Merged Targeted Quantification and Untargeted Profiling for Comprehensive Assessment of Acylcarnitine and Amino Acid Metabolism

Induced pluripotent stem cell-derived hepatocytes reveal TCA cycle disruption and the potential basis for triheptanoin treatment for malate dehydrogenase 2 deficiency

Mitochondrial malate dehydrogenase 2 (MDH2) is crucial to cellular energy generation through direct participation in the tricarboxylic acid (TCA) cycle and the malate aspartate shuttle (MAS). Inherited MDH2 deficiency is an ultra-rare metabolic disease caused by bi-allelic pathogenic variants in the MDH2 gene, resulting in early-onset encephalopathy, psychomotor delay, muscular hypotonia and frequent seizures. Currently, there is no cure for this devastating disease. We recently reported symptomatic improvement of a three-year-old girl with MDH2 deficiency following treatment with the triglyceride triheptanoin. Here, we aimed to better characterize this disease and improve our understanding of the potential utility of triheptanoin treatment. Using fibroblasts derived from this patient, we generated induced pluripotent stem cells (hiPSCs) and differentiated them into hepatocytes (hiPSC-Heps). Characterization of patient-derived hiPSCs and hiPSC-Heps revealed significantly reduced MDH2 protein expression. Untargeted proteotyping of hiPSC-Heps revealed global dysregulation of mitochondrial proteins, including upregulation of TCA cycle and fatty acid oxidation enzymes. Metabolomic profiling confirmed TCA cycle and MAS dysregulation, and demonstrated normalization of malate, fumarate and aspartate following treatment with the triheptanoin components glycerol and heptanoate. Taken together, our results provide the first patient-derived hiPSC-Hep-based model of MDH2 deficiency, confirm altered TCA cycle function, and provide further evidence for the implementation of triheptanoin therapy for this ultra-rare disease.

Synopsis

This study reveals altered expression of mitochondrial pathways including the tricarboxylic acid cycle and changes in metabolite profiles in malate dehydrogenase 2 deficiency and provides the molecular basis for triheptanoin treatment in this ultra-rare disease.

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry

Acylcarnitines are metabolic intermediates of fatty acids and branched-chain amino acids having vital biofunctions and pathophysiological significances. Here, we developed a high-throughput method for quantifying hundreds of acylcarnitines in one run using ultrahigh performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). This enabled simultaneous quantification of 1136 acylcarnitines (C0-C26) within 10-min with good sensitivity (limit of detection < 0.7 fmol), linearity (correlation coefficient > 0.992), accuracy (relative error < 20%), precision (coefficient of variation (CV), CV < 15%), stability (CV < 15%), and inter-technician consistency (CV < 20%, n = 6). We also established a quantitative structure-retention relationship (goodness of fit > 0.998) for predicting retention time (tR) of acylcarnitines with no standards and built a database of their multiple reaction monitoring parameters (tR, ion-pairs, and collision energy). Furthermore, we quantified 514 acylcarnitines in human plasma and urine, mouse kidney, liver, heart, lung, and muscle. This provides a rapid method for quantifying acylcarnitines in multiple biological matrices.

Dysregulated lipid metabolism in TMZ-resistant glioblastoma: pathways, proteins, metabolites and therapeutic opportunities

Glioblastoma (GBM) is a highly aggressive and lethal brain tumor with limited treatment options, such as the chemotherapeutic agent, temozolomide (TMZ). However, many GBM tumors develop resistance to TMZ, which is a major obstacle to effective therapy. Recently, dysregulated lipid metabolism has emerged as an important factor contributing to TMZ resistance in GBM. The dysregulation of lipid metabolism is a hallmark of cancer and alterations in lipid metabolism have been linked to multiple aspects of tumor biology, including proliferation, migration, and resistance to therapy. In this review, we aimed to summarize current knowledge on lipid metabolism in TMZ-resistant GBM, including key metabolites and proteins involved in lipid synthesis, uptake, and utilization, and recent advances in the application of metabolomics to study lipid metabolism in GBM. We also discussed the potential of lipid metabolism as a target for novel therapeutic interventions. Finally, we highlighted the challenges and opportunities associated with developing these interventions for clinical use, and the need for further research to fully understand the role of lipid metabolism in TMZ resistance in GBM. Our review suggests that targeting dysregulated lipid metabolism may be a promising approach to overcome TMZ resistance and improve outcomes in patients with GBM.

