PubMed

Heliyon. 2023 Dec 13;10(1):e23628. doi: 10.1016/j.heliyon.2023.e23628. eCollection 2024 Jan 15.ABSTRACTTriple-negative breast cancer stands out as the most aggressive subtype of breast malignancy and is characterized by an unfavourable prognosis. Objective: This systematic review summarizes the insights gleaned from metabolomic analyses of individuals afflicted with this cancer variant. The overarching goal was to delineate the molecular alterations associated with triple-negative breast cancer, pinpointing potential therapeutic targets and novel biomarkers. Methods: We systematically searched for evidence using the PubMed database and followed the PRISMA and STARLITE guidelines. The search parameters were delimited to articles published within the last 13 years. Results: From an initial pool of 148 scrutinized articles, 17 studies involving 1686 participants were deemed eligible for inclusion. The current body of research shows a paucity of studies, and the available evidence presents conflicting outcomes. Notwithstanding, Pathway Enrichment Analysis identified the urea and glucose-alanine cycles as the most affected metabolic pathways, followed by arginine, proline, and aspartate metabolism. Conclusion: Future investigations need to focus on elucidating which of those metabolites and/or pathways might be reliable candidates for novel therapeutic interventions or reliable biomarkers for diagnosis and prognosis of this subtype of breast cancer.PMID:38187259 | PMC:PMC10770474 | DOI:10.1016/j.heliyon.2023.e23628

Heliyon. 2023 Dec 12;10(1):e23592. doi: 10.1016/j.heliyon.2023.e23592. eCollection 2024 Jan 15.ABSTRACTMicrogravity, in space travel and prolonged bed rest conditions, induces cardiovascular deconditioning along with skeletal muscle mass loss and weakness. The findings of microgravity research may also aid in the understanding and treatment of human health conditions on Earth such as muscle atrophy, and cardiovascular diseases. Due to the paucity of biomarkers and the unknown underlying mechanisms of cardiovascular and skeletal muscle deconditioning in these environments, there are insufficient diagnostic and preventative measures. In this study, we employed hindlimb unloading (HU) mouse model, which mimics astronauts in space and bedridden patients, to first evaluate cardiovascular and skeletal muscle function, followed by proteomics and metabolomics LC-MS/MS-based analysis using serum samples. Three weeks of unloading caused changes in the function of the cardiovascular system in c57/Bl6 mice, as seen by a decrease in mean arterial pressure and heart weight. Unloading for three weeks also changed skeletal muscle function, causing a loss in grip strength in HU mice and atrophy of skeletal muscle indicated by a reduction in muscle mass. These modifications were partially reversed by a two-week recovery period of reloading condition, emphasizing the significance of the recovery process. Proteomics analysis revealed 12 dysregulated proteins among the groups, such as phospholipid transfer protein, Carbonic anhydrase 3, Parvalbumin alpha, Major urinary protein 20 (Mup20), Thrombospondin-1, and Apolipoprotein C-IV. On the other hand, metabolomics analysis showed altered metabolites among the groups such as inosine, hypoxanthine, xanthosine, sphinganine, l-valine, 3,4-Dihydroxyphenylglycol, and l-Glutamic acid. The joint data analysis revealed that HU conditions mainly impacted pathways such as ABC transporters, complement and coagulation cascades, nitrogen metabolism, and purine metabolism. Overall, our results indicate that microgravity environment induces significant alterations in the function, proteins, and metabolites of these mice. These observations suggest the potential utilization of these proteins and metabolites as novel biomarkers for assessing and mitigating cardiovascular and skeletal muscle deconditioning associated with such conditions.PMID:38187258 | PMC:PMC10770503 | DOI:10.1016/j.heliyon.2023.e23592

Am J Cancer Res. 2023 Dec 15;13(12):5785-5804. eCollection 2023.ABSTRACTThe human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.PMID:38187050 | PMC:PMC10767327

