CAVE: a cloud-based platform for analysis and visualization of metabolic pathways.

Flux balance analysis (FBA) is an important method for calculating optimal pathways to produce industrially important chemicals in genome-scale metabolic models (GEMs). However, for biologists, the requirement of coding skills poses a significant obstacle to using FBA for pathway analysis and engineering target identification. Additionally, a time-consuming manual drawing process is often needed to illustrate the mass flow in an FBA-calculated pathway, making it challenging to detect errors or discover interesting metabolic features. To solve this problem, we developed CAVE, a cloud-based platform for the integrated calculation, visualization, examination and correction of metabolic pathways. CAVE can analyze and visualize pathways for over 100 published GEMs or user-uploaded GEMs, allowing for quicker examination and identification of special metabolic features in a particular GEM. Additionally, CAVE offers model modification functions, such as gene/reaction removal or addition, making it easy for users to correct errors found in pathway analysis and obtain more reliable pathways. With a focus on the design and analysis of optimal pathways for biochemicals, CAVE complements existing visualization tools based on manually drawn global maps and can be applied to a broader range of organisms for rational metabolic engineering. CAVE is available at https://cave.biodesign.ac.cn/.

Metabolomics approach to study in vivo toxicity of graphene oxide nanosheets.

Although graphene oxide (GO) nanosheets are widely used in different fields, the mechanism of their toxicity remains relatively unknown. NMR-based metabolomics was used to study in vivo time and dose-dependent toxicity of GO nanosheets in mice. Sixty serum samples from mice in four different time intervals including 24 and 72 h and 7 and 21 days after injection of 0-, 1-, and 10-mg/kg b.w. were analyzed based on 1 HNMR spectra of each sample and multivariate methods. In comparison with the control group, 12 changed metabolites were identified in GO nanosheet-treated mice groups. These metabolites are involved in steroid hormone biosynthesis and steroid biosynthesis pathways. It was seen that the time factor is more important than the dose factor and the groups were separated in a time direction, completely. We found that GO nanosheets has toxicity and can affect steroidal hormones. However, this study shows that after 21 days, the treated groups regardless of their GO nanosheet dose are very close to the control group. This means that in one step exposure to GO nanosheets, their toxicity diminished after 21 days.

New chemical biopsy tool for spatially resolved profiling of human brain tissue in vivo.

It is extremely challenging to perform chemical analyses of the brain, particularly in humans, due to the restricted access to this organ. Imaging techniques are the primary approach used in clinical practice, but they only provide limited information about brain chemistry. Solid-phase microextraction (SPME) has been presented recently as a chemical biopsy tool for the study of animal brains. The current work demonstrates for the first time the use of SPME for the spatially resolved sampling of the human brain in vivo. Specially designed multi-probe sampling device was used to simultaneously extract metabolites from the white and grey matter of patients undergoing brain tumor biopsies. Samples were collected by inserting the probes along the planned trajectory of the biopsy needle prior to the procedure, which was followed by metabolomic and lipidomic analyses. The results revealed that studied brain structures were predominantly composed of lipids, while the concentration and diversity of detected metabolites was higher in white than in grey matter. Although the small number of participants in this research precluded conclusions of a biological nature, the results highlight the advantages of the proposed SPME approach, as well as disadvantages that should be addressed in future studies.

Application across species of a one health approach to liquid sample handling for respiratory based -omics analysis.

