PubMed

Diabetes. 2022 Nov 21:db23er02a. doi: 10.2337/db23-er02a. Online ahead of print.ABSTRACTIn the article cited above, affiliation 6 was incorrectly listed as "Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China" due to a composition error. The correct affiliation 6 is "Department of Endocrinology and Metabolism, Huashan Hospital, Fudan University, Shanghai, China." The editors apologize for the error. The online version of the article (https://doi.org/10.2337/db22-0260) has been updated to correct the affiliation.PMID:36409587 | DOI:10.2337/db23-er02a

J Clin Invest. 2022 Nov 21:e163472. doi: 10.1172/JCI163472. Online ahead of print.ABSTRACTBACKGROUND: The kynurenine pathway (KP) has been identified as a potential mediator linking acute illness to cognitive dysfunction by generating neuroactive metabolites in response to inflammation. Delirium (acute confusion) is a common complication of acute illness and is associated with increased risk of dementia and mortality. However, the molecular mechanism underlying delirium, particularly in relation to the KP, remain elusive.METHODS: We undertook a multi-center observational study with 586 hospitalized patients (248 with delirium) and investigated associations between delirium and KP metabolites measured in cerebrospinal fluid (CSF) and serum by targeted metabolomics. We also explored associations between KP metabolites and markers of neuronal damage and one-year mortality.RESULTS: In delirium, we found concentrations of the neurotoxic metabolite quinolinic acid in CSF (CSF-QA, OR 2.26 [1.78, 2.87], p<0.001) to be increased, as well as increases in several other KP metabolites in serum and CSF. In addition, CSF-QA was associated with the neuronal damage marker neurofilament light chain (NfL, β 0.43, p<0.001) and was a strong predictor of one-year mortality (HR 4.35 [2.93, 6.45] for CSF-QA ≥ 100 nmol/L, p<0.001). The associations between CSF-QA and delirium, neuronal damage, and mortality remained highly significant following adjustment for confounders and multiple comparisons.CONCLUSION: Our data identified how systemic inflammation, neurotoxicity, and delirium are strongly linked via the KP, and should inform future delirium prevention and treatment clinical trials that target enzymes of the KP.FUNDING: Norwegian Health Association and the South-Eastern Norway Regional Health Authorities.PMID:36409557 | DOI:10.1172/JCI163472

Rapid Commun Mass Spectrom. 2022 Nov 21:e9437. doi: 10.1002/rcm.9437. Online ahead of print.ABSTRACTRATIONALE: Databases of electron ionization mass spectra are often used in GC/MS-based untargeted metabolomics analysis. The results of the library search depend on several factors such as the size and quality of the database, the library search algorithm, and etc. We found out that the list of considered m/z values is another important parameter. Unfortunately, this information is not usually specified by software developers, and it is hidden from the end user.METHODS: We created synthetic data sets and figured out how several popular software products (AMDIS, ChromaTOF, MS Search, and Xcalibur) select the list of m/z values for the library search. Moreover, we considered data sets of real mass spectra (presented in both NIST and FiehnLib libraries) and compared the library search results obtained within different software products. All programs under consideration call the NIST MS Search binaries to perform the library search using the Identity algorithm.RESULTS: We found out that AMDIS and ChromaTOF can give biased library search results under particular conditions. In untargeted metabolomics, it can happen when NIST and FiehnLib libraries are used simultaneously, the scan range of the instrument is less than 85, and the correct answer is present only in the FiehnLib library.CONCLUSIONS: The main reason for biased results is that the information about the scan range is not stored in the metadata of library records. As a result, in the case of AMDIS and ChromaTOF software, some unrecorded peaks are considered as missing ones during the library search, the respective compound is penalized, and the correct answer falls outside the top 5 or even 10 hits. At the same time, the default algorithm for selecting the list of considered m/z values implemented in MS Search is free from such unexpected behavior.PMID:36409456 | DOI:10.1002/rcm.9437

