Dead in the water - Role of relic DNA and primer choice for targeted sequencing surveys of anaerobic sewage sludge intended for biological monitoring.

DNA-based monitoring of microbial communities that are responsible for the performance of anaerobic digestion of sewage wastes has the potential to improve resource recoveries for wastewater treatment facilities. By treating sludge with propidium monoazide (PMA) prior to amplicon sequencing, this study explored how the presence of DNA from dead microbial biomass carried over with feed sludge may mislead process-relevant biomarkers, and whether primer choice impacts such assessments. Four common primers were selected for amplicon preparation, also to determine if universal primers have sufficient taxonomic or functional coverage for monitoring ecological performance; or whether two domain-specific primers for Bacteria and Archaea are necessary. Anaerobic sludges of three municipal continuously stirred-tank reactors in Victoria, Australia, were sampled at one time-point. A total of 240 amplicon libraries were sequenced on a Miseq using two universal and two domain-specific primer pairs. Untargeted metabolomics was chosen to complement biological interpretation of amplicon gene-based functional predictions. Diversity, taxonomy, phylogeny and functional potentials were systematically assessed using PICRUSt2, which can predict community wide pathway abundance. The two chosen universal primers provided similar diversity profiles of abundant Bacteria and Archaea, compared to the domain-specific primers. About 16 % of all detected prokaryotic genera covering 30 % of total abundances and 6 % of PICRUSt2-estimated pathway abundances were affected by PMA. This showed that dead biomass in the anaerobic digesters impacted DNA-based assessments, with implications for predicting active processes, such as methanogenesis, denitrification or the identification of organisms associated with biological foams. Hence, instead of running two sequencing runs with two different domain-specific primers, we propose conducting PMA-seq with universal primer pairs for routine performance monitoring. However, dead sludge biomass may have some predictive value. In principal component analysis the compositional variation of 239 sludge metabolites resembled that of 'dead-plus-alive' biomass, suggesting that dead organisms contributed to the potentially process-relevant sludge metabolome.

Abrus precatorius Leaf Extract Stimulates Insulin-mediated Muscle Glucose Uptake: In vitro Studies and Phytochemical Analysis.

Diabetes mellitus, linked with insulin resistance and hyperglycaemia, is a leading cause of mortality. Glucose uptake through glucose transporter type 4, especially in skeletal muscle, is crucial for maintaining euglycaemia and is a key pathway targeted by antidiabetic medication. Abrus precatorius is a medicinal plant with demonstrated antihyperglycaemic activity in animal models, but its mechanisms are unclear.This study evaluated the effect of a 50% ethanolic (v/v) A. precatorius leaf extract on (1) insulin-stimulated glucose uptake and (2) related gene expression in differentiated C2C12 myotubes using rosiglitazone as a positive control, and (3) generated a comprehensive phytochemical profile of A. precatorius leaf extract using liquid chromatography-high resolution mass spectrometry to elucidate its antidiabetic compounds. A. precatorius leaf extract significantly increased insulin-stimulated glucose uptake, and insulin receptor substrate 1 and Akt substrate of 160 kDa gene expression; however, it had no effect on glucose transporter type 4 gene expression. At 250 µg/mL A. precatorius leaf extract, the increase in glucose uptake was significantly higher than 1 µM rosiglitazone. Fifty-five phytochemicals (primarily polyphenols, triterpenoids, saponins, and alkaloids) were putatively identified, including 24 that have not previously been reported from A. precatorius leaves. Abrusin, precatorin I, glycyrrhizin, hemiphloin, isohemiphloin, hispidulin 4'-O-ß-D-glucopyranoside, homoplantaginin, and cirsimaritin were putatively identified as known major compounds previously reported from A. precatorius leaf extract. A. precatorius leaves contain antidiabetic phytochemicals and enhance insulin-stimulated glucose uptake in myotubes via the protein kinase B/phosphoinositide 3-kinase pathway by regulating insulin receptor substrate 1 and Akt substrate of 160 kDa gene expression. Therefore, A. precatorius leaves may improve skeletal muscle insulin sensitivity and hyperglycaemia. Additionally, it is a valuable source of bioactive phytochemicals with potential therapeutic use for diabetes.

Expanding the phenotypic spectrum of CLCN2-related leucoencephalopathy and ataxia.

