Fast identification of anticancer constituents in Forsythiae Fructus based on metabolomics approaches

Metabolomics and cellular altered pathways in cancer biology: A review

Cancer is a deadly disease that affects a cell's metabolism and surrounding tissues. Understanding the fundamental mechanisms of metabolic alterations in cancer cells would assist in developing cancer treatment targets and approaches. From this perspective, metabolomics is a great analytical tool to clarify the mechanisms of cancer therapy as well as a useful tool to investigate cancer from a distinct viewpoint. It is a powerful emerging technology that detects up to thousands of molecules in tissues and biofluids. Like other "-omics" technologies, metabolomics involves the comprehensive investigation of micromolecule metabolites and can reveal important details about the cancer state that is otherwise not apparent. Recent developments in metabolomics technologies have made it possible to investigate cancer metabolism in greater depth and comprehend how cancer cells utilize metabolic pathways to make the amino acids, nucleotides, and lipids required for tumorigenesis. These new technologies have made it possible to learn more about cancer metabolism. Here, we review the cellular and systemic effects of cancer and cancer treatments on metabolism. The current study provides an overview of metabolomics, emphasizing the current technologies and their use in clinical and translational research settings.

Efficacy evaluation, active ingredients, and multitarget exploration of herbal medicine

Evidence shows that herbal medicine (HM) could be beneficial for the treatment of various diseases. However, complexities present in HM due to the unclear bioactive compounds, mechanisms of action, undetermined targets for therapy, and nonspecific features for metabolism, are currently an obstacle for the progression of novel drug discovery. Metabolomics could be a potential tool to overcome these issues and for the understanding of HM from a small-molecule metabolism level. The chinmedomics-based metabolomics method assesses the overall metabolism of organisms with a holistic view and shows great potential for understanding metabolic pathways, evaluating curative effects, clarifying mechanisms, discovering active ingredients, and precision medicine. This review focuses on the efficacy evaluation, active ingredient discovery, and target exploration of HM based on metabolomics and chinmedomics.

Forsythin inhibits β-hydroxybutyrate-induced oxidative stress in bovine macrophages by regulating p38/ERK, PI3K/Akt, and Nrf2/HO-1 signaling pathways

Ketosis is a metabolic disease of dairy cows in the perinatal period, β-hydroxybutyrate (β-HB) is the main component of ketosis. High levels of β-HB can trigger oxidative stress and inflammatory response in dairy cows, leading to decreased milk yield and multiple postpartum diseases. Forsythin (FOR), the major constituent of the herbal medicine Forsythia, has anti-inflammatory, anti-oxidant, and antiviral effects. FOR was demonstrated to have an antioxidant effect on PC12 cells. However, the effects of FOR on β-HB-stimulated bovine macrophages (BMs) has not been reported. Thus, the aim of the present study was to investigate the effects of FOR on β-HB-stimulated BMs. Firstly, the CCK8 test confirmed that FOR (50, 100, 200 μg/mL) has no effect on BMs activity, and we selected these concentrations for subsequent experiments. Secondly, through detecting the oxidation indexes ROS, MDA and antioxidant indexes CAT and SOD, we confirmed the antioxidant effect of FOR on BMs. Next, qRT-PCR confirmed that FOR dramatically reduced the mRNA levels of IL-1β and IL-6. Furthermore, the western blotting confirmed that FOR observably down-regulated β-HB-stimulated phosphorylation of p38, ERK and Akt and up-regulated expression of Nrf2, and HO-1. Above results suggested that FOR plays antioxidant effects on β-HB-induced BMs through p38, ERK and PI3K/Akt, Nrf2 and HO-1 signaling pathways. Therefore, we speculated that FOR may be a potential medicine to alleviate β-HB-induced inflammatory response and provide a preliminary reference for the research and development of FOR.

Natural Products Drug Discovery: On Silica or In-Silico?