Metabolomics. 2022 Nov 19;18(12):94. doi: 10.1007/s11306-022-01947-y.ABSTRACTBACKGROUND: Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of thousands of compounds, forming an essential knowledge base for the interpretation of metabolomics experiments.AIM OF REVIEW: We describe existing spectral library resources, highlight different strategies for compiling spectral libraries, and discuss quality considerations that should be taken into account when interpreting spectral library searching results. Finally, we describe how spectral libraries are empowering the next generation of machine learning tools in computational metabolomics, and discuss several opportunities for using increasingly accessible large spectral libraries.KEY SCIENTIFIC CONCEPTS OF REVIEW: This review focuses on the current state of spectral libraries for untargeted LC-MS/MS based metabolomics. We show how the number of entries in publicly accessible spectral libraries has increased more than 60-fold in the past eight years to aid molecular interpretation and we discuss how the role of spectral libraries in untargeted metabolomics will evolve in the near future.PMID:36409434 | DOI:10.1007/s11306-022-01947-y

Metabolomics. 2022 Nov 19;18(12):95. doi: 10.1007/s11306-022-01958-9.ABSTRACTINTRODUCTION: Plant cell walls play an important role in providing physical strength and defence against abiotic stress. Rice brittle culm (bc) mutants are a strength-decreased mutant because of abnormal cell walls, and it has been reported that the causative genes of bc mutants affect cell wall composition. However, the metabolic alterations in each organ of bc mutants have remained unknown.OBJECTIVES: To evaluate the metabolic changes in rice bc mutants, comparative analysis of the primary metabolites was conducted.METHODS: The primary metabolites in leaves, internodes, and nodes of rice bc mutants and wild-type control were measured using CE- and LC-MS/MS. Multivariate analyses using metabolomic data was performed.RESULTS: We found that mutations in each bc mutant had different effects on metabolism. For example, higher oxalate content was observed in bc3 and bc1 bc3 mutants, suggesting that surplus carbon that was not used for cell wall components might be used for oxalate synthesis. In addition, common metabolic alterations such as a decrease of sugar nucleotides in nodes were found in bc1 and Bc6, in which the causative genes are involved in cellulose accumulation.CONCLUSION: These results suggest that metabolic analysis of the bc mutants could elucidate the functions of causative gene and improve the cell wall components for livestock feed or bioethanol production.PMID:36409428 | DOI:10.1007/s11306-022-01958-9

Handb Exp Pharmacol. 2022 Nov 22. doi: 10.1007/164_2022_617. Online ahead of print.ABSTRACTThe metabolome is composed of a vast array of molecules, including endogenous metabolites and lipids, diet- and microbiome-derived substances, pharmaceuticals and supplements, and exposome chemicals. Correct identification of compounds from this diversity of classes is essential to derive biologically relevant insights from metabolomics data. In this chapter, we aim to provide a practical overview of compound identification strategies for mass spectrometry-based metabolomics, with a particular eye toward pharmacologically-relevant studies. First, we describe routine compound identification strategies applicable to targeted metabolomics. Next, we discuss both experimental (data acquisition-focused) and computational (software-focused) strategies used to identify unknown compounds in untargeted metabolomics data. We then discuss the importance of, and methods for, assessing and reporting the level of confidence of compound identifications. Throughout the chapter, we discuss how these steps can be implemented using today's technology, but also highlight research underway to further improve accuracy and certainty of compound identification. For readers interested in interpreting metabolomics data already collected, this chapter will supply important context regarding the origin of the metabolite names assigned to features in the data and help them assess the certainty of the identifications. For those planning new data acquisition, the chapter supplies guidance for designing experiments and selecting analysis methods to enable accurate compound identification, and it will point the reader toward best-practice data analysis and reporting strategies to allow sound biological and pharmacological interpretation.PMID:36409330 | DOI:10.1007/164_2022_617

Microbiol Spectr. 2022 Nov 21:e0262422. doi: 10.1128/spectrum.02624-22. Online ahead of print.ABSTRACTDNA methylation is an important factor in the regulation of gene expression. In analyzing genomic data of Stereum hirsutum FP-91666, we found a hypothetical bifunctional transcription regulator/O6Meguanine-DNA methyltransferase (named SaraC), which is widely present in both bacteria and fungi, and confirmed that its function in bacteria is mainly for DNA reparation. In this paper, we confirmed that SaraC has the function of DNA binding and demethylation through surface plasma resonance and reaction experiments in vitro. Then, we achieved the overexpression of SaraC (OES) in S. hirsutum, sequenced the methylation and transcription levels of the whole-genome, and further conducted untargeted metabolomics analyses of the OES transformants and the wild type (WT). The results confirmed that the overall-methylation levels of the transformants were significantly downregulated, and various genes related to secondary metabolism were upregulated. Through comparative untargeted metabolomic analyses, it showed that OES SA6 transformant produced a greater number of hybrid polyketides, and we identified 2 novel hybrid polyketides from the fermentation products of SA6. Our results show that overexpression SaraC can effectively stimulate the expression of secondary-metabolism-related genes, which could be a broad-spectrum tool for discovery of metabolites due to its cross-species conservation. IMPORTANCE Fungi are one of the important sources of active compounds. However, in fungi, most of the secondary metabolic biosynthetic gene clusters are weakly expressed or silenced under conventional culture conditions. How to efficiently excavate potential new compounds contained in fungi is becoming a research hot spot in the world. In this study, we found a DNA demethylation protein (SaraC) and confirmed that it is a global secondary metabolism regulator in Stereum hirsutum FP-91666. In the past, SaraC-like proteins were mainly regarded as DNA repair proteins, but our findings proved that it will be a powerful tool for mining secondary metabolites for overexpression of SaraC, which can effectively stimulate the expression of genes related to secondary metabolism.PMID:36409127 | DOI:10.1128/spectrum.02624-22

