Journal of Structural Biology 156 (2006) 453–460

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Structure determination of clathrin coats to subnanometer resolution by single particle cryo-electron microscopy

Alexander Fotin a, Tomas Kirchhausen b, Nikolaus GrigorieV c, Stephen C. Harrison d, Thomas Walz e, Yifan Cheng e,¤

a Biophysics Graduate Program, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USAb Department of Cell Biology and CBR Institute for Biomedical Research, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA

c Howard Hughes Medical Institute, Rosenstiel Basic Medical Sciences Research Center, Department of Biochemistry, Brandeis University, 415 South Street, Waltham, MA 02454, USA

d Howard Hughes Medical Institute, Children’s Hospital and Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 320 Longwood Avenue, Boston, MA 02115, USA

e Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115, USA

Received 25 March 2006; received in revised form 24 June 2006; accepted 4 July 2006Available online 11 July 2006

Abstract

Clathrin triskelions can assemble into lattices of diVerent shapes, sizes and symmetries. For many years, the structures of clathrin lat-tices have been studied by single particle cryo-electron microscopy, which probed the architecture of the D6 hexagonal barrel clathrincoat at the molecular level. By introducing additional image processing steps we have recently produced a density map for the D6 barrelclathrin coat at subnanometer resolution, enabling us to generate an atomic model for this lattice [Fotin, A., Cheng, Y., Sliz, P., GrigorieV,N., Harrison, S.C., Kirchhausen, T., Walz, T., 2004. Molecular model for a complete clathrin lattice from electron cryomicroscopy. Nature432, 573–579]. We describe in detail here the image processing steps that we have added to produce a density map at this high resolution.These procedures should be generally applicable and may thus help determine the structures of other large protein assemblies to higherresolution by single particle cryo-electron microscopy.© 2006 Elsevier Inc. All rights reserved.

Keywords: Clathrin coats; Clathrin cages; Cryo-electron microscopy; Single particle reconstruction; Endocytosis

1. Introduction

Clathrin-coated vesicles, found in all eukaryotic cells fromyeast to human, transport lipids and selected cargo mole-cules, such as transferrin receptors and low-density lipopro-tein receptors, from the plasma membrane to earlyendosomes. They also carry cargo molecules between thetrans-Golgi network and endosomes. In synapses, clathrin-coated vesicles are involved in the recycling of synapticvesicles and the uptake of neurotransmitters (reviewedin Brodsky et al., 2001; Kirchhausen, 2000; Sudhof, 2004).

* Corresponding author. Present address: Department of Biochemistryand Biophysics, University of California, San Francisco, 600 16th Street,San Francisco, CA 94143, USA. Fax: +1 415 514 4145.

E-mail address: ycheng@biochem.ucsf.edu (Y. Cheng).

1047-8477/$ - see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.jsb.2006.07.001

The building block of clathrin coats is a trimer, referred to asa triskelion, which has three elongated legs radiating from acentral hub (Kirchhausen and Harrison, 1981; Ungewickelland Branton, 1981). The clathrin coat has a striking molecu-lar organization: the clathrin legs intertwine so that thetriskelions form lattices with mostly pentagonal and hexago-nal facets. Assembly of clathrin coats on the membraneaccompanies introduction of membrane curvature, and even-tually the clathrin coat encapsulates a lipid vesicle (Pearseand Crowther, 1987; Ehrlich et al., 2004). Since clathrintriskelions can form lattices of diVerent shapes and sizes,clathrin coats can accommodate a large range of vesicle sizesand hence a large range of cargo proteins. For a detailedreview on clathrin structure and function, see Kirchhausen(2000).

454 A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460

Images of negatively stained clathrin-coated vesiclespuriWed from pig brain Wrst revealed the arrangement of theclathrin triskelions in coats of various designs (Crowtheret al., 1976). In particular, several lattices with high symme-try were identiWed, including what we now designate as thesmall “mini-coat” with tetrahedral symmetry, the “hexago-nal barrel” with D6 symmetry, and the “soccer ball” withicosahedral symmetry (Crowther et al., 1976). A less com-mon lattice design, the “tennis ball”, has the same size andnumber of hexagons and pentagons as the D6 barrel butonly D2 symmetry (Crowther et al., 1976).

