Classification of single-projection reconstructions for cryo-electron microscopy data of icosahedral viruses

Journal of

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Journal of Structural Biology 151 (2005) 79–91

StructuralBiology

Classification of single-projection reconstructionsfor cryo-electron microscopy data of icosahedral viruses

Sjors H.W. Scheres a, Roberto Marabini b, Salvatore Lanzavecchia c, Francesca Cantele c,Twan Rutten d,e, Stephen D. Fuller d,f, Jose M. Carazo a,b,*, Roger M. Burnett g,*,

Carmen San Martın a,g

a Biocomputing Unit, Centro Nacional de Biotecnologıa, Campus Universidad Autonoma, 28049 Madrid, Spainb Escuela Politecnica Superior, Universidad Autonoma de Madrid, 28049 Madrid, Spain

c Department of Structural Chemistry, University of Milano, via G. Venezian 21, 20133 Milano, Italyd Structural Biology Programme, European Molecular Biology Laboratory, Meyerhofstraße 1, Postfach 10.2209, 69017 Heidelberg, Germany

e Institute for Plant Genetics and Crop Plant Research (IPK) Leibniz-Institute, Corrensstraße 3, D-06466 Gatersleben, Germanyf The Division of Structural Biology, Wellcome Trust Centre for Human Genetics, The Henry Wellcome Building for Genomic Medicine,

University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7BN, UKg The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104, USA

Received 14 February 2005, and in revised form 15 April 2005Available online 12 May 2005

Abstract

We present a novel strategy for classification of heterogeneous electron microscopy data of icosahedral virus particles. The effec-tiveness of the procedure, which is based on classification of single-projection reconstructions (SPRs), is first investigated using sim-ulated data. Of several reconstruction approaches examined, best results were obtained with algebraic reconstruction techniques(ART) when providing prior information about the reconstruction in the form of a starting volume. The results presented indicatethat SPR-classification is sufficiently sensitive to classify assemblies with differences of only a few percent of the total mass. The use-fulness of this procedure is illustrated by application to a heterogeneous cryo-electron microscopy dataset of adenovirus mutantdl313, lacking minor coat protein IX. These data were successfully divided into two distinct classes, in agreement with gel analysisand immuno-electron microscopy results. The classes yielded a wildtype-like reconstruction and a reconstruction representing thepolypeptide IX-deficient dl313 virion. As the largest difference between these volumes is found at the location previously assignedto the external portion of minor coat protein polypeptide IIIa, questions arise concerning the current adenovirus model.� 2005 Elsevier Inc. All rights reserved.

Keywords: Adenovirus; Image classification; Cryo-electron microscopy; Polypeptide IX; Three-dimensional reconstruction

1. Introduction

Three-dimensional electron microscopy (3D-EM) is apowerful tool for structural characterization of icosahe-dral virus particles. The icosahedral symmetry allowsextensive averaging in the structure determination

1047-8477/$ - see front matter � 2005 Elsevier Inc. All rights reserved.

doi:10.1016/j.jsb.2005.04.003

* Corresponding authors.E-mail addresses: [email protected] (J.M. Carazo), burnett@

wistar.upenn.edu (R.M. Burnett).

process, which has led to several EM virus structures withresolutions higher than 10 A (Henderson, 2004). Fre-quently, biochemical purification of viruses (or any othermacromolecular complex) provides samples in which thecomplex may adopt several different conformations, orhave variable protein composition. Although 3D-EM iswell suited to the study of such structurally non-homoge-neous preparations, as it produces images of individualassemblies, sorting these into homogeneous classes hasbeen difficult to accomplish in practice.

mailto:[email protected]

mailto:burnett@

Fig. 1. Positions of capsid proteins in one facet of the currentadenovirus capsid model. Hexons forming the facet are in white andhexons from adjacent facets are in grey. Hexons at the fourindependent positions in the icosahedral asymmetric unit are labeled1–4. Hexons 2–4 in all three asymmetric units in the facet stay togetherupon capsid disruption to form the group-of-nine hexons (GON).Modified from (Stewart et al., 1993).

80 S.H.W. Scheres et al. / Journal of Structural Biology 151 (2005) 79–91

Classification of heterogeneous datasets into struc-turally unique classes is typically hindered by the vari-ation in particle orientation on the specimen support.We have pursued a classification approach for projec-tion data of icosahedral virus particles that seeks toeliminate this variation by reconstructing a single vol-ume for each projection. The icosahedral symmetryof a virus particle allows 60 views to be generated fromany non-axial view. Therefore, a three-dimensionalreconstruction can be calculated from a single projec-tion (Cantele et al., 2003; Caston et al., 1999). Thesesingle-projection reconstructions (SPRs) share a com-mon placement of the icosahedral symmetry axesresulting from the reconstruction procedure. The majorsource of variation among these volumes, besides thenoise, is the structural variability of the sample. Hence,it is possible to classify the EM images using SPRsmore easily than by using the two-dimensional projec-tion data directly.

Several methods exist for EM reconstruction. Mostvirus studies are carried out using Fourier–Bessel inver-sion (FBI (Crowther et al., 1970)), while weightedback-projection (WBP (Radermacher et al., 1992))has been a popular choice for single particles with low-er symmetry (Frank, 1996). The discrete Radon-trans-form method (DRT (Lanzavecchia et al., 1999, 2002))and iterative algebraic reconstruction techniques withblobs (ART (Marabini et al., 1998)) are two relativelynew reconstruction techniques. The former is computa-tionally efficient and has been applied successfully toyield model-free virus reconstructions based on SPRs(Cantele et al., 2003). ART is an iterative real-spacereconstruction technique that can yield results superiorto other methods, especially when the number of pro-jections is limited (Marabini et al., 2004). An addi-tional advantage of iterative real-space reconstructionmethods is that prior information about the volumeto be reconstructed can be incorporated into the recon-struction process with relative ease (Marabini et al.,2004).

