Hierarchical Distributed Adaptive Fault-Tolerant Control of Nonlinear Fractional-Order Multiagent Systems With Faults and Periodic Disturbances Using Event-Triggered Communication.

This article presents a distributed fault-tolerant control (FTC) scheme for nonlinear fractional-order (FO) multiagent systems (MASs) with the order lying in (0, 1, such that the proposed control architecture can be directly applied to both FO and integer-order (IO) systems without any modifications. To handle the unexpected actuator faults encountered by the FO MASs, a hierarchical FTC mechanism is developed for each system by constructing an event-triggered distributed FO estimator at the upper layer to estimate the leader system's output via conditionally triggered neighboring information, and an FTC unit at the lower layer to counteract the loss-of-effectiveness faults via Nussbaum function with FO criteria. To further address the unknown nonlinear functions involving bias faults and periodic disturbances, the Fourier series expansion technique is used to construct the input variables of fuzzy neural networks (FNNs), such that the FNNs with dynamically adjusted weight matrices, centers, and widths can be developed for each FO system to act as the learning module. It is shown by FO Lyapunov stability analysis that all follower systems can track the leader system against faults and periodic disturbances. Simulation results on FO systems and hardware-in-the-loop experiment results on IO fixed-wing unmanned aerial vehicles show the extensive feasibility of the developed scheme.

Reinforcement Learning-Based Fractional-Order Adaptive Fault-Tolerant Formation Control of Networked Fixed-Wing UAVs With Prescribed Performance.

This article investigates the fault-tolerant formation control (FTFC) problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults. To constrain the distributed tracking errors of follower UAVs with respect to neighboring UAVs in the presence of faults, finite-time prescribed performance functions (PPFs) are developed to transform the distributed tracking errors into a new set of errors by incorporating user-specified transient and steady-state requirements. Then, the critic neural networks (NNs) are developed to learn the long-term performance indices, which are used to evaluate the distributed tracking performance. Based on the generated critic NNs, actor NNs are designed to learn the unknown nonlinear terms. Moreover, to compensate for the reinforcement learning errors of actor-critic NNs, nonlinear disturbance observers (DOs) with skillfully constructed auxiliary learning errors are developed to facilitate the FTFC design. Furthermore, by using the Lyapunov stability analysis, it is shown that all follower UAVs can track the leader UAV with predesigned offsets, and the distributed tracking errors are finite-time convergent. Finally, comparative simulation results are presented to show the effectiveness of the proposed control scheme.

Zavarzinia marina sp. nov., a novel hydrocarbon-degrading bacterium isolated from deep chlorophyll maximum layer seawater of the West Pacific Ocean and emended description of the genus Zavarzinia.

A Gram-stain-negative, motile, non-spore-forming, strictly aerobic and rod-shaped bacterial strain, Adcm-6AT, was isolated from a seawater sample collected from the deep chlorophyll maximum layer in the West Pacific Ocean. Strain Adcm-6AT grew at 20-37 °C (optimum, 28-32 °C), at pH 6-11 (pH 7) and in the presence of 0-6 % (1-2 %) NaCl (w/v). Phylogenetic analysis based on 16S rRNA gene sequences indicated that it belonged to the genus Zavarzinia and had 97.7 and 96.9 % sequence similarity to Zavarzinia compransoris DSM 1231T and Zavarzinia aquatilis JCM 32263T, respectively. Digital DNA-DNA hybridization and average nucleotide identity values between strain Adcm-6AT and the two type strains were 22.2-22.9 % and 79.7-80.4 %, respectively. The principal fatty acids were C19:0 cyclo ω8c, summed feature 8 (C18:1 ω6c and/or C18:1 ω7c) and C16:0. The predominant respiratory quinone was Q-10. The polar lipids were diphosphatidylglycerol, two phosphatidylethanolamines, two phosphatidyglycerols and an unidentified lipid. The genomic DNA G+C content of strain Adcm-6AT was 67.7 %. Based on phylogenetic analysis and genomic-based relatedness indices, as well as phenotypic and genotypic characteristics, strain Adcm-6AT represents a novel species within the genus Zavarzinia, for which the name Zavarzinia marina sp. nov. is proposed. The type strain is Adcm-6AT (=MCCC M24951T=KCTC 82849T).

