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Effects of Chloramphenicol Treatment on Cellular Storage Granules and Membrane Structures in Rhodobacter sphaeroides

Published online by Cambridge University Press:  22 July 2022

Daniel Parrell
Affiliation:
Department of Biochemistry, University of Wisconsin, Madison, WI DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI
Rachelle A.S. Lemke
Affiliation:
DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI
Joseph Olson
Affiliation:
Department of Biochemistry, University of Wisconsin, Madison, WI
Timothy J. Donohue
Affiliation:
DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI
Elizabeth R. Wright*
Affiliation:
Department of Biochemistry, University of Wisconsin, Madison, WI DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI
*
*Corresponding authors: erwright2@wisc.edu

Abstract

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Type
3D Volume Electron Microscopy in Biology Research
Copyright
Copyright © Microscopy Society of America 2022

References

Mastronarde, D. N. (2005). Automated electron microscope tomography using robust prediction of specimen movements. J Struct Biol, 152(1), 36-51. doi:10.1016/j.jsb.2005.07.007CrossRefGoogle ScholarPubMed
Kremer, J. R., Mastronarde, D. N., & McIntosh, J. R. (1996). Computer visualization of three-dimensional image data using IMOD. J Struct Biol, 116(1), 71-76. doi:10.1006/jsbi.1996.0013CrossRefGoogle ScholarPubMed
Chen, M., et al. Ludtke, S. J. (2017). Convolutional neural networks for automated annotation of cellular cryo-electron tomograms. Nat Methods, 14(10), 983-985. doi:10.1038/nmeth.4405CrossRefGoogle ScholarPubMed
This research was supported by NIH F32 fellowship funds (1F32GM143854) awarded to DP. Funds from the University of Wisconsin-Madison, National Institutes of Health (R01GM104540 and R01GM104540-03S1) to E.R.W, and the Great Lakes Bioenergy Research Center (DOE DE-SC0018409) to T.D. We are grateful for the use of facilities and instrumentation at the Cryo-EM Research Center in the Department of Biochemistry at the University of Wisconsin, Madison.Google Scholar