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. 2015 Oct 20;112(42):13075-80.
doi: 10.1073/pnas.1516544112. Epub 2015 Oct 5.

Targeting glutamine metabolism rescues mice from late-stage cerebral malaria

Emile B Gordon  1 , Geoffrey T Hart  1 , Tuan M Tran  1 , Michael Waisberg  1 , Munir Akkaya  1 , Ann S Kim  1 , Sara E Hamilton  2 , Mirna Pena  1 , Takele Yazew  1 , Chen-Feng Qi  1 , Chen-Fang Lee  3 , Ying-Chun Lo  4 , Louis H Miller  5 , Jonathan D Powell  6 , Susan K Pierce  7
Affiliations

Targeting glutamine metabolism rescues mice from late-stage cerebral malaria

Emile B Gordon et al. Proc Natl Acad Sci U S A. .

Abstract

The most deadly complication of Plasmodium falciparum infection is cerebral malaria (CM) with a case fatality rate of 15-25% in African children despite effective antimalarial chemotherapy. There are no adjunctive treatments for CM, so there is an urgent need to identify new targets for therapy. Here we show that the glutamine analog 6-diazo-5-oxo-L-norleucine (DON) rescues mice from CM when administered late in the infection a time at which mice already are suffering blood-brain barrier dysfunction, brain swelling, and hemorrhaging accompanied by accumulation of parasite-specific CD8(+) effector T cells and infected red blood cells in the brain. Remarkably, within hours of DON treatment mice showed blood-brain barrier integrity, reduced brain swelling, decreased function of activated effector CD8(+) T cells in the brain, and levels of brain metabolites that resembled those in uninfected mice. These results suggest DON as a strong candidate for an effective adjunctive therapy for CM in African children.

