Setup and Annotation of Metabolomic Experiments by Integrating Biological and Mass Spectrometric Metadata

Xylitol is prothrombotic and associated with cardiovascular risk

BACKGROUND AND AIMS

The pathways and metabolites that contribute to residual cardiovascular disease risks are unclear. Low-calorie sweeteners are widely used sugar substitutes in processed foods with presumed health benefits. Many low-calorie sweeteners are sugar alcohols that also are produced endogenously, albeit at levels over 1000-fold lower than observed following consumption as a sugar substitute.

METHODS

Untargeted metabolomics studies were performed on overnight fasting plasma samples in a discovery cohort (n = 1157) of sequential stable subjects undergoing elective diagnostic cardiac evaluations; subsequent stable isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses were performed on an independent, non-overlapping validation cohort (n = 2149). Complementary isolated human platelet, platelet-rich plasma, whole blood, and animal model studies examined the effect of xylitol on platelet responsiveness and thrombus formation in vivo. Finally, an intervention study was performed to assess the effects of xylitol consumption on platelet function in healthy volunteers (n = 10).

RESULTS

In initial untargeted metabolomics studies (discovery cohort), circulating levels of a polyol tentatively assigned as xylitol were associated with incident (3-year) major adverse cardiovascular event (MACE) risk. Subsequent stable isotope dilution LC-MS/MS analyses (validation cohort) specific for xylitol (and not its structural isomers) confirmed its association with incident MACE risk [third vs. first tertile adjusted hazard ratio (95% confidence interval), 1.57 (1.12-2.21), P < .01]. Complementary mechanistic studies showed xylitol-enhanced multiple indices of platelet reactivity and in vivo thrombosis formation at levels observed in fasting plasma. In interventional studies, consumption of a xylitol-sweetened drink markedly raised plasma levels and enhanced multiple functional measures of platelet responsiveness in all subjects.

CONCLUSIONS

Xylitol is associated with incident MACE risk. Moreover, xylitol both enhanced platelet reactivity and thrombosis potential in vivo. Further studies examining the cardiovascular safety of xylitol are warranted.

The Yin and Yang of pathogens and probiotics: interplay between Salmonella enterica sv. Typhimurium and Bifidobacterium infantis during co-infection

Probiotic bacteria have been proposed as an alternative to antibiotics for the control of antimicrobial resistant enteric pathogens. The mechanistic details of this approach remain unclear, in part because pathogen reduction appears to be both strain and ecology dependent. Here we tested the ability of five probiotic strains, including some from common probiotic genera Lactobacillus and Bifidobacterium, to reduce binding of Salmonella enterica sv. Typhimurium to epithelial cells in vitro. Bifidobacterium longum subsp. infantis emerged as a promising strain; however, S. Typhimurium infection outcome in epithelial cells was dependent on inoculation order, with B. infantis unable to rescue host cells from preceding or concurrent infection. We further investigated the complex mechanisms underlying this interaction between B. infantis, S. Typhimurium, and epithelial cells using a multi-omics approach that included gene expression and altered metabolism via metabolomics. Incubation with B. infantis repressed apoptotic pathways and induced anti-inflammatory cascades in epithelial cells. In contrast, co-incubation with B. infantis increased in S. Typhimurium the expression of virulence factors, induced anaerobic metabolism, and repressed components of arginine metabolism as well as altering the metabolic profile. Concurrent application of the probiotic and pathogen notably generated metabolic profiles more similar to that of the probiotic alone than to the pathogen, indicating a central role for metabolism in modulating probiotic-pathogen-host interactions. Together these data imply crosstalk via small molecules between the epithelial cells, pathogen and probiotic that consistently demonstrated unique molecular mechanisms specific probiotic/pathogen the individual associations.

Time-restricted feeding restores metabolic flexibility in adult mice with excess adiposity

Introduction

Obesity is prevalent with the adult population in the United States. Energy-dense diets and erratic eating behavior contribute to obesity. Time-restricted eating is a dietary strategy in humans that has been advanced to reduce the propensity for obesity. We hypothesized that time-restricted feeding (TRF) would improve metabolic flexibility and normalize metabolic function in adult mice with established excess adiposity.

Methods

Male C57BL/6NHsd mice were initially fed a high-fat diet (HFD) for 12 weeks to establish excess body adiposity, while control mice were fed a normal diet. Then, the HFD-fed mice were assigned to two groups, either ad libitum HFD or TRF of the HFD in the dark phase (12 h) for another 12 weeks.

Results and discussion

Energy intake and body fat mass were similar in TRF and HFD-fed mice. TRF restored rhythmic oscillations of respiratory exchange ratio (RER), which had been flattened by the HFD, with greater RER amplitude in the dark phase. Insulin sensitivity was improved and plasma cholesterol and hepatic triacylglycerol were decreased by TRF. When compared to HFD, TRF decreased transcription of circadian genes Per1 and Per2 and genes encoding lipid metabolism (Acaca, Fads1, Fads2, Fasn, Scd1, and Srebf1) in liver. Metabolomic analysis showed that TRF created a profile that was distinct from those of mice fed the control diet or HFD, particularly in altered amino acid profiles. These included aminoacyl-tRNA-biosynthesis, glutathione metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis pathways. In conclusion, TRF improved metabolic function in adult mice with excess adiposity. This improvement was not through a reduction in body fat mass but through the restoration of metabolic flexibility.

RefMetaPlant: a reference metabolome database for plants across five major phyla

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants. Here, by leveraging an advanced LC-MS platform, we generated untargeted mass spectral data from >150 plant species collected across the five major phyla. Using a self-developed computation protocol, we constructed reference metabolome for 153 plant species. A 'Reference Metabolome Database for Plants' (RefMetaPlant) was built to encompass the reference metabolome, integrated standard compound mass spectral libraries for annotation, and related query and analytical tools like 'LC-MS/MS Query', 'RefMetaBlast' and 'CompoundLibBlast' for searches and profiling of plant metabolome and metabolite identification. Analogous to a reference genome in genomic research, RefMetaPlant provides a powerful platform to support plant genome-scale metabolite analysis to promote knowledge/data sharing and collaboration in the field of metabolomics. RefMetaPlant is freely available at https://www.biosino.org/RefMetaDB/.

Plasma metabolome of healthy and Rhodococcus equi-infected foals over time

BACKGROUND

Foals that develop pulmonary ultrasonographic lesions on Rhodococcus equi (R. equi) endemic farms are treated with antibiotics because those at risk of developing clinical pneumonia (~20%) cannot be recognised early. Candidate biomarkers identified using metabolomics may aid targeted treatment strategies against R. equi.

OBJECTIVES

(1) To describe how foal ageing affects their plasma metabolome (birth to 8 weeks) and (2) to establish the effects that experimental infection with Rhodococcus equi (R. equi) has on foal metabolome.

STUDY DESIGN

Experimental study.

METHODS

Nine healthy newborn foals were experimentally infected with R. equi as described in a previous study. Foals were treated with oral antibiotics if they developed clinical pneumonia (n = 4, clinical group) or remained untreated if they showed no signs of disease (n = 5, subclinical group). A group of unchallenged foals (n = 4) was also included in the study. By the end of the study period (8 weeks), all foals were free of disease. This status was confirmed with transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography. Plasma metabolomics was determined by GC-MS weekly for the study duration (8 weeks).

RESULTS

Foals' plasma metabolome was altered by ageing (birth to 8 weeks) and experimental infection with R. equi as demonstrated using multivariate statistical analysis. The intensities of 25 and 28 metabolites were altered by ageing and infection (p < 0.05) respectively. Furthermore, 20 metabolites changed by more than 2-fold between clinical and subclinical groups.

MAIN LIMITATIONS

The number of foals is limited. Foals were experimentally infected with R. equi.

CONCLUSIONS

Ageing and R. equi infection induced changes in the plasma metabolome of foals. These results provide an initial description of foal's plasma metabolome and serve as background for future identification of R. equi pneumonia biomarkers.

Almond Consumption for 8 Weeks Altered Host and Microbial Metabolism in Comparison to a Control Snack in Young Adults

Almond consumption can improve cardiometabolic (CM) health. However, the mechanisms underlying those benefits are not well characterized. This study explored the effects of consuming a snack of almonds vs. crackers for 8 weeks on changes in metabolomic profiles in young adults (clinicaltrials.gov ID: NCT03084003).

