Comparative genomic analysis of 255 Oenococcus oeni isolates from China: unveiling strain diversity and genotype-phenotype associations of acid resistance

Abstract

Oenococcus oeni, the only species of lactic acid bacteria capable of fully completing malolactic fermentation under challenging wine conditions, continues to intrigue researchers owing to its remarkable adaptability, particularly in combating acid stress. However, the mechanism underlying its superior adaptation to wine stresses still remains elusive due to the lack of viable genetic manipulation tools for this species. In this study, we conducted genomic sequencing and acid resistance phenotype analysis of 255 O. oeni isolates derived from diverse wine regions across China, aiming to elucidate their strain diversity and genotype-phenotype associations of acid resistance through comparative genomics. A significant correlation between phenotypes and evolutionary relationships was observed. Notably, phylogroup B predominantly consisted of acid-resistant isolates, primarily originating from Shandong and Shaanxi wine regions. Furthermore, we uncovered a noteworthy linkage between prophage genomic islands and acid resistance phenotype. Using genome-wide association studies, we identified key genes correlated with acid resistance, primarily involved in carbohydrates and amino acid metabolism processes. This study offers profound insights into the genetic diversity and genetic basis underlying adaptation mechanisms to acid stress in O. oeni.IMPORTANCEThis study provides valuable insights into the genetic basis of acid resistance in Oenococcus oeni, a key lactic acid bacterium in winemaking. By analyzing 255 isolates from diverse wine regions in China, we identified significant correlations between strain diversity, genomic islands, and acid resistance phenotypes. Our findings reveal that certain prophage-related genomic islands and specific genes are closely linked to acid resistance, offering a deeper understanding of how O. oeni adapts to acidic environments. These discoveries not only advance our knowledge of microbial stress responses but also pave the way for selecting and engineering acid-resistant strains, enhancing malolactic fermentation efficiency and wine quality. This research underscores the importance of genomics in improving winemaking practices and addressing challenges posed by high-acidity wines.

Keywords: genome-wide association study; genomic island; horizontal gene transfer; lactic acid bacteria; pan-genome.

Fig 1

Genomic characterization and functional annotation of O. oeni. (a) Boxplot illustrating the GC content (%) of O. oeni genomes across various provinces of China. Significant differences in GC content were observed between isolates from different provinces (P < 0.05, Kruskal-Wallis test). Pairwise comparisons indicated the following significance levels: *P < 0.05; **P < 0.01; ***P < 0.001 (Wilcoxon tests). Only significant results are presented in the figure. (b) Fan chart depicting the distribution of pan-genomic genes among 255 O. oeni isolates. (c) Functional annotation of the pan-genome utilizing the COG database. Pan-genome genes are categorized into four groups: information processing and storage, cellular processing and signaling, metabolism, and poorly characterized.

Fig 2

Strain diversity analysis of O. oeni using diverse methodologies. (a) Phylogenetic tree constructed from 300 strains, including 45 strains (highlighted with shaded labels) randomly selected from the data set of Lorentzen et al. , representing all four phylogroups. The strains shaded in red, blue, green, and gold correspond to phylogroups A, B, C, and D, respectively. The 255 isolates analyzed in this study are classified into either phylogroup A or B. (b) Results of PopPUNK analysis based on genome-wide variable length k-mers.

Fig 3

(a) Forest plot showing the correlation between acid resistance phenotype and variables such as strain diversity, isolation regions, and genomic islands. The points represent the odds ratio (OR) of each variable, with horizontal lines indicating the 95% confidence intervals; the vertical dashed line (x = 1) indicates no correlation, and the deviation of OR from 1 reflects the strength of the association (OR > 1 for positive correlation, OR < 1 for negative correlation). Statistical significance is indicated as follows: ns, P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001 (chi-square tests). (b) Distribution of MLST and PopPUNK results within phylogroups. Concentric rings from innermost to outermost represent MLST, PopPUNK, and phylogroups. (c) Distribution of isolation regions and genomic islands within phylogroups. Concentric rings from innermost to outermost represent isolation regions, genomic islands, and phylogroups.

Fig 4

Synteny analysis of genomic islands. The lines connecting the different genomic islands represent homologous genes, with the color of the lines indicating the level of similarity between the homologous genomes. The numbers below the genomic island names represent the length of each genomic island.

Fig 5

Functional annotation results of genes associated with acid resistance identified by GWAS. (a) Fan chart and (b) bar graph displaying COG annotations for genes in phylogroup A. (c) Fan chart and (d) bar graph illustrating COG annotations for genes in phylogroup B. (e) KEGG pathway enrichment analysis of candidate genes from phylogroups A and B presented in a dot plot. The x-axis represents the gene ratio (the ratio of genes in a pathway to the total number of genes analyzed), and the y-axis lists the significantly enriched KEGG pathways. The size of the dots corresponds to the number of genes involved in each pathway, and the color reflects the level of statistical significance. (f) Genes significantly associated with acid resistance are shared within phylogroups A and B. The presence or absence of genes within different isolates is indicated by solid and hollow symbols, respectively. The different colors of branches represent the different phylogroups, from left to right: phylogroups A2, B1, B2, and A1.