Abstract
Networked structures integrate numerous elements into one functional unit, while providing a balance between efficiency, robustness, and flexibility. Understanding how biological networks self-assemble will provide insights into how these features arise. Here, we demonstrate how nature forms exquisite muscle networks that can repair, regenerate, and adapt to external perturbations using the feather muscle network in chicken embryos as a paradigm. The self-assembled muscle networks arise through the implementation of a few simple rules. Muscle fibers extend outward from feather buds in every direction, but only those muscle fibers able to connect to neighboring buds are eventually stabilized. After forming such a nearest-neighbor configuration, the network can be reconfigured, adapting to perturbed bud arrangement or mechanical cues. Our computational model provides a bioinspired algorithm for network self-assembly, with intrinsic or extrinsic cues necessary and sufficient to guide the formation of these regenerative networks. These robust principles may serve as a useful guide for assembling adaptive networks in other contexts.
| Original language | English |
|---|---|
| Pages (from-to) | 10858-10867 |
| Number of pages | 10 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 166 |
| Issue number | 22 |
| DOIs | |
| Publication status | Published - 2019 May 28 |
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Self-assembly of biological networks via adaptive patterning revealed by avian intradermal muscle network formation. / Wu, Xiao shan; Yeh, Chao yuan; Hans, I-Chen; Jiang, Ting Xing; Wu, Ping; Widelitz, Randall B.; Baker, Ruth E.; Chuong, Cheng Ming.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 166, No. 22, 28.05.2019, p. 10858-10867.Research output: Contribution to journal › Article
TY - JOUR
T1 - Self-assembly of biological networks via adaptive patterning revealed by avian intradermal muscle network formation
AU - Wu, Xiao shan
AU - Yeh, Chao yuan
AU - Hans, I-Chen
AU - Jiang, Ting Xing
AU - Wu, Ping
AU - Widelitz, Randall B.
AU - Baker, Ruth E.
AU - Chuong, Cheng Ming
PY - 2019/5/28
Y1 - 2019/5/28
N2 - Networked structures integrate numerous elements into one functional unit, while providing a balance between efficiency, robustness, and flexibility. Understanding how biological networks self-assemble will provide insights into how these features arise. Here, we demonstrate how nature forms exquisite muscle networks that can repair, regenerate, and adapt to external perturbations using the feather muscle network in chicken embryos as a paradigm. The self-assembled muscle networks arise through the implementation of a few simple rules. Muscle fibers extend outward from feather buds in every direction, but only those muscle fibers able to connect to neighboring buds are eventually stabilized. After forming such a nearest-neighbor configuration, the network can be reconfigured, adapting to perturbed bud arrangement or mechanical cues. Our computational model provides a bioinspired algorithm for network self-assembly, with intrinsic or extrinsic cues necessary and sufficient to guide the formation of these regenerative networks. These robust principles may serve as a useful guide for assembling adaptive networks in other contexts.
AB - Networked structures integrate numerous elements into one functional unit, while providing a balance between efficiency, robustness, and flexibility. Understanding how biological networks self-assemble will provide insights into how these features arise. Here, we demonstrate how nature forms exquisite muscle networks that can repair, regenerate, and adapt to external perturbations using the feather muscle network in chicken embryos as a paradigm. The self-assembled muscle networks arise through the implementation of a few simple rules. Muscle fibers extend outward from feather buds in every direction, but only those muscle fibers able to connect to neighboring buds are eventually stabilized. After forming such a nearest-neighbor configuration, the network can be reconfigured, adapting to perturbed bud arrangement or mechanical cues. Our computational model provides a bioinspired algorithm for network self-assembly, with intrinsic or extrinsic cues necessary and sufficient to guide the formation of these regenerative networks. These robust principles may serve as a useful guide for assembling adaptive networks in other contexts.
UR - http://www.scopus.com/inward/record.url?scp=85066233284&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066233284&partnerID=8YFLogxK
U2 - 10.1073/pnas.1818506116
DO - 10.1073/pnas.1818506116
M3 - Article
C2 - 31072931
AN - SCOPUS:85066233284
VL - 166
SP - 10858
EP - 10867
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 22
ER -