The Impact of Delayed Storage on the Measured Proteome and Metabolome of Human Cerebrospinal Fluid

Impact of Cold Ischemia on the Stability of 1H-MRS-Detected Metabolic Profiles of Ovarian Cancer Specimens

Proton magnetic resonance spectroscopy (1H-MRS) of surgically collected tumor specimens may contribute to investigating cancer metabolism and the significance of the "total choline" (tCho) peak (3.2 ppm) as malignancy and therapy response biomarker. To ensure preservation of intrinsic metabolomic information, standardized handling procedures are needed. The effects of time to freeze (cold ischemia) were evaluated in (a) surgical epithelial ovarian cancer (EOC) specimens using high-resolution (HR) 1H-MRS (9.4 T) of aqueous extracts and (b) preclinical EOC samples (xenografts in SCID mice) investigated by in vivo MRI-guided 1H-MRS (4.7 T) and by HR-1H-MRS (9.4 T) of tumor extracts or intact fragments (using magic-angle-spinning (MAS) technology). No significant changes were found in the levels of 27 of 29 MRS-detected metabolites (including the tCho profile) in clinical specimens up to 2 h cold ischemia, besides an increase in lysine and a decrease in glutathione. EOC xenografts showed a 2-fold increase in free choline within 2 h cold ischemia, without further significant changes for any MRS-detected metabolite (including phosphocholine and tCho) up to 6 h. At shorter times (≤1 h), HR-MAS analyses showed unaltered tCho components, along with significant changes in lactate, glutamate, and glutamine. Our results support the view that a time to freeze of 1 h represents a safe threshold to ensure the maintenance of a reliable tCho profile in EOC specimens.

Pre-analytical aspects in metabolomics of human biofluids - sample collection, handling, transport, and storage

Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).

Stability of Metabolomic Content during Sample Preparation: Blood and Brain Tissues

Thermal and enzymatic reactions can significantly change the tissue metabolomic content during the sample preparation. In this work, we evaluated the stability of metabolites in human whole blood, serum, and rat brain, as well as in metabolomic extracts from these tissues. We measured the concentrations of 63 metabolites in brain and 52 metabolites in blood. We have shown that metabolites in the extracts from biological tissues are stable within 24 h at 4 °C. Serum and whole blood metabolomes are also rather stable, changes in metabolomic content of the whole blood homogenate become apparent only after 1–2 h of incubation at 4 °C, and become strong after 24 h. The most significant changes correspond to energy metabolites: the concentrations of ATP and ADP decrease fivefold, and the concentrations of NAD, NADH, and NADPH decrease below the detectable level. A statistically significant increase was observed for AMP, IMP, hypoxanthine, and nicotinamide. The brain tissue is much more metabolically active than human blood, and significant metabolomic changes occur already within the first several minutes during the brain harvest and sample homogenization. At a longer timescale (hours), noticeable changes were observed for all classes of compounds, including amino acids, organic acids, alcohols, amines, sugars, nitrogenous bases, nucleotides, and nucleosides.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Mass spectrometry-based method for quantification of nimodipine and glutamate in cerebrospinal fluid. Pilot study with patients after aneurysmal subarachnoid haemorrhage

WHAT IS KNOWN AND OBJECTIVE

Delayed cerebral ischaemia is an important cause of morbidity and mortality after aneurysmal subarachnoid haemorrhage (aSAH). Nimodipine is the only drug approved by the FDA for improving outcome after aSAH. Clinically, however, there are no specific values of this drug in cerebrospinal fluid (CSF) during aSAH treatment that could be associated to outcome improvement. Furthermore, the neurotransmitter glutamate acts as a secondary marker for brain injury. The aim was to establish a method to measure nimodipine and glutamate concentrations simultaneously in CSF of patients after aSAH.

METHODS

From June 2017 to June 2018, we prospectively collected clinical data of patients with aSAH admitted to our neurointensive care unit. All included patients received nimodipine orally (60 mg every 4 hours). Patients, who developed clinical vasospasm during their in-hospital stay, underwent intra-arterial application of nimodipine (IAN), followed by angiographic control. A method using high-performance liquid chromatography coupled with mass spectrometric analysis (LC-MS/MS) was established for quantification of both analytes in CSF.

