In vitro anti-malarial interaction and gametocytocidal activity of cryptolepine

Background

Discovery of novel gametocytocidal molecules is a major pharmacological strategy in the elimination and eradication of malaria. The high patronage of the aqueous root extract of the popular West African anti-malarial plant Cryptolepis sanguinolenta (Periplocaceae) in traditional and hospital settings in Ghana has directed this study investigating the gametocytocidal activity of the plant and its major alkaloid, cryptolepine. This study also investigates the anti-malarial interaction of cryptolepine with standard anti-malarials, as the search for new anti-malarial combinations continues.

Methods

The resazurin-based assay was employed in evaluating the gametocytocidal properties of C. sanguinolenta and cryptolepine against the late stage (IV/V) gametocytes of Plasmodium falciparum (NF54). A fixed ratio method based on the SYBR Green I fluorescence-based assay was used to build isobolograms from a combination of cryptolepine with four standard anti-malarial drugs in vitro using the chloroquine sensitive strain 3D7.

Results

Cryptolepis sanguinolenta (IC₅₀ = 49.65 nM) and its major alkaloid, cryptolepine (IC₅₀ = 1965 nM), showed high inhibitory activity against the late stage gametocytes of P. falciparum (NF54). In the interaction assays in asexual stage, cryptolepine showed an additive effect with both lumefantrine and chloroquine with mean ΣFIC₅₀s of 1.017 ± 0.06 and 1.465 ± 0.17, respectively. Cryptolepine combination with amodiaquine at therapeutically relevant concentration ratios showed a synergistic effect (mean ΣFIC₅₀ = 0.287 ± 0.10) whereas an antagonistic activity (mean ΣFIC₅₀ = 4.182 ± 0.99) was seen with mefloquine.

Conclusions

The findings of this study shed light on the high gametocytocidal properties of C. sanguinolenta and cryptolepine attributing their potent anti-malarial activity mainly to their effect on both the sexual and asexual stages of the parasite. Amodiaquine is a potential drug partner for cryptolepine in the development of novel fixed dose combinations.

     

TarMet: a reactive GUI tool for efficient and confident quantification of MS based targeted metabolic and stable isotope tracer analysis

Introduction

Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately.

Objectives

TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface.

Methods

TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically.

Results

TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well.

Conclusion

TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.

     

Functional analysis of <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> subpopulations associated with artemisinin resistance in Cambodia

Background

Plasmodium falciparum malaria is one of the most widespread parasitic infections in humans and remains a leading global health concern. Malaria elimination efforts are threatened by the emergence and spread of resistance to artemisinin-based combination therapy, the first-line treatment of malaria. Promising molecular markers and pathways associated with artemisinin drug resistance have been identified, but the underlying molecular mechanisms of resistance remains unknown. The genomic data from early period of emergence of artemisinin resistance (2008–2011) was evaluated, with aim to define k13 associated genetic background in Cambodia, the country identified as epicentre of anti-malarial drug resistance, through characterization of 167 parasite isolates using a panel of 21,257 SNPs.

Results

Eight subpopulations were identified suggesting a process of acquisition of artemisinin resistance consistent with an emergence-selection-diffusion model, supported by the shifting balance theory. Identification of population specific mutations facilitated the characterization of a core set of 57 background genes associated with artemisinin resistance and associated pathways. The analysis indicates that the background of artemisinin resistance was not acquired after drug pressure, rather is the result of fixation followed by selection on the daughter subpopulations derived from the ancestral population.

Conclusions

Functional analysis of artemisinin resistance subpopulations illustrates the strong interplay between ubiquitination and cell division or differentiation in artemisinin resistant parasites. The relationship of these pathways with the P. falciparum resistant subpopulation and presence of drug resistance markers in addition to k13, highlights the major role of admixed parasite population in the diffusion of artemisinin resistant background. The diffusion of resistant genes in the Cambodian admixed population after selection resulted from mating of gametocytes of sensitive and resistant parasite populations.

     

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.

     

Impaired mitochondrial calcium uptake caused by tacrolimus underlies beta-cell failure

Background

One of the most common side effects of the immunosuppressive drug tacrolimus (FK506) is the increased risk of new-onset diabetes mellitus. However, the molecular mechanisms underlying this association have not been fully clarified.

Methods

We studied the effects of the therapeutic dose of tacrolimus on mitochondrial fitness in beta-cells.

Results

We demonstrate that tacrolimus impairs glucose-stimulated insulin secretion (GSIS) in beta-cells through a previously unidentified mechanism. Indeed, tacrolimus causes a decrease in mitochondrial Ca²⁺ uptake, accompanied by altered mitochondrial respiration and reduced ATP production, eventually leading to impaired GSIS.

Conclusion

Our observations individuate a new fundamental mechanism responsible for the augmented incidence of diabetes following tacrolimus treatment. Indeed, this drug alters Ca²⁺ fluxes in mitochondria, thereby compromising metabolism-secretion coupling in beta-cells.

     

New insights into the mechanistic action of methyldehydrodieugenol B towards <Emphasis Type="Italic">Leishmania</Emphasis> (L.) <Emphasis Type="Italic">infantum</Emphasis> via a multiplatform based untargeted metabolomics approach

Introduction

Leishmaniasis is a parasitic neglected disease affecting millions of people worldwide. Clinical practice resorts to long and costly treatments with a therapeutic arsenal limited to highly toxic drugs, often associated to adverse side effects. Additionally, resistant strains are reported to be increasing.

Aim

In this work, the mechanistic action of a drug candidate (methydehydrodieugenol B), isolated from twigs of Nectandra leucantha, towards Leishmania infantum was studied by a global metabolomics approach using GC-MS and RPLC-MS platforms.

