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Improving Signal to Noise in Labeled Biological Specimens Using Energy-Filtered TEM of Sections with a Drift Correction Strategy and a Direct Detection Device

Published online by Cambridge University Press:  19 March 2014

Ranjan Ramachandra*
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
James C. Bouwer
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
Mason R. Mackey
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
Eric Bushong
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
Steven T. Peltier
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
Nguyen-Huu Xuong
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
Mark H. Ellisman
Affiliation:
Center for Research in Biological Systems, National Center for Microscopy and Imaging Research, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
*
*Corresponding author. raramachandra@ucsd.edu
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Abstract

Energy filtered transmission electron microscopy techniques are regularly used to build elemental maps of spatially distributed nanoparticles in materials and biological specimens. When working with thick biological sections, electron energy loss spectroscopy techniques involving core-loss electrons often require exposures exceeding several minutes to provide sufficient signal to noise. Image quality with these long exposures is often compromised by specimen drift, which results in blurring and reduced resolution. To mitigate drift artifacts, a series of short exposure images can be acquired, aligned, and merged to form a single image. For samples where the target elements have extremely low signal yields, the use of charge coupled device (CCD)-based detectors for this purpose can be problematic. At short acquisition times, the images produced by CCDs can be noisy and may contain fixed pattern artifacts that impact subsequent correlative alignment. Here we report on the use of direct electron detection devices (DDD’s) to increase the signal to noise as compared with CCD’s. A 3× improvement in signal is reported with a DDD versus a comparably formatted CCD, with equivalent dose on each detector. With the fast rolling-readout design of the DDD, the duty cycle provides a major benefit, as there is no dead time between successive frames.

