PubMed

Front Nutr. 2024 Jan 24;11:1322201. doi: 10.3389/fnut.2024.1322201. eCollection 2024.ABSTRACTINTRODUCTION: Cognitive decline is a common consequence of aging. Dietary patterns that lack fibers and are high in saturated fats worsen cognitive impairment by triggering pro-inflammatory pathways and metabolic dysfunctions. Emerging evidence highlights the neurocognitive benefits of fiber-rich diets and the crucial role of gut-microbiome-brain signaling. However, the mechanisms of this diet-microbiome-brain regulation remain largely unclear.METHODS: Accordingly, we herein investigated the unexplored neuroprotective mechanisms of dietary pulses-derived resistant starch (RS) in improving aging-associated neurocognitive function in an aged (60-weeks old) murine model carrying a human microbiome.RESULTS AND DISCUSSION: Following 20-weeks dietary regimen which included a western-style diet without (control; CTL) or with 5% w/w fortification with RS from pinto beans (PTB), black-eyed-peas (BEP), lentils (LEN), chickpeas (CKP), or inulin fiber (INU), we find that RS, particularly from LEN, ameliorate the cognitive impairments induced by western diet. Mechanistically, RS-mediated improvements in neurocognitive assessments are attributed to positive remodeling of the gut microbiome-metabolome arrays, which include increased short-chain fatty acids and reduced branched-chain amino acids levels. This microbiome-metabolite-brain signaling cascade represses neuroinflammation, cellular senescence, and serum leptin/insulin levels, while enhancing lipid metabolism through improved hepatic function. Altogether, the data demonstrate the prebiotic effects of RS in improving neurocognitive function via modulating the gut-brain axis.PMID:38352704 | PMC:PMC10864001 | DOI:10.3389/fnut.2024.1322201

Front Plant Sci. 2024 Jan 30;15:1320705. doi: 10.3389/fpls.2024.1320705. eCollection 2024.ABSTRACTEndogenous metabolism is primarily responsible for losses in sucrose content and processing quality in postharvest sugarbeet roots. The genes responsible for this metabolism and the transcriptional changes that regulate it, however, are largely unknown. To identify genes and metabolic pathways that participate in postharvest sugarbeet root metabolism and the transcriptional changes that contribute to their regulation, transcriptomic and metabolomic profiles were generated for sugarbeet roots at harvest and after 12, 40 and 120 d storage at 5 and 12°C and gene expression and metabolite concentration changes related to storage duration or temperature were identified. During storage, 8656 genes, or 34% of all expressed genes, and 225 metabolites, equivalent to 59% of detected metabolites, were altered in expression or concentration, indicating extensive transcriptional and metabolic changes in stored roots. These genes and metabolites contributed to a wide range of cellular and molecular functions, with carbohydrate metabolism being the function to which the greatest number of genes and metabolites classified. Because respiration has a central role in postharvest metabolism and is largely responsible for sucrose loss in sugarbeet roots, genes and metabolites involved in and correlated to respiration were identified. Seventy-five genes participating in respiration were differentially expressed during storage, including two bidirectional sugar transporter SWEET17 genes that highly correlated with respiration rate. Weighted gene co-expression network analysis identified 1896 additional genes that positively correlated with respiration rate and predicted a pyruvate kinase gene to be a central regulator or biomarker for respiration rate. Overall, these results reveal the extensive and diverse physiological and metabolic changes that occur in stored sugarbeet roots and identify genes with potential roles as regulators or biomarkers for respiratory sucrose loss.PMID:38352647 | PMC:PMC10861796 | DOI:10.3389/fpls.2024.1320705