Participants (n = 73, age: 18-19 years, BMI: 18-41 kg/m2) were randomly assigned to consume either almonds (2 oz/d, n = 38) or an isocaloric control snack of graham crackers (325 kcal/d, n = 35) daily for 8 weeks. Blood samples were collected at baseline prior to and at 4 and 8 weeks after the intervention. Metabolite abundances in the serum were quantified by hydrophilic interaction chromatography quadrupole (Q) time-of-flight (TOF) mass spectrometry (MS/MS), gas chromatography (GC) TOF MS, CSH-ESI (electrospray) QTOF MS/MS, and targeted analyses for free PUFAs, total fatty acids, oxylipins and endocannabinoids. Linear mixed model analyses with baseline-adjustment were conducted, and those results were used for enrichment and network analyses. Microbial community pathway predictions from 16S rRNA sequencing of fecal samples was done using PICRUST2.

Almond consumption enriched unsaturated triglycerides, unsaturated phosphatidylcholines, saturated and unsaturated lysophosphatidylcholines, tricarboxylic acids, and tocopherol clusters (p < 0.05). Targeted analyses reveal lower levels of omega-3 total fatty acids (TFAs) overall in the almond group compared to the cracker group (p < 0.05). Microbial amino acid biosynthesis, and amino sugar and nucleotide sugar metabolism pathways were also differentially enriched at the end of the intervention (p < 0.05).

The study demonstrates the differential effects of almonds on host tocopherol, lipid, and TCA cycle metabolism with potential changes in microbial metabolism, which may interact with host metabolism to facilitate the CM benefits.

Metabolomic Alterations in Mammary Glands from Pubertal Mice Fed a High-Fat Diet

Dietary malpractice is a risk factor for obesity. This study tested the hypothesis that consumption of a high-fat diet alters mammary metabolome in pubertal mice. We performed untargeted metabolomic analysis of primary metabolism on mammary glands from pubertal mice fed the AIN93G standard diet or a high-fat diet (HFD) for 3 weeks. We identified 97 metabolites for statistical comparisons. The HFD altered the amino acid metabolism considerably. This included elevated expression of branched-chain amino acids, non-essential amino acids (aspartic acid and glutamic acid), and methionine sulfoxide (oxidized methionine) and an alteration in the aminoacyl-tRNA biosynthesis pathway. Furthermore, elevations of fumaric acid and malic acid (both are citrate cycle intermediates) and glyceric acid (its phosphate derivatives are intermediates of glycolysis) in HFD-fed mice suggest an acceleration of both citrate cycle and glycolysis. Lower expression of glycerol, oleic acid, and palmitoleic acid, as well as decreased mammary expression of genes encoding lipid metabolism (Acaca, Fads1, Fasn, Scd1, and Srebf1) in HFD-fed mice indicate an attenuated lipid metabolism in the presence of adequate dietary fat. In conclusion, consumption of the HFD for 3 weeks alters metabolic profile of pubertal mammary glands. This alteration may affect mammary development and growth in pubertal mice.

Alteration in Plasma Metabolome in High-Fat Diet-Fed Monocyte Chemotactic Protein-1 Knockout Mice Bearing Pulmonary Metastases of Lewis Lung Carcinoma

Both clinical and laboratory studies have shown that monocyte chemotactic protein-1 (MCP-1) is involved in cancer spread. To understand the role of MCP-1 in metabolism in the presence of metastasis, we conducted an untargeted metabolomic analysis of primary metabolism on plasma collected from a study showing that MCP-1 deficiency reduces spontaneous metastasis of Lewis lung carcinoma (LLC) to the lungs in mice fed a high-fat diet (HFD). In a 2 × 2 design, wild-type (WT) or Mcp-1 knockout (Mcp-1 -/-) mice maintained on the AIN93G standard diet or HFD were subcutaneously injected with LLC cells to induce lung metastasis. We identified 87 metabolites for metabolomic analysis from this study. Amino acid metabolism was altered considerably in the presence of LLC metastases with the aminoacyl-tRNA biosynthesis pathways as the leading pathway altered. The HFD modified lipid and energy metabolism, evidenced by lower contents of arachidonic acid, cholesterol, and long-chain saturated fatty acids and higher contents of glucose and pyruvic acid in mice fed the HFD. These findings were supported by network analysis showing alterations in fatty acid synthesis and glycolysis/gluconeogenesis pathways between the 2 diets. Furthermore, elevations of the citrate cycle intermediates (citric acid, fumaric acid, isocitric acid, and succinic acid) and glyceric acid in Mcp-1 -/- mice, regardless of diet, suggest the involvement of MCP-1 in mitochondrial energy metabolism during LLC metastasis. The present study demonstrates that MCP-1 deficiency and the HFD altered plasma metabolome in mice bearing LLC metastases. These findings can be useful in understanding the impact of obesity on prevention and treatment of cancer metastasis.

Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals

Discovery of reliable signatures for the empirical diagnosis of neurological diseases-both infectious and non-infectious-remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23-74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed-providing a pathway for comprehensive diagnostics and therapeutics discovery.

Metabolomic signatures of low- and high-adiposity neonates differ based on maternal BMI

Maternal obesity [body mass index (BMI) > 30 kg/m²] is associated with greater neonatal adiposity, cord blood (CB) insulin levels, and a proinflammatory phenotype at birth, contributing to risk of future cardiometabolic disease in the offspring. Variation in neonatal adiposity within maternal BMI groups is underappreciated, and it remains unclear whether the metabolic impairments at birth are an outcome of maternal obesity or excess fetal fat accrual. We examined the hypothesis that CB metabolites associated with fetal fat accrual differ between offspring of normal-weight and obese women. Umbilical venous blood was collected at the time of scheduled cesarean delivery from 50 normal-weight women (LE; pregravid BMI = 22.3 ± 1.7 kg/m²) and 50 obese women (OB; BMI = 34.5 ± 3.0 kg/m²). Neonatal adiposity was estimated from flank skinfold thickness. The first (low adiposity, LA) and third (high adiposity, HA) tertiles of neonatal %body fat were used to create four groups: OBLA, OBHA, LELA, and LEHA. CB metabolites were measured via untargeted metabolomics. Broadly, the LA offspring of OB women (OBLA) metabolite signature differed from other groups. Lauric acid (C12:0) was 82-118% higher in OBLA vs. all other groups [false discovery rate (FDR) < 0.01]. Several other fatty acids, including palmitate, stearate, and linoleate, were higher in OBLA vs. OBHA groups. CB metabolites, such as lauric acid, a medium-chain fatty acid that may improve insulin sensitivity, were associated with neonatal adiposity differently between offspring of women with and without obesity. Changes in metabolically active lipids at birth may have long-term consequences for offspring metabolism.NEW & NOTEWORTHY Using untargeted metabolomics in 100 newborns, we found that cord blood metabolite signatures associated with neonatal adiposity differed between offspring of women with and without obesity.

A constitutive stress response is a result of low temperature growth in the Antarctic green alga Chlamydomonas sp. UWO241

The Antarctic green alga Chlamydomonas sp. UWO241 is an obligate psychrophile that thrives in the cold (4-6°C) but is unable to survive at temperatures ≥18°C. Little is known how exposure to heat affects its physiology or whether it mounts a heat stress response in a manner comparable to mesophiles. Here, we dissect the responses of UWO241 to temperature stress by examining its growth, primary metabolome and transcriptome under steady-state low temperature and heat stress conditions. In comparison with Chlamydomonas reinhardtii, UWO241 constitutively accumulates metabolites and proteins commonly considered as stress markers, including soluble sugars, antioxidants, polyamines, and heat shock proteins to ensure efficient protein folding at low temperatures. We propose that this results from life at extreme conditions. A shift from 4°C to a non-permissive temperature of 24°C alters the UWO241 primary metabolome and transcriptome, but growth of UWO241 at higher permissive temperatures (10 and 15°C) does not provide enhanced heat protection. UWO241 also fails to induce the accumulation of HSPs when exposed to heat, suggesting that it has lost the ability to fine-tune its heat stress response. Our work adds to the growing body of research on temperature stress in psychrophiles, many of which are threatened by climate change.

