PubMed

Metabolomics. 2024 Jun 28;20(4):67. doi: 10.1007/s11306-024-02130-1.ABSTRACTINTRODUCTION: Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma associated with Plasmodium falciparum and Epstein-Barr virus, both of which affect metabolic pathways. The metabolomic patterns of BL is unknown.MATERIALS AND METHODS: We measured 627 metabolites in pre-chemotherapy treatment plasma samples from 25 male children (6-11 years) with BL and 25 cancer-free area- and age-frequency-matched male controls from the Epidemiology of Burkitt Lymphoma in East African Children and Minors study in Uganda using liquid chromatography-tandem mass spectrometry. Unconditional, age-adjusted logistic regression analysis was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the BL association with 1-standard deviation increase in the log-metabolite concentration, adjusting for multiple comparisons using false discovery rate (FDR) thresholds and Bonferroni correction.RESULTS: Compared to controls, levels for 42 metabolite concentrations differed in BL cases (FDR < 0.001), including triacylglyceride (18:0_38:6), alpha-aminobutyric acid (AABA), ceramide (d18:1/20:0), phosphatidylcholine ae C40:6 and phosphatidylcholine C38:6 as the top signals associated with BL (ORs = 6.9 to 14.7, P < 2.4✕10- 4). Two metabolites (triacylglyceride (18:0_38:6) and AABA) selected using stepwise logistic regression discriminated BL cases from controls with an area under the curve of 0.97 (95% CI: 0.94, 1.00).CONCLUSION: Our findings warrant further examination of plasma metabolites as potential biomarkers for BL risk/diagnosis.PMID:38940866 | DOI:10.1007/s11306-024-02130-1

Arch Microbiol. 2024 Jun 28;206(7):329. doi: 10.1007/s00203-024-04058-5.ABSTRACTThe ability of cold-adapted bacteria to survive in extreme cold and diverse temperatures is due to their unique attributes like cell membrane stability, up-regulation of peptidoglycan biosynthesis, increased production of extracellular polymeric substances, and expansion of membrane pigment. Various cold-adapted proteins, including ice-nucleating proteins (INPs), antifreeze proteins (AFPs), cold shock proteins (Csps), and cold-acclimated proteins (CAPs), help the bacteria to survive in these environments. To sustain cells from extreme cold conditions and maintain stability in temperature fluctuations, survival strategies at the molecular level and their mechanism play significant roles in adaptations in cryospheric conditions. Furthermore, cold shock domains present in the multifunctional cold shock proteins play crucial roles in their adaptation strategies. The considerable contribution of lipopeptides, osmolytes, and membrane pigments plays an integral part in their survival in extreme environments. This review summarizes the evolutionary history of cold-adapted bacteria and their molecular and cellular adaptation strategies to thrive in harsh cold environments. It also discusses the importance of carotenoids produced, lipid composition, cryoprotectants, proteins, and chaperones related to this adaptation. Furthermore, the functions and mechanisms of adaptations within the cell are discussed briefly. One can utilize and explore their potential in various biotechnology applications and their evolutionary journey by knowing the inherent mechanism of their molecular and cellular adaptation to cold climatic conditions. This review will help all branches of the life science community understand the basic microbiology of psychrophiles and their hidden prospect in life science research.PMID:38940837 | DOI:10.1007/s00203-024-04058-5

Mass Spectrom Rev. 2024 Jun 28. doi: 10.1002/mas.21896. Online ahead of print.ABSTRACTDental caries, a prevalent global infectious condition affecting over 95% of adults, remains elusive in its precise etiology. Addressing the complex dynamics of caries demands a thorough exploration of taxonomic, potential, active, and encoded functions within the oral ecosystem. Metabolomic profiling emerges as a crucial tool, offering immediate insights into microecosystem physiology and linking directly to the phenotype. Identified metabolites, indicative of caries status, play a pivotal role in unraveling the metabolic processes underlying the disease. Despite challenges in metabolite variability, the use of metabolomics, particularly via mass spectrometry and nuclear magnetic resonance spectroscopy, holds promise in caries research. This review comprehensively examines metabolomics in caries prevention, diagnosis, and treatment, highlighting distinct metabolite expression patterns and their associations with disease-related bacterial communities. Pioneering in approach, it integrates singular and combinatory metabolomics methodologies, diverse biofluids, and study designs, critically evaluating prior limitations while offering expert insights for future investigations. By synthesizing existing knowledge, this review significantly advances our comprehension of caries, providing a foundation for improved prevention and treatment strategies.PMID:38940512 | DOI:10.1002/mas.21896

