Recent and potential developments of biofluid analyses in metabolomics

Present and foreseeable future of metabolomics in forensic analysis

The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed.

Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches

INTRODUCTION

Cardiovascular (CVD) risk assessment with traditional risk factors (age, sex, blood pressure, lipids, smoking and diabetes) has remained relatively invariant over the past decades despite some inaccuracies associated with this approach. However, the search for novel, robust and cost-effective risk markers of CVD risk is ongoing.

AREAS COVERED

A large share of the major developments in CVD risk prediction during the past five years has been made in large-scale biomarker discovery and the so called 'omics' - the rapidly growing fields of genomics, transcriptomics, epigenetics and metabolomics. This review focuses on how these new technologies are helping drive primary CVD risk estimation forward in recent years, and speculates on how they could be utilized more effectively for discovering novel risk factors in the future. Expert commentary: The search for new CVD risk factors is currently undergoing a significant revolution as the simple relationship between single risk factors and disease will have to be replaced by models that strive to integrate the whole field of omics into medicine.

Lipid and Metabolic Changes in Rheumatoid Arthritis

While the most obvious manifestations of rheumatoid arthritis (RA) involve inflammation and damage in the synovial joints, the systemic effects of the condition are widespread and life-threatening. Of particular interest is the 'lipid paradox' of RA, where patients with a numerically equivocal starting lipid profile have a significantly raised risk of cardiovascular (CV) events and response to therapy results in a 'normalization' of lipid levels and reduction in events. Changes in lipids can be seen before overt disease manifestations which suggest that they are closely linked to the more widespread inflammation-driven metabolic changes associated with tumour necrosis factor (TNF). Cachexia involves a shift in body mass from muscle to fat, which may or may not directly increase the cardiovascular risk. However, since TNF inhibition is associated with reduction in cardiovascular events, it does suggest that these widespread metabolic changes involving lipids are of importance. Analysis of single lipids or metabolites have been used to identify some of the key changes, but more recently, metabolomic and lipidomic approaches have been applied to identify a broad spectrum of small molecule changes and identify potentially altered metabolic pathways. Further work is needed to understand fully the metabolic changes in lipid profiles and identify novel ways of targeting desired profile changes, but work so far does suggest that a better understanding may allow management of patients to downregulate the systemic effects of their disease that puts them at risk of cardiovascular complications.

Urinary proteomics and metabolomics studies to monitor bladder health and urological diseases

Background

Assays of molecular biomarkers in urine are non-invasive compared to other body fluids and can be easily repeated. Based on the hypothesis that the secreted markers from the diseased organs may locally release into the body fluid in the vicinity of the injury, urine-based assays have been considered beneficial to monitoring bladder health and urological diseases. The urine proteome is much less complex than the serum and tissues, but nevertheless can contain biomarkers for diagnosis and prognosis of diseases. The urine metabolome has a much higher number and concentration of low-molecular metabolites than the serum or tissues, with a far lower lipid concentration, yet informs directly about dietary and microbial metabolism.

Discussion

We here discuss the use of mass spectrometry-based proteomics and metabolomics for urine biomarker assays, specifically with respect to the underlying mechanisms that trigger the pathological condition.

Conclusion

Molecular biomarker profiles, based on proteomics and metabolomics studies, reliably distinguish patients from healthy controls, stratify sub-populations with respect to treatment options, and predict therapeutic response of patients with urological disease.

Oesophageal squamous cell carcinoma (ESCC): Advances through omics technologies, towards ESCC salivaomics

Oesophageal Squamous Cell Carcinoma (ESCC) is one of the two main subtypes of oesophageal cancer, affecting mainly populations in Asia. Though there have been great efforts to develop methods for a better prognosis, there is still a limitation in the staging of this affection. As a result, ESCC is detected at advances stages, when the interventions on the patient do not have such a positive outcome, leading in many cases to recurrence and to a very low 5-year survival rate, causing high mortality. A way to decrease the number of deaths is the use of biomarkers that can trace the advance of the disease at early stages, when surgical or chemotherapeutic methodologies would have a greater effect on the evolution of the subject. The new high throughput omics technologies offer an unprecedented chance to screen for thousands of molecules at the same time, from which a new set of biomarkers could be developed. One of the most convenient types of samples is saliva, an accessible body fluid that has the advantage of being non-invasive for the patient, being easy to store or to process. This review will focus on the current status of the new omics technologies regarding salivaomics in ESCC, or when not evaluated yet, the achievements in related diseases.