Mammary Tumorigenesis and Metabolome in Male Adipose Specific Monocyte Chemotactic Protein-1 Deficient MMTV-PyMT Mice Fed a High-Fat Diet

Male breast cancer, while uncommon, is a highly malignant disease. Monocyte chemotactic protein-1 (MCP-1) is an adipokine; its concentration in adipose tissue is elevated in obesity. This study tested the hypothesis that adipose-derived MCP-1 contributes to male breast cancer. In a 2x2 design, male MMTV-PyMT mice with or without adipose-specific Mcp-1 knockout [designated as Mcp-1^-/- or wild-type (WT)] were fed the AIN93G standard diet or a high-fat diet (HFD) for 25 weeks. Mcp-1^-/- mice had lower adipose Mcp-1 expression than WT mice. Adipose Mcp-1 deficiency reduced plasma concentrations of MCP-1 in mice fed the HFD compared to their WT counterparts. Mcp-1^-/- mice had a longer tumor latency (25.2 weeks vs. 18.0 weeks) and lower tumor incidence (19% vs. 56%), tumor progression (2317% vs. 4792%), and tumor weight (0.23 g vs. 0.64 g) than WT mice. Plasma metabolomics analysis identified 56 metabolites that differed among the four dietary groups, including 22 differed between Mcp-1^-/- and WT mice. Pathway and network analyses along with discriminant analysis showed that pathways of amino acid and carbohydrate metabolisms are the most disturbed in MMTV-PyMT mice. In conclusion, adipose-derived MCP-1 contributes to mammary tumorigenesis in male MMTV-PyMT. The potential involvement of adipose-derived MCP-1 in metabolomics warrants further investigation on its role in causal relationships between cancer metabolism and mammary tumorigenesis in this male MMTV-PyMT model.

ADAP-KDB: A Spectral Knowledgebase for Tracking and Prioritizing Unknown GC-MS Spectra in the NIH's Metabolomics Data Repository

We report the development of a spectral knowledgebase named ADAP-KDB for tracking and prioritizing unknown gas chromatography-mass spectrometry (GC-MS) spectra in the NIH's Metabolomics Data Repository-a national and international repository for metabolomics data. ADAP-KDB consists of two parts. One part is a computational workflow that preprocesses raw mass spectrometry data and derives consensus mass spectra. The other part is a web portal for users to browse the consensus spectra and match query spectra against them. For each consensus spectrum, the Gini-Simpson diversity index and the p-value from χ² goodness-of-fit test are calculated to measure its statistical significance, which enables prioritization of unknown mass spectra for subsequent costly compound identification.

Hexosamine biosynthetic pathway and O-GlcNAc-processing enzymes regulate daily rhythms in protein O-GlcNAcylation

The integration of circadian and metabolic signals is essential for maintaining robust circadian rhythms and ensuring efficient metabolism and energy use. Using Drosophila as an animal model, we show that cellular protein O-GlcNAcylation exhibits robust 24-hour rhythm and represents a key post-translational mechanism that regulates circadian physiology. We observe strong correlation between protein O-GlcNAcylation rhythms and clock-controlled feeding-fasting cycles, suggesting that O-GlcNAcylation rhythms are primarily driven by nutrient input. Interestingly, daily O-GlcNAcylation rhythms are severely dampened when we subject flies to time-restricted feeding at unnatural feeding time. This suggests the presence of clock-regulated buffering mechanisms that prevent excessive O-GlcNAcylation at non-optimal times of the day-night cycle. We show that this buffering mechanism is mediated by the expression and activity of GFAT, OGT, and OGA, which are regulated through integration of circadian and metabolic signals. Finally, we generate a mathematical model to describe the key factors that regulate daily O-GlcNAcylation rhythm.

Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress

Metabolomics is a technology that generates large amounts of data and contributes to obtaining wide and integral explanations of the biochemical state of a living organism. Plants are continuously affected by abiotic stresses such as water scarcity, high temperatures and high salinity, and metabolomics has the potential for elucidating the response-to-stress mechanisms and develop resistance strategies in affected cultivars. This review describes the characteristics of each of the stages of metabolomic studies in plants and the role of metabolomics in the characterization of the response of various plant species to abiotic stresses.

Mass spectrometry-based forest tree metabolomics

Research in forest tree species has advanced slowly when compared with other agricultural crops and model organisms, mainly due to the long-life cycles, large genome sizes, and lack of genomic tools. Additionally, trees are complex matrices, and the presence of interferents (e.g., oleoresins and cellulose) challenges the analysis of tree tissues with mass spectrometry (MS)-based analytical platforms. In this review, advances in MS-based forest tree metabolomics are discussed. Given their economic and ecological significance, particular focus is given to Pinus, Quercus, and Eucalyptus forest tree species to better understand their metabolite responses to abiotic and biotic stresses in the current climate change scenario. Furthermore, MS-based metabolomics technologies produce large and complex datasets that require expertize to adequately manage, process, analyze, and store the data in dedicated repositories. To ensure that the full potential of forest tree metabolomics data are translated into new knowledge, these data should comply with the FAIR principles (i.e., Findable, Accessible, Interoperable, and Re-usable). It is essential that adequate standards are implemented to annotate metadata from forest tree metabolomics studies as is already required by many science and governmental agencies and some major scientific publishers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:126-157, 2021.

Metabolomic Profile of Weaned Pigs Challenged with E. coli and Supplemented with Carbadox or Bacillus subtilis

This study explored the metabolomic profiles in ileal mucosa and colon digesta in response to enterotoxigenic Escherichia coli F18 (ETEC) infection and dietary use of probiotics and low-dose antibiotics. Weaned pigs (n = 48, 6.17 ± 0.36 kg body weight) were randomly allotted to one of four treatments. Pigs in the negative control (NC) were fed a basal diet without ETEC challenge, whereas pigs in the positive control (PC), antibiotic, and probiotic groups were fed the basal diet, basal diet supplemented with 50 mg/kg of carbadox, or 500 mg/kg of Bacillus subtilis, respectively, and orally challenged with ETEC F18. All pigs were euthanized at day 21 post-inoculation to collect ileal mucosa and colon digesta for untargeted metabolomic profiling using gas chromatography coupled with time-of-flight mass spectrometry. Multivariate analysis highlighted a more distinct metabolomic profile of ileal mucosa metabolites in NC compared to the ETEC-challenged groups. The relative abundance of 19 metabolites from the ileal mucosa including polyamine, nucleotide, monosaccharides, fatty acids, and organic acids was significantly different between the NC and PC groups (q < 0.1). In colon digesta, differential metabolites including 2-monoolein, lactic acid, and maltose were reduced in the carbadox group compared with the probiotics group. In conclusion, several differential metabolites and metabolic pathways were identified in ileal mucosa, which may suggest an ongoing intestinal mucosal repair in the ileum of ETEC-challenged pigs on day 21 post-inoculation.

Plasma lipidome of healthy and Rhodococcus equi-infected foals over time

BACKGROUND

Many foals that develop thoracic ultrasonographic lesions as a result of Rhodococcus equi infection heal on their own. However, most of these foals receive antimicrobials because foals at risk of developing clinical pneumonia cannot be identified. Untargeted lipidomics is useful to identify candidate biomarkers.

OBJECTIVES

(a) To describe the changes that occur in foal lipidomics as a result of ageing (birth to 8 weeks) and (b) To compare these results with those observed in foals after experimental infection with R. equi.

STUDY DESIGN

Experimental study.

METHODS

Healthy newborn foals (n = 9) were challenged with R. equi intratracheally the first week of life. Foals were treated with antimicrobials if they developed clinical pneumonia (n = 4, "clinical group") or were closely monitored if they showed no signs of disease (n = 5 "subclinical group"). An unchallenged group (n = 4) was also included. All foals were free of disease (transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography) by 8 weeks of life. Plasma lipidomics was determined by LC-MS weekly for the study duration (8 weeks).

RESULTS

Both ageing and experimental infection altered the foal's plasma lipidome as demonstrated by multivariate statistical analysis. The intensities of 31 lipids were altered by ageing and 12 by infection (P < .05). Furthermore, nine lipids changed by more than twofold between clinical and subclinical groups.

MAIN LIMITATIONS

The number of foals is limited. Foals were experimentally challenged with R. equi.