Mutations in CLCN2 are a rare cause of autosomal recessive leucoencephalopathy with ataxia and specific imaging abnormalities. Very few cases have been reported to date. Here, we describe the clinical and imaging phenotype of 12 additional CLCN2 patients and expand the known phenotypic spectrum of this disorder. Informed consent was obtained for all patients. Patients underwent either whole-exome sequencing or focused/panel-based sequencing to identify variants. Twelve patients with biallelic CLCN2 variants are described. This includes three novel likely pathogenic missense variants. All patients demonstrated typical MRI changes, including hyperintensity on T2-weighted images in the posterior limbs of the internal capsules, midbrain cerebral peduncles, middle cerebellar peduncles and cerebral white matter. Clinical features included a variable combination of ataxia, headache, spasticity, seizures and other symptoms with a broad range of age of onset. This report is now the largest case series of patients with CLCN2-related leucoencephalopathy and reinforces the finding that, although the imaging appearance is uniform, the phenotypic expression of this disorder is highly heterogeneous. Our findings expand the phenotypic spectrum of CLCN2-related leucoencephalopathy by adding prominent seizures, severe spastic paraplegia and developmental delay.

Measures of insulin sensitivity, leptin, and adiponectin concentrations in cats in diabetic remission compared to healthy control cats.

Objectives: Firstly, to compare differences in insulin, adiponectin, leptin, and measures of insulin sensitivity between diabetic cats in remission and healthy control cats, and determine whether these are predictors of diabetic relapse. Secondly, to determine if these hormones are associated with serum metabolites known to differ between groups. Thirdly, if any of the hormonal or identified metabolites are associated with measures of insulin sensitivity. Animals: Twenty cats in diabetic remission for a median of 101 days, and 21 healthy matched control cats. Methods: A casual blood glucose measured on admission to the clinic. Following a 24 h fast, a fasted blood glucose was measured, and blood sample taken for hormone (i.e., insulin, leptin, and adiponectin) and untargeted metabolomic (GC-MS and LC-MS) analysis. A simplified IVGGT (1 g glucose/kg) was performed 3 h later. Cats were monitored for diabetes relapse for at least 9 months (270 days). Results: Cats in diabetic remission had significantly higher serum glucose and insulin concentrations, and decreased insulin sensitivity as indicated by an increase in HOMA and decrease in QUICKI and Bennett indices. Leptin was significantly increased, but there was no difference in adiponectin (or body condition score). Several significant correlations were found between insulin sensitivity indices, leptin, and serum metabolites identified as significantly different between remission and control cats. No metabolites were significantly correlated with adiponectin. No predictors of relapse were identified in this study. Conclusion and clinical importance: Insulin resistance, an underlying factor in diabetic cats, persists in diabetic remission. Cats in remission should be managed to avoid further exacerbating insulin resistance.

In vitro inhibitory activities of sugarcane extract on avian Eimeria sporozoites.

The current in vitro study aimed to investigate the effects of a processed sugarcane extract on the viability of avian Eimeria sporozoites. Treatments were applied to hatched sporozoites: 1) without additives (no-treatment control); 2) with ethanol; 3) with salinomycin; 4) with Polygain™. All treatments were incubated in RPMI media containing live sporozoites at 37 °C for 14 h and then the number of viable sporozoites were counted. Compared to the no-treatment control, Polygain™ decreased (P < 0.001) the counts of E. maxima, E. acervulina, E. bruneti, and E. mitis sporozoites to a level similar to salinomycin (P > 0.05). In conclusion, Polygain™ could be a potential candidate as an anticoccidial agent.

A Pharmacological Perspective on Plant-derived Bioactive Molecules for Epilepsy.

Epilepsy is a related chronic neurological condition of a predisposition for recurrent epileptic seizures, with various manifestations and causes. Although there are antiepileptic drugs, complementary natural therapies are widely used. The purpose of this systematic review was to analyze the antiepileptic/anticonvulsant pharmacological properties of plant-food derived bioactive molecules. In this regard, a systematic review of the PubMed database was made based on the inclusion criteria. Natural compounds/herbs with scientifically proven antiepileptic properties were selected. Experimental pharmacological studies in vitro and in vivo have shown that flavonoids, alkaloids and terpenoids may have anticonvulsant mechanisms similar to the new generation antiepileptic drugs. The relationships of structure-anticonvulsant effect, pharmacological models, seizure-inducing factors and response, effective dose were also analyzed and discussed. The results of in vitro and in vivo pharmacological studies analyzed in this systematic review support the clinical importance of plant-food-derived bioactive molecules for the complementary treatment of epilepsy. Thus, are opened new perspectives to develop new natural anticonvulsant drugs.

