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Fulltext Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis

Deng L, Guo F, Cheng KK, Zhu J, Gu H, Raftery D, et al.

J Proteome Res, 2020 05 01;19(5):1965-1974.
PMID: 32174118 DOI: 10.1021/acs.jproteome.9b00793

In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Matched MeSH terms: Metabolomics
Plasma Metabolites as Predictors of Warfarin Outcome in Atrial Fibrillation

Bawadikji AA, Teh CH, Sheikh Abdul Kader MAB, Abdul Wahab MJB, Syed Sulaiman SA, Ibrahim B

Am J Cardiovasc Drugs, 2020 Apr;20(2):169-177.
PMID: 31435902 DOI: 10.1007/s40256-019-00364-2

BACKGROUND: Warfarin is prescribed as an oral anticoagulant to treat/prevent thromboembolism in conditions such as atrial fibrillation. As there is a narrow therapeutic window, treatment with warfarin is challenging. Pharmacometabonomics using nuclear magnetic resonance (NMR) spectroscopy may provide novel techniques for the identification of novel biomarkers of warfarin.
PURPOSE: The aim was to determine the metabolic fingerprint that predicts warfarin response based on the international normalized ratio (INR) in patients who are already receiving warfarin (phase I: identification) and to ascertain the metabolic fingerprint that discriminates stable from unstable INR in patients starting treatment with warfarin (phase II: validation).
EXPERIMENTAL APPROACH: A total of 94 blood samples were collected for phase I: 44 patients with stable INR and 50 with unstable INR. Meanwhile, 23 samples were collected for phase II: nine patients with stable INR and 14 with unstable INR. Data analysis was performed using multivariate analysis including principal component analysis and partial least square-discriminate analysis (PLS-DA), followed by univariate and multivariate logistic regression (MVLR) to develop a model to identify unstable INR biomarkers.
KEY RESULTS: For phase I, the PLS-DA model showed the following results: sensitivity 93.18%, specificity 91.49% and accuracy 92.31%. In the MVLR analysis of phase I, ten regions were associated with unstable INR. For phase II, the PLS-DA model showed the following results: sensitivity 66.67%, specificity 61.54% and accuracy 63.64%.
CONCLUSIONS AND IMPLICATIONS: We have shown that the pharmacometabonomics technique was able to differentiate between unstable and stable INR with good accuracy. NMR-based pharmacometabonomics has the potential to identify novel biomarkers in plasma, which can be useful in individualizing treatment and controlling warfarin side effects, thus, minimizing undesirable effects in the future.

Matched MeSH terms: Metabolomics/methods
Fulltext Antioxidant, α-Glucosidase, and Nitric Oxide Inhibitory Activities of Six Algerian Traditional Medicinal Plant Extracts and 1H-NMR-Based Metabolomics Study of the Active Extract

Hellal K, Maulidiani M, Ismail IS, Tan CP, Abas F

Molecules, 2020 Mar 10;25(5).
PMID: 32164186 DOI: 10.3390/molecules25051247

Claims of effective therapy against diabetes using plants including Peganum harmala L., Zygophyllum album, Anacyclus valentinus L., Ammodaucus leucotrichus, Lupinus albus, and Marrubium vulgare in Algerian empirical medicine prompted our interest in evaluating their antidiabetic activity by screening their free radical scavenging (DPPH), α-glucosidase, and nitric oxide (NO) inhibitory activities as well as the total phenolic content (TPC). Extracts of the selected plants were prepared using different ratios of ethanol (0, 50, 80, and 100%). In this study, 100%, and 80% ethanol extracts of L. albus were found to be the most potent, in inhibiting α-glucosidase activity with IC50 values of 6.45 and 8.66 μg/mL, respectively. The 100% ethanol extract of A. leucotrichus exhibited the highest free radical scavenging activity with an IC50 value of 26.26 μg/mL. Moreover, the highest TPC of 612.84 μg GAE/mg extract was observed in M. vulgare, extracted with 80% ethanol. Metabolite profiling of the active extract was conducted using 1H-NMR metabolomics. Partial least square analysis (PLS) was used to assess the relationship between the α-glucosidase inhibitory activity of L. albus and the metabolites identified in the extract. Based on the PLS model, isoflavonoids (lupinoisoflavone G, lupisoflavone, lupinoisolone C), amino acids (asparagine and thiamine), and several fatty acids (stearic acid and oleic acid) were identified as metabolites that contributed to the inhibition of α-glucosidase activity. The results of this study have clearly strengthened the traditional claim of the antihyperglycemic effects of L. albus.

