Single particle analysis: Difference between revisions

Revision as of 15:47, 27 November 2023

Revision as of 01:53, 6 December 2023

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==Techniques==

Single particle analysis can be done on both [[negative stain|negatively stained]] and vitreous ice-embedded [[transmission electron cryomicroscopy]] (CryoTEM) samples. Single particle analysis methods are, in general, reliant on the sample being homogeneous, although techniques for dealing with conformational heterogeneity<ref>{{cite journal |last1=Lyle |first1=N |last2=Das |first2=RK |last3=Pappu |first3=RV |title=A quantitative measure for protein conformational heterogeneity. |journal=The Journal of chemicalChemical physicsPhysics |date=28 September 2013 |volume=139 |issue=12 |pages=121907 |doi=10.1063/1.4812791 |pmid=24089719|pmc=3724800 |bibcode=2013JChPh.139l1907L }}</ref> are being developed.

Images (micrographs) are taken with an electron microscope using [[Charge-coupled device|charged-coupled device]] (CCD) detectors coupled to a phosphorescent layer (in the past, they were instead collected on film and digitized using high-quality scanners). The image processing is carried out using specialized software [[Software tools for molecular microscopy|programs]], often run on multi-processor [[Computer cluster|computer clusters]]. Depending on the sample or the desired results, various steps of two- or three-dimensional processing can be done.

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===Tilt methods===

The specimen stage of the microscope can be tilted (typically along a single axis), allowing the single particle technique known as [[wikibooks:Three_Dimensional_Electron_Microscopy/Initial_model#Random_Conical_Tilt|random conical tilt.]]<ref name="RCT">{{Cite journal|vauthors=Radermacher M, Wagenknecht T, Verschoor A, Frank J |title=Three-dimensional reconstruction from a single-exposure, random conical tilt series applied to the 50S ribosomal subunit of Escherichia coli |journal=Journal of Microscopy |volume=146 |issue=Pt 2 |pages=113–36 |date=May 1987 |pmid=3302267 |doi=10.1111/j.1365-2818.1987.tb01333.x|doi-access=free }}</ref> An area of the specimen is imaged at both zero and at high angle (~60-70 degrees) tilts, or in the case of the related method of orthogonal tilt reconstruction,<ref>{{cite journalbook |last1=Leschziner |first1=A |title=The orthogonal tilt reconstruction method. |journalseries=Methods in enzymologyEnzymology |date=2010 |volume=482 |pages=237-62237–62 |doi=10.1016/S0076-6879(10)82010-5 |pmid=20888964|isbn=9780123849915 }}</ref> +45 and −45 degrees. Pairs of particles corresponding to the same object at two different tilts (tilt pairs) are selected, and by following the parameters used in subsequent alignment and classification steps a three-dimensional reconstruction can be generated relatively easily. This is because the viewing angle (defined as three [[Euler angles]]) of each particle is known from the tilt geometry.

3D reconstructions from random conical tilt suffer from missing information resulting from a restricted range of orientations. Known as the missing cone<ref>{{cite web |url=https://www.c-cina.org/research/algorithms/missing-cone/}}</ref> (due to the shape in reciprocal space), this causes distortions in the 3D maps. However, the missing cone problem can often be overcome by combining several tilt reconstructions. Tilt methods are best suited to [[Negative stain|negatively stained]] samples, and can be used for particles that adsorb to the carbon support film in preferred orientations. The phenomenon known as charging or beam-induced movement<ref>{{cite journal |last1=Li |first1=Xueming |last2=Mooney |first2=Paul |last3=Zheng |first3=Shawn |last4=Booth |first4=Christopher R. |last5=Braunfeld |first5=Michael B. |last6=Gubbens |first6=Sander |last7=Agard |first7=David A. |last8=Cheng |first8=Yifan |title=Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM |journal=Nature Methods |date=June 2013 |volume=10 |issue=6 |pages=584–590 |doi=10.1038/nmeth.2472 |urlpmid=https://www.nature.com/articles/nmeth.247223644547 |language=en |issn=1548-7105|pmc=3684049 }}</ref> makes collecting high-tilt images of samples in vitreous ice challenging.

===Map visualization and fitting===

Various software [[Software tools for molecular microscopy|programs]] are available that allow viewing the 3D maps. These often enable the user to manually dock in protein coordinates (structures from [[X-ray crystallography]] or NMR) of subunits into the electron density. Several programs can also fit subunits computationally.<ref>{{cite web |title=Cryo-EM structure solution with Phenix |url=https://phenix-online.org/documentation/overviews/cryo-em_index.html |website=phenix-online.org}}</ref><ref>{{cite journal |last1=Nicholls |first1=RA |last2=Tykac |first2=M |last3=Kovalevskiy |first3=O |last4=Murshudov |first4=GN |title=Current approaches for the fitting and refinement of atomic models into cryo-EM maps using CCP-EM. |journal=Acta crystallographicaCrystallographica. Section D, Structural biologyBiology |date=1 June 2018 |volume=74 |issue=Pt 6 |pages=492-505492–505 |doi=10.1107/S2059798318007313 |pmid=29872001|pmc=6096485 |bibcode=2018AcCrD..74..492N |doi-access=free }}</ref>

For higher-resolution structures, it is possible to build the macromolecule directly, without prior structual knowledge from other methods. Computer algorithms have also been developed for this task.<ref>{{citation |last1=Jamali |first1=Kiarash |last2=Käll |first2=Lukas |last3=Zhang |first3=Rui |last4=Brown |first4=Alan |last5=Kimanius |first5=Dari |last6=Scheres |first6=Sjors H.W. |title=Automated model building and protein identification in cryo-EM maps |journal=bioRxiv : The Preprint Server for Biology |date=16 May 2023 |pages=2023.05.16.541002 |doi=10.1101/2023.05.16.541002|pmid=37292681 |pmc=10245678 }}</ref>

As high-resolution cyro-EM models are relative new, quality control tools are not as plentiful as it is for X-ray models. Nevertheless, cyro-EM ("real space") versions of the [[difference density map]],<ref>{{cite journal |last1=Yamashita |first1=Keitaro |last2=Palmer |first2=Colin M. |last3=Burnley |first3=Tom |last4=Murshudov |first4=Garib N. |title=Cryo-EM single-particle structure refinement and map calculation using Servalcat |journal=Acta Crystallographica Section D Structural Biology |date=1 October 2021 |volume=77 |issue=10 |pages=1282–1291 |doi=10.1107/S2059798321009475 |pmid=34605431 |pmc=8489229 |bibcode=2021AcCrD..77.1282Y |doi-access=free |quote=}}</ref> cross-validation using a "free" map (comparable to the use of a free [[R-factor]]),<ref>{{cite journal |last1=Falkner |first1=B |last2=Schröder |first2=GF |title=Cross-validation in cryo-EM-based structural modeling. |journal=Proceedings of the National Academy of Sciences of the United States of America |date=28 May 2013 |volume=110 |issue=22 |pages=8930-58930–5 |doi=10.1073/pnas.1119041110 |pmid=23674685|pmc=3670386 |bibcode=2013PNAS..110.8930F |doi-access=free }}</ref><ref>{{cite journal |last1=Beckers |first1=Maximilian |last2=Mann |first2=Daniel |last3=Sachse |first3=Carsten |title=Structural interpretation of cryo-EM image reconstructions |journal=Progress in Biophysics and Molecular Biology |date=March 2021 |volume=160 |pages=26–36 |doi=10.1016/j.pbiomolbio.2020.07.004 |pmid=32735944 |doi-access=free}}</ref> and various [[structure validation]] tools have began to appear.

===Single particle ICP-MS===