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Molecular Cell, Volume 39

Supplemental Information

The Three-Dimensional Organization of Polyribosomes in Intact Human Cells Florian Brandt, Lars-Anders Carlson, F. Ulrich Hartl, Wolfgang Baumeister, and Kay Grünewald

Inventory of Supplemental Information

Inventory of Supplemental Information ..................................................................... 1

1 Supplemental Data .............................................................................................. 2

1.1 Supplemental Figure S 1 ............................................................................ 2

1.2 Supplemental Figure S 2 ............................................................................ 4

1.3 Supplemental Figure S 3 ............................................................................ 5

1.4 Supplemental Figure S 4 ............................................................................ 6

1.5 Supplemental Figure S 5 ............................................................................ 7

1.6 Supplemental Figure S 6 ............................................................................ 8

2 Supplemental Experimental Procedures ............................................................. 9

2.1 Next neighbor distribution (NND) ................................................................ 9

2.2 Supplemental Figure S 7 .......................................................................... 10

2.3 Template matching with ribosomal subunits ............................................. 11

3 Supplemental References ................................................................................. 14

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1 Supplemental Data

1.1 Supplemental Figure S 1

As noted in the main text, granular structures 1.5-times larger than ribosomes are

found frequently in tomograms of cells treated with Prm for 10 min. The granules are

often interspersed among ribosome accumulations (Supplemental Figure S1A and

S1A.I). 143 granules were picked manually from 8 tomograms of Prm-treated cells and

aligned to their centers-of-mass (Supplemental Figure S1B). By plotting the spherical

density distribution, it becomes evident that the granules are very similar in size

(Supplemental Figure S1C and S1D) with an average diameter of 38 ± 5 nm (Figure

1E), indicating that the granules probably have a defined composition and stochiometry.

The high electron density suggests a high nucleotide composition or the presence of

ribosomal subunits. It was reported previously, that Prm-induced ribosome run-off and

various other stress conditions lead to the reversible accumulation of 48S pre-initiation

complexes, mRNA, eIF3, eIF4F, PABP and other proteins into so called “stress

granules” (SG), which were so far only observed as large aggregates visible in

fluorescence micrographs after 1 h of Prm-treatment in mammalian cells (Buchan and

Parker, 2009; Kedersha et al., 2000). It is conceivable that the species we detect by

cryoET of Prm-treated cells represent early intermediates of SGs in which one or a few

48S complexes are residing on non-translated, locally sequestered mRNPs. Future

correlative studies that are outside the scope of the present work will further reveal the

identity and structural features of SGs and other RNPs.

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Figure S 1. Size distribution of granular cytosolic densities in puromycin-treated cells. (A) The figure displays a single slice of a subtomogram in the periphery of Prm-treated U87 cells (scale bar, 100 nm). Ribosomes (rib) and cytoskeletal components (act) components are similarily organized as in untreated cells. A granular, unidentified species (arrowheads) is only seen in Prm-treated cells, displayed in the enlarged panel (A.I, scale bar 50 nm). (B) A representative selection of manually picked subvolumes containing the unknown granular species are displayed at a voxel size of 1.642 nm. Box size, 52.5 nm. (C) Spherically averaged density distributions of the particels in (B) are plotted along the radius from the inner to the outer pixels (left to right). The dotted lines indicate the gradient maxima, or the presumed outer edge of the particles. Numbering as in (B). (D) The spherically averaged densities for each of 143 picked granules (from left to right) are plotted from inner to outer pixels (from top to bottom). Note the similar radial edges of the granules indicated by a similar decrease of density. (E) The distribution of spherically averaged radii of 143 granules is plotted with a mean value of 19 ± 2.5 nm.

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1.2 Supplemental Figure S 2

Figure S 2. Comparison of template matching with right and wrong handed references. (A) Slice of a test volume of the reconstructed cytosol of an untreated cell. Visual inspection in all slices volume suggests the presence of ca. 70-100 ribosomal particles. (B) Cross-correlation coefficients (CCC) of the ~140 highest CC peaks of the right or wrong handed template structure (schematics in grey and black). Note the convergence of CCCright and CCCwrong at around peak no. 90 (arrow). (C) CCC histograms of peaks with the right or wrong handed template structure as indicated. (D) Local comparison of peaks pairs that were detected with both templates CCCright/CCCwrong. About 83% of the highest CCCright/ CCCwrong are larger than 1, which gives a rough estimation of the true positive detection rate. The EMDB accession code for a subvolume containing ca. 70-100 untreated cytosolic 80S ribosomes is EMD-5227.

