PubMed

Sci Total Environ. 2024 Mar 26:172033. doi: 10.1016/j.scitotenv.2024.172033. Online ahead of print.ABSTRACTDecabromodiphenyl ether (BDE-209) is a common brominated flame retardant in electronic waste, and nano zero-valent iron (nZVI) is a new material in the field of environmental remediation. Little is known about how BDE-209 and nZVI combined exposure influences soil organisms. During the 28 days study, we determined the effects of single and combined exposures to BDE-209 and nZVI on the oxidative stress and metabolic response of earthworms (Eisenia fetida). On day 7, compared to CK, malondialdehyde (MDA) content increased in most combined exposure groups. To remove MDA and reactive oxygen species (ROS), superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities were induced in most combined exposure groups. On day 28, compared to CK, the activities of SOD and CAT were inhibited, while POD activity was significantly induced, indicating that POD plays an important role in scavenging ROS. Combined exposure to BDE-209 and nZVI significantly affected amino acid biosynthesis and metabolism, purine metabolism, and aminoacyl-tRNA biosynthesis pathways, interfered with energy metabolism, and aggravated oxidative stress in earthworms. These findings provide a basis for assessing the ecological impacts of using nZVI to remediate soils contaminated with BDE-209 from electronic waste.PMID:38547968 | DOI:10.1016/j.scitotenv.2024.172033

Cell Metab. 2024 Mar 23:S1550-4131(24)00082-2. doi: 10.1016/j.cmet.2024.03.003. Online ahead of print.ABSTRACTMetabolic dysfunction-associated fatty liver disease (MAFLD) has a global prevalence of about 25% and no approved therapy. Using metabolomic and proteomic analyses, we identified high expression of hepatic transketolase (TKT), a metabolic enzyme of the pentose phosphate pathway, in human and mouse MAFLD. Hyperinsulinemia promoted TKT expression through the insulin receptor-CCAAT/enhancer-binding protein alpha axis. Utilizing liver-specific TKT overexpression and knockout mouse models, we demonstrated that TKT was sufficient and required for MAFLD progression. Further metabolic flux analysis revealed that Tkt deletion increased hepatic inosine levels to activate the protein kinase A-cAMP response element binding protein cascade, promote phosphatidylcholine synthesis, and improve mitochondrial function. Moreover, insulin induced hepatic TKT to limit inosine-dependent mitochondrial activity. Importantly, N-acetylgalactosamine (GalNAc)-siRNA conjugates targeting hepatic TKT showed promising therapeutic effects on mouse MAFLD. Our study uncovers how hyperinsulinemia regulates TKT-orchestrated inosine metabolism and mitochondrial function and provides a novel therapeutic strategy for MAFLD prevention and treatment.PMID:38547864 | DOI:10.1016/j.cmet.2024.03.003

J Hazard Mater. 2024 Mar 20;470:134099. doi: 10.1016/j.jhazmat.2024.134099. Online ahead of print.ABSTRACTThe response of the meta-metabolome is rarely used to characterize the effects of contaminants on a whole community. Here, the meta-metabolomic fingerprints of biofilms were examined after 1, 3 and 7 days of exposure to five concentrations of cobalt (from background concentration to 1 × 10-5 M) in aquatic microcosms. The untargeted metabolomic data were processed using the DRomics tool to build dose-response models and to calculate benchmark-doses. This approach made it possible to use 100% of the chemical signal instead of being limited to the very few annotated metabolites (7%). These benchmark-doses were further aggregated into an empirical cumulative density function. A trend analysis of the untargeted meta-metabolomic feature dose-response curves after 7 days of exposure suggested the presence of a concentration range inducing defense responses between 1.7 × 10-9 and 2.7 × 10-6 M, and of a concentration range inducing damage responses from 2.7 × 10-6 M and above. This distinction was in good agreement with changes in the other biological parameters studied (biomass and chlorophyll content). This study demonstrated that the molecular defense and damage responses can be related to contaminant concentrations and represents a promising approach for environmental risk assessment of metals.PMID:38547754 | DOI:10.1016/j.jhazmat.2024.134099

