PubMed

Biomed Rep. 2023 Dec 20;20(2):25. doi: 10.3892/br.2023.1713. eCollection 2024 Feb.ABSTRACTMicrobial metabolites play an important role in regulating intestinal homeostasis and immune responses. Propofol is a common anesthetic in clinic, but it is not clear whether it affects intestinal metabolites in rats. Tail vein puncture was performed after adaptive feeding for 1 month in eight 2-month-old rats and they were given continuous intravenous infusion of propofol for 3 h. The feces of rats were divided into different groups based on time periods, with before and after anesthesia with propofol on days 1, 3 and 7 labeled as groups P, A1, A3 and A7, respectively. The effect of continuous intravenous infusion with propofol on rat fecal metabolites was determined using the non-targeted metabolomics technique gas chromatography coupled with a time-of-flight mass spectrometer analysis. The types and contents of metabolites in rat feces were changed after continuous intravenous infusion with propofol, but the changes were not statistically significant. The contents of the metabolites 3-hydroxyphenylacetic acid and palmitic acid increased from day 3 to 7, and it was shown that the two metabolites were positively correlated at a statistically significant level. Linoleic acid decreased to its lowest level on day 3, and it returned to pre-anesthesia level on day 7. At the same time, linoleic acid metabolism was a metabolic pathway that was co-enriched 7 days after infusion with propofol. Spearman correlation analysis showed that there was significant correlation between some differential metabolites and differential microorganisms. It was observed that zymosterol 1, cytosin and elaidic acid were negatively correlated with Alloprevotella in the A3 vs. P group. In the A7 vs. P group, cortexolone 3 and coprostan-3-one were positively correlated with Faecalibacterium, whilst aconitic acid was negatively correlated with it. In conclusion, the present study revealed statistically insignificant effects of continuous intravenous propofol on the intestinal metabolites in rats.PMID:38169795 | PMC:PMC10758916 | DOI:10.3892/br.2023.1713

Heliyon. 2023 Dec 9;10(1):e23509. doi: 10.1016/j.heliyon.2023.e23509. eCollection 2024 Jan 15.ABSTRACTDespite advances in medical technology, lung cancer still has one of the highest mortality rates among all malignancies. Therefore, efforts must be made to understand the precise mechanisms underlying lung cancer development. In this study, we conducted lung and gut microbiome analyses and a comprehensive lipid metabolome analysis of host tissues to assess their correlation. Alternations in the lung microbiome due to lung cancer, such as a significantly decreased abundance of Firmicutes and Deferribacterota, were observed compared to a mock group. However, mice with lung cancer had significantly lower relative abundances of Actinobacteria and Proteobacteria and higher relative abundances of Cyanobacteria and Patescibacteria in the gut microbiome. The activations of retinol, fatty acid metabolism, and linoleic acid metabolism metabolic pathways in the lung and gut microbiomes was inversely correlated. Additionally, changes occurred in lipid metabolites not only in the lungs but also in the blood, small intestine, and colon. Compared to the mock group, mice with lung cancer showed that the levels of adrenic, palmitic, stearic, and oleic (a ω-9 polyunsaturated fatty acid) acids increased in the lungs. Conversely, these metabolites consistently decreased in the blood (serum) and colon. Leukotriene B4 and prostaglandin E2 exacerbate lung cancer, and were upregulated in the lungs of the mice with lung cancer. However, isohumulone, a peroxisome proliferator-activated receptor gamma activator, and resolvin (an ω-3 polyunsaturated fatty acid) both have anti-cancer effects, and were upregulated in the small intestine and colon. Our multi-omics data revealed that shifts in the microbiome and metabolome occur during the development of lung cancer and are of possible clinical importance. These results reveal one of the gut-lung axis mechanisms related to lung cancer and provide insights into potential new targets for lung cancer treatment and prophylaxis.PMID:38169741 | PMC:PMC10758782 | DOI:10.1016/j.heliyon.2023.e23509

