Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Leveraging advances in biology to design biomaterials

Nature Materials volume 16, pages 1178–1185 (2017)Cite this article

Subjects

Abstract

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Advances in biomaterials fabrication and bioassays.
Figure 2: General next-generation biomaterial design framework.

Similar content being viewed by others

References

  1. Han, W. M. et al. Microstructural heterogeneity directs micromechanics and mechanobiology in native and engineered fibrocartilage. Nat. Mater. 15, 477–484 (2016).

    Article  CAS  Google Scholar 

  2. Vegas, A. J. et al. Long-term glycemic control using polymer-encapsulated human stem cell-derived beta cells in immune-competent mice. Nat. Med. 22, 306–311 (2016).

    Article  CAS  Google Scholar 

  3. Zhang, B. et al. Biodegradable scaffold with built-in vasculature for organ-on-a-chip engineering and direct surgical anastomosis. Nat. Mater. 15, 669–678 (2016).

    Article  CAS  Google Scholar 

  4. Singh, A. et al. Enhanced lubrication on tissue and biomaterial surfaces through peptide-mediated binding of hyaluronic acid. Nat. Mater. 13, 988–995 (2014).

    Article  CAS  Google Scholar 

  5. Hook, A. L. et al. Combinatorial discovery of polymers resistant to bacterial attachment. Nat. Biotechnol. 30, 868–875 (2012).

    Article  CAS  Google Scholar 

  6. Ali, O. A., Huebsch, N., Cao, L., Dranoff, G. & Mooney, D. J. Infection-mimicking materials to program dendritic cells in situ. Nat. Mater. 8, 151–158 (2009).

    Article  CAS  Google Scholar 

  7. DiPasquale, S. A. & Byrne, M. E. Controlled architecture for improved macromolecular memory within polymer networks. Curr. Opin. Biotechnol. 40, 170–176 (2016).

    Article  CAS  Google Scholar 

  8. Dooling, L. J., Buck, M. E., Zhang, W.-B. & Tirrell, D. A. Programming molecular association and viscoelastic behavior in protein networks. Adv. Mater. 28, 4651–4657 (2016).

    Article  CAS  Google Scholar 

  9. Jiang, Y., Chen, J., Deng, C., Suuronen, E. J. & Zhong, Z. Click hydrogels, microgels and nanogels: emerging platforms for drug delivery and tissue engineering. Biomaterials 35, 4969–4985 (2014).

    Article  CAS  Google Scholar 

  10. Wang, L. L. & Burdick, J. A. Engineered hydrogels for local and sustained delivery of RNA-interference therapies. Adv. Healthc. Mater. 6, 1601041 (2017).

    Article  CAS  Google Scholar 

  11. Alberti, K. et al. Functional immobilization of signaling proteins enables control of stem cell fate. Nat. Methods 5, 645–650 (2008).

    Article  CAS  Google Scholar 

  12. DeForest, C. A. & Tirrell, D. A. A photoreversible protein-patterning approach for guiding stem cell fate in three-dimensional gels. Nat. Mater. 14, 523–531 (2015).

    Article  CAS  Google Scholar 

  13. Ruoslahti, E. RGD and other recognition sequences for integrins. Annu. Rev. Cell Dev. Biol. 12, 697–715 (1996).

    Article  CAS  Google Scholar 

  14. Mitchell, A. C., Briquez, P. S., Hubbell, J. A. & Cochran, J. R. Engineering growth factors for regenerative medicine applications. Acta Biomater. 30, 1–12 (2016).

    Article  CAS  Google Scholar 

  15. Engler, A. J., Sen, S., Sweeney, H. L. & Discher, D. E. Matrix elasticity directs stem cell lineage specification. Cell 126, 677–689 (2006).

    CAS  Google Scholar 

  16. Cosgrove, B. D. et al. N-cadherin adhesive interactions modulate matrix mechanosensing and fate commitment of mesenchymal stem cells. Nat. Mater. 15, 1297–1306 (2016).

    Article  CAS  Google Scholar 

  17. Chaudhuri, O. et al. Hydrogels with tunable stress relaxation regulate stem cell fate and activity. Nat. Mater. 15, 326–334 (2016).

    Article  CAS  Google Scholar 

  18. Hall, M. S. et al. Fibrous nonlinear elasticity enables positive mechanical feedback between cells and ECMs. Proc. Natl Acad. Sci. USA 113, 14043–14048 (2016).

