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DNA-loop-extruding SMC complexes can traverse one another in vivo

Nature Structural & Molecular Biology volume 28, pages 642–651 (2021)Cite this article

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Abstract

Chromosome organization mediated by structural maintenance of chromosomes (SMC) complexes is vital in many organisms. SMC complexes act as motors that extrude DNA loops, but it remains unclear what happens when multiple complexes encounter one another on the same DNA in living cells and how these interactions may help to organize an active genome. We therefore created a crash-course track system to study SMC complex encounters in vivo by engineering defined SMC loading sites in the Bacillus subtilis chromosome. Chromosome conformation capture (Hi-C) analyses of over 20 engineered strains show an amazing variety of chromosome folding patterns. Through three-dimensional polymer simulations and theory, we determine that these patterns require SMC complexes to bypass each other in vivo, as recently seen in an in vitro study. We posit that the bypassing activity enables SMC complexes to avoid traffic jams while spatially organizing the genome.

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Fig. 1: Experimental system to study the effect of ‘collisions’ between SMC complexes.
Fig. 2: Specific interactions between SMC complexes leave unique Hi-C signatures.
Fig. 3: Validating and testing a model of in vivo Z-loop formation.
Fig. 4: The number of SMC complexes per chromosome tunes the shape of contact maps.
Fig. 5: Time-dependent change of Hi-C patterns in strains with three parS sites.
Fig. 6: Time-dependent change of Hi-C patterns in strains with wild-type parS sites.
Fig. 7: Schematic model illustrating how SMC encounters are resolved.

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Data availability

Plasmids and strains generated in this study are available from X.W. with a completed materials transfer agreement. Hi-C and ChIP-seq data that support the findings of this study have been deposited in the Gene Expression Omnibus with accession no. GSE155279. All next-generation sequencing data used in this study are listed and itemized in Supplementary Table 1 with the corresponding accession numbers. Unprocessed microscopy images, uncropped blot images and their associated molecular weight/size markers can be accessed in Mendeley Data at https://doi.org/10.17632/vgw8sjxsyv.1.

Code availability

Simulation codes used to generate Hi-C-like contact maps and SMC ChIP-seq-like occupancy profiles in this paper are available on Zenodo at https://doi.org/10.5281/zenodo.4918358 and also in the GitHub repository https://github.com/hbbrandao/bacterialSMCtrajectories.

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Acknowledgements

We thank M. Imakaev and A. Golobordko for the development of the polychrom simulation package, as well as E. Banigan, A. van den Berg, K. Polovnikov, Q. Liao and E. Schantz for discussions. We are grateful to S. Gruber, C. Broedersz, J. Dekker and J. Harju for critically evaluating our manuscript and exchanging ideas. We thank M. Suiter for strain building, Indiana University Center for Genomics and Bioinformatics for assistance with high throughput sequencing, A. Grossman for anti-SMC and anti-ParB antibodies, and D. Rudner for plasmids and anti-ScpA, anti-ScpB and anti-SigA antibodies. Support for this work comes from National Institute of Health grants R01GM141242 to X.W. and U01CA200147 and R01GM114190 to L.A.M. H.B.B. was partially supported by a Natural Sciences and Engineering Research Council of Canada Post-Graduate Fellowship (Doctoral). We also acknowledge support from the National Institutes of Health Common Fund 4D Nucleome Program (DK107980) to L.A.M. and H.B.B.

Author information

Author notes

  1. These authors contributed equally: Hugo B. Brandão, Zhongqing Ren.

Authors and Affiliations

  1. Graduate Program in Biophysics, Harvard University, Cambridge, MA, USA

    Hugo B. Brandão & Leonid A. Mirny

  2. Department of Biology, Indiana University, Bloomington, IN, USA

    Zhongqing Ren, Xheni Karaboja & Xindan Wang

  3. Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Leonid A. Mirny

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Contributions

H.B.B. and X.W. conceived the project. H.B.B. developed the theory and models and analyzed data with L.A.M, with input from X.W. Z.R. and X.W. performed Hi-C experiments and analyses. X.K. and X.W. constructed strains and performed and analyzed ChIP-seq, whole-genome sequencing, fluorescence microscopy and immunoblot experiments. H.B.B., L.A.M. and X.W. interpreted results and wrote the manuscript, with input from all authors.