Int J Med Sci. 2024 Jan 1;21(2):234-252. doi: 10.7150/ijms.85704. eCollection 2024.ABSTRACTLung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.PMID:38169594 | PMC:PMC10758149 | DOI:10.7150/ijms.85704

Int J Med Sci. 2024 Jan 1;21(2):413-423. doi: 10.7150/ijms.89141. eCollection 2024.ABSTRACTIntroduction: Hepatocellular carcinoma (HCC) is the fourth most prevalent cancer in China. Transcatheter arterial chemoembolization (TACE) is a common interventional therapy for HCC. In this study, we aimed to explore specific metabolites that can accurately predict prognosis after TACE in patients with HCC. Methods: Patients with HCC and healthy volunteers (n = 20 each) were recruited to our study; plasma samples were collected from patients before and after TACE and from healthy volunteers. Plasma samples were subjected to untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry metabolomics analysis, to identify metabolites significantly associated with the prognosis of patients with HCC after TACE. Results: Orthogonal filtered partial least squares discriminant analysis confirmed significant separation of the pre-TACE, post-TACE, and healthy groups, and 34 differential metabolites were identified between the pre-TACE and post-TACE groups. KEGG analysis revealed that phenylalanine, tyrosine, and tryptophan biosynthesis pathways and the phenylalanine metabolism pathway were potentially altered in HCC genesis and during TACE. Phenylalanine and tyrosine are involved in both pathways and were increased in the pre-TACE group relative to controls, with phenylalanine further increased in the post-TACE group. Receiver operating characteristic (ROC) curve analysis indicated that PC 36:4|PC 18:2_18:2 (area under the ROC curve (AUC) = 0.798) is a potential marker for assessment of prognosis in patients with HCC after TACE. Moreover, ROC curve analysis indicated that palmitoylcarnitine (AUC = 1) is a marker with potential value for HCC diagnosis. Conclusions: Limited studies had been conducted on the detection of metabolites in the plasma of HCC patients before and after TACE. PC 36:4|PC 18:2_18:2 is a potential marker for evaluation of the therapeutic effects of TACE. This finding may be beneficial for the treatment of patients with HCC after TACE.PMID:38169572 | PMC:PMC10758137 | DOI:10.7150/ijms.89141

Biol Reprod. 2024 Jan 3:ioad175. doi: 10.1093/biolre/ioad175. Online ahead of print.ABSTRACTThe Yangtze finless porpoises (YFP; Neophocaena asiaeorientalis a.) is an endemic and critically endangered species in China. Intensive captive breeding is essential for understanding the biology of critically endangered species, especially their pregnancy characteristics, knowledge of which is crucial for effective breeding management. Urine metabolomics can reveal metabolic differences, arising from physiological changes across pregnancy stages. Therefore, we used the urinary metabolomic technology, to explore urinary metabolite changes in pregnant YFPs. A total of 2281 metabolites were identified in all samples, which including organic acids and derivatives (24.45%), organoheterocyclic compounds (20.23%), benzenoids (18.05%), organic oxygen compounds (7.73%) and phenylpropanoids and polyketides (6.48%). There were 164, 387, and 522 metabolites demonstrating differential abundance during early pregnancy (EP), mid pregnancy (MP), and late pregnancy (LP), respectively, from the levels observed in nonpregnancy. The levels of pregnenolone (P5), 17α-hydroxyprogesterone (17-HOP), and tetrahydrocortisone (THE) were significantly higher during all pregnancy stages, indicating their important roles in fetal development. The differential metabolites between nonpregnancy and pregnancy were mainly associated with amino acid and carbohydrate metabolism. Moreover, metabolic activity varied across pregnancy stages; steroid hormone biosynthesis was predominant in EP, and amino acid biosynthesis and carbohydrate metabolism were predominant in MP and LP, respectively. Our results provide new insights into metabolic characteristics in the YFPs urine during pregnancy, and indicate that the differential levels of urine metabolites can determine pregnancy in YFPs, providing valuable information for the husbandry and management of pregnant YFPs in captivity.PMID:38169437 | DOI:10.1093/biolre/ioad175

