PubMed

Concentrations of legacy and new contaminants are related to metabolite profiles in Hudson Bay polar bears. Environ Res. 2018 Oct 11;168:364-374 Authors: Morris AD, Letcher RJ, Dyck M, Chandramouli B, Cosgrove J Abstract There are very few metabolomics assessments based on field accumulated, uncontrolled contaminant exposures in wildlife, particularly in the Arctic. In the present study, targeted metabolomics and contaminant data were analyzed together to assess potential influences of contaminant exposure on the hepatic metabolome of male polar bears (n = 29) from the southern and western Hudson Bay (SHB and WHB respectively), Canada. The 29 metabolites identified as important in the differentiation of the two subpopulations after partial least squares discriminant analysis (PLS-DA) included phosphatidylcholines (PCs), acylcarnitines (ACs; involved in β-oxidation of fatty acids), and the fatty acid (FA) arachidonic acid (ARA). Perfluorinated alkyl substances, polybrominated diphenyl ethers, dichlorodiphenyldichloroethylene (p,p'-DDE) and some highly chlorinated ortho-polychlorinated biphenyl congeners were greater in the SHB bears and were consistently inversely correlated with discriminating ACs and PCs between the subpopulations. The concentrations of discriminatory, legacy organochlorine pesticides along with one tetrachlorobiphenyl were greater in the WHB and were directly correlated with the VIP-identified ACs and PCs. ARA, glycerophospholipid and several amino acid metabolic pathways were identified as different between subpopulations and/or were impacted. ARA is an important, conditionally essential, dietary n-6 FA and is also part of the inflammation response, and elevated concentrations in the SHB could be related to differences in chronic contaminant exposure and/or differences in diet and/or season, among a number of possible explanations. Dietary tracers (stable isotopes of carbon and nitrogen) were correlated with some discriminatory metabolites, supporting the hypothesis that dietary variation was also an important factor in the differentiation of the subpopulations. The results suggest linkages between contaminant exposure in Hudson Bay polar bears and elements of the hepatic metabolome, particularly those related to lipid metabolism. PMID: 30384230 [PubMed - as supplied by publisher]

Serum metabolomics analysis of mice that received repeated airway exposure to a water-soluble PM2.5 extract. Ecotoxicol Environ Saf. 2018 Oct 29;168:102-109 Authors: Zhao C, Niu M, Song S, Li J, Su Z, Wang Y, Gao Q, Wang H Abstract BACKGROUND: Air pollutant exposure negatively affects human health; however, the molecular mechanisms causing disease remain largely unclear. OBJECTIVES: To explore the effects of respiratory particulate matter (PM2.5) exposure on the serum metabolome and to identify biomarkers for risk assessment of PM2.5 exposure. METHODS: PM2.5 from Nanjing, China, was collected, and its water-soluble extract was subjected to component analysis. BALB/c mice received acute or prolonged exposure to insoluble PM2.5 particles or its water-soluble extract, and lung tissue was submitted to histopathological analyses. Serum samples were collected pre- and post-PM2.5 exposure and analyzed by liquid chromatography/mass spectrometry. RESULTS: Component analysis revealed that metals and inorganic ions were the most abundant components in the soluble PM2.5 samples. Acute exposure to insoluble PM2.5 particles and prolonged exposure to the water-soluble PM2.5 extract both induced severe lung injury, and the lung histopathological scores were significantly associated with PM2.5 exposure. Metabolomics analysis showed that prolonged exposure to the water-soluble PM2.5 extract was associated with statistically significant metabolite changes; the serum concentrations of 30 known metabolites, including metabolites of phospholipids, amino acids and sphingolipids, differed significantly between the control and PM2.5 exposure group. Pathway analysis identified an association of the tricarboxylic acid cycle (TCA) and the phospholipase metabolism pathway with PM2.5 exposure. The most influential metabolites for discriminating between the PM2.5-exposure group serum and the control serum were LysoPE, LysoPC, LGPC, citric acid, PAF C-18, NeuAcalpha2-3Galbeta-Cer, Lyso-PAF C-16, ganglioside GA2, 1-sn-glycero-3-phosphocholine, PC and L-tryptophan. CONCLUSIONS: Respiratory exposure to water-soluble PM2.5 extract has developmental consequences affecting not only the respiratory system but also metabolism. PMID: 30384157 [PubMed - as supplied by publisher]

