Quantitative X-ray mapping biological cryosections

Ultramicroscopy 24 (1988) 237-250 North-Holland, Amsterdam

237

QUANTITATIVE X-RAY MAPPING OF BIOLOGICAL CRYOSECTIONS C.E. FIORI, R.D. LEAPMAN and C.R. SWYT Biomedical Engineering and Instrumentation Branch, DRS, National Institutes of Health, Bethesda, Maryland 20892, USA

and S.B. ANDREWS Laboratory of Neurobiology, NINCDS, National Institutes of Health, Bethesda, Ma~land 20892, USA Work presented August 1986; manuscril~t received 22 June 1987

The potential for applying X-ray mapping to the elemental microanalysis of biological cryosections is discussed. Methods are described for acquiring and processing data, including use of the top-hat digital filter to remove the average effects of the background contribution. Practical considerations for X-ray mapping are discussed in terms of typical counts per pixel and minimum detectability which depends on the number of pixels chosen to integrate the signal. These aspects are illustrated with elemental maps (Na, P, K, Ca and Fe) from freeze-dried cryosections of mouse cerebellar cortex. A calcium sensitivity in the range 0.5 to 2.5 mmol/kg wet weight of tissue is demonstrated. The correction for overlap of potassium K/] and calcium Ka is demonstrated with X-ray maps from cry.osectioned synaptosomes of squid optic lobe. Quantitative results obtained using internal standards to determine wet weight concentrations are in reasonable agreement with expected values. Alternate schemes applicable to X-ray maps for determining the dry mass concentration, such as the peak/continuum (Hall method), are also discussed.

1. Introduction

X-ray microanalysis in the analytical electron microscope (AEM) is now established as a valuable tool in cell physiology and cell biology, capable of providing direct information about the distributions of ions and bound atomic species at the subcellular level [1-7]. It is feasible not only to obtain energy-dispersive X-ray spectra (EDS) from individual points in a sample but also to obtain quantitative two-dimensional X-ray maps showing elemental distributions over extended areas of a sample [5,8-15]. This advance is important in that it allows the overall composition of cells and tissues to be examined, it provides for unbiased sampling, and it permits correlations between elemental distributions and morphology. The purpose of this paper is to discuss the potential and limitations for applying X-ray map-

ping in biology. We make special reference to ultrathin cryosections because these are generally recognized as the only preparations currently capable of yielding quantitative information about diffusible ions at the subcellular level, and are also preferable for quantitation of non-diffusible elements. We begin by making some general observations about X-ray images and by discussing methodologies for data analysis. Then we shall describe some details of our experimental procedures and instrumentation. Lastly, some recent results from the application of X-ray mapping to cellular neurobiology will be presented to illustrate the status of four areas of concern: (i) typical counting rates encountered in the AEM, (ii) sensitivity in terms of minimum detectable concentrations as a function of object size, (iii) the specific problem of potassium-calcium overlap, and (iv) methods for quantitation.

0304-3991/88/$03.50 © Elsevier Science Publishers B.V. (North-Holland Physics Publishing Division)

238

C.E. Fiori et aL / Quantitatiee X-ray mapping of biological cryosections

2. Elemental mapping 2.1. Data processing In the usual procedure of forming an X-ray image with an energy-dispersive spectrometer system, two channels of the multichannel analyzer which are on each side of a characteristic peak are defined as energy limits. The channels usually chosen have slightly fewer than one-half the number of counts in the peak channel, as this energy span provides the highest signal-to-noise ( S / N ) ratio. The electron beam is scanned over the face of the recording oscilloscope in synchrony with the beam over the specimen surface. Whenever an X-ray is detected and its resulting energy (voltage) pulse falls between the limits specified by the above channels a single pulse is sent to the display CRT to form a single "dot" of light. The dots comprising the image can be stored photographically, each dot saturating the film. Since the usual photographic film is capable of displaying many shades of gray, the dot map technique considerably underuses the capability of the film. Any X-ray photon within the energy range of interest, whether a characteristic or continuum X-ray from the specimen, or continuum from a grid bar of the specimen holder, is processed because there is no way to distinguish between sources. Variations in the X-ray production and hence in the analyte concentration can only be deduced from variation in the spatial distribution of the dots. Quantitation utilizing X-ray data recorded as dot maps is difficult at best. For example, it would be impossible to perform the algebraic operations required in the Hall [1] procedure. It is possible, however, to produce quantitative data with continuous scanning of the electron beam by storing the line and frame coordinates and the energy of each recorded X-ray [16]. The data from selected coordinates or clusters of coordinates (that do not have to be contiguous) can then be sorted into an ,2-ray spectrum that can be analyzed by any applicable algorithm. An alternative to continuous beam rastering is discrete rastering accomplished with what is usually called a digital scan generator. In this technique the x and y velocity components of the