Matched MeSH terms: Metabolomics
Fulltext Physical fitness in community-dwelling older adults is linked to dietary intake, gut microbiota, and metabolomic signatures

Castro-Mejía JL, Khakimov B, Krych Ł, Bülow J, Bechshøft RL, Højfeldt G, et al.

Aging Cell, 2020 03;19(3):e13105.
PMID: 31967716 DOI: 10.1111/acel.13105

When humans age, changes in body composition arise along with lifestyle-associated disorders influencing fitness and physical decline. Here we provide a comprehensive view of dietary intake, physical activity, gut microbiota (GM), and host metabolome in relation to physical fitness of 207 community-dwelling subjects aged +65 years. Stratification on anthropometric/body composition/physical performance measurements (ABPm) variables identified two phenotypes (high/low-fitness) clearly linked to dietary intake, physical activity, GM, and host metabolome patterns. Strikingly, despite a higher energy intake high-fitness subjects were characterized by leaner bodies and lower fasting proinsulin-C-peptide/blood glucose levels in a mechanism likely driven by higher dietary fiber intake, physical activity and increased abundance of Bifidobacteriales and Clostridiales species in GM and associated metabolites (i.e., enterolactone). These factors explained 50.1% of the individual variation in physical fitness. We propose that targeting dietary strategies for modulation of GM and host metabolome interactions may allow establishing therapeutic approaches to delay and possibly revert comorbidities of aging.

Matched MeSH terms: Metabolomics/methods
Fulltext (R)-Salbutamol Improves Imiquimod-Induced Psoriasis-Like Skin Dermatitis by Regulating the Th17/Tregs Balance and Glycerophospholipid Metabolism

Liu F, Wang S, Liu B, Wang Y, Tan W

Cells, 2020 02 24;9(2).
PMID: 32102363 DOI: 10.3390/cells9020511

Psoriasis is a skin disease that is characterized by a high degree of inflammation caused by immune dysfunction. (R)-salbutamol is a bronchodilator for asthma and was reported to alleviate immune system reactions in several diseases. In this study, using imiquimod (IMQ)-induced mouse psoriasis-like dermatitis model, we evaluated the therapeutic effects of (R)-salbutamol in psoriasis in vivo, and explored the metabolic pathway involved. The results showed that, compared with IMQ group, (R)-salbutamol treatment significantly ameliorated psoriasis, reversed the suppressive effects of IMQ on differentiation, extreme keratinocyte proliferation, and infiltration of inflammatory cells. Enzyme-linked immunosorbent assays (ELISA) showed that (R)-salbutamol markedly reduced the plasma levels of IL-17. Cell analysis using flow cytometry showed that (R)-salbutamol decreased the proportion of CD4+ Th17+ T cells (Th17), whereas it increased the percentage of CD25+ Foxp3+ regulatory T cells (Tregs) in the spleens. (R)-salbutamol also decreased the weight ratio of spleen to body. Furthermore, untargeted metabolomics showed that (R)-salbutamol affected three metabolic pathways, including (i) arachidonic acid metabolism, (ii) sphingolipid metabolism, and (iii) glycerophospholipid metabolism. These results demonstrated that (R)-salbutamol can alleviate IMQ-induced psoriasis through regulating Th17/Tregs cell response and glycerophospholipid metabolism. It may provide a new use of (R)-salbutamol in the management of psoriasis.

