Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). A 2-week controlled feeding study mimicking the participants’ habitual diets was conducted among 153 postmenopausal women from the Women’s Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography–tandem mass spectrometry (LC–MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography–mass spectrometry (GC–MS). Variable selection was performed to build prediction models for each dietary variable. The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Experimental methods for determining 3-D atomic structures, such as crystallography, are rarely taught in the undergraduate curriculum, yet are considered to be the norm for 3-D structure determination in a research setting. Although a fully physical understanding of crystallography takes years of practice, practical applications and basic interpretation of small-molecule crystallography can be readily integrated into undergraduate curricula to give students a research-like laboratory experience. Three 1-h crystallography laboratory modules were developed using the free Olex(2) software to determine the structure of (dithiolene)(2)Co(1,3,5-triaza-7-phosphaadamantane).dichloroethane, while introducing basic crystallography knowledge, crystal evaluation through microscopy, practical structure determination skills, and spatial awareness through 3-D printing. Following implementation in an advanced instrumental analysis class composed of 14 Master's and undergraduate students, the increase of topical knowledge of small molecule crystallography was 18-30% based on tailored assessment surveys, and student feedback was highly positive. This suggests that students without a prior background in crystallography were able to learn and retain information about small molecule crystallography from these laboratory modules.

This case study demonstrates the ability of high school chemistry students, with varying levels of math preparation, to experience learning-gains on state and district assessments as it relates to chemical reactions, thermodynamics, and kinetics. These advances were predicated on the use of a teaching style rooted in abstract reasoning. The methodology was presented to students and modeled by the instructor over an entire school year to reinforce key proportional relationships featured in the balanced chemical equation and related topics such as acids and bases, reaction rates, equilibrium, and conservation of matter. Despite the small sample size, there was a general increase in student success, indicated by a statistically significant difference between students receiving instruction rooted in concrete reasoning and students receiving instruction rich in abstract reasoning.

The rice (Oryza sativa L.) ethylene-responsive transcription factor gene SUB1A-1 confers tolerance to prolonged, complete submergence by limiting underwater elongation growth. Upon desubmergence, SUB1A-1 genotypes rapidly recover photosynthetic function and recommence development towards flowering. The underpinnings of the transition from stress amelioration to the return to homeostasis are not well known. Here, transcriptomic and metabolomic analyses were conducted to identify mechanisms by which SUB1A improves physiological function over the 24 hr following a sublethal submergence event. Evaluation of near-isogenic genotypes after submergence and over a day of reaeration demonstrated that SUB1A transiently constrains the remodelling of cellular activities associated with growth. SUB1A influenced the abundance of ca. 1,400 transcripts and had a continued impact on metabolite content, particularly free amino acids, glucose, and sucrose, throughout the recovery period. SUB1A promoted recovery of metabolic homeostasis but had limited influence on mRNAs associated with growth processes and photosynthesis. The involvement of low energy sensing during submergence and recovery was supported by dynamics in trehalose-6-phosphate and mRNAs encoding key enzymes and signalling proteins, which were modulated by SUB1A. This study provides new evidence of convergent signalling pathways critical to the rapidly reversible management of carbon and nitrogen metabolism in submergence resilient rice.

Cellular senescence displays a heterogeneous set of phenotypes linked to tumor suppression; however, after drug treatment, senescence may also be involved in stable or recurrent cancer. Metabolic changes during senescence can provide detailed information on cellular status and may also have implications for the development of effective treatment strategies. The metabolic response to Adriamycin (ADR) treatment, which causes senescence as well as cell death, was obtained with the aid of metabolic profiling and isotope tracing in two human breast cancer cell lines, MCF7 and MDA-MB-231. After 5 days of ADR treatment, more than 60% of remaining, intact cells entered into a senescent state, characterized by enlarged and flattened morphology and positive blue staining using SA-β-gal. Metabolic trajectory analysis showed that the two cell lines’ responses were significantly different and were divided into two distinct stages. The metabolic shift from the first stage to the second was reflected by a partial recovery of the TCA cycle, as well as amino acid and lipid metabolisms. Isotope tracing analysis indicated that the higher level of glutamine metabolism helped maintain senescence. The results suggest that the dynamic changes during senescence indicate a multi-step process involving important metabolic pathways which might allow breast cancer cells to adapt to persistent ADR treatment, while the higher level of anapleurosis may be important for maintaining the senescent state. Ultimately, a better understanding of metabolic changes during senescence might provide targets for cancer therapy and tumor eradication.

