Myo-Inositol Restores Tilapia's Ability Against Infection by Aeromonas sobria in Higher Water Temperature

Abstract

Bacterial infection presents severe challenge to tilapia farming, which is largely influenced by water temperature. However, how water temperature determines tilapias' survival to infection is not well understood. Here, we address this issue from the perspective of metabolic state. Tilapias were more susceptible to Aeromonas sobria infection at 33°C than at 18°C, which is associated with differential metabolism of the fish. Compared to the metabolome of tilapia at 18°C, the metabolome at 33°C was characterized with increased an tricarboxylic acid cycle and a reduced level of myo-inositol which represent the most impactful pathway and crucial biomarker, respectively. These alterations were accompanied with the elevated transcriptional level of 10 innate immune genes with infection time, where il-1b, il-6, il-8, and il-10 exhibited a higher expression at 33°C than at 18°C and was attenuated by exogenous myo-inositol in both groups. Interestingly, exogenous myo-inositol inactivated the elevated TCA cycle via inhibiting the enzymatic activity of succinate dehydrogenase and malate dehydrogenase. Thus, tilapias showed a higher survival ability at 33°C. Our study reveals a previously unknown relationship among water temperature, metabolic state, and innate immunity and establishes a novel approach to eliminate bacterial pathogens in tilapia at higher water temperature.

Keywords: Aeromonas sobria; bacterial infection; innate immunity; metabolome; myo-inositol; water temperature.

Figure 1

Survival of GIFT (genetically improved farmed tilapia, Oreochromis niloticus) to A. sobria infection cultured at 18°C and 33°C. Tilapias (n = 30 per group) were acclimated at 18°C and 33°C for 7 days before bacterial challenge. For bacterial infection, tilapias were injected with 10 µl 1 × 10⁵ CFU/fish A. sobria or 10 µl saline solution as negative control. Accumulative death was monitored for a total of 15 days. **p < 0.01.

Figure 2

Tilapia cultured at 18°C or 33°C had a different metabolome. (A) Representative total ion current chromatogram from 18°C or 33°C of samples. (B) Reproducibility of the metabolomic profiling platform used in the discovery phase. Abundance of metabolites quantified in samples over two technical replicates is shown. The Pearson correlation coefficient between technical replicates varies between 0.9307 and 0.9996. (C) Categories of the differential metabolites. One hundred fifteen metabolites with differential abundance are searched against in KEGG for their categories, and the pie chart is generated in Excel 2010 (Microsoft, USA). (D) Heat map of unsupervised hierarchical clustering of different metabolites (row). Blue and red indicate decrease and increase of the metabolites scaled to mean and standard deviation of row metabolite level, respectively (see color scale).

Figure 3

Differential metabolic profiles of tilapias cultured at different temperatures. (A) Heat map showing 97 differential metabolites. Red and blue indicate increase and decrease of metabolites relative to the median metabolite level, respectively (see color scale). (B) Z-score plot of differential metabolites based on the 18°C group. Each point represents one metabolite in one technical repeat and colored by sample types. (C) The different metabolites were classified into five categories, carbohydrate (23.71%), amino acid (29.9%), nucleotide (16.43%), fatty acid (18.56%), and others (11.34%). (D) Number of increased and decreased metabolites in these categories (C), 17 and 6 (carbohydrate), 24 and 5 (amino acid), 14 and 2 (nucleotide), 12 and 6 (fatty acid), and 8 and 3 (others), respectively.

Figure 4

Identification of crucial metabolites. (A) PCA analysis of 18°C and 33°C groups according to the treatment set. Each dot represents the technological replicate analysis of samples in the plot. PC 1 and PC 2 used in this plot explain 97.66% of the total variance which allows confident interpretation of the variation. (B) OPLS-DA analysis of 18°C and 33°C groups. Dots represent technological replicates. Component 1 (T score [1] = 91.29%) and Component 2 (orthogonal T score [1] = 2.4%) of OPLS-DA explain 93.69% of the total variance. (C) S-plot generates from OPLS-DA (R2X = 0.926, R2Y = 0.979, Q2 = 0.977). Predictive component p[1] and correlation p(corr)[1] differentiate 18°C from 33°C. Dot represents metabolites, and candidate biomarkers are highlighted in red. (D) Scatter plot of myo-inositol, myo-inositol-1-phosphate, and myo-inositol-2-phosphate. **p < 0.01.

Figure 5

Pathway enrichment and analysis. (A) Pathway enrichment of differential metabolites in the 33°C group compared with the 18°C group. In terms of impact value from the largest to the smallest, 1 to 9, respectively, represent alanine, aspartate and glutamate metabolism; taurine and hypotaurine metabolism; D-glutamine and D-glutamate metabolism; citrate cycle (TCA cycle); purine metabolism; arginine biosynthesis; aminoacyl-tRNA biosynthesis; pantothenate and CoA biosynthesis; and valine, leucine, and isoleucine biosynthesis. Significantly enriched pathways are selected to plot. (B) Integrative analysis of metabolites in significantly enriched pathways. Red and blue indicate increased and decreased metabolites, respectively.

Figure 6

Comparative metabolic pathway analysis between the 18°C and 33°C groups. Analysis of the metabolic profiles resulting from tilapias cultured at 18°C and 33°C provides a better insight into the effect of 97 differential abundances of metabolites (p < 0.01). Based on the KEGG compound (http://www.kegg.jp/kegg/compound/), metabolic network pathways in tilapias are further analyzed with iPath2.0 (http://pathways.embl.de/iPath2.cgi). Red line represents increase in the 33°C group; blue line represents decrease in the 33°C group.

Figure 7

Myo-inositol impacts the TCA cycle and promote tilapia’s ability against bacterial infection. (A) Survival of tilapias post A sobria infection in the presence of myo-inositol. Tilapias were treated with saline control (0 µg per fish) or different doses of myo-inositol (200, 400, and 800 µg per fish) at 33°C for 3 days, followed by bacterial challenge through intraperitoneal injection (1 × 10⁵ CFU A. sobria). The accumulative fish death was monitored for a total of 15 days postinfection (n =30 per group). (B) Activity of PDH, KGDH, SDH, and MDH of spleens at 18°C and 33°C. (C) Activity of PDH, KGDH, SDH, and MDH of spleens in the presence or absence of 800 µg myo-inositol per fish. Values are means ± SEM (n = 6 per group), and statistic difference is analyzed with non-parametric Kruskal–Wallis one-way analysis with Dunn’s multiple-comparison post hoc test. *p < 0.05; **p < 0.01 (B, C).

Figure 8

Innate immune responses of tilapias. (A) qRT-PCR for innate immune genes of tilapia treated with saline solution (control) or 800 µg myo-inositol for 3 days following A. sobria challenge through intraperitoneal injection (1 × 10³ CFU A. sobria). Spleens were collected at 0, 3, 6, and 9 h postinjection for RNA extraction and qRT-PCR. Values are means ± SEM from six biological replicates. **p < 0.01. (B) Survival of tilapias post A. sobria infection in the presence of myo-inositol. Tilapias were treated with saline control (0 µg per fish) or different doses of myo-inositol (200, 400, and 800 µg per fish) at 18°C for 3 days, followed by bacterial challenge through intraperitoneal injection (1 × 10⁵ CFU A. sobria). The accumulative fish death was monitored for a total of 15 days postinfection (n =30 per group).