Matched MeSH terms: Metabolomics/methods*
Fulltext Investigation of α-Glucosidase Inhibitory Metabolites from Tetracera scandens Leaves by GC-MS Metabolite Profiling and Docking Studies

Nokhala A, Siddiqui MJ, Ahmed QU, Ahamad Bustamam MS, Zakaria AZA

Biomolecules, 2020 02 12;10(2).
PMID: 32059529 DOI: 10.3390/biom10020287

Stone leaf (Tetracera scandens) is a Southeast Asian medicinal plant that has been traditionally used for the management of diabetes mellitus. The underlying mechanisms of the antidiabetic activity have not been fully explored yet. Hence, this study aimed to evaluate the α-glucosidase inhibitory potential of the hydromethanolic extracts of T. scandens leaves and to characterize the metabolites responsible for such activity through gas chromatography-mass spectrometry (GC-MS) metabolomics. Crude hydromethanolic extracts of different strengths were prepared and in vitro assayed for α-glucosidase inhibition. GC-MS analysis was further carried out and the mass spectral data were correlated to the corresponding α-glucosidase inhibitory IC50 values via an orthogonal partial least squares (OPLS) model. The 100%, 80%, 60% and 40% methanol extracts displayed potent α-glucosidase inhibitory potentials. Moreover, the established model identified 16 metabolites to be responsible for the α-glucosidase inhibitory activity of T. scandens. The putative α-glucosidase inhibitory metabolites showed moderate to high affinities (binding energies of -5.9 to -9.8 kcal/mol) upon docking into the active site of Saccharomyces cerevisiae isomaltase. To sum up, an OPLS model was developed as a rapid method to characterize the α-glucosidase inhibitory metabolites existing in the hydromethanolic extracts of T. scandens leaves based on GC-MS metabolite profiling.

Matched MeSH terms: Metabolomics
1H NMR-Based Metabolic Profiles Delineate the Anticancer Effect of Vitamin C and Oxaliplatin on Hepatocellular Carcinoma Cells

Lin C, Dong J, Wei Z, Cheng KK, Li J, You S, et al.

J Proteome Res, 2020 02 07;19(2):781-793.
PMID: 31916767 DOI: 10.1021/acs.jproteome.9b00635

Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Because of its high recurrence rate and heterogeneity, effective treatment for advanced stage of HCC is currently lacking. There are accumulating evidences showing the therapeutic potential of pharmacologic vitamin C (VC) on HCC. However, the metabolic basis underlying the anticancer property of VC remains to be elucidated. In this study, we used a high-resolution proton nuclear magnetic resonance-based metabolomics technique to assess the global metabolic changes in HCC cells following VC treatment. In addition, the HCC cells were also treated with oxaliplatin (OXA) to explore the potential synergistic effect induced by the combined VC and OXA treatment. The current metabolomics data suggested different mechanisms of OXA and VC in modulating cell growth and metabolism. In general, VC treatment led to inhibition of energy metabolism via NAD+ depletion and amino acid deprivation. On the other hand, OXA caused significant perturbation in phospholipid biosynthesis and phosphatidylcholine biosynthesis pathways. The current results highlighted glutathione metabolism, and pathways related to succinate and choline may play central roles in conferring the combined effect between OXA and VC. Taken together, this study provided metabolic evidence of VC and OXA in treating HCC and may contribute toward the potential application of combined VC and OXA as complementary HCC therapies.

Matched MeSH terms: Metabolomics
Fulltext Biosynthesis of Saxitoxin in Marine Dinoflagellates: An Omics Perspective

Akbar MA, Mohd Yusof NY, Tahir NI, Ahmad A, Usup G, Sahrani FK, et al.

Mar Drugs, 2020 Feb 05;18(2).
PMID: 32033403 DOI: 10.3390/md18020103

Saxitoxin is an alkaloid neurotoxin originally isolated from the clam Saxidomus giganteus in 1957. This group of neurotoxins is produced by several species of freshwater cyanobacteria and marine dinoflagellates. The saxitoxin biosynthesis pathway was described for the first time in the 1980s and, since then, it was studied in more than seven cyanobacterial genera, comprising 26 genes that form a cluster ranging from 25.7 kb to 35 kb in sequence length. Due to the complexity of the genomic landscape, saxitoxin biosynthesis in dinoflagellates remains unknown. In order to reveal and understand the dynamics of the activity in such impressive unicellular organisms with a complex genome, a strategy that can carefully engage them in a systems view is necessary. Advances in omics technology (the collective tools of biological sciences) facilitated high-throughput studies of the genome, transcriptome, proteome, and metabolome of dinoflagellates. The omics approach was utilized to address saxitoxin-producing dinoflagellates in response to environmental stresses to improve understanding of dinoflagellates gene-environment interactions. Therefore, in this review, the progress in understanding dinoflagellate saxitoxin biosynthesis using an omics approach is emphasized. Further potential applications of metabolomics and genomics to unravel novel insights into saxitoxin biosynthesis in dinoflagellates are also reviewed.