    Article  CAS  Google Scholar 

  19. Dalby, M. J., Gadegaard, N. & Oreffo, R. O. C. Harnessing nanotopography and integrin-matrix interactions to influence stem cell fate. Nat. Mater. 13, 558–569 (2014).

    Article  CAS  Google Scholar 

  20. Katz, B.-Z. et al. Physical state of the extracellular matrix regulates the structure and molecular composition of cell-matrix adhesions. Mol. Biol. Cell 11, 1047–1060 (2000).

    Article  CAS  Google Scholar 

  21. Downing, T. L. et al. Biophysical regulation of epigenetic state and cell reprogramming. Nat. Mater. 12, 1154–1162 (2013).

    Article  CAS  Google Scholar 

  22. Deligianni, D. D., Katsala, N. D., Koutsoukos, P. G. & Missirlis, Y. F. Effect of surface roughness of hydroxyapatite on human bone marrow cell adhesion, proliferation, differentiation and detachment strength. Biomaterials 22, 87–96 (2000).

    Article  Google Scholar 

  23. Annabi, N. et al. Controlling the porosity and microarchitecture of hydrogels for tissue engineering. Tissue Eng. Part B Rev. 16, 371–383 (2010).

    Article  CAS  Google Scholar 

  24. Bencherif, S. A. et al. Injectable cryogel-based whole-cell cancer vaccines. Nat. Commun. 6, 7556 (2015).

    Article  CAS  Google Scholar 

  25. Freeman, R., Boekhoven, J., Dickerson, M. B., Naik, R. R. & Stupp, S. I. Biopolymers and supramolecular polymers as biomaterials for biomedical applications. MRS Bull. 40, 1089–1101 (2015).

    Article  CAS  Google Scholar 

  26. Kolesky, D. B., Homan, K. A., Skylar-Scott, M. A. & Lewis, J. A. Three-dimensional bioprinting of thick vascularized tissues. Proc. Natl Acad. Sci. USA 113, 3179–3184 (2016).

    Article  CAS  Google Scholar 

  27. Di Cio, S. & Gautrot, J. E. Cell sensing of physical properties at the nanoscale: mechanisms and control of cell adhesion and phenotype. Acta Biomater. 30, 26–48 (2016).

    Article  CAS  Google Scholar 

  28. Zhu, J. & Marchant, R. E. Design properties of hydrogel tissue-engineering scaffolds. Expert Rev. Med. Devices 8, 607–626 (2011).

    Article  CAS  Google Scholar 

  29. Luo, Y. & Shoichet, M. S. A photolabile hydrogel for guided three-dimensional cell growth and migration. Nat. Mater. 3, 249–253 (2004).

    Article  CAS  Google Scholar 

  30. Mosiewicz, K. A. et al. In situ cell manipulation through enzymatic hydrogel photopatterning. Nat. Mater. 12, 1072–1078 (2013).

    Article  CAS  Google Scholar 

  31. Yang, C., Tibbitt, M. W., Basta, L. & Anseth, K. S. Mechanical memory and dosing influence stem cell fate. Nat. Mater. 13, 645–652 (2014).

    Article  CAS  Google Scholar 

  32. Tibbitt, M. W. & Anseth, K. S. Dynamic microenvironments: the fourth dimension. Sci. Transl. Med. 4, 160ps124 (2012).

    Article  CAS  Google Scholar 

  33. Jeon, H. et al. Directing cell migration and organization via nanocrater-patterned cell-repellent interfaces. Nat. Mater. 14, 918–923 (2015).

    Article  CAS  Google Scholar 

  34. Mehta, M., Schmidt-Bleek, K., Duda, G. N. & Mooney, D. J. Biomaterial delivery of morphogens to mimic the natural healing cascade in bone. Adv. Drug Deliv. Rev. 64, 1257–1276 (2012).

    Article  CAS  Google Scholar 

  35. Lee, T. T. et al. Light-triggered in vivo activation of adhesive peptides regulates cell adhesion, inflammation and vascularization of biomaterials. Nat. Mater. 14, 352–360 (2015).

    Article  CAS  Google Scholar 

  36. Gjorevski, N. et al. Designer matrices for intestinal stem cell and organoid culture. Nature 539, 560–564 (2016).

    Article  CAS  Google Scholar 

  37. Ranga, A. et al. 3D niche microarrays for systems-level analyses of cell fate. Nat. Commun. 5, 4324 (2014).

    Article  CAS  Google Scholar 

  38. Kobel, S. & Lutolf, M. High-throughput methods to define complex stem cell niches. BioTechniques 48, 9–22 (2010).

    Article  Google Scholar 

  39. Mei, Y. et al. Combinatorial development of biomaterials for clonal growth of human pluripotent stem cells. Nat. Mater. 9, 768–778 (2010).