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1.3 Supplemental Figure S 3

Figure S 3. 3D variance analysis of aligned and averaged particle sets. (A) Variance map of 1911 untreated ribosomes. Residual variance can only be seen inside the tRNA channel which can be expected for active ribosomes. (B) Variance map of 1568 Prm-treated ribosomes. No defined variance is detected in the aligned particle set at the attained resolution. Scale, 20 nm.

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1.4 Supplemental Figure S 4

Figure S 4 Comparison of in vivo 80S with mammalian 80S single particle structures. (A) Isosurface representations are shown in front view (from left to right, as indicated) for the template structure (as described in the text), the alignment start reference, the Prm-treated in vivo 80S average structure, the human 80S (Spahn et al., 2004) and the canine ribosome (Chandramouli et al., 2008). Indicated features; L7/L12 stalk, L1 arm, central protuberance (CP), peptide tunnel exit (PT), expansion segments ES7_1 (circle), ES39 (asterisk) (B) As in (A), but in back view, tilted about the x-axis by about 100 deg.

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1.5 Supplemental Figure S 5

Figure S 5 Comparison of nearest neighbor distances in untreated versus Prm-treated cells. The next neighbor center-to-center distance plot for the untreated particle set (1911 particles, black line) and the Prm-treated ribosomes (1568 particles, dashed line) indicates a small but statistically significant increase in median distance from 28.1 nm in the untreated to 32.6 nm in the Prm-treated set (Wilcoxon rank-sum test, p<10e-6).

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1.6 Supplemental Figure S 6

Figure S 6. Unimodal and alternating configurations in modules of tri-somes. The histograms of class population of the second closest neighbor ribosome are plotted for each cluster of closest neighbor configurations. The most frequently occurring configurations of second next neighbors are indicated by class indices. Note that for cluster #118 and cluster #42, the fraction of second next neighbors in the same (# 118, or #42) or in an alternate configuration (# 30, or #125) are almost equally frequent

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2 Supplemental Experimental Procedures

2.1 Next neighbor distribution (NND)

The relative distribution of ribosomes and their next neighbors (next neighbor

distribution, NND) within tomographic reconstructions was performed as follows.

Coordinates and angles of each individual ribosome were refined in a previous cross-

correlation-based alignment method, while keeping track of particle indices, tomogram

indices and the corresponding missing wedge geometry of the reconstruction. Then, the

NND was calculated for n (e.g. 2) next neighbors k of each particle i by back-rotation of

the relative Euclidean distance vectors Δ(x,y,z)ik and relative zxz-rotation matrices M(ψ,

φ, θ)ik into the reference (0,0,0) orientation using the inverted Euler angle set of particle i

(-φ,-θ,-ψ)i. For data clustering, the relative rotation matrices were transformed into

quaternions q(q0,qx,qy,qz)ik. For the (i x n) Euclidean distance vectors and for the relative

(i x n) quaternion sets the similarity of tupel pairs were calculated with a distance metric

of dot products: . Factors wT, wR were used to

weight translational and rotational similarities during hierarchical clustering. A

hierarchical cluster tree was calculated from the distance matrices of all particles to their

corresponding closest neighbor(s) using the linkage function of the MATLAB Statistics

ToolboxTM. Clustering was performed using the cluster function of the same package

using a cutoff distance to limit cluster size.

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All data plots were created using the MATLAB package (The MathWorks® Inc.).

Isosurface representations of structural models were generated using UCSF Chimera

(Pettersen et al., 2004) or 3ds Max® (Autodesk®).

2.2 Supplemental Figure S 7

A

B

Figure S 7. Schematic description of next neighbor nomenclature and description of configurations. (A) The schematic describes the relative numbering of adjacent ribosomes on the mRNA: i+1 ribosomes are located 5’ upstream, and i-1 ribosomes 3´ downstream of ribosome i. (B) The three dots indicate distance vectors from the center of ribosome i to the center (black), the large subunit (blue) or the small subunit (yellow) of its closest neighbor k. Thereby, the relative configuration of adjacent ribosomes i,k can be unambiguously depicted without the use of euler angles.

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2.3 Template matching with ribosomal subunits

To find the limit of reliable detection in a crowded eukaryotic cell a 60S subunit

template was cross-correlated with a tomogram of a crowded eukaryotic cell. Although

the 60S large subunit comprises ~70% of the mass of the entire 80S ribosome, its

overall shape and structural signature is markedly distinct from the entire ribosome and

this will affect the CC. A 60S template can be expected to additionally and preferentially

pick smaller particles in a tomogram of crowded cytoplasm, such as disassembled

subunits or other macromolecules of smaller size. Also, with the density of the 40S

subunit present within the spherical normalization mask, 80S particles are less likely to

be picked by an isolated 60S subunit, hence the resulting particle set is more

heterogenous. Still, in the hypothetical case of noise-less data and far-separated

particles, a 60S template could be expected to select 60S subunits within 80S

ribosomes. Thus, this test gauges the complexity of the experimental data.