To assess whether SPRs calculated with the methodsabove are useful for classifying structures with verysmall differences, we explored their performance withsimulated data. The resultant classification proceduresare generally applicable to projection data for icosahe-dral particles and can distinguish structural differencesas small as 3% of their total mass. We then applied thesemethods to a cryo-EM dataset of a structurally hetero-geneous sample of adenovirus deletion mutant dl313,which lacks polypeptide IX.

Human adenovirus type 5 (Ad5) is widely used forgene therapy and vaccine delivery (Russell, 2000). Thenon-enveloped icosahedral adenovirus virion (with amolecular mass of �150 MDa) is formed from at least11 structural proteins and a linear dsDNA genome(San Martın and Burnett, 2003). Each capsid facet has

12 trimers of the major coat protein, hexon, in a p3net (Fig. 1). Penton base and fiber occupy the vertices.The locations of the minor capsid proteins have been de-duced by combined EM/X-ray imaging studies (Fur-cinitti et al., 1989; Stewart et al., 1993).

The minor coat protein polypeptide IX contributesless than 3% to the virion mass (Furcinitti et al., 1989;Stewart et al., 1993) but is important for its stability(Colby and Shenk, 1981) and can be modified to retargetthe virus for gene transfer (Campos et al., 2004a; Dmi-triev et al., 2002; Vellinga et al., 2004). Experimental evi-dence (Furcinitti et al., 1989; van Oostrum and Burnett,1985) supports a model with polypeptide IX formingfour trimers on the surface of the groups-of-nine hexons(GONs, Fig. 1) that are released on dissociation of thevirion under mild conditions (Laver et al., 1969; Prageet al., 1970; Smith et al., 1965). An Ad5 E1 deletion mu-tant (dl313), lacking polypeptide IX, assembles intowildtype-like particles but has lower thermal stability(Colby and Shenk, 1981). It has been shown that IX de-leted mutants only pack up to 97% of the complete viralgenome (Ghosh-Choudhury et al., 1987).

We used three-dimensional (3D) reconstruction fromcryo-EM images to study dl313 mutant virions andinvestigate the structural effects of polypeptide IX. How-ever, biochemical and immuno-EM analysis showedthat the preparation contained a large proportion ofpolypeptide IX-containing virions. Using our newSPR-classification method, two distinct classes were suc-cessfully identified. These classes yielded two reconstruc-tions: a wildtype-like reconstruction and onerepresenting the polypeptide IX-deficient dl313 virion.The unexpected differences between these two arediscussed.

S.H.W. Scheres et al. / Journal of Structural Biology 151 (2005) 79–91 81

2. Materials and methods

2.1. Test data design

Simulated volumes (phantoms) were made using aquasi-atomic model of the Ad5 wildtype capsid. Thismodel was obtained by fitting the crystallographic struc-ture of hexon (Protein Data Bank Identifier 1P30) (Ruxet al., 2003) to a 15 A Ad5 wildtype cryo-EM recon-struction (see below) as described (San Martın et al.,2001). A volume of 251 · 251 · 251 voxels (4 A/voxel)was obtained by positioning blobs of density at the posi-tions of all Ca-atoms in the quasi-atomic model. A low-pass Fourier-filter at 25 A was applied, and the resultingvolume was termed the ‘‘wildtype’’ phantom. Similarly,a ‘‘mutant’’ phantom was built by omitting one of thetower domains of hexon 2 from the capsid model (Fig.2). This deletion of 252 of the 2826 residues from oneof the four hexon trimer structures in the icosahedralasymmetric unit corresponds to less than 3% of the totalmass in the wildtype phantom. Simulated projectiondatasets were obtained by projection onto images of251 · 251 pixels. By sampling the first and second Eulerprojection angles (/ and h) every 2� inside the icosahe-dral asymmetric unit, 181 projections were obtainedfor each phantom volume. Simulating imperfect angularassignments, zero-mean Gaussian noise was applied toall alignment parameters, with standard deviations of0.5� for the three Euler projection angles, and 0.5 pixelsfor the origin offsets. In addition, zero-mean Gaussian

Fig. 2. Simulated data. (A) Surface representation of the phantomvolume (white), with one icosahedral facet outlined (grey) and itsicosahedral symmetry axes marked. The four independent hexons inthe asymmetric unit are numbered 1–4 and the difference densitybetween the wildtype and the mutant phantom (a missing towerdomain in hexon 2) is highlighted in orange. (B) Three examples ofsimulated cryo-EM projections of the mutant phantom volume (signal-to-noise ratio �1.3). (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of thispaper.)

noise with a standard deviation of 25 U was applied tothe pixel intensity values.

2.2. SPR-calculations

Parameters for the different reconstruction programswere optimized comparing SPRs with the known phan-tom volumes. ART-reconstructions were performedwith the Xmipp package (Marabini et al., 1996; Sorzanoet al., 2004). A relaxation parameter of unity was usedfor all single-projection reconstructions. Without astarting volume, five cycles through the data were per-formed; three cycles appeared sufficient when providinga starting volume. Starting volumes were obtained withan ART reconstruction of 35 randomly selected projec-tions from the dataset. For these reconstructions, arelaxation parameter of 0.1 and a single cycle throughthe data were used. FBI was performed with an imple-mentation (FBI_SVD) that uses singular value decom-position (SVD) instead of standard matrix inversion tosolve the system of linear equations (Mancini et al.,2000). This is expected to perform better than the classi-cal method for limited data (Ferlenghi et al., 2001). Thenumber of annuli to be used in the inversion was set tocorrespond to an expected resolution of 30 A. Usingmore annuli did not lead to reconstructions with higherresolution. The singular value threshold was set to 0.5.WBP reconstructions were computed with an algorithmfor general geometry (Radermacher, 1992) using linearinterpolation to reconstruct only the symmetrically inde-pendent part (1/60) of the icosahedral particles (Canteleet al., 2003). DRT reconstructions were computed as de-scribed in (Lanzavecchia et al., 2002). Before computingthe inverse transform, missing data in the Radon spacewere filled with 20 cycles of a restoration filter basedon self consistency of the transform (see Lanzavecchiaet al., 1999, for details).