Elife. 2022 Nov 21;11:e76119. doi: 10.7554/eLife.76119. Online ahead of print.ABSTRACTMicrobes have disproportionate impacts on the macroscopic world. This is in part due to their ability to grow to large populations that collectively secrete massive amounts of secondary metabolites and alter their environment. Yet, the conditions favoring secondary metabolism despite the potential costs for primary metabolism remain unclear. Here we investigated the biosurfactants that the bacterium Pseudomonas aeruginosa makes and secretes to decrease the surface tension of surrounding liquid. Using a combination of genomics, metabolomics, transcriptomics, and mathematical modeling we show that the ability to make surfactants from glycerol varies inconsistently across the phylogenetic tree; instead, lineages that lost this ability are also worse at reducing the oxidative stress of primary metabolism on glycerol. Experiments with different carbon sources support a link with oxidative stress that explains the inconsistent distribution across the P. aeruginosa phylogeny and suggests a general principle: P. aeruginosa lineages produce surfactants if they can reduce the oxidative stress produced by primary metabolism and have excess resources, beyond their primary needs, to afford secondary metabolism. These results add a new layer to the regulation of a secondary metabolite unessential for primary metabolism but important to change physical properties of the environments surrounding bacterial populations.PMID:36409069 | DOI:10.7554/eLife.76119

Biomed Chromatogr. 2022 Nov 21:e5551. doi: 10.1002/bmc.5551. Online ahead of print.ABSTRACTCordycepin is an important quality control marker in Cordyceps militaris. This study aimed to explain the metabolic mechanisms for high-yielding cordycepin of Cordyceps militaris. In this study, high-yielding strains of cordycepin were obtained by UV mutagenesis, and the polysaccharide and protein contents were also changed. In high-yielding strains, the protein content significantly increased, whereas the polysaccharide content decreased. Simultaneously, metabolic differences for high and low-yielding cordycepin strains were detected by metabolomics. Metabolomics results showed that the relative content of most metabolites decreased in high-yielding cordycepin strains. Various metabolic pathways have been altered in high-yielding cordycepin strains, such as the citric acid cycle, purine metabolism, and pyrimidine metabolism, leading to an increase in cordycepin content. Additionally, changes in metabolic poly-pathways related to polysaccharide and protein synthesis, such as galactose metabolism and amino acid metabolism, also promoted an increase in cordycepin content. This study analyzes the high-yielding cordycepin causes in Cordyceps militaris at the metabolic level and provides a theoretical basis for further increasing cordycepin content.PMID:36408993 | DOI:10.1002/bmc.5551