Cancer metabolites: promising biomarkers for cancer liquid biopsy

Cancer exerts a multitude of effects on metabolism, including the reprogramming of cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation of cancer cells and adaptation to the tumor microenvironment. There is a growing body of evidence suggesting that aberrant metabolites play pivotal roles in tumorigenesis and metastasis, and have the potential to serve as biomarkers for personalized cancer therapy. Importantly, high-throughput metabolomics detection techniques and machine learning approaches offer tremendous potential for clinical oncology by enabling the identification of cancer-specific metabolites. Emerging research indicates that circulating metabolites have great promise as noninvasive biomarkers for cancer detection. Therefore, this review summarizes reported abnormal cancer-related metabolites in the last decade and highlights the application of metabolomics in liquid biopsy, including detection specimens, technologies, methods, and challenges. The review provides insights into cancer metabolites as a promising tool for clinical applications.

Diazo probe-based chemical isotope labeling assisted liquid chromatography-tandem mass spectrometry analysis for sensitive determination of amino acids in biofluids

Amino acids are important biomolecules and contribute to essential biological processes. Liquid chromatography tandem mass spectrometry (LC-MS) now is a powerful tool for the analysis of amino acid metabolites; however, the structural similarity and polarity of amino acids can lead to the poor chromatographic retention and low detection sensitivities. In this study, we used a pair of light and heavy isotopomers of diazo probes, d₀/d₅-2-(diazomethyl)-N-methyl-N-phenyl-benzamide (2-DMBA/d₅ -2-DMBA) to label amino acids. The paired MS probes of 2-DMBA and d₅ -2-DMBA carry diazo groups that can efficiently and specifically react with the carboxyl group on free amino acid metabolites under mild conditions. Benefiting from the transfer of the 2-DMBA/d₅ -2-DMBA to carboxyl group on amino acids, the ionization efficiencies of amino acids presented great enhancement during LC-MS analysis. The results suggested that the detection sensitivities of 17 amino acids increased by 9-133-fold upon 2-DMBA labeling, and the obtained limits of detection (LODs) of amino acids on-column ranged from 0.011 fmol-0.057 fmol. With the application of the developed method, we successfully achieved the sensitive and accurate detection of the 17 amino acids in microliter level of serum sample. Moreover, the contents of most amino acids were different in the serum from normal and B16F10-tumour mice, demonstrating that endogenous amino acids may play important roles in the regulation of tumors development. This developed method of chemical labeling of amino acids with diazo probes assisted LC-MS analysis provides a potentially valuable tool to investigate the relationships between amino acids metabolism and diseases.

From fundamentals in calibration to modern methodologies: A tutorial for small molecules quantification in liquid chromatography-mass spectrometry bioanalysis

Over the last two decades, liquid chromatography coupled to mass-spectrometry (LC‒MS) has become the gold standard to perform qualitative and quantitative analyses of small molecules. When quantitative analysis is developed, an analyst usually refers to international guidelines for analytical method validation. In this context, the design of calibration curves plays a key role in providing accurate results. During recent years and along with instrumental advances, strategies to build calibration curves have dramatically evolved, introducing innovative approaches to improve quantitative precision and throughput. For example, when a labeled standard is available to be spiked directly into the study sample, the concentration of the unlabeled analog can be easily determined using the isotopic pattern deconvolution or the internal calibration approach, eliminating the need for multipoint calibration curves. This tutorial aims to synthetize the advances in LC‒MS quantitative analysis for small molecules in complex matrices, going from fundamental aspects in calibration to modern methodologies and applications. Different work schemes for calibration depending on the sample characteristics (analyte and matrix nature) are distinguished and discussed. Finally, this tutorial outlines the importance of having international guidelines for analytical method validation that agree with the advances in calibration strategies and analytical instrumentation.