    Article  CAS  Google Scholar 

  40. Hook, A. L. et al. High throughput methods applied in biomaterial development and discovery. Biomaterials 31, 187–198 (2010).

    Article  CAS  Google Scholar 

  41. Vegas, A. J. et al. Combinatorial hydrogel library enables identification of materials that mitigate the foreign body response in primates. Nat. Biotechnol. 34, 345–352 (2016).

    Article  CAS  Google Scholar 

  42. Celiz, A. D. et al. Discovery of a novel polymer for human pluripotent stem cell expansion and multilineage differentiation. Adv. Mater. 27, 4006–4012 (2015).

    Article  CAS  Google Scholar 

  43. Shembekar, N., Chaipan, C., Utharala, R. & Merten, C. A. Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics. Lab Chip 16, 1314–1331 (2016).

    Article  CAS  Google Scholar 

  44. Mao, A. S. et al. Deterministic encapsulation of single cells in thin tunable microgels for niche modelling and therapeutic delivery. Nat. Mater. 16, 236–243 (2017).

    Article  CAS  Google Scholar 

  45. Brandenberg, N. & Lutolf, M. P. In situ patterning of microfluidic networks in 3d cell-laden hydrogels. Adv. Mater. 28, 7450–7456 (2016).

    Article  CAS  Google Scholar 

  46. Redondo, A. & LeSar, R. Modeling and simulation of biomaterials. Annu. Rev. Mater. Res. 34, 279–314 (2004).

    Article  CAS  Google Scholar 

  47. Gautieri, A. & Buehler, M. J. in Materiomics: Multiscale Mechanics of Biological Materials and Structures (eds Buehler, M. J. & Ballarini, R.) 13–55 (Springer, 2013).

    Book  Google Scholar 

  48. Karanasiou, G. S. et al. Stents: biomechanics, biomaterials, and insights from computational modeling. Ann. Biomed. Eng. 45, 853–872 (2017).

    Article  Google Scholar 

  49. Li, H. Smart Hydrogel Modelling (Springer, 2009).

    Book  Google Scholar 

  50. Belton, J.-M. et al. Hi-C: a comprehensive technique to capture the conformation of genomes. Methods 58, 268–276 (2012).

    Article  CAS  Google Scholar 

  51. Giresi, P. G., Kim, J., McDaniell, R. M., Iyer, V. R. & Lieb, J. D. FAIRE (formaldehyde-assisted isolation of regulatory elements) isolates active regulatory elements from human chromatin. Genome Res. 17, 877–885 (2007).

    Article  CAS  Google Scholar 

  52. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    Article  CAS  Google Scholar 

  53. Bennun, S. V. et al. Systems glycobiology: integrating glycogenomics, glycoproteomics, glycomics, and other 'omics data sets to characterize cellular glycosylation processes. J. Mol. Biol. 428, 3337–3352 (2016).

    Article  CAS  Google Scholar 

  54. Babu, P. Glycans in regeneration. ACS Chem. Biol. 9, 96–104 (2014).

    Article  CAS  Google Scholar 

  55. Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    Article  CAS  Google Scholar 

  56. Klein, Allon M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201.

    Article  CAS  Google Scholar 

  57. Angelo, M. et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20, 436–442 (2014).

    Article  CAS  Google Scholar 

  58. Rotem, A. et al. Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat. Biotechnol. 33, 1165–1172 (2015).

    Article  CAS  Google Scholar 

  59. Depince-Berger, A. E., Aanei, C., Iobagiu, C., Jeraiby, M. & Lambert, C. New tools in cytometry. Morphologie 100, 199–209 (2016).

    Article  Google Scholar 

  60. Fujita, K. Follow-up review: recent progress in the development of super-resolution optical microscopy. Microscopy 65, 275–281 (2016).

    Article  CAS  Google Scholar 

  61. Chen, B.-C. et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346 (2014).

  62. Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).

    Article  CAS  Google Scholar 

  63. Bougen-Zhukov, N., Loh, S. Y., Lee, H. K. & Loo, L.-H. Large-scale image-based screening and profiling of cellular phenotypes. Cytometry Part A 91, 115–125 (2016).

