KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Comparative metabolome analysis of ruminal changes in Holstein dairy cows fed low- or high-concentrate diets

Introduction

Currently, information on the comprehensive changes in the ruminal metabolites of dairy cows fed high-concentrate diet is limited.

Objectives

This study aimed to compare the composition of whole-ruminal metabolites in dairy cows that were fed a low concentrate diet or a high concentrate diet using modern metabolome analysis.

Methods

Cows were fed a low-concentrate diet (LC; 40% concentrate feeds, dry matter (DM) basis) or a high-concentrate diet (HC; 70% concentrate feeds, DM basis). GC/MS was used to analyze rumen fluid samples.

Results

As compared with the LC group, HC diet significantly increased the concentration of bacterial degradation products (included xanthine, hypoxanthine, uracil, etc.), some toxic compounds (included lipopolysaccharide, biogenic amines, ethanolamine, etc.) and 15 amino acids (included alanine, leucine, glycine, etc.). The enrichment analysis of differentially expressed metabolites indicated that three pathways, including aminoacyl-tRNA biosynthesis; phenylalanine, tyrosine, and tryptophan biosynthesis; and valine, leucine and isoleucine biosynthesis, were significantly enriched after the diet treatments. Correlation network analysis revealed that HC diets altered the ruminal metabolic pattern, and the metabolites in the HC group were more complicated than those in the LC group. The correlations between ruminal metabolites and blood parameters were mainly centralized in the ruminal metabolites and albumin (40 metabolites), followed by globulin (18 metabolites) and total protein (6 metabolites).

Conclusions

These findings revealed that HC feeding altered the concentrations of ruminal metabolites as well as the metabolic pattern, and the rumen metabolism could be reflected by blood metabolism to a certain degree.

     

Mitochondrial aconitase is a key regulator of energy production for growth and protein expression in Chinese hamster ovary cells

Introduction

Mammalian cells like Chinese hamster ovary (CHO) cells are routinely used for production of recombinant therapeutic proteins. Cells require a continuous supply of energy and nutrients to sustain high cell densities whilst expressing high titres of recombinant proteins. Cultured mammalian cells are primarily dependent on glucose and glutamine metabolism for energy production.

Objectives

The TCA cycle is the main source of energy production and its continuous flow is essential for cell survival. Modulated regulation of TCA cycle can affect ATP production and influence CHO cell productivity.

Methods

To determine the key metabolic reactions of the cycle associated with cell growth in CHO cells, we transiently silenced each gene of the TCA cycle using RNAi.

Results

Silencing of at least four TCA cycle genes was detrimental to CHO cell growth. With an exception of mitochondrial aconitase (or Aco2), all other genes were associated with ATP production reactions of the TCA cycle and their resulting substrates can be supplied by other anaplerotic and cataplerotic reactions. This study is the first of its kind to have established key role of aconitase gene in CHO cells. We further investigated the temporal effects of aconitase silencing on energy production, CHO cell metabolism, oxidative stress and recombinant protein production.

Conclusion

Transient silencing of mitochondrial aconitase inhibited cell growth, reduced ATP production, increased production of reactive oxygen species and reduced cell specific productivity of a recombinant CHO cell line by at least twofold.

     

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.

     

Crystal structure of <Emphasis Type="Italic">Escherichia coli</Emphasis> protein ybgI,a toroidal structure with a dinuclear metal site

Background

The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.

Results

The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.

Conclusion

The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.

     

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.

     

Cell culture medium supplemented with taurine decreases basic charge variant levels of a monoclonal antibody

Objective

To explore the impact of taurine on monoclonal antibody (mAb) basic charge variants in Chinese hamster ovary (CHO) cell culture.

Results

In fed-batch culture, adding taurine in the feed medium slightly increased the maximum viable cell density and mAb titers in CHO cells. What’s more, taurine significantly decreased the lysine variant and oxidized variant levels, which further decreased basic variant contents from 32 to 27%. The lysine variant content in the taurine culture was approximately 4% lower than that in control condition, which was the main reason for the decrease in basic variants. Real-time PCR and cell-free assay revealed that taurine played a critical role in the upregulation of relative basic carboxypeptidase and stimulating extracellular basic carboxypeptidase activities.

Conclusion

Taurine exhibits noticeable impact on lower basic charge variants, which are mainly due to the decrease of lysine variant and oxidized protein variants.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

Improved batch correction in untargeted MS-based metabolomics

Introduction

Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account.

Objectives

This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects.

Methods

Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC–MS and GC–MS data sets of samples from Arabidopsis thaliana.

Results

The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects—replacing them with very small numbers such as zero seems the worst of the approaches considered.

Conclusion

The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Association between autophagy and inflammation in patients with rheumatoid arthritis receiving biologic therapy

Background

Increasing evidence indicates a pathogenic role of deregulated autophagy in rheumatoid arthritis (RA). We examined the relationship between autophagy and inflammatory parameters in patients with RA receiving biologic therapy.

Methods

In 72 patients with RA and 20 healthy control subjects (HC), autophagosome levels were determined by the mean fluorescence intensity (MFI) of autophagosomotropic dye incorporated into circulating immune cells, and p62 expression levels in immune cells were measured by flow cytometry. We used immunoblotting to examine protein expression of LC3-II and p62 in peripheral blood mononuclear cells.

