Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata

Protection against H2O2-evoked toxicity in HT22 hippocampal neuronal cells by geissoschizine methyl ether via inhibiting ERK pathway

Oxidative stress is considered as an important mechanism underlying the pathology of neurodegenerative disorders. In this study, we utilized an in vitro model where oxidative stress process was evoked by exogenous hydrogen peroxide (H₂O₂) in HT22 murine hippocampal neurons and evaluated the neuroprotective effects of geissoschizine methyl ether (GME), a naturally occurring alkaloid from the hooks of Uncaria rhynchophylla (Miq.) Jacks. After a 24 h H₂O₂ (350 μM) insult, a significant decrease in cell survival and a sharp increase in intracellular reactive oxygen species were observed in HT22 cells. Encouragingly, GME (10-200 μM) effectively reversed these abnormal cellular changes induced by H₂O₂. Moreover, mechanistic studies using Western blot revealed that GME inhibited the increase of phospho-ERK protein expression, but not phospho-p38, caused by H₂O₂. Molecular docking simulation further revealed a possible binding mode that GME inhibited ERK protein, showing that GME favorably bound to ERK via multiple hydrophobic and hydrogen bond interactions. These findings indicate that GME provide effective neuroprotection via inhibiting ERK pathway and also encourage further ex vivo and in vivo pharmacological investigations of GME in treating oxidative stress-mediated neurological disorders.

Genome sequencing of Colletotrichum gloeosporioides ESO026 reveals plausible pathway of HupA

BACKGROUND

Colletotrichum gloeosporioides ES026, isolated as an endophytic fungal strain, was found to produce the important medicinal compound HuperzineA (HupA). In a genetic context, ES026 showed potential in elucidating the biosynthetic pathway of HupA.

METHODS AND RESULTS

The ES026 strain was sequenced using de-novo Illumina sequencing methods in this study. Assembling the cleaned data resulted in 58,594,804bp, consisting of 404 scaffolds. The G + C mol % content of this genome was 52.53%. The genome progressive-alignment with other 4 Colletotrichum strains revealed that ES026 showed closer relation with 030206, SMCG1#C and Nara gc5. More than 60 putative biosynthetic clusters were predicted with the fungal version antiSMASH4.0 program. More than 33 types I polyketide-related biosynthetic gene clusters were distributed, containing PKS and PKS-NRPS (polyketide-nonribosomal peptides) hybrid gene clusters. Another 8 NRPS biosynthetic gene clusters were distributed among the genome of ES026. The prenyltransferases, probably involved in aromatic prenyl-compounds and terpenoid biosynthesis, were analyzed using bioinformatics tools like MEGA.

CONCLUSION

We predicted a new possible biosynthetic pathway for the HupA from the pipecolic acid, based on the published HupA biosynthesis proposed pathway, the biosynthesis and pipecolic acid-derived compounds. We hypothesize that a hybrid PKS-NRPS mega-enzyme was probably involved in the biosynthesis of HupA with the pipecolic acid, the building block of rapamycin, as a HupA precursor. The rapamycin is produced from a polyketide biosynthesis pathway, and the domain incorporating the pipecolic acid is studied.

Reference gene selection for real-time quantitative PCR assays in different tissues of Huperzia serrata based on full-length transcriptome sequencing

Huperzia serrata (H. serrata) produces various types of effective lycopodium alkaloids, especially Huperzine A (HupA), which is a promising drug for the treatment of Alzheimer's disease. Numerous studies focused on the chemistry, bioactivities, toxicology, and clinical trials of HupA; however, the public genomic and transcriptomic resources are very limited for H. serrata research, especially for the selection of optimum reference genes. Based on the full-length transcriptome datasets and previous studies, 10 traditional and three new candidate reference genes were selected in different tissue of H. serrata. Then, two optimal reference genes GAPDHB and HisH2A were confirmed by four analysis methods. In order to further verify the accuracy of the two reference genes, they were used to analyze the expression patterns of four HupA-biosynthetic genes (lysine decarboxylas, RS-norcoclaurine 6-O-methyltransferase, cytochrome P45072A1, and copper amine oxidase). The data suggested that the expression pattern of HupA-biosynthetic genes was consistent with them in transcriptome sequencing in different tissue of H. serrata. This study identified that GAPDHB and HisH2A provides the reliable normalization for analyzing the HupA biosynthetic gene expression in different tissues of H. serrata on the transcriptional level.

