Microcomputer-assisted densitometer for quantitative receptor autoradiography

Journal of Neuros~'ience Methods, 13 (1985) 171 - 181

171

Elsevier NSM 00478

Research Papers

Microcomputer-assisted densitometer for quantitative receptor autoradiography David J. Berck and Thomas C. Rainbow Department of Pharmacology/G3, Unieers'iO" of Penn,~vh,ania, Philadelphia. P A 19104 ( U.S.A. (Received August 16th, 1,984) (Revised J a n u a ~ 30th, 1985) (Accepted February 10th, 1985)

Key words: quantitative autoradiography - LKB uhrofilm

receptor

densitometry

microcomputer

We describe here a simple, inexpensive microcomputer-assisted densitometer for use with quantitative receptor autoradiography. The resolution of this system is approximately 100 ~m. With this system, and an accompaning program DENS1T, it is relatively easy to convert density values of autoradiograms into molar quantities of bound ligand. The general design of the system and the logic of the DENSIT program are applicable to a variety of hardware systems.

Introduction

The recent development of a quantitative autoradiographic method for measuring receptors and binding sites in brain tissue (Quirion et al., 1981; Rainbow et al., 1982; Unnerstall et al., 1982; Pan et al., 1983) brings with it the need for a simple way to quantify autoradiograms. We describe here an inexpensive microcomputerbased densitometer, and an accompanying program DENSIT, designed to convert optical density values of receptor autoradiograms into molar quantities of bound ligand. We also give flow charts of the program DENSIT. When interpreted in a computer language, this program could be adapted to almost any microcomputer or computerized image analysis system.

Materials and Methods

Microcomputer-assisted densitometer Our system consists of a Bausch and Lomb Tri-Simplex Microprojector (Bausch and Lomb, Rochester, NY); an Analog Peripheral EI-100 Analog-to-Digital Converter with an attached, custom-built photocell (Cambridge Development LaboratoCorrespondence." D.J. Berck, P.O. Box 2213, Yale Station New Haven, CT 06520, U.S.A. (Reprints not available.) 0165-0270/85/$03.30 :"; 1985 Elsevier Science Publishers B.V. (Biomedical Division)

172

ries, Watertown~ MA): and an ATARI 800 microcomputer (ATARi, Sunnyvale, ('A! with accompanying dot-matrix printer, TV monitor and single-density floppy disk drive. The cost of this equipment is roughly $2000. Any TV may be hooked in through the switch box provided with the microcomputer, Any ATARI disk drive and printer may be hooked in through the interface. The Analog Peripheral A / I ) converter and the attached photocell will work with any microcomputer that has an RS-232 serial communications port. A number of commercially manufactured photocells are now available which will plug into the analog peripheral A / I ) converter. Tritium-sensitive sheetfilm (LKB Ultrofilm grain size 1.8/~m ± 0.3 ~Lm) autoradiograms prepared as described (Rainbow et al., 1982) are quantified by first being cut into strips and taped onto glass 3 × lin. microscope slides. The slide is then placed on the stage of the microprojector and the autoradiographic image is projected onto a sheet of white paper taped to a 33 cm 2 platform 15 cm in height. Nissl-stained tissue sections can be co-projected for verification of anatomical structures. The photocell is located below a 1 mm aperture in the center of the platform. The incident light from the Tri-Simplex projector is not spatially uniform so different portions of the image are quantified by moving the autoradiogram rather than by moving the photocell. A removable microscope stage (Edmund Scientific, Barrington, N J) is attached to the Tri-Simplex projector to manipulate manually autoradiograms mounted to slides. The intensity of light from the Tri-Simplex Projector is regulated by a variable transformer (Powerstat, Superior Electric, Bristol, CT). Autoradiograms are analyzed at a magnification of 10 × . corresponding to an anatomical resolution of 100/~m. This system allows easy identification of all nuclei and subregions of rat brain in any standard neuroanatomical atlas. Higher magnifications on the Tri-Simplex projector decrease by 50% or more the intensity of the light reaching the photocell. The amount of incident light transmitted by the autoradiogram is measured with the photocell. The voltage generated by the detected light is amplified by the Analog Peripheral and converted into an 8 bit digital number, ranging from 0-255. Four to eight readings are taken per structure bilaterally. These numbers are relayed to the ATARI computer via an RS-232 serial port at 300 baud, and averaged to provide a single density value for each individual structure.

