Ultra high performance liquid chromatography as a tool for the discovery and the analysis of biomarkers of diseases: A review

Simultaneous detection of trace protein biomarkers from a single drop of blood using AI-enhanced smartphone-based digital microscopy

The detection of early-stage diseases is often impeded by the low concentrations of protein biomarkers, necessitating sophisticated and costly technologies. In response, we have developed an advanced cyber-physical system that integrates blood plasma separation, biomarker detection, and analysis on a single microfluidic platform. This novel system enables the simultaneous detection of Neuron-Specific Enolase (NSE) and Carcinoembryonic Antigen (CEA) with high specificity and accuracy. Functionalized carbon dots (CDs) are employed for fluorescence-based quantification due to their superior biocompatibility, photostability, and resistance to photobleaching. The emission properties are optimized at 460 nm (blue) and 580 nm (yellow), yielding robust quantum efficiencies. The precise synthesis of CDs ensures reproducible fluorescence response with minimal background interference. A portable, smartphone-based fluorescence microscope equipped with 1000X magnification and UV excitation facilitates high-resolution image acquisition, serving as a low-cost alternative to conventional microscopy. Artificial intelligence algorithms are integrated for automated image analysis, enabling accurate quantification of biomarker concentrations. The system demonstrates impressive detection limits of 0.4 ng/mL and 0.9 ng/mL for CEA and NSE, respectively. The entire assay workflow, from sample introduction to result generation, is completed in 10 min. This integrated, portable diagnostic platform offers a transformative solution for point-of-care biomarker detection, particularly in resource-constrained settings, with the potential to democratize early disease screening and significantly reduce healthcare burdens globally.

Novel methods for the detection of glutathione by surface-enhanced Raman scattering: A perspective review

Detection of biomolecules, Glutathione (GSH) in particular, is important because it helps assess antioxidant capacity, cellular protection, detoxification processes, and potential disease associations. Monitoring glutathione levels can provide valuable information about overall health and well-being. Many medical disorders have been connected to glutathione levels. Higher glutathione levels have been seen in several cancer cell types, which may increase their resistance to radiation and chemotherapy. Glutathione levels can be measured through various methods, such as colorimetric assays and fluorescent probes. However, surface-enhanced Raman scattering (SERS) has been known as an efficient and selective technique for biomolecule detection. Here in this perspective review, we have reported two distinctive methods based on SERS technique in detection of GSH; heat-induced method and reversed reporting agent method. Several variables that can impact the detection scheme were elaborated in the "heat-induced method," including pretreatment, nanoparticle reduction time, the process temperature, the pH of the colloidal solution, the concentration of citrate buffer, and the concentration of participating nanoparticles. To choose the best reporting agent for a reverse reporting scheme using SERS approaches, several reporting agents were examined in the second method. In order to grasp the situation at hand, biomolecule detection-specifically, GSH detection schemes-was briefly discussed. SERS spectroscopy and its associated terminology were then covered followed by the perspective and outlook of GSH detection at the end. To meet the demands of real-time applications in everyday life and to enhance SERS methods for biomolecule detection-in particular, GSH detection-such a thorough investigation is unavoidable.

Technical considerations regarding saliva sample collection to achieve comparable protein identification and detection via one- and two-dimensional gel electrophoresis among humans

Background and aims

Recently, demands towards identifying various molecules in support of stress detection and potential clinical utilization are dramatically increasing. Moreover, the accuracy with which researchers quantify these informative molecules is now far more improved when compared to the past. As RNA or protein markers are conventionally detected via repeated invasive procedures from blood, it is critical to develop secure technologies to obtain the desired information via less stressful methodologies, such as saliva collection. Moreover, for superb interpretation, it became equally significant to obtain the information from the same exact specimen. RNA is easily degradable, thus it is paramount to supplement the samples with protective agents, such as RNAlater, to achieve accurate quantitative results.

Methods

In our research we investigated whether and how this commonly applied RNA protection procedure influences protein and peptide separation of the human saliva via quantitative two-dimensional protein electrophoresis.

Results

Our results revealed, in contrary to previously published data regarding plasma, the addition of RNAlater to saliva samples negatively influences isoelectric focusing and protein detection. We equally found the application oftentimes employed referred to as selective precipitation and reduction-alkylation, partially rescued separation, however, with a significant loss in protein yield and quality when compared to untreated samples.

Conclusion

Our results suggest collection of human saliva for biomarker identification must be performed with extreme diligence. We propose application of RNAlater should be avoided and snap freezing of the collected saliva is recommended when joint protein and RNA quantification is the ultimate goal.

Quantitative multiplexing of uric acid and creatinine using polydisperse plasmonic nanoparticles enabled by electrochemical-SERS and machine learning

Surface-enhanced Raman spectroscopy (SERS) is a promising technique for the detection of biomarkers, but it can struggle to quantify multiple analytes in complex fluids. This study combines electrochemical SERS (E-SERS) and machine learning for the quantitative multiplexed detection of uric acid (UA) and creatinine (CRN). Using classical polydisperse Ag nanoparticles (NPs) made by scalable synthesis, we achieved quantitative multiplexing with low limits of detection (LoDs) and high prediction accuracy, comparable to those made by sophisticated approaches. The E-SERS LoDs at the optimal applied potentials were 0.127 μM and 0.354 μM for UA and CRN respectively, compared to 0.504 μM and 1.02 μM for conventional SERS (recorded at 0 V). By collecting a multi-dimensional E-SERS dataset and applying a two-step partial least squares regression - multilayer perceptron (PLSR-MLP) machine learning algorithm, we were able to identify the analyte concentrations in unseen spectra with a prediction accuracy of 0.94. This research demonstrates the potential of E-SERS and machine learning for multiplexed detection in clinical settings.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS

Introduction

Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy.

Methods

Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS.

Results

A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy.

Discussion

This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Electrochemical aptasensor based on the engineered core-shell MOF nanostructures for the detection of tumor antigens

It is essential to develop ultrasensitive biosensors for cancer detection and treatment monitoring. In the development of sensing platforms, metal-organic frameworks (MOFs) have received considerable attention as potential porous crystalline nanostructures. Core-shell MOF nanoparticles (NPs) have shown different diversities, complexities, and biological functionalities, as well as significant electrochemical (EC) properties and potential bio-affinity to aptamers. As a result, the developed core-shell MOF-based aptasensors serve as highly sensitive platforms for sensing cancer biomarkers with an extremely low limit of detection (LOD). This paper aimed to provide an overview of different strategies for improving selectivity, sensitivity, and signal strength of MOF nanostructures. Then, aptamers and aptamers-modified core-shell MOFs were reviewed to address their functionalization and application in biosensing platforms. Additionally, the application of core-shell MOF-assisted EC aptasensors for detection of several tumor antigens such as prostate-specific antigen (PSA), carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA-125), cytokeratin 19 fragment (CYFRA21-1), and other tumor markers were discussed. In conclusion, the present article reviews the advancement of potential biosensing platforms toward the detection of specific cancer biomarkers through the development of core-shell MOFs-based EC aptasensors.

LC-MS/MS: A sensitive and selective analytical technique to detect COVID-19 protein biomarkers in the early disease stage

INTRODUCTION

The COVID-19 outbreak has put enormous pressure on the scientific community to detect infection rapidly, identify the status of disease severity, and provide an immediate vaccine/drug for the treatment. Relying on immunoassay and a real-time reverse transcription polymerase chain reaction (rRT-PCR) led to many false-negative and false-positive reports. Therefore, detecting biomarkers is an alternative and reliable approach for determining the infection, its severity, and disease progression. Recent advances in liquid chromatography and mass spectrometry (LC-MS/MS) enable the protein biomarkers even at low concentrations, thus facilitating clinicians to monitor the treatment in hospitals.

AREAS COVERED

This review highlights the role of LC-MS/MS in identifying protein biomarkers and discusses the clinically significant protein biomarkers such as Serum amyloid A, Interleukin-6, C-Reactive Protein, Lactate dehydrogenase, D-dimer, cardiac troponin, ferritin, Alanine transaminase, Aspartate transaminase, gelsolin and galectin-3-binding protein in COVID-19, and their analysis by LC-MS/MS in the early stage.

EXPERT OPINION

Clinical doctors monitor significant biomarkers to understand, stratify, and treat patients according to disease severity. Knowledge of clinically significant COVID-19 protein biomarkers is critical not only for COVID-19 caused by the coronavirus but also to prepare us for future pandemics of other diseases in detecting by LC-MS/MS at the early stages.

Ultra-performance convergence chromatography tandem mass spectrometry analysis of adrenal and gonadal steroid hormones in southern white rhinoceros(Ceratotherium simum simum) faeces and serum

Steroid hormone analysis is routinely undertaken in the assessment of stress response and reproductive function in the management of both captive and free-ranging wildlife species. Faecal samples have become the preferred sample type for analysis as collection is non-invasive and easily assessable. These investigations are generally aimed at aiding successful translocations, enhanced survival outcomes in captivity and improvement of reproductive rate. Immunoassays are the most common approach in the analysis of hormones, particularly in the case of the southern white rhinoceros (Ceratotherium simum simum). Non-specificity, attributed to structural similarity of steroid metabolites impedes accurate evaluations which can be eliminated by chromatographic techniques which are more specific, selective and provide comprehensive analyses. This study developed and validated three methods using ultra-performance convergence chromatography tandem mass spectrometry for the assessment of classical androgens, progestogens and adrenal steroids, as well as the C11-oxy androgens and C11-oxy progestogens in serum and faeces from white rhinoceros. The limit of detection and quantification were determined for each steroid, parameters such as accuracy (<19.8 % RSD) and precision (<20.2 % RSD) were established with recovery, matrix effect, and process efficiency within acceptable limits. Subsequent analysis of serum and faecal samples from five white rhinoceros identified novel steroids for the first time in this species. In addition to the classical adrenal steroids, the following C11-oxy steroids were detected in faecal samples: 11α-hydroxydihydroprogesterone (168 ng/g), 11α-hydroxyprogesterone (125.9 ng/g), 11β-hydroxyprogesterone (210.2 ng/g) and 11-ketoandrostenedione (3.3-19.6 ng/g) with 11-deoxycortisol being the major glucocorticoid (24.2-67.3 ng/g) together with 21-deoxycortisone (40.7 ng/g) and deoxycorticosterone (7.6-14.6 ng/g). In serum samples 11β-hydroxyandrostenedione (0.35-2.34 ng/mL) and 11β-hydroxytestosterone (0.18-1.62 ng/mL) were the predominant androgens with cortisol (5.8-20.5 ng/mL), the predominant glucocorticoid, while corticosterone, 18-hydroxycorticosterone and aldosterone were also detected. These methods can be applied independently to assess either androgens, progestogens, or adrenal steroid panels or in combination to assess the cohort of gonadal and adrenal steroids in faeces and/or serum, in southern white rhinoceros as well as other wildlife species. Analysis would enable the accurate assessment of reproductive health and stress responses while also distinguishing between stress and distress thus contributing to the conservation of wildlife species.

Associations of Hemoglobin Adducts of Acrylamide and Glycidamide with Prevalent Metabolic Syndrome in a Nationwide Population-Based Study

Environmental and dietary exposures to acrylamide (AA) have been linked with various metabolic-related outcomes, but the results are mixed. However, the association between long-term exposure to AA and the prevalence of metabolic syndrome (MetS) remains unknown. In this study, we aimed to assess the relationship between hemoglobin adducts of AA, biomarkers of internal exposure to AA, and MetS prevalence among a U.S. nationwide population. MetS patients were defined by meeting three or more of the following five characteristics: elevated blood pressure, high fasting glucose, abdominal obesity, hypertriglyceridemia, and lower high-density lipoprotein cholesterol (HDL-C). Multivariate-adjusted logistic regression models and restricted cubic spline models were used to analyze the associations between AA hemoglobin biomarkers and MetS prevalence. A total of 1552 MetS cases were documented. After adjustment for the potential confounders, the odds ratios (95% confidence intervals) of MetS prevalence in the highest quartile of AA hemoglobin biomarkers were 0.60 (0.40-0.89), 1.26 (0.84-1.89), 0.93 (0.71-1.21), and 1.61 (1.18-2.20) for HbAA, HbGA, the sum of HbAA and HbGA (HbAA + HbGA), and the ratio of HbGA to HbAA (HbGA/HbAA), compared with the lowest quartile, respectively. HbAA was significantly and inversely associated with blood pressure, fasting glucose, abdominal obesity, hypertriglyceridemia, and low HDL-C, while the HbGA/HbAA ratio was also positively associated with abdominal obesity, hypertriglyceridemia, and low HDL-C. The restricted cubic spline models revealed a positive relationship between the HbGA/HbAA ratio and the prevalence of MetS, while the HbAA level was inversely associated with MetS prevalence. Our current findings provided epidemiological evidence that HbAA and the HbGA/HbAA ratio were significantly associated with MetS prevalence among general U.S. adults. Further studies should be conducted to examine the association between internal exposure to AA and MetS prevalence.

Fast determination of 16 circulating neurotransmitters and their metabolites in plasma samples of spontaneously hypertensive rats intervened with five different Uncaria

This study aimed to establish a sensitive, reproducible, and rapid liquid chromatography method with tandem mass spectrometry detection to perform simultaneous quantitative analysis of 16 neurotransmitters and their metabolites in rat plasma, including levodopa, dopamine, norepinephrine, epinephrine, L-tryptophan, kynurenic acid, serotonin, melatonin, choline, acetylcholine, histamine, phenylethylamine, as well as excitatory (L-glutamic acid and L-aspartic acid) and inhibitory (γ-aminobutyric acid and L-glycine) neurotransmitters. These analytes were measured by ultra-high performance chromatography coupled with triple quadrupole mass spectrometry using a hydrophilic interaction chromatographic column (ethylene-bridged hybrid amide column). The internal standards of stable isotope labeling were used to improve the reliability of the results. Our method provided high linearity for all neurotransmitters (for all coefficients measured > 0.99), with inter- and intra-day accuracy from -14.82% to 17.49% and precision was between 0.89% and 17.70%. The method was subsequently verified in an animal study, where the intervention of five different Uncarias, the traditional Chinese medicine with hypotensive effects, was applied to the spontaneously hypertensive rats (SHRs). SHRs showed dysregulated plasma kynurenic acid, acetylcholine, and norepinephrine levels, and these neuroactive analytes were significantly restored by Uncaria treatment compared with the model group (SHR group). Compared with captopril, included as a positive control for its hypotensive effect, Uncaria had more effects on perturbing the levels of plasma neurotransmitters, which might indicate Uncaria's potential in treating symptoms related to the nervous system. These results suggested that the changes in the neurotransmitters and their metabolites in plasma may be related to the pathogenesis of hypertension. It also provided valuable information about the action mechanisms of Uncaria on its hypotensive effects.

Plasma Targeted Metabolomics Analysis for Amino Acids and Acylcarnitines in Patients with Prediabetes, Type 2 Diabetes Mellitus, and Diabetic Vascular Complications

BACKGROUND

We hypothesized that specific amino acids or acylcarnitines would have benefits for the differential diagnosis of diabetes. Thus, a targeted metabolomics for amino acids and acylcarnitines in patients with diabetes and its complications was carried out.

METHODS

A cohort of 54 normal individuals and 156 patients with type 2 diabetes mellitus and/or diabetic complications enrolled from the First Affiliated Hospital of Jinzhou Medical University was studied. The subjects were divided into five main groups: normal individuals, impaired fasting glucose, overt diabetes, diabetic microvascular complications, and diabetic peripheral vascular disease. The technique of tandem mass spectrometry was applied to obtain the plasma metabolite profiles. Metabolomics multivariate statistics were applied for the metabolic data analysis and the differential metabolites determination.

RESULTS

A total of 10 cross-comparisons within diabetes and its complications were designed to explore the differential metabolites. The results demonstrated that eight comparisons existed and yielded significant metabolic differences. A total number of 24 differential metabolites were determined from six selected comparisons, including up-regulated amino acids, down-regulated medium-chain and long-chain acylcarnitines. Altered differential metabolites provided six panels of biomarkers, which were helpful in distinguishing diabetic patients.

CONCLUSION

Our results demonstrated that the biomarker panels consisted of specific amino acids and acylcarnitines which could reflect the metabolic variations among the different stages of diabetes and might be useful for the differential diagnosis of prediabetes, overt diabetes and diabetic complications.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions - kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

Simultaneous determination of the herbicide bixlozone and its metabolites in plant and animal samples by liquid chromatography-tandem mass spectrometry

Tracing the herbicide bixlozone and its metabolites in food is necessary to assess their risks to human health. In the study, a rapid and effective analytical method using the quick, easy, cheap, effective, rugged, and safe method for the simultaneous determination of bixlozone and its metabolites (2,4-dichlorobenzoic acid, 3-hydroxy-propanamide-bixlozone, and 5'-hydroxy-bixlozone) in plant and animal samples (tomato, cucumber, apple, wheat flour, meat, milk, and egg) was developed based on ultra high performance liquid chromatography-tandem mass spectrometry. The method was validated based on the linearity (R²  > 0.99), sensitivity (limit of quantification = 0.01 mg/kg), recovery (70.2-115.1%), and precision (intraday 1.2-17.6%, interday 0.3-16.0%). Detection was achieved within 6.0 min. The method is reliable for the determination of four target compounds in all seven matrices. The satisfactory validation criteria and successful application show that the proposed methodology is suitable for the detection of four target compounds in real matrices.

Comprehensive Metabolomics Study in Children With Graves' Disease

OBJECTIVE

Graves' disease (GD) related hyperthyroidism (HT) has profound effects on metabolic activity and metabolism of macromolecules affecting energy homeostasis. In this study, we aimed to get a comprehensive understanding of the metabolic changes and their clinical relevance in GD children.

METHODS

We investigated serum substances from 30 newly diagnosed GD children and 30 age- and gender-matched healthy controls. We explored the metabolomics using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) analysis, and then analyzed the metabolomic data via multivariate statistical analysis.

RESULTS

By untargeted metabolomic analysis, a total of 730 metabolites were identified in all participants, among which 48 differential metabolites between GD and control groups were filtered out, including amino acids, dipeptides, lipids, purines, etc. Among these metabolites, 33 were detected with higher levels, while 15 with lower levels in GD group compared to controls. Pathway analysis showed that HT had a significant impact on aminoacyl-transfer ribonucleic acid (tRNA) biosynthesis, several amino acids metabolism, purine metabolism, and pyrimidine metabolism.

CONCLUSION

In this study, via untargeted metabolomics analysis, significant variations of serum metabolomic patterns were detected in GD children.

Association of urinary caffeine and caffeine metabolites with cardiovascular disease risk in adults

OBJECTIVES

Studies have shown that the consumption of a moderate amount of caffeine is associated with a reduced risk of cardiovascular disease (CVD) and may even be protective against CVD. The purpose of the current study was to evaluate the association between urinary caffeine and its related metabolites and CVD risk in a national representative sample of US adults.

METHODS

We analyzed cross-sectional data from the US National Health and Nutrition Examination Survey from 2009 and 2010. The associations between the levels of urinary caffeine metabolites and self-reported CVD, including congestive heart failure, coronary heart disease, angina, heart attack, and stroke, were examined separately in men and women using multivariate logistic regression models adjusted for covariates.

RESULTS

In total, 1916 participants (910 men and 1006 women) were included in the analysis. Among women, the odds ratios of CVD in the highest quartiles of 1,3-dimethylxanthine and 1,3,7-trimethylxanthine were 0.33 (95% confidence interval [CI], 0.12-0.92) and 0.35 (95% CI, 0.13-0.93), respectively, compared with the lowest quartiles. Each one-unit (µmol/L) increase in theophylline concentration was associated with a 0.24-mg/dL increase in high-density lipoprotein cholesterol in the fully adjusted model. Among men, no significant association was observed between urinary caffeine metabolites and CVD. Regarding the subtypes of CVD, compared with women in the lowest quartile for 1,3-dimethylxanthine and 1,3,7-trimethylxanthine, the odds of coronary heart disease decreased by 90% (95% CI, -99% to -11%) and 97% (95% CI, -99% to -47%), respectively, in those in the highest quartile.

CONCLUSIONS

Urinary 1,3-dimethylxanthine and 1,3,7-trimethylxanthine were significantly and inversely associated with CVDs in women. Additional studies are needed to further confirm the results of this study and explore the underlying mechanisms.<END ABSTRACT>.

Untargeted metabolomics analysis on Cicer arietinium L.-Induced Amelioration in T2D rats by UPLC-Q-TOF-MS/MS

ETHNOPHARMACOLOGICAL RELEVANCE

Cicer arietinium L., which belongs to Cicer genus, was not only a kind of traditional Chinese medicines (TCM) recorded in Pharmacopoeia of the People's Republic of China (version 2015), but also a kind of Uighur antidiabetic medicines. It has been used as an adjuvant drug or functional food for thousand years in Xinjiang province, China. However, the mechanisms of C. arietinium treatment in T2D have not been fully understood especially on the perspective of metabolomics.

AIM OF THE STUDY

To clarify the potential mechanisms of C. arietinium treatment in T2D from the perspective of metabolomics since T2D is indeed a kind of metabolic syndromes.

MATERIALS AND METHODS

T2D rat model was built by HFD for 4 weeks, combining with STZ administration. T2D rats were administrated C. arietinium extraction or metformin (positive control) for 4 weeks. UPLC-Q-TOF-MS was applied to screen and identify differential metabolites among groups.

RESULTS

After 4 weeks of treatments, IR and inflammation were greatly ameliorated in C. arietinium group. And the therapeutic efficiency of C. arietinium treatment was comparable to metformin treatment. Differential metabolites related to C. arietinium treatment, including acylcarnitines, amino acid related metabolites and organic acids, were further used to indicate relevant pathways in T2D rats, including glyoxylate and dicarboxylate metabolism, tricarboxylic acid cycle, vitamin B6 metabolism and energy metabolism.

CONCLUSIONS

In summary, C. arietinium treatment could effectively alleviate diabetic symptoms and regulate metabolic disorders in T2D rats.

An improved extraction method enables the comprehensive analysis of lipids, proteins, metabolites and phytohormones from a single sample of leaf tissue under water-deficit stress

Phytohormones play essential roles in the regulation of growth and development in plants. Plant hormone profiling is therefore essential to understand developmental processes and the adaptation of plants to biotic and/or abiotic stresses. Interestingly, commonly used hormone extraction and profiling methods do not adequately resolve other molecular entities, such as polar metabolites, lipids, starch and proteins, which would be required to comprehensively describe the continuing biological processes at a systematic level. In this article we introduce an updated version of a previously published liquid:liquid metabolite extraction protocol, which not only allows for the profiling of primary and secondary metabolites, lipids, starch and proteins, but also enables the quantitative analysis of the major plant hormone classes, including abscisic acid, auxins, cytokinins, jasmonates and salicylates, from a single sample aliquot. The optimization of the method, which uses the introduction of acidified water, enabling the complete purification of major plant hormones into the organic (methyl-tert-butyl-ether) phase, eliminated the need for solid-phase extraction for sample clean-up, and therefore reduces both sampling time and cost. As a proof-of-concept analysis, Arabidopsis thaliana plants were subjected to water-deficit stress, which were then profiled for hormonal, metabolic, lipidomic and proteomic changes. Surprisingly, we determined not only previously described molecular changes but also significant changes regarding the breakdown of specific galactolipids, followed by the substantial accumulation of unsaturated fatty-acid derivatives and diverse jasmonates in the course of adaptation to water-deficit stress.

A Critical Review of Bottom-Up Proteomics: The Good, the Bad, and the Future of this Field

Proteomics is the field of study that includes the analysis of proteins, from either a basic science prospective or a clinical one. Proteins can be investigated for their abundance, variety of proteoforms due to post-translational modifications (PTMs), and their stable or transient protein–protein interactions. This can be especially beneficial in the clinical setting when studying proteins involved in different diseases and conditions. Here, we aim to describe a bottom-up proteomics workflow from sample preparation to data analysis, including all of its benefits and pitfalls. We also describe potential improvements in this type of proteomics workflow for the future.

Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.

Analyzing protein glycosylation using UHPLC: a review

Ultrahigh performance liquid chromatography (UHPLC) uses small stationary-phase particle size (<2 μm) and high pressure in order to achieve rapid and efficient separations. The speed and high resolution of this method has made it a valuable tool for analyzing the complex glycosylation patterns found in post-translationally modified proteins. This article highlights the differences between UHPLC and HPLC and reviews recent UHPLC applications and developments for detecting glycosylated proteins (e.g., glycomics studies) and characterizing glycosylated pharmaceuticals (e.g., monoclonal antibodies).

Exposure to acrylamide and the risk of cardiovascular diseases in the National Health and Nutrition Examination Survey 2003-2006

BACKGROUND

Long-term exposure to acrylamide (AA) from diet sources may induce oxidative stress and chronic inflammation. However, the association between AA exposure and the prevalence of cardiovascular diseases (CVD) remains unclear.

OBJECTIVES

We aimed to examine the association between blood exposure levels of AA biomarkers and the prevalence of main types of CVD in a general population of US adults.

METHODS

We analyzed the associations between AA hemoglobin biomarkers [hemoglobin adducts of acrylamide (HbAA) and glycidamide (HbGA), sum of HbAA and HbGA (HbAA+HbGA), and ratio of HbGA to HbAA (HbGA:HbAA)] and self-reported diagnosis of CVD in 8290 adults (≥20 years of age) from the National Health and Nutrition Examination Survey (NHANES) 2003-2006. Multivariable logistic regression models were employed for estimating the associations in three groups classified by the combination of smoking status and serum cotinine levels.

RESULTS

In people exposed to environmental tobacco smoke (n = 4670), HbGA, HbAA+HbGA, and HbGA:HbAA were significantly and inversely associated with the prevalence of total CVD (p < 0.0001, p = 0.0155, and p = 0.0014 for trend, respectively) after adjusting for various covariates. The odd ratios (ORs) for total CVD in the highest quartiles of HbGA, HbAA+HbGA, and HbGA:HbAA were 0.311 [95% confidence interval (CI): 0.193-0.500], 0.664 (95% CI: 0.485-0.911), and 0.495 (95% CI: 0.326-0.752) when compared with the individual lowest quartiles. In active smokers (n = 2432), HbAA was positively associated with CVD risk (p = 0.0088 for trend), while HbGA:HbAA was inversely related to total CVD (p = 0.0137 for trend). However, no significant associations of any AA hemoglobin biomarker with total and individual CVD prevalence were observed in the nonsmoking group (n = 1188).

CONCLUSIONS

AA hemoglobin biomarkers are significantly associated with CVD in the active smoking group and the group exposed to environmental tobacco smoke but not in the nonsmoking group. Further prospective studies should clarify the causal relationship between HbAA and HbGA and the prevalence of CVD.

2D-DIGE and Fluorescence Image Analysis

2D-DIGE is still a very widespread technique in proteomics for the identification of panels of biomarkers, allowing to tackle with some important drawback of classical two-dimensional gel-electrophoresis. However, once 2D-gels are obtained, they must undergo a quite articulated multistep image analysis procedure before the final differential analysis via statistical mono- and multivariate methods. Here, the main steps of image analysis software are described and the most recent procedures reported in the literature are briefly presented.

Current state of bioanalytical chromatography in clinical analysis

Chromatographic methods have become popular in clinical analysis in both routine and research laboratories.