Type
EDGE Special Issue
Copyright
© Microscopy Society of America 2014 

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References

Ahn, C.C. & Krivanek, O.L. (1983). EELS Atlas . Warrendale, PA, USA: Gatan.Google Scholar
Anderson, I.M. (2008). Statistical and systematic errors in EFTEM spectral imaging. Microsc Microanal 14(Suppl 2), 774775. http://www.nist.gov/mml/mmsd/837-802-anderson-2008-medianfilter.cfm.Google Scholar
Aoyama, K., Matsumoto, R. & Komatsu, Y. (2002). How to make mapping images of biological specimens – data collection and image processing. J Electron Microsc 51(4), 257263.Google Scholar
Aronova, M.A., Kim, Y.C., Harmon, R., Sousa, A.A., Zhang, G. & Leapman, R.D. (2008). Three-dimensional elemental mapping of phosphorus by quantitative electron spectroscopic tomography (QuEST). J Struct Biol 161(3), 322335. (Reprinted from J. Struct. Biol, vol. 160, pp. 35–48, 2007).Google Scholar
Aronova, M.A., Kim, Y.C., Pivovarova, N.B., Andrews, S.B. & Leapman, R.D. (2009). Quantitative EFTEM mapping of near physiological calcium concentrations in biological specimens. Ultramicroscopy 109(3), 201212.Google Scholar
Berger, A. & Kohl, H. (1993). Optimum imaging parameters for elemental mapping in an energy filtering transmission electron-microscope. Optik 92(4), 175193.Google Scholar
Bosman, M. & Keast, V.J. (2008). Optimizing EELS acquisition. Ultramicroscopy 108(9), 837846.Google Scholar
Browning, N.D., Wallis, D.J., Nellist, P.D. & Pennycook, S.J. (1997). EELS in the STEM: Determination of materials properties on the atomic scale. Micron 28(5), 333348.Google Scholar
Bushong, E.A., Martone, M.E., Jones, Y.Z. & Ellisman, M.H. (2002). Protoplasmic astrocytes in CA1 stratum radiatum occupy separate anatomical domains. J Neurosci 22(1), 183192.CrossRefGoogle ScholarPubMed
Carter, C.B. & Williams, D.B. (2009). Transmission electron microscopy. New York, USA: Springer.Google Scholar
Daberkow, I., Herrmann, K.H., Liu, L.B. & Rau, W.D. (1991). Performance of electron image converters with yag single-crystal screen and CCD sensor. Ultramicroscopy 38(3–4), 215223.Google Scholar
Direct Electron (2013). Features of DE-12 Camera System. Available at: http://www.directelectron.com/cameras/de/overview/.Google Scholar
Edelstein, A., Amodaj, N., Hoover, K., Vale, R. & Stuurman, N. (2010). Computer Control of Microscopes Using μManager. Current Protocols in Molecular Biology 92, 14.20.114.20.17.Google Scholar
Egerton, R.F. (1984). Parallel-recording systems for electron-energy loss spectroscopy (EELS). J Electron Micr Tech 1(1), 3752.Google Scholar
Egerton, R.F. (1996). Electron Energy-Loss Spectroscopy. New York, USA: Plenum Press.Google Scholar
Egerton, R.F., Li, P. & Malac, M. (2004). Radiation damage in the TEM and SEM. Micron 35(6), 399409.Google Scholar
Fan, G.Y. & Ellisman, M.H. (1993). High-sensitivity lens-coupled slow-scan CCD camera for transmission electron-microscopy. Ultramicroscopy 52(1), 2129.Google Scholar
Fan, G.Y. & Ellisman, M.H. (2000). Digital imaging in transmission electron microscopy. J Microsc (Oxf) 200, 113.Google Scholar
Grogger, W., Varela, M., Ristau, R., Schaffer, B., Hofer, F. & Krishnan, K.M. (2005). Energy-filtering transmission electron microscopy on the nanometer length scale. J Electron Spectrosc 143(2–3), 139147.CrossRefGoogle Scholar
Heil, T., Gralla, B., Epping, M. & Kohl, H. (2012). Improving the reliability of the background extrapolation in transmission electron microscopy elemental maps by using three pre-edge windows. Ultramicroscopy 118, 1116.Google Scholar
Heil, T. & Kohl, H. (2010). Optimization of EFTEM image acquisition by using elastically filtered images for drift correction. Ultramicroscopy 110(7), 745750.Google Scholar
Hofer, F., Grogger, W., Kothleitner, G. & Warbichler, P. (1997). Quantitative analysis of EFTEM elemental distribution images. Ultramicroscopy 67(1–4), 83103.Google Scholar
Howell, S.B. (2006). Handbook of CCD Astronomy. Cambridge, UK: Cambridge University Press.Google Scholar
Hunt, J.A. & Williams, D.B. (1991). Electron energy-loss spectrum-imaging. Ultramicroscopy 38(1), 4773.Google Scholar
