Small Molecule Metabolites Research Articles

Identifying biochemical constituents involved in the mycosynthesis of zinc oxide nanoparticles.

Filamentous fungi are known to secrete biochemicals that drive the synthesis of nanoparticles (NPs) that vary in composition, size, and shape; a process deemed mycosynthesis. Following the introduction of precursor salts directly to the fungal mycelia or their exudates, mycosynthesis proceeds at ambient temperature and pressure, and near neutral pH, presenting significant energy and cost savings over traditional chemical or physical approaches. The mycosynthesis of zinc oxide (ZnO) NPs by various fungi exhibited a species dependent morphological preference for the resulting NPs, suggesting that key differences in the biochemical makeup of their individual exudates may regulate the controlled nucleation and growth of these different morphologies. Metabolomics and proteomics of the various fungal exudates suggest that metal chelators, such as hexamethylenetetramine, present in high concentrations in exudates of Aspergillus versicolor are critical for the production dense, well-formed, spheroid nanoparticles. The results also corroborate that the proteinaceous material in the production of ZnO NPs serves as a surface modifier, or protein corona, preventing excessive coagulation of the NPs. Collectively, these findings suggest that NP morphology is regulated by the small molecule metabolites, and not proteins, present in fungal exudates, establishing a deeper understanding of the factors and mechanism underlying mycosynthesis of NPs.

Bacillus halotolerans attenuates inflammation induced by enterotoxigenic Escherichia coli infection in vivo and in vitro based on its metabolite soyasaponin I regulating the p105-Tpl2-ERK pathway.

Soyasaponins, recognized for their anti-inflammatory and antioxidant effects, have not yet been fully explored for their role in combating enterotoxigenic Escherichia coli (ETEC) infections. Recent findings identified them in small-molecule metabolites of Bacillus, suggesting their broader biological relevance. This research screened 88 strains of B. halotolerans, identifying the strain BH M20221856 as significantly inhibitory against ETEC growth in vitro. It also reduced cellular damage and inflammatory response in IPEC-J2 cells. The antimicrobial activity of BH M20221856 was attributed to its small-molecule metabolites rather than secretory proteins. A total of 69 small molecules were identified from the metabolites of BH M20221856 using liquid chromatography mass spectrometry/mass spectrometry (LC-MS/MS). Among these, soyasaponin I (SoSa I) represented the largest multiple change in the enrichment analysis of differential metabolites and exhibited potent anti-ETEC effects in vivo. It significantly reduced the bacterial load of E. coli in mouse intestines, decreased serum endotoxin, D-lactic acid, and oxidative stress levels and alleviated intestinal pathological damage and inflammation. SoSa I enhanced immune regulation by mediating the p105-Tpl2-ERK signaling pathway. Further evaluations using transepithelial electrical resistance (TEER) and cell permeability assays showed that SoSa I alleviated ETEC-induced damage to epithelial barrier function. These results suggest that BH M20221856 and SoSa I may serve as preventative biologics against ETEC infections, providing new insights for developing strategies to prevent and control this disease.

NMR metabolomics of plant and yeast-based hydrolysates for cell culture media applications — A comprehensive assessment

Cultivated meat products, generated by growing isolated skeletal muscle and fat tissue, offer the promise of a more sustainable and ethical alternative to traditional meat production. However, with cell culture media used to grow the cells accounting for 55–95% of the overall production cost, achieving true sustainability requires significant media optimization. One means of dealing with these high costs is the use of low-cost complex additives such as hydrolysates to provide a wide range of nutrients, from small molecules (metabolites) to growth factors and peptides. Despite their potential, most hydrolysate products remain poorly characterized and many are thought to suffer from persistent issues of high batch-to-batch variability. Although there have been a number of isolated efforts to determine metabolic profiles for a handful of hydrolysate products, we present the first attempt at a more comprehensive metabolomic characterization of nine different products (four plant and five yeast-based) from two to four different lots each.NMR analysis identified 90 unique metabolites, with only 15 metabolites common to all hydrolysate products (including eight of the nine essential amino acids), and 16 metabolites found in only a single hydrolysate product. The different hydrolysate products were found to have substantial differences in metabolite concentrations (as a fraction of overall mass), ranging from a high of 43% in yeast extract to a low of 14% in soy hydrolysates. The proportion of various metabolites also varied between products, with carbohydrate concentrations particularly high in soy hydrolysates and nucleosides more prominent in two of the yeast products. Overall, yeast extract generally had higher metabolite concentrations than all the other products, whereas both yeast extract and cotton had the largest variety of metabolites. A direct calculation of batch-to-batch variability revealed although there are significant differences between lots, these are largely driven by a relatively small fraction of compounds. This report will hopefully serve as a useful starting point for a more nuanced consideration of hydrolysate products in cell culture media optimization, both in the context of cultivated meat and beyond.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus.

