DeltaMS: a tool to track isotopologues in GC- and LC-MS data

Introduction

Stable isotopic labeling experiments are powerful tools to study metabolic pathways, to follow tracers and fluxes in biotic and abiotic transformations and to elucidate molecules involved in metal complexing.

Objective

To introduce a software tool for the identification of isotopologues from mass spectrometry data.

Methods

DeltaMS relies on XCMS peak detection and X¹³CMS isotopologue grouping and then analyses data for specific isotope ratios and the relative error of these ratios. It provides pipelines for recognition of isotope patterns in three experiment types commonly used in isotopic labeling studies: (1) search for isotope signatures with a specific mass shift and intensity ratio in one sample set, (2) analyze two sample sets for a specific mass shift and, optionally, the isotope ratio, whereby one sample set is isotope-labeled, and one is not, (3) analyze isotope-guided perturbation experiments with a setup described in X¹³CMS.

Results

To illustrate the versatility of DeltaMS, we analyze data sets from case-studies that commonly pose challenges in evaluation of natural isotopes or isotopic signatures in labeling experiment. In these examples, the untargeted detection of sulfur, bromine and artificial metal isotopic patterns is enabled by the automated search for specific isotopes or isotope signatures.

Conclusion

DeltaMS provides a platform for the identification of (pre-defined) isotopologues in MS data from single samples or comparative metabolomics data sets.

Graphical Abstract

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Effects of <Emphasis Type="Italic">Penicillium bilaii</Emphasis> on maize growth are mediated by available phosphorus

Background and aims

Functional traits are promising indicators of global changes and ecosystem processes. Trait responses to environmental conditions have been examined widely in vascular plants. In contrast, few studies have focused on soil lichens and mosses composing biocrusts. We aimed to evaluate the potential of biocrust tissue traits as indicators of changes in climate and soil properties.

Methods

Isotope ratios and nutrient content in biocrust tissue were analyzed in 13 Mediterranean shrublands along an aridity gradient. Differences in tissue traits between biocrust groups (lichens and mosses), and relationships between tissue traits and climatic and soil variables were examined.

Results

Lichens and mosses differed in δ¹³C, δ¹⁵N and N content, indicating distinct physical and physiological attributes. Tissue traits correlated strongly with numerous climatic variables, likely due to a modulator effect on biocrust water relations and metabolism. We found contrasting responses of lichen and moss traits to climate, although they responded similarly to soil properties. Overall, the most responsive trait was δ¹⁵N, suggesting this trait is the best to reflect integrated processes occurring in the atmosphere and soil.

Conclusions

Biocrust tissue traits arise as cost-effective, integrative ecological indicators of global change drivers in Mediterranean ecosystems, with potential applications in response-effect trait frameworks.

     

Changes from pasture to a native tree plantation affect soil organic matter in a tropical soil,Panamá

Background and aims

We examined changes in soil organic matter arising from conversion of a 45-year old pasture to a 10 yr. old native tree plantation in Panamá, to evaluate the effect of monoculture and mixtures.

Methods

We intensively sampled the soil 0–10 cm depth in the pasture in 2001 and in 22 plantation plots in 2011, ranging from 5 monocultures to 3- and 6-species treatments; samples were also taken from an undisturbed forest site. Soil analyses included organic carbon (SOC) and δ¹³C.

Results

Conversion of the pasture to tree plantation resulted in an overall loss of SOC of 0.6 kg m^?2 (18%) in the top 10 cm, but neither tree species nor diversity had a significant effect. End-member δ¹³C values suggested that the contribution of C₃ plants to SOC was increased from 26% in the pasture to 55% after 10 years of plantation and SOC turnover times were calculated to be 21–36 yr.

Conclusions

The magnitude of the loss in soil SOC is smaller than the increases in tree biomass (~3 kg C m^?2) and litter (~0.3 kg C m^?2) in the plantation, but still a significant part of the ecosystem C balance.

     

Integrated analysis of microRNA-target interactions with clinical outcomes for cancers

Background

Clinical statement alone is not enough to predict the progression of disease. Instead, the gene expression profiles have been widely used to forecast clinical outcomes. Many genes related to survival have been identified, and recently miRNA expression signatures predicting patient survival have been also investigated for several cancers. However, miRNAs and their target genes associated with clinical outcomes have remained largely unexplored.

Methods

Here, we demonstrate a survival analysis based on the regulatory relationships of miRNAs and their target genes. The patient survivals for the two major cancers, ovarian cancer and glioblastoma multiforme (GBM), are investigated through the integrated analysis of miRNA-mRNA interaction pairs.

Results

We found that there is a larger survival difference between two patient groups with an inversely correlated expression profile of miRNA and mRNA. It supports the idea that signatures of miRNAs and their targets related to cancer progression can be detected via this approach.