Zengye Decoction Attenuated Severe Acute Pancreatitis Complicated with Acute Kidney Injury by Modulating the Gut Microbiome and Serum Amino Acid Metabolome

Objective

To explore the effect and underlying mechanism of Zengye decoction (ZYD), a traditional formula from China, on the severe acute pancreatitis (SAP) rat model with acute kidney injury (AKI).

Methods

The SAP-AKI model was induced by 3.5% sodium taurocholate. Rats were treated with normal saline or ZYD twice and sacrificed at 36 h after modeling. Amylase, lipase, creatinine, blood urea nitrogen, kidney injury molecule 1(KIM-1), and multiple organs' pathological examinations were used to assess the protective effect of ZYD. Gut microbiome detected by 16S rRNA sequencing analysis and serum amino acid metabolome analyzed by liquid chromatography-mass spectrometry explained the underlying mechanism. The Spearman correlation analysis presented the relationship between microflora and metabolites.

Results

ZYD significantly decreased KIM-1(P < 0.05) and the pathological score of the pancreas (P < 0.05), colon (P < 0.05), and kidney (P < 0.05). Meanwhile, ZYD shifted the overall gut microbial structure (β-diversity, ANOSIM R = 0.14, P=0.025) and altered the microbial compositions. Notably, ZYD reduced the potentially pathogenic bacteria—Bacteroidetes, Clostridiales vadin BB60 group, and uncultured_Clostridiales_bacterium, but promoted the short-chain fatty acid (SCFA) producers—Erysipelotrichaceae, Bifidobacterium, Lactobacillus, and Moryella (all P < 0.05). Moreover, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) presented a remarkable change in amino acid metabolome after SAP-AKI induction and an apparent regulation by ZYD treatment (R2Y 0.878, P=0.01; Q2 0.531, P=0.01). Spearman's correlation analysis suggested that gut bacteria likely influenced serum metabolites levels (absolute r > 0.4 and FDR P < 0.02).

Conclusions

ZYD attenuated SAP-AKI by modulating the gut microbiome and serum amino acid metabolome, which may be a promising adjuvant treatment.

Correlation between Acylcarnitine and Peripheral Neuropathy in Type 2 Diabetes Mellitus

OBJECTIVE

In patients with type 2 diabetes mellitus (T2DM), it is unknown whether acylcarnitine changes in the patient's plasma as diabetic peripheral neuropathy (DPN) occurs. The purpose of the present study was to investigate the correlation between acylcarnitines and DPN in Chinese patients with T2DM.

METHODS

A total of 508 patients admitted to the First Affiliated Hospital of Jinzhou Medical University were included in this study, and all of whom were hospitalized for T2DM from January 2018 to December 2020. The diagnostic criteria for DPN were based on the 2017 Chinese Guidelines for the Prevention of Type 2 Diabetes. The contents of 25 acylcarnitine metabolites in fasting blood were determined by mass spectrometry. The measured acylcarnitines were classified by factor analysis, and the factors were extracted. To determine the correlation between acylcarnitines and DPN, binary logistic regression analysis was applied.

RESULTS

Among the 508 T2DM patients, 270 had DPN. Six factors were extracted from 25 acylcarnitines, and the cumulative contribution rate of variance was 61.02%. After the adjustment for other potential confounding factors, such as other carnitines and conventional risk factors, Factor 2 was positively associated with an increased risk of DPN (OR: 1.38, 95% CI: 1.13-1.69). Factor 2 contained acetylcarnitine (C2), propionylcarnitine (C3), butylcarnitine (C4), and isovalerylcarnitine (C5).

CONCLUSIONS

Plasma levels of short-chain acylcarnitines (C2, C3, C4, and C5) were positively associated with DPN risk.

