Structure elucidation of metabolite x17299 by interpretation of mass spectrometric data

Introduction

A major bottleneck in metabolomic studies is metabolite identification from accurate mass spectrometric data. Metabolite x17299 was identified in plasma as an unknown in a metabolomic study using a compound-centric approach where the associated ion features of the compound were used to determine the true molecular mass.

Objectives

The aim of this work is to elucidate the chemical structure of x17299, a new compound by de novo interpretation of mass spectrometric data.

Methods

An Orbitrap Elite mass spectrometer was used for acquisition of mass spectra up to MS⁴ at high resolution. Synthetic standards of N,N,N-trimethyl-l-alanyl-l-proline betaine (l,l-TMAP), a diastereomer, and an enantiomer were chemically prepared.

Results

The planar structure of x17299 was successfully proposed by de novo mechanistic interpretation of mass spectrometric data without any laborious purification and nuclear magnetic resonance spectroscopic analysis. The proposed structure was verified by deuterium exchanged mass spectrometric analysis and confirmed by comparison to a synthetic standard. Relative configuration of x17299 was determined by direct chromatographic comparison to a pair of synthetic diastereomers. Absolute configuration was assigned after derivatization of x17299 with a chiral auxiliary group followed by its chromatographic comparison to a pair of synthetic standards.

Conclusion

The chemical structure of metabolite x17299 was determined to be l,l-TMAP.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Coordinate systems for supergenomes

Background

Genome sequences and genome annotation data have become available at ever increasing rates in response to the rapid progress in sequencing technologies. As a consequence the demand for methods supporting comparative, evolutionary analysis is also growing. In particular, efficient tools to visualize-omics data simultaneously for multiple species are sorely lacking. A first and crucial step in this direction is the construction of a common coordinate system. Since genomes not only differ by rearrangements but also by large insertions, deletions, and duplications, the use of a single reference genome is insufficient, in particular when the number of species becomes large.

Results

The computational problem then becomes to determine an order and orientations of optimal local alignments that are as co-linear as possible with all the genome sequences. We first review the most prominent approaches to model the problem formally and then proceed to showing that it can be phrased as a particular variant of the Betweenness Problem. It is NP hard in general. As exact solutions are beyond reach for the problem sizes of practical interest, we introduce a collection of heuristic simplifiers to resolve ordering conflicts.

Conclusion

Benchmarks on real-life data ranging from bacterial to fly genomes demonstrate the feasibility of computing good common coordinate systems.

     

Phylogenetic signal from rearrangements in 18 Anopheles species by joint scaffolding extant and ancestral genomes

Background

Genomes rearrangements carry valuable information for phylogenetic inference or the elucidation of molecular mechanisms of adaptation. However, the detection of genome rearrangements is often hampered by current deficiencies in data and methods: Genomes obtained from short sequence reads have generally very fragmented assemblies, and comparing multiple gene orders generally leads to computationally intractable algorithmic questions.

Results

We present a computational method, ADseq, which, by combining ancestral gene order reconstruction, comparative scaffolding and de novo scaffolding methods, overcomes these two caveats. ADseq provides simultaneously improved assemblies and ancestral genomes, with statistical supports on all local features. Compared to previous comparative methods, it runs in polynomial time, it samples solutions in a probabilistic space, and it can handle a significantly larger gene complement from the considered extant genomes, with complex histories including gene duplications and losses. We use ADseq to provide improved assemblies and a genome history made of duplications, losses, gene translocations, rearrangements, of 18 complete Anopheles genomes, including several important malaria vectors. We also provide additional support for a differentiated mode of evolution of the sex chromosome and of the autosomes in these mosquito genomes.

Conclusions

We demonstrate the method’s ability to improve extant assemblies accurately through a procedure simulating realistic assembly fragmentation. We study a debated issue regarding the phylogeny of the Gambiae complex group of Anopheles genomes in the light of the evolution of chromosomal rearrangements, suggesting that the phylogenetic signal they carry can differ from the phylogenetic signal carried by gene sequences, more prone to introgression.

     

Serum metabolomic study for detecting biomarkers of non-traumatic osteonecrosis of the femoral head

Introduction

Non-traumatic osteonecrosis of the femoral head (NTONFH) is a progressive disease, always leading to hip dysfunction if no early intervention was applied. The difficulty for early diagnosis of NTONFH is due to the slight symptoms at early stages as well as the high cost for screening patients by using magnetic resonance imaging.

