Metabolic Signature Profiling as a Diagnostic and Prognostic Tool in Pediatric Plasmodium falciparum Malaria

Profiling of metabolic alterations in mice infected with malaria parasites via high-resolution metabolomics

BACKGROUND

Malaria infection can result in distinct clinical outcomes from asymptomatic to severe. The association between patho-physiological changes and molecular changes in the host, and their correlation with severity of malaria progression is not fully understood.

METHODS

In this study, we addressed mass spectrometry-based temporal profiling of serum metabolite levels from mice infected with Plasmodium berhgei (strain ANKA).

RESULTS

We show global perturbations and identify changes in specific metabolites in correlation with disease progression. While metabolome-wide changes were apparent in late-stage malaria, a subset of metabolites exhibited highly correlated changes with disease progression. These metabolites changed early on following infection and either continued or maintained the change as mice developed severe disease. Some of these have the potential to be sentinel metabolites for severe malaria. Moreover, glycolytic metabolites, purine nucleotide precursors, tryptophan and its bioactive derivatives were many fold decreased in late-stage disease. Interestingly, uric acid, a metabolic waste reported to be elevated in severe human malaria, increased with disease progression, and subsequently appears to be detoxified into allantoin. This detoxification mechanism is absent in humans as they lack the enzyme uricase.

CONCLUSIONS

We have identified candidate marker metabolites that may be of relevance in the context of human malaria.

Comparative Analysis of Host Metabolic Alterations in Murine Malaria Models with Uncomplicated or Severe Malaria

Malaria varies in severity, with complications ranging from uncomplicated to severe malaria. Severe malaria could be attributed to peripheral hyperparasitemia or cerebral malaria. The metabolic interactions between the host and Plasmodium species are yet to be understood during these infections of varied pathology and severity. An untargeted metabolomics approach utilizing the liquid chromatography-mass spectrometry platform has been used to identify the affected host metabolic pathways and associated metabolites in the serum of murine malaria models with uncomplicated malaria, hyperparasitemia, and experimental cerebral malaria. We report that mice with malaria share similar metabolic attributes like higher levels of bile acids, bile pigments, and steroid hormones that have been reported for human malaria infections. Moreover, in severe malaria, upregulated levels of metabolites like phenylalanine, histidine, valine, pipecolate, ornithine, and pantothenate, with decreased levels of arginine and hippurate, were observed. Metabolites of sphingolipid metabolism were upregulated in experimental cerebral malaria. Higher levels of 20-hydroxy-leukotriene B₄ and epoxyoctadecamonoenoic acids were found in uncomplicated malaria, with lower levels observed for experimental cerebral malaria. Our study provides insights into host biology during different pathological stages of malaria disease and would be useful for the selection of animal models for evaluating diagnostic and therapeutic interventions against malaria. The raw data files are available via MetaboLights with the identifier MTBLS4387.

Metabolomic Analysis of Diverse Mice Reveals Hepatic Arginase-1 as Source of Plasma Arginase in Plasmodium chabaudi Infection

Infections disrupt host metabolism, but the factors that dictate the nature and magnitude of metabolic change are incompletely characterized. To determine how host metabolism changes in relation to disease severity in murine malaria, we performed plasma metabolomics on eight Plasmodium chabaudi-infected mouse strains with diverse disease phenotypes. We identified plasma metabolic biomarkers for both the nature and severity of different malarial pathologies. A subset of metabolic changes, including plasma arginine depletion, match the plasma metabolomes of human malaria patients, suggesting new connections between pathology and metabolism in human malaria. In our malarial mice, liver damage, which releases hepatic arginase-1 (Arg1) into circulation, correlated with plasma arginine depletion. We confirmed that hepatic Arg1 was the primary source of increased plasma arginase activity in our model, which motivates further investigation of liver damage in human malaria patients. More broadly, our approach shows how leveraging phenotypic diversity can identify and validate relationships between metabolism and the pathophysiology of infectious disease. IMPORTANCE Malaria is a severe and sometimes fatal infectious disease endemic to tropical and subtropical regions. Effective vaccines against malaria-causing Plasmodium parasites remain elusive, and malaria treatments often fail to prevent severe disease. Small molecules that target host metabolism have recently emerged as candidates for therapeutics in malaria and other diseases. However, our limited understanding of how metabolites affect pathophysiology limits our ability to develop new metabolite therapies. By providing a rich data set of metabolite-pathology correlations and by validating one of those correlations, our work is an important step toward harnessing metabolism to mitigate disease. Specifically, we showed that liver damage in P. chabaudi-infected mice releases hepatic arginase-1 into circulation, where it may deplete plasma arginine, a candidate malaria therapeutic that mitigates vascular stress. Our data suggest that liver damage may confound efforts to increase levels of arginine in human malaria patients.