Matched MeSH terms: Metabolomics
Fulltext Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case-control sets from EPIC

Schmidt JA, Fensom GK, Rinaldi S, Scalbert A, Appleby PN, Achaintre D, et al.

Int J Cancer, 2020 Feb 01;146(3):720-730.
PMID: 30951192 DOI: 10.1002/ijc.32314

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.

Matched MeSH terms: Metabolomics
Fulltext The anti-neuroinflammatory effects of Clinacanthus nutans leaf extract on metabolism elucidated through 1H NMR in correlation with cytokines microarray

Ahmad Azam A, Ismail IS, Kumari Y, Shaikh MF, Abas F, Shaari K

PLoS One, 2020;15(9):e0238503.
PMID: 32925968 DOI: 10.1371/journal.pone.0238503

Clinacanthus nutans (CN) (Acanthaceae) is well-known for its anti-inflammatory properties among Asian communities; however, there are currently no data specifically focused on the anti-inflammatory effects of CN on the brain tissue. Neuroinflammation is a common consequence of toxin intrusion to any part of the central nervous system (CNS). As an innate immune response, the CNS may react through both protective and/or toxic actions due to the activation of neuron cells producing pro- and/or anti-inflammatory cytokines in the brain. The unresolved activation of the inflammatory cytokines' response is associated with the pathogenesis of neurological disorders. The present study aimed to decipher the metabolic mechanism on the effects of 14 days oral treatment with CN aqueous extract in induced-lipopolysaccharides (LPS) rats through 1H NMR spectroscopic biomarker profiling of the brain tissue and the related cytokines. Based on the principal component analysis (PCA) of the nuclear magnetic resonance (NMR) spectral data, twenty-one metabolites in the brain tissue were profiled as biomarkers for the LPS (10 μL)-induced neuroinflammation following intracerebroventricular injection. Among the twenty-one biomarkers in the neuroinflammed rats, CN treatment of 1000 and 500 mg/kg BW successfully altered lactate, pyruvate, phosphorylcholine, glutamine, and α-ketoglutarate when compared to the negative control. Likewise, statistical isolinear multiple component analysis (SIMCA) showed that treatments by CN and the positive control drug, dextromethorphan (DXM, 5 mg/kg BW), have anti-neuroinflammatory potential. A moderate correlation, in the orthogonal partial least squares (OPLS) regression model, was found between the spectral metabolite profile and the cytokine levels. The current study revealed the existence of high levels of pro-inflammatory cytokines, namely IL-1α, IL-1β, and TNF-α in LPS-induced rats. Both CN dose treatments lowered IL-1β significantly better than DXM Interestingly, DXM and CN treatments both exhibited the upregulation of the anti-inflammatory cytokines IL-2 and 4. However, DXM has an advantage over CN in that the former also increased the expression of IL-10 of anti-inflammatory cytokines. In this study, a metabolomics approach was successfully applied to discover the mechanistic role of CN in controlling the neuroinflammatory conditions through the modulation of complex metabolite interactions in the rat brain.

Matched MeSH terms: Metabolomics
Fulltext The methanolic extract of Garcinia atroviridis (MeGa) reduces body weight and food intake, and improves lipid profiles by altering the lipid metabolism: a rat model