Refined Fractional-Order Fault-Tolerant Coordinated Tracking Control of Networked Fixed-Wing UAVs Against Faults and Communication Delays via Double Recurrent Perturbation FNNs.

This article investigates the fault-tolerant coordinated tracking control problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults and communication delays. By supplementing the commonly used Gaussian functions in the fuzzy neural networks (FNNs) with sine-cosine functions and constructing two kinds of recurrent loops within the FNN architecture, double recurrent perturbation FNNs are cleverly designed to learn the unknown terms containing faults and uncertainties. Then, adaptive laws are designed for double recurrent perturbation FNNs. Moreover, by assimilating fractional-order calculus into the sliding-mode surfaces and the control signals, refined transient-state and steady-state adjustment performances can be obtained. It is shown by Lyapunov stability analysis that all fixed-wing UAVs can coordinately track their desired trajectories and the tracking errors are uniformly ultimately bounded. Comparative simulation results are provided to show the effectiveness of the proposed control strategy.

The Global Regulator PhoU Positively Controls Growth and Butenyl-Spinosyn Biosynthesis in Saccharopolyspora pogona.

Butenyl-spinosyn, a highly effective biological insecticide, is produced by Saccharopolyspora pogona. However, its application has been severely hampered by its low yield. Recent studies have shown that PhoU plays a pivotal role in regulating cell growth, secondary metabolite biosynthesis and intracellular phosphate levels. Nevertheless, the function of PhoU remains ambiguous in S. pogona. In this study, we investigated the effects of PhoU on the growth and the butenyl-spinosyn biosynthesis of S. pogona by constructing the mutants. Overexpression of phoU increased the production of butenyl-spinosyn to 2.2-fold that of the wild-type strain. However, the phoU deletion resulted in a severe imbalance of intracellular phosphate levels, and suppression of the growth and butenyl-spinosyn biosynthesis. Quantitative Real-time PCR (qRT-PCR) analysis, distinctive protein detection and mass spectrometry revealed that PhoU widely regulated primary metabolism, energy metabolism and DNA repair, which implied that PhoU influences the growth and butenyl-spinosyn biosynthesis of S. pogona as a global regulator.

Promoting Butenyl-spinosyn Production Based on Omics Research and Metabolic Network Construction in Saccharopolyspora pogona.

Understanding the metabolism of Saccharopolyspora pogona on a global scale is essential for manipulating its metabolic capabilities to improve butenyl-spinosyn biosynthesis. Here, we combined multiomics analysis to parse S. pogona genomic information, construct a metabolic network, and mine important functional genes that affect the butenyl-spinosyn biosynthesis. This research not only elucidated the relationship between butenyl-spinosyn biosynthesis and the primary metabolic pathway but also showed that the low expression level and continuous downregulation of the bus cluster and the competitive utilization of acetyl-CoA were the main reasons for reduced butenyl-spinosyn production. Our framework identified 148 genes related to butenyl-spinosyn biosynthesis that were significantly differentially expressed, confirming that butenyl-spinosyn polyketide synthase (PKS) and succinic semialdehyde dehydrogenase (GabD) play an important role in regulating butenyl-spinosyn biosynthesis. Combined modification of these genes increased overall butenyl-spinosyn production by 6.38-fold to 154.1 ± 10.98 mg/L. Our results provide an important strategy for further promoting the butenyl-spinosyn titer.

Distributed prescribed performance containment control for unmanned surface vehicles based on disturbance observer.

