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Macrogenomic engineering via modulation of the scaling of chromatin packing density

Nature Biomedical Engineering volume 1, pages 902–913 (2017)Cite this article

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Abstract

Many human diseases result from the dysregulation of the complex interactions between tens to thousands of genes. However, approaches for the transcriptional modulation of many genes simultaneously in a predictive manner are lacking. Here, through the combination of simulations, systems modelling and in vitro experiments, we provide a physical regulatory framework based on chromatin packing-density heterogeneity for modulating the genomic information space. Because transcriptional interactions are essentially chemical reactions, they depend largely on the local physical nanoenvironment. We show that the regulation of the chromatin nanoenvironment allows for the predictable modulation of global patterns in gene expression. In particular, we show that the rational modulation of chromatin density fluctuations can lead to a decrease in global transcriptional activity and intercellular transcriptional heterogeneity in cancer cells during chemotherapeutic responses to achieve near-complete cancer cell killing in vitro. Our findings represent a ‘macrogenomic engineering’ approach to modulating the physical structure of chromatin for whole-scale transcriptional modulation.

Fully sequencing the human genome has allowed unprecedented exploration of the roles that genes play in diseases, including neurological and autoimmune disorders, heart disease, and cancer. One of the most significant findings from the human genome project was the fact that, in many cases, these diseases do not depend on the behaviour of individual genes, but on the complex interplay between tens to thousands of genes over long periods of time1,2,3. Despite this emerging understanding that many human diseases are thus inherently multifactorial and genomic in nature, no technologies have been developed that allow for the simultaneous, predictable engineering of multidimensional transcriptional interactions.

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Fig. 1: Genomic networks are highly interconnected and decentralized.
Fig. 2: Genomic interactions depend on a complex physical nanoenvironment.
Fig. 3: Control of higher-order chromatin packing density scaling allows manipulation of genomic information space.
Fig. 4: Chemotherapeutic stress increases variations in chromatin packing density.
Fig. 5: Chromatin protective agents rapidly decrease the spatial variations in chromatin packing density.
Fig. 6: Regulation of chromatin packing-density scaling modulates transcriptional heterogeneity.
Fig. 7: Rapid modulation of chromatin packing density scaling by CPT agents greatly enhances chemotherapeutic efficacy.

References

  1. Collins, F. S. Shattuck lecture—medical and societal consequences of the Human Genome Project. N. Engl. J. Med. 341, 28–37 (1999).

    Article  CAS  PubMed  Google Scholar 

  2. Bailey, J. N., Pericak-Vance, M. A. & Haines, J. L. The impact of the human genome project on complex disease. Genes 5, 518–535 (2014).

    Article  PubMed  Google Scholar 

  3. Forbes, S. A. et al. COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res. 43, 805–811 (2015).

    Article  Google Scholar 

  4. Iwafuchi-Doi, M. & Zaret, K. S. Pioneer transcription factors in cell reprogramming. Genes Dev. 28, 2679–2692 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Zhang, Z. & Pugh, B. F. High-resolution genome-wide mapping of the primary structure of chromatin. Cell 144, 175–186 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lupianez, D. G. et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene-enhancer interactions. Cell 161, 1012–1025 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Franke, M. et al. Formation of new chromatin domains determines pathogenicity of genomic duplications. Nature 538, 265–269 (2016).

    Article  CAS  PubMed  Google Scholar 

  8. Almassalha, L. M. et al. The greater genomic landscape: the heterogeneous evolution of cancer. Cancer Res. 76, 5605–5609 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lynch, H. T., Rendell, M., Shaw, T. G., Silberstein, P. & Ngo, B. T. Commentary on Almassalha et al. “The greater genomic landscape: the heterogeneous evolution of cancer”. Cancer Res. 76, 5602–5604 (2016).

    Article  CAS  PubMed  Google Scholar 

  10. Lee, M. C. et al. Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing. Proc. Natl Acad. Sci. USA 111, 4726–4735 (2014).