Huang-Lian-Jie-Du decoction treated sepsis via regulating ERK and SRC/STAT3 pathways and ameliorating metabolic status

LPS disturbed the metabolomic profiles and activated the ERK and SRC/STAT3 signaling pathways of mice, and HLJDD exerted therapeutic effects on sepsis induced by LPS.

Maternal Early Pregnancy Serum Metabolites and Risk of Gestational Diabetes Mellitus

CONTEXT

Significant gaps remain in the understanding of genetic and environmental risk factors, as well as related mechanisms that contribute to gestational diabetes mellitus (GDM).

OBJECTIVES

This study aimed to investigate early pregnancy maternal serum metabolites and subsequent risk of GDM.

DESIGN

Information on participant characteristics and GDM diagnosis was collected using in-person interviews and medical record abstraction, respectively. Early pregnancy serum samples were used for nontargeted metabolite profiling using a gas chromatography-mass spectrometry platform. Lasso regression was used to select a set of metabolites that are jointly associated with GDM case-control status. We evaluated the predictive performance of the set of selected metabolites using a receiver operating characteristics curve and area under the curve.

PARTICIPANTS

A total of 178 GDM cases and 180 controls participated in a pregnancy cohort study.

RESULTS

A set of 17 metabolites (linoleic acid, oleic acid, myristic acid, d-galactose, d-sorbitol, o-phosphocolamine, l-alanine, l-valine, 5-hydroxy-l-tryptophan, l-serine, sarcosine, l-pyroglutamic acid, l-mimosine, l-lactic acid, glycolic acid, fumaric acid, and urea) differentiated GDM cases from controls. Fold changes of relative abundance of these metabolites among GDM cases compared with controls ranged from 1.47 (linoleic acid) to 0.78 (5-hydroxy-l-tryptophan). Addition of these selected metabolites to a set of well-known GDM risk factors improved the area under the curve significantly from 0.71 to 0.87 (P = 3.97E-07).

CONCLUSIONS

We identified combinations of metabolites in early pregnancy that are associated with subsequent risk of GDM. Replication of findings may improve understanding of GDM pathogenesis and may have implications for the design of GDM prevention and early diagnosis protocols.

Recent applications of CE- and HPLC-MS in the analysis of human fluids

The present review intends to cover the literature on the use of CE-/LC-MS for the analysis of human fluids, from 2010 until present. It has been planned to provide an overview of the most recent practical applications of these techniques to less extensively used human body fluids, including, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate, tear fluid, breast fluid, amniotic fluid, and cerumen. Potential pitfalls related to fluid collection and sample preparation, with particular attention to sample clean-up procedures, and methods of analysis, from the research laboratory to a clinical setting will also be addressed. While being apparent that proteomics/metabolomics represent the most prominent approaches for global identification/quantification of putative biomarkers for a variety of human diseases, evidence is also provided of the suitability of these sophisticated techniques for the detection of heterogeneous components carried by these fluids.

Relative quantification of amine-containing metabolites using isobaric N,N-dimethyl leucine (DiLeu) reagents via LC-ESI-MS/MS and CE-ESI-MS/MS

Tandem mass spectrometry (MS/MS)-based relative quantification by isobaric labeling is a useful technique to compare different metabolic expression levels in biological systems. For the first time, we have labeled primary and secondary amine-containing small molecules using 4-plex isobaric N,N-dimethyl leucine (DiLeu) to perform relative quantification. Good labeling efficiency and quantification accuracy were demonstrated with a mixture of 12 metabolite standards including amino acids and small molecule neurotransmitters. Labeling amine-containing metabolites with DiLeu reagents also enabled the separation of polar metabolites by nanoRPLC and improved the detection sensitivity by CE-ESI-MS. The 4-plex DiLeu labeling technique combined with LC-MS/MS and CE-MS/MS platforms were applied to profile and quantify amine-containing metabolites in mouse urine. The variability of concentrations of identified metabolites in urine samples from different mouse individuals was illustrated by the ratios of reporter ion intensities acquired from online data-dependent analysis.

Global metabolomic analysis of a mammalian host infected with Bacillus anthracis

Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection.