synchronous electron beams are zero for a finite period of time and then the beam is instantaneously stepped to the next point. The displacements in the line (x) and frame (y) directions are equal. Each data point in the image, acquired while the beam is stationary, is called a pixel. For X-ray imaging purposes it is common to have between 128 and 512 pixels along the line and the same number of lines in the frame. Data accumulated with discrete rastering is conveniently stored in the digital computer. Since the area on the specimen surface is scanned point by point, in a two-dimensional array, the pulses generated during each dwell time can be counted and the value of the count stored in a corresponding array element in computer memory. With appropriate electronic circuitry the counts in this array can be displayed at the corresponding coordinates on a CRT with the brightness at each pointproportional to the number of counts. We will call such a display an X-ray intensity map to distinguish it from the X-ray dot map. An intensity map can fully utilize the gray scale of photographic film. But more important, such an image can be mathematically manipulated. For example, when an X-ray image is proUuced using an energy-dispersive spectrometer (EDS) in an analytical electron microscope a potentially serious artifact occurs if the peak-to-background ratio is low. Background removal from such an intensity map is possible, and the purpose of the next section is to discuss this artifact and describe a procedure to reduce its effect to a negligible level.

2.2. Background remot~al When the height of a characteristic peak in an X-ray spectrum is in the same order as the height cff t h e e n n t l n t n u t r n n ! l h o ~ a r n o o n o r o v

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that the contrast of the resulting X-ray image i~s as much a function of the continuum generation as it is of the desired characteristic X-ray generation. Consequently, a serious artifact can result which, in the worst case, manifests itself as a high-contrast X-ray image of an element which is not even present in the specimen. For "thin" specimens in the analytical electron mic~oscope the contrast

C E. Fiori et a t / Quantitative X-ray m a p p i n g of biological co'osections

mechanism of this artifact is due to mass-thickness changes of the specimen over the imaged area. With discrete rastering and the digital computer to store and process the data, it is possible to produce an X-ray intensity map with the contribution of the background removed at each pixel. Procedures that accomplish removal of the continuum contribution from images are the same as those applicable to EDS spectra [17]; they can be classified as either modeling or filtering. Background modeling consists of measuring a continuum energy distribution or calculating it from first principles and combining this with a mathematical description of the detector response function. The resulting function is then used to calculate an average background spectrum that can be subtracted from the observed spectral distribution. Background filtering as commonly used in the field of X-ray microanalysis ignores the physics of X-ray production, emission and detection; the background is viewed as an undesirable signal to be removed by modification of the frequency distribution of the spectrum by filtering. A method that does not require an explic;t model is more flexible and is clearly advantageous for applications such as imaging of irregular specimens and for applications in the analytical electron microscope operating with beam energy above 50 keV. In the latter case one can, in principle, calculate specimen continuum from a model. However, in practice the calculated continuum rarely accounts for the background since a significant proportion originates not from the specimen but from bulk sources such as the specimen support or holder. A simple and elegant filtering algorithm, first applied to energy-dispersive X-ray spectra by Schamber [18], is the top-hat digital filter. Calculations can be performed by a computer at every pixel within the pixel dwell time. Counts in a group of adjacent channels of a spectrum are "averaged" and the "average" assigned to the center channel of the group: the procedure is repeated at each channel of that part of the spectrum from which we wish to remove the continuum. One may describe the averaging by the following equation, using the notation of Statham [19]:

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where 3~' is the contents of the i th channel of the filtered spectrum and )) is the contents of the j t h channel of the original spectrum. The filter is divided into three sections: a positive central section consisting of 2M + 1 channels centered in turn at each channel in the region of interest, and two side sections each containing N channels. The average of the counts in the side sections is subtracted from the average in the central section. The effect of this particular averaging procedure is as follows: if the original spectrum is curved concave upward across the width of the filter centered on a particular channel, the average will be negative: if the curvature is convex the result is positive. The greater the curvature, the larger the value. In order for the filter to respond with the greatest measure to the curvature in spectral peaks, and with the least measure to the curvature i a the spectral background, the width of the filter must be carefully chosen. For a detailed treatment of the subject see Statham [19] and Schamber [20]. In general, the width of the filter for any given spectrometer system is chosen to be twice the full width at half the peak maximum amplitude (FWHM) of the Mn K a peak, with the number of channels in the central section equal to, or slightly more than, the combined number of channels in the side sections. A Pascal language procedure optimized for speed, based on eq. (1), is included as an appendix. The final step in the application of the digital filter is to extract a quantity: which will be as.q~r.,,-~.~A

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sent the characteristic intensity. We choose the sum of the counts in the central (positive) section. 3. Overlap corrections

There is a simple method related to spectral peak stripping that can be used in certain cases to remove from an image the average effect of peak

240

C E . Fiori et ai. / Quantitatiee X-ray m a p p i n g o f biological crvosections

3.5

3.6

:3.7 3.8 ENERGY (keV)

3.9

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Fig. 1. Digitally filtered, computer-generated, spectrum from hypothetical pure potassium at energies in the vicinity of the calcium K a peak. The digitally filtered calcium K a is also shown for reference. Note that positive and negative contributions nearly cancel (see text).