Skin Res Technol. 2024 Jul;30(7):e13792. doi: 10.1111/srt.13792.ABSTRACTBACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 15%-30% of children and 10% of adults globally, with its incidence being influenced by genetic, environmental, and various other factors. While the immune plays a crucial role in the development, the composition of gut microbiota and serum metabolites also contribute to its pathogenesis.SUBJECT: Study the characteristics of gut microbiota and serum metabolites in patients with atopic dermatitis METHOD: In this study, we collected stool and serum samples from 28 AD patients and 23 healthy individuals (NC) for metagenomic sequencing of gut microbiota and non-targeted metabolomic sequencing of serum.RESULT: Our results revealed a lower diversity of gut microbiota in the AD group compared to the NC group. The predominant Phylum in AD patients were Bacteroidetes, Pseudomonas, and Verrucomicrobia, with the most dominant bacterial genus being Faecalibacterium. At the species level, Prevotella copri and Faecalibacterium prausnitzii were found to be the most abundant bacteria. Significant differences in serum metabolite profiles were observed between NC and AD patients, with noticeable variations in metabolite expression levels. The majority of metabolites in the serum of AD patients exhibited low expression, while a few showed high expression levels. Notably, metabolites such as Cholesterol glucuronide, Styrene, Lutein, Betaine, Phosphorylcholine, Taurine, and Creatinine displayed the most pronounced alterations.CONCLUSION: These findings contribute to a further understanding of the complexities underlying this disease.PMID:38940462 | DOI:10.1111/srt.13792

J Extracell Biol. 2022 Nov 23;1(11):e66. doi: 10.1002/jex2.66. eCollection 2022 Nov.ABSTRACTPlasma extracellular vesicle (EV) number and composition are altered following myocardial infarction (MI), but to properly understand the significance of these changes it is essential to appreciate how the different isolation methods affect EV characteristics, proteome and sphingolipidome. Here, we compared plasma EV isolated from platelet-poor plasma from four healthy donors and six MI patients at presentation and 1-month post-MI using ultracentrifugation (UC), polyethylene glycol precipitation, acoustic trapping, size-exclusion chromatography (SEC) and immunoaffinity capture. The isolated EV were evaluated by Nanoparticle Tracking Analysis (NTA), Western blot, transmission electron microscopy (TEM), an EV-protein array, untargeted proteomics (LC-MS/MS) and targeted sphingolipidomics (LC-MS/MS). The application of the five different plasma EV isolation methods in patients presenting with MI showed that the choice of plasma EV isolation method influenced the ability to distinguish elevations in plasma EV concentration following MI, enrichment of EV-cargo (EV-proteins and sphingolipidomics) and associations with the size of the infarct determined by cardiac magnetic resonance imaging 6 months post-MI. Despite the selection bias imposed by each method, a core of EV-associated proteins and lipids was detectable using all approaches. However, this study highlights how each isolation method comes with its own idiosyncrasies and makes the comparison of data acquired by different techniques in clinical studies problematic.PMID:38939906 | PMC:PMC11080728 | DOI:10.1002/jex2.66

