A comprehensive strategy for studying protein-metabolite interactions by metabolomics and native mass spectrometry

Ion channels regulate energy homeostasis and the progression of metabolic disorders: Novel mechanisms and pharmacology of their modulators

The progression of metabolic diseases, featured by dysregulated metabolic signaling pathways, is orchestrated by numerous signaling networks. Among the regulators, ion channels transport ions across the membranes and trigger downstream signaling transduction. They critically regulate energy homeostasis and pathogenesis of metabolic diseases and are potential therapeutic targets for treating metabolic disorders. Ion channel blockers have been used to treat diabetes for decades by stimulating insulin secretion, yet with hypoglycemia and other adverse effects. It calls for deeper understanding of the largely elusive regulatory mechanisms, which facilitates the identification of new therapeutic targets and safe drugs against ion channels. In the article, we critically assess the two principal regulatory mechanisms, protein-channel interaction and post-translational modification on the activities of ion channels to modulate energy homeostasis and metabolic disorders through multiple novel mechanisms. Moreover, we discuss the multidisciplinary methods that provide the tools for elucidation of the regulatory mechanisms mediating metabolic disorders by ion channels. In terms of translational perspective, the mechanistic analysis of recently validated ion channels that regulate insulin resistance, body weight control, and adverse effects of current ion channel antagonists are discussed in details. Their small molecule modulators serve as promising new drug candidates to combat metabolic disorders.

Identifying of Anti-Thrombin Active Components From Curcumae Rhizoma by Affinity-Ultrafiltration Coupled With UPLC-Q-Exactive Orbitrap/MS

Recent studies concerning products that originate from natural plants have sought to clarify active ingredients, which both explains the mechanisms of the function and aids in quality control during production. As a traditional functional plant, Curcumae Rhizoma (CR) has been proven to be effective in promoting blood circulation and removing blood stasis. However, the components that play a role in its huge compound library are still unclear. The present study aimed to develop a high-throughput screening method to identify thrombin inhibitors in CR and validate them by in vitro and in vivo experiments. The effect of CR on thrombin in HUVECs cells was determined by ELISA, then an affinity-ultrafiltration-UPLC-Q-Exactive Orbitrap/MS approach was applied. Agatroban and adenosine were used as positive and negative drugs respectively to verify the reliability of the established method. The in vitro activity of the compounds was determined by specific substrate S-2238. The in vivo effect of the active ingredients was determined using zebrafish. Molecular docking was used to understand the internal interactions between compounds and enzymes. ELISA results showed that CR had an inhibitory effect on thrombin. The screening method established in this paper is reliable, by which a total of 15 active compounds were successfully identified. This study is the first to report that C7, 8, and 11 have in vitro thrombin-inhibitory activity and significantly inhibit thrombosis in zebrafish models at a safe dose. Molecular docking studies were employed to analyze the possible active binding sites, with the results suggesting that compound 16 is likely a better thrombin inhibitor compared with the other compounds. Based on the affinity-ultrafiltration-UPLC-Q-Exactive Orbitrap/MS approach, a precisely targeted therapy method using bio-active compounds from CR might be successfully established, which also provides a valuable reference for targeted therapy, mechanism exploration, and the quality control of traditional herbal medicine.

Plasma Lipidomics Identifies Unique Lipid Signatures and Potential Biomarkers for Patients With Aortic Dissection

Aortic dissection (AD) is a catastrophic cardiovascular emergency with a poor prognosis, and little preceding symptoms. Abnormal lipid metabolism is closely related to the pathogenesis of AD. However, comprehensive lipid alterations related to AD pathogenesis remain unclear. Moreover, there is an urgent need for new or better biomarkers for improved risk assessment and surveillance of AD. Therefore, an untargeted lipidomic approach based on ultra-high-performance liquid chromatograph-mass spectrometry was employed to unveil plasma lipidomic alterations and potential biomarkers for AD patients in this study. We found that 278 of 439 identified lipid species were significantly altered in AD patients (n = 35) compared to normal controls (n = 32). Notably, most lipid species, including fatty acids, acylcarnitines, cholesteryl ester, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylinositols, diacylglycerols, and triacylglycerols with total acyl chain carbon number ≥54 and/or total double bond number ≥4 were decreased, whereas phosphatidylethanolamines and triacylglycerols with total double bond number <4 accumulated in AD patients. Besides, the length and unsaturation of acyl chains in triacylglycerols and unsaturation of 1-acyl chain in phosphatidylethanolamines were decreased in AD patients. Moreover, lysophosphatidylcholines were the lipids with the largest alterations, at the center of correlation networks of lipid alterations, and had excellent performances in identifying AD patients. The area under the curve of 1.0 and accuracy rate of 100% could be easily obtained by lysophosphatidylcholine (20:0/0:0) or its combination with lysophosphatidylcholine (17:0/0:0) or lysophosphatidylcholine (20:1/0:0). This study provides novel and comprehensive plasma lipidomic signatures of AD patients, identifies lysophosphatidylcholines as excellent potential biomarkers, and would be beneficial to the pathogenetic study, risk assessment and timely diagnosis and treatment of AD.