CONCLUSIONS

Ageing and R. equi infection induced changes in the plasma lipidome of foals. These experimental results provide the background for future work in the discovery of earlier biomarkers of R. equi pneumonia. Early identification of foals at risk of developing clinical pneumonia is key in order to decrease antimicrobial use and development of antimicrobial resistance.

Exogenous GLP-1 stimulates TCA cycle and suppresses gluconeogenesis and ketogenesis in late-fasted northern elephant seals pups

The postweaning fast of northern elephant seal pups is characterized by a lipid-dependent metabolism and associated with a decrease in plasma glucagon-like peptide-1 (GLP-1), insulin, and glucose and increased gluconeogenesis (GNG) and ketogenesis. We have also demonstrated that exogenous GLP-1 infusion increased plasma insulin despite simultaneous increases in cortisol and glucagon, which collectively present contradictory regulatory stimuli of GNG, ketogenesis, and glycolysis. To assess the effects of GLP-1 on metabolism using primary carbon metabolite profiles in late-fasted seal pups, we dose-dependently infused late-fasted seals with low (LDG; 10 pM/kg; n = 3) or high (HDG; 100 pM/kg; n = 4) GLP-1 immediately following a glucose bolus (0.5 g/kg), using glucose without GLP-1 as control (n = 5). Infusions were performed in similarly aged animals 6-8 wk into their postweaning fast. The plasma metabolome was measured from samples collected at five time points just prior to and during the infusions, and network maps constructed to robustly evaluate the effects of GLP-1 on primary carbon metabolism. HDG increased key tricarboxylic acid (TCA) cycle metabolites, and decreased phosphoenolpyruvate and acetoacetate (P < 0.05) suggesting that elevated levels of GLP-1 promote glycolysis and suppress GNG and ketogenesis, which collectively increase glucose clearance. These GLP-1-mediated effects on cellular metabolism help to explain why plasma GLP-1 concentrations decrease naturally in fasting pups as an evolved mechanism to help conserve glucose during the late-fasting period.

Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling

Rice is one of the most economically important commodities globally. However, rice plants are salt susceptible species in which high salinity can significantly constrain its productivity. Several physiological parameters in adaptation to salt stress have been observed, though changes in metabolic aspects remain to be elucidated. In this study, rice metabolic activities of salt-stressed flag leaf were systematically characterized. Transcriptomics and metabolomics data were combined to identify disturbed pathways, altered metabolites and metabolic hotspots within the rice metabolic network under salt stress condition. Besides, the feasible flux solutions in different context-specific metabolic networks were estimated and compared. Our findings highlighted metabolic reprogramming in primary metabolic pathways, cellular respiration, antioxidant biosynthetic pathways, and phytohormone biosynthetic pathways. Photosynthesis and hexose utilization were among the major disturbed pathways in the stressed flag leaf. Notably, the increased flux distribution of the photorespiratory pathway could contribute to cellular redox control. Predicted flux statuses in several pathways were consistent with the results from transcriptomics, end-point metabolomics, and physiological studies. Our study illustrated that the contextualized genome-scale model together with multi-omics analysis is a powerful approach to unravel the metabolic responses of rice to salinity stress.

Uncovering mechanisms of global ocean change effects on the Dungeness crab (Cancer magister) through metabolomics analysis

The Dungeness crab is an economically and ecologically important species distributed along the North American Pacific coast. To predict how Dungeness crab may physiologically respond to future global ocean change on a molecular level, we performed untargeted metabolomic approaches on individual Dungeness crab juveniles reared in treatments that mimicked current and projected future pH and dissolved oxygen conditions. We found 94 metabolites and 127 lipids responded in a condition-specific manner, with a greater number of known compounds more strongly responding to low oxygen than low pH exposure. Pathway analysis of these compounds revealed that juveniles may respond to low oxygen through evolutionarily conserved processes including downregulating glutathione biosynthesis and upregulating glycogen storage, and may respond to low pH by increasing ATP production. Most interestingly, we found that the response of juveniles to combined low pH and low oxygen exposure was most similar to the low oxygen exposure response, indicating low oxygen may drive the physiology of juvenile crabs more than pH. Our study elucidates metabolic dynamics that expand our overall understanding of how the species might respond to future ocean conditions and provides a comprehensive dataset that could be used in future ocean acidification response studies.

Pharmacometabolomics of Respiratory Phenotypic Response to Dexamethasone in Preterm Infants at Risk for Bronchopulmonary Dysplasia

A prospective cohort study was performed in preterm infants less than 32 weeks gestation at birth who were treated with dexamethasone for developing or established bronchopulmonary dysplasia (BPD). Respiratory phenotype (Respiratory Severity Score (RSS)), serum, and urine metabolomics were assessed before and after treatment. Ten infants provided nine matched serum and nine matched urine samples. There was a significant decrease in RSS with steroid treatment. Serum gluconic acid had the largest median fold change (140 times decreased, P = 0.008). In metabolite set enrichment analysis, in both serum and urine, the urea cycle, ammonia recycling, and malate-aspartate shuttle pathways were most significantly enriched when comparing pretreatment and post-treatment (P value < 0.05). In regression analyses, 6 serum and 28 urine metabolites were significantly associated with change in RSS. Urine gluconic acid lactone was the most significantly correlated with clinical response (correlational coefficient 0.915). Pharmacometabolomic discovery of drug response biomarkers in preterm infants may allow precision therapeutics in BPD treatment.

Cheminformatics approach to exploring and modeling trait-associated metabolite profiles

Developing predictive and transparent approaches to the analysis of metabolite profiles across patient cohorts is of critical importance for understanding the events that trigger or modulate traits of interest (e.g., disease progression, drug metabolism, chemical risk assessment). However, metabolites’ chemical structures are still rarely used in the statistical modeling workflows that establish these trait-metabolite relationships. Herein, we present a novel cheminformatics-based approach capable of identifying predictive, interpretable, and reproducible trait-metabolite relationships. As a proof-of-concept, we utilize a previously published case study consisting of metabolite profiles from non-small-cell lung cancer (NSCLC) adenocarcinoma patients and healthy controls. By characterizing each structurally annotated metabolite using both computed molecular descriptors and patient metabolite concentration profiles, we show that these complementary features enhance the identification and understanding of key metabolites associated with cancer. Ultimately, we built multi-metabolite classification models for assessing patients’ cancer status using specific groups of metabolites identified based on high structural similarity through chemical clustering. We subsequently performed a metabolic pathway enrichment analysis to identify potential mechanistic relationships between metabolites and NSCLC adenocarcinoma. This cheminformatics-inspired approach relies on the metabolites’ structural features and chemical properties to provide critical information about metabolite-trait associations. This method could ultimately facilitate biological understanding and advance research based on metabolomics data, especially with respect to the identification of novel biomarkers.

Understanding the effect of repeated administration of meloxicam on feline renal cortex and medulla: A lipidomics and metabolomics approach

Repeated administration of meloxicam can cause kidney damage in cats by mechanisms that remain unclear. Metabolomics and lipidomics are powerful, noninvasive approaches used to investigate tissue response to drug exposure. Thus, the objective of this study was to assess the effects of meloxicam on the feline kidney using untargeted metabolomics and lipidomics approaches. Female young-adult purpose-breed cats were allocated into the control (n = 4) and meloxicam (n = 4) groups. Cats in the control and meloxicam groups were treated daily with saline and meloxicam at 0.3 mg/kg subcutaneously for 17 days, respectively. Renal cortices and medullas were collected at the end of the treatment period. Random forest and metabolic pathway analyses were used to identify metabolites that discriminate meloxicam-treated from saline-treated cats and to identify disturbed metabolic pathways in renal tissue. Our results revealed that the repeated administration of meloxicam to cats altered the kidney metabolome and lipidome and suggest that at least 40 metabolic pathways were altered in the renal cortex and medulla. These metabolic pathways included lipid, amino acid, carbohydrate, nucleotide and energy metabolisms, and metabolism of cofactors and vitamins. This is the first study using a pharmacometabonomics approach for studying the molecular effects of meloxicam on feline kidneys.

