A machine learning-based approach for improving plasmid DNA production in Escherichia coli fed-batch fermentations.

Artificial Intelligence (AI) technology is spearheading a new industrial revolution, which provides ample opportunities for the transformational development of traditional fermentation processes. During plasmid fermentation, traditional subjective process control leads to highly unstable plasmid yields. In this study, a multi-parameter correlation analysis was first performed to discover a dynamic metabolic balance among the oxygen uptake rate, temperature, and plasmid yield, whilst revealing the heating rate and timing as the most important optimization factor for balanced cell growth and plasmid production. Then, based on the acquired on-line parameters as well as outputs of kinetic models constructed for describing process dynamics of biomass concentration, plasmid yield, and substrate concentration, a machine learning (ML) model with Random Forest (RF) as the best machine learning algorithm was established to predict the optimal heating strategy. Finally, the highest plasmid yield and specific productivity of 1167.74 mg L-1 and 8.87 mg L-1/OD600 were achieved with the optimal heating strategy predicted by the RF model in the 50 L bioreactor, respectively, which was 71% and 21% higher than those obtained in the control cultures where a traditional one-step temperature upshift strategy was applied. In addition, this study transformed empirical fermentation process optimization into a more efficient and rational self-optimization method. The methodology employed in this study is equally applicable to predict the regulation of process dynamics for other products, thereby facilitating the potential for furthering the intelligent automation of fermentation processes.

Enhancing erythromycin production in Saccharopolyspora erythraea through rational engineering and fermentation refinement: A Design-Build-Test-Learn approach.

Industrial production of bioactive compounds from actinobacteria, such as erythromycin and its derivatives, faces challenges in achieving optimal yields. To this end, the Design-Build-Test-Learn (DBTL) framework, a systematic metabolic engineering approach, was employed to enhance erythromycin production in Saccharopolyspora erythraea (S. erythraea) E3 strain. A genetically modified strain, S. erythraea E3-CymRP21-dcas9-sucC (S. erythraea CS), was developed by suppressing the sucC gene using an inducible promoter and dcas9 protein. The strain exhibited improved erythromycin synthesis, attributed to enhanced precursor synthesis and increased NADPH availability. Transcriptomic and metabolomic analyses revealed altered central carbon metabolism, amino acid metabolism, energy metabolism, and co-factor/vitamin metabolism in CS. Augmented amino acid metabolism led to nitrogen depletion, potentially causing cellular autolysis during later fermentation stages. By refining the fermentation process through ammonium sulfate supplementation, erythromycin yield reached 1125.66 mg L-1, a 43.5% increase. The results demonstrate the power of the DBTL methodology in optimizing erythromycin production, shedding light on its potential for revolutionizing antibiotic manufacturing in response to the global challenge of antibiotic resistance.

Pathologically successful conversion hepatectomy for advanced giant hepatocellular carcinoma after multidisciplinary therapy: A case report and review of literature.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of death due to its complexity, heterogeneity, rapid metastasis and easy recurrence after surgical resection. We demonstrated that combination therapy with transcatheter arterial chemoembolization (TACE), hepatic arterial infusion chemotherapy (HAIC), Epclusa, Lenvatinib and Sintilimab is useful for patients with advanced HCC. CASE SUMMARY: A 69-year-old man who was infected with hepatitis C virus (HCV) 30 years previously was admitted to the hospital with abdominal pain. Enhanced computed tomography (CT) revealed a low-density mass in the right lobe of the liver, with a volume of 12.9 cm × 9.4 cm × 15 cm, and the mass exhibited a "fast-in/fast-out" pattern, with extensive filling defect areas in the right branch of the portal vein and an alpha-fetoprotein level as high as 657 ng/mL. Therefore, he was judged to have advanced HCC. During treatment, the patient received three months of Epclusa, three TACE treatments, two HAIC treatments, three courses of sintilimab, and twenty-one months of lenvatinib. In the third month of treatment, the patient developed severe side effects and had to stop immunotherapy, and the Lenvatinib dose had to be halved. Postoperative pathological diagnosis indicated a complete response. The patient recovered well after the operation, and no tumor recurrence was found. CONCLUSION: Multidisciplinary conversion therapy for advanced enormous HCC caused by HCV infection has a significant effect. Individualized drug adjustments should be made during any treatment according to the patient's tolerance to treatment.