Clathrin coats without membrane vesicles can be assem-bled in vitro from puriWed clathrin and adaptor protein(AP) complexes, such as AP-2, resulting in a mixture ofcoats of diVerent sizes and lattices. Typical coat designsinclude the tetrahedral “mini coat” (Fig. 1A), the hexagonalD6 “barrel” (Fig. 1B), and the icosahedral “soccer ball”(Fig. 1C) (Crowther et al., 1976). In vitro assembled clathrincoats were indeed used to calculate the Wrst three-dimen-sional (3D) reconstruction of a D6 barrel clathrin coatusing images obtained by cryo-electron microscopy (cryo-EM) of frozen hydrated specimens (Vigers et al., 1986).Although at a relatively modest resolution, the resultingdensity map conWrmed the previously proposed architec-ture of the D6 barrel, with hexagons at the top and bottomof the coat, each surrounded by six pentagons and joinedtogether by an equatorial ring of six hexagons (Crowtheret al., 1976; Vigers et al., 1986). Because of their high sym-metry and rigidity, in vitro assembled D6 barrels were alsoused for further single particle cryo-EM studies, whicheventually produced a structure at a resolution of 21 Å(Smith et al., 1998). This density map conWrmed the pre-dicted packing of the clathrin triskelions in the lattice. Fur-ther analysis of this density map, in light of the crystalstructure of the N-terminal domain of the clathrin heavychain (ter Haar et al., 1998), further revealed how the clath-

Fig. 1. (A–C) Schematic drawing of clathrin coats: (A) tetrahedral coat(mini-coat), (B) hexagonal D6 barrel coat, and (C) icosahedral coat (soc-cer ball). (D) Cryo-electron micrograph of in vitro assembled clathrincoats in vitriWed ice; mini-coats (thick circle), D6 barrel coats (thin circle)and inset: soccer ball (dashed circle).

rin triskelions interact with each other and how the individ-ual domains are oriented within the lattice (Musacchioet al., 1999).

Since the determination of the 21 Å resolution structureof the D6 clathrin coat (Smith et al., 1998), the instrumenta-tion, image processing algorithms and software packagesused in single particle cryo-EM have advanced consider-ably. In several cases the structures of protein complexeshave now been determined to subnanometer resolution,revealing individual �-helices (e.g., Cheng et al., 2004; Lud-tke et al., 2004). Determining the structures of clathrincoats to a similarly high resolution remained diYcult, how-ever, mainly because in vitro assembled clathrin coats con-sist of a mixture of diVerent sizes and lattice designs.Structural Xexibility, even within a coat population of thesame lattice design, posed further diYculties for obtaininghigher resolution reconstructions, and may have been thereason why most of the recent density maps of clathrincoats also have a resolution of less than 21 Å (Heymannet al., 2005; Smith et al., 2004).

We recently reported a 3D reconstruction of the D6 bar-rel clathrin coat at a nominal resolution of 7.9 Å (Fotinet al., 2004). Based on this subnanometer resolution densitymap and the crystal structures of a proximal region and theN-terminal domain of the clathrin heavy chain, we pro-posed a C� model for a complete D6 barrel clathrin coat.Among the reasons for the higher resolution of our clathrincoat reconstructions are an optimized procedure for theassembly of clathrin coats, the collection of high qualityimages using a microscope equipped with a Weld emissionelectron source, and the use of a new reWnement algorithmimplemented in the program FREALIGN (Stewart andGrigorieV, 2004). In addition, we have made modiWcationsto the image processing procedures. In particular, we haveimplemented strategies to select only clathrin coats withnear-perfect symmetry, to improve the alignment of theparticle images by masking out unstructured regions fromthe reference density map, and to apply “non-crystallo-graphic” averaging. Because these strategies should also beapplicable to the study of other large protein assembliesusing single particle cryo-EM, we describe in this manu-script the details of the procedures we used to improve theresolution of the 3D reconstruction of the clathrin D6 coat.

