METHOD OF STUDYING GENE EXPRESSION AND OF DIAGNOSING DISEASE

Abstract: A method for studying gene expression and diagnosing disease utilizing a combination of two-dimensional electrophoresis and double label autoradiography for analyzing proteins made as a result of cellular function and which have been separated by the electrophoretic technique. Also disclosed is a fully automatic method for quantitatively analyzing protein spots contained in a developed, double labelled electrophoresis gel.

Description: Description METHOD OF STUDYING GENE EXPRESSION AND OF DIAGNOSING DISEASE Technical Field The present invention relates to a diagnostic method. More particularly, it relates to a method of discerning and measuring gene expression and diagnosing diseases that are manifested by changes in protein biosynthesis. The measurement and identification of the proteins being synthesized is accomplished using gel electrophoresis and double-label autoradiography coupled with computer analysis of the radiolabel record. Background Art There are a number of diseases which produce changes in protein biosynthesis, which, changes generally occur before sympt ns of the disease beccme observable. As a result, the detection of changes in protein biosynthesis by cultured cells from a patient offer the opportunity to aid in the diagnosis of such diseases. Such changes also offer the opportunity to study gene expression in cells in general. In the research laboratory, cellular characteristics are determined by the genes being expressed by those cells as distinctive proteins. Thus the proteins being made are a fingerprint of cellular function and represent the genes being expressed. A method for comprehensively depicting which proteins are being made by certain cells would make available to the scientist a complete picture of which genes are being expressed at any given time. At the present time no such method is available. Two-dimensional polyacrylamide gel electrophoresis (1) is a powerful technique for separating cellular proteins. Under suitable conditions, each protein contained in a whole cell hcmogenate or its subcellular fractions can be isolated within the polyacrylamide gel and visualized by staining or by autoradiography. A finished gel frequently has several hundred to more than 1,000 individual protein spots and provides comprehensive, yet highly detailed, information about cellular proteins. Alterations in protein biosynthesis which are caused by cellular differentiation and transformation by genetic alteration or mutation, or by changes in the cell's environment can be detected by comparing electrophoretic gels containing proteins from experimentally manipulated cells with identically prepared gels containing proteins from control cells. Differences in gene expression between similar types of cells obtained from different sources can also be detected by cαtparing gels containing proteins from each cell line. However, at the present time detection of these phenomena is limited by the time required to cαπpare precisely the-hundreds or thousands of proteins being, -studied. Because of the great numbers of proteins which ' can be involved, computerized systems have been developed to facilitate the comparison of developed electrophoretic gels (2-19) . Such systems provide assistance in locating, matching and analyzing spots in gels which represent given proteins. Spot matching can at tines, offer problems because of small variations between the electrophoretic separations being compared. Such variations are coπmon and result from differences in batches of a pholines and acrylamide, irregularities in polymerization, and stretching of the isoelectric focusing gel during normal processing. Spot matching can be made more difficult as the result of increased gel to gel variations caused by interfering substances such as lipids, deoxyribonucleic acids or high concentrations of salt. The aforementioned problems in spot matching can be completely eliminated, however, by the use of double-label autoradiography (19-23). In this process, the proteins in 3 one cell sample is labeled with H and mixed with a second or 14 manipulated cell sample protein labeled with C. The cαnbined proteins are then coelectrophoresed to yield a double-labeled two-dimensional gel. Proteins fro either sample can be differentially detected by iirpregnating the gel with a scintillator and exposing it sequentially to two-x-ray 14 3 films, one sensitive only to C and another to both H and 14 C radiation. Since the images recorded on the paired films are cc pletely superimposable, identically located protein spots can be directly compared. The process of locating protein spots in images of two-dimensional polyacrylamide gels is difficult to computerize. It is complicated by the great variety of spot shapes, sizes and densities, and by fluctuations or streaks in the film background. It is further confounded by proteins that closely migrate during electrophoresis and touch or overlap-in the finished gel. Despite these difficulties, a number of computerized processes have been developed. In some (2,11,17) , broad image areas are identified which have densitites greater than an arbitrary threshold, and the positions of individual spots within these areas are located by progressively raising the threshold. In others (4,8), a second derivative of density is computed for each pixel in tHe image during a single raster pass. Spot locations are then identified by reference to inflections in the resulting secondary image. In still others (6,12,13,18), spots are found by detecting local maxima within the image. Some of these processes automatically match corresponding protein spots that are present in different images, while others rely on operator interaction to various extents. Each computerized process is the product of a new or different approach and is designed to function well for certain applications. The combination of two-dimensional electrophoresis (1) with various methods for double-label autoradiography (2-6) has already proven to be a valuable method for comparing complex protein mixtures. It has been successfully applied to the estimation of human genetic polymorphism (7,8) , the identification of human gene products (9) , the mapping of polypeptide genes with hybrid cells (10) , the genetic analysis of human lymphocyte proteins (11) , and the detection of a gene product that may relate to Duchenne muscular dystrophy (12) . The method also has been used for the detection of gene products of 1,25-dihydroxγ- vitamin O- (13, 14). Routine application of this powerful method has been limited by the time required by either manual or semi-autαnatic examination of the great numbers of proteins present in the double-labeled gels. To date, no fully automatic process has been described for the analysis of double-label autoradiography after electrophoresis. It obviously would be desirable to have a method which is fully automatic and capable of quantitatively analyzing each protein spot contained in a double-labeled gel. It is an object of the present invention to provide a method for diagnosing diseases which are manifested by changes in cellular protein biosynthesis. It is a further object to provide a rapid, fully automatic, method for quantitatively analyzing protein spots contained in developed, double-labeled electrophoresis gels. It is a still further object of this invention to provide a method for studying gene expression. Disclosure of Invention The methods of the present invention comprise a comprehensive analysis of cellular protein biosynthesis as evinced by electrophoretic gels obtained from two-dimensional gel electrophoresis, combined with double-label autoradio¬ graphy. To study gene expression in cells or tissue: control 14 cells are incubated with C leucine; experimental (hormone 3 stimulated or modified) cells are incubated with H leucine; the cells are then mixed, fractionated and/or solubilized and subjected to ^wo-dimensional electrophoresis. For the case of diagnosis of disease: cells obtained 3 from a diagnostic candidate are incubated with H leucine; 14 cells frcm control patients are incubated with C leucine; the cells are mixed and subjected to two-dimensional gel electrophoresis. In both of the above cases the gels are irrpregnated with a flour, such as Enhance (NEN-Dupont, Boston) , and exposed 3 14 sequentially to a sensitive x-ray film that records H and C 14 radiation, and to a film that records only C. (The gels in 14 3 each case have included strips with standard C and H protein for calibration purposes.) The