Unveiling the mechanism of efficient ß-phenylethyl alcohol conversion in wild-type Saccharomyces cerevisiae WY319 through multi-omics analysis.

ß-Phenylethanol (2-PE), as an important flavor component in wine, is widely used in the fields of flavor chemistry and food health. 2-PE can be sustainably produced through Saccharomyces cerevisiae. Although significant progress has been made in obtaining high-yield strains, as well as improving the synthesis pathways of 2-PE, there still lies a gap between these two fields to unpin. In this study, the macroscopic metabolic characteristics of high-yield and low-yield 2-PE strains were systematically compared and analyzed. The results indicated that the production potential of the high-yield strain might be contributed to the enhancement of respiratory metabolism and the high tolerance to 2-PE. Furthermore, this hypothesis was confirmed through comparative genomics. Meanwhile, transcriptome analysis at key specific growth rates revealed that the collective upregulation of mitochondrial functional gene clusters plays a more prominent role in the production process of 2-PE. Finally, findings from untargeted metabolomics suggested that by enhancing respiratory metabolism and reducing the Crabtree effect, the accumulation of metabolites resisting high 2-PE stress was observed, such as intracellular amino acids and purines. Hence, this strategy provided a richer supply of precursors and cofactors, effectively promoting the synthesis of 2-PE. In short, this study provides a bridge for studying the metabolic mechanism of high-yield 2-PE strains with the subsequent targeted strengthening of relevant synthetic pathways. It also provides insights for the synthesis of nonalcoholic products in S. cerevisiae.

Promoter screening and identification for metabolic regulation in Acremonium chrysogenum.

Acremonium chrysogenum is the major industrial producer of cephalosporin C (CPC), which is used as raw material for the production of significant cephalosporin antibiotics. Due to the lack of diverse promoter elements, the development of metabolic engineering transformation is relatively slow, resulting in a limited improvement on CPC production. In this study, based on the analysis of the transcriptome profile, 27 candidate promoters were selected to drive the expression of the reporter genes. The promoter activities of this library ranged from 0.0075 to 101 times of the control promoter PAngpdA . Simultaneously, a rapid screening method for potential bidirectional promoters was developed and 4 strong bidirectional promoters from 27 candidate options were identified and validated. Finally, the Golden Gate method was employed to combine promoter modules from the library with various target genes. Through a mixed transformation and screening process, high-yielding strains AG-6, AG-18, and AG-41 were identified, exhibiting an increase in CPC production of 30%, 35%, and 29%, respectively, compared to the control strain Ac-∆axl2:: eGFP. Therefore, the utilization of this promoter library offers a broader range of synthetic biology toolkits for the genetic engineering transformation of A. chrysogenum, thus establishing a solid foundation for the precise regulation of gene expression.

Towards a hybrid model-driven platform based on flux balance analysis and a machine learning pipeline for biosystem design.