2. Materials and methods

2.1. Clathrin coats preparation

Clathrin coats (without associated light chains) wereprepared as described in the supplementary information ofFotin et al. (2004).

2.2. Cryo-electron microscopy and image processing

To ensure the structural integrity of the clathrin coats,only freshly in vitro assembled clathrin coats were used fordata collection. The sample was diluted with coats assembly

A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460 455

buVer (Matsui and Kirchhausen, 1990) to a Wnal concentra-tion of »0.05 mg/ml before plunge freezing. 2.5 �l of dilutedsample were applied to a glow-discharged Quantifoil holeycarbon grid (Quantifoil Micro Tools GmbH, Germany),blotted with Wlter paper, and plunged into liquid ethane at¡180 °C using a Reichert KF-80 quick freezing apparatus.

Frozen hydrated clathrin coats were imaged using a Tec-nai F20 electron microscope equipped with a Weld-emissionelectron source (FEI Company, USA) and operated at anacceleration voltage of 200 kV. Micrographs at a defocusranging from ¡2 to ¡5 �m were recorded at a nominalmagniWcation of 50,000£ on Kodak SO-163 Wlm followingstrict low-dose procedures. The negatives were developedfor 12 minutes with full-strength Kodak D-19 developer at20 °C. Micrographs free of obvious drift were digitized witha Zeiss SCAI scanner using a step size of 7 �m. The digi-tized micrographs were binned over 6£ 6 pixels for initialimage processing, re-binned over 3£ 3 pixels during initialreWnement cycles, and over 2£ 2 pixels in the Wnal stages ofreWnement to give a Wnal pixel size on the specimen level of2.8 Å.

The program CTFFIND3 (Mindell and GrigorieV,2003) was used to determine the defocus values for the digi-tized micrographs. The clathrin coats were selected interac-tively using Ximdisp, the display program associated withthe MRC program suite (Crowther et al., 1996). The parti-cle images were subjected to several rounds of multi-refer-ence alignment, multi-variate statistic analysis andclassiWcation using the IMAGIC V software package (vanHeel et al., 1996) following established procedures (vanHeel et al., 2000). Unique class averages were used to gener-ate an initial 3D reconstruction of the D6 barrel clathrincoat by angular reconstitution (van Heel, 1987). No furtherreWnement of the initial 3D reconstruction was carried outwith IMAGIC V. Instead, the program FREALIGN (Stew-art and GrigorieV, 2004) was used to reWne further both theEuler angles and the in-plane shifts, to correct for the con-trast transfer function (CTF), and to calculate further 3Dreconstructions. The resolutions cited in this paper are thenominal resolutions based on the Fourier shell correlation(FSC)D0.143 criterion (Rosenthal and Henderson, 2003).The FSC curves were calculated without removing theunstructured density in the center of the coat. The surface-rendered views of the density maps were produced with theprogram Chimera (Pettersen et al., 2004).

3. Results

3.1. Particle selection

Thon rings (Thon, 1966) are easily seen in a laser diVrac-tometer and are therefore commonly used to assess thequality of micrographs, i.e., to identify images that containhigh-resolution information and are free of drift either dueto specimen charging or specimen movement. This selectionprocedure did not work well for our micrographs of vitri-Wed clathrin coats, because the signal from the vitreous ice

layer is very weak and there were too few particles in eachmicrograph to generate clearly visible Thon rings, espe-cially at higher resolution. Therefore, we could only discardmicrographs that were so strongly aVected by drift that itcould clearly be seen at rather low resolution. Furthermicrograph selection was therefore carried out once theparticles were selected and boxed out from the digitizedmicrographs.