Food Chem (Oxf). 2023 Dec 14;8:100187. doi: 10.1016/j.fochms.2023.100187. eCollection 2024 Jul 30.ABSTRACTThe synthetic pathways of some phenolics compounds in asparagus have been reported, however, the diversified phenolics compounds including their modification and transcription regulation remains unknown. Thus, multi-omics strategies were applied to detect the phenolics profiles, contents, and screen the key genes for phenolics biosynthesis and regulation in asparagus. A total of 437 compounds, among which 204 phenolics including 105 flavonoids and 82 phenolic acids were detected with fluctuated concentrations in roots (Rs), spears (Ss) and flowering twigs (Fs) of the both green and purple cultivars. Based on the detected phenolics profiles and contents correlated to the gene expressions of screened synthetic enzymes and regulatory TFs, a full phenolics synthetic pathway of asparagus was proposed for the first time, essential for future breeding of asparagus and scaled healthy phenolics production using synthetic biological strategies.PMID:38186632 | PMC:PMC10767369 | DOI:10.1016/j.fochms.2023.100187

Food Sci Biotechnol. 2023 Nov 20;33(1):91-101. doi: 10.1007/s10068-023-01467-y. eCollection 2024 Jan.ABSTRACTLicorice from Glycyrrhiza uralensis roots is used in foods and medicines. Although we are aware that licorice roots and leaves have distinct material compositions, the specific reasons for these differences remain unknown. Comparison of the metabolomes and transcriptomes between the leaves and roots revealed flavonoids and triterpenoid saponins were significantly different. Isoflavones were enriched in roots because of upregulation of genes encoding chalcone isomerase and flavone synthase, which are involved in isoflavone synthesis. Six triterpenoid saponins were significantly enriched only in the roots. The leaves did not accumulate glycyrrhetinic acid because of low expression levels of genes involved in its synthesis. A gene encoding a UDP glycosyltransferase, which likely catalyzes the key step in the transformation of glycyrrhetinic acid to glycyrrhizin, was screened. Our results provide information about the differences in flavonoid and triterpenoid synthesis between roots and leaves, and highlight targets for genetic engineering.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10068-023-01467-y.PMID:38186628 | PMC:PMC10767105 | DOI:10.1007/s10068-023-01467-y

Front Plant Sci. 2023 Dec 21;14:1319700. doi: 10.3389/fpls.2023.1319700. eCollection 2023.ABSTRACTTissue culture technology is the main method for the commercial propagation of blueberry plants, but blueberry plantlets grow slowly and have long growth cycles under in vitro propagation, resulting in low propagation efficiency. In addition, the long culturing time can also result in reduced nutrient content in the culture medium, and the accumulation of toxic and harmful substances that can lead to weak growth for the plantlets or browning and vitrification, which ultimately can seriously reduce the quality of the plantlets. Gamma-aminobutyric acid (GABA) is a four-carbon non-protein amino acid that can improve plant resistance to various stresses and promote plant growth, but the effects of its application and mechanism in tissue culture are still unclear. In this study, the effects of GABA on the growth of in vitro blueberry plantlets were analyzed following the treatment of the plantlets with GABA. In addition, the GABA-treated plantlets were also subjected to a comparative transcriptomic and metabolomic analysis. The exogenous application of GABA significantly promoted growth and improved the quality of the blueberry plantlets. In total, 2,626 differentially expressed genes (DEGs) and 377 differentially accumulated metabolites (DAMs) were detected by comparison of the control and GABA-treated plantlets. Most of the DEGs and DAMs were involved in carbohydrate metabolism and biosynthesis of secondary metabolites. The comprehensive analysis results indicated that GABA may promote the growth of blueberry plantlets by promoting carbon metabolism and nitrogen assimilation, as well as increasing the accumulation of secondary metabolites such as flavonoids, steroids and terpenes.PMID:38186593 | PMC:PMC10768180 | DOI:10.3389/fpls.2023.1319700

