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Genetic logic gates can be employed in metabolic engineering and synthetic biology to regulate gene expression based on diverse inputs. Design of tunable genetic logic gates with versatile dynamic performance is essential for expanding the usability of these toolsets. Here, using the p-coumaric acid biosensor system as a proof-of-concept, we initially investigated the parameters influencing the buffer (BUF) genetic logic gates. Subsequently, integrating binding sequences from the p-coumaric acid biosensor system and tetR or lacI regulation systems into a constitutive promoter yielded AND genetic logic gates. Additionally, characterized antisense RNAs (asRNAs) or single guide RNAs (sgRNAs) with various repression efficiencies were combined with BUF gates to construct a suite of p-coumaric acid-triggered NOT genetic logic gates. Finally, the designed BUF and NOT gates were combined to construct bifunctional genetic circuits that were subjected to orthogonality evaluation. The genetic logic gates established in this study can serve as valuable tools in future applications of metabolic engineering and synthetic biology.

Transcriptional factors-based biosensors are commonly used in metabolic engineering for inducible control of gene expression and related applications such as high-throughput screening and dynamic pathway regulations. Mining for novel transcriptional factors is essential for expanding the usability of these toolsets. Here, we report the identification, characterization, and engineering of a phenolic acid responsive regulator PadR from Bacillus amyloliquefaciens (BaPadR). This BaPadR-based biosensor system showed a unique ligand preference and exhibited a high output strength comparable to that of commonly used inducible expression systems. Through engineering the DNA binding region of BaPadR, we further enhanced the dynamic range of the biosensor system. The DNA sequences that are responsible for BaPadR recognition were located by promoter truncation and hybrid promoter building. To further explore the tunability of the sensor system, base substitutions were performed on the BaPadR binding region of the phenolic acid decarboxylase promoter (PpadC) and the hybrid promoter. This novel biosensor system can serve as a valuable tool in future synthetic biology applications.

Background Dysphagia, a prevalent geriatric syndrome, has been witnessing an upward trend in incidence rates, potentially leading to severe complications like aspiration pneumonia and asphyxia. Despite its significance, research on the prevalence and determinants of dysphagia among community-dwelling elderly remains scarce. Objective This study aims to ascertain the prevalence of dysphagia among Shanghai's elderly community by identifying influencing factors and analyzing occurrence rates and determinants across different age brackets. Methods Employing a cross-sectional survey approach, the study was conducted from July 2022 to May 2023. Using convenience sampling, the study involved 358 individuals aged 60 and above, selected from the outpatient and home care services of five community health service centers in Huangpu, Baoshan and Fengxian Districts of Shanghai. Demographic data were collected, and measurements of the Appendicular Skeletal Muscle Index (ASMI), grip strength, and walking speed were taken. The Eating Assessment Tool-10 (EAT-10) was utilized to assess the risk of dysphagia among the elderly. Results Out of the 358 community-dwelling elderly individuals surveyed, 80 (22.3%) exhibited symptoms of dysphagia (EAT-10≥3) (dysphagia group). Multivariate Logistic regression analysis identified advanced age (≥80 years) (OR=18.484, 95%CI=3.571-95.679), depressive state (OR=4.135, 95%CI=1.280-13.364), and a history of choking (OR=13.650, 95%CI=4.345-42.877) as significant risk factors for dysphagia (P