All SPRs were icosahedrally symmetrized, and (tospare computer resources) stored on grids of 100 ·100 · 100 voxels (10 A/voxel for the phantom; 11.6 Afor the experimental data), with a file size of 4 Mb each.Subsequent analyses were performed using variousprograms of the Xmipp package. Surface rendering wasdone with Amira (http://www.amiravis.com).

2.3. Adenovirus preparation and characterization

Ad5 wildtype and deletion mutant dl313 were pur-chased from the Vector Core Facility of the Universityof Pennsylvania Gene Therapy Program (http://www.uphs.upenn.edu/penngen/gtp/vcore.html). Bothviral samples were produced in 293 cells and purifiedby cesium chloride gradient centrifugation followingstandard procedures. For protein analysis, SDS gradientelectrophoresis of wildtype and dl313 Ad5 samples wascarried out using precast Novex Tris–glycine 4–20% gels

http://www.amiravis.com

http://www.uphs.upenn.edu/penngen/gtp/vcore.html

http://www.uphs.upenn.edu/penngen/gtp/vcore.html

Fig. 3. Single-particle reconstructions. Surface renderings of represen-tative SPRs, calculated using DRT, FBI_SVD, and ART + start. Theupper row shows SPRs calculated from a projection far from anysymmetry axis (/ = 4.3�; h = 83.6�). The lower row shows SPRs froma projection almost parallel to the threefold symmetry axis (/ = �0.4�;h = 70.4�). Reconstructions with ART or WBP yielded SPRs compa-rable to the ones obtained using DRT. Volumes were low-pass filteredto their resolution limit (shown), which was calculated using the 0.5criterion of Fourier-shell correlation with respect to the knownphantom volume.


from Invitrogen. After staining, the gel was scannedand the area below each peak in the intensity plot wasmeasured. Protein content ratios between dl313 andwildtype were calculated for four experiments, averaged,and normalized by adjusting the dl313:wildtype hexonratio to 1.

For immuno-EM, virus samples were adsorbed for5 min onto glow-discharged, Formvar/carbon coatednickel grids. After rinsing with TBS (20 mM Tris–HCl,pH 7.8, 150 mM NaCl) for 2 min and blocking withTBG (1% cold water fish gelatin, 0.1% bovine serum albu-min (BSA) in TBS) for 15 min, grids were incubated for50 min with either a 1/25 dilution of rabbit serum againstpolypeptide IX (Rosa-Calatrava et al., 2001) or a 1/2 rab-bit serum against polypeptide IIIa (Everitt et al., 1992).Grids were rinsed three times with TBG and incubatedwith 15% of 10 nm protein A–gold conjugate (BioCell)in TBS/BSA for 30 min. After three rinses in TBG, andthree in TBS, grids were stained with 2% uranyl acetateand examined in a Philips CM-100 electron microscope.

2.4. Cryo-EM and image processing

Virus samples of wildtype and dl313 Ad5 were vitri-fied in liquid ethane, mounted in a Gatan 626 cryostage,and examined in a Philips CM200 FEG microscopeoperating at 200 kV. Micrographs were recorded onKodak SO163 film under low dose conditions at anominal magnification of 38,000· with underfocus val-ues between 1.5 and 6.5 lm. Micrographs free of driftand astigmatism (34 for wildtype, 37 for dl313) wereselected and digitized in a Zeiss-SCAI scanner using astep size of 7 lm, then interpolated to 14 lm (3.68 Ain the sample).

The contrast transfer function (CTF) parameters ofeach micrograph were determined from its rotationallyaveraged power spectrum, obtained by patch averaging(de Haas et al., 1999). Initial sets of 1107 (wildtype)and 834 (dl313) particles were manually selected withWEB (Frank et al., 1996), extracted into 315 · 315 pixelframes, masked, and centered with SPIDER (Franket al., 1996). Only DNA containing particles (the vastmajority of the population) were selected. Phase inver-sion was corrected by CTF multiplication of the individ-ual images, and orientations were found using themodel-based polar Fourier transform (PFT) method(Baker and Cheng, 1996) with a 35 A resolution Ad2reconstruction (Stewart et al., 1991) as the initial model.Particles with the 10% worst correlation coefficients wererejected after each orientation search iteration, leavingfinal sets with evenly distributed projection angles of926 images for Ad5 wildtype and 714 images for dl313.The resolution of each reconstruction was estimatedusing the FSC = 0.5 criterion. The orientation searchand CTF correction programs are at http://www.stru-bi.ox.ac.uk/strubi/cryo/STRUBI_Virus_Structure.html.

3. Results

3.1. SPR-calculations from simulated projections

Using simulated data, we examined four differentreconstruction approaches for SPR-calculation: ART,DRT, FBI_SVD, and WBP. We also investigated the ef-fect of providing an initial volume to the ART-recon-struction process (ART + start), instead of the defaultoption to start from an all-zero volume (ART). Thestarting volume was obtained by reconstruction of a(heterogeneous) set of multiple projections. Althoughthis map may correspond to a mixture of different struc-tures, it does provide prior information to the recon-struction process about the overall features of thevolume to be reconstructed.