Front Plant Sci. 2023 Dec 19;14:1278745. doi: 10.3389/fpls.2023.1278745. eCollection 2023.ABSTRACTINTRODUCTION: In contrast to the dynamics observed in plant/pathogen interactions, endophytic fungi have the capacity to establish enduring associations within their hosts, leading to the development of a mutually beneficial relationship that relies on specialized chemical interactions. Research indicates that the presence of endophytic fungi has the ability to significantly modify the chemical makeup of the host organism. Our hypothesis proposes the existence of a reciprocal exchange of chemical signals between plants and fungi, facilitated by specialized chemical processes that could potentially manifest within the tissues of the host. This research aimed to precisely quantify the portion of the cumulative fungal endophytic community's metabolome detectable within host leaves, and tentatively evaluate its relevance to the host-endophyte interplay. The understory palm Astrocaryum sciophilum (Miq.) Pulle was used as a interesting host plant because of its notable resilience and prolonged life cycle, in a tropical ecosystem.METHOD: Using advanced metabolome characterization, including UHPLC-HRMS/MS and molecular networking, the study explored enriched metabolomes of both host leaves and 15 endophytic fungi. The intention was to capture a metabolomic "snapshot" of both host and endophytic community, to achieve a thorough and detailed analysis.RESULTS AND DISCUSSION: This approach yielded an extended MS-based molecular network, integrating diverse metadata for identifying host- and endophyte-derived metabolites. The exploration of such data (>24000 features in positive ionization mode) enabled effective metabolome comparison, yielding insights into cultivable endophyte chemodiversity and occurrence of common metabolites between the holobiont and its fungal communities. Surprisingly, a minor subset of features overlapped between host leaf and fungal samples despite significant plant metabolome enrichment. This indicated that fungal metabolic signatures produced in vitro remain sparingly detectable in the leaf. Several classes of primary metabolites were possibly shared. Specific fungal metabolites and/or compounds of their chemical classes were only occasionally discernible in the leaf, highlighting endophytes partial contribution to the overall holobiont metabolome. To our knowledge, the metabolomic study of a plant host and its microbiome has rarely been performed in such a comprehensive manner. The general analytical strategy proposed in this paper seems well-adapted for any study in the field of microbial- or microbiome-related MS and can be applied to most host-microbe interactions.PMID:38186589 | PMC:PMC10768666 | DOI:10.3389/fpls.2023.1278745

Anim Biosci. 2023 Dec 29. doi: 10.5713/ab.23.0308. Online ahead of print.ABSTRACTThe rumen microbiota plays a central role in the digestive process of ruminants. Its remarkable ability to break down complex plant fibers and proteins, converting them into essential organic compounds that provide animals with energy and nutrition. Research on rumen microbiota not only contributes to improving animal production performance and enhancing feed utilization efficiency but also holds the potential to reduce methane emission and environment impact. Nevertheless, studies on rumen microbiota face numerous challenges, including complexity, difficulties in cultivation, and obstacles in functional analysis. This review provides an overview of microbial species involved in the degradation of macromolecules, the fermentation processes, and methane production in the rumen, all based on cultivation methods. Additionally, the review introduces the applications, advantages, and limitations of emerging omics technologies such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics, in investigating the functionality of rumen microbiota. Finally, the article offers a forward-looking perspective on the new horizons and technologies in the field of rumen microbiota functional research. These emerging technologies, with continuous refinement and mutual complementation, have deepened our understanding of rumen microbiota functionality, thereby enabling effective manipulation of the rumen microbial community.PMID:38186256 | DOI:10.5713/ab.23.0308

Anim Biosci. 2023 Dec 29. doi: 10.5713/ab.23.0387. Online ahead of print.ABSTRACTAdvanced and innovative breeding and management of meat-producing animals are needed to address the global food security and sustainability challenges. Beef production is an important industry for securing animal protein resources in the world and meat quality significantly contributes to the economic values and human needs. Improvement of cattle feed efficiency has become an urgent task as it can lower the environmental burden of methane gas emissions and the reduce the consumption of human edible cereal grains. Cattle depend on their symbiotic microbiome and its activity in the rumen and gut to maintain growth and health. Recent developments in high-throughput omics analysis (metagenome, metatranscriptome, metabolome, metaproteome and so on) have made it possible to comprehensively analyze microbiome, hosts and their interactions and to define their roles in affecting cattle biology. In this review, we focus on the relationships among gut microbiome and beef meat quality, feed efficiency, methane emission as well as host genetics in beef cattle, aiming to determine the current knowledge gaps for the development of the strategies to improve the sustainability of beef production.PMID:38186252 | DOI:10.5713/ab.23.0387