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Reprogramming of arachidonic acid metabolism using α-terpineol to alleviate asthma: insights from metabolomics.

Asthma is a chronic inflammatory disorder in airways with typical pathologic features of airway inflammation and mucus hypersecretion. α-Terpineol is a monocyclic terpene found in many natural plants and foods. It has been reported to possess a wide range of pharmacological activities including anti-inflammatory and expectorant effects. However, the role of α-terpineol in asthma and its potential protective mechanism have not been well elucidated. This study is designed to investigate the pharmacological effect and mechanism of α-terpineol on asthmatic mice using the metabolomics platform. A murine model of asthma was established using ovalbumin (OVA) sensitization and then challenged for one week. The leukocyte count and inflammatory cytokines in the bronchoalveolar lavage fluid (BALF), lung histopathology, inflammatory infiltrate and mucus secretion were evaluated. An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based metabolomics study was performed on lung tissues and serum to explore endogenous small molecule metabolites affected by α-terpineol in asthmatic mice. After α-terpineol treatment, leukocyte count, inflammatory cytokines in the BALF, and peribronchial inflammation infiltration were significantly downregulated. Goblet cell hyperplasia and mucus secretion were attenuated, with the level of Muc5ac in BALF decreased. These results proved the protective effect of α-terpineol against airway inflammation, mucus hypersecretion and Th1/Th2 immune imbalance. To further investigate the underlying mechanisms of α-terpineol in asthma treatment, UPLC-MS/MS-based metabolomics analysis was performed. 26 and 15 identified significant differential metabolites were found in the lung tissues and serum of the control, model and α-terpineol groups, respectively. Based on the above differential metabolites, enrichment analysis showed that arachidonic acid (AA) metabolism was reprogrammed in both mouse lung tissues and serum. 5-Lipoxygenase (5-LOX) and cysteinyl leukotrienes (CysLTs) are the key enzyme and the end product of AA metabolism, respectively. In-depth studies have shown that pretreatment with α-terpineol can alleviate asthma by decreasing the AA level, downregulating the expression of 5-LOX and reducing the accumulation of CysLTs in mouse lung tissues. In summary, this study demonstrates that α-terpineol is a potential agent that can prevent asthma via regulating disordered AA metabolism.

Plasma amino acids pecularities and cardiometabolic risk factors in patients with coronary artery disease and atrial fibrillation

Studies targeting small molecule metabolites (amino acids, sugars, nucleotides, lipids) in connections with gut microbiota metabolites that impact the host metabolome give a possibility to define a special metabolic signature of different diseases. Plasma amino acids (AA) profile is known to be a new promising biomarker for the screening of coronary artery disease (CAD) pathogenesis connected with gut dysbiosis. The aim of our study was to estimate the spectrum of plasma amino acids in CAD patients with atrial fibrillation (AF) and to check their connections with the gut microbiota metabolites. 300 patients were divided into three groups: CAD – 149 patients with CAD but without arrhythmias, CAD+AF – 123 patients with CAD and AF paroxysm and control group– 28 patients without CAD and arrhythmias. Plasma AA level was detected by ion exchange liquid column chromatography. Significant changes in the content of plasma Glutamate, Glutamine, Glycine, Alanine, Valine and Tyrosine and combinations Isoleucine+Leucine/Valine, Glycine+Serine, Glycine/Methionine, Phenylalanine/Tyrosine, Glutamine/Glutamate in CAD+AF patients were detected. A strong reliable connection between plasma AA spectrum and gut microbiota metabolites trimethylamine, trimethylamine-N-oxide and total amount of fecal short chain fatty acids was determined. The highly validated plasma AA combinations Isoleucine – Glycine (area under ROC-curve 0.8122) and Phenylalanine – Glycine (area under ROC-curve 0.8061) that can be used as the early markers of AF paroxysm in CAD patients were proposed. Keywords: atrial fibrillation, cardiometabolic risk factors, coronary artery disease, gut microbiota metabolites, plasma amino acids