LC-MS untargeted metabolomics assesses the delayed response of glufosinate treatment of transgenic glufosinate resistant (GR) buffalo grasses (Stenotaphrum secundatum L.).

INTRODUCTION: Glufosinate resistant (GR) buffalo grasses were genetically modified to resist the broad-spectrum herbicide, glufosinate by inserting a novel pat gene into its genome. This modification results in a production of additional phosphinothricin acetyltransferase (PAT) to detoxify the deleterious effects of glufosinate. The GR grasses and its associated herbicide form a modern, weeding program, to eradicate obnoxious weeds in turf lawn without damaging the grasses at relatively low costs and labor. As with several principal crops which are genetically modified to improve agricultural traits, biosafety of the GR buffalo grasses is inevitably expected to become a public concern. For the first time, we had previously examined the metabolome of glufosinate-resistant buffalo grasses, using a GC-MS untargeted approach to assess the risk of GR as well as identify any pleotropic effects arising from the genetically modification process. In this paper, an untargeted high-resolution LC-MS (LC-HRMS) untargeted metabolomics approach was carried out to complement our previous findings with respect to GR and wild type (WT) buffalo grasses. OBJECTIVE: One of the major aims of this present work was to compare GR to WT buffalo grasses by including the detection of the secondary metabolome and determine any unprecedented metabolic changes. METHODS: Eight-week old plants of 4 GR buffalo grasses, (93-1A, 93-2B, 93-3 C and 93-5A) and 3 wild type varieties (WT 8-4A, WT 9-1B and WT 9-1B) were submerged in either 5 % v/v of glufosinate or distilled water 3 days prior to a LC-HRMS based untargeted metabolomics analysis (glufosinate-treated or control, samples, respectively). An Ultra-High-Performance Liquid Chromatography (UHPLC) system coupled to a Velos Pro Orbitrap mass spectrometer system was employed to holistically measure the primary and secondary metabolome of both GR and WT buffalo grasses either treated with or without glufosinate and subsequently apply several bioinformatic tools including the automated pathway analysis algorithm, mummichog. RESULTS: LC-HRMS untargeted based metabolomics clearly identified that the global metabolite pools of both GR and WT cultivars were highly similar, providing strong, supporting evidence of substantial equivalence between the GR and WT varieties. These findings indicate that if any associated risks to these GR grasses were somehow present, the risk would be within those acceptable ranges present in the WT. Additionally, mummichog-based pathway analysis indicated that phenylalanine metabolism and the TCA cycle were significantly impacted by glufosinate treatment in the WT cultivar. It was possible that alterations in the relative concentrations of several intermediates in these pathways were likely due to glufosinate-induced production of secondary metabolites to enhance plant defense mechanisms against herbicidal stress at the expense of primary metabolism. CONCLUSIONS: GR buffalo grasses were found to be near identical to its WT comparator based on this complementary LC-HRMS based untargeted metabolomics. Therefore, these results further support the safe use of these GR buffalo grasses with substantial evidence. Interestingly, despite protected by PAT, GR buffalo grasses still demonstrated the response to glufosinate treatment by up-regulating some secondary metabolite-related pathways.

Microbiota and Metabolite Profiling Combined With Integrative Analysis for Differentiating Cheeses of Varying Ripening Ages.

Cheese maturation and flavor development results from complex interactions between milk substrates, cheese microbiota and their metabolites. In this study, bacterial 16S rRNA-gene sequencing, untargeted metabolomics (gas chromatography-mass spectrometry) and data integration analyses were used to characterize and differentiate commercial Cheddar cheeses of varying maturity made by the same and different manufacturers. Microbiota and metabolite compositions varied between cheeses of different ages and brands, and could be used to distinguish the cheeses. Individual amino acids and carboxylic acids were positively correlated with the ripening age for some brands. Integration and Random Forest analyses revealed numerous associations between specific bacteria and metabolites including a previously undescribed positive correlation between Thermus and phenylalanine and a negative correlation between Streptococcus and cholesterol. Together these results suggest that multi-omics analyses has the potential to be used for better understanding the relationships between cheese microbiota and metabolites during ripening and for discovering biomarkers for validating cheese age and brand authenticity.