Representative SPRs are shown in Fig. 3. ART +start yielded the most accurate volumes. For the otherfour methods, severe artifacts occurred when the projec-tion direction coincided with a three- or fivefold icosahe-dral symmetry axis. SPRs calculated using ART + startlack these artifacts. A numerical analysis of all SPRs(Table 1) shows that FBI_SVD yielded significantly low-er resolution than the other methods.

To assess classification power, the average local den-sity within the deleted hexon tower was calculated foreach SPR. A separation index (see legend of Table 1)was calculated to measure how well the distributionsof these densities, on the one hand for wildtype SPRs,on the other hand for mutant SPRs, discriminated

http://www.strubi.ox.ac.uk/strubi/cryo/STRUBI_Virus_Structure.html.

http://www.strubi.ox.ac.uk/strubi/cryo/STRUBI_Virus_Structure.html.

Table 1Analysis of SPRs obtained from test projection data with five different approaches: ART with blobs (ART), the discrete Radon-transform method(DRT), Fourier–Bessel inversion (FBI_SVD), weighted back-projection (WBP), and ART with blobs and a starting volume (ART + start)

Resolution (r) (A) Density in wildtype Density in mutant Separation index CPU (min)

l (r) [min,max] l (r) [min,max]

ART 38.6 (3.6) 0.73 (11) [0.45,0.97] 0.25 (10) [0.05,0.51] 3.23 135DRT 38.7 (3.4) 0.79 (12) [0.43,1.03] 0.23 (09) [�0.02,0.50] 3.73 5FBI_SVD 48.6 (2.5) 0.61 (14) [0.07,0.89] 0.19 (11) [�0.03,0.68] 2.36 5WBP 36.6 (2.5) 0.69 (11) [0.41,0.92] 0.26 (10) [0.06,0.54] 2.89 0.1ART + start 36.1 (1.3) 0.73 (05) [0.60,0.84] 0.33 (03) [0.24,0.43] 6.86 80

The average (and standard deviation) values of the resolution limits of all SPRs were calculated using the 0.5 criterion of Fourier-shell correlationwith respect to the known phantom volume. The average local density at the deleted hexon tower (on an absolute scale) was normalized by that in thecorresponding wildtype phantom volume to give average (l), standard deviation (r), minimum (min), and maximum (max) values. The separationindex between the wildtype and mutant densities was calculated as the ratio of the difference to the standard deviation of the difference:ðlwt � lmutÞ=

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffir2wt þ r2mut

p. Approximate CPU times per SPR-calculation were obtained using a 1 GHz Alpha work station.


between the two sets of simulated data. FBI_SVD pro-vided the lowest value, illustrating its relatively poorseparation of wildtype and mutant SPRs. Higher indexvalues were obtained using ART, DRT or WBP. Despitelarge differences in computation times (ART is morethan two orders of magnitude slower than DRT orWBP), the three latter methods yielded comparable re-sults. SPRs calculated using ART + start gave by farthe best separation, as the variation in average local den-sity at the deleted hexon tower within the two subsets ofwildtype or mutant SPRs was relatively small comparedto that for the other methods.

3.2. Classification of simulated data

Phantom datasets with various amounts of structuralheterogeneity were created by mixing ‘‘wildtype’’ and‘‘mutant’’ SPRs in a 50:50, 70:30 or 90:10 ratio. A sim-ple histogram-based method was used to classify theSPRs. First, a normalized three-dimensional standarddeviation map was calculated for all SPRs in each dataset. In these maps, local regions of increased standarddeviation (termed peaks) indicate a large variationamong individual SPRs. The peaks were thresholdedat 3r and used as masks to calculate the average localdensity for all SPRs. A histogram showing the numberof SPRs in each local density range should ideally be bi-modal and indicate how the dataset must be divided toproduce two classes.

A representative standard deviation map and severalcorresponding histograms are shown in Fig. 4. Table 2shows a numerical analysis of all standard deviationmaps. As the only source of variability among the SPRsis the applied mutation, a single standard deviation peakshould lie where the hexon tower was deleted. In prac-tice, artifacts in the SPRs (Fig. 3) generated additionalpeaks in the standard deviation maps for all reconstruc-tion methods. Mainly, these extended radially along thefive- and threefold symmetry axes. Although the SPRscalculated with ART + start lack strong artifacts, the

corresponding standard deviation maps still exhibit in-creases along the symmetry axes, showing that someartifacts remain. The artifactual peaks form a noisybackground that might obscure the relevant one. Conse-quently, low degrees of structural heterogeneity could bedifficult to detect in a real case. At 50:50 and 70:30 wild-type:mutant ratios, all methods except FBI_SVD gavestandard deviation maps with the highest peak at the po-sition of the deleted tower. At a 90:10 ratio, this was nolonger true for any method. Nevertheless, by ruling outthe peaks along the symmetry axes, the relevant onecould still be detected.

The histograms for individual peaks were then in-spected (Fig. 4B). For ART + start, the histograms forpeaks at symmetry axes were relatively narrow and uni-modal. The other methods gave much broader distribu-tions with less clear modality. This corresponds to thelarger artifacts in their SPRs. All methods yielded bimo-dal distributions for the average density at the positionof the mutated hexon tower. In this respect, ART +start again provided the clearest answers and FBI_SVDperformed worst. The tower histograms were used todivide the datasets into two classes (see arrows in Fig.4B) and the results are presented in Table 2. Judgedby the number of misclassified projections, the relativeclassification performance of each method is highly cor-related with the quality of its SPRs (Table 1). Poorest re-sults were obtained with FBI_SVD, while ART + startperformed best, although the differences betweenART + start and the other three methods (ART,DRT, and WBP) were not large. Table 2 also indicatesthat the presence of strong artifactual peaks does notnecessarily impede correct classification, provided thatthe relevant peak can be selected.