Metabolomic profiling of active and inactive liver cystic echinococcosis

Cystic Echinococcosis (CE) is one of the life-threatening diseases worldwide. It is a parasitic zoonosis caused by tapeworms of the species Echinococcus granulosus sensu lato (s.l). The treatment options of CE vary from simple "watch and wait" approach to invasive treatment, based on the type and especially the nature of the cyst (active/inactive). Serological tests are inadequate to distinguish between active and inactive CE. A diagnostic reference that can determine whether the cyst is active or inactive can easily guide the treatment strategy. We aimed to test whether gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-quadropole time of flight mass spectrometry (LC-qTOF-MS) based metabolomics can establish a plasma metabolic fingerprint of CE patients and identify a diagnostic reference to discriminate active and inactive CE cysts. Metabolite concentrations were measured in plasma samples of 36 active CE patients, 17 inactive CE patients and 31 healthy controls. Multivariate statistical analysis on 232 identified metabolites obtained from two analytical platforms was performed by using principle component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) methods. The PLS-DA scores plot of the combined data set demonstrated a good separation between the groups. Compared to the healthy control group, decreased levels of squalene and increased levels of glyceric acid, 3-phosphoglycerate, glutamic acid, palmitoleic acid and oleic acid were determined in the CE patients. However, decreased levels of 3-phosphoglycerate and increased levels of 4-hydroxyphenylacetylglutamine, docosahexanoic acid were determined in active CE patients compared to the inactive CE patients. Determination of differences in metabolites may provide detailed understandings of potential metabolic process associated with active and inactive CE patients, and altered specific metabolic changes may provide some clues to obtain diagnostic reference for CE. This study has certain limitations: a. various factors affecting results of metabolomic studies such as lifestyle and dietary habits of the patients could not be fully controlled b. other infectious or malignant diseases of the liver should also be included as a positive control to evaluate the specificity of the diagnostic references.

Metabolome modulation of the host adaptive immunity in human malaria

Host responses to infection with the malaria parasite Plasmodium falciparum vary among individuals for reasons that are poorly understood. Here we reveal metabolic perturbations as a consequence of malaria infection in children and identify an immunosuppressive role of endogenous steroid production in the context of P. falciparum infection. We perform metabolomics on matched samples from children from two ethnic groups in West Africa, before and after infection with seasonal malaria. Analysing 306 global metabolomes, we identify 92 parasitaemia-associated metabolites with impact on the host adaptive immune response. Integrative metabolomic and transcriptomic analyses, and causal mediation and moderation analyses, reveal an infection-driven immunosuppressive role of parasitaemia-associated pregnenolone steroids on lymphocyte function and the expression of key immunoregulatory lymphocyte genes in the Gouin ethnic group. In children from the less malaria-susceptible Fulani ethnic group, we observe opposing responses following infection, consistent with the immunosuppressive role of endogenous steroids in malaria. These findings advance our understanding of P. falciparum pathogenesis in humans and identify potential new targets for antimalarial therapeutic interventions.

Metabolomics in infectious diseases and drug discovery

Metabolomics has emerged as an invaluable tool that can be used along with genomics, transcriptomics and proteomics to understand host-pathogen interactions at small-molecule levels. Metabolomics has been used to study a variety of infectious diseases and applications. The most common application of metabolomics is for prognostic and diagnostic purposes, specifically the screening of disease-specific biomarkers by either NMR-based or mass spectrometry-based metabolomics. In addition, metabolomics is of great significance for the discovery of druggable metabolic enzymes and/or metabolic regulators through the use of state-of-the-art flux analysis, for example, via the elucidation of metabolic mechanisms. This review discusses the application of metabolomics technologies to biomarker screening, the discovery of drug targets in infectious diseases such as viral, bacterial and parasite infections and immunometabolomics, highlights the challenges associated with accessing metabolite compartmentalization and discusses the available tools for determining local metabolite concentrations.