films are then analyzed by: (a) exactly aligning the x-ray film frcm the control patient with the x-ray film frcm the diagnostic candidate; (b) scanning and digitizing the optical density of the media containing the protein spots and storing the digitized image as a set of pixel numbers in a first storage means; (c) calculating the optical density gradient of each pixel and proceeding to (d) when gradient exceeds a preselected threshold; (d) identifying the center of each protein spot in the image by: (i) using pixels which have a gradient number exceeding the first threshold as a center, scanning the density of surrounding pixels until the pixel of greatest density is found and repeating the scanning of surrounding pixels using that pixel as the center until the center pixel of greatest density is found; (ii) storing the center pixel locations in a second storage means; (iii) calculating the density gradient of pixels in a plurality of directions radially outward from each center pixel; and (v) storing as a set of boundary locations in a third storage means the position of each pixel which has a density gradient which drops belcw a second threshold which indicates that the spot ends within the area of said pixel. In the preferred embodiment the first to fourth storage means are contained within a single computer. The method is effective and is computationally simple. A pair of images can be processed in approximately 5-_nin (2.5 min CPU time) thereby greatly reducing the time spent in analyzing experimental data. The preferred method requires 500 kilobytes of memory but can be modified so that it requires only 50 kilobytes with a 10-15-fold increase in processing time. It can also be transported to other systems which access digital image files one line at a time. The spot location method can locate protein spots whether they are ccmpletely resolved within the image or lie within unresolved clusters. Spot boundaries are delineated without shape restrictions and unresolved spots are "split" along an intervening density miniiπum. Overlapping spots, however, are not resolved mathematically, as in seme prior art methods (4,6,8,12,14,27) . In cases where the boundaries of spots are inappropriately positioned, the method allows for corrections to be made with operator interaction. Allowance is also made for editing dust spots and other spurious areas of film darkening frcm the final spot location file stored on a disk. Finally, the method can produce suitmaries of image analyses -"in various forms, including hard copy facsimiles of the images which identify the located spots and displays on the video • monitor which can be photographed. The genes being expressed are demonstrated by the ratio 3 14 of H: C in a spot rising above the ratio found in all other spots. The ccπputer can display the protein whose ratio uses above normal values or diminishes below normal thus illustrating whether genes are turned on or off. For diagnostic purposes, the absence of a spot, or the change in migration of a protein or the addition of a protein would be indicative of a possible physiological defect. These and other objects and advantages of the invention will be apparent frcm the drawings and the description of the preferred embodiment. Brief Description of Drawings Fig. 1 is a fluorographic image selected for demonstrat¬ ing the spot locating process. A 10% polyacrylamide gel 3 14 containing cytosolic proteins labeled with both H and C (150 mg protein; 1.72 x 10 H dpm; 1.72 x 10 C dpn) was 3 impregnated with EN HANCE and exposed to a pre-flashed X-Cmat AR film for 48 h at -70°C. The molecular weights of the resolved proteins range from 220,000 (top) to 17,000 (bottom) , and the isoelectric points range frcm 8 (left) to 4 (right) . The spot identified by the arrow is redisplayed in Fig. 2A. Fig. 2 shows the relationship between density values and calculated gradients. A well-resolved protein spot from the fluorographic image (Fig. 1) is displayed at full resolution in A. Cross-sectional views of this spot in the direction of the pH gradient are shown for density (B) and density gradient (C) at reduced resolution. Calculation of gradient values for each pixel within the spot's boundaries yields a second degree surface which is shown as a contour plot in D. Fig..3 shows the location of a detected spot. Density values within the spot displayed in Fig. 2A are shown in reduced resolution. Bold face numbers designate pixels having calculated gradient values at or above a threshold of 50, and light face numbers designate pixels with sub-threshold of gradient values. An iterative search for the spot's maximum begins with any pixel having a calculated gradient which equals or exceeds the threshold. A search initiated by 48 at the upper left begins in block AI where 145 is identified as the pixel having the greatest density value within the 7 x 7 pixel block (block B) where 209 is identified as the pixel with the greatest density value. Finally, block C, centered on 209 is searched for greater density values. As no greater values are found, 209 is identified as the spot's maximum, and the image coordinates of this pixel are designated as the spot's location. Fig. 4 shows spot detection at various gradient thresholds. A ccmplex area of the fluorographic image (Fig. 1) is displayed in A and gradient values in both A and B where values of 50 are identified by solid lines, values of 100 by broken lines, and values of 300 by solid lines labeled 300. Protein spots detected with, preselected thresholds of ' 300, 100, 50, and 25 are marked (±) in C, D, E, and F, respectively. Fig. 5 shows the accurate location of protein spots amid prominent vertical and horizontal streaks. Most protein spots can be successfully discriminated frcm streaks by varying the gradient threshold. A threshold value of 100 was selected for this image. Fig. 6 shows the accurate discrimination of overlapping protein spots. Although the two large protein spots located at the center of this figure were incompletely resolved during electrophoresis, the locations of both spots can be correctly identified. A threshold value of 50 was selected for this image. Fig. 7 shows the delineation of spot boundaries. Boundaries of protein spots located in Fig. 4D were delineated using a threshold (T*) of 12. Fig. 8 shows the responses of X-Omat AR and No-Screen 3 14 films to H and C. Single-labeled calibration strips were exposed to pireflashed X-Omat AR film for 48 hours at -70°C and to No-Screen film for 10 days at 22°C. The resulting film images were digitized by a rotating drum densito eter, and displayed on a McIDAS III video terminal. The film density produced by each calibration strip band was determined by averaging the digital data for a 10 x 10 pixel block within the band's image. Density values produced on X-Omat AR film 3 14 by H (1/ 2/) and C (_) are shown in A; those produced on No-Screen film are shewn in B (n=8) . Smooth curves were calculated frcm the plotted data by a cubic spline fitting 2 routine. (A pixel equals a 0.01 mm areas of film.) Fig. 9 shows the linearization of X-Omat AR film 3 14 responses to H and C. The spline-fitted curves shewn in Fig. 1A were linearized between density values of 50 ( ) and 205 (...) by re-expressing the ordinate as shewn. Linear regression equations were calculated for the transformed 3 14 curves with selected data points (1/W2/, H: C) having non-transformed density values f 50, 75, 100, 125, 150, 175 and 200. Both equations, given in the text, had regression coefficients (r) greater than 0.99. Fig. 10 shews the response of X-Omat AR film to mixtures 3 14 3 of H and C. Calibration strips containing mixtures of H- 14 and C-labeled proteins were exposed to the same films described in Fig. 8. The densities produced on the X-Omat AR films are plotted against the knewn H content in A. The density values ( ) are reploted in B against the total 3 isotopic content of the strips, expressed as H alone. The 3 resulting curve closely coincides with the H response curve ( ) replotted frcm Fig. 8A. Fig. 11 shows matching X-Omat AR and No-Screen images produced by exposure t the same double-labeled gel. Cytosolic 3 14 proteins labeled with both H and C were electrophoretically resolved within a 10.polyacrylamide gel. The gel, containing 150 l/m2/g of protein, 1.72 x 10 β 3 H dp , and 2.00 x 10 5 14 C 3 dpm, was impregnated ith En HANCE and exposed to an X-omat AR film (A) for 48 h at -70°C, and to a No-Screen film (B) for 10 d at 22°C. Molecular weights of the resolved proteins range frcm 220,000 (top) to 4 (right) . Images