Airway inflammation is highly prevalent in horses, with the majority of non-infectious cases being defined as equine asthma. Currently, cytological analysis of airway derived samples is the principal method of assessing lower airway inflammation. Samples can be obtained by tracheal wash (TW) or by lavage of the lower respiratory tract (bronchoalveolar lavage (BAL) fluid; BALF). Although BALF cytology carries significant diagnostic advantages over TW cytology for the diagnosis of equine asthma, sample acquisition is invasive, making it prohibitive for routine and sequential screening of airway health. However, recent technological advances in sample collection and processing have made it possible to determine whether a wider range of analyses might be applied to TW samples. Considering that TW samples are relatively simple to collect, minimally invasive and readily available in the horse, it was considered appropriate to investigate whether, equine tracheal secretions represent a rich source of cells and both transcriptomic and proteomic data. Similar approaches have already been applied to a comparable sample set in humans; namely, induced sputum. Sputum represents a readily available source of airway biofluids enriched in proteins, changes in the expression of which may reveal novel mechanisms in the pathogenesis of respiratory diseases, such as asthma and chronic obstructive pulmonary disease. The aim of this study was to establish a robust protocol to isolate macrophages, protein and RNA for molecular characterization of TW samples and demonstrate the applicability of sample handling to rodent and human pediatric bronchoalveolar lavage fluid isolates. TW samples provided a good quality and yield of both RNA and protein for downstream transcriptomic/proteomic analyses. The sample handling methodologies were successfully applicable to BALF for rodent and human research. TW samples represent a rich source of airway cells, and molecular analysis to facilitate and study airway inflammation, based on both transcriptomic and proteomic analysis. This study provides a necessary methodological platform for future transcriptomic and/or proteomic studies on equine lower respiratory tract secretions and BALF samples from humans and mice.

Breast Cancer: Targeting of Steroid Hormones in Cancerogenesis and Diagnostics.

Breast cancer is the most common malignancy in women with high mortality. Sensitive and specific methods for the detection, characterization and quantification of endogenous steroids in body fluids or tissues are needed for the diagnosis, treatment and prognosis of breast cancer and many other diseases. At present, non-invasive diagnostic methods are gaining more and more prominence, which enable a relatively fast and painless way of detecting many diseases. Metabolomics is a promising analytical method, the principle of which is the study and analysis of metabolites in biological material. It represents a comprehensive non-invasive diagnosis, which has a high potential for use in the diagnosis and prognosis of cancers, including breast cancer. This short review focuses on the targeted metabolomics of steroid hormones, which play an important role in the development and classification of breast cancer. The most commonly used diagnostic tool is the chromatographic method with mass spectrometry detection, which can simultaneously determine several steroid hormones and metabolites in one sample. This analytical procedure has a high potential in effective diagnosis of steroidogenesis disorders. Due to the association between steroidogenesis and breast cancer progression, steroid profiling is an important tool, as well as in monitoring disease progression, improving prognosis, and minimizing recurrence.

Spatiotemporal determination of metabolite activities in the corneal epithelium on a chip.

The corneal epithelial barrier maintains the metabolic activities of the ocular surface by regulating membrane transporters and metabolic enzymes responsible for the homeostasis of the eye as well as the pharmacokinetic behavior of drugs. Despite its importance, no established biomimetic in vitro methods are available to perform the spatiotemporal investigation of metabolism and determine the transportation of endogenous and exogenous molecules across the corneal epithelium barrier. This study introduces multiple corneal epitheliums on a chip namely, Corneal Epithelium on a Chip (CEpOC), which enables the spatiotemporal collection as well as analysis of micro-scaled extracellular metabolites from both the apical and basolateral sides of the barriers. Longitudinal samples collected during 48 h period were analyzed using untargeted liquid chromatography-mass spectrometry metabolomics method, and 104 metabolites were annotated. We observed the spatiotemporal secretion of biologically relevant metabolites (i.e., antioxidant, glutathione and uric acid) as well as the depletion of essential nutrients such as amino acids and vitamins mimicking the in vivo molecules trafficking across the human corneal epithelium. Through the shifts of extracellular metabolites and quantitative analysis of mRNA associated with transporters, we were able to investigate the secretion and transportation activities across the polarized barrier in a correlation with the expression of corneal transporters. Thus, CEpOC can provide a non-invasive, simple, yet effectively informative method to determine pharmacokinetics and pharmacodynamics as well as to discover novel biomarkers for drug toxicological and safety tests as advanced experimental model of the human corneal epithelium.