J Orthop Surg Res. 2024 Jan 3;19(1):6. doi: 10.1186/s13018-023-04486-x.ABSTRACTPURPOSE: Lower back pain (LBP), mainly caused by intervertebral disk (IVD) degeneration (IDD), is widely prevalent worldwide and is a serious socioeconomic burden. Numerous factors may trigger this degenerative process, and microbial dysbiosis has recently been implicated as one of the likely causes. However, the exact relationship between IDD and the microbiome remains obscure. In this study, we investigated the gut microbiota composition and fecal metabolic phenotype and discussed the possible influences of microbiome dysbiosis on IDD.METHODS: Fecal DNA was extracted from 16 fecal samples (eight rabbit models with IDD and eight sex- and age-matched healthy controls) and analyzed by high-throughput 16S rDNA sequencing. The fecal samples were also analyzed by liquid chromatography-mass spectrometry-based metabolomics. Multivariate analyses were conducted for the relationship between the omics data and IDD, linear discriminant analysis effect size was employed for biomarker discovery. Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the differential metabolites. The potential correlation between differential gut microbiota and metabolites was then assessed.RESULTS: The 16S rDNA sequencing results showed that the β-diversity of the gut microbiota was significantly different between the IDD and control groups, with distinct abundance levels of dominant genera. Moreover, 59 metabolites were significantly upregulated and 91 were downregulated in IDD rabbits versus the controls. The KEGG enrichment analysis revealed that the top pathways remarkably impacted by IDD were tyrosine metabolism, amino sugar and nucleotide sugar metabolism, benzoate degradation, ABC transporters, ascorbate and aldarate metabolism, pantothenate and CoA biosynthesis, and pyrimidine metabolism. The correlation analysis revealed that DL-tyrosine and N-acetylmuramic acid were associated with multiple differential bacterial genera, including Helicobacter and Vibrio, which may play important roles in the process of IVD degeneration.CONCLUSION: Our findings revealed that IDD altered gut microbiota and fecal metabolites in a rabbit model. The correlation analysis of microbiota and metabolome provides a deeper understanding of IDD and its possible etiopathogenesis. These results also provide a direction and theoretical basis for the clinical application of fecal transplantation, probiotics, and other methods to regulate gut microbiota in the treatment of LBP caused by IDD.PMID:38169417 | DOI:10.1186/s13018-023-04486-x

J Anim Sci Biotechnol. 2024 Jan 2;15(1):1. doi: 10.1186/s40104-023-00956-8.ABSTRACTBACKGROUND: Our previous study has reported that supplementation of oligosaccharide-based polymer enhances gut health and disease resistance of pigs infected with enterotoxigenic E. coli (ETEC) F18 in a manner similar to carbadox. The objective of this study was to investigate the impacts of oligosaccharide-based polymer or antibiotic on the host metabolic profiles and colon microbiota of weaned pigs experimentally infected with ETEC F18.RESULTS: Multivariate analysis highlighted the differences in the metabolic profiles of serum and colon digesta which were predominantly found between pigs supplemented with oligosaccharide-based polymer and antibiotic. The relative abundance of metabolic markers of immune responses and nutrient metabolisms, such as amino acids and carbohydrates, were significantly differentiated between the oligosaccharide-based polymer and antibiotic groups (q < 0.2 and fold change > 2.0). In addition, pigs in antibiotic had a reduced (P < 0.05) relative abundance of Lachnospiraceae and Lactobacillaceae, whereas had greater (P < 0.05) Clostridiaceae and Streptococcaceae in the colon digesta on d 11 post-inoculation (PI) compared with d 5 PI.CONCLUSIONS: The impact of oligosaccharide-based polymer on the metabolic and microbial profiles of pigs is not fully understood, and further exploration is needed. However, current research suggest that various mechanisms are involved in the enhanced disease resistance and performance in ETEC-challenged pigs by supplementing this polymer.PMID:38169416 | DOI:10.1186/s40104-023-00956-8