•;t, the positive central lobe of of the calcium Ka. if the width of the digital filter is correctly chosen it is possible to obtain nearly total suppression of the K / C a overlap. It must be emphasized that the filter width that optimally suppresses the K / C a overlap is not ideal for other overlaps. For example, the 140 eV central lobe filter illustrated in fig. 1 leaves a -1.5% potassium contribution in the calcium peak, but results in a - 4 % phosphorus contribution to the central lobe of sulfur. A stripping-type correction could easily be applied for such residual effects, lqnally, it must be remembered that an overlap correction removes only the average effect of the overlap and not the statistical effects.

3. Practical considerations

3.1. A data acquisition system for X-ray mapping overlap. This peak overlap results, for example, in a "calcium" image that is really formed from calcium K a plus potassium Kfl X-rays. Tbe method .requires background- and deadtime-corrected nominal K a images for both elements. For the potassium Kfl/calcium K a overlap the measured intensity ratio of the potassium Kfl to the potassium K a peak is used for the correction. Since the usual biological target satisfies the thin film criteria [21]. the observed ratio will not vary over the imaged area. Therefore, each pixel value in the potassium K a image can be multiplied by the measured ratio and the result subtracted from the C a / K overlap image. In the case of a K a / K a overlap the simplest strategy is to choose the imaging windows to avoid the overlap areas. An alternative procedure for digitally filtered images is cussed next, e.gain illustrated by the biologically important case of the potassium K f l / c a l c i u m K a overlap. Fia

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Elemental images were obtained using a Hitachi H700H transmission electron microscope equipped with a scanning transmission (STEM) unit. The microscope was operated with a conventional tungsten filament source and a beam voltage of !00 keV. Freeze-dried cryosections were analyzed in a Gatan 626 low temperature sample holder either at room temperature or at - 1 0 0 o C. X-rays emitted by the salnple were detected with a 30 mm 2 side-looking Tracor Northern Si(Li) spectrometer with a 7.6 /.tm beryllium window. The spectrometer diode was located 13 mm from the specimen. Pulses could be routed either to a stand-alone Tracor Northern 5500 Analyzer system for point analysis or to a Kevex 7000 analyzer system connected to our laboratory minicomputer for elemental mapping a n d / o r point analysis. X-ray images were recorded using a digitally controlled data acquisition system, designed and k,l~lt IJUllt

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[9-12,17]. The fo!lowing summarizes briefly the most important features of this system, ,4, dedicated satellite computer (DEC LSI 1i/"23) conirols the x-v position of the STEM probe and also a timer and gate which allow EDS acquisition to proceed for a given live-time interval at each pixel. To begin the image acquisition, programs

C.E. Fiort et al. / Quantitatwe X-ray map,~,,,g of biological co.osections

are downloaded from the host computer (DEC PDP 11/60) connected to the satellite by direct memory access. A digitally defined raster, containing as many as 512 x 512 pixels, produces the image serially. The Kevex 7000 system is interfaced directly to the host computer. At the appropriate time, spectral data collected at one pixel are read from the Kevex 7000 into the host where they are processed dynamically by applying the digital filter described above. The results of the computation are stored on disk for later access when the image is completed. Elemental maps may be viewed and analyzed by means of a DeAnza IP6400 image display system containing four 5 1 2 x 512 x 8 bit memory planes and an array processor. Basic image processing software, as described previously [9-11], is capable of performing operations such as smoothing, and forming intensity histograms. 3.2. Counts per pi."el: limitations and typical t,alues Typically we are interested in obtaining information from a pixel array of size 128 x 128 to 256 x 256. Thus it is immediately apparent that the signal per pixel in an X-ray map is very low because the dwell time per pixel is necessarily limited. Reasonable image acquisition times range from 30 min to several hours; this fimit depends on the stability of the sample in terms of drift and radiation damage, and also on the patience of the investigator. The effect of sample instability can be ameliorated by using multiple raster techniques where the drift is corrected after each scan over the specimen and the consecutive images are then summed. This approach has been applied successfully by Kowarski [13], w~,o demonstrated that a resolution of better than 100 A can be maintained over periods of 1 h even though the drift is 1-2 o A/s. It has been demonstrated by Johnson and l¢-..t.JtLOt.S

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recorded at lower resolution using acquisition times of the order of 12 h; this r~robably represents the upper limit for the analytical electron microscope. These restrictions therefore le;~d to pixel dwell times between 0.1 and 1 s depe: 'ing on the array size and total time. The signal from a biologicel specimen is opti-

