Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions
Article No.: 147, Pages 1 - 8
Abstract
Synthetic Biology aims to create biological systems from scratch that do not exist in nature. An important method in this context is the engineering of DNA sequences such that cells realize Boolean functions that serve as control mechanisms in biological systems, e.g. in medical or agricultural applications. Libraries of logic gates exist as predefined gene sequences, based on the genetic mechanism of transcriptional regulation. Each individual gate is composed of different biological parts to allow for the differentiation of their output signals. Even gates of the same logic type therefore exhibit different transfer characteristics, i.e. relation from input to output signals. Thus, simulation of the whole network of genetic gates is needed to determine the performance of a genetic circuit. This makes mapping Boolean functions to these libraries much more complicated compared to EDA. Yet, optimal results are desired in the design phase due to high lab implementation costs. In this work, we identify fundamental features of the transfer characteristic of gates based on transcriptional regulation which is widely used in genetic gate technologies. Based on this, we present novel exact (Branch-and-Bound) and heuristic (Branch-and-Bound, Simulated Annealing) algorithms for the problem of technology mapping of genetic circuits and evaluate them using a prominent gate library. In contrast to state-of-the-art tools, all obtained solutions feature a (near) optimal output performance. Our exact method only explores 6.5 % and the heuristics even 0.2 % of the design space.
References
[1]
Karim Abbas. 2020. Handbook of Digital CMOS Technology, Circuits, and Systems (1 ed.). Springer International Publishing, Cham.
[2]
Saed Alizamir, Steffen Rebennack, and Panos Pardalos. 2008. Improving the Neighborhood Selection Strategy in Simulated Annealing Using the Optimal Stopping Problem. In Global Optimization: Focus on Simulated Annealing, Cher Ming Tan (Ed.). I-Tech Education and Publication, Rijeka, 363--382.
[3]
Evan Appleton, Curtis Madsen, Nicholas Roehner, and Douglas Densmore. 2017. Design Automation in Synthetic Biology. Cold Spring Harbor Perspectives in Biology 9 (02 2017), a023978.
[4]
Vaughn Betz and Jonathan Rose. 1997. VPR: a new packing, placement and routing tool for FPGA research. In Field-Programmable Logic and Applications, Wayne Luk, Peter Y. K. Cheung, and Manfred Glesner (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 213--222.
[5]
Clive G. Bowsher and Peter S. Swain. 2012. Identifying sources of variation and the flow of information in biochemical networks. Proceedings of the National Academy of Sciences 109, 20 (2012), E1320--E1328. arXiv:https://www.pnas.org/content/109/20/E1320.full.pdf
[6]
Jens Clausen. 1999. Branch and Bound Algorithms - Principles And Examples.
[7]
Michael B. Elowitz and Stanislas Leibler. 2000. A synthetic oscillatory network of transcriptional regulators. Nature 403, 6767 (01 Jan 2000), 335--338.
[8]
Larry Goldstein and Michael Waterman. 1988. Neighborhood Size in the Simulated Annealing Algorithm. American Journal of Mathematical and Management Sciences 8, 3--4 (1988), 409--423.
[9]
Timothy S Jones, Samuel M D Oliveira, Chris J Myers, Christopher A Voigt, and Douglas Densmore. 2022. Genetic circuit design automation with Cello 2.0. Nature protocols 17, 4 (April 2022), 1097--1113.
[10]
François-Xavier Lehr, Maleen Hanst, Marc Vogel, Jennifer Kremer, H. Ulrich Göringer, Beatrix Suess, and Heinz Koeppl. 2019. Cell-Free Prototyping of AND-Logic Gates Based on Heterogeneous RNA Activators. ACS Synthetic Biology 8, 9 (2019), 2163--2173. arXiv:https://doi.org/10.1021/acssynbio.9b00238 31393707.
[11]
Tae Seok Moon, Chunbo Lou, Alvin Tamsir, Brynne Stanton, and Christopher Voigt. 2012. Genetic Programs Constructed from Layered Logic Gates in Single Cells. Nature 491 (10 2012).
[12]
David R. Morrison, Sheldon H. Jacobson, Jason J. Sauppe, and Edward C. Sewell. 2016. Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning. Discrete Optimization 19 (2016), 79--102.
[13]
Alec A. K. Nielsen, Bryan S. Der, Jonghyeon Shin, Prashant Vaidyanathan, Vanya Paralanov, Elizabeth A. Strychalski, David Ross, Douglas Densmore, and Christopher A. Voigt. 2016. Genetic circuit design automation. Science 352, 6281 (2016), aac7341.
[14]
Nicholas Roehner and Chris J. Myers. 2014. Directed Acyclic Graph-Based Technology Mapping of Genetic Circuit Models. ACS Synthetic Biology 3, 8 (2014), 543--555.
[15]
Fabio Romeo and Alberto Sangiovanni-Vincentelli. 1991. A theoretical framework for simulated annealing. Algorithmica 6, 1 (01 Jun 1991), 302.
[16]
Daniel J. Sayut, Yan Niu, and Lianhong Sun. 2009. Construction and Enhancement of a Minimal Genetic AND Logic Gate. Applied and Environmental Microbiology 75, 3 (2009), 637--642. arXiv:https://journals.asm.org/doi/pdf/10.1128/AEM.01684-08
[17]
Tobias Schladt, Nicolai Engelmann, Erik Kubaczka, Christian Hochberger, and Heinz Koeppl. 2021. Automated Design of Robust Genetic Circuits: Structural Variants and Parameter Uncertainty. ACS Synthetic Biology 10, 12 (2021), 3316--3329. arXiv:https://doi.org/10.1021/acssynbio.1c00193 34807573.
[18]
Zoe Swank, Nadanai Laohakunakorn, and Sebastian J. Maerkl. 2019. Cell-free gene-regulatory network engineering with synthetic transcription factors. Proceedings of the National Academy of Sciences 116, 13 (2019), 5892--5901. arXiv:https://www.pnas.org/doi/pdf/10.1073/pnas.1816591116
[19]
W. Swartz and C. Sechen. 1990. New algorithms for the placement and routing of macro cells. In 1990 IEEE International Conference on Computer-Aided Design. Digest of Technical Papers. IEEE Computer Society, Los Alamitos, CA, USA, 336--339.
[20]
Phrangboklang L. Thangkhiew and Kamalika Datta. 2018. Scalable in-memory mapping of Boolean functions in memristive crossbar array using simulated annealing. Journal of Systems Architecture 89 (2018), 49--59.
[21]
Prashant Vaidyanathan, Bryan S. Der, Swapnil Bhatia, Nicholas Roehner, Ryan Silva, Christopher A. Voigt, and Douglas Densmore. 2015. A Framework for Genetic Logic Synthesis. Proc. IEEE 103, 11 (2015), 2196--2207.
[22]
J. Yuan, L. Wang, X. Zhou, Y. Xia, and J. Hu. 2017. RBSA: Range-based simulated annealing for FPGA placement. In 2017 International Conference on Field Programmable Technology (ICFPT). IEEE Press, Los Alamitos, CA, USA, 1--8.
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- Technology Mapping of Genetic Circuits: From Optimal to Fast Solutions
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Published In
October 2022
1467 pages
ISBN:9781450392174
DOI:10.1145/3508352
- Conference Chair:
- Tulika Mitra,
- Program Chairs:
- Evangeline Young,
- Jinjun Xiong
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Published: 22 December 2022
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