Optical characterization of core-shell quantum dots embedded in synthetic saliva: Temporal dynamics

The present work reports the spectroscopic and thermo-optical properties of CdSe/ZnS and CdSe/CdS core-shell quantum dots (QDs) embedded in synthetic saliva. Spectroscopy studies were performed applying nonfunctionalized CdSe/ZnS QDs (3.4, 3.9 and 5.1 nm cores) and hydroxyl group-functionalized ultrasmall CdSe/CdS core-shell quantum dots (1.6 nm core) suspended in artificial saliva at different potential of hydrogen (pH) values. Saliva was chosen because it is important in a variety of functions such as protecting teeth through the buffering capacity of the formed biofilm, hydration, and dental remineralization. Thermo-optical characterizations using the thermal lens (TL) technique were performed in QD-biofluids for different QD sizes and pH values (3.9-8.3) of the synthetic oral fluids. Transient TL measurements were applied to determine the fluorescence quantum efficiency (η) in QD-biomaterial systems. High η value was obtained for ultrasmall CdSe/CdS QDs. Fluorescence spectral measurements of the biomaterials support the TL results. In addition, for nonfunctionalized (3.4 and 5.1 nm) and hydroxyl group-functionalized QDs, the temporal behavior of the fluorescence spectra was accomplished about approximately 1200 h at two different biofluid pH values (3.9 and 8.3). The temporal fluorescence intensity result is dependent on the pH of the saliva in which the QDs were embedded, QD functionalization and QD sizes. The time for an approximately 50% decrease in the peak intensity fluorescence of CdSe/ZnS QDs (3.4 nm core) and ultrasmall CdSe/CdS QDs is respectively 25 h and 312 h at pH 3.9 and 48 h and 360 h at pH 8.3.

Metabolomics techniques for nanotoxicity investigations

Nanomaterials are commonly defined as engineered structures with at least one dimension of 100 nm or less. Investigations of their potential toxicological impact on biological systems and the environment have yet to catch up with the rapid development of nanotechnology and extensive production of nanoparticles. High-throughput methods are necessary to assess the potential toxicity of nanoparticles. The omics techniques are well suited to evaluate toxicity in both in vitro and in vivo systems. Besides genomic, transcriptomic and proteomic profiling, metabolomics holds great promises for globally evaluating and understanding the molecular mechanism of nanoparticle–organism interaction. This manuscript presents a general overview of metabolomics techniques, summarizes its early application in nanotoxicology and finally discusses opportunities and challenges faced in nanotoxicology.

Use of Charged Nanoparticles in NMR-Based Metabolomics for Spectral Simplification and Improved Metabolite Identification

Metabolomics aims at a complete characterization of all metabolites in biological samples in terms of both their identities and concentrations. Because changes of metabolites and their concentrations are a direct reflection of cellular activity, it allows for a better understanding of cellular processes and function to be obtained. Although NMR spectroscopy is routinely applied to complex biological mixtures without purification, overlapping NMR peaks often pose a challenge for the comprehensive and accurate identification of the underlying metabolites. To address this problem, we present a novel nanoparticle-based strategy that differentiates between metabolites based on their electric charge. By adding electrically charged silica nanoparticles to the solution NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer-sized nanoparticles. Comparison of the edited with the original spectrum significantly facilitates analysis and reduces ambiguities in the identification of metabolites. This method makes NMR directly sensitive to the detection of molecular charges at constant pH, as demonstrated here both for model mixtures and human urine. The simplicity of the approach should make it useful for a wide range of metabolomics applications.

Metabolomic Analysis Using Liquid Chromatography/Mass Spectrometry for Gastric Cancer