    Article  Google Scholar 

  11. Almassalha, L. M. et al. Label-free imaging of the native, living cellular nanoarchitecture using partial-wave spectroscopic microscopy. Proc. Natl Acad. Sci. USA 113, E6372–E6381 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kim, J. S., Backman, V. & Szleifer, I. Crowding-induced structural alterations of random-loop chromosome model. Phys. Rev. Lett. 106, 168102 (2011).

    Article  PubMed  Google Scholar 

  13. Matsuda, H., Putzel, G. G., Backman, V. & Szleifer, I. Macromolecular crowding as a regulator of gene transcription. Biophys. J. 106, 1801–1810 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Morelli, M. J., Allen, R. J. & Wolde, P. R. T. Effects of macromolecular crowding on genetic networks. Biophys. J. 101, 2882–2891 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Hansen, M. M. et al. Macromolecular crowding creates heterogeneous environments of gene expression in picolitre droplets. Nat. Nanotechnol. 11, 191–197 (2016).

    Article  CAS  PubMed  Google Scholar 

  16. Richter, K., Nessling, M. & Lichter, P. Macromolecular crowding and its potential impact on nuclear function. Biochim. Biophys. Acta 1783, 2100–2107 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Ou, H. D. et al. ChromEMT: Visualizing 3D chromatin structure and compaction in interphase and mitotic cells. Science 357, eaag0025 (2017).

    Article  PubMed  Google Scholar 

  18. Fudenberg, G., Getz, G., Meyerson, M. & Mirny, L. A. High order chromatin architecture shapes the landscape of chromosomal alterations in cancer. Nat. Biotechnol. 29, 1109–1113 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Metze, K. Fractal dimension of chromatin: potential molecular diagnostic applications for cancer prognosis. Expert Rev. Mol. Diagn. 13, 719–735 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zack, T. I. et al. Pan-cancer patterns of somatic copy number alteration. Nat. Genet. 45, 1134–1140 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Boettiger, A. N. et al. Super-resolution imaging reveals distinct chromatin folding for different epigenetic states. Nature 529, 418–422 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mirny, L. A. The fractal globule as a model of chromatin architecture in the cell. Chromosome Res. 19, 37–51 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bancaud, A., Lavelle, C., Huet, S. & Ellenberg, J. A fractal model for nuclear organization: current evidence and biological implications. Nucleic Acids Res. 40, 8783–8792 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lebedev, D. V. et al. Fractal nature of chromatin organization in interphase chicken erythrocyte nuclei: DNA structure exhibits biphasic fractal properties. FEBS Lett. 579, 1465–1468 (2005).

    Article  CAS  PubMed  Google Scholar 

  26. Huet, S. et al. Relevance and limitations of crowding, fractal, and polymer models to describe nuclear architecture. Int. Rev. Cell Mol. Biol. 307, 443–479 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Dong, B. et al Superresolution intrinsic fluorescence imaging of chromatin utilizing native, unmodified nucleic acids for contrast. Proc. Natl Acad. Sci. USA 113, 9716–9721 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Flory, P. J. Principles of Polymer Chemistry (Cornell Univ. Press, Ithaca, 1953).

  29. Gennes, P. G. d. Scaling Concepts in Polymer Physics (Cornell Univ. Press, Ithaca, 1979).

  30. Doi, M. & Edwards, S. F. The Theory of Polymer Dynamics Vol. 73 (Oxford Univ. Press, Oxford, 1988).

  31. Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Rao, S. S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Dostie, J. et al. Chromosome conformation capture carbon copy (5C): a massively parallel solution for mapping interactions between genomic elements. Genome Res. 16, 1299–1309 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wu, W. et al. Using electron microscopy to calculate optical properties of biological samples. Biomed. Optics Exp. 7, 4749–4762 (2016).

