A Multi-Omics Study Revealing the Metabolic Effects of Estrogen in Liver Cancer Cells HepG2.

Hepatocellular carcinoma (HCC) that is triggered by metabolic defects is one of the most malignant liver cancers. A much higher incidence of HCC among men than women suggests the protective roles of estrogen in HCC development and progression. To begin to understand the mechanisms involving estrogenic metabolic effects, we compared cell number, viability, cytotoxicity, and apoptosis among HCC-derived HepG2 cells that were treated with different concentrations of 2-deoxy-d-glucose (2-DG) that blocks glucose metabolism, oxamate that inhibits lactate dehydrogenase and glycolysis, or oligomycin that blocks ATP synthesis and mitochondrial oxidative phosphorylation. We confirmed that HepG2 cells primarily utilized glycolysis followed by lactate fermentation, instead of mitochondrial oxidative phosphorylation, for cell growth. We hypothesized that estrogen altered energy metabolism via its receptors to carry out its anticancer effects in HepG2 cells. We treated cells with 17ß-estradiol (E2), 1,3,5-tris(4-hydroxyphenyl)-4-propyl-1H-pyrazole (PPT) an estrogen receptor (ER) α (ERα) agonist, or 2,3-bis(4-hydroxyphenyl)-propionitrile (DPN), an ERß agonist. We then used transcriptomic and metabolomic analyses and identified differentially expressed genes and unique metabolite fingerprints that are produced by each treatment. We further performed integrated multi-omics analysis, and identified key genes and metabolites in the gene-metabolite interaction contributed by E2 and ER agonists. This integrated transcriptomic and metabolomic study suggested that estrogen acts on estrogen receptors to suppress liver cancer cell growth via altering metabolism. This is the first exploratory study that comprehensively investigated estrogen and its receptors, and their roles in regulating gene expression, metabolites, metabolic pathways, and gene-metabolite interaction in HCC cells using bioinformatic tools. Overall, this study provides potential therapeutic targets for future HCC treatment.

Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches.

This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Development and application of time staggered/mass staggered-globally optimized targeted mass spectrometry.

The emerging requests for handling complex samples in system biology studies highlighted the need to expand the metabolite coverage in metabolomics analysis and to take advantage of the quantitative and targeted assays. Here, we developed a novel workflow to integrate time staggered or mass staggered scan methods with globally optimized targeted-mass spectrometry (GOT-MS), to enable broad metabolites coverage with better stability, repeatability, and quantitative capability. To establish these methods, two scheduled selected reaction monitoring (SRM) methods, time staggered and mass staggered approaches, were configured to achieve optimal sensitivity and scan speed and were combined with the GOT-MS strategy. Both methods took advantage of the systematic selection and rearrangement of all detectable metabolic peaks from a GOT-MS peak list, based on either retention time or m/z of the precursor ions. The established methods were then applied to the metabolic profile-based differentiation of Staphylococcus aureus N315 and N315 ex, an isogenic pair of Methicillin-resistant and susceptible S. aureus (MRSA and MSSA). A total of 464 metabolite peaks was detected successfully from pooled MSSA and MRSA bacterial metabolite extract using the GOT-MS method, and ts/ms-GOT-MS demonstrated better sensitivity and repeatability than the GOT-MS and previously established targeted metabolomics method. The semi-quantitative analysis in a broader metabolome coverage was also achieved with ts/ms-GOT-MS methods. Multivariate statistical analyses were also performed to determine whether metabolic profiling approach could differentiate MSSA from MRSA. The comparison of these methods to GOT-MS and targeted metabolic profiling demonstrated that ts/ms-GOT-MS are significantly improved hybrid metabolomics methods and can be used as promising tools for future studies.

Metabolic shift of Staphylococcus aureus under sublethal dose of methicillin in the presence of glucose.

Traditional strategies in developing novel drugs to treat antibiotic-resistant S. aureus have not been very successful to date, therefore, there is an urgent need for creative usage of existing agents that can treat and control S. aureus infection. This study demonstrated that a combination of glucose and a sublethal dose of antibiotic can reduce the survivability of S. aureus in a glucose concentration-dependent manner. Mass spectrometry-based targeted metabolic profiling detected massive metabolic profile shift of both methicillin-susceptible and resistant S. aureus after methicillin and glucose co-treatment. The dramatic alteration of metabolites from these metabolic pathways can be detected when 10 mg/L or higher concentration of glucose were added to methicillin treated culture. Our data also indicated that multiple biochemical metabolic pathways, including pyrimidine metabolism and valine, leucine, and isoleucine degradation showed a significant difference (p < 0.01) in comparison of control groups to glucose treatment groups. Taken together, this pilot study suggested that exogenous glucose in combination with a sublethal dose of antibiotics can disturb the metabolism of both methicillin-susceptible and resistant S. aureus, and enhance the antibiotic bactericidal effect.