J Agric Food Chem. 2024 Jan 3. doi: 10.1021/acs.jafc.3c06307. Online ahead of print.ABSTRACTOligomycins are potent antifungal and antitumor agents. Mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based metabolomic fingerprinting analysis of marine-derived actinomycetes in our in-house library provided an oligomycin-producing strain, Streptomyces sp. FXY-T5. Chemical investigation led to the discovery of five new oligomycins, 24-lumooligomycin B (1), 4-lumooligomycin B (2), 6-lumooligomycin B (3), 40-homooligomycin B (4), and 15-hydroxy-oligomycin B (5), together with seven biosynthetically related known derivatives. Their structures were assigned by MS, NMR, electronic circular dichroism (ECD), and single-crystal X-ray diffraction analyses. The biosynthesis pathway of oligomycins was first proposed based on the analysis of a type I modular polyketide synthase (PKS) system and targeted gene disruption. As expected, the isolated oligomycins showed significant antiagricultural fungal pathogen activity and antiproliferative properties from which the possible structure-activity relationships were first suggested. More importantly, oligomycins induced significant G1-phase cell cycle arrest on cancer cells and significantly attenuated their Cyclin D1 and PCNA expression through a β-catenin signaling pathway.PMID:38169320 | DOI:10.1021/acs.jafc.3c06307

Plant Physiol Biochem. 2023 Dec 23;206:108308. doi: 10.1016/j.plaphy.2023.108308. Online ahead of print.ABSTRACTSeed longevity is a critical characteristic in agriculture, yet the specific genes/proteins responsible for this trait and the molecular mechanisms underlying reduced longevity during seed aging remain largely elusive. Here we report the comparative proteome and metabolome profiling of three rice cultivars exhibiting varying degrees of aging tolerance: Dharial, an aging-tolerant cultivar; Ilmi, an aging-sensitive cultivar; and A2, a moderately aging-tolerant cultivar developed from the crossbreeding of Dharial and Ilmi. Artificial aging treatment (AAT) markedly reduced the germination percentage and enhanced the activities of antioxidant enzymes in all the cultivars. Further, proteomics results showed a key role of the ubiquitin (Ub)-proteasome pathway in the degradation of damaged proteins during AAT while other proteases were majorly reduced. In addition, proteins associated with energy production and protein synthesis were strongly reduced in Ilmi while these were majorly increased in A2 and Dharial. These, along with metabolomics results, suggest that Ub-proteasome mediated protein degradation during AAT results in the accumulation of free amino acids in Ilmi while tolerant cultivars potentially utilize those for energy production and synthesis of stress-related proteins, especially hsp20/alpha-crystallin family protein. Additionally, both Dharial and A2 seem to activate brassinosteroid signaling and suppress jasmonate signaling which initiates a signaling cascade that allows accumulation of enzymatic and non-enzymatic antioxidants for efficient detoxification of aging-induced ROS. Taken together, these results provide an in-depth understanding of the aging-induced changes in rice seeds and highlight key pathways responsible for maintaining seed longevity during AAT.PMID:38169224 | DOI:10.1016/j.plaphy.2023.108308