Alternative outlets for sustaining photosynthetic electron transport during dark-to-light transitions

Most forms of life on Earth cannot exist without photosynthesis. Our food and atmosphere depend on it. To obtain high photosynthetic yields, light energy must be efficiently coupled to the fixation of CO₂ into organic molecules. Suboptimal environmental conditions can severely impact the conversion of light energy to biomass and lead to reactive oxygen production, which in turn can cause cellular damage and loss of productivity. Hence, plants, algae, and photosynthetic bacteria have evolved a network of alternative outlets to sustain the flow of photosynthetically derived electrons. Our work is focused on the nature and integration of these outlets, which will inform a rational engineering of crop plants and algae to optimize photosynthesis and meet the increased global demand for food.

Environmental stresses dramatically impact the balance between the production of photosynthetically derived energetic electrons and Calvin–Benson–Bassham cycle (CBBC) activity; an imbalance promotes accumulation of reactive oxygen species and causes cell damage. Hence, photosynthetic organisms have developed several strategies to route electrons toward alternative outlets that allow for storage or harmless dissipation of their energy. In this work, we explore the activities of three essential outlets associated with Chlamydomonas reinhardtii photosynthetic electron transport: (i) reduction of O₂ to H₂O through flavodiiron proteins (FLVs) and (ii) plastid terminal oxidases (PTOX) and (iii) the synthesis of starch. Real-time measurements of O₂ exchange have demonstrated that FLVs immediately engage during dark-to-light transitions, allowing electron transport when the CBBC is not fully activated. Under these conditions, we quantified maximal FLV activity and its overall capacity to direct photosynthetic electrons toward O₂ reduction. However, when starch synthesis is compromised, a greater proportion of the electrons is directed toward O₂ reduction through both the FLVs and PTOX, suggesting an important role for starch synthesis in priming/regulating CBBC and electron transport. Moreover, partitioning energized electrons between sustainable (starch; energetic electrons are recaptured) and nonsustainable (H₂O; energetic electrons are not recaptured) outlets is part of the energy management strategy of photosynthetic organisms that allows them to cope with the fluctuating conditions encountered in nature. Finally, unmasking the repertoire and control of such energetic reactions offers new directions for rational redesign and optimization of photosynthesis to satisfy global demands for food and other resources.

Integrative metabolomics reveals unique metabolic traits in Guillain-Barré Syndrome and its variants

Guillain-Barré syndrome (GBS) is an acute fatal progressive disease caused by autoimmune mechanism mainly affecting peripheral nervous system. Although the syndrome is clinically sub-classified into several variants, specific biomarker and exact pathomechanism of each subtypes are not well elucidated yet. In current study, integrative metabolomic and lipidomic profiles were acquisitioned from cerebrospinal fluid samples of 86 GBS from three variants and 20 disease controls. And the data were systematically compared to our previous result on inflammatory demyelination disorders of central nervous system (IDDs) and healthy controls. Primary metabolite profiles revealed unique metabolic traits in which 9 and 7 compounds were specifically changed in GBS and IDD, respectively. Next, the biomarker panel with 10 primary metabolites showed a fairly good discrimination power among 3 GBS subtypes, healthy controls, and disease controls (AUCs ranged 0.849-0.999). The robustness of the biomarker panel was vigorously validated by multi-step statistical evaluation. Subsequent lipidomics revealed GBS variant-specific alteration where the significant elevations of lyso-phosphatidylcholines and sphingomyelins were unique to AIDP (acute inflammatory demyelinating polyneuropathy) and AMAN (acute motor axonal neuropathy), respectively. And metabolome-wide multivariate correlation analysis identified potential clinical association between GBS disability scale (Hughes score) and CSF lipids (monoacylglycerols, and sphingomyelins). Finally, Bayesian network analysis of covarianced structures of primary metabolites and lipids proposed metabolic hub and potential biochemical linkage associated with the pathology.

Umbilical cord blood metabolomics reveal distinct signatures of dyslipidemia prior to bronchopulmonary dysplasia and pulmonary hypertension

Pulmonary hypertension (PH) is a common consequence of bronchopulmonary dysplasia (BPD) and remains a primary contributor to increased morbidity and mortality among preterm infants. Unfortunately, at the present time, there are no reliable early predictive markers for BPD-associated PH. Considering its health consequences, understanding in utero perturbations that lead to the development of BPD and BPD-associated PH and identifying early predictive markers is of utmost importance. As part of the discovery phase, we applied a multiplatform metabolomics approach consisting of untargeted and targeted methodologies to screen for metabolic perturbations in umbilical cord blood (UCB) plasma from preterm infants that did ( n = 21; cases) or did not ( n = 21; controls) develop subsequent PH. A total of 1,656 features were detected, of which 407 were annotated by metabolite structures. PH-associated metabolic perturbations were characterized by reductions in major choline-containing phospholipids, such as phosphatidylcholines and sphingomyelins, indicating altered lipid metabolism. The reduction in UCB abundances of major choline-containing phospholipids was confirmed in an independent validation cohort consisting of UCB plasmas from 10 cases and 10 controls matched for gestational age and BPD status. Subanalyses in the discovery cohort indicated that elevations in the oxylipins PGE1, PGE2, PGF2a, 9- and 13-HOTE, 9- and 13-HODE, and 9- and 13-KODE were positively associated with BPD presence and severity. This expansive evaluation of cord blood plasma identifies compounds reflecting dyslipidemia and suggests altered metabolite provision associated with metabolic immaturity that differentiate subjects, both by BPD severity and PH development.

Effects of Centella asiatica extract on antioxidant status and liver metabolome of rotenone-treated rats using GC-MS

Centella asiatica has been used as a culinary vegetable or medicinal herb. In this study, the hepatoprotective effect of the standardized extract of C. asiatica (ECa233) in rotenone-treated rats was examined using a GC-MS-based metabolomic approach. ECa233 contains >80% triterpenoids with a ratio of madecassoside to asiaticoside of 1.5(±0.5):1. Rats were randomly divided into three groups (with six rats/group): sham negative control, rotenone positive control and the ECa233 test group. Rats in the ECa233 group received 10 mg/kg ECa233 orally for 20 days, followed by 2.5 mg/kg intraperitoneal rotenone injection to induce toxicity before being sacrificed. Metabolomic analysis showed that supplementation of ECa233 protected rat liver against rotenone toxicity. Pipecolinic acid was one of the most important metabolites; its level was decreased in the rotenone group as compared with the control. Supplementation with ECa233 before administration of rotenone raised pipecolinic acid to levels intermediate between controls and rotenone alone. The metabolomics approach also helped discover a possible new genuine epimetabolite in the present work. Antioxidant tests revealed that ECa233 inhibited lipid peroxidation and increased catalase activities in liver tissue.

Potent Attractant for Root-Knot Nematodes in Exudates from Seedling Root Tips of Two Host Species

Root-knot nematodes (RKN; Meloidogyne spp.) can parasitize over 2,000 plant species and are generally considered to be the most agriculturally damaging group of plant-parasitic nematodes worldwide. Infective juveniles (J2) are non-feeding and must locate and invade a host before their reserves are depleted. However, what attracts J2 to appropriate root entry sites is not known. An aim of this research is to identify semiochemicals that attract RKN to roots. J2 of the three RKN species tested are highly attracted to root tips of both tomato and Medicago truncatula. For both hosts, mutants defective in ethylene signaling were found to be more attractive than those of wild type. We determined that cell-free exudates collected from tomato and M. truncatula seedling root tips were highly attractive to M. javanica J2. Using a pluronic gel-based microassay to monitor chemical fractionation, we determined that for both plant species the active component fractionated similarly and had a mass of ~400 based on size-exclusion chromatography. This characterization is a first step toward identification of a potent and specific attractant from host roots that attracts RKN. Such a compound is potentially a valuable tool for developing novel and safe control strategies.