Additional tests included the application of generalclassification protocols for multi-variate statistical analy-sis and hierarchical clustering to the calculated SPRs.Whereas most eigenvectors of the multi-variate analysesof these volumes appeared as featureless maps, high-con-trast variations in a sharply defined region were observed

Fig. 4. Classification of simulated datasets. (A) Surface rendering of a representative standard deviation map of SPRs (green) obtained usingART + start for the mixed phantom dataset with a wildtype:mutant ratio of 70:30 (3r threshold). As a reference, the average of all correspondingSPRs is shown in white. Similar standard deviation maps were obtained for all methods, but the relative heights of the peaks varied (Table 2). Hexonsin the asymmetric unit are numbered as before. (B) Histograms of the average density within the peaks at the fivefold and threefold symmetry axes,and within the deleted tower, using DRT, FBI_SVD, and ART + start. The ART and WBP histograms were similar to those obtained with DRT.The arrows in the histograms for density at the deleted tower indicate where the SPRs were divided into two classes. The resultant numbers ofmisclassified projections are shown in Table 2.


in several of them. Successful classifications wereobtained by subsequent hierarchical clustering analysisusing only these eigenvectors (results not shown).

3.3. Characterization of the Ad5 dl313 preparation

A representative part of a dl313 micrograph, togetherwith enlarged views of single particles, is shown in Fig.5. Restriction analysis of total dl313 genomic DNAshowed some additional digestion fragments character-istic of wildtype Ad5 (not shown). The intensity of thecontaminant bands was far weaker than that of thedl313 bands, indicating that mutant particles outnum-bered the revertant wildtype particles in the preparation.However, protein analysis of the mutant preparationshowed otherwise.

Quantification of gel band intensities in an SDS-gelelectrophoresis analysis of wildtype and dl313 Ad5 viri-ons revealed that polypeptide IX in dl313 was 70–80%the level in wildtype Ad5 (Figs. 5C and D). The dl313

and wildtype particles were also investigated usingimmuno-EM (Fig. 6). Using an anti-polypeptide IX ser-um, 100% of the viral particles in the wildtype Ad5 prep-aration were labeled. For dl313, �30% of the virionswere devoid of gold particles. Strikingly, the dl313 labelwas ‘‘all or none’’: while labeled virions had as muchgold as wildtype, the others were completely unlabeled.Thus, these EM observations agreed with the SDS-gelband quantification results and indicated that thedl313 preparation was contaminated with a large pro-portion of virions with a wildtype-like content of poly-peptide IX.

3.4. Classification of the experimental dl313 dataset

We then applied the new classification techniques tothe heterogeneous dl313 dataset. Since ART + startyielded the best results in our phantom tests, we presenthere only the results obtained with this reconstructionmethod. Each SPR-calculation took approximately 2 hon a single 1 GHz Alpha CPU. Fig. 7A shows the resul-tant normalized standard deviation map for all SPRs.Strong radially stretched standard deviation peaks wereobserved along the three- and five-fold symmetry axes(5.9, 11.2r). The strongest peak not situated at a symme-try axis (7.2r, marked by an asterisk in Fig. 7A) was anelongated region at the edge of the icosahedral facet. Inaddition, several minor peaks (4.1–5.1r) appeared with-in the tower domains of all four independent hexons.

The standard deviation peaks were masked using a 3rthreshold, and these masks were used to calculate theaverage local density within each peak for all SPRs(Fig. 7B). As before, histograms of average density atthe symmetry axes showed relatively narrow, unimodaldistributions. Presumably, these peaks correspond tothe artifacts observed in the simulations. Broader distri-butions occurred for the hexon towers, suggesting thatthey have a continuous variation of density. Furtheranalysis revealed that this variation is compatible withsmall scaling differences between the various micro-graphs from which the projections were taken. The onlystandard deviation peak with a clearly bimodal histo-gram was the elongated one at the icosahedral edge.We concluded that this region was the likely source ofstructural heterogeneity.

Tab

le2

Histogram

-based

classificationofmixed

datasetsof18

0phan

tom

projectionswithva

riousratiosofwildtype:mutant(50:50,70

:30,

and90

:10)

usingfive

differentSPR

methods

Peakheigh

tsin

stan

darddeviationmap

sfordifferentwildtype:mutantratios

Number

ofmisclassifications

(outof18

0)

50:50

70:30

90:10

50:50

70:30

90:10

Tower

Fivefold

Threefold

Tower

Fivefold

Threefold

Tower

Fivefold

Threefold

ART

10.9

9.6

7.6

10.0

9.6

8.1

6.7

10.7

8.4

12

0DRT

11.3

10.6

6.6

12.3

9.9

7.0

7.2

12.0

8.3

01

0FBI_SVD

6.3

9.0

4.7

6.6

8.8

4.7

4.2

9.6

5.2

66

6WBP

11.0

9.4

5.6

10.7

9.0

6.1

6.0

10.4

6.6

33

1ART+start

11.5

9.8

6.5

12.3

8.9

7.3

7.5

10.5

8.0

00

0

Thedensities

aregiven(insigm

a)forthehighestpeaksin

allthecorrespondingstan

darddeviationmap

s,whichwerelocatedat

thedeleted

hexontower,orat

thefive-orthreefold

symmetry

axes.

Thetower

peak(3rthreshold)was

usedas

amaskto

assess

theav

erag

elocaldensity.Thecorrespondingone-dim

ensional

histogram

then

was

usedto

dividethedataset

into

twoclasses(F

ig.4).The

number

ofprojectionsthat

weremisclassified

byeach

methodisreported

foreach

dataset.


