SLIDE 1
Hybrid [integrative] methods for structure determination
- Marc A. Marti-Renom
Genome Biology Group (CNAG) Structural Genomics Group (CRG)
Marc A. Marti-Renom Genome Biology Group (CNAG) Structural - - PowerPoint PPT Presentation
Marc A. Marti-Renom Genome Biology Group (CNAG) Structural - - PowerPoint PPT Presentation
Hybrid [integrative] methods for structure determination Marc A. Marti-Renom Genome Biology Group (CNAG) Structural Genomics Group (CRG) IMP Integrative Modeling Since 1956 Francis Crick James Watson Maurice Wilkins Rosalind
SLIDE 2
SLIDE 3
Francis Crick Rosalind Franklin Maurice Wilkins James Watson
Integrative Modeling
Since 1956
SLIDE 4
Build geometric models
Spatial restraints Components Model X-ray crystallography NMR Electron microscopy Small-angle x-ray scattering Cross-linking HDXMS Proteomics, mass spectrometry Copurification Bioinformatics, physics Sampling and analysis
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The Integrative Modeling Platform (IMP)
http://www.integrativemodeling.org
IMP C++/Python library multifit/restrainer Simplicity Generalization Chimera tools/ web apps Domain-specific applications
Russel et al, PLoS Biology, 2012
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Russel et al, PLoS Biology, 2012
Stage 1: Gathering information. Stage 2: Choosing how to represent and evaluate models. Stage 3: Finding models that score well. Stage 4: Analyzing resulting models and information.
IMP
The Integrative Modeling Platform (IMP)
http://www.integrativemodeling.org
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Representation
- Atomic
- Rigid bodies
- Coarse grained
- Multi-scale
- Symmetry/periodicity
- Multi-state systems
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Scoring
- Proteomics
- Density maps
- EM images
- FRET
- Chemical cross linking
- Homology-derived restraints
- SAXS
- Native mass spec
- Statistical potentials
- Molecular mechanics forcefields
- Bayesian scoring functions
- Library of functional forms (ambiguity, ...)
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Sampling
- Monte-Carlo
- Conjugate Gradients
- Quasi-Newton
- Simplex
- Divide and conquer sampler
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Analysis
- Clustering
- Output
- Chimera
- Pymol
- PDBs
- Density maps
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- The NPC
Alber, F., Dokudovskaya, S., Veenhoff, L. M., Zhang, W., Kipper, J., Devos, D., Suprapto, A., et al. (2007). Nature, 450(7170), 695–701
SLIDE 12
- N
1 N 2
{Bj
}
n
r
- N
1
N
2
{Bj
}
n
r 1,2,5
- 2
3.0 1,5
- 9
1.5 Nup192 1 1 3
- 1
- 2
- 2
1.5 1,2,5
- 2
3.0 3
- 1
- Nup188
1 1 3
- 1
- Nup1
1 4
- 7
1.5 1,2,5
- 2
2.9 1,5
- 12
1.3 Nup170 1 1 3
- 1
- 2
- 3
1.3 1,2,5
- 3
2.5 3
- 1
- Nup157
1 1 3
- 1
- Nsp1
2 2 4
- 9
1.3 1,2,5
- 2
2.7 1,2,5
- 2
2.1 Nup133 1 1 3
- 1
- Gle1
1 3
- 1
- 1,2,5
- 2
2.6 1,5
- 4
1.6 Nup120 1 1 3
- 1
- 2,3
- 1
1.6 1,2,5
- 3
2.0 Nup60 1 4
- 3
1.6 Nup85 1 1 3
- 1
- 1,5
- 4
1.6 1,2,5
- 3
2.0 2
- 2
1.6 Nup84 1 1 3
- 1
- 3
- 1
- 1,2,5
- 2
2.3 Nup59 1 1 4
- 2
1.6 Nup145C 1 1 3
- 1
- 1,5
- 3
1.8 Seh1 1 1 1,2,3,5
- 1
2.2 2,3
- 1
1.8 Sec13 1 1 1,2,3,5
- 1
2.1 Nup57 1 1 4
- 2
1.8 Gle2 1 1 1,2,3,5
- 1
2.3 1,5
- 3
1.7 1,2,5
- 2
2.4 2,3
- 1
1.7 Nic96 2 2 3
- 1
- Nup53
1 1 4
- 2
1.7 1,2,5
- 2
2.3 1,5
- 6
1.5 Nup82 1 1 3
- 1
- Nup145N
2 2,3
- 1
1.5
- Representation
436 proteins!