J Extracell Biol. 2024 Feb 22;3(2):e140. doi: 10.1002/jex2.140. eCollection 2024 Feb.ABSTRACTExtracellular vesicles (EVs) have been involved in metabolic syndrome, although their specific role in the development of the pathology is still unknown. To further study the role of EVs, we have analysed by Raman tweezers microspectroscopy and mass spectrometry-based lipidomics the small EVs population secreted by fatty (ZF) and lean (ZL) hepatocytes obtained from Zucker rats. We have also explored in vivo and ex vivo biodistribution of these EVs through fluorine-18-radiolabelling using a positron emission tomography imaging. Based on the proportion of proteins to lipids and the types of lipids, our results indicate that within the range of small EVs, primary hepatocytes secrete different subpopulations of particles. These differences were observed in the enrichment of triglyceride species in EVs secreted by ZF hepatocytes. Biodistribution experiments showed accumulation in the brain, heart, lungs, kidney and specially in bladder after intravenous administration. In summary, we show that EVs released by a fatty hepatocytes carry a different lipid signature compared to their lean counterpart. Biodistribution experiment has shown no difference in the distribution of EVs secreted by ZF and ZL hepatocytes but has given us a first view of possible target organs for these particles. Our results might open a door to both pathology studies and therapeutic interventions.PMID:38939902 | PMC:PMC11080883 | DOI:10.1002/jex2.140

J Extracell Biol. 2023 Mar 31;2(4):e76. doi: 10.1002/jex2.76. eCollection 2023 Apr.ABSTRACTThe standardization of clinical studies using extracellular vesicles (EVs) has mainly focused on the procedures employed for their isolation and characterization; however, preanalytical aspects of sample collection, handling and storage also significantly impact the reproducibility of results. We conducted an online survey based on SPREC (Standard PREanalytical Code) among members of GEIVEX (Grupo Español de Investigación en Vesiculas Extracelulares) to explore how different laboratories handled fluid biospecimens destined for EV analyses. We received 70 surveys from forty-three different laboratories: 44% focused on plasma, 9% on serum and 16% on urine. The survey indicated that variability in preanalytical approaches reaches 94%. Moreover, in some cases, researchers had no access to all relevant preanalytical details of samples, with some sample aspects with potential impact on EV isolation/characterisation not coded within the current version of SPREC. Our study highlights the importance of working with common standard operating procedures (SOP) to control preanalytical conditions. The application of SPREC represents a suitable approach to codify and register preanalytical conditions. Integrating SPREC into the SOPs of laboratories/biobanks will provide a valuable source of information and constitute an advance for EV research by improving reproducibility and credibility.PMID:38939690 | PMC:PMC11080825 | DOI:10.1002/jex2.76

JACC Adv. 2023 Jan 27;2(1):100174. doi: 10.1016/j.jacadv.2022.100174. eCollection 2023 Jan.ABSTRACTBACKGROUND: High-sensitivity cardiac troponin T (hs-cTnT) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are cardiac biomarkers commonly detected in adults with type 2 diabetes (T2D) and are associated with heart failure risk.OBJECTIVES: The purpose of this study was to evaluate the effects of exercise training (ET) on hs-cTnT and NT-proBNP and evaluate the associations of these biomarkers with cardiorespiratory fitness among adults with T2D.METHODS: Participants of the HART-D (Health Benefits of Aerobic and Resistance Training in Individuals with Type 2 Diabetes) trial who were randomly assigned to one of 3 ET groups or a non-exercise control group were included. Cardiac biomarkers and cardiorespiratory fitness (evaluated by peak oxygen uptake [VO2peak]) were assessed at baseline and after 9 months. The effects of ET (3 ET groups pooled) vs non-exercise control on hs-cTnT and NT-proBNP were assessed using separate analysis of covariance models. Multivariable-adjusted linear regression was performed to identify factors associated with follow-up biomarkers and ΔVO2peak.RESULTS: The present study included 166 participants randomized to the ET (n = 135) and non-exercise control (n = 31) groups. Compared with the non-exercise control, ET did not significantly change hs-cTnT or NT-proBNP. In adjusted analysis, each ET group and ΔVO2peak were not significantly associated with hs-cTnT or NT-proBNP levels on follow-up. Among individuals in the ET group, baseline hs-cTnT was inversely associated with ΔVO2peak [per 1 SD higher log (hs-cTnT): β = -0.08 (95% CI = -0.15 to -0.01)].CONCLUSIONS: Among individuals with T2D, ET did not modify cardiac biomarkers. Higher baseline hs-cTnT was associated with blunted cardiorespiratory fitness improvement in response to exercise.PMID:38939024 | PMC:PMC11198483 | DOI:10.1016/j.jacadv.2022.100174