Metabolic modeling and machine learning (ML) are crucial components of the evolving next-generation tools in systems and synthetic biology, aiming to unravel the intricate relationship between genotype, phenotype, and the environment. Nonetheless, the comprehensive exploration of integrating these two frameworks, and fully harnessing the potential of fluxomic data, remains an unexplored territory. In this study, we present, rigorously evaluate, and compare ML-based techniques for data integration. The hybrid model revealed that the overexpression of six target genes and the knockout of seven target genes contribute to enhanced ethanol production. Specifically, we investigated the influence of succinate dehydrogenase (SDH) on ethanol biosynthesis in Saccharomyces cerevisiae through shake flask experiments. The findings indicate a noticeable increase in ethanol yield, ranging from 6 % to 10 %, in SDH subunit gene knockout strains compared to the wild-type strain. Moreover, in pursuit of a high-yielding strain for ethanol production, dual-gene deletion experiments were conducted targeting glycerol-3-phosphate dehydrogenase (GPD) and SDH. The results unequivocally demonstrate significant enhancements in ethanol production for the engineered strains Δsdh4Δgpd1, Δsdh5Δgpd1, Δsdh6Δgpd1, Δsdh4Δgpd2, Δsdh5Δgpd2, and Δsdh6Δgpd2, with improvements of 21.6 %, 27.9 %, and 22.7 %, respectively. Overall, the results highlighted that integrating mechanistic flux features substantially improves the prediction of gene knockout strains not accounted for in metabolic reconstructions. In addition, the finding in this study delivers valuable tools for comprehending and manipulating intricate phenotypes, thereby enhancing prediction accuracy and facilitating deeper insights into mechanistic aspects within the field of synthetic biology.

An inducible CRISPRi circuit for tunable dynamic regulation of gene expression in Saccharopolyspora erythraea.

Actinomyces are gram-positive bacteria known for their valuable secondary metabolites. Redirecting metabolic flux towards desired products in actinomycetes requires precise and dynamic regulation of gene expression. In this study, we integrated the CRISPR interference (CRISPRi) system with a cumate-inducible promoter to develop an inducible gene downregulation method in Saccharopolyspora erythraea, a prominent erythromycin-producing actinobacterium. The functionality of the cumate-inducible promoter was validated using the gusA gene as a reporter, and the successful inducible expression of the dCas9 gene was confirmed. The developed inducible CRISPRi strategy was then employed to downregulate the expression of target genes rppA in the wild-type strain NRRL2338 and sucC in the high erythromycin-producing strain E3. Through dynamic control of sucC expression, a significant enhancement in erythromycin production was achieved in strain E3. This study demonstrated the effectiveness of an inducible gene downregulation approach using CRISPRi and a cumate-inducible promoter, providing valuable insights for optimizing natural product production in actinomyces.

Enhancing and monitoring spore production in Clostridium butyricum using pH-based regulation strategy and a robust soft sensor based on back-propagation neural networks.

Clostridium butyricum is a probiotic that forms anaerobic spores and plays a crucial role in regulating gut microbiota. However, the total viable cell count and spore yield of C. butyricum in industrial production are comparatively low. To this end, we investigated the metabolic characteristics of the strain and proposed three distinct pH regulation strategies for enhancing spore production. In addition, precise measurement of fermentation parameters such as substrate concentration, total viable cell count, and spore concentration is crucial for successful industrial probiotics production. Nevertheless, online measurement of these intricate parameters in the fermentation of C. butyricum poses a considerable challenge owing to the complex, nonlinear, multivariate, and strongly coupled characteristics of the production process. Therefore, we analyzed the capacitance and conductivity acquired from a viable cell sensor as the core parameters for the fermentation process. Subsequently, a robust soft sensor was developed using a seven-input back-propagation neural network model with input variables of fermentation time, capacitance, conductivity, pH, initial total sugar concentration, ammonium ion concentration, and calcium ion concentration. The model enables the online monitoring of total viable biomass count, substrate concentrations, and spore yield, and can be extended to similar fermentation processes with pH changes as a characteristic feature.

Precise fermentation coupling with simultaneous separation strategy enables highly efficient and economical sophorolipids production.