A novel liquid chromatography/mass spectrometry method for determination of neurotransmitters in brain tissue: Application to human tauopathies

Neurotransmitters, small molecules widely distributed in the central nervous system are essential in transmitting electrical signals across neurons via chemical communication. Dysregulation of these chemical signaling molecules is linked to numerous neurological diseases including tauopathies. In this study, a precise and reliable liquid chromatography method was established with tandem mass spectrometry detection for the simultaneous determination of aspartic acid, asparagine, glutamic acid, glutamine, γ-aminobutyric acid, N-acetyl-l-aspartic acid, pyroglutamic acid, acetylcholine and choline in human brain tissue. The method was successfully applied to the analysis of human brain tissues from three different tauopathies; corticobasal degeneration, progressive supranuclear palsy and parkinsonism-dementia complex of Guam. Neurotransmitters were analyzed on ultra-high performance chromatography (UHPLC) using an ethylene bridged hybrid amide column coupled with tandem mass spectrometry (MS/MS). Identification and quantification of neurotransmitters was carried out by ESI+ mass spectrometry detection. We optimized sample preparation to achieve simple and fast extraction of all nine analytes. Our method exhibited an excellent linearity for all analytes (all coefficients of determination >0.99), with inter-day and intra-day precision yielding relative standard deviations 3.2%-11.2% and an accuracy was in range of 92.6%-104.3%. The present study, using the above method, is the first to demonstrate significant alterations of brain neurotransmitters caused by pathological processes in the brain tissues of patient with three different tauopathies.

Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome

Global profiling of xenobiotics in human matrices in an untargeted mode is gaining attention for studying the environmental chemical space of the human exposome. Defined as the study of a comprehensive inclusion of environmental influences and associated biological responses, human exposome science is currently evolving out of the metabolomics science. In analogy to the latter, the development and applications of high resolution mass spectrometry (HRMS) has shown potential and promise to greatly expand our ability to capture the broad spectrum of environmental chemicals in exposome studies. HRMS can perform both untargeted and targeted analysis because of its capability of full- and/or tandem-mass spectrum acquisition at high mass accuracy with good sensitivity. The collected data from target, suspect and non-target screening can be used not only for the identification of environmental chemical contaminants in human matrices prospectively but also retrospectively. This review covers recent trends and advances in this field. We focus on advances and applications of HRMS in human biomonitoring studies, and data acquisition and mining. The acquired insights provide stepping stones to improve understanding of the human exposome by applying HRMS, and the challenges and prospects for future research.

Application and Uses of Electronic Noses for Clinical Diagnosis on Urine Samples: A Review

The electronic nose is able to provide useful information through the analysis of the volatile organic compounds in body fluids, such as exhaled breath, urine and blood. This paper focuses on the review of electronic nose studies and applications in the specific field of medical diagnostics based on the analysis of the gaseous headspace of human urine, in order to provide a broad overview of the state of the art and thus enhance future developments in this field. The research in this field is rather recent and still in progress, and there are several aspects that need to be investigated more into depth, not only to develop and improve specific electronic noses for different diseases, but also with the aim to discover and analyse the connections between specific diseases and the body fluids odour. Further research is needed to improve the results obtained up to now; the development of new sensors and data processing methods should lead to greater diagnostic accuracy thus making the electronic nose an effective tool for early detection of different kinds of diseases, ranging from infections to tumours or exposure to toxic agents.

Analytical pitfalls and challenges in clinical metabolomics

Metabolomics-based strategies have become an integral part of modern clinical research, allowing for a better understanding of pathophysiological conditions and disease mechanisms, as well as providing innovative tools for more adequate diagnostic and prognosis approaches. Metabolomics is considered an essential tool in precision medicine, which aims for personalized prevention and tailor-made treatments. Nevertheless, multiple pitfalls may be encountered in clinical metabolomics during the entire workflow, hampering the quality of the data and, thus, the biological interpretation. This review describes the challenges underlying metabolomics-based experiments, discussing step by step the potential pitfalls of the analytical process, including study design, sample collection, storage, as well as preparation, chromatographic and electrophoretic separation, detection and data analysis. Moreover, it offers practical solutions and strategies to tackle these challenges, ensuring the generation of high-quality data.

Metabolomics study on the effects of Buchang Naoxintong capsules for treating cerebral ischemia in rats using UPLC-Q/TOF-MS

ETHNOPHARMACOLOGICAL RELEVANCE

Buchang Naoxintong Capsules (BNC) are widely prescribed in Chinese medicine for the treatment of cerebrovascular and cardiovascular diseases. However, the therapeutic effects and mechanisms are not yet well understood.

MATERIALS AND METHODS

In this study, a UPLC/TOF-MS-based metabolomic study was conducted to explore potential biomarkers that will increase our understanding of cerebral ischemia and to assess the integral efficacy of BNC in a middle cerebral artery occlusion (MCAO) rat model. Plasma metabolic profiles were analyzed and metabolic biomarkers were identified through multivariate data analysis.

RESULTS

Clear separations were observed between the sham, MCAO and BNC-treated groups. We identified 28 biomarkers in the MCAO rats using variable importance for the projections (VIP) values (VIP>1) and a t-test (P<0.05). The identified biomarkers were mainly related to disturbances in monoamine neurotransmitter metabolism, amino acid metabolism, energy metabolism and lipid metabolism. Moreover, a correlation network diagram of the plasma biomarkers perturbed by MCAO was constructed. Some biomarkers, such as glutamine, PE (17:0), LysoPE (20:1), LysoPE (24:0), and the ratios of LysoPE (24:1) to LysoPE (24:0), LysoPE (24:2) to LysoPE (24:0), showed obvious changes and a tendency for returning to baseline values in BNC-treated MCAO rats. In addition, MCAO rats receiving BNC treatment had improved neurological deficits and reduced cerebral infarct size demonstrating the therapeutic potential of BNC for treating cerebral ischemia.

