Malate enhances survival of zebrafish against Vibrio alginolyticus infection in the same manner as taurine

Abstract

Development of low-cost and eco-friendly approaches to fight bacterial pathogens is especially needed in aquaculture. We previously showed that exogenous malate reprograms zebrafish's metabolome to potentiate zebrafish survival against Vibrio alginolyticus infection. However, the underlying mechanism is unknown. Here, we use GC-MS based metabolomics to identify the malate-triggered metabolic shift. An activated TCA cycle and elevated taurine are identified as the key metabolic pathways and the most crucial biomarker of the reprogrammed metabolome, respectively. Taurine elevation is attributed to the activated TCA cycle, which is further supported by the increased expression of genes in the metabolic pathway of taurine biosynthesis from the isocitrate of the TCA cycle to taurine. Exogenous taurine increases the survival of zebrafish against V. alginolyticus infection as malate did. Moreover, exogenous taurine and malate regulate the expression of innate immunity genes and promote the generation of reactive oxygen species and nitrogen oxide in a similar way. The two metabolites can alleviate the excessive immune response to bacterial challenge, which protects fish from bacterial infection. These results indicate that malate enhances the survival of zebrafish to V. alginolyticus infection via taurine. Thus, our study highlights a metabolic approach to enhance a host's ability to fight bacterial infection.

Keywords: Taurine; Vibrio alginolyticus; aquaculture; malate; reprogramming metabolomics; zebrafish.

Figure 1.

Differential metabolomic profiling in malate group in response to V. alginolyticus infection. Zebrafish were injected with and without 70 μg malate as malate group and control group, respectively, five for each group. Humoral fluid was collected for GC-MS analysis. (a) Heat map showing differential 90 metabolites. Yellow and blue indicate increase and decrease of metabolites relative to the median metabolite level of the control, respectively (see color scale). (b) Z-score plot of differential metabolites based on control. Each point represents one metabolite in one technical repeat and colored by sample types. (c) Category of 90 differential abundance of metabolites.

Figure 2.

Pathway enrichment and analysis. (a) Pathway enrichment of varied metabolites in the malic acid group. Significantly enriched pathways are selected to be plotted based on raw p. 1, Alanine, aspartate, and glutamate metabolism; 2, Aminoacyl-tRNA biosynthesis; 3, Valine, leucine, and isoleucine biosynthesis; 4, Citrate cycle (TCA cycle); 5, Nitrogen metabolism; 6, D-Glutamine and D-glutamate metabolism; 7, Butanoate metabolism; 8, Arginine and proline metabolism; 9, Pantothenate and CoA biosynthesis; 10, Biosynthesis of unsaturated fatty acids; 11, Glycine, serine, and threonine metabolism; 12, Cyanoamino acid metabolism; 13, Glutathione metabolism; 14, Galactose metabolism. (b) integrative analysis of metabolites in significantly enriched pathways. Red and blue indicate increased and decreased metabolites, respectively.

Figure 3.

Identification of crucial metabolites. (a) PCA analysis of malic acid and control groups according to the treatments set. Each dot represents the technical replicate analysis of samples in the plot. T [1] and t0 [1] used in this plot explain 98.14% of the total variance which allows confident interpretation of the variation. (b) S-plot generates from OPLS-DA (R2X = 0.986 R2Y = 0.999, Q2 = 0.997). Predictive component p [1] and correlation p(corr) [1] differentiate malic acid from control. Dot represents metabolites and candidate biomarkers are highlighted in red. (c) Scatter plot of taurine, which comes from data 1a. Results (c) are displayed as mean ± SEM, and significant differences are identified (**p < 0.01) as determined by two-tailed Student’s t-test.

Figure 4.

Comparative metabolic pathway analysis. (a) Analysis of the metabolic profiles resulting from D. rerio injected by 70 μg malic acid provides a better insight into the effects of 90 significant metabolites (p < 0.01). Based on the KEGG compound (http://www.kegg.jp/kegg/compound/), metabolic network pathways in D. rerio are further analyzed with iPath2.0 (http://pathways.embl.de/iPath2.cgi). Red and blue lines represent increase and decrease in the malic acid group, respectively. (b) The activity of a-ketoglutaric dehydrogenase (KGDH) and succinate dehydrogenase (SDH). Twenty zebrafish spleens were collected in each group. Five were pooled as a sample, yielding four biological repeats for analysis of enzyme activity. Samples were collected in 24 h after the injection of malate for 3 days. Results (b) are displayed as mean ± SEM, and significant differences are identified (*p < 0.05, **p < 0.01) as determined by two-tailed Student’s t-test.