Metabolic Profiling of Diabetic Cats in Remission.

Background: The majority of diabetic cats in remission have abnormal glucose tolerance, and approximately one third relapse within 1 year. Greater understanding of the metabolic characteristics of diabetic cats in remission, and predictors of relapse is required to effectively monitor and manage these cats. Objectives: To identify and compare differences in plasma metabolites between diabetic cats in remission and healthy control cats using a metabolomics approach. Secondly, to assess whether identified metabolites are predictors of diabetic relapse. Animals: Twenty cats in diabetic remission for a median of 101 days, and 22 healthy matched control cats. Methods: Cats were admitted to a clinic, and casual blood glucose was recorded. After a 24 h fast, blood glucose concentration was measured, then a blood sample was taken for metabolomic (GCMS and LCMS) analyses. Three hours later, a simplified intravenous glucose tolerance test (1 g glucose/kg) was performed. Cats were monitored for diabetes relapse for at least 9 months (270 days) after baseline testing. Results: Most cats in remission continued to display impaired glucose tolerance. Concentrations of 16 identified metabolites differed (P ≤ 0.05) between remission and control cats: 10 amino acids and stearic acid (all lower in remission cats), and glucose, glycine, xylitol, urea and carnitine (all higher in remission cats). Moderately close correlations were found between these 16 metabolites and variables assessing glycaemic responses (most |r| = 0.31 to 0.69). Five cats in remission relapsed during the study period. No metabolite was identified as a predictor of relapse. Conclusion and clinical importance: This study shows that cats in diabetic remission have abnormal metabolism.

Impact of Natural Compounds on Neurodegenerative Disorders: From Preclinical to Pharmacotherapeutics.

Among the major neurodegenerative disorders (NDDs), Alzheimer's disease (AD) and Parkinson's disease (PD), are a huge socioeconomic burden. Over many centuries, people have sought a cure for NDDs from the natural herbals. Many medicinal plants and their secondary metabolites are reported with the ability to alleviate the symptoms of NDDs. The major mechanisms identified, through which phytochemicals exert their neuroprotective effects and potential maintenance of neurological health in ageing, include antioxidant, anti-inflammatory, antithrombotic, antiapoptotic, acetylcholinesterase and monoamine oxidase inhibition and neurotrophic activities. This article review the mechanisms of action of some of the major herbal products with potential in the treatment of NDDs according to their molecular targets, as well as their regional sources (Asia, America and Africa). A number of studies demonstrated the beneficial properties of plant extracts or their bioactive compounds against NDDs. Herbal products may potentially offer new treatment options for patients with NDDs, which is a cheaper and culturally suitable alternative to conventional therapies for millions of people in the world with age-related NDDs.

Inhibitory effect of a weight-loss Chinese herbal formula RCM-107 on pancreatic α-amylase activity: Enzymatic and in silico approaches.

Reducing carbohydrates digestion by having a low glycaemic index (GI) foods has been linked to weight loss. Inhibiting related enzymes is an alternative way to decrease carbohydrate digestion. RCM-107 (Slimming Plus), an eight-herb formula that is modified from RCM-104, indicated significant weight-loss action in clinical trials. However, no published research has studied its mechanism of action on reducing carbohydrate absorption via suppressing the activities of porcine pancreatic alpha-amylase (PPA). In this paper, we used fluorescence PPA inhibition assay to investigate the inhibitory effects of RCM-107 and the individual herbs present in this herbal mixture on amylase activity. Subsequently, molecular docking predicted the key active compounds that may be responsible for the enzyme inhibition. According to our results, both the RCM-107 formula and several individual herbs displayed α-amylase inhibitory effects. Also, marginal synergistic effects of RCM-107 were detected. In addition, alisol B, (-)-epigallocatechin-3-gallate (EGCG) and plantagoside have been predicted as the key active compounds that may be responsible for the α-amylase inhibition effect of RCM-107 according to inter-residue contact analysis. Finally, Glu233, Gln63, His305, Asp300 and Tyr151 are predicted to be markers of important areas with which potential amylase inhibitors would interact. Therefore, our data has provided new knowledge on the mechanisms of action of the RCM-107 formula and its individual herbal ingredients for weight loss, in terms of decreasing carbohydrate digestion via the inhibition of pancreatic alpha-amylase.

