Metabolic Profile Associated With Encystation in Acanthamoeba

Abstract

The genus Acanthamoeba includes widespread protozoa that can cause severe infections in humans. Their ability to form resistant cysts within infected tissues complicates treatment, making it essential to understand the encystation process for developing effective therapeutic strategies. This study utilized untargeted metabolomics (GC-MS) to analyze metabolic changes during the encystation of an Acanthamoeba strain in Neff's encystation saline. We conducted metabolite analysis at three stages of differentiation: the trophozoite-dominant phase (0 h), the pre-cyst-dominant phase (24 h), and the cyst-dominant phase (72 h). The results indicated a global metabolic downregulation during encystation, which is consistent with a state of dormancy. Components of the cyst wall such as cellobiose and lactose accumulated in the final phase. Arbutin and canavanine were annotated for the first time in Acanthamoeba. Encystation also led to changes in pathways related to glycine, serine, and threonine metabolism and biosynthesis of aminoacyl-tRNA. This study uncovered previously unknown metabolites and metabolic pathways at distinct stages of Acanthamoeba development.

Keywords: acanthamoeba; encystation; gas chromatography–mass spectrometry; metabolomics.

FIGURE 1

Encystation of Acanthamoeba (ATCC 30010) in Neff's encystation saline. Trophozoites (10⁷) were added to culture flasks containing 10 mL of the encystation medium. Quantification of the morphological stages was performed every 24 h in independent sets of flasks (n = 3). The data represent the mean and standard error of counts performed in triplicate.

FIGURE 2

PLS‐DA score plots of identified metabolites from Acanthamoeba (ATCC 30010) in Neff's encystation saline at times 0, 24, and 72 h. The PLS‐DA model demonstrated a clustering tendency of samples at distinct times of encystation. Quality parameters of the model: R ² = 0.896 and Q ² = 0.785, CV‐ANOVA p‐value = 4 × 17⁻¹⁰.

FIGURE 3

PLS‐DA models comparing the distinct times of encystation of Acanthamoeba (ATCC 30010) in Neff's saline in pairs. The models were built with the total features normalized by the intensity of the internal standard C18:0 L, transformed in log with base 2, and pareto scaled. A, C, E: Score plots comparing 0 × 24 h, 0 × 72 h, and 24 × 72 h, respectively. B, D, F: Quality parameters R ² (goodness of fit) and Q ² (predictive ability) values for 0 × 24 h, 0 × 72 h, and 24 × 72 h models, respectively. G: Table summarizing the exact R ², Q ², and CV‐ANOVA p‐values for all pairwise comparisons. In all score plots (A, C, E), a clear separation between groups is observed, suggesting distinct metabolic profiles at each time point. The high R ² and Q ² values (B, D, F), along with significant CV‐ANOVA results (G), confirm the robustness and predictive validity of the models.

FIGURE 4

Heatmap and hierarchical clustering analysis of metabolites built with samples of Acanthamoeba (ATCC 30010) at the distinct times of encystation. The heatmap construction with the identified metabolites used the following parameters: Euclidean distance and average linkage. The x axis presents the evaluated time points, while the y axis presents the identified metabolites. The abundance of each metabolite is represented by the color scale, varying from −4 (light green) to +4 (light red).