Improved experimental data processing for UHPLC–HRMS/MS lipidomics applied to nonalcoholic fatty liver disease

Introduction

Untargeted metabolomics workflows include numerous points where variance and systematic errors can be introduced. Due to the diversity of the lipidome, manual peak picking and quantitation using molecule specific internal standards is unrealistic, and therefore quality peak picking algorithms and further feature processing and normalization algorithms are important. Subsequent normalization, data filtering, statistical analysis, and biological interpretation are simplified when quality data acquisition and feature processing are employed.

Objectives

Metrics for QC are important throughout the workflow. The robust workflow presented here provides techniques to ensure that QC checks are implemented throughout sample preparation, data acquisition, pre-processing, and analysis.

Methods

The untargeted lipidomics workflow includes sample standardization prior to acquisition, blocks of QC standards and blanks run at systematic intervals between randomized blocks of experimental data, blank feature filtering (BFF) to remove features not originating from the sample, and QC analysis of data acquisition and processing.

Results

The workflow was successfully applied to mouse liver samples, which were investigated to discern lipidomic changes throughout the development of nonalcoholic fatty liver disease (NAFLD). The workflow, including a novel filtering method, BFF, allows improved confidence in results and conclusions for lipidomic applications.

Conclusion

Using a mouse model developed for the study of the transition of NAFLD from an early stage known as simple steatosis, to the later stage, nonalcoholic steatohepatitis, in combination with our novel workflow, we have identified phosphatidylcholines, phosphatidylethanolamines, and triacylglycerols that may contribute to disease onset and/or progression.

     

Absolute quantitative lipidomics reveals lipidome-wide alterations in aging brain

Introduction

The absolute quantitation of lipids at the lipidome-wide scale is a challenge but plays an important role in the comprehensive study of lipid metabolism.

Objectives

We aim to develop a high-throughput quantitative lipidomics approach to enable the simultaneous identification and absolute quantification of hundreds of lipids in a single experiment. Then, we will systematically characterize lipidome-wide changes in the aging mouse brain and provide a link between aging and disordered lipid homeostasis.

Methods

We created an in-house lipid spectral library, containing 76,361 lipids and 181,300 MS/MS spectra in total, to support accurate lipid identification. Then, we developed a response factor-based approach for the large-scale absolute quantifications of lipids.

Results

Using the lipidomics approach, we absolutely quantified 1212 and 864 lipids in human cells and mouse brains, respectively. The quantification accuracy was validated using the traditional approach with a median relative error of 12.6%. We further characterized the lipidome-wide changes in aging mouse brains, and dramatic changes were observed in both glycerophospholipids and sphingolipids. Sphingolipids with longer acyl chains tend to accumulate in aging brains. Membrane-esterified fatty acids demonstrated diverse changes with aging, while most polyunsaturated fatty acids consistently decreased.

Conclusion

We developed a high-throughput quantitative lipidomics approach and systematically characterized the lipidome-wide changes in aging mouse brains. The results proved a link between aging and disordered lipid homeostasis.

     

Monitoring cancer prognosis,diagnosis and treatment efficacy using metabolomics and lipidomics

Introduction

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

Objectives

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.

Methods

A literature search of the current relevant primary research was performed.

Results

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

Conclusion

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.

     

Quality assurance and quality control processes: summary of a metabolomics community questionnaire

Introduction

The Metabolomics Society Data Quality Task Group (DQTG) developed a questionnaire regarding quality assurance (QA) and quality control (QC) to provide baseline information about current QA and QC practices applied in the international metabolomics community.

Objectives

The DQTG has a long-term goal of promoting robust QA and QC in the metabolomics community through increased awareness via communication, outreach and education, and through the promotion of best working practices. An assessment of current QA and QC practices will serve as a foundation for future activities and development of appropriate guidelines.