241

mal when the probe current is high ( = 5 nA) and the EDS silicon crystal subtends a large solid angle at the sample (0.1-0.2 sr). The specimen thickness should be less than approximately 1000 in order to provide good spatial resolution. Moreover, the characteristic X-ray count rate is determined by basic physiological quantities such as the ionization cross-section and the fluorescence yield, and by basic physical quantities such as the average intracellular ionic concentration and the protein and nucleic ack, content. With these instrumental and sample parameters it is found that the characteristic X-ray count rate from a thin cryosection is only 50 to 200 per second at the most, even for abundant cellular elements such as phosphorus and potassium. In an X-ray map, signal levels of between 5 and 100 counts per pixel for the largest peaks in the EDS spectrum are therefore a fact of life, as has been discussed by Somlyo [8]. Minor peaks such as sodium, magnesium or calcium will generally give, on average, only a fraction of a count per pixel. Nevertheless, despite this fact we shall show that it is quite possible to quantitate relatively low elemental concentrations from an X-ray map. This is because the signal can be integrated over many pixels whenever the average concentration is to be estimated for an area large with respect to pixel area, and bec~l,~e the method of backg"ound removal described above is just as applicable to noisy data as to spectra with large numbers of counts [17]. Fig. 2a is a transmission electron micrograph of a cryo,;ection of mouse cerebellar cortex showing a blood vessel coursing through the neuronal tissue, i.e., the neuropil. The vessel is limited by an endothelial cell wall, and contains several erythrocytes surrounded by blood plasma: a stellate cell is also evident. The corresponding X-ray maps of Na, P, K and Fe, ~all recorded cc>ncurl;~,..liLi},

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rain 128 x 128 pixcls acquired for 200 n3s per pi.~:e! (live-time). The probe current was 4 nA, as measured by a Faraday cup, and the spatial resolution was about 500 A. The maximum, the minimum, and mean counts per pixel for all four elements are shown in table 1. The small numbers are ie line with the above discussion about the limited

242

CE. Fiori et al. / Quantitative X-ray mapping of biological cryosections

Fig. 2. (a) Conventional transmission electron rrucrograph of a freeze-dried cryosection of mouse cerebellar cortex. This field includes the nucleus of a stellate cell (N) and a blood vessel containing erythrocytes (R) and plasma (P) embedded within the substance of the brain; the vessel is lined by a single layer of endothelium (E). (b)-(e) Sodium, potassium, iron and phosphorus X-ray maps from same area recorded with 128 × 128 pixels and 200 ms dwell time. Brain tissues were prepared for AEM by obtaining slices of lateral cerebellum from 40--45 day NIH C57BL/6 mice and rapidly freezing the uncut pial surface of the slice against a liquid-helium-cooled copper block within 20-30 s of excision [22,23]. Cryosections, approximately 100 nm thick, were prepared at - 145 o C by means of a Reichert Ultracut E equipped with an FC-4 co'okit. CDosections were either transferred to and freeze-dried within the electron microscope using a Gatan Model 626 cryotransfer device or were freeze-dried and carbon-coated in an auxiliary, vacuum system. These procedures have been described in detail elsewhere [24,25]. Bar = 1 ~tm.

C.E. Fiori et al. / Quantitative X-ray mapping of biological co'osections Table 1 Observed numbers of characteristic counts in the entire 128 x 128 pixel X-ray maps of the cryosection of mouse cerebellar cortex shown in fig. 2; probe current was 4 nA and dwell time was 200 ms/pixel; net counts per pixel were determined by integrating the central lobe of digitally filtered spectra Element

Minimum counts per pixel

Maximum counts per pixel

Average counts per pixel

Na P K Fe

- 7 - 8 -4 - 5

11 50 37 13

0.94 4.34 8.45 0.59

243

Table 2 Quantitative estimates of concentrations (mmol/kg wet wt + SEM) in erythrocytes, plasma, and endothelial and stellate cell nuclei of the cryosection of cerebellum shown in fig. 2; relative sensitivity factors were 7.0 for Na, 1.5 for P, 1,0 for K, and 0.8 for Fe; absolute concentrations were calculated by sealing to the potassium concentration in these erythroeytes, i.e., 94 m m o l / k g wet wt; note the small negative bias for phosphorus concentration in plasma is due to P/S K,.# peak overlap (see text) Compartment

Concentration (mmol/kg wet weight) Na

P

K

Fe

Erythrocyte 0 + 2 19 _+ 2 94 ,+4 13.5,+0.6 Plasma 71 + 2 - 2.7 _+ 0.5 4.4-+ 0.3 0.3 _+0.2 Endothelialnucleus 1,+4 91 ,+11 100 + 4 0.2-+0.3 Stellate nucleus 34_+ 4 68 ,+ 8 64 + 6 0.2 +_0.3

signal; for example, the mean number of counts per pixel for the most abundant element, potassium, is only 8.45. We can interpret the maps qualitatively as follows. Phosphorus is concentrated in the living cells, i.e., in the neuronal, glial, and endothelial cells which all contain significant amounts of phosphorylated nucleotides and metabolites, phosphoproteins and nucleic acids; phosphorus is much lower in the red blood cells. Intracellular potassium is generally high and intracellular sodium is low, whereas the converse is true in the plasma. Such maintenance of physiological gradients of

diffusible cations is a good indicator of retained cellular integrity during preparation. Iron is found only in the hemoglobin-rich red blood cells.

3.3. Sensitivity The X-rays maps in fig. 2 were quantitated by determining the mean coun :s per pixel in 100-pixel regions of interest within erythrocytes (8 areas), blood plasma (8 areas), endothelia! cell nuclei (6 areas), and the stellate cell nucleus (7 areas). The ENDOTHELIAL CELL

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Fig. 3. Intensity histograms of counts/pixel for Na, P, K, and Fe obtained from the mean of mean counts in several 100-pixel regions of fig. 2: standard errors of the means (SEMs) are also indicated. Data are presented for e~'throcytes, plasma, and endothelial and stellate cell nuclei.