Sophorolipids (SLs) represent highly promising biosurfactants. However, its widespread production and application encounter obstacles due to the significant costs involved. Here, an intelligent and precise regulation strategy was elucidated for the fermentation process coupled with in-situ separation production mode, to achieve cost-effective SLs production. Firstly, a mechanism-assisted data-driven model was constructed for "on-demand feeding of cells". Moreover, a strategy of step-wise oxygen supply regulation based on the demand for cell metabolic capacity was developed, which accomplished "on-demand oxygen supply of cells", to optimize the control of energy consumption. Finally, a systematic approach was implemented by integrating a semi-continuous fermentation mode with in-situ separation technology for SLs production. This strategy enhanced SLs productivity and yield, reaching 2.30 g/L/h and 0.57 g/g, respectively. These values represented a 40.2% and 18.7% increase compared to fed-batch fermentation. Moreover, the concentration of crude SLs after separation reached 793.12 g/L, facilitating downstream separation and purification processes.

Ammonium sulfate supplementation enhances erythromycin biosynthesis by augmenting intracellular metabolism and precursor supply in Saccharopolyspora erythraea.

In this study, the cellular metabolic mechanisms regarding ammonium sulfate supplementation on erythromycin production were investigated by employing targeted metabolomics and metabolic flux analysis. The results suggested that the addition of ammonium sulfate stimulates erythromycin biosynthesis. Targeted metabolomics analysis uncovered that the addition of ammonium sulfate during the late stage of fermentation resulted in an augmented intracellular amino acid metabolism pool, guaranteeing an ample supply of precursors for organic acids and coenzyme A-related compounds. Therefore, adequate precursors facilitated cellular maintenance and erythromycin biosynthesis. Subsequently, an optimal supplementation rate of 0.02 g/L/h was determined. The results exhibited that erythromycin titer (1311.1 µg/mL) and specific production rate (0.008 mmol/gDCW/h) were 101.3% and 41.0% higher than those of the process without ammonium sulfate supplementation, respectively. Moreover, the erythromycin A component proportion increased from 83.2% to 99.5%. Metabolic flux analysis revealed increased metabolic fluxes with the supplementation of three ammonium sulfate rates.

Optimization of the Fermentative Production of Rhizomucor miehei Lipase in Aspergillus oryzae by Controlling Morphology.

Morphology plays an important role in the fermentation bioprocess of filamentous fungi. In this study, we investigated the controlling strategies of morphology that improved the efficiency of Rhizomucor miehei lipase (RML) production using a high-yield Aspergillus oryzae. First, the inoculated spore concentrations were optimized in seed culture, and the RML activity increased by 43.4% with the well-controlled mycelium pellets in both ideal sizes and concentrations. Then, the initial nitrogen source and agitation strategies were optimized to regulate the morphology of Aspergillus oryzae in a 5 L bioreactor, and the established stable fermentation system increased the RML activity to 232.0 U/mL, combined with an increase in total RML activity from 98,080 U to 487,179 U. Furthermore, the optimized fermentation strategy was verified by a high-yield Aspergillus oryzae and achieved an additional improvement of RML activity, up to 320.0 U/mL. Moreover, this optimized fermentation bioprocess was successfully scaled up to a 50 L bioreactor, and the RML activity reached 550.0 U/mL. This work has established a stable precision fermentation bioprocess for RML production by A. oryzae in bioreactors, and the controlling strategy developed in this study could potentially be extended to an industrial scale for RML production with high efficiency.

Cephalosporin C biosynthesis and fermentation in Acremonium chrysogenum.

Cephalosporins are currently the most widely used antibiotics in clinical practice. The main strain used for the industrial production cephalosporin C (CPC) is Acremonium chrysogenum. CPC has the advantages of possessing a broad antibacterial spectrum and strong antibacterial activity. However, the yield and titer of cephalosporins obtained from A. chrysogenum are much lower than penicillin, which is also a ß-lactam antibiotic produced by Penicillium chrysogenum. Molecular biology research into A. chrysogenum has focused on gene editing technologies, multi-omics research which has provided information on the differences between high- and low-yield strains, and metabolic engineering involving different functional genetic modifications and hierarchical network regulation to understand strain characteristics. Furthermore, optimization of the fermentation process is also reviewed as it provides the optimal environment to realize the full potential of strains. Combining rational design to control the metabolic network, high-throughput screening to improve the efficiency of obtaining high-performance strains, and real-time detection and controlling in the fermentation process will become the focus of future research in A. chrysogenum. This minireview provides a holistic and in-depth analysis of high-yield mechanisms and improves our understanding of the industrial value of A. chrysogenum. KEY POINTS: • Review of the advances in A. chrysogenum characteristics improvement and process optimization • Elucidate the molecular bases of the mechanisms that control cephalosporin C biosynthesis and gene expression in A. chrysogenum • The future development trend of A. chrysogenum to meet industrial needs.