Metabolic Impairment in Coronary Artery Disease: Elevated Serum Acylcarnitines Under the Spotlights

Coronary artery disease (CAD) remains the leading cause of death worldwide. Expanding patients' metabolic phenotyping beyond clinical chemistry investigations could lead to earlier recognition of disease onset and better prevention strategies. Additionally, metabolic phenotyping, at the molecular species level, contributes to unravel the roles of metabolites in disease development. In this cross-sectional study, we investigated clinically healthy individuals (n = 116, 65% male, 70.8 ± 8.7 years) and patients with CAD (n = 54, 91% male, 67.0 ± 11.5 years) of the COmPLETE study. We applied a high-coverage quantitative liquid chromatography-mass spectrometry approach to acquire a comprehensive profile of serum acylcarnitines, free carnitine and branched-chain amino acids (BCAAs), as markers of mitochondrial health and energy homeostasis. Multivariable linear regression analyses, adjusted for confounders, were conducted to assess associations between metabolites and CAD phenotype. In total, 20 short-, medium- and long-chain acylcarnitine species, along with L-carnitine, valine and isoleucine were found to be significantly (adjusted p ≤ 0.05) and positively associated with CAD. For 17 acylcarnitine species, associations became stronger as the number of affected coronary arteries increased. This implies that circulating acylcarnitine levels reflect CAD severity and might play a role in future patients' stratification strategies. Altogether, CAD is characterized by elevated serum acylcarnitine and BCAA levels, which indicates mitochondrial imbalance between fatty acid and glucose oxidation.

A clinically validated method to separate and quantify underivatized acylcarnitines and carnitine metabolic intermediates using mixed-mode chromatography with tandem mass spectrometry

Acylcarnitines are intermediate metabolites of the mitochondria that serve as biomarkers for inherited disorders of fatty acid oxidation and amino acid metabolism. The prevailing clinical method used to quantify acylcarnitines involves flow-injection tandem mass spectrometry, an approach with a number of limitations; foremost the inability to separate and therefore distinguish key isobaric acylcarnitine species. To address these issues, we report a clinically validated liquid chromatography tandem mass spectrometry method to quantify acylcarnitines, free carnitine, and carnitine metabolic intermediates in human plasma. Importantly, this method resolves clinically relevant isobaric and isomeric acylcarnitine species in a single 22 min analysis without the use of ion pairing or derivatization reagents. This unique combination of features is not achievable by existing acylcarnitine methods and is made possible by the use of a novel mixed-mode chromatographic separation. Further clinical validation studies demonstrate excellent limits of quantification, linearity, accuracy, and inter-assay precision for analyses of 38 different calibrated analytes. An additional 28 analytes are semi-quantitatively analyzed using surrogate calibrators. The study of residual patient specimens confirms the clinical utility of this method and suggests expanded applicability to the diagnosis of peroxisomal disorders. In summary, we report a clinically validated acylcarnitine method that utilizes a novel mixed-mode chromatographic separation to provide a number of advantages in terms of specificity, accuracy, sample preparation time, and clinical utility.

Diagnostic approach to thyroid cancer based on amino acid metabolomics in saliva by ultra-performance liquid chromatography with high resolution mass spectrometry

Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of non-invasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R² > 0.99), recovery (92.2 %-110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

A merged method for targeted analysis of amino acids and derivatives using parallel reaction monitoring combined with untargeted profiling by HILIC-Q-Orbitrap HRMS