Food Chem. 2024 Mar 21;448:139088. doi: 10.1016/j.foodchem.2024.139088. Online ahead of print.ABSTRACTThe duration of storage significantly influences the quality and market value of Qingzhuan tea (QZT). Herein, a high-resolution multiple reaction monitoring (MRMHR) quantitative method for markers of QZT storage year was developed. Quantitative data alongside multivariate analysis were employed to discriminate and predict the storage year of QZT. Furthermore, the content of the main biochemical ingredients, catechins and alkaloids, and free amino acids (FAA) were assessed for this purpose. The results show that targeted marker-based models exhibited superior discrimination and prediction performance among four datasets. The R2Xcum, R2Ycum and Q2cum of orthogonal projection to latent structure-discriminant analysis discrimination model were close to 1. The correlation coefficient (R2) and the root mean square error of prediction of the QZT storage year prediction model were 0.9906 and 0.63, respectively. This study provides valuable insights into tea storage quality and highlights the potential application of targeted markers in food quality evaluation.PMID:38547707 | DOI:10.1016/j.foodchem.2024.139088

J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Mar 26;1237:124101. doi: 10.1016/j.jchromb.2024.124101. Online ahead of print.ABSTRACTBACKGROUND: Vitamins are essential micronutrients that play key roles in many biological pathways associated with sepsis. The gut microbiome plays a pivotal role in the progression of sepsis and may contribute to the onset of multi-organ dysfunction syndrome (MODS). The aim of this study was to investigate the changes in serum vitamins, and their correlation with intestinal flora and metabolomic profiles in patients with sepsis.METHODS: The serum levels of vitamins were determined by Ultra Performance Liquid Chromatography (UPLC). 16S rRNA gene sequencing and Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) targeted metabolomics were used for microbiome and metabolome analysis.RESULTS: In the training cohort: After univariate, multivariate (OPLS-DA) and Spearman analyses, it was concluded that vitamin levels of 25 (OH) VD3 and (VD2 + VD3), as well as vitamins A and B9, differed significantly among healthy controls (HC), non-septic critical patients (NS), and sepsis patients (SS) (P < 0.05). The validation cohort confirmed the differential vitamin findings from the training cohort. Moreover, analyses of gut flora and metabolites in septic patients and healthy individuals revealed differential flora, metabolites, and metabolic pathways that were linked to alterations in serum vitamin levels. We found for the first time that vitamin B9 was negatively correlated with g_Sellimonas.CONCLUSION: Sepsis patients exhibited significantly lower levels of 25 (OH) VD3 and (VD2 + VD3), vitamins A and B9, which hold potential as predictive markers for sepsis prognosis. The changes in these vitamins may be associated with inflammatory factors, oxidative stress, and changes in gut flora.PMID:38547698 | DOI:10.1016/j.jchromb.2024.124101

Phytomedicine. 2024 Jan 26;128:155397. doi: 10.1016/j.phymed.2024.155397. Online ahead of print.ABSTRACTBACKGROUND: Acute lung injury (ALI) often leads to serious respiratory diseases with high incidence rates and mortality. For centuries, Xiebai San (XBS) has been a classical traditional Chinese medicine (TCM) about respiratory illness such as pneumonia in children. However, the related mechanism of XBS against ALI remains indistinct.PURPOSE: To reveal specific targets of XBS in lipopolysaccharide (LPS)-induced ALI mice using integrated pharmacology.STUDY DESIGN: The integrated method was to expound mechanism and targets of XBS inhibited ALI.METHODS: The primary components in XBS were identified by ultra high performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS). The potential drug targets were established using network pharmacology. The anti-ALI effect of XBS was evaluated in mice. Additionally, therapeutic targets were screened by integrating metabolome and transcriptome and verified in lung tissue.RESULTS: In total, 163 chemical components were identified in XBS, and a network of "3 drugs-18 components-86 targets" for XBS against ALI was constructed. In ALI mice, XBS alleviated lung inflammation by decreasing permeation and expression of neutrophils, tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) in bronchoalveolar lavage fluid (BALF), serum, and lung tissue. Next, the transcriptome of lung tissue was analyzed and enriched, indicating the importance of mitogen-activated protein kinase (MAPK), Janus kinase-signal transducer and activator of transcription (JAK-STAT), and others, which was consistent with network pharmacology prediction. Also, western blotting and immunohistochemistry results showed that XBS was against ALI mainly by inhibiting extracellular signal regulated kinase (ERK) and signal transducer and activator of transcription 3 (Stat3) phosphorylation. In addition, the metabolome of lung tissue revealed that XBS mainly regulated pathways involved in arachidonic acid, glycerophospholipid, and tryptophan metabolisms. The expression levels of leukotriene, phosphatidylcholine, kynurenine, and others were also verified.CONCLUSION: XBS alleviated inflammation of ALI by inhibiting the phosphorylation of the ERK/Stat3 pathway and regulating arachidonic acid, glycerophospholipid, and tryptophan metabolisms. This study will guide clinical precision medicine and promote modernization of XBS.PMID:38547623 | DOI:10.1016/j.phymed.2024.155397

