GC-MS based metabolomics of colon cancer cells using different extraction solvents

Characterization of the gut microbiota and fecal metabolome in the osteosarcoma mouse model

Previous studies have reported the correlation between gut microbiota (GM), GM-derived metabolites, and various intestinal and extra-intestinal cancers. However, limited studies have investigated the correlation between GM, GM-derived metabolites, and osteosarcoma (OS). This study successfully established a female BALB/c nude mouse model of OS. Mice (n = 14) were divided into the following two groups (n = 7/group): OS group named OG, injected with Saos-2 OS cells; normal control group named NCG, injected with Matrigel. The GM composition and metabolites were characterized using 16S rDNA sequencing and untargeted metabolomics, respectively. Bioinformatics analysis revealed that amino acid metabolism was dysregulated in OS. The abundances of bone metabolism-related genera Alloprevotella, Rikenellaceae_RC9_gut_group, and Muribaculum were correlated with amino acid metabolism, especially histidine metabolism. These findings suggest the correlation between GM, GM-derived metabolites, and OS pathogenesis. Clinical significance: The currently used standard therapeutic strategies for OS, including surgery, chemotherapy, and radiation, are not efficacious. The findings of this study provided novel insights for developing therapeutic, diagnostic, and prognostic strategies for OS.

Intratumoral metabolic heterogeneity of colorectal cancer

Although the metabolic phenotype within tumors is known to differ significantly from that of the surrounding normal tissue, the importance of this heterogeneity is just becoming widely recognized. Colorectal cancer (CRC) is often classified as the Warburg phenotype, a metabolic type in which the glycolytic system is predominant over oxidative phosphorylation (OXPHOS) in mitochondria for energy production. However, this dichotomy (glycolysis vs. OXPHOS) may be too simplistic and not accurately represent the metabolic characteristics of CRC. Therefore, in this review, we decompose metabolic phenomena into factors based on their source/origin and reclassify them into two categories: extrinsic and intrinsic. In the CRC context, extrinsic factors include those based on the environment, such as hypoxia, nutrient deprivation, and the tumor microenvironment, whereas intrinsic factors include those based on subpopulations, such as pathological subtypes and cancer stem cells. These factors form multiple layers inside and outside the tumor, affecting them additively, dominantly, or mutually exclusively. Consequently, the metabolic phenotype is a heterogeneous and fluid phenomenon reflecting the spatial distribution and temporal continuity of these factors. This allowed us to redefine the characteristics of specific metabolism-related factors in CRC and summarize and update our accumulated knowledge of their heterogeneity. Furthermore, we positioned tumor budding in CRC as an intrinsic factor and a novel form of metabolic heterogeneity, and predicted its metabolic dynamics, noting its similarity to circulating tumor cells and epithelial-mesenchymal transition. Finally, the possibilities and limitations of using human tumor tissue as research material to investigate and assess metabolic heterogeneity are discussed.

Metabolomic Characterization of the Antiproliferative Activity of Bioactive Compounds from Fruit By-Products Against Colon Cancer Cells

This methodological work demonstrates the potential of metabolomic approaches based on liquid chromatography coupled to high-resolution mass spectrometry (LC-ESI(+/-)-HRMS) to investigate the antiproliferative capacity of underexplored biomasses (e.g., Passiflora mollissima seeds and Physalys peruviana calyx), by evaluating the molecular changes induced at the metabolite expression levels on HT-29 human colon cancer cells. This protocol describes in detail the optimal conditions to obtain bioactive extracts by pressurized liquid extraction (PLE), the experimental procedure to grow and treat HT-29 human colon cancer cells and CCD-18Co normal human colon fibroblasts with the target extracts, the metabolites extraction from the cytosolic fraction, and subsequent metabolomic fingerprinting. After treatment for 48 and 72 h, the viability of HT-29 colon cancer cells is markedly affected, and metabolites can be extracted for investigation. Following the proposed metabolomic data analysis and interpretation workflow, altered cellular redox homeostasis, as well as inactivation or dysfunction on other metabolic pathways, constitutes valuable biological information to understand the mechanisms underlying the antiproliferative effect.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Comparison of Lysis and Detachment Sample Preparation Methods for Cultured Triple-Negative Breast Cancer Cells Using UHPLC–HRMS-Based Metabolomics

