Metabolomic Profiling and Anti- Helicobacter pylori Activity of Caulerpa lentillifera (Sea Grape) Extract

Abstract

Helicobacter pylori is a gastric pathogen implicated in peptic ulcer disease and gastric cancer. The increasing prevalence of antibiotic-resistant strains underscores the urgent need for alternative therapeutic strategies. In this study, we investigated the chemical composition and antibacterial activity of an aqueous extract from Caulerpa lentillifera (sea grape), a farm-cultivated edible green seaweed collected from Krabi Province, Thailand. Ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) revealed that the extract was enriched in bioactive nucleosides and phenolic compounds. In vitro assays demonstrated dose-dependent inhibition of H. pylori growth following exposure to sea grape extract. Furthermore, untargeted intracellular metabolomic profiling of H. pylori cells treated with the extract uncovered significant perturbations in central carbon and nitrogen metabolism, including pathways associated with the tricarboxylic acid (TCA) cycle, one-carbon metabolism, and alanine, aspartate, and glutamate metabolism. Pyrimidine biosynthesis was selectively upregulated, indicating a potential stress-induced shift toward nucleotide salvage and DNA repair. Of particular note, succinate levels were markedly reduced despite accumulation of other TCA intermediates, suggesting disruption of electron transport-linked respiration. These findings suggest that bioactive metabolites from C. lentillifera impair essential metabolic processes in H. pylori, highlighting its potential as a natural source of antimicrobial agents targeting bacterial physiology.

Keywords: Caulerpa lentillifera; Helicobacter pylori; chemical composition; metabolomics; sea grape.

Figure 1

Metabolite profiling of sea grape extract using UHPLC-MS/MS. (A–D) Base peak chromatograms (BPCs) of the blank (A,C) and sea grape extract (B,D) analyzed in positive (A,B) and negative (C,D) electrospray ionization (ESI) modes. Chromatographic profiles of the extract show diverse metabolite signals compared to the blank, indicating successful extraction and detection of numerous ionizable compounds. (E) Venn diagram summarizing metabolite feature detection: a total of 256 features were identified, with 174 features unique to the positive ESI mode, 110 features in the negative ESI mode, and 28 features detected in both modes.

Figure 2

Enrichment analysis of chemical classes in sea grape extract. Detected metabolites were subjected to chemical class enrichment analysis using the MetaboAnalyst 6.0 platform. (A) Enrichment overview based on chemical super-classes, comprising 39 predefined metabolite sets. (B) Enrichment overview of the top 25 main classes out of 617 sets. Bar lengths represent the enrichment ratio, indicating the degree of overrepresentation within each class, while bar color reflects the associated p-value, with darker red indicating greater statistical significance.

Figure 3

Effects of sea grape extract on H. pylori growth after 1 and 24 h treatments. The experiments were conducted in ½-strength BHI broth using a 12-well plate format. Bacterial growth was assessed by measuring OD₆₀₀ and normalized to the water-treated control (0 mg/mL extract). Each experiment was performed in biological triplicates. Statistical analyses were conducted using one-way ANOVA followed by Duncan’s Multiple Range Test (DMRT) and Dunnett’s post hoc test (two-sided). Different letters above the bars indicate groups that are significantly different from each other based on DMRT (p < 0.05); lowercase letters correspond to the 1 h treatment group, and uppercase letters to the 24 h group. Asterisks denote significant differences between each treatment and the control according to Dunnett’s test. Significance levels: *** (p < 0.001), ** (p < 0.01), * (p < 0.05).

Figure 4

Experimental workflow for metabolomics analysis of H. pylori treated with sea grape extract. H. pylori liquid cultures were filtered through a PVDF membrane to retain bacterial cells on the surface. The membrane was first transferred onto a blood agar plate to allow cell acclimatization. After acclimation, the membrane was transferred onto treatment plates containing either sea grape extract or control medium. For each sample, two parallel setups were prepared: one for intracellular metabolite extraction and the other for bacterial growth assessment (growth results shown in Figure S2).

Figure 5

Overview of intracellular metabolite profiles of H. pylori treated with sea grape extract or control. (A) UHPLC-MS/MS analysis detected a total of 646 metabolites from H. pylori samples. Of these, 377 metabolites were identified in positive ESI mode and 345 in negative ESI mode, with 76 metabolites detected in both modes. (B) PCA 2D score plot showing the separation between sea grape-treated and control samples. (C) PLS-DA 2D score plot further highlighting the distinction between treatment groups. (D) Top 25 metabolites ranked by variable importance in projection (VIP) scores (component 1) from the PLS-DA model, indicating key metabolites contributing to group separation. Metabolite (1), 4-hydroxy-5-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy-1H-benzo[f][2]benzofuran-3-one (C₁₈H₁₈O₉); Metabolite (2), 2-formylbenzenesulfonate (contaminant); cGMP, guanosine cyclic monophosphate; Metabolite (3), 2-[5-[2-[2-[5-[2-[2-[5-[2-[2-[5-(2-hydroxybutyl)oxolan-2-yl]propanoyloxy]propyl]oxolan-2-yl]propanoyloxy]propyl]oxolan-2-yl]propanoyloxy]propyl]oxolan-2-yl]propanoic acid (C₄₁H₆₈O₁₃); Metabolite (4), [(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-[[(E)-3-phenylprop-2-enoyl]oxymethyl]oxan-2-yl] 3,4,5-trihydroxybenzoate (C₂₂H₂₂O₁₁); CMP, cytidine monophosphate; Metabolite (5), EDTA (contaminant); Metabolite (6), 3-[(3S,5S,8R,10S,13R,14S,17R)-3-[4,5-dihydroxy-6-(hydroxymethyl)-3-[3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyoxan-2-yl]oxy-14-hydroxy-10,13-dimethyl-1,2,3,4,5,6,7,8,9,11,12,15,16,17-tetradecahydrocyclopenta[a]phenanthren-17-yl]-2H-furan-5-one (C₃₅H₅₄O₁₄).

Figure 6

Heatmap of intracellular metabolite profiles in H. pylori treated with sea grape extracts. Intracellular metabolite intensities from H. pylori treated with control, low-dose, or high-dose sea grape extract were standardized using z-score normalization (${\displaystyle \frac{x-\mu }{\sigma }}$). Complete-linkage hierarchical clustering was performed to group samples and metabolites based on similarity. Yellow indicates relatively high metabolite abundance, whereas blue indicates low abundance. To account for the growth-inhibitory effects of sea grape extract, metabolite intensities were further normalized to the relative bacterial growth, and the resulting growth-adjusted heatmap is shown on the right. Metabolite pathway enrichment analysis was performed using KEGG pathway sets in MetaboAnalyst 6.0.