Modulating the catalytic activity of AMPK has neuroprotective effects against α-synuclein toxicity

Background

Metabolic perturbations and slower renewal of cellular components associated with aging increase the risk of Parkinson’s disease (PD). Declining activity of AMPK, a critical cellular energy sensor, may therefore contribute to neurodegeneration.

Methods

Here, we overexpress various genetic variants of the catalytic AMPKα subunit to determine how AMPK activity affects the survival and function of neurons overexpressing human α-synuclein in vivo.

Results

Both AMPKα1 and α2 subunits have neuroprotective effects against human α-synuclein toxicity in nigral dopaminergic neurons. Remarkably, a modified variant of AMPKα1 (T172Dα1) with constitutive low activity most effectively prevents the loss of dopamine neurons, as well as the motor impairments caused by α-synuclein accumulation. In the striatum, T172Dα1 decreases the formation of dystrophic axons, which contain aggregated α-synuclein. In primary cortical neurons, overexpression of human α-synuclein perturbs mitochondrial and lysosomal activities. Co-expressing AMPKα with α-synuclein induces compensatory changes, which limit the accumulation of lysosomal material and increase the mitochondrial mass.

Conclusions

Together, these results indicate that modulating AMPK activity can mitigate α-synuclein toxicity in nigral dopamine neurons, which may have implications for the development of neuroprotective treatments against PD.

     

α-synuclein interacts with SOD1 and promotes its oligomerization

Background

Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS) are both neurodegenerative diseases leading to impaired execution of movement. α-Synuclein plays a central role in the pathogenesis of PD whereas Cu, Zn superoxide dismutase (SOD1) is a key player in a subset of familial ALS cases. Under pathological conditions both α-synuclein and SOD1 form oligomers and fibrils. In this study we investigated the possible molecular interaction of α-synuclein and SOD1 and its functional and pathological relevance.

Results

Using a protein-fragment complementation approach and co-IP, we found that α-synuclein and SOD1 physically interact in living cells, human erythrocytes and mouse brain tissue. Additionally, our data show that disease related mutations in α-synuclein (A30P, A53T) and SOD1 (G85R, G93A) modify the binding of α-synuclein to SOD1. Notably, α-synuclein accelerates SOD1 oligomerization independent of SOD1 activity.

Conclusion

This study provides evidence for a novel interaction of α-synuclein and SOD1 that might be relevant for neurodegenerative diseases.

     

Role of cytochrome <Emphasis Type="Italic">c</Emphasis> in α-synuclein radical formation: implications of α-synuclein in neuronal death in Maneb- and paraquat-induced model of Parkinson’s disease

Background

The pathological features of Parkinson’s disease (PD) include an abnormal accumulation of α-synuclein in the surviving dopaminergic neurons. Though PD is multifactorial, several epidemiological reports show an increased incidence of PD with co-exposure to pesticides such as Maneb and paraquat (MP). In pesticide-related PD, mitochondrial dysfunction and α-synuclein oligomers have been strongly implicated, but the link between the two has not yet been understood. Similarly, the biological effects of α-synuclein or its radical chemistry in PD is largely unknown. Mitochondrial dysfunction during PD pathogenesis leads to release of cytochrome c in the cytosol. Once in the cytosol, cytochrome c has one of two fates: It either binds to apaf1 and initiates apoptosis or can act as a peroxidase. We hypothesized that as a peroxidase, cytochrome c leaked out from mitochondria can form radicals on α-synuclein and initiate its oligomerization.

Method

Samples from controls, and MP co-exposed wild-type and α-synuclein knockout mice were studied using immuno-spin trapping, confocal microscopy, immunohistochemistry, and microarray experiments.