Dysregulation of cellular metabolism is now a well-recognized hallmark of cancer. Studies investigating the metabolic features of cancer cells have shed new light onto processes in cancer cell biology and have identified many potential novel treatment options. The advancement of mass spectrometry-based metabolomics has improved the ability to monitor multiple metabolic pathways simultaneously in various experimental settings. However, questions still remain as to how certain steps in the metabolite extraction process affect the metabolic profiles of cancer cells. Here, we use ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC–HRMS) untargeted metabolomics to investigate the effects of different detachment and lysis methods on the types and abundances of metabolites extracted from MDA-MB-231 cells through the use of in-house standards libraries and pathway analysis software. Results indicate that detachment methods (trypsinization vs. scraping) had the greatest effect on metabolic profiles whereas lysis methods (homogenizer beads vs. freeze–thaw cycling) had a lesser, though still significant, effect. No singular method was clearly superior over others, with certain metabolite classes giving higher abundances or lower variation for each detachment–lysis combination. These results indicate the importance of carefully selecting sample preparation methods for cell-based metabolomics to optimize the extraction performance for certain compound classes.

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.

Microbial Metabolites in Colorectal Cancer: Basic and Clinical Implications

Colorectal cancer (CRC) is one of the leading cancers that cause cancer-related deaths worldwide. The gut microbiota has been proved to show relevance with colorectal tumorigenesis through microbial metabolites. By decomposing various dietary residues in the intestinal tract, gut microbiota harvest energy and produce a variety of metabolites to affect the host physiology. However, some of these metabolites are oncogenic factors for CRC. With the advent of metabolomics technology, studies profiling microbiota-derived metabolites have greatly accelerated the progress in our understanding of the host-microbiota metabolism interactions in CRC. In this review, we briefly summarize the present metabolomics techniques in microbial metabolites researches and the mechanisms of microbial metabolites in CRC pathogenesis, furthermore, we discuss the potential clinical applications of microbial metabolites in cancer diagnosis and treatment.

Metabolite profiling of chondrosarcoma cells: A robust GC-MS method for the analysis of endogenous metabolome

Chondrosarcoma is the 2nd most frequent bone sarcoma. In this study, the metabolic profiling of human chondrosarcoma SW-1353 cell line was investigated for the first time. To obtain more precise information about the metabolites from chondrosarcoma cells, pretreatment methods including washing steps/solvents, harvesting conditions, and extraction protocols for chondrosarcoma SW-1353 cells were evaluated in the context of metabolite profiling by GC-MS technique. In addition, a total of 32 representative metabolites (related to amino acid metabolism, TCA cycle, glycolysis, and fatty acid metabolism) were quantitatively determined. We found that a fast water rinse step before metabolic quenching, may reduce the contaminants and improve sensitivity. Trypsin/ethylene diamine tetraacetic acid treatment led to a large amount of metabolite leakage, which was not suitable for metabolomics research. Methanol was selected as a more suitable extraction solvent among four extraction approaches applied to SW-1353 cells. The final protocol can provide a simple, robust, and reproducible method to obtain precise information about the metabolites from chondrosarcoma cells, which is helpful to further understand the chondrosarcoma cell physiology and the mechanism of drug resistance in this disease, from the perspective of metabolomics.

Gas chromatography-mass spectrometry untargeted profiling of non-Hodgkin's lymphoma urinary metabolite markers

Non-Hodgkin's lymphoma (NHL) is a cancer of the lymphatic system where the lymphoid and hematopoietic tissues are infiltrated by malignant neoplasms of B, T, and natural killer lymphocytes. Effective and less invasive methods for NHL screening are urgently needed. Herein, we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to investigate metabolic changes in non-volatile derivatized compounds from urine samples of NHL patients (N = 15) and compare them to healthy controls (N = 34). Uni- and multivariate data analysis showed 18 endogenous metabolites, including amino acids and their metabolites, sugars, small organic acids, and vitamins, as statistically significant for group differentiation. A receiver operating characteristic curve (ROC) generated from a support vector machine (SVM) algorithm-based model achieved 0.998 of predictive accuracy, displaying the potential and relevance of GC-MS-detected urinary non-volatile compounds for predictive purposes. Furthermore, a specific panel of key metabolites was also evaluated, showing similar results. All in all, our results indicate that this robust GC-MS method is an effective screening tool for NHL diagnosis and it is able to highlight different pathways of the disease. Graphical Abstract.