Res Sq. 2024 Feb 1:rs.3.rs-3914827. doi: 10.21203/rs.3.rs-3914827/v1. Preprint.ABSTRACTIon suppression is a major problem in mass spectrometry (MS)-based metabolomics; it can dramatically decrease measurement accuracy, precision, and signal-to-noise sensitivity. Here we report a new method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) plus novel companion algorithms to 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. We have evaluated the method across ion chromatography (IC), hydrophilic interaction liquid chromatography (HILIC), and reverse phase liquid chromatography (RPLC)-MS systems in both positive and negative ionization modes, with clean and unclean ion sources, and across different biological matrices. Across the broad range of conditions tested, all detected metabolites exhibited ion suppression ranging from 1% to 90+% and coefficient of variations ranging from 1% to 20%, but the Workflow and companion algorithms were highly effective at nulling out that suppression and error. Overall, the Workflow corrects ion suppression across diverse analytical conditions and produces robust normalization of non-targeted metabolomic data.PMID:38352620 | PMC:PMC10862963 | DOI:10.21203/rs.3.rs-3914827/v1

Nat Prod Rep. 2024 Feb 14. doi: 10.1039/d3np00050h. Online ahead of print.ABSTRACTCovering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry, have provided valuable molecular insights into the mechanisms of life. Non-targeted metabolomics aims to detect and (relatively) quantify all observable small molecules present in a biological system. By comparing small molecule abundances between different conditions or timepoints in a biological system, researchers can generate new hypotheses and begin to understand causes of observed phenotypes. Functional metabolomics aims to investigate the functional roles of metabolites at the scale of the metabolome. However, most functional metabolomics studies rely on indirect measurements and correlation analyses, which leads to ambiguity in the precise definition of functional metabolomics. In contrast, the field of natural products has a history of identifying the structures and bioactivities of primary and specialized metabolites. Here, we propose to expand and reframe functional metabolomics by integrating concepts from the fields of natural products and chemical biology. We highlight emerging functional metabolomics approaches that shift the focus from correlation to physical interactions, and we discuss how this allows researchers to uncover causal relationships between molecules and phenotypes.PMID:38351834 | DOI:10.1039/d3np00050h

Gut Microbes. 2024 Jan-Dec;16(1):2311888. doi: 10.1080/19490976.2024.2311888. Epub 2024 Feb 13.ABSTRACTPre-eclampsia (PE) is the most common complication of pregnancy and seriously threatens the health and safety of the mother and child. Studies have shown that an imbalance in gut microbiota can affect the progression of PE. Trimethylamine N-oxide (TMAO) is an intestinal microbiota-derived metabolite that is thought to be involved in the occurrence of PE; however, its causal relationship and mechanism remain unclear. In this clinical cohort study, including 28 patients with eclampsia and 39 matched healthy controls, fecal samples were collected for 16S rRNA gene sequencing, and serum was collected for targeted metabolomics research. The results showed that the level of TMAO and the abundance of its source bacteria had significantly increased in patients with PE, and were positively correlated with the clinical progression of PE. Fecal microbiota transplantation (FMT) was applied to an antibiotic-depleted-treated mouse model and targeted inhibition of TMAO. The results of the FMT experiment revealed that mice that received fecal microbiota transplantation from patients with PE developed typical PE symptoms and increased oxidative stress and inflammatory damage, both of which were reversed by 3,3-Dimethyl-1-butanol (DMB), a TMAO inhibitor, which also improved pregnancy outcomes in the model mice. Similar results were obtained in the classical NG-Nitroarginine methyl ester (L-NAME) induced PE mouse model. Mechanistically, TMAO promotes the progression of PE by regulating inflammatory and oxidative stress-related signaling pathways, affecting the migration and angiogenesis of vascular endothelial cells, as well as the migration and invasion of trophoblast cells. Our results reveal the role and mechanism of gut microbiota and TMAO in the progression of PE, provides new ideas for exploring the pathogenesis and therapeutic targets of PE, and determines the potential application value of TMAO as a target for PE intervention.PMID:38351748 | DOI:10.1080/19490976.2024.2311888

