Flavonoids are a diverse class of plant polyphenols with essential roles in development, defense, and environmental adaptation, as well as significant applications in medicine, nutrition, and cosmetics. However, their naturally low abundance in plant tissues poses a major barrier to large-scale utilization. This review provides a comprehensive and forward-looking synthesis of flavonoid biosynthesis, regulation, transport, and yield enhancement strategies. We highlight key advances in understanding transcriptional and epigenetic control of flavonoid pathways, focusing on the roles of MYB, bHLH, and WD40 transcription factors and chromatin modifications. We also examine flavonoid transport mechanisms at cellular and tissue levels, supported by emerging spatial metabolomics data. Distinct from conventional reviews, this review explores how plant cell factories, genome editing, environmental optimization, and artificial intelligence (AI)-driven metabolic engineering can be integrated to boost flavonoid production. By bridging foundational plant science with synthetic biology and digital tools, this review outlines a novel roadmap for sustainable, high-yield flavonoid production with broad relevance to both research and industry.

Modern agriculture has gained significant economic benefits worldwide with the use of genetically modified (GM) technologies. While GM crops provide convenience to humans, their biosafety has attracted increasing concern. In this study, the Illumina MiSeq was used to perform a high-throughput sequencing of the V3-V4 hypervariable regions of 16S rRNA gene (16S rDNA) amplicons to compare the rhizosphere bacterial communities of the EPSPS/GAT dual transgenic glyphosate-tolerant soybean line Z106, its recipient variety ZH10, and Z106 with glyphosate application (Z106G) during flowering, seed filling, and maturing stages under field settings. At each of the three stages, the alpha and beta diversity of rhizosphere bacterial communities revealed no significant differences between ZH10, Z106, and Z106G. However, some bacterial taxa demonstrated a greater proportional contribution, particularly the nitrogen-fixing rhizobium Ensifer fredii, in the rhizospheric soil of Z106 at the seed filling and maturing stages, when compared to ZH10 and Z106G. The present study therefore suggests that the EPSPS/GAT dual transgenic line Z106 and exogenous glyphosate application have a minimal effect on the composition of the soybean rhizosphere bacterial community but have no impact on the structure of the rhizosphere microbial community during a single planting season.

Rare earth element (REE) mining exerts profound impacts on aquatic ecosystems, yet the microbial community responses and water quality under such stress remain underexplored. In this study, the surface (0.2 m) and subsurface (1.0 m) water along a spatial transect from proximal to distal points was investigated in a REE-mining area of Ganzhou, China. Physicochemical analyses revealed pronounced gradients of nitrogen (e.g., NH₄⁺−N, NO₃⁻−N), heavy metals (e.g., Mn, Zn, Pb), and REEs (e.g., La, Nd, Ce), with higher accumulation near mining sources and partial attenuation downstream. Dissolved oxygen and redox potential indicated mildly reducing conditions at contaminated points, potentially promoting denitrification and altering nitrogen cycling. Metagenomic sequencing showed significant shifts in microbial community composition, with enrichment of metal- and nitrogen-tolerant taxa, and key denitrifiers (e.g., Acidovorax, Bradyrhizobium, Rhodanobacter), particularly at upstream polluted points. KEGG-based gene annotation highlighted dynamic nitrogen transformations mediated by multiple pathways, including nitrification, denitrification, dissimilatory nitrate reduction to ammonium, and nitrogen fixation. Notably, genes associated with nitrite and nitrate reduction (e.g., nir, nar, nrf) were enriched near mining sources, indicating enhanced nitrogen conversion potential, while downstream activation of nitrogen-fixing genes suggested partial ecosystem recovery. Meanwhile, some microbial such as Variovorax carried metal tolerant genes (e.g., ars, chr, cnr). These findings demonstrate that REE and heavy metal contamination restructure microbial networks, modulate nitrogen cycling, and create localized ecological stress gradients. This study provides a comprehensive assessment of mining-related water pollution, microbial responses, and ecological risks, offering valuable insights for monitoring, restoration, and sustainable management of REE-impacted aquatic environments.

Acid rain can lower the pH of groundwater and affect its hydrogeochemistry and microbial ecology. However, the effects of acid rain on the hydrogeochemistry and microbial ecology of red soil groundwater systems in southern China are poorly understood. Previous research had mainly investigated the sources and patterns of groundwater acidification, but not the microbial mechanisms that contribute to this process and their associations with hydrochemical factors. To address this knowledge gap, we conducted a soil column experiment to simulate the infiltration of acid rain through various filter materials (coarse, medium, and fine sand) and to examine the hydrochemical and microbial features of the infiltrate, which can reveal how simulated acid rain (pH 3.5–7.0) alters the hydrochemistry and microbial community composition in red soil aquifers. The results showed that the pH of the leachate decreased due to simulated acid rain, and that the leaching efficiency of nitrogen and metal ions was influenced by the particle size of the filter media. Illumina 16S rRNA gene sequencing revealed that the leachate was dominated by Proteobacteria, Patescibacteria, Actinobacteria, and Acidobacteria, with Proteobacteria accounting for 67.04–74.69% of the bacterial community and containing a high proportion of nitrifying and denitrifying bacteria. Additionally, several genera with heavy metal tolerance, such as Burkholderia-Caballeronia-Paraburkholderia, Delftia, Methylversatilis, Aquicella, and Ralstonia, were widely distributed in the leachate, indicating the strong adaptive capacity of the microbial population. A correlation analysis between the hydrochemical factors and the microbial community structure revealed that pH was the most influential factor, followed by NO₂ ⁻-N, Fe, Al, Cu, Mn, and others. These results indicate that acidification modifies the hydrochemical conditions of the aquifer, creating an environment that is unfavorable for microbial growth and survival. However, some microorganisms may acquire resistance genes to cope with environmental changes.

Engineered phytoremediation strategies provide cost effective options for eliminating antibiotics and antibiotic resistance genes (ARGs) from wastewater. However, there is a knowledge gap in understanding the impact of these phytoremediation strategies on the on the diversity and composition of ARGs as well as the key driving biotic and biological factors of ARGs at the metagenomic level in real scenarios. Through metagenomic sequencing, this study demonstrates that phytoremediation with Iris pseudacorus L., Myriophyllum verticillatum L., Eichhornia crassipes (Mart.) Solms and Oenanthe javanica (Bl. DC) significantly alters the pattern of antibiotic resistome. This study is the first to reveal, at the omics level, that phytoremediation enhances the diversity of ARGs (3.2 %∼11.6 % improvement), despite reducing their absolute abundances. Furthermore, this study highlights that plant varieties have a significant impact on the performance of phytoremediation in mitigating ARGs. The non-dominant bacterial taxa, specifically Verrucomicrobia, Planctomycetes, and Actinobacteria, play a crucial role in shaping the pattern of the antibiotic resistome during the wastewater treatment. The changes in the total organic carbon, total nitrogen and antibiotics robustly influence the environmental behaviors of antibiotic resistome and microbiome. In summary, this study gives insight into the impact of different phytoremediation strategies on mitigating ARGs at the omics level in real scenarios.