Jasmina Saric

Global metabolic responses of mice to Trypanosoma brucei brucei infection

Human African trypanosomiasis (HAT) is transmitted by tsetse flies and, if untreated, is fatal. Treatment depends on infection stage, and early diagnosis is crucial for effective disease management. The systemic host biochemical changes induced by HAT that enable biomarker discovery or relate to therapeutic outcome are largely unknown. We have characterized the multivariate temporal responses of mice to Trypanosoma brucei brucei infection, using 1H nuclear magnetic resonance (NMR) spectroscopic metabolic phenotyping of urine and plasma. Marked alterations in plasma metabolic profiles were detected already 1 day postinfection. Elevated plasma concentrations of lactate, branched chain amino acids, and acetylglycoprotein fragments were noted. T. brucei brucei-infected mice also had an imbalance of plasma alanine and valine, consistent with differential gluconeogenesis (parasite)-ketogenesis (host) pathway counterflux, involving stimulated host glycolysis, ketogenesis, and enhanced lipid oxidation in the host. Histopathologic evidence of T. brucei brucei-induced extramedullary hepatic hemopoiesis, renal interstitial nephritis, and a provoked inflammatory response was also noted. Metabolic disturbance of gut microbiotal activity was associated with infection, as indicated by changes in the urinary concentrations of the microbial co-metabolites, including hippurate. Concluding, parasite infection results in multiple systemic biochemical effects in the host and disturbance of the symbiotic gut microbial metabolic interactions. Investigation of these transgenomic metabolic alterations may underpin the development of new diagnostic criteria and metrics of therapeutic efficacy.

Global metabolic responses of NMRI mice to an experimental Plasmodium berghei infection

We present a metabolism-driven top-down systems biology approach to characterize metabolic changes in the mouse resulting from an infection with Plasmodium berghei, using high-resolution (1)H NMR spectroscopy and multivariate data analysis techniques. Twelve female NMRI mice were infected intravenously with approximately 20 million P. berghei-parasitized erythrocytes. Urine and plasma samples were collected 4-6 h before infection, and at days 1, 2, 3, and 4 postinfection. Multivariate analysis of spectral data showed differentiation between samples collected before and after infection, with growing metabolic distinction as the time postinfection progressed. Our analysis of plasma from P. berghei-infected mice showed marked increases in lactate and pyruvate levels, and decreased glucose, creatine, and glycerophosphoryl choline compared with preinfection, indicating glycolytic upregulation, and increased energy demand due to P. berghei infection. The dominant changes in the urinary metabolite profiles included increased levels of pipecolic acid, phenylacetylglycine, and dimethylamine, and decreased concentrations of taurine and trimethylamine- N-oxide, which may, among other factors, indicate a disturbance of the gut microbial community caused by the parasite. Although several of the observed metabolic changes are also associated with other parasitic infections, the combination of metabolic changes and, in particular, the occurrence of pipecolic acid in mouse urine postinfection are unique to a P. berghei infection. Hence, metabolic profiling may provide a sensitive diagnostic tool of Plasmodium infection and the control of malaria more generally.

Metabolic Profiling of an Echinostoma caproni Infection in the Mouse for Biomarker Discovery

Background Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states. The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse, and to compare the biomarkers extracted from different biofluids (plasma, stool, and urine) in terms of characterizing acute and chronic stages of this intestinal fluke infection. Methodology/Principal Findings Twelve female NMRI mice were infected with 30 E. caproni metacercariae each. Plasma, stool, and urine samples were collected at 7 time points up to day 33 post-infection. Samples were also obtained from non-infected control mice at the same time points and measured using 1H nuclear magnetic resonance (NMR) spectroscopy. Spectral data were subjected to multivariate statistical analyses. In plasma and urine, an altered metabolic profile was already evident 1 day post-infection, characterized by reduced levels of plasma choline, acetate, formate, and lactate, coupled with increased levels of plasma glucose, and relatively lower concentrations of urinary creatine. The main changes in the urine metabolic profile started at day 8 post-infection, characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection. Conclusion/Significance The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery. In the case of E. caproni, a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection. For practical purposes, however, future diagnosis might aim at a single biofluid, in which case urine would be chosen for further investigation, based on quantity of biomarkers, ease of sampling, and the degree of differentiation from the non-infected control group.

Generating super-shedders: co-infection increases bacterial load and egg production of a gastrointestinal helminth

Co-infection by multiple parasites is common within individuals. Interactions between co-infecting parasites include resource competition, direct competition and immune-mediated interactions and each are likely to alter the dynamics of single parasites. We posit that co-infection is a driver of variation in parasite establishment and growth, ultimately altering the production of parasite transmission stages. To test this hypothesis, three different treatment groups of laboratory mice were infected with the gastrointestinal helminth Heligmosomoides polygyrus, the respiratory bacterial pathogen Bordetella bronchiseptica lux+ or co-infected with both parasites. To follow co-infection simultaneously, self-bioluminescent bacteria were used to quantify infection in vivo and in real-time, while helminth egg production was monitored in real-time using faecal samples. Co-infection resulted in high bacterial loads early in the infection (within the first 5 days) that could cause host mortality. Co-infection also produced helminth ‘super-shedders’; individuals that chronically shed the helminth eggs in larger than average numbers. Our study shows that co-infection may be one of the underlying mechanisms for the often-observed high variance in parasite load and shedding rates, and should thus be taken into consideration for disease management and control. Further, using self-bioluminescent bacterial reporters allowed quantification of the progression of infection within the whole animal of the same individuals at a fine temporal scale (daily) and significantly reduced the number of animals used (by 85%) compared with experiments that do not use in vivo techniques. Thus, we present bioluminescent imaging as a novel, non-invasive tool offering great potential to be taken forward into other applications of infectious disease ecology.

