Determination of nonylphenol ethoxylate metabolites in vegetables and crops by high performance liquid chromatography-tandem mass spectrometry

A method has been developed for the simultaneous determination of the concentration of nonylphenol (4-NP), nonylphenol monoethoxylates (NP₁EO) and nonylphenol diethoxylates (NP₂EO) in vegetables and crops by liquid chromatography-tandem quadrupole mass spectrometry (HPLC-MS/MS). These target compounds were extracted from vegetable and crop samples with acetonitrile, and then the extracts were cleaned using solid phase extraction with graphitised carbon black tandem primary secondary amine (PSA) cartridges. The MS method enabled highly reliable identification by monitoring the corresponding ammonium adduct [M+NH₄]⁺ in the positive mode for NP₁EO and NP₂EO, and the deprotonated molecule [M−H]⁻ in the negative mode for 4-NP. Recoveries for the spiked samples ranged from 65% to 118%. The limit of detection (LOD) of 4-NP, NP₁EO and NP₂EO was 3, 5 and 0.1 μg kg⁻¹, respectively. This method would be useful for the quick and routine detection of the residues of 4-NP, NP₁EO and NP₂EO in vegetables and crops.     

Early detection of food pathogens and food spoilage microorganisms: Application of metabolomics

BackgroundFood safety is a major issue, with a large number of people around the world suffering from illness due to the consumption of contaminated and unsafe food products. An early detection of food pathogens and spoilage microorganisms is an important step that can help to control a foodborne outbreak, thus avoiding the loss of a massive amount of food products.Scope and approachMetabolomics is generally a hypothesis generating tool that makes use of different analytical instruments to analyse as many metabolites as possible in a given biological sample. Metabolomics has already been successfully applied to different areas of food science. Here, I present metabolomics as a valuable tool for studying the metabolism of food pathogens and spoilage microorganisms.Key findings and conclusionsThe scientific area of metabolomics has improved tremendously over last decade. Due to the rapid development of instrumental platforms, it is now possible to analyse a wide range of metabolites present in food and produced by microorganisms. This approach has a high potential to determine biomarkers which can later be used for the development of early detection tools for food pathogens and spoilage microorganisms, thus ensuring a better management of food safety.     

Targeting the gut microbiota by dietary nutrients: A new avenue for human health

The gut microbiota is a complex ecosystem consisted of trillions of microbes that have co-evolved with their host for hundreds of millions of years. During the last decade, a growing body of knowledge has suggested that there is a compelling set of connections among diet, gut microbiota and human health. Various physiological functions of the host, ranging from metabolic and immune regulation to nerve and endocrine development, are possibly mediated by the structural components of microbial cell or the products of microbial metabolism, which are greatly influenced by dietary macronutrients and micronutrients. Thus, governing the production and activity of these microbial-associated small molecules and metabolites through dietary intervention may provide promising strategies for the improvement of human health and disease. In this review article, we first provide an overview of current findings about the intimate interrelationships between diet and gut microbiota. We also introduce the physiological effects of some microbial-associated small molecules and metabolites on the host as well as the detailed signaling mechanisms.     

Isolation and structural characterisation of five new and 14 known metabolites from the commercial starfish Archaster typicus

From the commercially available starfish Archaster typicus, five new (1–5) and 14 known (6–19) metabolites were isolated and identified. Detailed 1D and 2D NMR spectroscopic data, including ¹H, ¹³C, DEPT, HSQC, HMBC, and NOESY, established the structures of the new metabolites as sodium 5α-cholesta-9(11),24-dien-3β,6α,20β-triol-23-one 3-sulphate (1), sodium 5α-cholesta-9(11)-en-3β,6α,20β-triol-23-one 3-sulphate (2), sodium (25R)-5α-cholestane-3β,4β,6α,8,14α,15β,26-heptaol-15-sulphate (3), sodium (25R)-5α-cholestane-3β,6α,8,14α,15β,26-hexaol 15-sulphate (4), and sodium cholest-25(27)-ene-3β,4β,5α,6α,7β,8β,14α,15α,24,26-decanol 6-sulphate (5). Other spectroscopic techniques, including IR, ESI–MS, and HR-ESI–MS, were also adopted to further confirm the structures of the metabolites. These five steroids (1–5) are reported in nature for the first time. All of the steroids found in A. typicus (1–12) were tested for anticancer activities against MDA-MB-435 and Colo205 tumour cells. However, only sodium 5α-cholesta-9(11)-en-3β,6α,20β-triol-23-one 3-sulphate (2) and 27-nor-5α-cholestane-3β,4β,5,6α,7β,8,14,15α,24α-nonaol (6) exhibited weak activities.     

