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Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance.
Ashraf, MF, Hou, D, Hussain, Q, Imran, M, Pei, J, Ali, M, Shehzad, A, Anwar, M, Noman, A, Waseem, M, et al
International journal of molecular sciences. 2022;(2)
Abstract
Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.
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Plasma Metabolomics Profile of "Insulin Sensitive" Male Hypogonadism after Testosterone Replacement Therapy.
Zolla, L, Ceci, M
International journal of molecular sciences. 2022;(3)
Abstract
Male hypogonadism is a disorder characterized by low levels of testosterone, but patients can either show normal insulin (insulin-sensitive (IS)) or over time they can become insulin-resistant (IR). Since the two groups showed different altered metabolisms, testosterone replacement therapy (TRT) could achieve different results. In this paper, we analyzed plasma from 20 IS patients with low testosterone (<8 nmol/L) and HOMAi < 2.5. The samples, pre- and post-treatment with testosterone for 60 days, were analyzed by UHPLC and mass spectrometry. Glycolysis was significantly upregulated, suggesting an improved glucose utilization. Conversely, the pentose phosphate pathway was reduced, while the Krebs cycle was not used. Branched amino acids and carnosine metabolism were positively influenced, while β-oxidation of fatty acids (FFA) was not activated. Cholesterol, HDL, and lipid metabolism did not show any improvements at 60 days but did so later in the experimental period. Finally, both malate and glycerol shuttle were reduced. As a result, both NADH and ATP were significantly lower. Interestingly, a significant production of lactate was observed, which induced the activation of the Cori cycle between the liver and muscles, which became the main source of energy for these patients without involving alanine. Thus, the treatment must be integrated with chemicals which are not restored in order to reactivate energy production.
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Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study.
Stepien, M, Keski-Rahkonen, P, Kiss, A, Robinot, N, Duarte-Salles, T, Murphy, N, Perlemuter, G, Viallon, V, Tjønneland, A, Rostgaard-Hansen, AL, et al
International journal of cancer. 2021;(3):609-625
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Abstract
Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.
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Leonurine affected homocysteine-methionine metabolism based on metabolomics and gut microbiota studies of clinical trial samples.
Liao, J, Suguro, R, Zhao, X, Yu, Y, Cui, Y, Zhu, YZ
Clinical and translational medicine. 2021;(10):e535
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Metabolomic Profiling of Human Urine Samples Using LC-TIMS-QTOF Mass Spectrometry.
Di Poto, C, Tian, X, Peng, X, Heyman, HM, Szesny, M, Hess, S, Cazares, LH
Journal of the American Society for Mass Spectrometry. 2021;(8):2072-2080
Abstract
The identification of metabolites in biological samples is challenging due to their chemical and structural diversity. Ion mobility spectrometry (IMS) separates ionized molecules based on their mobility in a carrier buffer gas giving information about the ionic shape by measuring the rotationally averaged collision cross-section (CCS) value. This orthogonal descriptor, in combination with the m/z, isotopic pattern distribution, and MS/MS spectrum, has the potential to improve the identification of molecular molecules in complex mixtures. Urine metabolomics can reveal metabolic differences, which arise as a result of a specific disease or in response to therapeutic intervention. It is, however, complicated by the presence of metabolic breakdown products derived from a wide range of lifestyle and diet-related byproducts, many of which are poorly characterized. In this study, we explore the use of trapped ion mobility spectrometry (TIMS) via LC parallel accumulation with serial fragmentation (PASEF) for urine metabolomics. A total of 362 urine metabolites were characterized from 80 urine samples collected from healthy volunteers using untargeted metabolomics employing HILIC and RP chromatography. Additionally, three analytes (Trp, Phe, and Tyr) were selected for targeted quantification. Both the untargeted and targeted data was highly reproducible and reported CCS measurements for identified metabolites were robust in the presence of the urine matrix. A comparison of CCS values among different laboratories was also conducted, showing less than 1.3% ΔCCS values across different platforms. This is the first report of a human urine metabolite database compiled with CCS values experimentally acquired using an LC-PASEF TIMS-qTOF platform.
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Untargeted metabolomics reveals plasma metabolites predictive of ectopic fat in pancreas and liver as assessed by magnetic resonance imaging: the TOFI_Asia study.