DENSIT program

In the language of computerized image processing, the 8 bit representation of the photocell voltage is called a grey level (Castteman, 1979). This is a measure of the amount of transmitted light and is inversely related to the density of the autoradiogram. For analyzing autoradiograms, we define a term called relative density (RD), which is the reciprocal of the grey level of the brain structure (GL) minus the reciprocal of the grey level of the film background (FB), so that RD = 1 / G L - 1/FB. We use relative densities in place of optical densities [defined as log(GL of incident l i g h t / G L of transmitted light)] because they are slightly more accurate when used in conjunction with radiolabeled standards to convert grey levels into the concentration

173

of applied radioactivity (Rainbow et al., 1984a). It also corrects for the contribution of film background to the grey level of the autoradiogram. To convert RDs into the concentration of applied radioactivity (Curies/rag protein), we construct a standard curve of known amounts of radioactivity (X) in brain-mash plotted against the RDs they produce (Y). Because film responds to radioactivity in a logarithmic fashion, plotting ln(X) against In(Y) transforms this relationship from a curve to a straight line of the form, Y = mX + b, where m is the slope, b is the y-intercept and In is the natural log function (Unnerstall et al., 1982; Pan et al., 1983; Rainbow et al., 1984a). Doing a least-squares linear regression on the ordered pairs (ln(X), ln(Y)) gives m and b. Thus, using the slope and intercept from the standard curve, we can take the natural logarithm of any RD from a brain autoradiogram, substitute it into the equation Y = mX + b, solve for X, take its inverse-log (X = eXt and obtain the concentration of radioactivity that would have produced that RD. Dividing this in turn by the specific radioactivity of the radioligand used to make the autoradiogram (expressed in Curies/mmol) gives the molar concentration of bound ligand in that brain region. D E N S I T has two parts. The first part is a program that does a In In linear regression on values generated by brain-mash standards to obtain a slope and a Y-intercept. The second part is a program that uses the previously calculated slopes and intercepts to convert grey levels of autoradiograms into molar quantities. Both programs use a common subroutine to fetch grey levels from the photocell, display them on the TV monitor, and then average them when the user has finished taking readings. In our version of DENSIT, the current grey level of the autoradiogram is always displayed. If the user wants to accept this reading, he can press any key on the computer's keyboard. This "freezes" the value on the screen, transferring it to a variable that keeps a running average of the collected grey levels. The screen then displays the current grey level from the photocell. To take readings from a different radiolabeled standard or brain structure, the user presses the spacebar of the computer keyboard. The program then averages all the collected grey values, transfers that to the appropriate variable for that brain structure or standard and clears the running average variable for use with the next group of readings. The subroutine that retrieves grey levels from the photocell will be specific to the microprocessor of the computer. In our ATARl-based version of DENSIT, this subroutine involves several ATARI-specific commands to access the RS-232 serial port and to monitor the keyboard. For instance, decimal location 764 in the ATAR1 computer stores the ASCII value of the last key that was pressed. The program will check the contents of memory location 764 to determine if the spacebar has been pressed (ASCII value 33). If it has, then the program averages the collected grey levels and exits the subroutine, returning the averaged value to either one of the main programs. If it has not, the subroutine continues to take readings. With machine-specific modifications to access the RS-232 port and to monitor the appropriate memory location that watches the keyboard, this subroutine would work on any microcomputer that runs BASIC. The flow chart for program 1, the standards program, is given in Fig. 1. The user is first prompted to obtain the grey level of film background. This value is returned