New insights into cheddar cheese microbiota-metabolome relationships revealed by integrative analysis of multi-omics data.

Cheese microbiota and metabolites and their inter-relationships that underpin specific cheese quality attributes remain poorly understood. Here we report that multi-omics and integrative data analysis (multiple co-inertia analysis, MCIA) can be used to gain deeper insights into these relationships and identify microbiota and metabolite fingerprints that could be used to monitor product quality and authenticity. Our study into different brands of artisanal and industrial cheddar cheeses showed that Streptococcus, Lactococcus and Lactobacillus were the dominant taxa with overall microbial community structures differing not only between industrial and artisanal cheeses but also among different cheese brands. Metabolome analysis also revealed qualitative and semi-quantitative differences in metabolites between different cheeses. This also included the presence of two compounds (3-hydroxy propanoic acid and O-methoxycatechol-O-sulphate) in artisanal cheese that have not been previously reported in any type of cheese. Integrative analysis of multi-omics datasets revealed that highly similar cheeses, identical in age and appearance, could be distinctively clustered according to cheese type and brand. Furthermore, the analysis detected strong relationships, some previously unknown, which existed between the cheese microbiota and metabolome, and uncovered specific taxa and metabolites that contributed to these relationships. These results highlight the potential of this approach for identifying product specific microbe/metabolite signatures that could be used to monitor and control cheese quality and product authenticity.

Utilization of GC-MS untargeted metabolomics to assess the delayed response of glufosinate treatment of transgenic herbicide resistant (HR) buffalo grasses (Stenotaphrum secundatum L.).

INTRODUCTION: Herbicide resistant (HR) buffalo grasses were genetically engineered to resist the non-selective herbicide, glufosinate in order to facilitate a modern, 'weeding program' which is highly effective in terms of minimizing costs and labor. The resistant trait was conferred by an insertion of the pat gene to allow for the production of the enzyme phosphinothricin acetyltransferase (PAT) to detoxify the glufosinate inhibitive effect. To date, there are only a few reports using metabolomics as well as molecular characterizations published for glufosinate-resistant crops with no reports on HR turfgrass. Therefore, for the first time, this study examines the metabolome of glufosinate-resistant buffalo grasses which not only will be useful to future growers but also the scientific community. OBJECTIVE: A major aim of this present work is to characterize and evaluate the metabolic alterations which may arise from a genetic transformation of HR buffalo grasses by comprehensively using gas chromatography-mass spectrometry (GC-MS) based untargeted metabolomics. METHODS: Eight-week old plants of 4 HR buffalo grasses, (93-1A, 93-2B, 93-3C and 93-5A) and 3 wild type varieties (WT 8-4A, WT 9-1B and WT 9-1B) were selected for physiological, molecular and metabolomics experiments. Plants were either sprayed with 1, 5, 10 and 15% v/v of glufosinate to evaluate the visual injuries or submerged in 5% v/v of glufosinate 3 days prior to a GC-MS based untargeted metabolomics analysis. In contrast, the control group was treated with distilled water. Leaves were extracted in 1:1 methanol:water and then analysed, using an in-house GC-MS untargeted workflow. RESULTS: Results identified 199 metabolites with only 6 of them (cis-aconitic acid, allantoin, cellobiose, glyceric acid, maltose and octadecanoic acid) found to be statistically significant (p < 0.05) between the HR and wild type buffalo grass varieties compared to the control experiment. Among these metabolites, unusual accumulation of allantoin was prominent and was an unanticipated effect of the pat gene insertion. As expected, glufosinate treatment caused significant metabolic alterations in the sensitive wild type, with the up-regulation of several amino acids (e.g. phenylalanine and isoleucine) which was likely due to glufosinate-induced senescence. The aminoacyl-tRNA biosynthetic pathway was identified as the most significant enriched pathway as a result of glufosinate effects because a number of its intermediates were amino acids. CONCLUSION: HR buffalo grasses were very similar to its wild type comparator based on a comprehensive GC-MS based untargeted metabolomics and therefore, should guarantee the safe use of these HR buffalo grasses. The current metabolomics analyses not only confirmed the effects of glufosinate to up-regulate free amino acid pools in the sensitive wild type but also several alterations in sugar, sugar phosphate and organic acid metabolism have been reported.

