Transcription factor-based biosensors: a molecular-guided approach for natural product engineering
TL;DR: In this article, the development and application of engineered allosteric transcription factor-based biosensors are described that enable optimization of precursor availability, product titers, and downstream product tailoring for advancing the natural product bioeconomy.
About: This article is published in Current Opinion in Biotechnology.The article was published on 2021-06-01. It has received 38 citations till now.
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TL;DR: The current advancements made in biosensors and the applications in detection of various non-communicable and communicable diseases, as well as future prospects of nano-biosensors for diagnostics are dealt with.
Abstract: The outstretched applications of biosensors in diverse domains has become the reason for their attraction for scientific communities. Because they are analytical devices, they can detect both quantitative and qualitative biological components through the generation of detectable signals. In the recent past, biosensors witnessed significant changes and developments in their design as well as features. Nanotechnology has revolutionized sensing phenomena by increasing biodiagnostic capacity in terms of specificity, size, and cost, resulting in exceptional sensitivity and flexibility. The steep increase of non-communicable diseases across the world has emerged as a matter of concern. In parallel, the abrupt outbreak of communicable diseases poses a serious threat to mankind. For decreasing the morbidity and mortality associated with various communicable and non-communicable diseases, early detection and subsequent treatment are indispensable. Detection of different biological markers generates quantifiable signals that can be electrochemical, mass-based, optical, thermal, or piezoelectric. Speculating on the incumbent applicability and versatility of nano-biosensors in large disciplines, this review highlights different types of biosensors along with their components and detection mechanisms. Moreover, it deals with the current advancements made in biosensors and the applications of nano-biosensors in detection of various non-communicable and communicable diseases, as well as future prospects of nano-biosensors for diagnostics.
37 citations
TL;DR: In this paper , a combined screening and selection approach was developed to refine the affinities and specificities of generalist transcription factors; using RamR as a starting point, they evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC50) < 30 μM) biosensors for the alkaloids tetrahydropapaverine, papaverine and noscapine.
Abstract: A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors; using RamR as a starting point, we evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC50) < 30 μM) biosensors for the alkaloids tetrahydropapaverine, papaverine, glaucine, rotundine and noscapine. High-resolution structures reveal multiple evolutionary avenues for the malleable effector-binding site and the creation of new pockets for different chemical moieties. These sensors further enabled the evolution of a streamlined pathway for tetrahydropapaverine, a precursor to four modern pharmaceuticals, collapsing multiple methylation steps into a single evolved enzyme. Our methods for evolving biosensors enable the rapid engineering of pathways for therapeutic alkaloids. A combined screening and selection approach enables the evolution of the generalist transcription factor RamR into specific and sensitive biosensors for various alkaloids and in turn a streamlined pathway for tetrahydropapaverine biosynthesis.
23 citations
TL;DR: In this article , the design and optimization principles for a diverse array of whole-cell biosensors based on transcription factors (TF) including activators or repressors derived from heavy metal resistance systems, alkanes, and aromatics metabolic pathways of bacteria.
15 citations
TL;DR: A review of the current trends and advances in tuning gene expression and regulation and considering their engineering at each of the three stages of gene regulation: genomic, mRNA, and protein can be found in this paper.
15 citations
TL;DR: In this paper, the authors describe the Design-Build-Test-Learn (DBTL) cycle for metabolic engineering experiments in streptomycetes and how it can be used for the discovery and production of novel specialized metabolites.
Abstract: Streptomycetes are producers of a wide range of specialized metabolites of great medicinal and industrial importance, such as antibiotics, antifungals, or pesticides. Having been the drivers of the golden age of antibiotics in the 1950s and 1960s, technological advancements over the last two decades have revealed that very little of their biosynthetic potential has been exploited so far. Given the great need for new antibiotics due to the emerging antimicrobial resistance crisis, as well as the urgent need for sustainable biobased production of complex molecules, there is a great renewed interest in exploring and engineering the biosynthetic potential of streptomycetes. Here, we describe the Design-Build-Test-Learn (DBTL) cycle for metabolic engineering experiments in streptomycetes and how it can be used for the discovery and production of novel specialized metabolites.
13 citations
References
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TL;DR: In vivo generation of mouse models carrying clinically relevant mutations using C→T and A→G editors is demonstrated, making it feasible to model and potentially cure relevant genetic diseases.