Wu, ZE, Fraser, K, Kruger, MC, Sequeira, IR, Yip, W, Lu, LW, Plank, LD, Murphy, R, Cooper, GJS, Martin, JC, et al
International journal of obesity (2005). 2021;(8):1844-1854
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Abstract
BACKGROUND Excess visceral obesity and ectopic organ fat is associated with increased risk of cardiometabolic disease. However, circulating markers for early detection of ectopic fat, particularly pancreas and liver, are lacking. METHODS Lipid storage in pancreas, liver, abdominal subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) from 68 healthy or pre-diabetic Caucasian and Chinese women enroled in the TOFI_Asia study was assessed by magnetic resonance imaging/spectroscopy (MRI/S). Plasma metabolites were measured with untargeted liquid chromatography-mass spectroscopy (LC-MS). Multivariate partial least squares (PLS) regression identified metabolites predictive of VAT/SAT and ectopic fat; univariate linear regression adjusting for potential covariates identified individual metabolites associated with VAT/SAT and ectopic fat; linear regression adjusted for ethnicity identified clinical and anthropometric correlates for each fat depot. RESULTS PLS identified 56, 64 and 31 metabolites which jointly predicted pancreatic fat (R2Y = 0.81, Q2 = 0.69), liver fat (RY2 = 0.8, Q2 = 0.66) and VAT/SAT ((R2Y = 0.7, Q2 = 0.62)) respectively. Among the PLS-identified metabolites, none of them remained significantly associated with pancreatic fat after adjusting for all covariates. Dihydrosphingomyelin (dhSM(d36:0)), 3 phosphatidylethanolamines, 5 diacylglycerols (DG) and 40 triacylglycerols (TG) were associated with liver fat independent of covariates. Three DGs and 12 TGs were associated with VAT/SAT independent of covariates. Notably, comparison with clinical correlates showed better predictivity of ectopic fat by these PLS-identified plasma metabolite markers. CONCLUSIONS Untargeted metabolomics identified candidate markers of visceral and ectopic fat that improved fat level prediction over clinical markers. Several plasma metabolites were associated with level of liver fat and VAT/SAT ratio independent of age, total and visceral adiposity, whereas pancreatic fat deposition was only associated with increased sulfolithocholic acid independent of adiposity-related parameters, but not age.
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Urinary metabolomic profiling reveals difference between two traditional Chinese medicine subtypes of coronary heart disease.
Guo, N, Chen, Y, Yang, X, Yan, H, Fan, B, Quan, J, Wang, M, Yang, H
Journal of chromatography. B, Analytical technologies in the biomedical and life sciences. 2021;:122808
Abstract
The World Health Organization has shown that coronary heart disease (CHD) is a more common cause of death than cancer. In traditional Chinese medicine (TCM), CHD is classified as a form of thoracic obstruction that can be divided in different subtypes including Qi stagnation with blood stasis (QS) and Qi deficiency with blood stasis (QD). Different treatment strategies are used based on this subtyping. Owing to the lack of scientific markers in the diagnosis of these subtypes, subjective judgments made by clinicians have limited the objective manner for utility of TCM in the treatment of CHD. Untargeted (UHPLC-QTOF-MS) and targeted (UHPLC-MS/MS) metabolomics approaches were employed to search significantly different metabolites related to the QS or QD subtypes of CHD with angina pectoris in this study. A total of 42 metabolites were obtained in the untargeted metabolomics analysis and 34 amino acids were detected in the targeted metabolomics analysis. In total, 16 metabolites were found significantly different among different groups. The results showed distinct metabolic profiles of urine samples not only between CHD patients and healthy controls, but also between the two subtypes of CHD. Pathway analysis of the significantly varied metabolites revealed that there were subtype-related differences in the activity of pathways. Therefore, urinary metabolomics can reveal the pathological changes of CHD in different subtypes, make the diagnosis of CHD in different subtypes in an objective manner and comprehensive and contribute to personalized treatment by providing scientific evidence.
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Characterization of Metabolites in Plasma, Urine and Feces of Healthy Participants after Taking Brahmi Essence for Twelve Weeks Using LC-ESI-QTOF-MS Metabolomic Approach.