Natural products have been the most important source for drug development throughout the human history. Over time, the formulation of drugs has evolved from crude drugs to refined chemicals. In modern drug discovery, conventional natural products lead-finding usually uses a top-down approach, namely bio-guided fractionation. In this approach, the crude extracts are separated by chromatography and resulting fractions are tested for activity. Subsequently, active fractions are further refined until a single active compound is obtained. However, this is a painstakingly slow and expensive process. Among the alternatives that have been developed to improve this situation, metabolomics has proved to yield interesting results having been applied successfully to drug discovery in the last two decades. The metabolomics-based approach in lead-finding comprises two steps: (1) in-depth chemical profiling of target samples, e.g. plant extracts, and bioactivity assessment, (2) correlation of the chemical and biological data by chemometrics. In the first step of this approach, the target samples are chemically profiled in an untargeted manner to detect as many compounds as possible. So far, NMR spectroscopy, LC-MS, GC-MS, and MS/MS spectrometry are the most common profiling tools. The profile data are correlated with the biological activity with the help of various chemometric methods such as multivariate data analysis. This in-silico analysis has a high potential to replace or complement conventional on-silica bioassay-guided fractionation as it will greatly reduce the number of bioassays, and thus time and costs. Moreover, it may reveal synergistic mechanisms, when present, something for which the classical top-down approach is clearly not suited. This chapter aims to give an overview of successful approaches based on the application of chemical profiling with chemometrics in natural products drug discovery.

Using omics approaches to dissect the therapeutic effects of Chinese herbal medicines on gastrointestinal cancers

Chinese herbal medicines offer a rich source of anti-cancer drugs. Differences between the pharmacology of Chinese herbal medicines and modern synthetic chemicals hinder the development of drugs derived from herbal products. To address this challenge, novel omics approaches including transcriptomics, proteomics, genomics, metabolomics, and microbiomics have been applied to dissect the pharmacological benefits of Chinese herbal medicines in cancer treatments. Numerous Chinese herbal medicines have shown potential anti-tumor effects on different gastrointestinal (GI) cancers while eliminating the side effects associated with conventional cancer therapies. The present study aimed to provide an overview of recent research focusing on Chinese herbal medicines in GI cancer treatment, based on omics approaches. This review also illustrates the potential utility of omics approaches in herbal-derived drug discovery. Omics approaches can precisely and efficiently reveal the key molecular targets and intracellular interaction networks of Chinese herbal medicines in GI cancer treatment. This study summarizes the application of different omics-based approaches in investigating the effects and mechanisms of Chinese herbal medicines in GI cancers. Future research directions are also proposed for this area of study.

Potential of Forsythoside I as a therapeutic approach for acute lung injury: Involvement of TXNIP/NLRP3 inflammasome

OBJECTIVE

To explore the role of Forsythoside I (FI) in acute lung injury (ALI) mouse and its underling mechanism.

METHODS

The cell models of ALI are constructed by LPS induction. After pretreatment with different concentrations of FI, the lung injury is assessed by pathological changes of lung tissues and cell apoptosis. The cell viability, levels of pro-inflammatory cytokines, and the activation of TXNIP/NLRP3 pathway are inspected to investigate whether the effect of FI on inflammatory response is exerted by regulating the TXNIP/NLRP3 pathway.

RESULTS

LPS induces inflammatory cell infiltration, tissue necrosis and pulmonary interstitial edema of mouse tissues, and LPS increases the protein concentration and levels of pro-inflammatory factors in mouse BALF. Additionally, enhanced cell apoptotic level, increased W/D ratio and MPO activity, as well as suppressed SOD activity are observed in LPS-induced mouse models. Those inflammation response, oxidative stress and lung injury can be attenuated by FI (12.5 mg/kg, 25 mg/kg, 50 mg/kg) in a dose-dependent manner. Meanwhile, both in vitro and in vivo studies reveal that FI can lead to suppressed TXNIP expression and inactivated NLRP3 inflammasomes. TXNIP is an upstream target of NLRP3, and FI mitigates ALI by decreasing TXNIP to block NLRP3 inflammasomes.