From Metabolite to Metabolome: Metabolomics Applications in Plasmodium Research

Advances in research over the past few decades have greatly improved metabolomics-based approaches in studying parasite biology and disease etiology. This improves the investigation of varied metabolic requirements during life stages or when following transmission to their hosts, and fulfills the demand for improved diagnostics and precise therapeutics. Therefore, this review highlights the progress of metabolomics in malaria research, including metabolic mapping of Plasmodium vertebrate life cycle stages to investigate antimalarials mode of actions and underlying complex host-parasite interactions. Also, we discuss current limitations as well as make several practical suggestions for methodological improvements which could drive metabolomics progress for malaria from a comprehensive perspective.

Joint and unique multiblock analysis of biological data - multiomics malaria study

Modern profiling technologies enable us to obtain large amounts of data which can be used later for a comprehensive understanding of the studied system. Proper evaluation of such data is challenging, and cannot be carried out by bare analysis of separate data sets. Integrated approaches are necessary, because only data integration allows us to find correlation trends common for all studied data sets and reveal hidden structures not known a priori. This improves the understanding and interpretation of complex systems. Joint and Unique MultiBlock Analysis (JUMBA) is an analysis method based on the OnPLS-algorithm that decomposes a set of matrices into joint parts containing variations shared with other connected matrices and variations that are unique for each single matrix. Mapping unique variations is important from a data integration perspective, since it certainly cannot be expected that all variation co-varies. In this work we used JUMBA for the integrated analysis of lipidomic, metabolomic and oxylipins data sets obtained from profiling of plasma samples from children infected with P. falciparum malaria. P. falciparum is one of the primary contributors to childhood mortality and obstetric complications in the developing world, which makes the development of new diagnostic and prognostic tools, as well as a better understanding of the disease, of utmost importance. In the presented work, JUMBA made it possible to detect already known trends related to the disease progression, but also to discover new structures in the data connected to food intake and personal differences in metabolism. By separating the variation in each data set into joint and unique, JUMBA reduced the complexity of the analysis and facilitated the detection of samples and variables corresponding to specific structures across multiple data sets, and by doing this enabled fast interpretation of the studied system. All of this makes JUMBA a perfect choice for multiblock analysis of systems biology data.

Mining the Human Host Metabolome Toward an Improved Understanding of Malaria Transmission

The big data movement has led to major advances in our ability to assess vast and complex datasets related to the host and parasite during malaria infection. While host and parasite genomics and transcriptomics are often the focus of many computational efforts in malaria research, metabolomics represents another big data type that has great promise for aiding our understanding of complex host-parasite interactions that lead to the transmission of malaria. Recent analyses of the complement of metabolites present in human blood, skin and breath suggest that host metabolites play a critical role in the transmission cycle of malaria. Volatile compounds released through breath and skin serve as attractants to mosquitoes, with malaria-infected hosts appearing to have unique profiles that further increase host attractiveness. Inside the host, fluctuations in the levels of certain metabolites in blood may trigger increased production of transmission-competent sexual stages (gametocytes), setting the stage for enhanced transmission of malaria from human to mosquito. Together, these recent discoveries suggest that metabolites of human blood, skin and breath play critical roles in malaria transmission. This review discusses recent advances in this area, with a focus on metabolites that have been identified to play a role in malaria transmission and methods that may lead to an improved understanding of malaria transmission.

Metabolomic-Based Methods in Diagnosis and Monitoring Infection Progression

A robust biomarker screening and validation is crucial for overcoming the current limits in the clinical management of infectious diseases. In this chapter, a general workflow for metabolomics is summarized. Subsequently, an overview of the major contributions of this omics science to the field of biomarkers of infectious diseases is discussed. Different approaches using a variety of analytical platforms can be distinguished to unveil the key metabolites for the diagnosis, prognosis, response to treatment and susceptibility for infectious diseases. To allow the implementation of such biomarkers into the clinics, the performance of large-scale studies employing solid validation criteria becomes essential. Focusing on the etiological agents and after an extensive review of the field, we present a comprehensive revision of the main metabolic biomarkers of viral, bacterial, fungal, and parasitic diseases. Finally, we discussed several articles which show the strongest validation criteria. Following these research avenues, precious clinical resources will be revealed, allowing for reduced misdiagnosis, more efficient therapies, and affordable costs, ultimately leading to a better patient management.