Objective

The aim was to detect biomarkers of early-stage NTONFH, which was beneficial to the exploration of a cost-effective approach for the early diagnose of the disease.

Methods

Metabolomic approaches were employed in this study to detect biomarkers of early-stage NTONFH (22 patients, 23 controls), based on the platform of ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and the uses of multivariate statistic analysis, putative metabolite identification, metabolic pathway analysis and biomarker analysis.

Results

In total, 33 serum metabolites were found altered between NTONFH group and control group. In addition, glycerophospholipid metabolism and pyruvate metabolism were highly associated with the disease.

Conclusion

The combination of LysoPC (18:3), l-tyrosine and l-leucine proved to have a high diagnostic value for early-stage NTONFH. Our findings may contribute to the protocol for early diagnosis of NTONFH and further elucidate the underlying mechanisms of the disease.

     

Furosemide enhances the sensitivity of urinary metabolomics for assessment of kidney function

Introduction

The ability of urinary metabolomics to detect meaningful, tissue-specific, biological effects (i.e., toxicity, disease) is compounded by high background variability. We hypothesize that sensitivity can be enhanced by imposing a tissue-targeted metabolic stressor.

Objective

We tested whether the sensitivity of metabolomics to assess kidney function is improved under the diuretic stress of furosemide.

Methods

To mildly compromise kidney, rats were given a sub-acute dose of d-serine. Then at 24 h postdose, we administered vehicle solution (control) or the diuretic drug, furosemide, and conducted NMR-based urinary metabolomics.

Results

Principal Components and OPLS discriminant analyses showed no effects on urinary profiles in rats receiving d-serine alone. However, the effects of d-serine were observable under furosemide-induced stress, as urinary profiles classified separately from rats receiving furosemide alone or vehicle-treated controls (p?<?0.001). Furthermore, this profile was uniquely different from a co-treatment effect observed following co-administration of d-serine?+?furosemide. We identified 24 metabolites to classify the effects of furosemide in normal rats vs. d-serine-compromised rats. Most notably, a furosemide-induced increase in urinary excretion of α-ketoglutarate, creatinine, trigonelline, and tryptophan in control rats, was significantly reduced in d-serine exposed rats (p?<?0.05). Interestingly, increased tryptophan metabolism has been shown to correlate with the severity of kidney transplant failure and chronic kidney disease.

Conclusions

We attribute these effects to differences in kidney function, which were only detectable under the stress imposed by furosemide. This technique may extend to other organ systems and may provide improved sensitivity for assessment of tissue function or early detection of disease.

     

An efficient biocatalytic synthesis of imidazole-4-acetic acid

Objective

To develop a new and efficient biocatalytic synthesis method of imidazole-4-acetic acid (IAA) from l-histidine (l-His).

Results

l-His was converted to imidazole-4-pyruvic acid (IPA) by an Escherichia coli whole-cell biocatalyst expressing membrane-bound l-amino acid deaminase (ml-AAD) from Proteus vulgaris firstly. The obtained IPA was subsequently decarboxylated to IAA under the action of H₂O₂. Under optimum conditions, 34.97 mM IAA can be produced from 50 mM l-His, with a yield of 69.9%.

Conclusions

Compared to the traditional chemical synthesis, this biocatalytic method for IAA production is not only environmentally friendly, but also more cost effective, thus being promising for industrial IAA production.

     

Individualized,discrete event,simulations provide insight into inter- and intra-subject variability of extended-release,drug products

Objective

Develop and validate particular, concrete, and abstract yet plausible in silico mechanistic explanations for large intra- and interindividual variability observed for eleven bioequivalence study participants. Do so in the face of considerable uncertainty about mechanisms.

Methods

We constructed an object-oriented, discrete event model called subject (we use small caps to distinguish computational objects from their biological counterparts). It maps abstractly to a dissolution test system and study subject to whom product was administered orally. A subject comprises four interconnected grid spaces and event mechanisms that map to different physiological features and processes. Drugs move within and between spaces. We followed an established, Iterative Refinement Protocol. Individualized mechanisms were made sufficiently complicated to achieve prespecified Similarity Criteria, but no more so. Within subjects, the dissolution space is linked to both a product-subject Interaction Space and the GI tract. The GI tract and Interaction Space connect to plasma, from which drug is eliminated.

Results

We discovered parameterizations that enabled the eleven subject simulation results to achieve the most stringent Similarity Criteria. Simulated profiles closely resembled those with normal, odd, and double peaks. We observed important subject-by-formulation interactions within subjects.

