Chapter 31 Biological Applications of Energy-Filtered TEM Martin Saunders and Jeremy A. Shaw Abstract The techniques of electron energy-loss spectroscopy (EELS) and energy-filtered TEM (EFTEM) are routinely applied in the physical sciences to map the distribution of elements at the nanoscale. EELS can also provide details of the bonding/valence of elements through variations in the fine structure of elemental peaks in the spectrum. While applications of these techniques in biology are less prevalent, their ability to detect both the light elements (e.g., C, N, O, P, S) that form the building blocks of biological systems and heavier elements (e.g., metals) makes them potentially important techniques for investigating local chemical variations in tissues and cells. Successful application of EELS and EFTEM in biology requires both an understanding of the techniques themselves and expertise in specimen preparation. Care must be taken to avoid the diffusion of elements during the preparation process to avoid artifacts in the resulting element maps. The power of the techniques is demonstrated here using tissue from a marine mollusc (chiton). Key words Transmission electron microscopy, Electron spectroscopy, Composition, Elemental mapping

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Introduction The twin techniques of electron energy-loss spectroscopy (EELS) and energy-filtered transmission electron microscopy (EFTEM) provide information on the presence and distribution of elements and can be used to investigate the form of those elements, e.g., their bonding, valence, and coordination [1–4]. They are extensively used in the physical sciences, where they routinely provide compositional and electronic information down to the nanoscale and, on the latest-generation instruments, at near-atomic resolution [5]. Applications of EELS and EFTEM in biology are, however, less widespread, in part due to the tendency for the necessary instrumentation to be located in materials science and engineering departments from which biologists are often excluded, but also because of the increased complexity of applying these techniques in biological research. The potential benefits of the techniques in biological research are, however, significant as they are capable of detecting the light elements central to biology, e.g., C, N, O, P,

John Kuo (ed.), Electron Microscopy: Methods and Protocols, Methods in Molecular Biology, vol. 1117, DOI 10.1007/978-1-62703-776-1_31, © Springer Science+Business Media New York 2014

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Fig. 1 Bright field TEM image of superior epithelial tissue from the marine chiton Acanthopleura hirtosa (Mollusca: Polyplacophora). The superior epithelium is responsible for hardening the animal’s teeth with iron biominerals. Iron is stored in the tissue as ferritin, which aggregates into large electron dense siderosomes (S), prior to delivery into the teeth. Scale bar = 500 nm

and S [6–10], in addition to key metals related to biological function, e.g., Fe and Ca [11–17], and the broad spectrum of elements arising from nonbiological materials introduced into biological systems either intentionally or unintentionally [18, 19]. This potential can be demonstrated by analyzing the composition of tissue from a marine mollusc (chiton), which hardens its teeth with iron and calcium mineral phases. This is achieved by transporting large quantities of iron into the teeth from stores of ferritin within the surrounding tissue. The ferritin is aggregated into siderosomes containing thousands of individual ferritin molecules, each with an iron core of ferrihydrite ~8 nm in diameter (see Fig. 1). This complex biomineralization system results in a laminated biocomposite structure comprised of iron oxides, iron hydroxides, and calcium phosphate, with the exact structure/phases dependent on the species [12–14, 16]. EELS involves the analysis of the energy lost by electrons passing through a thin section. An energy-loss spectrum is formed by collecting these transmitted electrons and physically dispersing them as a function of their energy, typically using a magnetic prism (or multiple prisms). To acquire EELS data, you will need either a dedicated electron spectrometer or an energy filter that allows both imaging and spectroscopy. The filter can either be built into the microscope column just below the objective lens (an in-column filter) or attached to

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Fig. 2 Electron energy-loss spectra. (a) Low-loss spectrum from the field of view shown in Fig. 1 showing the dominant zero-loss peak (at 0 eV) and plasmon peak (at ~20 eV). (b) Series of core-loss edges from C, N, O, and Fe from the same chiton sample. The energies of the peaks determine which elements are present while the fine structure can reveal information on the local bonding environment, e.g., valence or oxidation state

the bottom of the TEM after the projector lens system (a post-column filter). The former design (available for Zeiss or JEOL TEMs) must be included in the microscope design at construction. The latter (available from Gatan) can be retrofitted to any TEM. In a thin sample, the EEL spectrum is dominated by a large peak at zero energy loss representing the electrons that pass through the specimen with no significant loss of energy (the elastic scattered electrons). In the so-called low-loss region of the spectrum (the first few tens of eV energy loss), the main signals are the broad plasmon peaks corresponding to collective vibrations of the valence electrons in the specimen (see Fig. 2a). Weak signals associated with the excitation of chromophores have been analyzed in special cases [20], but applications in this area are rare.