Metabolomics in Systems Biology. Adv Exp Med Biol. 2018;1102:51-68 Authors: Baharum SN, Azizan KA Abstract Over the last decade, metabolomics has continued to grow rapidly and is considered a dynamic technology in envisaging and elucidating complex phenotypes in systems biology area. The advantage of metabolomics compared to other omics technologies such as transcriptomics and proteomics is that these later omics only consider the intermediate steps in the central dogma pathway (mRNA and protein expression). Meanwhile, metabolomics reveals the downstream products of gene and expression of proteins. The most frequently used tools are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Some of the common MS-based analyses are gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). These high-throughput instruments play an extremely crucial role in discovery metabolomics to generate data needed for further analysis. In this chapter, the concept of metabolomics in the context of systems biology is discussed and provides examples of its application in human disease studies, plant responses towards stress and abiotic resistance and also microbial metabolomics for biotechnology applications. Lastly, a few case studies of metabolomics analysis are also presented, for example, investigation of an aromatic herbal plant, Persicaria minor metabolome and microbial metabolomics for metabolic engineering applications. PMID: 30382568 [PubMed - in process]

Recent Development in Omics Studies. Adv Exp Med Biol. 2018;1102:1-9 Authors: Aizat WM, Ismail I, Noor NM Abstract The central dogma of molecular biology (DNA, RNA, protein and metabolite) has engraved our understanding of genetics in all living organisms. While the concept has been embraced for many decades, the development of high-throughput technologies particularly omics (genomics, transcriptomics, proteomics and metabolomics) has revolutionised the field to incorporate big data analysis including bioinformatics and systems biology as well as synthetic biology area. These omics approaches as well as systems and synthetic biology areas are now increasingly popular as seen by the growing numbers of publication throughout the years. Several journals which have published most of these related fields are also listed in this chapter to overview their impact and target journals. PMID: 30382565 [PubMed - in process]

Related Articles Artificial Intelligence and amniotic fluid multiomics analysis: The prediction of perinatal outcome in asymptomatic short cervix. Ultrasound Obstet Gynecol. 2018 Oct 31;: Authors: Bahado-Singh RO, Sonek J, McKenna D, Cool D, Aydas B, Turkoglu O, Bjorndahl T, Mandal R, Wishart D, Friedman P, Graham SF, Yilmaz A Abstract OBJECTIVE: To evaluate the utility of Artificial Intelligence i.e. Deep Learning (DL) and other machine learning techniques for the prediction of important pregnancy outcomes in asymptomatic short cervical length (CL). METHOD: The amniotic fluid (AF) had been obtained from second trimester patients with asymptomatic women with short cervical length (<15 mm). CL, funneling and the presence of AF 'sludge' were assessed in all cases. Combined targeted metabolomic and proteomic analysis of amniotic fluid (AF) was performed. A combination of liquid Chromatography -Mass spectrometry (LC-MS-MS and) and proton Nuclear Mass Spectrometry (1 H-NMR) -based metabolomics and targeted proteomics analysis (Bioplex Human cytokine Group-1 assay (Bio-Rad) consisting of chemokines, cytokines and growth factors, were performed on the AF samples. To determine the robustness of the markers we used multiple machine learning techniques including deep learning (DL) to predict moderate prematurity, <34 weeks, latency period prior to delivery, and NICU stay. Logistic regression analysis was also used. Omics biomarkers were evaluated alone and in combination with standard sonographic, clinical and demographic factors to predict outcome. Predictive accuracy was calculated using area under the receiver operating characteristics curve (AUC) and 95% CI, sensitivity and specificity values. RESULTS: Of a total of 32 patients in the study, complete omics analysis, demographic and clinical data and outcomes information was available in 26. Of these 11 (42.3%) of patients delivered at ≥ 34 weeks while 15 (57.7%) delivered < 34 weeks. There was no statistically significant difference in the CL (mean /SD CL 11.2 (4.40)mm versus 8.9 (5.30) mm, p=0.31. DL had an AUC (95%CI) of 0.89 (0.81-0.97) for delivery < 34 weeks gestation, 0.89 (0.79-0.99) for delivery < 28 days post -amniocentesis and 0.792 (0. 70-0.89) for NICU stay. These values were overall higher than for the other five machine learning methods. Each ML technique individually yielded statistically significantly prediction of the different perinatal outcomes. CONCLUSIONS: This is the first report using AI combined with proteomics , metabolomics and ultrasound assessment . Good to excellent prediction of important perinatal outcomes were achieved in asymptomatic mid-trimester CL shortening. AIM: The aim was to predict important perinatal outcomes in asymptomatic patients with shortened cervical length (CL) using Artificial intelligence analysis of amniotic fluid metabolomics and proteomics data. This article is protected by copyright. All rights reserved. PMID: 30381856 [PubMed - as supplied by publisher]

