Metabolite-based biosensors for natural product discovery and overproduction

Rational construction of genome-minimized Streptomyces host for the expression of secondary metabolite gene clusters

Streptomyces offer a wealth of naturally occurring compounds with diverse structures, many of which possess significant pharmaceutical values. However, new product exploration and increased yield of specific compounds in Streptomyces have been technically challenging due to their slow growth rate, complex culture conditions and intricate genetic backgrounds. In this study, we screened dozens of Streptomyces strains inhabiting in a plant rhizosphere for fast-growing candidates, and further employed CRISPR/Cas-based engineering techniques for stepwise refinement of a particular strain, Streptomyces sp. A-14 that harbors a 7.47 Mb genome. After strategic removal of nonessential genomic regions and most gene clusters, we reduced its genome size to 6.13 Mb, while preserving its growth rate to the greatest extent. We further demonstrated that cleaner metabolic background of this engineered strain was well suited for the expression and characterization of heterologous gene clusters, including the biosynthetic pathways of actinorhodin and polycyclic tetramate macrolactams. Moreover, this streamlined genome is anticipated to facilitate directing the metabolic flux towards the production of desired compounds and increasing their yields.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Label-free biomolecular and cellular methods in small molecule epigallocatechin-gallate research

Small molecule natural compounds are gaining popularity in biomedicine due to their easy access to wide structural diversity and their proven health benefits in several case studies. Affinity measurements of small molecules below 100 Da molecular weight in a label-free and automatized manner using small amounts of samples have now become a possibility and reviewed in the present work. We also highlight novel label-free setups with excellent time resolution, which is important for kinetic measurements of biomolecules and living cells. We summarize how molecular-scale affinity data can be obtained from the in-depth analysis of cellular kinetic signals. Unlike traditional measurements, label-free biosensors have made such measurements possible, even without the isolation of specific cellular receptors of interest. Throughout this review, we consider epigallocatechin gallate (EGCG) as an exemplary compound. EGCG, a catechin found in green tea, is a well-established anti-inflammatory and anti-cancer agent. It has undergone extensive examination in numerous studies, which typically rely on fluorescent-based methods to explore its effects on both healthy and tumor cells. The summarized research topics range from molecular interactions with proteins and biological films to the kinetics of cellular adhesion and movement on novel biomimetic interfaces in the presence of EGCG. While the direct impact of small molecules on living cells and biomolecules is relatively well investigated in the literature using traditional biological measurements, this review also highlights the indirect influence of these molecules on the cells by modifying their nano-environment. Moreover, we underscore the significance of novel high-throughput label-free techniques in small molecular measurements, facilitating the investigation of both molecular-scale interactions and cellular processes in one single experiment. This advancement opens the door to exploring more complex multicomponent models that were previously beyond the reach of traditional assays.

Engineering of a Substrate Affinity Reduced S-Adenosyl-methionine Synthetase as a Novel Biosensor for Growth-Coupling Selection of L-Methionine Overproducers

Biosensors are powerful tools for monitoring specific metabolites or controlling metabolic flux towards the products in a single cell, which play important roles in microbial cell factory construction. Despite their potential role in metabolic flux monitoring, the development of biosensors for small molecules is still limited. Reported biosensors often exhibit bottlenecks of poor specificity and a narrow dynamic range. Moreover, fine-tuning the substrate binding affinity of a crucial enzyme can decrease its catalytic activity, which ultimately results in the repression of the corresponding essential metabolite biosynthesis and impairs cell growth. However, increasing intracellular substrate concentration can elevate the availability of the essential metabolite and may lead to restore cellular growth. Herein, a new strategy was proposed for constructing whole-cell biosensors based on enzyme encoded by essential gene that offer inherent specificity and universality. Specifically, S-adenosyl-methionine synthetase (MetK) in E. coli was chosen as the crucial enzyme, and a series of MetK variants were identified that were sensitive to L-methionine concentration. This occurrence enabled the engineered cell to sense L-methionine and exhibit L-methionine dose-dependent cell growth. To improve the biosensor's dynamic range, an S-adenosyl-methionine catabolic enzyme was overexpressed to reduce the intracellular availability of S-adenosyl-methionine. The resulting whole-cell biosensor effectively coupled the intracellular concentration of L-methionine with growth and was successfully applied to select strains with enhanced L-methionine biosynthesis from random mutagenesis libraries. Overall, our study presents a universal strategy for designing and constructing growth-coupled biosensors based on crucial enzyme, which can be applied to select strains overproducing high value-added metabolites in cellular metabolism.