The dl313 dataset was then divided into two classes of221 and 493 projections, corresponding to low and highdensity at the elongated peak (Fig. 7B), and two sepa-rate volumes with resolutions of 20 and 19 A were ob-tained using FBI_SVD (Figs. 7C and D). In agreementwith the criterion for dividing the dataset into two clas-ses, the strongest difference between the reconstructionsof the two dl313 classes (+11r) was an elongated peak atthe edge of the icosahedral facet (Fig. 7D). This positionis assigned to the external portion of polypeptide IIIa inthe current capsid model (Fig. 1). Weaker, Y-shaped dif-ference density (+5.2r) was observed between the largecavities of the GONs, corresponding to the density as-signed to polypeptide IX. There was no significant dif-ference density inside the capsid, or negative differencedensity. Comparison with an independently determinedreconstruction of wildtype Ad5 at 15 A (not shown) re-vealed that the volume resulting from the larger classwas practically identical to the wildtype capsid structure.Therefore, we termed this the ‘‘wildtype-like’’ dl313

class, while the smaller class was termed ‘‘IX-deficient’’dl313 class.

In view of the unexpected position of the strongestdifference peak, we performed a more detailed analysisof the difference density previously assigned to polypep-tide IX. We found that among all SPRs, the averagedensity in this region has a correlation coefficient of0.73 with the average density at the external polypeptideIIIa position. Moreover, division of the image datasetinto two groups according to the (monomodal) histo-gram of SPR density within the region previously as-signed to polypeptide IX yielded two classes that were88% identical to the classes derived from classificationwith respect to the peak at the edge.

As a control, the SPR standard deviation map wascalculated for a presumably homogeneous wildtypeAd5 dataset. This map (not shown) showed peaks alongthe symmetry axes and within the hexon towers thatwere similar to those for the dl313 Ad5 dataset. Theelongated edge peak was not present, confirming thatit corresponded to the structural change in the mutant.

4. Discussion

4.1. Classification using SPRs

Using simulated data, we demonstrated that SPRscan be used to classify heterogeneous projection sets oficosahedral particles. Of the five SPR approaches exam-ined, FBI_SVD yielded volumes with the poorest resolu-tion. It was correspondingly limited in detectingstructural differences, as demonstrated by the poorestperformance in classifying the phantom data. Presum-ably, this was mainly due to the relatively strong arti-facts in its SPRs. Its performance may reflect the fact

Fig. 5. Characterization of the Ad5 dl313 preparation. (A) A representative cryo-EM field and (B) a gallery of viral particles. The bars represent1000 A in (A) and 500 A in (B). (C) SDS gradient electrophoresis of wildtype and dl313 Ad5 virions. The viral protein corresponding to each band,and the molecular weights of the markers, are indicated. (D) Quantification of gel band intensities. The relative band intensity (Idl313/Iwt) is shown forseveral viral proteins, after setting the hexon ratio to unity.


that the FBI algorithm uses normal equations that mayserve to amplify noise in the reconstruction. This is inagreement with (Caston et al., 1999), who state thatFBI may not allow high resolution SPRs for largeviruses. The use of SVD ameliorates this effect but doesnot completely eliminate it (Fernando, Brady, and Ful-ler, manuscript in preparation) in a standard implemen-tation (Press et al., 1992).

ART + start provided the least artifactual SPRs andperformed best in classification of structural variability,albeit at significant computational cost. The currentimplementation of ART could be speeded up (60 times)by reconstructing only the icosahedral asymmetric unitinstead of the entire volume. All the other methods are re-stricted to the information available from a single projec-tion. When these are near symmetry axes, the effectivenumber of views is reduced to a fraction of the normal60 and consequently their SPRs have severe artifacts.ART + start supplements the low information contentof a single projection with additional knowledge of theoverall features of the volume to be reconstructed. Theprior knowledge is incorporated into the iterative recon-struction process in the form of a starting volume. As thisis obtained by combining a heterogeneous set of projec-

tions, it may be argued that it introduces a source of errorin the reconstruction that cannot be removed by a singleprojection.However, our resultswith simulated data indi-cate that, in practice, ART is not hindered by bias towardsthis incorrect starting volume. In fact, improved wildtypeand mutant SPRs were obtained with ART + start com-pared to plainART,which starts froman all-zero volume.

For classification purposes, the SPR volumes them-selves are less important than correctly assessing andlocating any structural variation among them. Due tothe scarcity of data, single-projection reconstructionsare underdetermined problems, for which many differentvolumes are a possible solution. In ART + start, thestarting volume decreases the intrinsic variability ofthe SPRs by restricting the set of possible solutions tothose nearby. This leads to cleaner SPR standard devia-tion maps and histograms, thus emphasizing any struc-tural variation. Nevertheless, these advantages ofART + start did not necessarily lead to more accurateclasses in our simulated tests (Table 2). Thus, WBPand DRT may be computationally cheap alternativesfor ART + start. In situations where structural variationis subtle, or lies close to a symmetry axis, the superiorperformance of ART + start may be critical for success.

Fig. 6. Immuno-EM labeling of polypeptides IX (upper row) and polypeptide IIIa (lower row) in the Ad5 wildtype and dl313 preparations. Insetsshow the number of gold labels per virus particle in the polypeptide IX labeling experiment. Note the bimodal distribution for dl313, indicating thatapproximately 30% of the virions are completely free of label (arrowheads). Only broken particles are labeled (arrows) with antibodies to thepolypeptide IIIa. The bar represents 2000 A.


