Novel screening methods--biosensors

Redox biosensors in a context of multiparameter imaging

A wide variety of genetically encoded fluorescent biosensors are available to date. Some of them have already contributed significantly to our understanding of biological processes occurring at cellular and organismal levels. Using such an approach, outstanding success has been achieved in the field of redox biology. The probes allowed researchers to observe, for the first time, the dynamics of important redox parameters in vivo during embryogenesis, aging, the inflammatory response, the pathogenesis of various diseases, and many other processes. Given the differences in the readout and spectra of the probes, they can be used in multiparameter imaging in which several processes are monitored simultaneously in the cell. Intracellular processes form an extensive network of interactions. For example, redox changes are often accompanied by changes in many other biochemical reactions related to cellular metabolism and signaling. Therefore, multiparameter imaging can provide important information concerning the temporal and spatial relationship of various signaling and metabolic processes. In this review, we will describe the main types of genetically encoded biosensors, the most frequently used readout, and their use in multiplexed imaging mode.

Real Time Monitoring of NADPH Concentrations in Corynebacterium glutamicum and Escherichia coli via the Genetically Encoded Sensor mBFP

Analyses of intracellular NADPH concentrations are prerequisites for the design of microbial production strains and process optimization. mBFP was described as metagenomics derived, blue fluorescent protein showing NADPH-dependent fluorescence. Characterization of mBFP showed a high specificity for binding of NADPH (K_D 0.64 mM) and no binding of NADH, the protein exclusively amplified fluorescence of NADPH. mBFP catalyzed the NADPH-dependent reduction of benzaldehyde and further aldehydes, which fits to its classification as short chain dehydrogenase. For in vivo NADPH analyses a codon-optimized gene for mBFP was introduced into Corynebacterium glutamicum WT and the phosphoglucoisomerase-deficient strain C. glutamicum Δpgi, which accumulates high levels of NADPH. For determination of intracellular NADPH concentrations by mBFP a calibration method with permeabilized cells was developed. By this means an increase of intracellular NADPH concentrations within seconds after the addition of glucose to nutrient-starved cells of both C. glutamicum WT and C. glutamicum Δpgi was observed; as expected the internal NADPH concentration was significantly higher for C. glutamicum Δpgi (0.31 mM) when compared to C. glutamicum WT (0.19 mM). Addition of paraquat to E. coli cells carrying mBFP led as expected to an immediate decrease of intracellular NADPH concentrations, showing the versatile use of mBFP as intracellular sensor.

Discovering novel hydrolases from hot environments

Novel hydrolases from hot and other extreme environments showing appropriate performance and/or novel functionalities and new approaches for their systematic screening are of great interest for developing new processes, for improving safety, health and environment issues. Existing processes could benefit as well from their properties. The workflow, based on the HotZyme project, describes a multitude of technologies and their integration from discovery to application, providing new tools for discovering, identifying and characterizing more novel thermostable hydrolases with desired functions from hot terrestrial and marine environments. To this end, hot springs worldwide were mined, resulting in hundreds of environmental samples and thousands of enrichment cultures growing on polymeric substrates of industrial interest. Using high-throughput sequencing and bioinformatics, 15 hot spring metagenomes, as well as several sequenced isolate genomes and transcriptomes were obtained. To facilitate the discovery of novel hydrolases, the annotation platform Anastasia and a whole-cell bioreporter-based functional screening method were developed. Sequence-based screening and functional screening together resulted in about 100 potentially new hydrolases of which more than a dozen have been characterized comprehensively from a biochemical and structural perspective. The characterized hydrolases include thermostable carboxylesterases, enol lactonases, quorum sensing lactonases, gluconolactonases, epoxide hydrolases, and cellulases. Apart from these novel thermostable hydrolases, the project generated an enormous amount of samples and data, thereby allowing the future discovery of even more novel enzymes.

