Segmentation by classification: A novel and reliable approach for semi-automatic selection of HIV/SIV envelope spikes |
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| Affiliation: | 1. Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530, United States;2. Department of Biological Science, Florida State University, Tallahassee, FL 32306-4295, United States;3. Institute of Molecular Biophysics, Florida State University, Tallahassee, FL 32306-4380, United States;1. School of Fundamental Sciences, Massey University, Private Bag 11-222, Palmerston North, New Zealand;2. Riddet Institute, Massey University, Private Bag 11-222, Palmerston North, New Zealand;1. Hefei National Laboratory for Physical Sciences at Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, PR China;2. Cancer Hospital, Chinese Academy of Science, Hefei, Anhui, PR China;3. School of Life Sciences, Anhui University, Hefei, Anhui, PR China;1. W.M. Keck Center for Transgene Research, University of Notre Dame, Notre Dame, IN 46556, United States;2. Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, United States;3. Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, United States;1. Carbohydrate Enzyme Biotechnology Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India;2. CIISA-Faculdade de Medicina Veterinária, Universidade de Lisboa, Av. da Universidade Técnica, 1300-477 Lisboa, Portugal;1. Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel;2. Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, Israel;3. R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel |
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| Abstract: | We describe a semiautomated approach to segment Env spikes from the membrane envelope of Simian Immunodeficiency Virus visualized by cryoelectron tomography of frozen-hydrated specimens. Multivariate data analysis is applied to a large set of overlapping subvolumes extracted semiautomatically from the viral envelope and does not utilize a template of the target structure. The major manual step used in the method involves determination of six points that define an ellipsoid approximating the virion shape. The approach is robust to departures of the actual virion from this starting ellipsoid. A point cage of sufficient density is generated to ensure that any spike-like protein is identified multiple times. Subsequently translational alignment of class averages to a cylindrical reference on a curved surface separates subvolumes with spikes from those without. Spike containing subvolumes identified multiple times are removed by proximity analysis. Slightly different procedures segment spikes in the equatorial and the polar regions. Once all spikes are segmented, further alignment of class averages using separately the polar and spin angles produces recognizable spike images. Our approach localized 96% of the equatorial spikes and 85% of all spikes identified manually; it identifies a significant number of additional spikes missed by manual selection. Two types of spike shapes were segmented, one with near 3-fold symmetry resembling the conventional spike, the other had a T-shape resembling the spike structure obtained when antibodies such as PG9 bind to HIV Env. The approach should be applicable to segmentation of any protein spikes extending from a cellular or virion envelope. |
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| Keywords: | Cryoelectron microscopy Electron tomography Membrane proteins Multivariate data analysis |
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