Synthetic Lateral Inhibition in Periodic Pattern Forming Microbial Colonies
Authors: Jordi Pla
Salva Duran-Nebreda
Blai Vidiella
Ricard Solé
Jordi Piñero
Nuria Conde-Pueyo
Journal: ACS Synthetic Biology (2021)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: developmental biology; lateral inhibition; pattern formation; synthetic biology.
Affiliations: Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain, ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain, Evolution of Technology Lab, Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain, Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, United States

Abstract:  Multicellular entities are characterized by intricate spatial patterns, intimately related to the functions they perform. These patterns are often created from isotropic embryonic structures, without external information cues guiding the symmetry breaking process. Mature biological structures also display characteristic scales with repeating distributions of signals or chemical species across space. Many candidate patterning modules have been used to explain processes during development and typically include a set of interacting and diffusing chemicals or agents known as morphogens. Great effort has been put forward to better understand the conditions in which pattern-forming processes can occur in the biological domain. However, evidence and practical knowledge allowing us to engineer symmetry-breaking is still lacking. Here we follow a different approach by designing a synthetic gene circuit in E. coli that implements a local activation long-range inhibition mechanism. The synthetic gene network implements an artificial differentiation process that changes the physicochemical properties of the agents. Using both experimental results and modeling, we show that the proposed system is capable of symmetry-breaking leading to regular spatial patterns during colony growth. Studying how these patterns emerge is fundamental to further our understanding of the evolution of biocomplexity and the role played by self-organization. The artificial system studied here and the engineering perspective on embryogenic processes can help validate developmental theories and identify universal properties underpinning biological pattern formation, with special interest for the area of synthetic developmental biology. 