Metabolomics is a post-genomics research field for analysis of low molecular weight compounds in biological samples and has shown great potentials for elucidating complex mechanisms associated with diseases. However, metabolomics studies on gastric cancer (GC), which is the second leading cause of cancer death worldwide, remain scarce, and the molecular mechanisms to metabolomics phenotypes are also still not fully understood. This study reports that the metabolic pathways can be exploited as biomarkers for diagnosis and treatment of GC progression as a case study. Importantly, the urinary metabolites and metabolic patterns were analyzed by high-throughput liquid chromatography mass spectrometry (LC-MS) metabolomics strategy coupled with chemometric evaluation. Sixteen metabolites (nine upregulated and seven downregulated) were differentially expressed and may thus serve as potential urinary biomarkers for human GC. These metabolites were mainly involved in multiple metabolic pathways, including citrate cycle (malic acid, succinic acid, 2-oxoglutarate, citric acid), cyanoamino acid metabolism (glycine, alanine), primary bile acid biosynthesis (glycine, taurine, glycocholic acid), arginine and proline metabolism (urea, L-proline), and fatty acid metabolism (hexadecanoic acid), among others. Network analysis validated close association between these identified metabolites and altered metabolic pathways in a variety of biological processes. These results suggest that urine metabolic profiles have great potential in detecting GC and may aid in understanding its underlying mechanisms. It provides insight into disease pathophysiology and can serve as the basis for developing disease biomarkers and therapeutic interventions for GC diseases.

Myo-inositol improves the host's ability to eliminate balofloxacin-resistant Escherichia coli

Antibiotic-resistant mechanisms are associated with fitness costs. However, why antibiotic-resistant bacteria usually show increasing adaptation to hosts is largely unknown, especially from the host's perspective. The present study reveals the host's varied response to balofloxacin-resistant Escherichia coli (BLFX-R) using an integrated proteome and metabolome approach and identifies myo-inositol and phagocytosis-related proteins as crucial biomarkers. Originally, macrophages have an optimal attractive preference to BLFX-S due to more polarization of BLFX-S than BLFX-R, which renders faster elimination to BLFX-S than BLFX-R. The slower elimination to BLFX-R may be reversed by exogenous myo-inositol. Primarily, myo-inositol depolarizes macrophages, elevating adherence to both BLFX-S and BLFX-R. Since the altered adherence is equal to both strains, the myo-inositol-treated macrophages are free of the barrier to BLFX-R and thereby promote phagocytosis of BLFX-R. This work provides a novel strategy based on metabolic modulation for eliminating antibiotic-resistant bacteria with a high degree of host adaptation.

Diagnostic model of saliva peptide finger print analysis of oral squamous cell carcinoma patients using weak cation exchange magnetic beads

Whole saliva (WS) was used for diagnosis of oral squamous cell carcinoma (OSCC); two polypeptides may be used for OSCC diagnosis.

Saliva diagnostics utilizing nanotechnology and molecular technologies to detect oral squamous cell carcinoma (OSCC) has become an attractive field of study. However, no specific methods have been established. To refine the diagnostic power of saliva peptide fingerprints for the early detection of OSCC, we screened the expression spectrum of salivary peptides in 40 T1 stage OSCC patients (and healthy controls) using MALDI-TOF-MS combined with magnetic beads. Fifty proteins showed significantly different expression levels in the OSCC samples (P<0.05). Potential biomarkers were also predicted. The novel diagnostic proteomic model with m/z peaks of 1285.6 Da and 1432.2 Da are of certain value for early diagnosis of OSCC.

Potential of mass spectrometry metabolomics for chemical food safety

This review aims to describe the most significant applications of mass spectrometry-based metabolomics in the field of chemical food safety. A particular discussion of all the different analytical steps involved in the metabolomics workflow (sample preparation, mass spectrometry analytical platform and data processing) will be addressed.

NMR-based metabolomics: from sample preparation to applications in nutrition research

Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Measurement of these metabolites is achieved through use of analytical techniques such as NMR and mass spectrometry coupled to liquid chromatography. Combining metabolomic data with multivariate data analysis tools allows the elucidation of alterations in metabolic pathways under different physiological conditions. Applications of NMR-based metabolomics have grown in recent years and it is now widely used across a number of disciplines. The present review gives an overview of the developments in the key steps involved in an NMR-based metabolomics study. Furthermore, there will be a particular emphasis on the use of NMR-based metabolomics in nutrition research.

The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine

Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human.