Delivery of acetamiprid to tea leaves enabled by porous silica nanoparticles: efficiency, distribution and metabolism of acetamiprid in tea plants

BACKGROUND

Pesticide residue and its poor utilization remains problematic in agricultural development. To address the issue, a nano-pesticide has been developed by incorporating pesticide acetamiprid in porous silica nanoparticles.

RESULTS

This nano-pesticide had an acetamiprid loading content of 354.01 mg g^-1. Testing LC₅₀ value against tea aphids of the commercial preparation was three times that of the nano-pesticide. In tea seedlings (Camellia sinensis L.), acetamiprid was transported upward from the stem to the young leaves. On day 30, the average retained concentrations in tea leaves treated with the commercial preparation were about 1.3 times of that in the nano-pesticide preparation. The residual concentrations of dimethyl-acetamiprid in leaves for plants treated with the commercial preparation were about 1.1 times of that in the nano-pesticide preparation. Untargeted metabolomics of by LC-MS on the young leaves of tea seedlings under nano-pesticide and commercial pesticide treatments showed significant numbers of differentially expressed metabolites (P < 0.05 and VIP > 1). Between the nano-pesticide treatment group and the commercial preparation treatment group there were 196 differentially expressed metabolites 2 h after treatment, 200 (7^th day), 207 (21^st day), and 201 (30^th day) in negative ion mode, and 294 (2^nd h), 356 (7^th day), and 286 (30^th day) in positive ion mode. Preliminary identification showed that the major differentially expressed metabolites were glutamic acid, salicylic acid, p-coumaric acid, ribonic acid, glutamine, naringenin diglucoside, sanguiin H4, PG (34:2) and epiafzelechin.

CONCLUSIONS

This work demonstrated that our nano-pesticide outperformed the conventional pesticide acetamiprid in terms of insecticidal activity and pesticide residue, and the absorption, transportation and metabolism of nano-pesticide in tea plant were different, which pave a new pathway for pest control in agricultural sector.

Untargeted metabolomics of human plasma reveal lipid markers unique to chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

Chronic obstructive pulmonary disease (COPD) is characterised by airway inflammation and progressive airflow limitation, whereas idiopathic pulmonary fibrosis (IPF) is characterised by a restrictive pattern due to fibrosis and impaired gas exchange. We undertook metabolomic analysis of blood samples in IPF, COPD and healthy controls (HC) to determine differences in circulating molecules and identify novel pathogenic pathways. An untargeted metabolomics using an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS) was performed to profile plasma of patients with COPD (n = 21), and IPF (n = 24) in comparison to plasma from healthy controls (HC; n = 20). The most significant features were identified using multiple database matching. One-way ANOVA and variable importance in projection (VIP) scores were also used to highlight metabolites that influence the specific disease groups. Non-polar metabolites such as fatty acids (FA) and membrane lipids were well resolved and a total of 4805 features were identified. The most prominent metabolite composition differences in lipid mediators identified at ∼2-3 fold higher in both diseases compared to HC were palmitoleic acid, oleic acid and linoleic acid; and dihydrotestosterone was lower in both diseases. We demonstrated that COPD and IPF were characterised by systemic changes in lipid constituents such as essential FA sampled from circulating plasma.

Untargeted Defining Protein-Metabolites Interaction Based on Label-Free Kinetic Size Exclusion Chromatography-Mass Spectrometry

The specific interactions between protein and metabolites (PMIs) are closely related to many cellular processes and play a vital role in signal transduction and regulating material and energy metabolism. However, most of the available analytical strategies for PMIs involve chemical modification of metabolites or immobilization of protein, which has restricted current PMIs study mainly to lipid-protein and hydrophobic metabolites. In this work, a label-free online kinetic size exclusion chromatography-mass spectrometry (KSEC-MS) method combined with untargeted metabolomics was developed to define PMIs in a complex system. The metabolite mixture and target protein were injected into the SEC column sequentially without preincubation, and the separation results of KSEC were monitored by global metabolite profiling with mass spectrometry. The potential ligands in the metabolite mixture can be discovered if their migration patterns were affected by the target protein and the variation was positively correlated with the concentration of target protein. To verify this approach, carbonic anhydrase was first selected as a test protein, and acetazolamide as its known inhibitor was successfully defined. Furthermore, human serum albumin (HSA) as the common transport carrier of metabolites was selected as a target protein to demonstrate the usefulness of this approach. Multiple endogenous ligands of HSA were simultaneously defined from the extracted metabolites of human serum; most of them are polar metabolites rather than nonpolar lipids. This approach can provide a novel way for mapping and identifying unknown PMIs in a complex system, especially for polar metabolites-protein interactions.

