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.

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.

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.

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.

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.

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.

Mapping carbon fate during bleaching in a model cnidarian symbiosis: the application of 13 C metabolomics.

Coral bleaching is a major threat to the persistence of coral reefs. Yet we lack detailed knowledge of the metabolic interactions that determine symbiosis function and bleaching-induced change. We mapped autotrophic carbon fate within the free metabolite pools of both partners of a model cnidarian-dinoflagellate symbiosis (Aiptasia-Symbiodinium) during exposure to thermal stress via the stable isotope tracer (13 C bicarbonate), coupled to GC-MS. Symbiont photodamage and pronounced bleaching coincided with substantial increases in the turnover of non13 C-labelled pools in the dinoflagellate (lipid and starch store catabolism). However, 13 C enrichment of multiple compounds associated with ongoing carbon fixation and de novo biosynthesis pathways was maintained (glucose, fatty acid and lipogenesis intermediates). Minimal change was also observed in host pools of 13 C-enriched glucose (a major symbiont-derived mobile product). However, host pathways downstream showed altered carbon fate and/or pool composition, with accumulation of compatible solutes and nonenzymic antioxidant precursors. In hospite symbionts continue to provide mobile products to the host, but at a significant cost to themselves, necessitating the mobilization of energy stores. These data highlight the need to further elucidate the role of metabolic interactions between symbiotic partners, during the process of thermal acclimation and coral bleaching.

Root spatial metabolite profiling of two genotypes of barley (Hordeum vulgare L.) reveals differences in response to short-term salt stress.

Barley (Hordeum vulgare L.) is the most salt-tolerant cereal crop and has excellent genetic and genomic resources. It is therefore a good model to study salt-tolerance mechanisms in cereals. We aimed to determine metabolic differences between a cultivated barley, Clipper (tolerant), and a North African landrace, Sahara (susceptible), previously shown to have contrasting root growth phenotypes in response to the early phase of salinity stress. GC-MS was used to determine spatial changes in primary metabolites in barley roots in response to salt stress, by profiling three different regions of the root: root cap/cell division zone (R1), elongation zone (R2), and maturation zone (R3). We identified 76 known metabolites, including 29 amino acids and amines, 20 organic acids and fatty acids, and 19 sugars and sugar phosphates. The maintenance of cell division and root elongation in Clipper in response to short-term salt stress was associated with the synthesis and accumulation of amino acids (i.e. proline), sugars (maltose, sucrose, xylose), and organic acids (gluconate, shikimate), indicating a potential role for these metabolic pathways in salt tolerance and the maintenance of root elongation. The processes involved in root growth adaptation and the underlying coordination of metabolic pathways appear to be controlled in a region-specific manner. This study highlights the importance of utilizing spatial profiling and will provide us with a better understanding of abiotic stress response(s) in plants at the tissue and cellular level.

Metal and metalloid containing natural products and a brief overview of their applications in biology, biotechnology and biomedicine.

Bioinorganic natural product chemistry is a relatively unexplored but rapidly developing field with enormous potential for applications in biology, biotechnology (especially in regards to nanomaterial development, synthesis and environmental cleanup) and biomedicine. In this review the occurrence of metals and metalloids in natural products and their synthetic derivatives are reviewed. A broad overview of the area is provided followed by a discussion on the more common metals and metalloids found in natural sources, and an overview of the requirements for future research. Special attention is given to metal hyperaccumulating plants and their use in chemical synthesis and bioremediation, as well as the potential uses of metals and metalloids as therapeutic agents. The potential future applications and development in the field are also discussed.

Innovative Alternative Technologies to Extract Carotenoids from Microalgae and Seaweeds.

Marine microalgae and seaweeds (microalgae) represent a sustainable source of various bioactive natural carotenoids, including ß-carotene, lutein, astaxanthin, zeaxanthin, violaxanthin and fucoxanthin. Recently, the large-scale production of carotenoids from algal sources has gained significant interest with respect to commercial and industrial applications for health, nutrition, and cosmetic applications. Although conventional processing technologies, based on solvent extraction, offer a simple approach to isolating carotenoids, they suffer several, inherent limitations, including low efficiency (extraction yield), selectivity (purity), high solvent consumption, and long treatment times, which have led to advancements in the search for innovative extraction technologies. This comprehensive review summarizes the recent trends in the extraction of carotenoids from microalgae and seaweeds through the assistance of different innovative techniques, such as pulsed electric fields, liquid pressurization, supercritical fluids, subcritical fluids, microwaves, ultrasounds, and high-pressure homogenization. In particular, the review critically analyzes technologies, characteristics, advantages, and shortcomings of the different innovative processes, highlighting the differences in terms of yield, selectivity, and economic and environmental sustainability.

Egg Dispersal in the Phasmatodea: Convergence in Chemical Signaling Strategies Between Plants and Animals?

Numerous tree species' seeds contain an 'elaiosome' that acts as a food reward for ants and thus induces dispersal of the seeds. Many stick and leaf insect species appear to have evolved a convergent adaptation for dispersal whereby the egg 'capitulum' serves to induce ants to pick up and carry their eggs. Here, we investigated whether the capitulum facilitates egg dispersal by ants in the Australian stick insect Eurycnema goliath. The total fatty acid composition of E. goliath egg capsules and egg capitula were characterized to identify potential signaling compounds. Removing capitula from E. goliath eggs significantly reduced the likelihood of eggs being carried into the nests of Rhytidoponera metallica ants. Furthermore, attaching capitula to inert objects (polystyrene balls) resulted in these objects being carried into nests by R. metallica. Several fatty acids were present on the egg capsule surface in only trace amounts, whereas they made up over 10% of the dry weight of egg capitula. The fatty acid composition of egg capitula consisted mostly of palmitic acid (C16:0), linoleic acid (C18: 2n6c), oleic acid (C18:1n9c), linolenic acid (C18:3n3), and stearic acid (C18:0). Previously reported research has found that a diglyceride lipid species of oleic acid induces carrying behavior in R. metallica when added to inert artificial stimuli. Therefore, we propose that the dispersal mechanism of E. goliath eggs has converged upon the same chemical signaling pathway used by plants to exploit ant behavior.

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.

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.

A quantitative analysis of microalgal lipids for optimization of biodiesel and omega-3 production.

The lipid characteristics of microalgae are known to differ between species and change with growth conditions. This work provides a methodology for lipid characterization that enables selection of the optimal strain, cultivation conditions, and processing pathway for commercial biodiesel production from microalgae. Two different microalgal species, Nannochloropsis sp. and Chlorella sp., were cultivated under both nitrogen replete and nitrogen depleted conditions. Lipids were extracted and fractionated into three major classes and quantified gravimetrically. The fatty acid profile of each fraction was analyzed using GC-MS. The resulting quantitative lipid data for each of the cultures is discussed in the context of biodiesel and omega-3 production. This approach illustrates how the growth conditions greatly affect the distribution of fatty acid present in the major lipid classes and therefore the suitability of the lipid extracts for biodiesel and other secondary products.

Normalizing and integrating metabolomics data.

Metabolomics research often requires the use of multiple analytical platforms, batches of samples, and laboratories, any of which can introduce a component of unwanted variation. In addition, every experiment is subject to within-platform and other experimental variation, which often includes unwanted biological variation. Such variation must be removed in order to focus on the biological information of interest. We present a broadly applicable method for the removal of unwanted variation arising from various sources for the identification of differentially abundant metabolites and, hence, for the systematic integration of data on the same quantities from different sources. We illustrate the versatility and the performance of the approach in four applications, and we show that it has several advantages over the existing normalization methods.

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.

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.

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.