A quantitative metabolomics study of bacterial metabolites in different domains.

Absolute metabolite concentrations are essential information for quantitative metabolomics studies, as concentrations are closely related to metabolic reactions, enzyme kinetics and other important biological activities. A well-performed metabolites extraction procedure, a reliable detection method, and a robust quantitative approach are all critical factors for obtaining absolute metabolite concentrations. Here, we used a HPLC-MS/MS based platform to successfully develop a 13C-labeled quantitative metabolomics approach, and applied this novel method to quantify bacterial metabolite concentrations in three different domains (i.e., intracellularly, extracellularly and to the whole culture), with high accuracy for a model Escherichia coli bacteria. The bacterial culture was grown in universal 13C-labeled medium and the metabolites were extracted by 40/40/20/methanol/ACN/H2O with 0.1% formic acid. One hundred and twenty-five metabolites were initially screened and one hundred and six 13C metabolites were confidently detected from the model bacteria grown in 13C-labeled medium. A subset of twenty-one metabolites was subsequently quantified using 12C-metabolite chemical standards to assist the calculation of 13C metabolite concentration. This rigorous 13C-labled quantitative method was then applied to characterize the metabolic profile changes in three domains of E. coli going through antibiotic treatment. Our results demonstrated that metabolites from all three domains can be used to significantly differentiate the ampicillin treatment group and control group (without ampicillin). In conclusion, our work demonstrated that the quantitative metabolomics approach can be used as a valuable tool to study bacterial metabolism in different domains and to understand their response to environmental perturbations.

Rapid differentiation of Lactobacillus species via metabolic profiling.

Lactobacillus, the major genus of lactic acid bacteria group, plays functional roles in the human body, for example, convert sugars to lactic acid. They are the significant microbiota which can be found at a number of human body sites, such as the digestive system, urinary system, and genital system. A number of Lactobacillus species are often used as probiotics and can benefit host health when administered in adequate amounts. Due to their diverse functional characteristics, it is essential to have identification and high-resolution typing techniques to support the need in health and nutritional research of Lactobacillus species. In this study, we took advantages of both targeted and untargeted metabolomic technologies by using a triple quadrupole mass spectrometer (MS) in combination with a linear ion trap-Orbitrap hybrid MS, to investigate their capability and performance in deciphering the subtle metabolic difference in four closely related Lactobacillus species/strains. First, we evaluated the selected reaction monitoring (SRM) and high-resolution MS data for metabolite quantitation. Then the acquired data quality was further evaluated via the number of metabolites detected, the coefficient variation (CV) distribution, signal intensity distribution and so on. The established platforms were eventually applied to differentiate four Lactobacillus species in identical growth conditions. The proposed workflow demonstrated the capability of targeted and untargeted metabolomics in differentiating closely related bacterial strains/species.

Metabolic signature of the aging eye in mice.

Aging is a major risk factor for age-related ocular diseases including age-related macular degeneration in the retina and retinal pigment epithelium (RPE), cataracts in the lens, glaucoma in the optic nerve, and dry eye syndrome in the cornea. We used targeted metabolomics to analyze metabolites from young (6 weeks) and old (73 weeks) eyes in C57 BL6/J mice. Old mice had diminished electroretinogram responses and decreased number of photoreceptors in their retinas. Among the 297 detected metabolites, 45-114 metabolites are significantly altered in aged eye tissues, mostly in the neuronal tissues (retina and optic nerve) and less in cornea, RPE/choroid, and lens. We noted that changes of metabolites in mitochondrial metabolism and glucose metabolism are common features in the aged retina, RPE/choroid, and optic nerve. The aging retina, cornea, and optic nerve also share similar changes in Nicotinamide adenine dinucleotide (NAD), 1-methylnicotinamides, 3-methylhistidine, and other methylated metabolites. Metabolites in taurine metabolism are strikingly influenced by aging in the cornea and lens. In conclusion, the aging eye has both common and tissue-specific metabolic signatures. These changes may be attributed to dysregulated mitochondrial metabolism, reprogrammed glucose metabolism and impaired methylation in the aging eye. Our findings provide biochemical insights into the mechanisms of age-related ocular changes.

Comparative Metabolomics Elucidates Postprandial Metabolic Modifications in Plasma of Obese Individuals with Metabolic Syndrome.