Lim WF, Nasir SM, Teh LK, James RJ, Izhar MHM, Salleh MZ

Turk J Biol, 2020;44(6):437-448.
PMID: 33402870 DOI: 10.3906/biy-2005-2

Garcinia species are widely used for their slimming effects via increased fat burning and suppression of satiety. However, scientific evidence for the biological effects of Garcinia atroviridis (GA) is lacking. We investigated the phytochemical composition, safety profiles, and antioxidant and antiobesity effects of methanolic extracts of Garcinia atroviridis (MeGa) in obese female rats. Repeated dose toxicity studies were conducted according to the OECD guidelines. Upon sacrifice, haematological, biochemical, lipid profile, and serum-based metabolomics analyses were performed to evaluate metabolic expression changes and their related pathways. MeGa contains several phytochemical groups and GA fruit acids. MeGa was found to be nontoxic in both male and female rats with an oral lethal dose (LD50) of 2000 mg/kg. After 9 weeks of treatment, MeGa-treated obese rats had lower weight gain and better lipid profiles (cholesterol and triglyceride), which correlated with the altered metabolic pathways involved in the metabolism of lipid (glycerophospholipid) and biosynthesis of unsaturated fatty acid. In addition, MeGa caused differential metabolism pathways of arachidonic acid and tryptophan that affect the inflammatory response and suppression of appetite. We concluded that MeGa is safe, and its slimming effects are due to the differential metabolism of lipids.

Matched MeSH terms: Metabolomics
Fulltext Gluconobacter dominates the gut microbiome of the Asian palm civet Paradoxurus hermaphroditus that produces kopi luwak

Watanabe H, Ng CH, Limviphuvadh V, Suzuki S, Yamada T

PeerJ, 2020;8:e9579.
PMID: 32821539 DOI: 10.7717/peerj.9579

Coffee beans derived from feces of the civet cat are used to brew coffee known as kopi luwak (the Indonesian words for coffee and palm civet, respectively), which is one of the most expensive coffees in the world owing to its limited supply and strong market demand. Recent metabolomics studies have revealed that kopi luwak metabolites differ from metabolites found in other coffee beans. To produce kopi luwak, coffee beans are first eaten by civet cats. It has been proposed that fermentation inside the civet cat digestive tract may contribute to the distinctively smooth flavor of kopi luwak, but the biological basis has not been determined. Therefore, we characterized the microbiome of civet cat feces using 16S rRNA gene sequences to determine the bacterial taxa that may influence fermentation processes related to kopi luwak. Moreover, we compared this fecal microbiome with that of 14 other animals, revealing that Gluconobacter is a genus that is, uniquely found in feces of the civet cat. We also found that Gluconobacter species have a large number of cell motility genes, which may encode flagellar proteins allowing colonization of the civet gut. In addition, genes encoding enzymes involved in the metabolism of hydrogen sulfide and sulfur-containing amino acids were over-represented in Gluconobacter. These genes may contribute to the fermentation of coffee beans in the digestive tract of civet cats.

Matched MeSH terms: Metabolomics
Metabolomics-Guided Isolation of Anti-Trypanosomal Compounds from Endophytic Fungi of the Mangrove plant Avicennia Lanata

Mazlan NW, Tate R, Yusoff YM, Clements C, Edrada-Ebel R

Curr Med Chem, 2020;27(11):1815-1835.
PMID: 31272343 DOI: 10.2174/0929867326666190704130105

Endophytic fungi have been explored not just for their ecological functions but also for their secondary metabolites as a new source of these pharmacologically active natural products. Accordingly, many structurally unique and biologically active compounds have been obtained from the cultures of endophytic fungi. Fusarium sp. and Lasiodiplodia theobromae were isolated from the root and stem of the mangrove plant Avicennia lanata, respectively, collected from Terengganu, Malaysia. High-resolution mass spectrometry and NMR spectroscopy were used as metabolomics profiling tools to identify and optimize the production of bioactive secondary metabolites in both strains at different growth stages and culture media. The spectral data was processed by utilizing Mzmine 2, a quantitative expression analysis software and an in house MS-Excel macro coupled with the Dictionary of Natural Products databases for dereplication studies. The investigation for the potential bioactive metabolites from a 15-day rice culture of Fusarium sp. yielded four 1,4- naphthoquinone with naphthazarin structures (1-4). On the other hand, the endophytic fungus L. theobromae grown on the 15-day solid rice culture produced dihydroisocoumarins (5-8). All the isolated compounds (1-8) showed significant activity against Trypanosoma brucei brucei with MIC values of 0.32-12.5 µM. Preliminary cytotoxicity screening against normal prostate cells (PNT2A) was also performed. All compounds exhibited low cytotoxicity, with compounds 3 and 4 showing the lowest cytotoxicity of only 22.3% and 38.6% of the control values at 100 µg/mL, respectively. Structure elucidation of the isolated secondary metabolites was achieved using 2D-NMR and HRESI-MS as well as comparison with literature data.