Related Articles UPLC/MS-Based Metabolomics Investigation of the Protective Effect of Hydrogen Gas Inhalation on Mice with Calcium Oxalate-Induced Renal Injury. Biol Pharm Bull. 2018;41(11):1652-1658 Authors: Lu H, Ding J, Liu W, Peng Z, Chen W, Sun X, Guo Z Abstract Hydrogen has a significant protective effect on calcium oxalate-induced renal injury, but its effect on metabolic profiles is unknown. This study showed the effects of hydrogen on serum and urine metabolites in a renal injury model. Ultra-HPLC quadrupole time-of-flight-MS-based metabolomics was used to characterise metabolic variations. Twenty-five serum metabolites and 14 urine metabolites showed differences in the the nitrogen and oxygen inhalation (NO), nitrogen and oxygen inhalation combined with calcium oxalate induction (CaOx), and hydrogen inhalation combined with calcium oxalate induction (HO+CaOx) groups. Nineteen serum metabolites and 7 urine metabolites showed significant restoration to normal levels after hydrogen gas (H2) treatment. These metabolites are primarily related to amino acid metabolism, fatty acid metabolism, and phospholipid metabolism. This study showed that a comprehensive metabolomics approach is an effective strategy to elucidate the mechanisms underlying the effects of hydrogen treatment on calcium oxalate-induced renal injury. PMID: 30381664 [PubMed - in process]

Related Articles Erratum for Hardison et al., "Transient Nutrient Deprivation Promotes Macropinocytosis-Dependent Intracellular Bacterial Community Development". mSphere. 2018 Oct 31;3(5): Authors: Hardison RL, Heimlich DR, Harrison A, Beatty WL, Rains S, Moseley MA, Thompson JW, Justice SS, Mason KM PMID: 30381357 [PubMed - in process]

Related Articles Hydrophilic interaction liquid chromatography coupled with quadrupole-orbitrap ultra high resolution mass spectrometry to quantitate nucleobases, nucleosides, and nucleotides during white tea withering process. Food Chem. 2018 Nov 15;266:343-349 Authors: Zhao F, Qiu X, Ye N, Qian J, Wang D, Zhou P, Chen M Abstract Nucleotides, nucleosides, and nucleobases are important bioactive compounds. Recent studies suggested that they possess taste activity. However, it remains unknown about their presence in white tea and how they change during white tea manufacture. Here, we first established method based on hydrophilic interaction liquid chromatography coupled with quadrupole-orbitrap ultra high resolution mass spectrometry (HILIC-Quadrupole-Orbitrap-UHRMS) platform, then applied it to study the dynamic changes of nucleotides, nucleosides, and nucleobases during white tea withering process. Five compounds, including adenosine 5'-monophosphate monohydrate (AMP), guanosine 5'-monophosphate disodium salt hydrate (GMP), adenosine, cytidine, thymine and uracil, were detected from withering samples. They showed a general decline trend during white tea withering process, however, considerable amount of them was retained after withering for 48 h except adenosine which was below detection limit after withering for 21 h. This study provided a complete picture about nucleotides, nucleosides and nucleobases changes during white tea withering process. PMID: 30381196 [PubMed - in process]