Curr Med Chem. 2024 Feb 13. doi: 10.2174/0109298673284520240112055108. Online ahead of print.ABSTRACTGastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics, transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances associated with various omics are concurrently altered during gastric cancer development. Furthermore, environmental exposures and family history can also induce modifications in endogenous substances. Therefore, in this study, we primarily investigated alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA, and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels in the context of GC development, employing genomics, transcriptomics, proteomics, and metabolomics. Additionally, we elucidate the impact of exposure factors, including HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and metabolomics; ii) the influence of environmental exposure and family history on multi- -omics data; iii) the integrated analysis of multi-omics data using machine learning techniques.PMID:38351697 | DOI:10.2174/0109298673284520240112055108

Plast Reconstr Surg. 2024 Feb 14. doi: 10.1097/PRS.0000000000011335. Online ahead of print.ABSTRACTBACKGROUND: Microfat and nanofat are two commonly used techniques in various surgical procedures from skin rejuvenation to scar correction that are known to contribute to tissue regeneration. While microfat mainly contains adipocytes and is well suited for tissue augmentation, nanofat is rich in lipids, adipose derived stem cells, microvascular fragments, and growth factors, making it attractive for esthetic use. We have previously demonstrated that the mechanical processing of microfat into nanofat significantly changes its proteomic profile. Considering that mechanical fractionation leads to adipocyte disruption and lipid release, we aimed to analyze the lipidomic profile for its regenerative properties.METHODS: Microfat and nanofat samples were isolated from fourteen healthy patients. Lipidomic profiling was performed by liquid chromatography tandem mass spectrometry. Resulting data was compared against the Human Metabolome and LIPID MAPS® Structure Database. Metaboanalyst was used to analyze metabolic pathways and lipids of interest.RESULTS: From 2,388 mass-to-charge ratio features, metabolic pathway enrichment analysis between microfat and nanofat samples revealed 109 pathways that were significantly enriched. While microfat samples revealed higher intensity levels of sphingosines, different eicosanoids and fat-soluble vitamins, increased levels of coumaric acids and prostacyclin were found in nanofat.CONCLUSIONS: This is the first study that has analyzed the lipidomic profile of micro- and nanofat, providing evidence that mechanical emulsification of microfat into nanofat leads to changes in their lipid profile. From 109 biological pathways, anti-inflammatory, anti-fibrotic and anti-melanogenic lipid mediators were particularly enriched in nanofat samples when compared to microfat. Although further studies are necessary to have a deeper understanding on the composition of these specific lipid mediators in nanofat samples, we propose that they might contribute to its regenerative effects on tissue.PMID:38351517 | DOI:10.1097/PRS.0000000000011335

AMB Express. 2024 Feb 13;14(1):21. doi: 10.1186/s13568-024-01680-w.ABSTRACTBlue light promotes primordium differentiation and fruiting body formation of mushroom. However, the blue light response mechanism of mushroom remains unclear. In this study, mycelium of Flammulina filiformis was exposed to blue light, red light and dark conditions, and then the comparative metabolome and transcriptome analysis was applied to explore metabolic regulation mechanism of F. filiformis under blue light and red light conditions. The yield of the fruiting body of F. filiformis under blue light condition was much higher than that under dark and red light conditions. Metabolome analysis showed that blue light treatment reduced the concentrations of many low molecular weight carbohydrates in the pilei, but it promoted the accumulation of some low molecular weight carbohydrates in the stipes. Blue light also decreased the accumulation of organic acids in the stipes. Blue light treatment reduced the levels of tyrosine and tryptophan in the stipes, but it largely promoted the accumulation of lysine in this organ. In the stipes of F. filiformis, blue light shifted metabolite flow to synthesis of lysine and carbohydrates through inhibiting the accumulation of aromatic amino acids and organic acids, thereby enhancing its nutritional and medicinal values. The transcriptome analysis displayed that blue light enhanced accumulation of lysine in fruiting body of F. filiformis through downregulation of lysine methyltransferase gene and L-lysine 6-monooxygenase gene. Additionally, in the stipes, blue light upregulated many hydrolase genes to improve the ability of the stipe to biodegrade the medium and elevated the growth rate of the fruiting body.PMID:38351413 | DOI:10.1186/s13568-024-01680-w