Unraveling mosquito metabolism with mass spectrometry-based metabolomics.

Nearly half a million people die annually due to mosquito-borne diseases. Despite aggressive mosquito population-control efforts, current strategies are limited in their ability to control these vectors. A better understanding of mosquito metabolism through modern approaches can contribute to the discovery of novel metabolic targets and/or regulators and lead to the development of better mosquito-control strategies. Currently, cutting-edge technologies such as gas or liquid chromatography-mass spectrometry-based metabolomics are considered 'mature technologies' in many life-science disciplines but are still an emerging area of research in medical entomology. This review primarily discusses recent developments and progress in the application of mass spectrometry-based metabolomics to answer multiple biological questions related to mosquito metabolism.

Investigation of steatosis profiles induced by pesticides using liver organ-on-chip model and omics analysis.

Several studies have reported a correlation between pesticides exposure and metabolic disorders. Dichlorodiphenyltrichloroethane (DDT) and permethrin (PMT), two pesticides highly prevalent in the environment, have been associated to dysregulation of liver lipids and glucose metabolisms and non-alcoholic fatty liver disease (NAFLD). However, the effects of DDT/PMT mixtures and mechanisms mediating their action remain unclear. Here, we used multi-omic to investigate the liver damage induced by DDT, PMT and their mixture in rat liver organ-on-chip. Organ-on-chip allow the reproduction of in vivo-like micro-environment. Two concentrations, 15 and 150 µM, were used to expose the hepatocytes for 24 h under perfusion. The transcriptome and metabolome analysis suggested a dose-dependent effect for all conditions, with a profile close to control for pesticides low-doses. The comparison between control and high-doses detected 266/24, 256/24 and 1349/30 genes/metabolites differentially expressed for DDT150, PMT150 and Mix150 (DDT150/PMT150). Transcriptome modulation reflected liver inflammation, steatosis, necrosis, PPAR signaling and fatty acid metabolism. The metabolome analysis highlighted common signature of three treatments including lipid and carbohydrates production, and a decrease in amino acids and krebs cycle intermediates. Our study illustrates the potential of organ-on-chip coupled to multi-omics for toxicological studies and provides new tools for chemical risk assessment.

An ambient-temperature storage and stabilization device performs comparably to flash-frozen collection for stool metabolomics in infants.

BACKGROUND: Stool metabolites provide essential insights into the function of the gut microbiome. The current gold standard for storage of stool samples for metabolomics is flash-freezing at - 80 °C which can be inconvenient and expensive. Ambient temperature storage of stool is more practical, however no available methodologies adequately preserve the metabolomic profile of stool. A novel sampling kit (OMNImet.GUT; DNA Genotek, Inc.) was introduced for ambient temperature storage and stabilization of feces for metabolomics; we aimed to test the performance of this kit vs. flash-freezing. To do this stool was collected from an infant's diaper was divided into two aliquots: 1) flash-frozen and 2) stored in an OMNImet.GUT tube at ambient temperature for 3-4 days. Samples from the same infant were collected at 2 different time points to assess metabolite changes over time. Subsequently, all samples underwent metabolomic analysis by liquid chromatography - tandem mass spectrometry (LC-MS/MS). RESULTS: Paired fecal samples (flash-frozen and ambient temperature) from 16 infants were collected at 2 time points (32 individual samples, 64 aliquots). Similar numbers of metabolites were detected in both the frozen and ambient temperature samples (1126 in frozen, 1107 in ambient temperature, 1064 shared between sample types). Metabolite abundances were strongly correlated between storage methods (median Spearman correlation Rs = 0.785 across metabolites). Hierarchical clustering analysis and principal component analysis showed that samples from the same individuals at a given time point clustered closely, regardless of the storage method. Repeat samples from the same individual were compared by paired t-test, separately for the frozen and OMNImet.GUT. The number of metabolites in each biochemical class that significantly changed (p < 0.05) at timepoint 2 relative to timepoint 1 was similar in flash-frozen versus ambient temperature storage. Changes in microbiota modified metabolites over time were also consistent across both methodologies. CONCLUSION: Ambient temperature storage and stabilization of stool in the OMNImet.GUT device yielded comparable metabolomic results to flash freezing in terms of 1) the identity and abundance of detected biochemicals 2) the distinct metabolomic profiles of subjects and 3) changes in metabolites over time that are plausibly microbiota-induced. This method potentially provides a more convenient, less expensive home collection and storage option for stool metabolomic analysis.

