Chewing the fat on natural killer T cell development

Natural killer T cells (NKT cells) are selected in the thymus by self-glycolipid antigens presented by CD1d molecules. It is currently thought that one specific component of the lysosomal processing pathway, which leads to the production of isoglobotrihexosylceramide (iGb3), is essential for normal NKT cell development. New evidence now shows that NKT cell development can be disrupted by a diverse range of mutations that interfere with different elements of the lysosomal processing and degradation of glycolipids. This suggests that lysosomal storage diseases (LSDs) in general, rather than one specific defect, can disrupt CD1d antigen presentation, leading to impaired development of NKT cells

Systems Biology: The Next Frontier for Bioinformatics

Biochemical systems biology augments more traditional disciplines, such as genomics, biochemistry and molecular biology, by championing (i) mathematical and computational modeling; (ii) the application of traditional engineering practices in the analysis of biochemical systems; and in the past decade increasingly (iii) the use of near-comprehensive data sets derived from ‘omics platform technologies, in particular “downstream” technologies relative to genome sequencing, including transcriptomics, proteomics and metabolomics. The future progress in understanding biological principles will increasingly depend on the development of temporal and spatial analytical techniques that will provide high-resolution data for systems analyses. To date, particularly successful were strategies involving (a) quantitative measurements of cellular components at the mRNA, protein and metabolite levels, as well as in vivo metabolic reaction rates, (b) development of mathematical models that integrate biochemical knowledge with the information generated by high-throughput experiments, and (c) applications to microbial organisms. The inevitable role bioinformatics plays in modern systems biology puts mathematical and computational sciences as an equal partner to analytical and experimental biology. Furthermore, mathematical and computational models are expected to become increasingly prevalent representations of our knowledge about specific biochemical systems

Host reticulocytes provide metabolic reservoirs that can be exploited by malaria parasites

Human malaria parasites proliferate in different erythroid cell types during infection. Whilst Plasmodium vivax exhibits a strong preference for immature reticulocytes, the more pathogenic P. falciparum primarily infects mature erythrocytes. In order to assess if these two cell types offer different growth conditions and relate them to parasite preference, we compared the metabolomes of human and rodent reticulocytes with those of their mature erythrocyte counterparts. Reticulocytes were found to have a more complex, enriched metabolic profile than mature erythrocytes and a higher level of metabolic overlap between reticulocyte resident parasite stages and their host cell. This redundancy was assessed by generating a panel of mutants of the rodent malaria parasite P. berghei with defects in intermediary carbon metabolism (ICM) and pyrimidine biosynthesis known to be important for P. falciparum growth and survival in vitro in mature erythrocytes. P. berghei ICM mutants (pbpepc-, phosphoenolpyruvate carboxylase and pbmdh-, malate dehydrogenase) multiplied in reticulocytes and committed to sexual development like wild type parasites. However, P. berghei pyrimidine biosynthesis mutants (pboprt-, orotate phosphoribosyltransferase and pbompdc-, orotidine 5′-monophosphate decarboxylase) were restricted to growth in the youngest forms of reticulocytes and had a severe slow growth phenotype in part resulting from reduced merozoite production. The pbpepc-, pboprt- and pbompdc- mutants retained virulence in mice implying that malaria parasites can partially salvage pyrimidines but failed to complete differentiation to various stages in mosquitoes. These findings suggest that species-specific differences in Plasmodium host cell tropism result in marked differences in the necessity for parasite intrinsic metabolism. These data have implications for drug design when targeting mature erythrocyte or reticulocyte resident parasites

BCKDH: the missing link in apicomplexan mitochondrial metabolism is required for full virulence of Toxoplasma gondii and Plasmodium berghei

While the apicomplexan parasites Plasmodium falciparum and Toxoplasma gondii are thought to primarily depend on glycolysis for ATP synthesis, recent studies have shown that they can fully catabolize glucose in a canonical TCA cycle. However, these parasites lack a mitochondrial isoform of pyruvate dehydrogenase and the identity of the enzyme that catalyses the conversion of pyruvate to acetyl-CoA remains enigmatic. Here we demonstrate that the mitochondrial branched chain ketoacid dehydrogenase (BCKDH) complex is the missing link, functionally replacing mitochondrial PDH in both T. gondii and P. berghei. Deletion of the E1a subunit of T. gondii and P. berghei BCKDH significantly impacted on intracellular growth and virulence of both parasites. Interestingly, disruption of the P. berghei E1a restricted parasite development to reticulocytes only and completely prevented maturation of oocysts during mosquito transmission. Overall this study highlights the importance of the molecular adaptation of BCKDH in this important class of pathogens