RESULTS AND DISCUSSION

In 15 (60%) of 25 patients, nimodipine and glutamate concentrations were measured. After IAN for treatment of vasospasms, CSF nimodipine concentrations were slightly higher than in patients who received nimodipine only orally (0.60 ± 0.27 ng/mL vs 0.48 ± 0.18 ng/mL). Patients developing vasospasm exhibited higher glutamate concentrations than patients without vasospasm (188.84 ng/mL vs136.07 ng/mL).

WHAT IS NEW AND CONCLUSION

The developed method allowed the simultaneous quantification of nimodipine and glutamate in CSF. Furthermore, we demonstrated that IAN resulted in higher concentrations in CSF, when compared to oral application only.

Mass spectrometry-based intraoperative tumor diagnostics

In surgical oncology, decisions regarding the amount of tissue to be removed can have important consequences: the decision between preserving sufficient healthy tissue and eliminating all tumor cells is one to be made intraoperatively. This review discusses the latest technical innovations for a more accurate tumor margin localization based on mass spectrometry. Highlighting the latest mass spectrometric inventions, real-time diagnosis seems to be within reach; focusing on the intelligent knife, desorption electrospray ionization, picosecond infrared laser and MasSpec pen, the current technical status is evaluated critically concerning its scientific and medical practice.

Pre- and Post-analytical Factors in Biomarker Discovery

The translation of promising biomarkers, which were identified in biomarker discovery experiments, to clinical assays is one of the key challenges in present-day proteomics research. Many so-called "biomarker candidates" fail to progress beyond the discovery phase, and much emphasis is placed on pre- and post-analytical variability in an attempt to provide explanations for this bottleneck in the biomarker development pipeline. With respect to such variability, there is a large number of pre- and post-analytical factors which may impact the outcomes of proteomics experiments and thus necessitate tight control. This chapter highlights some of these factors and provides guidance for addressing them on the basis of examples from previously published proteomics studies.

Interlaboratory proficiency processing scheme in CSF aliquoting: implementation and assessment based on biomarkers of Alzheimer's disease

BACKGROUND

In this study, we tested to which extent possible between-center differences in standardized operating procedures (SOPs) for biobanking of cerebrospinal fluid (CSF) samples influence the homogeneity of the resulting aliquots and, consequently, the concentrations of the centrally analyzed selected Alzheimer's disease biomarkers.

METHODS

Proficiency processing samples (PPSs), prepared by pooling of four individual CSF samples, were sent to 10 participating centers, which were asked to perform aliquoting of the PPSs into two secondary aliquots (SAs) under their local SOPs. The resulting SAs were shipped to the central laboratory, where the concentrations of amyloid beta (Aβ) 1-42, pTau181, and albumin were measured in one run with validated routine analytical methods. Total variability of the concentrations, and its within-center and between-center components, were analyzed with hierarchical regression models.

RESULTS

We observed neglectable variability in the concentrations of pTau181 and albumin across the centers and the aliquots. In contrast, the variability of the Aβ1-42 concentrations was much larger (overall coefficient of variation 31%), with 28% of the between-laboratory component and 10% of the within-laboratory (i.e., between-aliquot) component. We identified duration of the preparation of the aliquots and the centrifugation force as two potential confounders influencing within-center variability and biomarker concentrations, respectively.

CONCLUSIONS

Proficiency processing schemes provide objective evidence for the most critical preanalytical variables. Standardization of these variables may significantly enhance the quality of the collected biospecimens. Studies utilizing retrospective samples collected under different local SOPs need to consider such differences in the statistical evaluations of the data.

Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative)

BACKGROUND

The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data.

CONTENT

This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices.

SUMMARY

Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.