Evaluation of a nanoflow interface based on the triple-tube coaxial sheath-flow sprayer for capillary electrophoresis-mass spectrometry coupling in metabolomics.

The performance of an original CE-MS interface that allows the in-axis positioning of the electrospray with respect to the MS inlet was evaluated. The variations in the geometrical alignment of this configuration in the absence of a nebulizing gas afforded a significant reduction in the sheath-liquid flow rate from 3 µL/min to as low as 300 nL/min. The sheath liquid and BGE were respectively composed of H2O-iPrOHCH3COOH 50:50:1 (v/v/v) and 10% acetic acid (pH 2.2). A significant gain in sensitivity was obtained, and it was correlated to the effective mobility of the analytes. Compounds with low mobility values showed a greater sensitivity gain. Special attention was paid to the detection of proteinogenic amino acids. Linear response functions were obtained from 15 ng/mL to 500 ng/mL. The limits of quantification, as low as 34.3 ng/mL, were improved by a factor of up to six compared to the conventional configuration. The in-axis setup was ultimately applied to the absolute quantification of four important amino acids, alanine, tyrosine, methionine and valine, in standard reference material (NIST plasma). The accuracies ranged from 78 to 113%, thus demonstrating the potential of this configuration for metabolomics.

Hyphenated high-resolution mass spectrometry-the "all-in-one" device in analytical toxicology?

This trend article reviews papers with hyphenated high-resolution mass spectrometry (HRMS) approaches applied in analytical toxicology, particularly in clinical and forensic toxicology published since 2016 and referenced in PubMed. The article focuses on the question of whether HRMS has or will become the all-in-one device in these fields as supposed by the increasing number of HRMS presentations at scientific meetings, corresponding original papers, and review articles. Typical examples for the different application fields are discussed such as targeted or untargeted drug screening, quantification, drug metabolism studies, and metabolomics approaches. Considering the reviewed papers, HRMS is currently the only technique that fulfills the criteria of an all-in-one device for the various applications needed in analytical toxicology.Graphical abstract.

Capillary ultrahigh-pressure liquid chromatography-mass spectrometry for fast and high resolution metabolomics separations.

LC-MS is an important tool for metabolomics due its high sensitivity and broad metabolite coverage. The goal of improving resolution and decreasing analysis time in HPLC has led to the use of 5 - 15 cm long columns packed with 1.7 - 1.9 µm particles requiring pressures of 8 - 12 kpsi. We report on the potential for capillary LC-MS based metabolomics utilizing porous C18 particles down to 1.1 µm diameter and columns up to 50 cm long with an operating pressure of 35 kpsi. Our experiments show that it is possible to pack columns with 1.1 µm porous particles to provide predicted improvements in separation time and efficiency. Using kinetic plots to guide the choice of column length and particle size, we packed 50 cm long columns with 1.7 µm particles and 20 cm long columns with 1.1 µm particles, which should produce equivalent performance in shorter times. Columns were tested by performing isocratic and gradient LC-MS analyses of small molecule metabolites and extracts from plasma. These columns provided approximately 100,000 theoretical plates for metabolite standards and peak capacities over 500 in 100 min for a complex plasma extract with robust interfacing to MS. To generate a given peak capacity, the 1.1 µm particles in 20 cm columns required roughly 75% of the time as 1.7 µm particles in 50 cm columns with both operated at 35 kpsi. The 1.1 µm particle packed columns generated a given peak capacity nearly 3 times faster than 1.7 µm particles in 15 cm columns operated at ~10 kpsi. This latter condition represents commercial state of the art for capillary LC. To consider practical benefits for metabolomics, the effect of different LC-MS variables on mass spectral feature detection was evaluated. Lower flow rates (down to 700 nL/min) and larger injection volumes (up to 1 µL) increased the features detected with modest loss in separation performance. The results demonstrate the potential for fast and high resolution separations for metabolomics using 1.1 µm particles operated at 35 kpsi for capillary LC-MS.