produced by a 14 C calibration strip are located to the left of the gel images, 3 and a similar image produced by a H calibration strip is located to the right of the gel image on the X-Omat AR film 14 only. The No-Screen film records disintegrations of C along by direct autoradiography. The computerized process 3 14 then calculates the absolute H and C content of each protein spot from the paired films by knowledge of their responses to the isotopes. Fig. 12 is a perspective view of a computer system which employes the present invention. Fig. 13 is a graphic representation of one of the steps performed as part of the present invention. Fig. 14A and 14B are a flow chart of the processing carried out by the computer system of Fig. 12. Fig. 15 is a schematic representation of the data structures which are produced by the computer system, of Fig. 12 while carrying out the process of Fig. 14. Description of the Preferred Embodiment Referring first to Fig. 12, a computer system employed to practice the present invention can be seen which includes an 1MB 4381 (Group II) central processing unit 1 which is coupled to a 640 megabyte disc drive 2 (IBM Model 3350) and a 9-track, high speed tape drive unit 3. The processor 1 is accessible through a number of peripheral devices, including a dot matrix printer 4 (Okidata Model 93) and a Televideo CRT terminal 5. An image display monitor 6 (Aydin Controls) is also connected to the processor 1 and it includes local memory for storing a series of 480 by 640 pixel image frames. The stored images may be displayed on its screen 7 and the digital data within any stored image frame can be identified and accessed by using a variable-sized cursor which may be moved on the screen by a joystick 8. As will be described in more detail belcw, the operator may control the system by entering information through a terminal keyboard 9 in response to prompting messages produced on the terminal display 10. Matched films produced frcm the two-dimensional gels are digitized on an Optronics P-1000 densitcmeter 11 connected to the tape drive 3 by a microprocessor-based controller (not 2 shown) . The density of each 0.01 mm film area (pixel) is converted to an 8 bit number ranging frc 0 to 255 (0.0 to 3.0 optical density units) which is recorded on magnetic tape. Digitized images (1400 x 1800 pixels) may then be entered into the processor 1 and stored at full resolution in the disc drive 2. These digitized images may be displayed on the monitor screen 7 and they may be processed according to the present invention to automatically locate protein spots. The ccmputer system of Fig. 12 executes a stored program to process a selected digitized image stored iri the disc drive 2. This process is indicated by the flow chart of Figs. 14A and 14B. Referring particularly to Figs. 14 and 15, the selected image is read frcm the disc.drive 2 and is.processed by a set of instructions indicated by process block 20 to produce another image that is written out to disc drive 2. This second image of density numbers is more suitable for display on the monitor 6. Each element of the second image is calculated by taking the average value of successive 3-element blocks of the first image. The resulting 467 by 600 element image is a set of 8-bit numbers which each represent the average optical density of a block of pixels in the original digitized image. As indicated by decision block 21, the operator can begin the protein spot location program. As will become apparent frcm the description belcw, the gradient threshold is a variable in the process which enables the operator to control the sensitivity of the protein spot location. By entering smaller values at the keyboard 9 as indicated by process block 21, smaller protein spots will be located. Of course, such increased sensitivity also increases the likelihood that artifacts in the image data will be improperly identified as valid protein spots. Once the gradient threshold value (GL) has been set, a loop is entered in which an optical density gradient value is calculated for each pixel, or element, of the averaged image. As indicated by process block 22, the gradient for each element in the averaged image is calculated by using the values of the eight adjacent optical density numbers. If the D array element is indicated as D(X,Y) , then the gradient value G(X,Y) at this pixel is calculated as follows: G(X,Y) = [D(X-1,Y+1)+D(X,Y+1)+D(X+1,Y+1)] - [D(X-l,Y-1)+D(X,Y-1)+D(X+l,Y-1) ] + [D(X-l,Y-l)+D(X-l,Y)+D(X-l,Y+l)] - [D(X+l,Y-1)+D(X+l,Y)+D(X+l,Y+1)] For the element D(2m2) for example, the gradient value is: 6(2,2) = [D(1,3)+D(2,3)+D(3,3)]-[D(1,1)+D(2,1)+ D(3,l)]+D(l,l)+D(l,2)+D(l,3)]- [D(3,l)+D(3,2)+D(3,3)] where D(l,l) D(l,2) D(l,3) are the density values D(2,l) D(2,2) D(2,3) D(3,l) D(3,2) D(3,3) As indicated at decision block 23, the calculated gradient value is then compared with the gradient threshold GL, and if it is greater, an iterative search is done to find the maximum as indicated.at process block 25. This search is initiated by examining the optical density of a 7 by 7 block of elements in the averaged image which are centered on the current element. When the pixel with the highest density is located, it becomes the center of a new 7 by 7 block of elements which are examined. The search ends when the center of the 7 by 7 block is the highest density element. The location of this spot center C. in the averaged image is stored in a spot center table 27, as indicated by process block 28. The spot center table 27 is scanned after each center is located to make sure the same center is not entered more than once. Because the spot center may encompass an area of several pixels, each new center within two pixels of an existing center is dropped. After the entire image has been processed, as indicated at decision block 29, the loop is exited. As shown in Fig. 15, the spot center table 27 contains a list of spot centers C,-- ■ —C. along with their locations (X and Y) in the 467 by 600 averaged image. Referring still to Figs. 14B and 15, a loop is then entered at 30 in which the boundaries for each located spot are found. As indicated by process block 31 and as shown in Fig. 13, this process starts by examining the change in image density at successive locations radially outward from the spot center C.. The density numbers in the averaged image are employed for this purpose and a gradient number is calculated for successive elements along the eight paths indicated by the vectors 32. The gradient number is merely the change in optical density between the image element D. and'that of the next element D. .. which is radially outward from the spot center C.. 1 G. = D. - D.., l l l+l The edge f the spot is defined as the Point P at which the gradient G. drops below a second preset threshold value "T". The value of T is selected so that the edge is positioned at the first density value D. which is less than two standard deviations above the local background optical density for well resolved spots, or at the lowest optical density point between two incompletely resolved spots. By searching in eight directions from the spot center C. , eight points P1-P8 are thus located. As indicated by process block 33, an interpolation process is then employed to fit a closed curve to the eight points P1-P8. This curve, indicated by the dashed line 34 in Fig. 13 is calculated by a least squares fit to a general equation of the second degree in which no assumptions are made about spot shape. Many such curve fitting routines are known to the art, but in the preferred embodiment a FORERAN program entitled "CURV" is employed for this purpose. The resulting second order equation is then employed to locate a series of thirty-six points B1-B36 which are located at successive ten degree intervals around the spot center C.. The array location (X and Y) of each boundary point B1-B36 is stored in a boundary point table 35. As each boundary is found, it is drawn on a graphics image which overlays the protein spot image on monitor screen 7. After the entire image has been processed, the operator can edit boundaries which are in error and redraw an outline which is more reasonable using joystick 8. The boundary point _ table is saved as a file on the disc drive 2. Since the second autoradiographic image is directly aligned with the first image, the spot finding and curve fitting steps can be skipped. Using tables 27 and 35, the data are read fom the second image and then can be compared with the first image. ' The following are detailed descriptions of the method of the