Whale sharks Rhincodon typus get cleaned by the blue-streak cleaner wrasse Labroides dimidiatus and the moon wrasse Thalassoma lunare in the Philippines

Cleaning interactions are essential for healthy marine ecosystem communities. This study reports the first documentation of the whale shark Rhincodon typus cleaning behaviour in the Indo-West Pacific by two wrasse species, the blue-streak cleaner wrasse Labroides dimidiatus and the moon wrasse Thalassoma lunare in Cebu, Philippines. This study documented 36 cleaning interactions with 14 individual whale sharks. The cleaning interactions appear opportunistic rather than targeted by the sharks, unlike that observed in other species of elasmobranchs. Further work should focus on understanding the drivers of these unique cleaning interactions.     

Characterizing the metabolic actions of natural stresses in the California red abalone, <Emphasis Type="Italic">Haliotis rufescens</Emphasis> using <Superscript>1</Superscript>H NMR metabolomics

Withering syndrome in California red abalone (Haliotis rufescens) is caused by the Rickettsiales-like prokaryote (WS-RLP) Candidatus Xenohaliotis californiensis. WS-RLP infection is not sufficient to cause withering syndrome, and for reasons not yet well understood additional stressors such as elevated water temperature appear to influence disease development. Using nuclear magnetic resonance (NMR) based metabolomics, we have investigated the influence of food availability, temperature, and bacterial infection, both individually and in combination, on the metabolic status of the red abalone. Food limitation caused dramatic reductions in all observed classes of foot muscle metabolites, while at the same time metabolite levels within the digestive gland were preserved or increased. We also found that food limitation in combination with elevated temperature led to greater metabolic perturbations in both tissue types than those observed under food limitation alone. WS-RLP infection and food-limitation resulted in many of the same metabolic changes within the tissues studied, although the effects of infection were less severe. We observed increased levels of homarine in the digestive gland of both food-limited and WS-RLP-infected animals, yet only observed increased homarine levels in the foot muscle of infected abalone. These results further support the recently established glucose-to-homarine ratio in foot muscle as a potential marker for differentiating WS-RLP-infected animals from those of both healthy and food limited abalone. Furthermore, we found that the NMR metabolic data correlates well with histological measurements supporting the use of the metabolomics approach for characterizing both normal and pathological events in marine species, particularly during periods of environmentally relevant stress.     

Evidence of continued hunting of whale sharks <Emphasis Type="Italic">Rhincodon typus</Emphasis> in the Maldives

Superficial dermal wounds in whale sharks are reported to heal rapidly as with many other elasmobranchs. Here observations of two wounded whale sharks (Rhincodon typus) in Maldivian waters suggest that free ranging sharks are able to recover and rapidly heal from the effects of deeper wounding on internal organs or amputations. One specimen observed impaled by a wooden harpoon shaft, was subsequently re-encountered nearly a year later. The other suffered a near severed first dorsal fin but showed signs of rapid healing. These observations illustrate that despite national bans in whale sharks fishing, the practise persists in the Maldives. Further research to increase understanding of the demography of aggregations of this species is necessary before the impact of illegal exploitation on regional population trends can be determined. National governments are encouraged to enhance marine conservation outreach and education programmes throughout their territories.     

Metabolic profiling of gender: Headspace-SPME/GC–MS and <Superscript>1</Superscript>H NMR analysis of urine

This study aims to investigate the metabolic difference between male and female healthy adults using a combination of GC–MS and NMR metabolomics techniques. While metabolomics has shown wide applications in characterizing the status and progression of many diseases, physiological factors such as gender often contribute high levels of variability that can hinder the detection of biomarkers of interest, such as in disease detection. We carried out a detailed exploration of gender related metabolic profiling of human urine using a Headspace-SPME/GC–MS approach and detected over two hundred peaks. Fifty-nine metabolites were identified using the NIST library. ¹H NMR spectroscopy was also utilized, and resulted in the identification of eighteen metabolites. We find that both GC–MS and NMR are able to capture human gender metabolic differences, and their combination allows a significantly better understanding of this difference. Subtle differences between genders are found to be related to the metabolism of fats, amino acids, and TCA cycle intermediates.     

