Biological Switches: Past and Future Milestones of Transcription Factor-Based Biosensors.

Since the description of the operon in 1961 by Jacob and Monod, transcriptional regulation in prokaryotes has been studied extensively and has led to the development of transcription factor-based biosensors. Due to the broad variety of detectable small molecules and their various applications across biotechnology, biosensor research and development have increased exponentially over the past decades. Throughout this period, key milestones in fundamental knowledge, synthetic biology, analytical tools, and computational learning have led to an immense expansion of the biosensor repertoire and its application portfolio.

Fundamentals and Exceptions of the LysR-type Transcriptional Regulators.

LysR-type transcriptional regulators (LTTRs) are emerging as a promising group of macromolecules for the field of biosensors. As the largest family of bacterial transcription factors, the LTTRs represent a vast and mostly untapped repertoire of sensor proteins. To fully harness these regulators for transcription factor-based biosensor development, it is crucial to understand their underlying mechanisms and functionalities.

Delaying production with prokaryotic inducible expression systems.

Background: Engineering bacteria with the purpose of optimizing the production of interesting molecules often leads to a decrease in growth due to metabolic burden or toxicity. By delaying the production in time, these negative effects on the growth can be avoided in a process called a two-stage fermentation.

Main Text: During this two-stage fermentation process, the production stage is only activated once sufficient cell mass is obtained.

MoBioS: Modular Platform Technology for High-Throughput Construction and Characterization of Tunable Transcriptional Biological Sensors.

All living organisms have evolved and fine-tuned specialized mechanisms to precisely monitor a vast array of different types of molecules. These natural mechanisms can be sourced by researchers to build Biological Sensors (BioS) by combining them with an easily measurable output, such as fluorescence. Because they are genetically encoded, BioS are cheap, fast, sustainable, portable, self-generating and highly sensitive and specific.

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli.

Background: Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli.

Results: A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs.

Biosensor-driven, model-based optimization of the orthogonally expressed naringenin biosynthesis pathway.

Background: The rapidly expanding synthetic biology toolbox allows engineers to develop smarter strategies to tackle the optimization of complex biosynthetic pathways. In such a strategy, multi-gene pathways are subdivided in several modules which are each dynamically controlled to fine-tune their expression in response to a changing cellular environment. To fine-tune separate modules without interference between modules or from the host regulatory machinery, a sigma factor (σ) toolbox was developed in previous work for tunable orthogonal gene expression.

Chimeric LysR-Type Transcriptional Biosensors for Customizing Ligand Specificity Profiles toward Flavonoids.

Transcriptional biosensors enable key applications in both metabolic engineering and synthetic biology. Due to nature's immense variety of metabolites, these applications require biosensors with a ligand specificity profile customized to the researcher's needs. In this work, chimeric biosensors were created by introducing parts of a donor regulatory circuit from Sinorhizobium meliloti, delivering the desired luteolin-specific response, into a nonspecific biosensor chassis from Herbaspirillum seropedicae.

Modularization and Response Curve Engineering of a Naringenin-Responsive Transcriptional Biosensor.

To monitor the intra- and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism.

Development of N-acetylneuraminic acid responsive biosensors based on the transcriptional regulator NanR.

Transcriptional biosensors have various applications in metabolic engineering, including dynamic pathway control and high-throughput screening of combinatorial strain libraries. Previously, various biosensors have been created from naturally occurring transcription factors (TFs), largely relying on native sequences without the possibility to modularly optimize their response curve. The lack of design and engineering techniques thus greatly hinders the development of custom biosensors.

Standardization in synthetic biology: an engineering discipline coming of age.

Background: Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited.

Purpose: In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts.

Tailor-made transcriptional biosensors for optimizing microbial cell factories.

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness.

Development of an in vivo glucosylation platform by coupling production to growth: Production of phenolic glucosides by a glycosyltransferase of Vitis vinifera.

Glycosylation of small molecules can significantly alter their properties such as solubility, stability, and/or bioactivity, making glycosides attractive and highly demanded compounds. Consequently, many biotechnological glycosylation approaches have been developed, with enzymatic synthesis and whole-cell biocatalysis as the most prominent techniques. However, most processes still suffer from low yields, production rates and inefficient UDP-sugar formation.

Multivariate modular metabolic engineering for pathway and strain optimization.

Despite the potential in utilizing microbial fermentation for chemical production, the field of industrial biotechnology still lacks a standard, universally applicable principle for strain optimization. A key challenge has been in finding and applying effective ways to address metabolic flux imbalances. Strategies based on rational design require significant a priori knowledge and often fail to take a holistic view of cellular metabolism.