Synthetic biology and biomimetic chemistry as converging technologies fostering a new generation of smart biosensors

Scognamiglio, Viviana; Antonacci, Amina; Lambreva, Maya D.; Liţescu, Simona Carmen; Rea, Giuseppina

doi:10.1016/j.bios.2015.07.078

Cited by 51 publications

(16 citation statements)

References 84 publications

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“…Inspired by the natural bio-recognition elements, synthetic receptors are designed to mimic their function with better attributes such as sensitivity, robustness, and detection range. While responding to the external stimuli, they have features which switch between on/off status to recognize and transduce the interaction [ 17 ]. Novel advances, such as toggle switches, synthetic entities mimicking natural molecules, and gene networks, facilitate the redesign of switchable functions and sensing elements.…”

Section: Biosensing Technologies and Food Sustainabilitymentioning

confidence: 99%

“…Examples of related biosensing technologies are: synthetic cell-based biosensors; artificial liposomes; and bioinspired synthetic molecules like biomimetics, molecular imprinting polymers, aptamers, peptide nucleic acids, and ribozymes. These biosensing technologies have been widely applied to molecule sensing, biofuel production, waste degradation, and fine chemical production [ 17 , 18 ].…”

Section: Biosensing Technologies and Food Sustainabilitymentioning

confidence: 99%

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Biosensors for Sustainable Food Engineering: Challenges and Perspectives

et al. 2018

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Current food production faces tremendous challenges from growing human population, maintaining clean resources and food qualities, and protecting climate and environment. Food sustainability is mostly a cooperative effort resulting in technology development supported by both governments and enterprises. Multiple attempts have been promoted in tackling challenges and enhancing drivers in food production. Biosensors and biosensing technologies with their applications, are being widely applied to tackling top challenges in food production and its sustainability. Consequently, a growing demand in biosensing technologies exists in food sustainability. Microfluidics represents a technological system integrating multiple technologies. Nanomaterials, with its technology in biosensing, is thought to be the most promising tool in dealing with health, energy, and environmental issues closely related to world populations. The demand of point of care (POC) technologies in this area focus on rapid, simple, accurate, portable, and low-cost analytical instruments. This review provides current viewpoints from the literature on biosensing in food production, food processing, safety and security, food packaging and supply chain, food waste processing, food quality assurance, and food engineering. The current understanding of progress, solution, and future challenges, as well as the commercialization of biosensors are summarized.

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Section: Biosensing Technologies and Food Sustainabilitymentioning

confidence: 99%

Section: Biosensing Technologies and Food Sustainabilitymentioning

confidence: 99%

Biosensors for Sustainable Food Engineering: Challenges and Perspectives

et al. 2018

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“…Engineering complexity and refactoring cell capabilities were detailed recently considering that currently is a critical moment for synthetic biology, because the initial fervor for the main achievements attained gives way to a deeper understanding of the complexity of biological systems in order to significantly progress in the applicability of design principles for living organisms [199]. A recent review considered the role of synthetic biology in supporting biosensor technology, reflecting on the features that make it a useful tool for designing and constructing engineered biological systems for sensing application and reporting examples from the literature [200]. Another revision describes the current therapeutic delivery tools, the limitations that hamper their use in human applications, the biological tools and strategies that are at the vanguard of synthetic biology discussing their potential to advance the specificity, efficiency, and safety of the current generation of cell and gene therapies, including how they can be used to confer curative effects improving those of conventional therapeutics [201].…”

Section: Novel Perspectives For the Near Futurementioning

confidence: 99%

Synthetic Biology: Computational Modeling Bridging the Gap between In Vitro and In Vivo Reactions

Duschak¹

2015

Curr Synthetic Sys Biol

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The synthetic biology firstly refers to the design and fabrication of biological components and systems that do not already exist in the natural world and to the redesign and fabrication of existing biological systems. The link of computational tools to cell-free systems, converts to synthetic biology is an emerging field expert to build artificial biological systems through the combination of molecular biology and engineering approaches. Herein, most findings describing the differences between in vivo and in vitro reactions and systems have been extensively described. The specific applications of computational tools to the design of an in vitro gene expression platform known as the artificial cell, its components and the strategies developed to predict activities of processor modules and to control the expression of genes have been discussed in detail. Potential applications of artificial cells in drug delivery, in biosynthesis, among others, have been described. Two sources of models for the possible developing of the computational toolbox for cell-free synthetic biology include: i) Physical models of single cellular components able to be created from original principles, guiding to focus on tools to predict structure and dynamics of particular components;ii) A wide-range of mathematical models for predicting system dynamics of natural cells.Regarding modeling algorithms, there is a broad kind of models available for synthetic biologists and some areas of potential growth identified for researchers interested in developing tools for cell-free systems. Among them, deterministic, exploratory, molecular dynamic, stochastic, all atom models, among others, have been described and discussed. By using computational models to set up quantitative differences between in vitro reactions and in vivo systems, could identify specific mechanisms in living organisms to be further used in in vitro reactions in order to facilitate their processes. Thus, computational modeling would bridge the gap between in vitro and in vivo reactions. CSSB, an open access journalThe synthetic biology refers to • The design and fabrication of biological components and systems that do not already exist in the natural world and the redesign and fabrication of existing biological systems.

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“…A QdoR-based biosensor was also applied to monitor kaempferol production in single cells by flow cytometry (Siedler et al, 2014). Inspired by these features, TFs can be developed as the main elements to construct whole-cell biosensors that can regulate the transcription level of reporter genes in response to specific metabolites (Scognamiglio et al, 2015). L-Arginine production in C. glutamicum is organized by an arg cluster of argCJBDFRGH that can be classified into argCJBDFR and argGH operons.…”

Section: Introductionmentioning

confidence: 99%

Development of a Novel Biosensor-Driven Mutation and Selection System via in situ Growth of Corynebacterium crenatum for the Production of L-Arginine

Chen

Peng

et al. 2020

Front. Bioeng. Biotechnol.

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The high yield mutants require a high-throughput screening method to obtain them quickly. Here, we developed an L-arginine biosensor (ARG-Select) to obtain increased L-arginine producers among a large number of mutant strains. This biosensor was constructed by ArgR protein and argC promoter, and could provide the strain with the output of bacterial growth via the reporter gene sacB; strains with high Larginine production could survive in 10% sucrose screening. To extend the screening limitation of 10% sucrose, the sensitivity of ArgR protein to L-arginine was decreased. Corynebacterium crenatum SYPA5-5 and its systems pathway engineered strain Cc6 were chosen as the original strains. This biosensor was employed, and L-arginine hyperproducing mutants were screened. Finally, the HArg1 and DArg36 mutants of C. crenatum SYPA5-5 and Cc6 could produce 56.7 and 95.5 g L −1 of L-arginine, respectively, which represent increases of 35.0 and 13.5%. These results demonstrate that the transcription factor-based biosensor could be applied in high yield strains selection as an effective high-throughput screening method.

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Synthetic biology and biomimetic chemistry as converging technologies fostering a new generation of smart biosensors

Cited by 51 publications

References 84 publications

Biosensors for Sustainable Food Engineering: Challenges and Perspectives

Biosensors for Sustainable Food Engineering: Challenges and Perspectives

Synthetic Biology: Computational Modeling Bridging the Gap between In Vitro and In Vivo Reactions

Development of a Novel Biosensor-Driven Mutation and Selection System via in situ Growth of Corynebacterium crenatum for the Production of L-Arginine

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