Retracted: No

PubPeer comments:
 **1 Forged authorship, _i.e._ usurped or theft of authorsu2019 names and affiliations**: The name of Bertrand Chapron was unduly used by the 2 main authors Tim Chen and C.Y.J. Chen; so was his affiliation to _Laboratoire d Ocu00e9anographie Physique et Spatiale_. His name and affiliation to Ifremer were wrongly merged with the name of _Institut des Sciences et des Techniques de Communication_ at Abidjan, Ivory Coast. B. Chapron never took part in this publication, which is totally outside his scientific field of expertise; neither did he give his consent to be the co-author. B. Chapron had no prior contact with Tim Chen and John CY Chen in any shape or form, until he became aware that his name was being unduly cited by the two above-cited authors. **2 Unethical practice of the journal**: The editor of _Iranian Journal of Science and Technology, Transactions of Civil Engineering_ was contacted three times by emails between January and April 2021 for this paper and asked to remove the name and affiliation of B. Chapron. In April 2021, his last answer was: u201c_We will process soon_u201d. But nothing was done so far. **3 Affiliations and email address(es) of the corresponding author(s)**: **3.1.** The academic affiliation of the corresponding author Tim Chen (timchen@tdtu.edu.vn) is: _Faculty of Information Technology, Ton Duc Thang University (TDTU), Ho Chi Minh City, Vietnam_. Ifremer contacted TDTU in January 2021 to report the usurpation of Bertrand Chapronu2019s identity. TDTU led its own investigation into Tim Chenu2019s activities. However, Ifremer is not in a legal position to disclose the outcome of TDTUu2019s investigation. **3.2.** The affiliations of the corresponding author C.Y.J. Chen (jc343965@gmail.com) to _Department of Computer Science and Engineering, BRAC University_ -Bangladesh, and _Faculty of Management Science, Covenant University_ -Nigeria, are erroneous. According to the information available on internet, there is no _Faculty of Management Science_ at Covenant University-Nigeria. The author C.Y.J. Chen exhibited 29 different academic affiliations in different institutes and or universities in 15 different countries (_i.e._ Bangladesh, Nigeria, Saudi Arabia, United States, Papua New Guinea, Taiwan, United Kingdom, Brasilia, Australia, China, Russia, Kazakhstan, Vietnam, Spain, Egypt) for the 66 papers (at least) published between 2018 and 2021 in which he is a co-author with Tim Chen (timchen@tdtu.edu.vn). **4 Similarities with any other studies (by using Compilatio software)**: u00b0 Compilatio software allowed to detect a similarity of 36% (SI) matching with at least two other papers by the two same authors Tim Chen and John CY Chen: u00b0 https: doi.org 10.12989 eas.2019.17.3.307 with a matching similarity of 23%; u00b0 https: doi:10.1108 ec-11-2018-0522 with a matching similarity of 9%. **5 Related papers by the same two authors Tim Chen and CYJ alias John Chen**: Questionable practices in some other papers written by Tim Chen and C.Y.J. alias John Chen, including a withdrawn paper, are addressed in several posts that are part of the [IFREMER_2021_CC] scientific integrity case handled by [Ifremer] ; contact email address: [ddis@ifremer.fr](mailto:ddis@ifremer.fr) , 
 _Retraction Watch_ has reported on February 3rd, 2022: u201c[French ocean institute goes public about authors who forged their researchersu2019 names] .u201d , 
 _Retraction Watch_ has reported on February 3rd, 2022: u201c[French ocean institute goes public about authors who forged their researchersu2019 names] .u201d , 
 The logic is hard (or impossible) to follow. Some examples below. * What is the dimension of both sides of (1)? $n times 1$, $m times 1$, something else? ![file] * What does the parameter $s$ stand for in (6)? ![file] * Which of the variables depend on $u$ so that the minimum operator in (20) and (21) would make sense? ![file] , 
  Furthermore, intelligence is also a popular field, which catches many researchersu2019 attention. Many algorithms, which are inspired by the **tinny intelligence** from creatures in the Mother Nature, are included in this field. In general, the swarm intelligence method requires evolutionary computing and is imitating the particular behaviors or the survival skills of creatures. For instance, cat swarm optimization (CSO) is proposed by modeling the catu2019s behaviors in the mathematical forms (Chu et al. 2006, 2007); interactive artificial bee colony (IABC) is proposed by simulating the nectar collection behavior of bees (Chu and Tsai 2007); and evolved bat algorithm (EBA) is proposed based on the prey-finding process of bats (Tsai et al. 2012). These algorithms have been applied to solve many problems in engineering and finance fields. Recycled from [Tsai et al (2016)]  Furthermore, swarm intelligence is also a popular field, which catches many researchersu2019 attention. Many algorithms, which are inspired by the **tinny intelligence** from creatures in the Mother Nature, are included in this field. In general, the swarm intelligence method requires evolutionary computing and is imitating the particular behaviors or the survival skills of creatures. For instance, Cat Swarm Optimization (CSO) is proposed by modeling the catu2019s behaviors in the mathematic forms (Chu et al., 2006, 2007); Interactive Artificial Bee Colony (IABC) is proposed by simulating the nectar collection behavior of bees (Tsai et al., 2009); and Evolved Bat Algorithm (EBA) is proposed based on the prey finding process of bats (Tsai et al., 2012). These algorithms have been applied to solve many problems in engineering and finance fields . Also recycled in [Chen et al (2020)] :  Furthermore, intelligence is also a popular field, which catches many researchersu2019 attention. Many algorithms, which are inspired by the **tinny intelligence** from creatures in the Mother Nature, are included in this field. In general, the swarm intelligence method requires evolutionary computing and is imitating the particular behaviors or the survival skills of creatures. For instance, cat swarm optimization (CSO) is proposed by modeling the catu2019s behaviors in the mathematic forms (Chu et al., 2006, Chu and Tsai, 2007); interactive artificial bee colony (IABC) is proposed by simulating the nectar collection behavior of bees (Tsai et al., 2009); and evolved bat algorithm (EBA) is proposed based on the prey finding process of bats (Tsai et al., 2012). These algorithms have been applied to solve many problems in engineering and finance fields. ---------------------------------  The field of swarm intelligence includes various algorithms inspired by **tinny intelligent** from creatures in the Mother Nature. Several algorithms in swarm intelligence are proposed one after another. Most of the algorithms are developed by imitating behaviors or the particular survival skills of creatures. For example, Tsai et al. (2012) proposes a newly developed swarm intelligence algorithm called Evolved Bat Algorithm (EBA) in the early 2012. EBA is an algorithm inspired by the theory of the bat echolocation in the natural world. [Tsai et al (2016)](http: www.icicelb.org ellb contents 2016 7 elb-07-07-09.pdf):  Inspired by the **tinny intelligent** behaviors in biome, many swarm intelligence algorithms have been developed such as flower pollination algorithm [10], Artificial Bee Colony (ABC) algorithm [6], Particle Swarm Optimization (PSO) algorithm [7], firefly algorithm [19], and Bat Algorithm (BA) [18]. Optimization problem can be solved efficiently by these swarm intelligence algorithms. Algorithms in swarm intelligence are also employed to solve engineering problems in many different fields. ,