Clin Chim Acta. 2023 Dec 31:117749. doi: 10.1016/j.cca.2023.117749. Online ahead of print.ABSTRACTThe measurement of steroid hormones in blood and urine, which reflects steroid biosynthesis and metabolism, has been recognized as a valuable tool for identifying and distinguishing steroidogenic disorders. The application of mass spectrometry enables the reliable and simultaneous analysis of large panels of steroids, ushering in a new era for diagnosing adrenal diseases. However, the interpretation of complex hormone results necessitates the expertise and experience of skilled clinicians. In this scenario, machine learning techniques are gaining worldwide attention within healthcare fields. The clinical values of combining mass spectrometry-based steroid profiles analysis with machine learning models, also known as steroid metabolomics, have been investigated for identifying and discriminating adrenal disorders such as adrenocortical carcinomas, adrenocortical adenomas, and congenital adrenal hyperplasia. This promising approach is expected to lead to enhanced clinical decision-making in the field of adrenal diseases. This review will focus on the clinical performances of steroid profiling, which is measured using mass spectrometry and analyzed by machine learning techniques, in the realm of decision-making for adrenal diseases.PMID:38169194 | DOI:10.1016/j.cca.2023.117749

Nat Biotechnol. 2024 Jan 2. doi: 10.1038/s41587-023-02033-x. Online ahead of print.ABSTRACTAdoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .PMID:38168992 | DOI:10.1038/s41587-023-02033-x

Nat Biotechnol. 2024 Jan 2. doi: 10.1038/s41587-023-01985-4. Online ahead of print.ABSTRACTThe throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.PMID:38168990 | DOI:10.1038/s41587-023-01985-4

Food Funct. 2024 Jan 3. doi: 10.1039/d3fo04366e. Online ahead of print.ABSTRACTXylooligosaccharides (XOSs) have recently garnered interest for their potential as an anti-constipation agent. In this study, we investigated the effects of XOSs derived from corn cobs on constipation in mice through a comprehensive analysis of both the metabolome and transcriptome. Our multi-omics approach revealed that XOSs primarily modulated butanoate metabolism and steroid hormone biosynthesis pathways, as well as key signaling pathways such as PPAR and NF-kappa B. Notably, we observed a decrease in inflammatory biomarker expression and an elevation of butyric acid metabolite levels with XOSs treatment. A deeper analysis of gene expression and metabolite alterations highlighted significant changes in genes encoding critical enzymes and metabolites involved in these pathways. Overall, these findings underscore the considerable potential of XOSs derived from corn cobs as a dietary supplement for effectively alleviating constipation.PMID:38168976 | DOI:10.1039/d3fo04366e

J Gastrointest Cancer. 2024 Jan 2. doi: 10.1007/s12029-023-00990-9. Online ahead of print.ABSTRACTOBJECTIVE: Breakthroughs in omics technology have led to a deeper understanding of the fundamental molecular changes that play a critical role in the development and progression of cancer. This review delves into the hidden molecular drivers of colorectal cancer (CRC), offering potential for clinical translation through novel biomarkers and personalized therapies.METHODS: We summarizes recent studies utilizing various omics approaches, including genomics, transcriptomics, proteomics, epigenomics, metabolomics and data integration with computational algorithms, to investigate CRC.RESULTS: Integrating multi-omics data in colorectal cancer research unlocks hidden biological insights, revealing new pathways and mechanisms. This powerful approach not only identifies potential biomarkers for personalized prognosis, diagnosis, and treatment, but also predicts patient response to specific therapies, while computational tools illuminate the landscape by deciphering complex datasets.CONCLUSIONS: Future research should prioritize validating promising biomarkers and seamlessly translating them into clinical practice, ultimately propelling personalized CRC management to new heights.PMID:38168859 | DOI:10.1007/s12029-023-00990-9