Anal Chem. 2024 Jan 8. doi: 10.1021/acs.analchem.3c04618. Online ahead of print.ABSTRACTThe accuracy of the structural annotation of unidentified peaks obtained in metabolomic analysis using liquid chromatography/tandem mass spectrometry (LC/MS/MS) can be enhanced using retention time (RT) information as well as precursor and product ions. Unified-hydrophilic-interaction/anion-exchange liquid chromatography high-resolution tandem mass spectrometry (unified-HILIC/AEX/HRMS/MS) has been recently developed as an innovative method ideal for nontargeted polar metabolomics. However, the RT prediction for unified-HILIC/AEX has not been developed because of the complex separation mechanism characterized by the continuous transition of the separation modes from HILIC to AEX. In this study, we propose an RT prediction model of unified-HILIC/AEX/HRMS/MS, which enables the comprehensive structural annotation of polar metabolites. With training data for 203 polar metabolites, we ranked the feature importance using a random forest among 12,420 molecular descriptors (MDs) and constructed an RT prediction model with 26 selected MDs. The accuracy of the RT model was evaluated using test data for 51 polar metabolites, and 86.3% of the ΔRTs (difference between measured and predicted RTs) were within ±1.50 min, with a mean absolute error of 0.80 min, indicating high RT prediction accuracy. Nontargeted metabolomic data from the NIST SRM 1950-Metabolites in frozen human plasma were analyzed using the developed RT model and in silico MS/MS prediction, resulting in a successful structural estimation of 216 polar metabolites, in addition to the 62 identified based on standards. The proposed model can help accelerate the structural annotation of unknown hydrophilic metabolites, which is a key issue in metabolomic research.PMID:38186224 | DOI:10.1021/acs.analchem.3c04618

J Dent Res. 2024 Jan 7:220345231214195. doi: 10.1177/00220345231214195. Online ahead of print.ABSTRACTPeriodontitis has been emphasized as a risk factor of insulin resistance-related systemic diseases. Accumulating evidence has suggested a possible "oral-gut axis" linking oral infection and extraoral diseases, but it remains unclear whether periodontal pathogens can survive the barriers of the digestive tract and how they play their pathogenic roles. The present study established a periodontitis mouse model through oral ligature plus Porphyromonas gingivalis inoculation and demonstrated that periodontitis aggravated diet-induced obesity and insulin resistance, while also causing P. gingivalis enrichment in the intestine. Metabolic labeling strategy validated that P. gingivalis could translocate to the gastrointestinal tract in a viable state. Oral administration of living P. gingivalis elicited insulin resistance, while administration of pasteurized P. gingivalis had no such effect. Combination analysis of metagenome sequencing and nontargeted metabolomics suggested that the tryptophan metabolism pathway, specifically indole and its derivatives, was involved in the pathogenesis of insulin resistance caused by oral administration of living P. gingivalis. Moreover, liquid chromatography-high-resolution mass spectrometry analysis confirmed that the aryl hydrocarbon receptor (AhR) ligands, mainly indole acetic acid, tryptamine, and indole-3-aldehyde, were reduced in diet-induced obese mice with periodontitis, leading to inactivation of AhR signaling. Supplementation with Ficz (6-formylindolo (3,2-b) carbazole), an AhR agonist, alleviated periodontitis-associated insulin resistance, in which the restoration of gut barrier function might play an important role. Collectively, these findings reveal that the oral-gut translocation of viable P. gingivalis works as a fuel linking periodontitis and insulin resistance, in which reduction of AhR ligands and inactivation of AhR signaling are involved. This study provides novel insight into the role of the oral-gut axis in the pathogenesis of periodontitis-associated comorbidities.PMID:38185909 | DOI:10.1177/00220345231214195