In silico identification and characterization of small molecule binding to the CD1d immunoreceptor

CD1 immunoreceptors are a non-classical major histocompatibility complex (MHC) that present antigens to T cells to elucidate immune responses against disease. The antigen repertoire of CD1 has been composed primarily of lipids until recently when CD1d-restricted T cells were shown to be activated by non-lipidic small molecules, such as phenyl pentamethyl dihydrobenzofuran sulfonate (PPBF) and related benzofuran sulfonates. To date structural insights into PPBF/CD1d interactions are lacking, so it is unknown whether small molecule and lipid antigens are presented and recognized through similar mechanisms. Furthermore, it is unknown whether CD1d can bind to and present a broader range of small molecule metabolites to T cells, acting out functions analogous to the MHC class I related protein MR1. Here, we perform in silico docking and molecular dynamics simulations to structurally characterize small molecule interactions with CD1d. PPBF was supported to be presented to T cell receptors through the CD1d F’ pocket. Virtual screening of CD1d against more than 17,000 small molecules with diverse geometry and chemistry identified several novel scaffolds, including phytosterols, cholesterols, triterpenes, and carbazole alkaloids, that serve as candidate CD1d antigens. Protein-ligand interaction profiling revealed conserved residues in the CD1d F’ pocket that similarly anchor small molecules and lipids. Our results suggest that CD1d could have the intrinsic ability to bind and present a broad range of small molecule metabolites to T cells to carry out its function beyond lipid antigen presentation. Communicated by Ramaswamy H. Sarma

Identification of characteristic flavor compounds and small molecule metabolites during the ripening process of Nuodeng ham by GC-IMS, GC–MS combined with metabolomics

To investigate effects of metabolites and volatile compounds on the quality of Nuodeng ham, gas chromatography-mass spectrometry (GC–MS), ultra-high performance liquid chromatography-Q exactive orbitrap-mass spectrometry (UHPLC-QE-MS), and gas chromatography-ion transfer spectroscopy (GC-IMS) were used to analyze the differences of free fatty acids, small molecule metabolites and volatile compounds of Nuodeng ham at different ripening stages (the first, second and third year sample). 40 free fatty acids were detected. 757 and 300 metabolites were detected in positive and negative ion modes, respectively. 48 differential metabolites (VIP ≥ 1.5, P < 0.05) might important components affecting flavor differences of Nuodeng ham. Metabolic pathways revealed that fermenting-ripening of ham was associated with 31 metabolic pathways, among, 19 pathways were significant (Impact > 0.01, P < 0.05). 58 volatile compounds were identified, combined with PCA and PLS-DA, 15 flavor markers were screened out. These findings provide a scientific basis for further research on the flavor formation mechanism of Nuodeng ham.

Spatial Distribution and Characterization of the Small-Molecule Metabolites and In Situ Hydrolyzed Oligosaccharides in the Rhizome of Glycyrrhiza uralensis by Desorption Electrospray Ionization-Mass Spectrometry Imaging and High-Resolution Liquid Chromatography-Mass Spectrometry.