Among diVerent lattice designs present in the in vitroassembled coats, the hexagonal D6 barrel has been the tar-get of almost all cryo-EM studies (Fotin et al., 2004; Hey-mann et al., 2005; Smith et al., 1998, 2004; Vigers et al.,1986). By using stringent relatively high salt assembly con-ditions, D6 barrels containing AP-2 can be made the mostabundant clathrin coat in the preparation, but the forma-tion of other clathrin coats, such as mini coats and soccerballs, cannot be completely prevented. A typical image ofin vitro assembled clathrin coats embedded in vitreous iceshows the presence of these three clathrin lattices (markedby diVerent circles in Fig. 1D). Since the diVerent types ofclathrin coats have diVerent sizes, as a Wrst particle selectioncriterion, only particles with a size consistent with that of ahexagonal D6 barrel were interactively selected from thedigitized micrographs. Viewed along the 6-fold axis, the sizeof the D6 barrel is similar to that of the mini coat. The twocoats can be distinguished, however, because the D6 barrelseen in this orientation displays sharp straight edges whilemini coats appear round. Using this rough size selection cri-terion, 9426 particles of D6 barrel coats were manuallyselected from 350 digitized micrographs.

In a next step to assess the quality of the micrographs,we calculated rotationally averaged Fourier power spectrafor all the boxed-out particles from the individual micro-graphs and obtained an average. Good micrographsrecorded with an electron microscope equipped with a Weldemission electron source should show Thon rings thatextend towards the edge of the power spectrum (Fig. 2A).By contrast, Thon rings from poor micrographs will onlyextend to a relatively low resolution (Fig. 2B). The loss ofThon rings in the high-resolution range can be due to anumber of factors, such as beam-induced specimen move-ment, severe astigmatism of the objective lens and local tiltof the specimen. We did not diVerentiate among thesecauses and simply discarded all micrographs for which thesummed rotationally averaged Fourier power spectra of theparticles did not show Thon rings extending to 1/10 Å¡1.Based on this criterion, particles from 125 of the initial 350digitized micrographs were excluded from further process-ing. A similar procedure to select high quality micrographshas been used in other laboratories (e.g., Saad et al., 2001).We found that there was a direct correlation between thevisibility of the Thon rings in the sum of the rotationallyaveraged Fourier power spectra and the correlation coeY-

cient determined by CTFFIND3 (Mindell and GrigorieV,2003), which is a program that Wnds the defocus values of amicrograph by Wtting simulated Fourier power spectra tothe experimental one. The correlation coeYcient between

456 A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460

the simulated and the experimental Fourier power spec- the 3D reference structure is one of the parameters listed

trum provides a quality estimate for the defocus determina-tion. The micrographs we selected in this step all hadcorrelation coeYcients higher than 0.2.

The remaining particles were subjected to 10 cycles ofiterative multi-reference alignment, multi-variate statisticanalysis and classiWcation, following a standard protocol(van Heel et al., 2000). Particles corresponding to classaverages that did not show well-deWned features or did notcorrespond to the size of D6 barrels were excluded fromfurther image processing. After this second particle selec-tion step, only 5250 particles remained in the data set,about half of the initially selected particles.

We selected the unique class averages and used them toreconstruct an initial 3D density map of the D6 barrelclathrin coat using the angular reconstitution procedureimplemented in the IMAGIC V software package (vanHeel et al., 1996). The initial 3D reconstruction at a nomi-nal resolution of 42 Å (not shown) revealed all the struc-tural features of a D6 barrel clathrin coat expected frompreviously determined structures (e.g., Smith et al., 1998).Further reWnement of the density map was performedusing FREALIGN (Stewart and GrigorieV, 2004). Theweighted correlation coeYcient (named PRES in FRE-ALIGN which is calculated as the inverse cosine of thecorrelation coeYcient) between the particle images and