With rapid advances in the development of metabolic pathways and synthetic biology toolkits, a persisting challenge in microbial bioproduction is how to optimally rewire metabolic fluxes and accelerate the concomitant high-throughput phenotype screening. Here we developed a biosensor-assisted titratable CRISPRi high-throughput (BATCH) screening approach that combines a titratable mismatch CRISPR interference and a biosensor mediated screening for high-production phenotypes in Escherichia coli. We first developed a programmable mismatch CRISPRi that could afford multiple levels of interference efficacy with a one-pot sgRNA pool (a total of 16 variants for each target gene) harboring two consecutive random mismatches in the seed region of sgRNA spacers. The mismatch CRISPRi was demonstrated to enable almost a full range of gene knockdown when targeting different positions on genes. As a proof-of-principle demonstration of the BATCH screening system, we designed doubly mismatched sgRNA pools targeting 20 relevant genes in E. coli and optimized a PadR-based p-coumaric acid biosensor with broad dynamic range for the eGFP fluorescence guided high-production screening. Using sgRNA variants for the combinatorial knockdown of pfkA and ptsI, the p-coumaric acid titer was increased by 40.6% to o 1308.6 mg/l from glycerol in shake flasks. To further demonstrate the general applicability of the BATCH screening system, we recruited a HpdR-based butyrate biosensor that facilitated the screening of E. coli strains achieving 19.0% and 25.2% increase of butyrate titer in shake flasks with sgRNA variants targeting sucA and ldhA, respectively. This work reported the establishment of a plug-and-play approach that enables multilevel modulation of metabolic fluxes and high-throughput screening of high-production phenotypes.

[Objective] Phosphorus absorption and utilization by plants mainly depend on phosphorus transporters, among which the low-affinity phosphorus transporters encoded by the PHT2 family are responsible for the absorption, transport and reuse of phosphate by plants under normal phosphorus conditions. We aim to explore the role and expression pattern of NtPHT2;1 gene in tobacco phosphate transport, and to cultivate new tobacco varieties with efficient phosphorus utilization through NtPHT2;1. [Methods] We cloned NtPHT2;1 using the cDNA of a common tobacco K326 as a template, and conducted bioinformatics analysis and subcellular localization analysis of the protein. The expression pattern of this gene under abiotic stress including low phosphorus were analyzed by fluorescence quantitative PCR. [Results] (1) The total length of NtPHT2;1 gene was 1 764 bp, encoding 587 amino acids. (2) NtPHT2;1 protein was localized to chloroplast. (3) The homology between NtPHT2;1 and CaPHT2;1 protein was 91%. (4) Nt- PHT2;1 promoter contains cis-acting elements involved in the regulation of plant aging and stress. (5) The expression of NtPHT2;1 was the highest in leaves, and expression in new leaves was higher than that in old leaves. There was no significant difference in the expression of this gene under low phosphorus compared with normal conditions. (6) The expression of this gene was decreased significantly under salt stress and drought stress. [Conclusion] NtPHT2;1 gene is involved in phosphate transport and utilization in growth and development of tobacco plants.

Endogenous metabolic pathways in microbial cells are usually precisely controlled by sophisticated regulation networks. However, the lack of such regulations when introducing heterologous pathways in microbial hosts often causes unbalanced enzyme expression and carbon flux distribution, hindering the construction of highly efficient microbial biosynthesis systems. Here, using naringenin as the target compound, we developed an Autonomous Cascaded Artificial Dynamic (AutoCAD) regulation system to automatically coordinate the pathway expression and redirect carbon fluxes for enhanced naringenin production. The AutoCAD regulation system, consisting of both intermediate-based feedforward and product-based feedback control genetic circuits, resulted in a 16.5-fold increase in naringenin titer compared with the static control. Fed-batch fermentation using the strain with AutoCAD regulation further enhanced the naringenin titer to 277.2 mg/L. The AutoCAD regulation system, with intermediate-based feedforward control and product-triggered feedback control, provides a new paradigm of developing complicated cascade dynamic control to engineer heterologous pathways.

Dynamic regulation has been proved efficient in controlling gene expression at transcriptional, translational, and post-translational level. However, the dynamic regulation at gene replication level has been rarely explored so far. In this study, we established dynamic regulation at gene copy level through engineering controllable plasmid replication to dynamically control the gene expression. Prototypic genetic circuits with different control logic were applied to enable diversified dynamic behaviors of gene copy. To explore the applicability of this strategy, the dynamic gene copy control was employed in regulating the biosynthesis of p-coumaric acid, which resulted in an up to 78% increase in p-coumaric acid titer to 1.69 g/L in shake flasks. These results indicated the great potential of applying dynamic gene copy control for engineering biosynthesis of valuable compounds in metabolic engineering.