present invention. Example 1 Materials and Methods Software and hardware. Programs for locating, integrating and matching protein spots were written in IBM FORTRAN 77. These programs were run on the Man-computer Interactive Data Access 2 System III (McIDAS III) located within the Space Science and Engineering Center at the University of Wisconsin-Madison. The McIDAS III (25) consists of an IBM 4381 (Group II) , twelve 3350 disk units (each capable of storing 640 megabytes) , and a printer. The central processing unit is accessible through video terminals which consist of an image display monitor, an alpha-numeric CRT, a keyboard and two cursor control joysticks. Each video terminal has a series of image and graphic frames that are stored locally for rapid access. Image frames (480 x 640 six-bit pixels) can be sequentially displayed and overlayed with graphic frames (480 x 640 three-bit pixels) . Digital data within any image frame can be accessed by the operator with a variable-sized cursor controlled by the joysticks. Autoradiographs and fluorographs. Cytosolic proteins, labeled 3 14 with H and C, were extracted frαn cultured embryonic chick duodena and resolved by the O'Farrell method of two- dimensional polyacrylamide gel electrophoresis (1) . The resulting double-labeled gels were impregnated with scintillator, dried under vacuum and exposed sequentially to two types of x-ray film. One type of film (Kodak X-Omat AR-5) recorded the disintegrations of both isotopes within the gels, and the other type of film (Kodak No-Screen 2T) recorded the 14 disintegrations of C alone. The preparation of these matching x-ray film images is described hereinafter. Digitization of film images. Matching X-Qnat AR and No-Screen film images were precisely aligned (± 1.8 mm) during digitization. Good alignment of the images was easily achieved during film exposure by fastening each double-labeled gel to a masonite board having the same dimensions as the x-ray films. When both films were aligned with this board during exposure, the images produced by the gel were positioned in nearly the same place. Small differences in image registration were corrected prior to digitization by overlaying one film on the other and realigning the images with the aid of a light box. When aligned, a single new edge was cut for both films with a straight-edged paper cutter. This new edge was then used to mount identically the matched films on the rotating drum of a densitcmeter. Matched films produced frcm the two-dimensional gels were digitized on a Optronics P-1000 densitcmeter (Chelmsford, MA) connected to a tape drive via an on-line microprocessor. The 2 density of each 0.01 mm film area (pixel) was converted to an 8 bit number ranging frcm 0 to 255 (0,0 to 3.0 optical density units) and recorded on magnetic tape. Digitized images (1400 x 1800 pixels) were entered into the McIDAS III for processing and stored at full resolution. Reduced images were created by replacing each 3 x 3 block of pixels with a single pixel having a grey scale value equal to the mean of the 9 replaced values. These averaged images were used for displaying and interactively examining the digital data on a video terminal and for automatically locating the protein spots. To begin the spot location process, reduced fluorographic and autoradiographic images of the same two-dimensional gel were entered into a video teπninal. The alignment of matching images was visually checked by overlaying the images on the monitor. Images with registration differences in excess of 2 pixels in the horizontal or vertical directions were rescanned before analysis.. The area of the gel to be analyzed was then specified by positioning a variable sized cursor box over the appropriate area of the fluorographic image. To demonstrate the spot finding process, a fluorographic image (Fig. 1) was selected which is representative of the images we have generated. This ' image contains more than 300 protein spots of many shapes, sizes and densities, and is characterized by the presence of streaks, background fluctuations, and clusters of incompletely resolved spots. The sections which follow focus on selected areas of this image. The relationship between density and the calculated gradient is illustrated in Fig. 2. Shown in Fig. 2A is a single protein spot selected frcm a relatively uncrσwded area of the fluorographic image. This spot is not representative of all spots in the image but has a shape that is characteristic of well-resolved spots (1) . It has an indistinct border that is approximately circular and a- density maximum that is slightly off-center in the cirection of lower molecular weight. When examined in the direction of the pH gradient, hcweverv the .spot's density is symmetrically distributed about the maximum (Fig. 2B) . Fig. 2C shows the calculated gradient values for the same pixels whose densities are displayed in Fig. 2B. Low gradient values identify image areas where the density remains constant, such as in background areas or at the spot's maximum, and high gradient values identify areas where the density differs greatly with small changes in location. Each gradient value, therefore, is analogous to a first derivative of density as a function of location in two dimensions. If the gradient is calculated for each pixel of this protein spot, the second degree surface displayed in Fig. 2D is formed. This surface " rises sharply at the spot's edge but decreases in the area of the spot's maximum. The marked changes in this surface at the extreme edges of the spot provide a sensitive means of detecting the spot's boundaries. To detect protein spots throughout the entire fluoro¬ graphic image, each pixel's gradient value is compared to a preselected threshold (see below) . This comparison is made ininediately following each gradient calculation. Pixels having gradient values below the threshold value are predominantly located in the background areas of the image and are ignored. Conversely, pixels with gradient values which equal or exceed the threshold are located within the boundaries of a spot. These pixels signal the presence of a protein spot and initiate a search for its exact location. Location of detected spots. Whenever a protein spot is detected, an iterative search routine is initiated which locates the spot's maximum. The search begins in a 7 x ' 7 block of pixels centered on the pixel whose gradient vaiue equals or exceed the threshold. The densities of the 49 pixels within this block are then scanned until the pixel with greatest density is identified. This pixel becomes the- center of a new 7 7 block which is similarly searched for the pixel of greatest density. As illustrated in Fig. 3, the process is repeated until the pixel at the spot's maximum is identified. This pixel is designated as the spot' location and its image coordinates are kept in memory. In processing the entire fluorographic image, it frequently happens that a spot's location is identified more than- once. This repetition occurs when more than one pixel within the spot's boundaries has a gradient value at or above the selected threshold. Repeated entries are prevented by comparing each new location with those sorted in memory and ignoring any duplicates. This maximum of a detected spot will occasionally encompass an area of several pixels when a spot covers a large area of the image or contains sufficient radioactivity to saturate the film during exposure. In this case, each new location which lies within a radius of 2 pixels frcm a recorded location is emitted. The final list of spot locations is written to a disk file. Threshold selection. The detection of protein spots requires the pre-selection of a gradient threshold. Selection of a high threshold results in the detection of only those few spots in which adjacent pixels have*greatly differing density values. In contrast, selection of a low threshold leads to the detection of virtually every spot in the image. As larger gradient values are generally associated with larger spots, gradient threshold selection is roughly comparable to specifying the minimum size that a spot must have in order to be detected. The operator " can therefore control the sensitivity of the spot detection process by varying the threshold value. The effect of varying the gradient threshold is illustrated in Fig. 4. Displayed in part A of this figure is one of the more complex areas of the fluorographic image. Superimposed on this image area is a contour plot (Fig. 4B) of the corresponding . gradient surface which identifies pixels with gradient values in