244

CE. Fiori et al. / Quantitative X-ray mapping of biological co'osections

mean values were obtained using a "histogram program" controlled by a digitizing-tablet and stylus, with output overlaid on the image display monitor [9-11]. As well as computing the mean numbers of counts per pixel (P), this program determined the standard deviations ( a ) of the numbers of counts. This was useful for estimating the statistical error in each region of interest since the regions were small enough to be taken as homogeneous. The estimated standard deviation of an N-pixel region is given simply by the standard error of the mean (SEM),

ON=O/yON.

(2)

Final uncertainties in mean counts per pixel were determined from the SEM of the mean counts in all similar regions of interest. Therefore, these also included possible differences in composition between similar regions due to changes in section thickness or biological variability. The errors calculated in this way were generally greater than the net statistical errors estimated from eq. (2) by setting N equal to the sum of pixels from all similar regions of interest. Fig. 3 shows histograms of the mean counts per pixel for Na, P, K and Fe obtained from all the regions of interest with errors calculated as described above. Despite the apparently high noise level in the image, which contains, in places, only a fraction of a count per pixel, accuracy in these determinations was quite good. This is reasonable when one considers that 20% of the image area was analyzed, and this is equivalent to about 200 s of acquisition time in each of the four compartments. In table 2 quantitative estimates of the concentrations iv.. m m o l / k g wet wt are obtained by adopting previously determined sensitivity factors between elements. We used the erythrocyte as an internal standard [24] by assuming that the K concentration m" th;~ c,,~l| ;ra ~ ; t , , ; c t h . . . . . . . . measured chemically in isolated erythrocytes, i.e., 94 mmol/kg wet wt. This approach for quantitation assumes the standard is well characterized, that the section is uniformly thick, and that there is no differential shrinkage between compartments [26,27]; alternative methods will be discussed later. The concentrations determined for all four elevA

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ments in erythrocytes are consistent with published data [28]; for the blood plasma, the determinations are less accurate, as is often the case for cellular compartments with a high water content (94% in this instance). The elemental content estimated for the two types of nuclei are within the physiological range, although it is apparent that the Na content of the neuronal (steUate) cell is markedly higher than that of the endothelial cell. The N a / K ratio of the steUate cell nucleus is comparable to chemical measurements of brain tissue, although the absolute concentrations are approximately 25% lower [29,30]. Our direct measurements of Na and K concentrations specifically in the cytoplasm of neuronal branches are, as discussed below, somewhat higher and therefore more in line with published data on brain electrolytes [29-32]. These conclusions are statistically justified even though there is less than one sodium count per pixel in the image data. A transmission electron micrograph and the corresponding P, K and Ca X-ray maps from an area of neuropil in a similar cryosection of mouse cerebellar cortex are shown in fig. 4. The dwell time per pixel was again 200 ms and data were acquired from 128 × 128 pixels. Regions of interest marked on the micrograph include a part of the relatively large nucleus (N) at the top of the image, the intermediate-sized Purkinje cell dendrite (P), and the small dendritic spine process (S); table 3 shows the ek nental concentrations in these areas. Analysis of these data illustrates both the potential and limitations of the mapping technique. The quantitation was performed as described above, making use of an erythrocyte in the sample to determine the potassium concentrations ( m m o l / k g wet wt) in the structures of interest. and using known sensitivity factors to determine phosphorus and calcium concentrations. Calcium detectability in the nucleus, as defined by twice the standard error of the mean it ocw~d (anproximately 1.0 m m o l / k g wet wt) because the intensity was integrated in 600 pixels. From this result it seems reasonable that potassium or calcium concentrations as low as 0.1 m m o l / k g wet wt might be detectable under optimum conditions when the number of pixels is large. In the dendrite (250 pixels) calcium sensitivity is about a factor of

C.E. Fiori et aL / Quantitative X-ray mapping of biological co,osections

ti

245

,

Fig. 4. (a) Conventional transmission electron micrograph of a freeze-dried cryosection of mouse cerebellar cortex; the field mainly illustrates the complex web of sectioned processes of neurons and glial cells known as nev, ropil. Within the neuropil various characteristic structures such as synaptic vesicle-filled parallel fiber terminals (arrowhead) can be recognized. Regions analyzed are: 1 /~m2 area of stellate cell nucleus (N); 0.4/,tm 2 area of Purkinje cell d e n d n : c (D); and 0.03 ~ m 2 area of spiny process (S) of dendrite. (b)-(d) Corresponding 128×128 pixel X-ray maps, recorded with 200 ms dwell time, showing the distribution of phosphorus, potassium, and calcium, respectively. Misregistrauon between lower parts of TEM and elemental maps is attributed to difference in sample tilt. Bar = 1 btm.