Facile Synthesis of Iron and Nitrogen Co-Doped Carbon Dot Nanozyme as Highly Efficient Peroxidase Mimics for Visualized Detection of Metabolites

Visual detection based on nanozymes has great potential for the rapid detection of metabolites in clinical analysis or home-based health management. In this work, iron and nitrogen co-doped carbon dots (Fe,N-CDs) were conveniently synthesized as a nanozyme for the visual detection of glucose (Glu) or cholesterol (Chol). Using inexpensive and readily available precursors, Fe,N-CDs with peroxidase-like activity were conveniently prepared through a simple hydrothermal method. Co-doping of Fe and N atoms enhanced the catalytic activity of the nanozyme. The nanozyme had a low Michaelis constant (Km) of 0.23 mM when hydrogen peroxide (H2O2) was used as the substrate. Free radical trapping experiments revealed that the reactive oxygen species (ROS) generated in the nanozyme-catalyzed process were superoxide anion radicals (•O2-), which can oxidize colorless 3,3',5,5'-tetramethylbenzidine (TMB) to generate blue oxidation product (ox-TMB) with characteristics absorbance at 652 nm. Based on this mechanism, a colorimetric sensor was constructed to detect H2O2 ranging from 0.1 μM to 200 μM with a detection limit (DL) of 75 nM. In the presence of glucose oxidase (Gox) or Chol oxidase (Chox), Glu or Chol was oxidized, respectively, and generated H2O2. Based on this, indirect detection of Glu and Chol was realized with linear detection ranges of 5-160 μM and 2-200 μM and DLs of 2.8 μM and 0.8 μM, respectively. A paper-based visual detection platform was fabricated using Fe,N-CDs as nanozyme ink to prepare testing paper by inkjet printing. Using a smartphone to record the RGB values of the testing paper after the reaction, visual detection of Glu and Chol can be achieved with linear detection ranges of 5-160 μM (DL of 3.3 μM) and 2-200 μM (DL of 1.0 μM), respectively.

Aflatoxin detection technologies: recent advances and future prospects

Aflatoxins have posed serious threat to food safety and human health. Therefore, it is important to detect aflatoxins in samples rapidly and accurately. In this review, various technologies to detect aflatoxins in food are discussed, including conventional ones such as thin-layer chromatography (TLC), high performance liquid chromatography (HPLC), enzyme linked immunosorbent assay (ELISA), colloidal gold immunochromatographic assay (GICA), radioimmunoassay (RIA), fluorescence spectroscopy (FS), as well as emerging ones (e.g., biosensors, molecular imprinting technology, surface plasmon resonance). Critical challenges of these technologies include high cost, complex processing procedures and long processing time, low stability, low repeatability, low accuracy, poor portability, and so on. Critical discussion is provided on the trade-off relationship between detection speed and detection accuracy, as well as the application scenario and sustainability of different technologies. Especially, the prospect of combining different technologies is discussed. Future research is necessary to develop more convenient, more accurate, faster, and cost-effective technologies to detect aflatoxins.

Highly sensitive fluorescence detection of tobacco mosaic virus RNA based on polysaccharide and ARGET ATRP double signal amplification

Plant diseases caused by tobacco mosaic viruses (TMV) reduce the yield and quality of crops and cause significant losses. Early detection and prevention of TMV has important value of research and reality. Herein, a fluorescent biosensor was constructed for highly sensitive detection of TMV RNA (tRNA) based on the principle of base complementary pairing, polysaccharides and atom transfer radical polymerization by electron transfer activated regeneration catalysts (ARGET ATRP) as double signal amplification strategy. The 5'-end sulfhydrylated hairpin capture probe (hDNA) was first immobilized on amino magnetic beads (MBs) by a cross-linking agent, which specifically recognizes tRNA. Then, chitosan binds to BIBB, providing numerous active sites for fluorescent monomer polymerization, which successfully significantly amplifying the fluorescent signal. Under optimal experimental conditions, the proposed fluorescent biosensor for the detection of tRNA has a wide detection range from 0.1 pM to 10 nM (R² = 0.998) with a limit of detection (LOD) as low as 1.14 fM. In addition, the fluorescent biosensor showed satisfactory applicability for the qualitative and quantitative analysis of tRNA in real samples, thereby demonstrating the potential in the field of viral RNA detection.

