Pre-administration of rats with <Emphasis Type="Italic">Helicobacter pylori</Emphasis> γ-glutamyl-transpeptidase alleviates osteoarthritis

Objective

To determine the efficacy of Helicobacter pylori γ-glutamyl-transpeptidase (GGT) in osteoarthritis (OA) therapy.

Results

Oral administration of rats with rGGT alleviated joint pain in the acute phase of iodoacetate (IA)-induced OA. The CXCL1/IL-6 in blood and in articular tissue as well as circulating granulocytes in the recipients of GGT, were reduced. This might be associated with the expansion of regulatory T cells in the inguinal lymph nodes and increased articular IL-10.

Conclusion

We provide preclinical evidence that H. pylori GGT may represent a promising candidate for OA therapy.

     

Monitoring cancer prognosis,diagnosis and treatment efficacy using metabolomics and lipidomics

Introduction

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

Objectives

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.

Methods

A literature search of the current relevant primary research was performed.

Results

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

Conclusion

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.

     

The lncRNA MEG3 downregulation leads to osteoarthritis progression via miR-16/SMAD7 axis

Background

Osteoarthritis (OA) is a chronic joint disease and there is no a definitive cure at present. Long non-coding RNAs (lncRNAs) have been confirmed to play important roles in the development of OA. However, the underlying mechanism of lncRNA maternally expressed gene 3 (MEG3) in OA has not been well elucidated.

Methods

The rat OA model and interleukin-1β (IL-1β)-induced rat chondrocytes were constructed. The expression pattern of lncRNA MEG3 and miR-16 was detected by RT-qPCR assay in cartilage tissues of rat OA model. The effect of MEG3 and miR-16 on IL-1β-induced chondrocytes was evaluated on the basis of cell viability and apoptosis. Then, the interaction among MEG3, miR-16 SMAD7 was explored by dual-luciferase reporter assay and RIP assay.

Results

It is found that lncRNA MEG3 was down-regulated and miR-16 was up-regulated in rat OA cartilage tissues. MEG3 knockdown promoted proliferation and inhibited apoptosis, while miR-16 knockdown suppressed proliferation and promoted apoptosis in IL-1β-induced rat chondrocytes. Moreover, MEG3 was involved in miR-16 pathway and MEG3 suppressed miR-16 expression. Additionally, SMAD7 was a target gene of miR-16 and miR-16 suppressed SMAD7 expression in IL-1β-induced chondrocytes. Moreover, the expression of SMAD7 induced by MEG3 or si-MEG3 was markedly reversed by the introduction of miR-16 or anti-miR-16. Furthermore, MEG3 exerted its anti-proliferation and pro-apoptosis by regulating miR-16 and SMAD7.

Conclusion

MEG3 was down-regulated and miR-16 was up-regulated in cartilage tissues of rat OA model. MEG3 knockdown might lead to the progression of OA through miR-16/SMAD7 axis.

     

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

Introduction

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

Objectives

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

Methods

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

Results

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

Conclusion

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

     

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.

     

Fungi as a source of marker compounds for the control of illicit use of drugs: mesterolone as a case study

Introduction

Anabolic steroids are frequently misused for performance enhancement during sports competitions. One of the major bottlenecks in the confident analysis of steroids and their metabolites is the non-availability/cost of standard reference compounds.

Objective

The study objective was to identify the common metabolites of prohibited anabolic steroids that are produced in both fungi and human and thus can be synthesized in bulk using fungal cultures. Mesterolone is used as a case study.

Methods

The study was conducted in three steps; we first studied the fungal transformation of mesterolone. In the second step, these metabolites were used as references to detect in human urine after the oral use of mesterolone using LC-ESI-QqQ-MS/MS. In the third step, 12 fungal cultures were screened to evaluate their potential to produce reference markers.

Results

This led to the detection of two metabolites, 6α-hydroxymesterolone (M1) and 7α-hydroxymesterolone (M2) that were found to be common in both, fungal cultures and human urine samples. Moreover, Rhizopus stolonifer and Beauveria bassiana can be considered as good candidates to produce M1 and M2 metabolites, respectively.

Conclusion

This approach can be employed for the synthesis of marker compounds of other prohibited anabolic steroids thus can be detected efficiently during national and international sports competitions.

     

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.

     

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.

     

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.

     

Stimulation of mouse vibrissal follicle growth by recombinant human fibroblast growth factor 20

Objectives

To explore potential effects of recombinant human fibroblast growth factor 20 (rhFGF20) in the growth of cultured mouse vibrissal follicles.

Results

The growth of cultured mouse vibrissal follicles was significantly induced by rhFGF20 in a dose dependent pattern in the in vitro vibrissal follicle organ culture model. However, too high concentration of rhFGF20 could inhibit the growth of vibrissal follicles. We further demonstrated that rhFGF20 stimulated the proliferation of hair matrix cells and activated Wnt/β-catenin signaling pathway.

Conclusions

The rhFGF20 might be a potential therapeutic agent to treat hair loss disorders.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Male breast cancer: thirteen years experience of a single center

Background

This retrospective study analysed the epidemiological, clinical, and therapeutic profiles of breast cancer in males.

Methods

We report our experience at the Hospital of the University of Baskent, where 20 cases of male breast cancer were observed and treated between 1995–2008.

Results

Median age at presentation was 66,7 ± 10,9 years. Average follow-up was 63 ± 18,5 months. The main presenting symptom was a mass in 65% of cases (13 patients). Ýnvasive ductal carcinoma was the most frequent pathologic type (70% of cases).

Conclusion

Male breast cancer patients have an incidence of prostate cancer higher than would be predicted in the general population. Cause of men have a higher rate of ER positivity the responses with hormonal agents are good.

     

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.

     

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.

     

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.

     

Association between HMGB1 and asthma: a literature review

Background

Recently, some studies demonstrated that HMGB1, as proinflammatory mediator belonging to the alarmin family, has a key role in different acute and chronic immune disorders. Asthma is a complex disease characterised by recurrent and reversible airflow obstruction associated to airway hyper-responsiveness and airway inflammation.

Objective

This literature review aims to analyse advances on HMGB1 role, employment and potential diagnostic application in asthma.

Methods

We reviewed experimental studies that investigated the pathogenetic role of HMGB in bronchial airway hyper-responsiveness, inflammation and the correlation between HMGB1 level and asthma.

Results

A total of 19 studies assessing the association between HMGB1 and asthma were identified.

Conclusions

What emerged from this literature review was the confirmation of HMGB-1 involvement in diseases characterised by chronic inflammation, especially in pulmonary pathologies. Findings reported suggest a potential role of the alarmin in being a stadiation method and a marker of therapeutic efficacy; finally, inhibiting HMGB1 in humans in order to contrast inflammation should be the aim for future further studies.