CONCLUSION

This study provides a useful approach for exploring the mechanism of MCAO-induced cerebral ischemia and evaluating the efficacy of BNC.

Metabonomics: analytical techniques and associated chemometrics at a glance

Without any prior knowledge, it can be an overwhelming task to get an overview of and insight into the field of metabonomics. This chapter introduces the concept of metabonomics, the most commonly applied techniques, and the inevitably indispensable multivariate statistical analyses in an easily digestible yet comprehensive manner.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.

Lipidomics: new insight into kidney disease

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.

Structure-function analysis of NEET proteins uncovers their role as key regulators of iron and ROS homeostasis in health and disease

A novel family of 2Fe-2S proteins, the NEET family, was discovered during the last decade in numerous organisms, including archea, bacteria, algae, plant and human; suggesting an evolutionary-conserved function, potentially mediated by their CDGSH Iron-Sulfur Domain. In human, three NEET members encoded by the CISD1-3 genes were identified. The structures of CISD1 (mitoNEET, mNT), CISD2 (NAF-1), and the plant At-NEET uncovered a homodimer with a unique "NEET fold", as well as two distinct domains: a beta-cap and a 2Fe-2S cluster-binding domain. The 2Fe-2S clusters of NEET proteins were found to be coordinated by a novel 3Cys:1His structure that is relatively labile compared to other 2Fe-2S proteins and is the reason of the NEETs' clusters could be transferred to apo-acceptor protein(s) or mitochondria. Positioned at the protein surface, the NEET's 2Fe-2S's coordinating His is exposed to protonation upon changes in its environment, potentially suggesting a sensing function for this residue. Studies in different model systems demonstrated a role for NAF-1 and mNT in the regulation of cellular iron, calcium and ROS homeostasis, and uncovered a key role for NEET proteins in critical processes, such as cancer cell proliferation and tumor growth, lipid and glucose homeostasis in obesity and diabetes, control of autophagy, longevity in mice, and senescence in plants. Abnormal regulation of NEET proteins was consequently found to result in multiple health conditions, and aberrant splicing of NAF-1 was found to be a causative of the neurological genetic disorder Wolfram Syndrome 2. Here we review the discovery of NEET proteins, their structural, biochemical and biophysical characterization, and their most recent structure-function analyses. We additionally highlight future avenues of research focused on NEET proteins and propose an essential role for NEETs in health and disease. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases.

Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics has been a subject of dramatic developments over the past decade. This review focuses on state of the art in LC-MS-based lipidomics, covering all the steps of global lipidomic profiling. On the basis of review of 185 original papers and application notes, we can conclude that typical LC-MS-based lipidomics methods involve: (1) extraction using chloroform/MeOH or MTBE/MeOH protocols, both with addition of internal standards covering each lipid class; (2) separation of lipids using short microbore columns with sub-2-μm or 2.6-2.8-μm (fused-core) particle size with C18 or C8 sorbent with analysis time <30 min; (3) electrospray ionization in positive- and negative-ion modes with full spectra acquisition using high-resolution MS with capability to MS/MS. Phospholipids (phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, phosphatidylserines, phosphatidylglycerols) followed by sphingomyelins, di- and tri-acylglycerols, and ceramides were the most frequently targeted lipid species.

Ultra-performance liquid chromatography-mass spectrometry as a sensitive and powerful technology in lipidomic applications

Lipidomics, the comprehensive illumination of lipid-based information in biology systems, involves in identifying lipids and profiling lipids and lipid-derived mediators. The development of lipidomics enables the characterization of lipid species and detailed lipid profiling in body fluid, tissue or cell, and allows for a wider understanding of the biological roles of lipid networks. Lipidomic research has been greatly facilitated by recent advances in ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and involved in lipid extraction, lipid identification and data analysis supporting applications from qualitative and quantitative assessment of multiple lipid species. UPLC technique, different mass spectrometry technique, lipid extraction and data analysis in lipidomics are reviewed. Afterwards, examples are provided on the use of UPLC-MS for finding lipid biomarkers in disease, drug, food, nutrition and plant fields. We also discuss the UPLC-MS-based lipidomics for the future perspectives and their potential problems.

A label-free electrochemical immunosensor based on an ionic organic molecule and chitosan-stabilized gold nanoparticles for the detection of cardiac troponin T

A immunosensor based on an ionic organic molecule and chitosan-stabilized gold nanoparticles was developed for the detection of cardiac troponin T (cTnT).