Engineered Microorganisms for the Production of Food Additives Approved by the European Union-A Systematic Analysis

In the 1950s, the idea of a single harmonized list of food additives for the European Union arose. Already in 1962, the E-classification system, a robust food safety system intended to protect consumers from possible food-related risks, was introduced. Initially, it was restricted to colorants, but at later stages also preservatives, antioxidants, emulsifiers, stabilizers, thickeners, gelling agents, sweeteners, and flavorings were included. Currently, the list of substances authorized by the European Food Safety Authority (EFSA) (referred to as "E numbers") comprises 316 natural or artificial substances including small organic molecules, metals, salts, but also more complex compounds such as plant extracts and polymers. Low overall concentrations of such compounds in natural producers due to inherent regulation mechanisms or production processes based on non-regenerative carbon sources led to an increasing interest in establishing more reliable and sustainable production platforms. In this context, microorganisms have received significant attention as alternative sources providing access to these compounds. Scientific advancements in the fields of molecular biology and genetic engineering opened the door toward using engineered microorganisms for overproduction of metabolites of their carbon metabolism such as carboxylic acids and amino acids. In addition, entire pathways, e.g., of plant origin, were functionally introduced into microorganisms, which holds the promise to get access to an even broader range of accessible products. The aim of this review article is to give a systematic overview on current efforts during construction and application of microbial cell factories for the production of food additives listed in the EU "E numbers" catalog. The review is focused on metabolic engineering strategies of industrially relevant production hosts also discussing current bottlenecks in the underlying metabolic pathways and how they can be addressed in the future.

Tetramethylpyrazine-Inducible Promoter Region from Rhodococcus jostii TMP1

An inducible promoter region, P_TTMP (tetramethylpyrazine [TTMP]), has been identified upstream of the tpdABC operon, which contains the genes required for the initial degradation of 2,3,5,6-tetramethylpyrazine in Rhodococcus jostii TMP1 bacteria. In this work, the promoter region was fused with the gene for the enhanced green fluorescent protein (EGFP) to investigate the activity of P_TTMP by measuring the fluorescence of bacteria. The highest promoter activity was observed when bacteria were grown in a nutrient broth (NB) medium supplemented with 5 mM 2,3,5,6-tetramethylpyrazine for 48 h. Using a primer extension reaction, two transcriptional start sites for tpdA were identified, and the putative −35 and −10 promoter motifs were determined. The minimal promoter along with two 15 bp long direct repeats and two 7 bp inverted sequences were identified. Also, the influence of the promoter elements on the activity of P_TTMP were determined using site-directed mutagenesis. Furthermore, P_TTMP was shown to be induced by pyrazine derivatives containing methyl groups in the 2- and 5-positions of the heterocyclic ring, in the presence of the LuxR family transcriptional activator TpdR.

Building a minimal and generalizable model of transcription factor-based biosensors: Showcasing flavonoids

Progress in synthetic biology tools has transformed the way we engineer living cells. Applications of circuit design have reached a new level, offering solutions for metabolic engineering challenges that include developing screening approaches for libraries of pathway variants. The use of transcription‐factor‐based biosensors for screening has shown promising results, but the quantitative relationship between the sensors and the sensed molecules still needs more rational understanding. Herein, we have successfully developed a novel biosensor to detect pinocembrin based on a transcriptional regulator. The FdeR transcription factor (TF), known to respond to naringenin, was combined with a fluorescent reporter protein. By varying the copy number of its plasmid and the concentration of the biosensor TF through a combinatorial library, different responses have been recorded and modeled. The fitted model provides a tool to understand the impact of these parameters on the biosensor behavior in terms of dose–response and time curves and offers guidelines to build constructs oriented to increased sensitivity and or ability of linear detection at higher titers. Our model, the first to explicitly take into account the impact of plasmid copy number on biosensor sensitivity using Hill‐based formalism, is able to explain uncharacterized systems without extensive knowledge of the properties of the TF. Moreover, it can be used to model the response of the biosensor to different compounds (here naringenin and pinocembrin) with minimal parameter refitting.