174

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175

from the subroutine and its reciprocal is stored in the variable FLMBAK. This is subtracted from the grey levels of the standards to obtain relative densities. The program then prompts the user to enter the specific radioactivity of the radiolabeled brain-mash standards, expressed in n C i / m g protein. These standards are constructed and calibraIed as previously described (Unnerstall et al., 1982, Pan et al., 1983, Rainbow et al., 1984a). The specific radioactivity of the first standard is stored in the array RELDNS. The arrays for both R E L D N S and CONC can hold as many values as the computer's memory will accommodate, though in practice, we use no more than 8 standards. The program repeats this process until values for all the standards have been entered, which in our version of DENSIT, the user signals by pressing the "0" key of the computer. Now, the program does a In-In linear regression on the R E L D N S and CONC arrays to obtain the slope and the intercept. The general formulas for this are: SUM(X'Y) - (SUM(X)*SUM(Y)/N) nl-

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The program then returns to the user the calculated slope and Y-intercept for use with the second program. The flow chart of program 2 is shown in Fig. 2. It is designed to convert relative density readings of brain structures into molar concentration of specifically bound ligand. The user is asked to input the slope and Y-intercept of the standard curve, along with the specific radioactivity of the radioligand used to produce the autoradiogram. He then establishes a list of up to 25 brain structures to analyze, The user is then prompted to take a reading of film background, which is stored in the variable F L M B A K (for the sake of simplicity, we assume that film background density is uniform for all autoradiograms of a single session of analysis). The user must then take readings of total binding for each structure. The relative density of total binding is stored in the array RELDNS. Next, the program calculates the

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177

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molar concentration of total binding, using the slope and intercept of the standard curve and the specific radioactivity of the radioligand. The general formula for this is: Biochemical value = 1000*(EX P((In(RD)-INTRCP)/SLOPE)/SPECAC) where EXP i's the inverse natural log function, e x and SPECAC is the specific radioactivity of the radioligand, in Ci/mmol. We multiply by 1000 to convert n C i / m g P into p C i / m g P, so that the molar concentration is expressed in fmot. It is important to check whether RD_< 0 before calculating ln(RD) because ln(0) is negative infinity. If RD _< 0, the program will make the total binding equal 0. The user is then asked if he wishes to correct his readings for non-specific binding. If the answer is no, then the program will subtract zero from all total readings. If the answer is yes, then the user is further asked if his non-specific binding is anatomically uniform and can be represented by a single grey level. For some radioligands, we have found that the definition of non-specific binding varies among brain regions (e.g. Rainbow et al, 1984b). If there is homogeneous non-specific binding, the user is then prompted to read the grey level for the non-specific. The program will then store the relative density value of the non-specific binding in the array variable NSRLDN. The program then calculates the molar concentration of non-specific binding, and stores the value in the variable array NSFMMG. If the non-specific binding happens to be the same or less than film background, the program assigns it a value of zero. The program then calculates the specific binding for each structure by subtracting non-specific binding from the total binding. If the user feels that the non-specific binding is anatomically heterogeneous, then the program will prompt him to obtain separate non-specific readings of each structure, and then calculate relative density. The program will then calculate the molar concentration of the non-specific for each structure and store it in the variable array NSFMMG. If the relative density for any non-specific is less than or equal to zero, the program assigns N S F M M G for that structure the value zero. Then, the program calculates the specific binding just as it would if non-specific binding were anatomically homogeneous. Finally, the program prints the molar concentration of total binding, relative density of total binding, molar concentration of non-specific binding, relative density of non-specific binding, and molar concentration of specific binding of each brain structure in tabular form.