Method

QA was defined as the set of procedures that are performed in advance of analysis of samples and that are used to improve data quality. QC was defined as the set of activities that a laboratory does during or immediately after analysis that are applied to demonstrate the quality of project data. A questionnaire was developed that included 70 questions covering demographic information, QA approaches and QC approaches and allowed all respondents to answer a subset or all of the questions.

Result

The DQTG questionnaire received 97 individual responses from 84 institutions in all fields of metabolomics covering NMR, LC-MS, GC-MS, and other analytical technologies.

Conclusion

There was a vast range of responses concerning the use of QA and QC approaches that indicated the limited availability of suitable training, lack of Standard Operating Procedures (SOPs) to review and make decisions on quality, and limited use of standard reference materials (SRMs) as QC materials. The DQTG QA/QC questionnaire has for the first time demonstrated that QA and QC usage is not uniform across metabolomics laboratories. Here we present recommendations on how to address the issues concerning QA and QC measurements and reporting in metabolomics.

     

A multidimensional <Superscript>1</Superscript>H NMR lipidomics workflow to address chemical food safety issues

Introduction

Although it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.

Objectives

The study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.

Method

The robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.

Results

Our results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.

Conclusion

This work demonstrates the potential of fast multidimensional ¹H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues.

     

<Emphasis Type="Italic">massPix</Emphasis>: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Introduction

Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.

Objectives

We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.

Methods

massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.

Results

Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.

Conclusion

massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.

     

Unbiased lipidomic profiling reveals metabolomic changes during the onset and antipsychotics treatment of schizophrenia disease

Introduction

Schizophrenia (SCH) is one of the most common psychiatric disorders, which involves impairments in motivation and cognition. The pathological mechanisms underlying SCH are still unknown, and no effective therapies can prevent or treat perfectly the cognitive impairments and deficit symptoms caused by SCH.

Objectives

We aimed to find the lipid expression change in plasma that underlie SCH onset and antipsychotics treatment.

Methods

We performed a data independent acquisition-based untargeted lipidomic approach on a quadrupole-time of flight liquid chromatography coupled to mass spectrometry platform. The plasma lipidomic profiles of SCH patients (n?=?20) pre- and post-antipsychotics treatment were acquired as well as healthy controls (n?=?29). Grouped or paired t-test were used to analyze the data.

Results

Over 1000 features were detected by our lipidomic analysis, of which 445 lipids belonging to 17 lipid species were reliably identified by tandem mass spectrometry. After statistical analysis, 47 lipids belonging to 9 lipid species were found to be dysregulated between naive SCH patients and healthy controls, and 50 lipids belonging to 9 lipid species were found to be dysregulated after antipsychotics treatment. These findings include several new SCH-relevant lipid species such as sphingomyelin, acylcarnitine and ceramide. Four types of lipid expression regulative patterns can be concluded from the above mentioned findings, revealing information about mechanism, side-effect and potential target of antipsychotics.

Conclusions

The work presented here have revealed several new lipid species which are significantly dysregulated in SCH disease development or antipsychotics treatment. These lipids provide new evidence for the pathological studies of SCH and new antipsychotics development, or can be considered as potentially candidate biomarkers for further validation.

     

Prepartal overfeeding alters the lipidomic profiles in the liver and the adipose tissue of transition dairy cows

Introduction

Physiological adaptations in the energy metabolism of dairy cows during the periparturient period are partly mediated by insulin resistance (IR), which may subsequently induce metabolic disorders postpartum. The molecular mechanisms underlying IR in dairy cows are largely unknown.

Objective

This study aimed to find a novel insight into the molecular mechanisms underlying IR in dairy cows during the periparturient period by analyzing the effects of prepartal overfeeding on the lipidomic profiles in the liver and adipose tissue (AT).

Methods

Sixteen cows were allocated to controlled-energy and high-energy feeding groups. Lipidomic profiling was conducted on liver and adipose tissue samples collected at 8 days prior to the predicted parturition, and 1 day (only AT) and 9 days after the actual parturition.