Characterization and spatial distribution studies of the metabolome in plants are crucial for revealing the physiology of plants and developing functional foods. Using the rhizome of Glycyrrhiza uralensis as a case, we integrated desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) and high-resolution liquid chromatography/mass spectrometry approaches aimed at characterizing and locating both the small molecules and the macromolecular polysaccharides. Under the optimal conditions, 21 flavonoids and 12 triterpenoids were detected and characterized in different tissues of the rhizome and another 19 components were characterized exclusively by DESI-MSI. Combined with hydrophilic interaction chromatography/ion mobility-quadrupole time-of-flight mass spectrometry, eight different degrees of polymerization of oligosaccharides (after in situ acid hydrolysis) were characterized from the rhizome of G. uralensis. Majority of these metabolites are located in the cortex, phloem, and medulla, which lays the foundation for understanding the physiology of G. uralensis. The useful information can benefit the sustainable utilization and further development of Glycyrrhiza resource.

In vivo continuous monitoring of peptides and proteins: Challenges and opportunities

Fluctuations in the systemic concentration levels of metabolites, nutritionally relevant peptide hormones, protein biomarkers, and therapeutic materials provide a wealth of information that can be used to inform real-time clinical intervention. Thus, therapeutic outcomes for many disease states could be improved through the implementation of continuous monitoring systems. The most well-represented example of in vivo continuous monitoring of a small-molecule metabolite is the continuous glucose monitors used extensively in diabetes management. Unfortunately, to date, there is yet to be a marketed product that meets the engineering challenges or regulatory requirements for continuous sensing of peptides or proteins. A critical limitation of realizing this type of sensing is the limited availability of affinity-type biosensing elements, such as aptamers or antibodies. These molecules, while highly specific, have dissociation constants in the nano–picomolar range, which prevents reversibility between the biosensing element and analyte. In this review, several key challenges regarding the use of affinity-type biosensing elements to measure the concentration of peptides/proteins continuously in vivo are discussed. We discuss several examples of research groups working to overcome these limitations through specific engineering of biosensing elements, or by modulating the binding interaction itself using external energy. We then turn the discussion to insulin, a crucial therapeutic peptide for diabetes with the potential to enhance patient outcomes via continuous monitoring in vivo. This serves as a case study to explain why protein/peptide sensors currently suffer from translation. Finally, we summarize the current literature for insulin detection and discuss general translation toward in vivo continuous sensing of peptide/protein analytes.

Combating Obesity: Harnessing the Synergy of Postbiotics and Prebiotics for Enhanced Lipid Excretion and Microbiota Regulation

Obesity is a chronic metabolic disease that can be induced by a high-fat diet (HFD) and predisposes to a variety of complications. In recent years, various bioactive substances, such as probiotics, prebiotics, and postbiotics, have been widely discussed because of their good anti-lipid and anti-inflammatory activities. In this paper, soybean protein isolate was used as a substrate to prepare the postbiotic. Compound prebiotics (galactose oligosaccharides, fructose oligosaccharides, and lactitol) preparation Aunulife Postbiotics and Prebiotics Composition (AYS) is the research object. Weight loss and bowel movements in mice induced by a high-fat diet were studied. Moreover, qualitative and quantitative analyses of small-molecule metabolites in AYS were performed to identify the functional molecules in AYS. After 12 weeks of feeding, the weight gain of mice that were fed with high-dose AYS (group H) and low-dose AYS (group L) from 4 to 12 weeks was 6.72 g and 5.25 g (p &lt; 0.05), both of which were significantly lower than that of the high-fat diet (group DM, control group) group (7.73 g) (p &lt; 0.05). Serum biochemical analysis showed that TC, TG, and LDL-C levels were significantly lower in mice from the H and L groups (p &lt; 0.05). In addition, the fecal lipid content of mice in the L group reached 5.89%, which was significantly higher than that of the DM group at 4.02% (p &lt; 0.05). The study showed that AYS changed the structure of the intestinal microbiota in mice on a high-fat diet, resulting in a decrease in the relative abundance of Firmicutes and Muribaculaceae and an increase in the relative abundance of Bacteroidetes, Verrucomicrobia, and Lactobacillus. The metabolomics study results of AYS showed that carboxylic acids and derivatives, and organonitrogen compounds accounted for 51.51% of the AYS metabolites, among which pantothenate, stachyose, betaine, and citrate had the effect of preventing obesity in mice. In conclusion, the administration of prebiotics and postbiotic-rich AYS reduces weight gain and increases fecal lipid defecation in obese mice, potentially by regulating the intestinal microbiota of mice on a high-fat diet.

