Recent advances in capillary electrophoresis‐mass spectrometry: Instrumentation,methodology and applications

Capillary electrophoresis (CE) offers fast and high‐resolution separation of charged analytes from small injection volumes. Coupled to mass spectrometry (MS), it represents a powerful analytical technique providing (exact) mass information and enables molecular characterization based on fragmentation. Although hyphenation of CE and MS is not straightforward, much emphasis has been placed on enabling efficient ionization and user‐friendly coupling. Though several interfaces are now commercially available, research on more efficient and robust interfacing with nano‐electrospray ionization (ESI), matrix‐assisted laser desorption/ionization (MALDI) and inductively coupled plasma mass spectrometry (ICP) continues with considerable results. At the same time, CE‐MS has been used in many fields, predominantly for the analysis of proteins, peptides and metabolites. This review belongs to a series of regularly published articles, summarizing 248 articles covering the time between June 2016 and May 2018. Latest developments on hyphenation of CE with MS as well as instrumental developments such as two‐dimensional separation systems with MS detection are mentioned. Furthermore, applications of various CE‐modes including capillary zone electrophoresis (CZE), nonaqueous capillary electrophoresis (NACE), capillary gel electrophoresis (CGE) and capillary isoelectric focusing (CIEF) coupled to MS in biological, pharmaceutical and environmental research are summarized.     

Analysis of amino acids in latent fingerprint residue by capillary electrophoresis‐mass spectrometry

The analysis of the chemical composition of fingerprints is important for the development and improvement of existing fingerprint enhancement techniques. This study demonstrates the first analysis of a latent fingerprint sample, using an optimized CE‐MS method. In total 12 amino acids were detected in the fingerprint sample. MS/MS fragmentation was used to provide additional identity confirmation, for which eight of the twelve detected amino acids generated confirmatory product ions. Nine amino acids were quantified and their relative abundances were consistent with previous studies with serine and glycine being the most abundant. The successful detection of amino acids from latent fingerprints demonstrates that CE‐MS is a potential future technique for further study of such compounds in fingerprint samples.     

Metabolic profiling of yeast culture using gas chromatography coupled with orthogonal acceleration accurate mass time-of-flight mass spectrometry: Application to biomarker discovery

Yeast and yeast cultures are frequently used as additives in diets of dairy cows. Beneficial effects from the inclusion of yeast culture in diets for dairy mammals have been reported, and the aim of this study was to develop a comprehensive analytical method for the accurate mass identification of the ‘global’ metabolites in order to differentiate a variety of yeasts at varying growth stages (Diamond V XP, Yea-Sacc and Levucell). Microwave-assisted derivatization for metabolic profiling is demonstrated through the analysis of differing yeast samples developed for cattle feed, which include a wide range of metabolites of interest covering a large range of compound classes. Accurate identification of the components was undertaken using GC-oa-ToFMS (gas chromatography-orthogonal acceleration-time-of-flight mass spectrometry), followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for data reduction and biomarker discovery. Semi-quantification (fold changes in relative peak areas) was reported for metabolites identified as possible discriminative biomarkers (p-value <0.05, fold change >2), including d-ribose (four fold decrease), myo-inositol (five fold increase), l-phenylalanine (three fold increase), glucopyranoside (two fold increase), fructose (three fold increase) and threitol (three fold increase) respectively.     

Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg⁻¹ day⁻¹ or 250 mg kg⁻¹ day⁻¹ for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.     

Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics

Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential ¹²C-/¹³C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N-Methyl-D-aspartic and tyrosine were identified. The changes of these biomarkers were likely due to the disruption of the endocrine system of silkworm by DDT. This work illustrates that the method of CIL LC-MS is useful to generate quantitative submetabolome profiles from a small volume of silkworm hemolymph with much higher coverage than conventional LC-MS methods, thereby facilitating the discovery of potential metabolite biomarkers related to EDC or other chemical exposure.     