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. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LacI-, TetR- and AraC-based inducible circuits.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

New Intracellular Shikimic Acid Biosensor for Monitoring Shikimate Synthesis in Corynebacterium glutamicum

The quantitative monitoring of intracellular metabolites with in vivo biosensors provides an efficient means of identifying high-yield strains and observing product accumulation in real time. In this study, a shikimic acid (SA) biosensor was constructed from a LysR-type transcriptional regulator (ShiR) of Corynebacterium glutamicum. The SA biosensor specifically responded to the increase of intracellular SA concentration over a linear range of 19.5 ± 3.6 to 120.9 ± 1.2 fmole at the single-cell level. This new SA biosensor was successfully used to (1) monitor the SA production of different C. glutamicum strains; (2) develop a novel result-oriented high-throughput ribosome binding site screening and sorting strategy that was used for engineering high-yield shikimate-producing strains; and (3) engineer a whole-cell biosensor through the coexpression of the SA sensor and a shikimate transporter shiA gene in C. glutamicum RES167. This work demonstrated that a new intracellular SA biosensor is a valuable tool facilitating the fast development of microbial SA producer.

Development of a novel cellulase biosensor that detects crystalline cellulose hydrolysis using a transcriptional regulator

Successful utilization of cellulose as renewable biomass depends on the development of economically feasible technologies, which can aid in enzymatic hydrolysis. In this study, we developed a whole-cell biosensor for detecting cellulolytic activity that relies on the recognition of cellobiose using the transcriptional factor CelR from Thermobifida fusca and transcriptional activation of its downstream gfp reporter gene. The fluorescence intensity of whole-cell biosensor, which was named as cellobiose-detectible genetic enzyme screening system (CBGESS), was directly proportional to the concentration of cellobiose. The strong fluorescence intensity of CBGESS demonstrated the ability to detect cellulolytic activity with two cellulosic substrates, carboxymethyl cellulose and p-nitrophenyl β-D-cellobioside in cellulase-expressing Escherichia coli. In addition, CBGESS easily sensed crystalline cellulolytic activity when commercial Celluclast 1.5L was dropped on an Avicel plate. Therefore, CBGESS is a powerful tool for detecting cellulolytic activity with high sensitivity in the presence of soluble or insoluble cellulosic substrates. CBGESS may be further applied to excavate novel cellulases or microbes from both genetic libraries and various environments.

Development of a Bacterial Biosensor for Rapid Screening of Yeast p-Coumaric Acid Production

Transcription factor-based biosensors are used to identify producer strains, a critical bottleneck in cell factory engineering. Here, we address two challenges with this methodology: transplantation of heterologous transcriptional regulators into new hosts to generate functional biosensors and biosensing of the extracellular product concentration that accurately reflects the effective cell factory production capacity. We describe the effects of different translation initiation rates on the dynamic range of a p-coumaric acid biosensor based on the Bacillus subtilis transcriptional repressor PadR by varying its ribosomal binding site. Furthermore, we demonstrate the functionality of this p-coumaric acid biosensor in Escherichia coli and Corynebacterium glutamicum. Finally, we encapsulate yeast p-coumaric acid-producing cells with E. coli-biosensing cells in picoliter droplets and, in a microfluidic device, rapidly sort droplets containing yeast cells producing high amounts of extracellular p-coumaric acid using the fluorescent E. coli biosensor signal. As additional biosensors become available, such approaches will find broad applications for screening of an extracellular product.

Systems metabolic engineering strategies for the production of amino acids

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

Development of a single-cell GlxR-based cAMP biosensor for Corynebacterium glutamicum

Cyclic adenosine monophosphate (cAMP) plays a regulatory role as second messenger in many species. In the industrial model organism Corynebacterium glutamicum, cAMP acts as effector of the global transcriptional regulator GlxR, a homolog of enterobacterial Crp. The cAMP-GlxR complex activates or represses the expression of about 200 target genes. CyaB, a membrane-bound class III adenylate cyclase, synthesizes cAMP from ATP, but another yet unknown cAMP-forming enzyme is likely present in C. glutamicum. Recently, we identified the cAMP phosphodiesterase CpdA, which catalyzes the conversion of cAMP to AMP. As a tool to search for additional cAMP-forming and degrading enzymes, we constructed a plasmid-based cAMP biosensor by fusing the promoter of cg3195, a gene strongly repressed by GlxR, to the eyfp reporter gene. In control experiments, the biosensor showed the predicted responses to increased levels of cAMP or GlxR. The biosensor was able to distinguish between C. glutamicum wild type and mutants with defects in cAMP biosynthesis or degradation. Most importantly, the sensor allowed successful sorting of mixtures of wild type and mutant strains by fluorescence activated cell sorting (FACS), thus meeting the requirements for high-throughput screening of libraries for single mutant cells with an altered cAMP level.