Related Articles Untargeted metabolite profiling for koji-fermentative bioprocess unravels the effects of varying substrate types and microbial inocula. Food Chem. 2018 Nov 15;266:161-169 Authors: Seo HS, Lee S, Singh D, Shin HW, Cho SA, Lee CH Abstract Untargeted metabolomics unraveled the effects of varying substrates (soybean, wheat, and rice) and inocula (Aspergillus oryzae and Bacillus amyloliquefaciens) on metabolite compositions of koji, a starter ingredient in various Asian fermented foods. Multivariate analyses of the hyphenated mass spectrometry datasets for different koji extracts highlighted 61 significantly discriminant primary metabolites (sugars and sugar alcohols, organic acids, amino acids, fatty acids, nucleosides, phenolic acids, and vitamins) according to varying substrates and inocula combinations. However, 59 significantly discriminant secondary metabolites were evident for koji-types with varying substrates only, viz., soybean (flavonoids, soyasaponins, and lysophospholipids), wheat (flavones and lysophospholipids), and rice (flavonoids, fatty acids derivatives, and lysophospholipids). Independently, the substrates influenced primary metabolite compositions in koji (soybean > wheat, rice). The inocula choice of A. oryzae engendered higher carbohydrates, organic acids, and lipid derivative levels commensurate with high α-amylase and β-glucosidase activities, while B. amyloliquefaciens affected higher amino acids levels, in respective koji types. PMID: 30381171 [PubMed - in process]

Related Articles Metabolic and proteomic responses to long-term protein restriction in a pig model. J Agric Food Chem. 2018 Nov 01;: Authors: Li Y, Yin J, Han H, Liu G, Deng D, Kim SW, Wu G, Li T, Yin Y Abstract Protein restriction is associated with extended lifespan and reduced incidence and progression of multiple age-related diseases. The underlying mechanism of metabolic and proteomic responses to the long-term dietary protein restriction, however, has not been fully uncovered. The present study aimed to identify the metabolic and proteomic profiles in a low-protein diet-fed pig model. Intestinal and liver metabolomics showed that amino acid metabolism was highly associated with dietary protein restriction. Interestingly, blood was characterized by markedly higher abundances of Ser, Gly, Glu, Thr, Ala, Lys, and Met levels, and lower abundances of His, Val, and Ile levels regardless of the age of pigs from piglets to adult pigs. Amino acid transporters might contribute to the changed amino acid pools and serve as a feedback regulatory mechanism in response to protein restriction. iTRAQ-based quantitative proteomics approach identified more than 10 differently expressed proteins in protein restricted pigs and KEGG pathway analysis showed that significant enrichment of proteins involved in metabolic pathways, PI3K-Akt signaling pathway, lysosome, spliceosome, oxidative phosphorylation, phagosome, and DNA replication. Western blot analysis further confirmed that protein restriction markedly inactivated Akt and mTOR signals in pigs. This study indicates that dietary protein restriction leads to a shift in the host metabolism in a pig model, especially for amino acid metabolism. Along with proteomics, our findings unveil potential mechanisms for integrating how protein restriction modulates host metabolism. PMID: 30380847 [PubMed - as supplied by publisher]

Related Articles Investigation into Cellular Glycolysis for the Mechanism Study of Energy Metabolism Disorder Triggered by Lipopolysaccharide. Toxins (Basel). 2018 Oct 29;10(11): Authors: Zhang R, Ji J, Blaženović I, Pi F, Wang T, Zhang Y, Sun X Abstract Lipopolysaccharide (LPS) is the main virulence factor of Gram-negative bacteria, which can incite inflammation in tissues by inducing cells to secrete a variety of proinflammatory mediators, including cytokines, chemokines, interleukins, and prostaglandins. Herein, we chose LPS as an inducer to establish an inflammatory model of HeLa cells, and explored the effects of LPS on energy metabolism. We treated HeLa cells with different concentrations (0, 0.4, 1.0, 2.0, 4.0, and 6.0 μg/mL) of LPS for 24 h, and explored its effects on intercellular adenosine triphosphate (ATP) levels, intercellular nitrous oxide (NO) content, mitochondrial functions, and enzyme activities related to energy metabolism. Furthermore, we used metabonomics to study the metabolites that participated in energy metabolism. We found a positive correlation between LPS concentrations and intracellular ATP levels. In addition, LPS increased intracellular NO production, altered mitochondrial functions, strengthened glycolytic enzyme activities, and changed metabolites related to energy metabolism. Hence, in this study, we showed that LPS can strengthen energy metabolism by enhancing glycolysis, which could be used as an early diagnostic biomarker or a novel therapeutic target for inflammation-associated cancers. PMID: 30380670 [PubMed - in process]