Although higher intakes of dairy milk are associated with a lower risk of metabolic syndrome (MetS), the underlying protective mechanism remains unclear. This study investigated the dynamic metabolic profile shift following the ingestion of low-fat milk or an isocaloric volume of rice milk in obese individuals with metabolic syndrome (MetS). In a randomized, double-blind, crossover study, postprandial plasma samples ( n = 266) were collected from 19 MetS participants. Plasma samples were analyzed by a targeted metabolomics platform which specifically detects 117 metabolites from 25 metabolic pathways. The comprehensive time-course metabolic profiling in MetS participants indicated that the postprandial metabolic profiles distinguish low-fat milk and rice milk consumption in a time-dependent manner. Metabolic biomarkers, such as orotate, leucine/isoleucine and adenine, showed significantly different trends in the two test beverages. Bayesian statistics identified 12 metabolites associated with clinical characteristics of postprandial vascular endothelial function, such as flow-mediated dilation (FMD), postprandial plasma markers of oxidative stress and NO status. Furthermore, metabolic pathway analysis based on these metabolite data indicated the potential utility of metabolomics to provide mechanistic insights of dietary interventions to regulate postprandial metabolic excursions.

Comparative metabolomics revealing Staphylococcus aureus metabolic response to different antibiotics.

It is known that changes in bacterial metabolism can contribute to the modulation of bacterial susceptibility to antibiotics. Understanding how bacterial metabolism is impacted by antibiotics may improve our understanding of the antibiotic mechanism of actions from a metabolic perspective. Here, we utilized a mass spectrometry-based targeted metabolic profiling technique to characterize the metabolome of a pair of isogenic methicillin-susceptible and resistant Staphylococcus aureus (MSSA and MRSA) strains RN450 and 450M treated with the sublethal dose of three antibiotics from different classes (ß-lactams, aminoglycosides and quinolones). These treatments induced a set of metabolic alterations after 6 h of co-incubation with antibiotics. Similar and divergent metabolic perturbations were observed from different antibiotics to the tested strains. Different metabolic response from MSSA and MRSA to the same antibiotics was also detected in the study and indicated the potentially different stress response mechanism in MSSA and MRSA metabolism. This work has shown that a complex set of metabolic changes can be induced by a variety of antibiotics, and the comparative metabolomics strategy can provide a good understanding of this process from a metabolic perspective.

Comparing the impact of ultrafine particles from petrodiesel and biodiesel combustion to bacterial metabolism by targeted HPLC-MS/MS metabolic profiling.

Alterations of gut bacterial metabolism play an important role in their host metabolism, and can result in diseases such as obesity and diabetes. While many factors were discovered influencing the gut bacterial metabolism, exposure to ultrafine particles (UFPs) from engine combustions were recently proposed to be a potential risk factor for the perturbation of gut bacterial metabolism, and consequentially to obesity and diabetes development. This study focused on evaluation of how UFPs from diesel engine combustions impact gut bacterial metabolism. We hypothesize that UFPs from different type of diesel (petrodiesel vs. biodiesel) will both impact bacterial metabolism, and the degree of impact is also diesel type-dependent. Targeted metabolic profiling of 221 metabolites were applied to three model gut bacteria in vitro, Streptococcus salivarius, Lactobacillus acidophilus and Lactobacillus fermentum. UFPs from two types of fuels, petrodiesel (B0) and a biodiesel blend (B20: 20% soy biodiesel/80% B0 by volume), were exposed to the bacteria and their metabolic changes were compared. For each bacterial strain, metabolites with significantly changed abundance were observed in both perturbations, and all three strains have increased number of altered metabolites detected from B20 UFPs perturbation in comparison to B0 UFPs. Multivariate statistical analysis further confirmed that the metabolic profiles were clearly different between testing groups. Metabolic pathway analyses also demonstrated several important metabolic pathways, including pathways involves amino acids biosynthesis and sugar metabolism, were significantly impacted by UFPs exposure.

Targeted High Performance Liquid Chromatography Tandem Mass Spectrometry-based Metabolomics differentiates metabolic syndrome from obesity.

