Integration of high-throughput omics technologies in medicinal plant research: The new era of natural drug discovery

Medicinal plants are natural sources to unravel novel bioactive compounds to satisfy human pharmacological potentials. The world's demand for herbal medicines is increasing year by year; however, large-scale production of medicinal plants and their derivatives is still limited. The rapid development of modern technology has stimulated multi-omics research in medicinal plants, leading to a series of breakthroughs on key genes, metabolites, enzymes involved in biosynthesis and regulation of active compounds. Here, we summarize the latest research progress on the molecular intricacy of medicinal plants, including the comparison of genomics to demonstrate variation and evolution among species, the application of transcriptomics, proteomics and metabolomics to explore dynamic changes of molecular compounds, and the utilization of potential resources for natural drug discovery. These multi-omics research provide the theoretical basis for environmental adaptation of medicinal plants and allow us to understand the chemical diversity and composition of bioactive compounds. Many medicinal herbs' phytochemical constituents and their potential health benefits are not fully explored. Given their large diversity and global distribution as well as the impacts of growth duration and environmental factors on bioactive phytochemicals in medicinal plants, it is crucial to emphasize the research needs of using multi-omics technologies to address basic and applied problems in medicinal plants to aid in developing new and improved medicinal plant resources and discovering novel medicinal ingredients.

Next-generation -omics approaches to drive carboxylate production by acidogenic fermentation of food waste: a review

Acidogenic fermentation of food waste using mixed microbial cultures can produce carboxylates [or volatile fatty acids (VFA)] as high-valued bioproducts via a complex interplay of microorganisms during different stages of this process. However, the present fermentation systems are incapable of reaching the industrially relevant VFA production yields of ≥50 g/L primarly due to the complex process operation, competitive metabolic pathways, and limited understanding of microbial interplays. Recent reports have demonstrated the significant roles played by microbial communities from different phyla, which work together to control the process kinetics of various stages underlying acidogenic fermentation. In order to fully delineate the abundance, structure, and functionality of these microbial communities, next-generation high-throughput meta-omics technologies are required. In this article, we review the potential of metagenomics and metatranscriptomics approaches to enable microbial community engineering. Specifically, a deeper analysis of taxonomic relationships, shifts in microbial communities, and differences in the genetic expression of key pathway enzymes under varying operational and environmental parameters of acidogenic fermentation could lead to the identification of species-level functionalities for both cultivable and non-cultivable microbial fractions. Furthermore, it could also be used for successful gene sequence-guided microbial isolation and consortium development for bioaugmentation to allow VFA production with high concentrations and purity. Such highly controlled and engineered microbial systems could pave the way for tailored and high-yielding VFA synthesis, thereby creating a petrochemically competitive waste-to-value chain and promoting the circular bioeconomy.Research HighlightsMixed microbial mediated acidogenic fermentation of food waste.Metagenomics and metatranscriptomics based microbial community analysis.Omics derived function-associated microbial isolation and consortium engineering.High-valued sustainable carboxylate bio-products, i.e. volatile fatty acids.

Carbon Nanotubes Induce Metabolomic Profile Disturbances in Zebrafish: NMR-Based Metabolomics Platform

The present study aims to investigate the metabolic effects of single-walled carbon nanotubes (SWCNT) on zebrafish (Danio rerio) using ¹H nuclear magnetic resonance (¹H-NMR) spectroscopy. However, there is no significant information available regarding the characterization of organic molecules, and metabolites with SWCNT exposure. Noninvasive biofluid methods have improved our understanding of SWCNT metabolism in zebrafish in recent years. Here, we used targeted metabolomics to quantify a set of metabolites within biological systems. SWCNT at various concentrations was given to zebrafish, and the metabolites were extracted using two immiscible solvent systems, methanol and chloroform. Metabolomics profiling was used in association with univariate and multivariate data analysis to determine metabolomic phenotyping. The metabolites, malate, oxalacetate, phenylaniline, taurine, sn-glycero-3-phosphate, glycine, N-acetyl mate, lactate, ATP, AMP, valine, pyruvate, ADP, serine, niacinamide are significantly impacted. The metabolism of amino acids, energy and nucleotides are influenced by SWCNT which might indicate a disturbance in metabolic reaction networks. In conclusion, using high-throughput analytical methods, we provide a perspective of metabolic impacts and the underlying associated metabolic pathways.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Exploring the Regulation Mechanism of Xihuang Pill, Olibanum and β-Boswellic Acid on the Biomolecular Network of Triple-Negative Breast Cancer Based on Transcriptomics and Chemical Informatics Methodology

Background

Xihuang Pill (XHP) is mainly used to treat “Ru Yan (breast cancer)”. Evidence-based medical evidence and showed that XHP improves the efficacy of chemotherapy and reduced chemotherapy-induced toxicity in breast cancer patients. However, the mechanism of XHP against breast cancer is not clear.

Methods

The effect of XHP extract on cell half-inhibitory concentration (IC50) and cell viability of MD-MB-231 cells was detected by CCK-8 method. The cell inhibition rate of MDA-MB-453 cells were detected by MTT method. Apoptosis was detected by flow cytometry, cell transfer ability was detected by Transwell method, and cell proliferation ability was detected by colony formation assay. The expression of Notch1, β-catenin and c-myc mRNA in MDA-MB-453 cells were detected by real-time fluorescence quantitative PCR. Then, chemical informatics and transcriptomics methodology was utilized to predict the potential compounds and targets of XHP, and collect triple negative breast cancer (TNBC) genes and the data of Olibanum and β-boswellic acid intervention MD-MB-231 cells (from GSE102891). The cytoscape software was utilized to undergo network construction and network analysis. Finally, the data from the network analysis was imported into the DAVID database for enrichment analysis of signaling pathways and biological processes.

Results

The IC50 was 15.08 g/L (for MD-MB-231 cells). After interfering with MD-MB-231 cells with 15.08 g/L XHP extract for 72 h, compared with the control group, the cell viability, migration and proliferation was significantly decreased, while early apoptosis and late apoptosis were significantly increased (P < 0.01). After interfering with MDA-MB-453 cells with 6 g/L XHP extract for 72 h, compared with the control group, the cell inhibition and apoptosis rate increased, while the expression of Notch1, β-catenin and c-myc mRNA decreased. (P < 0.05). The chemical informatics and transcriptomics analysis showed that four networks were constructed and analyzed: (1) potential compounds-potential targets network of XHP; (2) XHP-TNBC PPI network; (3) DEGs PPI network of Olibanum-treated MD-MB 231 cells; (4) DEGs PPI network of β-boswellic acid -treated MD-MB 231 cells. Several anti-TNBC biological processes, signaling pathways, targets and so on were obtained.

Conclusion

XHP may exert anti-TNBC effects through regulating biological processes, signaling pathways, targets found in this study.

Agarwood Induction: Current Developments and Future Perspectives

Agarwood is a resinous part of the non-timber Aquilaria tree, which is a highly valuable product for medicine and fragrance purposes. To protect the endangered Aquilaria species, mass plantation of Aquilaria trees has become a sustainable way in Asian countries to obtain the highly valuable agarwood. As only physiologically triggered Aquilaria tree can produce agarwood, effective induction methods are long sought in the agarwood industry. In this paper, we attempt to provide an overview for the past efforts toward the understanding of agarwood formation, the evolvement of induction methods and their further development prospects by integrating it with high-throughput omics approaches.