Related Articles Metabonomic profiling of chronic intermittent hypoxia in a mouse model. Respir Physiol Neurobiol. 2018 10;256:157-173 Authors: Conotte S, Tassin A, Conotte R, Colet JM, Zouaoui Boudjeltia K, Legrand A Abstract Chronic intermittent hypoxia (ChIH) is a dominant feature of obstructive sleep apnoea (OSA) and is associated to metabolic alterations and oxidative stress (OS). Although management of OSA is well established, the research of new biomarkers that are independent of confounding factors remains necessary to improve the early detection of comorbidity and therapeutic follow-up. In this study, the urinary metabonomic profile associated to intermittent hypoxia was evaluated in a mouse model. When exposed to intermittent hypoxia, animals showed a significant alteration in energy metabolism towards anaerobic pathways and signs of OS imbalance. A compensatory response was observed over time. Our data also indicates an excess production of vitamin B3, liver function modulations and a stimulation of creatine synthesis which could be used to evaluate the ChIH repercussions. As well, TMAO and allantoin could constitute interesting biomarker candidates, respectively in the context of cardiovascular risk and OS associated to OSA. PMID: 29522877 [PubMed - indexed for MEDLINE]

Plasma metabolomics of children with aberrant serum lipids and inadequate micronutrient intake. PLoS One. 2018;13(10):e0205899 Authors: Li KJ, Jenkins N, Luckasen G, Rao S, Ryan EP Abstract Blood lipids have served as key biomarkers for cardiovascular disease (CVD) risk, yet emerging evidence indicates metabolite profiling might reveal a larger repertoire of small molecules that reflect altered metabolism, and which may be associated with early disease risk. Inadequate micronutrient status may also drive or exacerbate CVD risk factors that emerge during childhood. This study aimed to understand relationships between serum lipid levels, the plasma metabolome, and micronutrient status in 38 children (10 ± 0.8 years) at risk for CVD. Serum lipid levels were measured via autoanalyzer and average daily micronutrient intakes were calculated from 3-day food logs. Plasma metabolites were extracted using 80% methanol and analyzed via ultra-high-performance liquid chromatography-tandem mass spectrometry. Spearman's rank-order coefficients (rs) were computed for correlations between the following serum lipids [total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides (TG)], 805 plasma metabolites, and 17 essential micronutrients. Serum lipid levels in the children ranged from 128-255 mg/dL for total cholesterol, 67-198 mg/dL for LDL, 31-58 mg/dL for HDL, and 46-197 mg/dL for TG. The majority of children (71 to 100%) had levels lower than the Recommended Daily Allowance for vitamin E, calcium, magnesium, folate, vitamin D, and potassium. For sodium, 76% of children had levels above the Upper Limit of intake. Approximately 30% of the plasma metabolome (235 metabolites) were significantly correlated with serum lipids. As expected, plasma cholesterol was positively correlated with serum total cholesterol (rs = 0.6654; p<0.0001). Additionally, 27 plasma metabolites were strongly correlated with serum TG (rs ≥0.60; p≤0.0001), including alanine and diacylglycerols, which have previously been associated with cardiometabolic and atherosclerotic risk in adults and experimental animals. Plasma metabolite profiling alongside known modifiable risk factors for children merit continued investigation in epidemiological studies to assist with early CVD detection, mitigation, and prevention via lifestyle-based interventions. PMID: 30379930 [PubMed - in process]