Sci Rep. 2024 Feb 13;14(1):3584. doi: 10.1038/s41598-024-54122-9.ABSTRACTLiver failure secondary to metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most common cause for liver transplantation in many parts of the world. Moreover, the prevalence of MASLD not only increases the demand for liver transplantation, but also limits the supply of suitable donor organs because steatosis predisposes grafts to ischemia-reperfusion injury (IRI). There are currently no pharmacological interventions to limit hepatic IRI because the mechanisms by which steatosis leads to increased injury are unclear. To identify potential novel mediators of IRI, we used liquid chromatography and mass spectrometry to assess temporal changes in the hepatic lipidome in steatotic and non-steatotic livers after warm IRI in mice. Our untargeted analyses revealed distinct differences between the steatotic and non-steatotic response to IRI and highlighted dynamic changes in lipid composition with marked changes in glycerophospholipids. These findings enhance our knowledge of the lipidomic changes that occur following IRI and provide a foundation for future mechanistic studies. A better understanding of the mechanisms underlying such changes will lead to novel therapeutic strategies to combat IRI.PMID:38351300 | PMC:PMC10864394 | DOI:10.1038/s41598-024-54122-9

Sci Rep. 2024 Feb 13;14(1):3626. doi: 10.1038/s41598-024-53929-w.ABSTRACTMental disorders are complex disorders influenced by multiple genetic, environmental, and biological factors. Specific microbiota imbalances seem to affect mental health status. However, the mechanisms by which microbiota disturbances impact the presence of depression, stress, anxiety, and eating disorders remain poorly understood. Currently, there are no robust biomarkers identified. We proposed a novel pyramid-layer design to accurately identify microbial/metabolomic signatures underlying mental disorders in the TwinsUK registry. Monozygotic and dizygotic twins discordant for mental disorders were screened, in a pairwise manner, for differentially abundant bacterial genera and circulating metabolites. In addition, multivariate analyses were performed, accounting for individual-level confounders. Our pyramid-layer study design allowed us to overcome the limitations of cross-sectional study designs with significant confounder effects and resulted in an association of the abundance of genus Parabacteroides with the diagnosis of mental disorders. Future research should explore the potential role of Parabacteroides as a mediator of mental health status. Our results indicate the potential role of the microbiome as a modifier in mental disorders that might contribute to the development of novel methodologies to assess personal risk and intervention strategies.PMID:38351227 | PMC:PMC10864280 | DOI:10.1038/s41598-024-53929-w

Sci Rep. 2024 Feb 13;14(1):3627. doi: 10.1038/s41598-024-54144-3.ABSTRACTThe study aimed to assess the metabolomic profile of the synovial fluid (SF) of dogs affected by spontaneous osteoarthritis (OA) and compare any differences based on disease progression. Sixty client-owned dogs affected by spontaneous OA underwent clinical, radiographic, and cytologic evaluations to confirm the diagnosis. The affected joints were divided into four study groups based on the Kallgreen-Lawrence classification: OA1 (mild), OA2 (moderate), OA3 (severe), and OA4 (extremely severe/deforming). The osteoarthritic joint's SF was subjected to cytologic examination and 1H-NMR analysis. The metabolomic profiles of the study groups' SF samples were statistically compared using one-way ANOVA. Sixty osteoarthritic joints (45 stifles, 10 shoulders and 5 elbows) were included in the study. Fourteen, 28, and 18 joints were included in the OA1, OA2, and OA3 groups, respectively (0 joints in the OA4 group). Metabolomic analysis identified 48 metabolites, five of which were significantly different between study groups: Mannose and betaine were elevated in the OA1 group compared with the OA2 group, and the 2-hydroxyisobutyrate concentration decreased with OA progression; in contrast, isoleucine was less concentrated in mild vs. moderate OA, and lactate increased in severe OA. This study identified different 1H-NMR metabolomic profiles of canine SF in patients with progressive degrees of spontaneous OA, suggesting 1H-NMR metabolomic analysis as a potential alternative method for monitoring OA progression. In addition, the results suggest the therapeutic potentials of the metabolomic pathways that involve mannose, betaine, 2-hydroxyisobutyrate, isoleucine, and lactate.PMID:38351089 | PMC:PMC10864333 | DOI:10.1038/s41598-024-54144-3