Metabolic profiling of a Schistosoma mansoni infection in mouse tissues using magic angle spinning-nuclear magnetic resonance spectroscopy.

In order to enhance our understanding of physiological and pathological consequences of a patent Schistosoma mansoni infection in the mouse, we examined the metabolic responses of different tissue samples recovered from the host animal using a metabolic profiling strategy. Ten female NMRI mice were infected with approximately 80 S. mansoni cercariae each, and 10 uninfected age- and sex-matched animals served as controls. At day 74 post infection (p.i.), mice were killed and jejunum, ileum, colon, liver, spleen and kidney samples were removed. We employed (1)H magic angle spinning-nuclear magnetic resonance spectroscopy to generate tissue-specific metabolic profiles. The spectral data were analyzed using multivariate modelling methods including an orthogonal signal corrected-projection to latent structure analysis and hierarchical principal component analysis to assess the differences and/or similarities in metabolic responses between infected and non-infected control mice. Most tissues obtained from S. mansoni-infected mice were characterized by high levels of amino acids, such as leucine, isoleucine, lysine, glutamine and asparagine. High levels of membrane phospholipid metabolites, including glycerophosphoryl choline and phosphoryl choline were found in the ileum, colon, liver and spleen of infected mice. Additionally, low levels of energy-related metabolites, including lipids, glucose and glycogen were observed in ileum, spleen and liver samples of infected mice. Energy-related metabolites in the jejunum, liver and renal medulla were found to be positively correlated with S. mansoni worm burden upon dissection. These findings show that a patent S. mansoni infection causes clear disruption of metabolism in a range of tissues at a molecular level, which can be interpreted in relation to the previously reported signature in a biofluid (i.e. urine), giving further evidence of the global effect of the infection.

Heteronuclear 19F−1H Statistical Total Correlation Spectroscopy as a Tool in Drug Metabolism: Study of Flucloxacillin Biotransformation

We present a novel application of the heteronuclear statistical total correlation spectroscopy (HET-STOCSY) approach utilizing statistical correlation between one-dimensional 19F/1H NMR spectroscopic data sets collected in parallel to study drug metabolism. Parallel one-dimensional (1D) 800 MHz 1H and 753 MHz 19F{1H} spectra (n = 21) were obtained on urine samples collected from volunteers (n = 6) at various intervals up to 24 h after oral dosing with 500 mg of flucloxacillin. A variety of statistical relationships between and within the spectroscopic datasets were explored without significant loss of the typically high 1D spectral resolution, generating 1H-1H STOCSY plots, and novel 19F-1H HET-STOCSY, 19F-19F STOCSY, and 19F-edited 1H-1H STOCSY (X-STOCSY) spectroscopic maps, with a resolution of approximately 0.8 Hz/pt for both nuclei. The efficient statistical editing provided by these methods readily allowed the collection of drug metabolic data and assisted structure elucidation. This approach is of general applicability for studying the metabolism of other fluorine-containing drugs, including important anticancer agents such as 5-fluorouracil and flutamide, and is extendable to any drug metabolism study where there is a spin-active X-nucleus (e.g., 13C, 15N, 31P) label present.

Systematic Evaluation of Extraction Methods for Multiplatform-Based Metabotyping: Application to the Fasciola hepatica Metabolome

Combining data from multiple analytical platforms is essential for comprehensive study of the molecular phenotype (metabotype) of a given biological sample. The metabolite profiles generated are intrinsically dependent on the analytical platforms, each requiring optimization of instrumental parameters, separation conditions, and sample extraction to deliver maximal biological information. An in-depth evaluation of extraction protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola hepatica, using ultra performance liquid chromatography and capillary electrophoresis coupled with mass spectroscopy is presented. The spectrometric methods were characterized by performance, and metrics of merit were established, including precision, mass accuracy, selectivity, sensitivity, and platform stability. Although a core group of molecules was common to all methods, each platform contributed a unique set, whereby 142 metabolites out of 14,724 features were identified. A mixture design revealed that the chloroform:methanol:water proportion of 15:59:26 was globally the best composition for metabolite extraction across UPLC-MS and CE-MS platforms accommodating different columns and ionization modes. Despite the general assumption of the necessity of platform-adapted protocols for achieving effective metabotype characterization, we show that an appropriately designed single extraction procedure is able to fit the requirements of all technologies. This may constitute a paradigm shift in developing efficient protocols for high-throughput metabolite profiling with more-general analytical applicability.