Matched MeSH terms: Metabolomics
A metabolomic approach to investigate effects of ocean acidification on a polar microalga Chlorella sp

Tan YH, Lim PE, Beardall J, Poong SW, Phang SM

Aquat Toxicol, 2019 Dec;217:105349.
PMID: 31734626 DOI: 10.1016/j.aquatox.2019.105349

Ocean acidification, due to increased levels of anthropogenic carbon dioxide, is known to affect the physiology and growth of marine phytoplankton, especially in polar regions. However, the effect of acidification or carbonation on cellular metabolism in polar marine phytoplankton still remains an open question. There is some evidence that small chlorophytes may benefit more than other taxa of phytoplankton. To understand further how green polar picoplankton could acclimate to high oceanic CO2, studies were conducted on an Antarctic Chlorella sp. Chlorella sp. maintained its growth rate (∼0.180 d-1), photosynthetic quantum yield (Fv/Fm = ∼0.69) and chlorophyll a (0.145 fg cell-1) and carotenoid (0.06 fg cell-1) contents under high CO2, while maximum rates of electron transport decreased and non-photochemical quenching increased under elevated CO2. GCMS-based metabolomic analysis reveal that this polar Chlorella strain modulated the levels of metabolites associated with energy, amino acid, fatty acid and carbohydrate production, which could favour its survival in an increasingly acidified ocean.

Matched MeSH terms: Metabolomics
Microenvironmental Interplay Predominated by Beneficial Aspergillus Abates Fungal Pathogen Incidence in Paddy Environment

Fan X, Matsumoto H, Wang Y, Hu Y, Liu Y, Fang H, et al.

Environ Sci Technol, 2019 Nov 19;53(22):13042-13052.
PMID: 31631659 DOI: 10.1021/acs.est.9b04616

Rice fungal pathogens, responsible for severe rice yield loss and biotoxin contamination, cause increasing concerns on environmental safety and public health. In the paddy environment, we observed that the asymptomatic rice phyllosphere microenvironment was dominated by an indigenous fungus, Aspergillus cvjetkovicii, which positively correlated with alleviated incidence of Magnaporthe oryzae, one of the most aggressive plant pathogens. Through the comparative metabolic profiling for the rice phyllosphere microenvironment, two metabolites were assigned as exclusively enriched metabolic markers in the asymptomatic phyllosphere and increased remarkably in a population-dependent manner with A. cvjetkovicii. These two metabolites evidenced to be produced by A. cvjetkovicii in either a phyllosphere microenvironment or artificial media were purified and identified as 2(3H)-benzofuranone and azulene, respectively, by gas chromatography coupled to triple quadrupole mass spectrometry and nuclear magnetic resonance analyses. Combining with bioassay analysis in vivo and in vitro, we found that 2(3H)-benzofuranone and azulene exerted dissimilar actions at the stage of infection-related development of M. oryzae. A. cvjetkovicii produced 2(3H)-benzofuranone at the early stage to suppress MoPer1 gene expression, leading to inhibited mycelial growth, while azulene produced lately was involved in blocking of appressorium formation by downregulation of MgRac1. More profoundly, the microenvironmental interplay dominated by A. cvjetkovicii significantly blocked M. oryzae epidemics in the paddy environment from 54.7 to 68.5% (p < 0.05). Our study first demonstrated implication of the microenvironmental interplay dominated by indigenous and beneficial fungus to ecological balance and safety of the paddy environment.

Matched MeSH terms: Metabolomics
Fulltext Metabolite profiling of Andrographis paniculata (Burm. f.) Nees. young and mature leaves at different harvest ages using 1H NMR-based metabolomics approach