A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments

<p>Abstract</p> <p>Background</p> <p>Gas chromatography-mass spectrometry (GC-MS) is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies.</p> <p>Results</p> <p>A new approach for matching signal peaks based on dynamic programming is presented. The proposed approach relies on both peak retention times and mass spectra. The alignment of more than two peak lists involves three steps: (1) all possible pairs of peak lists are aligned, and similarity of each pair of peak lists is estimated; (2) the guide tree is built based on the similarity between the peak lists; (3) peak lists are progressively aligned starting with the two most similar peak lists, following the guide tree until all peak lists are exhausted. When two or more experiments are performed on different sample states and each consisting of multiple replicates, peak lists within each set of replicate experiments are aligned first (within-state alignment), and subsequently the resulting alignments are aligned themselves (between-state alignment). When more than two sets of replicate experiments are present, the between-state alignment also employs the guide tree. We demonstrate the usefulness of this approach on GC-MS metabolic profiling experiments acquired on wild-type and mutant <it>Leishmania mexicana </it>parasites.</p> <p>Conclusion</p> <p>We propose a progressive method to match signal peaks across multiple GC-MS experiments based on dynamic programming. A sensitive peak similarity function is proposed to balance peak retention time and peak mass spectra similarities. This approach can produce the optimal alignment between an arbitrary number of peak lists, and models explicitly within-state and between-state peak alignment. The accuracy of the proposed method was close to the accuracy of manually-curated peak matching, which required tens of man-hours for the analyzed data sets. The proposed approach may offer significant advantages for processing of high-throughput metabolomics data, especially when large numbers of experimental replicates and multiple sample states are analyzed.</p

Non-canonical metabolic pathways in the malaria parasite detected by isotope-tracing metabolomics

The malaria parasite, Plasmodium falciparum, proliferates rapidly in human erythrocytes by actively scavenging multiple carbon sources and essential nutrients from its host cell. However, a global overview of the metabolic capacity of intraerythrocytic stages is missing. Using multiple

Mitochondrial metabolism of sexual and asexual blood stages of the malaria parasite Plasmodium falciparum

BACKGROUND: The carbon metabolism of the blood stages of Plasmodium falciparum, comprising rapidly dividing asexual stages and non-dividing gametocytes, is thought to be highly streamlined, with glycolysis providing most of the cellular ATP. However, these parasitic stages express all the enzymes needed for a canonical mitochondrial tricarboxylic acid (TCA) cycle, and it was recently proposed that they may catabolize glutamine via an atypical branched TCA cycle. Whether these stages catabolize glucose in the TCA cycle and what is the functional significance of mitochondrial metabolism remains unresolved. RESULTS: We reassessed the central carbon metabolism of P. falciparum asexual and sexual blood stages, by metabolically labeling each stage with (13)C-glucose and (13)C-glutamine, and analyzing isotopic enrichment in key pathways using mass spectrometry. In contrast to previous findings, we found that carbon skeletons derived from both glucose and glutamine are catabolized in a canonical oxidative TCA cycle in both the asexual and sexual blood stages. Flux of glucose carbon skeletons into the TCA cycle is low in the asexual blood stages, with glutamine providing most of the carbon skeletons, but increases dramatically in the gametocyte stages. Increased glucose catabolism in the gametocyte TCA cycle was associated with increased glucose uptake, suggesting that the energy requirements of this stage are high. Significantly, whereas chemical inhibition of the TCA cycle had little effect on the growth or viability of asexual stages, inhibition of the gametocyte TCA cycle led to arrested development and death. CONCLUSIONS: Our metabolomics approach has allowed us to revise current models of P. falciparum carbon metabolism. In particular, we found that both asexual and sexual blood stages utilize a conventional TCA cycle to catabolize glucose and glutamine. Gametocyte differentiation is associated with a programmed remodeling of central carbon metabolism that may be required for parasite survival either before or after uptake by the mosquito vector. The increased sensitivity of gametocyte stages to TCA-cycle inhibitors provides a potential target for transmission-blocking drugs

Accurate detection of acute sleep deprivation using a metabolomic biomarker—A machine learning approach

Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography–mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through “fitness for duty” or “post-accident analysis” assessments

Metabolomics and lipidomics reveal perturbation of sphingolipid metabolism by a novel anti-trypanosomal 3-(oxazolo[4,5-b]pyridine-2-yl)anilide

Introduction: Trypanosoma brucei is the causative agent of human African trypanosomiasis, which is responsible for thousands of deaths every year. Current therapies are limited and there is an urgent need to develop new drugs. The anti-trypanosomal compound, 3-(oxazolo[4,5-b]pyridine-2-yl)anilide (OXPA), was initially identified in a phenotypic screen and subsequently optimized by structure–activity directed medicinal chemistry. It has been shown to be non-toxic and to be active against a number of trypanosomatid parasites. However, nothing is known about its mechanism of action. Objective: Here, we have utilized an untargeted metabolomics approach to investigate the biochemical effects and potential mode of action of this compound in T. brucei. Methods: Total metabolite extracts were analysed by HILIC-chromatography coupled to high resolution mass spectrometry. Results: Significant accumulation of ceramides was observed in OXPA-treated T. brucei. To further understand drug-induced changes in lipid metabolism, a lipidomics method was developed which enables the measurement of hundreds of lipids with high throughput and precision. The application of this LC–MS based approach to cultured bloodstream-form T. brucei putatively identified over 500 lipids in the parasite including glycerophospholipids, sphingolipids and fatty acyls, and confirmed the OXPA-induced accumulation of ceramides. Labelling with BODIPY-ceramide further confirmed the ceramide accumulation following drug treatment. Conclusion: These findings clearly demonstrate perturbation of ceramide metabolism by OXPA and indicate that the sphingolipid pathway is a promising drug target in T. brucei.No Full Tex