Phytomedicine. 2024 Jan 28;128:155396. doi: 10.1016/j.phymed.2024.155396. Online ahead of print.ABSTRACTBACKGROUND: Abnormalities in glucose metabolism may be the underlying cause of β-cell dysfunction and identity impairment resulting from high glucose exposure. In China, Coptis deltoidea C. Y. Cheng et Hsiao (YL) has demonstrated remarkable hypoglycemic effects.HYPOTHESIS/PURPOSE: To investigate the hypoglycemic effect of YL and determine the mechanism of YL in treating diabetes.METHODS: A type 2 diabetes mouse model was used to investigate the pharmacodynamics of YL. YL was administrated once daily for 8 weeks. The hypoglycemic effect of YL was assessed by fasting blood glucose, an oral glucose tolerance test, insulin levels, and other indexes. The underlying mechanism of YL was examined by targeting glucose metabolomics, western blotting, and qRT-PCR. Subsequently, the binding capacity between predicted AMP-activated protein kinase (AMPK) and important components of YL (Cop, Ber, and Epi) were validated by molecular docking and surface plasmon resonance. Then, in AMPK knockdown MIN6 cells, the mechanisms of Cop, Ber, and Epi were inversely confirmed through evaluations encompassing glucose-stimulated insulin secretion, markers indicative of β-cell identity, and the examination of glycolytic genes and products.RESULTS: YL (0.9 g/kg) treatment exerted notable hypoglycemic effects and protected the structural integrity and identity of pancreatic β-cells. Metabolomic analysis revealed that YL inhibited the hyperactivated glycolysis pathway in diabetic mice, thereby regulating the products of the tricarboxylic acid cycle. KEGG enrichment revealed the intimate relationship of this process with the AMPK signaling pathway. Cop, Ber, and Epi in YL displayed high binding affinities for AMPK protein. These compounds played a pivotal role in preserving the identity of pancreatic β-cells and amplifying insulin secretion. The mechanism underlying this process involved inhibition of glucose uptake, lowering intracellular lactate levels, and elevating acetyl coenzyme A and ATP levels through AMPK signaling. The use of a glycolytic inhibitor corroborated that attenuation of glycolysis restored β-cell identity and function.CONCLUSION: YL demonstrates significant hypoglycemic efficacy. We elucidated the potential mechanisms underlying the protective effects of YL and its active constituents on β-cell function and identity by observing glucose metabolism processes in pancreatic tissue and cells. In this intricate process, AMPK plays a pivotal regulatory role.PMID:38547617 | DOI:10.1016/j.phymed.2024.155396