Signal Intensities Derived from Different NMR Probes and Parameters Contribute to Variations in Quantification of Metabolites

We discovered that serious issues could arise that may complicate interpretation of metabolomic data when identical samples are analyzed at more than one NMR facility, or using slightly different NMR parameters on the same instrument. This is important because cross-center validation metabolomics studies are essential for the reliable application of metabolomics to clinical biomarker discovery. To test the reproducibility of quantified metabolite data at multiple sites, technical replicates of urine samples were assayed by 1D-¹H-NMR at the University of Alberta and the University of Michigan. Urine samples were obtained from healthy controls under a standard operating procedure for collection and processing. Subsequent analysis using standard statistical techniques revealed that quantitative data across sites can be achieved, but also that previously unrecognized NMR parameter differences can dramatically and widely perturb results. We present here a confirmed validation of NMR analysis at two sites, and report the range and magnitude that common NMR parameters involved in solvent suppression can have on quantitated metabolomics data. Specifically, saturation power levels greatly influenced peak height intensities in a frequency-dependent manner for a number of metabolites, which markedly impacted the quantification of metabolites. We also investigated other NMR parameters to determine their effects on further quantitative accuracy and precision. Collectively, these findings highlight the importance of and need for consistent use of NMR parameter settings within and across centers in order to generate reliable, reproducible quantified NMR metabolomics data.     

Metabolic signatures of esophageal cancer: NMR-based metabolomics and UHPLC-based focused metabolomics of blood serum

Focused metabolic profiling is a powerful tool for the determination of biomarkers. Here, a more global proton nuclear magnetic resonance (¹H NMR)-based metabolomic approach coupled with a relative simple ultra high performance liquid chromatography (UHPLC)-based focused metabolomic approach was developed and compared to characterize the systemic metabolic disturbances underlying esophageal cancer (EC) and identify possible early biomarkers for clinical prognosis. Serum metabolic profiling of patients with EC (n = 25) and healthy controls (n = 25) was performed by using both ¹H NMR and UHPLC, and metabolite identification was achieved by multivariate statistical analysis. Using orthogonal projection to least squares discriminant analysis (OPLS-DA), we could distinguish EC patients from healthy controls. The predictive power of the model derived from the UHPLC-based focused metabolomics performed better in both sensitivity and specificity than the results from the NMR-based metabolomics, suggesting that the focused metabolomic technique may be of advantage in the future for the determination of biomarkers. Moreover, focused metabolic profiling is highly simple, accurate and specific, and should prove equally valuable in metabolomic research applications. A total of nineteen significantly altered metabolites were identified as the potential disease associated biomarkers. Significant changes in lipid metabolism, amino acid metabolism, glycolysis, ketogenesis, tricarboxylic acid (TCA) cycle and energy metabolism were observed in EC patients compared with the healthy controls. These results demonstrated that metabolic profiling of serum could be useful as a screening tool for early EC diagnosis and prognosis, and might enhance our understanding of the mechanisms involved in the tumor progression.     

Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were recorded by both ¹H NMR and accurate mass LC-quadrupole time-of-flight (QTOF) MS. Different analytical selectivities were found for these both profiling techniques. In fact, NMR and LCMS provided complementary data, as the metabolites detected belong to essentially different metabolic pathways. Yet, upon unsupervised multivariate analysis, both NMR and LCMS datasets revealed a clear segregation of, on the one hand, the cherry tomatoes and, on the other hand, the beef and round tomatoes. Intra-method (NMR–NMR, LCMS–LCMS) and inter-method (NMR–LCMS) correlation analyses were performed enabling the annotation of metabolites from highly correlating metabolite signals. Signals belonging to the same metabolite or to chemically related metabolites are among the highest correlations found. Inter-method correlation analysis produced highly informative and complementary information for the identification of metabolites, even in de case of low abundant NMR signals. The applied approach appears to be a promising strategy in extending the analytical capacities of these metabolomics techniques with regard to the discovery and identification of biomarkers and yet unknown metabolites. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Multimodal biomarker discovery for active Onchocerca volvulus infection

