LBP is constituted of six saccharides of α-(1→4)-GalA, α-(1→6)-Glc, β-(1→3)-Galp, β-(1→6)-Galp, α-(1→5) -Ara, and β-(1→4)–Galp. Enzymatic selectivity is essential to combine the diverse saccharides into LBP. After the glycosidic bond is formed, the stereochemistry of LBP can be retained or reversed by glycosyltransferases [34,35,36]. In fact, multiple metabolic pathways might participate in LBP biosynthesis in goji berry, including the galactose metabolism pathway, tricarboxylic acid cycle, glyoxylic acid cycle, propionic acid metabolism, amino sugars metabolism, starch metabolism, and sucrose metabolism. These pathways provide precursors for the anabolism of various carbohydrates [37,38]. Among these pathways, sucrose synthetic pathway is mainly responsible for plant cell wall formation and biomass accumulation. Sucrose phosphate synthase (SPS) and sucrose phosphate phosphatase (SPP) are the two essential enzymes in sucrose biosynthesis [39]. In addition, the acid invertase (AI), sucrose synthase (SS), and SPS involved in sucrose metabolism are the key enzymes of the plant carbon metabolic pathway [40]. Sucrose synthesis is closely associated with the metabolism of amino sugar, nucleotide sugar, and galactose [41]. The fruits of goji berry mainly synthesize glucose and fructose, and the LBP content is mainly determined by fructose content in goji fruits.

The α-galactosidase (GALA) participates in several steps of galactose metabolism. These carbohydrate anabolic pathways are the prerequisite for LBP synthesis, and they can regulate carbohydrate accumulation. UDP-glucose pyrophosphorylase (UGP) is an essential enzyme involved in carbohydrate metabolism, which can affect normal cell development, polysaccharide synthesis, and stress response in S. cerevisiae and other fungi [42,43]. The key enzymes in the LBP synthetic pathway, UDP-glucuronate 4-epimerase (GAE), malate synthase (MS), and α-galactosidase (GALA), have not been characterized yet [37]. These key genes play important roles in the synthesis of LBP, and the information might be obtained by analyzing the transcriptome of goji berry (Figure 1).

The transcriptome of goji berry can help recover genes in the LBP biosynthetic pathway. Several studies about transcriptome of goji berry have been applied. Wang et al. prepared the leaf transcriptome of goji berry and elucidated the mechanisms of carotenoid biosynthesis in goji berry [44]. Chen et al. obtained 139,333 predicted genes of goji berry, and they identified genes in the flavonoid and taurine biosynthetic pathways [45]. Ma et al. analyzed the transcriptome of goji berry and identified the candidate genes involved in sugar metabolism under elevated CO₂, which helped recover the LBP biosynthetic pathway [37]. However, current omics data in public databases have not recovered the whole LBP biosynthetic pathway in goji berry.

To explore the key enzymes in the LBP biosynthetic pathway, collecting fresh tissues of goji berry at different growth phases and different planting areas are necessary. Sequencing of these fresh tissues would give an array of transcriptome data, and de novo assembly of these data would obtain full gene profiles of goji berry. Further transcriptome comparison analysis would give insights into the details of the LBP biosynthetic pathway (Figure 2). To predict the key enzymes in LBP synthetic pathways, phylogenetic, gene similarity network analysis, and other bioinformatic methods can be used to identify the candidate key genes [46]. Diverse glycosyltransferase genes were identified from public omics data by using phylogenetic analyses and plant secondary product glycosyltransferase (PSPG) homolog [28,29,30]. Thus, finding homologous in goji genomes is possible to predict potential glycosyltransferases for LBP synthesis. As the sugar metabolic pathway is complex, characterizing candidate LBP synthetic genes identified with bioinformatic strategies will help identify efficient enzymes for LBP biosynthesis in engineered yeasts.

The glycosyltransferases can determine saccharide compositions and arrangements of the LBP. The bioinformatic strategy was used for the recovery of glycosyltransferases functioned in ginsenoside biosynthesis. The omics data in the public database were downloaded and assembled. The open reading frames (ORFs) were predicted and annotated with the help of CAZy and other databases. The candidate glycosyltransferase genes were selected for sequence alignment. Only predicted glycosyltransferase genes with more than 1320 bp and PSPG motif were used for further analysis. The glycosyltransferase genes were clustered based on the similarity, in order to reduce the redundancy. Besides, gene expression level can be determined at different growth stages, which can help identify real glycosyltransferase genes. The identified potential glycosyltransferase genes for ginsenosides were selected for expression. The enzymatic characterization of the glycosyltransferases was identified (Figure 2), and the characterized glycosyltransferases were used for adding activated sugars to the substrates [28,29,30,31]. Recently, another two cellulose synthases were identified to function as glycosyltransferases in saponin biosynthesis [47,48], showing identification of glycosyltransferases for LBP synthesis is complex. Nowadays, the use of gene similarity and network analysis have been widely used for gene identification [46].