Minale, G, Saesong, T, Temkitthawon, P, Waranuch, N, Nuengchamnong, N, Chootip, K, Kamkaew, N, Kongbangkerd, T, Engsuwan, J, Ingkaninan, K
Molecules (Basel, Switzerland). 2021;(10)
Abstract
Brahmi essence, developed from Bacopa monnieri (L.) Wettst. standardized extract and mulberry juice, was proven to improve the memory speed of healthy participants aged 55-80 years old, following a 12-week dietary program. However, the metabolites have not yet been reported. Our objective was to characterize the altered metabolites in the plasma, urine, and feces of healthy volunteers after consumption of Brahmi essence for 12 weeks, using the LC-MS metabolomics approach. The altered metabolites were selected from OPLS-DA S-plots; 15 metabolites in the plasma, 7 in the urine, and 17 in the feces samples were tentatively identified by comparison with an online database and literature. The metabolites in the plasma samples were in the classes of amino acids, acylcarnitine, and phospholipids. Benzeneactamide-4-O-sulphate and 3-hydroxyhippuric acid were found in urine samples. The metabolites in the class of amino acids, together with jujubogenin and pseudojujubogenin, were identified in the fecal samples. The aminoacyl-tRNA, aromatic amino acids, and branched-chain amino acid biosynthetic pathways were mainly related to the identified metabolites in all three samples. It could be implied that those metabolites and their pathways might be linked with the effect of Brahmi essence on memory speed.
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The effect of obstructive sleep apnea on peripheral blood amino acid and biogenic amine metabolome at multiple time points overnight.
Kiens, O, Taalberg, E, Ivanova, V, Veeväli, K, Laurits, T, Tamm, R, Ottas, A, Kilk, K, Soomets, U, Altraja, A
Scientific reports. 2021;(1):10811
Abstract
There are no clinical studies that have investigated the differences in blood serum metabolome between obstructive sleep apnea (OSA) patients and controls. In a single-center prospective observational study, we compared metabolomic profiles in the serum of OSA patients with apnea-hypopnea index (AHI) ≥ 15/h and control individuals. Peripheral blood was obtained at 3 different time points overnight: 9:00 p.m.; 5:00 a.m. and 7:00 a.m. We used a targeted approach for detecting amino acids and biogenic amines and analyzed the data with ranked general linear model for repeated measures. We recruited 31 patients with moderate-to-severe OSA and 32 controls. Significant elevations in median concentrations of alanine, proline and kynurenine in OSA patients compared to controls were detected. Significant changes in the overnight dynamics of serum concentrations occurred in OSA: glutamine, serine, threonine, tryptophan, kynurenine and glycine levels increased, whereas a fall occurred in the same biomarker levels in controls. Phenylalanine and proline levels decreased slightly, compared to a steeper fall in controls. The study indicates that serum profiles of amino acid and biogenic amines are significantly altered in patients with OSA referring to vast pathophysiologic shifts reflected in the systemic metabolism.
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Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants.
Ali, S, Tyagi, A, Bae, H
International journal of molecular sciences. 2021;(13)
Abstract
Plants, being sessile, face an array of biotic and abiotic stresses in their lifespan that endanger their survival. Hence, optimized uptake of mineral nutrients creates potential new routes for enhancing plant health and stress resilience. Recently, minerals (both essential and non-essential) have been identified as key players in plant stress biology, owing to their multifaceted functions. However, a realistic understanding of the relationship between different ions and stresses is lacking. In this context, ionomics will provide new platforms for not only understanding the function of the plant ionome during stresses but also identifying the genes and regulatory pathways related to mineral accumulation, transportation, and involvement in different molecular mechanisms under normal or stress conditions. This article provides a general overview of ionomics and the integration of high-throughput ionomic approaches with other "omics" tools. Integrated omics analysis is highly suitable for identification of the genes for various traits that confer biotic and abiotic stress tolerance. Moreover, ionomics advances being used to identify loci using qualitative trait loci and genome-wide association analysis of element uptake and transport within plant tissues, as well as genetic variation within species, are discussed. Furthermore, recent developments in ionomics for the discovery of stress-tolerant genes in plants have also been addressed; these can be used to produce more robust crops with a high nutritional value for sustainable agriculture.