Protein profiling for cancer biomarker discovery using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and infrared imaging: a review

Cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Cancer biomarker-based diagnostics have applications for establishing disease predisposition, early detection, cancer staging, therapy selection, identifying whether or not a cancer is metastatic, therapy monitoring, assessing prognosis, and advances in the adjuvant setting. Full adoption of cancer biomarkers in the clinic has to date been slow, and only a limited number of cancer biomarker products are currently in routine use.Among proteomic technologies, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is a technique that has allowed rapid progress in cancer biology. Different further developed methods including e.g. SELDI (surface-enhanced laser desorption/ionization) and MELDI (material-enhanced laser desorption/ionization) are simple and high-throughput techniques that analyze with high sensitivity and specificity intact proteins expressed in complex biological mixtures, such as serum, urine, and tissues. The combination of mass spectrometry (MS) with infrared (IR) spectroscopic imaging is an attempt to combine different technologies in systems analytics. Both MALDI-TOF and infrared tissue imaging enable studying proteins distribution in tissue samples with a resolution down to 50 and 5 μm, respectively.In this review, we summarize recent applications and the synergistic combination of these new technologies to proteomic profiling for cancer biomarker discovery.     

Study of immobilized metal affinity chromatography sorbents for the analysis of peptides by on‐line solid‐phase extraction capillary electrophoresis‐mass spectrometry

Several commercial immobilized metal affinity chromatography sorbents were evaluated in this study for the analysis of two small peptide fragments of the amyloid β‐protein (Aβ) (Aβ(1–15) and Aβ(10–20) peptides) by on‐line immobilized metal affinity SPE‐CE (IMA‐SPE‐CE). The performance of a nickel metal ion (Ni(II)) sorbent based on nitrilotriacetic acid as a chelating agent was significantly better than two copper metal ion (Cu(II)) sorbents based on iminodiacetic acid. A BGE of 25 mM phosphate (pH 7.4) and an eluent of 50 mM imidazole (in BGE) yielded a 25‐fold and 5‐fold decrease in the LODs by IMA‐SPE‐CE‐UV for Aβ(1–15) and Aβ(10–20) peptides (0.1 and 0.5 μg/mL, respectively) with regard to CE‐UV (2.5 μg/mL for both peptides). The phosphate BGE was also used in IMA‐SPE‐CE‐MS, but the eluent needed to be substituted by a 0.5% HAc v/v solution. Under optimum preconcentration and detection conditions, reproducibility of peak areas and migration times was acceptable (23.2 and 12.0%RSD, respectively). The method was more sensitive for Aβ(10–20) peptide, which could be detected until 0.25 μg/mL. Linearity for Aβ(10–20) peptide was good in a narrow concentration range (0.25–2.5 μg/mL, R² = 0.93). Lastly, the potential of the optimized Ni(II)‐IMA‐SPE‐CE‐MS method for the analysis of amyloid peptides in biological fluids was evaluated by analyzing spiked plasma and serum samples.     

Urinary metabolomic study of non‐small cell lung carcinoma based on ultra high performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

Metabolic profiles from human urine reveal the significant difference of carnitine and acylcarnitines levels between non‐small cell lung carcinoma patients and healthy controls. Urine samples from cancer patients and healthy individuals were assayed in this metabolomic study using ultra high performance liquid chromatography coupled to quadrupole time‐of‐flight mass spectrometry. The data were normalized by the sum of all intensities and creatinine calibration, respectively, before orthogonal partial least squares discriminant analysis. Twenty differential metabolites were identified based on standard compounds or tandem mass spectrometry fragments. Among them, some medium‐/long‐chain acylcarnitines, for example, cis‐3,4‐methylene heptanoylcarnitine, were found to be downregulated while carnitine was upregulated in urine samples from the cancer group compared to the control group. Receiver operating characteristic analysis of the two groups showed that the area under curve for the combination of carnitine and 11 selected acylcarnitines was 0.958. This study suggests that the developed carnitine and acylcarnitines profiling method has the potential to be used for screening non‐small cell lung carcinoma.     

Metabolomic profiling of serum in the progression of Alzheimer's disease by capillary electrophoresis–mass spectrometry

There is high interest in the discovery of early diagnostic biomarkers of Alzheimer's disease, for which metabolomics exhibits a great potential. In this work, a metabolomic approach based on ultrafiltration and analysis by CE‐MS has been used to obtain representative fingerprints of polar metabolites from serum samples in order to distinguish between patients with Alzheimer's disease, mild cognitive impairment, and healthy controls. By the use of partial least squares discriminant analysis it was possible to classify patients according to the disease stage and then identify potential markers. Significant increase was observed with progression of disease in levels of choline, creatinine, asymmetric dimethyl‐arginine, homocysteine‐cysteine disulfide, phenylalanyl‐phenylalanine, and different medium chain acylcarnitines. On the other hand, asparagine, methionine, histidine, carnitine, acetyl‐spermidine, and C5‐carnitine were reduced in these serum samples. In this way, multiple essential pathways were found implicated in the underlying pathology, such as oxidative stress or defects in energy metabolism. However, the most interesting results are related to the association of several vascular risk factors with Alzheimer's disease.     