in the FREALIGN output Wle. Since a lower PRES valueindicates a better match between the particle images andthe reference structure, we used this parameter, togetherwith the FSC curve, to follow the progress of the reWne-ment of the orientational parameters. After 20 iterativereWnement cycles using only relatively low resolutioninformation in the range of 800–40 Å, we displayed thedistribution of particles in PRES bins (Fig. 2C). The histo-gram shows a clearly bimodal distribution of the particleswith a boundary around a PRES value of 62°. Weremoved the particles from the data set that had PRESvalues higher than 62°, corresponding to the second peakin the histogram, and calculated a 3D reconstruction withthe remaining 1450 particles with PRES values lower than62°. The features of the clathrin legs in the resulting 3Dreconstruction were much better deWned than in the onecalculated from the whole dataset of 5250 particles. Thedistribution of particle images into the two peaks had nocorrelation with the orientation of the particles. The 1450“high quality” particles provided all the views needed todeWne the D6 asymmetric unit (see Supplementary Fig. 1din Fotin et al., 2004) and were used for further reWnementcycles. The 3D reconstruction after these reWnementcycles reached a resolution of 14.8 Å (Fig. 3, green FSCcurve). For comparison, the remaining 3,800 particles

Fig. 2. Rotationally averaged summation of Fourier power spectra of all boxed out particles from (A) a “good” micrograph and (B) a micrograph withlimited resolution. The outer ring corresponds to a spatial frequency of 1/10 Å¡1. (C) Distribution of PRES values of aligned clathrin particles. Peak I andpeak II include 1460 and 3790 particles, respectively. The particles in peak I have lower PRES values and are therefore more similar to the reference model.

A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460 457

from the second peak were also used for a separate reWne-ment, but the resulting 3D reconstruction never exceededa resolution of 26 Å (Fig. 3, red FSC curve).

Fig. 3. The FSC curves correspond to 3D reconstructions calculated fromthe particles of the second PRES peak (red), from the particles of Wrstpeak (green), after removing the central unstructured density from the ref-erence map (blue) and after applying a tight mask to the reference map(purple). The FSC curves were calculated without removing the unstruc-tured density in the center of the coat.

3.2. Removing unstructured density from the 3D reference map

All previously published 3D reconstructions of D6 bar-rel clathrin coats showed a layer of unstructured densitybeneath the N-terminal domains of the clathrin legs (Smithet al., 1998, 2004). This layer of density probably representsthe AP-2 complexes, for which the position, and perhapsthe stoichiometry, is likely to vary from coat to coat. Sincetheir arrangements do not follow the D6 symmetry of theclathrin lattices, D6 symmetrization of the 3D reconstruc-tion causes the densities for the AP-2 complexes to besmeared out into a featureless layer of density. Our symme-trized 3D reconstruction obtained with FREALIGN alsocontains this layer of unstructured density. Fig. 4A shows a3D map of the D6 barrel clathrin coat at a resolution of12.5 Å, and removal of the front half of the map reveals thatthe center of the 3D reconstruction is almost completelyWlled with unstructured density (Fig. 4B). In the iterativereWnement process, the 3D reconstruction obtained fromeach cycle is used as the reference 3D map for the nextcycle, to which all the raw images are aligned. The presenceof a central unstructured density in the 3D reference map islikely to cause misalignment of individual particle images,an eVect that will limit the resolution. To prevent its

Fig. 4. The central density of the 3D reference model corresponding to an unstructured AP-2 protein shell was masked out during the reWnement proce-dure. (A) UnmodiWed density map of the reference model and (C) density map of the reference model after removal of the central density. (B) and (D)Same density maps as in (A) and (C) but with the front half removed to show the interior of the density maps.

458 A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460

inXuence on the alignment of the particle images, particu-larly in the high-resolution range, we applied a soft-edgedmask (Gaussian mask with a fall-oV of 6 pixels) to the refer-ence map to remove the central unstructured density(Fig. 3C and D). This procedure further improved the reso-lution of the 3D reconstruction to 13 Å (Fig. 3, blue FSCcurve).