BMC Plant Biol. 2024 Jan 8;24(1):34. doi: 10.1186/s12870-023-04712-y.ABSTRACTBACKGROUND: Drought stress can substantially restrict maize growth and productivity, and global warming and an increasing frequency of extreme weather events are likely to result in more yield losses in the future. Therefore, unraveling the molecular mechanism underlying the response to drought stress is essential for breeding drought-resilient crops.RESULTS: In this study, we subjected the 3-leaf-period plants of two maize inbred lines, a drought-tolerant line (si287) and a drought-sensitive line (X178), to drought stress for seven days while growing in a chamber. Subsequently, we measured physiological traits and analyzed transcriptomic and metabolic profiles of two inbred lines. Our KEGG analysis of genes and metabolites revealed significant differences in pathways related to glycolysis/gluconeogenesis, flavonoid biosynthesis, starch and sucrose metabolism, and biosynthesis of amino acids. Additionally, our joint analysis identified proline, tryptophan and phenylalanine are crucial amino acids for maize response to drought stress. Furthermore, we concentrated on tryptophan (Trp), which was found to enhance tolerance via IAA-ABA signaling, as well as SA and nicotinamide adenine dinucleotide (NAD) consequent reactive oxygen species (ROS) scavenging. We identified three hub genes in tryptophan biosynthesis, indole-3-acetaldehyde oxidase (ZmAO1, 542,228), catalase 1 (ZmCAT1, 542,369), and flavin-containing monooxygenase 6 (ZmYUC6, 103,629,142), High expression of these genes plays a significant role in regulating drought tolerance. Two metabolites related to tryptophan biosynthesis, quinolinic acid, and kynurenine improved maize tolerance to drought stress by scavenging reactive oxygen species.CONCLUSIONS: This study illuminates the mechanisms underlying the response of maize seedlings to drought stress. Especially, it identifies novel candidate genes and metabolites, enriching our understanding of the role of tryptophan in drought stress. The identification of distinct resistance mechanisms in maize inbred lines will facilitate the exploration of maize germplasm and the breeding of drought-resilient hybrids.PMID:38185653 | DOI:10.1186/s12870-023-04712-y

Lipids Health Dis. 2024 Jan 8;23(1):6. doi: 10.1186/s12944-023-01999-6.ABSTRACTBACKGROUND: Long-chain fatty acids (LCFAs) are involved in regulating multiple physiological processes as signalling molecules. Gas chromatography-mass spectrometry (GC-MS) is widely used to quantify LCFAs. However, current quantitative methods for LCFAs using GC-MS have demonstrated complicated issues. Psoriasis is a chronic inflammatory skin disease, and its pathogenesis may be related to the overproduction of interleukin-17A (IL-17A). Clinical efficacy of anti-IL-17A monoclonal antibody (mAb) treatment in psoriasis patients has been demonstrated. Recent studies suggest that LCFAs play varying roles in the pathogenesis of psoriasis. However, more comprehensive research is needed to illuminate the mechanism of LCFAs in psoriasis.METHODS: The established in situ derivatization method for analysing LCFAs with a GC-MS platform was utilized to conduct serum lipidomics analysis of healthy volunteers and psoriasis patients receiving pretherapy and posttreatment with of anti-IL-17A mAb. Imiquimod (IMQ)-treated wild type (WT) and T-cell receptor delta chain knock-out (Tcrd-/-) mice were used to investigate the correlation between IL-17A and abnormal changes in LCFAs in psoriasis patients.RESULTS: A rapid and sensitive in situ extraction derivatization method for quantifying LCFAs using GC-MS was established. Serum lipidomic results showed that psoriasis patients had higher levels of saturated fatty acids (SFAs) and ω-6 polyunsaturated fatty acids (PUFAs) but lower levels of monounsaturated fatty acids (MUFAs) and ω-3 PUFAs than healthy individuals, indicating impaired serum LCFA metabolism. Anti-IL-17A mAb treatment affected most of these LCFA changes. Analysis of LCFAs in IMQ-treated mice showed that LCFAs increased in the serum of WT mice, while there were no significant changes in the Tcrd-/- mice. SFAs increased in IMQ-treated WT mice, while MUFAs showed the opposite trend, and PUFAs did not change significantly.CONCLUSIONS: This study presented a dependable method for quantifying LCFAs that enhanced sensitivity and reduced analysis time. The lipidomic analysis results showed that anti-IL-17A mAb not only ameliorated skin lesions in psoriasis patients but also affected abnormal LCFAs metabolism. Furthermore, the study indicated a potential correlation between IL-17A and abnormal LCFA metabolism in psoriasis patients, which was supported by the alterations in serum LCFAs observed in IMQ-treated WT and Tcrd-/- mice.PMID:38185620 | DOI:10.1186/s12944-023-01999-6