基于质谱的蛋白质组学技术在神经退行性疾病生物标志物研究中的应用

蛋白质组学是在整体水平上研究细胞、组织或生物体蛋白质组成及变化规律的科学.与传统的生物学研究相比,蛋白质组学具有快速、灵敏、高通量的优点.神经退行性疾病是一类由神经系统内特定神经细胞的进程性病变或丢失而导致神经功能障碍的疾病,严重危害人类健康.近年来,基于质谱的蛋白质组学技术在神经退行性疾病的研究中得到了广泛应用.本文简要介绍了蛋白质组学在样品分离、多肽定量、质谱检测及生物标志物临床验证等方面的技术发展,并结合实例综述了基于质谱的蛋白质组学在神经退行性疾病生物标志物发现与验证中的研究进展.     

Verification of protein biomarker specificity for the identification of biological stains by quadrupole time‐of‐flight mass spectrometry

Advances in proteomics technology over the past decade offer forensic serologists a greatly improved opportunity to accurately characterize the tissue source from which a DNA profile has been developed. Such information can provide critical context to evidence and can help to prioritize downstream DNA analyses. Previous proteome studies compiled panels of “candidate biomarkers” specific to each of five body fluids (i.e ., peripheral blood, vaginal/menstrual fluid, seminal fluid, urine, and saliva). Here, a multiplex quadrupole time‐of‐flight mass spectrometry assay has been developed in order to verify the tissue/body fluid specificity the 23 protein biomarkers that comprise these panels and the consistency with which they can be detected across a sample population of 50 humans. Single‐source samples of these human body fluids were accurately identified by the detection of one or more high‐specificity biomarkers. Recovery of body fluid samples from a variety of substrates did not impede accurate characterization and, of the potential inhibitors assayed, only chewing tobacco juice appeared to preclude the identification of a target body fluid. Using a series of 2‐component mixtures of human body fluids, the multiplex assay accurately identified both components in a single‐pass. Only in the case of saliva and peripheral blood did matrix effects appear to impede the detection of salivary proteins.     

Combination of dynamic pH junction with capillary electrophoresis‐mass spectrometry for the determination of systemins in plant samples

Systemin is an important group of plant peptide hormones participating in the regulation of plant defensive responses. An improved method, based on dynamic pH junction and capillary electrophoresis‐quadrupole time‐of‐flight mass spectrometry, was developed for online enrichment and sensitive determination of trace systemins in plants. After optimization, the online enrichment factors for six target systemins ranged from 90‐ to 127‐fold. The detection limits reached lower than 0.5 nM, which were comparable with the sensitivity of LC‐MS method. Satisfactory quantitative results were obtained in terms of linearity (R² ≥ 0.993), dynamic range (3–120 ng/mL), and reproducibility (≤6.7%). For the analysis of real plant samples, a rapid sample preparation method was developed, using two steps of SPE purification with different retention and separation mechanisms. Finally, this method realized the successful detection of tomato systemin and tobacco hydroxyproline‐rich systemin I from plant leaves with shorter analysis time.     

Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery

Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single “super”-list reflective of the overall preference or importance within the population. This “super”-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable.     

Lipid profiling of cyanobacteria Synechococcus sp. PCC 7002 using two‐dimensional liquid chromatography with quadrupole time‐of‐flight mass spectrometry