Curr Opin Biotechnol. 2024 Mar 27;87:103115. doi: 10.1016/j.copbio.2024.103115. Online ahead of print.ABSTRACTWith the continuous increment in global population growth, compounded by post-pandemic food security challenges due to labor shortages, effects of climate change, political conflicts, limited land for agriculture, and carbon emissions control, addressing food production in a sustainable manner for future generations is critical. Microorganisms are potential alternative food sources that can help close the gap in food production. For the development of more efficient and yield-enhancing products, it is necessary to have a better understanding on the underlying regulatory molecular pathways of microbial growth. Nevertheless, as microbes are regulated at multiomics scales, current research focusing on single omics (genomics, proteomics, or metabolomics) independently is inadequate for optimizing growth and product output. Here, we discuss digital twin (DT) approaches that integrate systems biology and artificial intelligence in analyzing multiomics datasets to yield a microbial replica model for in silico testing before production. DT models can thus provide a holistic understanding of microbial growth, metabolite biosynthesis mechanisms, as well as identifying crucial production bottlenecks. Our argument, therefore, is to support the development of novel DT models that can potentially revolutionize microorganism-based alternative food production efficiency.PMID:38547588 | DOI:10.1016/j.copbio.2024.103115

J Breath Res. 2024 Mar 28. doi: 10.1088/1752-7163/ad38d5. Online ahead of print.ABSTRACTWe explored appropriate technical setups for the detection of volatile organic compounds (VOCs) from exhaled cow breath by comparing six different polymer-based solid-phase extraction (SPE) cartridges currently on the market for GC-MS screening. Exhaled breath was sampled at a single timepoint from five lactating dairy cows using six different SPE cartridges (Bond Elut ENV; Chromabond HRX; Chromabond HRP; Chromabond HLB; Chromabond HR-XCW and Chromabond HR-XAW). The trapped VOCs were analyzed by Dynamic Headspace Vacuum In-Tube Extraction gas chromatography/mass spectrometry (DHS-V-ITEX-GC-MS). Depending on the SPE cartridge, we detected 1174 to 1312 VOCs per cartridge. Most VOCs were alkenes, alkanes, esters, ketones, alcohols, aldehydes, amines, nitriles, ethers, amides, carboxylic acids, alkynes, azoles, terpenes, pyridines, or sulfur-containing compounds. The six SPE cartridges differed in their specificity for the chemical compounds, with the XAW cartridge showing the best specificity for ketones. The greatest differences between the tested SPE cartridges appeared in the detection of specific VOCs. In total, 176 different VOCs were detected with a match factor >80%. The greatest number of specific VOCs was captured by XAW (149), followed by ENV (118), HLB (117), HRP (115), HRX (114), and XCW (114)). We conclude that the tested SPE cartridges are suitable for VOC sampling from exhaled cow breath, but the SPE cartridge choice enormously affects the detected chemical groups and the number of detected VOCs. Therefore, an appropriate SPE adsorbent cartridge should be selected according to our proposed inclusion criteria. For targeted metabolomics approaches, the SPE cartridge choice depends on the VOCs or chemical compound groups of interest based on our provided VOC list. For untargeted approaches without information on the animals' metabolic condition, we suggest using multi-sorbent SPE cartridges or multiple cartridges per animal.PMID:38547532 | DOI:10.1088/1752-7163/ad38d5