Distinct amino acid and lipid perturbations characterize acute versus chronic malaria

Chronic malaria is a major public health problem and significant challenge for disease eradication efforts. Despite its importance, the biological factors underpinning chronic malaria are not fully understood. Recent studies have shown that host metabolic state can influence malaria pathogenesis and transmission, but its role in chronicity is not known. Here, with the goal of identifying distinct modifications in the metabolite profiles of acute versus chronic malaria, metabolomics was performed on plasma from Plasmodium-infected humans and nonhuman primates with a range of parasitemias and clinical signs. In rhesus macaques infected with Plasmodium coatneyi, significant alterations in amines, carnitines, and lipids were detected during a high parasitemic acute phase and many of these reverted to baseline levels once a low parasitemic chronic phase was established. Plasmodium gene expression, studied in parallel in the macaques, revealed transcriptional changes in amine, fatty acid, lipid and energy metabolism genes, as well as variant antigen genes. Furthermore, a common set of amines, carnitines, and lipids distinguished acute from chronic malaria in plasma from human Plasmodium falciparum cases. In summary, distinct host-parasite metabolic environments have been uncovered that characterize acute versus chronic malaria, providing insights into the underlying host-parasite biology of malaria disease progression.

Biologically Active Ajuga Species Extracts Modulate Supportive Processes for Cancer Cell Development

Backround:Ajuga species have been used in traditional medicine for their diuretic, anti-inflammatory, wound-healing, and hepatoprotective properties.

Purpose: The phytochemical profile and anticancer potential of three Ajuga sp. (A. genevensis, A. chamaepitys, and A. laxmannii) from Romania was investigated.

Materials and Methods: The phytochemicals were extracted from the aerial parts of Ajuga sp. by using different solvents and methods. The hydroalcoholic extracts were examined for total phenolic, flavonoid and iridoid contents, and HPLC/MS was used to analyze the polyphenolic compounds and iridoids. The phytochemical profile was also evaluated by principal component analysis in connection with antitumor efficacy of extracts. The antiproliferative potential was evaluated using the ELISA BrdU-colorimetric immunoassay. Western Blot with regard to inflammatory protein NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) p65 subunit expression in cell lysates was performed. Quantification of oxidative stress marker malondialdehyde (MDA) was determined by high-performance liquid chromatography (HPLC). Enzymatic and non-enzymatic antioxidant capability was assessed by measuring catalase activity and by evaluating the total antioxidant capacity (TAC) of treated cells.

Results:Ajuga laxmannii ethanol extract showed the highest total phenolic and flavonoid content, while A. genevensis ethanol extract was more abundant in iridoids. The overall cytostatic effect of the investigated plant extracts was exerted through strong inhibitory actions on NF-κB, the key molecule involved in the inflammatory response and via oxidative stress modulatory effects in both murine colon carcinoma and melanoma cell lines.

Conclusion:Ajuga laxmannii showed the most significant antitumor activity and represents an important source of bioactive compounds, possibly an additional form of treatment alongside conventional anticancer drugs.

Insights into physiological roles of unique metabolites released from Plasmodium-infected RBCs and their potential as clinical biomarkers for malaria

Plasmodium sp. are obligate intracellular parasites that derive most of their nutrients from their host meaning the metabolic circuitry of both are intricately linked. We employed untargeted, global mass spectrometry to identify metabolites present in the culture supernatants of P. falciparum-infected red blood cells synchronized at ring, trophozoite and schizont developmental stages. This revealed a temporal regulation in release of a distinct set of metabolites compared with supernatants of non-infected red blood cells. Of the distinct metabolites we identified pipecolic acid to be abundantly present in parasite lysate, infected red blood cells and infected culture supernatant. Further, we performed targeted metabolomics to quantify pipecolic acid concentrations in both the supernatants of red blood cells infected with P. falciparum, as well as in the plasma and infected RBCs of P. berghei-infected mice. Measurable and significant hyperpipecolatemia suggest that pipecolic acid has the potential to be a diagnostic marker for malaria.