Scaled traumatic brain injury results in unique metabolomic signatures between gray matter, white matter, and serum in a piglet model. PLoS One. 2018;13(10):e0206481 Authors: Baker EW, Henderson WM, Kinder HA, Hutcheson JM, Platt SR, West FD Abstract Traumatic brain injury (TBI) is a leading cause of death and long-term disability in the United States. The heterogeneity of the disease coupled with the lack of comprehensive, standardized scales to adequately characterize multiple types of TBI remain to be major challenges facing effective therapeutic development. A systems level approach to TBI diagnosis through the use of metabolomics could lead to a better understanding of cellular changes post-TBI and potential therapeutic targets. In the current study, we utilize a GC-MS untargeted metabolomics approach to demonstrate altered metabolism in response to TBI in a translational pig model, which possesses many neuroanatomical and pathophysiologic similarities to humans. TBI was produced by controlled cortical impact (CCI) in Landrace piglets with impact velocity and depth of depression set to 2m/s;6mm, 4m/s;6mm, 4m/s;12mm, or 4m/s;15mm resulting in graded neural injury. Serum samples were collected pre-TBI, 24 hours post-TBI, and 7 days post-TBI. Partial least squares discriminant analysis (PLS-DA) revealed that each impact parameter uniquely influenced the metabolomic profile after TBI, and gray and white matter responds differently to TBI on the biochemical level with evidence of white matter displaying greater metabolic change. Furthermore, pathway analysis revealed unique metabolic signatures that were dependent on injury severity and brain tissue type. Metabolomic signatures were also detected in serum samples which potentially captures both time after injury and injury severity. These findings provide a platform for the development of a more accurate TBI classification scale based unique metabolomic signatures. PMID: 30379914 [PubMed - in process]

Increased Plasma Acetylcarnitine in Sepsis Is Associated With Multiple Organ Dysfunction and Mortality: A Multicenter Cohort Study. Crit Care Med. 2018 Oct 30;: Authors: Chung KP, Chen GY, Chuang TY, Huang YT, Chang HT, Chen YF, Liu WL, Chen YJ, Hsu CL, Huang MT, Kuo CH, Yu CJ Abstract OBJECTIVES: Recent metabolomic studies of sepsis showed that increased circulatory acylcarnitines were associated with worse survival. However, it is unknown whether plasma carnitine and acylcarnitines can reflect the severity of sepsis, and the role of specific acylcarnitines in prognostic assessment need further confirmation. This study aimed to clarify these questions. DESIGN: Prospective multicenter cohort studies with derivation and validation cohort design. SETTING: ICUs at two medical centers and three regional hospitals in Taiwan. PATIENTS: Patients with sepsis and acute organ dysfunction were enrolled. Recruitment of the derivation (n = 90) and validation cohorts (n = 120) occurred from October 2010 through March 2012 and January 2013 through November 2014, respectively. INTERVENTIONS: Plasma samples were collected immediately after admission, and the levels of carnitine and acylcarnitines were measured by ultra-high performance liquid chromatography-mass spectrometry. MEASUREMENTS AND MAIN RESULTS: In the derivation cohort, increased plasma levels of short- and medium-chain acylcarnitines were significantly associated with hepatobiliary dysfunction, renal dysfunction, thrombocytopenia, and hyperlactatemia. However, acetylcarnitine is the only acylcarnitine significantly correlating with various plasma cytokine concentrations and also associated with blood culture positivity and 28-day mortality risk. The association between plasma acetylcarnitine and multiple organ dysfunction severity, blood culture positivity, and 28-day mortality, was confirmed in the validation cohort. Patients with high plasma acetylcarnitine (≥ 6,000 ng/mL) had significantly increased 28-day mortality compared with those with plasma acetylcarnitine less than 6,000 ng/mL (52.6% vs 13.9%; hazard ratio, 5.293; 95% CI, 2.340-11.975; p < 0.001 by Cox proportional hazard model). CONCLUSIONS: We confirm that plasma acetylcarnitine can reflect the severity of organ dysfunction, inflammation, and infection in sepsis and can serve as a prognostic biomarker for mortality prediction. PMID: 30379669 [PubMed - as supplied by publisher]