High-throughput metabolomic approach revealed the acupuncture exerting intervention effects by perturbed signatures and pathways

Metabolomics can capture global changes and the overall physiological status in biochemical networks and pathways in order to elucidate sites of perturbations. High-throughput metabolomics and acupuncturology have similar characteristics such as entirety, comprehensiveness and dynamic changes, and can identify potential candidates for acupuncture effects and provide valuable information towards understanding therapy mechanisms. Saliva has recently gained popularity as a potential tool for biomarker monitoring, as its composition may potentially reflect plasma metabolite levels and, therefore, may be used as an indicator of the physiological state. However, the underlying mechanism of acupuncture, remains largely unknown, which hinders its widespread use. Acupuncture would produce unique characterization of metabolic perturbations. In this study, UPLC/ESI-HDMS in high-accuracy mode coupled with pattern recognition analysis was carried out to investigate the mechanism and saliva metabolite biomarkers for acupuncture treatment at 'Zusanli' acupoint (ST-36) as a case study. Putative metabolite identifications for these ions were obtained through a mass-based database search. As a result, the top canonical pathways including phenylalanine metabolism, alanine, aspartate and glutamate metabolism, d-glutamine and d-glutamate metabolism, and steroid hormone biosynthesis pathways were acutely perturbed. 26 differential metabolites were identified by chemical profiling, and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. These results provide useful insights into biomarker discovery utilizing metabolomics as an efficient and cost effective platform. This study opens new possibilities for the selection of saliva as a source of metabolite biomarkers representative of specific disorders.

Metabolomics for biomarker discovery in gastroenterological cancer

The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.

Plasma metabolomic biomarker panel to distinguish patients with amyotrophic lateral sclerosis from disease mimics

Our objective was to identify plasma biomarkers of ALS that can aid in distinguishing patients with ALS from those with disease mimics. In this multi-center study, plasma samples were collected from 172 patients recently diagnosed with ALS, 50 healthy controls, and 73 neurological disease mimics. Samples were analyzed using metabolomics. Using all identified biochemicals detected in > 50% of all samples in the metabolomics analysis, samples were classified as ALS or mimic with 65% sensitivity and 81% specificity by LASSO analysis (AUC of 0.76). A subset panel of 32 candidate biomarkers classified these diagnosis groups with a specificity of 90%/sensitivity 58% (AUC of 0.81). Creatinine was lower in subjects with lower revised ALS Functional Rating Scale (ALSFRS-R) scores. In conclusion, ALS can be distinguished from neurological disease mimics by global biochemical profiling of plasma samples. Our analysis identified ALS versus mimics with relatively high sensitivity. We identified a subset of 32 metabolites that identify patients with ALS with a high specificity. Interestingly, lower creatinine correlates significantly with a lower ALSFRS-R score. Finally, molecules previously reported to be important in disease pathophysiology, such as urate, are included in our metabolite panel.

Metabolomic profiling for identification of potential biomarkers in the protective effects of modified Sinisan against liver injury in dimethylnitrosamine treated rats

Metabolomics is a new platform based on the comprehensive analysis of low molecular weight metabolites and provides a powerful approach to discover biomarkers in biological systems. Modified Sinisan (MSNS), a traditional Chinese medicine formula, displayed bright prospects in the prevention and therapy of liver injury. However, its molecular mechanism of hepatoprotective effects remains unclear. This paper was designed to explore the effects and potential mechanisms of MSNS against dimethylnitrosamine-induced liver injury. Global metabolic profiling was performed by ultra-performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC/ESI-Q-TOF-MS) in conjunction with multivariate data analysis and pathway analysis. Eleven serum biomarkers were identified and pathway analysis results showed that phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, tryptophan metabolism, retinol metabolism, tyrosine metabolism were perturbed by liver injury. More importantly, MSNS has showed satisfactory pharmacological effect on liver injury through partially regulating the perturbed pathways, correlates well to the biochemical and histopathological detection results. The present study proved that the robust metabolomics approach is promising for unraveling hepatoprotective effects of MSNS and these findings provide new insights into mechanisms of the liver injury, and its pathophysiologic processes.

Promising molecular targets and biomarkers for male BPH and LUTS

Benign prostatic hyperplasia (BPH) is a major health concern for aging men. BPH is associated with urinary voiding dysfunction and lower urinary tract symptoms (LUTS), which negatively affects quality of life. Surgical resection and medical approaches have proven effective for improving urinary flow and relieving LUTS but are not effective for all men and can produce adverse effects that require termination of the therapeutic regimen. Thus, there is a need to explore other therapeutic targets to treat BPH/LUTS. Complicating the treatment of BPH/LUTS is the lack of biomarkers to effectively identify pathobiologies contributing to BPH/LUTS or to gauge successful response to therapy. This review will briefly discuss current knowledge and will highlight new studies that illuminate the pathobiologies contributing to BPH/LUTS, potential new therapeutic strategies for successfully treating BPH/LUTS, and new approaches for better defining these pathobiologies and response to therapeutics through the development of biomarkers and phenotyping strategies.

