eprintid: 10106800 rev_number: 14 eprint_status: archive userid: 608 dir: disk0/10/10/68/00 datestamp: 2020-08-07 12:07:54 lastmod: 2021-09-23 22:38:13 status_changed: 2020-08-07 12:07:54 type: article metadata_visibility: show creators_name: Gorochowski, TE creators_name: Hauert, S creators_name: Kreft, J-U creators_name: Marucci, L creators_name: Stillman, NR creators_name: Tang, T-YD creators_name: Bandiera, L creators_name: Bartoli, V creators_name: Dixon, DOR creators_name: Fedorec, AJH creators_name: Fellermann, H creators_name: Fletcher, AG creators_name: Foster, T creators_name: Giuggioli, L creators_name: Matyjaszkiewicz, A creators_name: McCormick, S creators_name: Montes Olivas, S creators_name: Naylor, J creators_name: Rubio Denniss, A creators_name: Ward, D title: Toward Engineering Biosystems With Emergent Collective Functions ispublished: pub divisions: UCL divisions: B02 divisions: C08 divisions: D09 divisions: F96 keywords: synthetic biology, multi-agent modeling, systems biology, emergence, multi-scale, bioengineering, consortia, collectives note: Copyright © 2020 Gorochowski, Hauert, Kreft, Marucci, Stillman, Tang, Bandiera, Bartoli, Dixon, Fedorec, Fellermann, Fletcher, Foster, Giuggioli, Matyjaszkiewicz, McCormick, Montes Olivas, Naylor, Rubio Denniss and Ward. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)(http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. abstract: Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales. date: 2020 date_type: published official_url: https://doi.org/10.3389/fbioe.2020.00705 oa_status: green full_text_type: pub pmcid: PMC7332988 language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1800902 doi: 10.3389/fbioe.2020.00705 lyricists_name: Fedorec, Alexander lyricists_id: AFEDO75 actors_name: Flynn, Bernadette actors_id: BFFLY94 actors_role: owner full_text_status: public publication: Frontiers in Bioengineering and Biotechnology volume: 8 article_number: 705 event_location: Switzerland citation: Gorochowski, TE; Hauert, S; Kreft, J-U; Marucci, L; Stillman, NR; Tang, T-YD; Bandiera, L; ... Ward, D; + view all <#> Gorochowski, TE; Hauert, S; Kreft, J-U; Marucci, L; Stillman, NR; Tang, T-YD; Bandiera, L; Bartoli, V; Dixon, DOR; Fedorec, AJH; Fellermann, H; Fletcher, AG; Foster, T; Giuggioli, L; Matyjaszkiewicz, A; McCormick, S; Montes Olivas, S; Naylor, J; Rubio Denniss, A; Ward, D; - view fewer <#> (2020) Toward Engineering Biosystems With Emergent Collective Functions. Frontiers in Bioengineering and Biotechnology , 8 , Article 705. 10.3389/fbioe.2020.00705 <https://doi.org/10.3389/fbioe.2020.00705>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10106800/1/fbioe-08-00705.pdf