A review of metabolomics approaches and their application in identifying causal pathways of childhood asthma

Because asthma is a disease that results from host-environment interactions, an approach that allows assessment of the effect of the environment on the host is needed to understand the disease. Metabolomics has appealing potential as an application to study pathways to childhood asthma development. The objective of this review is to provide an overview of metabolomics methods and their application to understanding host-environment pathways in asthma development. We reviewed recent literature on advances in metabolomics and their application to study pathways to childhood asthma development. We highlight the (1) potential of metabolomics in understanding the pathogenesis of disease and the discovery of biomarkers; (2) choice of metabolomics techniques, biospecimen handling, and data analysis; (3) application to studying the role of the environment on asthma development; (4) review of metabolomics applied to the outcome of asthma; (5) recommendations for application of metabolomics-based -omics data integration in understanding disease pathogenesis; and (6) limitations. In conclusion, metabolomics allows use of biospecimens to identify useful biomarkers and pathways involved in disease development and subsequently to inform a greater understanding of disease pathogenesis and endotypes and prediction of the clinical course of childhood asthma phenotypes.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Strategies to assess and optimize stability of endogenous amines during cerebrospinal fluid sampling

INTRODUCTION

Metabolic profiling of cerebrospinal fluid (CSF) is a promising technique for studying brain diseases. Measurements should reflect the in vivo situation, so ex vivo metabolism should be avoided.

OBJECTIVE

To investigate the effects of temperature (room temperature vs. 4 °C), centrifugation and ethanol, as anti-enzymatic additive during CSF sampling on concentrations of glutamic acid, glutamine and other endogenous amines.

METHODS

CSF samples from 21 individuals were processed using five different protocols. Isotopically-labeled alanine, isoleucine, glutamine, glutamic acid and dopamine were added prior to sampling to trace any degradation. Metabolomics analysis of endogenous amines, isotopically-labeled compounds and degradation products was performed with a validated LC-MS method.

RESULTS

Thirty-six endogenous amines were quantified. There were no statistically significant differences between sampling protocols for 31 out of 36 amines. For GABA there was primarily an effect of temperature (higher concentrations at room temperature than at 4 °C) and a small effect of ethanol (lower concentrations if added) due to possible degradation. O-phosphoethanolamine concentrations were also lower when ethanol was added. Degradation of isotopically-labeled compounds (e.g. glutamine to glutamic acid) was minor with no differences between protocols.

CONCLUSION

Most amines can be considered stable during sampling, provided that samples are cooled immediately to 4 °C, centrifuged, and stored at - 80 °C within 2 h. The effect of ethanol addition for more unstable metabolites needs further investigation. This was the first time that labeled compounds were used to monitor ex vivo metabolism during sampling. This is a useful strategy to study the stability of other metabolites of interest.

Distinct metabolomic signature in cerebrospinal fluid in early parkinson's disease

OBJECTIVE

The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis.

METHODS

By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PD patients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (Tübingen cohort).

RESULTS

We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P < .05) in PD patients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PD patients vs healthy controls) in a second (n = 18) as well as in a third and completely independent validation set (n = 36). The biomarker signature is composed of the three markers-mannose, threonic acid, and fructose-and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800.

CONCLUSION

We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to early-stage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD. © 2017 International Parkinson and Movement Disorder Society.

The potential of volatile organic compounds for the detection of active disease in patients with ulcerative colitis

BACKGROUND

To optimise treatment of ulcerative colitis (UC), patients need repeated assessment of mucosal inflammation. Current non-invasive biomarkers and clinical activity indices do not accurately reflect disease activity in all patients and cannot discriminate UC from non-UC colitis. Volatile organic compounds (VOCs) in exhaled air could be predictive of active disease or remission in Crohn's disease.

AIM

To investigate whether VOCs are able to differentiate between active UC, UC in remission and non-UC colitis.

METHODS

UC patients participated in a 1-year study. Clinical activity index, blood, faecal and breath samples were collected at each out-patient visit. Patients with clear defined active faecal calprotectin >250 μg/g and inactive disease (Simple Clinical Colitis Activity Index <3, C-reactive protein <5 mg/L and faecal calprotectin <100 μg/g) were included for cross-sectional analysis. Non-UC colitis was confirmed by stool culture or radiological evaluation. Breath samples were analysed by gas chromatography time-of-flight mass spectrometry and kernel-based method to identify discriminating VOCs.

RESULTS

In total, 72 UC (132 breath samples; 62 active; 70 remission) and 22 non-UC-colitis patients (22 samples) were included. Eleven VOCs predicted active vs. inactive UC in an independent internal validation set with 92% sensitivity and 77% specificity (AUC 0.94). Non-UC colitis patients could be clearly separated from active and inactive UC patients with principal component analysis.

CONCLUSIONS

Volatile organic compounds can accurately distinguish active disease from remission in UC and profiles in UC are clearly different from profiles in non-UC colitis patients. VOCs have demonstrated potential as new non-invasive biomarker to monitor inflammation in UC.

Laboratory-based clinical audit as a tool for continual improvement: an example from CSF chemistry turnaround time audit in a South-African teaching hospital

INTRODUCTION

Timeliness of laboratory results is crucial to patient care and outcome. Monitoring turnaround times (TAT), especially for emergency tests, is important to measure the effectiveness and efficiency of laboratory services. Laboratory-based clinical audits reveal opportunities for improving quality. Our aim was to identify the most critical steps causing a high TAT for cerebrospinal fluid (CSF) chemistry analysis in our laboratory.

MATERIALS AND METHODS

A 6-month retrospective audit was performed. The duration of each operational phase across the laboratory work flow was examined. A process-mapping audit trail of 60 randomly selected requests with a high TAT was conducted and reasons for high TAT were tested for significance.

RESULTS

A total of 1505 CSF chemistry requests were analysed. Transport of samples to the laboratory was primarily responsible for the high average TAT (median TAT = 170 minutes). Labelling accounted for most delays within the laboratory (median TAT = 71 minutes) with most delays occurring after regular work hours (P < 0.05). CSF chemistry requests without the appropriate number of CSF sample tubes were significantly associated with delays in movement of samples from the labelling area to the technologist's work station (caused by a preference for microbiological testing prior to CSF chemistry).

CONCLUSION

A laboratory-based clinical audit identified sample transportation, work shift periods and use of inappropriate CSF sample tubes as drivers of high TAT for CSF chemistry in our laboratory. The results of this audit will be used to change pre-analytical practices in our laboratory with the aim of improving TAT and customer satisfaction.

Metabolomics and Its Application to Acute Lung Diseases

Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a "snapshot" in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS). We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity, which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical decision-making and investigators can use them to design clinical trials.

Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases

Metabolomics is a systemic study of metabolites, which are small molecules generated by the process of metabolism. The metabolic profile of saliva can provide an early outlook of the changes associated with a wide range of diseases, including oral cancer and periodontal diseases. It is possible to measure levels of disease-specific metabolites using different methods as presented in this study. However, many challenges exist including incomplete understanding of the complicated metabolic pathways of different oral diseases. The review concludes with the discussion on future perspectives of salivary metabolomics from a clinician point of view. Salivary metabolomics may afford a new research avenue to identify local and systemic disorders but also to aid in the design and modification of therapies. A MEDLINE search using keywords "salivary metabolomics" returned 23 results in total, of which seven were omitted for being reviews or letters to the editor. The rest of the articles were used for preparation of the review, 13 of these were published in the last 5 years.

Gas chromatography-mass spectrometry of biofluids and extracts

Gas chromatography-mass spectrometry (GC-MS) has been widely used in metabonomics analyses of biofluid samples. Biofluids provide a wealth of information about the metabolism of the whole body and from multiple regions of the body that can be used to study general health status and organ function. Blood serum and blood plasma, for example, can provide a comprehensive picture of the whole body, while urine can be used to monitor the function of the kidneys, and cerebrospinal fluid (CSF) will provide information about the status of the brain and central nervous system (CNS). Different methods have been developed for the extraction of metabolites from biofluids, these ranging from solvent extracts, acids, heat denaturation, and filtration. These methods vary widely in terms of efficiency of protein removal and in the number of metabolites extracted. Consequently, for all biofluid-based metabonomics studies, it is vital to optimize and standardize all steps of sample preparation, including initial extraction of metabolites. In this chapter, recommendations are made of the optimum experimental conditions for biofluid samples for GC-MS, with a particular focus on blood serum and plasma samples.

Biobanking of Cerebrospinal Fluid for Biomarker Analysis in Neurological Diseases

Cerebrospinal fluid (CSF) reflects pathophysiological aspects of neurological diseases, where neuroprotective strategies and biomarkers are urgently needed. Therefore, biobanking is very relevant for biomarker discovery and evaluation for these neurological diseases.An important aspect of CSF biobanking is quality control, needed for e.g. consistent patient follow-up and the exchange of patient samples between research centers. Systematic studies to address effects of pre-analytical and storage variation on a broad range of CSF proteins are needed and initiated.Important features of CSF biobanking are intensive collaboration in international networks and the tight application of standardized protocols. The current adoption of standardized protocols for CSF and blood collection and for biobanking of these samples, as presented in this chapter, enables biomarker studies in large cohorts of patients and controls.In conclusion, biomarker research in neurodegenerative diseases has entered a new era due to the collaborative and multicenter efforts of many groups. The streamlining of biobanking procedures, including sample collection, quality control, and the selection of optimal control groups for investigating biomarkers is an important improvement to perform high quality biomarker studies.

Sample collection and preparation of biofluids and extracts for liquid chromatography-mass spectrometry

Nowadays, metabonomics has been widely applied to the area of biomedicine. Based on metabolic profiling analysis, metabolomic studies can provide information of the metabolic phenotype affected by genetic or environmental factors. Liquid chromatography-mass spectrometry has been proven to be a robust platform for metabolic profiling by sensitive measurement of low molecular weight compounds. However, this sensitive platform requires standard protocols in the preanalytical stage to avoid unwanted results caused by improper operations. Therefore, in this chapter, we will present a systemic protocol for the collection and preparation of biofluids and extracts, such as blood, urine, tissues, and cell lines, including the collection and storage of samples in the clinic and the extraction procedures in the laboratory.

Cerebrospinal fluid proteomics in multiple sclerosis

Multiple sclerosis (MS) is an immune mediated chronic inflammatory disease of the central nervous system usually initiated during young adulthood, affecting approximately 2.5 million people worldwide. There is currently no cure for MS, but disease modifying treatment has become increasingly more effective, especially when started in the first phase of the disease. The disease course and prognosis are often unpredictable and it can be challenging to determine an early diagnosis. The detection of novel biomarkers to understand more of the disease mechanism, facilitate early diagnosis, predict disease progression, and find treatment targets would be very attractive. Over the last decade there has been an increasing effort toward finding such biomarker candidates. One promising strategy has been to use state-of-the-art quantitative proteomics approaches to compare the cerebrospinal fluid (CSF) proteome between MS and control patients or between different subgroups of MS. In this review we summarize and discuss the status of CSF proteomics in MS, including the latest findings with a focus on the last five years. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

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.

Two birds with one stone: doing metabolomics with your proteomics kit

Proteomic research facilities and laboratories are facing increasing demands for the integration of biological data from multiple ‘-OMICS’ approaches. The aim to fully understand biological processes requires the integrated study of genomes, proteomes and metabolomes. While genomic and proteomic workflows are different, the study of the metabolome overlaps significantly with the latter, both in instrumentation and methodology. However, chemical diversity complicates an easy and direct access to the metabolome by mass spectrometry (MS). The present review provides an introduction into metabolomics workflows from the viewpoint of proteomic researchers. We compare the physicochemical properties of proteins and peptides with metabolites/small molecules to establish principle differences between these analyte classes based on human data. We highlight the implications this may have on sample preparation, separation, ionisation, detection and data analysis. We argue that a typical proteomic workflow (nLC-MS) can be exploited for the detection of a number of aliphatic and aromatic metabolites, including fatty acids, lipids, prostaglandins, di/tripeptides, steroids and vitamins, thereby providing a straightforward entry point for metabolomics-based studies. Limitations and requirements are discussed as well as extensions to the LC-MS workflow to expand the range of detectable molecular classes without investing in dedicated instrumentation such as GC-MS, CE-MS or NMR.

Looking back into the future: 30 years of metabolomics at TNO

Metabolites have played an essential role in our understanding of life, health, and disease for thousands of years. This domain became much more important after the concept of metabolism was discovered. In the 1950s, mass spectrometry was coupled to chromatography and made the technique more application-oriented and allowed the development of new profiling technologies. Since 1980, TNO has performed system-based metabolic profiling of body fluids, and combined with pattern recognition has led to many discoveries and contributed to the field known as metabolomics and systems biology. This review describes the development of related concepts and applications at TNO in the biomedical, pharmaceutical, nutritional, and microbiological fields, and provides an outlook for the future.

Plasma and cerebrospinal proteomes from children with cerebral malaria differ from those of children with other encephalopathies

Clinical signs and symptoms of cerebral malaria in children are nonspecific and are seen in other common encephalopathies in malaria-endemic areas. This makes accurate diagnosis difficult in resource-poor settings. Novel malaria-specific diagnostic and prognostic methods are needed. We have used 2 proteomic strategies to identify differentially expressed proteins in plasma and cerebrospinal fluid from children with a diagnosis of cerebral malaria, compared with those with a diagnosis of malaria-slide-negative acute bacterial meningitis and other nonspecific encephalopathies. Here we report the presence of differentially expressed proteins in cerebral malaria in both plasma and cerebrospinal fluid that could be used to better understand pathogenesis and help develop more-specific diagnostic methods. In particular, we report the expression of 2 spectrin proteins that have known Plasmodium falciparum–binding partners involved in the stability of the infected red blood cell, suppressing further invasion and possibly enhancing the red blood cell's ability to sequester in microvasculature.

Metabolomics in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an untargeted approach via high-resolution mass spectrometry

Amyotrophic lateral sclerosis (ALS) is characterized by the absence of reliable diagnostic biomarkers. The aim of the study was to (i) devise an untargeted metabolomics methodology that reliably compares cerebrospinal fluid (CSF) from ALS patients and controls by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS); (ii) ascertain a metabolic signature of ALS by use of the LC-HRMS platform; (iii) identify metabolites for use as diagnostic or pathophysiologic markers. We developed a method to analyze CSF components by UPLC coupled with a Q-Exactive mass spectrometer that uses electrospray ionization. Metabolomic profiles were created from the CSF obtained at diagnosis from ALS patients and patients with other neurological conditions. We performed multivariate analyses (OPLS-DA) and univariate analyses to assess the contribution of individual metabolites as well as compounds identified in other studies. Sixty-six CSF samples from ALS patients and 128 from controls were analyzed. Metabolome analysis correctly predicted the diagnosis of ALS in more than 80% of cases. OPLS-DA identified four features that discriminated diagnostic group (p < 0.004). Our data demonstrate that untargeted metabolomics with LC-HRMS is a robust procedure to generate a specific metabolic profile for ALS from CSF and could be an important aid to the development of biomarkers for the disease.

An alternative derivatization method for the analysis of amino acids in cerebrospinal fluid by gas chromatography-mass spectrometry

The determination of the concentrations of l-amino acids in cerebrospinal fluid (CSF) has been used to gain biochemical insight into central nervous system disorders. This paper describes a microwave-assisted derivatization (MAD) method using N,O-bis-(trimethylsilyl)trifluoroacetamide (BSTFA) as a derivatizing agent for determining the concentrations of l-amino acids in human CSF by gas chromatography with mass spectrometry (GC/MS). The experimental design used to optimize the conditions showed that the optimal derivatization time was 3min with a microwave power of 210W. The method showed good performance for the validation parameters. The sensitivity was very good, with limits of detection (LODs) ranging from 0.01μmolL(-1) to 4.24μmolL(-1) and limits of quantification (LOQs) ranging from 0.02 to 7.07μmolL(-1). The precision, measured using the relative standard deviation (RSD), ranged from 4.12 to 15.59% for intra-day analyses and from 6.36 to 18.71% for inter-day analyses. The coefficients of determination (R(2)) were above 0.990 for all amino acids. The optimized and validated method was applied to the determination of amino acid concentrations in human CSF.