Table 3 Concentrations ( m m o l / k g wet wt + S E M ) of phosphorus, potassium, and calcium in three areas of the cryosection of mouse cerebellum shown in fig. 4; the relative sensitivity factors were 1.5 for phosphorus, 1.0 for potassium, and 0.9 for calcium; the mean potassium concentration over the whole field was taken to be 98 m m o l / k g wet weight (obtained from erythrocyte in~ernal _ . in . . . . . . . . . . . ~t~r~-4arA'~" .... ,~r. note . . . +h- '-," ,a.ger uncertainty concentration for smaller areas; the slight, systematic, negative bias in Ca concentration is due to overlap of the potassium Kfl peak (see text) Compartment

Number of pixels

Concentration ( m m o l / k g wet wt) p K Ca

Nucleus Dendrite Spine

600 250 18

70 + 3 92 +__ 5 48+14

83 + 2 72 _+3 83+8

- 1.0 + 0.5 1.2 + 1.0 -2.2+2.5

two lower than in the nucleus. In the spine there are only 18 pixels and the detectability for calcium rises to 3 m m o l / k g wet wt. The X-ray map exhaustively samples the whole scanned area, thus it is useful for searching for foci of high calcium concentrations which are present under some conditions in locations that are not easily identified from the morphology. However, our main interest la

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centrations of calcium in small but morphologically identifiable structures like the pre~:rmptic terminals and dendritic spines [32]. In these organelles the number of pixels may be too few to obtain acceptable statistical error in an image, so that a full spectral analysis from a point in the sample is necessary.

246

C.E. Fiori et al. / Quantitative X-ray mapping of biological co'osections

3.4. Potassium Ki~ / calcium Ka overlap correction: a biological example Synaptosomes are mechanically pinched off and resealed presynaptic nerve endings that display many of the important biochemical properties of in situ endings. Synaptosomes from squid brain are interesting because they are highly enriched in the neurotransmitter acetylcholine, which they can secrete in a calcium-dependent fashion [33]. X-ray maps of sulfur, potassium and calcium fi'om a cryosection of a suspension of squid synaptosomes are presented in fig. 5. The data were recorded with 100 ms dwell time per pixel over 256 × 256 pixels but only a .128 × 128 region is shown. Various kinds of cell fragments are revealed by their content of phosphorus and sulfur, but those structures which are likely to be biochemically intact synaptosomes can be distinguished by a high potassium concentration. A few areas of high calcium are seen but these do not correlate with the high-K synaptosomes, which have quite low internal calcium. These images can be used to illustrate the lower limit of calcium measurements in the presence of high potassium. In the matrix of known composition, ten areas each containing 200 pixels were analyzed; the

potassium and calcium counts per pixel were 0.57 + 0.02 and 0.31 + 0.02, respectively, the latter corresponding to the known calcium concentration of 9.0 mmol/kg wet wt with an error of + 0.6. Ten synaptosomes were analyzed, each containing an average of 100 pixels; the potassium and calcium counts per pixel were 4.2 + 0.4 and 0.02 + 0.02, respectively. Since the relative sensitivity factors for potassium and calcium are known (see table 3), the mean potassium concentration within the synaptosomes can be estimated at 140 + 13 mmol/kg wet wt. In contrast, the calcium concentration is calculated as 0.6 + 0.6 mmol/kg; that is, calcium was not detected in the synaptosomes. Thus, although sensitivity for mapping calcium was not optimal in this case and clearly could have been improved by increases in counting time, section thickness and beam current, the detection of very low levels (e.g. 0.1-0.5 m m o l / k g wet wt) requires a more sophisticated spectral analysis such as iinear-least-squares unraveling of individual X-ray spectra [35]. This reflects the fact that small uncertainties in experimental parameters introduced by discarding the spectra in the mapping technique can affect the accuracy of the analysis.

Fi~,. 5. X-ray m a p s ¢19R~!28 ,~Y,q~ .~.... ~! ,u,,,~ : _ _ ,.n ^c ,~vv , . . . tn~/p~xcl~ . . . . . . . . . . . ~rom a freeze-dried cryosection of isolated nerve ,- . . . . r . . . acquired . . . . . -,, a ,.,,,,,.,, terminals, i.e., synaptosomes, f~om squid brain; (a) sulfur, (b) p o t a s s i u m , and (c) calcium. S y n a p t o s o m e s (arrowheads) can be recognized as circular profiles, 0.5-2.0 p.m diameter, which are K-rich (and often S-rich) but Ca-poor. Various other tissue-derived structures, including r-. **:,. fragments, are also evident in this field. T h e X-ray background d u e to support film can be seen at the ...,,-,,,.h lower left where the section was torn. S y n a p t o s o m e s were prepared from the optic lobe of the squid, Loligo peaiii, by biochemical fractionation according to the procedure of Pant et al. [34]. The s y n a p t o s o m e s were resuspeaded in an artificial seawater of k n o w n composition containing 10% ( w / v ) serum a l b u m i n to serve as a m a c r o m o l e c u l a r matrix prior to direct freezing and cryosectioning as described in the legend to fig. 2. Calcium (matrix concentration = 9 m m o l / k g wet wt) was used as the standard e l e m e n t for quantitation. Bar = 1 ~ m .