Biomarkers of Brain Injury in Cerebral Infections

BACKGROUND

Central nervous system (CNS) infections present a major burden of disease worldwide and are associated with high rates of mortality and morbidity. Swift diagnosis and initiation of appropriate treatment are vital to minimize the risk of poor outcome; however, tools are lacking to accurately diagnose infection, assess injury severity, and predict outcome. Biomarkers of structural neurological injury could provide valuable information in addressing some of these challenges.

CONTENT

In this review, we summarize experimental and clinical research on biomarkers of neurological injury in a range of CNS infectious diseases. Data suggest that in both adults and children, the biomarkers S100B and neuron-specific enlose (NSE), among others, can provide insight into the pathophysiology of CNS infection and injury severity, evolution, and response to treatment. Research into the added utility of combining a panel of biomarkers and in assessing biomarker association with clinical and radiological outcomes warrants further work. Various factors, including age, the establishment of normative values, and comparison of biomarker concentrations across different testing platforms still present challenges in biomarker application.

SUMMARY

Research regarding the value of biomarkers in CNS infections is still in its infancy. However, early evidence supports their utility in diagnosis and prognosis, and potentially as effective surrogate end points in the assessment of novel interventions.

Stable isotopic internal standard correction for quantitative analysis of hydroxyeicosatetraenoic acids (HETEs) in serum by on-line SPE-LC-MS/MS in selected reaction monitoring mode

The influence of the inclusion of a stable isotopic labeled internal standard (SIL-IS) on the quantitative analysis of hydroxyeicosatetranoic acids (HETEs) in human serum is evaluated in this research. A solid-phase extraction-liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) platform, one of the preferred approaches for targeted analysis of biofluids through the selected reaction monitoring (SRM) operational mode, was used to determine HETEs. These compounds were chosen as targeted metabolites because of their involvement in cardiovascular disease, cancer and osteoporosis. 15HETE-d8 was chosen as internal standard to evaluate matrix effects. Thus, the physico-chemical properties of the SIL-IS were the basis to evaluate the analytical features of the method for each metabolite through four calibration models. Two of the models were built with standard solutions at different concentration levels, but one of the calibration sets was spiked with an internal standard (IS). The other two models were built with the serum pool from osteoporotic patients, which was spiked at different concentrations with the target analytes. In this case, one of the serum calibration sets was also spiked with the IS. The study shows that the IS allowed noticeable correction of matrix effects for some HETE isomers at certain concentration levels, while accuracy was decreased at low concentration (15ng/mL) of them. Therefore, characterization of the method has been properly completed at different concentration levels.

Omics technologies and their applications to evaluate metal toxicity in mice M. spretus as a bioindicator

Metals are important components of living organisms since many biological functions critically depend on their interaction with some metal in the cell. However, human activities have increased toxic metal levels in the terrestrial and aquatic ecosystems affecting living organisms. The impact of metals on cellular metabolism and global homeostasis has been traditionally assessed in free-living organisms by using conventional biomarkers; however, to obtain a global vision of metal toxicity mechanisms and the responses that metals elicit in the organisms, new analytical methodologies are needed. We review the use of omics approaches to assess the response of living organisms under metal stress illustrating the possibilities of different methodologies on the basis of our previous results. Most of this research has been based on free-living mice Mus spretus, a conventional bioindicator used to monitor metal pollution in Doñana National Park (DNP) (SW Spain), which is an important European biological reserve for migrating birds affected by agricultural, mining and industrial activities. The benefits of using omic techniques such as heterologous microarrays, proteomics methodologies (2-DE, iTRAQ®), metallomics, ionomics or metabolomics has been remarked; however, the complexity of these areas requires the integration of omics to achieve a comprehensive assessment of their environmental status. This article is part of a Special Issue entitled: Environmental and structural proteomics.