Metabolomics analysis to evaluate the antibacterial activity of the essential oil from the leaves of Cinnamomum camphora (Linn.) Presl

ETHNOPHARMACOLOGY RELEVANCE

Cinnamomum camphora (Linn.) Presl (C. camphora) is one of the oldest herbal medicines used as a traditional medicine, owning a wide range of biological functions including anti-bacterial, anti-oxidative, anti-fungal, anti-inflammatory, insecticidal and repellent activities.

OBJECTIVE

The aim of this study was to investigate the antibacterial activity and mechanism of action of the essential oil (EO) from C. camphora.

MATERIALS AND METHODS

The EO was isolated from the leaves of C. camphora by hydrodistillation, and the chemical compositions of the EO were analyzed by gas chromatography-mass spectrometry (GC-MS). The minimum inhibitory concentration (MIC) and the minimal bactericidal concentration (MBC) values of the EO were estimated by the microbroth dilution method. Growth curve was investigated by turbidimetry. Apoptosis was measured by flow cytometry. Morphological change of bacteria was observed by field emission scanning electron microscopy and transmission electron microscopy. The integrity of cell membrane was evaluated by NanoDrop and BCA Protein Assay Kit. The methicillin-resistant Staphylococcus aureus (MRSA) metabolic profile in the presence of the EO was explored by GC-MS-based metabolomics. Isocitrate dehydrogenase (ICDH), α-ketoglutarate dehydrogenase (α-KGDH), succinic dehydrogenase (SDH) and malic dehydrogenase (MDH) activities were detected by commercial kits.

RESULTS

The main components of the EO from the leaves of C. camphora were identified to be linalool (26.6%), eucalyptol (16.8%), α-terpineol (8.7%), isoborneol (8.1%), β-phellandrene (5.1%), and camphor (5.0%). The EO had good activity against MRSA, Staphylococcus aureus, Enterococcus faecalis, Bacillus subtilis, Salmonella gallinarum and Escherichia coli. MRSA was selected as the model bacterium to illustrate antibacterial mechanism of action of the EO, and the MIC and MBC values was 0.8 and 1.6 mg/mL, respectively. Apoptosis rate of MRSA increased in a concentration-dependent manner after the addition of EO. The cell morphology was damaged by the EO. There were 74 significantly different metabolites, including 29 upregulated and 45 downregulated metabolites in the result of metabolomics evaluation. Seven pathways were enriched by shared differential metabolites. The EO enhanced the activity of ICDH by 47.35%, while weaken MDH, SDH and α-KGDH by 72.63%, 31.52% and 63.29%, respectively.

CONCLUSIONS

The EO from C. camphora showed anti-MRSA activity via damaging cell membranes and disturbing the amino metabolism.

Analysis of low-molecular-weight metabolites in stomach cancer cells by a simplified and inexpensive GC/MS metabolomics method

GC/MS coupled metabolomics analysis, using a simplified and much less expensive silylation process with trimethylsilyl cyanide (TMSCN), was conducted to investigate metabolic abnormalities in stomach cancer cells. Under optimized conditions for derivatization by TMSCN and methanol extraction, 228 metabolites were detected using GC/MS spectrometry analysis, and 89 metabolites were identified using standard compounds and the NIST database. Ten metabolite levels were found to be lower in stomach cancer cells relative to normal cells. Among those ten metabolites, four metabolites-ribose, proline, pyroglutamic acid, and glucose-were known to be linked to cancers. In particular, pyroglutamic acid level showed a drastic reduction of 22-fold in stomach cancer cells. Since glutamine and glutamic acid are known to undergo cyclization to pyroglutamic acid, the 22-fold reduction might be the actual reduction in the levels of glutamine and/or glutamic acid-both known to be cancer-related. Hence, the marked reduction in pyroglutamic acid level might serve as a biomarker to aid early detection of stomach cancer. Graphical abstract.

Comparative metabolomics of MCF-7 breast cancer cells using different extraction solvents assessed by mass spectroscopy

Metabolic profiling of cancer cells can play a vital role in revealing the molecular bases of cancer development and progression. In this study, gas chromatography coupled with mass spectrometry (GC-MS) was employed for the determination of signatures found in ER+/PR+ breast cancer cells derived from MCF-7 using different extraction solvents including: A, formic acid in water; B, ammonium hydroxide in water; C, ethyl acetate; D, methanol: water (1:1, v/v); and E, acetonitrile: water (1:1, v/v). The greatest extraction rate and diversity of metabolites occurs with extraction solvents A and E. Extraction solvent D showed moderate extraction efficiency, whereas extraction solvent B and C showed inferior metabolite diversity. Metabolite set enrichment analysis (MSEA) results showed energy production pathways to be key in MCF-7 cell lines. This study showed that mass spectrometry could identify key metabolites associated with cancers. The highest enriched pathways were related to energy production as well as Warburg effect pathways, which may shed light on how energy metabolism has been hijacked to encourage tumour progression and eventually metastasis in breast cancer.

