated image having a gray level value below the cut-off point are set to 0 (black). The white blob in this third binary quantized image is the nucleus for the region belonging to red blood cells.
A closing filter is applied to the third binary quantized image; thus the holes, ie the black dots in the white area, are closed.
The hole filling function found in MIL is applied to the remaining blobs (step 435).
The binary quantized image obtained after processing is a new mask containing only white blood cells.
• The erase boundary blob function of MIL is now applied to the remaining blobs (step 435) to remove those that contain pixels that coincide with the boundaries of the image area. Such a blob cannot be included in further processing because it does not know how many cells have been lost when it coincides with the boundaries of the image area.
• The erosion filter is applied to this mask 6 times; therefore, all bound blobs (white blood cell nuclei) are released (step 437).
A “thick” filter is applied 14 times (step 439). A “thick” filter is equivalent to an expansion filter. That is, it increases the size of the blob by adding successive rows of pixels around the blob. If the growing blob meets the next growing neighboring blob, the thick filter will not combine the two growing blobs. Thus adjacent blobs can be separated.
A first binary quantization mask (containing all cells) and a third binary quantization mask (containing white blood cell separation nuclei) are combined with a RECPMSSTRICTFRPOSED MIL operator. Each constructed fourth mask includes a blob that is copied from the first mask, thus showing white blood cells possible by the third mask (step 441).
The blobs in the fourth mask are measured for their area and compactness: area (A) is the number of pixels in the blob; compactness is obtained from the perimeter (p) and the area of the blob (A), which is It is equal to p2 / 4 (A). The more complex the shape, the greater the value. The circle has the smallest compact value (1.0). The perimeter is the total length of the edge in the blob with the tolerance made for the staircase effect that occurs when the diagonal edge is digitized (the inner corner counts as 1.414 rather than 2.0). is there. Blobs are retained in the fourth mask only if their area is 1000-8000 pixels, and they have a compactness of 3 or less, thus allowing a relatively rough outline for the cells. Blobs that touch the image boundaries are excluded from further processing (step 443). The fourth mask is applied to the hue component in the following manner (steps 445, 447, 449 and 451).
• Pixels from the hue component are duplicated in a new image that retains their hue, but their coordinates match white (255) in the mask; all other pixels in the new image are set to 0 (black) (Step 445).
-Pixel values in each of the adjacent non-zero pixel regions, i.e. blobs corresponding to red cell images, are checked for values between 190-255. The number of such pixels in each blob is counted (step 447).
If there are more than 200 such pixels, the blob indicates nucleated red blood cells. The coordinates of the center of gravity of each such cell are stored; and the mask is binary quantized so that all pixels with non-0 pixel regions are set to 255 (white); As tagged image file format (TIFF) files.
The program moves to the next stored coordinates for possible fetal cells that do not match any of the coordinates stored during the previous step. The entire process is repeated until a preset number of nucleated red blood cells is identified. Results including the coordinates of the nucleated red blood cells and the name of the respective mask file, and various characteristic codes of the blood slide are stored in the result text file. The nucleated red blood cell whose coordinates are stored is the fetal cell sought. (Step 451).
• After the subject of interest, such as a fetal cell, has been identified, a second signal is generated, for example, by the in situ PCR or PCR in situ hybridization or FISH described above.

Detection of Diagnostic Signal A smear containing in situ PCR or PCR in situ hybridized cells is deposited on the stage (FIG. 2, 201). The necessary calibration steps are taken as before. Calibration compensates the software for daily changes in performance as well as changes from microscopes, cameras, etc. to another. Detection of diagnostic signals in the embodiment method proceeds as follows, as shown in the flowchart of FIG.
-Select the objective lens magnification 60x (63) (step 501).
The xy stage moves to the fetal cell position on the stage according to the data from the result file corresponding to the detection of the first signal as described above (step 503).
An optical field of view is obtained using a CCD camera (FIG. 2, 209) and transferred as an RGB image to the computer (FIG. 2, 211) (step 505).
Transfer the RGB image to the HLS model (step 507).
The TIFF file containing the black and white masks is captured as another image (step 509).
The pixel of the hue component that does not correspond to the white area in the mask is set to 0 (black) (step 511).
A pixel value corresponding to a signal generated according to PCR is obtained for the remaining area indicating fetal cells. For example, the signal is the color produced for alkaline phosphatase, ie red. Pixel values in the range of 0 to 30 are sought for the non-black region of the hue component (step 513).
The stage is moved to the next untreated fetal cell and the above process is repeated (step 515).

  The PC 211 executes a software program called SIMPLE that controls the operation of the frame grabber and image processing circuit 217. SIMPLE also processes the image collected by the frame grabber and image processor circuit 217 and subsequently stores the image and processing data as a disk file on the PC 211. SIMPLE provides an icon-based environment with special procedures that are particularly suitable for performing image processing tasks such as filtering, object selection and measurement. Most of the SIMPLE tasks are operated by a human operator using a positioning device connected to the PC 211, such as a mouse or trackball (not shown).