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Of most interest for biological research are the core-loss signals, which provide information on specific elements. The coreloss signals are associated with electrons being excited from inner (core) electron shells into the outer (valence) shells of the atoms in the specimen. They occur at characteristic energies for each element (approximately the element’s ionization energies) and have a fine structure that is representative of the form of the element, e.g., its valence/oxidation state, bonding environment, and coordination (see Fig. 2b). In EELS, a spectrum showing the number of electrons as a function of energy loss is acquired, allowing the elements present to be identified from their characteristic energies and details of the elements’ state to be determined from the fine structure [2]. In EFTEM, images are formed at user-defined energies by using an energy-selecting slit to define the energy range of the electrons forming the image while filtering out the unwanted electrons. By selecting the energy range corresponding to a specific element, the distribution of a given element can be directly imaged in the form of an element map. These elemental signals sit on a background signal created by energy-loss events at lower energies, i.e., plasmon peaks and lowerenergy element peaks. The elemental signal can be separated from the background by fitting a suitable function through the pre-edge background data. For EFTEM element mapping, this is typically done using the three-window method [1] where two background (or pre-edge) images are acquired at energies just below the characteristic element energy and a third image (the post-edge image) is acquired above the characteristic element energy (see Fig. 3). The two pre-edge images are used to fit a background function allowing extrapolation of the background to the post-edge energy and the removal of the background intensity. If the background can be accurately removed, the final element map will contain quantitative intensity variations corresponding to the distribution of the element (number of atoms per unit projected area). An example of this three-window approach for the mapping of iron in the chiton tissue is shown in Fig. 4. The two pre-edge images are acquired at energies of 645 ± 20 eV and 685 ± 20 eV, while the post-edge image is acquired at 735 ± 20 eV, slightly above the onset of the Fe L2,3 edge. The resulting element map clearly shows the iron distribution in the tissue. For some elements, multiple signals at different energies may be detectable by EELS. In the case of Fe, in addition to the L-edge used to create the map in Fig. 4, an M-edge can be found at ~54 eV. The choice of which peak to map can often be difficult. Higher intensity levels (and hence better signal-to-noise and shorter acquisition times) are associated with low energy-loss edges. Signals close to the dominant plasmon peaks in the low-loss region of the spectrum are, however, difficult to map accurately due to

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Fig. 3 EELS spectrum showing the O and Fe core-loss edges along with the location (for Fe) of the two pre-edge and post-edge energy windows used to acquire the three images in the three-window technique. The final element map is obtained by fitting a background from the two pre-edge images and extrapolating and subtracting that background from the post-edge image (see Fig. 4)

problems fitting appropriate background models to extract the elemental signal. While we have successfully mapped Fe using the M-edge in very thin sections, where the plasmon peaks are less significant, for more conventional section thicknesses, the higher energy L-edge produces more reliable results. The ability of EFTEM to acquire multiple element maps, including key biological elements such as C, N, and O, is illustrated in Fig. 5, where a set of element maps acquired from the same field of view is shown. In each case, the energy range for each of the pre- and post-edge images has been optimized using the spectral data shown in Fig. 2b, and the acquisition times have been adjusted to provide good signal-to-noise (from 120 s per image for C up to 240 s per image for iron). In situations where it is difficult to fit a suitable background, e.g., where multiple signals overlap, the jump ratio imaging method may be more useful. In this case, only two images need to be acquired, the post-edge image and one pre-edge image. The jump ratio is produced by dividing the post-edge image by the pre-edge image. The resulting image will show higher intensity where the element is located, but the resulting data is only a qualitative indication of the element distribution. Jump ratio imaging has fewer problems with noisy data as it does not require the fitting of a background function. For many biological EFTEM applications, obtaining high signal-to-noise is problematic as element concentrations

