Impact of Weissella cibaria BYL4.2 and its supernatants on Penicillium chrysogenum metabolism

Abstract

Lactic acid bacteria (LAB) can produce a vast spectrum of antifungal metabolites to inhibit fungal growth. The purpose of this study was to elucidate the antifungal effect of isolated Weissella cibaria BYL4.2 on Penicillium chrysogenum, the antifungal activity of W. cibaria BYL4.2 against P. chrysogenum was evaluated by the superposition method, results showed that it had obviously antifungal activity against P. chrysogenum. Studying the probiotic properties of BYL4.2 and determining it as beneficial bacteria. Furtherly, different treatments were carried out to characterize the antifungal activity of cell-free supernatant (CFS) produced by W. cibaria BYL4.2, and it was shown that the CFS was pH-dependent, partly heat-sensitive, and was not influenced by proteinaceous treatment. The CFS of W. cibaria BYL4.2 was analyzed by high-performance liquid chromatography (HPLC) and found the highest content of lactic acid. Screening of metabolic markers by a non-targeted metabolomics approach based liquid chromatography-mass spectrometry (LC-MS). The results speculated that organic acid especially detected D-tartaric acid was the main antifungal substance of CFS, which could cause the down-regulation of metabolites in the ABC transporters pathway, thereby inhibiting the growth of P. chrysogenum. Therefore, this study may provide important information for the inhibitory mechanism of W. cibaria BYL4.2 on P. chrysogenum, and provide a basis for further research on the antifungal effect of Weissella.

Keywords: LAB; Penicillium chrysogenum; Weissella cibaria; antifungal effect; metabolome.

FIGURE 1

Identification and screening of antifungal LAB. The colony picture (A) and microscopic picture (×1,000) (B) of LAB isolates. Inhibition of Penicillium chrysogenum by Weissella cibaria BYL4.2 by agar overlay method after 3 day incubation at 28°C. Control P. chrysogenum (C). W. cibaria BYL4.2 (D) overlaid by P. chrysogenum. Phylogenetic tree analysis of W. cibaria BYL4.2 using the neighbor-joining algorithm. The numbers above the branches are confidence limits expressed as percentages. The scale bar represents 0.05% sequence divergence (E). Growth kinetics (square) and acidification profile (circle) of W. cibaria BYL4.2 in MRS broth at 37°C for 24 h (F).

FIGURE 2

Effects of Weissella cibaria BYL4.2-CFS on the antifungal activity of Penicillium chrysogenum. Antifungal activity of BYL4.2-CFS in agar diffusion assay (the front and back) (A). Antifungal effect after heat treatment (a), acid treatment (b) and protease action (c), and untreated W. cibaria BYL4.2-CFS as a control (B). Data are means ± SDs; *p ≤ 0.05 and ***p ≤ 0.001.

FIGURE 3

The score scatter plot of principal component analysis (PCA). PDB and Weissella cibaria BYL4.2-CFS + PDB of positive ion mode (A) and negative ion mode (B) and Penicillium chrysogenum and W. cibaria BYL4.2-CFS + P. chrysogenum of positive ion mode (C) and negative ion mode (D). PDB, PDB; PDB_L, W. cibaria BYL4.2-CFS + PDB; P, P. chrysogenum; L_P, W. cibaria BYL4.2-CFS + P. chrysogenum.

FIGURE 4

Validation of partial least squares discriminant analysis (PLS-DA) models. Pairwise comparation of among PDB, PDB_L, L_P, and P in positive ion mode (A,C,E,G) and negative ion mode (B,D,F,H).

FIGURE 5

Venn diagrams of positive (A,C) and negative (B,D) ion modes of differential metabolites in PDB_L vs. PDB and L_P vs. P groups.

FIGURE 6

Volcano plot of differential metabolites and classification of the Human Metabolome Database (HMDB) compounds. (A,C) PDB_L vs. PDB groups; (B,D) L_P vs. P groups, red is up-regulation, blue is down-regulation (FC > 1.2 or <1.2, p < 0.05).

FIGURE 7

Comparison of the relative abundance of metabolites in PDB_L vs. PDB groups (A) and in L_P vs. P groups (B). Levels of significance are defined as **p < 0.01 and ***p < 0.001.

FIGURE 8

Differential metabolites involved in each metabolic pathway and the number of metabolites. The 20 most abundant metabolic pathways enriched by KEGG (A,C) PDB_L vs. PDB groups; (B,D) L_P vs. P groups.