Juan Carlos García-Cañaveras

Targeted profiling of circulating and hepatic bile acids in human, mouse, and rat using a UPLC-MRM-MS-validated method

Bile acids (BAs) are a group of chemically related steroids recognized as regulatory molecules whose profiles can change in different physio-pathological situations. We have developed a sensitive, fast, and reproducible ultraperformance liquid chromatography/multiple reaction monitoring/mass spectrometry method to determine the tissue and sera BA profiles in different species (human, rat, and mouse) by quantifying 31 major and minor BA species in a single 21-min run. The method has been validated according to FDA guidelines, and it generally provides good results in terms of intra- and interday precision (less than 8.6% and 16.0%, respectively), accuracy (relative error measurement between –11.9% and 8.6%), and linearity (R2 > 0.996 and dynamic ranges between two and four orders of magnitude), with limits of quantification between 2.5 and 20 nM. The new analytical approach was applied to determine BA concentrations in human, rat, and mouse serum and in liver tissue. Our comparative study confirmed and extended previous reports, showing marked interspecies differences in circulating and hepatic BA composition. The targeted analysis revealed the presence of unexpected minoritary BAs, such as tauro-alpha-Muricholic acid in human serum, thus allowing us to obtain a thorough profiling of human samples. Its great sensitivity, low sample requirements (25 µl of serum, 5 mg of tissue), and comprehensive capacity to profile a considerable number of BAs make the present method a good choice to study BA metabolism in physiological and pathological situations, particularly in toxicological studies.

Mammalian cell metabolomics: Experimental design and sample preparation

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics field involves harder sample processing methods, including metabolism quenching and metabolite extraction, as compared to the use of body fluids, although such critical issues are frequently overlooked. This review aims to overview the common experimental procedures used in mammalian cell metabolomics based on mass spectrometry, by placing special emphasis on discussing sample preparation approaches, although other aspects, such as cell metabolomics applications, culture systems, cellular models, analytical platforms, and data analysis, are also briefly covered. This review intends to be a helpful tool to assist researchers in addressing decisions when planning a metabolomics study involving the use of mammalian cells.

A Comprehensive Untargeted Metabonomic Analysis of Human Steatotic Liver Tissue by RP and HILIC Chromatography Coupled to Mass Spectrometry Reveals Important Metabolic Alterations

Steatosis, or excessive accumulation of lipids in the liver, is a generally accepted previous step to the development of more severe conditions like nonalcoholic steatohepatitis, fibrosis, and cirrhosis. We aimed to characterize the metabolic profile that defines simple steatosis in human tissue and to identify potential disturbances in the hepatic metabolism that could favor the switch to progressive liver damage. A total of 46 samples, 23 from steatotic and 23 from nonsteatotic human livers, were analyzed following a holistic LC-MS-based metabonomic analysis that combines RP and HILIC chromatographic separations. Multivariate statistical data analysis satisfactorily classified samples and revealed steatosis-associated biomarkers. Increased levels of bile acids and phospholipid degradation products, and decreased levels of antioxidant species, were found in steatotic livers, indicating disturbances in lipid and bile acid homeostasis and mitochondrial dysfunction. Changes in hypoxanthine, creatinine, glutamate, glutamine, or γ-glutamyl-dipeptides concentrations, suggestive of alterations in energy metabolism and amino acid metabolism and transport, were also found. The results show that the proposed analytical strategy is suitable to achieve a comprehensive metabolic profile of steatotic human liver tissue and provide new insights into the metabolic alterations occurring in fatty liver that could contribute to its predisposition to damage evolution.

Chemometric approaches to improve PLSDA model outcome for predicting human non-alcoholic fatty liver disease using UPLC-MS as a metabolic profiling tool

An MS-based metabolomics strategy including variable selection and PLSDA analysis has been assessed as a tool to discriminate between non-steatotic and steatotic human liver profiles. Different chemometric approaches for uninformative variable elimination were performed by using two of the most common software packages employed in the field of metabolomics (i.e., MATLAB and SIMCA-P). The first considered approach was performed with MATLAB where the PLS regression vector coefficient values were used to classify variables as informative or not. The second approach was run under SIMCA-P, where variable selection was performed according to both the PLS regression vector coefficients and VIP scores. PLSDA models performance features, such as model validation, variable selection criteria, and potential biomarker output, were assessed for comparison purposes. One interesting finding is that variable selection improved the classification predictiveness of all the models by facilitating metabolite identification and providing enhanced insight into the metabolic information acquired by the UPLC-MS method. The results prove that the proposed strategy is a potentially straightforward approach to improve model performance. Among others, GSH, lysophospholipids and bile acids were found to be the most important altered metabolites in the metabolomic profiles studied. However, further research and more in-depth biochemical interpretations are needed to unambiguously propose them as disease biomarkers.

Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction

BACKGROUND & AIMS Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. METHODS A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. RESULTS A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). CONCLUSIONS A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant.

LC-MS untargeted metabolomic analysis of drug-induced hepatotoxicity in HepG2 cells.