Results

Reproducibility of values We tested the reliability of the system by re-reading autoradiograms and comparing the values obtained within the same day and on different days. The autoradiograms were either made with [3H]prazosin which labels the a I subtype of the adrenergic receptor (Rainbow and Biegon, 1983) or with [3H]QNB which labels

179

muscarinic cholinergic receptors (Rainbow et al., 1982). Autoradiograms produced with [3H]prazosin are less than half as dense as those made with [3H]QNB, so this allowed us to test the accuracy of the system at two levels of optical density. For 5 trials within the same day, the standard error of the readings was roughly 1% of the mean for [3H]QNB autoradiograms and 2-3% of the mean for [3H]prazosin autoradiograms. A comparable degree of accuracy was observed between readings taken on different days in which the densitometer was turned off and on each time (Table 1). In all cases, we first 'zeroed' the Tri-Simplex projector by using the variable transformer to adjust the incident light to a grey level slight below 255. These results indicate that when light intensity is kept constant, our microcomputer-assisted densitometer gives acceptably reproducible reasurements of receptor concentration, with slightly greater accuracy at higher optical densities.

Effects of background illumination We house our microcomputer-assisted densitometer in a converted closet. To assess the effects of background illumination on our readings, we compared measurements taken in total darkness with readings taken under ambient room light. We also examined a third illumination condition in which the overhead light in the closet was turned off, but ambient light from an adjacent room was allowed to enter through the doorway. We found no difference in readings taken in total darkness as

TABLE 1 R E P R O D U C I B I L I T Y OF D E N S I T O M E T R I C M E A S U R E M E N T S Results are m e a n s + S.E.M. for 15 separate readings of a single [3H]QNB autoradiogram prepared as described in Rainbow et al. (1982) and of a single [3H]prazosin autoradiogram prepared as described in Rainbow and Biegon (1983). Readings were taken over a 3-day interval. %Error is defined as ( S . E . M . / m e a n ) × 100. Structure

fmol/mg P

%Error

4 620.5 +_60.1 2 814.7 + 22.9

1.42 0.81

1 508.1 _+ 9.6

0.64

215.9 + 8.0

3.70

753.5 + l l . 6

1.54

283.2+_ 6.3

2.22

221.7 + 5.0

2.26

744.0 + 11).2

1.37

[ ¢H]QNB Caudate-putamen Parietal cortex Layers I-II Parietal cortex Layer V

[ ~H]prazosin Dentate gyrus Molecular layer Mediodorsal N. Thalamus Ventromedial N. Hypothalamus Parietal cortex Layers 11 IV Parietal cortex Layer V

1g0

compared to the partial illumination of the third condition. However. direct ovc~~ head illumination decreased measurements by roughly 30%,. This indicated that it was necessary to shield the densitometer from direct overhead light to take readings. though indirect ambient light that does not reach the photocell does not appear ~,, affect the measurements.

Discussion Our microcomputer-based densitometer with the companion program DENSIT is a useful alternative to expensive, dedicated densitometers and the tedium of manual densitometry. The general design of the system--interfacing a photocell to a microcomputer and using a histology projector or film enlarger to project autoradiograms-- is applicable to a wide variety of hardware systems. A similar system using a Z80-based microprocessor has been described (Dauth et al., 1981) as well as an microprocessor-based densitometer system for scanning gels (Widdoss et al., 1978). The logic of the DENSIT program and the specific algorithms used to quantify receptor concentration are also applicable to a variety of hardware systems. We have recently rewritten the program in the 'C' computer language and adapted it for use on an IBM Personal Computer-based image processing system (Kruglinski and Rainbow, unpublished). It is important to realize that even computerized image-processing systems require manual sampling of brain regions for densitometric analysis (Goochee et al., 1980: Gallistel et al., 1982). With present techniques of computerized image processing, it is relatively easy to digitize the vast amount of information contained in a brain receptor autoradiogram. However, it is still difficult to extract this information in a comprehensible form. One approach is to publish pseudocolor maps of receptor concentrations with accompanying color scales (Altair et al., 1984). Even if the page charges for color prints were reduced to facilitate the routine publication of such maps, it is still awkward to use them to accurately present receptor concentrations in specific brain regions. Usually, they are accompanied by tables of brain structures with appropriate f m o l / m g values (Altair et al., 1984; Whitehouse et al., 1983), necessitating the use of microdensitometry and some equivalent of the DENSIT program.