JACC Adv. 2023 Jan 27;2(1):100170. doi: 10.1016/j.jacadv.2022.100170. eCollection 2023 Jan.NO ABSTRACTPMID:38939018 | PMC:PMC11198037 | DOI:10.1016/j.jacadv.2022.100170

J Extracell Biol. 2024 Apr 22;3(4):e149. doi: 10.1002/jex2.149. eCollection 2024 Apr.ABSTRACTIsolation of extracellular vesicles (EV) has been developing rapidly in parallel with the interest in EVs. However, commonly utilized protocols may not suit more challenging sample matrixes and could potentially yield suboptimal results. Knowing and assessing the pitfalls of isolation procedure to be used, should be involved to some extent for EV analytics. EVs in cow milk are of great interest due to their abundancy and large-scale availability as well as their cross-species bioavailability and possible use as drug carriers. However, the characteristics of milk EVs overlap with those of other milk components. This makes it difficult to isolate and study EVs individually. There exists also a lack of consensus for isolation methods. In this study, we demonstrated the differences between various differential centrifugation-based approaches for isolation of large quantities of EVs from cow milk. Samples were further purified with gradient centrifugation and size exclusion chromatography (SEC) and differences were analyzed. Quality measurements were conducted on multiple independent platforms. Particle analysis, electron microscopy and RNA analysis were used, to comprehensively characterize the isolated samples and to identify the limitations and possible sources of contamination in the EV isolation protocols. Vesicle concentration to protein ratio and RNA to protein ratios were observed to increase as samples were purified, suggesting co-isolation with major milk proteins in direct differential centrifugation protocols. We demonstrated a novel size assessment of vesicles using a particle mobility analyzer that matched the sizing using electron microscopy in contrast to commonly utilized nanoparticle tracking analysis. Based on the standards of the International Society for Extracellular Vesicles and the quick checklist of EV-Track.org for EV isolation, we emphasize the need for complete characterization and validation of the isolation protocol with all EV-related work to ensure the accuracy of results and allow further analytics and experiments.PMID:38938848 | PMC:PMC11080921 | DOI:10.1002/jex2.149

J Extracell Biol. 2022 Mar 15;1(2):e32. doi: 10.1002/jex2.32. eCollection 2022 Feb.ABSTRACTThe composition of extracellular vesicles (EVs) is altered in many pathological conditions, and their molecular content provides essential information on features of parent cells and mechanisms of crosstalk between cells and organs. Metabolic Syndrome (MetS) is a cluster of clinical manifestations including obesity, insulin resistance, dyslipidemia and hypertension that increases the risk of cardiovascular disease and type 2 diabetes mellitus. Here, we investigated the crosstalk between liver and adipocytes by characterizing EVs secreted by primary hepatocytes isolated from Zucker rat model, and studied the effect they have on 3T3-L1 adipocytes. We found that steatotic hepatocytes secrete EVs with significantly reduced exosomal markers in comparison with their lean counterpart. Moreover, proteomic analysis revealed that those EVs reflect the metabolic state of the parent cell in that the majority of proteins upregulated relate to fat metabolism, fatty acid synthesis, glycolysis, and pentose phosphate pathway. In addition, hepatocytes-secreted EVs influenced lipolysis and insulin sensitivity in recipient 3T3-L1 adipocytes. Untargeted metabolomic analysis detected alterations in different adipocyte metabolic pathways in cells treated with hepatic EVs. In summary, our work showed that steatosis has a significant impact in the amount and composition of EVs secreted by hepatocytes. Moreover, our data point to the involvement of hepatic-EVs in the development of pathologies associated with MetS.PMID:38938664 | PMC:PMC11080919 | DOI:10.1002/jex2.32

