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.

     

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.

     

Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics

Introduction

Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

Objectives

We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

Methods

Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA^® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

Results

A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

Conclusion

Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

     

Metabolomics analysis of liver reveals profile disruption in bovines upon steroid treatment

Introduction

The surveillance of illegal anabolic practices in bovine meat production is necessary to guarantee consumers’ health. Screening strategies based on the recognition of indirect biological effects are considered by the community as promising tools to overcome some limitations of classical analytical methods and might therefore concur to ensure safer food for the consumer.

Objectives

The present work aims at characterizing the metabolic profile induced in liver by administration of anabolic steroids, and at identifying potential disturbances in the hepatic metabolism.

Methods

A total of 32 liver samples, 16 from untreated bulls and 16 from bulls treated with an ear implant (Revalor-XS^®) containing trenbolone acetate (200 mg) and β-estradiol (40 mg), were analyzed following a LC–MS-based metabolomic analysis combining RP and HILIC chromatographic separations. Different multivariate statistical tools were applied to the datasets to select common metabolites that may be considered as potential markers based on their significant changes in concentrations after administration of sexual steroids.

Results

Eight candidate markers were identified. Moreover, a subset of four markers was also validated by a different laboratory that performed the same analysis using an independent instrumental and elaboration platform, confirming the robustness of the results achieved.

Conclusion

This study was performed mimicking experimental conditions that may be used during a potential misuse practice. It is promising in the objective of setting up an analytical strategy to highlight sexual steroids abuse in livestock animals.

     

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.

     

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.

     

Clinical utility of the low-density Infinium QC genotyping Array in a genomics-based diagnostics laboratory

Background

With 15,949 markers, the low-density Infinium QC Array-24 BeadChip enables linkage analysis, HLA haplotyping, fingerprinting, ethnicity determination, mitochondrial genome variations, blood groups and pharmacogenomics. It represents an attractive independent QC option for NGS-based diagnostic laboratories, and provides cost-efficient means for determining gender, ethnic ancestry, and sample kinships, that are important for data interpretation of NGS-based genetic tests.

Methods

We evaluated accuracy and reproducibility of Infinium QC genotyping calls by comparing them with genotyping data of the same samples from other genotyping platforms, whole genome/exome sequencing. Accuracy and robustness of determining gender, provenance, and kinships were assessed.

Results

Concordance of genotype calls between Infinium QC and other platforms was above 99%. Here we show that the chip’s ancestry informative markers are sufficient for ethnicity determination at continental and sometimes subcontinental levels, with assignment accuracy varying with the coverage for a particular region and ethnic groups. Mean accuracies of provenance prediction at a regional level were varied from 81% for Asia, to 89% for Americas, 86% for Africa, 97% for Oceania, 98% for Europe, and 100% for India. Mean accuracy of ethnicity assignment predictions was 63%. Pairwise concordances of AFR samples with the samples from any other super populations were the lowest (0.39–0.43), while the concordances within the same population were relatively high (0.55–0.61). For all populations except African, cross-population comparisons were similar in their concordance ranges to the range of within-population concordances (0.54–0.57). Gender determination was correct in all tested cases.

Conclusions

Our results indicate that the Infinium QC Array-24 chip is suitable for cost-efficient, independent QC assaying in the settings of an NGS-based molecular diagnostic laboratory; hence, we recommend its integration into the standard laboratory workflow. Low-density chips can provide sample-specific measures for variant call accuracy, prevent sample mix-ups, validate self-reported ethnicities, and detect consanguineous cases. Integration of low-density chips into QC procedures aids proper interpretation of candidate sequence variants. To enhance utility of this low-density chip, we recommend expansion of ADME and mitochondrial markers. Inexpensive Infinium-like low-density human chips have a potential to become a “Swiss army knife” among genotyping assays suitable for many applications requiring high-throughput assays.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

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.

     

Model based dynamics analysis in live cell microtubule images

Background

The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data.

Results

In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior.

Conclusion

Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior.

     

Characterization of ankylosing spondylitis and rheumatoid arthritis using <Superscript>1</Superscript>H NMR-based metabolomics of human fecal extracts

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by ¹H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by ¹H NMR metabolomics.