Effect of the phenolic compounds from Sabara jaboticaba (Plinia jaboticaba (Vell. ) Berg) in reducing health risks caused by obesity / Efeito dos compostos fenólicos da jabuticaba Sabará (Plinia jaboticaba (Vell. ) Berg) na redução dos riscos à saúde causados pela obesidade

Sabara jaboticaba (Plinia jaboticaba (Vell.) Berg) is a Brazilian native fruit from Atlantic Forest, rich in polyphenols and appreciated for consumption both in natura and in various preparations. This study aimed to evaluate whether phenolic compounds of Sabara jaboticaba, in the form of phenolic extract (PEJ), can reduce the health risks caused by obesity and associated health problems induced by a fat-sucrose-rich diet (HFSD) in C57BL/6J mice. Initially, for 14 weeks, 66 8-week-old male mice were randomly distributed into two groups: negative control (CH), fed with standard AIN96M diet and water ad libitum; positive control (HFS), fed with HFSD and water ad libitum. At the end of this stage, 10 animals from each group were euthanized under anesthesia and their organs and tissues collected. The remaining animals were redistributed into four groups for another 14 weeks: group CH, fed a standard diet and water; HFS group, fed with HFSD and water; PEJ1 group, fed with HFSD and PEJ at the dose of 50 mg equivalent of gallic acid (GAE)/kg of body weight (BW); group J100 fed with HFSD and PEJ at the dose of 100 mg GAE/kg BW. Food intake, BW, and fasting blood glucose (FBG) were measured weekly and water (CH and HFS) or PEJ (PEJ1 and PEJ2) were daily administered. In the 26th week the intraperitoneal insulin tolerance test (ipITT) was performed, in the 27th, the oral glucose tolerance test (oGTT), and, in the 28th, the analyzes related to energy homeostasis. At the end of the experiment, the animals were euthanized under anesthesia and their organs and tissues were collected. When compared to the HFS group, animals that received PEJ showed decrease in BW gain of approx. 30% and of approx. 45% in the gain of total white adipose tissues (WAT). In addition, the PEJ groups showed less hypertrophied adipocytes. Inflammation markers were significantly reduced in both treated groups. The FBG was approx. 13% lower for the PEJ groups compared to the HFS group. In addition, the mean values of ipITT, oGTT, insulin and HOMA-IR demonstrated that PEJ increased insulin sensitivity and decreased glucose intolerance. GLUT4 expression in the muscle was also increased in the treated groups. The fecal lipid content was lower in the PEJ groups when compared to the HFS group, suggesting that PEJ inhibited pancreatic lipase activity both in vitro and in vivo. In the PEJ groups, the levels of total cholesterol, LDL and NEFA were reduced and those of HDL increased. The hepatic concentration of TAG was also reduced by PEJ. Energy expenditure and UCP1 expression were higher for both supplemented groups when compared to the HFS group. PEJ positively altered the intestinal microbiota and the analysis of metabolites showed that animals treated with PEJ had different metabolomic profile. Together, these results demonstrated that polyphenols from jaboticaba may be used as adjuvants against obesity and associated health problems