Jin, L., Milazzo, A.C., Kleinfelder, S., Li, S.D., Leblanc, P., Duttweiler, F., Bouwer, J.C., Peltier, S.T., Ellisman, M.H. & Xuong, N.H. (2008). Applications of direct detection device in transmission electron microscopy. J Struct Biol 161(3), 352358.Google Scholar
Krivanek, O., Gubbens, A., Kundmann, M. & Carpenter, G. (1993). Elemental mapping with an energy-selecting imaging filter. In Proceedings of The Annual Meeting-Electron Microscopy Society Of America, Microscopy Society of America (ed.), pp. 586586. San Francisco, CA, USA: San Francisco Press.Google Scholar
Leapman, R.D. (2003). Detecting single atoms of calcium and iron in biological structures by electron energy-loss spectrum-imaging. J Microsc (Oxf) 210, 515.Google Scholar
Leapman, R.D. & Aronova, M.A. (2007). Localizing specific elements bound to macromolecules by EFTEM. Method Cell Biol 79, 593613.Google Scholar
Lozano-Perez, S., Bernal, V.D. & Nicholls, R.J. (2009). Achieving sub-nanometre particle mapping with energy-filtered TEM. Ultramicroscopy 109(10), 12171228.Google Scholar
Meijering, E., Dzyubachyk, O. & Smal, I. (2012). Methods for cell and particle tracking. Method Enzymol 504, 183200.Google Scholar
Milazzo, A.C., Lanman, J., Bouwer, J.C., Jin, L., Peltier, S.T., Johnson, J.E., Kleinfelder, S., Xuong, N.H. & Ellisman, M.H. (2009). Advanced detector development for electron microscopy enables new insight into the study of the virus life cycle in cells and Alzheimer’s disease. Microsc Microanal 15, 89.Google Scholar
Milazzo, A.C., Leblanc, P., Duttweiler, F., Jin, L., Bouwer, J.C., Peltier, S., Ellisman, M., Bieser, F., Matis, H.S., Wieman, H., Denes, P., Kleinfelder, S. & Xuong, N.H. (2005). Active pixel sensor array as a detector for electron microscopy. Ultramicroscopy 104(2), 152159.Google Scholar
Milazzo, A.C., Moldovan, G., Lanman, J., Jin, L.A., Bouwer, J.C., Klienfelder, S., Peltier, S.T., Ellisman, M.H., Kirkland, A.I. & Xuong, N.H. (2010). Characterization of a direct detection device imaging camera for transmission electron microscopy. Ultramicroscopy 110(7), 741744.Google Scholar
Mitchell, D. (2002). Dave Mitchell DigitalMicrograph Scripting Website. Available at http://www.dmscripting.com/copy_all_tags_between_images.html.Google Scholar
Schaffer, B., Grogger, W. & Kothleitner, G. (2004). Automated spatial drift correction for EFTEM image series. Ultramicroscopy 102(1), 2736.Google Scholar
Shigematsu, H. & Sigworth, F.J. (2013). Noise models and cryo-EM drift correction with a direct-electron camera. Ultramicroscopy 131, 6169.Google Scholar
Shu, X.K., Lev-Ram, V., Deerinck, T.J., Qi, Y.C., Ramko, E.B., Davidson, M.W., Jin, Y.S., Ellisman, M.H. & Tsien, R.Y. (2011). A genetically encoded tag for correlated light and electron microscopy of intact cells, tissues, and organisms. PLos Biol 9(4), 110.Google Scholar
Shuman, H. & Kruit, P. (1985). Quantitative data-processing of parallel recorded electron energy-loss spectra with low signal to background. Rev Sci Instrum 56(2), 231239.Google Scholar
Suenaga, K., Sato, Y., Liu, Z., Kataura, H., Okazaki, T., Kimoto, K., Sawada, H., Sasaki, T., Omoto, K., Tomita, T., Kaneyama, T. & Kondo, Y. (2009). Visualizing and identifying single atoms using electron energy-loss spectroscopy with low accelerating voltage. Nat Chem 1(5), 415418.Google Scholar
Terada, S., Aoyama, T., Yano, F. & Mitsui, Y. (2001). Time-resolved acquisition technique for elemental mapping by energy-filtering TEM. J Electron Microsc 50(2), 8387.Google Scholar
Xuong, N.H., Jin, L., Kleinfelder, S., Li, S.D., Leblanc, P., Duttweiler, F., Bouwer, J.C., Peltier, S.T., Milazzo, A.C. & Ellisman, M. (2007). Future directions for camera systems in electron microscopy. Method Cell Biol 79, 721739.Google Scholar
Xuong, N.H., Milazzo, A.C., Leblanc, P., Duttweiler, F., Bouwer, J.C., Peltier, S.T., Ellisman, M., Denes, P., Bieser, F. & Matis, H.S. (2004). First use of a high-sensitivity active pixel sensor array as a detector fpr electron microscopy. Proc SPIE 5301, 242.Google Scholar
Zhang, P.J., Land, W., Lee, S., Juliani, J., Lefman, J., Smith, S.R., Germain, D., Kessel, M., Leapman, R., Rouault, T.A. & Subramaniam, S. (2005). Electron tomography of degenerating neurons in mice with abnormal regulation of iron metabolism. J Struct Biol 150(2), 144153.Google Scholar