Single particle analysis

Last updated
Single particle analysis segments and averages many particles from a sample, allowing for computer algorithms to process the individual images into a combined "representative" image. This allows for improvements in signal to noise, and can be combined with deconvolution to provide limited improvements to spatial resolution in the image. SingleParticleAnalysis.png
Single particle analysis segments and averages many particles from a sample, allowing for computer algorithms to process the individual images into a combined "representative" image. This allows for improvements in signal to noise, and can be combined with deconvolution to provide limited improvements to spatial resolution in the image.

Single particle analysis is a group of related computerized image processing techniques used to analyze images from transmission electron microscopy (TEM). [1] These methods were developed to improve and extend the information obtainable from TEM images of particulate samples, typically proteins or other large biological entities such as viruses. Individual images of stained or unstained particles are very noisy, and so hard to interpret. Combining several digitized images of similar particles together gives an image with stronger and more easily interpretable features. An extension of this technique uses single particle methods to build up a three-dimensional reconstruction of the particle. Using cryo-electron microscopy it has become possible to generate reconstructions with sub-nanometer resolution and near-atomic resolution [2] [3] first in the case of highly symmetric viruses, and now in smaller, asymmetric proteins as well. [4] Single particle analysis can also be performed by inductively coupled plasma mass spectrometry (ICP-MS).

Contents

Techniques

Single particle analysis can be done on both 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 [5] are being developed.

Images (micrographs) are taken with an electron microscope using 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 programs, often run on multi-processor computer clusters. Depending on the sample or the desired results, various steps of two- or three-dimensional processing can be done.

In addition, single particle analysis can also be performed in an individual particle mode using an ICP-MS unit.

Alignment and classification

Biological samples, and especially samples embedded in thin vitreous ice, are highly radiation sensitive, thus only low electron doses can be used to image the sample. This low dose, as well as variations in the metal stain used (if used) [6] means images have high noise relative to the signal given by the particle being observed. By aligning several similar images to each other so they are in register and then averaging them, an image with higher signal-to-noise ratio can be obtained. As the noise is mostly randomly distributed and the underlying image features constant, by averaging the intensity of each pixel over several images only the constant features are reinforced. Typically, the optimal alignment (a translation and an in-plane rotation) to map one image onto another is calculated by cross-correlation.

However, a micrograph often contains particles in multiple different orientations and/or conformations, and so to get more representative image averages, a method is required to group similar particle images together into multiple sets. This is normally carried out using one of several data analysis and image classification algorithms, such as multi-variate statistical analysis and hierarchical ascendant classification, or k-means clustering.[ citation needed ]

Often data sets of tens of thousands of particle images are used, and to reach an optimal solution an iterative procedure of alignment and classification is used, whereby strong image averages produced by classification are used as reference images for a subsequent alignment of the whole data set.

Image filtering

Image filtering (band-pass filtering) is often used to reduce the influence of high and/or low spatial frequency information in the images, which can affect the results of the alignment and classification procedures. This is particularly useful in negative stain images. The algorithms make use of fast Fourier transforms (FFT), often employing Gaussian shaped soft-edged masks in reciprocal space to suppress certain frequency ranges. High-pass filters remove low spatial frequencies (such as ramp or gradient effects), leaving the higher frequencies intact. Low-pass filters remove high spatial frequency features and have a blurring effect on fine details.

Contrast transfer function

Due to the nature of image formation in the electron microscope, bright-field TEM images are obtained using significant underfocus. This, along with features inherent in the microscope's lens system, creates blurring of the collected images visible as a point spread function. The combined effects of the imaging conditions are known as the contrast transfer function (CTF), and can be approximated mathematically as a function in reciprocal space. Specialized image processing techniques such as phase flipping and amplitude correction / Wiener filtering can (at least partially) [7] correct for the CTF, and allow high resolution reconstructions.

Three-dimensional reconstruction

Transmission electron microscopy images are projections of the object showing the distribution of density through the object, similar to medical X-rays. By making use of the projection-slice theorem a three-dimensional reconstruction of the object can be generated by combining many images (2D projections) of the object taken from a range of viewing angles. Proteins in vitreous ice ideally adopt a random distribution of orientations (or viewing angles), allowing a fairly isotropic reconstruction if a large number of particle images are used. This contrasts with electron tomography, where the viewing angles are limited due to the geometry of the sample/imaging set up, giving an anisotropic reconstruction. Filtered back projection is a commonly used method of generating 3D reconstructions in single particle analysis, although many alternative algorithms exist. [3]

Before a reconstruction can be made, the orientation of the object in each image needs to be estimated. Several methods have been developed to work out the relative Euler angles of each image. Some are based on common lines (common 1D projections and sinograms), others use iterative projection matching algorithms. The latter works by beginning with a simple, low resolution 3D starting model and compares the experimental images to projections of the model and creates a new 3D to bootstrap towards a solution.