This paper introduces a distributed containment control strategy for multiple unmanned surface vehicles (USVs) under the unknown external disturbances. The communication network of the USVs is a fixed, directed topology and only a part of the follower USVs can read the states of leader USVs. To guarantee the transient and steady-state performance of the system, the tracking errors are converted into new error functions. By utilizing the disturbance observer, the external disturbances are effectively estimated. According to the new group of errors, a distributed containment controller is proposed with the estimated external disturbances. Furthermore, using graph theory and Lyapunov approach, it is proved that all variables of the multiple USV systems are bounded and the tracking errors can be confined within the specified performance ranges. Finally, simulation results illustrate the effectiveness of the designed distributed containment controller.

Distributed Fractional-Order Intelligent Adaptive Fault-Tolerant Formation-Containment Control of Two-Layer Networked Unmanned Airships for Safe Observation of a Smart City.

This article investigates a distributed fractional-order fault-tolerant formation-containment control (FOFTFCC) scheme for networked unmanned airships (UAs) to achieve safe observation of a smart city. In the proposed control method, an interval type-2 fuzzy neural network (IT2FNN) is first developed for each UA to approximate the unknown term associated with the loss-of-effectiveness faults in the distributed error dynamics, and then a disturbance observer (DO) is proposed to compensate for the approximation error and bias fault encountered by each UA, such that the composite learning strategy composed of the IT2FNN and the DO is obtained for each UA. Moreover, fractional-order (FO) calculus is incorporated into the control scheme to provide an extra degree of freedom for the parameter adjustments. The salient feature of the proposed control scheme is that the composite learning algorithm and FO calculus are integrated to achieve a satisfactory fault-tolerant formation-containment control performance even when a portion of leader/follower UAs is subjected to the actuator faults in a distributed communication network. Furthermore, it is shown by Lyapunov stability analysis that all leader UAs can track the virtual leader UA with time-varying offset vectors, and all follower UAs can converge into the convex hull spanned by the leader UAs. Finally, comparative hardware-in-the-loop (HIL) experimental results are presented to show the effectiveness and superiority of the proposed method.

Distributed Adaptive Fault-Tolerant Time-Varying Formation Control of Unmanned Airships With Limited Communication Ranges Against Input Saturation for Smart City Observation.

This article investigates the distributed fault-tolerant time-varying formation control problem for multiple unmanned airships (UAs) against limited communication ranges and input saturation to achieve the safe observation of a smart city. To address the strongly nonlinear functions caused by the time-varying formation flight with limited communication ranges and bias faults, intelligent adaptive learning mechanisms are proposed by incorporating fuzzy neural networks. Moreover, Nussbaum functions are introduced to handle the input saturation and loss-of-effectiveness faults. The distinct features of the proposed control scheme are that time-varying formation flight, actuator faults including bias and loss-of-effectiveness faults, limited communication ranges, and input saturation are simultaneously considered. It is proven by Lyapunov stability analysis that all UAs can achieve a safe formation flight for the smart city observation even in the presence of actuator faults. Hardware-in-the-loop experiments with open-source Pixhawk autopilots are conducted to show the effectiveness of the proposed control scheme.

Fractional-Order Adaptive Fault-Tolerant Synchronization Tracking Control of Networked Fixed-Wing UAVs Against Actuator-Sensor Faults via Intelligent Learning Mechanism.

This article presents an enhanced fault-tolerant synchronization tracking control scheme using fractional-order (FO) calculus and intelligent learning architecture for networked fixed-wing unmanned aerial vehicles (UAVs) against actuator and sensor faults. To increase the flight safety of networked UAVs, a recurrent wavelet fuzzy neural network (RWFNN) learning system with feedback loops is first designed to compensate for the unknown terms induced by the inherent nonlinearities, unexpected actuator, and sensor faults. Then, FO sliding-mode control (FOSMC), involving the adjustable FO operators and the robustness of SMC, are dexterously proposed to further enhance flight safety and reduce synchronization tracking errors. Moreover, the dynamic parameters of the RWFNN learning system embedded in the networked fixed-wing UAVs are updated based on adaptive laws. Furthermore, the Lyapunov analysis ensures that all fixed-wing UAVs can synchronously track their references with bounded tracking errors. Finally, comparative simulations and hardware-in-the-loop experiments are conducted to demonstrate the validity of the proposed control scheme.