Conclusion

We hypothesize that there were interactions within bioequivalence study participants corresponding to the subject-by-formulation interactions within subjects. Further progress requires methods to transition currently abstract subject mechanisms iteratively and parsimoniously to be more physiologically realistic. As that objective is achieved, the approach presented is expected to become beneficial to drug development (e.g., controlled release) and to a reduction in the number of subjects needed per study plus faster regulatory review.

     

Importing statistical measures into Artemis enhances gene identification in the <Emphasis Type="Italic">Leishmania</Emphasis> genome project

Background

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces.

Results

Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODON USAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence.

Conclusion

An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.

     

Effect of high hydrostatic pressure treatment on isoquercetin production from rutin by commercial α-<Emphasis Type="SmallCaps">l</Emphasis>-rhamnosidase

Objectives

To optimize conversion of rutin to isoquercetin by commercial α-l-rhamnosidase using high hydrostatic pressure (HHP).

Results

The de-rhamnosylation activity of α-l-rhamnosidase for isoquercetin production was maximal at pH 6.0 and 50 °C using HHP (150 MPa). The enzyme showed high specificity for rutin. The specific activity for rutin at HHP was 1.5-fold higher than that at atmospheric pressure. The enzyme completely hydrolysed 20 mM rutin in tartary buckwheat extract after 2 h at HHP, with a productivity of 10 mM h^?1. The productivity and conversion were 2.2- and 1.5-fold higher at HHP than at atmospheric pressure, respectively.

Conclusions

This is the first report concerning the enzymatic hydrolysis of isoquercetin in tartary buckwheat at HHP.

     

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.

     

Unexpected differential metabolic responses of <Emphasis Type="Italic">Campylobacter jejuni</Emphasis> to the abundant presence of glutamate and fucose

Introduction

Campylobacter jejuni is the leading cause of foodborne bacterial enteritis in humans, and yet little is known in regard to how genetic diversity and metabolic capabilities among isolates affect their metabolic phenotype and pathogenicity.

Objectives

For instance, the C. jejuni 11168 strain can utilize both l-fucose and l-glutamate as a carbon source, which provides the strain with a competitive advantage in some environments and in this study we set out to assess the metabolic response of C. jejuni 11168 to the presence of l-fucose and l-glutamate in the growth medium.

Methods

To achieve this, untargeted hydrophilic liquid chromatography coupled to mass spectrometry was used to obtain metabolite profiles of supernatant extracts obtained at three different time points up to 24 h.

Results

This study identified both the depletion and the production and subsequent release of a multitude of expected and unexpected metabolites during the growth of C. jejuni 11168 under three different conditions. A large set of standards allowed identification of a number of metabolites. Further mass spectrometry fragmentation analysis allowed the additional annotation of substrate-specific metabolites. The results show that C. jejuni 11168 upon l-fucose addition indeed produces degradation products of the fucose pathway. Furthermore, methionine was faster depleted from the medium, consistent with previously-observed methionine auxotrophy.

Conclusions

Moreover, a multitude of not previously annotated metabolites in C. jejuni were found to be increased specifically upon l-fucose addition. These metabolites may well play a role in the pathogenicity of this C. jejuni strain.

     

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.

     

1,5-Anhydroglucitol predicts CKD progression in macroalbuminuric diabetic kidney disease: results from non-targeted metabolomics

Introduction

Metabolomics allows exploration of novel biomarkers and provides insights on metabolic pathways associated with disease. To date, metabolomics studies on CKD have been largely limited to Caucasian populations and have mostly examined surrogate end points.

Objective

In this study, we evaluated the role of metabolites in predicting a primary outcome defined as dialysis need, doubling of serum creatinine or death in Brazilian macroalbuminuric DKD patients.

Methods

Non-targeted metabolomics was performed on plasma from 56 DKD patients. Technical triplicates were done. Metabolites were identified using Agilent Fiehn GC/MS Metabolomics and NIST libraries (Agilent MassHunter Work-station Quantitative Analysis, version B.06.00). After data cleaning, 186 metabolites were left for analyses.