Methods are also available for making 3D reconstructions of helical samples (such as tobacco mosaic virus), taking advantage of the inherent helical symmetry. Both real space methods (treating sections of the helix as single particles) and reciprocal space methods (using diffraction patterns) can be used for these samples.

Tilt methods

The specimen stage of the microscope can be tilted (typically along a single axis), allowing the single particle technique known as random conical tilt. [8] 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, [9] +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 [10] (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 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 [11] makes collecting high-tilt images of samples in vitreous ice challenging.

Map visualization and fitting

Various software 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. [12] [13]

For higher-resolution structures, it is possible to build the macromolecule directly, without prior structural knowledge from other methods. Computer algorithms have also been developed for this task. [14]

As high-resolution cryo-EM models are relative new, quality control tools are not as plentiful as it is for X-ray models. Nevertheless, cryo-EM ("real space") versions of the difference density map, [15] cross-validation using a "free" map (comparable to the use of a free R-factor), [16] [17] and various structure validation tools have began to appear.

Single particle ICP-MS

Single particle-induced coupled plasma-mass spectroscopy (SP-ICP-MS) is used in several areas where there is the possibility of detecting and quantifying suspended particles in samples of environmental fluids, assessing their migration, assessing the size of particles and their distribution, and also determining their stability in a given environment. SP-ICP-MS was designed for particle suspensions in 2000 by Claude Degueldre. He first tested this new methodology at the Forel Institute of the University of Geneva and presented this new analytical approach at the 'Colloid 2oo2' symposium during the spring 2002 meeting of the EMRS, and in the proceedings in 2003. [18] This study presents the theory of SP ICP-MS and the results of tests carried out on clay particles (montmorillonite) as well as other suspensions of colloids. This method was then tested on thorium dioxide nanoparticles by Degueldre & Favarger (2004), [19] zirconium dioxide by Degueldre et al (2004) [20] and gold nanoparticles, which are used as a substrate in nanopharmacy, and published by Degueldre et al (2006). [21] Subsequently, the study of uranium dioxide nano- and micro-particles gave rise to a detailed publication, Ref. Degueldre et al (2006). [22] Since 2010 the interest for SP ICP-MS has exploded.

Examples

Primary database

Related Research Articles

<span class="mw-page-title-main">Electron microscope</span> Type of microscope with electrons as a source of illumination

An electron microscope is a microscope that uses a beam of electrons as a source of illumination. They use electron optics that are analogous to the glass lenses of an optical light microscope to control the electron beam, for instance focusing them to produce magnified images or electron diffraction patterns. As the wavelength of an electron can be up to 100,000 times smaller than that of visible light, electron microscopes have a much higher resolution of about 0.1 nm, which compares to about 200 nm for light microscopes. Electron microscope may refer to:

<span class="mw-page-title-main">Scanning electron microscope</span> Electron microscope where a small beam is scanned across a sample

A scanning electron microscope (SEM) is a type of electron microscope that produces images of a sample by scanning the surface with a focused beam of electrons. The electrons interact with atoms in the sample, producing various signals that contain information about the surface topography and composition of the sample. The electron beam is scanned in a raster scan pattern, and the position of the beam is combined with the intensity of the detected signal to produce an image. In the most common SEM mode, secondary electrons emitted by atoms excited by the electron beam are detected using a secondary electron detector. The number of secondary electrons that can be detected, and thus the signal intensity, depends, among other things, on specimen topography. Some SEMs can achieve resolutions better than 1 nanometer.

<span class="mw-page-title-main">Structural biology</span> Study of molecular structures in biology

Structural biology, as defined by the Journal of Structural Biology, deals with structural analysis of living material at every level of organization. Early structural biologists throughout the 19th and early 20th centuries were primarily only able to study structures to the limit of the naked eye's visual acuity and through magnifying glasses and light microscopes.

<span class="mw-page-title-main">Inductively coupled plasma mass spectrometry</span> Type of mass spectrometry that uses an inductively coupled plasma to ionize the sample

Inductively coupled plasma mass spectrometry (ICP-MS) is a type of mass spectrometry that uses an inductively coupled plasma to ionize the sample. It atomizes the sample and creates atomic and small polyatomic ions, which are then detected. It is known and used for its ability to detect metals and several non-metals in liquid samples at very low concentrations. It can detect different isotopes of the same element, which makes it a versatile tool in isotopic labeling.