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Fig. 4 Application of the three-window technique to map the iron distribution in ferritin accumulated in the chiton tissue. (a–c) Pre- and post-edge images for the Fe L2,3 edge centered at 645 eV, 685 eV, and 735 eV, respectively, with a energy window of 40 eV. (d) Resulting Fe element map once the background has been removed from the post-edge image. Scale bar = 500 nm

can be low and beam damage limits acquisition times. Thus, jump ratio imaging is often a preferable alternative to the full three-window element mapping technique. In all cases, it is advisable to acquire electron energy-loss spectra from the specimen before conducting energy-filtered imaging. It is only the presence of the elemental signature in the spectrum that provides proof that the element is present. EFTEM techniques are prone to weak artifactual intensity variations created by fluctuations in the background. Thus, a low-intensity false-positive result can occur in situations where the element is not present, and it is only the spectral confirmation that provides evidence of the element’s presence. A second reason for acquiring representative spectra is that this allows for the optimization of the energies of the

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Fig. 5 Comparable element maps for (a) carbon, (b) nitrogen, (c) oxygen, and (d) iron from the same field of view as shown in Fig. 1. Scale bar = 500 nm

signal and background windows used to form the image. By ensuring that the post-edge window is positioned on a strong feature in the elemental signal, good signal-to-noise will result in the final image [21]. A basic procedure for the acquisition of an EEL spectrum suitable for the optimization of the pre- and post-edge windows for EFTEM is provided in Subheading 3.2. An alternative to element mapping by energy-filtered TEM is to acquire EEL spectra as a function of position by running the microscope in Scanning TEM (STEM) mode and acquiring a full spectrum at each point in the scan. This generates a data cube with two of the dimensions representing the position of the electron beam as it is scanned and the third dimension representing the energy lost by the electrons. This data cube can be post-processed to extract the elemental information as a function of probe position. This has the advantage that the presence of the element

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is confirmed through its appearance in the spectrum and that both the location and electronic state, e.g., valence/oxidation state, of the element can be mapped [22]. Acquiring the full data cube also allows for the data to be interrogated and elements to be identified and mapped long after the data is acquired (unlike EFTEM where specific acquisition conditions must be set up for each element we wish to analyze at the time of data acquisition). The disadvantages are that longer data acquisition times are required compared to EFTEM and that the technique is more technically demanding and complex. As EELS and EFTEM rely partly on the assumption that the target material is of even thickness, analyses of biological material are best conducted on resin-embedded samples cut with an ultramicrotome. Conventional benchtop and microwave-assisted chemical fixation and cryogenic methods can be used successfully for preparing embedded biological samples for EELS and EFTEM (see Chapters 1, 2, 3, and 8 of this volume). However, a number of provisos exist when the target of the preservation is to capture the elemental composition rather than pure structure. Certain elements, whether they exist as mobile ions or are bound to cellular components, can be moved, lost, or changed during the various processing steps. As such, a thorough understanding of the sample’s chemistry is required, together with the specific interactions that may occur between the target elements and their exposure to the chemicals necessary for preparing material for TEM. Often, a compromise must be made between the good structural preservation that can be achieved with routine TEM sample preparation and protocols that aim to preserve the qualitative or quantitative elemental composition. No single protocol exists, as the method is dependent on the sample, the target element, and how this element is integrated into the tissue. For a detailed overview of the specific considerations needed for biological microanalysis, we recommend [23, 24]. High-pressure freezing (HPF) is a reliable method for preserving the structural and elemental composition of cultured cells or whole tissues. This is followed by freeze-substitution of the sample, which can be loosely defined as a low-temperature dehydration technique. The freeze-substitution solution uses an organic solvent containing a range of additives (e.g., uranyl acetate, osmium tetroxide, and water), which act as fixatives and contrast agents to biological tissues for structural imaging in the TEM. Care must be taken when preparing the freeze-substitution medium to exclude elements that may share characteristic peaks with target elements for analysis (e.g., the low-energy edges of Os and U interfere with our ability to map the Fe M-edge or the Au O-edge). It is possible to omit any or all of the additives from the organic solvent; however, this commonly compromises the samples structural preservation. In this case, it is recommended that