Front Pharmacol. 2022 Nov 2;13:1038188. doi: 10.3389/fphar.2022.1038188. eCollection 2022.ABSTRACTZhuyu pill (ZYP) is a traditional Chinese medicine prescription composed of two drugs, Coptis chinensis Franch. and Tetradium ruticarpum (A. Jussieu) T. G. Hartley, and is commonly used in the clinical treatment of diseases of the digestive system. However, the mechanism underlying the effect of ZYP on colitis remains unclear. In this study, a colitis rat model was induced with 2,4,6-trinitro-benzenesulfonic acid (TNBS, 100 mg/kg) and treated with ZYP (low dose: 0.6 g/kg, high dose: 1.2 g/kg). Disease activity index, colonic weight index, and weight change ratio were used to evaluate the model and efficacy. LC-MS and 16S rRNA gene sequencing were used to measure differences in fecal metabolism and microorganism population among the control, model, low-dose ZYP, and high-dose ZYP groups. To elucidate the mechanism of interventional effect of ZYP, Spearman correlation analysis was used to analyze the correlation between fecal metabolism and fecal microbial number. High-dose and low-dose ZYP both exhibited significant interventional effects on colitis rat models, and high-dose ZYP produced a better interventional effect compared with low-dose ZYP. Based on a metabolomics test of fecal samples, significantly altered metabolites in the model and high-dose ZYP treatment groups were identified. In total, 492 metabolites were differentially expressed. Additionally, sequencing of the 16S rRNA gene in fecal samples revealed that the high-dose ZYP could improve TNBS-induced fecal microbiota dysbiosis. Ultimately, changes in tryptophan metabolism and Firmicutes and Gammaproteobacteria populations were detected after ZYP treatment in both colitis and cholestasis. Therefore, we conclude that tryptophan metabolism and Firmicutes and Gammaproteobacteria populations are the core targets of the anti-inflammatory effect of ZYP. These findings provide a scientific basis for further investigation of the anti-inflammatory mechanism of ZYP in the future.PMID:36408242 | PMC:PMC9666482 | DOI:10.3389/fphar.2022.1038188

Front Aging Neurosci. 2022 Nov 3;14:964429. doi: 10.3389/fnagi.2022.964429. eCollection 2022.ABSTRACTAging is an intricate biological event that occurs in both vertebrates and invertebrates. During the aging process, the brain, a vulnerable organ, undergoes structural and functional alterations, resulting in behavioral changes. The hippocampus has long been known to be critically associated with cognitive impairment, dementia, and Alzheimer's disease during aging; however, the underlying mechanisms remain largely unknown. In this study, we hypothesized that altered metabolic and gene expression profiles promote the aging process in the hippocampus. Behavioral tests showed that exploration, locomotion, learning, and memory activities were reduced in aged mice. Metabolomics analysis identified 69 differentially abundant metabolites and showed that the abundance of amino acids, lipids, and microbiota-derived metabolites (MDMs) was significantly altered in hippocampal tissue of aged animals. Furthermore, transcriptomic analysis identified 376 differentially expressed genes in the aged hippocampus. A total of 35 differentially abundant metabolites and 119 differentially expressed genes, constituting the top 200 correlations, were employed for the co-expression network. The multi-omics analysis showed that pathways related to inflammation, microglial activation, synapse, cell death, cellular/tissue homeostasis, and metabolism were dysregulated in the aging hippocampus. Our data revealed that metabolic perturbations and gene expression alterations in the aged hippocampus were possibly linked to their behavioral changes in aged mice; we also provide evidence that altered MDMs might mediate the interaction between gut and brain during the aging process.PMID:36408109 | PMC:PMC9669972 | DOI:10.3389/fnagi.2022.964429

Front Mol Neurosci. 2022 Nov 4;15:1032362. doi: 10.3389/fnmol.2022.1032362. eCollection 2022.ABSTRACTAlcohol use disorder (AUD) is highly prevalent and one of the leading causes of disability in the US and around the world. There are some molecular biomarkers of heavy alcohol use and liver damage which can suggest AUD, but these are lacking in sensitivity and specificity. AUD treatment involves psychosocial interventions and medications for managing alcohol withdrawal, assisting in abstinence and reduced drinking (naltrexone, acamprosate, disulfiram, and some off-label medications), and treating comorbid psychiatric conditions (e.g., depression and anxiety). It has been suggested that various patient groups within the heterogeneous AUD population would respond more favorably to specific treatment approaches. For example, there is some evidence that so-called reward-drinkers respond better to naltrexone than acamprosate. However, there are currently no objective molecular markers to separate patients into optimal treatment groups or any markers of treatment response. Objective molecular biomarkers could aid in AUD diagnosis and patient stratification, which could personalize treatment and improve outcomes through more targeted interventions. Biomarkers of treatment response could also improve AUD management and treatment development. Systems biology considers complex diseases and emergent behaviors as the outcome of interactions and crosstalk between biomolecular networks. A systems approach that uses transcriptomic (or other -omic data, e.g., methylome, proteome, metabolome) can capture genetic and environmental factors associated with AUD and potentially provide sensitive, specific, and objective biomarkers to guide patient stratification, prognosis of treatment response or relapse, and predict optimal treatments. This Review describes and highlights state-of-the-art research on employing transcriptomic data and artificial intelligence (AI) methods to serve as molecular biomarkers with the goal of improving the clinical management of AUD. Considerations about future directions are also discussed.PMID:36407766 | PMC:PMC9673015 | DOI:10.3389/fnmol.2022.1032362

