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Entropy-regularized deconvolution of cellular cryotransmission electron tomograms
Cryo-electron tomography (cryo-ET) allows for the high-resolution visualization of biological macromolecules. However, the technique is limited by a low signal-to-noise ratio (SNR) and variance in contrast at different frequencies, as well as reduced Z resolution. Here, we applied entropy-regularize...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685678/ https://www.ncbi.nlm.nih.gov/pubmed/34876518 http://dx.doi.org/10.1073/pnas.2108738118 |
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author | Croxford, Matthew Elbaum, Michael Arigovindan, Muthuvel Kam, Zvi Agard, David Villa, Elizabeth Sedat, John |
author_facet | Croxford, Matthew Elbaum, Michael Arigovindan, Muthuvel Kam, Zvi Agard, David Villa, Elizabeth Sedat, John |
author_sort | Croxford, Matthew |
collection | PubMed |
description | Cryo-electron tomography (cryo-ET) allows for the high-resolution visualization of biological macromolecules. However, the technique is limited by a low signal-to-noise ratio (SNR) and variance in contrast at different frequencies, as well as reduced Z resolution. Here, we applied entropy-regularized deconvolution (ER-DC) to cryo-ET data generated from transmission electron microscopy (TEM) and reconstructed using weighted back projection (WBP). We applied deconvolution to several in situ cryo-ET datasets and assessed the results by Fourier analysis and subtomogram analysis (STA). |
format | Online Article Text |
id | pubmed-8685678 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-86856782022-01-06 Entropy-regularized deconvolution of cellular cryotransmission electron tomograms Croxford, Matthew Elbaum, Michael Arigovindan, Muthuvel Kam, Zvi Agard, David Villa, Elizabeth Sedat, John Proc Natl Acad Sci U S A Biological Sciences Cryo-electron tomography (cryo-ET) allows for the high-resolution visualization of biological macromolecules. However, the technique is limited by a low signal-to-noise ratio (SNR) and variance in contrast at different frequencies, as well as reduced Z resolution. Here, we applied entropy-regularized deconvolution (ER-DC) to cryo-ET data generated from transmission electron microscopy (TEM) and reconstructed using weighted back projection (WBP). We applied deconvolution to several in situ cryo-ET datasets and assessed the results by Fourier analysis and subtomogram analysis (STA). National Academy of Sciences 2021-12-07 2021-12-14 /pmc/articles/PMC8685678/ /pubmed/34876518 http://dx.doi.org/10.1073/pnas.2108738118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Croxford, Matthew Elbaum, Michael Arigovindan, Muthuvel Kam, Zvi Agard, David Villa, Elizabeth Sedat, John Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title | Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title_full | Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title_fullStr | Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title_full_unstemmed | Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title_short | Entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
title_sort | entropy-regularized deconvolution of cellular cryotransmission electron tomograms |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685678/ https://www.ncbi.nlm.nih.gov/pubmed/34876518 http://dx.doi.org/10.1073/pnas.2108738118 |
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