<span class="mw-page-title-main">Transmission electron microscopy</span> Imaging and diffraction using electrons that pass through samples

Transmission electron microscopy (TEM) is a microscopy technique in which a beam of electrons is transmitted through a specimen to form an image. The specimen is most often an ultrathin section less than 100 nm thick or a suspension on a grid. An image is formed from the interaction of the electrons with the sample as the beam is transmitted through the specimen. The image is then magnified and focused onto an imaging device, such as a fluorescent screen, a layer of photographic film, or a detector such as a scintillator attached to a charge-coupled device or a direct electron detector.

Electron crystallography is a method to determine the arrangement of atoms in solids using a transmission electron microscope (TEM). It can involve the use of high-resolution transmission electron microscopy images, electron diffraction patterns including convergent-beam electron diffraction or combinations of these. It has been successful in determining some bulk structures, and also surface structures. Two related methods are low-energy electron diffraction which has solved the structure of many surfaces, and reflection high-energy electron diffraction which is used to monitor surfaces often during growth.

<span class="mw-page-title-main">Scanning transmission electron microscopy</span> Scanning microscopy using thin samples and transmitted electrons

A scanning transmission electron microscope (STEM) is a type of transmission electron microscope (TEM). Pronunciation is [stɛm] or [ɛsti:i:ɛm]. As with a conventional transmission electron microscope (CTEM), images are formed by electrons passing through a sufficiently thin specimen. However, unlike CTEM, in STEM the electron beam is focused to a fine spot which is then scanned over the sample in a raster illumination system constructed so that the sample is illuminated at each point with the beam parallel to the optical axis. The rastering of the beam across the sample makes STEM suitable for analytical techniques such as Z-contrast annular dark-field imaging, and spectroscopic mapping by energy dispersive X-ray (EDX) spectroscopy, or electron energy loss spectroscopy (EELS). These signals can be obtained simultaneously, allowing direct correlation of images and spectroscopic data.

<span class="mw-page-title-main">Transmission electron cryomicroscopy</span>

Transmission electron cryomicroscopy (CryoTEM), commonly known as cryo-EM, is a form of cryogenic electron microscopy, more specifically a type of transmission electron microscopy (TEM) where the sample is studied at cryogenic temperatures. Cryo-EM, specifically 3-dimensional electron microscopy (3DEM), is gaining popularity in structural biology.

<span class="mw-page-title-main">Cryogenic electron tomography</span>

Cryogenic electron tomography (cryoET) is an imaging technique used to reconstruct high-resolution (~1–4 nm) three-dimensional volumes of samples, often biological macromolecules and cells. cryoET is a specialized application of transmission electron cryomicroscopy (CryoTEM) in which samples are imaged as they are tilted, resulting in a series of 2D images that can be combined to produce a 3D reconstruction, similar to a CT scan of the human body. In contrast to other electron tomography techniques, samples are imaged under cryogenic conditions. For cellular material, the structure is immobilized in non-crystalline, vitreous ice, allowing them to be imaged without dehydration or chemical fixation, which would otherwise disrupt or distort biological structures.

<span class="mw-page-title-main">Richard Henderson (biologist)</span> British biologist

Richard Henderson is a British molecular biologist and biophysicist and pioneer in the field of electron microscopy of biological molecules. Henderson shared the Nobel Prize in Chemistry in 2017 with Jacques Dubochet and Joachim Frank."Thanks to his work, we can look at individual atoms of living nature, thanks to cryo-electron microscopes we can see details without destroying samples, and for this he won the Nobel Prize in Chemistry."

<span class="mw-page-title-main">Electron tomography</span>

Electron tomography (ET) is a tomography technique for obtaining detailed 3D structures of sub-cellular, macro-molecular, or materials specimens. Electron tomography is an extension of traditional transmission electron microscopy and uses a transmission electron microscope to collect the data. In the process, a beam of electrons is passed through the sample at incremental degrees of rotation around the center of the target sample. This information is collected and used to assemble a three-dimensional image of the target. For biological applications, the typical resolution of ET systems are in the 5–20 nm range, suitable for examining supra-molecular multi-protein structures, although not the secondary and tertiary structure of an individual protein or polypeptide. Recently, atomic resolution in 3D electron tomography reconstructions has been demonstrated.