Identification of a TetR family regulator and a polyketide synthase gene cluster involved in growth development and butenyl-spinosyn biosynthesis of Saccharopolyspora pogona.

Butenyl-spinosyn produced by Saccharopolyspora pogona exhibits strong insecticidal activity and broad pesticidal spectrum. However, its synthetic level was low in the wild-type strain. At present, important functional genes involved in butenyl-spinosyn biosynthesis remain unknown, which leads to difficulty in efficiently editing its genome to improve the butenyl-spinosyn yield. To accelerate the genetic modification of S. pogona, we conducted comparative proteomics analysis to screen differentially expressed proteins related to butenyl-spinosyn biosynthesis. A TetR family regulatory protein was selected from the 289 differentially expressed proteins, and its encoding gene (SP_1288) was successfully deleted by CRISPR/Cas9 system. We further deleted a 32-kb polyketide synthase gene cluster (cluster 28) to reduce the competition for precursors. Phenotypic analysis revealed that the deletion of the SP_1288 and cluster 28 resulted in a 3.10-fold increase and a 35.4% decrease in the butenyl-spinosyn levels compared with the wild-type strain, respectively. The deletion of cluster 28 affected the cell growth, glucose consumption, mycelium morphology, and sporulation by controlling the expression of ptsH, ptsI, amfC, and other genes related to sporulation, whereas SP_1288 did not. These findings confirmed not only that the CRISPR/Cas9 system can be applied to the S. pogona genome editing but also that SP_1288 and cluster 28 are closely related to the butenyl-spinosyn biosynthesis and growth development of S. pogona. The strategy reported here will be useful to reveal the regulatory mechanism of butenyl-spinosyn and improve antibiotic production in other actinomycetes. KEY POINTS: • SP_1288 deletion can significantly promote the butenyl-spinosyn biosynthesis. • Cluster 28 deletion showed pleiotropic effects on S. pogona. • SP_1288 and cluster 28 were deleted by CRISPR/Cas9 system in S. pogona.

Deletion of a hybrid NRPS-T1PKS biosynthetic gene cluster via Latour gene knockout system in Saccharopolyspora pogona and its effect on butenyl-spinosyn biosynthesis and growth development.

Butenyl-spinosyn, a promising biopesticide produced by Saccharopolyspora pogona, exhibits stronger insecticidal activity and a broader pesticidal spectrum. However, its titre in the wild-type S. pogona strain is too low to meet the industrial production requirements. Deletion of non-target natural product biosynthetic gene clusters resident in the genome of S. pogona could reduce the consumption of synthetic precursors, thereby promoting the biosynthesis of butenyl-spinosyn. However, it has always been a challenge for scientists to genetically engineer S. pogona. In this study, the Latour gene knockout system (linear DNA fragment recombineering system) was established in S. pogona. Using the Latour system, a hybrid NRPS-T1PKS cluster (˜20 kb) which was responsible for phthoxazolin biosynthesis was efficiently deleted in S. pogona. The resultant mutant S. pogona-Δura4-Δc14 exhibited an extended logarithmic phase, increased biomass and a lower glucose consumption rate. Importantly, the production of butenyl-spinosyn in S. pogona-Δura4-Δc14 was increased by 4.72-fold compared with that in the wild-type strain. qRT-PCR analysis revealed that phthoxazolin biosynthetic gene cluster deletion could promote the expression of the butenyl-spinosyn biosynthetic gene cluster. Furthermore, a TetR family transcriptional regulatory gene that could regulate the butenyl-spinosyn biosynthesis has been identified from the phthoxazolin biosynthetic gene cluster. Because dozens of natural product biosynthetic gene clusters exist in the genome of S. pogona, the strategy reported here will be used to further promote the production of butenyl-spinosyn by deleting other secondary metabolite synthetic gene clusters.