     

The metabolome 18 years on: a concept comes of age

Background

The term ‘metabolome’ was introduced to the scientific literature in September 1998.

Aim and key scientific concepts of the review

To mark its 18-year-old ‘coming of age’, two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

     

Identifying anti-HSV compounds from unrelated plants using NMR and LC–MS metabolomic analysis

Introduction

Plants have been used to treat various ailments and diseases, including viral infections. Often activity is reported after screening plants traditionally used, without identifying the active principles.

Objectives

This study investigated the use of metabolomics to identify common compound groups or compounds from unrelated plants, but with similar reported biological activity. Plants with anti-viral activities against Herpes Simplex Virus (HSV), Cytomegalovirus (CMV) and Human Immunodeficiency Virus (HIV) were collected and analysed. A few non-active plants, with no reported anti-viral activity were included as control samples.

Methods

1H-NMR and LC–MS metabolomic analysis were conducted, to determine the chemical similarity between plants with similar activity using SIMCA and XCMS online.

Results

Plants with anti-HSV, anti-HIV and anti-CMV activity, presented specific clusters, with the non-active samples separating from the active samples. The anti-HSV group presented a clear contribution plot and chlorogenic acid was identified by NMR. LC–MS metabolomic analysis confirmed the NMR results and furthermore identified several chlorogenic acid isomers including the main substructures of chlorogenic acids.

Conclusion

Metabolomic analysis on unrelated plants with similar activity can be used to identify the active compound groups or compounds, thereby eliminating the need for screening of plants to determine biological activity, additionally providing information on possible active principles. The two analytical methods identified chlorogenic acids and its building blocks as common and important compounds within plants with anti-HSV activity. Intensified research on plants containing chlorogenic acids should be the focus of future research for development of accessible anti-HSV treatments.

     

Strategy for automated metabolic profiling of glioma subtypes from ex-vivo HRMAS spectra

Introduction

Infiltrating gliomas are primary brain tumors that express significant biological and clinical heterogeneity in adults, which complicates their treatment and prognosis. Characterization of tumor subtypes using spectroscopic analysis may assist in predicting malignant transformation and quantification of response to therapy.

Study objective

To implement an automated algorithm for classification of metabolomic profiles for the classification of glioma pathological grades and the prediction of malignant progression using spectra obtained by high-resolution magic angle spinning (HR-MAS) spectroscopy of patient-derived tissue samples.

Methods

237 image-guided tissue samples were obtained from 152 patients who underwent surgery for newly diagnosed or recurrent glioma and analyzed via HR-MAS spectroscopy. Orthogonal projection to latent structures discriminant analysis was used as a classifier and the variable-influence-on-projection values were evaluated to identify signature spectral regions.

Results

The accuracy of classifiers developed for discriminating glioma subtypes was 68% for newly diagnosed grade II versus III samples; 86 and 92% for new and recurrent grade III versus IV, respectively; 95% for newly diagnosed grade II versus IV; and 88% for recurrent grade II versus IV lesions. Classifiers distinguished between samples from newly diagnosed vs. recurrent lesions with an accuracy of 78% for grade III and 99% for grade IV glioma.

Conclusion

Classifying metabolomic profiles for new and recurrent glioma without prior assumptions regarding spectral components identified candidate in vivo biomarkers for use in assessing changes that are likely to impact treatment decisions.

     

Variation of the microbiota and metabolome along the canine gastrointestinal tract

Introduction

The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.

Objective

To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.

Methods

Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.

Results

Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.

Conclusion

The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.

     

Profiling of faecal water and urine metabolites among Papua New Guinea highlanders believed to be adapted to low protein intake

Introduction

Adequate amount of proteins from foods are normally needed to maintain muscle mass of the human body. Although protein intakes of Papua New Guinea (PNG) highlanders are less than biologically adequate, protein deficiency related disorders have rarely been reported. It has been postulated that gut microbiota play a role in such low-protein-adaptation.

Objective

To explore underlying biological mechanisms of low-protein adaptation among PNG highlanders by investigating metabolomic profiles of faecal water and urine.

Methods

We performed metabolome analysis using faecal water extracted from faecal samples of PNG highlanders, PNG non-highlanders and Japanese subjects. We paid special attention to amino acids and other metabolites produced by gut microbiota, as well as to metabolites involved in nitrogen recycling in the human gut.