Mendelian randomization analysis to elucidate the causal relationship between small molecule metabolites and ovarian cancer risk

BackgroundSmall molecule metabolites are potential biomarkers for ovarian cancer. However, the causal relationship between small molecule metabolites and ovarian cancer remains unclear.MethodsSingle nucleotide polymorphisms (SNPs) correlated with 53 distinct small molecule metabolites were identified as instrumental variables (IVs) from comprehensive genome-wide association studies. Aggregate data encompassing 25,509 cases of ovarian cancer and 40,941 controls of European descent were procured from the Ovarian Cancer Association Consortium. To evaluate causative associations, four Mendelian randomization techniques—including inverse-variance weighted, weighted median, maximum likelihood, and MR-Egger regression—were employed.ResultsIn total, 242 SNPs were delineated as IVs for the small molecule metabolites under consideration. A significant association with the overarching risk of ovarian cancer was observed for six distinct metabolites. Hexadecenoylcarnitine and methioninesulfoxide were associated with a 32% and 31% reduced risk, respectively. Fifteen metabolites were linked to subtype ovarian cancers. For instance, both methionine sulfoxide and tetradecanoyl carnitine exhibited an inverse association with the risk of clear cell and high-grade serous ovarian cancers. Conversely, tryptophan demonstrated a 1.72-fold elevated risk for endometrioid ovarian cancer.ConclusionThis study identified several metabolites with putative causal effects on ovarian cancer risk using Mendelian randomization analysis. The findings provide insight into the etiological role of small molecule metabolites and highlight potential early detection biomarkers for ovarian cancer. Subsequent investigations are imperative to corroborate these findings and elucidate the underlying pathophysiological mechanisms.

Serum Metabolic Fingerprints Characterize Systemic Lupus Erythematosus.

Metabolic fingerprints in serum characterize diverse diseases for diagnostics and biomarker discovery. The identification of systemic lupus erythematosus (SLE) by serum metabolic fingerprints (SMFs) will facilitate precision medicine in SLE in an early and designed manner. Here, a discovery cohort of 731 individuals including 357 SLE patients and 374 healthy controls (HCs), and a validation cohort of 184 individuals (SLE/HC, 91/93) are constructed. Each SMF is directly recorded by nano-assisted laser desorption/ionization mass spectrometry (LDI MS) within 1 minute using 1µL of native serum, which contains 908 mass to charge features. Sparse learning of SMFs achieves the SLE identification with sensitivity/specificity and area-under-the-curve (AUC) up to 86.0%/92.0% and 0.950 for the discovery cohort. For the independent validation cohort, it exhibits no performance loss by affording the sensitivity/specificity and AUC of 89.0%/100.0% and 0.992. Notably, a metabolic biomarker panel is screened out from the SMFs, demonstrating the unique metabolic pattern of SLE patients different from both HCs and rheumatoid arthritis patients. In conclusion, SMFs characterize SLE by revealing its unique metabolic pattern. Different regulation of small molecule metabolites contributes to the precise diagnosis of autoimmune disease and further exploration of the pathogenic mechanisms.

The metabolic effects of intermittent versus continuous feeding in critically ill patients