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Data generation Data interpretation
Method Experiments Restraint RC RO RA Functional form of activated feature restraint 30 nup sequences Protein excluded volume restraint- 1,864
- 30 nup
- 48
- | (Ndc1,Pom152,Pom34)
- 64
- | (Ndc1,Pom152,Pom34)
- Bioinformatics and Membrane fractionation
- 80
- (Pom152)
- 1 S-value
- | C51
- Hydrodynamics
experiments
30 S-values Protein chain restraint- 1,680
- | 1
- 456
- | 1, j 1
- 456
- | 1, j 1
- 456
- | 1, j 1
- Immuno-Electron microscopy
- 456
- | 1, j 1
- Overlay
assays
13 contacts Protein interaction restraint 20 112 20 Protein contact Violated for f > fo. f is the distance between two protein particles, fo is the sum of the particle radii multiplied by a tolerance factor of 1.3, and is 0.01 nm. Applied to particle: B Bj ,s,,i- | (2,4,9), (1,2,3)
- 4 complexes
- | (1,2,3), (2,4,6), (Nup82,Nic96,Nup49,Nup57)
- Affinity purification
- | (1,2,3), (2,4,9)
- Scoring
SLIDE 14
- Score
1010 108 106 104 102 0.60 0.52 0.44 0.36 Contact similarity
Optimization
Score 100 200 2,000 4,000 300 Number of configurations
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Integrating data
Immuno-EM Ultracentrifugation Nucleoporin stoichiometry NPC symmetry Nuclear envelope pore volume Overlay assays Affinity purifications
+ + +
a
SLIDE 16
- FG nucleoporins
The STRUCTURE of NPC
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IMP-based efforts
PCS9K-Fab complex Sali, Cheng, Agard, Pons Nup84 complex, Sali, Rout, Chait Nuclear Pore Complex, Sali, Rout, Chait Nuclear Pore Complex transport, Sali, Rout, Chait, Chook, Liphardt 26 Proteasome Sali, Baumeister Spindle Pole Body Sali, Davis, Muller Chromatin globin domain Marti-Renom Lymphoblastoid cell genome Alber, Chen Microtubule nucleation Sali, Agard Ribosomes, Sali, Frank; Sali, Akey Hsp90 landscape Sali, Agard TRiC/CCC Sali, Frydman, Chiu Actin Sali, Chiu RyR channel Sali, Serysheva, Chiu
T
SLIDE 18
Who Is developing with IMP?
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Whale sperm myoglobin structure (1960) alpha-globin genomic domain structure (2011)
From proteins to genomes
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Resolution Gap
Marti-Renom, M. A. & Mirny, L. A. PLoS Comput Biol 7, e1002125 (2011)
μ 10 10 10 Resolution s Time 10 10 10 10 10 10 10 10 μm Volume 10 10 10 10 10 DNA length nt 10 10 10 10
Knowledge
IDM INM
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“Bridging” the Resolution Gap
Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013). Nature Reviews Genetics, 14(6), 390–403.
A compartments 20 Mb 2 Mb B compartments Interaction preference TADs Compartments
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Experiments Computation
Hybrid Method
Baù, D. & Marti-Renom, M. A. Methods 58, 300–306 (2012).
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Hi-C technology
Lieberman-Aiden, E. et al. Science 326, 289–293 (2009).
http://3dg.umassmed.edu
A B C D
Chr.18 (Hind III)
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Biomolecular structure determination 2D-NOESY data Chromosome structure determination 3C-based data
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3C-like data
Nora, E. P., et al. (2012). Spatial partitioning of the regulatory landscape of the X-inactivation centre. Nature
SLIDE 26
http://www.3Dgenomes.org
SLIDE 27 P1 P2 P1 P2 P1 P2
i i+2 i+1 i+n
SLIDE 28
On TADs and hormones
Davide Baù François Serra François le Dily
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Progesterone-regulated transcription in breast cancer
> ¡2,000 ¡genes ¡Up-‑regulated ¡ > ¡2,000 ¡genes ¡Down-‑regulated ¡
Regulation in 3D?
Vicent)et#al#2011,))Wright)et#al#2012,)Ballare)et#al#2012)
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Experimental design
HiC libraries Chr.18 (NcoI) Chr.18 (Hind III) ChIP-Seq RNA-Seq Hi-C
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Are there TADs? how robust?
Chr.18
>30 25 15 10 >30 25 15 10
+Pg
- Pg
conserved ± 2 0 0 k b o r m o r e 1 0 0 k b
8% 12% 80%
>2,000 detected TADs
Mb) C. Size (M
Chromosome
1 3 5 7 X 9 11 15 13 17 19 21
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Are TADs homogeneous?
H3K36me2 H3K4me3 H3K4me1 H3K14ac H3K9me3 H3K27me3 HP1 H1.2
Chr.2
5 Mb
- Pg
- 1.0
- 0.5
0.0 0.5 1.0
Correlation coefficient Same TAD Same random TAD Inter-TADs Consecutive TADs
*** *** ***
Chr.2
5 Mb
+Pg/-Pg
- 1.0
- 0.5
0.0 0.5 1.0
Correlation coefficient Same TAD Same random TAD Inter-TADs Consecutive TADs
*** *** ***
SLIDE 33
Do TADs respond differently to Pg treatment?