Abstract: A recently developed adenine base editor (ABE) efficiently converts A to G and is potentially useful for clinical applications. However, its precision and efficiency in vivo remains to be addressed. Here we achieve A-to-G conversion in vivo at frequencies up to 100% by microinjection of ABE mRNA together with sgRNAs. We then generate mouse models harboring clinically relevant mutations at Ar and Hoxd13, which recapitulates respective clinical defects. Furthermore, we achieve both C-to-T and A-to-G base editing by using a combination of ABE and SaBE3, thus creating mouse model harboring multiple mutations. We also demonstrate the specificity of ABE by deep sequencing and whole-genome sequencing (WGS). Taken together, ABE is highly efficient and precise in vivo, making it feasible to model and potentially cure relevant genetic diseases. CRISPR-based base editors allow for single nucleotide genome editing in a range of organisms. Here the authors demonstrate the in vivo generation of mouse models carrying clinically relevant mutations using C→T and A→G editors.
2,114 citations
TL;DR: De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding, to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.
Abstract: There are 20(200) possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.
1,008 citations
TL;DR: A structure-based computational method was used to construct soluble receptors that bind trinitrotoluene, l-lactate or serotonin with high selectivity and affinity, and these engineered receptors can function as biosensors for their new ligands.
Abstract: The formation of complexes between proteins and ligands is fundamental to biological processes at the molecular level. Manipulation of molecular recognition between ligands and proteins is therefore important for basic biological studies1 and has many biotechnological applications, including the construction of enzymes2,3,4, biosensors5,6, genetic circuits7, signal transduction pathways8 and chiral separations9. The systematic manipulation of binding sites remains a major challenge. Computational design offers enormous generality for engineering protein structure and function10. Here we present a structure-based computational method that can drastically redesign protein ligand-binding specificities. This method was used to construct soluble receptors that bind trinitrotoluene, l-lactate or serotonin with high selectivity and affinity. These engineered receptors can function as biosensors for their new ligands; we also incorporated them into synthetic bacterial signal transduction pathways, regulating gene expression in response to extracellular trinitrotoluene or l-lactate. The use of various ligands and proteins shows that a high degree of control over biomolecular recognition has been established computationally. The biological and biosensing activities of the designed receptors illustrate potential applications of computational design.
709 citations
TL;DR: A method for tuning the expression of multiple genes within operons by generating libraries of tunable intergenic regions (TIGRs), recombining various post-transcriptional control elements and screening for the desired relative expression levels is described.
Abstract: Many applications of synthetic biology require the balanced expression of multiple genes. Although operons facilitate coordinated expression of multiple genes in prokaryotes and eukaryotes, coordinating the many post-transcriptional processes that determine the relative levels of gene expression in operons by a priori design remains a challenge. We describe a method for tuning the expression of multiple genes within operons by generating libraries of tunable intergenic regions (TIGRs), recombining various post-transcriptional control elements and screening for the desired relative expression levels. TIGRs can vary the relative expression of two reporter genes over a 100-fold range and balance expression of three genes in an operon that encodes a heterologous mevalonate biosynthetic pathway, resulting in a sevenfold increase in mevalonate production. This technology should be useful for optimizing the expression of multiple genes in synthetic operons, both in prokaryotes and eukaryotes.
537 citations
TL;DR: A modular engineering approach was systematically removed metabolic pathway bottlenecks and led to significant titre improvements in a multi-gene fatty acid metabolic pathway to demonstrate a generalized approach to engineering cell factories for valuable metabolites production.
Abstract: Microbial fatty acid-derived fuels have emerged as promising alternatives to petroleum-based transportation fuels. Here we report a modular engineering approach that systematically removed metabolic pathway bottlenecks and led to significant titre improvements in a multi-gene fatty acid metabolic pathway. On the basis of central pathway architecture, E. coli fatty acid biosynthesis was re-cast into three modules: the upstream acetyl coenzyme A formation module; the intermediary acetyl-CoA activation module; and the downstream fatty acid synthase module. Combinatorial optimization of transcriptional levels of these three modules led to the identification of conditions that balance the supply of acetyl-CoA and consumption of malonyl-CoA/ACP. Refining protein translation efficiency by customizing ribosome binding sites for both the upstream acetyl coenzyme A formation and fatty acid synthase modules enabled further production improvement. Fed-batch cultivation of the engineered strain resulted in a final fatty acid production of 8.6 g l(-1). The modular engineering strategies demonstrate a generalized approach to engineering cell factories for valuable metabolites production.
423 citations