Plant J. 2024 Jan 3. doi: 10.1111/tpj.16612. Online ahead of print.ABSTRACTGlobal climate change is predicted to result in increased yield losses of agricultural crops caused by environmental conditions. In particular, heat and drought stress are major factors that negatively affect plant development and reproduction, and previous studies have revealed how these stresses induce plant responses at physiological and molecular levels. Here, we provide a comprehensive overview of current knowledge concerning how drought, heat, and combinations of these stress conditions affect the status of plants, including crops, by affecting factors such as stomatal conductance, photosynthetic activity, cellular oxidative conditions, metabolomic profiles, and molecular signaling mechanisms. We further discuss stress-responsive regulatory factors such as transcription factors and signaling factors, which play critical roles in adaptation to both drought and heat stress conditions and potentially function as 'hubs' in drought and/or heat stress responses. Additionally, we present recent findings based on forward genetic approaches that reveal natural variations in agricultural crops that play critical roles in agricultural traits under drought and/or heat conditions. Finally, we provide an overview of the application of decades of study results to actual agricultural fields as a strategy to increase drought and/or heat stress tolerance. This review summarizes our current understanding of plant responses to drought, heat, and combinations of these stress conditions.PMID:38168757 | DOI:10.1111/tpj.16612

APMIS. 2024 Jan 2. doi: 10.1111/apm.13365. Online ahead of print.ABSTRACTMaintaining healthy vaginal microflora post-puberty is critical. In this study we explore the potential of vaginal lactic acid bacteria (LAB) and their extracellular metabolites against the pathogenicity of Candida albicans. The probiotic culture free supernatant (PCFS) from Lactobacillus crispatus, L. gasseri, and L. vaginalis exhibit an inhibitory effect on budding, hyphae, and biofilm formation of C. albicans. LGPCFS manifested the best potential among the LAB PCFS, inhibiting budding for 24 h and restricting hyphae formation post-stimulation. LGPCFS also pre-eminently inhibited biofilm formation. Furthermore, L. gasseri itself grew under RPMI 1640 stimulation suppressing the biofilm formation of C. albicans. The PCFS from the LAB downregulated the hyphal genes of C. albicans, inhibiting the yeast transformation to fungi. Hyphal cell wall proteins HWP1, ALS3, ECE1, and HYR1 and transcription factors BCR1 and CPH1 were downregulated by the metabolites from LAB. Finally, the extracellular metabolome of the LAB was studied by LC-MS/MS analysis. L.gasseri produced the highest antifungal compounds and antibiotics, supporting its best activity against C. albicans. Vaginal LAB and their extracellular metabolites perpetuate C. albicans at an avirulent state. The metabolites produced by these LAB in vitro have been identified, and can be further exploited as a preventive measure against vaginal candidiasis.PMID:38168754 | DOI:10.1111/apm.13365

Commun Biol. 2024 Jan 2;7(1):6. doi: 10.1038/s42003-023-05687-0.ABSTRACTMouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.PMID:38168632 | DOI:10.1038/s42003-023-05687-0

EBioMedicine. 2024 Jan 1;99:104911. doi: 10.1016/j.ebiom.2023.104911. Online ahead of print.ABSTRACTBACKGROUND: The high variability in clinical and metabolic presentations of inborn errors of cobalamin (cbl) metabolism (IECM), such as the cblC/epicblC types with combined deficits in methylmalonyl-coA mutase (MUT) and methionine synthase (MS), are not well understood. They could be explained by the impaired expression/activity of enzymes from other metabolic pathways.METHODS: We performed metabolomic, genomic, proteomic, and post-translational modification (PTM) analyses in fibroblasts from three cblC cases and one epi-cblC case compared with three cblG cases with specific MS deficits and control fibroblasts.FINDINGS: CblC patients had metabolic profilings consistent with altered urea cycle, glycine, and energy mitochondrial metabolism. Metabolomic analysis showed partial disruption and increased glutamate/ketoglutarate anaplerotic pathway of the tricarboxylic acid cycle (TCA), in patient fibroblasts. RNA-seq analysis showed decreased expression of MT-TT (mitochondrial tRNA threonine), MT-TP (mitochondrial tRNA proline), OXCT1 (succinyl CoA:3-oxoacid CoA transferase deficiency), and MT-CO1 (cytochrome C oxidase subunit 1). Proteomic changes were observed for key mitochondrial enzymes, including NADH:ubiquinone oxidoreductase subunit A8 (NDUFA8), carnitine palmitoyltransferase 2 (CPT2), and ubiquinol-cytochrome C reductase, complex III subunit X (UQCR10). Propionaldehyde addition in ornithine aminotransferase was the predominant PTM in cblC cells and could be related with the dramatic cellular increase in propionate and methylglyoxalate. It is consistent with the decreased concentration of ornithine reported in 3 cblC cases. Whether the changes detected after multi-omic analyses underlies clinical features in cblC and cblG types of IECM, such as peripheral and central neuropathy, cardiomyopathy, pulmonary hypertension, development delay, remains to be investigated.INTERPRETATION: The omics-related effects of IECM on other enzymes and metabolic pathways are consistent with the diversity and variability of their age-related metabolic and clinical manifestations. PTMs are expected to produce cumulative effects, which could explain the influence of age on neurological manifestations.FUNDING: French Agence Nationale de la Recherche (Projects PREDICTS and EpiGONE) and Inserm.PMID:38168585 | DOI:10.1016/j.ebiom.2023.104911