Results

Five ceramides (Cers) were identified to be significantly increased by prepartal overfeeding in AT in the analysis of the variance between groups within time points. Principal component-linear discriminant analysis showed that lipidomic profiles between the feeding groups were mainly characterized by phosphatidylcholines (PC), phosphatidylethanolamines (PE), lysophophosphatidylcholines (LysoPC), and lysophosphatidylethanolamines (LysoPE) in the liver, and by Cer, PE, and phosphatidylinositols (PI) in AT. Lipid class levels indicated that prepartal overfeeding elevated the concentration of PE, PI, LysoPC, LysoPE, and sphingomyelin in the liver, and increased the concentration of Cer in AT during the periparturient period.

Conclusion

Prepartal overfeeding significantly altered the concentrations of various sphingolipids, phospholipids, and lysophospholipids in the liver and AT of dairy cows during the periparturient period.

     

Ultra high performance liquid chromatography–high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets

Introduction and objectives

The purpose of this study was to use high accurate mass metabolomic profiling to investigate differences within a phenotypically diverse canine population, with breed-related morphological, physiological and behavioural differences. Previously, using a broad metabolite fingerprinting approach, lipids appear to dominate inter- and intra- breed discrimination. The purpose here was to use Ultra High Performance Liquid Chromatography–High Resolution Mass Spectrometry (UHPLC–HRMS) to identify in more detail, inter-breed signatures in plasma lipidomic profiles of home-based, client-owned dogs maintained on different diets and fed according to their owners’ feeding regimens.

Methods

Nine dog breeds were recruited in this study (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese: 7–12 dogs per breed). Metabolite profiling on a MTBE lipid extract of fasted plasma was performed using UHPLC-HRMS.

Results

Multivariate modelling and classification indicated that the main source of lipidome variance was between the three breeds Chihuahua, Dachshund and Greyhound and the other six breeds, however some intra-breed variance was evident in Labrador Retrievers. Metabolites associated with dietary intake impacted on breed-associated variance and following filtering of these signals out of the data-set unique inter-breed lipidome differences for Chihuahua, Golden Retriever and Greyhound were identified.

Conclusion

By using a phenotypically diverse home-based canine population, we were able to show that high accurate mass lipidomics can enable identification of metabolites in the first pass plasma profile, capturing distinct metabolomic variability associated with genetic differences, despite environmental and dietary variability.

     

Follicular fluid lipidomics reveals lipid alterations by LH addition during IVF cycles

Introduction

Ovulation induction protocols are key components for performing assisted reproduction treatments successfully. The importance of adding exogenous LH to the controlled ovarian stimulation protocols in young women is still a matter of discussion in the clinical practice.

Objective

To estimate how LH addition to controlled ovarian stimulation protocols may affect the follicular fluid lipid profile of women undergoing in vitro fertilization treatment.

Methods

We conducted the study using 28 self-paired samples, 14 per group. The patients received FSH during their first cycle of ovarian stimulation (FSH group). If the treatment did not result in pregnancy, the same patients returned for a new cycle and received stimulus with the addition of LH to the previous protocol (Low-dose-LH group). Lipidomics analysis was performed by UPLC-MS^E mass spectrometry. The software Progenesis QI was used to identify potential lipid biomarkers. Statistical analysis was performed using the SPSS 18.0 and MetaboAnalyst 2.0 software.

Results

The analysis of clinical data showed no statistically significant differences between groups, in contrast to lipidomic analysis. Concerning lipidomic profile, the lipids differentially expressed in FSH group belong to the following subclasses:triacylglycerols; branched fatty acids and diacylglycerophosphoethanolamines; while in Low-dose-LH group the subclasses are gangliosides; acylglycerophosphoethanolamines; triacylglycerols; acylglycerophosphoserines; GalNAcβ1-3Galα1-4Galβ1-4Glc-(Globo series); amino fatty acids; triacylglycerols and prostaglandins.