Microbial production of natural compounds has attracted extensive attention due to their high value in pharmaceutical, cosmetic, and food industries. Constructing efficient microbial cell factories for biosynthesis of natural products requires the fine-tuning of gene expressions to minimize the accumulation of toxic metabolites, reduce the competition between cell growth and product generation, as well as achieve the balance of redox or co-factors. In this review, we focus on recent advances in fine-tuning gene expression at the DNA, RNA, and protein levels to improve the microbial biosynthesis of natural products. Commonly used regulatory toolsets in each level are discussed, and perspectives for future direction in this area are provided.

Transcriptional factor-based biosensors (TFBs) have been widely used in dynamic pathway control or high-throughput screening. Here, we systematically explored the tunability of a salicylic acid responsive regulator MarR from Escherichia coli aiming to explore its engineering potential. The effect of endogenous MarR in E. coli on the MarR-PmarO biosensor system was investigated. Furthermore, to investigate the function of marO binding boxes in this biosensor system, a series of hybrid promoters were constructed by placing the marO binding boxes in the strong constitutive pL promoter. The engineered hybrid promoters became responsive to MarR and salicylic acid. To further study the influence of each nucleotide in the marO box on MarR binding, we employed dynamic modeling to simulate the interaction and binding energy between each nucleotide in the marO boxes with the corresponding residues on MarR. Guided by the results of the simulation, we introduced mutations to key positions on the hybrid promoters and investigated corresponding dynamic performance. Two promoter variants I12AII4T and I12AII14T that exhibited improved responsive strengths and shifted dynamic ranges were obtained, which can be beneficial for future metabolic engineering research.

Metabolic engineering is a promising approach for the synthesis of valuable compounds. Transcriptional factor-based biosensors are efficient tools to regulate the metabolic pathway dynamically. Here, we engineered the p-coumaric acid responsive regulator PadR from Bacillus subtilis. We found that yveF and yveG, two previously uncharacterized components in the sensor system, showed positive impacts on the regulation of PadR-PpadC sensor system, mostly on assisting the release of the repression by PadR. By site directed PadR engineering, we obtained two mutants, K64A and H38A, which exhibited increased dynamic range and superior sensitivity. To increase the promoter strength of the sensor system and investigate whether the PadR binding boxes can function in a plug-and-play manner, a series of hybrid promoters were constructed. Four of them, P1, P2, P7, and P9, showed increased strength compared to PpadC and can be regulated by PadR and p-coumaric acid. The PadR variants and hybrid promoters obtained in this paper would expand the applicability of this sensor system in future metabolic engineering research.

Engineering microbial cell factories has been widely applied to produce compounds spanning from intricate natural products to bulk commodities. In each case, host robustness is essential to ensure the reliable and sustainable production of targeted metabolites. However, it can be negatively affected by metabolic burden, pathway toxicity, and harsh environment, resulting in a decreased titer and productivity. Enhanced robustness enables host to have better production performance under complicated growth circumstances. Here, we review current strategies for boosting host robustness, including metabolic balancing, genetic and phenotype stability enhancement, and tolerance engineering. In addition, we discuss the challenges and future perspectives on microbial host engineering for increased robustness.

BACKGROUND: In industrial fermentation, pH fluctuation resulted from microbial metabolism influences the strain performance and the final production. The common way to control pH is adding acid or alkali after probe detection, which is not a fine-tuned method and often leads to increased costs and complex downstream processing. Here, we constructed an intelligent pH-sensing and controlling genetic circuits called Genetic pH Shooting (GPS) to realize microbial self-regulation of pH. RESULTS: In order to achieve the self-regulation of pH, GPS circuits consisting of pH-sensing promoters and acid-/alkali-producing genes were designed and constructed. Designed pH-sensing promoters in the GPS can respond to high or low pHs and generate acidic or alkaline substances, achieving endogenously self-responsive pH adjustments. Base shooting circuit (BSC) and acid shooting circuit (ASC) were constructed and enabled better cell growth under alkaline or acidic conditions, respectively. Furthermore, the genetic circuits including GPS, BSC and ASC were applied to lycopene production with a higher yield without an artificial pH regulation compared with the control under pH values ranging from 5.0 to 9.0. In scale-up fermentations, the lycopene titer in the engineered strain harboring GPS was increased by 137.3% and ammonia usage decreased by 35.6%. CONCLUSIONS: The pH self-regulation achieved through the GPS circuits is helpful to construct intelligent microbial cell factories and reduce the production costs, which would be much useful in industrial applications.

