Integrated transcriptomic and metabolomic analysis reveals the molecular basis of tissue-specific accumulation of bioactive steroidal alkaloids in Fritillaria unibracteata.

Fritillaria unibracteata is an endangered medicinal plant whose bulb has been used as a Chinese herb to suppress cough, asthma and excessive phlegm for centuries. Steroidal alkaloids, which are synthesized via the steroid synthesis pathways, are their significant bioactive constituents. However, few studies on genes involved in steroidal alkaloid biosynthesis in F. unibracteata have been reported, mainly due to the lack of the F. unibracteata genome. In this paper, comparative transcriptomic and metabolomic analyses of four different tissues of F. unibracteata (leaves, flowers, stems, and bulbs) were performed. Imperialine, peiminine, and peimisine were among the significant bioactive compounds that were considerably abundant in bulb tissue, according to the metabolomic findings. Then, 83.60 Gb transcriptome sequencing of four different tissues was performed, of which one gene encoding phosphomevalonate kinase was directly functionally characterized to verify the accuracy of sequences obtained from the transcriptome. A total of 9217 differentially expressed unigenes (DEGs) were identified in four different tissues of F. unibracteata. GO and KEGG enrichments revealed that phenylpropanoid biosynthesis, MVA-mediated terpenoid backbone biosynthesis, and steroid biosynthesis were enriched in bulb tissue, whereas enrichment of MEP-mediated terpenoid backbone biosynthesis, photosynthesis, photosynthesis-antenna protein and carotenoid biosynthesis was observed in aerial tissues. Moreover, clustering analysis indicated that the downstream steroid biosynthesis pathway was more important in steroidal alkaloid biosynthesis compared to the upstream terpenoid backbone biosynthesis pathway. Hence, MVA-mediated biosynthesis of steroidal alkaloids was proposed, in which 15 bulb-clustered DEGs were positively correlated with a high accumulation of bioactive steroid alkaloids, further validating our proposal. In addition, 36 CYP450s showing a positive correlation with bioactive steroidal alkaloids provided candidate enzymes to catalyze the subsequent steps of steroidal alkaloid biosynthesis. In addition, the transcription factors and ABC transporters clustered in bulb tissue might be responsible for the regulation and transportation of steroidal alkaloid biosynthesis. Protein-protein interaction analysis implied a highly complex steroid alkaloid biosynthesis network in which delta (24)-sterol reductase might be one of the central catalysts. Based on the integrated transcriptome and metabolome, this current study is a first step in understanding the tissue-specific biosynthesis of steroidal alkaloids in F. unibracteata. Furthermore, key genes and regulators identified herein could facilitate metabolic engineering to improve steroidal alkaloids in F. unibracteata.

Concrete Strength Prediction Using Different Machine Learning Processes: Effect of Slag, Fly Ash and Superplasticizer.

Blast furnace slag (BFS) and fly ash (FA), as mining-associated solid wastes with good pozzolanic effects, can be combined with superplasticizer to prepare concrete with less cement utilization. Considering the important influence of strength on concrete design, random forest (RF) and particle swarm optimization (PSO) methods were combined to construct a prediction model and carry out hyper-parameter tuning in this study. Principal component analysis (PCA) was used to reduce the dimension of input features. The correlation coefficient (R), the explanatory variance score (EVS), the mean absolute error (MAE) and the mean square error (MSE) were used to evaluate the performance of the model. R = 0.954, EVS = 0.901, MAE = 3.746, and MSE = 27.535 of the optimal RF-PSO model on the testing set indicated the high generalization ability. After PCA dimensionality reduction, the R value decreased from 0.954 to 0.88, which was not necessary for the current dataset. Sensitivity analysis showed that cement was the most important feature, followed by water, superplasticizer, fine aggregate, BFS, coarse aggregate and FA, which was beneficial to the design of concrete schemes in practical projects. The method proposed in this study for estimation of the compressive strength of BFS-FA-superplasticizer concrete fills the research gap and has potential engineering application value.