Neurol Neuroimmunol Neuroinflamm. 2024 May;11(3):e200219. doi: 10.1212/NXI.0000000000200219. Epub 2024 Mar 28.ABSTRACTBACKGROUND AND OBJECTIVES: People with multiple sclerosis (MS) have a dysregulated circulating metabolome, but the metabolome of MS brain lesions has not been studied. The aims of this study were to identify differences in the brain tissue metabolome in MS compared with controls and to assess its association with the cellular profile of corresponding tissue.METHODS: MS tissues included samples from the edge and core of chronic active or inactive lesions and periplaque white matter (WM). Control specimens were obtained from normal WM. Metabolomic analysis was performed using mass-spectrometry coupled with liquid/gas chromatography and subsequently integrated with single-nucleus RNA-sequencing data by correlating metabolite abundances with relative cell counts, as well as individual genes using Multiomics Factor Analysis (MOFA).RESULTS: Seventeen samples from 5 people with secondary progressive MS and 8 samples from 6 controls underwent metabolomic profiling identifying 783 metabolites. MS lesions had higher levels of sphingosines (false discovery rate-adjusted p-value[q] = 2.88E-05) and sphingomyelins and ceramides (q = 2.15E-07), but lower nucleotide (q = 0.05), energy (q = 0.001), lysophospholipid (q = 1.86E-07), and monoacylglycerol (q = 0.04) metabolite levels compared with control WM. Periplaque WM had elevated sphingomyelins and ceramides (q = 0.05) and decreased energy metabolites (q = 0.01) and lysophospholipids (q = 0.05) compared with control WM. Sphingolipids and membrane lipid metabolites were positively correlated with astrocyte and immune cell abundances and negatively correlated with oligodendrocytes. On the other hand, long-chain fatty acid, endocannabinoid, and monoacylglycerol pathways were negatively correlated with astrocyte and immune cell populations and positively correlated with oligodendrocytes. MOFA demonstrated associations between differentially expressed metabolites and genes involved in myelination and lipid biosynthesis.DISCUSSION: MS lesions and perilesional WM demonstrated a significantly altered metabolome compared with control WM. Many of the altered metabolites were associated with altered cellular composition and gene expression, indicating an important role of lipid metabolism in chronic neuroinflammation in MS.PMID:38547430 | DOI:10.1212/NXI.0000000000200219

Nat Prod Res. 2024 Mar 28:1-8. doi: 10.1080/14786419.2024.2333049. Online ahead of print.ABSTRACTThe extract of the White Sea sponge Halichondria panicea (Pallas, 1766) exhibits cytotoxic and cytostatic effects. The main part of the extract consists of hydrophilic low molecular weight compounds: free amino acids (13.9%), glucose (19.9%), polyatomic alcohols (glycerin and others) (6.1%), carboxylic acids (0.7%) and nitrogenous heterocycles (1.2%). Of the substances specific to the metabolome, bicyclic diketopiperazines (four derivatives), pyroglutamic acid, phenylacetic acid, and two steroids (3β,5α)cholest-7-en-3-ol and dihydrocholesterol were identified. Toxicants characteristic of the genus Halichondria were not found in the White Sea sponge.PMID:38547385 | DOI:10.1080/14786419.2024.2333049

Am J Respir Cell Mol Biol. 2024 Mar 28. doi: 10.1165/rcmb.2024-0080PS. Online ahead of print.ABSTRACTIn recent years, metabolomics, the systematic study of small molecule metabolites in biological samples, has yielded fresh insights into the molecular determinants of pulmonary diseases and critical illness. The purpose of this article is to orient the reader to this emerging field by discussing the fundamental tenets underlying metabolomics research, the tools and techniques that serve as foundational methodologies, and the various statistical approaches to analysis of metabolomics datasets. We present several examples of metabolomics applied to pulmonary and critical care medicine in order to illustrate the potential of this avenue of research to deepen our understanding of pathophysiology. We conclude by reviewing recent advances in the field and future research directions that stand to further the goal of personalizing medicine in order to improve patient care.PMID:38547373 | DOI:10.1165/rcmb.2024-0080PS

Anal Chem. 2024 Mar 28. doi: 10.1021/acs.analchem.3c05659. Online ahead of print.ABSTRACTCharacterizing the profiles of proteome and metabolome at the single-cell level is of great significance in single-cell multiomic studies. Herein, we proposed a novel strategy called one-shot single-cell proteome and metabolome analysis (scPMA) to acquire the proteome and metabolome information in a single-cell individual in one injection of LC-MS/MS analysis. Based on the scPMA strategy, a total workflow was developed to achieve the single-cell capture, nanoliter-scale sample pretreatment, one-shot LC injection and separation of the enzyme-digested peptides and metabolites, and dual-zone MS/MS detection for proteome and metabolome profiling. Benefiting from the scPMA strategy, we realized dual-omic analysis of single tumor cells, including A549, HeLa, and HepG2 cells with 816, 578, and 293 protein groups and 72, 91, and 148 metabolites quantified on average. A single-cell perspective experiment for investigating the doxorubicin-induced antitumor effects in both the proteome and metabolome aspects was also performed.PMID:38547315 | DOI:10.1021/acs.analchem.3c05659