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suitable duplicate samples are processed for comparative structural observations. Although freezing circumvents issues relating to the extraction or displacement of elements in biological samples, it must be stressed that subsequent freeze-substitution, resin embedding, and cutting of ultrathin sections on water can each result in element loss and/or redistribution. For further reading we recommend [25]. In some instances, cryo-ultramicrotomy of frozen hydrated material and subsequent freeze-drying of the sections may be applicable. While this may improve the retention of elements, the removal of water will result in uneven sample thickness.

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2.1 Specimen Preparation

1. High-pressure freezer (HPF). For cryogenic sample preservation (see Note 1). 2. Tools and consumables for processing and handling HPF material (see Chapter 8 of this volume). 3. Extracellular filler (such as 1–2 % low gelling temperature agarose or 10–20 % bovine serum albumin). For assisting the freezing process (see Note 2). 4. Sample holders. As per brand/model of high-pressure freezer. 5. Micropipette and tips (0.1–2.5 μL and 2–20 μL). For transferring filler and/or samples into sample holders. 6. Dry block heater and temperature-controlled microscope stage (set to ~37 °C range). Important if using agarose to prevent it from cooling below its gelling temperature during sample loading. Agarose must be kept as a liquid until the point of freezing. 7. Cryovials. For storing frozen samples or conducting the freezesubstitution process. 8. Freeze-substitution system (see Note 3). 9. Resin embedding media. Used as part of an increasing concentration series to infiltrate the cells/tissue prior to polymerization and sectioning (see Chapter 1 of this volume for details). The resin should be free of any elements that are intended for analysis. Epon 812 (Procure 812) or Lowicryl HM20 is recommended for most samples. 10. Ultramicrotome. For cutting ultrathin sections of resinembedded material. 11. Diamond knife. For cutting ultrathin sections of resin-embedded material. 12. TEM grids (see Note 4). 13. TEM grid boxes (recommend long-term storage in a desiccator).

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2.2 Electron EnergyLoss Spectroscopy

1. Transmission electron microscope (TEM) or scanning transmission electron microscope (STEM). The energy resolution achievable with EELS depends on the electron source— better spectral resolution will be achieved with a field emission source. A monochromator, available on the latest, high-end TEMs, will provide even greater energy resolution. 2. Electron spectrometer. Two commercial options exist [26]: (a) In-column: The spectrometer is built into the TEM column below the objective lens. It must be included when the instrument is purchased and cannot be retrofitted onto an existing instrument. In-column filters are available for Zeiss and JEOL TEMs. (b) Post-column: The spectrometer is attached to the bottom of the TEM column under the viewing/camera chamber (or on the top for dedicated STEM instruments with inverted columns). Two variants are available from Gatan—a dedicated EELS spectrometer (for EELS only) or an imaging filter (for both EELS and EFTEM). These can be attached to any TEM and can be purchased on installation or retrofitted onto an existing instrument. In order to provide detailed procedures for a specific situation, the Methods section of this chapter assumes the use of a Gatan Imaging Filter. 3. Computer for data analysis. While all spectrometers are provided with suitable computers for data acquisition and analysis, a second computer with relevant software for off-line data analysis is desirable. 4. Data storage. While single spectrum acquisition results in relatively small data files, STEM-EELS spectrum imaging can create very large amounts of data in a relatively short time frame. Suitable data storage is therefore critical for modern instruments.

2.3 EnergyFiltered TEM

1. Transmission electron microscope (TEM). For high spatial resolution (nanoscale) analysis, a field emission source is desirable to ensure sufficient signal at high resolution. For most biological analyses, where larger fields of view at lower spatial resolution are more generally required, a LaB6 source is acceptable and in many cases preferable. 2. Electron spectrometer. With the exception of the dedicated post-column EELS spectrometer, the in-column and postcolumn options outlined above are again applicable. In order to provide detailed procedures for a specific situation, the Methods section of this chapter assumes the use of a Gatan Imaging Filter.

