A self-regulated network for dynamically balancing multiple precursors in complex biosynthetic pathways.

Microbial synthesis has emerged as a promising and sustainable alternative to traditional chemical synthesis and plant extraction. However, the competition between synthetic pathways and central metabolic pathways for cellular resources may impair final production efficiency. Moreover, when the synthesis of target product requires multiple precursors from the same node, the conflicts of carbon flux have further negative impacts on yields. In this study, a self-regulated network was developed to relieve the competition of precursors in complex synthetic pathways. Using 4-hydroxycoumarin (4-HC) synthetic pathway as a proof of concept, we employed an intermediate as a trigger to dynamically rewire the metabolic flux of pyruvate and control the expression levels of genes in 4-HC synthetic pathway, achieving self-regulation of multiple precursors and enhanced titer. Transcriptomic analysis results additionally demonstrated that the gene transcriptional levels of both pyruvate kinase PykF and synthetic pathway enzyme SdgA dynamically changed according to the intermediate concentrations. Overall, our work established a self-regulated network to dynamically balance the metabolic flux of two precursors in 4-HC biosynthesis, providing insight into balancing biosynthetic pathways where multiple precursors compete and interfere with each other.

Bacterial synthesis of C3-C5 diols via extending amino acid catabolism.

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.

Harnessing plasmid replication mechanism to enable dynamic control of gene copy in bacteria.

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.

Establishing an Autonomous Cascaded Artificial Dynamic (AutoCAD) regulation system for improved pathway performance.

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.

Advancing microbial production through artificial intelligence-aided biology.

Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for value-added compound production. To optimize metabolism and reach optimal productivity, synthetic biology has developed various genetic devices to engineer microbial systems by gene editing, high-throughput protein engineering, and dynamic regulation. However, current synthetic biology methodologies still rely heavily on manual design, laborious testing, and exhaustive analysis. The emerging interdisciplinary field of artificial intelligence (AI) and biology has become pivotal in addressing the remaining challenges. AI-aided microbial production harnesses the power of processing, learning, and predicting vast amounts of biological data within seconds, providing outputs with high probability. With well-trained AI models, the conventional Design-Build-Test (DBT) cycle has been transformed into a multidimensional Design-Build-Test-Learn-Predict (DBTLP) workflow, leading to significantly improved operational efficiency and reduced labor consumption. Here, we comprehensively review the main components and recent advances in AI-aided microbial production, focusing on genome annotation, AI-aided protein engineering, artificial functional protein design, and AI-enabled pathway prediction. Finally, we discuss the challenges of integrating novel AI techniques into biology and propose the potential of large language models (LLMs) in advancing microbial production.

Engineering a Streptococcus Cas9 Ortholog with an RxQ PAM-Binding Motif for PAM-Free Gene Control in Bacteria.

The RNA-guided Cas9 endonucleases have revolutionized gene editing and regulation, but their targeting scope is limited by the protospacer adjacent motif (PAM) requirement. The most extensively used SpCas9 from Streptococcus pyogenes recognizes the NGG PAM via an RxR PAM-binding motif within its PAM-interaction (PI) domain. To overcome the strict PAM requirement, we identified and characterized a Cas9 ortholog from Streptococcus equinus HC5 (SeHCas9) that shows high sequence identity with SpCas9 but harbors a different RxQ PAM-binding motif. Complete PAM profiling revealed that SeHCas9 recognized an NAG PAM and accommodated NKG and NAW PAMs. We investigated the PAM interaction mechanism by identifying the crucial role of R1336 within the RxQ motif in determining PAM specificity, as well as the essentiality of two conserved residues (R1152 and Q1229) across Cas9 orthologs bearing the RxQ motif for PAM recognition. Further protein engineering created two variants, SeHdCas9-Q1229R and SeHdCas9-RR, that showed robust repression across an NNG and NNN PAM range, respectively. Our work proposes a novel Cas9 PAM interaction mechanism and establishes PAM-free Cas9 variants for bacterial gene control with almost no targeting restriction.