Science. 2024 Mar 29;383(6690):1484-1492. doi: 10.1126/science.adh2771. Epub 2024 Mar 28.ABSTRACTCellular purines, particularly adenosine 5'-triphosphate (ATP), fuel many metabolic reactions, but less is known about the direct effects of pyrimidines on cellular metabolism. We found that pyrimidines, but not purines, maintain pyruvate oxidation and the tricarboxylic citric acid (TCA) cycle by regulating pyruvate dehydrogenase (PDH) activity. PDH activity requires sufficient substrates and cofactors, including thiamine pyrophosphate (TPP). Depletion of cellular pyrimidines decreased TPP synthesis, a reaction carried out by TPP kinase 1 (TPK1), which reportedly uses ATP to phosphorylate thiamine (vitamin B1). We found that uridine 5'-triphosphate (UTP) acts as the preferred substrate for TPK1, enabling cellular TPP synthesis, PDH activity, TCA-cycle activity, lipogenesis, and adipocyte differentiation. Thus, UTP is required for vitamin B1 utilization to maintain pyruvate oxidation and lipogenesis.PMID:38547260 | DOI:10.1126/science.adh2771

Circ Res. 2024 Mar 29;134(7):855-857. doi: 10.1161/CIRCRESAHA.124.324333. Epub 2024 Mar 28.NO ABSTRACTPMID:38547248 | DOI:10.1161/CIRCRESAHA.124.324333

Circ Res. 2024 Mar 29;134(7):842-854. doi: 10.1161/CIRCRESAHA.123.323634. Epub 2024 Mar 28.ABSTRACTBACKGROUND: Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D).METHODS: This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years.RESULTS: We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, Butyrivibrio, Faecalibacterium) and enzymes involved in fiber degradation (eg, xylanase EC3.2.1.156) were positively associated with fiber intake, inversely associated with prevalent T2D, and favorably associated with T2D-related metabolic traits. We identified 159 metabolites associated with fiber intake, 47 of which were associated with incident T2D. We identified 18 of these 47 metabolites associated with the identified fiber-related bacteria, including several microbial metabolites (eg, indolepropionate and 3-phenylpropionate) inversely associated with the risk of T2D. Both Butyrivibrio and Faecalibacterium were associated with these favorable metabolites. The associations of fiber-related bacteria, especially Faecalibacterium and Butyrivibrio, with T2D were attenuated after further adjustment for these microbial metabolites.CONCLUSIONS: Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D.PMID:38547246 | DOI:10.1161/CIRCRESAHA.123.323634

PLoS One. 2024 Mar 28;19(3):e0301037. doi: 10.1371/journal.pone.0301037. eCollection 2024.ABSTRACTBACKGROUND: The favorable health-promoting adaptations to exercise result from cumulative responses to individual bouts of physical activity. Older adults often exhibit anabolic resistance; a phenomenon whereby the anabolic responses to exercise and nutrition are attenuated in skeletal muscle. The mechanisms contributing to age-related anabolic resistance are emerging, but our understanding of how chronological age influences responsiveness to exercise is incomplete. The objective was to determine the effects of healthy aging on peripheral blood metabolomic response to a single bout of resistance exercise and whether any metabolites in circulation are predictive of anabolic response in skeletal muscle.METHODS: Thirty young (20-35 years) and 49 older (65-85 years) men and women were studied in a cross-sectional manner. Participants completed a single bout of resistance exercise consisting of eight sets of 10 repetitions of unilateral knee extension at 70% of one-repetition maximum. Blood samples were collected before exercise, immediately post exercise, and 30-, 90-, and 180-minutes into recovery. Proton nuclear magnetic resonance spectroscopy was used to profile circulating metabolites at all timepoints. Serial muscle biopsies were collected for measuring muscle protein synthesis rates.RESULTS: Our analysis revealed that one bout of resistance exercise elicits significant changes in 26 of 33 measured plasma metabolites, reflecting alterations in several biological processes. Furthermore, 12 metabolites demonstrated significant interactions between exercise and age, including organic acids, amino acids, ketones, and keto-acids, which exhibited distinct responses to exercise in young and older adults. Pre-exercise histidine and sarcosine were negatively associated with muscle protein synthesis, as was the pre/post-exercise fold change in plasma histidine.CONCLUSIONS: This study demonstrates that while many exercise-responsive metabolites change similarly in young and older adults, several demonstrate age-dependent changes even in the absence of evidence of sarcopenia or frailty.TRIAL REGISTRATION: Clinical trial registry: ClinicalTrials.gov NCT03350906.PMID:38547208 | DOI:10.1371/journal.pone.0301037