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3. Computer for data analysis. As with EELS, a second computer equipped with relevant software for off-line data analysis is desirable. 4. Data storage. As with EELS, standard EFTEM analysis results in relatively small data files. Techniques such as EFTEM spectrum imaging or energy-filtered tomography can, however, increase the need for suitable data storage significantly.

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3.1 Preparing Specimens for EELS and EFTEM

As described above, the full range of chemical and cryogenic methods of TEM sample preparation can be used for EFTEM with the proviso that consideration is given to the samples chemistry and potential artifacts that may arise as a result of such processing. Detailed sample preparation methods are provided in Chapters 1, 2, 3, and 7 of this volume, and a wide range of model systems are expertly described by [27]. Our preference is to always opt for cryogenic methods where possible. Specific considerations for cryogenically preparing samples intended for analysis by EELS and EFTEM are provided (see Notes 1–4).

3.1.1 Cryopreparation

1. Bring freshly prepared material to the HPF. The aim of sample preparation for biological TEM is to preserve the target tissues or cells as close to their natural state as possible. It cannot be understated that samples intended for observation by TEM should be living and unstressed immediately prior to chemical or cryogenic fixation (or as close to it as is feasible). Collecting samples too early and storing them (e.g., refrigeration) prior to further treatment is not optimal as it can lead to significant structural and chemical change. 2. Ensure all items (tools, consumables, fillers, etc.) are prepared in advance and are within practical reach. A common approach with HPF is to practice sample dissection and loading prior to undertaking the full study. The HPF sample holders are small, and the loading process must be swift but careful to prevent drying and to minimize the chance of cellular disruption. Often, creative loading strategies must be developed to reduce the lag between dissection and the final immobilization by freezing. With practice, this process can generally be achieved in ~30 s. 3. Freeze the sample by HPF (see Chapter 8). 4. Transfer frozen samples into cryovials, either for storage under LN2 or into preprepared vials containing frozen freezesubstitution media (see Note 3). 5. Freeze-substitute samples using an acceptable protocol (see Note 3). The principles of the freeze-substitution process

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and more recent developments are described by [27] and [28], respectively. 6. On completion of the freeze-substitution process, samples should be rinsed 3–4 times in 100 % dry acetone (or other solvent depending on freeze-substitution media used). 7. Infiltrate samples with increasing resin/solvent concentrations as per an appropriate protocol developed for the sample type (see Chapters 1 and 2). 8. Embed infiltrated samples into molds, paying attention to sample orientation relative to the plane needed for sectioning, if relevant. 9. Polymerise resin and proceed with microtomy to produce semithin (0.5–1 μm) and ultrathin sections (100–150 nm) for initial screening by light microscopy and final observation by TEM/EFTEM, respectively (see Notes 5 and 6). 3.2 Electron EnergyLoss Spectroscopy: Obtaining a Single Spectrum from a Selected Region of Interest

1. Insert specimen into microscope. A standard single tilt specimen holder is usually sufficient. 2. Carry out standard TEM alignments for basic imaging (see Note 7). 3. Obtain an image on the energy filter. Most instruments will have a specific operating mode for this, which will automatically drop the image magnification to compensate for the remagnification of the energy filter. 4. Ensure that the spectrometer zero energy is correctly set to microscope operating voltage, i.e., that the spectrometer is set to detect electrons passing through the specimen without losing energy. This can be achieved automatically by pressing the “ALIGN ZLP” button in the control software. 5. Choose the magnification to achieve the desired field of view. The filter alignments are dependent on the magnification. It is therefore essential to select the intended magnification before aligning the filter (and to repeat the alignment process if the magnification is later changed). 6. Find a thin, relatively uniform area of the specimen. In most cases any part of the section will be okay. If the section is thick you may need to move off the section. If this is the situation you will need to complete step 7 (focusing) before moving off the section. 7. Adjust the focus of the image. This is best done using an image formed using electrons that have lost energy instead of using a standard bright field image. To do this: (a) Insert the energy-selecting slit of the spectrometer to form an image using the electrons that have not lost energy passing through the sample (the zero-loss or elastic image).