The neglected tropical disease onchocerciasis, or river blindness, is caused by infection with the filarial nematode Onchocerca volvulus. Current estimates indicate that 17 million people are infected worldwide, the majority of them living in Africa. Today there are no non-invasive tests available that can detect ongoing infection, and that can be used for effective monitoring of elimination programs. In addition, to enable pharmacodynamic studies with novel macrofilaricide drug candidates, surrogate endpoints and efficacy biomarkers are needed but are non-existent. We describe the use of a multimodal untargeted mass spectrometry-based approach (metabolomics and lipidomics) to identify onchocerciasis-associated metabolites in urine and plasma, and of specific lipid features in plasma of infected individuals (O. volvulus infected cases: 68 individuals with palpable nodules; lymphatic filariasis cases: 8 individuals; non-endemic controls: 20 individuals). This work resulted in the identification of elevated concentrations of the plasma metabolites inosine and hypoxanthine as biomarkers for filarial infection, and of the urine metabolite cis-cinnamoylglycine (CCG) as biomarker for O. volvulus. During the targeted validation study, metabolite-specific cutoffs were determined (inosine: 34.2 ng/ml; hypoxanthine: 1380 ng/ml; CCG: 29.7 ng/ml) and sensitivity and specificity profiles were established. Subsequent evaluation of these biomarkers in a non-endemic population from a different geographical region invalidated the urine metabolite CCG as biomarker for O. volvulus. The plasma metabolites inosine and hypoxanthine were confirmed as biomarkers for filarial infection. With the availability of targeted LC-MS procedures, the full potential of these 2 biomarkers in macrofilaricide clinical trials, MDA efficacy surveys, and epidemiological transmission studies can be investigated.     

Phospholipid capture combined with non-linear chromatographic correction for improved serum metabolite profiling

Serum analysis with LC/MS can yield thousands of potential metabolites. However, in metabolomics, biomarkers of interest will often be of low abundance, and ionization suppression from high abundance endogenous metabolites such as phospholipids may prevent the detection of these metabolites. Here a cerium-modified column and methyl-tert-butyl-ether (MTBE) liquid–liquid extraction were employed to remove phospholipids from serum in order to obtain a more comprehensive metabolite profile. XCMS, an in-house developed data analysis software platform, showed that the intensity of existing endogenous metabolites increased, and that new metabolites were observed. This application of phospholipid capture in combination with XCMS non-linear data processing has enormous potential in metabolite profiling, for biomarker detection and quantitation.     

1H-NMR and MS Based Metabolomics Study of the Intervention Effect of Curcumin on Hyperlipidemia Mice Induced by High-Fat Diet

Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD) feeding for 12 weeks. The HFD induced animals were orally administered with curcumin (40, 80 mg/kg) or lovastatin (30 mg/kg, positive control) once a day during the inducing period. Serum biochemistry assay of TC, TG, LDL-c, and HDL-c was conducted and proved that treatment of curcumin or lovastatin can significantly improve the lipid profiles. Subsequently, metabolomics analysis was carried out for urine samples. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) was employed to investigate the anti-hyperlipidemia effect of curcumin and to detect related potential biomarkers. Totally, 35 biomarkers were identified, including 31 by NMR and nine by MS (five by both). It turned out that curcumin treatment can partially recover the metabolism disorders induced by HFD, with the following metabolic pathways involved: TCA cycle, glycolysis and gluconeogenesis, synthesis of ketone bodies and cholesterol, ketogenesis of branched chain amino acid, choline metabolism, and fatty acid metabolism. Besides, NMR and MS based metabolomics proved to be powerful tools in investigating pharmacodynamics effect of natural products and underlying mechanisms.     