CONCLUSION

FI protects against ALI through the mediation of TXNIP/NLRP3 inflammasome axis and therefore has a certain potential for ALI treatment.

Quality grade evaluation and the related research of Forsythia suspensa from different places on the market

Quality grade evaluation, content determination and antioxidant activity in vitro research of Forsythia suspensa and seeds from different places.

Lemna minor studies under various storage periods using extended-polarity extraction and metabolite non-target screening analysis

Plant metabolomic studies cover a broad band of compounds, including various functional groups with different polarities and other physiochemical properties. For this reason, specific optimized methods are needed in order to enable efficient and non-destructive extraction of molecules over a large range of LogD values. This study presents a simple and efficient extraction procedure for Lemna minor samples demonstrating polarity extension of the molecular range. The Lemna samples chosen were kept under the following storage conditions: 1) fresh, 2) stored for a few days at -80 °C, and 3) stored for 6 months at -80 °C. The samples were extracted using five specifically chosen solvents: 100 % ethanol, 100 % methanol (MeOH), acidic 90 % MeOH (MeOH-water-formic acid (FAC) (90:9.5:0.5, v/v/v), MeOH-water (50:50, v/v), and 100 % water. The final extraction procedure was conducted subject to three solvent conditions, and the subsequent polarity-extended analysis was applied for Lemna minor samples using RPLC-HILIC-ESI-TOF-MS. The extraction yield is in descending order (acidic 90 % MeOH), 50 % MeOH, 100 % water and 100 % MeOH. The results displayed significant molecular differences, both in the extracts investigated and in the fresh Lemna samples, compared to stored samples, in terms of the extraction yield and reducing contents as well as the number of features. The storage of Lemna minor resulted in changes to the fingerprint of its metabolites as the reducing contents increased. The comparisons enable a direct view of molecule characterizations, in terms of their polarity, molecular mass, and signal intensity. This parametric information would appear ideal for further statistical data analysis. Consequently, the extraction procedure and the analysis/data evaluation are highly suitable for the so-called extended-polarity non-target screening procedure.

Development of an LC-MS multivariate nontargeted methodology for differential analysis of the peptide profile of Asian hornet venom (Vespa velutina nigrithorax): application to the investigation of the impact of collection period variation

Insect venom is a highly complex mixture of bioactive compounds, containing proteins, peptides, and small molecules. Environmental factors can alter the venom composition and lead to intraspecific variation in its bioactivity properties. The investigation of discriminating compounds caused by variation impacts can be a key to manage sampling and explore the bioactive compounds. The present study reports the development of a peptidomic methodology based on UHPLC-ESI-QTOF-HRMS analysis followed by a nontargeted multivariate analysis to reveal the profile variance of Vespa velutina venom collected in different conditions. The reliability of the approach was enhanced by optimizing certain XCMS data processing parameters and determining the sample peak threshold to eliminate the interfering features. This approach demonstrated a good repeatability and a criterion coefficient of variation (CV) > 30% was set for deleting nonrepeatable features from the matrix. The methodology was then applied to investigate the impact of collection period variation. PCA and PLS-DA models were used and validated by cross-validation and permutation tests. A slight discrimination was found between winter and summer hornet venom in two successive years with 10 common discriminating compounds. Graphical abstract.

Metabolomics biotechnology, applications, and future trends: a systematic review

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed. Mass spectrometry-based metabolomics has been used in a variety of disease research areas. However, the deep research of metabolites remains a difficult and lengthy process. Fortunately, mass spectrometry is considered to be a universal tool with high specificity and sensitivity and is widely used around the world. Mass spectrometry technology has been applied to various basic disciplines, providing technical support for the discovery and identification of endogenous substances in living organisms. The combination of metabolomics and mass spectrometry is of great significance for the discovery and identification of metabolite biomarkers. The mass spectrometry tool could further improve and develop the exploratory research of the life sciences. This mini review discusses metabolomics biotechnology with a focus on recent applications of metabolomics as a powerful tool to elucidate metabolic disturbances and the related mechanisms of diseases.

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed.