Metabolic Profiling and Quantitative Analysis of Cerebrospinal Fluid Using Gas Chromatography-Mass Spectrometry: Current Methods and Future Perspectives

Towards a better understanding of idiopathic epilepsy through metabolic fingerprinting of cerebrospinal fluid in dogs

Cerebrospinal fluid metabolomics is a promising research technology in the elucidation of nervous system disorders. Therefore, in this work, a cerebrospinal fluid (CSF) metabolomics method using liquid chromatography coupled to mass spectrometry was optimized and validated to cover a wide range of metabolites. An acceptable coefficient of variance regarding instrumental, within-lab and intra-assay precision was found for 95, 70 and 96 of 102 targeted metabolites, together with 1256, 676 and 976 untargeted compounds, respectively. Moreover, approximately 75% of targeted metabolites and 50% of untargeted compounds displayed good linearity across different dilution ranges. Consequently, metabolic alterations in CSF of dogs with idiopathic epilepsy (IE) were studied by comparing CSF of dogs diagnosed with IE (Tier II) to dogs with non-brain related disease. Targeted metabolome analysis revealed higher levels of cortisol, creatinine, glucose, hippuric acid, mannose, pantothenol, and 2-phenylethylamine (P values < 0.05) in CSF of dogs with IE, whereas CSF of dogs with IE showed lower levels of spermidine (P value = 0.02). Untargeted CSF metabolic fingerprints discriminated dogs with IE from dogs with non-brain related disease using Orthogonal Partial Least Squares Discriminant Analysis (R2(Y) = 0.997, Q2(Y) = 0.828), from which norepinephrine was putatively identified as an important discriminative metabolite.

Biomarkers identification in follicular fluid in relation to live birth in in vitro fertilization of women with polycystic ovary syndrome in different subtypes by using UPLC-MS method

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common infertility disorder which affects reproductive-aged women. However, metabolic change profiles of follicular fluid (FF) in lean and obese women diagnosed with and without PCOS remains unclear.

METHODS

95 infertile women were divided into four subgroups: LC (lean control), OC (overweight control), LP (lean PCOS), and OP (overweight PCOS). The FF samples were collected during oocyte retrieval and assayed by ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) metabolomics.

RESULTS

A total of 236 metabolites were identified by metabolic analysis. The pathway enrichment analysis revealed that the glycerophospholipid metabolism (impact = 0.11182), ether lipid metabolism (impact = 0.14458), and primary bile acid biosynthesis (impact = 0.03267) were related to metabolic pathway between PCOS and control. Correlation analyses showed that epitestosterone sulfate was found positively correlated with fertilization rate in PCOS, while falcarindione, lucidone C. and notoginsenoside I was found to be negatively correlated. The combined four biomarkers including lucidone C, epitestosterone sulfate, falcarindione, and notoginsenoside I was better in predicting live birth rate, with AUC of 0.779.

CONCLUSION

The follicular fluid of women with PCOS showed unique metabolic characteristics. Our study provides better identification of PCOS follicular fluid metabolic dynamics, which may serve as potential biomarkers of live birth.

Metabolic Profiling of Aromatic Compounds

Metabolic profiling is a powerful modern tool in searching for novel biomarkers and indicators of normal or pathological processes in the body [...].

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Pocket-Size Wireless Nanoelectrospray Ionization Mass Spectrometry for Metabolic Analysis of Salty Biofluids and Single Cells

Analysis of volume-limited biological samples such as single cells and biofluids not only benefits clinical purposes but also promotes fundamental research in life sciences. Detection of these samples, however, imposes strict requirements on measurement performance because of the minimal volume and concentrated salts of the samples. Herein, we developed a self-cleaning nanoelectrospray ionization device powered by a pocket-size "MasSpec Pointer" (MSP-nanoESI) for metabolic analysis of salty biological samples with limited volume. The self-cleaning effect induced by Maxwell-Wagner electric stress helps with keeping the borosilicate glass capillary tip free from clogging and thus increasing salt tolerance. This device possesses a high sample economy (about 0.1 μL per test) due to its pulsed high voltage supply, sampling method (dipping the nanoESI tip into analyte solution), and contact-free electrospray ionization (ESI) (the electrode does not touch the analyte solution during ESI). High repeatable results could be acquired by the device with a relative standard deviation (RSD) of 1.02% for voltage output and 12.94% for MS signals of caffeine standard. Single MCF-7 cells were metabolically analyzed directly from phosphate buffered saline, and two types of untreated cerebrospinal fluid from hydrocephalus patients were distinguished with 84% accuracy. MSP-nanoESI gets rid of the bulky apparatus and could be held in hand or put into one's pocket for transportation, and it could operate for more than 4 h without recharge. We believe this device will boost scientific research and clinical usage of volume-limited biological samples with high-concentration salts in a low-cost, convenient, and rapid manner.

Biomarkers identification in follicular fluid of women with OHSS by using UPLC-MS method

To figure out the differentially changed metabolites and disturbed pathways in follicular fluid (FF) of patients with OHSS in comparison to the control group undergoing in vitro fertilization (IVF), we conducted this metabolomic analysis between two groups, the OHSS group included 30 patients treated with oocyte retrieval and developed OHSS in the next 7-14 days, while another 30 patients without OHSS tendency were selected as the control group. The FF samples were obtained during the process of oocyte retrieval. FF samples were analyzed using ultra-high liquid chromatography-tandem mass spectrometry (UPLC-MS). The results identified a total of 59 differentially changed metabolites, including 33 decreased metabolites (P < 0.01) and 26 increased metabolites (P < 0.01) in FF of OHSS compared with the control group. 12 metabolites could be the most valuable biomarkers for OHSS based on ROC results. Our correlation analyses showed that deoxyinosine levels were found positively correlated with serum estradiol (E2) levels in OHSS patients, while L-isoleucine, pyruvic acid, maleamate, and arachidonic acid were found to be positively correlated with the number of retrieved oocytes. Furthermore, 4-hydroxyphenylacetaldehyde, deoxycorticosterone, creatinine, and creatine were found to be negatively associated with serum E2 levels, while 4-hydroxyphenylacetaldehyde, L-carnitine, isovaleric acid and L-2-hydroxyglutaric acid were negatively related with the number of oocytes retrieved in OHSS patients. Taken together, our study provides better identification of OHSS FF metabolic dynamics, suggesting the metabolic compounds can be used as valuable predictors or treatment targets of OHSS.

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Cerebrospinal Fluid Amino Acid Metabolite Signatures of Diabetic Cognitive Dysfunction Based on Targeted Mass Spectrometry

BACKGROUND

Diabetic cognitive dysfunction (DCD) is one of severe diabetic complications and might develop to irreversible dementia. Early diagnosis and detection of DCD is significant for prevention and treatment.

OBJECTIVE

The main objective of this study was to investigate the amino acid profiles of rat with DCD in the cerebrospinal fluid (CSF) to distinguish the early specific biomarkers.

METHODS

In total, rats were assigned into control and model groups. Model was induced by intraperitoneal injection of streptozotocin. The Morris water maze (MWM) method was used to evaluate learning and memory in rats on the 13th week after the model established. CSF samples were collected via cisterna magna puncture at the 0th, 5th, 9th, and 13th week, and amino acids profiling of CSF samples were performed via ultra performance liquid chromatography multiple reaction monitoring mass spectrometry (UPLC-MRM-MS). The amino acid profile was processed through multivariate analysis to identify potential biomarkers, and the related metabolic pathways were analyzed by MetaboAnalyst 5.0.

RESULTS

Compared to the control group, the escape latency of the MWM was significantly prolonged in model group rats (p <  0.05). Different amino acid profiles were obtained between two groups. L-Alanine, L-Glutamine, L-Lysine, L-Serine, and L-Threonine were identified as potential biomarkers for DCD. These biomarkers are principally involved in glycine, serine, and threonine metabolism, aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and glyoxylate and dicarboxylate metabolism.

CONCLUSION

There are amino acid biomarkers in the CSF of rat with DCD. The mechanism of DCD is related to those pathways, which provide help for the early diagnosis and treatment and mechanism research.