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(b) Adjust the microscope/filter settings to obtain an image using electrons that have lost energy. Ideally you would like to form this image at the energy loss corresponding to the signal you wish to map, e.g., the core-loss energy for a particular element. However, this may be impractical if the signal is at high energy loss as there may be insufficient signal to obtain a suitable image. If this is the case, obtain an image in the 100–200 eV energy-loss range. (c) Obtain a live image at this energy loss. Depending on the detectors available, this image could be acquired onto a TV-rate camera or with a CCD camera. (d) Optimize the image by adjusting the focus. You may need to adjust the beam intensity and acquisition time to provide sufficient image quality for accurate focusing. (e) Return to viewing the zero-loss/elastic image. You may need to adjust the beam intensity and camera settings to avoid saturating the camera. 8. Align the energy filter. On older systems, this has to be done manually. On current systems the filter alignments are corrected automatically through software (using the “TUNE GIF” button). You may be asked to adjust the beam intensity during the alignment process. Once the filter is successfully tuned, do not change magnification or you will need to retune the filter. 9. Find the area of interest. 10. Switch the operating mode of the energy filter to spectroscopy mode (see Note 8). 11. Acquire a live, short acquisition time, low-loss spectrum on the camera. 12. Manually adjust the spectrometer zero point to set the zero-loss peak at the spectrometer’s zero energy channel (see Note 9). 13. Select the energy range of interest (see Note 10). 14. Acquire the EEL spectrum. This can be done either using a single acquisition time with a suitable acquisition time to give sufficient signal-to-noise or using a cumulative acquisition mode where repeated acquisitions are averaged to improve the signal-to-noise. 15. The resultant spectrum can be analyzed to identify the elements present from the energies at which characteristic coreloss signals occur. 16. Suitable energy windows for EFTEM can be determined by identifying the energy ranges at which the maximum signal occurs for a given element and finding suitable regions in front of the elemental signal where backgrounds can be fitted.

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3.3 Element Mapping via Energy-Filtered TEM: Using PostColumn Gatan Imaging Filter

1. Insert specimen into microscope. A standard single tilt specimen holder will suffice. 2. Carry out standard TEM alignments for basic imaging (see Note 10). 3. Obtain an image on the energy filter. Most instruments will have a specific operating mode for this, which will automatically drop the image magnification to compensate for the remagnification of the energy filter. 4. Ensure that the spectrometer zero energy is correctly set to microscope operating voltage, i.e., that the spectrometer is set to detect electrons passing through the specimen without losing energy. This can be achieved automatically by pressing the “ALIGN ZLP” button in the control software. 5. Choose the magnification to achieve the desired field of view. The filter alignments are dependent on the magnification. It is therefore essential to select the intended magnification before aligning the filter (and to repeat the alignment process if the magnification is later changed). 6. Find a thin, relatively uniform area of the specimen. In most cases, any part of the section will be okay. If the section is thick you may need to move off the section. If this is the situation you will need to complete Step 7 (focusing) before moving off the section. 7. Adjust the focus of the image. This is best done using an image formed using electrons that have lost energy instead of using a standard bright field image. To do this: (a) Insert the energy-selecting slit of the spectrometer to form an image using the electrons that have not lost energy passing through the sample (the zero-loss or elastic image). (b) Adjust the microscope/filter settings to obtain an image using electrons that have lost energy. Ideally you would like to form this image at the energy loss corresponding to the signal you wish to map, e.g., the core-loss energy for a particular element. However, this may be impractical if the signal is at high energy loss as there may be insufficient signal to obtain a suitable image. If this is the case, obtain an image in the 100–200 eV energy-loss range. (c) Obtain a live image at this energy loss. Depending on the detectors available, this image could be acquired onto a TV-rate camera or live with a CCD camera. (d) Optimize the image by adjusting the focus. You may need to adjust the beam intensity and acquisition time to provide sufficient image quality for accurate focusing. (e) Return to viewing the zero-loss/elastic image. You may need to adjust the beam intensity and camera settings to avoid saturating the camera.