Mining plant metabolomes: Methods, applications, and perspectives

Plants produce a variety of metabolites that are essential for plant growth and human health. To fully understand the diversity of metabolites in certain plants, lots of methods have been developed for metabolites detection and data processing. In the data-processing procedure, how to effectively reduce false-positive peaks, analyze large-scale metabolic data, and annotate plant metabolites remains challenging. In this review, we introduce and discuss some prominent methods that could be exploited to solve these problems, including a five-step filtering method for reducing false-positive signals in LC-MS analysis, QPMASS for analyzing ultra-large GC-MS data, and MetDNA for annotating metabolites. The main applications of plant metabolomics in species discrimination, metabolic pathway dissection, population genetic studies, and some other aspects are also highlighted. To further promote the development of plant metabolomics, more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed. With the improvement of these technologies and the development of genomics and transcriptomics, plant metabolomics will be widely used in many fields.

Chemical Discrimination of Astragalus mongholicus and Astragalus membranaceus Based on Metabolomics Using UHPLC-ESI-Q-TOF-MS/MS Approach

Astragalus mongholicus (MG) and Astragalus membranaceus (MJ), both generally known as Huangqi in China, are two perennial herbals widely used in variety diseases. However, there were still some differences in the chemical ingredients between MG and MJ. In this paper, metabolomics combined with the ultra-high performance liquid chromatography coupled with electrospray ionization/quadrupole time-of-flight mass spectrometry (UHPLC-ESI-Q-TOF-MS/MS) was employed to contrastively analyze the chemical constituents between MG and MJ. As a result, principal component analysis showed that MG and MJ were separated clearly. A total of 53 chemical markers were successfully identified for the discrimination of MG and MJ. Of them, the contents of 36 components including Astragaloside I~III, Astragaloside IV, Agroastragaloside I, etc. in MJ were significantly higher than those in MG. On the contrary, the contents of 17 other components including coumaric acid, formononetin, sophoricoside, etc. in MG were obviously higher than those in MJ. The results showed that the distinctive constituents in MG and MJ were remarkable, and MJ may own stronger pharmacological activities than MG. In a word, MG and MJ may be treated as two different herbs. This paper demonstrated that metabolomics was a vitally credible technology to rapidly screen the characteristic chemical composition of traditional Chinese medicine.

Selection of Reference Genes for Expression Analysis in Chinese Medicinal Herb Huperzia serrata

Huperzine A (HupA) is a powerful and selective inhibitor of acetylcholinesterase. It has attracted widespread attention endangering the ultimate plant sources of Lycopodiaceae family. In this study, we used Huperzia serrata, extensively used in Traditional Chinese medicine (TCM), a slow growing vascular plant as the model plant of the Lycopodiaceae family to develop and validate the reference genes. We aim to use gene expression platform to understand the gene expression of different tissues and developmental stages of this medicinal herb. Eight candidate reference genes were selected based on RNA-seq data and evaluated with qRT-PCR. The expression of L/ODC and cytochrome P450s genes known for their involvement in lycopodium alkaloid biosynthesis, were also studied to validate the selected reference genes. The most stable genes were TBP, GAPDH, and their combination (TBP + GAPDH). We report for the first time the reference gene of H. serrata’s different tissues which would provide important insights into understanding their biological functions comparing other Lycopodiaceae plants and facilitate a good biopharming approach.