Amino acids are naturally occurring and structurally diverse metabolites in biological system, whose potentials for chemical expansion, however, have not been fully explored. Here, we devise a metabolic platform capable of producing industrially important C3-C5 diols from amino acids. The presented platform combines the natural catabolism of charged amino acids with a catalytically efficient and thermodynamically favorable diol formation pathway, created by expanding the substrate scope of the carboxylic acid reductase toward noncognate ω-hydroxylic acids. Using the established platform as gateways, seven different diol-convertible amino acids are converted to diols including 1,3-propanediol, 1,4-butanediol, and 1,5-pentanediol. Particularly, we afford to optimize the production of 1,4-butanediol and demonstrate the de novo production of 1,5-pentanediol from glucose, with titers reaching 1.41 and 0.97 g l-1, respectively. Our work presents a metabolic platform that enriches the pathway repertoire for nonnatural diols with feedstock flexibility to both sugar and protein hydrolysates.

Proteins found in nature have traditionally been the most frequently used biocatalysts to produce numerous natural products ranging from commodity chemicals to pharmaceuticals. Protein engineering has emerged as a powerful biotechnological toolbox in the development of metabolic engineering, particularly for the biosynthesis of natural products. Recently, protein engineering has become a favored method to improve enzymatic activity, increase enzyme stability, and expand product spectra in natural product biosynthesis. This review summarizes recent advances and typical strategies in protein engineering, highlighting the paramount role of protein engineering in improving and diversifying the biosynthesis of natural products. Future prospects and research directions are also discussed.

Ultrahigh-temperature–pressure experiments are crucial for understanding the physical and chemical properties of matter. The recent development of boron-doped diamond (BDD) heaters has made such melting experiments possible in large-volume presses. However, estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained, owing to the lack of a suitable thermometer. Here, we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K. The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes, the actual sizes of cell assemblies after compression, the effects of the electrode, thermocouple and anvil, and the heat dissipation by the pressure-transmitting medium. The virtual thermometer reproduces the power–temperature relationships of ultrahigh-temperature–pressure experiments below 2600 K at press loads of 2.8–7.9 MN (∼19 to 28 GPa) within experimental uncertainties. The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power–temperature relationships below 2600 K. Furthermore, our model shows that the temperature distribution inside a BDD heater (19–26 K/mm along the radial direction and <83 K/mm along the longitudinal direction) is more homogeneous than those inside conventional heaters such as graphite or LaCrO3 heaters (100–200 K/mm). Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences. [ABSTRACT FROM AUTHOR]

Writing artificial logic and dynamic function into complex cellular background to achieve desired phenotypes or improved outputs calls for the development of new genetic tools as well as their innovative use. In this study, we present a sensor-regulator and RNAi-based bifunctional dynamic control network that can provide simultaneous upregulation and downregulation of cellular metabolism for engineered biosynthesis. The promoter-regulator-mediated upregulation function and its transduced downregulation function through RNAi are systematically verified and characterized. We apply this dynamic control network to regulate the phosphoenolpyruvate metabolic node in Escherichia coli and achieve autonomous distribution of carbon flux between its native metabolism and the engineered muconic acid biosynthetic pathway. This allows muconic acid biosynthesis to reach 1.8 g L-1. This study also suggests the circumstances where dynamic control approaches are likely to take effects.