Conclusion

The differences found between the groups may contribute to the establishment of potential therapeutical targets based on LH-associated lipid biomarkers aiming to individualize treatments and obtain reproductive success.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Amelioration of patients with chronic spontaneous urticaria in treatment with vitamin D supplement

Background

Spontaneous urticaria is a common allergic skin condition affecting 0.5–1% of individuals and may burden on health care expenditure or may be associated with remarkable morbidity.

Aim

In this study, we measured the effect of vitamin D supplementation in patients with a diagnosis of CSU. Furthermore, quality of life and cytokine changes were evaluated.

Methods

The clinical trial was conducted on 20 patients with idiopathic chronic urticaria. Vitamin D was administered orally for 8 weeks and disease activity was measured pre- and post-treatment using USS and DLQI. On the other hand expressions of IL-17, IL-10, Foxp3, and TGF-β by Real-time RT-PCR were assessed.

Results

USS questionnaire showed that severity of idiopathic urticaria after the intervention, which compared with the first day reached a significant 55% reduction. The DLQI quality of life questionnaire 2 months after treatment showed 55% improvement. Along with the significant improvement of clinical symptoms, use of vitamin D increase FOXP3 gene expression and downregulation of IL-10, TGF-B, and FOXP3, IL-17, but these changes were not statistically significant.

Limitation

These might happen due to lack of enrolled population in the investigation.

Conclusion

Vitamin D can be used along with standard medical care and it’s a safe and cost-effective method for the treatment of chronic urticaria with deficiency of vitamin D.

     

Annotation of the human cerebrospinal fluid lipidome using high resolution mass spectrometry and a dedicated data processing workflow

Introduction

Due to its proximity with the brain, cerebrospinal fluid (CSF) could be a medium of choice for the discovery of biomarkers of neurological and psychiatric diseases using untargeted analytical approaches.

Objectives

This study explored the CSF lipidome in order to generate a robust mass spectral database using an untargeted lipidomic approach.

Methods

Cerebrospinal fluid samples from 45 individuals were analyzed by liquid chromatography coupled to high-resolution mass spectrometry method (LC-HRMS). A dedicated data processing workflow was implemented using XCMS software and adapted filters to select reliable features. In addition, an automatic annotation using an in silico lipid database and several MS/MS experiments were performed to identify CSF lipid species.

Results

Using this complete workflow, 771 analytically relevant monoisotopic lipid species corresponding to 550 unique lipids which represent five major lipid families (i.e., free fatty acids, sphingolipids, glycerophospholipids, glycerolipids, and sterol lipids) were detected and annotated. In addition, MS/MS experiments enabled to improve the annotation of 304 lipid species. Thanks to LC-HRMS, it was possible to discriminate between isobaric and also isomeric lipid species; and interestingly, our study showed that isobaric ions represent about 50 % of the total annotated lipid species in the human CSF.

Conclusion

This work provides an extensive LC/HRMS database of the human CSF lipidome which constitutes a relevant foundation for future studies aimed at finding biomarkers of neurological disorders.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Analysis of influencing factor of coexisting prediabetes and prehypertension in adult residents of Jilin Province

Background

To explore the risk factors of coexisting prediabetes and prehypertension, to provide theoretical basis for early intervention.

Methods

A multi-stage stratified random cluster sampling method was used to randomly select adult residents from Jilin Province in 2013 for questionnaire surveys, physical examinations, and laboratory tests.

Results

The prevalence of coexisting prediabetes and prehypertension in Jilin Province was 11.3%. The binary Logistic regression results showed that age, sex, education, triglyceride (TG), BMI, waist circumference and alcohol consumption were the effects of factor coexisting prediabetes and prehypertension.

Conclusion

It is important to pay attention to the early stage of hypertension and diabetes, control the transition from prehypertension and prediabetes to hypertension and diabetes, and improve the health of residents.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Exhaled breath analysis: a review of ‘breath-taking’ methods for off-line analysis

Background

The potential of exhaled breath sampling and analysis has long attracted interest in the areas of medical diagnosis and disease monitoring. This interest is attributed to its non-invasive nature, access to an unlimited sample supply (i.e., breath), and the potential to facilitate a rapid at patient diagnosis. However, progress from laboratory setting to routine clinical practice has been slow. Different methodologies of breath sampling, and the consequent difficulty in comparing and combining data, are considered to be a major contributor to this. To fulfil the potential of breath analysis within clinical and pre-clinical medicine, standardisation of some approaches to breath sampling and analysis will be beneficial.