  In order to process a data image using SIMPLE, a number of image calibration steps must first be performed. In one embodiment, a new slide appropriately stained using fluorescent in situ hybridization (FISH) is placed under a fluorescent microscope. The object of interest to be recognized, ie the nucleus or chromosomal region, has unique color characteristics. Multiple targets can be delineated simultaneously in a particular sample by combining fluorescence detection procedures. That is, if different targets are labeled with different chromosomes that fluoresce at different wavelengths, the software program can separately identify objects that emit all color information providing different fluorophores available for imagery. Targets with different affinities on different chromosomes are distinguished by the combination of emitted colors. Each target emits a wavelength corresponding to two or more phosphors, but the intensity of each is different, for example. Thus, all three color components of the microscope image are used during processing.

For each new sample inserted under the microscope, a pretreatment operation is first performed. The flow diagram of FIG. 2 illustrates the pretreatment steps of this embodiment of the present invention. Pre-processing is used to let the software correct for sample-to-sample changes.

In one embodiment, a slide containing FISH-treated cells is placed on the XY stage 201. The XY stage 201 is moved to the initial observation position that is found to contain rare cells. Iterates until a predetermined number of rare cells of a specific type is measured. In the application contemplated by this embodiment for identifying multiple targets of chromosomal DNA, the loop is performed until 20-200 nuclei have been processed. Data representing the measurement of chromosomal regions within those nuclei is collected in ASCII files.

The filtering process 12000 operates on a pixel-pixel basis as follows.
In step 12001, a hole filling filter is applied to the image. This filter, available through the SIMPLE language, is determined by looking for dark areas in a bright object when dark holes are seen in the bright fluorescent chromosome. Those areas are illuminated. The output of the hole filling filter is retained in a temporary image file 1201 and used as input to the erosion filter, step 12003. Lotion filters that are also available through the SIMPLE language replace the central pixel of the small core with the darkest pixel in the core. The core 3x3 used is used. Another operational step 12005 is performed next to grow objects until they meet, but not merge. This process also creates a contour that defines the edges of all objects. The logical NOT operation step 12007 selects a pixel in the contour other than the contour. Finally, in step 12009, the result of 12007 is logically operated on the stored temporary image file 12101. This results in only the pixels defined in both the temporary image file 12101 and the retained step 12007.

  When using a combination of fluorescence detection procedures, more than one chromosomal region is detected per unit nucleus. Thus, it is possible to recognize two chromosome regions for chromosome 21, two other for chromosome 18, one for chromosome X, and one for chromosome Y. Allows discovery of possible numerical anomalies detected by. The enumeration of cross signals is performed after the completion of 20100 nuclear measurements via an application program outside SIMPLE compiled using CLIPPER. This program reads the measurement result ASCII file and classifies the chromosomal regions detected according to their RGB color combinations. When two or more different phosphors are used in combination, they are used to distinguish different targets (some of which are labeled with one or more phosphors) using different combinations of RGB color values. The For example, a target is stained with red and green phosphors, while one target accepts the phosphor and emits 30% red and 70% green, and another target accepts the phosphor and 70% red and 30%. While emitting 3% green, the third target accepts the phosphor and emits only red. The third target is identified based on their relative radiation. Increased to trisomy 21 in a particular sample if the number of signals representing a particular chromosome, eg, a chromosomal region corresponding to chromosome 21, is two or more above the statistically significant level selected by the operator Reports identifying gender are issued.

  Although the present invention has been described with respect to clinical detection of chromosomal abnormalities in cell-containing samples, the imaging methods described herein have other clinical uses. For example, the described image processing steps can be used to automate urine analysis methods. The technology of this application can be combined with application 08 / 132,804, filed Oct. 7, 1993, to visualize and analyze a wide range of cell types based on their morphological structure. Cell morphology can be observed for diagnostic conditions, and cell morphology is correlated with physiological conditions. Such conditions are known to those skilled in the art. See, for example, Harrisonwo. Various cellular properties and abnormalities are detected based on these techniques. Finally, the specific source of the sample is not a limitation of the present invention as the sample is obtained from a blood sample, a plasma sample, a urine sample or cells from the cervix. The cell visualization and image analysis techniques described herein can be used for any condition that can be detected by individual cell analysis, tissue morphology or other properties of the isolated cells.

  Antibodies specific for human fetal hemoglobin (Research Diagnostics Inc. NJ) and embryonic epsilon hemoglobin chain (Immuno-Rx, GA) are commercially available and can be used as fluorescently labeled antibodies, or the fluorescence signal can be expressed by fluorescence labeling. Generated by the use of secondary antibodies. Fluorescent lights can be generated by other types of staining or labeling for rare cells as is known in the art. The type of fluorescent staining required for this processing step is known in the art and will not be discussed in further detail.