Integrated Cytokine and Metabolic Analysis of Pathological Responses to Parasite Exposure in Rodents

Parasitic infections cause a myriad of responses in their mammalian hosts, on immune as well as on metabolic level. A multiplex panel of cytokines and metabolites derived from four parasite-rodent models, namely, Plasmodium berghei−mouse, Trypanosoma brucei brucei−mouse, Schistosoma mansoni−mouse, and Fasciola hepatica−rat were statistically coanalyzed. 1H NMR spectroscopy and multivariate statistical analysis were used to characterize the urine and plasma metabolite profiles in infected and noninfected animals. Each parasite generated a unique metabolic signature in the host. Plasma cytokine concentrations were obtained using the ‘Meso Scale Discovery’ multi cytokine assay platform. Multivariate data integration methods were subsequently used to elucidate the component of the metabolic signature which is associated with inflammation and to determine specific metabolic correlates with parasite-induced changes in plasma cytokine levels. For example, the relative levels of acetyl glycoproteins extracted from the plasma metabolite profile in the P. berghei-infected mice were statistically correlated with IFN-γ, whereas the same cytokine was anticorrelated with glucose levels. Both the metabolic and the cytokine data showed a similar spatial distribution in principal component analysis scores plots constructed for the combined murine data, with samples from all infected animals clustering according to the parasite species and whereby the protozoan infections (P. berghei and T. b. brucei) grouped separately from the helminth infection (S. mansoni). For S. mansoni, the main infection-responsive cytokines were IL-4 and IL-5, which covaried with lactate, choline, and d-3-hydroxybutyrate. This study demonstrates that the inherently differential immune response to single- and multicellular parasites not only manifests in the cytokine expression, but also consequently imprints on the metabolic signature, and calls for in-depth analysis to further explore direct links between immune features and biochemical pathways.

Panorganismal Metabolic Response Modeling of an Experimental Echinostoma caproni Infection in the Mouse

Metabolic profiling of host tissues and biofluids during parasitic infections can reveal new biomarker information and aid the elucidation of mechanisms of disease. The multicompartmental metabolic effects of an experimental Echinostoma caproni infection have been characterized in 12 outbred female mice infected orally with 30 E. caproni metacercariae each, using a further 12 uninfected animals as a control group. Mice were killed 36 days postinfection and brain, intestine (colon, ileum, jejeunum), kidney, liver, and spleen were removed. Metabolic profiles of tissue samples were measured using high-resolution magic angle spinning 1H NMR spectroscopy and biofluids measured by applying conventional 1H NMR spectroscopy. Spectral data were analyzed via principal component analysis, partial least-squares-derived methods and hierarchical projection analyses. Infection-induced metabolic changes in the tissues were correlated with altered metabolite concentrations in the biofluids (urine, plasma, fecal water) using hierarchical modeling and correlation analyses. Metabolic descriptors of infection were identified in liver, renal cortex, intestinal tissues but not in spleen, brain or renal medulla. The main physiological change observed in the mouse was malabsorption in the small intestine, which was evidenced by decreased levels of various amino acids in the ileum, for example, alanine, taurine, glutamine, and branched chain amino acids. Furthermore, altered gut microbial activity or composition was reflected by increased levels of trimethylamine in the colon. Our modeling approach facilitated in-depth appraisal of the covariation of the metabolic profiles of different biological matrices and found that urine and plasma most closely reflected changes in ileal compartments. In conclusion, an E. caproni infection not only results in direct localized (ileum and jejenum) effects, but also causes remote metabolic changes (colon and several peripheral organs), and therefore describes the panorganismal metabolic response of the infection.

Advances in metabolic profiling of experimental nematode and trematode infections.

Metabonomics, which is the combination of metabolic profiling of biological samples using spectroscopic methods, together with multivariate data analysis, is a powerful approach for biomarker recovery. Moreover, metabonomics holds promise to enhance our understanding of host-parasite interactions at the metabolic level, and therefore provides a framework for discovery of novel targets for diagnostics, drugs and vaccines. In this review, we summarise progress made to date with metabolic profiling strategies applied to different host-parasite models in the laboratory. First, we emphasise the application of two parasitic worm infections that are particularly relevant for Southeast Asia and the Peoples Republic of China, namely the trematode Schistosoma japonicum causing schistosomiasis, and the nematode Necator americanus causing hookworm disease. Next, we review metabolic profiling studies on the liver fluke Fasciola hepatica in the rat model, the intestinal fluke Echinostoma caproni harboured in mice and characterise the metabolic responses in the hamster to a S. japonicum-N. americanus co-infection. We extract parasite-specific biomarkers and distinguish them from a more general response to an infection at the biochemical level. For example, suppression of tricarboxylic acid cycle metabolites is only noted for a Schistosoma spp. infection, whereas alterations in metabolites derived from the gut microbiota are common for all the parasitic infections investigated thus far. Finally, we explore how the insight gained with experimental infections could be transferred to human populations and conclude with a section on research needs with regard to molecular diagnostics in parasitology.