Mass spectrometry based environmental metabolomics: a primer and review

Environmental metabolomics can be described as the study of the interactions of living organisms with their natural environments at the metabolic level. Until recently, nuclear magnetic resonance (NMR) spectroscopy has been the primary bioanalytical tool for measuring metabolite levels in this field. While NMR has some specific advantages, the higher sensitivity offered by mass spectrometry (MS) is beginning to revolutionise our ability to probe environmental metabolomes. This review provides the first comprehensive overview of the use and capabilities of MS within environmental metabolomics. Its primary aims are to introduce environmental scientists to the range of MS approaches used in metabolomics and to highlight the breadth and diversity of environmental and ecological research conducted, from ecophysiology and ecotoxicology to chemical ecology. The review is structured around MS approaches: non-targeted gas chromatography–MS, non-targeted directed infusion MS, and both non-targeted and targeted liquid chromatography–MS. Each section begins with a brief introduction to the analytical method, including some advantages and limitations in the context of metabolomics research, and then exemplifies the use of that technique in environmental metabolomics. The review concludes with a discussion on some of the challenges that remain in MS based environmental metabolomics and provides recommendations for the path ahead.

     

Urinary metabolomic phenotyping of nickel induced acute toxicity in rat: an NMR spectroscopy approach

The metabolomic approach has been widely used in toxicology to investigate mechanisms of toxicity. To understand the mammalian system??s response to nickel exposure, we analysed the NiCl₂ induced metabolomic changes in urine of rats using ¹H nuclear magnetic resonance (¹H NMR) spectroscopy together with clinically relevant biochemical parameters. Male Sprague?CDawley rats were administered intraperitoneally with NiCl₂ at doses of 4, 10 and 20?mg/kg body weight. Urine samples were collected at 8, 16, 24, 72, 96 and 120?h post treatment. The metabolomic profile of rat urine showed prominent changes in citrate, dimethylamine, creatinine, choline, trimethylamine oxide (TMAO), phenyl alanine and hippurate at all doses. Principal component analysis of urine ¹H NMR spectra demonstrated the dose and time dependent development of toxicity. The metabolomic time trajectory, based on pattern recognition analysis of ¹H NMR spectra of urine, illustrated clear separation of pre and post treatments (temporal). Only animals treated with a low dose of NiCl₂ returned to normal physiology. The ¹H NMR spectral data correlated well with the clinically relevant nephrotoxic biomarkers. The urinary metabolomic phenotyping for NiCl₂ induced nephrotoxicity was defined according to the predictive ability of the known metabolite biomarkers, creatinine, citrate and TMAO. The current approach demonstrates that metabolomics, one of the most important platform in system biology, may be a promising tool for identifying and characterizing biochemical responses to toxicity.     

生态代谢组学研究进展

代谢组学指某一生物系统中产生的或已存在的代谢物组的研究,以质谱和核磁共振技术为分析平台,以信息建模与系统整合为目标。随着代谢组学中的研究方法与技术成为生态学研究的有力工具,生态代谢组学概念应运而生,即研究某一个生物体对环境变化的代谢物组水平的响应。理清代谢组学与生态代谢组学学科发展的脉络,综述代谢组学研究中的常用技术及其优势与局限性,论述代谢组学技术在生态学研究中的应用现状,展望代谢组学技术与其他系统生物学组学技术的结合在生态学中的应用前景,提出生态代谢组学研究者未来要完成的任务和面对的挑战。     

Human metabolic profiles are stably controlled by genetic and environmental variation

¹H Nuclear Magnetic Resonance spectroscopy (¹H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top‐down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource. In our unique design, identical and non‐identical twin pairs donated plasma and urine samples longitudinally. We acquired ¹H NMR spectra on the samples, and statistically decomposed variation in metabolite concentration into familial (genetic and common‐environmental), individual‐environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual‐environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in ¹H NMR‐detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker‐discovery studies. We provide a power‐calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect ¹H NMR‐based biomarkers quantifying predisposition to disease.     

Whale Sharks,Rhincodon typus,Aggregate around Offshore Platforms in Qatari Waters of the Arabian Gulf to Feed on Fish Spawn

Whale sharks, Rhincodon typus, are known to aggregate to feed in a small number of locations in tropical and subtropical waters. Here we document a newly discovered major aggregation site for whale sharks within the Al Shaheen oil field, 90 km off the coast of Qatar in the Arabian Gulf. Whale sharks were observed between April and September, with peak numbers observed between May and August. Density estimates of up to 100 sharks within an area of 1 km² were recorded. Sharks ranged between four and eight metres’ estimated total length (mean 6.92±1.53 m). Most animals observed were actively feeding on surface zooplankton, consisting primarily of mackerel tuna, Euthynnus affinis, eggs.     