Results

Experiments with MP co-exposed mice showed cytochrome c release in cytosol and its co-localization with α-synuclein. Subsequently, we used immuno-spin trapping method to detect the formation of α-synuclein radical in samples from an in vitro reaction mixture consisting of cytochrome c, α-synuclein, and hydrogen peroxide. These experiments indicated that cytochrome c plays a role in α-synuclein radical formation and oligomerization. Experiments with MP co-exposed α-synuclein knockout mice, in which cytochrome c-α synuclein co-localization and interaction cannot occur, mice showed diminished protein radical formation and neuronal death, compared to wild-type MP co-exposed mice. Microarray data from MP co-exposed wild-type and α-synuclein knockout mice further showed that the absence of α-synuclein per se or its co-localization with cytochrome c confers protection from MP co-exposure, as several important pathways were unaffected in α-synuclein knockout mice.

Conclusions

Altogether, these results show that peroxidase activity of cytochrome c contributes to α-synuclein radical formation and oligomerization, and that α-synuclein, through its co-localization with cytochrome c or on its own, affects several biological pathways which contribute to increased neuronal death in an MP-induced model of PD.

     

The alpha-1A adrenergic receptor agonist A61603 reduces cardiac polyunsaturated fatty acid and endocannabinoid metabolites associated with inflammation in vivo

Introduction

Alpha-1-adrenergic receptors (α1-ARs) are G-protein coupled receptors (GPCRs) with three highly homologous subtypes (α1A, α1B, and α1D). Of these three subtypes, only the α1A and α1B are expressed in the heart. Multiple pre-clinical models of heart injury demonstrate cardioprotective roles for the α1A. Non-selective α1-AR activation promotes glycolysis in the heart, but the functional α1-AR subtype and broader metabolic effects have not been studied.

Objectives

Given the high metabolic demands of the heart and previous evidence indicating benefit from α1A activation, we chose to investigate the effects of α1A activation on the cardiac metabolome in vivo.

Methods

Mice were treated for 1 week with a low, subpressor dose of A61603, a highly selective and potent α1A agonist. Cardiac tissue and serum were analyzed using a non-targeted metabolomics approach.

Results

We identified previously unrecognized metabolic responses to α1A activation, most notably broad reduction in the abundance of polyunsaturated fatty acids (PUFAs) and endocannabinoids (ECs).

Conclusion

Given the well characterized roles of PUFAs and ECs in inflammatory pathways, these findings suggest a possible role for cardiac α1A-ARs in the regulation of inflammation and may offer novel insight into the mechanisms underlying the cardioprotective benefit of selective pharmacologic α1A activation.

     

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.

     

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.

     

Loss of parkin promotes lipid rafts-dependent endocytosis through accumulating caveolin-1: implications for Parkinson’s disease

Background

Parkinson’s disease (PD) is characterized by progressive loss of midbrain dopaminergic neurons, resulting in motor dysfunctions. While most PD is sporadic in nature, a significant subset can be linked to either autosomal dominant or recessive mutations. PARK2, encoding the E3 ubiquitin ligase, parkin, is the most frequently mutated gene in autosomal recessive early onset PD. It has recently been reported that PD-associated gene products such as PINK1, α-synuclein, LRRK2, and DJ-1, as well as parkin associate with lipid rafts, suggesting that the dysfunction of these proteins in lipid rafts may be a causal factor of PD. Therefore here, we examined the relationship between lipid rafts-related proteins and parkin.

Results

We identified caveolin-1 (cav-1), which is one of the major constituents of lipid rafts at the plasma membrane, as a substrate of parkin. Loss of parkin function was found to disrupt the ubiquitination and degradation of cav-1, resulting in elevated cav-1 protein level in cells. Moreover, the total cholesterol level and membrane fluidity was altered by parkin deficiency, causing dysregulation of lipid rafts-dependent endocytosis. Further, cell-to-cell transmission of α-synuclein was facilitated by parkin deficiency.

Conclusions

Our results demonstrate that alterations in lipid rafts by the loss of parkin via cav-1 may be a causal factor of PD, and cav-1 may be a novel therapeutic target for PD.

     

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.

     

A cold-adapted and glucose-stimulated type II α-glucosidase from a deep-sea bacterium <Emphasis Type="Italic">Pseudoalteromonas</Emphasis> sp. K8

Objectives

To express and characterize a putative α-glucosidase, Pagl, from Pseudoalteromonas sp. K8 obtained via genome mining approach.