Identifying, Characterizing, and Engineering a Phenolic Acid-Responsive Transcriptional Factor from Bacillus amyloliquefaciens.

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.

Establishing Tunable Genetic Logic Gates with Versatile Dynamic Performance by Varying Regulatory Parameters.

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.

Fine-tuning gene expression for improved biosynthesis of natural products: From transcriptional to post-translational regulation.

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.

Biosensor-enabled pathway optimization in metabolic engineering.

Microbes can convert inexpensive renewable substrates to valuable metabolites by their natural metabolic pathways. To maximize the productivity, the pathways yet require further optimization, which remains challenging for our limited knowledge of complex biology. Genetically encoded biosensors are able to detect metabolite concentrations or environmental changes and transfer these inputs to measurable or actionable outputs, thus providing enabling regulation and monitoring tools for complicated pathway optimization. Here, we review recent advances in biosensor-mediated dynamic regulation and strain screening for the highest microbial production of diverse desirable products.

COVID-19 affects psychological symptoms of pregnant women indirectly by increasing their maternal concerns.

BACKGROUND: Pregnant women themselves are at higher risk for psychological symptoms. The impact of ongoing COVID-19 may increase the risk. However, it is uncertain whether COVID-19 affects pregnant women's psychological symptoms directly or indirectly being mediated. METHODS: This survey was conducted in four obstetrics and gynecology hospitals in Beijing from February 28, 2020, to April 26, 2020. Pregnant women who visited the antenatal-care clinic were mobilized to finish the online questionnaires, including the Generalized Anxiety Disorder 7-Item Scale, Patient Health Questionnaire-9, Connor-Davidson resilience scale, and Insomnia Severity Index. RESULTS: A total of 828 pregnant women were included in the analysis. The estimated self-reported rates of anxiety, depression, insomnia, and any of the three were 12.2 %, 24.3 %, 13.3 %, and 33.1 %, respectively. Mediating effect analysis showed that pregnant women's response to COVID-19 was not directly associated with psychological symptoms but indirectly through the mediating effect of maternal concerns, which accounted for 32.35 % of the total effect. Stratified analysis by psychological resilience showed that women's attitude toward COVID-19 (OR, 2.68, 95 % CI: 1.16-6.18) was associated with a higher risk of psychological symptoms in those with poor psychological resilience. LIMITATIONS: The study was a non-probability sampling survey, and the causal relationship between maternal concerns and psychological symptoms could not be determined due to the study's design. CONCLUSIONS: Under public health emergencies such as COVID-19, routine antenatal care should still be prioritized, and concerns related to childbirth-related caused by such emergencies should also be addressed, especially for those with weak psychological resilience.

Engineering a PAM-flexible SpdCas9 variant as a universal gene repressor.

The RNA-guided CRISPR-associated Cas9 proteins have been widely applied in programmable genome recombination, base editing or gene regulation in both prokaryotes and eukaryotes. SpCas9 from Streptococcus pyogenes is the most extensively engineered Cas9 with robust and manifold functionalities. However, one inherent limitation of SpCas9 is its stringent 5'-NGG-3' PAM requirement that significantly restricts its DNA target range. Here, to repurpose SpCas9 as a universal gene repressor, we generate and screen variants of the deactivated SpCas9 (SpdCas9) with relaxed 5'-CAT-3' PAM compatibility that can bind to the start codon ATG of almost any gene. Stepwise structure-guided mutations of the PAM-interacting residues and auxiliary PAM-proximal residues of the SpdNG (5'-NG-3' PAM) create a PAM-flexible variant SpdNG-LWQT that preferentially accommodates 5'-NRN-3' PAMs. SpdNG-LWQT is demonstrated to be effective in gene repression with the advantage of customizable sgRNA design in both Escherichia coli and Saccharomyces cerevisiae. This work validates the feasibility of purposeful PAM expansion of Cas9 towards signature PAMs and establishes a universal SpdCas9-based gene repressor.

Exploring the Tunability and Dynamic Properties of MarR-PmarO Sensor System in Escherichia coli.

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.