Identification of novel metabolomic biomarkers in an experimental model of septic acute kidney injury. Am J Physiol Renal Physiol. 2018 Oct 31;: Authors: Izquierdo-Garcia JL, Nin N, Cardinal-Fernandez P, Rojas Y, de Paula M, Granados R, Martínez-Caro L, Ruiz-Cabello J, Lorente JÁ Abstract The aim of this study is the identification of metabolomic biomarkers of sepsis and sepsis-induced acute kidney injury (AKI) in an experimental model. Pigs were anesthetized and monitored to measure mean arterial pressure (MAP), systemic blood flow (QT), mean pulmonary arterial pressure (MPAP), renal artery blood flow (QRA), renal cortical blood flow (QRC), and urine output (UO). Sepsis was induced at t=0 min by the administration of live Escherichia coli (n=6) or saline (n=8). At t=300 min, animals were sacrificed. Renal tissue, urine and serum samples were analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy. Principal component analyses were performed on the processed NMR spectra to highlight kidney injury biomarkers. Sepsis was associated with decreased QT and MAP, and decreased QRA, QRC and urine output. Creatinine serum concentration and neutrophil gelatinase-associated lipocalin serum and urine concentrations increased. NMR-based metabolomics analysis found metabolic differences between control and septic animals: (i) in kidney tissue, increased lactate and nicotinuric acid, and decreased valine, aspartate, glucose and threonine; (ii) in urine, increased isovaleroglycine, aminoadipic acid, N-acetylglutamine, N-acetylaspartate and ascorbic acid, and decreased myoinositol and phenylacetylglycine; (iii) in serum, increased lactate, alanine, pyruvate and glutamine, and decreased valine, glucose and betaine concentrations. The concentration of several metabolites altered in renal tissue and urine samples from septic animals showed a significant correlation with markers of AKI (i.e., creatinine and NGAL serum concentrations). NMR-based metabolomics is a potentially useful tool for biomarker identification of sepsis-induced AKI. PMID: 30379100 [PubMed - as supplied by publisher]

Flow Injection-Traveling Wave Ion Mobility-Mass Spectrometry for Rapid Prostate Cancer Metabolomics. Anal Chem. 2018 Oct 31;: Authors: Zang X, Monge ME, Gaul DA, Fernandez FM Abstract Flow injection-traveling wave ion mobility-mass spectrometry (FI-TWIM-MS) was applied to the non-targeted metabolic profiling of serum extracts from 61 prostate cancer (PCa) patients and 42 controls with an analysis speed of 6 minutes per sample, including a wash run. Comprehensive data mining of the mobility-mass domain was used to discriminate species with various charge states and filter matrix salt cluster ions. Specific criteria were developed to ensure correct grouping of adducts, in-source fragments, and impurities in the dataset. Endogenous metabolites were identified with high confidence using FI-TWIM-MS/MS and collision cross-section (CCS) matching with chemical standards or CCS databases. PCa patient samples were distinguished from control samples with good accuracies (88.3-89.3%), sensitivities (88.5-90.2%), and specificities (88.1%) using supervised multivariate classification methods. Although largely underutilized in metabolomics studies, FI-TWIM-MS proved advantageous in terms of analysis speed, separation of ions in complex mixtures, improved signal-to-noise ratio, and reduction of spectral congestion. Results from this study showcase the potential of FI-TWIM-MS as a high throughput metabolic profiling tool for large scale metabolomics studies. PMID: 30379062 [PubMed - as supplied by publisher]

The protective effects of Poria cocos-derived polysaccharide CMP33 against IBD in mice and its molecular mechanism. Food Funct. 2018 Oct 31;: Authors: Liu X, Yu X, Xu X, Zhang X, Zhang X Abstract In this study, the protective effects of a carboxymethyl polysaccharide CMP33 from Poria cocos against inflammatory bowel disease (IBD) were investigated using TNBS-induced colitis in mice. The results showed that CMP33 markedly ameliorated the severity of colitis, including a 2-fold decrease in the mortality rate, a 50% decrease in disease activity index, and a 36%-44% decrease in macro- or microscopic histopathological score, compared with TNBS administration. Moreover, CMP33 decreased the levels of pro-inflammatory cytokines and increased the levels of anti-inflammatory cytokines in the colon tissue and serum of colitic mice. Using iTRAQ-coupled- nano-HPLC-MS/MS-based proteomics, the protein profiles after TNBS, high- or low-dose CMP33 and salazosulfapyridine (SASP) treatments were compared and many differentially expressed proteins were identified. Among them, 7 proteins (Hmgcs2, Fabp2, Hp, B4galnt2, B3gnt6, Sap and Ca1) were proposed to be the common targeting protein group (TPG) of CMP33 and drug SASP. Particularly, some targeting proteins were CMP33-dose-specific: high-dose-specific TPG (Mtco3, Gal-6, Mptx, S100 g and Hpx) and low-dose-specific TPG (Zg16, Hexb, Insl5, Cept1, Hspb6 and Ifi27l2b), suggesting the complex acting mechanism of CMP33. GC-TOF-MS-based metabolomics revealed that oleic acid and dihydrotestosterone could be the common targets of CMP33 and SASP. By integrative analysis of proteomics and metabolomics, key protein-metabolite pathways (PMP) were identified, PMP for high-dose: 2-hydroxybutyric acid - (GPT, GGH) - glutathione - ALB - testosterone - TTR - dihydrotestosterone; PMP for low-dose: (PYY, FABP2, HMGCS2) - oleic acid - TTR - dihydrotestosterone. In total, these results demonstrated the protective effects of CMP33 against IBD in mice through the potential TPG and PMP. PMID: 30378628 [PubMed - as supplied by publisher]