PCBs and DDE, but not PBDEs, increase with trophic level and marine input in nestling bald eagles

Concentrations of persistent contaminants often vary widely among individuals within a population. We hypothesized that such variation was caused mainly by differences in diet (biomagnification) and in coastal systems by the tendency of marine systems to act as contaminant sinks. We examined the relationship between contaminant concentrations and stable isotope ratios in nestling plasma from an apex predator with a particularly broad diet. Our study included freshwater, estuarine, inshore and pelagic breeding sites. Bald eagles (Haliaeetus leucocephalus) at the pelagic marine sites showed high trophic level and marine input, eagles at the freshwater sites showed low trophic level and marine input, and eagles at the estuarine and inshore marine sites had intermediate values. The relationship between trophic level and marine input may reflect longer food chains in pelagic compared to terrestrial ecosystems. ∑PCBs and DDE concentrations generally increased with trophic level and marine input, with the exception of the freshwater sites, while ∑PBDEs, hydroxylated-PBDEs and hydroxylated-PCBs increased with marine input, but were independent of trophic level. The relationships for ∑PCBs and DDE were often slightly stronger with marine input than trophic level, suggesting that oceanographic processes may be more important than trophic level. At freshwater locations, spatial variation may be more important than trophic level due to the heterogeneity of contaminant profiles between feeding locations (lakes, rivers, agricultural fields). Adults had similar isotopic composition to their chicks but higher contamination. Based on nests where prey composition was determined independently, isotopic enrichment values for nestling plasma were 1.6 ± 0.1 (δ¹⁵N) and − 0.4 ±0.2 (δ¹³C). We conclude that trophic level and marine influence are significant factors influencing PCB and DDE concentrations in eagles. However, trophic level in particular did not influence PBDEs, possibly due to their being metabolized by eagles.     

Physiological and structural events post mortem of importance for drip loss in pork

Early post mortem metabolism and structural changes from 3 to 24 h, together with pH, temperature and impedance Py development were investigated in 37 Duroc×Landrace×Large White (DLY) pigs covering a range of drip loss from 2.2 to 12.6%. Multivariate statistical analysis was used to assess the impacts of different metabolites, pH and temperature, impedance, cytoskeletal protein degradation and extracellular cross-sectional area on drip loss. Taken as single factors, the concentration of lactate could explain 80% of the variation in drip, inosine monophosphate (IMP) and adenosine triphosphate (ATP) concentration explained 71 and 68%, respectively, whereas inosin and glycogen levels explained only 59 and 60%. The extracellular area was found to explain 39% of the variation in drip. The area between fibres provided more significant information than did the area between fibre bundles. The degradation of the cytoskeletal proteins was not related to drip loss. Impedance Py development over 24 h could explain 66% of the variation in drip, whereas pH and temperature explained 85 and 87%, respectively. A model including all measured variables could explain 83% of the variation in drip. However, only pH, temperature, impedance, [ATP]_{1 h} and [lactate]_{1 h and 2 h} were significant in relation to drip. By reducing the variables in the multivariate analysis, 89% of the variation in drip could be explained by a model containing only pH_{2 h} and temperature_{1 min}. To explain variation in drip loss, pH and temperature measurements at significant time points were sufficient. Variation in post-mortem metabolites did, however, explain why variation in pH and temperature occurred. Development of drip channels was ruled by pH and temperature while impedance development was highly correlated to pH. This multi-faceted study shows those parameters, which can best be used to indicate or predict WHC, as well as those indicating the basic mechanism underlying variations in drip.