Resolution in the context of structural biology is the ability to distinguish the presence or absence of atoms or groups of atoms in a biomolecular structure. Usually, the structure originates from methods such as X-ray crystallography, electron crystallography, or cryo-electron microscopy. The resolution is measured of the "map" of the structure produced from experiment, where an atomic model would then be fit into. Due to their different natures and interactions with matter, in X-ray methods the map produced is of the electron density of the system, whereas in electron methods the map is of the electrostatic potential of the system. In both cases, atomic positions are assumed similarly.

In structural biology, as well as in virtually all sciences that produce three-dimensional data, the Fourier shell correlation (FSC) measures the normalised cross-correlation coefficient between two 3-dimensional volumes over corresponding shells in Fourier space (i.e., as a function of spatial frequency). The FSC is the three-dimensional extension of the two-dimensional Fourier ring correlation (FRC); also known as: spatial frequency correlation function.

Experimental approaches of determining the structure of nucleic acids, such as RNA and DNA, can be largely classified into biophysical and biochemical methods. Biophysical methods use the fundamental physical properties of molecules for structure determination, including X-ray crystallography, NMR and cryo-EM. Biochemical methods exploit the chemical properties of nucleic acids using specific reagents and conditions to assay the structure of nucleic acids. Such methods may involve chemical probing with specific reagents, or rely on native or analogue chemistry. Different experimental approaches have unique merits and are suitable for different experimental purposes.

Virus quantification is counting or calculating the number of virus particles (virions) in a sample to determine the virus concentration. It is used in both research and development (R&D) in academic and commercial laboratories as well as in production situations where the quantity of virus at various steps is an important variable that must be monitored. For example, the production of virus-based vaccines, recombinant proteins using viral vectors, and viral antigens all require virus quantification to continually monitor and/or modify the process in order to optimize product quality and production yields and to respond to ever changing demands and applications. Other examples of specific instances where viruses need to be quantified include clone screening, multiplicity of infection (MOI) optimization, and adaptation of methods to cell culture.

Super-resolution microscopy is a series of techniques in optical microscopy that allow such images to have resolutions higher than those imposed by the diffraction limit, which is due to the diffraction of light. Super-resolution imaging techniques rely on the near-field or on the far-field. Among techniques that rely on the latter are those that improve the resolution only modestly beyond the diffraction-limit, such as confocal microscopy with closed pinhole or aided by computational methods such as deconvolution or detector-based pixel reassignment, the 4Pi microscope, and structured-illumination microscopy technologies such as SIM and SMI.

<span class="mw-page-title-main">Joachim Frank</span> German-born American biophysicist and Nobel laureate (born 1940)

Joachim Frank ; born September 12, 1940) is a German-American biophysicist at Columbia University and a Nobel laureate. He is regarded as the founder of single-particle cryo-electron microscopy (cryo-EM), for which he shared the Nobel Prize in Chemistry in 2017 with Jacques Dubochet and Richard Henderson. He also made significant contributions to structure and function of the ribosome from bacteria and eukaryotes.

<span class="mw-page-title-main">Cryogenic electron microscopy</span> Form of transmission electron microscopy (TEM)

Cryogenic electron microscopy (cryo-EM) is a cryomicroscopy technique applied on samples cooled to cryogenic temperatures. For biological specimens, the structure is preserved by embedding in an environment of vitreous ice. An aqueous sample solution is applied to a grid-mesh and plunge-frozen in liquid ethane or a mixture of liquid ethane and propane. While development of the technique began in the 1970s, recent advances in detector technology and software algorithms have allowed for the determination of biomolecular structures at near-atomic resolution. This has attracted wide attention to the approach as an alternative to X-ray crystallography or NMR spectroscopy for macromolecular structure determination without the need for crystallization.

<span class="mw-page-title-main">Bridget Carragher</span> American physicist

Bridget Olivia Carragher is a South African physicist specialized in electron microscopy.

Microcrystal electron diffraction, or MicroED, is a CryoEM method that was developed by the Gonen laboratory in late 2013 at the Janelia Research Campus of the Howard Hughes Medical Institute. MicroED is a form of electron crystallography where thin 3D crystals are used for structure determination by electron diffraction. Prior to this demonstration, macromolecular (protein) electron crystallography was only used on 2D crystals, for example.