Results

Our results indicated that amino acid levels were higher in faecal water from PNG highlanders than PNG non-highlanders, but amino acid levels did not differ between PNG highlanders and Japanese subjects. Among PNG highlander samples, amino acid levels tended to be higher in those who consumed less protein.

Conclusion

We speculated that a greater proportion of urea was excreted to the intestine among the PNG highlanders than other groups, and that the urea was used for nitrogen salvage. Intestinal bacteria are essential for producing ammonia from urea and also for producing amino acids from ammonia, which is a key process in low-protein adaptation. Profiling the gut microbiota of PNG highlanders is an important avenue for further research into the mechanisms of low-protein adaptation.

     

<Emphasis Type="Italic">Candida haemulonii</Emphasis> sensu lato: Update of the Determination of Susceptibility Profile in Argentina and Literature Review

Purpose of review

This review summarizes the information available of Candida haemulonii sensu lato, and updates the in vitro susceptibility profile of the isolates of these species from Argentina. C. haemulonii sensu lato causes fungemia in low frequency in adults and children; however, the knowledge about this emerging yeast is relevant since it is considered as a multi-resistant pathogen.

Recent findings

The discovery of new antifungal molecules, the determination of epidemiological cutoff value and clinical breakpoints for some yeasts of clinical impact, and the update of techniques to determine the in vitro susceptibility profile to yeast have generated some available information, although, for C. haemulonii sensu lato, this information is not always useful for clinical application.

Summary

We determined the susceptibility profile of C. haemulonii sensu lato strains isolated in Argentina, as a first step to establish the epidemiological cutoff values in our region. We also review the current situation in other countries.

     

High salt and fat intake,inflammation, and risk of cancer

Background

Inflammatory conditions are involved in the pathophysiology of cancer. Recent findings have revealed that excessive salt and fat intake is involved in the development of severe inflammatory reactions.

Methods

literature search was performed on various online databases (PubMed, Scopus, and Google Scholar) regarding the roles of high salt and fat intake in the induction of inflammatory reactions and their roles in the etiopathogenesis of cancer.

Results

The results indicate that high salt and fat intake can induce severe inflammatory conditions. However, various inflammatory conditions have been strongly linked to the development of cancer. Hence, high salt and fat intake might be involved in the pathogenesis of cancer progression via putative mechanisms related to inflammatory reactions.

Conclusion

Reducing salt and fat intake may decrease the risk of cancer.

     

Tartrate inhibition of prostatic acid phosphatase improves seminal fluid metabolite stability

Introduction

Human seminal fluid (hSF) has been suggested as a biofluid suitable to characterise male reproductive organ pathology with metabolomics. However, various enzymatic processes, including phosphorylcholine hydrolysis mediated by prostatic acid phosphatase (PAP), cause unwanted metabolite variation that may complicate metabolomic analysis of fresh hSF samples.

Objectives

To investigate the effects of PAP inhibition with tartrate.

Methods

Using NMR spectroscopy, the kinetics of phosphorylcholine to choline hydrolysis was characterized in hSF samples from three subjects at different temperatures and tartrate concentrations. Principal components analysis was used to characterise the effects of tartrate and temperature on personal differences in metabolite profiles. Potential effects of tartrate on RNA quantification were also determined.

Results

Metabolite profiles and the kinetics of phosphorylcholine degradation are reproducible in independent samples from three ostensibly normal subjects. Increasing concentrations of tartrate and refrigerated sample storage (279 K) resulted in greatly reduced reaction rates as judged by apparent rate constants. Multivariate statistical analysis showed that personal differences in metabolite profiles are not overshadowed by tartrate addition, which stabilises phosphorylcholine and choline concentrations. The tartrate signal also served as an internal concentration standard in the samples, allowing the determination of absolute metabolite concentrations in hSF. Furthermore, the presence of tartrate did not affect RNA expression analysis by qPCR.

Conclusion

Based on these results we recommend as standard protocol for the collection of hSF samples, that 10 mM tartrate are added immediately to samples, followed by sample storage/handling at 277 K until clinical processing within 6 h to remove/inactivate enzymes and isolate metabolite supernatant and other cellular fractions.