Levels of human proteins in plasma associated with acute paediatric malaria

Background

The intimate interaction between the pathophysiology of the human host and the biology of the Plasmodium falciparum parasite results in a wide spectrum of disease outcomes in malaria. Development of severe disease is associated with a progressively augmented imbalance in pro- and anti-inflammatory responses to high parasite loads and sequestration of parasitized erythrocytes. Although these phenomena collectively constitute common denominators for the wide variety of discrete severe malaria manifestations, the mechanistic rationales behind discrepancies in outcome are poorly understood. Exploration of the human pathophysiological response by variations in protein profiles in plasma presents an excellent opportunity to increase the understanding. This is ultimately required for better prediction, prevention and treatment of malaria, which is essential for ongoing elimination and eradication efforts.

Results

An affinity proteomics approach was used to analyse 541 paediatric plasma samples collected from community controls and patients with mild or severe malaria in Rwanda. Protein profiles were generated with an antibody-based suspension bead array containing 255 antibodies targetting 115 human proteins. Here, 57 proteins were identified with significantly altered levels (adjusted p-values < 0.001) in patients with malaria compared to controls. From these, the 27 most significant proteins (adjusted p-values < 10⁻¹⁴) were selected for a stringent analysis approach. Here, 24 proteins showed elevated levels in malaria patients and included proteins involved in acute inflammatory response as well as cell adhesion. The remaining three proteins, also implicated in immune regulation and cellular adhesivity, displayed lower abundance in malaria patients. In addition, 37 proteins (adjusted p-values < 0.05) were identified with increased levels in patients with severe compared to mild malaria. This set includes, proteins involved in tissue remodelling and erythrocyte membrane proteins. Collectively, this approach has been successfully used to identify proteins both with known and unknown association with different stages of malaria.

Conclusion

In this study, a high-throughput affinity proteomics approach was used to find protein profiles in plasma linked to P. falciparum infection and malaria disease progression. The proteins presented herein are mainly involved in inflammatory response, cellular adhesion and as constituents of erythrocyte membrane. These findings have a great potential to provide increased conceptual understanding of host-parasite interaction and malaria pathogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12936-018-2576-y) contains supplementary material, which is available to authorized users.

Metabolomic changes in vertebrate host during malaria disease progression

Metabolomics refers to top-down systems biological analysis of metabolites in biological specimens. Phenotypic proximity of metabolites makes them interesting candidates for studying biomarkers of environmental stressors such as parasitic infections. Moreover, the host-parasite interaction directly impinges upon metabolic pathways since the parasite uses the host metabolite pool as a biosynthetic resource. Malarial infection, although not recognized as a classic metabolic disorder, often leads to severe metabolic changes such as hypoglycemia and lactic acidosis. Thus, metabolomic analysis of the infection has become an invaluable tool for promoting a better understanding of the host-parasite interaction and for the development of novel therapeutics. In this review, we summarize the current knowledge obtained from metabolomic studies of malarial infection in rodent models and human patients. Metabolomic analysis of experimental rodent malaria has provided significant insights into the mechanisms of disease progression including utilization of host resources by the parasite, sexual dimorphism in metabolic phenotypes, and cellular changes in host metabolism. Moreover, these studies also provide proof of concept for prediction of cerebral malaria. On the other hand, metabolite analysis of patient biofluids generates extensive data that could be of use in identifying biomarkers of infection severity and in monitoring disease progression. Through the use of metabolomic datasets one hopes to assess crucial infection-specific issues such as clinical severity, drug resistance, therapeutic targets, and biomarkers. Also discussed are nascent or newly emerging areas of metabolomics such as pre-erythrocytic stages of the infection and the host immune response. This review is organized in four broad sections-methodologies for metabolomic analysis, rodent infection models, studies of human clinical specimens, and potential of immunometabolomics. Data summarized in this review should serve as a springboard for novel hypothesis testing and lead to a better understanding of malarial infection and parasite biology.