Proc Natl Acad Sci U S A. 2024 Apr 2;121(14):e2317492121. doi: 10.1073/pnas.2317492121. Epub 2024 Mar 28.ABSTRACTEnergy metabolism is highly interdependent with adaptive cell migration in vivo. Mechanical confinement is a critical physical cue that induces switchable migration modes of the mesenchymal-to-amoeboid transition (MAT). However, the energy states in distinct migration modes, especially amoeboid-like stable bleb (A2) movement, remain unclear. In this report, we developed multivalent DNA framework-based nanomachines to explore strategical mitochondrial trafficking and differential ATP levels during cell migration in mechanically heterogeneous microenvironments. Through single-particle tracking and metabolomic analysis, we revealed that fast A2-moving cells driven by biomimetic confinement recruited back-end positioning of mitochondria for powering highly polarized cytoskeletal networks, preferentially adopting an energy-saving mode compared with a mesenchymal mode of cell migration. We present a versatile DNA nanotool for cellular energy exploration and highlight that adaptive energy strategies coordinately support switchable migration modes for facilitating efficient metastatic escape, offering a unique perspective for therapeutic interventions in cancer metastasis.PMID:38547056 | DOI:10.1073/pnas.2317492121

J Antimicrob Chemother. 2024 Mar 28:dkae083. doi: 10.1093/jac/dkae083. Online ahead of print.ABSTRACTINTRODUCTION: The DOLAM trial revealed that switching from triple antiretroviral therapy (three-drug regimen; 3DR) to dolutegravir plus lamivudine (two-drug regimen; 2DR) was virologically non-inferior to continuing 3DR after 48 weeks of follow-up. Weight increased with 2DR relative to 3DR but it did not impact on metabolic parameters.METHODS: Multiomics plasma profile was performed to gain further insight into whether this therapy switch might affect specific biological pathways. DOLAM (EudraCT 201500027435) is a Phase 4, randomized, open-label, non-inferiority trial in which virologically suppressed persons with HIV treated with 3DR were assigned (1:1) to switch to 2DR or to continue 3DR for 48 weeks. Untargeted proteomics, metabolomics and lipidomics analyses were performed at baseline and at 48 weeks. Univariate and multivariate analyses were performed to identify changes in key molecules between both therapy arms.RESULTS: Switching from 3DR to 2DR showed a multiomic impact on circulating plasma concentration of N-acetylmuramoyl-L-alanine amidase (Q96PD5), insulin-like growth factor-binding protein 3 (A6XND0), alanine and triglyceride (TG) (48:0). Correlation analyses identified an association among the up-regulation of these four molecules in persons treated with 2DR.CONCLUSIONS: Untargeted multiomics profiling studies identified molecular changes potentially associated with inflammation immune pathways, and with lipid and glucose metabolism. Although these changes could be associated with potential metabolic or cardiovascular consequences, their clinical significance remains uncertain. Further work is needed to confirm these findings and to assess their long-term clinical consequences.PMID:38546974 | DOI:10.1093/jac/dkae083

J Med Internet Res. 2024 Mar 28;26:e41065. doi: 10.2196/41065.ABSTRACTBACKGROUND: Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes.OBJECTIVE: This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors.METHODS: We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A1c, systolic blood pressure, and BMI.RESULTS: Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A1c, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR).CONCLUSIONS: This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.PMID:38546730 | DOI:10.2196/41065