Spacecraft assembly facilities are oligotrophic and low-humidity environments, which are routinely cleaned using alcohol wipes for benchtops and spacecraft materials, and alkaline detergents for floors. Despite these cleaning protocols, spacecraft assembly facilities possess a persistent, diverse, dynamic, and low abundant core microbiome, where the Acinetobacter are among the dominant members of the community. In this report, we show that several spacecraft-associated Acinetobacter metabolize or biodegrade the spacecraft cleaning reagents of ethanol (ethyl alcohol), 2-propanol (isopropyl alcohol), and Kleenol 30 (floor detergent) under ultraminimal conditions. Using cultivation and stable isotope labeling studies, we show that ethanol is a sole carbon source when cultivating in 0.2 × M9 minimal medium containing 26 μM Fe(NH4)2(SO4)2. Although cultures expectedly did not grow solely on 2-propanol, cultivations on mixtures of ethanol and 2-propanol exhibited enhanced plate counts at mole ratios of ≤0.50. In support, enzymology experiments on cellular extracts were consistent with oxidation of ethanol and 2-propanol by a membrane-bound alcohol dehydrogenase. In the presence of Kleenol 30, untargeted metabolite profiling on ultraminimal cultures of Acinetobacter radioresistens 50v1 indicated (1) biodegradation of Kleenol 30 into products including ethylene glycols, (2) the potential metabolism of decanoate (formed during incubation of Kleenol 30 in 0.2 × M9), and (3) decreases in the abundances of several hydroxy- and ketoacids in the extracellular metabolome. In ultraminimal medium (when using ethanol as a sole carbon source), A. radioresistens 50v1 also exhibits a remarkable survival against hydrogen peroxide (∼1.5-log loss, ∼108 colony forming units (cfu)/mL, 10 mM H2O2), indicating a considerable tolerance toward oxidative stress under nutrient-restricted conditions. Together, these results suggest that the spacecraft cleaning reagents may (1) serve as nutrient sources under oligotrophic conditions and (2) sustain extremotolerances against the oxidative stresses associated with low-humidity environments. In perspective, this study provides a plausible biochemical rationale to the observed microbial ecology dynamics of spacecraft-associated environments.

The Warburg effect is a well-known phenomenon in cancer, but the glutamine addiction in which cancer cells utilize glutamine as an alternative source of energy is less well known. Recent efforts have focused on preventing cancer cell proliferation associated with glutamine addiction by targeting glutaminase using the inhibitor BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide). In the current study, an investigation of the BPTES induced changes in metabolism was made in two human breast cancer cell lines, MCF7 (an estrogen receptor dependent cell line) and MDA-MB231 (a triple negative cell line), relative to the non-cancerous cell line, MCF10A. NMR spectroscopy combined with a recently established smart-isotope tagging approach enabled quantitative analysis of 41 unique metabolites representing numerous metabolite classes including carbohydrates, amino acids, carboxylic acids and nucleotides. BPTES induced metabolism changes in the cancer cell lines were especially pronounced under hypoxic conditions with up to 1/3 of the metabolites altered significantly (p < 0.05) relative to untreated cells. The BPTES induced changes were more pronounced for MCF7 cells, with 14 metabolites altered significantly (p < 0.05) compared to seven for MDA-MB231. Analyses of the results indicate that BPTES affected numerous metabolic pathways including glycolysis, TCA cycle, nucleotide and amino acid metabolism in cancer. The distinct metabolic responses to BPTES treatment determined in the two breast cancer cell lines offer valuable metabolic information for the exploration of the therapeutic responses to breast cancer.

Chronic kidney disease (CKD) is a public health problem with very high prevalence and mortality. Yet, there is a paucity of effective treatment options, partly due to insufficient knowledge of underlying pathophysiology. We combined metabolomics (GCMS) with kidney gene expression studies to identify metabolic pathways that are altered in adults with non-diabetic stage 3–4 CKD versus healthy adults. Urinary excretion rate of 27 metabolites and plasma concentration of 33 metabolites differed significantly in CKD patients versus controls (estimate range−68% to +113%). Pathway analysis revealed that the citric acid cycle was the most significantly affected, with urinary excretion of citrate, cis-aconitate, isocitrate, 2-oxoglutarate and succinate reduced by 40–68%. Reduction of the citric acid cycle metabolites in urine was replicated in an independent cohort. Expression of genes regulating aconitate, isocitrate, 2-oxoglutarate and succinate were significantly reduced in kidney biopsies. We observed increased urine citrate excretion (+74%, p=0.00009) and plasma 2-oxoglutarate concentrations (+12%, p=0.002) in CKD patients during treatment with a vitamin-D receptor agonist in a randomized trial. In conclusion, urinary excretion of citric acid cycle metabolites and renal expression of genes regulating these metabolites were reduced in non-diabetic CKD. This supports the emerging view of CKD as a state of mitochondrial dysfunction.