BMC Bioinformatics. 2024 Feb 14;25(1):69. doi: 10.1186/s12859-024-05679-9.ABSTRACTBACKGROUND: Technological advances have enabled the generation of unique and complementary types of data or views (e.g. genomics, proteomics, metabolomics) and opened up a new era in multiview learning research with the potential to lead to new biomedical discoveries.RESULTS: We propose iDeepViewLearn (Interpretable Deep Learning Method for Multiview Learning) to learn nonlinear relationships in data from multiple views while achieving feature selection. iDeepViewLearn combines deep learning flexibility with the statistical benefits of data and knowledge-driven feature selection, giving interpretable results. Deep neural networks are used to learn view-independent low-dimensional embedding through an optimization problem that minimizes the difference between observed and reconstructed data, while imposing a regularization penalty on the reconstructed data. The normalized Laplacian of a graph is used to model bilateral relationships between variables in each view, therefore, encouraging selection of related variables. iDeepViewLearn is tested on simulated and three real-world data for classification, clustering, and reconstruction tasks. For the classification tasks, iDeepViewLearn had competitive classification results with state-of-the-art methods in various settings. For the clustering task, we detected molecular clusters that differed in their 10-year survival rates for breast cancer. For the reconstruction task, we were able to reconstruct handwritten images using a few pixels while achieving competitive classification accuracy. The results of our real data application and simulations with small to moderate sample sizes suggest that iDeepViewLearn may be a useful method for small-sample-size problems compared to other deep learning methods for multiview learning.CONCLUSION: iDeepViewLearn is an innovative deep learning model capable of capturing nonlinear relationships between data from multiple views while achieving feature selection. It is fully open source and is freely available at https://github.com/lasandrall/iDeepViewLearn .PMID:38350879 | DOI:10.1186/s12859-024-05679-9

Stat Med. 2024 Jan 10. doi: 10.1002/sim.9994. Online ahead of print.ABSTRACTThe prevalence of chronic non-communicable diseases such as obesity has noticeably increased in the last decade. The study of these diseases in early life is of paramount importance in determining their course in adult life and in supporting clinical interventions. Recently, attention has been drawn to approaches that study the alteration of metabolic pathways in obese children. In this work, we propose a novel joint modeling approach for the analysis of growth biomarkers and metabolite associations, to unveil metabolic pathways related to childhood obesity. Within a Bayesian framework, we flexibly model the temporal evolution of growth trajectories and metabolic associations through the specification of a joint nonparametric random effect distribution, with the main goal of clustering subjects, thus identifying risk sub-groups. Growth profiles as well as patterns of metabolic associations determine the clustering structure. Inclusion of risk factors is straightforward through the specification of a regression term. We demonstrate the proposed approach on data from the Growing Up in Singapore Towards healthy Outcomes cohort study, based in Singapore. Posterior inference is obtained via a tailored MCMC algorithm, involving a nonparametric prior with mixed support. Our analysis has identified potential key pathways in obese children that allow for the exploration of possible molecular mechanisms associated with childhood obesity.PMID:38197220 | DOI:10.1002/sim.9994