RNA-Seq-Based Transcriptomic Analysis of Saccharopolyspora spinosa Revealed the Critical Function of PEP Phosphonomutase in the Replenishment Pathway.

Spinosyns, the secondary metabolites produced by Saccharopolyspora spinosa, are the active ingredients in a family of novel biological insecticides. Although the complete genome sequence of S. spinosa has been published, the transcriptome of S. spinosa remains poorly characterized. In this study, high-throughput RNA sequencing (RNA-seq) technology was applied to dissect the transcriptome of S. spinosa. Through transcriptomic analysis of different periods of S. spinosa growth, we found large numbers of differentially expressed genes and classified them according to their different functions. Based on the RNA-seq data, the CRISPR-Cas9 method was used to knock out the PEP phosphonomutase gene (orf 06952-4171). The yield of spinosyns A and D in S. spinosa-ΔPEP was 178.91 mg/L and 42.72 mg/L, which was 2.14-fold and 1.76-fold higher than that in the wild type (83.51 and 24.34 mg/L), respectively. The analysis of the mutant strains also verified the validity of the transcriptome data. The deletion of the PEP phosphonomutase gene leads to an increase in pyruvate content and affects the biosynthesis of spinosad. The replenishment of phosphoenol pyruvate in S. spinosa provides the substrate for the production of spinosad. We envision that these transcriptomic analysis results will contribute to the further study of secondary metabolites in actinomycetes.

Distributed adaptive fault-tolerant close formation flight control of multiple trailing fixed-wing UAVs.

This paper considers the reliable control problem for multiple trailing fixed-wing unmanned aerial vehicles (UAVs) against actuator faults and wake vortices. A distributed adaptive fault-tolerant control (FTC) scheme is proposed by using a distributed sliding-mode estimator, dynamic surface control architecture, neural networks, and disturbance observers. The proposed control scheme can make all trailing fixed-wing UAVs converge to the leading UAV with pre-defined time-varying relative positions even when all trailing UAVs encounter the wake vortices generated by the leading UAV and a portion of trailing UAVs is subjected to the actuator faults. It is shown that under the proposed distributed FTC scheme, the tracking errors of all trailing UAVs with respect to their desired positions are bounded. Comparative simulation results are provided to illustrate the effectiveness of the proposed control scheme.

Deciphering the Metabolic Pathway Difference Between Saccharopolyspora pogona and Saccharopolyspora spinosa by Comparative Proteomics and Metabonomics.

Butenyl-spinosyn, a secondary metabolite produced by Saccharopolyspora pogona, exhibits strong insecticidal activity than spinosyn. However, the low synthesis capacity and unknown metabolic characteristics of butenyl-spinosyn in wild-type S. pogona limit its broad application and metabolic engineering. Here, we showed that S. pogona exhibited increased glucose consumption ability and growth rate compared with S. spinosa, but the production of butenyl-spinosyn was much lower than that of spinosyn. To further elucidate the metabolic mechanism of these different phenotypes, we performed a comparative proteomic and metabolomic study on S. pogona and S. spinosa to identify the change in the abundance levels of proteins and metabolites. We found that the abundance of most proteins and metabolites associated with glucose transport, fatty acid metabolism, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine and pyrimidine metabolism, and target product biosynthesis in S. pogona was higher than that in S. spinosa. However, the overall abundance of proteins involved in butenyl-spinosyn biosynthesis was much lower than that of the high-abundance protein chaperonin GroEL, such as the enzymes related to rhamnose synthesis. We speculated that these protein and metabolite abundance changes may be directly responsible for the above phenotypic changes in S. pogona and S. spinosa, especially affecting butenyl-spinosyn biosynthesis. Further studies revealed that the over-expression of the rhamnose synthetic genes and methionine adenosyltransferase gene could effectively improve the production of butenyl-spinosyn by 2.69- and 3.03-fold, respectively, confirming the reliability of this conjecture. This work presents the first comparative proteomics and metabolomics study of S. pogona and S. spinosa, providing new insights into the novel links of phenotypic change and metabolic difference between two strains. The result will be valuable in designing strategies to promote the biosynthesis of butenyl-spinosyn by metabolic engineering.