Front Plant Sci. 2022 Nov 3;13:1022961. doi: 10.3389/fpls.2022.1022961. eCollection 2022.ABSTRACTThe gibberellic acid (GA)-stimulated Arabidopsis (GASA) gene family is highly specific to plants and plays crucial roles in plant growth and development. CcGASA4 is a member of the GASA gene family in citrus plants; however, the current understanding of its function in citrus is limited. We used CcGASA4-overexpression transgenic citrus (OEGA) and control (CON) plants to study the role of CcGASA4 in Shatian pomelo. The RNA sequencing (RNA-seq) analysis showed that 3,522 genes, including 1,578 upregulated and 1,944 downregulated genes, were significantly differentially expressed in the CON versus OEGA groups. The Gene Ontology enrichment analysis showed that 178 of the differentially-expressed genes (DEGs) were associated with flowers. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEGs were enriched in 134 pathways, including "plant-pathogen interaction", "MAPK signaling pathway-plant", "phenylpropane biosynthesis", "plant hormone signal transduction", "phenylalanine, tyrosine and tryptophan biosynthesis", and "flavonoid and flavonol biosynthesis". The most significantly-enriched pathway was "plant-pathogen interaction", in which 203 DEGs were enriched (126 DEGs were upregulated and 78 were downregulated). The metabolome analysis showed that 644 metabolites were detected in the OEGA and CON samples, including 294 differentially-accumulated metabolites (DAMs; 83 upregulated versus 211 downregulated in OEGA compared to CON). The metabolic pathway analysis showed that these DAMs were mainly involved in the metabolic pathways of secondary metabolites, such as phenylpropanoids, phenylalanine, flavone, and flavonol biosynthesis. Thirteen flavonoids and isoflavones were identified as DAMs in OEGA and CON. We also discovered 25 OEGA-specific accumulated metabolites and found 10 that were associated with disease resistance. CcGASA4 may therefore play a functional role in activating the expression of MAPK signaling transduction pathway and disease resistance genes, inhibiting the expression of auxin- and ethylene-related genes, and activating or inhibiting the expression of brassinosteroid biosynthesis- and abscisic acid-related genes. CcGASA4 may also play a role in regulating the composition and abundance of flavonoids, isoflavones, amino acids, purines, and phenolic compounds. This study provides new insights into the molecular mechanisms of action of CcGASA4 in citrus plants.PMID:36407630 | PMC:PMC9671072 | DOI:10.3389/fpls.2022.1022961

Front Plant Sci. 2022 Nov 3;13:1055779. doi: 10.3389/fpls.2022.1055779. eCollection 2022.ABSTRACTFlesh color is an important target trait in peach [Prunus persica (L.) Batsch] breeding. In this study, two white-fleshed peach cultivars were crossed [Changsong Whitepeach (WP-1) × 'Xiacui'], and their hybrid F1 generation showed color segregation of white flesh (BF1) and yellow flesh (HF1). Metabolome analysis revealed that the flesh color segregation in the hybrid F1 generation was related to the carotenoid content. The decrease in β-carotene and β-cryptoxanthin in BF1 flesh and increase in β-cryptoxanthin oleate, rubixanthin caprate, rubixanthin laurate and zeaxanthin dipalmitate in HF1 flesh contributed to their difference in carotenoid accumulation. Transcriptome analysis demonstrated that compared with BF1, HF1 showed significant up-regulation and down-regulation of ZEP and CCD8 at the core-hardening stage, respectively, while significant down-regulation of NCED in the whole fruit development stage. The down-regulation of NCED might inhibit the breakdown of the violaxanthin and its upstream substances and further promote the accumulation of carotenoids, resulting in yellow flesh. Therefore, NCED may be a key gene controlling the fruit color traits of peach. In this study, targeted metabolomics and transcriptomics were used to jointly explore the mechanism controlling the fruit color of peach, which may help to identify the key genes for the differences in carotenoid accumulation and provide a reference for the breeding of yellow-fleshed peach.PMID:36407629 | PMC:PMC9669654 | DOI:10.3389/fpls.2022.1055779