Quantification of run order effect on chromatography - mass spectrometry profiling data

Chromatographic systems coupled with mass spectrometry detection are widely used in biological studies investigating how levels of biomolecules respond to different internal and external stimuli. Such changes are normally expected to be of low magnitude and therefore all experimental factors that can influence the analysis need to be understood and minimized. Run order effect is commonly observed and constitutes a major challenge in chromatography-mass spectrometry based profiling studies that needs to be addressed before the biological evaluation of measured data is made. So far there is no established consensus, metric or method that quickly estimates the size of this effect. In this paper we demonstrate how orthogonal projections to latent structures (OPLS®) can be used for objective quantification of the run order effect in profiling studies. The quantification metric is expressed as the amount of variation in the experimental data that is correlated to the run order. One of the primary advantages with this approach is that it provides a fast way of quantifying run-order effect for all detected features, not only internal standards. Results obtained from quantification of run order effect as provided by the OPLS can be used in the evaluation of data normalization, support the optimization of analytical protocols and identification of compounds highly influenced by instrumental drift. The application of OPLS for quantification of run order is demonstrated on experimental data from plasma profiling performed on three analytical platforms: GCMS metabolomics, LCMS metabolomics and LCMS lipidomics.

Systems Biology-Based Investigation of Host-Plasmodium Interactions

Malaria is a serious, complex disease caused by parasites of the genus Plasmodium. Plasmodium parasites affect multiple tissues as they evade immune responses, replicate, sexually reproduce, and transmit between vertebrate and invertebrate hosts. The explosion of omics technologies has enabled large-scale collection of Plasmodium infection data, revealing systems-scale patterns, mechanisms of pathogenesis, and the ways that host and pathogen affect each other. Here, we provide an overview of recent efforts using systems biology approaches to study host-Plasmodium interactions and the biological themes that have emerged from these efforts. We discuss some of the challenges in using systems biology for this goal, key research efforts needed to address those issues, and promising future malaria applications of systems biology.

Integrative metabolomics and transcriptomics signatures of clinical tolerance to Plasmodium vivax reveal activation of innate cell immunity and T cell signaling

Almost invariably, humans become ill during primary infections with malaria parasites which is a pathology associated with oxidative stress and perturbations in metabolism. Importantly, repetitive exposure to Plasmodium results in asymptomatic infections, which is a condition defined as clinical tolerance. Integration of transcriptomics and metabolomics data provides a powerful way to investigate complex disease processes involving oxidative stress, energy metabolism and immune cell activation. We used metabolomics and transcriptomics to investigate the different clinical outcomes in a P. vivax controlled human malaria infection trial. At baseline, the naïve and semi-immune subjects differed in the expression of interferon related genes, neutrophil and B cell signatures that progressed with distinct kinetics after infection. Metabolomics data indicated differences in amino acid pathways and lipid metabolism between the two groups. Top pathways during the course of infection included methionine and cysteine metabolism, fatty acid metabolism and urea cycle. There is also evidence for the activation of lipoxygenase, cyclooxygenase and non-specific lipid peroxidation products in the semi-immune group. The integration of transcriptomics and metabolomics revealed concerted molecular events triggered by the infection, notably involving platelet activation, innate immunity and T cell signaling. Additional experiment confirmed that the metabolites associated with platelet activation genes were indeed enriched in the platelet metabolome.

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Plasmodium vivax infection induces significant change in blood metabolomics.

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Naïve and semi-immune subjects exhibit different molecular profiles.

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Network integration of metabolites/genes hinges on innate activation, chemokines and T cell signaling.

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Involvement of platelet activation is confirmed by platelet metabolomics.

Metabolome-wide association study of peripheral parasitemia in Plasmodium vivax malaria

BACKGROUND

Plasmodium vivax is one of the leading causes of malaria worldwide. Infections with this parasite cause diverse clinical manifestations, and recent studies revealed that infections with P. vivax can result in severe and fatal disease. Despite these facts, biological traits of the host response and parasite metabolism during P. vivax malaria are still largely underexplored. Parasitemia is clearly related to progression and severity of malaria caused by P. falciparum, however the effects of parasitemia during infections with P. vivax are not well understood.