Acknowledgements Supported by NS19597, NS20006, Sloan and Klingenstein fellowships. TCR was an Established Investigator of the American Heart Association. We thank Drs. Scott Manaker, David Robinson, and Barry Wolfe for helpful comments in the design of the DENSIT program and the preparation of this manuscript.

181

References Altair, C.A., Walter, R.J., Jr., Neve, K.A. and Marshall, J.F. (1984) Computer-assisted video analysis of [~H]spiroperidol binding autoradiograms, J. Neurosci. Meth., 10:173 188. Castelmam K.R. (1979) Digital Image Processing, Prentice-Hall, Englewood Cliffs, NJ. Dauth, G.W., Frey, K.A. and Gilman, S. (1981) A low cost microcomputer based densitometer system for quantitative autoradiography, Soc. Neurosci. Abstr., 7: 501. Gallistel, ('.R., Piner, C.T., Allen, T.O., Adler, N.T., Yadin, E. and Negin, M. (1982) Computer assisted analysis of 2-DG autoradiograms, Neurosci. Biobehav. Rev., 6: 409-420. Goochee, C., Rasband, W. and Sokoloff, L. (1980) Computerized densitometrv and color coding of [lac]deoxyglucose autoradiographs, Ann. Neurol., 7:359 370. Pan, H.S., Frey. K.A., Young, A.B. and Penney, J.B., Jr. (1983) Changes in [~H]muscimol binding in substantia nigra, entopeduncular nucleus, globus pallidus and thalamus after striatal lesions as demonstrated by quantitative receptor autoradiography, J. Neurosci., 3:1189-1198. Quirion, R., Hammer, R.P., Jr., Herkenham, M. and Pert, C.B. (1981) Phencyclidine (angel dust) a "Opiate' receptors: Visualization by tritium-sensitive film. Proc. nat. Acad. Sci. U.S.A., 78:5881 5885. Rainbow, T.C. and Biegon, A. (1983) Quantitative autoradiography of [3H]prazosin binding sites in rat forebrain, Neurosci. Lett., 40:221 226. Rainbow, T.C., Bleisch, W.V., Biegon, A. and McEwen, B.S. (1982) Quantitative densitometry of neurotransmitter receptors, J. Neurosci. Meth., 5:127 138. Rainbow, T.C., Biegon, A. and Berck, D.J. (1984a), Quantitative receptor autoradiography with tritiumlabeled ligands: Comparison of biochemical and densitoraetric measurements, J, Neurnsci. Meth., 11 : 231 241. Rainbow, T,C., Parsons, B. and Wolfe, B.B. (1984b) Quantitative autoradiography of B-1 and B-2 receptors in rat brain. Proc. nat. Acad. Sci. U.S.A., 81:1585 1589. Unnerstall, J.R., Niehoff, D.L., Kuhar, M.J. and Palacios, J.M. (1982) Quantitative receptor autoradiography using [-~H]Ultrofilm: application to multiple benzodiazepine receptors, J. Neurosci. Meth., 6: 59-73. Whitehouse, P.J., Wamsley, J.K., Zarbin, M.A., Price, D.L., Tourtellotte, W.W. and Kuhar, M.J. (1983l Amyotrophic lateral sclerosis: Alterations in neurotransmitter receptors, Ann. Neurol., 14:8 16. Widdoss, A.S. and Ferris, C.D. (1978) A microprocessor-based scanning densitometer, Biomed. Sci. lnstrum., 14: 115-119.