Front Plant Sci. 2022 Nov 3;13:1024239. doi: 10.3389/fpls.2022.1024239. eCollection 2022.ABSTRACTPholidota chinensis Lindl. is an epiphytic or lithophytic perennial herb of Orchidaceae family used as a garden flower or medicinal plant to treat high blood pressure, dizziness and headache in traditional Chinese medicine. Gastrodin (GAS) is considered as a main bioactive ingredient of this herb but the biosynthetic pathway remains unclear in P. chinensis. To elucidate the GAS biosynthesis and identify the related genes in P. chinensis, a comprehensive analysis of transcriptome and metabolome of roots, rhizomes, pseudobulbs and leaves were performed by using PacBio SMART, Illumina Hiseq and Ultra Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS). A total of 1,156 metabolites were identified by UPLC-MS/MS, of which 345 differential metabolites were mainly enriched in phenylpropanoid/phenylalanine, flavone and flavonol biosynthesis. The pseudobulbs make up nearly half of the fresh weight of the whole plant, and the GAS content in the pseudobulbs was also the highest in four tissues. Up to 23,105 Unigenes were obtained and 22,029 transcripts were annotated in the transcriptome analysis. Compared to roots, 7,787, 8,376 and 9,146 differentially expressed genes (DEGs) were identified in rhizomes, pseudobulbs and leaves, respectively. And in total, 80 Unigenes encoding eight key enzymes for GAS biosynthesis, were identified. Particularly, glycosyltransferase, the key enzyme of the last step in the GAS biosynthetic pathway had 39 Unigenes candidates, of which, transcript28360/f2p0/1592, was putatively identified as the most likely candidate based on analysis of co-expression, phylogenetic analysis, and homologous searching. The metabolomics and transcriptomics of pseudobulbs versus roots showed that 8,376 DEGs and 345 DEMs had a substantial association based on the Pearson's correlation. This study notably enriched the metabolomic and transcriptomic data of P. chinensis, and it provides valuable information for GAS biosynthesis in the plant.PMID:36407583 | PMC:PMC9673822 | DOI:10.3389/fpls.2022.1024239

Front Nutr. 2022 Nov 3;9:1019205. doi: 10.3389/fnut.2022.1019205. eCollection 2022.ABSTRACTMiao Sour Soup (MSS) is a fermented product from the Qiandongnan region of Guizhou Province, which enrich many beneficial ingredients and is widely consumed in the whole China. Fermented food is beneficial to physical health with the potential positive regulating affection on simple obesity. In this study, we analyzed the mechanism of action of MSS to prevent simple obesity induced by high-fat diet by proteomics and metabolomics. Quantitative proteomics with tandem mass tagging labeling and liquid chromatography-mass spectrometry was used to analyze the changes of liver proteins and metabolites after the MSS intervention. MSS intervention upregulated 33 proteins and 9 metabolites and downregulated 19 proteins and 10 metabolites. Bioinformatics analysis showed that MSS could prevent simple obesity by acting on the PPAR signaling pathway, retinol metabolism, fatty acid β-oxidation, fatty acid degradation, fatty acid biosynthesis, glycine, serine and threonine metabolism, pyruvate metabolism, citrate cycle (TCA cycle) and other signaling pathways. This study provides new insights into the use of MSS to prevent simple obesity caused by high-fat diets and the search for healthy eating patterns with MSS.PMID:36407552 | PMC:PMC9671556 | DOI:10.3389/fnut.2022.1019205

Front Nutr. 2022 Nov 4;9:988653. doi: 10.3389/fnut.2022.988653. eCollection 2022.NO ABSTRACTPMID:36407539 | PMC:PMC9672814 | DOI:10.3389/fnut.2022.988653