excess of 50, 100 or 300. A close examination of this contour plot reveals that only the three largest spots contain pixels with gradients of 300 or more. Setting the threshold at 300 therefore results in the detection and location of these spots alone (Fig. 4C) . As progressively lower thresholds are selected, the spot detection process becomes increasingly sensitive: a total of 16 spots are detected with the threshold set at 100 (Fig. 4D) , 25 spots are detected with the threshold at 50 (Fig. 4E) and 31 spots are detected with the threshold at 25 (Fig. 4F) . Each drop in the threshold value allows smaller protein spots to be detected. The minimum increase in density over background required for spot detection at a gradient threshold of 50 is described hereinafter in the paragraph entitled "Demonstration of Maximum Sensitivity in Spot Detection." Although lowering the threshold value allows greater sensitivity of spot detection, the injudicious selection of a low theshold can result in sporadic identification of streaks or background fluctuations as protein spots. Consequently, the threshold should l_e sufficiently low to achieve the highest sensitivity possible in the absence of a significant number of errors. An optimal threshold value can easily be determined for a given image, and then used to process all other images produced under identical conditions from similar protein mixtures. In practice, one image frcm each series df images is processed at several different threshold values and the located spots are checked on the video terminal. The threshold value yielding the most suitable analysis is then selected and used in processing the remaining images. Accuracy of spot locations. By careful selection of the gradient threshold, protein spots can be accurately located even in problematic image areas. Shown in Fig. 5 is an area of the fluorographic image where the spots are partically obscured by prominent vertical and horizontal streaks. These streaks, which occur with increasing severity with larger protein loads (1) , are commonly encountered in images produced frcm two-dimensional gels. As demonstrated in this figure, most protein spots can be accurately located even when they appear within steaks which trail frcm larger spots. The spot location process also retains good accuracy in situations where two (or more) protein spots overlap due to incomplete resolution (Fig. 6) . However, image areas characterized by extremely poor resolution, such as the basic edge of the image, should be avoided during processing. Infrequent situations arise in which a spot cannot be located, as illustrated in Fig. 7. Although the small spot (ai) lying next to one of the largest spots in the fluorographic image can be detected, its location is consistently overlooked. This emission results from low image resolution relative to the 7 7 pixel block searched for the spot's maximum. A 7 x 7 pixel block searched for the spot's maximum also includes pixels frcm the larger spot which have greater density values. Any search which begins with the smaller spot necessarily ends in the location of the neighboring larger spot. A similar situation leading to spot omission arises when a spot (b) forms the shoulder of another larger spot. If a spot of particular interest is emitted during processing, these spacing problems can be overcome by reprocessing the image after 'reducing it to one-fourth of its original size rather than to the usual one-ninth. Delineation of spot boundaries. The search for a spot's edges begins with the pixel recorded as the spot's maximum and proceeds along eight lines radiating symmetrically outward. A new gradient (G*) is calculated for each pixel in these search lines by use of a simplified formula: G* = Dl - D 2 where D, and D„ represent density values at the adjacent pixels which also lie in the search line (D.. lies nearer to the spot's maximum) . The spot's edge is defined as the first pixel encountered in each line which has a gradient value less than a specified threshold (T*) . This threshold is selected so that the edge is positioned at the first density value which is less than two standard deviations above local background for well resolved spots or at the lowest density value between incompletely resolved spots. The full boundary of the spot is then delineated by fitting a closed curve to the eight located pixels. This curve is calculated by a least squares fit to a general equation of the second degree which makes no assumptions about spot shapes. The image coordinates for pixels located at every 10 degrees of arc along the calculated curve are written to a disk file. Calculated curves are deleted if they are hyperbolas or parabolas or if any radius of the curve is less than 2 pixels. Using a video terminal, the boundaries delineated by this technique are superimposed over the fluorographic image to verify that the slection of T* is correct (Fig. 8) . Variations in T* change the areas enclosed by the calculated boundaries. As T* is raised, the spot's edges are located at pixels having density values that significantly exceed local background. As T* is lowered, the spot's edges are located at pixels having density values equal to local background. Pairing comparable spots in the matching images. After the protein spots in the fluorographic image are fully located, they are paired with comparable spots in the matching autoradiographic image. This pairing process is accomplished by locating a spot in the autoradiographic image which has a maximum density value within 2 pixels of each located spot in the fluorographic image. The boundaries of the newly located spots are then delineated by the same curves calculated for the fluorographic image after appropriate registration adjustments. This pairing process is accurate provided the matching images are precisely aligned before analysis. Demonstration of Maximum Sensitivity in Spot Detection. A 3 x 3 pixel block in the upper left quadrant of a protein spot can be simulated by the following model: b b xb b xb xyb xb xyb xzb where bl is the background film density, xl is a percentage increase over background density, and Y and z_ are different percentage increases over x. Within this model, the gradient equation presented in "Delineation of spot boundaries" section can be solved for xl, as shown below: Gradient (g) - xb + xyb + xzb - b + b + xb b + b + xb - xb + xyb + xzb = xyb + xzb - 2b + 2b - xyb - xzb Rearrangement of the second term yields: g = xyb + xzb - 2b + xyb + xcb - 2b = 2 xyb + xzb -2b = 2b x y + z -2 Since the density increases at the edge of a spot, x, y_ and z. must be greater than 1, and the equation becomes: g = 2b(x(y + z)-2) Solving the : x = ( g / 2b + 2)/y + z) The value of x represents the balance percentage increase over background density required for detection of a spot. If, for example, a gradient (g) of 50 is selected as a threshold, film background equals 30, and γ_ and z ^ are 20 and 30% greater than x, respectively, then: 5 +2 / (1,2 + 1.3) = 1.13 x =2(30) In this example, the spot's edge is detected at a location where density increases to 13% above background. Solving for y_ and z. allcws the calculation of the density values within the 3 x 3 pixel block. These density values are: 30 30 34 30 34 41 34 41 44 and the edge of the spot is located at the center pixel, 4 density units above background. Example 2 Materials and Methods Chemicals, animals, and media. X-Omat-AR-5 x-ray film, No-Screen 2T x-ray film, GBX developer and GBX fixer were 3 obtained frcm Eastman Kcdak Co. EN HANCE was purchased frcm New England Nuclear. L-[ϋ- C]Leu (336 mCI/mmol) and 3 L-[4,5- H]Leu (56 Ci/nmol) were obtained from Amersham Corp. in aqueous solutions containing 2% ethanol. Eighteen-day-old chicken embryos (White Leghorn) were obtained from Sunnyside Hatcheries (Oregon, WI) and maintained overnight in a humidified incubator before use. Waymouth's 752/1 medium, penicillin and streptαnycin were purchased from GIBCO (Grand Island, NY) , and low leucine medium was prepared according to the published formulation for Waymouth's 752/1 medium (3&) by reducing the leucine concentration. Low leucine medium with 3 13=4 radiolabel contained H-leucine and C-leucine at specific activities of 3.17 and 0.317 mCi/l/m2/mol, respectively. All other reagents were of analytical grade. 