Cheesomics: the future pathway to understanding cheese flavour and quality.

Cheese is a fermented dairy product, harboring diverse microbial communities (microbiota) that change over time and vary depending on the type of cheese and their respective starter and adjunct cultures. These microorganisms play a crucial role in determining the flavor, quality and safety of the final product. Exploring the composition of cheese microbiota and the underlying molecular mechanisms involved in cheese ripening has been the subject of many studies. Recent advances in next generation sequencing (NGS) methods and the development of sophisticated bioinformatics tools have provided deeper insights into the composition and potential functionality of cheese microbiota far beyond the information provided by culture-dependent methods. These advances, which include rRNA gene amplicon sequencing and metagenomics, have been complemented and expanded in recent years by the application of metatranscriptomics, metaproteomics and metabolomics. This paper reviews studies in which application of these meta-omics technologies has led to a better understanding of the microbial composition and functionality of cheese and highlights opportunities by which the integration of outputs from diverse multi-omics analytical platforms (cheesomics) could be used in the future to advance our knowledge of the cheese ripening process and identify biomarkers for predicting cheese flavor, quality, texture and safety, and bioactive metabolites with potential to influence human health.

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants.

Type 2 Diabetes Mellitus has reached epidemic proportions as a result of over-nutrition and increasingly sedentary lifestyles. Current therapies, although effective, are not without limitations. These limitations, the alarming increase in the prevalence of diabetes, and the soaring cost of managing diabetes and its complications underscores an urgent need for safer, more efficient and affordable alternative treatments. Over 1200 plant species are reported in ethnomedicine for treating diabetes and these represents an important and promising source for the identification of novel antidiabetic compounds. Evaluating medicinal plants for desirable bioactivity goes hand-in-hand with methods in analytical biochemistry for separating and identifying lead compounds. This review aims to provide a comprehensive summary of current methods used in antidiabetic plant research to form a useful resource for researchers beginning in the field. The review summarises the current understanding of blood glucose regulation and the general mechanisms of action of current antidiabetic medications, and combines knowledge on common experimental approaches for screening plant extracts for antidiabetic activity and currently available analytical methods and technologies for the separation and identification of bioactive natural products. Common in vivo animal models, in vitro models, in silico methods and biochemical assays used for testing the antidiabetic effects of plants are discussed with a particular emphasis on in vitro methods such as cell-based bioassays for screening insulin secretagogues and insulinomimetics. Enzyme inhibition assays and molecular docking are also highlighted. The role of metabolomics, metabolite profiling, and dereplication of data for the high-throughput discovery of novel antidiabetic agents is reviewed. Finally, this review also summarises sample preparation techniques such as liquid-liquid extraction, solid phase extraction, and supercritical fluid extraction, and the critical function of nuclear magnetic resonance and high resolution liquid chromatography-mass spectrometry for the dereplication, putative identification and structure elucidation of natural compounds from evidence-based medicinal plants.

Recent developments in metabolomics-based research in understanding transgenic grass metabolism.

BACKGROUND: Transgenic herbicide-resistant (HR) turfgrass together with its associated, broad spectrum herbicides promise cheap, selective and efficient weed control by excluding infested weeds resulting in turf lawn with high uniformity and aesthetic value. The concept of this "weeding program" initiated from modern biotechnology has been widely implemented in several principal crops including maize, soybean, canola and cotton as early as the 1990s. Transgenic HR turfgrass classified as a genetically modified organism (GMO) has undoubtedly caused public concern with respect to its biosafety and legalities similar to well-established HR crops. Nevertheless, applying metabolomics-based approaches which focuses on the identification of the global metabolic state of a biological system in response to either internal or external stimuli can also provide a comprehensive characterization of transgenic grass metabolism and its involvement in biosecurity and public perception. AIM OF REVIEW: This review summaries the recent applications of metabolomics applied to HR crops to predict the molecular and physiological phenotypes of HR turfgrass species, glyphosate-resistant Kentucky bluegrass (Poa pratensis L.) and glufosinate-resistant creeping bentgrass (Agrotis stonifera L.). Additionally, this review also presents background knowledge with respect to the application of metabolomics, transformation of HR crops and its biosafety concerns, turfgrass botanical knowledge and its economic and aesthetic value. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purpose of this review is to demonstrate the molecular and physiological phenotypes of HR turfgrass based on several lines of evidence primarily derived from metabolomics data applied to HR crops to identify alterations on HR turfgrass metabolism as a result of genetic modification that confers resistant traits.