A jabuticaba Sabará (Plinia jaboticaba (Vell.) Berg) é um fruto nativo da Mata Atlântica brasileira, rico em polifenóis e apreciado para o consumo tanto in natura quanto em preparos variados. O objetivo deste trabalho foi avaliar se compostos fenólicos da jabuticaba Sabará, na forma de extrato fenólico (PEJ), são capazes de reduzir os riscos à saúde causados pela obesidade e problemas de saúde associados induzidos por uma dieta rica em lipídios e sacarose (HFSD) em camundongos C57BL/6J. Inicialmente, durante 14 semanas, 66 animais machos com oito semanas de vida foram distribuídos aleatoriamente em dois grupos: controle negativo (CH), alimentado com dieta padrão AIN96M e água ad libitum; controle positivo (HFS), alimentado com HFSD e água ad libitum. Ao final desta etapa, 10 animais de cada grupo foram eutanasiados sob anestesia e seus órgãos e tecidos coletados. Os animais restantes foram redistribuídos em quatro grupos por mais 14 semanas: grupo CH, alimentado com dieta padrão e água; grupo HFS, alimentado com HFSD e água; grupo PEJ1, alimentado com HFSD e PEJ na dose de 50 mg equivalente de ácido gálico (EAG)/kg de massa corporal (m.c.); grupo J100 alimentado com HFSD e PEJ na dose de 100 mg EAG/kg m.c. O consumo de ração, a massa corporal e a glicemia de jejum (FBG) foram medidos semanalmente e as gavagens de água (CH e HFS) ou PEJ (PEJ1 e PEJ2) foram realizadas diariamente. Na 26ª semana foi realizado o teste intraperitoneal de tolerância à insulina (ipITT), na 27ª o teste oral de tolerância à glicose (oGTT) e na 28ª as análises relacionadas a homeostase energética. Ao final do experimento os animais foram eutanasiados sob anestesia e seus órgãos e tecidos coletados. Quando comparados ao grupo HFS, animais que receberam o PEJ apresentaram ganho de massa corporal aprox. 30% menor e aprox. 45% menos massa total de tecidos adiposos brancos (TAB). Além disso, os grupos PEJ apresentaram adipócitos menos hipertrofiados. Marcadores de inflamação foram significativamente reduzidos em ambos os grupos tratados. A FBG foi aprox. 13% inferior para os grupos PEJ em relação ao grupo HFS. Além disso, os valores médios de ipITT, oGTT, insulina e HOMA-IR demonstraram que o PEJ aumentou a sensibilidade à insulina e diminuiu a intolerância à glicose. A expressão do GLUT4 no músculo estava aumentada nos grupos tratados. O conteúdo lipídico fecal dos grupos PEJ foi superior ao do grupo HFS, sugerindo que, assim como ocorreu in vitro, o extrato inibiu a atividade da lipase pancreática in vivo. Os níveis de colesterol total (PEJ1), LDL e NEFA foram reduzidos e os de HDL aumentados. A concentração hepática de TAG também foi reduzida pelo PEJ. O gasto energético e a expressão de UCP1 foram superiores para ambos os grupos suplementados quando comparados ao grupo HFS. PEJ alterou positivamente a microbiota intestinal e a análise de metabólitos mostrou que os animais tratados com PEJ possuíam perfil metabolômico diferente. Em conjunto, estes resultados demonstraram que os CFJS podem ser usados como adjuvantes no combate a obesidade e problemas de saúde associados

Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples.

The human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts. Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.

A combined LC-MS and NMR approach to reveal metabolic changes in the hemolymph of honeybees infected by the gut parasite Nosema ceranae.