Keywords: CD8+ T cells; DON; adjunctive therapy; cerebral malaria; glutamine metabolism.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
DON treatment reduced the mortality associated with ECM. C57BL/6 mice were infected with PbA on day 0 and were injected i.p. with saline (NoRx) (n = 49) or with DON (1.3 mg/kg) beginning on day 5 p.i. at 7:00 AM (DON Rx d5a) (n = 28), on day 5 p.i. at 11:00 PM (DON Rx d5p) (n = 28), or on day 6 p.i. at 7:00 AM (DON Rx d6a) (n = 28). DON treatment was continued every day or every other day as shown in Fig. S1. (A) Kaplan–Meier survival plots. (B) Clinical scores from 0 (no symptoms) to 10 (moribund) of mice in A. (C) Peripheral blood parasitemia for mice in A. Data for DON Rx d5a were combined from three independent experiments, data for DON Rx d5p were combined from four independent experiments, and data for DON Rx d6a were combined from two independent experiments. Data in B and C are shown as mean and SEM. (D) Fold changes in PbA 18s RNA in brains of DON-treated and untreated PbA-infected mice on day 6a p.i. compared with PbA 18s RNA in brains of PbA-infected untreated mice on day 5p p.i. Each dot represents a mouse with the mean and SD given. The results shown are combined from three independent experiments, each having three or four mice per group. A Mann–Whitney test showed no significant difference.
Fig. S1.
Fig. S1.
DON treatment schedule. DON treatment (1.3 mg/kg) was initiated on day 5 p.i. at 7:00 AM (d5a), day 5 p.i. at 11:00 PM (d5p), or day 6 p.i. at 7:00 AM (d6a) and was continued every day or every other day as shown.
Fig. S2.
Fig. S2.
Clinical scores for mice that survived or died with or without DON treatment. (A) Clinical scores for mice that were not treated starting at day 5 p.i. at 11:00 PM (d5p) and then at day 6 p.i. at 7:00 AM (d6a). (B) Clinical scores measured on d5p and on d6a for mice that either survived or died after treatment with DON on d5p. The average clinical score at d5p is significantly higher for the mice that died than for mice that survived (P = 0.0045). (C) Clinical scores measured on d6a and on d7 at 7:00 AM (d7a) for mice treated on d6a with DON that survived or died. Each dot represents a mouse, and dots are staggered around time points. The average clinical score at d6a is significantly higher for the mice that died than for mice that survived (P = 0.017). A plus sign indicates a mouse that died after the first time point.
Fig. S3.
Fig. S3.
Late cessation of DON Rx leads to increased parasitemia. C57BL/6 mice were infected with PbA on day 0 and given saline (No Rx) or DON (1.3 mg/kg) every other day beginning at 7:00 AM on day 1 p.i. (DON Rx d1a). The peripheral blood parasitemia was determined by flow cytometry on the days indicated.
Fig. 2.
Fig. 2.
DON treatment promoted BBB function and reduced brain swelling but did not acutely resolve brain hemorrhages in PbA-infected mice. All mice were infected with PbA and treated with saline or DON (1.3 mg/kg) on day 5p p.i., and the brains were removed and analyzed on the days and times indicated. (A) Representative images of the brains of mice injected with EB. (B) EB levels in the brains were quantified and expressed relative to the EB levels in the brains of PbA-infected, untreated mice on d6a p.i. Each symbol represents one mouse. The data are combined from three independent experiments and are shown as mean and SD. (C) Brain water content expressed as the weight of each brain after desiccation divided by the weight before desiccation × 100 is given. Data are combined from two independent experiments and are shown as mean and SD. (D) Representative images of brain sections; hemorrhages are indicated by white arrows. (E) Quantification of brain hemorrhages. Each symbol represents one mouse. Data are combined from three independent experiments. Mann–Whitney tests were used for comparison of groups (**P < 0.005, ***P < 0.0005).
Fig. 3.
Fig. 3.
DON treatment reduced CD8+ T-cell degranulation but not the accumulation of immune cells in the brains of PbA-infected mice. Uninfected mice and mice infected with PbA were treated with DON (1.3 mg/kg) or saline on day 5p p.i. (A–E) On day 6a p.i. mice were perfused with cold PBS, the brains and/or spleens were removed, and single-cell suspensions were prepared. Cells were analyzed by flow cytometry using the gating strategy shown in Fig. S4. Shown are the number of cells per brain for macrophage/dendritic cells (DC) (A), neutrophils (B), NK cells (C), CD 4+ T cells (D), and CD8+ T cells (E). Data were combined from three independent experiments. (F) Representative flow cytometry plots of GAP50 MHC class I Db tetramer-binding CD8+ T cells in unenriched spleen/lymph node cell populations (Left and Right) and in GAP50-tetramer–binding cells enriched by GAP50-tetramer-bound magnetic beads (Center). (G) The number of GAP50-tetramer–binding CD8+ T cells in spleen and brains. Data were combined from three independent experiments. (H) Representative flow cytometry plots of CD8+ T cells in the spleens of mice that received fluorescently labeled CD107-specific Abs i.v. 1 h before being killed to allow labeling of CD107-expressing cells in vivo. (I and J)The percent of total CD8+ T cells that expressed CD107 (I) and the percent of GAP50-tetramer–binding CD8+ T cells that expressed CD107 (J) are shown. Data were combined from three independent experiments. Mann–Whitney tests were used for statistical analysis. ns, not significant; *P < 0.05, **P < 0.005, ***P <0.0005.
Fig. S4.
Fig. S4.
Gating strategy to identify immune cells in the brain and spleens. Single-cell suspensions were gated, excluding very small cells or debris, and cell doublets were excluded by side-scatter width. The LIVE/DEAD aqua dye was used to label dead cells, and only living cells were gated. The pan leukocyte marker CD45.2 was used to gate on leukocytes. Cells were gated on CD3+ cells that include CD4+ and CD8+ T cells, NK T cells, and γδ T cells. CD3+ cells were gated further on CD8+ and CD4+ cells. The CD3− gate was used to subset cells further into neutrophils (Ly6G+, Ly6C+), macrophages/dendritic cells (DC cells) (Ly6G−, Ly6C+), and NK cells (NK1.1+). Leukocytes per spleen and brain preparation were counted on a hemocytometer, and the numbers of each cell type were calculated.
Fig. 4.
Fig. 4.
DON significantly alters metabolism in the brain during ECM. (A–C) Principle components analysis for each of three tissue types collected from mice at day 6a p.i. for the five experimental groups defined by infection, treatment, and clinical outcome (Table S1). Principal components were determined from all detectable metabolites for the brain (438 metabolites) (A), liver (544 metabolites) (B), and serum (563 metabolites) (C). Each sphere represents one tissue sample from one mouse. (D) Venn diagram showing the number of differentially abundant brain metabolites for the two main comparisons: infected, untreated mice vs. uninfected, untreated mice and infected, DON-treated mice with low clinical scores vs. infected, untreated mice. Differential abundance thresholds were an absolute fold-change in abundance of ≥1.2 and a false-discovery rate of <5% (Welch’s t test).
Fig. 5.
Fig. 5.
Recovery from ECM with DON treatment is associated with normal brain metabolites. Clustering heat map showing the normalized abundance of the 81 metabolites that were shared between the two main comparisons in Fig. 4D. Each row is a metabolite, and each column represents brain tissue from a single mouse. Unsupervised hierarchical clustering of samples was performed using Ward’s method for linkage analysis and Pearson’s dissimilarity as distance measure. Metabolites were grouped according to pathway annotations (labels at right).
Fig. S5.
Fig. S5.
The effect of PbA infection and DON treatment during PbA infection on the glutaminolysis pathway in the brain, liver, and serum. (A) DON blocks the first step of glutaminolysis by inhibiting glutaminase. (B) PbA infection and DON treatment of PbA-infected mice affect the glutaminolysis pathway differently in the brain than in the liver and serum. Shown are absolute fold change and FDRs by Welch’s t test for the indicated two-way comparisons. Positive fold changes (red shading) represent significantly increased (FDR <0.05) metabolite abundance in the first group compared with the second group. Negative fold changes (blue shading) represent significantly decreased (FDR <0.05) metabolite abundance in the first group compared with the second group.
Fig. S6.
Fig. S6.
DON significantly alters citrulline, urea, and nitric oxide metabolism in the brain during ECM. (A and B) Pathways analysis of differentially abundant metabolites for each two-way comparison (shown in Fig. 4D) demonstrated several significantly overrepresented pathways that are shared between the two comparisons. Shown are the ratio of overlap of metabolites in the dataset with metabolites in the pathway and the log(P value) of the overlap by Fisher’s exact test. Metabolites discussed in the text are shown in bold.
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