Conclusions

This integrated analysis can help to discover coordinated expression signatures of miRNAs and their target mRNAs that can be employed for therapeutics in human cancers.

     

Beclin 1 regulates neuronal transforming growth factor-β signaling by mediating recycling of the type I receptor ALK5

Background

Beclin 1 is a key regulator of multiple trafficking pathways, including autophagy and receptor recycling in yeast and microglia. Decreased beclin 1 levels in the CNS result in neurodegeneration, an effect attributed to impaired autophagy. However, neurons also rely heavily on trophic factors, and signaling through these pathways requires the proper trafficking of trophic factor receptors.

Results

We discovered that beclin 1 regulates signaling through the neuroprotective TGF-β pathway. Beclin 1 is required for recycling of the type I TGF-β receptor ALK5. We show that beclin 1 recruits the retromer to ALK5 and facilitates its localization to Rab11⁺ endosomes. Decreased levels of beclin 1, or its binding partners VPS34 and UVRAG, impair TGF-β signaling.

Conclusions

These findings identify beclin 1 as a positive regulator of a trophic signaling pathway via receptor recycling, and suggest that neuronal death induced by decreased beclin 1 levels may also be due to impaired trophic factor signaling.

     

Imbalanced plant stoichiometry at contrasting geologic-derived phosphorus sites in subtropics: the role of microelements and plant functional group

Aims

In western North America ectomycorrhizal fungi are critical to establishment of conifers in low nitrogen soils. Fire can affect both ectomycorrhizal fungi and soil properties, and inoculation with ectomycorrhizal fungi is recommended when planting on burns for restoration. The aim of this study was to examine how Suillus species used in inoculation affect whitebark pine (Pinus albicaulis L.) seedlings planted in fire-impacted soil.

Methods

In a greenhouse experiment, Suillus-colonized and uncolonized whitebark pine seedlings were planted in unsterilized and sterilized (control) soil from a recent burn. After 6 months, foliar nitrogen and carbon content, concentration, and stable isotope values were assessed, along with growth parameters.

Results

When seedlings were colonized, biomass was 61% greater, foliar nitrogen content 25% higher, foliar nitrogen concentration 30–63% lower; needles had lower δ¹⁵N and higher δ¹³C. Differences were more pronounced in sterilized soil where colonization was higher. Foliar N content was negatively correlated with δ¹⁵N values.

Conclusions

Colonization by host-specific fungi produced larger seedlings with higher foliar nitrogen content in both burn soils. The hypothesis that ectomycorrhizal fungi on roots fractionate nitrogen isotopes leading to lower δ¹⁵N in needles is supported. This helps explain restoration outcomes, and bridges the gap between field and in vitro investigations.

     

Automation of chemical assignment for identifying molecular formula of S-containing metabolites by combining metabolomics and chemoinformatics with <Superscript>34</Superscript>S labeling

Introduction

Sulfur-containing metabolites (S-metabolites) in organisms including plants have unique benefits to humans. So far, few analytical methods have explored such metabolites.

Objectives

We aimed to develop an automatic chemically assigning platform by metabolomics and chemoinformatics with ³⁴S labeling to identify the molecular formula of S-metabolites.

Methods

Direct infusion analysis using Fourier transform ion cyclotron resonance-mass spectrometry provided ultra-high-resolution data including clearly separated isotopic ions—¹⁵N, ³⁴S, ¹⁸O, and ¹³C₂—in the flower, silique, leaf, stem, and root of non-labeled and ³⁴S-labeled Arabidopsis thaliana. Chemoinformatic analysis assigned several elemental compositions of S-metabolites to the acquired S-containing monoisotopic ions using mass accuracy and peak resolution in the non-labeled metabolome data. Possible elemental compositions were characterized on the basis of diagnostic scores of the exact mass and isotopic ion pattern, and a database search. By comparing elemental compositions assigned to the ³⁴S-labeled data with those assigned to the non-labeled data, the elemental composition of S-metabolites were determined. The determined elemental compositions were surveyed using the in-house database, which stores molecular formulae downloaded from metabolome databases.

Results

We identified 35 molecular formulae for known S-metabolites and characterized 72 for unknown. Chemoinformatics required around 1.5 min to analyze a pair of the non-labeled and ³⁴S-labeled data of the organ.

Conclusion

In this study, we developed an automation platform for automatically identifying the presence of S-metabolites. We identified the molecular formula of known S-metabolites, which are accessible in free databases, together with that of unknown. This analytical method did not focus on identifying the structure of S-metabolites, but on the automatic identification of their molecular formula.

     

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.