    Article  Google Scholar 

  35. Subramanian, H. et al. Nanoscale cellular changes in field carcinogenesis detected by partial wave spectroscopy. Cancer Res. 69, 5357–5363 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Bancaud, A. et al. Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin. EMBO J. 28, 3785–3798 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dong, B. et al. Superresolution intrinsic fluorescence imaging of chromatin utilizing native, unmodified nucleic acids for contrast. Proc. Natl Acad. Sci. USA 113, 9716–9721 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Cherkezyan, L. et al. Interferometric spectroscopy of scattered light can quantify the statistics of subdiffractional refractive-index fluctuations. Phys. Rev. Lett. 111, 033903 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Rogers, J. D., Radosevich, A. J., Yi, J. & Backman, V. Modeling light scattering in tissue as continuous random media using a versatile refractive index Correlation Function. IEEE J. Sel. Top. Quantum Electron. 20, 7000514 (2013).

    PubMed  PubMed Central  Google Scholar 

  40. Cherkezyan, L., Subramanian, H. & Backman, V. What structural length scales can be detected by the spectral variance of a microscope image? Opt. Lett. 39, 4290–4293 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Rogers, J. D., Capoglu, I. R. & Backman, V. Nonscalar elastic light scattering from continuous random media in the Born approximation. Opt. Lett. 34, 1891–1893 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Schoenfelder, S. et al. Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells. Nat. Genet. 42, 53–61 (2010).

    Article  CAS  PubMed  Google Scholar 

  43. Cherkezyan, C. et al. Review of interferometric spectroscopy of scattered light for the quantification of subdiffractional structure of biomaterials. J. Biomed. Optics 22, 030901–030919 (2017).

    Article  Google Scholar 

  44. Almassalha, L. M. et al. The global relationship between chromatin physical topology, fractal structure, and gene expression. Sci. Rep. 7, 41061 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kim, J. S. & Szleifer, I. Depletion effect on polymers induced by small depleting spheres. J. Phys. Chem. C 114, 20864–20869 (2010).

    Article  CAS  Google Scholar 

  46. Subramanian, H. et al. Optical methodology for detecting histologically unapparent nanoscale consequences of genetic alterations in biological cells. Proc. Natl Acad. Sci. USA 105, 20118–20123 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Damania, D. et al. Role of cytoskeleton in controlling the disorder strength of cellular nanoscale architecture. Biophys. J. 99, 989–996 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Roy, H. K. et al. Optical detection of buccal epithelial nanoarchitectural alterations in patients harboring lung cancer: implications for screening. Cancer Res. 70, 7748–7754 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Roy, H. K., Hensing, T. & Backman, V. Nanocytology for field carcinogenesis detection: novel paradigm for lung cancer risk stratification. Future Oncol. 7, 1–3 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Damania, D. et al. Nanocytology of rectal colonocytes to assess risk of colon cancer based on field cancerization. Cancer Res. 72, 2720–2727 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Konda, V. J. et al. Nanoscale markers of esophageal field carcinogenesis: potential implications for esophageal cancer screening. Endoscopy 45, 983–988 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Roy, H. K. et al. Nano-architectural alterations in mucus layer fecal colonocytes in field carcinogenesis: potential for screening. Cancer Prev. Res. 6, 1111–1119 (2013).

    Article  Google Scholar 

  53. Stypula-Cyrus, Y. et al. HDAC up-regulation in early colon field carcinogenesis is involved in cell tumorigenicity through regulation of chromatin structure. PLoS ONE 8, e64600 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Cherkezyan, L. et al. Nanoscale changes in chromatin organization represent the initial steps of tumorigenesis: a transmission electron microscopy study. BMC Cancer 14, 189 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Wali, R. K. et al. Higher-order chromatin modulator cohesin SA1 is an early biomarker for colon carcinogenesis: race-specific implications. Cancer Prev. Res. 9, 844–854 (2016).

    Article  Google Scholar 

  56. Roy, H. K. et al. Nanocytological field carcinogenesis detection to mitigate overdiagnosis of prostate cancer: a proof of concept study. PLoS ONE  10, e0115999 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Paek, A. L., Liu, J. C., Loewer, A., Forrester, W. C. & Lahav, G. Cell-to-cell variation in p53 dynamics leads to fractional killing. Cell 165, 631–642 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Shaffer, S. M. et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546, 431–435 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Almassalha, L. M. Live cell partial wave spectroscopic microscopy: label-free imaging of the native, living cellular nanoarchitecture. Preprint at https://doi.org/10.1101/061747 (2016).

