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.

     

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.

     

Rabbit plasma metabolomic analysis of Nitroproston®: a multi target natural prostaglandin based-drug

Introduction

Nitroproston® is a novel multi-target drug bearing natural prostaglandin E₂ (PGE₂) and nitric oxide (NO)-donating fragments for treatment of inflammatory and obstructive diseases (i.e., asthma and obstructive bronchitis).

Objectives

To investigate the effects of Nitroproston® administration on plasma metabolomics in vivo.

Methods

Experimental in vivo study randomly assigning the target drug (treatment group) or a saline solution without the drug (vehicle control group) to 12 rabbits (n?=?6 in each group). Untargeted (5880 initial features; 1869 negative–4011 positive ion peaks; UPLC–IT–TOF/MS) and 84 targeted moieties (Nitroproston® related metabolites, prostaglandins, steroids, purines, pyrimidines and amino acids; HPLC–QQQ–MS/MS) were measured from plasma at 0, 2, 4, 6, 8, 12, 18, 24, 32 and 60 min after administration.

Results

PGE₂, 13,14-dihydro-15-keto-PGE₂, PGB₂, 1,3-GDN and 15-keto-PGE₂ increased in the treatment group. Steroids (i.e., cortisone, progesterone), organic acids, 3-oxododecanoic acid, nicotinate d-ribonucleoside, thymidine, the amino acids serine and aspartate, and derivatives pyridinoline, aminoadipic acid and uric acid increased (p?<?0.05 AUCROC curve?>?0.75) after treatment. Purines (i.e., xanthine, guanine, guanosine), bile acids, acylcarnitines and the amino acids l-tryptophan and l-phenylalanine were decreased. Nitroproston® impacted steroidogenesis, purine metabolism and ammonia recycling pathways, among others.

Conclusion

Nitroproston®, a multi action novel drug based on natural prostaglandins, altered metabolites (i.e., guanine, adenine, cortisol, cortisone and aspartate) involved in purine metabolism, urea and ammonia biological cycles, steroidogenesis, among other pathways. Suggested mechanisms of action, metabolic pathway interconnections and useful information to further understand the metabolic effects of prostaglandin administration are presented.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

Urinary metabolite markers characterizing tuberculosis treatment failure

Background

Considering that approximately 15% of the nine million new tuberculosis (TB) cases reported per annum are not treated successfully, new, distinctive and specific biomarkers are needed to better characterize the biological basis of a poor treatment outcome.

Methods

Urine samples from 41 active pulmonary TB patients were collected at baseline (time of diagnosis), during treatment (weeks 1, 2 and 4) and 2 weeks after treatment completion (week 26). These samples were divided into successful (cured) and unsuccessful (failed) treatment outcome groups and analyzed using a GCxGC-TOFMS metabolomics research approach.

Results

The metabolite data collected showed clear differentiation of the cured and failed treatment outcome groups using the samples collected at the time of diagnosis, i.e. before any treatment was administered.

Conclusions

The treatment failure group was characterized by an imbalanced gut microbiome, in addition to elevated levels of metabolites associated with abnormalities in the long-chain fatty acid β-oxidation pathway, accompanied by reduced l-carnitine and short-chain fatty acids, indicative of a mitochondrial trifunctional protein defect in particular. Furthermore, an altered amino acid metabolism was also observed in these patients, which confirms previous findings and associations to increased interferon gamma due to the host’s immune response to M. tuberculosis and a compromised insulin secretion.

     

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.

     

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.

     

Change of the <Emphasis Type="Italic">N</Emphasis>-terminal codon bias combined with tRNA supplementation outperforms the selected fusion tags for production of human <Emphasis Type="SmallCaps">d</Emphasis>-amino acid oxidase as active inclusion bodies

Objectives

To optimize the production of active inclusion bodies (IBs) containing human d-amino acid oxidase (hDAAO) in Escherichia coli.

Results

The optimized initial codon region combined with the coexpressed rare tRNAs, fusion of each of the N-terminal partners including cellulose-binding module, thioredoxin, glutathione S-transferase and expressivity tag, deletion of the incorporated linker, and improvement of tRNA abundance affected the production and activity for oxidizing d-alanine of the hDAAO in IBs. Compared with the optimized fusion constructs and expression host, IBs yields and activity were increased to 2.6- and 2.8-fold respectively by changing the N-terminal codon bias of the hDAAO. The insoluble hDAAO codon variant displayed the same substrate specificity as the soluble one for oxidizing d-alanine, d-serine and d-aspartic acid. The freshly prepared hDAAO codon variant was used for analyzing the l-serine racemization activity of the bacterially expressed maize serine racemase.

Conclusions

Optimization of the N-terminal codon bias combined with the coexpression of rare tRNAs is a novel and efficient approach to produce active IBs of the hDAAO.

     

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.