References

  1. ↑ Frank, Joachim (2006). Three-dimensional electron microscopy of macromolecular assemblies: visualization of biological molecules in their native state. Oxford: Oxford University Press. ISBN   978-0-19-518218-7.[ page needed ]
  2. ↑ Zhou ZH (April 2008). "Towards atomic resolution structural determination by single-particle cryo-electron microscopy". Current Opinion in Structural Biology. 18 (2): 218–28. doi:10.1016/j.sbi.2008.03.004. PMC   2714865 . PMID   18403197.
  3. 1 2 Wang Q, Matsui T, Domitrovic T, Zheng Y, Doerschuk PC, Johnson JE (March 2013). "Dynamics in cryo EM reconstructions visualized with maximum-likelihood derived variance maps". Journal of Structural Biology. 181 (3): 195–206. doi:10.1016/j.jsb.2012.11.005. PMC   3870017 . PMID   23246781.
  4. ↑ Bartesaghi, Alberto; Merk, Alan; Banerjee, Soojay; Matthies, Doreen; Wu, Xiongwu; Milne, Jacqueline L. S.; Subramaniam, Sriram (2015-06-05). "2.2 Å resolution CryoTEM structure of β-galactosidase in complex with a cell-permeant inhibitor". Science. 348 (6239): 1147–1151. Bibcode:2015Sci...348.1147B. doi:10.1126/science.aab1576. ISSN   1095-9203. PMC   6512338 . PMID   25953817.
  5. ↑ Lyle, N; Das, RK; Pappu, RV (28 September 2013). "A quantitative measure for protein conformational heterogeneity". The Journal of Chemical Physics. 139 (12): 121907. Bibcode:2013JChPh.139l1907L. doi:10.1063/1.4812791. PMC   3724800 . PMID   24089719.
  6. ↑ Pandithage, Ruwin (2 October 2013). "Brief Introduction to Contrasting for EM Sample Preparation".
  7. ↑ Downing KH, Glaeser RM (August 2008). "Restoration of weak phase-contrast images recorded with a high degree of defocus: the "twin image" problem associated with CTF correction". Ultramicroscopy. 108 (9): 921–8. doi:10.1016/j.ultramic.2008.03.004. PMC   2694513 . PMID   18508199.
  8. ↑ Radermacher M, Wagenknecht T, Verschoor A, Frank J (May 1987). "Three-dimensional reconstruction from a single-exposure, random conical tilt series applied to the 50S ribosomal subunit of Escherichia coli". Journal of Microscopy. 146 (Pt 2): 113–36. doi: 10.1111/j.1365-2818.1987.tb01333.x . PMID   3302267.
  9. ↑ Leschziner, A (2010). "The Orthogonal Tilt Reconstruction Method". Cryo-EM, Part B: 3-D Reconstruction. Methods in Enzymology. Vol. 482. pp. 237–62. doi:10.1016/S0076-6879(10)82010-5. ISBN   9780123849915. PMID   20888964.
  10. ↑ https://www.c-cina.org/research/algorithms/missing-cone/.{{cite web}}: Missing or empty |title= (help)
  11. ↑ Li, Xueming; Mooney, Paul; Zheng, Shawn; Booth, Christopher R.; Braunfeld, Michael B.; Gubbens, Sander; Agard, David A.; Cheng, Yifan (June 2013). "Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM". Nature Methods. 10 (6): 584–590. doi:10.1038/nmeth.2472. ISSN   1548-7105. PMC   3684049 . PMID   23644547.
  12. ↑ "Cryo-EM structure solution with Phenix". phenix-online.org.
  13. ↑ Nicholls, RA; Tykac, M; Kovalevskiy, O; Murshudov, GN (1 June 2018). "Current approaches for the fitting and refinement of atomic models into cryo-EM maps using CCP-EM". Acta Crystallographica. Section D, Structural Biology. 74 (Pt 6): 492–505. Bibcode:2018AcCrD..74..492N. doi: 10.1107/S2059798318007313 . PMC   6096485 . PMID   29872001.
  14. ↑ Jamali, Kiarash; Käll, Lukas; Zhang, Rui; Brown, Alan; Kimanius, Dari; Scheres, Sjors H.W. (16 May 2023), "Automated model building and protein identification in cryo-EM maps", BioRxiv: The Preprint Server for Biology: 2023.05.16.541002, doi:10.1101/2023.05.16.541002, PMC   10245678 , PMID   37292681