An Efficient High-Throughput Screening of High Gentamicin-Producing Mutants Based on Titer Determination Using an Integrated Computer-Aided Vision Technology and Machine Learning.

The "design-build-test-learn" (DBTL) cycle has been adopted in rational high-throughput screening to obtain high-yield industrial strains. However, the mismatch between build and test slows the DBTL cycle due to the lack of high-throughput analytical technologies. In this study, a highly efficient, accurate, and noninvasive detection method of gentamicin (GM) was developed, which can provide timely feedback for the high-throughput screening of high-yield strains. First, a self-made tool was established to obtain data sets in 24-well plates based on the color of the cells. Subsequently, the random forest (RF) algorithm was found to have the highest prediction accuracy with an R2 value of 0.98430 for the same batch. Finally, a stable genetically high-yield strain (998 U/mL) was successfully screened out from 3005 mutants, which was verified to improve the titer by 72.7% in a 5 L bioreactor. Moreover, the verified new data sets were updated on the model database in order to improve the learning ability of the DBTL cycle.

Engineering the methyltransferase through inactivation of the genK and genL leads to a significant increase of gentamicin C1a production in an industrial strain of Micromonospora echinospora 49-92S.

In this study, a single-component high-yielding Micromonospora echinospora strain 49-92S-KL01 was constructed by deleting methyltransferase-encoding genes genK and genL. In 5-L fermentation trials, gentamicin C1a titers in the mutant strain were 3.22-fold higher than that in the parental strain (211 U/mL vs. 50 U/mL). The glycolysis pathway and tricarboxylic acid cycle fluxes were reduced by 26.8% and 26.6%, respectively, compared to the parental strain according to the metabolic flux analysis during the stationary phase, resulting in lower levels of energy supplements required for the cellular maintenance. Meanwhile, a significant enhancement in precursor (paromamine) accumulation and availability was observed in 49-92S-KL01 compared to parental strain. These results indicate that genK and genL significantly affect the synthesis of gentamicin C1a. In addition, this study provides a more rational strategy for gentamicin C1a production.

Engineering of succinyl-CoA metabolism in view of succinylation regulation to improve the erythromycin production.

As a novel protein post-translational modification (PTM), lysine succinylation is widely involved in metabolism regulation by altering the activity of catalytic enzymes. Inactivating succinyl-CoA synthetase in Saccharopolyspora erythraea HL3168 E3 was proved significantly inducing the global protein hypersuccinylation. To investigate the effects, succinylome of the mutant strain E3ΔsucC was identified by using a high-resolution mass spectrometry-based proteomics approach. PTMomics analyses suggested the important roles of succinylation on protein biosynthesis, carbon metabolism, and antibiotics biosynthesis in S. erythraea. Enzymatic experiments in vivo and in vitro were further conducted to determine the succinylation regulation in the TCA cycle. We found out that the activity of aconitase (SACE_3811) was significantly inhibited by succinylation in E3ΔsucC, which probably led to the extracellular accumulation of pyruvate and citrate during the fermentation. Enzyme structural analyses indicated that the succinylation of K278 and K373, conservative lysine residues locating around the protein binding pocket, possibly affects the activity of aconitase. To alleviate the metabolism changes caused by succinyl-CoA synthetase inactivation and protein hypersuccinylation, CRISPR interference (CRISPRi) was applied to mildly downregulate the transcription level of gene sucC in E3. The erythromycin titer of the CRISPRi mutant E3-sucC-sg1 was increased by 54.7% compared with E3, which was 1200.5 mg/L. Taken together, this work not only expands our knowledge of succinylation regulation in the TCA cycle, but also validates that CRISPRi is an efficient strategy on the metabolic engineering of S. erythraea. KEY POINTS: • We reported the first systematic profiling of the S. erythraea succinylome. • We found that the succinylation regulation on the activity of aconitase. • We enhanced the production of erythromycin by using CRISPRi to regulate the transcription of gene sucC.