Many methods exist that may be used to classifySPRs. The histogram-based method presented herewas merely chosen for its simplicity. A variety of otherclassification methods were tested on the phantom SPRsto see if they would be superior to the simple histogrammethod for the task in this study (detecting a missingsmall piece of structure). The more general multi-variatestatistical analysis and hierarchical clustering protocolsgave very similar results (not shown), although they re-quired more interaction by the user. In addition, wetested the possibility of using the volumes obtained bySPR-classification as initial references for supervisedclassification (Gao et al., 2004). However, we found thatprojection matching of the phantom images with projec-tions of the two volumes yielded very small differences incross-correlation coefficients that were dominated bynoise. Consequently, 30% of the projections were classi-fied incorrectly (versus a maximum of 3% using SPR-classification). The reason for the higher effectivenessof the SPR-classification method may lie in the fact thatit is based on a small part of the 3D-volumes (as indi-cated by regions of locally increased SPR-variance),whereas projection matching takes the entire (noisy)

2D-image into account. Still, we do not exclude that ref-erence-based classification, together with re-alignmentof the experimental images, may be useful in some cases.For example, when structural variation is more complexthan the presence or absence of a piece, or if more thantwo classes are present, the more general approachesmentioned above may be more effective than classifica-tion using histograms of average density in multiple re-gions of the SPRs.

4.2. Ad5 dl313 sample heterogeneity

DNA restriction analysis of the dl313 sample showedsome contamination by wildtype virus, but the amountof wildtype DNA detected was significantly lower thanthat of dl313. Since the mutant was produced in HEK293 cells carrying a large part of the Ad5 genome (Louiset al., 1997), homologous recombination could have oc-curred (Hehir et al., 1996). This is inevitable at low fre-quency, and is especially problematic in viruses carryingE1 deletions with no substituted transgene, as in dl313.However, SDS protein gel quantification and immuno-EM labeling with anti-IX serum indicated that the dl313

Fig. 7. Classification of experimental dl313 data. (A) Surface rendering of the standard deviation map of SPRs (green) obtained using ART + startfor the dl313 dataset (3r threshold). As a reference, a surface rendering of the average of all calculated SPRs is shown in white. (B) Histograms ofaverage local density within the standard deviation peaks at the fivefold and threefold symmetry axes, within one of the hexon towers and at theelongated peak at the edge of the icosahedral facet. The location of the elongated peak is indicated with an asterisk in (A). The arrow indicates thecut-off used to divide the dataset into two classes. (C and D) Surface renderings of the reconstructions obtained using all projections from the classeswith low (C) and high (D) average density within the elongated peak. The contour level of both reconstructions gives 100% of the expected wildtypecapsid (estimated to be 150 MDa at 1.33 g/cm3). Superimposed on the latter volume, the normalized difference map (thresholded at 3r) between thesetwo volumes (high minus low density) is shown in transparent orange. Hexons are numbered as before. The bar represents 100 A in (C and D).


preparation contained only 30% less polypeptide IX thanwildtype Ad5. It is known that the HEK 293 cells rou-tinely used to grow adenovirus E1 mutants can express10–20% the amount of polypeptide IX in a wildtype infec-tion (Takayesu et al., 1994). Our results suggest that aconsiderable amount of this host-expressed polypeptideIX is incorporated into the dl313 virions.

It is striking that the immuno-EM assay showed thatviral particles contained either the whole wildtype com-plement of polypeptide IX or none at all. While the viri-ons that completely lack polypeptide IX may reflectassembly in cells containing little or none of this protein,it seems more likely that incorporation of polypeptideIX is a highly cooperative process. A further factorinfluencing heterogeneity is that dl313 particles are lessstable than wildtype (Colby and Shenk, 1981), whichwould favor their removal during purification. A combi-nation of all three effects (recombination, host cellexpression, and particle instability) is probably responsi-ble for the high amount of polypeptide IX-containingvirions in our dl313 preparation.

4.3. SPR-classification of the dl313 data

The effectiveness of SPR-classification with experi-mental data was illustrated for the structurally heteroge-

neous dl313 sample. Since polypeptide IX accounts forless than 3% of the virion mass and only 30% of the par-ticles in the sample lack this minor coat protein, thiscryo-EM dataset represented a challenging test casefor the new classification techniques. Furthermore,whereas the phantom was a hollow shell, the dl313 par-ticles contained DNA, which may have further compli-cated classification.

Several observations support the conclusion that thedl313 dataset was successfully divided into two struc-tural classes corresponding to wildtype and polypeptideIX-deficient virions: (i) a clearly bimodal distribution ofaverage local density in the SPRs; (ii) the relative size ofthe two classes (29% lack local density) agrees well withthe �30:70 ratio of wildtype and dl313 virions in bothgel quantification and immuno-EM; (iii) the volumereconstructed from the larger class is almost identicalto the known wildtype structure; (iv) the volume recon-structed from the smaller class is significantly differentfrom the latter one.

Some caution should be exercised in using the fourthargument as there is a danger that it can become circu-lar, particularly when histograms do not show clear sep-arations. Maps based on the extremes of density atregions of high variance in the SPR maps are boundto differ. Whenever possible, the classification should


be correlated with other experimental evidence, as forthe polypeptide IX mutant. The argument in this caseis further strengthened by the fact that no structural het-erogeneity was revealed when the same procedures wereapplied to the wildtype Ad5 cryo-EM dataset.