Objectives

The aim of this review is to investigate the heterogeneity of breath sampling methods by performing an in depth bibliometric search to identify the current state of art in the area. In addition, the review will discuss and critique various breath sampling methods for off-line breath analysis.

Methods

Literature search was carried out in databases MEDLINE, BIOSIS, EMBASE, INSPEC, COMPENDEX, PQSCITECH, and SCISEARCH using the STN platform which delivers peer-reviewed articles. Keywords searched for include breath, sampling, collection, pre-concentration, volatile. Forward and reverse search was then performed on initially included articles. The breath collection methodologies of all included articles was subsequently reviewed.

Results

Sampling methods differs between research groups, for example regarding the portion of breath being targeted. Definition of late expiratory breath varies between studies.

Conclusions

Breath analysis is an interdisciplinary field of study using clinical, analytical chemistry, data processing, and metabolomics expertise. A move towards standardisation in breath sampling is currently being promoted within the breath research community with a view to harmonising analysis and thereby increasing robustness and inter-laboratory comparisons.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

Lipid response patterns in acute phase paediatric <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> malaria

Introduction

Several studies have observed serum lipid changes during malaria infection in humans. All of them were focused at analysis of lipoproteins, not specific lipid molecules. The aim of our study was to identify novel patterns of lipid species in malaria infected patients using lipidomics profiling, to enhance diagnosis of malaria and to evaluate biochemical pathways activated during parasite infection.

Methods

Using a multivariate characterization approach, 60 samples were representatively selected, 20 from each category (mild, severe and controls) of the 690 study participants between age of 0.5–6 years. Lipids from patient’s plasma were extracted with chloroform/methanol mixture and subjected to lipid profiling with application of the LCMS-QTOF method.

Results

We observed a structured plasma lipid response among the malaria-infected patients as compared to healthy controls, demonstrated by higher levels of a majority of plasma lipids with the exception of even-chain length lysophosphatidylcholines and triglycerides with lower mass and higher saturation of the fatty acid chains. An inverse lipid profile relationship was observed when plasma lipids were correlated to parasitaemia.

Conclusions

This study demonstrates how mapping the full physiological lipid response in plasma from malaria-infected individuals can be used to understand biochemical processes during infection. It also gives insights to how the levels of these molecules relate to acute immune responses.

     

Synthesis and physicochemical characterization of the one-carbon carrier 10-formyltetrahydrofolate; a reference standard for metabolomics

Introduction

Metabolomics analysis depends on the identification and validation of specific metabolites. This task is significantly hampered by the absence of well-characterized reference standards. The one-carbon carrier 10-formyltetrahydrofolate acts as a donor of formyl groups in anabolism, where it is a substrate in formyltransferase reactions in purine biosynthesis. It has been reported as an unstable substance and is currently unavailable as a reference standard for metabolomics analysis.

Objectives

The current study was undertaken to provide the metabolomics community thoroughly characterized 10-formyltetrahydrofolate along with analytical methodology and guidelines for its storage and handling.

Methods

Anaerobic base treatment of 5,10-methenyltetrahydrofolate chloride in the presence of antioxidant was utilized to prepare 10-formyltetrahydrofolate.

Results

Pure 10-formyltetrahydrofolate has been prepared and physicochemically characterized. Conditions toward maintaining the stability of a solution of the dipotassium salt of 10-formyltetrahydrofolate have been determined.

Conclusion

This study describes the facile preparation of pure (>90%) 10-formyltetrahydrofolate, its qualitative physicochemical characterization, as well as conditions to enable its use as a reference standard in physiologic samples.