Method

L. infantum promastigotes were grown in culture medium for 72 h and treated with methydehydrodieugenol B at 58.18 μg.mL-1 concentration; after 48 h treatment, enzyme activity was quenched, cells washed and frozen until analysis. For GC-MS analysis (Fiehn’s method), 1:1 methanol:water extracts were prepared and derivatized with O-methoxyamine in pyridine at room temperature for 90 min, followed by silylation with BSTFA/1% TMCS at 40 °C for 30 min. Pure methanolic extracts were also prepared and analyzed directly by RPLC-MS with a acetonitrile/water mobile phase acidulated with formic acid and gradient elution.

Result

Several amino acids, fatty acids, carbohydrates, and glycerolipids were found as discriminant metabolites, mostly decreased in treated samples. Due to the complexity of the parasite metabolism and the great diversity of altered metabolites, a multi-target mechanism was assigned to the drug candidate, where changes in the cell energy sources and in the lipid composition of the parasite plasma membrane were prominent.

Conclusion

These results contributed to elucidate the broad action of methyldehydrodieugenol B against Leishmania, paving the way in the search of novel alternative therapies.

     

Predicting adverse drug reactions through interpretable deep learning framework

Background

Adverse drug reactions (ADRs) are unintended and harmful reactions caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the drug development pipeline can help to enhance drug safety and reduce financial costs.

Methods

In this paper, we developed machine learning models including a deep learning framework which can simultaneously predict ADRs and identify the molecular substructures associated with those ADRs without defining the substructures a-priori.

Results

We evaluated the performance of our model with ten different state-of-the-art fingerprint models and found that neural fingerprints from the deep learning model outperformed all other methods in predicting ADRs. Via feature analysis on drug structures, we identified important molecular substructures that are associated with specific ADRs and assessed their associations via statistical analysis.

Conclusions

The deep learning model with feature analysis, substructure identification, and statistical assessment provides a promising solution for identifying risky components within molecular structures and can potentially help to improve drug safety evaluation.

     

Identification of <Emphasis Type="Italic">O</Emphasis>-GlcNAcylated proteins in <Emphasis Type="Italic">Plasmodium falciparum</Emphasis>

Background

Post-translational modifications (PTMs) constitute a huge group of chemical modifications increasing the complexity of the proteomes of living beings. PTMs have been discussed as potential anti-malarial drug targets due to their involvement in many cell processes. O-GlcNAcylation is a widespread PTM found in different organisms including Plasmodium falciparum. The aim of this study was to identify O-GlcNAcylated proteins of P. falciparum, to learn more about the modification process and to understand its eventual functions in the Apicomplexans.

Methods

The P. falciparum strain 3D7 was amplified in erythrocytes and purified. The proteome was checked for O-GlcNAcylation using different methods. The level of UDP-GlcNAc, the donor of the sugar moiety for O-GlcNAcylation processes, was measured using high-pH anion exchange chromatography. O-GlcNAcylated proteins were enriched and purified utilizing either click chemistry labelling or adsorption on succinyl-wheat germ agglutinin beads. Proteins were then identified by mass-spectrometry (nano-LC MS/MS).

Results

While low when compared to MRC5 control cells, P. falciparum disposes of its own pool of UDP-GlcNAc. By using proteomics methods, 13 O-GlcNAcylated proteins were unambiguously identified (11 by click-chemistry and 6 by sWGA-beads enrichment; 4 being identified by the 2 approaches) in late trophozoites. These proteins are all part of pathways, functions and structures important for the parasite survival. By probing clicked-proteins with specific antibodies, Hsp70 and α-tubulin were identified as P. falciparum O-GlcNAc-bearing proteins.

Conclusions

This study is the first report on the identity of P. falciparum O-GlcNAcylated proteins. While the parasite O-GlcNAcome seems close to those of other species, the structural differences exhibited by the proteomes provides a glimpse of innovative therapeutic paths to fight malaria. Blocking biosynthesis of UDP-GlcNAc in the parasites is another promising option to reduce Plasmodium life cycle.

     

Phosphodiesterase 4 inhibitors and drugs of abuse: current knowledge and therapeutic opportunities

Background

Long-term exposure to drugs of abuse causes an upregulation of the cAMP-signaling pathway in the nucleus accumbens and other forebrain regions, this common neuroadaptation is thought to underlie aspects of drug tolerance and dependence. Phosphodiesterase 4 (PDE4) is an enzyme that the selective hydrolyzes intracellular cAMP. It is expressed in several brain regions that regulate the reinforcing effects of drugs of abuse.

Objective

Here, we review the current knowledge about central nervous system (CNS) distribution of PDE4 isoforms and the effects of systemic and brain-region specific inhibition of PDE4 on behavioral models of drug addiction.

Methods

A systematic literature search was performed using the Pubmed.

Results

Using behavioral sensitization, conditioned place preference and drug self-administration as behavioral models, a large number of studies have shown that local or systemic administration of PDE4 inhibitors reduce drug intake and/or drug seeking for psychostimulants, alcohol, and opioids in rats or mice.

Conclusions

Preclinical studies suggest that PDE4 could be a therapeutic target for several classes of substance use disorder. We conclude by identifying opportunities for the development of subtype-selective PDE4 inhibitors that may reduce addiction liability and minimize the side effects that limit the clinical potential of non-selective PDE4 inhibitors. Several PDE4 inhibitors have been clinically approved for other diseases. There is a promising possibility to repurpose these PDE4 inhibitors for the treatment of drug addiction as they are safe and well-tolerated in patients.

     

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.

     

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.

     

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.

     

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.

     

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.

     

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.