3 Film calibration strips. Cytosolic protein, labeled with H 14 and/or C, was serially diluted into identical PAGE solutions (1) containing 10% acrylamide. These solutions were layered between a pair of glass plates to form 120 x 150 x 0.75 mm slab gels composed of 9 horizontal bands. As soon as each band was poured, its upper surface was overlayed with water until polymerization was complete. This surface was then rinsed with water and gently dried with a length of Whatman filter paper (W. and R. Balstαn, Eng.) before being overlayed again with the next band. The lowermost band of each gel contained no radiolabel and served as a control for background deteπninations. Each added layer contained successively greater amounts of radiolabeled protein. After polymerization of the uppermost band, the gels were removed from the plates and fixed for 1 h in an aqueous solution containing 10% (w/v) trichloroacetic acid, 10% (v/v) glacial acetic acid and 30% (v/v/) methanol. Fixed gels were soaked 3 with shaking for 1 h in 65 ml of EN HANCE and for a second h in water, and were dried on filter paper for 30 min at 80°C using a BioRad gel dryer. All bands of the dried gels were approximately 1 cm in width and contained a uniform level of radioactivity per unit area. Identical calibration strips were produced frcm each dried gel by making one-half inch wide vertical slices through the horizontal bands with a paper cutter. The amount of H 14 and/or C contained in each band was determined by cutting our replicate polyacrylamide discs with a 7 mm diameter cork borer, burning each disc in a model 306 TriCarb sample oxidizer (Packard Instrument Co., Downers Grove, IL) , and 3 14 measuring the released H 2 0 and CO- by liquid scintillation spectremetry. The measured radioactivity, adjusted for recovery from the sample oxidizer and for counting efficiency, 2 was expressed as disintegrations/O.01 mm area of gel/unit time. Exposure of x-ray films to calibration strips. Dried calibration strips were taped face up, by the edges, on smooth-sided masonite boards (8 x 10 x 0.-25 in) and exposed to preflashed X-Omat AR-5 x-ray films (8 x 10 in) . Preflashing was accomplished under conditions which raised the background film density by 0.15 OD with an electronic flash (Model 283, Vivitar Corp., Santa Monica, CA) fitted with-3 filters (38). The sensitized film surfaces were placed in direct.contact with the calibraton strips, and the opposite surfaces were covered with protective yellow paper and a second masonite board. Pairs of boards containing films were stacked between two steel plates (14 x 12 x 0.33 in) connected on all sides by * bolts which were evenly tightened until the boards were clamped together with high pressure. The clamped stack was then wrapper in aluminum foil to exclude light and was buried in dry ice for 48 h. Following exposure of the X-Omat AR films, the same calibration stips were repositioned, in similar fashion, on non-preflashed No-Screen 2T x-ray film (8 x 10 in) . Exposure of these films was accc plished at 22°C for 10 d. Film processing. Both types of x-ray films were developed manually using GBX developer and fixer. At the end of the specified exposures, the films were quickly removed from between the steel plates and placed in individual film holders designed for use with vertical film processing baths. X-Cmat AR films were developed for 5 min at 20°C, fixed for 3 min and washed for 10 min. No-Screen films were developed for 5 min at 20°C, fixed for 10 min and washed for 30 min. Preparation of double-labeled protein samples. Duodena from 19-day-old chick embryos were cultured according to a previously described technique (39, 40) . The duodena were incubated for the first 18 h in Waymoth's 752/1 medium and in similar medium containing a ' reduced concentration of leucine (74.41/m2/M) for the remaining 6 h. The low leucine medium was replaced with fresh medium after the 21st h of culturing. 3 aannd with identical medium containing both H-leucine and 14 C-leucine after the 22nd h. All media contained penicillin (50 units/ml) , streptomycin (50 g/ml) and ethanol (0.1%). Tissue uptake of radiolabeled leucine was determined as previously described (14) and found to be linear during the 2 h labeling period. After 24 h of culturing, the duodena were rinsed in 4°C buffer (50 M PO., 150 mM NaCl, pH 7.4) , placed in vials by pairs, and frozen on dry ice. At a later time, the contents of each vial were transferred to a Potter-Elvehjem hemogenizer containing an additional 0.5 ml of buffer and homogenized on ice with a motor-driven pestle. Cytosolic extracts were obtained from the 4 hemogenates by ultracentrifugation (100,000 x g; 45 min; 4°C) and subsequent recovery of the supernatants. Each extract was analyzed for protein content by the Lowry method (41) and for radiolabel incorporation by trichloroacetic acid analysis (35) . er Radiolabel incorporation was found to be 11.47 + 0.04 x 10 l-\ dpm/mg of cytosolic protein. Double-label two-dimensional gels. Radiolabeled cytosolic extracts were lyophilized and resuspended in sodium dodecyl sulfate-free lysis buffer (1) to a final concentration of 6 mg/ml. A 25 microliter aliquot of each extract was resolved by two dimensional electrophoresis by the Kendrick Laboratory (Madison, WI) . Isoelectric focusing was ccmpleted at 400 V for 15 h and 800 V for 45 min, and the molecular weight separation was accomplished in 10% acrylamide gels (120 x 150 0.75 mm) . Gels were processed and positioned on x-ray films as described above under "Film Calibration Strips." Digitization of film images. Films exposed to calibration strips and two-dimensional gels were converted to digital images and entered into the McIDAS II for analysis as previously described. Calibration of the x-ray films. The responses of the x-ray 3 14 films to H and C are determined by the use of calibration strips. These strips, prepared by incorporating radiolabeled proteins into bands of 10% prolyacrylamide gel, contain known amounts of radioactivity per unit area. When calibration strips having the radioactive content listed in Table I are exposed to preflashed X-Cmat AR film for 48 h at -70°C, they produce density values like those shown in Fig. 8A. X-Omat AR film density is raised above background when the level of 14 3 radioactivity exceeds 100 C or 500 H disintegrations/pixel. Beyond these approximate thresholds, greater film densities 14 3 are produced by C than by equal amounts of H, reflecting 14 the higher energy associated with C disintegrations. When exposed to No-Screen film for 10 d at 22°C, the calibration strips produce density values like those shown in Fig. 8B. 3 The No-Screen film is completely insensitive to H, even at levels approaching 100,000 disintegrations/pixel, and is less 14 2 sensitive to C than the X-Cmat AR film. Smooth curves fitted to the calibration strip data are used to convert density values into isotopic disintegrations. 14 No-Scrren densities are converted directly into C 14 disintegrations using a C standard curve (Fig. 8B) . X-Cmat .AR densities, however, cannot be directly decoded into the 2 14 correct numbers of H and C disintegrations since identical densities are produced by many different combinations of the two isotopes. Instead, X-Omat AR densities are converted into 3 3 equivalent numbers of H disintegrations using a H standard curve (Fig. 8A) . These numbers are then decoded into the 3 14 correct amounts of H and C using an equation which relates the two isotopes on X-Cmat AR film. 3 14 Relationship of H to C on X-Cmat AR film. As shown in Fig. 8A, each density value lying within the calibrated response range of the X-Cmat AR film can be decoded into 3 14 disintegrations of either H or C. A density value of 100, 3 14 for example, decodes into 5,090 H disintegrations or 775 C disintegrations, and a density value of 200 decodes into 3 14 15,600 H disintegrations or 2,210 Y C disintegrations. It 3 follows, therefore, that a number of Y H disintegrations can 14 be equated t a different number of C disintegrations for each value of film density. In the. examples above, 5,090 . . 3 14 disintegrations of H are equal to 775 disintegrations of C with regard to their ability to darken X-Cmat AR film, and 3 14 15,600 H disintegrations are equivalent to 2,210 C disintegrations. 