As the reWnement proceeded to high resolution, we alsoapplied a tight mask to the reference map by setting the FRE-ALIGN parameter XSTD to 2.0. This mask removes noisedensities in the solvent area. This procedure is equivalent tosolvent Xattening, which has already been used in other stud-ies (Yonekura and Toyoshima, 2000). At this stage, our 3Dreconstruction of the D6 barrel clathrin coat had a nominalresolution of 12.5Å (Fig. 3, purple FSC curve).

3.3. Local symmetry density averaging

The last step used to improve the resolution of the 3Dreconstruction of the clathrin coat was to apply local sym-metry density averaging. The D6 barrel clathrin coat isformed by 36 triskelions, comprising a total of 108 clathrinmolecules. The D6 symmetry imposed during the reWne-ment procedure only results, however, in a 12-fold averag-ing. Each asymmetric unit thus contains nine independentclathrin molecules and these D6 symmetry-independentmolecules can be averaged to improve further the signal-to-noise ratio of the 3D reconstruction. The procedure usedfor local symmetry density averaging has been described indetail before (Fotin et al., 2004). This Wnal step resulted insubnanometer resolution of our 3D reconstruction of theclathrin coat (7.9 Å, Supplementary Fig. 1e in Fotin et al.,2004).

4. Discussion

To visualize high-resolution features in single particlecryo-EM reconstructions, it is necessary to boost the signal-to-noise ratio of the reconstructions. This task is commonlyaccomplished by averaging thousands of individual particleimages. It is, however, not only the number of particleimages that will determine what resolution the resulting 3Dreconstruction will have but also the quality of thoseimages. We therefore attempted to select only the very bestparticle images for inclusion in the structure determination.Our selection was based on two types of criteria, as shownin the Xow-chart in Fig. 5.

The Wrst criterion concerned the quality of the individualmicrographs (part A in Fig. 5). While this can often simplybe assessed by inspection of the micrographs in a laserdiVractometer, our images of vitriWed clathrin coats did notproduce suYcient signal to see the Thon rings towards highresolution. Therefore, we judged the quality of individualmicrographs based on the Thon rings seen in the sum of therotationally averaged Fourier power spectra from all parti-cles selected from a given micrograph, similar to a previ-ously described method (Saad et al., 2001). This method

requires that particles be selected from all micrographs,even from those that are of poor quality and will be dis-carded at a later stage. This is a signiWcant drawback con-sidering that particle picking, either manually done or usingautomated procedures, is a tedious and time-consumingprocess. We found, however, that there is a correlationbetween our micrograph selection based on the averagedFourier power spectra of the particles and the correlationcoeYcient output by CTFFIND3. In our case, all selectedmicrographs had a correlation coeYcient 70.2, whilemicrographs with a correlation coeYcient of less than 0.2were discarded. Therefore, it seems possible to select highquality micrographs based on the correlation coeYcientfrom CTFFIND3, so that only the particles from “good”images are picked. The cut-oV correlation coeYcient valuemay diVer slightly for diVerent specimens. In the case ofhuman transferrin receptor–transferrin complex (Chenget al., 2004), we used a cut-oV value of 0.18.

Our second selection criterion focused on the structuralheterogeneity of the particles (part B in Fig. 5). In vitroassembled clathrin coats are large protein assemblies dis-playing both structural heterogeneity, such as diVerent lat-tice designs, and structural Xexibility due to their large sizeand hollow interior. Selecting particles with as little devia-tion from the D6 barrel structure as possible should there-fore help signiWcantly in resolving high-resolution featuresin 3D reconstructions. As we used FREALIGN to align theraw images to reference models, we could use the PRESvalue of the individual particle images as a means to iden-tify and discard imperfect particles from the data set. Suchsimilarity criteria between particle images and a referencemodel to remove “bad” particles is commonly used, andwas also used, for example, to select the “best” 9 particles tocalculate a 3D reconstruction of the icosahedral catalyticcore of the pyruvate dehydrogenase complex from Bacillusstearothermophilus (Borgnia et al., 2004). Since the refer-ence model improves from iteration to iteration, the simi-larity between the particle images and the reference modelis assessed in each cycle. During the reWnement of the den-sity map towards higher resolution, the selection of parti-cles that pass the selection criterion may change. In the caseof our D6 barrel clathrin coat, the imperfections of theclathrin coats were most readily detected during reWnementat low resolution, between 800 Å and 40 Å, probablybecause in this low-resolution range raw images of theclathrin coats have clearly deWned features that are not con-taminated by high frequency noise. We therefore perma-nently removed the particles corresponding to the secondpeak in the PRES histogram (Fig. 2) after only 20 reWne-ment cycles. In reWnement cycles including higher resolu-tion information, the diVerence between perfect andimperfect coats becomes smaller due to the contaminatingnoise. Although we did not track the change in PRES val-ues for individual particles during reWnement cycles, thisobservation argues that it becomes less eYcient to sort outthe perfect D6 barrel coats once the reWnement has pro-ceeded to a higher resolution range.