An integrated approach for the valorization of mango seed kernel: Efficient extraction solvent selection, phytochemical profiling and antiproliferative activity assessment

A novel valorization strategy is proposed in this work for the sustainable utilization of a major mango processing waste (i.e. mango seed kernel, MSK), integrating green pressurized-liquid extraction (PLE), bioactive assays and comprehensive HRMS-based phytochemical characterization to obtain bioactive-rich fractions with high antioxidant capacity and antiproliferative activity against human colon cancer cells. Thus, a two steps PLE procedure was proposed to recover first the non-polar fraction (fatty acids and lipids) and second the polar fraction (polyphenols). Efficient selection of the most suitable solvent for the second PLE step (ethanol/ethyl acetate mixture) was based on the Hansen solubility parameters (HSP) approach. A comprehensive GC- and LC-Q-TOF-MS/MS profiling analysis allowed the complete characterization of the lipidic and phenolic fractions obtained under optimal condition (100% EtOH at 150 °C), demonstrating the abundance of oleic and stearic acids, as well as bioactive xanthones, phenolic acids, flavonoids, gallate derivatives and gallotannins. The obtained MSK-extract exhibited higher antiproliferative activity against human colon adenocarcinoma cell line HT-29 compared to traditional extraction procedures described in literature for MSK utilization (e.g. Soxhlet), demonstrating the great potential of the proposed valorization strategy as a valuable opportunity for mango processing industry to deliver a value-added product to the market with health promoting properties.

Rapid Solution-Phase Hydrogen/Deuterium Exchange for Metabolite Compound Identification

Rapid, solution-phase hydrogen/deuterium exchange (HDX) coupled with mass spectrometry (MS) is demonstrated as a means for distinguishing small-molecule metabolites. HDX is achieved using capillary vibrating sharp-edge spray ionization (cVSSI) to allow sufficient time for reagent mixing and exchange in micrometer-sized droplets. Different compounds are observed to incorporate deuterium with varying efficiencies resulting in unique isotopic patterns as revealed in the MS spectra. Using linear regression techniques, parameters representing contribution to exchange by different hydrogen types can be computed. In this proof-of-concept study, the exchange parameters are shown to be useful in the retrodiction of the amount of deuterium incorporated within different compounds. On average, the exchange parameters retrodict the exchange level with ~ 2.2-fold greater accuracy than treating all exchangeable hydrogens equally. The parameters can be used to produce hypothetical isotopic distributions that agree (± 16% RMSD) with experimental measurements. These initial studies are discussed in light of their potential value for identifying challenging metabolite species.

Alteration of intracellular metabolome in osteosarcoma stem cells revealed by liquid chromatography-tandem mass spectrometry

Cancer stem cells (CSCs) are the origin of many malignant tumours, including osteosarcoma that mainly affects adolescents and is accompanied by a poor prognosis. However, little is known about the intrinsic biological information of osteosarcoma stem cells, particularly for the metabolomics features. Hence, an ultra-high performance liquid chromatography coupled with tandem Q-Exactive Orbitrap mass spectrometer (UHPLC-QE-MS)-based metabolomics approach was developed to investigate the metabolism changes in the human osteosarcoma (HOS) cell line in order to understand its possible mechanism. HMDB, METLIN and m/z Cloud databases were used to identify the metabolic markers. Additionally, the compounds were further identified using standards of the metabolites. Comparing HOS-CSCs with non-CSCs, 154 different metabolites were identified in both the positive and negative modes. Based on the clearly distinct metabolites, the changed metabolic pathways were analysed using MetaboAnalyst. The top five altered pathways included alanine, aspartate and glutamate metabolism; arginine and proline metabolism; glutathione metabolism; cysteine and methionine metabolism; and the citrate cycle (TCA cycle). The downregulation of the TCA cycle and elevation of oxidized glutathione levels suggested a decline of mitochondrial metabolism, while most of the amino acid metabolisms were upregulated. Further biological experiments including an analysis of mitochondrial activity confirmed the above hypotheses that were deduced from metabolomics results. These findings not only enhance our understanding of the altered metabolome in osteosarcoma stem cells but also demonstrate the great potential of such a metabolomics method based on UHPLC-QE-MS in large-scale cell studies.