Front Plant Sci. 2024 Jun 13;15:1395046. doi: 10.3389/fpls.2024.1395046. eCollection 2024.ABSTRACTINTRODUCTION: Global warming has led to increased environmental stresses on plants, notably drought. This affects plant distribution and species adaptability, with some medicinal plants showing enhanced drought tolerance and increased medicinal components. In this pioneering study, we delve into the intricate tapestry of Arnebia guttata, a medicinal plant renowned for its resilience in arid environments. By fusing a rich historical narrative with cutting-edge analytical methodologies, this research endeavors to demystify the plant's intricate response to drought stress, illuminating its profound implications for medicinal valorization.METHODS: The methodology includes a comprehensive textual research and resource investigation of A. guttata, regionalization studies, field sample distribution analysis, transcriptome and metabolome profiling, rhizosphere soil microbiome analysis, and drought stress experiments. Advanced computational tools like ArcGIS, MaxEnt, and various bioinformatics software were utilized for data analysis and modeling.RESULTS: The study identified significant genetic variations among A. guttata samples from different regions, correlating with environmental factors, particularly precipitation during the warmest quarter (BIO18). Metabolomic analysis revealed marked differences in metabolite profiles, including shikonin content, which is crucial for the plant's medicinal properties. Soil microbial community analysis showed variations that could impact plant metabolism and stress response. Drought stress experiments demonstrated A. guttata's resilience and its ability to modulate metabolic pathways to enhance drought tolerance.DISCUSSION: The findings underscore the complex interplay between genetic makeup, environmental factors, and microbial communities in shaping A. guttata's adaptability and medicinal value. The study provides insights into how drought stress influences the synthesis of active compounds and suggests that moderate stress could enhance the plant's medicinal properties. Predictive modeling indicates future suitable growth areas for A. guttata, aiding in resource management and conservation efforts. The research contributes to the sustainable development of medicinal resources and offers strategies for improving the cultivation of A. guttata.PMID:38938629 | PMC:PMC11210590 | DOI:10.3389/fpls.2024.1395046

Front Psychiatry. 2024 Jun 13;15:1422939. doi: 10.3389/fpsyt.2024.1422939. eCollection 2024.ABSTRACTMajor depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.PMID:38938457 | PMC:PMC11210496 | DOI:10.3389/fpsyt.2024.1422939

J Extracell Biol. 2023 Apr 25;2(5):e84. doi: 10.1002/jex2.84. eCollection 2023 May.ABSTRACTContaminants within cell culture media often co-isolate with eukaryotic extracellular vesicles (EVs) thus affecting their biological properties. It has yet to be investigated if this is also true for bacterial EVs (BEVs), especially for organisms grown in complex culture media containing animal-derived products. To address this question, we isolated BEVs from the fastidious bacterium Helicobacter pylori grown in either standard Brain Heart Infusion (BHI) medium or BHI depleted of animal-derived products (D-BHI). We show that BEVs prepared from bacteria grown in D-BHI medium have similar morphologies, size ranges and yields to those prepared from standard medium. Similarly, no differences were found in the ability of H. pylori BEVs to induce IL-8 responses in epithelial cells. However, H. pylori BEVs prepared from D-BHI medium were of higher purity than those prepared from standard medium. Importantly, proteomic analyses detected 3.4-fold more H. pylori proteins and 10-fold fewer bovine-derived proteins in BEV samples prepared from D-BHI rather than the standard method. Fifty-seven H. pylori proteins were uniquely detected in BEV samples prepared from D-BHI. In conclusion, we have described an improved method for BEV isolation. Furthermore, we demonstrate how animal-derived products in bacteriological culture media may adversely affect proteomic analyses of BEVs.PMID:38938280 | PMC:PMC11080860 | DOI:10.1002/jex2.84

J Exp Bot. 2024 Jun 28:erae267. doi: 10.1093/jxb/erae267. Online ahead of print.ABSTRACTDue to technological advances in mass spectrometry, significant progress has been achieved recently in plant hormone research. Nowadays, plant hormonomics is well established as a fully integrated scientific field focused on the analysis of phytohormones, mainly on their isolation, identification and spatiotemporal quantification in plants. This review represents a comprehensive meta-study of the advances in the phytohormone analysis by mass spectrometry over the past decade. To address current trends and future perspectives, Web of Science data were systematically collected and key features such as mass spectrometry-based analyses were evaluated using multivariate data analysis methods. Our findings showed that plant hormonomics is currently divided into targeted and untargeted approaches. Both aim to miniaturize the sample, allowing high-resolution quantification to be covered in plant organs as well as subcellular compartments. Therefore, we can study plant hormone biosynthesis, metabolism and signalling at a spatio-temporal resolution. Moreover, this trend has recently been accelerated by technological advances such as fluorescence-activated cell sorting or mass spectrometry imaging.PMID:38938164 | DOI:10.1093/jxb/erae267

