biological circuits
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2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Fengyu Zhang ◽  
Yanhong Sun ◽  
Yihao Zhang ◽  
Wenting Shen ◽  
Shujing Wang ◽  
...  

AbstractSynthetic Biology aims to create predictable biological circuits and fully operational biological systems. Although there are methods to create more stable oscillators, such as repressilators, independently controlling the oscillation of reporter genes in terms of their amplitude and period is only on theoretical level. Here, we introduce a new oscillator circuit that can be independently controlled by two inducers in Escherichia coli. Some control components, including σECF11 and NahR, were added to the circuit. By systematically tuning the concentration of the inducers, salicylate and IPTG, the amplitude and period can be modulated independently. Furthermore, we constructed a quantitative model to forecast the regulation results. Under the guidance of the model, the expected oscillation can be regulated by choosing the proper concentration combinations of inducers. In summary, our work achieved independent control of the oscillator circuit, which allows the oscillator to be modularized and used in more complex circuit designs.


2021 ◽  
Author(s):  
Santiago Chaillou ◽  
Eleftheria-Pinelopi Stamou ◽  
Leticia L. Torres ◽  
Ana B. Riesco ◽  
Warren Hazelton ◽  
...  

Plasmids of the ColE1 family are among the most frequently used plasmids in molecular biology. They were adopted early in the field for many biotechnology applications, and as model systems to study plasmid biology. The mechanism of replication of ColE1 plasmids is well understood, involving the interaction between a plasmid-encoded sense-antisense gene pair (RNAI and RNAII). Because of its mechanism of replication, bacterial cells cannot maintain two different plasmids with the same origin, with one being rapidly lost from the population — a process known as plasmid incompatibility. While mutations in the regulatory genes RNAI and RNAII have been reported to make colE1 plasmids more compatible, there has been no attempt to engineer compatible colE1 origins, which can be used for multi-plasmid applications and that can bypass design constrains created by the current limited plasmid origin repertoire available. Here, we show that by targeting sequence diversity to the loop regions of RNAI (and RNAII), it is possible to select new viable colE1 origins that are compatible with the wild-type one. We demonstrate origin compatibility is not simply determined by sequence divergence in the loops, and that pairwise compatibility is not an accurate guide for higher order interactions. We identify potential principles to engineer plasmid copy number independently from other regulatory strategies and we propose plasmid compatibility as a tractable model to study biological orthogonality. New characterised plasmid origins increase flexibility and accessible complexity of design for challenging synthetic biology applications where biological circuits can be dispersed between multiple independent genetic elements.


2021 ◽  
Author(s):  
Angel Fernando Cisneros Caballero ◽  
Francois D. Rouleau ◽  
Carla Bautista ◽  
Pascale Lemieux ◽  
Nathan Dumont-Leblond

Synthetic biology aims to engineer biological circuits, which often involve gene expression. A particularly promising group of regulatory elements are riboswitches because of their versatility with respect to their targets, but early synthetic designs were not as attractive because of a reduced dynamic range with respect to protein regulators. Only recently, the creation of toehold switches helped overcome this obstacle by also providing an unprecedented degree of orthogonality. However, a lack of automated design and optimization tools prevents the widespread and effective use of toehold switches in high-throughput experiments. To address this, we developed Toeholder, a comprehensive open-source software for toehold design and in silico benchmarking. Toeholder takes into consideration sequence constraints as well as data derived from molecular dynamics simulations of a toehold switch. We describe the software and its in silico validation results, as well as its potential applications and impacts on the management and design of toehold switches.


2021 ◽  
Author(s):  
Ana Maria Restrepo Sierra ◽  
Stefan T. Arold ◽  
Raik Grünberg

Cell-free transcription and translation systems promise to accelerate and simplify the engineering of proteins, biological circuits and metabolic pathways. Their encapsulation on microfluidic platforms can generate millions of cell-free reactions in picoliter volume droplets. However, current methods struggle to create DNA diversity between droplets while also reaching sufficient protein expression levels. In particular, efficient multi-gene expression has remained elusive. We here demonstrate that co-encapsulation of DNA-coated beads with a defined cell-free system allows high protein expression while also supporting genetic diversity between individual droplets. We optimize DNA loading on commercially available microbeads through direct binding as well as through the sequential coupling of up to three genes via a solid-phase Golden Gate assembly or BxB1 integrase-based recombineering. Encapsulation with an off-the-shelf microfluidics device allows for single or multiple protein expression from a single DNA-coated bead per 14 pL droplet. We envision that this approach will help to scale up and parallelize the rapid prototyping of more complex biological systems.