Glycerolipid is a main component of membranes in oxygenic photosynthetic organisms. Up to now, the majority of publication in this area has focused on the physiological functions of glycerolipids and lipoprotein complexes in photosynthesis, but the study on the separation and identification of glycerolipids in thylakoid membrane in cyanobacteria is relatively rare. Here we report a new method to separate and identify five photosynthetic glycerolipid classes, including monoglucosyl diacylglycerol, monogalactosyl diacylglycerol, digalactosyl diacylglycerol, sulfoquinovosyl diacylglycerol, and phosphatidylglycerol, in cyanobacteria Synechococcus sp. PCC 7002 by two‐dimensional (normal‐ and reversed‐phase) liquid chromatography online coupled to quadrupole time‐of‐flight mass spectrometry. Over twice as many lipid species were detected by our method compared to the previously reported methods. Ten new odd‐chain fatty acid glycerolipids were discovered for the first time. Moreover, complete separation of isomers of monogalactosyl diacylglycerol and monoglucosyl diacylglycerol was achieved. According to the tandem mass spectrometry results, we found that the head group of monoglucosyl diacylglycerols was not as stable as that of monogalactosyl diacylglycerols, which might explain why the organism chose monogalactosyl diacylglycerols and digalactosyl diacylglycerols instead of monoglucosyl diacylglycerols as the main content of the photosynthetic membranes in the history of evolution. This work will benefit further research on the physiological function of glycerolipids.     

Analysis of active alkaloids in the Menispermaceae family by nonaqueous capillary electrophoresis‐ion trap mass spectrometry

A nonaqueous CE‐IT MS with a nanospray ionization interface method was developed for the identification and quantification of tetrandrine (TET), fangchinoline (FAN), and sinomenine (SIN) using berberine as internal standard. The TET, FAN, and SIN standard solutions were directly infused into IT‐MS for collecting MS^1–3 spectra. The major fragment ions of analytes were confirmed and possible main cleavage pathways of fragment ions were studied. A bare fused‐silica capillary was used for separation of the analytes. A sheath liquid (50% aqueous methanol containing 0.2% acetic acid) to the capillary effluent with a nanoelectrospray ionization interface was added. Separation buffer comprised 80 mM solution of ammonium acetate, in a mixture of 70% methanol, 20% ACN, and 10% water, which also contained 1% acetic acid. The CE‐MS method was validated for linearity, sensitivity, accuracy, and precision, and then used to determine the content of the above components. The detection limits of TET, FAN, and SIN are 0.05, 0.08, and 0.15μg/mL, respectively. The precision was no more than 4.67% and the mean recovery of the analytes were 95.36–99.24%. This method was successfully applied to determine TET, FAN, and SIN in real samples radix Stephaniae tetrandrae and rhizomes of Menispermum dauricum.     

Metabolomics‐based approach for ranking the candidate structures of unidentified peaks in capillary electrophoresis time‐of‐flight mass spectrometry

One of the technical challenges encountered during metabolomics research is determining the chemical structures of unidentified peaks. We have developed a metabolomics‐based chemoinformatics approach for ranking the candidate structures of unidentified peaks. Our approach uses information about the known metabolites detected in samples containing unidentified peaks and involves three discrete steps. The first step involves identifying “precursor/product metabolites” as potential reactants or products derived from the unidentified peaks. In the second step, candidate structures for the unidentified peak are searched against the PubChem database using a molecular formula. These structures are then ranked by structural similarity against precursor/product metabolites and candidate structures. In the third step, the migration time is predicted to refine the candidate structures. Two simulation studies were conducted to highlight the efficacy of our approach, including the use of 20 proteinogenic amino acids as pseudo‐unidentified peaks, and leave‐one‐out experiments for all of the annotated metabolites with and without filtering against the Human Metabolome Database. We also applied our approach to two unidentified peaks in a urine sample, which were identified as glycocyamidine and N ‐acetylglycine. These results suggest that our approach could be used to identify unidentified peaks during metabolomics analysis.     

CE‐MS for metabolomics: Developments and applications in the period 2016–2018

In the field of metabolomics, CE‐MS is now recognized as a strong analytical technique for the analysis of (highly) polar and charged metabolites in a wide range of biological samples. Over the past few years, significant attention has been paid to the design and improvement of CE‐MS approaches for (large‐scale) metabolic profiling studies and for establishing protocols in order to further expand the role of CE‐MS in metabolomics. In this paper, which is a follow‐up of a previous review paper covering the years 2014–2016 (Electrophoresis 2017, 38, 190–202), main advances in CE‐MS approaches for metabolomics studies are outlined covering the literature from July 2016 to June 2018. Aspects like developments in interfacing designs and data analysis tools for improving the performance of CE‐MS for metabolomics are discussed. Representative examples highlight the utility of CE‐MS in the fields of biomedical, clinical, microbial, and plant metabolomics. A complete overview of recent CE‐MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings and MS detection mode. Finally, some general conclusions and perspectives are given.