Medicinal Plant Research 2025, Vol.15, No.5, 206-213 http://hortherbpublisher.com/index.php/mpr 211 in synthetic biology tools, gene cluster discovery, and regulatory network modeling will propel translation of L. japonicus metabolic engineering from laboratory to industry (Choi et al., 2019; García-Granados et al., 2019; Ng et al., 2020; Bharadwaj et al., 2021). 7 Research Challenges and Limitations 7.1 Unresolved key steps in metabolic pathway elucidation Despite significant progress in the elucidation of alkaloid, flavonoid, polysaccharide, and other specialized metabolite biosynthesis pathways, many of the crucial enzymatic steps remain poorly characterized. The comprehensive catalytic mechanisms, substrate specificity, and tissue- or developmental-stage-selective expression of such critical enzymes remain largely unknown, preventing full understanding of metabolite formation (Wei et al., 2023). 7.2 Insufficient systematic identification of functional genes and regulatory factors Although transcriptomic and genomic studies have discovered large numbers of candidate genes, systematic verification of functional genes and regulatory factors such as transcriptional factors and signaling components is not yet sufficient. It limits the possibilities to build full regulatory networks for the biosynthesis of active compounds in L. japonicus (Lee et al., 2020). 7.3 Technical limitations and constraints in experimental systems Technical issues, such as low-quality or availability of high-quality reference genomes, inefficient transformation, and variable in vivo or in vitro systems, make functional analyses difficult. Furthermore, the nature of metabolite profiling and multi-omics integration challenges pathway resolution and reproducibility (Birchfield and McIntosh, 2020; Zhang et al., 2023). 7.4 Gap between basic research and applied translation Though basic research has enhanced understanding of biosynthesis of active metabolites, implementation of such insights into practical practices—e.g., metabolic engineering, high-yield large-scale cultivation, or mass production—remains to be fully achieved. Needed to promote laboratory-to-industry translation are enhanced gene function validation, pathway optimization, and scalable manufacturing technologies. 8 Concluding Remarks Over the past few years, notable progress has been made in elucidating the biosynthetic pathways of the valuable bioactive metabolites of L. japonicus var. tongzi, including alkaloids, flavonoids, polysaccharides, and other special metabolites. Genomics sequencing, transcriptomics, proteomics, and metabolomics jointly disclosed a huge number of functional genes, biosynthetic enzymes, and regulatory factors, and it is easier nowadays to imagine the complex networks of active compound biosynthesis. These studies have enhanced tissue-specific expression, pathway regulation, and metabolite accumulation profile knowledge and offer a foundation for basic and applied research. Genomic data has been identified to be central for the facilitation of sustainable exploitation of L. japonicus var. tongzi resources. They enable the identification of useful functional genes, contribute to targeted breeding or metabolic engineering projects, and facilitate precision agriculture for improved active compound production. Integration of genomic data with multi-omics tools maximizes the molecular mechanism-to-application link and offers new opportunities for resource maximization and medicinal product development. The combination of synthetic biology and multi-omics approaches will likely encompass more understanding and rational regulation of metabolite biosynthesis. Network-scale investigation, pathway reconstruction, and heterologous expression systems might possibly ensure high-efficiency production of valuable compounds, including research using laboratory setting and application to industry. These approaches will not merely enhance present knowledge on L. japonicus var. tongzi metabolism but also accelerate its modernization, sustainable utilization, and its application in evidence-based medicine.
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