Changes in lipids composition and metabolism in colorectal cancer: a review

Altered metabolism of lipids is currently considered a hallmark characteristic of many malignancies, including colorectal cancer (CRC). Lipids are a large group of metabolites that differ in terms of their fatty acid composition. This review summarizes recent evidence, documenting many alterations in the content and composition of fatty acids, polar lipids, oxylipins and triacylglycerols in CRC patients' sera, tumor tissues and adipose tissue. Some of altered lipid molecules may be potential biomarkers of CRC risk, development and progression. Owing to a significant role of many lipids in cancer cell metabolism, some of lipid metabolism pathways may also constitute specific targets for anti-CRC therapy.

Quantitative analysis of chemoresistance-inducing fatty acid in food supplements using UHPLC-ESI-MS/MS

Polyunsaturated fatty acids are important signaling molecules. A recent study reported hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid, 12-oxo-5Z,8E,10E-heptadecatrienoic acid, and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid as chemotherapy resistance-inducing factors when tumor cells were treated with cisplatin. Marine-based food supplements like fish oil or algae extracts are rich in polyunsaturated fatty acids and can contain large amounts of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid. Thus, it was concluded that oral uptake of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid might induce chemoresistance as shown in a mouse model. Cancer patients tend to consume food supplements containing polyunsaturated fatty acids on a regular basis. The uptake of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid should be controlled, because even low concentrations of 0.5 ng mL^-1 showed chemoresistance-inducing effects in animal experiments. For accurate analysis of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid a validated method was developed by using ultrahigh-performance liquid chromatography hyphenated to quadrupole time of flight mass spectrometry via electrospray ionization and sample preparation by solid-phase extraction (SPE) with 3-aminopropyl silica. A combined targeted/untargeted approach was utilized using MS/MS by data-independent acquisition with SWATH and applied to commercial food supplements (refined fish oil, fish oil capsules, algae oil capsules, and flaxseed capsules). Accurate quantification of hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid on the MS/MS level with simultaneous untargeted fatty acid screening revealed additional information. The LODs for hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic acid were 0.036 ng mL^-1 and 0.054 ng mL^-1, respectively. Since hexadeca-4Z,7Z,10Z,13Z-tetraenoic acid was present in the samples in large amounts and (12S)-hydroxy-5Z,8E,10E-heptadecatrienoic was not expected to be present in high concentrations, two calibration ranges, namely, 0.5-20 ng mL^-1 and 5-200 ng mL^-1, were validated. An untargeted screening identified 18-39 free fatty acids being present in the lipid extracts of the food supplement samples. Graphical abstract ᅟ.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Recent advances in using mass spectrometry for mitochondrial metabolomics and lipidomics - A review

Metabolomics and lipidomics generally targets a huge number of intermediate and end products of cellular metabolism in body fluids, tissues, and cells etc. At present, mass spectrometry (MS) based metabolic or lipid profiling of routine biological specimens including the whole cells, tissues, plasma, serum and urine etc., can cover hundreds of metabolites or lipid species in one analysis, which has qualified deep elucidation of global metabolic and lipid networks. Mitochondria are important intracellular organelles and many critical biochemical reactions occur here, they provide building block for new cells, control redox balance, participate in apoptosis and behave as a signalling platform. Evidence suggests high prevalence of mitochondrial dysfunction occurs in a variety of cancers and other diseases, thus there is an urgent demand for investigating and clarifying mitochondrial metabolic and lipid alterations induced by diseases. Nevertheless, mitochondria contribute a small fraction to cellular contents, profiling of whole cell is probably unsuitable for monitoring alterations in mitochondria. Therefore, metabolomics and lipidomics analyses specially for mitochondria are necessary to understand disturbed metabolic and lipid pathways induced by environment and diseases. However, methods for comprehensively profiling metabolites and lipids in mitochondria have been limited at present. This review summarizes the current states and progress of MS-based mitochondrial metabolomics and lipidomics study. Details of mitochondrial isolation procedure, analytical methods and their applications are described. The challenges and opportunities are also given.