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8. Align the energy filter. On older systems this had to be done manually. On current systems the filter alignments are corrected automatically through software (using the “TUNE GIF” button). You may be asked to adjust the beam intensity during the alignment process. Once the filter is successfully tuned, do not change magnification or you will need to retune the filter. 9. Find the area of interest. 10. Adjust the beam intensity until the beam is slightly larger than the field of view. This ensures maximum intensity is available for the element mapping (low signal levels will produce poor quality data that can give misleading results). 11. Determine the effective thickness of the specimen by acquiring a thickness map (by selecting “Acquire thickness map” from the menu options). If the sample is too thick (typically t/λ >1, where t is the absolute thickness and λ is the mean free path for inelastic scattering of the electrons), move to a thinner part of the section. If the entire section is too thick, you will need to cut thinner sections. 12. Acquire an element map (by selecting “Acquire element map” from the menu options): (a) When selecting the element, you will need to specify the electron energy losses at which the signal and background images will be acquired. Ideally these should be optimized as discussed in Subheading 1 if you are to obtain the highest quality, most reliable data. (b) Select an acquisition time to obtain images with sufficient signal-to-noise to ensure accurate background removal and good quality data. Typically, the higher the energy loss being acquired, the longer the acquisition time that is required. Some level of compromise between signal level and acquisition time may be required as very long acquisition times (several min) may result in specimen drift, which in turn results in image artifacts. 13. Once the signal and background images have been acquired, they must be aligned to account for sample drift. This is usually done automatically through software but can be done manually if needed. The long acquisition times associated with EFTEM often lead to X-rays hitting the detector. This can lead to errors in the automated image alignment function. If this happens, image processing can be used to remove the X-rays and the alignment repeated. 14. Save the raw signal and background images together with the element map. This allows you to reprocess the data at a later date if required, for example, calculating a jump ratio image for comparison with the element map.

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Notes 1. A frozen sample can be produced in various ways, including plunge, slam, and high-pressure freezing. The goal of freezing is to instantaneously immobilize all biological activity (and elements of interest), thereby preserving the sample close to its native state. The growth of ice crystals remains the principal artifact arising from the freezing process and must be avoided at all costs. The only reliable method for freezing samples to a depth >10 μm without noticeable ice damage is high-pressure freezing. For a detailed appraisal of sample preparation by high-pressure freezing, see Chapter 8 of this volume. 2. An extracellular filler is needed to A) fill all empty spaces surrounding the sample during the freezing process and B) bind any free water present surrounding the sample to assist in the freezing process. Intracellular cryoprotectants that penetrate cells/tissues should be avoided as they can interrupt cellular processes and potentially redistribute mobile ions. The addition of agarose or BSA to culture media or a suitable buffer that is physiologically compatible with the sample (such as phosphate buffered saline) is a common approach if studying cultured cells or tissues, respectively. In the EELS/EFTEM context, the elemental composition of the filler should be considered with respect to those elements that are intended for analysis. 3. Freeze-substitution is a process where the ice present in a frozen sample is replaced by an organic solvent at low temperature. It is essentially a dehydration process that, once complete, allows the sample to be returned to room temperature and processed into resin. In the context of conducting EELS/ EFTEM, the freeze-substitution step is responsible for most of the movement/extraction of diffusible ions in biological samples. Careful thought must be given to factors such as the solubility of the elements of interest and how well they are bound to cellular constituents. 4. While EELS/EFTEM can be conducted on most TEM grids, consideration must be given to sample stability (aim to minimize drift during longer acquisitions) and grid composition (which again should not conflict with any elements of interest). In our experience, continuous carbon filmed 200 mesh copper grids suit most applications. 5. As the EELS and EFTEM techniques rely on the assumption that the material being analyzed is of constant thickness, it is important to ensure that sections cut with an ultramicrotome are free from defects. For normal soft tissues and cells, this only occurs if the resin infiltration is poor. Sample heterogeneity can lead to problems with section thickness if significant differences