Obesity treatment by epigallocatechin-3-gallate-regulated bile acid signaling and its enriched Akkermansia muciniphila

Dysregulated bile acid (BA) synthesis is accompanied by dysbiosis, leading to compromised metabolism. This study analyzes the effect of epigallocatechin-3-gallate (EGCG) on diet-induced obesity through regulation of BA signaling and gut microbiota. The data revealed that EGCG effectively reduced diet-increased obesity, visceral fat, and insulin resistance. Gene profiling data showed that EGCG had a significant impact on regulating genes implicated in fatty acid uptake, adipogenesis, and metabolism in the adipose tissue. In addition, metabolomics analysis revealed that EGCG altered the lipid and sugar metabolic pathways. In the intestine, EGCG reduced the FXR agonist chenodeoxycholic acid, as well as the FXR-regulated pathway, suggesting intestinal FXR deactivation. However, in the liver, EGCG increased the concentration of FXR and TGR-5 agonists and their regulated signaling. Furthermore, our data suggested that EGCG activated Takeda G protein receptor (TGR)-5 based on increased GLP-1 release and elevated serum PYY level. EGCG and antibiotics had distinct antibacterial effects. They also differentially altered body weight and BA composition. EGCG, but not antibiotics, increased Verrucomicrobiaceae, under which EGCG promoted intestinal bloom of Akkermansia muciniphila. Excitingly, A. muciniphila was as effective as EGCG in treating diet-induced obesity. Together, EGCG shifts gut microbiota and regulates BA signaling thereby having a metabolic beneficial effect.-Sheng, L., Jena, P. K., Liu, H.-X., Hu, Y., Nagar, N., Bronner, D. N., Settles, M. L., Bäumler, A. J. Wan, Y.-J. Y. Obesity treatment by epigallocatechin-3-gallate-regulated bile acid signaling and its enriched Akkermansia muciniphila.

The serum metabolomics signature of type 2 diabetes is obscured in Alzheimer's disease

There is evidence for systemic metabolic impairment in Alzheimer's disease (AD), and type 2 diabetes (T2D) increases AD risk. Although studies analyzing blood metabolomics signatures have shown differences between cognitively healthy (CH) and AD subjects, these signatures have not been compared with individuals with T2D. We utilized untargeted analysis platforms (primary metabolism and complex lipids) to characterize the serum metabolome of 126 overnight-fasted elderly subjects classified into four groups based upon AD status (CH or AD) and T2D status [nondiabetic (ND) or T2D]. Cognitive diagnosis groups were a priori weighted equally with T2D subjects. We hypothesized that AD subjects would display a metabolic profile similar to cognitively normal elderly individuals with T2D. However, partial least squares-discriminant analysis (PLS-DA) modeling resulted in poor classification across the four groups (<50% classification accuracy of test subjects). Binary classification of AD vs. CH was poor, but binary classification of T2D vs. ND was good, providing >79.5% and >76.9% classification accuracy for held-out samples using primary metabolism and complex lipids, respectively. When modeling was limited to CH subjects, T2D discrimination improved for the primary metabolism platform (>89.5%) and remained accurate for complex lipids (>73% accuracy). Greater abundances of glucose, fatty acids (C20:2), and phosphatidylcholines and lower abundances of glycine, maleimide, octanol, and tryptophan, cholesterol esters, phosphatidylcholines, and sphingomyelins were identified in CH subjects with T2D relative to those without T2D. In contrast, T2D was not accurately discriminated within AD subjects. Results herein suggest that AD may obscure the typical metabolic phenotype of T2D.

Optimized GC-MS metabolomics for the analysis of kidney tissue metabolites

INTRODUCTION

Metabolomics is a promising approach for discovery of relevant biomarkers in cells, tissues, organs, and biofluids for disease identification and prediction. The field has mostly relied on blood-based biofluids (serum, plasma, urine) as non-invasive sources of samples as surrogates of tissue or organ-specific conditions. However, the tissue specificity of metabolites pose challenges in translating blood metabolic profiles to organ-specific pathophysiological changes, and require further downstream analysis of the metabolites.

OBJECTIVES

As part of this project, we aim to develop and optimize an efficient extraction protocol for the analysis of kidney tissue metabolites representative of key primate metabolic pathways.

METHODS

Kidney cortex and medulla tissues of a baboon were homogenized and extracted using eight different extraction protocols including methanol/water, dichloromethane/methanol, pure methanol, pure water, water/methanol/chloroform, methanol/chloroform, methanol/acetonitrile/water, and acetonitrile/isopropanol/water. The extracts were analyzed by a two-dimensional gas chromatography time-of-flight mass-spectrometer (2D GC-ToF-MS) platform after methoximation and silylation.

RESULTS

Our analysis quantified 110 shared metabolites in kidney cortex and medulla tissues from hundreds of metabolites found among the eight different solvent extractions spanning low to high polarities. The results revealed that medulla is metabolically richer compared to the cortex. Dichloromethane and methanol mixture (3:1) yielded highest number of metabolites across both the tissue types. Depending on the metabolites of interest, tissue type, and the biological question, different solvents can be used to extract specific groups of metabolites.

CONCLUSION

This investigation provides insights into selection of extraction solvents for detection of classes of metabolites in renal cortex and medulla, which is fundamentally important for identification of prognostic and diagnostic metabolic kidney biomarkers for future therapeutic applications.

Feline urine metabolomic signature: characterization of low-molecular-weight substances in urine from domestic cats

Objectives This aim of this study was to characterize the composition and content of the feline urine metabolome. Methods Eight healthy domestic cats were acclimated at least 10 days before starting the study. Urine samples (~2 ml) were collected by ultrasound-guided cystocentesis. Samples were centrifuged at 1000 × g for 8 mins, and the supernatant was analyzed by gas chromatography/time-of-flight mass spectrometery. The urine metabolome was characterized using an untargeted metabolomics approach. Results Three hundred and eighteen metabolites were detected in the urine of the eight cats. These molecules are key components of at least 100 metabolic pathways. Feline urine appears to be dominated by carbohydrates, carbohydrate conjugates, organic acid and derivatives, and amino acids and analogs. The five most abundant molecules were phenaceturic acid, hippuric acid, pseudouridine phosphate and 3-(4-hydroxyphenyl) propionic acid. Conclusions and relevance This study is the first to characterize the feline urine metabolome. The results of this study revealed the presence of multiple low-molecular-weight substances that were not known to be present in feline urine. As expected, the origin of the metabolites detected in urine was diverse, including endogenous compounds and molecules biosynthesized by microbes. Also, the diet seemed to have had a relevant role on the urine metabolome. Further exploration of the urine metabolic phenotype will open a window for discovering unknown, or poorly understood, metabolic pathways. In turn, this will advance our understanding of feline biology and lead to new insights in feline physiology, nutrition and medicine.

Molecular Profiling of Pierce's Disease Outlines the Response Circuitry of Vitis vinifera to Xylella fastidiosa Infection

Pierce's disease is a major threat to grapevines caused by the bacterium Xylella fastidiosa. Although devoid of a type 3 secretion system commonly employed by bacterial pathogens to deliver effectors inside host cells, this pathogen is able to influence host parenchymal cells from the xylem lumen by secreting a battery of hydrolytic enzymes. Defining the cellular and biochemical changes induced during disease can foster the development of novel therapeutic strategies aimed at reducing the pathogen fitness and increasing plant health. To this end, we investigated the transcriptional, proteomic, and metabolomic responses of diseased Vitis vinifera compared to healthy plants. We found that several antioxidant strategies were induced, including the accumulation of gamma-aminobutyric acid (GABA) and polyamine metabolism, as well as iron and copper chelation, but these were insufficient to protect the plant from chronic oxidative stress and disease symptom development. Notable upregulation of phytoalexins, pathogenesis-related proteins, and various aromatic acid metabolites was part of the host responses observed. Moreover, upregulation of various cell wall modification enzymes followed the proliferation of the pathogen within xylem vessels, consistent with the intensive thickening of vessels' secondary walls observed by magnetic resonance imaging. By interpreting the molecular profile changes taking place in symptomatic tissues, we report a set of molecular markers that can be further explored to aid in disease detection, breeding for resistance, and developing therapeutics.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

Metabolomics of tomato xylem sap during bacterial wilt reveals Ralstonia solanacearum produces abundant putrescine, a metabolite that accelerates wilt disease

Ralstonia solanacearum thrives in plant xylem vessels and causes bacterial wilt disease despite the low nutrient content of xylem sap. We found that R. solanacearum manipulates its host to increase nutrients in tomato xylem sap, enabling it to grow better in sap from infected plants than in sap from healthy plants. Untargeted GC/MS metabolomics identified 22 metabolites enriched in R. solanacearum-infected sap. Eight of these could serve as sole carbon or nitrogen sources for R. solanacearum. Putrescine, a polyamine that is not a sole carbon or nitrogen source for R. solanacearum, was enriched 76-fold to 37 µM in R. solanacearum-infected sap. R. solanacearum synthesized putrescine via a SpeC ornithine decarboxylase. A ΔspeC mutant required ≥ 15 µM exogenous putrescine to grow and could not grow alone in xylem even when plants were treated with putrescine. However, co-inoculation with wildtype rescued ΔspeC growth, indicating R. solanacearum produced and exported putrescine to xylem sap. Intriguingly, treating plants with putrescine before inoculation accelerated wilt symptom development and R. solanacearum growth and systemic spread. Xylem putrescine concentration was unchanged in putrescine-treated plants, so the exogenous putrescine likely accelerated disease indirectly by affecting host physiology. These results indicate that putrescine is a pathogen-produced virulence metabolite.