  15. ↑ Yamashita, Keitaro; Palmer, Colin M.; Burnley, Tom; Murshudov, Garib N. (1 October 2021). "Cryo-EM single-particle structure refinement and map calculation using Servalcat". Acta Crystallographica Section D Structural Biology. 77 (10): 1282–1291. Bibcode:2021AcCrD..77.1282Y. doi: 10.1107/S2059798321009475 . PMC   8489229 . PMID   34605431.
  16. ↑ Falkner, B; Schröder, GF (28 May 2013). "Cross-validation in cryo-EM-based structural modeling". Proceedings of the National Academy of Sciences of the United States of America. 110 (22): 8930–5. Bibcode:2013PNAS..110.8930F. doi: 10.1073/pnas.1119041110 . PMC   3670386 . PMID   23674685.
  17. ↑ Beckers, Maximilian; Mann, Daniel; Sachse, Carsten (March 2021). "Structural interpretation of cryo-EM image reconstructions". Progress in Biophysics and Molecular Biology. 160: 26–36. doi: 10.1016/j.pbiomolbio.2020.07.004 . PMID   32735944.
  18. ↑ C. Degueldre & P. -Y. Favarger, « Colloid analysis by single particle inductively coupled plasma-mass spectroscopy: a feasibility study », Colloids and Surfaces A: Physicochemical and Engineering Aspects, symposium C of the E-MRS 2002 Spring Meeting in Strasbourg, France, vol. 217, no 1, 28 avril 2003, p. 137–142 (ISSN 0927-7757, DOI 10.1016/S0927-7757(02)00568-X)
  19. ↑ C Degueldre et P. -Y Favarger, « Thorium colloid analysis by single particle inductively coupled plasma-mass spectrometry », Talanta, vol. 62, no 5, 19 avril 2004, p. 1051–1054 (ISSN 0039-9140, DOI 10.1016/j.talanta.2003.10.016
  20. ↑ C. Degueldre, P. -Y. Favarger et C. Bitea, « Zirconia colloid analysis by single particle inductively coupled plasma–mass spectrometry », Analytica Chimica Acta, vol. 518, no 1, 2 août 2004, p. 137–142 (ISSN 0003-2670, DOI 10.1016/j.aca.2004.04.015)
  21. ↑ C. Degueldre, P. -Y. Favarger et S. Wold, « Gold colloid analysis by inductively coupled plasma-mass spectrometry in a single particle mode », Analytica Chimica Acta, vol. 555, no 2, 12 janvier 2006, p. 263–268 (ISSN 0003-2670, DOI 10.1016/j.aca.2005.09.021)
  22. ↑ C. Degueldre, P. -Y. Favarger, R. Rossé et S. Wold, « Uranium colloid analysis by single particle inductively coupled plasma-mass spectrometry », Talanta, vol. 68, no 3, 15 janvier 2006, p. 623–628 (ISSN 0039-9140, DOI 10.1016/j.talanta.2005.05.006
  23. ↑ Arias-Palomo E, Recuero-Checa MA, Bustelo XR, Llorca O (December 2007). "3D structure of Syk kinase determined by single-particle electron microscopy". Biochim. Biophys. Acta. 1774 (12): 1493–9. doi:10.1016/j.bbapap.2007.10.008. PMC   2186377 . PMID   18021750.
  24. ↑ Japanese Protein databank http://www.pdbj.org/emnavi/emnavi_movie.php?id=5137
  25. ↑ Zhang J, Baker ML, Schröder GF, et al. (January 2010). "Mechanism of folding chamber closure in a group II chaperonin". Nature. 463 (7279): 379–83. Bibcode:2010Natur.463..379Z. doi:10.1038/nature08701. PMC   2834796 . PMID   20090755.
  26. ↑ Japanese Protein databank http://www.pdbj.org/emnavi/emnavi_movie.php?id=1623
  27. ↑ Gipson P, Mills DJ, Wouts R, Grininger M, Vonck J, Kühlbrandt W (May 2010). "Direct structural insight into the substrate-shuttling mechanism of yeast fatty acid synthase by electron cryomicroscopy". Proceedings of the National Academy of Sciences of the United States of America. 107 (20): 9164–9. Bibcode:2010PNAS..107.9164G. doi: 10.1073/pnas.0913547107 . PMC   2889056 . PMID   20231485.
  28. ↑ Japanese Protein databank http://www.pdbj.org/emnavi/emnavi_movie.php?id=5160
  29. ↑ Zhang X, Jin L, Fang Q, Hui WH, Zhou ZH (April 2010). "3.3 A cryo-EM structure of a nonenveloped virus reveals a priming mechanism for cell entry". Cell. 141 (3): 472–82. doi:10.1016/j.cell.2010.03.041. PMC   3422562 . PMID   20398923.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.