A missing piece in the Arctic food web puzzle? Stomach contents of Greenland sharks sampled in Svalbard, Norway

Harbour seals in Svalbard have short longevity, despite being protected from human hunting and having limited terrestrial predation at their haulout sites, low contaminant burdens and no fishery by-catch issues. This led us to explore the diet of Greenland sharks (Somniosus microcephalus) in this region as a potential seal predator. We examined gastrointestinal tracts (GITs) from 45 Greenland sharks in this study. These sharks ranged from 229 to 381?cm in fork length and 136–700?kg in body mass; all were sexually immature. Seal and whale tissues were found in 36.4 and 18.2%, respectively, of the GITs that had contents (n?=?33). Based on genetic analyses, the dominant seal prey species was the ringed seal (Pusa hispida); bearded seal (Erignathus barbatus) and hooded seal (Cystophora cristata) tissues were each found in a single shark. The sharks had eaten ringed seal pups and adults based on the presence of lanugo-covered prey (pups) and age determinations based on growth rings on claws (≤1?year and adults). All of the whale tissue was from minke whale (Balenoptera acutorostrata) offal, from animals that had been harvested in the whale fishery near Svalbard. Fish dominated the sharks’ diet, with Atlantic cod (Gadus morhua), Atlantic wolffish (Anarhichas lupus) and haddock (Melanogrammus aeglefinus) being the most important fish species. Circumstantial evidence suggests that these sharks actively prey on seals and fishes, in addition to eating carrion such as the whale tissue. Our study suggests that Greenland sharks may play a significant predatory role in Arctic food webs.     

Microbial metabolites are associated with a high adherence to a Mediterranean dietary pattern using a 1H-NMR-based untargeted metabolomics approach

The study of biomarkers of dietary patterns including the Mediterranean diet (MedDiet) is scarce and could improve the assessment of these patterns. Moreover, it could provide a better understanding of health benefits of dietary patterns in nutritional epidemiology. We aimed to determine a robust and accurate biomarker associated with a high adherence to a MedDiet pattern that included dietary assessment and its biological effect. In this cross-sectional study, we included 56 and 63 individuals with high (H-MDA) and low (L-MDA) MedDiet adherence categories, respectively, all from the Prevención con Dieta Mediterránea trial. A ¹H-NMR-based untargeted metabolomics approach was applied to urine samples. Multivariate statistical analyses were conducted to determine the metabolite differences between groups. A stepwise logistic regression and receiver operating characteristic curves were used to build and evaluate the prediction model for H-MDA. Thirty-four metabolites were identified as discriminant between H-MDA and L-MDA. The fingerprint associated with H-MDA included higher excretion of proline betaine and phenylacetylglutamine, among others, and decreased amounts of metabolites related to glucose metabolism. Three microbial metabolites — phenylacetylglutamine, p-cresol and 4-hydroxyphenylacetate — were included in the prediction model of H-MDA (95% specificity, 95% sensitivity and 97% area under the curve). The model composed of microbial metabolites was the biomarker that defined high adherence to a Mediterranean dietary pattern. The overall metabolite profiling identified reflects the metabolic modulation produced by H-MDA. The proposed biomarker may be a better tool for assessing and aiding nutritional epidemiology in future associations between H-MDA and the prevention or amelioration of chronic diseases.     

Easy preparation of a large-size random gene mutagenesis library in Escherichia coli

