3D Variability Analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM
By Ali Punjani, David J. Fleet. 2020
808 citations recorded by the source corpus.
Single particle cryo-EM excels in determining static structures of protein molecules, but existing 3D reconstruction methods have been ineffective in modelling flexible proteins. We introduce 3D variability analysis (3DVA), an algorithm that fits a linear subspace model of conformational change to cryo-EM data at high resolution. 3DVA enables the resolution and visualization of detailed molecular motions of both large and small proteins, revealing new biological insight from single particle cryo-EM data. Experimental results demonstrate the ability of 3DVA to resolve multiple flexible motions of α-helices in the sub-50 kDa transmembrane domain of a GPCR complex, bending modes of a sodium ion channel, five types of symmetric and symmetry-breaking flexibility in a proteasome, large motions in a spliceosome complex, and discrete conformational states of a ribosome assembly. 3DVA is implemented in the cryoSPARC software package.
Subfields: Molecular Biology, Structural Biology
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In Molecular Biology
- Andriy Kryshtafovych
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- John Moult
- Yang Zhang
- Janusz M. Bujnicki
- Minkyung Baek
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In Structural Biology
- Tristan Cragnolini
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- Thomas Mulvaney
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- Aaron Sweeney
- Néstor Sampedro Vallina
Citations in the corpus
- RNA origami scaffolds facilitate cryo-EM characterization of a Broccoli–Pepper aptamer FRET pair (2023, positive): “The 241297 particles from the ‘good’ class were used for 3D Variability Analysis (3DVA) solving for three orthogonal principal modes and a filter resolution of 7 Å (33).”
- Integrating model simulation tools and cryo‐electron microscopy (2022, methodology): “CryoSPARC uses a 3D variability analysis algorithm to identify classes from a continuously variable population of particles 62 : here, probabilistic principal component analysis (where principle components are estimated using an expectation maximization algorithm) 67,68 is used to identify the main…”
- RNA target highlights in CASP15: Evaluation of predicted models by structure providers (2023, methodology): “From multidimensional chemical mapping, 58 medium-resolution cryo-EM maps, 59 and heterogeneity analysis, 60 we obtained one map for the SARS-CoV-2 SL5 domain and four maps for the BtCoV-HKU5 SL5 domain, after data analysis suggested flexibility in SL5a (Table 1).”
- Hallucinating protein assemblies (2022, methodology): “…L120C TEM (FEI Thermo Scientific) equipped with a 4K × 4K Gatan OneView camera at a magnification of 57,000x and pixel size of 2.51 Å. Micrographs collection was automated using EPU software (FEI Thermo Scientific) and were imported into CisTEM software ( 45 ) or cryoSPARC software ( 46 , 47 ).”
- Cryo-EM reveals an entangled kinetic trap in the folding of a catalytic RNA (2022, methodology): “To address this, we first performed 3D variability analysis, which uses probabilistic principal components analysis to fit a linear subspace describing variability in the particles (28), to generate multiple maps across the first principal component (movie S1 and fig.”