Phosphorylated carbohydrates are indispensable cogs in several key metabolic wheels for all forms of life. Here, a straightforward liquid chromatography method coupled to mass spectrometry detection was developed for phosphorylated sugars. For separation of the targeted compounds, hydrophilic interaction chromatography (HILIC) was used with a bridged-ethylene hybrid amide column under alkaline conditions using triethylamine as a mobile phase modifier. Methylphosphonic acid was added to the aqueous mobile phase to reduce the tailing of compounds containing phosphate groups, which are known to interact with stainless steel components of the separation system. Under alkaline conditions and addition of methylphosphonic acid, the retention behavior can be attributed to both conventional HILIC mechanisms as well as ion-pairing interactions in the mobile phase. This hypothesis is supported by comparing the retention behavior of phosphorylated sugars and unmodified sugars. The HILIC method resolved eight biologically important phosphorylated sugars and thereby enables simultaneous detection and quantification of these compounds: fructose-1,6-bisphosphate, glucose-1-phosphate, glucose-6-phosphate, lactose-1-phosphate, mannose-6-phosphate, ribose-5-phosphate, sucrose-6-phosphate, and threhalose-6-phosphate. Fructose-1-phosphate and fructose-6-phosphate were not resolved but quantification of total fructose-phosphate is possible.

The increasing scientific and industrial interest in metabolomics often takes advantage of the high level of qualitative and quantitative information provided by nuclear magnetic resonance (NMR) spectroscopy. However, several chemical and physical factors can affect the frequency of an NMR resonance. Especially in complex biological samples such as biofluids, small perturbations in NMR chemical shifts can complicate the recovery of biomarker information in metabolomics studies using multivariate statistics and pattern recognition tools. Novel segment-wise peak alignment algorithms have been proposed in the literature to correct the misalignment of NMR signals. The approach presented here, the Intensity Fluctuation Frequency Difference (IFFD) algorithm, is a highly efficient method designed to reduce variability in peak positions across the multiple NMR spectra used in metabolomics studies. This automated method refines segmentation using differences in the frequencies of the intensity fluctuations of signals and baseline noise to improve spectral alignment. Alignment is performed sequentially using an open source program, icoshift, employing a fast Fourier transform (FFT) engine to align all spectra simultaneously. The IFFD-icoshift method is illustrated for H-1 NMR spectra measured for 50 human urine samples collected from healthy volunteers: 41 samples, including urine from a pregnant female, were collected randomly following a normal dietary routine and 9 samples were collected after dietary supplementation with ibuprofen, alcoholic beverages or an energy drink. We demonstrate the superior performance of IFFD-icoshift alignment over a wide range of peaks and its capacity to enhance the interpretability and robustness of multivariate statistical analysis. This approach is widely applicable for NMR-based metabolic studies and is potentially suitable for many other types of data sets such as chromatographic profiles and MS data.

Oxygen deficiency, caused by flooding of all or a portion of a plant, leads to significant gene regulatory and metabolic responses associated with survival. When oxygen-deprived in light, aerial organs and root systems respond in distinct manners because of their respective autotrophy and heterotrophy, as well as intrinsic differences in cell biology and organ function. To better understand organ-specific responses to oxygen deficiency, we monitored changes in the metabolome of roots and shoots of Arabidopsis thaliana seedlings using gas chromatography-mass spectrometry and H-1-nuclear magnetic resonance spectroscopy. Only roots accumulated high amounts of -aminobutyrate (GABA) and lactate, whereas both organs accumulated alanine (Ala) upon hypoxia. Meta-analysis of gene regulation data revealed higher induction of mRNAs coding for fermentative enzymes in roots as compared with shoots. However, the elevation in GABA level was not correlated with changes in transcript abundance, supporting the proposal that post-translational mechanisms are important in metabolic acclimation to hypoxia. The biosynthesis, degradation and function of GABA and Ala during oxygen deprivation and re-aeration is discussed. Finally, a systematic survey of low-oxygen mediated regulation of genes associated with primary metabolism across organs and cell types reveals exciting new avenues for future studies.