Proteomics Clin Appl. 2024 Jan 9:e2300035. doi: 10.1002/prca.202300035. Online ahead of print.ABSTRACTPURPOSE: This study was aimed to analyze serum amino acid metabolite profiles in frailty patients, gain a better understanding of the metabolic mechanisms in frailty, and assess the diagnostic value of metabolomics-based biomarkers of frailty.EXPERIMENTAL DESIGN: This study utilized the ultra-performance liquid chromatography tandem mass spectrometry to examine amino acids associated with frailty. Additionally, we employed multivariate statistical methods, metabolomic data analysis, receiver operating characteristic (ROC) curve analysis, and pathway enrichment analysis.RESULTS: Among the assayed amino acid metabolites, we identified biomarkers for frailty. ROC curve analysis for frailty diagnosis based on the modified Fried's frailty index showed that the areas under ROC curve of tryptophan, phenylalanine, aspartic acid, and combination were 0.775, 0.679, 0.667, and 0.807, respectively. ROC curve analysis for frailty diagnosis based on Frail Scale showed that the areas under ROC curve of cystine, phenylalanine, and combination of amino acids (cystine, L-Glutamine, citrulline, tyrosine, kynurenine, phenylalanine, glutamin acid) were 0.834, 0.708, and 0.854 respectively.CONCLUSION AND CLINICAL RELEVANCE: In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.CLINICAL SIGNIFICANCE: Frailty is a clinical syndrome, as a consequence it is challenging to identify at early course of the disease, even based on the existing frailty scales. Early diagnosis and appropriate patient management are the key to improve the survival and limit disabilities in frailty patients. Proven by the extensive laboratory and clinical studies on frailty, comprehensive analysis of metabolic levels in frail patients, identification of biomarkers and study of pathogenic pathways of metabolites contribute to the prediction and early diagnosis of frailty. In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.PMID:38196151 | DOI:10.1002/prca.202300035

Int Microbiol. 2024 Jan 9. doi: 10.1007/s10123-023-00475-6. Online ahead of print.ABSTRACTSun-drying is a traditional process for preparing dried shrimp in coastal area of South China, but its impacts on nutrition and the formation of flavor-contributory substances in dried shrimp remain largely unknown. This study aimed to examine the effects of the production process on the microbiota and metabolites in dried shrimp. 16S rDNA amplicon sequencing was employed to identify 170 operational taxonomic units (OTUs), with Vibrio, Photobacterium, and Shewanella emerging as the primary pathogenic bacteria in shrimp samples. Lactococcus lactis was identified as the principal potential beneficial microorganism to accrue during the dried shrimp production process and found to contribute significantly to the development of desirable shrimp flavors. LC-MS-based analyses of dried shrimp sample metabolomes revealed a notable increase in compounds associated with unsaturated fatty acid biosynthesis, arachidonic acid metabolism, amino acid biosynthesis, and flavonoid and flavanol biosynthesis throughout the drying process. Subsequent exploration of the relationship between metabolites and bacterial communities highlighted the predominant coexistence of Bifidobacterium, Clostridium, and Photobacterium contributing heterocyclic compounds and metabolites of organic acids and their derivatives. Conversely, Arthrobacter and Staphylococcus were found to inhibit each other, primarily in the presence of heterocyclic compounds. This comprehensive investigation provides valuable insights into the dynamic changes in the microbiota and metabolites of dried shrimps spanning different drying periods, which we expect to contribute to enhancing production techniques and safety measures for dried shrimp processing.PMID:38196020 | DOI:10.1007/s10123-023-00475-6