Drug Chem Toxicol. 2024 Jun 27:1-9. doi: 10.1080/01480545.2024.2369587. Online ahead of print.ABSTRACTCardiotoxicity is a well-established adverse effect of several drugs across multiple therapeutic indications. It is particularly prevalent following anticancer therapy. In order to evaluate the changes in cellular metabolism associated with methotrexate cardiotoxicity, we treated Wistar rats with a single high dose of methotrexate (HDMTX), and after five days, the animals were sacrificed. We then analyzed the cardiotoxicity parameters in serum like Cardiac enzymes(CK-MB, Troponin T, ALP), Inflammatory markers (TNF-α and IL-6), oxidative stress markers (NO, NOX-2), histopathology and cardiac tissue with the goal of identifying a metabolic signature of cardiotoxicity using discovery-based metabolomics. The biochemical parameters for cardiac enzymes, oxidative stress and inflammatory markers showed a significant increase in all three categories in rats treated with HDMTX. These findings were mirrored in the histopathological analysis confirming cardiotoxicity due to HDMTX. The results showed a total of 95 metabolites that were found to be significantly (p < 0.05) modulated: either up- or downregulated in the HDMTX-treated group when compared with the control group. Using integrated pathway analysis we found these metabolites were associated with many important cardiac tissue metabolic pathways, such as the malate aspartate shuttle, taurine and hypotaurine metabolism, betaine metabolism, spermidine biosynthesis, and homocysteine degradation. Among them, L-arginine, homocysteine, and betaine were significantly upregulated, suggesting their possible association with cardiac tissue injury. Overall, we provided evidence for using untargeted metabolomics to identify novel metabolites associated with HDMTX cardiac toxicity.PMID:38938090 | DOI:10.1080/01480545.2024.2369587

Mol Plant. 2024 Jun 26:S1674-2052(24)00193-X. doi: 10.1016/j.molp.2024.06.013. Online ahead of print.ABSTRACTSteroidal glycoalkaloids (SGAs) are specialized metabolites produced by hundreds of Solanum species, including important vegetable crops such as tomato, potato and eggplant. Though SGAs are better known for their role in defence in plants and 'anti-nutritional' effects (e.g., toxicity and bitterness) to humans, many of these molecules have documented anti-cancer, anti-microbial, anti-inflammatory, anti-viral and anti-pyretic activities. Among these, α-solasonine and α-solamargine isolated from black nightshade (Solanum nigrum), are reported to have potent anti-tumor, anti-proliferative and anti-inflammatory activities. Notably, α-solasonine and α-solamargine, along with the core steroidal aglycone solasodine are the most widespread SGAs produced among the Solanum plants. However, it is still unknown how plants synthesize these bioactive steroidal molecules. Through comparative metabolomic-transcriptome guided approach, biosynthetic logic, combinatorial expression in Nicotiana benthamiana and functional recombinant enzyme assays, here we report the discovery of 12 enzymes from S. nigrum that converts the staring cholesterol precursor to solasodine aglycone, and the downstream α-solasonine, α-solamargine and malonyl-solamargine SGA products. We further identified 6 enzymes from cultivated eggplant that catalyse the production of α-solasonine, α-solamargine and malonyl-solamargine SGAs from solasodine aglycone, via glycosylation and atypical malonylation decorations. Our work provides the gene tool box and platform for engineering the production of high value, steroidal bioactive molecules in heterologous hosts using synthetic biology.PMID:38937971 | DOI:10.1016/j.molp.2024.06.013

Lipids Health Dis. 2024 Jun 27;23(1):202. doi: 10.1186/s12944-024-02191-0.ABSTRACTBACKGROUND: Digestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear.METHODS: Using a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results.RESULTS: Significant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships.CONCLUSION: Our findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.PMID:38937739 | DOI:10.1186/s12944-024-02191-0

