Metabolomic investigation of human diseases biomarkers by CE and LC coupled to MS

Metabolomics Data Treatment: Basic Directions of the Full Process

The present chapter describes basic aspects of the main steps for data processing on mass spectrometry-based metabolomics platforms, focusing on the main objectives and important considerations of each step. Initially, an overview of metabolomics and the pivotal techniques applied in the field are presented. Important features of data acquisition and preprocessing such as data compression, noise filtering, and baseline correction are revised focusing on practical aspects. Peak detection, deconvolution, and alignment as well as missing values are also discussed. Special attention is given to chemical and mathematical normalization approaches and the role of the quality control (QC) samples. Methods for uni- and multivariate statistical analysis and data pretreatment that could impact them are reviewed, emphasizing the most widely used multivariate methods, i.e., principal components analysis (PCA), partial least squares-discriminant analysis (PLS-DA), orthogonal partial least square-discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Criteria for model validation and softwares used in data processing were also approached. The chapter ends with some concerns about the minimal requirements to report metadata in metabolomics.

Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury.

Setting: Outpatient sports medicine clinic.

Participants: Twenty-six male youth sport participants.

Methods: Urine was analyzed pre-injury and after SRC by ¹H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome.

Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036).

Conclusion: We found that ¹H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Metabolomic Profiling of Poor Ovarian Response Identifies Potential Predictive Biomarkers

OBJECTIVE

To characterize the serum metabolomic profile and its role in the prediction of poor ovarian response (POR).

PATIENTS

Twenty-five women with normal ovarian reserve (24-33 years, antral follicle count [AFC] ≥5, anti-Müllerian hormone [AMH] ≥1.2 ng/ml) as the control group and another twenty-five women with POR (19-35 years, AFC <5, AMH < 1.2 ng/ml) as the study group were collected in our study. The serum levels of the women in both groups were determined from their whole blood by untargeted liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analysis and cell signal pathways analysis were used to reveal the results.

RESULTS

A total of 538 different metabolites were finally identified in the two groups. Tetracosanoic acid, 2-arachidonoylglycerol, lidocaine, cortexolone, prostaglandin H2,1-naphthylamine, 5-hydroxymethyl-2-furancarboxaldehyde, 2,4-dinitrophenol, and D-erythrulose1-phosphate in POR were significantly different from control as were most important metabolites in support vector machines (p <0.05). Metabolomic profiling, together with support vector machines and pathway analysis found that the nicotinate and nicotinamide metabolism pathway, including L-aspartic acid, 6-hydroxynicotinate, maleic acid, and succinic acid semialdehyde, was identified to have significant differences in POR women compared to control women, which may be associated with ovarian reserve.

CONCLUSION

This study indicated that LC-MS-based untargeted metabolomics analysis of serum provided biological markers for women with POR. The nicotinate and nicotinamide metabolism pathway may offer new insight into the complementary prediction and therapeutic potential of POR. The functional associations of these metabolites need further investigation.

Serum TEM5 and TEM7 concentrations correlate with clinicopathologic features and poor prognosis of colorectal cancer patients

PURPOSE

Colorectal cancer (CRC) is a serious threat worldwide; therefore, discovering sensitive and specific serum biomarkers for early stages of CRC is a great challenge. In this study, we evaluated whether tumour endothelial marker 5 (TEM5) and 7 (TEM7) circulating in blood serum can be useful as blood-based markers for detection, progression, and prognosis in CRC patients. Moreover, their specificity and sensitivity in the early diagnosis of CRC were compared with common carcinoma diagnostic markers, i.e. CEA and Ca 19-9.

MATERIALS AND METHODS

The study included 45 CRC patients and 35 healthy individuals. The serum concentration of TEM5 and TEM7 were quantified using sandwich ELISA.

RESULTS

The mean TEM5 and TEM7 serum concentrations were statistically significantly higher in the CRC patients than in the healthy controls. Moreover, the mean TEM5 and TEM7 concentrations were statistically significantly higher in the serum of patients with late stage (III/IV) compared to early stage (I/II) cancer. The TEM5 and TEM7 values increased along the development of the T, N, and M stages. The TEM5 and TEM7 sensitivity and specificity in CRC detection were higher than routinely used blood markers (CEA, Ca19-9). The high TEM5 and TEM7 concentrations were associated with worse overall survival compared to CRC patients of low TEM5 and TEM7 concentrations.

CONCLUSIONS

Taken together, these findings suggest that TEM5 and TEM7 serum concentrations can be considered as useful biomarkers for the detection of CRC patients and for monitoring cancer progression and identifying patients with a high possibility of poor survival.

Metabolomics Biomarkers for Detection of Colorectal Neoplasms: A Systematic Review

BACKGROUND

Several approaches have been suggested to be useful in the early detection of colorectal neoplasms. Since metabolites are closely related to the phenotype and are available from different human bio-fluids, metabolomics are candidates for non-invasive early detection of colorectal neoplasms.