Nosema ceranae is an emerging and invasive gut pathogen in Apis mellifera and is considered as a factor contributing to the decline of honeybee populations. Here, we used a combined LC-MS and NMR approach to reveal the metabolomics changes in the hemolymph of honeybees infected by this obligate intracellular parasite. For metabolic profiling, hemolymph samples were collected from both uninfected and N. ceranae-infected bees at two time points, 2 days and 10 days after the experimental infection of emergent bees. Hemolymph samples were individually analyzed by LC-MS, whereas each NMR spectrum was obtained from a pool of three hemolymphs. Multivariate statistical PLS-DA models clearly showed that the age of bees was the parameter with the strongest effect on the metabolite profiles. Interestingly, a total of 15 biomarkers were accurately identified and were assigned as candidate biomarkers representative of infection alone or combined effect of age and infection. These biomarkers included carbohydrates (α/ß glucose, α/ß fructose and hexosamine), amino acids (histidine and proline), dipeptides (Glu-Thr, Cys-Cys and γ-Glu-Leu/Ile), metabolites involved in lipid metabolism (choline, glycerophosphocholine and O-phosphorylethanolamine) and a polyamine compound (spermidine). Our study demonstrated that this untargeted metabolomics-based approach may be useful for a better understanding of pathophysiological mechanisms of the honeybee infection by N. ceranae.

Plasma metabolites in treatment-requiring retinopathy of prematurity: Potential biomarkers identified by metabolomics.

Retinopathy of prematurity (ROP) is a potentially blinding condition caused by disruption of retinal vascularization and metabolism. This study aims to identify altered metabolites from plasma in patients with treatment-requiring ROP (TR-ROP) compared with controls. An untargeted metabolomics analysis was performed to reveal the metabolomic profiles of the plasma between TR-ROP patients (n = 38) and age-matched infants (n = 23). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the potential signaling pathways of the changed metabolites. Under positive ion mode, a total of 29 metabolites were significantly altered in plasma between TR-ROP patients and controls, and 23 altered metabolites were identified under negative ion mode. KEGG analyses indicated that "protein digestion and absorption" and "aminoacyl-tRNA biosynthesis" were the most enriched pathways of the altered metabolites. These results demonstrated that metabolomic profiles changed in plasma of TR-ROP, and the altered metabolites could be served as potential biomarkers for the diagnosis and prognosis of TR-ROP patients. Besides, the metabolomic profiles might provide clues to discover novel therapeutic strategies in ROP treatment.

Discovery of different metabotypes in overconditioned dairy cows by means of machine learning.

Using data from targeted metabolomics in serum in combination with machine learning (ML) approaches, we aimed at (1) identifying divergent metabotypes in overconditioned cows and at (2) exploring how metabotypes are associated with lactation performance, blood metabolites, and hormones. In a previously established animal model, 38 pregnant multiparous Holstein cows were assigned to 2 groups that were fed differently to reach either high (HBCS) or normal (NBCS) body condition score (BCS) and backfat thickness (BFT) until dryoff at -49 d before calving [NBCS: BCS < 3.5 (3.02 ± 0.24) and BFT < 1.2 cm (0.92 ± 0.21), mean ± SD; HBCS: BCS > 3.75 (3.82 ± 0.33) and BFT > 1.4 cm (2.36 ± 0.35)]. Cows were then fed the same diets during the dry period and the subsequent lactation, and maintained the differences in BFT and BCS throughout the study. Blood samples were collected weekly from 7 wk antepartum (ap) to 12 wk postpartum (pp) to assess serum concentrations of metabolites (by targeted metabolomics and by classical analyses) and metabolic hormones. Metabolic clustering by applying 4 supervised ML-based classifiers [sequential minimal optimization (SMO), random forest (RF), alternating decision tree (ADTree), and naïve Bayes-updatable (NB)] on the changes (d 21 pp minus d 49 ap) in concentrations of 170 serum metabolites resulted in 4 distinct metabolic clusters: HBCS predicted HBCS (HBCS-PH, n = 13), HBCS predicted NBCS (HBCS-PN, n = 6), NBCS predicted NBCS (NBCS-PN, n = 15), and NBCS predicted HBCS (NBCS-PH, n = 4). The accuracies of SMO, RF, ADTree, and NB classifiers were >70%. Because the number of NBCS-PH cows was low, we did not consider this group for further comparisons. Dry matter intake (kg/d and percentage of body weight) and energy intake were greater in HBCS-PN than in HBCS-PH in early lactation, and HBCS-PN also reached a positive energy balance earlier than did HBCS-PH. Milk yield was not different between groups, but milk protein percentage was greater in HBCS-PN than in HBCS-PH cows. The circulating concentrations of fatty acids (FA) increased during early lactation in both groups, but HBCS-PN cows had lower concentrations of ß-hydroxybutyrate, indicating lower ketogenesis compared with HBCS-PH cows. The concentrations of insulin, insulin-like growth factor 1, leptin, adiponectin, haptoglobin, glucose, and revised quantitative insulin sensitivity check index did not differ between the groups, whereas serum concentrations of glycerophospholipids were lower before calving in HBCS-PH than in HBCS-PN cows. Glycine was the only amino acid that had higher concentration after calving in HBCS-PH than in HBCS-PN cows. The circulating concentrations of some short- (C2, C3, and C4) and long-chain (C12, C16:0, C18:0, and C18:1) acylcarnitines on d 21 pp were greater in HBCS-PH than in HBCS-PN cows, indicating incomplete FA oxidation. In conclusion, the use of ML approaches involving data from targeted metabolomics in serum is a promising method for differentiating divergent metabotypes from apparently similar BCS phenotypes. Further investigations, using larger numbers of cows and farms, are warranted for confirmation of this finding.