Distributed Finite-Time Fault-Tolerant Containment Control for Multiple Unmanned Aerial Vehicles.

This paper investigates the distributed finite-time fault-tolerant containment control problem for multiple unmanned aerial vehicles (multi-UAVs) in the presence of actuator faults and input saturation. The distributed finite-time sliding-mode observer (SMO) is first developed to estimate the reference for each follower UAV. Then, based on the estimated knowledge, the distributed finite-time fault-tolerant controller is recursively designed to guide all follower UAVs into the convex hull spanned by the trajectories of leader UAVs with the help of a new set of error variables. Moreover, the unknown nonlinearities inherent in the multi-UAVs system, computational burden, and input saturation are simultaneously handled by utilizing neural network (NN), minimum parameter learning of NN (MPLNN), first-order sliding-mode differentiator (FOSMD) techniques, and a group of auxiliary systems. Furthermore, the graph theory and Lyapunov stability analysis methods are adopted to guarantee that all follower UAVs can converge to the convex hull spanned by the leader UAVs even in the event of actuator faults. Finally, extensive comparative simulations have been conducted to demonstrate the effectiveness of the proposed control scheme.

Interaction of a novel Bacillus velezensis (BvL03) against Aeromonas hydrophila in vitro and in vivo in grass carp.

This study evaluated the inhibition and interaction of Bacillus velezensis BvL03 as a probiotic agent against Aeromonas hydrophila. Strain BvL03 isolated from sediment samples of fish ponds had excellent antimicrobial activity against several fish pathogenic bacteria, especially Aeromonas, including A. hydrophila, A. veronii, A. caviae, and A. sobria. The successful amplification of lipopeptide antimicrobial chemical biosynthetic genes, including iturin family (ituA, ituB, and ituD), bacillomycin family (bacA, bacD, and bacAB), surfactin family (srfAB, srfC, and srfAA), and subtilosin family (albF and sunT) from the genome of BvL03 strain, confirmed its predominant antimicrobial activity. The challenge test suggested that BvL03 significantly decreased fish mortality when challenged with A. hydrophila, which had a cumulative mortality of 12.5% in the treatment group. Toxicity and hemolytic activity of A. hydrophila after co-cultured with BvL03 were relieved as confirmed by the cell experiments, when the initial inoculated concentration of BvL03 was 109 cfu/mL or higher. Moreover, the BvL03 strain labeled with GFP protein (BvL03-GFP) and AhX040 strain labeled with mCherry protein (AhX040-mCherry) were injected into grass carps. The fluorescence levels were monitored by using In Vivo Imaging System (IVIS), in which the green color was steadily increasing, whereas the red color was gradually weakening. Whole genome sequencing revealed that strain BvL03 possesses 15 gene clusters related to antibacterial compounds, including 5 NRPS gene clusters and 3 PKS gene clusters. These results suggested that B. velezensis BvL03 has the potential to be developed as a probiotic candidate against A. hydrophila infection in aquaculture.

[Effect of fcl gene for butenyl-spinosyn biosynthesis and growth of Saccharopolyspora pogona].