Using Accurate Mass Gas Chromatography-Mass Spectrometry with the MINE Database for Epimetabolite Annotation

Mass spectrometry-based untargeted metabolomics often detects statistically significant metabolites that cannot be readily identified. Without defined chemical structure, interpretation of the biochemical relevance is not feasible. Epimetabolites are produced from canonical metabolites by defined enzymatic reactions and may represent a large fraction of the structurally unidentified metabolome. We here present a systematic workflow for annotating unknown epimetabolites using high resolution gas chromatography-accurate mass spectrometry with multiple ionization techniques and stable isotope labeled derivatization methods. We first determine elemental formulas, which are then used to query the "metabolic in-silico expansion" database (MINE DB) to obtain possible molecular structures that are predicted by enzyme promiscuity from canonical pathways. Accurate mass fragmentation rules are combined with in silico spectra prediction programs CFM-ID and MS-FINDER to derive the best candidates. We validated the workflow by correctly identifying 10 methylated nucleosides and 6 methylated amino acids. We then employed this strategy to annotate eight unknown compounds from cancer studies and other biological systems.

Metabolomic characteristics of cholesterol-induced non-obese nonalcoholic fatty liver disease in mice

Nonalcoholic fatty liver disease (NAFLD) in non-obese patients remains a clinical condition with unclear etiology and pathogenesis. Using a metabolomics approach in a mouse model that recapitulates almost all the characteristic features of non-obese NAFLD, we aimed to advance mechanistic understanding of this disorder. Mice fed high fat, high cholesterol, cholate (HFHCC) diet for three weeks consistently developed hepatic pathology similar to NAFLD and nonalcoholic steatohepatitis (NASH) without changes to body weight or fat pad weights. Gas- and liquid chromatography/mass spectrometry-based profiling of lipidomic and primary metabolism changes in the liver and plasma revealed that systemic mechanisms leading to steatosis and hepatitis in this non-obese NAFLD model were driven by a combination of effects directed by elevated free cholesterol, cholesterol esters and cholic acid, and associated changes to metabolism of sphingomyelins and phosphatidylcholines. These results demonstrate that mechanisms underlying cholesterol-induced non-obese NAFLD are distinct from NAFLD occurring as a consequence of metabolic syndrome. In addition, this investigation provides one of the first metabolite reference profiles for interpreting effects of dietary and hepatic cholesterol in human non-obese NAFLD/NASH patients.

Integrated Strategy for Unknown EI-MS Identification Using Quality Control Calibration Curve, Multivariate Analysis, EI-MS Spectral Database, and Retention Index Prediction

Compound identification using unknown electron ionization (EI) mass spectra in gas chromatography coupled with mass spectrometry (GC-MS) is challenging in untargeted metabolomics, natural product chemistry, or exposome research. While the total count of EI-MS records included in publicly or commercially available databases is over 900 000, efficient use of this huge database has not been achieved in metabolomics. Therefore, we proposed a "four-step" strategy for the identification of biologically significant metabolites using an integrated cheminformatics approach: (i) quality control calibration curve to reduce background noise, (ii) variable selection by hypothesis testing in principal component analysis for the efficient selection of target peaks, (iii) searching the EI-MS spectral database, and (iv) retention index (RI) filtering in combination with RI predictions. In this study, the new MS-FINDER spectral search engine was developed and utilized for searching EI-MS databases using mass spectral similarity with the evaluation of false discovery rate. Moreover, in silico derivatization software, MetaboloDerivatizer, was developed to calculate the chemical properties of derivative compounds, and all retention indexes in EI-MS databases were predicted using a simple mathematical model. The strategy was showcased in the identification of three novel metabolites (butane-1,2,3-triol, 3-deoxyglucosone, and palatinitol) in Chinese medicine Senkyu for quality assessment, as validated using authentic standard compounds. All tools and curated public EI-MS databases are freely available in the 'Computational MS-based metabolomics' section of the RIKEN PRIMe Web site ( http://prime.psc.riken.jp ).

Honeybee gut microbiota promotes host weight gain via bacterial metabolism and hormonal signaling

Social bees harbor a simple and specialized microbiota that is spatially organized into different gut compartments. Recent results on the potential involvement of bee gut communities in pathogen protection and nutritional function have drawn attention to the impact of the microbiota on bee health. However, the contributions of gut microbiota to host physiology have yet to be investigated. Here we show that the gut microbiota promotes weight gain of both whole body and the gut in individual honey bees. This effect is likely mediated by changes in host vitellogenin, insulin signaling, and gustatory response. We found that microbial metabolism markedly reduces gut pH and redox potential through the production of short-chain fatty acids and that the bacteria adjacent to the gut wall form an oxygen gradient within the intestine. The short-chain fatty acid profile contributed by dominant gut species was confirmed in vitro. Furthermore, metabolomic analyses revealed that the gut community has striking impacts on the metabolic profiles of the gut compartments and the hemolymph, suggesting that gut bacteria degrade plant polymers from pollen and that the resulting metabolites contribute to host nutrition. Our results demonstrate how microbial metabolism affects bee growth, hormonal signaling, behavior, and gut physicochemical conditions. These findings indicate that the bee gut microbiota has basic roles similar to those found in some other animals and thus provides a model in studies of host-microbe interactions.

Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration

Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other 'omic' families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license.

Serum phosphatidylethanolamine levels distinguish benign from malignant solitary pulmonary nodules and represent a potential diagnostic biomarker for lung cancer

BACKGROUND

Recent computed tomography (CT) screening trials showed that it is effective for early detection of lung cancer, but were plagued by high false positive rates. Additional blood biomarker tests designed to complement CT screening and reduce false positive rates are highly desirable.

OBJECTIVE

Identify blood-based metabolite biomarkers for diagnosing lung cancer.

MEHTODS

Serum samples from subjects participating in a CT screening trial were analyzed using untargeted GC-TOFMS and HILIC-qTOFMS-based metabolomics. Samples were acquired prior to diagnosis (pre-diagnostic, n= 17), at-diagnosis (n= 25) and post-diagnosis (n= 19) of lung cancer and from subjects with benign nodules (n= 29).

RESULTS

Univariate analysis identified 40, 102 and 30 features which were significantly different between subjects with malignant (pre-, at- and post-diagnosis) solitary pulmonary nodules (SPNs) and benign SPNs, respectively. Ten metabolites were consistently different between subjects presenting malignant (pre- and at-diagnosis) or benign SPNs. Three of these 10 metabolites were phosphatidylethanolamines (PE) suggesting alterations in lipid metabolism. Accuracies of 77%, 83% and 78% in the pre-diagnosis group and 69%, 71% and 67% in the at-diagnosis group were determined for PE(34:2), PE(36:2) and PE(38:4), respectively.

CONCLUSIONS

This study demonstrates evidence of early metabolic alterations that can possibly distinguish malignant from benign SPNs. Further studies in larger pools of samples are warranted.

Computational Strategies for Biological Interpretation of Metabolomics Data

Biological interpretation of metabolomics data relies on two basic steps: metabolite identification and functional analysis. These two steps need to be applied in a coordinated manner to enable effective data understanding. The focus of this chapter is to introduce the main computational concepts and workflows during this process. After a general overview of the field, three sections will be presented: the first section will introduce the main computational methods and bioinformatics tools for metabolite identification using spectra from common analytical platforms; the second section will focus on introducing major bioinformatics approaches for functional enrichment analysis of metabolomics data; and the last section will discuss the three main workflows in current metabolomics studies, including the chemometrics approach, the metabolic profiling approach and the more recent chemo-enrichment analysis approach. The chapter ends with summary and future perspectives on computational metabolomics.