Front Nutr. 2022 Nov 3;9:1051964. doi: 10.3389/fnut.2022.1051964. eCollection 2022.ABSTRACTIn the protein nutrition strategy of middle-aged and elderly people, some believe that low protein is good for health, while others believe high protein is good for health. Facing the contradictory situation, the following hypothesis is proposed. There is a process of change from lower to higher ratio of protein nutritional requirements that are good for health in the human body after about 50 years of age, and the age at which the switch occurs is around 65 years of age. Hence, in this study, 50, 25-month-old male rats were randomly divided into five groups: Control (basal diet), LP (low-protein diet with a 30% decrease in protein content compared to the basal diet), HP (high-protein diet with a 30% increase in protein content compared to the basal diet), Model 1 (switched from LP to HP feed at week 4), and Model 2 (switched from LP to HP feed at week 7). After a total of 10 weeks intervention, the liver and serum samples were examined for aging-related indicators, and a newly comprehensive quantitative score was generated using principal component analysis (PCA). The effects of the five protein nutritional modalities were quantified in descending order: Model 1 > HP > LP > Control > Model 2. Furthermore, the differential metabolites in serum and feces were determined by orthogonal partial least squares discriminant analysis, and 15 differential metabolites, significantly associated with protein intake, were identified by Spearman's correlation analysis (p < 0.05). Among the fecal metabolites, 10 were positively correlated and 3 were negatively correlated. In the serum, tyrosine and lactate levels were positively correlated, and acetate levels were negatively correlated. MetaboAnalyst analysis identified that the metabolic pathways influenced by protein intake were mainly related to amino acid and carbohydrate metabolism. The results of metabolomic analysis elucidate the mechanisms underlying the preceding effects to some degree. These efforts not only contribute to a unified protein nutrition strategy but also positively impact the building of a wiser approach to protein nutrition, thereby helping middle-aged and older populations achieve healthy aging.PMID:36407526 | PMC:PMC9673908 | DOI:10.3389/fnut.2022.1051964

Front Cell Dev Biol. 2022 Nov 3;10:977960. doi: 10.3389/fcell.2022.977960. eCollection 2022.ABSTRACTPurpose: Accumulating evidence suggests that solute carrier family 39 member 1 (SLC39A1) conceivably function as a tumor suppressor, but the underlying mechanism in renal cell carcinoma (RCC) is poorly understood. Methods: OSRC-2 renal cancer cells were first transfected with SLC39A1 overexpressed vectors and empty vectors and then used in transcriptomics, proteomics, and metabolomics integrated analyses. Results: SLC39A1 significantly altered several metabolisms at transcriptional, protein and metabolic levels, including purine and pyrimidine metabolism, amino acids and derivatives metabolism, lactose metabolism, and free fatty acid metabolism. Additionally, SLC39A1 could promote ferroptosis, and triggered significant crosstalk in PI3K-AKT signal pathway, cAMP signal pathway, and peroxisome proliferators-activated receptor (PPAR) signal pathway. Conclusion: We found SLC39A1 transfection impaired tumor metabolism and perturbed tumor metabolism-related pathways, which was a likely cause of the alteration in cell proliferation, migration, and cell cycle progression in RCC cells. These multi-omics analyses results provided both a macroscopic picture of molecular perturbation by SLC39A1 and novel insights into RCC tumorigenesis and development.PMID:36407113 | PMC:PMC9669761 | DOI:10.3389/fcell.2022.977960

Int J Endocrinol Metab. 2022 Aug 15;20(3):e120812. doi: 10.5812/ijem-120812. eCollection 2022 Jul.ABSTRACTBACKGROUND: Due to the worldwide spread of COVID-19, various countries have designed scientific studies on different aspects of the disease. Patients with diabetes mellitus (DM) have been proven to be at higher risk of COVID-19-related complications, hospitalization, and death.OBJECTIVES: The aim was to conduct a scientometric analysis of scholarly outputs on diabetes and COVID-19.METHODS: Web of Science was searched for scientific publications on diabetes and COVID-19 by Middle Eastern researchers until September 14, 2021. Collected data were analyzed for document type, subject area, countries, top journals, citation number, and authors' collaboration network using VOS viewer 1.6.15 and bibliometrix R-package 4.1.1.RESULTS: Overall, the characteristics of 603 documents on DM and COVID-19 were analyzed. The top three productive countries in the field were Iran, Turkey, and Saudi Arabia. The top affiliation was from Iran; "Tehran University of Medical Sciences" (n = 168), followed by "Shahid Beheshti University of Medical Sciences" (n = 82). The total citation number was 3704 times. The highest cited paper (348) was a systematic review from Iran, published in arch Acad Emerg Med. The top source was "Diabetes & Metabolic Syndrome: Clinical Research & Reviews," with 26 documents.CONCLUSIONS: The current study provides an overview of the quantity and quality of published scholarly documents on the intersection of DM and COVID-19 in the region. Our findings help scientists find the existing gaps, manage the research budgets, identify active authors and scientific institutes to collaborate with, and use their experience to produce new knowledge in the future.PMID:36407029 | PMC:PMC9661537 | DOI:10.5812/ijem-120812