Both obesity and the metabolic syndrome are risk factors for type 2 diabetes and cardiovascular disease. Identification of novel biomarkers are needed to distinguish metabolic syndrome from equally obese individuals in order to direct them to early interventions that reduce their risk of developing further health problems. We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established metabolic syndrome criteria (i.e. elevated waist circumference, hypertension, elevated fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol) in plasma samples from obese men ( n = 29; BMI = 35.5 ± 5.2 kg/m2) and women ( n = 40; 34.9 ± 6.7 kg/m2), of which 26 met the criteria for metabolic syndrome (17 men and 9 women). Compared to obese individuals without metabolic syndrome, univariate statistical analysis and partial least squares discriminant analysis showed that a specific group of metabolites from multiple metabolic pathways (i.e. purine metabolism, valine, leucine and isoleucine degradation, and tryptophan metabolism) were associated with the presence of metabolic syndrome. Receiver operating characteristic curves generated based on the PLS-DA models showed excellent areas under the curve (0.85 and 0.96, for metabolites only model and enhanced metabolites model, respectively), high specificities (0.86 and 0.93), and good sensitivities (0.71 and 0.91). Moreover, principal component analysis revealed that metabolic profiles can be used to further differentiate metabolic syndrome with 3 versus 4-5 metabolic syndrome criteria. Collectively, these findings support targeted metabolomics approaches to distinguish metabolic syndrome from obesity alone, and to stratify metabolic syndrome status based on the number of criteria met. Impact statement We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established MetS criteria. To our best knowledge, the findings of this study provide the first evidence that metabolic profiles can be used to differentiate participants with MetS from similarly obese individuals who do not meet established criteria of MetS. Furthermore, the study demonstrated that within MetS participants, their unique metabolic profiles correlated to the number of criteria used for MetS determination. Taken together, this metabolic profiling approach can potentially serve as a novel tool for MetS detection and monitoring, and provide useful metabolic information for future interventions targeting obesity and MetS.

Evaluating metabolic response to light exposure in Lactobacillus species via targeted metabolic profiling.

This study reported metabolic profiles of three representative strains from Lactobacillus species, and explored their metabolic response to visible light exposure. We utilized strains from three Lactobacillus species, Lactobacillus acidophilus, Lactobacillus fermentum and Lactobacillus delbrueckii as our model bacteria and applied mass spectrometry base targeted metabolomics to specifically investigate 221 metabolites within multiple metabolic pathways. Similar and diverse metabolome from three tested strains were discovered. Furthermore, all three Lactobacillus strains demonstrated different metabolic profiles in comparison between light expose verse control. In all three strains, 12 metabolites were detected to have significant differences (p-value<0.01) in light exposure culture compared to the control samples (culture grown without light exposure). Principal components analysis using these significantly changed metabolites clearly separated the exposure and control groups in all three studied Lactobacillus strains. Additionally, metabolic pathway impact analysis indicated that several commonly impacted pathways can be observed.

Development and validation of a liquid chromatography/tandem mass spectrometry assay for the simultaneous determination of dabigatran etexilate, intermediate metabolite and dabigatran in 50µL rat plasma and its application to pharmacokinetic study.

A simple, rapid and specific high performance liquid chromatography-electrospray ionization tandem mass spectrometry method was developed for simultaneous determination of dabigatran etexilate (BIBR 1048 MS), the intermediate metabolite (BIBR 1087 SE) and dabigatran (BIBR 953 ZW). In this method, a stacked protein precipitation with methanol was performed in Sirocco 96-well filtration plates to extract analytes using only 50µL plasma. The analysis was performed on an Ultimate TM XB-C18 (4.6×50mm, 5µm) column using gradient elution with a mobile phase composed of methanol containing 0.01% formic acid and pure water at a flow rate of 0.3mL/min. The gradient was set to 90% methanol containing 0.01% formic acid for the first 1.0min, after which it dropped to 10%, and then was kept at 10% for the next 5min followed by an additional 1.0min at the initial composition of 90% methanol containing 0.01% formic acid for equilibration. Detection was performed on a triple-quadrupole mass spectrometer electrospray ionization interface in positive ion mode. Linear calibration curves were obtained over the concentration ranges of 1-500ng/mL for all analytes. The validated LC-MS/MS method for its selectivity, sensitivity, linearity, precision, accuracy, recovery, matrix effect and stability had been successfully applied to a pharmacokinetic study of analytes in rat plasma following a single oral administration of 15mg/kg dabigatran etexilate.

Isolation and purification of diastereoisomeric flavonolignans from silymarin by binary-column recycling preparative high-performance liquid chromatography.

Silymarin extracted from Silybum marianum (L.) Gaertn consists of a large number of flavonolignans, of which diastereoisomeric flavonolignans including silybin A and silybin B, and isosilybin A and isosilybin B are the main bioactive components, whose preparation from the crude extracts is still a difficult task. In this work, binary-column recycling preparative high-performance liquid chromatography systems without sample loop trapping, where two columns were switched alternately via one or two six-port switching valves, were established and successfully applied to the isolation and purification of the four diastereoisomeric flavonolignans from silymarin. The proposed system showed significant advantages over conventional preparative high-performance liquid chromatography with a single column in increasing efficiency and reducing the cost. To obtain the same amounts of products, the proposed system spends only one tenth of the time that the conventional system spends, and needs only one eleventh of the solvent that the conventional system consumes. Using the proposed system, the four diastereoisomers were successfully isolated from silymarin with purities over 98%.