Hepatotoxicity is the number one cause for agencies not approving and withdrawing drugs for the market. Drug‐induced human hepatotoxicity frequently goes undetected in preclinical safety evaluations using animal models. Human‐derived in vitro models represent a common alternative to in vivo tests to detect toxic effects during preclinical testing. Most current in vitro toxicity assays rely on the measurement of nonspecific or low sensitive endpoints, which result in poor concordance with human liver toxicity. Therefore, making more accurate predictions of the potential hepatotoxicity of new drugs remains a challenge. Metabolomics, whose aim is to globally assess all the metabolites present in a biological sample, may represent an alternative in the search for sensitive sublethal markers of drug‐induced hepatotoxicity. To this end, a comprehensive LC‐MS‐based untargeted metabolite profiling analysis of HepG2 cells, exposed to a set of well‐described model hepatotoxins and innocuous compounds, was performed. It allowed to determine meaningful metabolic changes triggered by a toxic insult and gave a first estimation of the main toxicity‐related pathways. Based on these metabolic patterns, a partial least squares‐discriminant analysis model, able to discriminate between nontoxic and hepatotoxic compounds, was constructed. The approach described herein may provide an alternative for animal testing in preclinical stages of drug development and a controlled experimental approach to gain a better understanding of the underlying causes of hepatotoxicity.

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

AbstractMS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (−) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids. Graphical abstractA novel analytical workflow for the LC-MS-based metabolomic analysis of adherent cultured hepatic cells was developed. Three key steps were evaluated: a) cell harvesting, which includes cell detachment and metabolism quenching; b) metabolite extraction; and c) LC-MS analysis, assessing the use of RP and HILIC chromatographies. The final protocol allowed us to extend the metabolome coverage and enabled the detection of a wide range of metabolites from highly polar compounds to a wide range of lipids

A lipidomic cell-based assay for studying drug-induced phospholipidosis and steatosis

Phospholipidosis and steatosis are two toxic effects, which course with overaccumulation of different classes of lipids in the liver. MS‐based lipidomics has become a powerful tool for the comprehensive determination of lipids. LC‐MS lipid profiling of HepG2 cells is proposed as an in vitro assay to study and anticipate phospholipidosis and steatosis. Cells with and without preincubation with a mixture of free fatty acids (FFA; i.e. oleic and palmitic) were exposed to a set of well‐known steatogenic and phospholipidogenic compounds. The use of FFA preloading accelerated the accumulation of phospholipids, thus leading to a better discrimination of phospholipidosis, and magnified the lipidomic alterations induced by steatogenic drugs. Phospholipidosis was characterized by increased levels of phosphatidylcholines, phosphatidylethanolamines, phosphatidylserines, and phosphatidylinositols, while steatosis induced alterations in FA oxidation and triacylglyceride (TG) synthesis pathways (with changes in the levels of FFA, acylcarnitines, monoacylglycerides, diacylglycerides, and TG). Interestingly, palmitic and oleic acids incorporation into lipids differed. A characteristic pattern was observed in the fold of change of particular TG species in the case of steatosis (TG(54:3) > TG(52:2) > TG(50:1) > TG(48:0)). Based on the levels of those lipids containing only palmitic and/or oleic acid moieties a partial least squares‐discriminant analysis model was built, which showed good discrimination among nontoxic, phospholipidogenic and steatogenic compounds. In conclusion, it has been shown that the use of FFA preincubation together with intracellular LC‐MS based lipid profiling could be a useful approach to identify the potential of drug candidates to induce phospholipidosis and/or steatosis.

Ultra-performance liquid chromatography-mass spectrometry targeted profiling of bile acids: application to serum, liver tissue, and cultured cells of different species.

Currently, there is increasing interest in developing accurate methods for the quantitative analysis of bile acids (BAs) in biological samples. We have developed a sensitive, fast, and reproducible UPLC-MRM-MS method for BA profiling in serum, liver tissue, or cultured cells of different species (human, rat, and mouse). This method, validated according to FDA guidelines, allows the quantification of 12 non-conjugated, 8 glycine-conjugated, and 11 taurine-conjugated BAs, using 5 additional deuterated BAs as internal standards in a single analytical run. The main features of this analytical approach are its high sensitivity, low sample requirements, versatility, and comprehensive capacity to profile a considerable number of BAs in samples of different species, which make it a valuable tool with potential applications in many research areas focusing on BAs, particularly in toxicological studies.

RpeakChrom: Novel R package for the automated characterization and optimization of column efficiency in high-performance liquid chromatography analysis

Characterization of chromatographic columns using the traditional van Deemter method is limited by the necessity of calculating extra‐column variance, issue particularly relevant when modeling asymmetrical peaks eluted from monolithic columns. A novel R package that implements Parabolic Variance Modified Gaussian approach for accurate peak modeling, van Deemter equation and two alternatives approaches, based on van Deemter, has been developed to calculate the height equivalent to a theoretical plate (HETP). To assess package capabilities conventional packed reverse‐phase and monolithic HPLC columns were characterized. Peaks eluted from the monolithic column showed a high value of factor asymmetry due, in part, to the contribution of extra‐column factors. Such deviation can be circumvented by the two alternatives approaches implemented in the R‐package. Furthermore, increased values of eddy diffusion and mass transfer kinetics terms in HETP were observed for the packed column, while accuracy was below 9% in all cases. These results showed the usefulness of the R‐package for both modeling chromatographic peaks and assessing column efficiency. The RpeakChrom package could become a helpful tool for testing new stationary phases during column development and to evaluate column during its lifetime. This R tool is freely available from CRAN (https://CRAN.R-project.org/package=RpeakChrom).