3 3 An equation which related H disintegrations ( H,. ) to 14 14 C disintegrations ( C,. ) is derived if X-Cmate AR film density (D-^ r is expressed as mathematical functions of the isotopes D XAE" f <W I" ** = f ( dis> . (2 > and the two functions are equated by elimination of the variable D^^. Both functions can be specifically defined by a non-linear regression procedure applied to the calibration strip data. However, this complicated procedure is avoided by linearizing the data and defining the functions by simple linear regression. As shown in Fig. 9, a plot of ^ D XAR^ " 14 vs * ^°^ disintegrations is approximately linear 3 14 for both H and C at density values ranging frcm 50 to 205. Calculation of the best-fit lines for these transformed data defines functions 1 and 2 as: By equating expression 3 and 4, an equation is derived which 3 ddiiirectly relates disintegrations of H to disintegrations of 14, C: (5) re-expressed The deviation from linearity seen in Fig. 9 affects the conversion by less than 6%, as shown in Table II. Calculating the isotopic content of a double-labeled gel. By 3 14 use of an equation relating to H to C, the isotopic content of any region of a double-labeled gel is calculated frcm the 14 images produced on X-Cmat AR and No-Screen films. The C content is calculated by converting No-Screen density values to C disintegrations and summing the disintegrations within 14 the selected area. This C total is divided by the exposure 14 time (min) of the No-Screen film to yield C dpm/gel area. Density values within the same area of the X-Cmat AR film are 3 converted to equivalent H disintegrations, summed and divided 3 by exposure time to yield equivalent H dpm/gel area. The 3 true H content is then calculated frcm this number by 14 subtracting the C content re-expressed (equation 5) as 3 equivalent H dpm/gel area. To test the method, additional calibration strips were 3 14 constructed which contained known mixtures of H and C per unit area. When exposed to the same X-Cmat AR films as the single-labeled strips, these double-labeled strips produced the density values shewn in Fig. 10A. As expected, X-Qmat AR film responded independently to both isotopes. When the level 14 of C was held constant, the film density rose with 3 . 3 increasing levels of H. Similarly, when the level of H was held constant, the film density rose with increasing levels of 14 C. Next, the radioactivity in each calibration strip band 3 was re-expressed H alone. Th s was accomplished by 14 converting the known disintegrations of C to equivalent 3 disintegrations of H (equation 5) and adding them to the 3 3 kncwn disintegrations of H. When these H totals, expressed as logarithms, were plotted against the corresponding density values (Fig. 3B) , the resulting curve was nearly identical to 3 the standard curve for H alone (Fig. 8A) . This finding 3 demonstrates that X-Cmat AR film responds to mixtures of H 14 and C in the same way that it responds to equivalent amounts 3 of H. Finally, the double-labeled calibration strips were exposed to the same No-Screen films as the single labeled stips. Using the method described above, the radioactivity contained in each band was calculated frcm the images produced on the -X-Cmat AR and No-Screen- films. As determined frcm 14 Table II, the calculations had errors of 4.0 ± 1.0% for C, 9.8 + 8.1% for 3 H, and 8.6 ± 10.0% for the 3 H 14 C ratio. Automatic analysis of double-labeled sample gels. Calculations for determining the isotopic content of double-labeled gels were computerized and further tested with 4 radiolabeled protein samples resolved electrophoretically within two-dimensional gels. Each sample was prepared by culturing embryonic chick duodena in medium cont ining both 3 14 H- and C-leucine and extracting the cytosolic proteins. Since the proteins within each sample were labeled with both , isotopes simultaneously, they all contained the same ratio of 3 14 H to C. This ratio was found to be 8.64 ± 0.09 by direct analysis. The computerized analysis of these sample gels could therefore be considered correct if a ratio of 8.64 was determined for each spot. Sequential exposure of the gels to X-Cmat AR and No-Screen films produced matching pairs of images like those 3 14 displayed in Fig. 11. Standard curves for H and C were calculated frcm the density values produced on these films by newly prepared calibration strips. The curves were similar to those shown in Fig. 8 and were entered into McIDAS III for decoding the images into isotopic disintegrations. Protein spots were located as previously described, within the entire gel image excepting the unresolved sections along the edges. Spots having density values greater than the calibrated film response ranges were automatically deleted, and those resulting frcm digitization artifacts (dust, scratches, etc.) were manually edited frcm memory. As shown in Table IV, the autcamatic analysis calculated the istopic content of 3 14 approximately 250 spots in each gel. The ratio of H: C within these spots averaged 8.07 to 9.03, closely agreeing with the experimentally determined ration of 8.64. The results of these tests demonstrate that the isotopic content of a double-labeled gel is accurately determined by use of the computerized process. This process, however, yields accurate data only when five experimental conditions 3 14 are met. First, the x-ray film responses to H and C, and 3 14 - the equation relating H to C on the X-Cmat AR film, must be determined for each set of films. The shapes of the X-Omat AR response curves change with small variations in preflashing conditions and exposure time (38) . Response curves for both types of film also vary with the concentrations of scintillator and acrylamide within the gels, the thickness of the gels, and the conditions of film exposure and development (21, 38, 42). Because of these variables, it'is difficult to reproduce the same response curves for different sets of films. Second, calibration strips and sample gels must be processed in identical fashion. Fluorography is reduced by increasing concentrations of acrylamide and protein stain (42, 43) , by incomplete saturation of the gel with scintillator, and by increasing thickness of the gel (21) . Consequently, calibration strips and sample gels must have the same thicknesses, contain the same acrylamide concentrations, and be fixed, stained, impregnated with scintillator and dried in identical fashion. Better accuracy is achieved when protein staining is avoided. If EKTHANCE is used, strips and gels should be dried for as short a time as possible and immediately exposed to X-Omat AR films to reduce the loss of the volatile fluor. Third, calibration stips and sample gels must contact the x-ray films with high pressure during exposure to maximize the efficiency with which the radioactive disintegrations darken the films. Sufficient pressure to maintain good contact is easily achieved by using steel pressure plates. Fourth, each set of films (X-Cmat AR or No-Screen) should undergo exposure and subsequent development as a single batch. This increases the reproducibility between films by controlling for temperature changes that affect exposure and development (44,45). Finally, exposures must be selected so that imageareas of interest have density values that lie within the calibrated response ranges of the films. This can be accomplished by adjusting the levels of radioactivity within the calibration strips to match the levels of radioactivity* contained by the sample, and then selecting appropriate exposure times. When a sample contains a complex mixture of proteins, it is unlikely that an exposure time can be selected which will be appropriate for every protein. With short exposures, radio-labeled proteins which are present in lesser amounts may produce no images at all. With longer exposures, these minor constitutents of the - protein mixture may produce detectable images while the major consituents saturate the film with isotopic disintegrations. In such cases, a comprehensive analysis of the protein mixture can only be accomplished by: 1) making a series of identical sample gels and exposing them to films for different lengths of time, or 2) making a series of gels which contain different amounts of the same sample and exposing all of than to films .for the same length of time. As shewn in Table III, the computerized process 14 calculated the C content of the double-labeled calibration 3 strips with greater accuracy than the H content. Calculated 14 C values differed from the known values by an average of 3 4.0 -. while calculated H values differed frcm the knewn values by an average of 9.8%. Preliminary research in this 4 1l,aboratory indicates that the higher error associated with 3. H calculations related to problems with fluorography. Irregularities in the gel surface, which frequently appear during drying, decrease the contact between the gel and film, and thereby decrease the efficiency with which radio-active disintegrations are recorded. Formation of these surface irregularities can be greatly reduced by the complete