CE. Fiori et al. / Quantitative X-ray mapping of biological co,osections

3.5. Quantitation The point-analysis of cryosections is normally performed by making use of the continuum or Hall method [1-3]. This scheme has the advantage of giving the concentration in terms of mmol/kg dry wt, so that results are independent of specimen shrinkage and compression. In the Hall method the concentration is determined by forming a ratio of characteristic X-ray counts to continuum counts. The former is proportional to the mass of a particular element, whereas the latter is proportk,,nal to the total mass. Quantitation is performed by means of standards. The method can be extended to X-ray maps if the total integrated continuum counts within a selected energy range are recorded at every pixel along with the background- and deadtime-corrected characteristic X-ray signals. The choice of the best energy r~nge for the continuum involves a consideration of statistics and instrumental effects. For a discussion of the various physical, statistical and practical considerations for choosing the continuum energy see Fiori et al. [21] and Kitazawa et al. [35]. We integrate over an approximately 0.1 keV window centered at any peak-free region between about 1.0 and 1.7 keV. This energy range is a good choice because it contains a minimum component of continuum radiation originating from the relatively thick support grid and specimen holder. Calculation of the characteristic/continuum images such that pixel intensity is linearly proportional to elemental concentration is carried out in a manner analogous to a point mode analysis. If the continuum image has low average counts per pixel it can be smoothed (eg. by weighted averar=ing of counts from nearest-neighbor pixels) before the division to improve the signal-to-noise ratio. This procedure is valid if one can assume that the average atomic number is approximately constant over most of the field of view. If one cannot make this assumption then the image must be broken into discrete regions which are treated separately. The characteristic and continuum counts are then summed over the pixels in the region and the ratios used to determine the concentration of each analyte.

247

If it is assumed that sample thickness, shrinkage and compression in the sample are all uniform, then quantitation can be performed by using a well defined internal standard (such as the internal erythrocyte method described above) in which case concentrations are determined as mmol/l analyzed volume, which is similar to mmol/kg wet wt [24,26]. This approach has the simplicity of being direct and is less susceptible to mass loss of the light elements. Alternative schemes for determining the total mass in each pixel depend on electron scattering, either elastic [36] or inelastic [37]. The main advantage here is that the data can be acquired at very low dose, thu~, opeifing up the possibility of taking measurements ~,n hydrated sections. Elastic scattering can be detected by means of an annular darkfield detector and the mass-thickness can be calibrated with a known standard [38]. There may be some departure from linearity for samples with thickness greater than the elastic mean free path. Inelastic scattering can be measured by an electron energy loss spectrometer and has been demonstrated to be useful for cryosections [39]. Both methods can easily be generalized to apply to images rather than the point mode [38-40].

4, Conclusions It is possible to detect and quantify relatively low concentrations of elements in an X-ray map by integrating the digitally filtered counts over many pixels. In order to achieve this good sensitivity it has been assumed that we know where to look for a particular element, e.g. by referring to the simultaneously acquired elastic dark-field image. The more difficult problem of localizing elements in otherwise poorly characterized regions with low concentra~ion~ ~ no' been ~4~re~ed; this would require a consideration of pattern recognition techniques. One advantage of elemental mapping over point analysis is that a wide area of the tissue can be exhaustively analyzed. Furthermore, the compartments to be analyzed quantitatively can be selected after, rather than before, data acquisition, thus allowing a great degree of flexibility. For X-ray peaks like iron K a for which

C.E. Fiori et aL / Quantitative X-ray mapping of biological co'osections

248

overlap is not a problem, sensitivities are estimated to be in the range 0.1 to 0.5 mmol/kg wet weight of tissue under optimized conditions. For the special and important case of calcium Ka which overlaps with potassium Kfl, uncertainties in experimental parameters, e.g. energy calibration, require that the whole spectrum be analyzed in order to achieve this level of detectability. Elemental mapping with characteristic X-rays has proven useful in studying the distribution of major ions such as potassium and sodium in brain tissues. This approach has also been successfully used for the detection of calcium in cases where the cellular concentration is unusually high [5,15] although, at present, sensitivity is insufficient for detecting calcium under typical physiological circumstances. The power and versatility of the mapping approach suggests a wide range of potential app!ications in many areas of cell physiology where changes in the concentration and distribution of major elements are important.

Appendix The top-hat digital filter described by eq. (1) can be applied to an X-ray spectrum in a time proportior'al to the number of channels by calculating the summations in the formula from the difference of two pre-calculated summations; i.e.: h

h

k-1

Y'- Yj= Y'- Yj- E ) ) = S h - Sk_,, j=k

j=0

PROCEDURE TopHatFilter ( V A R y : ARRAY [yl..yh : INTEGER] OF REAL ;{ original spectrum } VAR f : ARRAY [fl..fh : INTEGER] OF REAL ; { filtered spectrum } M : INTEGER ; { 2M+1 channels in central section } N : INTEGER) ; { N channels in side sections } VAR iop,q,r "INTEGER; S • ARRAY[0..MaxSpectrumChannels ] OF REAL; BEGIN S[0]:=0; FOR i : = 1 T O y h - y l + l DOS[i] :=y[yl+ip :=N; q : = N + t , . , ! + M + I ; r:=N+M+M+N+