Intermittent (or bolus) feeding regimens in critically ill patients have been of increasing interest to clinicians and scientists. Changes in amino acid, fat and carbohydrate metabolites over time might yet deliver other benefits (e.g. modulation of the circadian rhythm and sleep, and impacts on ghrelin secretion, insulin resistance and autophagy). We set out to characterise these changes in metabolite concentration. The Intermittent versus Continuous Feeding in Critically Ill paitents study (NCT02358512) was an eight-centre single-blinded randomised controlled trial. Patients were randomised to received a continuous (control arm) or intermittent (6x/day, intervention arm) enteral feeding regimen. Blood samples were taken on trial days 1, 7 and 10 immediately before and 30 min after intermittent feeds, and at equivalent timepoints in the control arm. A pre-planned targeted metabolomic analysis was performend using Nuclear Resonance Spectroscopy. Five hundred and ninety four samples were analysed from 75 patients. A total of 24 amino acid-, 19 lipid based-, and 44 small molecule metabolite features. Across the main two axes of variation (40–60% and 6–8% of variance), no broad patterns distinguished between intermittent or continuous feeding arms, across intra-day sampling times or over the 10 days from initial ICU admission. Logfold decreases in abundance were seen in metabolites related to amino acids (Glutamine − 0.682; Alanine − 0.594), ketone body metabolism (Acetone − 0.64; 3-Hydroxybutyric Acid − 0.632; Acetonacetic Acid − 0.586), fatty acid (carnitine − 0.509) and carbohydrate metabolism ( Maltose − 0.510; Citric Acid − 0.485). 2–3 Butanediol, a by-product of sugar-fermenting microbial metabolism also decreased (− 0.489). No correlation was seen with change in quadriceps muscle mass for any of the 20 metabolites varying with time (all p > 0.05). Increasing severity of organ failure was related to increasing ketone body metabolism (3 Hydroxybutyric Acid-1 and − 3; p = 0.056 and p = 0.014), carnitine deficiency (p = 0.002) and alanine abundancy (p − 0.005). A 6-times a day intermittent feeding regimen did not alter metabolite patterns across time compared to continuous feeding in critically ill patients, either within a 24 h period or across 10 days of intervention. Future research on intermittent feeding regimens should focus on clinical process benefits, or extended gut rest and fasting.

Plant Metabolomics: Current Initiatives and Future Prospects.

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants' physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.

Bacillus subtilis partially inhibits African swine fever virus infection in vivo and in vitro based on its metabolites arctiin and genistein interfering with the function of viral topoisomerase II.

African swine fever virus (ASFV) is a highly fatal swine disease that severely affects the pig industry. Although ASFV has been prevalent for more than 100 years, effective vaccines or antiviral strategies are still lacking. In this study, we identified four Bacillus subtilis strains that inhibited ASFV proliferation in vitro. Pigs fed with liquid biologics or powders derived from four B. subtilis strains mixed with pellet feed showed reduced morbidity and mortality when challenged with ASFV. Further analysis showed that the antiviral activity of B. subtilis was based on its metabolites arctiin and genistein interfering with the function of viral topoisomerase II. Our findings offer a promising new strategy for the prevention and control of ASFV that may significantly alleviate the economic losses in the pig industry.

Investigation of the active ingredients of Shuangshen Ningxin Fomula and the mechanism underlying their protective effects against myocardial ischemia-reperfusion injury by mass spectrometric imaging

BackgroundTraditional Chinese medicine, particularly Shuangshen Ningxin Capsule (SSNX), has been studied intensely. SSNX includes total ginseng saponins (from Panax ginseng Meyer), total phenolic acids from Salvia miltiorrhiza Bunge, and total alkaloids from Corydalis yanhusuo W. T. Wang. It has been suggested to protect against myocardial ischemia by a mechanism that has not been fully elucidated. MethodsThe composition and content of SSNX were determined by UHPLC-Q-TOFQ-TOF / MS. Then, a rat model of myocardial ischemia-reperfusion injury was established, and the protective effect of SSNX was measured. The protective mechanism was investigated using spatial metabolomics. ResultsWe found that SSNX significantly improved left ventricular function and ameliorated pathological damages in rats with myocardial ischemia-reperfusion injury. Using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), the protective mechanism of SSNX was examined by comparing the monomer components of drugs targeted in myocardial tissue with the distribution of myocardial energy metabolism-related molecules and phospholipids. Interestingly, some lipids display inconsistent content distribution in the myocardial ischemia risk and non-risk zones. These discrepancies reflect the degree of myocardial injury in different regions. ConclusionThese findings suggest that SSNX protects against myocardial ischemia-reperfusion injury by correcting abnormal myocardial energy metabolism, changing the levels and distribution patterns of phospholipids, and stabilizing the structure of the myocardial cell membrane. MALDI-TOF MS can detect the spatial distribution of small molecule metabolites in the myocardium and can be used in pharmacological research.

ATP-dependent transporters: emerging players at the crossroads of immunity and metabolism.