Results

Pagl was expressed and purified to homogeneity, with a molecular mass of 60 kDa. It was optimally active at pH 8.5 and 30 °C, and showed cold-adapted activity. Pagl exhibited specific activity towards substrates with α-1,4-linkage, with the highest specific activity of 19.4 U/mg for maltose, followed by pNPαG and maltodextrins, suggesting that Pagl belongs to the type II α-glucosidase. Interestingly, the activity of Pagl is significantly enhanced (2.7 times) in the presence of 200 mM glucose.

Conclusion

The unique catalytic properties of Pagl make it an attractive candidate for several industrial applications.

     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.

     

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.

     

The altered human serum metabolome induced by a marathon

Introduction

Endurance races have been associated with a substantial amount of adverse effects which could lead to chronic disease and long-term performance impairment. However, little is known about the holistic metabolic changes occurring within the serum metabolome of athletes after the completion of a marathon.

Objectives

Considering this, the aim of this study was to better characterize the acute metabolic changes induced by a marathon.

Methods

Using an untargeted two dimensional gas chromatography time-of-flight mass spectrometry metabolomics approach, pre- and post-marathon serum samples of 31 athletes were analyzed and compared to identify those metabolites varying the most after the marathon perturbation.

Results

Principle component analysis of the comparative groups indicated natural differentiation due to variation in the total metabolite profiles. Elevated concentrations of carbohydrates, fatty acids, tricarboxylic acid cycle intermediates, ketones and reduced concentrations of amino acids indicated a metabolic shift between various fuel substrate systems. Additionally, elevated odd-chain fatty acids and α-hydroxy acids indicated the utilization of α-oxidation and autophagy as alternative energy-producing mechanisms. Adaptations in gut microbe-associated markers were also observed and correlated with the metabolic flexibility of the athlete.

Conclusion

From these results it is evident that a marathon places immense strain on the energy-producing pathways of the athlete, leading to extensive protein degradation, oxidative stress, mammalian target of rapamycin complex 1 inhibition and autophagy. A better understanding of this metabolic shift could provide new insights for optimizing athletic performance, developing more efficient nutrition regimens and identify strategies to improve recovery.

     

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.

     

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.

     

Safety and pharmacodynamic effects of a pharmacological chaperone on α-galactosidase A activity and globotriaosylceramide clearance in Fabry disease: report from two phase 2 clinical studies

Background

Fabry disease (FD) is a genetic disorder resulting from deficiency of the lysosomal enzyme α-galactosidase A (α-Gal A), which leads to globotriaosylceramide (GL-3) accumulation in multiple tissues. We report on the safety and pharmacodynamics of migalastat hydrochloride, an investigational pharmacological chaperone given orally at 150 mg every-other-day.

Methods

Two open-label uncontrolled phase 2 studies of 12 and 24 weeks (NCT00283959 and NCT00283933) in 9 males with FD were combined. At multiple time points, α-Gal A activity and GL-3 levels were quantified in blood cells, kidney and skin. GL-3 levels were also evaluated through skin and renal histology.

Results

Compared to baseline, increased α-Gal A activity of at least 50% was demonstrated in blood, skin and kidney in 6 of 9 patients. Patients’ increased α-Gal A activities paralleled the α-Gal A increases observed in vitro in HEK-293 cells transfected with the corresponding mutant form of the enzyme. The same 6 patients who demonstrated increases of α-Gal A activity also had GL-3 reduction in skin, urine and/or kidney, and had α-Gal A mutations that responded in transfected cells incubated with the drug. The 3 patients who did not show a consistent response in vivo had α-Gal A mutations that did not respond to migalastat HCl in transfected cells. Migalastat HCl was well tolerated.

Conclusions

Migalastat HCl is a candidate pharmacological chaperone that provides a novel genotype-specific treatment for FD. It enhanced α-Gal A activity and resulted in GL-3 substrate decrease in patients with responsive GLA mutations. Phase 3 studies are ongoing.

Trial registration

Clinicaltrial.gov: NCT00283959 and NCT00283933

     

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.