1 ]+S[i1 ]; 1; { initialize filter section indices }

FORi:=0TOyh-yI-(N+M+M+N) DO BEGIN f [ fl + i ] := ( S [ q ] - S [ p ] ) / (2*M + 1 ) + (S[p]- S[i] + S [r]- S[q]/(2" p := p+ 1;

q := q + 1"

r := r + 1"

N) ;

{ advance filter }

END; END; { TopHatFilter }

For X-ray spectra, it is recommended to choose M = N. Thus, there are 4 N + 1 channels in the top-hat filter, N in each of the two side sections and 2N + 1 in the center section. Since the center section should span an energy range approximately equal to the F W H M (full width at half maximum) of the X-ray detector, then N can be calculated as follows: N = FWHM/2K, where K is the number of eV per X-ray spectrum channel. The number of channels filtered equals the number of channels in the center section (2N + 1), requiring a total of 6N + 1 channels centered at the peak energy to be sampled and processed.

(A.1)

j=0

Refer-nc-~ where S, is calculated from: S0=0,

Si=y, + S,_ 1.

(A.2)

Re-writing (A.1) in terms of S gives: S~ ~ . ; ~ -

)"=

S,_

.~,

,

2M+ ! S,_ M- 1 -

S,_,~t_ x-1

+ S, . ,,I* ~ -

S , + .,¢

2N (A.3) Eqs. (A.2) and (A.3) form the basis for the following Pascal procedure (written by K.E. Gorlen, National Institutes of Health):

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[22] D.M.D. Landis and T.S. Reese, J. Cell Biol. 97 (1983) 1169. [23] J.E. Heuser, T.S. Reese, M.J. Dennis, Y. Jan. L. Jan and L. Evans, J. Cell Biol. 81 (1979) 275. [24] S.B. Andrews, J.E. Mazurkiewicz and R.G. Kirk, J. Cell Biol. 96 (1983) 1389. [25] S.B. Andrews and T.S. Reese, Ann. NY Acad. Sci. 483 (1986) 284. [26] A. Dorge, R. Rick, K. Gehnng and K. Thureau, Pfliigers Arch. Eur. J. Physiol. 373 (1978) 85. [27] B. Gupta, The electron microprobe X-ray analysis of frozen-hydrated sections with new information on fluid transporting epithelia, in: Microbeam Analysis in Biology, Eds. C.P. Lecbene and R.R. Warner (Academic Press, New York, 1979) pp. 375-408. [28] P.L. Altman and D.S. Dittmer, Eds., Biology Data Book, Vol. III, 2nd ed. (Federation of American Societies for Experimental Biology, Bethesda, MD, 1974)p. 1771. [29] H. Pappius, Riv. Patol. Nerv. Ment. 91 (1970) 311. [30] R. Katzman, Neurology 11 (1961) 27. [31] A.P. Somlyo, R. Urbanics, G. Vadasz, A.G.B. Kovach and A.V. Somlyo, Biochem. Biophys. Res. Commun. 132 (1985) 1071. [32] S.B. Andrews, R.D. Leapman, D.M.D. Landis and T.S. Reese, Proc. Natl. Acad. Sci. USA 84 (1987) 1713. [33] M.J. Dowdall and V.P. Whittaker, J. Neurochem. 20 (1973) 921. [34] HC. Pant, H.B. Pollard, G.D. Pappas and H.D. Gainer. Proc. Natl. Acad. Sci. USA 76 (1979) 6071. [35] T. Kitazawa, H. Shuman and A.P. Somlyo. Ultramicroscopy 11 (1983) 251. [36] B.P. Halloran and R.G. Kirk, Quantitative electron probe nnticroanalysis of ultrathin biological se,.zicns, in: Microbeam Analysis in Biology, Eds. C. Lechene and R.R. Warner (Academic Press, New York, 1979) pp. 571-90. [37] R.D. Leapman, C.E. Fiori and C.R. Swyt, J. Microscopy 133 (1984) 239. [38] J.Wall, Mass measurement with the electron microscope, in: Scanning Electron Microscopy/1979, Vol. II, Ed. O. Johari (SEM, AMF O'Hare, IL, 1979) p. 291. [39] D.A. Kopf, A. LeFurgey, L.A. Hawkey, B.L. Craig and P. In, ram, Mass thickness images of frozen-hydrated and freeze-dried sections, in: Microbeam Analysis - 1986, Eds. A.D. Romig and W.F. Chambers (San Francisco Press, San Francisco, CA, 1986) pp. 241-247. [40] R.D. Leapman, C.E. Fiori and C.R. Swyt, Mass thicknes_~ by inelastic scattering in microanalysis of organic samples. in" Analytical Electron Microscopy, Eds. D.B. Williams and D.C. Jo y (San Francisco .IViCbb, dlO. 'k../~. . . . . . . .,..~i..tli . . . . .Fiiliigi~,l, ... 1984) pp. 83--88.