  60. Du, P., Kibbe, W. A. & Lin, S. M. lumi: a pipeline for processing Illumina microarray. Bioinformatics 24, 1547–1548 (2008).

    Article  CAS  PubMed  Google Scholar 

  61. Li, H. et al. Versatile pathway-centric approach based on high-throughput sequencing to anticancer drug discovery. Proc. Natl Acad. Sci. USA 109, 4609–4614 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Pertea, M., Kim, D., Pertea, G. M., Leek, J. T. & Salzberg, S. L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 11, 1650–1667 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work has been supported by the National Science Foundation grant EFRI-1240416, the National Science Foundation Graduate Research Fellowship grant DGE-0824162, National Institutes of Health T32 training grants T32GM008152 and T32HL076139, the Lefkofsky Innovation Award, The Robert H. Lurie Comprehensive Cancer Center Translational Bridge Award, the Chicago Biomedical Consortium with support from the Searle Funds at The Chicago Community Trust, the National Institute of Health through the Chicago Region Physical Science Oncology Center U54CA193419, as well as grants R01CA200064, R01CA165309, and R01EB016983. Flow Cytometry was performed by the Northwestern University Flow Cytometry Facility, which has received support from NCI CA060553.

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Author notes

  1. Luay M. Almassalha, Greta M. Bauer and Wenli Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA

    Luay M. Almassalha, Greta M. Bauer, Wenli Wu, Lusik Cherkezyan, Di Zhang, Alexis Kendra, Scott Gladstein, John E. Chandler, David VanDerway, Igal Szleifer & Vadim Backman

  2. Department of Obstetrics and Gynecology, Prentice Women’s Hospital, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA

    Brandon-Luke L. Seagle & Shohreh Shahabi

  3. Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA

    Andrey Ugolkov, Thomas V. O’Halloran, Igal Szleifer & Vadim Backman

  4. Schulze Center for Novel Therapeutics, Division of Oncology Research, Mayo Clinic, Rochester, MN, 55905, USA

    Daniel D. Billadeau

  5. Department of Molecular Biosciences, Northwestern University, Evanston, IL, 60208, USA

    Thomas V. O’Halloran & Igal Szleifer

  6. Department of Chemistry, Northwestern University, Evanston, IL, 60208, USA

    Thomas V. O’Halloran

  7. Monopar Therapeutics, Inc., Northbrook, IL, 60062, USA

    Andrew P. Mazar

  8. Section of Gastroenterology, Boston Medical Center/Boston University School of Medicine, Boston, MA, 02118, USA

    Hemant K. Roy

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  1. Luay M. Almassalha
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Contributions

T.V.O., A.P.M., H.K.R., I.S., S.S. and V.B. conceived the research; L.C., J.E.C. and V.B. developed the PWS instrumentation; G.M.B., W.W., L.M.A., A.K., S.G. and D.V. performed the experiments, molecular dynamics simulations and mathematical modelling; Andrey Ugolkov (A.U.) and Daniel D. Billadeau (D.D.B.) contributed to the design of experiments;  G.M.B., W.W., L.M.A. and V.B. wrote the original draft; G.M.B., L.M.A., L.C., A.K., S.G., J.E.C., B.-L.L.S., T.V.O., H.K.R., I.S., S.S. and V.B. reviewed and edited the paper.

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Correspondence to Igal Szleifer or Vadim Backman.

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Supplementary Information

Macrogenomic model and analysis, and supplementary figures and references

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Supplementary Table 1

Microarray source data for Fig. 3 and Supplementary Fig. 5

Supplementary Table 2

Normalized Σ values for Figs. 4 and 5 and Supplementary Figs. 1 and 2

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Almassalha, L.M., Bauer, G.M., Wu, W. et al. Macrogenomic engineering via modulation of the scaling of chromatin packing density. Nat Biomed Eng 1, 902–913 (2017). https://doi.org/10.1038/s41551-017-0153-2

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