Results

Patients with RA had significantly higher levels of autophagosome reflected by MFI of Cyto-ID in circulating lymphocytes, monocytes, and granulocytes (median values, 3.6, 11.6, and 64.8, respectively) compared with HC (1.9, 6.0, and 35.8; respectively) (all p?<?0.001). p62 MFI levels in lymphocytes and granulocytes from patients with RA (17.1 and 8.6, respectively) were significantly lower than those in the corresponding cells from HC (20.2, p?<?0.05; and 13.1, p?<?0.001, respectively). Significantly higher levels of LC3-II protein expression in contrast to lower p62 protein levels were observed in patients with RA than in HC. The autophagosome levels in immune cells were significantly correlated with inflammatory parameters in patients with RA, and they were significantly decreased with disease remission after treatment with tumor necrosis factor-α inhibitors or interleukin-6 receptor inhibitor.

Conclusions

Elevated autophagy with significant correlation to inflammation suggests the involvement of autophagy in RA pathogenesis. The effectiveness of biologic therapy might be partly related to the downregulation of autophagy expression.

     

An LC–MS-based lipidomics pre-processing framework underpins rapid hypothesis generation towards CHO systems biotechnology

Introduction

Given a raw LC–MS dataset, it is often required to rapidly generate initial hypotheses, in conjunction with other ‘omics’ datasets, without time-consuming lipid verifications. Furthermore, for meta-analysis of many datasets, it may be impractical to conduct exhaustive confirmatory analyses. In other cases, samples for validation may be difficult to obtain, replicate or maintain. Thus, it is critical that the computational identification of lipids is of appropriate accuracy, coverage, and unbiased by a researcher’s experience and prior knowledge.

Objectives

We aim to prescribe a systematic framework for lipid identifications, without usage of their characteristic retention-time by fully exploiting their underlying mass features.

Results

Initially, a hybrid technique, for deducing both common and distinctive daughter ions, is used to infer parent lipids from deconvoluted spectra. This is followed by parent confirmation using basic knowledge of their preferred product ions. Using the framework, we could achieve an accuracy of ~?80% by correctly identified 101 species from 18 classes in Chinese hamster ovary (CHO) cells. The resulting inferences could explain the recombinant-producing capability of CHO-SH87 cells, compared to non-producing CHO-K1 cells. For comparison, a XCMS-based study of the same dataset, guided by a user’s ad-hoc knowledge, identified less than 60 species of 12 classes from thousands of possibilities.

Conclusion

We describe a systematic LC–MS-based framework that identifies lipids for rapid hypothesis generation.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

Circulating sterols as predictors of early allograft dysfunction and clinical outcome in patients undergoing liver transplantation

Introduction

Sensitive and specific assessment of the hepatic graft metabolism after liver transplantation (LTX) is essential for early detection of postoperative dysfunction implying the need for consecutive therapeutic interventions.

Objectives

Here, we assessed circulating liver metabolites of the cholesterol pathway, amino acids and acylcarnitines and evaluated their predictive value on early allograft dysfunction (EAD) and clinical outcome in the context of LTX.

Methods

The metabolites were quantified in the plasma of 40 liver graft recipients one day pre- and 10 days post-LTX by liquid chromatography/tandem mass spectrometry (LC–MS/MS). Plant sterols as well as cholesterol and its precursors were determined in the free and esterified form; lanosterol in the free form only. Metabolites and esterification ratios were compared to the model for early allograft function scoring (MEAF) which is calculated at day 3 post-LTX from routine parameters defining EAD.

Results

The hepatic esterification ratio of all sterols, but not amino acids and acylcarnitine concentrations, showed substantial metabolic disturbances post-LTX and correlated to the MEAF. In ROC analysis, the low esterification ratio of β-sitosterol and stigmasterol from day 1 and of the other sterols from day 3 were predictive for a high MEAF, i.e. EAD. Additionally, the ratio of esterified β-sitosterol and free lanosterol were predictive for all days and the esterification ratio of the other sterols at day 3 or 4 post-LTX for 3-month mortality.

Conclusion

Low ratios of circulating esterified sterols are associated with a high risk of EAD and impaired clinical outcome in the early postoperative phase following LTX.

     

Predicting synthetic lethal genetic interactions in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> using short polypeptide clusters

Background

Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear.

Results

In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one.

Conclusion

We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins.

     

MiR-9 enhances the sensitivity of A549 cells to cisplatin by inhibiting autophagy

Objectives

To demonstrate that miR-9 inhibits autophagy by down-regulating Beclin1 and thus enhances the sensitivity of A549 cells to cisplatin.

Results

MiR-9 inhibited Beclin1 expression by binding to its 3′UTR. The inhibition decreased the cisplatin-induced autophagy in A549 cells, evidenced by the decreased expression of LC3II and GFP-LC3 puncta and the increased expression of P62. Upregulation of miR-9 level enhanced the sensibility of A549 cells to cisplatin and increased the cisplatin-induced apoptosis. Overexpression of Beclin1 reversed above effects of miR-9 mimics, cisplatin-induced autophagy was increased and apoptosis was decreased.

Conclusions

MiR-9 inhibits autophagy via targeting Beclin1 3′UTR and thus enhances cisplatin sensitivity in A549 cells.

     

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.

     

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.