Lipidomics Profile Changes of Type 2 Diabetes Mellitus with Acute Myocardial Infarction

The morbidity and mortality of cardiovascular disease (CVD)/acute myocardial infarction (AMI) of type 2 diabetes mellitus (T2DM) patients are extremely higher than those without T2DM. Biomarkers can be used to predict the occurrence of acute myocardial infarction, thus effectively reducing the incidence of CVD events, particularly in T2DM patients. Lipids have been shown to be biomarkers and potential therapeutic targets for human diseases. The aim of our study was to investigate the prognostic value of lipid biomarkers for predicting AMI in T2DM patients. A total of 420 subjects were recruited in this research. Liquid Chromatography-Electrospray Ionization-Quadrupole Time of Flight-Mass Spectrometer- (LC-ESI-QTOF-MS-) and Liquid Chromatography/Mass Spectrometer- (LC/MS-) based metabolomic methods were applied to characterize metabolic profiles in each plasma sample. In the first untargeted set, 40 T2DM patients with AMI, 40 T2DM patients without AMI, and 40 control subjects were gender- and age-matched. Eight lipid metabolites showed a significant difference among three groups. Then, in the second set, targeted metabolic profiling assays for these 8 lipid biomarker concentrations in plasma were performed; another 100 T2DM patients with AMI, 100 T2DM patients without AMI, and 100 control subjects were selected independently. Receiver operating characteristic (ROC) curves were constructed, and the area under the ROC curves (AUC) was calculated to determine the potential biomarkers. ROC curve analysis showed that the AUC value of lysophosphatidylcholine (LysoPC) 18:0 is more than 0.7, indicating that LysoPC 18:0 may be a potential sensitive and specific biomarker for T2DM with AMI. The changed plasma concentrations of lipids were significantly associated with T2DM with AMI, which showed great value to be biomarkers, though it requires a prospective cohort study for further validation.

Metabolomics for a Millenniums-Old Crop: Tea Plant ( Camellia sinensis)

Tea cultivation and utilization dates back to antiquity. Today it is the most widely consumed beverage on earth due to its pleasant taste and several beneficial health properties attributed to specific metabolites. Metabolomics has a tremendous potential to correlate tea metabolites with taste and health properties in humans. Our review on the current application of metabolomics in the science of tea suggests that metabolomics is a promising frontier in the evaluation of tea quality, identification of functional genes responsible for key metabolites, investigation of their metabolic regulation, and pathway analysis in the tea plant. Furthermore, the challenges, possible solutions, and the prospects of metabolomics in tea science are reviewed.

Efficient ligand discovery from natural herbs by integrating virtual screening, affinity mass spectrometry and targeted metabolomics

Although natural herbs have been a rich source of compounds for drug discovery, identification of bioactive components from natural herbs suffers from low efficiency and prohibitive cost of the conventional bioassay-based screening platforms. Here we develop a new strategy that integrates virtual screening, affinity mass spectrometry (MS) and targeted metabolomics for efficient discovery of herb-derived ligands towards a specific protein target site. Herb-based virtual screening conveniently selects herbs of potential bioactivity whereas affinity MS combined with targeted metabolomics readily screens candidate compounds in a high-throughput manner. This new integrated approach was benchmarked on screening chemical ligands that target the hydrophobic pocket of the nucleoprotein (NP) of Ebola viruses for which no small molecule ligands have been reported. Seven compounds identified by this approach from the crude extracts of three natural herbs were all validated to bind to the NP target in pure ligand binding assays. Among them, three compounds isolated from Piper nigrum (HJ-1, HJ-4 and HJ-6) strongly promoted the formation of large NP oligomers and reduced the protein thermal stability. In addition, cooperative binding between these chemical ligands and an endogenous peptide ligand was observed, and molecular docking was employed to propose a possible mechanism. Taken together, we established a platform integrating in silico and experimental screening approaches for efficient discovery of herb-derived bioactive ligands especially towards non-enzyme protein targets.

Agonism activities of lyso-phosphatidylcholines (LPC) Ligands binding to peroxisome proliferator-activated receptor gamma (PPARγ)

PPARγ is an isoform of peroxisome proliferator-activated receptor (PPAR) belonging to a super family of nuclear receptors and is a primary target of the effective drug to treat the type II diabetes. The experiments found that Lyso-phosphatidylcholines (LPC) could bind to PPARγ, but the binding modes remain unknown. We used the Molecular Docking and Molecular Dynamic (MD) simulations to study the binding of four LPC ligands (LPC16:0, LPC18:0, LPC18:1-1 and LPC18:1-2) to PPARγ. The two-step MD simulations were employed to determine the final binding modes. The 20 ns MD simulations for four final LPC-PPARγ complexes were performed to analyze their structures, the binding key residues, and agonism activities. The results reveal that three LPC ligands (LPC16:0, LPC18:0 and LPC18:1-1) bind to Arm II and III regions of the Ligand Binding Domain (LBD) pocket, whereas they do not interact with Tyr473 of Helix 12 (H12). In contrast, LPC18:1-2 can form the hydrogen bonds with Tyr473 and bind into Arm I and II regions. Comparing with the paradigm systems of the full agonist (Rosiglitazone-PPARγ) and the partial agonist (MRL24-PPARγ), our results indicate that LPC16:0, LPC18:0 and LPC18:1-1 could be the potential partial agonists and LPC18:1-2 could be a full agonist. The in-depth analysis of the residue fluctuations and structure alignment confirm the present prediction of the LPC agonism activities.Communicated by Ramaswamy H. Sarma.