OBJECTIVES

We aimed to summarize current knowledge on performance characteristics of metabolomics biomarkers that are potentially applicable in a screening setting for the early detection of colorectal neoplasms.

DESIGN

We conducted a systematic literature search in PubMed and Web of Science and searched for biomarkers for the early detection of colorectal neoplasms in easy-to-collect human bio-fluids. Information on study design and performance characteristics for diagnostic accuracy was extracted.

RESULTS

Finally, we included 41 studies in our analysis investigating biomarkers in different bio-fluids (blood, urine, and feces). Although single metabolites mostly had limited ability to distinguish people with and without colorectal neoplasms, promising results were reported for metabolite panels, especially amino acid panels in blood samples, as well as nucleosides in urine samples in several studies. However, validation of the results is limited.

CONCLUSIONS

Panels of metabolites consisting of amino acids in blood and nucleosides in urinary samples might be useful biomarkers for early detection of advanced colorectal neoplasms. However, to make metabolomic biomarkers clinically applicable, future research in larger studies and external validation of the results is required.

Recent advances in CE and microchip-CE in clinical applications: 2014 to mid-2017

CE and microchip CE (ME) are powerful tools for the analysis of a number of different analytes and have been applied to a variety of clinical fields and human samples. This review will present an overview of the most recent applications of these techniques to different areas of clinical medicine during the period of 2014 to mid-2017. CE and ME have been applied to clinical chemistry, drug detection and monitoring, hematology, infectious diseases, oncology, endocrinology, neonatology, nephrology, and genetic screening. Samples examined range from serum, plasma, and urine to lest utilized materials such as tears, cerebral spinal fluid, sweat, saliva, condensed breath, single cells, and biopsy tissue. Examples of clinical applications will be given along with the various detection systems employed.

Metabolomic findings in sepsis as a damage of host-microbial metabolism integration

Metabolomics globally evaluates the totality of the endogenous metabolites in patient's body, at the same time reflecting gene function, enzyme activity and degree of organ dysfunction in sepsis. The authors performed the analysis of the main chemical classes of low molecular weight compounds (amino acids, polyols, fatty acids, hydroxy acids, amines, nucleotides and their derivatives) that quantitatively distinguish patients with sepsis from healthy ones. The following keywords were used to find papers published in the Scopus and Web of Science databases from 2008 to 2015: (marker OR biomarker) AND (sepsis OR critical ill OR pneumonia OR hypoxia). Key words for the search were the following: metabolomics, metabolic profiling, sepsis, metabolism, biomarkers, critically ill patients, multiple organ failure. Several metabolomic findings in sepsis are still waiting for an explanation. When assessing metabolomic analysis results in patients with sepsis we should take into account the intervention of microbial metabolism. Among the low molecular weight compounds detected in septic patient blood, a special attention should be paid to the molecules which could be attributed to "common metabolites" of man and bacteria. The genomic region overlap and the production of enzymes which are similar in function and final products could be a possible reason for this phenomenon. For example, microbial biodegradation products of aromatic compounds are increased many times in blood of patients with sepsis. On the one hand, it shows a high metabolic activity of the bacteria. On the other hand, these molecules are intermediates in the metabolism of aromatic amino acids such as tyrosine and phenylalanine in human body. It is important that there are many clinical studies, which confirmed the diagnostic and prognostic significance of series of aromatic metabolites, including those with intrinsic biological activity. We can't exclude the presence of signaling pathways, cell receptors, transmembrane transporters and others which are common for a human and bacteria and their direct participation in mechanisms of organ dysfunction and hypotension in sepsis. Thus, today, we should not limit ourselves studying eukaryotic cells while searching for new molecular mechanisms of sepsis-associated organ failure and septic shock. We should take into account and simulate in the experiments the changes of a human internal environment, which occur during the radical microbiome "restructuring" in critically ill patients. This approach opens up new prospects for an objective monitoring of diseases, carrying out an assessment of the integral metabolic profile in a given time on common metabolites (particularly aromatic), and in future will provide new targets for therapeutic effects.

Metabolic Profiling of Liver Tissue in Diabetic Mice Treated with Artemisia Capillaris and Alisma Rhizome Using LC-MS and CE-MS

Artemisia Capillaris (AC) and Alisma Rhizome (AR) are natural products for the treatment of liver disorders in oriental medicine clinics. Here, we report metabolomic changes in the evaluation of the treatment effects of AC and AR on fatty livers in diabetic mice, along with a proposition of the underlying metabolic pathway. Hydrophobic and hydrophilic metabolites extracted from mouse livers were analyzed using HPLC-QTOF and CE-QTOF, respectively, to generate metabolic profiles. Statistical analysis of the metabolites by PLS-DA and OPLA-DA fairly discriminated between the diabetic, and the AC- and AR-treated mice groups. Various PEs mostly contributed to the discrimination of the diabetic mice from the normal mice, and besides, DG (18:1/16:0), TG (16:1/16:1/20:1), PE (21:0/20:5), and PA (18:0/21:0) were also associated with discrimination by s-plot. Nevertheless, the effects of AC and AR treatment were indistinct with respect to lipid metabolites. Of the 97 polar metabolites extracted from the CE-MS data, 40 compounds related to amino acid, central carbon, lipid, purine, and pyrimidine metabolism, with [Formula: see text] values less than 0.05, were shown to contribute to liver dysregulation. Following treatment with AC and AR, the metabolites belonging to purine metabolism preferentially recovered to the metabolic state of the normal mice. The AMP/ATP ratio of cellular energy homeostasis in AR-treated mice was more apparently increased ([Formula: see text]) than that of AC-treated mice. On the other hand, amino acids, which showed the main alterations in diabetic mice, did not return to the normal levels upon treatment with AR or AC. In terms of metabolomics, AR was a more effective natural product in the treatment of liver dysfunction than AC. These results may provide putative biomarkers for the prognosis of fatty liver disorder following treatment with AC and AR extracts.

Effectiveness of an individualized program of muscular strength and endurance with aerobic training for improving germ cell cancer-related fatigue in men undergoing chemotherapy: EFICATEST study protocol for a randomized controlled trial

Background

Patients with testicular germ cell cancer (GCC) have a high cure rate; however, cancer-related fatigue is the most common complication among patients with GCC undergoing treatment with chemotherapy. Although exercise is widely recommended, information about the physio-pathological effects of cancer therapy on skeletal muscle is very limited. Our aim is to evaluate the effects of an individualized program of muscular strength and endurance with aerobic training on cancer-related fatigue.

Methods/Design

The present study is a randomized controlled trial comparing an individualized program of muscular strength and endurance with aerobic training compared to a control group. We will conduct this trial in patients undergoing chemotherapy, recruited by the Department of Oncology of Virgen de la Victoria Hospital (Málaga). Patients will be included and evaluated before the first cycle of chemotherapy and assigned randomly to the experimental or control group. Cancer-related fatigue, physical condition and biological samples will be measured at the beginning and at the end of an 8-week intervention by the same evaluator, who will be unaware of the allocation of participants to each group. Furthermore, there will be monitoring for 6 months (24 weeks) after training for all outcome variables.

Discussion

This study hopes to offer patients with GCC an individualized exercise program with aerobic training for cancer-related fatigue. Such a scheme, if beneficial, could be implemented successfully within public health.

Trial registration

ClinicalTrials.gov Identifier: NCT02433197. Date of registration: 13 April 2015.

Metabolomics of adherent mammalian cells by capillary electrophoresis-mass spectrometry: HT-29 cells as case study

In this work, the optimization of an effective protocol for cell metabolomics is described with special emphasis in the sample preparation and subsequent analysis of intracellular metabolites from adherent mammalian cells by capillary electrophoresis-mass spectrometry. As case study, colon cancer HT-29 cells, a human cell model to investigate colon cancer, are employed. The feasibility of the whole method for cell metabolomics is demonstrated via a fast and sensitive profiling of the intracellular metabolites HT-29 cells by capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF MS). The suitability of this methodology is further corroborated through the examination of the metabolic changes in the polyamines pathway produced in colon cancer HT-29 cells by difluoromethylornithine (DFMO), a known potent ornithine decarboxylase inhibitor. The selection of the optimum extraction conditions allowed a higher sample volume injection that led to an increase in CE-TOF MS sensitivity. Following a non-targeted metabolomics approach, 10 metabolites (namely, putrescine, ornithine, gamma-aminobutyric acid (GABA), oxidized and reduced glutathione, 5'-deoxy-5'-(methylthio)adenosine, N-acetylputrescine, cysteinyl-glycine, spermidine and an unknown compound) were found to be significantly altered by DFMO (p<0.05) in HT-29 cells. In addition to the effect of DFMO on polyamine metabolism, minor modifications of other metabolic pathways (e.g., related to intracellular thiol redox state) were observed.

The emergence of metabolomics as a key discipline in the drug discovery process

Metabolomics is a recent science that could be defined as the comprehensive qualitative and quantitative analysis of all small molecular weight compounds present in a cell, organ (including biofluids) or organism at a specific time point. More and more applications have been found these past years to metabolomics in the pharmaceutical field. Specifically in the drug discovery process, metabolomics open new perspectives, in new targets identification, in toxicological studies and in bioactive natural products discovery. The challenge in metabolomics is to find a technological approach allowing the reproducible identification and quantitation of as much metabolites as possible. In this context, mass spectrometry and NMR are emerging as key and complementary technologies.