BIOLOGICAL SIGNIFICANCE

This work presents new contributions in the study of environmental metal pollution in terrestrial ecosystems using Mus spretus mice as bioindicator in Doñana National Park (SW Spain) and surroundings. In addition, it has been demonstrated that the integration of omics multi-analytical approaches provides a very suitable approach for the study of the biological response and metal interactions in exposed and free-living mice (Mus musculus and Mus spretus, respectively) under metal pollution.

Untargeted metabolomic profiling in saliva of smokers and nonsmokers by a validated GC-TOF-MS method

A GC-TOF-MS method was developed and validated for a metabolic fingerprinting in saliva of smokers and nonsmokers. We validated the method by spiking 37 different metabolites and 6 internal standards to saliva between 0.1 μM and 2 mM. Intraday coefficients of variation (CVs) (accuracies) were on average, 11.9% (85.8%), 8.2% (88.9%), and 10.0% (106.7%) for the spiked levels 25, 50, and 200 μM, respectively (N = 5). Interday CVs (accuracies) were 12.4% (97%), 18.8% (95.5%), and 17.2% (105.9%) for the respective levels of 25, 50, and 200 μM (N = 5). The method was applied to saliva of smokers and nonsmokers, obtained from a 24 h diet-controlled clinical study, in order to identify biomarkers of endogenous origin, which could be linked to smoking related diseases. Automated peak picking, integration, and statistical analysis were conducted by the software tools MZmine, Metaboanalyst, and PSPP. We could identify 13 significantly altered metabolites in smokers (p < 0.05) by matching them against MS libraries and authentic standard compounds. Most of the identified metabolites, including tyramine, adenosine, and glucose-6-phosphate, could be linked to smoking-related perturbations and may be associated with established detrimental effects of smoking.

NMR metabolomics profiling of blood plasma mimics shows that medium- and long-chain fatty acids differently release metabolites from human serum albumin

Metabolite profiling by NMR of body fluids is increasingly used to successfully differentiate patients from healthy individuals. Metabolites and their concentrations are direct reporters of body biochemistry. However, in blood plasma the NMR-detected free-metabolite concentrations are also strongly affected by interactions with the abundant plasma proteins, which have as of yet not been considered much in metabolic profiling. We previously reported that many of the common NMR-detected metabolites in blood plasma bind to human serum albumin (HSA) and many are released by fatty acids present in fatted HSA. HSA is the most abundant plasma protein and main transporter of endogenous and exogenous metabolites. Here, we show by NMR how the two most common fatty acids (FAs) in blood plasma - the long-chain FA, stearate (C18:0) and medium-chain FA, myristate (C14:0) - affect metabolite-HSA interaction. Of the set of 18 common NMR-detected metabolites, many are released by stearate and/or myristate, lactate appearing the most strongly affected. Myristate, but not stearate, reduces HSA-binding of phenylalanine and pyruvate. Citrate signals were NMR invisible in the presence of HSA. Only at high myristate-HSA mole ratios 11:1, is citrate sufficiently released to be detected. Finally, we find that limited dilution of blood-plasma mimics releases HSA-bound metabolites, a finding confirmed in real blood plasma samples. Based on these findings, we provide recommendations for NMR experiments for quantitative metabolite profiling.

Microextraction by Packed Sorbent (MEPS) and Solid-Phase Microextraction (SPME) as Sample Preparation Procedures for the Metabolomic Profiling of Urine

For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS) and solid-phase microextraction (SPME), completely modified this scenario by introducing unprecedented control over this process. Urine is a biological fluid that is very interesting for metabolomics studies, allowing human health and disease characterization in a minimally invasive form. In this manuscript, we will critically review the most relevant and promising works in this field, highlighting how the metabolomic profiling of urine can be an extremely valuable tool for the early diagnosis of highly prevalent diseases, such as cardiovascular, oncologic and neurodegenerative ones.