Identification of Root-Secreted Compounds Involved in the Communication Between Cucumber, the Beneficial Bacillus amyloliquefaciens, and the Soil-Borne Pathogen Fusarium oxysporum

Colonization of plant growth-promoting rhizobacteria (PGPR) is critical for exerting their beneficial effects on the plant. Root exudation is a major factor influencing the colonization of both PGPR and soil-borne pathogens within the root system. However, the tripartite interaction of PGPR, plant roots, and soil-borne pathogens is poorly understood. We screened root exudates for signals that mediate tripartite interactions in the rhizosphere. In a split-root system, we found that root colonization of PGPR strain Bacillus amyloliquefaciens SQR9 on cucumber root was significantly enhanced by preinoculation with SQR9 or the soil-borne pathogen Fusarium oxysporum f. sp. cucumerinum, whereas root colonization of F. oxysporum f. sp. cucumerinum was reduced upon preinoculation with SQR9 or F. oxysporum f. sp. cucumerinum. Root exudates from cucumbers preinoculated with SQR9 or F. oxysporum f. sp. cucumerinum were analyzed and 109 compounds were identified. Correlation analysis highlighted eight compounds that significantly correlated with root colonization of SQR9 or F. oxysporum f. sp. cucumerinum. After performing colonization experiments with these chemicals, raffinose and tryptophan were shown to positively affect the root colonization of F. oxysporum f. sp. cucumerinum and SQR9, respectively. These results indicate that cucumber roots colonized by F. oxysporum f. sp. cucumerinum or SQR9 increase root secretion of tryptophan to strengthen further colonization of SQR9. In contrast, these colonized cucumber roots reduce raffinose secretion to inhibit root colonization of F. oxysporum f. sp. cucumerinum.

Obese Mice Fed a Diet Supplemented with Enzyme-Treated Wheat Bran Display Marked Shifts in the Liver Metabolome Concurrent with Altered Gut Bacteria

BACKGROUND

Enzyme-treated wheat bran (ETWB) contains a fermentable dietary fiber previously shown to decrease liver triglycerides (TGs) and modify the gut microbiome in mice. It is not clear which mechanisms explain how ETWB feeding affects hepatic metabolism, but factors (i.e., xenometabolites) associated with specific microbes may be involved.

OBJECTIVE

The objective of this study was to characterize ETWB-driven shifts in the cecal microbiome and to identify correlates between microbial changes and diet-related differences in liver metabolism in diet-induced obese mice that typically display steatosis.

METHODS

Five-week-old male C57BL/6J mice fed a 45%-lard-based fat diet supplemented with ETWB (20% wt:wt) or rapidly digestible starch (control) (n = 15/group) for 10 wk were characterized by using a multi-omics approach. Multivariate statistical analysis was used to identify variables that were strong discriminators between the ETWB and control groups.

RESULTS

Body weight and liver TGs were decreased by ETWB feeding (by 10% and 25%, respectively; P < 0.001), and an index of liver reactive oxygen species was increased (by 29%; P < 0.01). The cecal microbiome showed an increase in Bacteroidetes (by 42%; P < 0.05) and a decrease in Firmicutes (by 16%; P < 0.05). Metabolites that were strong discriminators between the ETWB and control groups included decreased liver antioxidants (glutathione and α-tocopherol); decreased liver carbohydrate metabolites, including glucose; lower hepatic arachidonic acid; and increased liver and plasma β-hydroxybutyrate. Liver transcriptomics revealed key metabolic pathways affected by ETWB, especially those related to lipid metabolism and some fed- or fasting-regulated genes.

CONCLUSIONS

Together, these changes indicate that dietary fibers such as ETWB regulate hepatic metabolism concurrently with specific gut bacteria community shifts in C57BL/6J mice. It is proposed that these changes may elicit gut-derived signals that reach the liver via enterohepatic circulation, ultimately affecting host liver metabolism in a manner that mimics, in part, the fasting state.

Metabolic variations in different citrus rootstock cultivars associated with different responses to Huanglongbing

Huanglongbing (HLB) is one of the most destructive bacterial diseases of citrus. No resistant cultivars have been identified, although tolerance has been observed in the genus Poncirus and some of its hybrids with Citrus that are commonly used as rootstocks. In this study we exploited this tolerance by comparing five different tolerant hybrids with a cultivar that shows pronounced HLB sensitivity to discern potential contributing metabolic factors. Whole leaves of infected and non-infected greenhouse-grown seedlings were extracted and subjected to untargeted GC-TOF MS based metabolomics. After BinBase data filtering, 342 (experiment 1) and 650 (experiment 2) unique metabolites were quantified, of which 122 and 195, respectively, were assigned by chemical structures. The number of metabolites found to be differently regulated in the infected state compared with the non-infected state varied between the cultivars and was largest (166) in the susceptible cultivar Cleopatra mandarin (Citrus reticulata) and lowest (3) in the tolerant cultivars US-897 (C. reticulata 'Cleopatra' × Poncirus trifoliata) and US-942 (C. reticulata 'Sunki' × P. trifoliata) from experiment 2. Tolerance to HLB did not appear to be associated with accumulation of higher amounts of protective metabolites in response to infection. Many metabolites were found in higher concentrations in the tolerant cultivars compared with susceptible Cleopatra mandarin and may play important roles in conferring tolerance to HLB. Lower availability of specific sugars necessary for survival of the pathogen may also be a contributing factor in the decreased disease severity observed for these cultivars.

eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics

Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC/MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-time-of-flight (TOF) MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign, and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-triple quadrupole (QqQ) MS, LC-QqQ, and NMR. eRah is freely available at http://CRAN.R-project.org/package=erah .

Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry

The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future.

Environmental Metabolomics of the Tomato Plant Surface Provides Insights on Salmonella enterica Colonization

Foodborne illness-causing enteric bacteria are able to colonize plant surfaces without causing infection. We lack an understanding of how epiphytic persistence of enteric bacteria occurs on plants, possibly as an adaptive transit strategy to maximize chances of reentering herbivorous hosts. We used tomato (Solanum lycopersicum) cultivars that have exhibited differential susceptibilities to Salmonella enterica colonization to investigate the influence of plant surface compounds and exudates on enteric bacterial populations. Tomato fruit, shoot, and root exudates collected at different developmental stages supported growth of S. enterica to various degrees in a cultivar- and plant organ-dependent manner. S. enterica growth in fruit exudates of various cultivars correlated with epiphytic growth data (R(2) = 0.504; P = 0.006), providing evidence that plant surface compounds drive bacterial colonization success. Chemical profiling of tomato surface compounds with gas chromatography-time of flight mass spectrometry (GC-TOF-MS) provided valuable information about the metabolic environment on fruit, shoot, and root surfaces. Hierarchical cluster analysis of the data revealed quantitative differences in phytocompounds among cultivars and changes over a developmental course and by plant organ (P < 0.002). Sugars, sugar alcohols, and organic acids were associated with increased S. enterica growth, while fatty acids, including palmitic and oleic acids, were negatively correlated. We demonstrate that the plant surface metabolite landscape has a significant impact on S. enterica growth and colonization efficiency. This environmental metabolomics approach provides an avenue to understand interactions between human pathogens and plants that could lead to strategies to identify or breed crop cultivars for microbiologically safer produce.

IMPORTANCE

In recent years, fresh produce has emerged as a leading food vehicle for enteric pathogens. Salmonella-contaminated tomatoes represent a recurrent human pathogen-plant commodity pair. We demonstrate that Salmonella can utilize tomato surface compounds and exudates for growth. Surface metabolite profiling revealed that the types and amounts of compounds released to the plant surface differ by cultivar, plant developmental stage, and plant organ. Differences in exudate profiles explain some of the variability in Salmonella colonization susceptibility seen among tomato cultivars. Certain medium- and long-chain fatty acids were associated with restricted Salmonella growth, while sugars, sugar alcohols, and organic acids correlated with larger Salmonella populations. These findings uncover the possibility of selecting crop varieties based on characteristics that impair foodborne pathogen growth for enhanced safety of fresh produce.