4.4. Analysis of the dl313 difference density

Despite the presumably correct classification of thedl313 data, biologically relevant questions regarding thissample remain. Extensive evidence supports the currentadenovirus capsid model where trimers of polypeptideIX occupy the four large external cavities in the GON(Furcinitti et al., 1989; Stewart et al., 1993; van Oostrumand Burnett, 1985). We had therefore expected to see thelargest difference density between the wildtype-like andIX-deficient dl313 reconstructions in those regions pre-dicted by the model. However, while difference densitywas indeed present at these locations, much stronger dif-ference density was observed at the position currentlyassigned to the external portion of polypeptide IIIa, acomponent required for capsid assembly which pene-trates the hexon shell at the facet edges (Stewart et al.,1993). Furthermore, both differences were highly corre-

Fig. 8. Schematic representation of the SPR classification method, as used(SPR) is calculated for each of the projection images. The standard deviatiopeaks stronger than 3r, that are not situated along the icosahedral symmetryshow the numbers of SPRs in each range of local density. Non-monomodaldata. Conventional reconstruction with these subsets yields high-resolution v

lated. We see two possible explanations for these obser-vations: particles lacking polypeptide IX also lackpolypeptide IIIa; or, polypeptide IX is situated at thesite previously assigned to the external portion of poly-peptide IIIa and the much weaker differences at theGON cavities are an artifact.

The first possibility, loss of both polypeptides IX andIIIa in dl313, agrees with the current capsid model andthe two- and three-dimensional difference imaging dataupon which it was based. However, it does not explainwhy there was no difference density for the inner portionof polypeptide IIIa, which comprises one-third of theprotein mass in the current adenovirus capsid model(Stewart et al., 1993). The second model, involving areassignment of polypeptide IX (and therefore also ofIIIa) is in better agreement with gel quantification re-sults, which indicated that the dl313 preparation con-tained wildtype levels of polypeptide IIIa (Fig. 5).Although this is not evidence that the polypeptide IIIapresent was actually bound to the capsid, immuno-EMresults suggest that this was the case (Fig. 6). Labelingwith anti-IIIa serum produced similar results in wildtypeand dl313 preparations, and no significant differenceswere observed in the quantities of gold particles free

for the dl313 experimental images. A single-projection reconstructionn map of all SPRs is inspected for the presence of relevant peaks, i.e.,axes. Subsequently, histograms are calculated for each relevant peak todistributions indicate structural heterogeneity and how to classify theolumes that are analyzed for their differences.


from the virions, as would be expected if IIIa had beenreleased to the solution. In addition, anti-IIIa labelingonly produced label in broken viral particles, indicatingthat polypeptide IIIa is not accessible to the antibodiesfrom outside the capsid. Furthermore, a recent reportsuggests that there is experimental evidence to supporta relocation of polypeptide IX (Campos et al., 2004b).To comply with the observed stoichiometry (van Oos-trum and Burnett, 1985) in a model with polypeptideIX located at the position previously assigned to poly-peptide IIIa, its 12 copies, now present at only three sitesper facet instead of four, would have to oligomerize intotetramers instead of trimers. However, such a modeldoes not account for the dissociation of the adenoviruscapsid into GONs, which have been shown to containpolypeptide IX (van Oostrum and Burnett, 1985), andcontradicts a 2D EM/X-ray difference analysis wheredensity for polypeptide IX was observed at the GONcavities, and not at the GON edges (Furcinitti et al.,1989).

5. Conclusions

A key finding from our studies is that structural var-iability of icosahedral particles can be classified fromprojection data using SPRs (Fig. 8). SPR-classificationis sufficiently sensitive to classify assemblies with differ-ences of only a few percent of the total mass. In a com-parison of several reconstruction approaches, bestresults were obtained using ART when providing priorinformation about the reconstruction in the form of astarting volume. In principle, any dataset of particleswith icosahedral symmetry may be subjected to SPR-classification. However, the applicability of this methodmay be limited when differences are expected near theicosahedral symmetry axes, since SPRs exhibit artifac-tual density variations in these regions.

The new method showed its utility in revealing aninteresting biological problem that will require furtherinvestigation. Successful classification of a challengingcryo-EM dataset of a heterogeneous adenovirus dl313

mutant preparation yielded two distinct volumes pre-sumed to correspond to wildtype and IX-deficient viri-ons. The fact that the largest difference between themwas at the location previously assigned to the externalportion of polypeptide IIIa was unexpected and raisesquestions about the current adenovirus capsid model.

Note added in proof

A recent report (A quasi-atomic model of humanadenovirus type 5 capsid. Celine M.S. Fabry, ManuelRosa-Calatrava, James F. Conway, Chloe Zubieta, Ste-phen Cusack, Rob W.H. Ruigrok and Guy Schoehn.

The EMBO Journal (2005) 24, 1645–1654) indicates thata different polypeptide IX-deleted Ad5 mutant also lacksdensity at both IX and IIIa positions. Fabry et al. showthat IX-deficient virions loose polypeptide IIIa upon asingle cycle of freezing and thawing.

Acknowledgments

We thank Drs. C. Kedinger and M. Rosa-Calatravafor the anti-IX serum, Dr. E. Everitt for the polypeptideIIIa antibody, Dr. A.K. Sandhu for the DNA-restrictionanalysis, and Dr. L. Xu and P. Hembach for help withprotein electrophoresis and quantification. Fundingcame from grants from the National Institutes of Health(AI-17270), the National Science Foundation (MCB 95-07102), the Wistar Institute Cancer Center (CA 09171),and the Human Frontiers Science Program (RGP0320/2001-M) to R.M.B.; the Spanish Comision Interministe-rial de Ciencia y Tecnologıa (BIO2002-10855-E;BFU2004-00217/BMC), Comunidad Autonoma de Ma-drid (07B-0032), National Institutes of Health(1R01HL70472-01), European Union (QLRI-CT-2001-00015; IST-2003-508833; FP6-502828), and Fondo deInvestigaciones Sanitarias (G03-185) to J.M.C.; First2002 of the University of Milano to S.L.; the WellcomeTrust to S.D.F.; Fundacion BBVA (2004X578) toC.S.M. S.D.F. is a Wellcome Trust Principal ResearchFellow. R.M. is a Ramon y Cajal Research Scientist.

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Classification of single-projection reconstructions for cryo-electron microscopy data of icosahedral viruses