With continuously increased scan rate and sensitivity, high resolution mass spectrometry (HRMS) allows for both reliable targeted analysis (e.g., parallel reaction monitoring, PRM) and a global overview for discovery-based untargeted profiling (e.g., data dependent acquisition, DDA) to be performed. Based on previous study on PRM for large scale targeted metabolomics quantification, we developed an innovative method merged targeted and untargeted approaches in a single run. In our workflow, the scheduled PRM for targeted analysis of amino acids and derivatives combined with the full scan was acquired in every sample injection by hydrophilic interaction liquid chromatography tandem quadrupole-Orbitrap high resolution mass spectrometry (HILIC-Q-Orbitrap HRMS). The identification of metabolic features from full scan was further performed with DDA methodology on grouped quality control (QC) samples and matched with available database. Specifically, 20 amino acids and 40 derivatives were selected for targeted analysis with optimal chromatographic separation and PRM parameters. All isomers within the selected metabolites were totally separated in the robust HILIC condition. 36 of selected metabolites were well-detected and showed a good linearity and reproducibility in NIST SRM 1950 plasma. Moreover, the absolute quantification performance of targeted PRM method was systematically validated using 10 amino acids with the corresponding stable isotope-labeled internal standards (SIL-IS). Finally, the newly developed method was successfully applied to analysis of the plasma samples from patients of pancreatic benign tumor and pancreatic cancer. The significant reduction of circulating amino acids in patients with pancreatic malignancy was confirmed by targeted PRM method and other amino acids modifications as well as polar metabolites were identified with untargeted profiling. Therefore, we have established a workflow that combines specifically and reliably targeted PRM method as well as broad-coverage untargeted profiling, which provides an innovative strategy for basic and clinical metabolomics study.

The first knock-in rat model for glutaric aciduria type I allows further insights into pathophysiology in brain and periphery

Glutaric aciduria type I (GA-I, OMIM # 231670) is an inborn error of metabolism caused by a deficiency of glutaryl-CoA dehydrogenase (GCDH). Patients develop acute encephalopathic crises (AEC) with striatal injury most often triggered by catabolic stress. The pathophysiology of GA-I, particularly in brain, is still not fully understood. We generated the first knock-in rat model for GA-I by introduction of the mutation p.R411W, the rat sequence homologue of the most common Caucasian mutation p.R402W, into the Gcdh gene of Sprague Dawley rats by CRISPR/CAS9 technology. Homozygous Gcdh^ki/ki rats revealed a high excretor phenotype, but did not present any signs of AEC under normal diet (ND). Exposure to a high lysine diet (HLD, 4.7%) after weaning resulted in clinical and biochemical signs of AEC. A significant increase of plasmatic ammonium concentrations was found in Gcdh^ki/ki rats under HLD, accompanied by a decrease of urea concentrations and a concomitant increase of arginine excretion. This might indicate an inhibition of the urea cycle. Gcdh^ki/ki rats exposed to HLD showed highly diminished food intake resulting in severely decreased weight gain and moderate reduction of body mass index (BMI). This constellation suggests a loss of appetite. Under HLD, pipecolic acid increased significantly in cerebral and extra-cerebral liquids and tissues of Gcdh^ki/ki rats, but not in WT rats. It seems that Gcdh^ki/ki rats under HLD activate the pipecolate pathway for lysine degradation. Gcdh^ki/ki rat brains revealed depletion of free carnitine, microglial activation, astroglyosis, astrocytic death by apoptosis, increased vacuole numbers, impaired OXPHOS activities and neuronal damage. Under HLD, Gcdh^ki/ki rats showed imbalance of intra- and extracellular creatine concentrations and indirect signs of an intracerebral ammonium accumulation. We successfully created the first rat model for GA-I. Characterization of this Gcdh^ki/ki strain confirmed that it is a suitable model not only for the study of pathophysiological processes, but also for the development of new therapeutic interventions. We further brought up interesting new insights into the pathophysiology of GA-I in brain and periphery.

Mass spectrometry with derivatization method for concurrent measurement of amino acids and acylcarnitines in plasma of diabetic type 2 patients with diabetic nephropathy

BACKGROUND

Amino acids (AAs) and acylcarnitines play a key role in metabolic disease and can be used as biomarkers of various diseases such as malignancies, type 2 diabetes (T2D), insulin resistance, and cardiovascular diseases, therefore, designing an accurate and simple laboratory method that simultaneously measure both groups of substances, could improve the process of analytes quantification. In this research, a flow injection tandem mass spectrometry (FI-MS/MS) method for simultaneous measurement of AAs and acylcarnitines in addition to results of validation is explained.

