The interactions between plants and rhizosphere microbes mediated by plant root exudates are increasingly being investigated. The root-derived metabolites of medicinal plants are relatively diverse and have unique characteristics. However, whether medicinal plants influence their rhizosphere microbial community remains unknown. How medicinal plant species drive rhizosphere microbial community changes should be clarified. In this study involving high-throughput sequencing of rhizosphere microbes and an analysis of root exudates using a gas chromatograph coupled with a time-of-flight mass spectrometer, we revealed that the root exudate metabolites and microorganisms differed among the rhizosphere soils of five medicinal plants. Moreover, the results of a correlation analysis indicated that bacterial and fungal profiles in the rhizosphere soils of the five medicinal plants were extremely significantly or significantly affected by 10 root-associated metabolites. Furthermore, among the 10 root exudate metabolites, two (carvone and zymosterol) had opposite effects on rhizosphere bacteria and fungi. Our study findings suggest that plant-derived exudates modulate changes to rhizosphere microbial communities.

This study investigates the interplay between volatile and non-volatile flavor metabolites and endophytic microbial communities during three developmental stages of Passiflora ligularis fruit juice. Using bioinformatics and metabolomics, we characterize microbial diversity and metabolic variations to understand flavor development. A total of 1490 bacterial and 1158 fungal operational taxonomic units (OTUs) were identified. Young fruits had higher microbial diversity, dominated by Proteobacteria and Firmicutes (bacteria) and Ascomycota and Basidiomycota (fungi). As the fruit matured, Proteobacteria increased while Firmicutes decreased, indicating that microbial succession is tied to development. Metabolomic profiling identified 87 volatile and 1002 non-volatile metabolites, with distinct chemical classes varying across stages. Saturated hydrocarbons and fatty alcohols were the main volatile metabolites, while organic acids and lipids among non-volatile metabolites showed stage-dependent changes, influencing flavor complexity. Correlation analysis showed microbial-flavor interactions: Proteobacteria negatively correlated with metabolites, while Firmicutes positively correlated with metabolites. Ascomycota positively correlated with volatile metabolites, whereas Basidiomycota showed an inverse relationship, highlighting their differential contributions to flavor biosynthesis. This study enhances understanding of microbial and metabolic factors shaping P. ligularis fruit flavor, highlighting the importance of microbial influence on fruit metabolomics. The findings suggest the potential for microbiome engineering to improve flavor quality, aiding postharvest management and industrial processing in the food and beverage industry.

The quality of Coffee arabica L. beans, particularly the aroma, is a key determinant of commercial value. Fatty acids, as precursors of volatile aroma compounds, play a crucial role in this quality. Screening and identification of their related genes are of particular significance. This study identified 21 members of the CaFAD gene family in the C. arabica genome using bioinformatics tools. Gene duplication events observed in the CaFAD gene family were likely driven by natural selection and mutation pressure, with natural selection being more prominent. Transcriptome sequencing, qRT-PCR, and fatty acid profiling across four fruit developmental stages revealed that CaFAD8 was closely associated with fatty acid synthesis regulation. Fatty acid content was initially high but decreased during the later stages, while CaFAD8 expression showed an inverse pattern. Subcellular localization indicated that CaFAD8 functions primarily on the inner membrane. CaFAD8-OE heterologous expression experiment in Arabidopsis thaliana reduced the total fatty acid content in seeds but increased unsaturated fatty acids, including oleic, linoleic, and linolenic acids. These findings suggest that CaFAD8 promotes fatty acid unsaturation and provides insights into fatty acid metabolism in C. arabica. This study offers a foundation for understanding CaFAD gene regulation and supports breeding strategies for high-oil C. arabica varieties.

The genetic relationships between Coffea arabica resources were analyzed via specific length amplified fragment sequencing (SLAF-seq) and transcriptome sequencing to provide the theoretical basis for breeding new varieties. Twenty C. arabica accessions were used to analyze genetic diversity on the basis of SNPs identified in SLAFs and the transcriptome data. For the SLAF-seq analysis of 20 C. arabica accessions, two Coffea canephora accessions, one Coffea liberica accession, and one Coffea racemosa accession, the number of reads ranged from 2,665,424 to 7,210,310, with a GC content of 38.49%–40.91% and a Q30 value of 94.99%–96.36%. A total of 3,347,069 SLAF tags were obtained, with an average sequencing depth of 13.90×. Moreover, the 1,048,575 SNPs identified in the polymorphic SLAFs were filtered, then the remaining 198,955 SNPs were used to construct a phylogenetic tree, perform a principal component analysis, and characterize the population structure. For the transcriptome analysis, 128.50 Gb clean reads were generated for the 20 C. arabica accessions, with a GC content of 44.36%–51.09% and a Q30 value of 94.55%–95.40%. Furthermore, 25,872 genes’ expression levels were used for the correlation analysis. The phylogenetic relationships as well as the results of the principal component analysis, population structure analysis, and correlation analysis clearly distinguished C. arabica Typica-type accessions from the C. arabica Bourbon-type accessions. Notably, several C. arabica local selections with unknown genetic backgrounds were classified according to all four clustering results.