J Ethnopharmacol. 2024 Jun 25:118492. doi: 10.1016/j.jep.2024.118492. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Simiao Pills, a classical traditional Chinese medicine prescription recorded in Cheng Fang Bian Du, has been traditionally used to treat hyperuricemia due to its heat-clearing and diuretic properties. Studies have shown that Simiao Pills effectively reduce uric acid levels. However, further research is needed to elucidate the precise composition of Simiao Pills for treating hyperuricemia and their potential pharmacological mechanism.AIM OF THE STUDY: This study aimed to investigate the therapeutic effects of Simiao Pills on hyperuricemia, with a particular focus on evaluating their protective role against hyperuricemia-induced renal injury and elucidating the underlying mechanism of action.MATERIALS AND METHODS: UPLC-MS/MS was used to identify the components of Simiao Pills. The hyperuricemia model mice were established by intraperitoneal injecting potassium oxonate (PO) and oral administrating hypoxanthine (HX). Network pharmacology, transcriptome, and metabolomics analyses were integrated to explore the mechanism of Simiao Pills in reducing uric acid and protecting the kidney. Mechanistic and functional studies were conducted to validate the potential mechanisms.RESULTS: Simiao Pills were found to contain 12 characteristic components. Treatment with Simiao Pills significantly reduced serum uric acid levels and ameliorated hyperuricemia-induced renal injury. Simiao Pills inhibited the enzymatic activities of XOD and XDH, and regulated the uric acid transporters in the kidney and ileum. Transcriptome and network pharmacology analyses highlighted quercetin, berberine, kaempferol, and baicalein as the principal active components of Simiao Pills acting on the kidney during hyperuricemia treatment, primarily impacting fibrosis, apoptosis, and inflammation-related signaling pathways. Metabolomic analysis unveiled 21 differential metabolites and 5 metabolic pathways associated with Simiao Pills against renal injury associated with hyperuricemia. Further experimental results validated that Simiao Pills reduced renal fibrosis, apoptotic renal cells, serum inflammation levels, and inhibited the NF-κB/ NLRP3/IL-1β signaling pathway.CONCLUSION: This study demonstrated that Simiao Pills significantly reduced serum uric acid levels and improved renal injury by regulating inflammation, apoptosis, and renal fibrosis. These findings have provided a robust scientific pharmacological basis for the use of Simiao Pills in treating hyperuricemia patients.PMID:38936642 | DOI:10.1016/j.jep.2024.118492

Clin Chim Acta. 2024 Jun 25:119832. doi: 10.1016/j.cca.2024.119832. Online ahead of print.ABSTRACTBACKGROUND: Coronary atherosclerosis (CAS) is a prevalent and chronic life-threatening disease. However, the detection of CAS at an early stage is difficult because of the lack of effective noninvasive diagnostic methods. The present study aimed to characterize the plasma metabolome of early-stage CAS patients to discover metabolomic biomarkers, develop a novel metabolite-based model for accurate noninvasive diagnosis of early-stage CAS, and explore the underlying metabolic mechanisms involved.METHODS: A total of 100 patients with early-stage CAS and 120 age- and sex-matched control subjects were recruited from the Chinese Han population and further randomly divided into training (n = 120) and test sets (n = 100). The metabolomic profiles of the plasma samples were analyzed by an integrated untargeted liquid chromatography-mass spectrometry approach, including two separation modes and two ionization modes. Univariate and multivariate statistical analyses were employed to identify potential biomarkers and construct an early-stage CAS diagnostic model.RESULTS: The integrated analytical method established herein improved metabolite coverage compared with single chromatographic separation and MS ionization mode. A total of 80 metabolites were identified as potential biomarkers of early-stage CAS, and these metabolites were mainly involved in glycerophospholipid, fatty acid, sphingolipid, and amino acid metabolism. An effective diagnostic model for early-stage CAS was established, incorporating 11 metabolites and achieving areas under the receiver operating characteristic curve (AUCs) of 0.984 and 0.908 in the training and test sets, respectively.CONCLUSIONS: Our study not only successfully developed an effective noninvasive diagnostic model for identifying early-stage CAS but also provided novel insights into the pathogenesis of CAS.PMID:38936535 | DOI:10.1016/j.cca.2024.119832