Lipidomics reveal the protective effects of a vegetable-derived isothiocyanate against retinal degeneration.

Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the ageing population. Without effective treatment strategies that can prevent disease progression, there is an urgent need for novel therapeutic interventions to reduce the burden of vision loss and improve patients' quality of life. Dysfunctional innate immune responses to oxidative stress observed in AMD can be caused by the formation of oxidised lipids, whilst polyunsaturated fatty acids have shown to increase the risk of AMD and disease progression in affected individuals. Previously, our laboratory has shown that the vegetable-derived isothiocyanate, L-sulforaphane (LSF), can protect human adult pigment epithelial cells from oxidative damage by upregulating gene expression of the oxidative stress enzyme Glutathione-S-Transferase µ1. This study aims to validate the protective effects of LSF on human retinal cells under oxidative stress conditions and to reveal the key players in fatty acid and lipid metabolism that may facilitate this protection. Methods: The in vitro oxidative stress model of AMD was based on the exposure of an adult retinal pigment epithelium-19 cell line to 200µM hydrogen peroxide. Percentage cell proliferation following LSF treatment was measured using tetrazolium salt-based assays. Untargeted fatty acid profiling was performed by gas chromatography-mass spectrometry. Untargeted lipid profiling was performed by liquid chromatography-mass spectrometry. Results: Under hydrogen peroxide-induced oxidative stress conditions, LSF treatment induced dose-dependent cell proliferation. The key fatty acids that were increased by LSF treatment of the retinal cells include oleic acid and eicosatrienoic acid. LSF treatment also increased levels of the lipid classes phosphatidylcholine, cholesteryl ester and oxo-phytodienoic acid but decreased levels of phosphatidylethanolamine lipids. Conclusions: We propose that retinal cells at risk of oxidative damage and apoptosis can be pre-conditioned with LSF to regulate levels of selected fatty acids and lipids known to be implicated in the pathogenesis and progression of AMD.

L-Sulforaphane Confers Protection Against Oxidative Stress in an In Vitro Model of Age-Related Macular Degeneration.

BACKGROUND: In age-related macular degeneration, oxidative damage and abnormal neovascularization in the retina are caused by the upregulation of vascular endothelium growth factor and reduced expression of Glutathione-S-transferase genes. Current treatments are only palliative. Compounds from cruciferous vegetables (e.g. L-Sulforaphane) have been found to restore normal gene expression levels in diseases including cancer via the activity of histone deacetylases and DNA methyltransferases, thus retarding disease progression. OBJECTIVE: To examine L-Sulforaphane as a potential treatment to ameliorate aberrant levels of gene expression and metabolites observed in age-related macular degeneration. METHOD: The in vitro oxidative stress model of AMD was based on the exposure of Adult Retinal Pigment Epithelium-19 cell line to 200µM hydrogen peroxide. The effects of L-Sulforaphane on cell proliferation were determined by MTS assay. The role of GSTM1, VEGFA, DNMT1 and HDAC6 genes in modulating these effects was investigated using quantitative real-time polymerase chain reaction. The metabolic profiling of L-Sulforaphane-treated cells via gas-chromatography massspectrometry was established. Significant differences between control and treatment groups were validated using one-way ANOVA, student t-test and post-hoc Bonferroni statistical tests (p<0.05). RESULTS: L-Sulforaphane induced a dose-dependent increase in cell proliferation in the presence of hydrogen peroxide by upregulating Glutathione-S-Transferase µ1 gene expression. Metabolic profiling revealed that L-Sulforaphane increased levels of 2-monopalmitoglycerol, 9, 12, 15,-(Z-Z-Z)- Octadecatrienoic acid, 2-[Bis(trimethylsilyl)amino]ethyl bis(trimethylsilyl)-phosphate and nonanoic acid but decreased ß-alanine levels in the absence or presence of hydrogen peroxide, respectively. CONCLUSION: This study supports the use of L-Sulforaphane to promote regeneration of retinal cells under oxidative stress conditions.

Review of recent developments in GC-MS approaches to metabolomics-based research.

BACKGROUND: Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available. AIM OF REVIEW: This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.