Clin Chim Acta. 2024 Jan 5:117745. doi: 10.1016/j.cca.2023.117745. Online ahead of print.ABSTRACTBACKGROUND: It is difficult to distinguish type 2 myocardial infarction (T2MI) from type 1 myocardial infarction (T1MI), although their management varies.OBJECTIVES: Using optical coherence tomography (OCT) and pseudo-targeted metabolomics to identify biomarkers, investigate metabolic differences, and establish a T2MI subclassification.METHODS: Among 1519 patients with MI, 97 T2MI patients are identified who are 1:1 matched with 97 T1MI patients after considering age, gender, ST-segment elevation, time from onset to coronary angiography, and hs-cTnI on admission by propensity score matching. Plasma pseudo-targeted metabolomics at baseline was determined.RESULTS: The clinical characteristics of the two groups were comparable, while the T1MI showed more severe coronary lesions than T2MI according to OCT imaging. 90 differential metabolites were identified between the two groups, among 1027 endogenous metabolites in 20 classes. N-Acetyl-L-Leucine, free fatty acid (15:1), Thymidine-5'-triphosphate, Mevalonic acid 5-pyrophosphate, and five oligopeptides were candidate biomarkers (AUC≥0.85) distinguishing T2MI from T1MI. 12 KEGG pathways showed significant differences, mainly involving amino acid, nucleotide, and their derivatives metabolism, and signaling pathways such as mTOR, cGMP-PKG, and cAMP. Other differences were observed in TCA cycle (P=0.08) and ROS (P=0.05). Proteolysis and coronary heart disease risk lipid level were lower in T2MI. T2MI had a decrease of differential abundance score in almost all the KEGG enrichment pathways. Furthermore, T2MI can be subdivided into three subtypes by hierarchical cluster analysis of AUCs with causes/triggers of T2MI.CONCLUSIONS: There are significant metabolic profile differences between T1MI and T2MI. Several candidate metabolic biomarkers can effectively distinguish the two groups.PMID:38185283 | DOI:10.1016/j.cca.2023.117745

EBioMedicine. 2024 Jan 6;100:104958. doi: 10.1016/j.ebiom.2023.104958. Online ahead of print.ABSTRACTBACKGROUND: The malignant childhood brain tumour, medulloblastoma, is classified clinically into molecular groups which guide therapy. DNA-methylation profiling is the current classification 'gold-standard', typically delivered 3-4 weeks post-surgery. Pre-surgery non-invasive diagnostics thus offer significant potential to improve early diagnosis and clinical management. Here, we determine tumour metabolite profiles of the four medulloblastoma groups, assess their diagnostic utility using tumour tissue and potential for non-invasive diagnosis using in vivo magnetic resonance spectroscopy (MRS).METHODS: Metabolite profiles were acquired by high-resolution magic-angle spinning NMR spectroscopy (MAS) from 86 medulloblastomas (from 59 male and 27 female patients), previously classified by DNA-methylation array (WNT (n = 9), SHH (n = 22), Group3 (n = 21), Group4 (n = 34)); RNA-seq data was available for sixty. Unsupervised class-discovery was performed and a support vector machine (SVM) constructed to assess diagnostic performance. The SVM classifier was adapted to use only metabolites (n = 10) routinely quantified from in vivo MRS data, and re-tested. Glutamate was assessed as a predictor of overall survival.FINDINGS: Group-specific metabolite profiles were identified; tumours clustered with good concordance to their reference molecular group (93%). GABA was only detected in WNT, taurine was low in SHH and lipids were high in Group3. The tissue-based metabolite SVM classifier had a cross-validated accuracy of 89% (100% for WNT) and, adapted to use metabolites routinely quantified in vivo, gave a combined classification accuracy of 90% for SHH, Group3 and Group4. Glutamate predicted survival after incorporating known risk-factors (HR = 3.39, 95% CI 1.4-8.1, p = 0.025).INTERPRETATION: Tissue metabolite profiles characterise medulloblastoma molecular groups. Their combination with machine learning can aid rapid diagnosis from tissue and potentially in vivo. Specific metabolites provide important information; GABA identifying WNT and glutamate conferring poor prognosis.FUNDING: Children with Cancer UK, Cancer Research UK, Children's Cancer North and a Newcastle University PhD studentship.PMID:38184938 | DOI:10.1016/j.ebiom.2023.104958