Twin-layer biosensor for real-time monitoring of alkane metabolism

Intracellular metabolic sensors can be used for efficient screening and optimization of microbial cell factories. In particular, the sensors are useful in acquiring information about pathway dynamics and bottlenecks in a straightforward manner. Here, we developed a twin-layer biosensor that functions simultaneously at two levels: through transcription factor mediated sensing and enzyme-metabolite interaction, providing insights into the dynamics of alkane metabolism. In addition, the sensor can be used for monitoring either alkane degradation or biosynthesis, depending on the used cellular context. Alkanes are monitored using a fluorescent reporter green fluorescent protein placed under a native alkane-inducible promoter, whereas a bacterial luciferase producing bioluminescence signal enzymatically detects a specific metabolic intermediate in the alkane production/degradation pathway. First, we employed the sensor to investigate the native alkane degradation route in Acinetobacter baylyi ADP1. The highest fluorescence and luminescence signals were obtained for dodecane. Second, we constructed a non-native alkane synthesis pathway in A. baylyi ADP1, of which the functionality was confirmed with the sensor. The twin-layer approach provides convenient means to study and optimize the kinetics and performance of the heterologous pathway and will facilitate the development of an efficient cell factory.

Taking control over microbial populations: Current approaches for exploiting biological noise in bioprocesses

Phenotypic plasticity of microbial cells has attracted much attention and several research efforts have been dedicated to the description of methods aiming at characterizing phenotypic heterogeneity and its impact on microbial populations. However, different approaches have also been suggested in order to take benefit from noise in a bioprocess perspective, e.g. by increasing the robustness or productivity of a microbial population. This review is dedicated to outline these controlling methods. A common issue, that has still to be addressed, is the experimental identification and the mathematical expression of noise. Indeed, the effective interfacing of microbial physiology with external parameters that can be used for controlling physiology depends on the acquisition of reliable signals. Latest technologies, like single cell microfluidics and advanced flow cytometric approaches, enable linking physiology, noise, heterogeneity in productive microbes with environmental cues and hence allow correctly mapping and predicting biological behavior via mathematical representations. However, like in the field of electronics, signals are perpetually subjected to noise. If appropriately interpreted, this noise can give an additional insight into the behavior of the individual cells within a microbial population of interest. This review focuses on recent progress made at describing, treating and exploiting biological noise in the context of microbial populations used in various bioprocess applications.

Characterisation of a 3-hydroxypropionic acid-inducible system from Pseudomonas putida for orthogonal gene expression control in Escherichia coli and Cupriavidus necator

3-hydroxypropionic acid (3-HP) is an important platform chemical used as a precursor for production of added-value compounds such as acrylic acid. Metabolically engineered yeast, Escherichia coli, cyanobacteria and other microorganisms have been developed for the biosynthesis of 3-HP. Attempts to overproduce this compound in recombinant Pseudomonas denitrificans revealed that 3-HP is consumed by this microorganism using the catabolic enzymes encoded by genes hpdH, hbdH and mmsA. 3-HP-inducible systems controlling the expression of these genes have been predicted in proteobacteria and actinobacteria. In this study, we identify and characterise 3-HP-inducible promoters and their corresponding LysR-type transcriptional regulators from Pseudomonas putida KT2440. A newly-developed modular reporter system proved possible to demonstrate that PpMmsR/P_mmsA and PpHpdR/P_hpdH are orthogonal and highly inducible by 3-HP in E. coli (12.3- and 23.3-fold, respectively) and Cupriavidus necator (51.5- and 516.6-fold, respectively). Bioinformatics and mutagenesis analyses revealed a conserved 40-nucleotide sequence in the hpdH promoter, which plays a key role in HpdR-mediated transcription activation. We investigate the kinetics and dynamics of the PpHpdR/P_hpdH switchable system in response to 3-HP and show that it is also induced by both enantiomers of 3-hydroxybutyrate. These findings pave the way for use of the 3-HP-inducible system in synthetic biology and biotechnology applications.