Reconstruction of the Genome-Scale Metabolic Model of Saccharopolyspora erythraea and Its Application in the Overproduction of Erythromycin.

Saccharopolyspora erythraea is considered to be an effective host for erythromycin. However, little is known about the regulation in terms of its metabolism. To develop an accurate model-driven strategy for the efficient production of erythromycin, a genome-scale metabolic model (iJL1426) was reconstructed for the industrial strain. The final model included 1426 genes, 1858 reactions, and 1687 metabolites. The accurate rates of the growth predictions for the 27 carbon and 31 nitrogen sources available were 92.6% and 100%, respectively. Moreover, the simulation results were consistent with the physiological observation and 13C metabolic flux analysis obtained from the experimental data. Furthermore, by comparing the single knockout targets with earlier published results, four genes coincided within the range of successful knockouts. Finally, iJL1426 was used to guide the optimal addition strategy of n-propanol during industrial erythromycin fermentation to demonstrate its ability. The experimental results showed that the highest erythromycin titer was 1442.8 µg/mL at an n-propanol supplementation rate of 0.05 g/L/h, which was 45.0% higher than that without n-propanol supplementation, and the erythromycin-specific synthesis rate was also increased by 30.3%. Therefore, iJL1426 will lead to a better understanding of the metabolic capabilities and, thus, is helpful in a systematic metabolic engineering approach.

Knockout and functional analysis of BSSS-related genes in Acremonium chrysogenum by novel episomal expression vector containing Cas9 and AMA1.

OBJECTIVE: The target sorB gene, related to sorbicillinoid production, and the free expression element, AMA1, were used to verify the methodological approach in Acremonium chrysogenum. RESULT: CRISPR-Cas9 episomal expression system was used to introduce a point mutation into the sorB gene and the addition of sorB donor DNA achieved complete knockout of target genes. Four BSSS (yeast bud site selection system)-related genes, axl1, axl2, bud3, and bud4 were knocked out without impact on yield, dry weight, or pH. Relationships between morphology and stress tolerance in knockout strains were analyzed. CONCLUSION: The gene-editing system used in the current study exceeded 80% efficiency and arthrospores development was found to differ from that in wild-type strain.

Comparative genomic and transcriptomic analysis guides to further enhance the biosynthesis of erythromycin by an overproducer.

Omics approaches have been applied to understand the boosted productivity of natural products by industrial high-producing microorganisms. Here, with the updated genome sequence and transcriptomic profiles derived from high-throughput sequencing, we exploited comparative omics analysis to further enhance the biosynthesis of erythromycin in an industrial overproducer, Saccharopolyspora erythraea HL3168 E3. By comparing the genome of E3 with the wild type NRRL23338, we identified fragment deletions inside 56 coding sequences and 255 single-nucleotide polymorphisms over the genome of E3. A substantial number of genomic variations were observed in genes responsible for pathways which were interconnected to the biosynthesis of erythromycin by supplying precursors/cofactors or by signal transduction. Furthermore, the transcriptomic data suggested that genes involved in the biosynthesis of erythromycin were significantly upregulated constantly, whereas some genes in biosynthesis clusters of other secondary metabolites contained nonsense mutations and were expressed at extremely low levels. Through comparative transcriptomic analysis, l-glutamine/l-glutamate and 2-oxoglutarate were identified as reporter metabolites. Around the node of 2-oxoglutarate, genomic mutations were also observed. Based on the omics association analysis, readily available strategies were proposed to engineer E3 by simultaneously overexpressing sucB (coding for 2-oxoglutarate dehydrogenase E2 component) and sucA (coding for 2-oxoglutarate dehydrogenase E1 component), which increased the erythromycin titer by 71% compared to E3 in batch culture. This study provides more promising molecular targets to engineer for enhanced production of erythromycin by the overproducer.