     

Statistical analysis of fractionation resistance by functional category and expression

Background

The current literature establishes the importance of gene functional category and expression in promoting or suppressing duplicate gene loss after whole genome doubling in plants, a process known as fractionation. Inspired by studies that have reported gene expression to be the dominating factor in preventing duplicate gene loss, we analyzed the relative effect of functional category and expression.

Methods

We use multivariate methods to study data sets on gene retention, function and expression in rosids and asterids to estimate effects and assess their interaction.

Results

Our results suggest that the effect on duplicate gene retention fractionation by functional category and expression are independent and have no statistical interaction.

Conclusion

In plants, functional category is the more dominant factor in explaining duplicate gene loss.

     

Crop metabolomics: from diagnostics to assisted breeding

Background

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

Aim of Review

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

Key Scientific Concepts of Review

Translational metabolomics applied to crop breeding programs.

     

Effects of zinc ex vivo on taurine uptake in goldfish retinal cells

Background

Taurine and zinc exert neurotrophic effects in the central nervous system. Current studies demonstrate that Na⁺/Cl^- dependent neurotransmitter transporters, similar to that of taurine, are modulated by micromolar concentrations of zinc. This study examined the effect of zinc sulfate ex vivo on [³H]taurine transport in goldfish retina.

Methods

Isolated cells were incubated in Ringer with zinc (0.1–100 µM). Taurine transport was done with 50 nM [³H]taurine or by isotopic dilution with taurine (0.001–1 mM) and 50 nM [³H]taurine.

Results

Zinc reduced the capacity of taurine transport without changes in affinity, and caused a noncompetitive inhibition of high affinity taurine transport, with an EC₅₀= 0.072 µM. The mechanism by which zinc affects taurine transport is unknown at the present.

Conclusions

There may be a binding site of zinc in the transporter that affects union or translocation of taurine, or possibly the formation of taurine-zinc complexes, rather than free zinc, could affect the operation of the transporter.

     

Effects of magnesium deficiency on magnesium uptake activity of rice root,evaluated using <Superscript>28</Superscript> Mg as a tracer

Aims

The mechanisms underlying magnesium (Mg) uptake by plant roots remain to be fully elucidated. In particular, there is little information about the effects of Mg deficiency on Mg uptake activity. A Mg uptake kinetic study is essential for better understanding the Mg uptake system.

Methods

We performed a Mg uptake tracer experiment in rice plants using ²⁸?Mg.

Results

Mg uptake was mediated by high- and low-affinity transport systems. The K _m value of the high-affinity transport system was approximately 70 μM under Mg-deficient conditions. The Mg uptake activity was promoted by Mg deficiency, which in turn fell to the basal level after 5- min of Mg resupply. The induced uptake rate was inhibited by ionophore treatment, suggesting that an energy-dependent uptake system is enhanced by Mg deficiency.

Conclusions

The Mg uptake changes rapidly with Mg conditions in rice, as revealed by a ²⁸?Mg tracer experiment. This technique is expected to be applicable for Mg uptake analyses, particularly in mutants or other lines.

     

Measurement of the <Superscript>15</Superscript>N/<Superscript>14</Superscript>N ratio of phenylalanine in fermentation matrix by isotope ratio mass spectrometry

Objectives

To determine the origin of ¹⁵N-labeled phenylalanine in microbial metabolic flux analysis using ¹⁵N as a tracer, a method for measuring phenylalanine δ¹⁵N using HPLC coupled with elemental analysis-isotope ratio mass spectrometry (EA-IRMS) was developed.

Results

The original source of the ¹⁵N-labeled phenylalanine was determined using this new method that consists of three steps: optimization of the HPLC conditions, evaluation of the isotope fractionation effects, and evaluation of the effect of pre-processing on the phenylalanine nitrogen stable isotope. In addition, the use of a ¹⁵N-labeled inorganic nitrogen source, rather than ¹⁵N-labeled amino acids, was explored using this method.

Conclusions

The method described here can also be applied to the analysis of metabolic flux.

     

Predicting ovarian cancer recurrence by plasma metabolic profiles before and after surgery

Background

Previous metabolomic studies have revealed that plasma metabolic signatures may predict epithelial ovarian cancer (EOC) recurrence. However, few studies have performed metabolic profiling of pre- and post-operative specimens to investigate EOC prognostic biomarkers.

Objective

The aims of our study were to compare the predictive performance of pre- and post-operative specimens and to create a better model for recurrence by combining biomarkers from both metabolic signatures.

Methods

Thirty-five paired plasma samples were collected from 35 EOC patients before and after surgery. The patients were followed-up until December, 2016 to obtain recurrence information. Metabolomics using rapid resolution liquid chromatography–mass spectrometry was performed to identify metabolic signatures related to EOC recurrence. The support vector machine model was employed to predict EOC recurrence using identified biomarkers.