Metabolomics techniques are the comprehensive assessment of endogenous metabolites in a biological system and may provide additional insight into the molecular mechanisms. Er-Zhi-Wan (EZW) is a traditional Chinese medicine formula, which contains Fructus Ligustri Lucidi (FLL) and Herba Ecliptae (HE). EZW is widely used to prevent and treat various liver injuries through the nourishment of the liver. However, the precise molecular mechanism of hepatoprotective effects has not been comprehensively explored. Here, an integrated metabolomics strategy was designed to assess the effects and possible mechanisms of EZW against carbon tetrachloride-induced liver injury, a commonly used model of both acute and chronic liver intoxication. High-performance chromatography/quadrupole time-of-flight mass spectrometry (HPLC/QTOF-MS) combined with chemometric approaches including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discover differentiating metabolites in metabolomics data of rat plasma and urine. Results indicate six differentiating metabolites, tryptophan, sphinganine, tetrahydrocorticosterone, pipecolic acid, L-2-amino-3-oxobutanoic acid and phosphoribosyl pyrophosphate, in the positive mode. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan metabolism, sphingolipid metabolism, steroid hormone biosynthesis, lysine degradation, glycine, serine and threonine metabolism, and pentose phosphate pathway. Of note, EZW has a potential pharmacological effect, which might be through regulating multiple perturbed pathways to the normal state. Our findings also showed that the robust integrated metabolomics techniques are promising for identifying more biomarkers and pathways and helping to clarify the function mechanisms of traditional Chinese medicine.

Metabolomics and chemical genomics studies can each provide unique insights into plant biology. Although a variety of analytical techniques can be used for the interrogation of plant systems, nuclear magnetic resonance (NMR) provides unbiased characterization of abundant metabolites. An example methodology is provided for probing the metabolism of Arabidopsis thaliana in a chemical genomics experiment including methods for tissue treatment, tissue collection, metabolite extraction, and methods to minimize variance in biological and technical sample replicates. Additionally, considerations and methods for data analysis, including multivariate statistics, univariate statistics, and data interpretation are included. The process is illustrated by examining the metabolic effects of chemical treatment of Arabidopsis with Sortin 1, also known as vacuolar protein sorting inhibitor 1. Sortin 1 was applied to Arabidopsis seedlings to examine metabolic effects in a chemical genomics experiment and to demonstrate the utility of metabolomics in conjunction with other "omics" techniques.

A chemometric technique, visual interpretation of z-score ratios (VIZR), written in the open source code R, has been developed to identify metabolic differences between individual biosamples and a control group. To demonstrate the capabilities of VIZR, 49 urine samples were collected from healthy volunteers: 41 samples were collected randomly following a normal dietary routine and 7 test samples were collected after dietary supplementation with either ibuprofen or alcoholic beverages. An eighth test sample was prepared by 50 % dilution of a control sample. Sample analysis was conducted by 1H nuclear magnetic resonance (NMR) spectroscopy and the collected data were subjected to VIZR analysis, which successfully discriminated each of the 8 test samples from the 41 control samples. In addition, VIZR analysis revealed the NMR spectral regions responsible for the disparity between the individual test samples and the control group. The self-normalizing nature of the VIZR calculation provides a robust analysis independent of dilution effects, which is especially important in urine analyses. Potential applications of VIZR include high-throughput data analysis for toxicological profiling, disease diagnosis, and biomarker identification in any type of biosample for which a control dataset can be established. Although demonstrated herein for the statistical analysis of 1H NMR data, the VIZR program is platform independent and could be applied to digitized metabolic datasets acquired using other techniques including hyphenated mass spectrometry measurements.

Global climate change has increased flooding events, which affect both natural vegetation dynamics and crop productivity. The flooded environment is lethal for most plant species because it restricts gas exchange and induces an energy and carbon crisis. Flooding survival strategies have been studied in Oryza sativa, a cultivated monocot. However, our understanding of plant adaptation to natural flood-prone environments remains scant, even though wild plants represent a valuable resource of tolerance mechanisms that could be used to generate stress-tolerant crops. Here we identify mechanisms that mediate the distinct flooding survival strategies of two related wild dicot species: Rumex palustris and Rumex acetosa. Whole transcriptome sequencing and metabolite profiling reveal flooding-induced metabolic reprogramming specific to R. acetosa. By contrast, R. palustris uses the early flooding signal ethylene to increase survival by regulating shade avoidance and photomorphogenesis genes to outgrow submergence and by priming submerged plants for future low oxygen stress. These results provide molecular resolution of flooding survival strategies of two species occupying distinct hydrological niches. Learning how these contrasting flood adaptive strategies evolved in nature will be instrumental for the development of stress-tolerant crop varieties that deliver enhanced yields in a changing climate.