Real-Time Assessment of Intracellular Metabolites in Single Cells through RNA-Based Sensors

Quantification of the concentration of particular cellular metabolites reports on the actual utilization of metabolic pathways in physiological and pathological conditions. Metabolite concentration also constitutes the readout for screening cell factories in metabolic engineering. However, there are no direct approaches that allow for real-time assessment of the levels of intracellular metabolites in single cells. In recent years, the modular architecture of natural bacterial RNA riboswitches has inspired the design of genetically encoded synthetic RNA devices that convert the intracellular concentration of a metabolite into a quantitative fluorescent signal. These so-called RNA-based sensors are composed of a metabolite-binding RNA aptamer as the sensor domain, connected through an actuator segment to a signal-generating reporter domain. However, at present, the variety of available RNA-based sensors for intracellular metabolites is still very limited. Here, we go through natural mechanisms for metabolite sensing and regulation in cells across all kingdoms, focusing on those mediated by riboswitches. We review the design principles underlying currently developed RNA-based sensors and discuss the challenges that hindered the development of novel sensors and recent strategies to address them. We finish by introducing the current and potential applicability of synthetic RNA-based sensors for intracellular metabolites.

TFBMiner: A User-Friendly Command Line Tool for the Rapid Mining of Transcription Factor-Based Biosensors

Transcription factors responsive to small molecules are essential elements in synthetic biology designs. They are often used as genetically encoded biosensors with applications ranging from the detection of environmental contaminants and biomarkers to microbial strain engineering. Despite our efforts to expand the space of compounds that can be detected using biosensors, the identification and characterization of transcription factors and their corresponding inducer molecules remain labor- and time-intensive tasks. Here, we introduce TFBMiner, a new data mining and analysis pipeline that enables the automated and rapid identification of putative metabolite-responsive transcription factor-based biosensors (TFBs). This user-friendly command line tool harnesses a heuristic rule-based model of gene organization to identify both gene clusters involved in the catabolism of user-defined molecules and their associated transcriptional regulators. Ultimately, biosensors are scored based on how well they fit the model, providing wet-lab scientists with a ranked list of candidates that can be experimentally tested. We validated the pipeline using a set of molecules for which TFBs have been reported previously, including sensors responding to sugars, amino acids, and aromatic compounds, among others. We further demonstrated the utility of TFBMiner by identifying a biosensor for S-mandelic acid, an aromatic compound for which a responsive transcription factor had not been found previously. Using a combinatorial library of mandelate-producing microbial strains, the newly identified biosensor was able to distinguish between low- and high-producing strain candidates. This work will aid in the unraveling of metabolite-responsive microbial gene regulatory networks and expand the synthetic biology toolbox to allow for the construction of more sophisticated self-regulating biosynthetic pathways.

Lab on a Chip Device for Diagnostic Evaluation and Management in Chronic Renal Disease: A Change Promoting Approach in the Patients' Follow Up

Lab-on-a-chip (LOC) systems are miniaturized devices aimed to perform one or several analyses, normally carried out in a laboratory setting, on a single chip. LOC systems have a wide application range, including diagnosis and clinical biochemistry. In a clinical setting, LOC systems can be associated with the Point-of-Care Testing (POCT) definition. POCT circumvents several steps in central laboratory testing, including specimen transportation and processing, resulting in a faster turnaround time. Provider access to rapid test results allows for prompt medical decision making, which can lead to improved patient outcomes, operational efficiencies, patient satisfaction, and even cost savings. These features are particularly attractive for healthcare settings dealing with complicated patients, such as those affected by chronic kidney disease (CKD). CKD is a pathological condition characterized by progressive and irreversible structural or functional kidney impairment lasting for more than three months. The disease displays an unavoidable tendency to progress to End Stage Renal Disease (ESRD), thus requiring renal replacement therapy, usually dialysis, and transplant. Cardiovascular disease (CVD) is the major cause of death in CKD, with a cardiovascular risk ten times higher in these patients than the rate observed in healthy subjects. The gradual decline of the kidney leads to the accumulation of uremic solutes, with negative effect on organs, especially on the cardiovascular system. The possibility to monitor CKD patients by using non-invasive and low-cost approaches could give advantages both to the patient outcome and sanitary costs. Despite their numerous advantages, POCT application in CKD management is not very common, even if a number of devices aimed at monitoring the CKD have been demonstrated worldwide at the lab scale by basic studies (low Technology Readiness Level, TRL). The reasons are related to both technological and clinical aspects. In this review, the main technologies for the design of LOCs are reported, as well as the available POCT devices for CKD monitoring, with a special focus on the most recent reliable applications in this field. Moreover, the current challenges in design and applications of LOCs in the clinical setting are briefly discussed.

Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications

Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.