Results

Global metabolomic profiles distinguished recurrent from non-recurrent EOC using both pre- and post-operative plasma. Ten common significant biomarkers, hydroxyphenyllactic acid, uric acid, creatinine, lysine, 3-(3,5-diiodo-4-hydroxyphenyl) lactate, phosphohydroxypyruvic acid, carnitine, coproporphyrinogen, l-beta-aspartyl-l-glutamic acid and 24,25-hydroxyvitamin D3, were identified as predictive biomarkers for EOC recurrence. The area under the receiver operating characteristic (AUC) values in pre- and post-operative plasma were 0.815 and 0.909, respectively; the AUC value after combining the two sets reached 0.964.

Conclusion

Plasma metabolomic analysis could be used to predict EOC recurrence. While post-operative biomarkers have a predictive advantage over pre-operative biomarkers, combining pre- and post-operative biomarkers showed the best predictive performance and has great potential for predicting recurrent EOC.

     

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.

     

Soil micro-food web interactions and rhizosphere priming effect

Background

Seeds host bacterial inhabitants but only a limited knowledge is available on which taxa inhabit seed, which niches could be colonized, and what the routes of colonization are.

Scope

Within this commentary, a discussion is provided on seed bacterial inhabitants, their taxa, and from where derive the seed colonizers.

Conclusions

Seeds/and grains host specific bacteria deriving from the anthosphere, carposphere, or from cones of gymnosperms and inner tissues of plants after a long colonization from the soil to reproductive organs.

     

Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method

Background

Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into cellular heterogeneity. Subsequently, a challenging computational problem is to cluster high dimensional noisy datasets with substantially fewer cells than the number of genes.

Methods

In this paper, we introduced a consensus clustering framework conCluster, for cancer subtype identification from single-cell RNA-seq data. Using an ensemble strategy, conCluster fuses multiple basic partitions to consensus clusters.

Results

Applied to real cancer scRNA-seq datasets, conCluster can more accurately detect cancer subtypes than the widely used scRNA-seq clustering methods. Further, we conducted co-expression network analysis for the identified melanoma subtypes.

Conclusions

Our analysis demonstrates that these subtypes exhibit distinct gene co-expression networks and significant gene sets with different functional enrichment.

     

Production of δ-decalactone from linoleic acid via 13-hydroxy-9(Z)-octadecenoic acid intermediate by one-pot reaction using linoleate 13-hydratase and whole <Emphasis Type="Italic">Yarrowia lipolytica</Emphasis> cells

Objective

To produce δ-decalactone from linoleic acid by one-pot reaction using linoleate 13-hydratase with supplementation with whole Yarrowia lipolytica cells.

Results

Whole Y. lipolytica cells at 25 g l^?1 produced1.9 g l^?1 δ-decalactone from 7.5 g 13-hydroxy-9(Z)-octadecenoic acid l^?1 at pH 7.5 and 30 °C for 21 h. Linoleate 13-hydratase from Lactobacillus acidophilus at 3.5 g l^?1 with supplementation with 25 g Y. lipolytica cells l^?1 in one pot at 3 h produced 1.9 g l^?1 δ-decalactone from 10 g linoleic acid l^?1 via 13-hydroxy-9(Z)-octadecenoic acid intermediate at pH 7.5 and 30°C after 18 h, with a molar conversion yield of 31 % and productivity of 106 mg l^?1 h^?1.

Conclusion

To the best of our knowledge, this is the first production of δ-decalactone using unsaturated fatty acid.

     

Nitrogen deposition decreases the benefits of symbiosis in a native legume

Aims

Anthropogenic nitrogen deposition can provide legumes with a cheap source of nitrogen relative to symbiotic nitrogen fixation, leading to the potential breakdown of this critical symbiosis. Here, the effects of nitrogen deposition were tested on a native symbiosis between legumes and rhizobia.

Methods

Deposition rates, soil nitrogen concentration, and plant nitrogen isotopic composition were quantified along a predicted deposition gradient in California. Acmispon strigosus seedlings were exposed to fertilization spanning nitrogen concentrations observed in the plant’s California range. Both wild and experimental plants from pristine and nitrogen polluted sites were tested using rhizobial strains that varied in nitrogen fixation.

Results

Deposition intensity was tightly correlated with nitrogen concentration in soils. The growth benefits of rhizobial nodulation were dramatically reduced by even modest levels of mineral nitrogen, and all Acmispon lines failed to form root nodules at high nitrogen concentrations.

Conclusions

Our dataset suggests that anthropogenic deposition has greatly increased soil nitrogen concentrations in Southern California leading to significantly reduced benefits of rhizobial symbiosis. If nitrogen deposition increases continue, plant host mortality and a total collapse of the symbiosis could result.

     

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.