Biotechnol Bioeng. 2024 Jan 7. doi: 10.1002/bit.28653. Online ahead of print.ABSTRACTHepatic physiology depends on the liver's complex structural composition which among others, provides high oxygen supply rates, locally differential oxygen tension, endothelial paracrine signaling, as well as residual hemodynamic shear stress to resident hepatocytes. While functional improvements were shown by implementing these factors into hepatic culture systems, direct cause-effect relationships are often not well characterized-obfuscating their individual contribution in more complex microphysiological systems. By comparing increasingly complex hepatic in vitro culture systems that gradually implement these parameters, we investigate the influence of the cellular microenvironment to overall hepatic functionality in pharmacological applications. Here, hepatocytes were modulated in terms of oxygen tension and supplementation, endothelial coculture, and exposure to fluid shear stress delineated from oxygen influx. Results from transcriptomic and metabolomic evaluation indicate that particularly oxygen supply rates are critical to enhance cellular functionality-with cellular drug metabolism remaining comparable to physiological conditions after prolonged static culture. Endothelial signaling was found to be a major contributor to differential phenotype formation known as metabolic zonation, indicated by WNT pathway activity. Lastly, oxygen-delineated shear stress was identified to direct cellular fate towards increased hepatic plasticity and regenerative phenotypes at the cost of drug metabolic functionality - in line with regenerative effects observed in vivo. With these results, we provide a systematic evaluation of critical parameters and their impact in hepatic systems. Given their adherence to physiological effects in vivo, this highlights the importance of their implementation in biomimetic devices, such as organ-on-a-chip systems. Considering recent advances in basic liver biology, direct translation of physiological structures into in vitro models is a promising strategy to expand the capabilities of pharmacological models.PMID:38184801 | DOI:10.1002/bit.28653

Cardiovasc Diabetol. 2024 Jan 6;23(1):14. doi: 10.1186/s12933-023-02102-0.ABSTRACTOBJECTIVE: To delineate the metabolomic differences in plasma samples between patients with coronary artery disease (CAD) and those with concomitant CAD and type 2 diabetes mellitus (T2DM), and to pinpoint distinctive metabolites indicative of T2DM risk.METHOD: Plasma samples from CAD and CAD-T2DM patients across three centers underwent comprehensive metabolomic and lipidomic analyses. Multivariate logistic regression was employed to discern the relationship between the identified metabolites and T2DM risk. Characteristic metabolites' metabolic impacts were further probed through hepatocyte cellular experiments. Subsequent transcriptomic analyses elucidated the potential target sites explaining the metabolic actions of these metabolites.RESULTS: Metabolomic analysis revealed 192 and 95 significantly altered profiles in the discovery (FDR < 0.05) and validation (P < 0.05) cohorts, respectively, that were associated with T2DM risk in univariate logistic regression. Further multivariate regression analyses identified 22 characteristic metabolites consistently associated with T2DM risk in both cohorts. Notably, pipecolinic acid and L-pipecolic acid, lysine derivatives, exhibited negative association with CAD-T2DM and influenced cellular glucose metabolism in hepatocytes. Transcriptomic insights shed light on potential metabolic action sites of these metabolites.CONCLUSIONS: This research underscores the metabolic disparities between CAD and CAD-T2DM patients, spotlighting the protective attributes of pipecolinic acid and L-pipecolic acid. The comprehensive metabolomic and transcriptomic findings provide novel insights into the mechanism research, prophylaxis and treatment of comorbidity of CAD and T2DM.PMID:38184583 | DOI:10.1186/s12933-023-02102-0