Novel Technologies for Optimal Strain Breeding

The implementation of a knowledge-based bioeconomy requires the rapid development of highly efficient microbial production strains that are able to convert renewable carbon sources to value-added products, such as bulk and fine chemicals, pharmaceuticals, or proteins at industrial scale. Starting from classical strain breeding by random mutagenesis and screening in the 1950s via rational design by metabolic engineering initiated in the 1970s, a range of powerful new technologies have been developed in the past two decades that can revolutionize future strain engineering. In particular, next-generation sequencing technologies combined with new methods of genome engineering and high-throughput screening based on genetically encoded biosensors have allowed for new concepts. In this chapter, selected new technologies relevant for breeding microbial production strains with a special emphasis on amino acid producers will be summarized.

A Cell-Cell Communication-Based Screening System for Novel Microbes with Target Enzyme Activities

The development of synthetic biological devices has increased rapidly in recent years and the practical benefits of such biological devices are becoming increasingly clear. Here, we further improved the design of a previously reported high-throughput genetic enzyme screening system by investigating device-compatible biological components and phenol-mediated cell-cell communication, both of which increased the efficiency and practicality of the screening device without requiring the use of flow cytometry analysis. A sensor cell was designed to detect novel microbes with target enzyme activities on solid media by forming clear, circular colonies with fluorescence around the unknown microbes producing target enzymes. This mechanism of detection was enabled by the combination of pre-effector phenolic substrate treatment in the presence of target enzyme-producing microbes and control of the growth and fluorescence of remote sensor cells via phenol-mediated cell-cell communication. The sensor cells were applied to screen soil bacteria with phosphatase activity using phenyl phosphate as phenolic substrates. The sensor cells facilitated successful visualization of phosphatase activity in unknown microbes, which were identified by 16S rRNA analysis. Enzyme activity assays confirmed that the proposed screening technique was able to find 23 positive clones out of 33 selected colonies. Since many natural enzymatic reactions produce phenolic compounds from phenol-derived substrates, we anticipate that the proposed technique may have broad applications in the assessment and screening of novel microbes with target enzymes of interest. This method also can provide insights into the identification of novel enzymes for which screening assays are not yet available.

A Critical and Comparative Review of Fluorescent Tools for Live-Cell Imaging

Fluorescent tools have revolutionized our ability to probe biological dynamics, particularly at the cellular level. Fluorescent sensors have been developed on several platforms, utilizing either small-molecule dyes or fluorescent proteins, to monitor proteins, RNA, DNA, small molecules, and even cellular properties, such as pH and membrane potential. We briefly summarize the impressive history of tool development for these various applications and then discuss the most recent noteworthy developments in more detail. Particular emphasis is placed on tools suitable for single-cell analysis and especially live-cell imaging applications. Finally, we discuss prominent areas of need in future fluorescent tool development-specifically, advancing our capability to analyze and integrate the plethora of high-content data generated by fluorescence imaging.

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. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription factor

A whole-cell biosensor utilizing a transcription factor (TF) is an effective tool for sensitive and selective detection of specialty chemicals or anthropogenic molecules, but requires access to an expanded repertoire of TFs. Using homology modeling and ligand docking for binding pocket identification, assisted by conservative mutations in the pocket, we engineered a novel specificity in an Acinetobacter TF, PobR, to ‘sense’ a chemical p-nitrophenol (pNP) and measured the response via a fluorescent protein reporter expressed from a PobR promoter. Out of 10⁷ variants of PobR, four were active when dosed with pNP, with two mutants showing a specificity switch from the native effector 4-hydroxybenzoate (4HB). One of the mutants, pNPmut1 was then used to create a smart microbial cell responding to pNP production from hydrolysis of an insecticide, paraoxon, in a coupled assay involving phosphotriesterase (PTE) enzyme expressed from a separate promoter. We show the fluorescence of the cells correlated with the catalytic efficiency of the PTE variant expressed in each cell. High selectivity between similar molecules (4HB versus pNP), high sensitivity for pNP detection (∼2 μM) and agreement of apo- and holo-structures of PobR scaffold with predetermined computational models are other significant results presented in this work.

Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a large-scale metagenomic library(1). We previously proposed a genetic enzyme screening system (GESS) that uses dimethylphenol regulator activated by phenol or p-nitrophenol. Since a vast amount of natural enzymatic reactions produce these phenolic compounds from phenol deriving substrates, this single genetic screening system can be theoretically applied to screen over 200 different enzymes in the BRENDA database. Despite the general applicability of GESS, applying the screening process requires a specific procedure to reach the maximum flow cytometry signals. Here, we detail the developed screening process, which includes metagenome preprocessing with GESS and the operation of a flow cytometry sorter. Three different phenolic substrates (p-nitrophenyl acetate, p-nitrophenyl-β-D-cellobioside, and phenyl phosphate) with GESS were used to screen and to identify three different enzymes (lipase, cellulase, and alkaline phosphatase), respectively. The selected metagenomic enzyme activities were confirmed only with the flow cytometry but DNA sequencing and diverse in vitro analysis can be used for further gene identification.

Molecular Buffers Permit Sensitivity Tuning and Inversion of Riboswitch Signals

Predictable integration of foreign biological signals and parts remains a key challenge in the systematic engineering of synthetic cellular actuations, and general methods to improve signal transduction and sensitivity are needed. To address this problem we modeled and built a molecular signal buffer network in Saccharomyces cerevisiae inspired by chemical pH buffer systems. The molecular buffer system context-insulates a riboswitch enabling synthetic control of colony formation and modular signal manipulations. The riboswitch signal is relayed to a transcriptional activation domain of a split transcription factor, while interacting DNA-binding domains mediate the transduction of signal and form an interacting molecular buffer. The molecular buffer system enables modular signal inversion through integration with repressor modules. Further, tuning of input sensitivity was achieved through perturbation of the buffer pair ratio guided by a mathematical model. Such buffered signal tuning networks will be useful for domestication of RNA-based sensors enabling tunable outputs and library-wide selections for drug discovery and metabolic engineering.

On-Demand Targeting: Investigating Biology with Proximity-Directed Chemistry

Proximity enhancement is a central chemical tenet underpinning an exciting suite of small-molecule toolsets that have allowed us to unravel many biological complexities. The leitmotif of this opus is "tethering"-a strategy in which a multifunctional small molecule serves as a template to bring proteins/biomolecules together. Scaffolding approaches have been powerfully applied to control diverse biological outcomes such as protein-protein association, protein stability, activity, and improve imaging capabilities. A new twist on this strategy has recently appeared, in which the small-molecule probe is engineered to unleash controlled amounts of reactive chemical signals within the microenvironment of a target protein. Modification of a specific target elicits a precisely timed and spatially controlled gain-of-function (or dominant loss-of-function) signaling response. Presented herein is a unique personal outlook conceptualizing the powerful proximity-enhanced chemical biology toolsets into two paradigms: "multifunctional scaffolding" versus "on-demand targeting". By addressing the latest advances and challenges in the established yet constantly evolving multifunctional scaffolding strategies as well as in the emerging on-demand precision targeting (and related) systems, this Perspective is aimed at choosing when it is best to employ each of the two strategies, with an emphasis toward further promoting novel applications and discoveries stemming from these innovative chemical biology platforms.