elimination of air bubbles between the gel's surface and the rigid polyurethane cover sheet after placing the gel on the dryer. Fluorography is also disrupted by the incomplete impregnation of sample gels with scintillator. Gels 3 14 containing a uniform mixture of H and C per unit area may produce slightly mottled images " on X-Omat AR film when impregnated with either ENHA CE or 2,5-diphenyloxazole (44) . This mottling is not apparent in images produced on No-Screen film by the same gels, indicating that the cause related to a heterogeneous distribution of scintillator within the gel. Although its exact cause is unknown, this mottling also 3 contributes to the error in the H calculations, and thereby 3 14 increases the variability of the H: C ratios calculated for protein spots in the double-labeled sample gels. The computerized process is designed to facilitate the comparison of complex protein mixtures. By rapidly 3 14 calculating H: C ratios for large numbers of protein spots contained in a double-labeled two-dimensional gel, it can aid an investigator in detecting differences between paired samples. Such differences are indicated by isotope ratios which differ significantly frcm a mean ratio calculated for all protein spots detected in a gel. As spot ratios within the test gels (Table IV) had coefficients of variation (standard deviation/mean) of approximately 25%, proteins whose sysnthesis rate is altered by 50% should be detectable at a significance level of 0.05%. This approach greatly facilitates the analysis of double-label studies that attempt to identify proteins biosynthesized in response to experimental manipulation. Direct exposure DEF-5 x-ray film, manufactured by Kodak may be used as a suitable replacement for No-Screen 2T x-ray film in double-label autoradiography. The No-Screen film is 14 more sensitive to C than X-Cmat AR film when both films are darkened by direct autoradiography. In addition to the isotopes employed, other ccmbinations that might be used are 3 35 75 35 H and S or Se and S. TABLE I Single-labeled calibration strips for determining x-ray film responses. Multibanded calibration strips were formed from acrylamide 3 14 solutions containing serially diluted H- or C-labeled proteins as described under "Materials and Methods." The radioactive content of these strips is shown here. Band Disintegrations per minute (dpm) x 10 /pixel a NO. 14 C strips H strips 1 1200 5800 2 600 2930 3 300 1480 4 149 744 5 74.5 375 6 37.2 189 7 18.6 95.3 8 9.3 48.1 9 0.0 0.0 ^ pixel is defined as a unit of area having dimension of 0.1 x 0.1 mm. I TABLE II 3 14 Accuracy of an equation relating H to C on X-Omat AR film. 3 14 An equation relating the abilities of H and C to darken X-Cmat AR film was derived frcm the linearized film responses. 14 By use of this equation, C disintegrations producing densities within the calibrated response range of the film are 3 converted to an equivalent number of H disintegrations with little error. Digitized Disintegrations/pixel/48 h Error 3 film density Kncwn H equivalent Kncwn 14, of 14, 'H 40 143 841 892 5.72 50 280 1730 1750 1.09 75 536 3470 3390 2.39 100 775 5150 5090 1.01 125 1010 6870 • • 6930 0.85 150 1290 8920 9120 2.26 175 1670 11700 11900 0.02 200 2210 15800 15500 1.91 Calculated as ( 3 H equivalent of 14 C) /Known 3 E - 1 x 100% TABLE III The kncwn and calculated isotopic contents of double-labeled calibration strips. Double-labeled calibration strips composed of 9 polyacrylamide bands were exposed to X-Cmat AR film for 48 h at -70°C, and to 3 14 No-Screen film for 10 d at 22°C. The H and C contained in each band was calculated frcm the film images by reference to 14 3 3 14 standard curves. Calculated values for C, H and the H: C ratio are displayed here alongside the kncwn values. 3 14 Band Disintegrations per minute x H: C ratio 10 - '/pixel No. Calculated Known Calculated Known Calculated Known 14 C 14 C 3 H 3 H 1 83.3 86.8 747 604 8.97 6.96 2 83.3 86.8 1220 1210 14.6 13.9 3 83.3 86.8 2200 2430 26.4 • 28.0 4 164 169 1400 1210 8.54 7.16 5 164 169 2280 2430. 13.9 14.4 6 164 169 4650 4860 28.4 28.8 7 347 329 2500 2430 . 7.20 7.39 8 347 329 4060 4860 11.7 14.8 9 0 0 0 0 — — TABLE IV Summary of the automatic analysis of double-labeled sample gels. 3 14 Gel Spots Ratio of H: C spots (x ± S.D.) 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Claims: Claims 1. A method of locating protein spots in an electrophoresis gel and detecting the boundaries of said spots, said method comprising: (a) dividing the area of X-ray film which has been exposed to the gel into a plurality of small area pixels; (b) scanning and digitizing the optical density of the film containing a record of the protein spots and storing the digitized image as a set of pixel numbers in a first storage means; (c) calculating the optical density gradients of each pixel and storing the resulting set of pixel gradient numbers in a second storage means; (d) identifying the center of each protein spot in the image by: (i) scanning the set of pixel gradient numbers and locating those pixels in which the gradient number exceeds a first threshold which indicates that the pixel is within a protein spot; (ii) using pixels which have a gradient number exceeding the first threshold as a center, scanning the density gradients of surrounding pixels until the pixel of greatest density is found and repeating the scanning of surround¬ ing pixels using that pixel as the center until the center pixel of greatest density is found; (iii) storing the center pixel locations in a third storage means; (iv) calculating the density gradient of pixels in a plurality of directions radially outward frcm each center pixel; and (v) storing as a set of boundary locations in a fourth storage means the position of each pixel which has a density gradient which drops below a second threshold which indicates that the spot ends within the area of said pixel. 2. A method for determining gene expression by comparative electrophoretic analysis which comprises incubating control cells in radioactively labeled amino acids wherein the radioactive label is characterized by strong radiation emission incubating experimental cells in radioactively labeled amino acids wherein the radioactive label is character¬ ized by weak radiation emission mixing the cells solulizing the mixed cells subjecting the solubilized cells to two-dimensional gel electrophoresis impregnating the electrophoretic gel with a fluor exposing the thus impregnated gel to a first film which is sensitive to both the weak and strong radiation exposing the thus impregnated gel to a second film which is sensitive only to the strong radiation accurately aligning the films in superposition detecting the radiolabeled protein spots in accordance with the procedure of claim 1 and computing the amount and ratio of the radiolabels (isotopes) in each spot whereby the particular genes expressed or suppressed in the experimental cells can be identified. 3. The method of claim 2 wherein the strong radiation 14 3 emitter is C and the weak radiation emitter is H. 4. The method of claim 3 wherein the strong radiation 35 3 emitter is S and the weak radiation emitter is H. 5. The method of claim 3 wherein the strong radiation 75 35 emitter is Se and the weak radiation emitter is S. 6. A method for diagnosing a disease in a patient which is characterized by changes in protein biosynthesis which comprises taking a skin biopsy of the patient culturing the fibroblasts frcm said skin 3 incubating said fibroblasts in H leucine 14 incubating fibroblasts from a normal subject in C leucine 14 3 mixing the resulting C and H labeled cells subjecting the mixed cells to two-dimensional electrophoresis impregnating the electrophoretic gel with a fluor exposing the thus impregnated gel to a first film which is sensitive to both the weak and strong radiation exposing the thus impregnated gel to a second film which is sensitive only to the strong radiation accurately aligning the films in superposition detecting the radiolabeled protein spots in accordance with the procedure of claim 1 and computing the amount and ratio of the radiolabels (isotopes) in each spot whereby alterations in protein biosynthesis associated with certain disease states can be identified.

Inventors: BISHOP CHARLES W, DELUCA HECTOR F, KENDRICK NANCY C, SANTEK DAVID A, BISHOP, CHARLES, W., DELUCA, HECTOR, F., KENDRICK, NANCY, C., SANTEK, DAVID, A.
Applicants: WISCONSIN ALUMNI RES FOUND, WISCONSIN ALUMNI RESEARCH FOUNDATION
Application year: 1986
Main classification: G01N27
IPC codes: C12Q1, G01N27, G01N33