We performed this test by direct comparison within one tomogram. In the figure

below, the workflow and results from template matching with 80S or 60S reference

structures and alignment with just a 60S structure are shown (Figure S 8). We calculate

that ca. 75% of 60S correlation peaks do not overlap with the 80S correlation peaks

within 4 voxel (6.6 nm) radius, and hence are probably false positives like dissociated

subunits or non-ribosomal complexes. And yet, additional density of the 40S subunit is

clearly seen at a low resolution in both extracted particle sets (middle and lower right

panels), although less pronounced in the case of particles picked with a 60S template

(lower right). The CC-aligned average of these particles thus does not exhibit the same

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resolution as the 80S dataset due to the expectable heterogeneity of the particle set, as

mentioned above.

Figure S 8. Template matching and 3D alignment with the 80S ribosome or the 60S subunit. The two lower panels on the right show averaged structures of 228, or 302 particles extracted from a cellular tomogram using an 80S, or a 60S reference structure, respectively. In both cases, 3D alignment was performed using a low-pass filtered 60S structure (upper right panel).

To further test the detection limit, we performed template matching with 80S, 60S

and 40S template structures in a simulated tomogram as done in a recent report (Beck

et al., 2009). The simulated tomogram contained the randomly placed electron density

maps (emdb-1480) (Chandramouli et al., 2008) of forty-eight 80S ribosomes, twelve

60S subunits and twelve 40S subunits resized to the experimental binned voxel size of

1.64³ nm³, deformed by the missing wedge and obstructed by the reported noise model

(Beck et al., 2009) at a signal-to-noise ratio of 0.2 (Figure S 9 A). The distribution of

cross-correlation peaks (Figure S 9 B) shows that ribosome identification by CC-

thresholding is more reliable with the 80S template than with the subunits. Thus, the

same test in these synthetic data concurs with the 60S template matching in the

experimental data as shown above. When we localize the 12 highest CC peaks of the

60S template structure (Figure S 9C, indicated by blue spheres), 9 out of 12 peaks co-

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localize with isolated 60S densities, not with 80S densities. In an experimental, cellular

tomogram as above, this effect can be expected to be much stronger due to a higher

structural heterogeneity and lower signal-to-noise ratio.

Figure S 9. Simulated template matching with multiple references. (A) A tomogram containing forty-eight 80S ribosomes, 12 60S subunits and 12 40S subunits with known coordinates was simulated at a signal-to-noise ratio of 0.2. Three low-pass filtered templates (isosurface schemes at the bottom) were used to perform template matching with the same parameters (pixel size, angular sampling) as in our experimental volumes. (B) The cross-correlation coefficients for each template were extracted as done previously and sorted according to peak height. For the 80S templates, a clear drop of peak heights is observed around the known number of particles. (C) Visualization of the highest twelve CC peaks (indicated by petrol spheres) obtained with the 60S template in the picking list. Grey isosurfaces represent the randomly placed particles before noise addition as described in (A). Colocalization is found with isolated 60S densities in 9 out of 12 peaks but not 60S subunits in the 80S context.

To conclude, in the crowded environment of the cell a 60S template will correlate

better with dissociated ribosomal subunits and other macromolecular complexes. Using

the current template matching procedures, the particle selection has to be performed

with a reference carrying (at least at low resolution) the structural signature of the entire

ribosome.

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3 Supplemental References

Kuffner. J.J. (2004). Effective Sampling and Distance Metrics for 3D Rigid Body Path Planning. Proc. IEEE Int'l Conf. on Robotics and Automation (ICRA'2004), New Orleans, April 2004. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004). UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem. 25(13):1605-12. Beck, M., Malmstrom, J.A., Lange, V., Schmidt, A., Deutsch, E.W., and Aebersold, R. (2009). Visual proteomics of the human pathogen Leptospira interrogans. Nat Methods 6, 817-U855. Buchan, J.R., and Parker, R. (2009). Eukaryotic Stress Granules: The Ins and Outs of Translation. Mol Cell 36, 932-941. Chandramouli, P., Topf, M., Menetret, J.F., Eswar, N., Cannone, J.J., Gutell, R.R., Sali, A., and Akey, C.W. (2008). Structure of the mammalian 80S ribosome at 8.7 A resolution. Structure 16, 535-548. Kedersha, N., Cho, M.R., Li, W., Yacono, P.W., Chen, S., Gilks, N., Golan, D.E., and Anderson, P. (2000). Dynamic shuttling of TIA-1 accompanies the recruitment of mRNA to mammalian stress granules. J Cell Biol 151, 1257-1268.