Genetically encoded sensors enable real-time observation of metabolite production

Engineering cells to produce valuable metabolic products is hindered by the slow and laborious methods available for evaluating product concentration. Consequently, many designs go unevaluated, and the dynamics of product formation over time go unobserved. In this work, we develop a framework for observing product formation in real time without the need for sample preparation or laborious analytical methods. We use genetically encoded biosensors derived from small-molecule responsive transcription factors to provide a fluorescent readout that is proportional to the intracellular concentration of a target metabolite. Combining an appropriate biosensor with cells designed to produce a metabolic product allows us to track product formation by observing fluorescence. With individual cells exhibiting fluorescent intensities proportional to the amount of metabolite they produce, high-throughput methods can be used to rank the quality of genetic variants or production conditions. We observe production of several renewable plastic precursors with fluorescent readouts and demonstrate that higher fluorescence is indeed an indicator of higher product titer. Using fluorescence as a guide, we identify process parameters that produce 3-hydroxypropionate at 4.2 g/L, 23-fold higher than previously reported. We also report, to our knowledge, the first engineered route from glucose to acrylate, a plastic precursor with global sales of $14 billion. Finally, we monitor the production of glucarate, a replacement for environmentally damaging detergents, and muconate, a renewable precursor to polyethylene terephthalate and nylon with combined markets of $51 billion, in real time, demonstrating that our method is applicable to a wide range of molecules.

Analysis of amino acid substitutions in AraC variants that respond to triacetic acid lactone

The Escherichia coli regulatory protein AraC regulates expression of ara genes in response to l-arabinose. In efforts to develop genetically encoded molecular reporters, we previously engineered an AraC variant that responds to the compound triacetic acid lactone (TAL). This variant (named "AraC-TAL1") was isolated by screening a library of AraC variants, in which five amino acid positions in the ligand-binding pocket were simultaneously randomized. Screening was carried out through multiple rounds of alternating positive and negative fluorescence-activated cell sorting. Here we show that changing the screening protocol results in the identification of different TAL-responsive variants (nine new variants). Individual substituted residues within these variants were found to primarily act cooperatively toward the gene expression response. Finally, X-ray diffraction was used to solve the crystal structure of the apo AraC-TAL1 ligand-binding domain. The resolved crystal structure confirms that this variant takes on a structure nearly identical to the apo wild-type AraC ligand-binding domain (root-mean-square deviation 0.93 Å), suggesting that AraC-TAL1 behaves similar to wild-type with regard to ligand recognition and gene regulation. Our results provide amino acid sequence-function data sets for training and validating AraC modeling studies, and contribute to our understanding of how to design new biosensors based on AraC.

Synthetic biology for pharmaceutical drug discovery

Synthetic biology (SB) is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell-cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity.

Transcription factor-based biosensors in biotechnology: current state and future prospects

Living organisms have evolved a plethora of sensing systems for the intra- and extracellular detection of small molecules, ions or physical parameters. Several recent studies have demonstrated that these principles can be exploited to devise synthetic regulatory circuits for metabolic engineering strategies. In this context, transcription factors (TFs) controlling microbial physiology at the level of transcription play a major role in biosensor design, since they can be implemented in synthetic circuits controlling gene expression in dependency of, for example, small molecule production. Here, we review recent progress on the utilization of TF-based biosensors in microbial biotechnology highlighting different areas of application. Recent advances in metabolic engineering reveal TF-based sensors to be versatile tools for strain and enzyme development using high-throughput (HT) screening strategies and adaptive laboratory evolution, the optimization of heterologous pathways via the implementation of dynamic control circuits and for the monitoring of single-cell productivity in live cell imaging studies. These examples underline the immense potential of TF-based biosensor circuits but also identify limitations and room for further optimization.

Putting RNA to work: Translating RNA fundamentals into biotechnological engineering practice

Synthetic biology, in close concert with systems biology, is revolutionizing the field of metabolic engineering by providing novel tools and technologies to rationally, in a standardized way, reroute metabolism with a view to optimally converting renewable resources into a broad range of bio-products, bio-materials and bio-energy. Increasingly, these novel synthetic biology tools are exploiting the extensive programmable nature of RNA, vis-à-vis DNA- and protein-based devices, to rationally design standardized, composable, and orthogonal parts, which can be scaled and tuned promptly and at will. This review gives an extensive overview of the recently developed parts and tools for i) modulating gene expression ii) building genetic circuits iii) detecting molecules, iv) reporting cellular processes and v) building RNA nanostructures. These parts and tools are becoming necessary armamentarium for contemporary metabolic engineering. Furthermore, the design criteria, technological challenges, and recent metabolic engineering success stories of the use of RNA devices are highlighted. Finally, the future trends in transforming metabolism through RNA engineering are critically evaluated and summarized.

