MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using ß-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories.

Synthesis and properties of nano-polyaniline films doped with camphor sulfonic acid.

Polyaniline (PANI) is an important conductive polymer with good stability in the air and high conductivity. It can be used in the field of sensors, cells and capacitors. In this paper, PANI is prepared in the (NH4)2S2O8/HCI solution system. We used XRD, SEM and other relevant means to characterize the morphology and property of PANI-CSA, and we applied four-point probe measurement and FTIR to study the optical and electrical properties. We also analyzed the possible impact to infrared reflectance of various doping concentrations and the mechanism. The results show that the PANI-CSA film has the best performance and the highest infrared reflectivity when the doping ratio is 2:2.

Encoding Genetic Circuits with DNA Barcodes Paves the Way for High-Throughput Profiling of Dose-Response Curves of Metabolite Biosensors.

Metabolite biosensors, through which the intracellular metabolite concentrations could be converted to changes in gene expression, are widely used in a variety of applications according to the different output signals. However, it remains challenging to fine-tune the dose-response relationships of biosensors to meet the needs of various scenarios. On the other hand, the short read length of next-generation sequencing (NGS) has greatly limited the design capability of sequence libraries. To address these issues, we describe a DNA trackable assembly method, coupled with fluorescence-activated cell sorting and NGS (Sort-Seq), to achieve the characterization of dose-response curves in a massively parallel manner. As a proof of the concept, we constructed a malonyl-CoA biosensor library containing 5184 combinations with six levels of transcription factor dosage, four different operator positions, and 216 possible upstream enhancer sequence (UAS) designs in Saccharomyces cerevisiae BY4700. By using Sort-Seq and machine learning approach, we obtained comprehensive dose-response relationships of the combinatorial sequence space. Therefore, our pipeline provides a platform for the design, tuning, and profiling of biosensor response curves and shows great potential to facilitate the rational design of genetic circuits.

Acetate accumulation and regulation by process parameters control in Chinese hamster ovary cell culture.

Chinese hamster ovary (CHO) cells represent a group of predominantly used mammalian hosts for producing recombinant therapeutic proteins. Known for their rapid proliferation rates, CHO cells undergo aerobic glycolysis that is characterized by fast glucose consumption, that ultimately gives rise to a group of small-molecule organic acids. However, only the function of lactate has been extensively studied in CHO cell culture. In this study, we observed the accumulation of acetate from the late exponential phase to harvest day, potentially contributing to the pH decline in late culture stage regardless of lactate consumption. In addition, we evaluated the acidification of the fresh media and the cell culture suspension, and the data revealed that acetate presented a lower acidification capacity compared to lactate and exhibited limited inhibitory effect on cells with less than 20 mM supplemented in the media. This study also explored the ways to control acetate accumulation in CHO cell culture by manipulating the process parameters such as temperature, glucose, and pH control. The positive correlation between the specific glucose consumption rate and acetate generation rate provides evidence of the endogenous acetate generation from overflow metabolism. Reducing these parameters (temperature, glucose consumption) and HCl-controlled low pH ultimately suppress acetate build-up. In addition, the specific acetate generation rate and relevant glucose consumption rate are found to be a metabolic trait associated with specific cell lines. Taken together, the results presented in these experiments provide a means to advance industrial CHO cell culture process control and development.

Encoding Genetic Circuits with DNA Barcodes Paves the Way for Machine Learning-Assisted Metabolite Biosensor Response Curve Profiling in Yeast.