Results

During a median follow-up time of 2.5 years, the PO occurred in 17 patients (30.3%). In non-parametric testing, 13 metabolites were associated with the PO. In univariate Cox regression, only 1,5-anhydroglucitol (HR 0.10; 95% CI 0.01–0.63, p?=?.01), norvaline and l-aspartic acid were associated with the PO. After adjustment for baseline renal function, 1,5-anhydroglucitol (HR 0.10; 95% CI 0.02–0.63, p?=?.01), norvaline (HR 0.01; 95% CI 0.001–0.4, p?=?.01) and aspartic acid (HR 0.12; 95% CI 0.02–0.64, p?=?.01) remained significantly and inversely associated with the PO.

Conclusion

Our results show that lower levels of 1,5-anhydroglucitol, norvaline and l-aspartic acid are associated with progression of macroalbuminuric DKD. While norvaline and l-aspartic acid point to interesting metabolic pathways, 1,5-anhydroglucitol is of particular interest since it has been previously shown to be associated with incident CKD. This inverse biomarker of hyperglycemia should be further explored as a new tool in DKD.

     

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.

     

Normalisation and weighting in life cycle assessment: <Emphasis Type="Italic">quo vadis</Emphasis>?

Purpose

Building on the rhetoric question “quo vadis?” (literally “Where are you going?”), this article critically investigates the state of the art of normalisation and weighting approaches within life cycle assessment. It aims at identifying purposes, current practises, pros and cons, as well as research gaps in normalisation and weighting. Based on this information, the article wants to provide guidance to developers and practitioners. The underlying work was conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative, Task Force on Cross-Cutting issues in life cycle impact assessment (LCIA).

Methods

The empirical work consisted in (i) an online survey to investigate the perception of the LCA community regarding the scientific quality and current practice concerning normalisation and weighting; (ii) a classification followed by systematic expert-based assessment of existing methods for normalisation and weighting according to a set of five criteria: scientific robustness, documentation, coverage, uncertainty and complexity.

Results and discussion

The survey results showed that normalised results and weighting scores are perceived as relevant for decision-making, but further development is needed to improve uncertainty and robustness. The classification and systematic assessment of methods allowed for the identification of specific advantages and limitations.

Conclusions

Based on the results, recommendations are provided to practitioners that desire to apply normalisation and weighting as well as to developers of the underlying methods.

     

Isolation and characterization of a novel <Emphasis Type="SmallCaps">l</Emphasis>-glutamate oxidase with strict substrate specificity from <Emphasis Type="Italic">Streptomyces diastatochromogenes</Emphasis>

Objectives

To find an l-glutamate oxidase (LGox), to be used for the quantitative analysis of l-glutamic acid, an lgox gene encoding LGox from Streptomyces diastatochromogenes was isolated, cloned and characterized.

Results

The gene had an ORF of 1974 bp encoding a protein of 657 amino acid residues. In comparison to the LGox precursor, the proteinase K-treated enzyme exhibited improved affinity to substrate and with a K _m of 0.15 mM and V _max of 62 μmol min^?1 mg^?1. The 50% thermal inactivation temperature of the proteinase K treated enzyme was increased from 50 to 70 °C. The enzyme exhibited strict specificity for l-glutamate.

Conclusions

LGox treated by proteinase K exhibited strict specificity for l-glutamate, good thermostability and high substrate affinity.

     

Multienzymatic cascade synthesis of fucosyloligosaccharide via a two-step fermentation strategy in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Objectives

To achieve multienzymatic cascade synthesis of fucosyl oligosaccharide from d-mannose by two-step fermentation pathway in Escherichia coli.

Results

E. coli BL21(DE3) harboring pET-22b(+) vectors with six genes, i.e., glucokinase (Glk), phosphomannomutase (ManB), mannose-1-phosphate guanylytransferase (ManC), GDP-mannose 4,6-dehydratase (Gmd), GDP-4-keto-6-deoxy-d-mannose-3,5-epimerase/4-reductase (WcaG), and α-1,2-fucosyltransferase (Fuct) were co-inoculated, and the multienzyme synthetic pathway was constructed to produce fucosyloligosaccharide using d-mannose as substrate. The product, analyzed by LC/MS, fucosyloligosaccharide was formed under the catalysis of Fuct using GDP-fucose as donor substrate and lactose as acceptor substrate. Fucosyloligosaccharides reached 22 mM by a two-step fermentation compared to 3.7 mM with a one-pot fermentation.

Conclusions

Fucosyloligosaccharide was produced by a two-step fermentation to avoid the inhibitory effect of GDP-fucose on Gmd. Two-step fermentation is a rational synthetic pathway for accumulating fucosyloligosaccharide.

     

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.