Pre-analytical factors influencing the stability of cerebrospinal fluid proteins

Cerebrospinal fluid (CSF) is a potential source for new biomarkers due to its proximity to the brain. This study aimed to clarify the stability of the CSF proteome when undergoing pre-analytical factors. We investigated the effects of repeated freeze/thaw cycles, protease inhibitors and delayed storage for 4h, 24h or 14 days at -20°C, 4°C and room temperature (RT) after centrifugation compared with our standard practice of two hours at RT before placing the samples in an -80°C environment. The results were obtained using immunoassays for amyloid-beta 1-42 (Aβ42), tau, phosphorylated tau (P-tau) and cystatin C and using surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectrometry for proteomic profiling. Tau and P-tau were susceptible to repeated freeze/thaw cycles while SELDI-TOF analysis produced eight significant peaks and additional artefact peaks from samples with added protease inhibitors. Delayed storage for different durations and in different temperatures produced six significant SELDI-TOF peaks. Aβ42 and tau were susceptible to increased temperatures and the duration before storage, whereas P-tau and cystatin C were not. Transthyretin and several of its isoforms were found using SELDI-TOF and were susceptible to freeze/thaw cycles and to increased temperature and length of time prior to storage. We recommend that CSF should be collected and centrifuged immediately after sampling and prior to storage at -80°C without the addition of protease inhibitors. Freeze/thawing should be avoided because of the instability of tau, P-tau and transthyretin. Standardised CSF sampling, handling and storage for biomarker research are essential for accurately comparing the results obtained by different studies and institutions.

GC/MS-based metabolomic analysis of cerebrospinal fluid (CSF) from glioma patients

Metabolomics has recently undergone rapid development; however, metabolomic analysis in cerebrospinal fluid (CSF) is not a common practice. We analyzed the metabolite profiles of preoperative CSF samples from 32 patients with histologically confirmed glioma using gas chromatography/mass spectrometry (GC/MS). We assessed how alterations in the metabolite levels were related to the World Health Organization (WHO) tumor grades, tumor location, gadolinium enhancement on magnetic resonance imaging (MRI), and the isocitrate dehydrogenase (IDH) mutation status. Sixty-one metabolites were identified in the CSF from glioma patients using targeted, quantitative and non-targeted, semi-quantitative analysis. The citric and isocitric acid levels were significantly higher in the glioblastoma (GBM) samples than in the grades I-II and grade III glioma samples. In addition, the lactic and 2-aminopimelic acid levels were relatively higher in the GBM samples than in the grades I-II glioma samples. The CSF levels of the citric, isocitric, and lactic acids were significantly higher in grade I-III gliomas with mutant IDH than in those with wild-type IDH. The tumor location and enhancement obtained using MRI did not significantly affect the metabolite profiles. Higher CSF levels of lactic acid were statistically associated with a poorer prognosis in grades III-IV malignant gliomas. Our study suggests that the metabolomic analysis of CSF from glioma patients may be useful for predicting the glioma grade, metabolic state, and prognosis of gliomas.

LC-MS metabolomics from study design to data-analysis - using a versatile pathogen as a test case

Thanks to significant improvements in LC-MS technology, metabolomics is increasingly used as a tool to discriminate the responses of organisms to various stimuli or drugs. In this minireview we discuss all aspects of the LC-MS metabolomics pipeline, using a complex and versatile model organism, Leishmania donovani, as an illustrative example. The benefits of a hyphenated mass spectrometry platform and a detailed overview of the entire experimental pipeline from sampling, sample storage and sample list set-up to LC-MS measurements and the generation of meaningful results with state-of-the-art data-analysis software will be thoroughly discussed. Finally, we also highlight important pitfalls in the processing of LC-MS data and comment on the benefits of implementing metabolomics in a systems biology approach.