METHODS

Samples were mixed with internal standards and after derivatization (with butanolic-HCL), AAs, and acylcarnitines were quantified by tandem mass spectrometry (SCIEX API 3200). Analytical performance studies were designed based on the Clinical and Laboratory Standards Institute (CLSI) guidelines including precision, accuracy, linearity, and limit of detection-quantification (LOD-LOQ) experiments. Samples from patients with T2D in different stages of kidney disease were also analyzed to ensure the clinical usage of the method.

RESULTS

Performance evaluation of the method demonstrated adequate results. The mean of estimated inter-assay precision (reported as a coefficient variation) for AAs and acylcarnitines were less than 8.7% and 12.3%, the estimated mean bias was below 8.8% and 10.2% respectively. LOD of analytes ranged between 0.6-10 μmol per liter (μmol/L) for AAs and 0.02-1 μmol/L for acylcarnitines. LOQ analytes showed a range of 2-25 μmol/L and 0.05-5 μmol/L for AAs and carnitine/acylcarnitines respectively. In diabetic patients sample analysis, a significant increase in acylcarnitines (C2, C4, C5DC, C6, C8, C10, C14) and citrulline with a significant decrease in valine were seen in patients with severely increased albuminuria.

CONCLUSION

FI-MS/MS method with pre-injection derivatization with butanolic-HCL can be used for concurrent measurement of AAs and carnitine/acylcarnitines in a short time and it satisfies the analytical performance requirements. This method is applied for AAs and carnitine/acylcarnitines measurement in patient with T2DM and results show some of the acylcarnitines and AAs can be involved in diabetic nephropathy development.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40200-021-00786-3.

A facile synthesis of isotope labeled acylcarnitines

Acylcarnitines are a big family of small molecule metabolites with various acyl groups attached to the hydroxyl moiety of l-carnitine. They are good indicators of multiple metabolic disorders. For instance, the newborn screening panel uses flow injection tandem mass spectrometry to analyze more than 30 different acylcarnitines and amino acids extracted from dried blood spots. A facile approach has been developed for the synthesis of isotope labeled acylcarnitines whose mass shift over their unlabeled counterparts can be any number in the range of 3 to 12 Da. This strategy makes it more convenient to provide authentic internal standards for acylcarnitines profiling analyses, thereby expanding their clinical applications.

Quantification of endogenous aminoacids and aminoacid derivatives in urine by hydrophilic interaction liquid chromatography tandem mass spectrometry

Aminoacids and their derivatives are key biologically important metabolites and reliable, rapid and accurate, quantification for these analytes in urine remains an important analytical challenge. Here a fast and reliable HILIC-tandem MS method is presented for application in clinical or nutritional studies. The developed method was validated according to existing guidelines adapted for endogenous analytes. The validation strategy provided evidence of linearity, LOD and LOQ, accuracy, precision, matrix effect and recovery. The surrogate matrix approach was applied for calibration proving satisfactory accuracy and precision based on standard criteria over the working concentration ranges. Intra and inter day accuracy was found to range between 0.8 and 20% for the LQC (low QC) and between 0.05 and 15 % for MQC (medium QC) and HQC (high QC). Inter and intraday precision were found to be between 3 and 20 % for the LQC and between 1 and 15% for the MQC and HQC. The stability of the analytes, in both surrogate and pooled urine QC samples, was found to be within 15% over a short period at 4 °C or after a up to 3 freeze-thaw cycles. The uncertainty of the method was also assessed to provide increased confidence for the acquired measurements. The method was successfully applied to a subset of human urine samples involved in a study of amino acids dietary uptake. This method may provide a valuable tool for many applications or studies where amino acid metabolic signatures in the excreted urine are under investigation.