Changes in Oxygen Availability during Glucose-Limited Chemostat Cultivations of Penicillium chrysogenum Lead to Rapid Metabolite, Flux and Productivity Responses.

Bioreactor scale-up from the laboratory scale to the industrial scale has always been a pivotal step in bioprocess development. However, the transition of a bioeconomy from innovation to commercialization is often hampered by performance loss in titer, rate and yield. These are often ascribed to temporal variations of substrate and dissolved oxygen (for instance) in the environment, experienced by microorganisms at the industrial scale. Oscillations in dissolved oxygen (DO) concentration are not uncommon. Furthermore, these fluctuations can be exacerbated with poor mixing and mass transfer limitations, especially in fermentations with filamentous fungus as the microbial cell factory. In this work, the response of glucose-limited chemostat cultures of an industrial Penicillium chrysogenum strain to different dissolved oxygen levels was assessed under both DO shift-down (60% → 20%, 10% and 5%) and DO ramp-down (60% → 0% in 24 h) conditions. Collectively, the results revealed that the penicillin productivity decreased as the DO level dropped down below 20%, while the byproducts, e.g., 6-oxopiperidine-2-carboxylic acid (OPC) and 6-aminopenicillanic acid (6APA), accumulated. Following DO ramp-down, penicillin productivity under DO shift-up experiments returned to its maximum value in 60 h when the DO was reset to 60%. The result showed that a higher cytosolic redox status, indicated by NADH/NAD+, was observed in the presence of insufficient oxygen supply. Consistent with this, flux balance analysis indicated that the flux through the glyoxylate shunt was increased by a factor of 50 at a DO value of 5% compared to the reference control, favoring the maintenance of redox status. Interestingly, it was observed that, in comparison with the reference control, the penicillin productivity was reduced by 25% at a DO value of 5% under steady state conditions. Only a 14% reduction in penicillin productivity was observed as the DO level was ramped down to 0. Furthermore, intracellular levels of amino acids were less sensitive to DO levels at DO shift-down relative to DO ramp-down conditions; this difference could be caused by different timescales between turnover rates of amino acid pools (tens of seconds to minutes) and DO switches (hours to days at steady state and minutes to hours at ramp-down). In summary, this study showed that changes in oxygen availability can lead to rapid metabolite, flux and productivity responses, and dynamic DO perturbations could provide insight into understanding of metabolic responses in large-scale bioreactors.

Ultrasound assisted in situ separation of sophorolipids in multi-phase fermentation system to achieve efficient production by Candida bombicola.

BACKGROUND: Sophorolipids (SLs) are regarded as one of the most promising biosurfactants. However, high production costs are the main obstacle to extended SLs application. Semi-continuous fermentation, which is based on in situ separation, is a promising technology for achieving high SLs productivity. METHODS AND RESULTS: In this study, the sedimentation mechanism of SLs was analyzed. The formation of a hydrophobic mixture of SLs and rapeseed oil was a key factor in sedimentation. And the hydrophobicity and density of the mixture determined SLs sedimentation rate. On this basis, ultrasonic enhanced sedimentation technology (UEST) was introduced, by which the sedimentation rates were increased by 46.9%-485.4% with different ratio of rapeseed oil to SLs. UEST-assisted real-time in situ separation and semi-continuous fermentation were performed. SLs productivity and yield were 2.15 g L-1  h-1 and 0.58 g g-1 , respectively, simultaneously the loss ratio of cells, glucose, and rapeseed oil were significantly reduced. CONCLUSIONS: This study provides a new horizon for optimization of the SLs fermentation process.