Preanalytical aspects and sample quality assessment in metabolomics studies of human blood

BACKGROUND

Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies.

METHODS

We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach.

RESULTS

Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability.

CONCLUSIONS

Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data.

Isothermal vitrification methodology development for non-cryogenic storage of archival human sera

Biorepositories worldwide collect human serum samples and store them for future research. Currently, hundreds of biorepositories across the world store human serum samples in refrigerators, freezers, or liquid nitrogen without following any specific cryopreservation protocol. This method of storage is both expensive and potentially detrimental to the biospecimens. To decrease both cost of storage and the freeze/thaw stresses, we explored the feasibility of storing archival human serum samples at non-cryogenic temperatures using isothermal vitrification. When biospecimens are vitrified, biochemical reactions can be stopped, the specimen ceases to degrade, and macromolecules can be stabilized without requiring cryogenic storage. In this study, 0.2, 0.4, or 0.8M trehalose; 0, 0.005 or 0.01M dextran; and 0 or 10% (v/v) glycerol was added to human serum samples. The samples were either dried diffusively as sessile droplets or desiccated under vacuum after they are adsorbed onto glass microfiber filters. The glass transition temperatures (Tg) of the desiccated samples were measured by temperature-ramp Fourier Transform Infrared (FTIR) spectroscopy. Sera samples vitrified at 4±2°C when 0.8M trehalose and 0.01M dextran were added and the samples were vacuum dried for two hours. Western immunoblotting showed that vitrified serum proteins were minimally degraded when stored for up to one month at 4°C. About 80% of all proteins were recovered after storage at 4°C on glass microfiber filters, and recovery did not decrease with storage time. These results demonstrated the feasibility of long-term storage of vitrified serum at hypothermic (and non-cryogenic) temperatures.

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue

The revival of interest in cancer cell metabolism in recent years has prompted the need for quantitative analytical platforms for studying metabolites from in vivo sources. We implemented a quantitative polar metabolomics profiling platform using selected reaction monitoring with a 5500 QTRAP hybrid triple quadrupole mass spectrometer that covers all major metabolic pathways. The platform uses hydrophilic interaction liquid chromatography with positive/negative ion switching to analyze 258 metabolites (289 Q1/Q3 transitions) from a single 15-min liquid chromatography-mass spectrometry acquisition with a 3-ms dwell time and a 1.55-s duty cycle time. Previous platforms use more than one experiment to profile this number of metabolites from different ionization modes. The platform is compatible with polar metabolites from any biological source, including fresh tissues, cancer cells, bodily fluids and formalin-fixed paraffin-embedded tumor tissue. Relative quantification can be achieved without using internal standards, and integrated peak areas based on total ion current can be used for statistical analyses and pathway analyses across biological sample conditions. The procedure takes ∼12 h from metabolite extraction to peak integration for a data set containing 15 total samples (∼6 h for a single sample).

Metabolomics of human cerebrospinal fluid identifies signatures of malignant glioma

Cerebrospinal fluid is routinely collected for the diagnosis and monitoring of patients with neurological malignancies. However, little is known as to how its constituents may change in a patient when presented with a malignant glioma. Here, we used a targeted mass-spectrometry based metabolomics platform using selected reaction monitoring with positive/negative switching and profiled the relative levels of over 124 polar metabolites present in patient cerebrospinal fluid. We analyzed the metabolic profiles from 10 patients presenting malignant gliomas and seven control patients that did not present malignancy to test whether a small sample size could provide statistically significant signatures. We carried out multiple unbiased forms of classification using a series of unsupervised techniques and identified metabolic signatures that distinguish malignant glioma patients from the control patients. One subtype identified contained metabolites enriched in citric acid cycle components. Newly diagnosed patients segregated into a different subtype and exhibited low levels of metabolites involved in tryptophan metabolism, which may indicate the absence of an inflammatory signature. Together our results provide the first global assessment of the polar metabolic composition in cerebrospinal fluid that accompanies malignancy, and demonstrate that data obtained from high throughput mass spectrometry technology may have suitable predictive capabilities for the identification of biomarkers and classification of neurological diseases.