Nearly 50 ATP-binding cassette (ABC) transporters are encoded by mammalian genomes. These transporters are characterized by conserved nucleotide-binding and hydrolysis (i.e., ATPase) domains, and power directional transport of diverse substrate classes - ions, small molecule metabolites, xenobiotics, hydrophobic drugs, and even polypeptides - into or out of cells or subcellular organelles. Although immunological functions of ABC transporters are only beginning to be unraveled, emerging literature suggests these proteins have under-appreciated roles in the development and function of T lymphocytes, including many of the key effector, memory and regulatory subsets that arise during responses to infection, inflammation or cancers. One transporter in particular, MDR1 (Multidrug resistance-1; encoded by the ABCB1 locus in humans), has taken center stage as a novel player in immune regulation. Although MDR1 remains widely viewed as a simple drug efflux pump in tumor cells, recent evidence suggests that this transporter fills key endogenous roles in enforcing metabolic fitness of activated CD4 and CD8 T cells. Here, we summarize current understanding of the physiological functions of ABC transporters in immune regulation, with a focus on the anti-oxidant functions of MDR1 that may shape both the magnitude and repertoires of antigen-specific effector and memory T cell compartments. While much remains to be learned about the functions of ABC transporters in immunobiology, it is already clear that they represent fertile new ground, both for the definition of novel immunometabolic pathways, and for the discovery of new drug targets that could be leveraged to optimize immune responses to vaccines and cancer immunotherapies.

Surface-enhanced Raman database of 24 metabolites: Stable measurement of spectra, extraction and analysis of the main features

Surface-enhanced Raman spectroscopy (SERS) has been used in Raman-based metabolomics to provide abundant molecular fingerprint information in situ with extremely high sensitivity, without damaging the sample. However, poor reproducibility, caused by the randomness of the adsorption sites, and the short-range effect of SERS have hindered the development of SERS in metabolomics, resulting in very few SERS reference databases for small-molecule metabolites. In this work, our previously proposed large laser spot-swift mapping SERS method was adopted for the measurement of 24 commercially available metabolite standards, to provide reproducible and reliable references for Raman-based metabolomics study. Among these 24 metabolites, 22 contained no Raman data in PubChem. Other than the SERS spectra data, we extracted and explained the molecular vibration information of these metabolites, and combined with the density functional theory (DFT) calculations, we provided a new possibility for the fast Raman recognition of small-molecule metabolites. Accordingly, a large laser spot-swift mapping SERS database of metabolites in human serum was initially established, which contained not only the original spectral data but also other detailed feature information regarding the Raman peaks. With continuous accumulation, this database could play a promising role in Raman-based metabolomics and other Raman-related research.

Metabolomic studies for medicinal plant raw materials

Every year, medicinal plant raw materials are increasingly found in the production of medicines. Despite a number of positive properties of plants and raw materials obtained from them, there are also negative aspects of the introduction of native (natural) drugs. For example, biological active substances, their quantity and activity, depend on the season of the year and the climatic conditions of the region. These factors are highly variable, and correlations of biologically active substances with weather are difficult to predict. Thus, only with the help of modern analytical instruments and validated methods can it be possible to create statistically reliable algorithms for searching for biologically active substances.The polythematic abstract and bibliographic database has been analyzed. The main attention was paid to such scientometric databases as: Web of Science Core Collection, Medline, PubMed, RSCI, as well as data from the eLIBRARY.ru portal over the past 10 years. An assessment was made of the statistical data and publication activity of the authors regarding the request for metabolomics of medicinal plant raw materials in medicine and veterinary medicine.Metabolomic studies of medicinal plants aim to provide a complete and accurate study of all small molecule metabolites and complement other omics technologies such as genomics, transcriptomics and proteomics.Based on the literature reviewed, it can be concluded that there are two main approaches to collecting metabolomic data: targeted and untargeted analysis. Targeted and untargeted metabolomics analyzes are similar in sample collection, preparation, and chromatographic conditions (stationary phase and mobile phase). However, targeted metabolomics studies mainly focus on multiple metabolites from the same or different pathways.