Tree Physiol. 2024 Jan 9:tpae003. doi: 10.1093/treephys/tpae003. Online ahead of print.ABSTRACTNeedle blights are serious fungal diseases affecting European natural and planted pine forests. Brown-spot needle blight disease (BSNB), caused by the fungus Lecanosticta acicola, causes canopy defoliation and severe productivity losses with consequences depending on host susceptibility. To gain new insights into BSNB plant-pathogen interactions, constitutive and pathogen-induced traits were assessed in two host species with differential disease susceptibility. Six-months-old Pinus radiata (susceptible) and Pinus pinea (more resistant) seedlings were needle inoculated with L. acicola under controlled conditions. Eighty days after inoculation, healthy-looking needles from symptomatic plants were assessed for physiological parameters and sampled for biochemical analysis. Disease progression, plant growth, leaf gas-exchanges and biochemical parameters were complemented with hormonal and untargeted primary metabolism analysis and integrated for a holistic analysis. Constitutive differences between pine species were observed. Pinus pinea presented higher stomatal conductance and transpiration rate and higher amino and organic acids, abscisic acid as well as putrescine content than P. radiata. Symptoms from BSNB disease were observed in 54.54% of P. radiata and 45.45% of P. pinea seedlings, being more pronounced and generalized in P. radiata. For both species, plant height, sub-stomatal CO2 concentration and water-use efficiency were impacted by infection. In P. radiata, total soluble sugars, starch and total flavonoids content increased after infection. No differences in hormone content after infection were observed. However, secondary metabolism was induced in P. pinea visible through total phenolics, flavonoids and putrescine accumulation. Overall, the observed results suggest that P. pinea constitutive and induced traits may function as two layers of a defence strategy which contributed for an increased BSNB resistance in comparison with P. radiata. This is the first integrative study linking plant physiological and molecular traits in Pinus-Lecanosticta acicola pathosystem, contributing to a better understanding of the underlying resistance mechanisms to BSNB disease in pines.PMID:38195942 | DOI:10.1093/treephys/tpae003

Commun Biol. 2024 Jan 9;7(1):69. doi: 10.1038/s42003-023-05759-1.ABSTRACTOur previous work has shown that D-ribose (RIB)-induced depressive-like behaviors in mice. However, the relationship between variations in RIB levels and depression as well as potential RIB participation in depressive disorder is yet unknown. Here, a reanalysis of metabonomics data from depressed patients and depression model rats is performed to clarify whether the increased RIB level is positively correlated with the severity of depression. Moreover, we characterize intestinal epithelial barrier damage, gut microbial composition and function, and microbiota-gut-brain metabolic signatures in RIB-fed mice using colonic histomorphology, 16 S rRNA gene sequencing, and untargeted metabolomics analysis. The results show that RIB caused intestinal epithelial barrier impairment and microbiota-gut-brain axis dysbiosis. These microbial and metabolic modules are consistently enriched in peripheral (fecal, colon wall, and serum) and central (hippocampus) glycerophospholipid metabolism. In addition, three differential genera (Lachnospiraceae_UCG-006, Turicibacter, and Akkermansia) and two types of glycerophospholipids (phosphatidylcholine and phosphatidylethanolamine) have greater contributions to the overall correlations between differential genera and glycerophospholipids. These findings suggest that the disturbances of gut microbiota by RIB may contribute to the onset of depressive-like behaviors via regulating glycerophospholipid metabolism, and providing new insight for understanding the function of microbiota-gut-brain axis in depression.PMID:38195757 | DOI:10.1038/s42003-023-05759-1

Nat Commun. 2024 Jan 9;15(1):393. doi: 10.1038/s41467-023-44468-5.ABSTRACTIgG secreted by B cells carry asparagine N(297)-linked glycans in the fragment crystallizable (Fc) region. Changes in Fc glycosylation are related to health or disease and are functionally relevant, as IgG without Fc glycans cannot bind to Fcɣ receptors or complement factors. However, it is currently unknown whether ɣ-heavy chain (ɣHC) glycans also influence the function of membrane-bound IgG-B-cell receptors (BCR) and thus the outcome of the B-cell immune response. Here, we show in a germinal center (GC)-derived human B-cell line that ɣHC glycans do not affect membrane expression of IgG-BCRs. Furthermore, antigen binding or other BCR-facilitated mechanisms appear unaffected, including BCR downmodulation or BCR-mediated signaling. As expected, secreted IgG lacking Fc glycosylation is unable to carry out effector functions. Together, these observations indicate that IgG-Fc glycosylation serves as a mechanism to control the effector functions of antibodies, but does not regulate the activation of IgG-switched B cells, as its absence had no apparent impact on BCR function.PMID:38195612 | DOI:10.1038/s41467-023-44468-5