Osmolytes are accumulated intracellularly to offset the effects of osmotic stress and protect cellular proteins against denaturation. Because different taxa accumulate different osmolytes, they can also be used as "dietary biomarkers" to study foraging. Potential osmolyte biomarkers include glycine betaine, trimethylamine N-oxide (TMAO), homarine, dimethylsulfoniopropionate (DMSP), and the osmolyte analog arsenobetaine (AsB). We present a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for the simultaneous measurement of these osmolytes in serum or plasma. Varying concentrations of osmolytes were added to serum and samples and extracted in 90% acetonitrile and 10% methanol containing 10 μM deuterated internal standards (D(9)-glycine betaine, D(9)-trimethylamine-N-oxide, (13)C(2)-arsenobetaine, D(6)-DMSP, and D(4)-homarine). Analytes were separated on a normal-phase modified silica column and detected using isotope dilution tandem mass spectrometry in multiple reaction monitoring (MRM) mode. The assay was linear for all six compounds (r(2) values=0.983-0.996). Recoveries were greater than 85%, and precision for within-batch coefficients of variation (CVs) were less than 8.2% and between-batch CVs were less than 6.1%. Limits of detection ranged from 0.02 to 0.12 μmol/L. LC-MS/MS is a simple method with high throughput for measuring low levels of osmolytes that are often present in biological samples.     

Metabolomic evaluation of rat liver and testis to characterize the toxicity of triazole fungicides

The effects of two triazole fungicides, myclobutanil and triadimefon, on endogenous rat metabolite profiles in blood serum, liver, and testis was assessed using proton nuclear magnetic resonance (¹H-NMR) spectroscopy. Adult male Sprague-Dawley rats were dosed daily by gavage for 14 days with myclobutanil or triadimefon, at two dose levels for each triazole. Following exposure, serum, liver, and testis were collected and processed for NMR analysis. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of the resulting spectra were used to determine changes in metabolite profiles as a result of exposure. Using this approach, responses common to both triazoles were identified, as well as responses indicative of differences in the toxicity of these two compounds. Although changes were observed in serum metabolites following exposure, none were robust enough to be considered a biomarker of exposure/effect. A number of metabolic changes were, however, observed in the liver with both triazoles, particularly in metabolites related to the methionine cycle. The testes of myclobutanil-exposed animals displayed altered levels of creatine and creatinine, consistent with testicular toxicity. Overall, the results of this study support the possible application of a metabolomics approach to assessing the toxicity of triazole fungicides and identifying biomarkers of exposure and/or effect.RNM supported by EPA/NCSU Cooperative Training Agreement #CT826512010 with the Department of Environmental and Molecular Toxicology, North Caroline State University, Raleigh.The research described in this article has been reviewed by the U.S. Environmental Protection Agency, and approved for publication. Approval does not signify that the contents necessarily reflect the views and the policies of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.     

Translational biomarker discovery in clinical metabolomics: an introductory tutorial

Metabolomics is increasingly being applied towards the identification of biomarkers for disease diagnosis, prognosis and risk prediction. Unfortunately among the many published metabolomic studies focusing on biomarker discovery, there is very little consistency and relatively little rigor in how researchers select, assess or report their candidate biomarkers. In particular, few studies report any measure of sensitivity, specificity, or provide receiver operator characteristic (ROC) curves with associated confidence intervals. Even fewer studies explicitly describe or release the biomarker model used to generate their ROC curves. This is surprising given that for biomarker studies in most other biomedical fields, ROC curve analysis is generally considered the standard method for performance assessment. Because the ultimate goal of biomarker discovery is the translation of those biomarkers to clinical practice, it is clear that the metabolomics community needs to start “speaking the same language” in terms of biomarker analysis and reporting-especially if it wants to see metabolite markers being routinely used in the clinic. In this tutorial, we will first introduce the concept of ROC curves and describe their use in single biomarker analysis for clinical chemistry. This includes the construction of ROC curves, understanding the meaning of area under ROC curves (AUC) and partial AUC, as well as the calculation of confidence intervals. The second part of the tutorial focuses on biomarker analyses within the context of metabolomics. This section describes different statistical and machine learning strategies that can be used to create multi-metabolite biomarker models and explains how these models can be assessed using ROC curves. In the third part of the tutorial we discuss common issues and potential pitfalls associated with different analysis methods and provide readers with a list of nine recommendations for biomarker analysis and reporting. To help readers test, visualize and explore the concepts presented in this tutorial, we also introduce a web-based tool called ROCCET (ROC Curve Explorer & Tester, http://www.roccet.ca). ROCCET was originally developed as a teaching aid but it can also serve as a training and testing resource to assist metabolomics researchers build biomarker models and conduct a range of common ROC curve analyses for biomarker studies.