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Correspondence to Leonid A. Mirny or Xindan Wang.

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Peer review information Nature Structural & Molecular Biology thanks Davide Michieletto, Marcelo Nollmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Exponential growth does not strongly affect the Hi-C contact patterns.

a, The B. subtilis genome is displayed in genomic coordinates (kilobases) and the angular coordinates used to designate the locations of the parS sites. b, Hi-C maps for cells in exponential growth for the strains with parS sites at −94o, −59o, and both −94o and −59o. For details on strain names refer to Supplementary Table 1 and 2.

Extended Data Fig. 2 SMC complexes can slow each other down.

a, Time-course (similar to Fig. 1d) comparing the extrusion rates away from (but not between) the S1 and S2 parS sites. The green dashed line tracks the leading edge of the hairpin trace as it emerges from the −94o parS (S1) site and moves towards the ter; the red dashed line tracks the leading edge of the hairpin trace as it emerges from the −59o parS (S2) site and moves towards the ori. b, Demonstration that when two parS sites are in one strain, the angle of the hairpin traces changes compared to single parS sites. The yellow and blue dashed lines are superimposed on the Hi-C map to help visualize the angle change. c, The relationship between the tilt of the hairpin trace and the loop extrusion speeds (v1, v2 and v3) is captured by a simple geometric relation. The equation shows that for equal v1 across strains with one or two parS sites (as indicated in panel (a)), it follows that v2 > v3.

Extended Data Fig. 3 The blocking and unloading model of loop extruder interactions does not produce all the features seen in the Hi-C map.

The parameter sweep was conducted for varying numbers of extruders and facilitated dissociation rates. The experimental data (for the strain with parS sites at both −94o and −59o) is shown on the top left of the figure. These contact maps were generated with the semi-analytical approach without making the shortest path approximation as described in Appendix 3 of Banigan et al, 202030 (also see Supplementary Notes 1-5). Notably, Lines 4 and 5 are missing in all of the plots with the blocking and unloading model - this is due to either traffic jams forming between extruders (for high numbers of extruders), or an insufficient loading rate (for low numbers of extruders) preventing the efficient formation of nested doublets and triplets.

Extended Data Fig. 4 The number of extrusion complexes tunes the relative frequency of singlet- to adjoining-doublet interactions.

a, In the experimental Hi-C map for the −59o−94o strain after 60 min of SirA expression, the frequency of singlet contacts to adjoining doublet contacts is close to 1:1. This is only achieved when the number of extrusion complexes is >40 and for sufficiently high bypassing rates. b, A parameter sweep over the number of extruders and the bypassing rate. The best matched parameter combination is shown boxed in red. For a description of how we obtained the overall best parameters, see Methods and Supplementary Figs. 4-7.

Extended Data Fig. 5 Parameter sweep of the bypassing and unloading rates for N = 40 extruders/chromosome.

The experimental data (for the −59o−94o strain) is shown on the top left of the figure, and the model parameter sweep is below. The model with the most similar pattern in both angles of the Hi-C traces and the relative intensities of the different lines corresponds to a bypassing rate of 0.05 s−1 and an unloading rate between 0.001 s−1 and 0.005 s−1. From the sweep, we find that the bypassing rate can control the angle between Hi-C map hairpin structures, while the ratio of the bypassing to unloading rates tunes the relative frequency of nested-doublet and nested-triplet interactions. These contact maps were generated with the semi-analytical approach30 (see Supplementary Notes 1–5).

Extended Data Fig. 6 Hi-C maps for exponentially growing cells.

Hi-C maps for strains with (a) two parS sites, and (b) three parS sites. Cells were growing exponentially.

Extended Data Fig. 7 Hi-C time course of cells under G1 arrest.