Hepatoxicity mechanism of cantharidin-induced liver LO2 cells by LC-MS metabolomics combined traditional approaches.

Hepatotoxicity induced by Mylabris has been reported in both clinical and animal experiments. Cantharidin (CTD), the main active compound of Mylabris was responsible for the hepatotoxicity, which aroused widespread concern. However, the mechanism of CTD hepatotoxicity remained unclear. In this study, LO2 cells were exposed to two doses of CTD (6.25 and 25 µM) for 12 h, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were measured. The metabolites in LO2 cells were profiled by LC-MS. Partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis were used for screening potential biomarkers. The MetPA software was used for clustering and pathway analysis. Network pharmacology was used to predict the genes acted with potential biomarkers. Compared with the control group, the levels of ALT, AST, and LDH was significantly increased after CTD treatment. A total of 46 potential biomarkers for hepatotoxicity induced by CTD were identified. And downregulated potential biomarkers reflected the inhibitory effects of CTD toxicity on metabolism of LO2. Moreover, CTD-induced liver toxicity of LO2 cells is mainly related to three pathways: cysteine and methionine metabolism; glutathione metabolism; and glycine, serine, and threonine metabolism. Furtherly, the mRNA expression of CES2, DNMT1, NOS1, NOS3, S1PR2, and CES1 screened by network pharmacology were regulated by CTD. These studies provide valuable mechanistic insights into CTD-associated hepatotoxicity that will aid in the development of therapeutic prevention and treatment options for this liver disease.

Inter-laboratory reproducibility of an untargeted metabolomics GC-MS assay for analysis of human plasma.

There is a long-standing concern for the lack of reproducibility of the untargeted metabolomic approaches used in pharmaceutical research. Two types of human plasma samples were split into two batches and analyzed in two individual labs for untargeted GC-MS metabolomic profiling. The two labs used the same silylation sample preparation protocols but different instrumentation, data processing software, and database. There were 55 metabolites annotated reproducibly, independent of the labs. The median coefficient variations (CV%) of absolute spectra ion intensities in both labs were less than 30%. However, the comparison of normalized ion intensity among biological groups, were inconsistent across labs. Predicted power based on annotated metabolites was evaluated post various normalization, data transformation and scaling. For the first time our study reveals the numerical details about the variations in metabolomic annotation and relative quantification using plain inter-laboratory GC-MS untargeted metabolomic approaches. Especially we compare several commonly used post-acquisition strategies and found normalization could not strengthen the annotation accuracy or relative quantification precision of untargeted approach, instead it will impact future experimental design. Standardization of untargeted metabolomics protocols, including sample preparation, instrumentation, data processing, etc., is critical for comparison of untargeted data across labs.