RESULTS

We conducted an exploratory study using a high-resolution metabolomics platform that uncovered significant associations between parasitemia levels and plasma metabolites from 150 patients with P. vivax malaria. Most plasma metabolites were inversely associated with higher levels of parasitemia. Top predicted metabolites are implicated into pathways of heme and lipid metabolism, which include biliverdin, bilirubin, palmitoylcarnitine, stearoylcarnitine, phosphocholine, glycerophosphocholine, oleic acid and omega-carboxy-trinor-leukotriene B4.

CONCLUSIONS

The abundance of several plasma metabolites varies according to the levels of parasitemia in patients with P. vivax malaria. Moreover, our data suggest that the host response and/or parasite survival might be affected by metabolites involved in the degradation of heme and metabolism of several lipids. Importantly, these data highlight metabolic pathways that may serve as targets for the development of new antimalarial compounds.

The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children

BACKGROUND

Oxylipins and endocannabinoids are low molecular weight bioactive lipids that are crucial for initiation and resolution of inflammation during microbial infections. Metabolic complications in malaria are recognized contributors to severe and fatal malaria, but the impact of malaria infection on the production of small lipid derived signalling molecules is unknown. Knowledge of immunoregulatory patterns of these molecules in malaria is of great value for better understanding of the disease and improvement of treatment regimes, since the action of these classes of molecules is directly connected to the inflammatory response of the organism.

METHODS

Detection of oxylipins and endocannabinoids from plasma samples from forty children with uncomplicated and severe malaria as well as twenty controls was done after solid phase extraction followed by chromatography mass spectrometry analysis. The stable isotope dilution method was used for compound quantification. Data analysis was done with multivariate (principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA®) and univariate approaches (receiver operating characteristic (ROC) curves, t tests, correlation analysis).

RESULTS

Forty different oxylipin and thirteen endocannabinoid metabolites were detected in the studied samples, with one oxylipin (thromboxane B2, TXB2) in significantly lower levels and four endocannabinoids (OEA, PEA, DEA and EPEA) at significantly higher levels in infected individuals as compared to controls according to t test analysis with Bonferroni correction. Three oxylipins (13-HODE, 9-HODE and 13-oxo-ODE) were higher in severe compared to uncomplicated malaria cases according to the results from multivariate analysis. Observed changes in oxylipin levels can be connected to activation of cytochrome P450 (CYP) and 5-lipoxygenase (5-LOX) metabolic pathways in malaria infected individuals compared to controls, and related to increased levels of all linoleic acid oxylipins in severe patients compared to uncomplicated ones. The endocannabinoids were extremely responsive to malaria infection with majority of this class of molecules found at higher levels in infected individuals compared to controls.

CONCLUSIONS

It was possible to detect oxylipin and endocannabinoid molecules that can be potential biomarkers for differentiation between malaria infected individuals and controls and between different classes of malaria. Metabolic pathways that could be targeted towards an adjunctive therapy in the treatment of malaria were also pinpointed.

A metabolomic analytical approach permits identification of urinary biomarkers for Plasmodium falciparum infection: a case-control study

BACKGROUND

Currently available diagnostic techniques of Plasmodium falciparum infection are not optimal for non-invasive, population-based screening for malaria. It was hypothesized that a mass spectrometry-based metabolomics approach could identify urinary biomarkers of falciparum malaria.

METHODS

The study used a case-control design, with cases consisting of 21 adults in central Ethiopia with a diagnosis of P. falciparum infection confirmed with microscopy, and 25 controls of adults with negative blood smears for malaria matched on age and sex. Urinary samples were collected from these individuals during presentation at the clinic, and a second sample was collected from both cases and controls 4 weeks later, after the cases had received anti-malarial medication. The urine samples were screened for small molecule urinary biomarkers, using mass spectrometry-based metabolomics analyses followed by multivariate analysis using principal component analysis and orthogonal partial least square-discriminant analysis. The chemical identity of statistically significant malaria biomarkers was confirmed using tandem mass spectrometry.

RESULTS

The urinary metabolic profiles of cases with P. falciparum infection were distinct from healthy controls. After treatment with anti-malarial medication, the metabolomic profile of cases resembled that of healthy controls. Significantly altered levels of 29 urinary metabolites were found. Elevated levels of urinary pipecolic acid, taurine, N-acetylspermidine, N-acetylputrescine and 1,3-diacetylpropane were identified as potential biomarkers of falciparum malaria.