  Computers and image processing techniques are constantly changing. Although new techniques that meet the requirements of the above described methods and apparatus are not specifically described herein, they are specifically contemplated as within the scope of the present invention. For example, some conventional pixel and image file formats are described above, but others are used. The image file is compressed using JPEG or GIF as known in the art or other techniques still developed. Processing is performed in the RGB color description space instead of the currently used HLS space. Other color spaces are also used as desired by the skilled artisan, particularly when it facilitates post-pursuit characteristic detection.

  The invention has been described with reference to specific embodiments. Additional variations will be apparent to those skilled in the art and are intended to be within the scope of the present invention.

  In embodiments of the invention, for example, genetic diagnosis of prenatal and pre-implantation, or analysis of subcellular components of cells for detection of chromosomal abnormalities in sex chromosomes of embryos or fetal cells is described.

  FIG. 13 is a photomicrograph of combined immunostaining and FISH analysis of cells for identification of X and Y chromosomes in the cells and the presence of fetal hemoglobin. Fetal hemoglobin is present in the sample as shown by the orange fluorescent signal detected from the cell throughout the cytoplasm of the cell in the right quadrant of the figure. X and Y are shown as green water red fluorescent spots in the cell nucleus, respectively.

4 is a flow chart summarizing the method of one embodiment of the present invention. 1 is a block diagram of an analysis system used in one embodiment of an aspect of the present invention. It is a flowchart of the stage I which leads to the detection of a 1st signal. It is a flowchart of the stage II which leads to detection of a 1st signal. It is a flowchart of the stage II which leads to detection of a 1st signal. It is a flowchart of a detection of a 2nd signal. 1 is a schematic diagram of a change in apparatus showing one embodiment of the present invention using a continuous cutting technique. 1 is a block diagram of an analysis and reagent distribution system used in one embodiment of an aspect of the present invention. 1 shows an overview of a multi-target microscope system that is an embodiment of the present invention. This is an image composition method. It is a flowchart of the calibration process of one embodiment of this invention. It is a flowchart of the pre-processing process of one embodiment of this invention. It is a flowchart of the main process process of one embodiment of this invention. It is a flowchart of the main process process of one embodiment of this invention. Photomicrograph combining immunostaining and FISH analysis of cells prepared by the method of the present invention as described in Example 1 to identify fetal hemoglobin with FSh in cells and immunostaining and X and Y chromosomes It is.

Claims (15)

  Reacting a cell sample with at least one antibody, causing each antibody to bind to a particular cellular component and react to generate a unique fluorescent signal; using one or more nucleic acid probes to incubate the cell in situ Treating each nucleic acid probe with a target nucleic acid sequence to generate a unique fluorescent signal; generating one or more images of the reaction and processed cell sample; and the antibody And a method for identifying a multicellular component in a cell, comprising the step of detecting and analyzing the fluorescence signal of the image corresponding to both the nucleic acid probe and the nucleic acid probe.   The method of claim 1, wherein the cell sample is a blood sample.   The method of claim 1, wherein the blood sample is a peripheral blood sample.   4. The method of claim 3, wherein the blood sample is from a pregnant woman.   The method of claim 1, further comprising the step of quantifying the fluorescent signal compared to a control sample. The method according to claim 1, wherein the one or more nucleic acid probes are configured to be crossed to X and / or Y chromosomes in the cell sample.   Imagining a labeled probe with hybrid fluorescence targeted to the nucleic acid and a fixed sample with fluorescent staining directed to the non-nucleic acid component of the cell of interest, the fluorescent label of the probe and immunostaining is different; fluorescence from the sample Determining the number of objects of display fluorescence of interest from the immunostaining and the probe; and whether there is a genetic condition from a statistical prediction of the number of cells that show fluorescence from the immunostaining and the probe. A method for operating a computer device for detecting whether or not a genetic condition determined by at least one target nucleic acid is present in a cell sample.   The method according to claim 7, wherein the nucleic acid probe is configured to be hybridized with the X and / or Y chromosome in the cell sample.   8. The method of claim 7, wherein the immunostaining binds to fetal hemoglobin.   Treating a maternal blood sample containing a naturally occurring concentration of fetal cells with fluorescent immunostaining directed at a non-nucleic acid component of the cell of interest; a fluorescent nucleic acid probe directed at the nucleic acid sequence of interest; Covering a portion of the cell sample using a computerized microscopic visual device operatively configured to detect the fluorescent immunostaining and the fluorescent signal from the fluorescent nucleic acid probe Preparing a maternal blood sample containing a naturally occurring concentration of fetal cells, comprising: observing an optical field; and identifying cells having a nucleic acid sequence of interest by said fluorescent signal detection. how to.   11. The method of claim 10, wherein the cell of interest is a fetal cell.   The method of claim 11, wherein the fetal cells are derived from maternal blood.   11. The method of claim 10, wherein the nucleic acid probe contains an X and / or Y chromosomal DNA sequence.   11. The method of claim 10, wherein the computer-processed visual device utilizes one purpose for obtaining the immunostaining and a fluorescent signal from the nucleic acid probe.   11. The method of claim 10, further comprising automatically generating a tentative diagnosis based on the number of cells identified as having a nucleic acid sequence of interest.

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