Biomark Res. 2024 Jan 9;12(1):6. doi: 10.1186/s40364-023-00555-9.ABSTRACTBACKGROUND: Metabolic associated steatohepatitis (MASH) is metabolic disease that may progress to cirrhosis and hepatocellular carcinoma. Mouse models of diet-induced MASH, which is characterized by the high levels of fats, sugars, and cholesterol in diets, are commonly used in research. However, mouse models accurately reflecting the progression of MASH in humans remain to be established. Studies have explored the potential use of serological metabolites as biomarkers of MASH severity in relation to human MASH.METHODS: We performed a comparative analysis of three mouse models of diet-induced MASH in terms of phenotypic and metabolomic characteristics; MASH was induced using different diets: a high-fat diet; a Western diet; and a high-fat, high-cholesterol diet. Liver cirrhosis was diagnosed using standard clinical approaches (e.g., METAVIR score, hyaluronan level, and collagen deposition level). Mouse serum samples were subjected to nuclear magnetic resonance spectroscopy-based metabolomic profiling followed by bioinformatic analyses. Metabolomic analysis of a retrospective cohort of patients with hepatocellular carcinoma was performed; the corresponding cirrhosis scores were also evaluated.RESULTS: Using clinically relevant quantitative diagnostic methods, the severity of MASH was evaluated. Regarding metabolomics, the number of lipoprotein metabolites increased with both diet and MASH progression. Notably, the levels of very low-density lipoprotein (VLDL) and low-density lipoprotein (LDL) significantly increased with fibrosis progression. During the development of diet-induced MASH in mice, the strongest upregulation of expression was noted for VLDL receptor. Metabolomic analysis of a retrospective cohort of patients with cirrhosis indicated lipoproteins (e.g., VLDL and LDL) as predominant biomarkers of cirrhosis.CONCLUSIONS: Our findings provide insight into the pathophysiology and metabolomics of experimental MASH and its relevance to human MASH. The observed upregulation of lipoprotein expression reveals a feedforward mechanism for MASH development that may be targeted for the development of noninvasive diagnosis.PMID:38195587 | DOI:10.1186/s40364-023-00555-9

Life Sci Alliance. 2024 Jan 9;7(3):e202302057. doi: 10.26508/lsa.202302057. Print 2024 Mar.ABSTRACTJuvenile neuronal ceroid lipofuscinosis (or Batten disease) is an autosomal recessive, rare neurodegenerative disorder that affects mainly children above the age of 5 yr and is most commonly caused by mutations in the highly conserved CLN3 gene. Here, we generated cln3 morphants and stable mutant lines in zebrafish. Although neither morphant nor mutant cln3 larvae showed any obvious developmental or morphological defects, behavioral phenotyping of the mutant larvae revealed hyposensitivity to abrupt light changes and hypersensitivity to pro-convulsive drugs. Importantly, in-depth metabolomics and lipidomics analyses revealed significant accumulation of several glycerophosphodiesters (GPDs) and cholesteryl esters, and a global decrease in bis(monoacylglycero)phosphate species, two of which (GPDs and bis(monoacylglycero)phosphates) were previously proposed as potential biomarkers for CLN3 disease based on independent studies in other organisms. We could also demonstrate GPD accumulation in human-induced pluripotent stem cell-derived cerebral organoids carrying a pathogenic variant for CLN3 Our models revealed that GPDs accumulate at very early stages of life in the absence of functional CLN3 and highlight glycerophosphoinositol and BMP as promising biomarker candidates for pre-symptomatic CLN3 disease.PMID:38195117 | DOI:10.26508/lsa.202302057