2021 ◽  
Author(s):  
Briar Doty ◽  
Stefan Mihalas ◽  
Anton Arkhipov ◽  
Alex Piet

Deep convolutional neural networks (CNNs) are powerful computational tools for a large variety of tasks (Goodfellow, 2016). Their architecture, composed of layers of repeated identical neural units, draws inspiration from visual neuroscience. However, biological circuits contain a myriad of additional details and complexity not translated to CNNs, including diverse neural cell types (Tasic, 2018). Many possible roles for neural cell types have been proposed, including: learning, stabilizing excitation and inhibition, and diverse normalization (Marblestone, 2016; Gouwens, 2019). Here we investigate whether neural cell types, instantiated as diverse activation functions in CNNs, can assist in the feed-forward computational abilities of neural circuits. Our heterogeneous cell type networks mix multiple activation functions within each activation layer. We assess the value of mixed activation functions by comparing image classification performance to that of homogeneous control networks with only one activation function per network. We observe that mixing activation functions can improve the image classification abilities of CNNs. Importantly, we find larger improvements when the activation functions are more diverse, and in more constrained networks. Our results suggest a feed-forward computational role for diverse cell types in biological circuits. Additionally, our results open new avenues for the development of more powerful CNNs.


2021 ◽  
Author(s):  
Fengyu Zhang ◽  
Yanhong Sun ◽  
Yihao Zhang ◽  
Wenting Shen ◽  
Shujing Wang ◽  
...  

Abstract Synthetic Biology aims to create predictable biological circuits and fully operational biological systems. Although there are methods to create more stable oscillators, such as repressilators, orthogonally controlling the oscillation of reporter genes in terms of their amplitude and period is only on theoretical level. Here, we introduce a new oscillator circuit that can be orthogonally controlled by two inducers in Escherichia coli. Some control components, including σECF11 and NahR, were added to the circuit. By systematically tuning the concentration of the inducers, salicylate and IPTG, the amplitude and period can be modulated independently. Furthermore, we constructed a quantitative model to forecast the regulation results. Under the guidance of the model, the expected oscillation can be regulated by choosing the proper concentration combinations of inducers. In summary, our work achieved orthogonal control of the oscillator circuit, which allows the oscillator to be modularized and used in more complex circuit designs.


Author(s):  
Christopher J. Robinson ◽  
Jonathan Tellechea-Luzardo ◽  
Pablo Carbonell ◽  
Adrian J. Jervis ◽  
Cunyu Yan ◽  
...  

Metabolic engineering technologies have been employed with increasing success over the last three decades for the engineering and optimization of industrial host strains to competitively produce high-value chemical targets. To this end, continued reductions in the time taken from concept, to development, to scale-up are essential. Design–Build–Test–Learn pipelines that are able to rapidly deliver diverse chemical targets through iterative optimization of microbial production strains have been established. Biofoundries are employing in silico tools for the design of genetic parts, alongside combinatorial design of experiments approaches to optimize selection from within the potential design space of biological circuits based on multi-criteria objectives. These genetic constructs can then be built and tested through automated laboratory workflows, with performance data analysed in the learn phase to inform further design. Successful examples of rapid prototyping processes for microbially produced compounds reveal the potential role of biofoundries in leading the sustainable production of next-generation bio-based chemicals.


2021 ◽  
Vol 90 (1) ◽  
Author(s):  
Max A. English ◽  
Raphaël V. Gayet ◽  
James J. Collins

In 1961, Jacob and Monod proposed the operon model of gene regulation. At the model's core was the modular assembly of regulators, operators, and structural genes. To illustrate the composability of these elements, Jacob and Monod linked phenotypic diversity to the architectures of regulatory circuits. In this review, we examine how the circuit blueprints imagined by Jacob and Monod laid the foundation for the first synthetic gene networks that launched the field of synthetic biology in 2000. We discuss the influences of the operon model and its broader theoretical framework on the first generation of synthetic biological circuits, which were predominantly transcriptional and posttranscriptional circuits. We also describe how recent advances in molecular biology beyond the operon model—namely, programmable DNA- and RNA-binding molecules as well as models of epigenetic and posttranslational regulation—are expanding the synthetic biology toolkit and enabling the design of more complex biological circuits. Expected final online publication date for the Annual Review of Biochemistry, Volume 90 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Yunhee Hwang ◽  
Seong Gyeong Kim ◽  
Sungho Jang ◽  
Jongmin Kim ◽  
Gyoo Yeol Jung

Abstract Background Synthetic biological circuits are widely utilized to control microbial cell functions. Natural and synthetic riboswitches are attractive sensor modules for use in synthetic biology applications. However, tuning the fold-change of riboswitch circuits is challenging because a deep understanding of the riboswitch mechanism and screening of mutant libraries is generally required. Therefore, novel molecular parts and strategies for straightforward tuning of the fold-change of riboswitch circuits are needed. Results In this study, we devised a toehold switch-based modulator approach that combines a hybrid input construct consisting of a riboswitch and transcriptional repressor and de-novo-designed riboregulators named toehold switches. First, the introduction of a pair of toehold switches and triggers as a downstream signal-processing module to the hybrid input for coenzyme B12 resulted in a functional riboswitch circuit. Next, several optimization strategies that focused on balancing the expression levels of the RNA components greatly improved the fold-change from 260- to 887-fold depending on the promoter and host strain. Further characterizations confirmed low leakiness and high orthogonality of five toehold switch pairs, indicating the broad applicability of this strategy to riboswitch tuning. Conclusions The toehold switch-based modulator substantially improved the fold-change compared to the previous sensors with only the hybrid input construct. The programmable RNA-RNA interactions amenable to in silico design and optimization can facilitate further development of RNA-based genetic modulators for flexible tuning of riboswitch circuitry and synthetic biosensors.


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