    Article  Google Scholar 

  64. Prestwich, G. D. et al. What is the greatest regulatory challenge in the translation of biomaterials to the clinic? Sci. Transl. Med. 4, 160cm114 (2012).

    Article  Google Scholar 

  65. Ratcliffe, A. Difficulties in the translation of functionalized biomaterials into regenerative medicine clinical products. Biomaterials 32, 4215–4217 (2011).

    Article  CAS  Google Scholar 

  66. Hench, L. L. & Thompson, I. Twenty-first century challenges for biomaterials. J. R. Soc. Interface 7, S379–S391 (2010).

    Article  CAS  Google Scholar 

  67. Amato, S. F. & Ezzell, R. M. Jr (eds) Regulatory Affairs for Biomaterials and Medical Devices 1st edn (Woodhead, 2014).

    Google Scholar 

  68. Groen, N. et al. Stepping into the omics era: opportunities and challenges for biomaterials science and engineering. Acta Biomater. 34, 133–142 (2016).

    Article  CAS  Google Scholar 

  69. Kumar, V., Bhalla, A. & Rathore, A. S. Design of experiments applications in bioprocessing: concepts and approach. Biotechnol. Prog. 30, 86–99 (2014).

    Article  CAS  Google Scholar 

  70. Mandenius, C.-F. & Brundin, A. Bioprocess optimization using design-of-experiments methodology. Biotechnol. Prog. 24, 1191–1203 (2008).

    Article  CAS  Google Scholar 

  71. Keskin Gündoğdu, T., Deniz, İ., Çalışkan, G., Şahin, E. S. & Azbar, N. Experimental design methods for bioengineering applications. Crit. Rev. Biotechnol. 36, 368–388 (2016).

    Article  CAS  Google Scholar 

  72. Lim, M. et al. Intelligent bioprocessing for haemotopoietic cell cultures using monitoring and design of experiments. Biotechnol. Adv. 25, 353–368 (2007).

    Article  CAS  Google Scholar 

  73. Lewis, A. M., Abu-Absi, N. R., Borys, M. C. & Li, Z. J. The use of 'omics technology to rationally improve industrial mammalian cell line performance. Biotechnol. Bioeng. 113, 26–38 (2016).

    Article  CAS  Google Scholar 

  74. Wuest, D. M., Harcum, S. W. & Lee, K. H. Genomics in mammalian cell culture bioprocessing. Biotechnol. Adv. 30, 629–638 (2012).

    Article  CAS  Google Scholar 

  75. Villaverde, A. F. & Banga, J. R. Reverse engineering and identification in systems biology: strategies, perspectives and challenges. J. R. Soc. Interface 11, 20130505 (2014).

    Article  Google Scholar 

  76. Chaudhuri, O. et al. Extracellular matrix stiffness and composition jointly regulate the induction of malignant phenotypes in mammary epithelium. Nat. Mater. 13, 970–978 (2014).

    Article  CAS  Google Scholar 

  77. Scharp, D. W. & Marchetti, P. Encapsulated islets for diabetes therapy: history, current progress, and critical issues requiring solution. Adv. Drug Deliv. Rev. 67–68, 35–73 (2014).

    Article  CAS  Google Scholar 

  78. Pepper, A. R. et al. A prevascularized subcutaneous device-less site for islet and cellular transplantation. Nat. Biotechnol. 33, 518–523 (2015).

    Article  CAS  Google Scholar 

  79. Pagliuca, F. W. et al. Generation of functional human pancreatic β cells in vitro. Cell 159, 428–439 (2014).

    Article  CAS  Google Scholar 

  80. Tomei, A. A. et al. Device design and materials optimization of conformal coating for islets of Langerhans. Proc. Natl Acad. Sci. USA 111, 10514–10519 (2014).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge funding from National Institutes of Health (R01 DE013033; R01 DE013349) and the National Science Foundation funded Materials Research Science and Engineering Centers at Harvard University (DMR-1420570).

Author information

Authors and Affiliations

  1. Harvard School of Engineering and Applied Sciences, Cambridge, 02138, Massachusetts, USA

    Max Darnell & David J. Mooney

  2. Wyss Institute for Biologically Inspired Engineering, Cambridge, 02138, Massachusetts, USA

    Max Darnell & David J. Mooney

Authors
  1. Max Darnell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David J. Mooney
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David J. Mooney.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Darnell, M., Mooney, D. Leveraging advances in biology to design biomaterials. Nature Mater 16, 1178–1185 (2017). https://doi.org/10.1038/nmat4991

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmat4991

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research