Tajidin NE, Shaari K, Maulidiani M, Salleh NS, Ketaren BR, Mohamad M

Sci Rep, 2019 11 14;9(1):16766.
PMID: 31727911 DOI: 10.1038/s41598-019-52905-z

Andrographis paniculata (Burm. F.) Nees. is considered as the herb of the future due to its precious chemical compounds, andrographolide (ANDRO), neoandrographolide (NAG) and 14-deoxyandrographolide (DAG). This study aims to profile the metabolites in young and mature leaf at six different harvest ages using 1HNMR-based metabolomics combined with multivariate data analysis. Principal component analysis (PCA) indicated noticeable and clear discrimination between young and mature leaves. A comparison of the leaves stage indicated that young leaves were separated from mature leaves due to its larger quantity of ANDRO, NAG, DAG, glucose and sucrose. These similar metabolites are also responsible for the PCA separation into five clusters representing the harvest age at 14, 16, 18, 20, 22 weeks of leaves extract. Loading plots revealed that most of the ANDRO and NAG signals were present when the plant reached at the pre-flowering stage or 18 weeks after sowing (WAS). As a conclusion, A. paniculata young leaves at pre-flowering harvest age were found to be richer in ANDRO, NAG and DAG compared to mature leaves while glucose and choline increased with harvest age. Therefore, young leaves of A. paniculata should be harvested at 18 WAS in order to produce superior quality plant extracts for further applications by the herbal, nutraceutical and pharmaceutical industries.

Matched MeSH terms: Metabolomics/methods*
1H-NMR-based metabolomics to investigate the effects of Phoenix dactylifera seed extracts in LPS-IFN-γ-induced RAW 264.7 cells

Abdul-Hamid NA, Abas F, Ismail IS, Tham CL, Maulidiani M, Mediani A, et al.

Food Res Int, 2019 11;125:108565.
PMID: 31554083 DOI: 10.1016/j.foodres.2019.108565

Inflammation has been revealed to play a central role in the onset and progression of many illnesses. Nuclear magnetic resonance (NMR) based metabolomics method was adopted to evaluate the effects of Phoenix dactylifera seeds, in particular the Algerian date variety of Deglet on the metabolome of the LPS-IFN-γ-induced RAW 264.7 cells. Variations in the extracellular and intracellular profiles emphasized the differences in the presence of tyrosine, phenylalanine, alanine, proline, asparagine, isocitrate, inosine and lysine. Principal component analysis (PCA) revealed noticeable clustering patterns between the treated and induced RAW cells based on the metabolic profile of the extracellular metabolites. However, the effects of treatment on the intracellular metabolites appears to be less distinct as suggested by the PCA and heatmap analyses. A clear group segregation was observed for the intracellular metabolites from the treated and induced cells based on the orthogonal partial least squares-discriminant analysis (OPLS-DA) score plot. Likewise, 11 of the metabolites in the treated cells were significantly different from those in the induced groups, including amino acids and succinate. The enrichment analysis demonstrated that treatment with Deglet seed extracts interfered with the energy and of amino acids metabolism. Overall, the obtained data reinforced the possible application of Deglet seeds as a functional food with anti-inflammatory properties.

Matched MeSH terms: Metabolomics/methods*
Urine NMR Metabolomic Study on Biochemical Activities to Investigate the Effect of P. betle Extract on Obese Rats

Abdul Ghani ZDF, Ab Rashid AH, Shaari K, Chik Z

Appl Biochem Biotechnol, 2019 Oct;189(2):690-708.
PMID: 31111377 DOI: 10.1007/s12010-019-03042-w

The present studies are to evaluate the ability of PB to induce weight loss and urine metabolite profile of Piper betle L. (PB) leaf extracts using metabolomics approach. Dried PB leaves were extracted with ethanol 70% and the studies were performed in different groups of rats fed with high fat (HFD) and normal diet (ND). Then, fed with the PB extract with 100, 300, and 500 mg/kg and two negative control groups given water (WTR). The body weights were monitored and evaluated. Urine was collected and 1H NMR-based metabolomics approach was used to detect the metabolite changes. Results showed that PB-treated group demonstrated inhibition of body weight gain. The trajectory of urine metabolites showed that PB-treated group gave the different distribution from week 12 to 16 compared with the control groups. In 1H NMR metabolomic approach analysis, the urine metabolites gave the best separation in principle component 1 and 3, with 40.0% and 9.56% of the total variation. Shared and unique structures (SUS) plot model showed that higher concentration PB-treated group was characterized by high level of indole-3-acetate, aspartate, methanol, histidine, and creatine, thus caused an increased the metabolic function and maintaining the body weight of the animals treated.