Observed/expected ratio (Log2) Frequencies Expression levels (Log2 RPKM) 30 20 10
- 1
- 2
2.0 1.5 1.0 0.5 0.0
- 0.5
- 1.0
4 3 2 1
- 1
- 2
- 3
Log2 fold change ZBTB2 RMND1 C6orf211 CCDC170 ESR1 SYNE1
- Pg
+Pg
Expression levels (Log2 RPKM) 4 3 2 1 8 7 6 5 4 3 2 1
- 1
- 2
Log2 fold change MRFAP1 S100P MRFAP1L1 BLOC1S4 KIAA0232 TBC1D14 CCDC96 TADA2B GRPEL1
- Pg
+Pg
Observed Expected 100-90 100-90 0-10 0-10% % of genes per TAD with positive or negative fold change
TAD 469 TAD 821
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Do TADs respond differently to Pg treatment?
Observed/expected ratio (Log2) Frequencies Expression levels (Log2 RPKM) 30 20 10- 1
- 2
- 0.5
- 1.0
- 1
- 2
- 3
- Pg
- 1
- 2
- Pg
Repressed TADs Activated TADs Other TADs Mean Replicate 1 Replicate 2 Pg induced fold change per TAD (6h)
Fold change 6h Pg
- 1.0
- 0.5
0.0 0.5 1.0 1.5 Fold change per TAD (Log2)
*** *** ***
Fold change 1h Pg
Repressed TADs Activated TADs Other TADs Repressed TADs Activated TADs Other TADs*** *** ***
- 2.0
- 1.0
0.0 1.0 2.0 3.0 Pg induced fold change (log2) per gene
Repressed TADs Activated TADs Other TADs*** *** ***
Repressed TADs Activated TADs Other TADs- 2.0
- 1.0
0.0 1.0 2.0 Pg induced fold change (log2) per TAD non-coding *** *** **
Repressed TADs Activated TADs Other TADs
- 2.0
- 1.0
0.0 1.0 2.0 3.0 Pg induced changes in intra-TAD interactions (z-score)
SLIDE 35
Chr1:26,800,000-28,700,000
4 3 2
5 4 3 2 1
2.2 0.6 0.9
pool 1 pool 2
0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5
models (micra) FISH (micra) r= 0.94
1-5 2-4 2-3 3-4
Modeling 3D TADs
61 genomic regions containing 209 TADs covering 267Mb
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How TADs respond structurally to Pg?
Repressed TADs Activated TADs Other TADs *** ** 0.8 0.9 1.0 1.1 1.2
PG induced changes in accessibility
Repressed TADs Activated TADs Other TADs *** ** .95 1.00 1.05 1.10
Pg induced changes in radius or giration
non-TSS TSS 20 40 60 80 100
Particle accessibility (%)
***
50 100 150 200 cl12 [13] Pg cl14 [10] mixt cl17 [10] Pg cl11 [30] Pg cl2 [267] Pg cl13 [11] Pg cl1 [297] Pg cl10 [69] Pg cl9 [84] Pg cl16 [10] Pg + cl4 [172] Pg + cl6 [142] Pg + cl7 [89] Pg + cl3 [176] Pg + cl8 [85] Pg + cl15 [10] Pg + cl5 [144] Pg + dRMSD (nm)Chr2:9,600,000-13,200,000 Chr2 U170 (activated)
50 100 150 200 cl23 [11] Pg + cl24 [10] Pg + cl5 [34] Pg + cl26 [10] Pg + cl27 [10] Pg + cl28 [10] Pg + cl21 [12] Pg + cl9 [21] Pg + cl19 [14] Pg cl16 [15] Pg cl10 [20] Pg cl6 [32] Pg cl7 [32] Pg cl18 [15] Pg cl25 [10] Pg cl17 [15] Pg cl20 [12] Pg cl3 [73] Pg cl14 [16] Pg cl22 [12] Pg cl13 [16] Pg cl1 [118] Pg cl12 [17] Pg cl4 [46] Pg cl11 [18] Pg cl15 [16] Pg cl2 [112] Pg cl8 [25] Pg dRMSD (nm)Chr6:71,800,000-76,500,000 Chr6 U767 (repressed)
- Pg
+Pg
- Pg
+Pg
SLIDE 37
Model for TAD regulation
Structural transition
+ P g
DHS HP1 H1.2 H2A MNAse H3K27me3 H3K9m3 H3K14ac H3K4me1 H3K36me2 H3K4me3
Histone H1 Nucleosome Histones H2A/H2B Progesteone ReceptorRepressed TAD chr1 U41
DHS HP1 H1.2 H2A MNAse H3K27me3 H3K9m3 H3K14ac H3K4me1 H3K36me2 H3K4me3
Activated TAD chr2 U207
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STRUCTURE FUNCTION
SLIDE 39
Acknowledgments
http://marciuslab.org http://3DGenomes.org http://cnag.cat · http://crg.cat
Open positions http://marciuslab.org
François Serra Davide Baù François le Dily
- David Dufour
Mike Goodstadt Gireesh Bogu Francisco Martínez-Jiménez
Miguel Beato, Thomas Graf and Guillaume Filion