Multi-dimensional characterization and identification of sterols in untargeted LC-MS analysis using all ion fragmentation technology

Sterols are an important type of lipids, and play many important roles in physiological and pathological processes. However, comprehensive analysis of sterols especially identification of unknown sterols is challenging. In this work, LC-MS with all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. AIF technology provided holistic and multi-dimensional characterization for both knowns and unknowns sterols, including accurate m/z, isotope pattern, retention time (RT), and co-eluted peak profiles between MS1 and MS2 ions in one analysis. We further developed an analysis strategy by integrating the multi-dimensional properties to support unambiguous identification of sterols, including distinguishing sterol isomers. The developed strategy enabled to identify a total of 23 sterols in mouse samples, and quantified 19 sterols in mouse liver tissues. More importantly, we demonstrated that AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures in biological samples. In summary, we employed the LC-MS based AIF technology to develop multi-dimensional characterization and identification of both known and unknown sterols in complex biological samples. The comprehensive analysis of sterols facilitates to provide molecular insights to many physiological and pathological activities in biology.

An Integrated LC-MS/MS Strategy for Quantifying the Oxidative-Redox Metabolome in Multiple Biological Samples

The cellular redox balance plays a significant role in cell fate decisions and in the regulation of responses to various kinds of stress. In this study, we defined a novel concept of the oxidative-redox metabolome, and established a method for the simultaneous quantification of 23 metabolites involved in the oxidative-redox metabolome, covering NAD⁺ pathway, FAD pathway, GSSG pathway, and ATP pathway by using the AB SCIEX 5500 QTRAP LC/MS/MS system. Corresponding oxidative-redox metabolomics analysis was performed in plasma of humans, hamsters and mice, and hamsters were demonstrated to display a stronger resemblance than mice to humans. The known reductant dithiothreitol (DTT) and oxidant hydrogen peroxide (H₂O₂) were selected to treat A549 and HeLa cells to validate the current method, showing that DTT moderately increased while H₂O₂ greatly decreased most analytes. Antibiotic treatment may disturb the oxidative-redox balance in vivo. By comparing the oxidative-redox metabolome in antibiotic-fed hamsters with that of control hamsters, we demonstrated a substantial metabolic disparity between the two, further verifying the applicability and reliability of our method.

Exploring the Lipidome: Current Lipid Extraction Techniques for Mass Spectrometry Analysis

In recent years, high-throughput lipid profiling has contributed to understand the biological, physiological and pathological roles of lipids in living organisms. Across all kingdoms of life, important cell and systemic processes are mediated by lipids including compartmentalization, signaling and energy homeostasis. Despite important advances in liquid chromatography and mass spectrometry, sample extraction procedures remain a bottleneck in lipidomic studies, since the wide structural diversity of lipids imposes a constrain in the type and amount of lipids extracted. Differences in extraction yield across lipid classes can induce a bias on down-stream analysis and outcomes. This review aims to summarize current lipid extraction techniques used for untargeted and targeted studies based on mass spectrometry. Considerations, applications, and limitations of these techniques are discussed when used to extract lipids in complex biological matrices, such as tissues, biofluids, foods, and microorganisms.

Large-scale targeted metabolomics method for metabolite profiling of human samples

Targeted metabolomics has significant advantages for quantification but suffers from reduced metabolite coverage. In this study, we developed a large-scale targeted metabolomics method and expanded its applicability to various human samples. This approach initially involved unbiased identification of metabolites in human cells, tissues and body fluids using ultra high-performance liquid chromatography (UHPLC) coupled to high-resolution Orbitrap mass spectrometry (MS). Targeted metabolomics method was established with utility of UHPLC-triple quadrupole MS, which enables targeted profiling of over 400 biologically important metabolites (e.g., amino acids, sugars, nucleotides, dipeptides, coenzymes, and fatty acids), covering 92 metabolic pathways (e.g., Krebs cycle, glycolysis, amino acids metabolism, ammonia recycling, and one-carbon metabolism). The present method displayed better sensitivity, repeatability and linearity than the Orbitrap MS-based untargeted metabolomics approach and demonstrated excellent performance in lung cancer biomarker discovery, in which 107 differential metabolites were able to discriminate between carcinoma and adjacent normal tissues, implicating the Warburg effect, alteration of redox state, and nucleotide metabolism of lung cancer. This new method is flexible and expandable and offers many advantages for metabolomics analysis, such as wide metabolite coverage, good repeatability and linearity and excellent capability in biomarker discovery, making it useful for both basic and clinical metabolic research.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.