A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460 459

The bimodal distribution of particles in the PRES histo-gram may not be typical, as we did not observe the samedistribution for the tetrahedral coats. One reason might bethe smaller size of the tetrahedral mini-coats, which couldlimit the structural Xexibility in this lattice design. Perma-nently removing bad particles from the data set at an earlystage of the reWnement process based on the PRES valueshould improve the reconstruction, regardless of whetherthere is a bimodal distribution of the particles in the PREShistogram or not. If there is no obvious separation between“good” and “bad” particles in the PRES histogram, thebest cut-oV value has to be experimentally determined. Inthe case of the tetrahedral mini-coats, we simply used thesame PRES cut-oV criterion as in the D6 barrel coats.

3D reconstructions obtained by single particle averagingoften show featureless densities for unstructured domains.For example, the RNA of Sindbis virus appears as anunstructured density in 3D reconstructions with imposedicosahedral symmetry since the RNA in the core is notpacked with icosahedral symmetry (Zhang et al., 2002).Similarly, AP-2 complexes in in vitro assembled clathrincoats do not follow the symmetry of the clathrin lattice. Inour D6-symmetrized reconstructions of the hexagonal bar-rel, the densities for the AP-2 complexes thus appear as a

layer of unstructured density beneath the N-terminaldomains of the clathrin molecules. This unstructured den-sity will contaminate, especially at high-resolution spatialfrequency, the signal from the ordered structural features ofthe 3D reference map, which grows weaker towards higherresolution. Removing featureless density prior to calculat-ing FSC curves thus helps to more accurately estimate theresolution of 3D reconstructions. It is more important,however, to remove the featureless density from the refer-ence map also during the reWnement process itself. Thiseliminates its inXuence on the alignment of the particleimages and thus produces better orientational parametersand a better map. Masking has to be done carefully toavoid the introduction of spurious features in the recon-struction that could inXuence the FSC or could be taken asreal features in the structure. In particular, a smooth edgehas to be used and the mask has to be suYciently generousto make sure it does not aVect density of the structure itself.In our masking procedure, we used a Gaussian mask.

All the image processing steps described here were nec-essary to determine the 3D structure of the D6 barrelclathrin coat to subnanometer resolution. We applied thesame procedures to the clathrin D6 barrel coat with asso-ciated light chains and obtained a density map with a

Fig. 5. Flow chart of particle selections. Part A concerns the selection of good micrographs and part B shows the selection for undistorted particles.

460 A. Fotin et al. / Journal of Structural Biology 156 (2006) 453–460

nominal resolution of 8.2 Å. We believe that similar proce-dures could be applied to other types of large proteinassemblies, such as viruses, to obtain 3D reconstructionsat higher resolutions.

Acknowledgments

We thank Werner Boll and Iris Rapoport for help in thepuriWcation of clathrin and adaptors. This work was sup-ported by National Institutes of Health Grant GM62580(to David DeRosier) and GM36548 (T.K). The molecularEM facility at Harvard Medical School was established bya generous donation from the Giovanni Armenise HarvardCenter for Structural Biology.

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