CONCLUSION

The urinary biomarkers of malaria identified have potential for the development of non-invasive and rapid diagnostic test of P. falciparum infection.

Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria

INTRODUCTION

Several studies have observed serum lipid changes during malaria infection in humans. All of them were focused at analysis of lipoproteins, not specific lipid molecules. The aim of our study was to identify novel patterns of lipid species in malaria infected patients using lipidomics profiling, to enhance diagnosis of malaria and to evaluate biochemical pathways activated during parasite infection.

METHODS

Using a multivariate characterization approach, 60 samples were representatively selected, 20 from each category (mild, severe and controls) of the 690 study participants between age of 0.5-6 years. Lipids from patient's plasma were extracted with chloroform/methanol mixture and subjected to lipid profiling with application of the LCMS-QTOF method.

RESULTS

We observed a structured plasma lipid response among the malaria-infected patients as compared to healthy controls, demonstrated by higher levels of a majority of plasma lipids with the exception of even-chain length lysophosphatidylcholines and triglycerides with lower mass and higher saturation of the fatty acid chains. An inverse lipid profile relationship was observed when plasma lipids were correlated to parasitaemia.

CONCLUSIONS

This study demonstrates how mapping the full physiological lipid response in plasma from malaria-infected individuals can be used to understand biochemical processes during infection. It also gives insights to how the levels of these molecules relate to acute immune responses.

Towards Improving Point-of-Care Diagnosis of Non-malaria Febrile Illness: A Metabolomics Approach

Introduction

Non-malaria febrile illnesses such as bacterial bloodstream infections (BSI) are a leading cause of disease and mortality in the tropics. However, there are no reliable, simple diagnostic tests for identifying BSI or other severe non-malaria febrile illnesses. We hypothesized that different infectious agents responsible for severe febrile illness would impact on the host metabololome in different ways, and investigated the potential of plasma metabolites for diagnosis of non-malaria febrile illness.

Methodology

We conducted a comprehensive mass-spectrometry based metabolomics analysis of the plasma of 61 children with severe febrile illness from a malaria-endemic rural African setting. Metabolite features characteristic for non-malaria febrile illness, BSI, severe anemia and poor clinical outcome were identified by receiver operating curve analysis.

Principal Findings

The plasma metabolome profile of malaria and non-malaria patients revealed fundamental differences in host response, including a differential activation of the hypothalamic-pituitary-adrenal axis. A simple corticosteroid signature was a good classifier of severe malaria and non-malaria febrile patients (AUC 0.82, 95% CI: 0.70–0.93). Patients with BSI were characterized by upregulated plasma bile metabolites; a signature of two bile metabolites was estimated to have a sensitivity of 98.1% (95% CI: 80.2–100) and a specificity of 82.9% (95% CI: 54.7–99.9) to detect BSI in children younger than 5 years. This BSI signature demonstrates that host metabolites can have a superior diagnostic sensitivity compared to pathogen-detecting tests to identify infections characterized by low pathogen load such as BSI.

Conclusions

This study demonstrates the potential use of plasma metabolites to identify causality in children with severe febrile illness in malaria-endemic settings.

In the tropics, malaria is commonly attributed to be the cause of most childhood fevers, while in fact this condition is more commonly caused by other pathogens that are clinically indistinguishable from malaria. These so-called non-malaria febrile illnesses include bacterial bloodstream infections, which are associated with a higher mortality than malaria. Most health care facilities in the tropics have malaria diagnostic tests available, but tests for non-malarial febrile illnesses are extremely limited. There is the critical need for new tests that can address the question ‘if a febrile patient is not suffering from malaria, then what is it and what treatment will be effective?’ Using metabolomics, we have comprehensively screened the biochemical profile of patients with severe febrile illness for biological markers of non-malaria febrile illness. The results show that severe malaria and non-malaria febrile illness trigger a distinct metabolic response in the host. We demonstrate that this pathophysiological difference can be exploited for differential diagnosis of severe febrile illness and identification of patients with bacterial bloodstream infections.