Matched MeSH terms: Metabolomics*
Physiological and metabolic responses of Scenedesmus quadricauda (Chlorophyceae) to nickel toxicity and warming

Yong WK, Sim KS, Poong SW, Wei D, Phang SM, Lim PE

3 Biotech, 2019 Aug;9(8):315.
PMID: 31406637 DOI: 10.1007/s13205-019-1848-8

An ecologically important tropical freshwater microalga, Scenedesmus quadricauda, was exposed to Ni toxicity under two temperature regimes, 25 and 35 °C to investigate the interactive effects of warming and different Ni concentrations (0.1, 1.0 and 10.0 ppm). The stress responses were assessed from the growth, photosynthesis, reactive oxygen species (ROS) generation and metabolomics aspects to understand the effects at both the physiological and biochemical levels. The results showed that the cell densities of the cultures were higher at 35 °C compared to 25 °C, but decreased with increasing Ni concentrations at 35 °C. In terms of photosynthetic efficiency, the maximum quantum yield of photosystem II (Fv/Fm) of S. quadricauda remained consistent across different conditions. Nickel concentration at 10.0 ppm affected the maximum rate of relative electron transport (rETRm) and saturation irradiance for electron transport (Ek) in photosynthesis. At 25 °C, the increase of non-photochemical quenching (NPQ) values in cells exposed to 10.0 ppm Ni might indicate the onset of thermal dissipation process as a self-protection mechanism against Ni toxicity. The combination of warming and Ni toxicity induced a strong oxidative stress response in the cells. The ROS level increased significantly by 40% after exposure to 10.0 ppm of Ni at 35 °C. The amount of Ni accumulated in the biomass was higher at 25 °C compared to 35 °C. Based on the metabolic profile, temperature contributed the most significant differentiation among the samples compared to Ni treatment and the interaction between the two factors. Amino acids, sugars and organic acids were significantly regulated by the combined factors to restore homeostasis. The most affected pathways include sulphur, amino acids, and nitrogen metabolisms. Overall, the results suggest that the inhibitory effect of Ni was lower at 35 °C compared to 25 °C probably due to lower metal uptake and primary metabolism restructuring. The ability of S. quadricauda to accumulate substantial amount of Ni and thrive at 35 °C suggests the potential use of this strain for phycoremediation and outdoor wastewater treatment.

Matched MeSH terms: Metabolomics
Fulltext Global serum metabolomics profiling of colorectal cancer

Hashim NAA, Ab-Rahim S, Suddin LS, Saman MSA, Mazlan M

Molecular and clinical oncology, 2019 Jul;11(1):3-14.
PMID: 31289671 DOI: 10.3892/mco.2019.1853

Accurate diagnosis of colorectal cancer (CRC) relies on the use of invasive tools such as colonoscopy and sigmoidoscopy. Non-invasive tools are less sensitive in detecting the disease, particularly in the early stage. A number of researchers have used metabolomics analyses on serum/plasma samples of patients with CRC compared with normal healthy individuals in an effort to identify biomarkers for CRC. The aim of the present review is to compare reported serum metabolomics profiles of CRC and to identify common metabolites affected among these studies. A literature search was performed to include any experimental studies on global metabolomics profile of CRC using serum/plasma samples published up to March 2018. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used to assess the quality of the studies reviewed. In total, nine studies were included. The studies used various analytical platforms and were performed on different populations. A pathway enrichment analysis was performed using the data from all the studies under review. The most affected pathways identified were protein biosynthesis, urea cycle, ammonia recycling, alanine metabolism, glutathione metabolism and citric acid cycle. The metabolomics analysis revealed levels of metabolites of glycolysis, tricarboxylic acid cycle, anaerobic respiration, protein, lipid and glutathione metabolism were significantly different between cancer and control samples. Although the majority of differentiating metabolites identified were different in the different studies, there were several metabolites that were common. These metabolites include pyruvic acid, glucose, lactic acid, malic acid, fumaric acid, 3-hydroxybutyric acid, tryptophan, phenylalanine, tyrosine, creatinine and ornithine. The consistent dysregulation of these metabolites among the different studies suggest the possibility of common diagnostic biomarkers for CRC.

Matched MeSH terms: Metabolomics

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