Fluorescent Reporter Libraries as Useful Tools for Optimizing Microbial Cell Factories: A Review of the Current Methods and Applications

The use of genetically encoded fluorescent reporters allows speeding up the initial optimization steps of microbial bioprocesses. These reporters can be used for determining the expression level of a particular promoter, not only the synthesis of a specific protein but also the content of intracellular metabolites. The level of protein/metabolite is thus proportional to a fluorescence signal. By this way, mean expression profiles of protein/metabolites can be determined non-invasively at a high-throughput rate, allowing the rapid identification of the best producers. Actually, different kinds of reporter systems are available, as well as specific cultivation devices allowing the on-line recording of the fluorescent signal. Cell-to-cell variability is another important phenomenon that can be integrated into the screening procedures for the selection of more efficient microbial cell factories.

Analytics for Metabolic Engineering

Realizing the promise of metabolic engineering has been slowed by challenges related to moving beyond proof-of-concept examples to robust and economically viable systems. Key to advancing metabolic engineering beyond trial-and-error research is access to parts with well-defined performance metrics that can be readily applied in vastly different contexts with predictable effects. As the field now stands, research depends greatly on analytical tools that assay target molecules, transcripts, proteins, and metabolites across different hosts and pathways. Screening technologies yield specific information for many thousands of strain variants, while deep omics analysis provides a systems-level view of the cell factory. Efforts focused on a combination of these analyses yield quantitative information of dynamic processes between parts and the host chassis that drive the next engineering steps. Overall, the data generated from these types of assays aid better decision-making at the design and strain construction stages to speed progress in metabolic engineering research.

Developing a high-throughput screening method for threonine overproduction based on an artificial promoter

BACKGROUND

L-Threonine is an important amino acid for animal feed. Though the industrial fermentation technology of threonine achieved a very high level, there is still significant room to further improve the industrial strains. The biosensor-based high-throughput screening (HTS) technology has demonstrated its powerful applications. Unfortunately, for most of valuable fine chemicals such as threonine, a HTS system has not been established mainly due to the absence of a suitable biosensor. In this study, we developed a HTS method to gain high-yielding threonine-producing strains.

RESULTS

Novel threonine sensing promoters including cysJp and cysHp were discovered by proteomic analyses of Escherichia coli in response to extracellular threonine challenges. The HTS method was constructed using a device composed of the fused cysJp and cysHp as a promoter and a linked enhanced green fluorescent protein gene as a reporter. More than 400 strains were selected with fluorescence activated cell sorting technology from a library of 20 million mutants and tested within 1 week. Thirty-four mutants have higher productivities than the starting industrial producer. One mutant produced 17.95 % more threonine in a 5-L jar fermenter.

CONCLUSIONS

This method should play a functional role for continuous improvement of threonine industry. Additionally, the threonine sensor construction using promoters obtained by proteomics analyses is so convenient that it would be easily extended to develop HTS models for other biochemicals.

Design of an ectoine-responsive AraC mutant and its application in metabolic engineering of ectoine biosynthesis

Advanced high-throughput screening methods for small molecules may have important applications in the metabolic engineering of the biosynthetic pathways of these molecules. Ectoine is an excellent osmoprotectant that has been widely used in cosmetics. In this study, the Escherichia coli regulatory protein AraC was engineered to recognize ectoine as its non-natural effector and to activate transcription upon ectoine binding. As an endogenous reporter of ectoine, the mutated AraC protein was successfully incorporated into high-throughput screening of ectoine hyper-producing strains. The ectoine biosynthetic cluster from Halomonas elongata was cloned into E. coli. By engineering the rate-limiting enzyme L-2,4-diaminobutyric acid (DABA) aminotransferase (EctB), ectoine production and the specific activity of the EctB mutant were increased. Thus, these results demonstrated the effectiveness of engineering regulatory proteins into sensitive and rapid screening tools for small molecules and highlighted the importance and efficacy of directed evolution strategies applied to the engineering of genetic components for yield improvement in the biosynthesis of small molecules.