Figure 5.

Taurine biosynthesis pathway and ability against bacterial infection. (a) qRT-PCR for expression of taurine biosynthesis pathway genes. Upper, relative gene expression; Lower, shown in the metabolic pathway. Twenty-five zebrafish spleens were collected in each group. Five were pooled as a sample, yielding five biological repeats for analysis of gene expression. Samples were collected in 24 h after the injection of malate for 3 days. qRT-PCR was based on the key genes of taurine biosynthesis pathways in D. rerio. Red represents increase, blue represents decrease, and black represents unchanged in the malate-reprogramming group. (b) Percent survival of zebrafish in the presence of the indicated doses of taurine, 21 zebrafish each group. (c) Relative concentrations of taurine in the presence of PBS, 12.5 μg of taurine, 300 μg of taurine, and 70 μg of malate, five zebrafish each group. Taurine is measured by GC-MS analysis. Results are displayed as mean ± SEM, and significant differences are identified (*p < 0.05, **p < 0.01) as determined by two-tailed Student’s t-test (a and c) and Log-rank (Mantel-Cox) test, Gehan-Breslow-Wilcoxon test, and Tarone-Ware test (b).

Figure 6.

Expression of innate immunity genes in the presence of malate or taurine or/and bacterial infection. (a) Expression in the absence or presence of 70 μg malate or 12.5 μg taurine. Twenty-five zebrafish spleens were collected in each group. Five were pooled as a sample, yielding five biological repeats for analysis of gene expression. Samples were collected in 24 h after the injection of malate or taurine for 3 days. (b) Phagocytosis in the absence or presence of 70 μg malate or 12.5 μg taurine. Macrophages were separated from head kidney of Nile tilapia and incubated with 20 mM malate or taurine. Then, 1:100 bacterial cells were added. Three biological repeats were performed. (c) qRT-PCR for expression of innate immune genes post bacterial infection. Twenty-five zebrafish spleens were collected in each group. Five were pooled as a sample, yielding five biological repeats for analysis of gene expression. Zebrafish were treated with PBS, malate, or taurine for 3 days and then challenged by bacteria. Samples were collected at 30 h post the bacterial challenge. They included PBS group, only PBS injection without bacterial challenge; PBS live group, survival after PBS injection and bacterial challenge; PBS dying, dying after PBS injection and bacterial challenge; Taurine live, survival after taurine injection and bacterial challenge; Taurine dying, dying after taurine injection and bacterial challenge; Malate live, survival after malate injection and bacterial challenge; Malate dying, dying after malate injection and bacterial challenge. Results are displayed as mean ± SEM, and significant differences are identified (*p < 0.05, **p < 0.01) as determined by two-tailed Student’s t-test.

Figure 7.

Effect of malate and taurine on gene expression of NO biosynthesis. (a) Expression of NO biosynthesis genes in the absence or presence of 70 μg malate or 12.5 μg taurine. Left, shown in the metabolic pathway; Right, relative gene expression. (b) The activity of iNOS in the absence or presence of 70 μg malate or 12.5 μg taurine. (c) The activity of iNOS in samples as Figure 6c post bacterial challenge. (d) ROS in the absence or presence of 70 μg malate or 12.5 μg taurine. (e) ROS in samples as Figure 6c post bacterial challenge. (f) GSH-PX in the absence or presence of 70 μg malate or 12.5 μg taurine. (g) GSH-PX in samples as Fig 6 C post bacterial challenge. (a, b, d, and f) Twenty zebrafish spleens were collected in each group. Five were pooled as a sample, yielding four biological repeats for analysis of gene expression. Samples were collected in 24 h after the injection of malate or taurine for 3 days. (c, e, and g) Twenty zebrafish spleens were collected in each group. Five were pooled as a sample, yielding four biological repeats for analysis of gene expression. Zebrafish were treated with PBS, malate, or taurine for 3 days and then challenged by bacteria. Samples were collected at 30 h post the bacterial challenge. They included PBS group, only PBS injection without bacterial challenge; PBS live group, survival after PBS injection and bacterial challenge; PBS dying, dying after PBS injection and bacterial challenge; Taurine live, survival after taurine injection and bacterial challenge; Taurine dying, dying after taurine injection and bacterial challenge; Malate live, survival after malate injection and bacterial challenge; Malate dying, dying after malate injection and bacterial challenge. Results are displayed as mean ± SEM, and significant differences are identified (*p < 0.05; **p < 0.01) as determined by two-tailed Student’s t-test.