Metabolism. 2024 Jan 4:155771. doi: 10.1016/j.metabol.2023.155771. Online ahead of print.ABSTRACTBACKGROUND: Hepatocellular carcinoma (HCC) continues to pose a significant health challenge and is often diagnosed at advanced stages. Metabolic reprogramming is a hallmark of many cancer types, including HCC and it involves alterations in various metabolic or nutrient-sensing pathways within liver cells to facilitate the rapid growth and progression of tumours. However, the role of STAT3-NFκB in metabolic reprogramming is still not clear.APPROACH AND RESULTS: Diethylnitrosamine (DEN) administered animals showed decreased body weight and elevated level of serum enzymes. Also, Transmission electron microscopy (TEM) analysis revealed ultrastructural alterations. Increased phosphorylated signal transducer and activator of transcription-3 (p-STAT3), phosphorylated nuclear factor kappa B (p-NFκβ), dynamin related protein 1 (Drp-1) and alpha-fetoprotein (AFP) expression enhance the carcinogenicity as revealed in immunohistochemistry (IHC). The enzyme-linked immunosorbent assay (ELISA) concentration of IL-6 was found to be elevated in time dependent manner both in blood serum and liver tissue. Moreover, immunoblot analysis showed increased level of p-STAT3, p-NFκβ and IL-6 stimulated the upregulation of mitophagy proteins such as Drp-1, Phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK-1). Meanwhile, downregulation of Poly [ADP-ribose] polymerase 1 (PARP-1) and cleaved caspase 3 suppresses apoptosis and enhanced expression of AFP supports tumorigenesis. The mRNA level of STAT3 and Drp-1 was also found to be significantly increased. Furthermore, we performed high-field 800 MHz Nuclear Magnetic Resonance (NMR) based tissue and serum metabolomics analysis to identify metabolic signatures associated with the progression of liver cancer. The metabolomics findings revealed aberrant metabolic alterations in liver tissue and serum of 75th and 105th days of intervention groups in comparison to control, 15th and 45th days of intervention groups. Tissue metabolomics analysis revealed the accumulation of succinate in the liver tissue samples, whereas, serum metabolomics analysis revealed significantly decreased circulatory levels of ketone bodies (such as 3-hydroxybutyrate, acetate, acetone, etc.) and membrane metabolites suggesting activated ketolysis in advanced stages of liver cancer.CONCLUSION: STAT3-NFκβ signaling axis has a significant role in mitochondrial dysfunction and metabolic alterations in the development of HCC.PMID:38184165 | DOI:10.1016/j.metabol.2023.155771

Neurobiol Dis. 2024 Jan 4:106402. doi: 10.1016/j.nbd.2024.106402. Online ahead of print.ABSTRACTSocial dominance is a universal phenomenon among grouped animals that profoundly affects survival, health, and reproductive success by determining access to resources, and exerting a powerful influence on subsequent behavior. However, the understanding of pain and anxiety comorbidities in dominant or subordinate animals suffering from chronic pain is not well-defined. Here, we provide evidence that subordinate mice are more susceptible to pain-induced anxiety compared to dominant mice. We propose that the gut microbiota may play a mediating role in this mechanism. Our findings demonstrate that transplantation of fecal microbiota from subordinate mice with chronic inflammatory pain, but not dominant mice, into antibiotics-treated pseudo-germ-free mice significantly amplifies anxiety-like phenotypes, highlighting the critical involvement of gut microbiota in this behavioral response. Using chronic inflammatory pain model, we carried out 16S rRNA sequencing and untargeted metabolomic analyses to explore the relationship between microbiota and metabolites in a stable social hierarchy of mice. Interestingly, anxiety-like behaviors were directly associated with some microbial genera and metabolites, especially bile acid metabolism. Overall, we have demonstrated a close relationship between social status and anxiety susceptibility, highlighting the contributions of gut microbiota and the associated metabolites in the high-anxiety state of subordinate mice with chronic inflammatory pain.PMID:38184015 | DOI:10.1016/j.nbd.2024.106402

J Hazard Mater. 2024 Jan 2;465:133417. doi: 10.1016/j.jhazmat.2023.133417. Online ahead of print.ABSTRACTThe widespread presence of soil microplastics (MPs) has become a global environmental problem. MPs of different properties (i.e., types, sizes, and concentrations) are present in the environment, while studies about the impact of MPs having different properties are limited. Thus, this study investigated the effects of three common polymers (polystyrene, polyethylene, and polypropylene) with two concentrations (0.01% and 0.1% w/w) on growth and stress response of lettuce (Lactuca sativa L.), soil enzymes, and rhizosphere microbial community. Lettuce growth was inhibited under MPs treatments. Moreover, the antioxidant system, metabolism composition, and phyllosphere microbiome of lettuce leaves was also perturbed. MPs reduced phytase activity and significantly increased dehydrogenase activity. The diversity and structure of rhizosphere microbial community were disturbed by MPs and more sensitive to polystyrene microplastics (PSMPs) and polypropylene microplastics (PPMPs). In general, the results by partial least squares pathway models (PLS-PMs) showed that the presence of MPs influenced the soil-rhizosphere-plant system, which may have essential implications for assessing the environmental risk of MPs.PMID:38183945 | DOI:10.1016/j.jhazmat.2023.133417