Metabolomic analysis reveals metabolic changes caused by bisphenol A in rats

Bisphenol A (BPA) is a widely used material known to cause adverse effects in humans and other mammals. To date, little is known about the global metabolomic alterations caused by BPA using urinalysis. Sprague-Dawley rats were orally administrated BPA at the levels of 0, 0.5 μg/kg/day and 50 mg/kg/day covering a low dose and a reference dose for 8 weeks. We conducted a capillary electrophoresis in tandem with electrospray ionization time-of-flight mass spectrometry based nontargeted metabolomic analysis using rat urine. To verify the metabolic alteration at both low and high doses, reverse transcription-polymerase chain reaction (RT-PCR) and western blotting were further conducted to analyze hepatic expression of methionine adenosyltransferase Iα (Mat1a) and methionine adenosyltransferase IIα (Mat2a). Hepatic S-adenosylmethionine (SAMe) was also analyzed. A total of 199 metabolites were profiled. Statistical analysis and pathway mapping indicated that the most significant metabolic perturbations induced by BPA were the increased biotin and riboflavin excretion, increased synthesis of methylated products, elevated purine nucleotide catabolism, and increased flux through the choline metabolism pathway. We found significantly higher mRNA and protein levels of Mat1a and Mat2a, and significantly higher SAMe levels in rat liver at both low and high doses. These two genes encode critical isoenzymes that catalyze the formation of SAMe, the principal biological methyl donor involved in the choline metabolism. In conclusion, an elevated choline metabolism is underlying the mechanism of highly methylated environment and related metabolic alterations caused by BPA. The data of BPA-elevated accepted biomarkers of injury indicate that BPA induces DNA methylation damage and broad protein degradation, and the increased deleterious metabolites in choline pathway may also be involved in the toxicity of BPA.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Metabolomics in toxicology and preclinical research

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

Universal quantitative NMR analysis of complex natural samples

Nuclear Magnetic Resonance (NMR) is a universal and quantitative analytical technique. Being a unique structural tool, NMR also competes with metrological techniques for purity determination and reference material analysis. In pharmaceutical research, applications of quantitative NMR (qNMR) cover mostly the identification and quantification of drug and biological metabolites. Offering an unbiased view of the sample composition, and the possibility to simultaneously quantify multiple compounds, qNMR has become the method of choice for metabolomic studies and quality control of complex natural samples such as foods, plants or herbal remedies, and biofluids. In this regard, NMR-based metabolomic studies, dedicated to both the characterization of herbal remedies and clinical diagnosis, have increased considerably.

Thermo-optical characterization of cadmium selenide/zinc sulfide (CdSe/ZnS) quantum dots embedded in biocompatible materials

Cadmium selenide/zinc sulfide (CdSe/ZnS) core-shell quantum dots (QDs) embedded in biocompatible materials were thermally and optically characterized with a thermal lens (TL) technique. Transient TL measurements were performed with a mode-mismatched, dual-beam (excitation and probe) configuration. A thermo-optical study of the CdSe/ZnS QDs was performed for different core diameters (3.5, 4.0, 5.2, and 6.6 nm) in aqueous solution and synthetic saliva, and three different core diameters (2.4, 2.9, and 4.1 nm) embedded in restorative dental resin (0.025% by mass). The thermal diffusivity results are characteristic of the biocompatible matrices. The radiative quantum efficiencies for aqueous solution and biofluid materials are dependent on the core size of the CdSe/ZnS core-shell QDs. The results obtained from the fluorescence spectral measurements for the biocompatible materials support the TL results.

NMR-based metabolomics coupled with pattern recognition methods in biomarker discovery and disease diagnosis

Molecular biomarkers could detect biochemical changes associated with disease processes. The key metabolites have become an important part for improving the diagnosis, prognosis, and therapy of diseases. Because of the chemical diversity and dynamic concentration range, the analysis of metabolites remains a challenge. Assessment of fluctuations on the levels of endogenous metabolites by advanced NMR spectroscopy technique combined with multivariate statistics, the so-called metabolomics approach, has proved to be exquisitely valuable in human disease diagnosis. Because of its ability to detect a large number of metabolites in intact biological samples with isotope labeling of metabolites using nuclei such as H, C, N, and P, NMR has emerged as one of the most powerful analytical techniques in metabolomics and has dramatically improved the ability to identify low concentration metabolites and trace important metabolic pathways. Multivariate statistical methods or pattern recognition programs have been developed to handle the acquired data and to search for the discriminating features from biosample sets. Furthermore, the combination of NMR with pattern recognition methods has proven highly effective at identifying unknown metabolites that correlate with changes in genotype or phenotype. The research and clinical results achieved through NMR investigations during the first 13 years of the 21st century illustrate areas where this technology can be best translated into clinical practice. In this review, we will present several special examples of a successful application of NMR for biomarker discovery, implications for disease diagnosis, prognosis, and therapy evaluation, and discuss possible future improvements.