The experimental time course of G1 arrest for a strain with (a) a single parS site at the −59o (top) and −91o (bottom), and (b) with two parS sites at −59o −91o (top) and −91o −117o (bottom). The experiments show that almost no change occurs to the angle of the hairpin traces when only a single parS site is present. However, when two parS sites are present, the hairpins increasingly tilt away from each other. c, A 3D polymer simulation with the blocking, bypassing and unloading model of loop extrusion showing that when a single parS site is present, increasing the numbers of loop extruders, N, on the chromosome also does not change the observed hairpin angle for the same strains as in (a). Loop extrusion parameters use a bypassing rate of 0.05 s−1 and a facilitated dissociation rate of 0.003 s−1 (that is same as Fig. 4a); the number of extrusion complexes is denoted by N.

Extended Data Fig. 8 Quantification of chromosome copy numbers and cell lengths per nucleoid.

a, Whole genome sequencing plots for cells after the indicated minutes of replication inhibition by SirA. The computed ori:ter ratio indicates that by 60 min of SirA expression, cells have finished chromosome replication. b, The quantification of microscopy images reveals the numbers of origins per nucleoid, and cell lengths per nucleoid. The numbers of cells analyzed were n = 725, 580, 702, 557 for the four time points (exponential, 60 min, 90 min, 120 min), respectively. Means and standard deviations are shown. These values are used to calculate the numbers of SMC complexes per chromosome at different time points. To estimate the absolute numbers of SMC complexes/chromosome (independently of the Hi-C data and polymer simulations), we use the reference value of 30 SMC complexes/ori as measured in (Wilhelm et al, 2015)32, which converts to 34 SMC complexes/chromosome (indicated by *). We infer that these calculated values agree well with the numbers of loop extrusion complexes (as found by Hi-C and polymer modeling), if there are two SMC complexes per loop extrusion complex; this inference assumes that the error on the reference value of 30 SMC complexes/ori is sufficiently small. For calculations, see the attached Supplementary Data.

Extended Data Fig. 9 Overexpression of SMC complexes speeds up the change of Hi-C patterns with time.

a, Replication inhibition Hi-C time course following induction of SirA for a strain with parS sites at −27o and −59o. b, The SMC complex (SMC, ScpA and ScpB) was overexpressed in the same background as the strain in panel A. We found that prolonged over-expression of SMC complexes at 90 min and 120 min did not recapitulate the experiments seen in G1 arrested cells in (a) but caused the interaction lines to become shorter. These patterns are likely due to non-specific loading of SMC complexes outside of parS, creating traffic jams along the DNA. In simulations, when we increase the numbers of off-parS loaded extruders, while keeping the numbers of on-parS loaded extruders consistent, we can observe similar changes in the Hi-C maps. Numbers of on-parS versus off-parS loading are average values for the simulation. c, With SMC overexpression, the 60 min time point (following SirA induction) more closely resembles the 90 min point than the 60 m time point with no SMC overexpression. This indicates that increasing the numbers of SMC complexes on the chromosome leads to an increase in the tilts of the hairpin diagonals away from each other.

Extended Data Fig. 10 Simulations of blocking and unloading (without bypassing) do not reproduce the wild-type Hi-C map.

a, Analytical results demonstrating there is a high likelihood of collisions between SMC complexes near the ori due to the high density of parS sites. Calculations were performed for a facilitated unloading rate of 0.0006 s−1 and an extrusion rate of 0.8 kb/s. b, 3D polymer simulations showing that even a few loop extruders (for example 5 extruders) results in a missing central diagonal and long-range tethers between the ori and other genome positions. With more extruders per chromosome, the traffic jams between SMC complexes near the origin becomes more likely, preventing juxtaposition of the arms. For very low numbers of extruders (for example 2 extruders), the central diagonal is present, but it is much fainter than observed experimentally.

Supplementary information

Supplementary Information

Supplementary Figs. 1–7, Notes 1–5 and Tables 1–4.

Reporting Summary

Supplementary Data 1

Calculations of SMC numbers from imaging, marker frequency analysis and western blots with error propagation. The xlsx format allows readers to check the formula used for calculations.

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Brandão, H.B., Ren, Z., Karaboja, X. et al. DNA-loop-extruding SMC complexes can traverse one another in vivo. Nat Struct Mol Biol 28, 642–651 (2021). https://doi.org/10.1038/s41594-021-00626-1

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