The fcl gene encodes GDP-fucose synthase, which catalyzes two-step differential isomerase and reductase reactions in the synthesis of GDP-L-fucose from GDP-D-mannose. It also participates in the biosynthesis of amino sugar and ribose sugar, and is one of the key enzymes to regulate the metabolism of sugar and nucleotides in organisms. The presence of fcl gene in Saccharopolyspora pogona was found through sequencing result of genome. The mutant S. pogona-fcl and S. pogona-Δfcl were constructed by gene engineering technology. The results showed that the gene had an effects on growth and development, protein expression and transcriptional level, insecticidal activity, and biosynthesis of butenyl-spinosyn of Saccharopolyspora pogona. The results of HPLC analysis showed that the yield of butenyl-spinosyn in S. pogona-Δfcl was 130% compared with that in S. pogona, which reduced by 25% in S. pogona-fcl. The results of determination of insecticidal activity showed that S. pogona-Δfcl had a stronger insecticidal activity against Helicoverpa armigera than that of S. pogona, while the S. pogona-fcl had a lower insecticidal activity against Helicoverpa armigera compared with S. pogona. Scanning electron microscopy (SEM) was used to observe the morphology of the mycelia. It was found that the surface of the S. pogona-Δfcl was wrinkled, and the mycelium showed a short rod shape. There was no significant difference in mycelial morphology between S. pogona-fcl and S. pogona. Aboved all showed that deletion of fcl gene in S. pogona hindered the growth and development of mycelia, but was beneficial to increase the biosynthesis of butenyl-spinosyn and improve insecticidal activity. Whereas the fcl gene over-expression was not conducive to the biosynthesis of butenyl-spinosyn and reduced their insecticidal activity. SDS-PAGE results showed that the difference of protein expression among the three strains was most obvious at 96 hours, which was identified by real-time fluorescence quantitative polymerase chain reaction, the results showed that there were significant differences of related genes in transcriptional levels among the three strains. Based on the results of the study, a network metabolic control map was constructed to analyze the effect of fcl gene on growth and the regulation pathway of butenyl-spinosyn biosynthesis, which provided an experimental basis for revealing the regulation mechanism of butenyl-spinosyn biosynthesis and related follow-up studies.

Characterizing Two Cytochrome P450s in Tiacumicin Biosynthesis Reveals Reaction Timing for Tailoring Modifications.

Functions of the tailoring enzymes for the biosynthesis of tiacumicin B (1) have been previously determined. However, the reaction timing remains elusive. Herein, we report the in vitro biochemical characterization of two P450 enzymes TiaP1 and TiaP2. The investigation of their substrate scope and kinetic parameters clearly demonstrates that the TiaP2-catalyzed C-20 hydroxylation is the first tailoring step and the TiaP1-catalyzed C-18 hydroxylation is the last step in the biosynthesis of 1.

Impact on strain growth and butenyl-spinosyn biosynthesis by overexpression of polynucleotide phosphorylase gene in Saccharopolyspora pogona.

Polynucleotide phosphorylase is a highly conserved protein found in bacteria and fungi that can regulate the transcription of related enzymes involved in amino acid metabolism, organic acid metabolism, and cell biosynthesis. We studied the effect of polynucleotide phosphorylase on Saccharopolyspora pogona (S. pogona) growth and the synthesis of secondary metabolites. First, we generated the overexpression vector pOJ260-PermE-pnp via overlap extension PCR. The vector pOJ260-PermE-pnp was then introduced into S. pogona by conjugal transfer, thereby generating the recombination strain S. pogona-Pnp. Results showed that engineering strains possessed higher biomass than those of the wild-type strains. Moreover, the ability of these strains to produce spores on solid medium was stronger than that of the wild-type strains. HPLC results revealed that the butenyl-spinosyn yield in S. pogona-Pnp increased by 1.92-fold compared with that of S. pogona alone. These findings revealed that overexpression of polynucleotide phosphorylase effectively promoted butenyl-spinosyn biosynthesis in S. pogona. This result may be extended to other Streptomyces for strain improvement.