Nanoparticle microarray for high-throughput microbiome metabolomics using matrix-assisted laser desorption ionization mass spectrometry. Anal Bioanal Chem. 2018 Oct 30;: Authors: Hansen RL, Dueñas ME, Looft T, Lee YJ Abstract A high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI)-MS-based metabolomics platform was developed using a pre-fabricated microarray of nanoparticles and organic matrices. Selected organic matrices, inorganic nanoparticle (NP) suspensions, and sputter coated metal NPs, as well as various additives, were tested for metabolomics analysis of the turkey gut microbiome. Four NPs and one organic matrix were selected as the optimal matrix set: α-cyano-4-hydroycinnamic acid, Fe3O4 and Au NPs in positive ion mode with 10 mM sodium acetate, and Cu and Ag NPs in negative ion mode with no additive. Using this set of five matrices, over two thousand unique metabolite features were reproducibly detected across intestinal samples from turkeys fed a diet amended with therapeutic or sub-therapeutic antibiotics (200 g/ton or 50 g/ton bacitracin methylene disalicylate (BMD), respectively), or non-amended feed. Among the thousands of unique features, 56 of them were chemically identified using MALDI-MS/MS, with the help of in-parallel liquid chromatography (LC)-MS/MS analysis. Lastly, as a proof of concept application, this protocol was applied to 52 turkey cecal samples at three different time points from the antibiotic feed trial. Statistical analysis indicated variations in the metabolome of turkeys with different ages or treatments. Graphical abstract ᅟ. PMID: 30377739 [PubMed - as supplied by publisher]

Identification of TMAO-producer phenotype and host-diet-gut dysbiosis by carnitine challenge test in human and germ-free mice. Gut. 2018 Oct 30;: Authors: Wu WK, Chen CC, Liu PY, Panyod S, Liao BY, Chen PC, Kao HL, Kuo HC, Kuo CH, Chiu THT, Chen RA, Chuang HL, Huang YT, Zou HB, Hsu CC, Chang TY, Lin CL, Ho CT, Yu HT, Sheen LY, Wu MS Abstract OBJECTIVE: The gut microbiota-derived metabolite, trimethylamine N-oxide (TMAO) plays an important role in cardiovascular disease (CVD). The fasting plasma TMAO was shown as a prognostic indicator of CVD incident in patients and raised the interest of intervention targeting gut microbiota. Here we develop a clinically applicable method called oral carnitine challenge test (OCCT) for TMAO-related therapeutic drug efforts assessment and personalising dietary guidance. DESIGN: A pharmacokinetic study was performed to verify the design of OCCT protocol. The OCCT was conducted in 23 vegetarians and 34 omnivores to validate gut microbiota TMAO production capacity. The OCCT survey was integrated with gut microbiome, host genotypes, dietary records and serum biochemistry. A humanised gnotobiotic mice study was performed for translational validation. RESULTS: The OCCT showed better efficacy than fasting plasma TMAO to identify TMAO producer phenotype. The omnivores exhibited a 10-fold higher OR to be high TMAO producer than vegetarians. The TMAO-associated taxa found by OCCT in this study were consistent with previous animal studies. The TMAO producer phenotypes were also reproduced in humanised gnotobiotic mice model. Besides, we found the faecal CntA gene was not associated with TMAO production; therefore, other key relevant microbial genes might be involved. Finally, we demonstrated the urine TMAO exhibited a strong positive correlation with plasma TMAO (r=0.92, p<0.0001) and improved the feasibility of OCCT. CONCLUSION: The OCCT can be used to identify TMAO-producer phenotype of gut microbiota and may serve as a personal guidance in CVD prevention and treatment. TRIAL REGISTRATION NUMBER: NCT02838732; Results. PMID: 30377191 [PubMed - as supplied by publisher]