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exist between the hardness of the sample and the resin. Examples include material that is difficult to infiltrate, such as insect cuticle, or hard structures such as biominerals or certain synthetic nanoparticles. Sections containing these sorts of materials may be unstable under the electron beam or contain holes where material has fallen out during the sectioning process. 6. The section thickness is an important consideration for EELS and EFTEM. While conventional ultrathin sections cut for TEM range from 70 to 100 nm in thickness, the optimum section thickness for EELS/EFTEM depends on several factors, and we typically cut sections in the 120–150 nm range. Higher operating voltages may be necessary for EFTEM to ensure maximum beam current and, therefore, good signal-to-noise. This allows for thicker specimens, which can improve the signal levels by providing a higher projected concentration of the elements under analysis. Increasing the specimen thickness can also improve specimen stability, which is often crucial at the acquisition times required for EFTEM (typically ranging from tens of seconds to several min). 7. In this mode the choice of objective aperture size may affect the spectral data by controlling the collection angle for the spectrometer [2]. 8. By default the spectrometer will be set to view the low-loss (high intensity) region of the spectrum. You are advised to spread the beam to reduce the intensity to prevent damage to the CCD camera. 9. The zero-loss peak alignment for imaging and spectroscopy is typically be different. Thus, it is necessary to make a manual adjustment of the zero peak position when using spectroscopy mode. 10. The choice of objective aperture size will affect the image resolution [29]. Unlike conventional TEM imaging, for EFTEM smaller apertures will yield higher resolution (but with reduced signal levels). A compromise between image resolution and signal-to-noise may therefore need to be made. Most biological EFTEM is conducted at relatively low magnifications such that resolution is not an issue and large objective apertures can be used, which maximize the image intensity. References 1. Brydson R (2001) Electron energy loss spectroscopy. BIOS Scientific Publishers Limited, Oxford 2. Keast VJ, Scott AJ, Brydson R et al (2001) Electron energy-loss near-edge structure—a tool for the investigation of electronic structure on the nanometre scale. J Microsc (Oxford) 203:135–175

3. Thomas PJ, Midgley PA (2002) An introduction to energy-filtered transmission electron microscopy. Topics Catalysis 21:109–138 4. Verbeek J, Van Dyck D, Van Tendeloo G (2004) Energy-filtered transmission electron microscopy: an overview. Spectrochimica Acta Part B 59:1529–1534

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5. Pennycook SJ (2012) Energy-filtered transmission electron microscopy: an overview. MRS Bull 37:943–951 6. Aranova MA, Kim YC, Zhang G et al (2007) Quantification and thickness correction of EFTEM phosphorus maps. Ultramicroscopy 107:232–244 7. Arsenault AL, Ottensmeyer FP (1983) Quantitative spatial distributions of calcium, phosphorus, and sulfur in calcifying epiphysis by high resolution electron spectroscopic imaging. Proc Natl Acad Sci U S A 80:1322–1326 8. Leapman RD, Jarnik M, Stevens AC (1997) Spatial distributions of sulfur-rich proteins in cornifying epithelia. J Struct Biol 120:168–179 9. Clode PL, Saunders M, Ludwig M et al (2009) Urate deposits in symbiotic marine algae. Plant Cell Environ 32:170–177 10. Lipovsek S, Letofsky-Papst I, Hofer F et al (2012) Application of analytical electron microscopic methods to investigate the function of spherites in the midgut of the larval antlion Euroleon nostras (Neuroptera: Myrmeleontidae). Microsc Res Tech 75:397–407 11. Aranova MA, Kim YC, Pivovarova NB et al (2009) Quantitative EFTEM mapping of near physiological calcium concentrations in biological specimens. Ultramicroscopy 109:201–212 12. Shaw JA, Clode PL, Brooker LR et al (2009) The chiton stylus canal: an element delivery pathway for tooth cusp biomineralization. J Morphol 270:588–600 13. Shaw JA, Clode PL, Brooker LR et al (2009) Ultrastructure of the epithelial cells associated with tooth biomineralization in the chiton Acanthopleura hirtosa. Microsc Microanal 15: 154–165 14. Saunders M, Kong C, Shaw JA et al (2009) Characterization of biominerals in the radula teeth of the chiton, acanthopleura hirtosa. J Struct Biol 167:55–61 15. Usher KM, Shaw JA, Kaksonen AH et al (2010) Elemental composition of extracellular polymeric substances and granules in chalcopyrite bioleaching microbes. Hydrometallurgy 104:376–381 16. Saunders M, Kong C, Shaw JA et al (2011) Matrix-mediated biomineralization in marine

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