Sci Rep. 2024 Jan 2;14(1):152. doi: 10.1038/s41598-023-50646-8.ABSTRACTIn the field of data analysis, it is often faced with a large number of missing values, especially in metabolomics data, this problem is more prominent. Data imputation is a common method to deal with missing metabolomics data, while traditional data imputation methods usually ignore the differences in missing types, and thus the results of data imputation are not satisfactory. In order to discriminate the missing types of metabolomics data, a missing data classification model (PX-MDC) based on particle swarm algorithm and XGBoost is proposed in this paper. First, the missing values in a given missing data set are obtained by panning the missing values to obtain the largest subset of complete data, and then the particle swarm algorithm is used to search for the concentration threshold of missing data and the proportion of low concentration deletions as a percentage of overall deletions. Next, the missing data are simulated based on the search results. Finally, the training data are trained using the XGBoost model using the feature set proposed in this paper in order to build a classifier for the missing data. The experimental results show that the particle swarm algorithm is able to match the traditional enumeration method in terms of accuracy and significantly reduce the search time in concentration threshold search. Compared with the current mainstream methods, the PX-MDC model designed in this paper exhibits higher accuracy and is able to distinguish different deletion types for the same metabolite. This study is expected to make an important breakthrough in metabolomics data imputation and provide strong support for research in related fields.PMID:38168582 | DOI:10.1038/s41598-023-50646-8

Bioresour Technol. 2023 Dec 31:130278. doi: 10.1016/j.biortech.2023.130278. Online ahead of print.ABSTRACTThis work aimed to elucidate the metabolic mechanism of heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria influenced by varying concentrations of ammonium nitrogen (NH4+-N) in high-strength synthetic wastewater treatment. The results showed that the removal rates of NH4+-N and total nitrogen, along with enzymatic activities related to nitrification and denitrification, increased with rising NH4+-N concentrations (N500:500 mg/L, N1000:1000 mg/L and N2000:2000 mg/L). The relative abundances of HN-AD bacteria were 50 %, 62 % and 82 % in the three groups. In the N2000 group, the cAMP signaling pathway, glycerophospholipid metabolites, purines and pyrimidines related to DNA/RNA synthesis, electron donor NAD+-related energy, the tricarboxylic acid (TCA) cycle and glutamate metabolism were upregulated. Therefore, influent NH4+-N at 2000 mg/L promoted glutamate metabolism to accelerate the TCA cycle, and enhanced cellular energy and advanced denitrification activity of bacteria for HN-AD. This mechanism, in turn, enhanced microbial growth and the carbon and nitrogen metabolism of bacteria for HN-AD.PMID:38168563 | DOI:10.1016/j.biortech.2023.130278