Genetically encoded biosensors are valuable tools used in the precise engineering of metabolism. Although a large number of biosensors have been developed, the fine-tuning of their dose-response curves, which promotes the applications of biosensors in various scenarios, still remains challenging. To address this issue, we leverage a DNA trackable assembly method and fluorescence-activated cell sorting coupled with next-generation sequencing (FACS-seq) technology to set up a novel workflow for construction and comprehensive characterization of thousands of biosensors in a massively parallel manner. An FapR-fapO-based malonyl-CoA biosensor was used as proof of concept to construct a trackable combinatorial library, containing 5184 combinations with 6 levels of transcription factor dosage, 4 different operator positions, and 216 possible upstream enhancer sequence (UAS) designs. By applying the FACS-seq technique, the response curves of 2632 biosensors out of 5184 combinations were successfully characterized to provide large-scale genotype-phenotype association data of the designed biosensors. Finally, machine-learning algorithms were applied to predict the genotype-phenotype relationships of the uncharacterized combinations to generate a panoramic scanning map of the combinatorial space. With the assistance of our novel workflow, a malonyl-CoA biosensor with the largest dynamic response range was successfully obtained. Moreover, feature importance analysis revealed that the recognition sequence insertion scheme and the choice of UAS have a significant impact on the dynamic range. Taken together, our pipeline provides a platform for the design, tuning, and profiling of biosensor response curves and shows great potential to facilitate the rational design of genetic circuits.

Cost-Effectiveness Analysis of Triple Combination Preparations in the Treatment of Moderate-to-Severe Chronic Obstructive Pulmonary Disease.

Objectives: This study analyzed the long-term cost-effectiveness of fluticasone/umeclidinium/vilanterol triple combination (FF/UMEC/VI) vs. budesonide/formoterol double combination (BUD/FOR) in the treatment of moderate-to-severe chronic obstructive pulmonary disease (COPD) and provides evidence for COPD treatment decisions. Methods: From the perspective of the healthcare system, a Markov model was established that consists of four states-stable period, non-severely deteriorating period, severely deteriorating period, and death-according to real-world COPD progression. The model period comprises 6 months, with a cycle length of 14 years. The initial state, transition probabilities, costs, and utility data were collected from the FULFIL trial, published literature, hospital record surveys, and China Health Statistics Yearbook. The discount rate was 5%, and the threshold was set as the Chinese per capita GDP in 2020 (¥72,447). The cost, utility, transition probabilities, and discount rate were calculated through TreeagePro11 software. The results were analyzed via one-way factor analysis and probability sensitivity analysis. Results: The baseline study shows that the 14-year treatment for FF/UMEC/VI and BUD/FOR groups are ¥199,765.55 and ¥173,030.05 with effectiveness at 8.54 quality-adjusted life years (QALYs) and 7.73 QALYs, respectively. The incremental cost-effectiveness ratio is ¥33,006.80/QALY, which is below the threshold. A tornado diagram of a one-way sensitivity analysis shows that the top three factors that affected the results are the non-severe deterioration rates of FF/UMEC/VI, the cost of FF/UMEC/VI and the non-severe deterioration rates of BUD/FOR. Probabilistic sensitivity analysis shows that FF/UMEC/VI (compared to BUD/FOR) can be made cost-effective under the willingness-to-pay (WTP) threshold (¥38,000). Furthermore, the likelihood of cost-effectiveness increases with a higher WTP. Conclusions: Compared with the double combination (BUD/FOR), the triple combination (FF/UMEC/VI) is more cost-effective under the Chinese per capita GDP threshold.

Enhanced Production of Crude Violacein from Glucose in Escherichia coli by Overexpression of Rate-Limiting Key Enzyme(S) Involved in Violacein Biosynthesis.

Crude violacein, consisting of violacein and deoxyviolacein, displays many attractive bio-activities in the field of drug therapy. To produce crude violacein from an industrially economic carbon source, we firstly introduced the violacein pathway into Escherichia coli B8/pTRPH1, which was previously engineered to accumulate tryptophan from glucose. A crude violacein production capacity of 0.25 g L-1 OD600-1 was obtained using glucose-containing medium. By further overexpressing each of the five genes involved in violacein synthesis pathway, VioE was found as the rate-limiting step for the violacein production. The optimal strain of B8/pTRPH1-pVio-VioE was then used for fed-batch fermentation in a 5-L bioreactor and a crude violacein titer of 4.45 g L-1, as well as a productivity of 98.7 mg L-1 h-1, was obtained. This engineered strain showed the highest violacein titer and productivity reported so far. Our optimal strain of E. coli B8/pTRPH1-pVio-VioE by overexpression of the rate-limiting VioE in violacein synthesis pathway was a potential violacein producer by directly using glucose for industrial application.