Abstract
Mycosporine-like amino acids (MAAs) are ultraviolet-absorbing metabolites with recognized photoprotective and pharmacological benefits, predominantly found in marine organisms. Due to the inefficiency of extraction from natural sources, microbial biosynthesis using heterologous hosts is an attractive alternative. Disubstituted MAAs, such as shinorine, porphyra-334, and mycosporine-2-glycine, are synthesized by conjugating serine, threonine, or glycine to mycosporine-glycine (MG), a reaction catalyzed by either a d-Ala-d-Ala ligase homolog (MysD) or a nonribosomal peptide synthetase (MysE). While MysD enzymes often yield diverse byproducts due to substrate promiscuity, MysE demonstrates higher substrate specificity; however, only a serine-specific MysE has been biochemically characterized. In this study, we enhanced shinorine production in by expressing Anabaena variabilis mysE (Av.mysE). Functional expression required coexpression of a phosphopantetheinyl transferase (PPTase), which was absent in but native to . The A. variabilis PPTase supported the MysE activity in both hosts. Furthermore, we engineered the MysE adenylation domain to alter specificity from serine to alanine, enabling de novo biosynthesis of MG-alanine, a rare MAA previously detected only as a minor MysD byproduct. These findings demonstrate the utility of MysE engineering for expanding MAA diversity and advancing the sustainable microbial production of novel sunscreen compounds.
Keywords: mycosporine-glycine-alanine, MysE, nonribosomal peptide synthetase (NRPS), shinorine, phosphopantetheinyl transferase (PPTase), Yarrowia lipolytica

1. Introduction
Mycosporine-like amino acids (MAAs) represent a class of compounds containing a cyclohexene-imine ring structure, derived from a variety of organisms, including cyanobacteria, algae, phytoplanktons, and corals. − Initially acknowledged for their role as natural sunscreens, MAAs effectively absorb ultraviolet (UV) radiation across both the UVA and UVB spectra, with peak absorption occurring between 310 and 360 nm. Beyond their photoprotective properties, MAAs exhibit antioxidant and anti-inflammatory potential, which might be useful for functional food, cosmetics, and pharmaceutical applications.
MAAs are synthesized through a series of enzymatic reactions that begin with sedoheptulose 7-phosphate (S7P), an intermediate of the pentose phosphate pathway (Figure A). S7P is converted to demethyl-4-deoxygadusol (DDG) by DDGS synthase (DDGS), then methylated to result in 4-deoxygadusol (4-DG) by O-methyltransferase (O-MT). Subsequently, an ATP-grasp enzyme facilitates the attachment of glycine at the C3 position of the 4-DG, leading to the formation of mycosporine-glycine (MG). Finally, an additional amino acid is attached at the C1 position of the MG by either d-Ala-d-Ala ligase homologue or nonribosomal peptide synthetase (NRPS), resulting in the synthesis of various MAAs such as shinorine (MG-serine), porphyra-334 (MG-threonine), and mycosporine-2-glycine (M2G). In prokaryotes, such as cyanobacteria, the genes involved in MAA biosynthesis are organized into biosynthetic gene clusters (Figure B). These genes are typically named as mysA (encoding DDGS), mysB (O-MT), mysC (ATP-grasp enzyme), mysD (d-Ala-d-Ala ligase homologue), and mysE (NRPS). The biosynthetic gene clusters often contain genes involved in the further diversification of MAA structures. For instance, MysH in Nostoc linckia NIES-25 transforms shinorine and porphyra-334 into their corresponding palythines via oxidative decarboxylation at the C3 glycyl moiety. Additionally, the biosynthesis of more complex MAAs, such as aplysiapalythine E, has been proposed. This is based on discontinuous biosynthetic gene clusters found in Nostoc sp. UHCC 0926, including MysIa homologue of MysHand MysF, which is thought to methylate the C3 amino group of palythine.
1.

Metabolic pathways and biosynthetic gene clusters for MAAs. (A) MAAs are synthesized from S7P, an intermediate of the pentose phosphate pathway. Various MAAs are produced by attaching different amino acids to MG, facilitated by the d-Ala-d-Ala ligase (MysD) or NRPS (MysE) enzymes from the strains depicted in section (B). (B) The biosynthetic gene clusters for MAAs. DDG, Demethyl-4-deoxygadusol; DDGS, DDG synthase; 4-DG, 4-deoxygadusol; MG, mycosporine glycine; NRPS, nonribosomal peptide synthetase; O-MT, O-methyltransferase; S7P, sedoheptulose 7-phosphate.
d-Ala-d-Ala ligase homologue (MysD) and NRPS (MysE) play pivotal roles in the biosynthesis of MAAs, each with distinctive characteristics and limitations. MysD enzymes have diverse substrate specificity, attaching various amino acids to MG. For example, MysDs from Nostoc punctiforme, N. linckia, and Aphanothece halophytica exhibit serine, threonine, and glycine specificity, yielding shinorine, porphyra-334, and M2G, respectively (Figure A). ,, However, the low substrate specificity of MysD leads to the generation of various MAA byproducts, which poses a significant drawback. On the other hand, MysE exhibits high specificity toward serine, producing shinorine exclusively without any byproducts. Nonetheless, the potential of MysE to exhibit specificity beyond serine is still largely unexplored. To date, serine-specific mysE genes derived from Anabaena variabilis and Fischerella sp. PCC 9339 were functionally characterized (Figure B). More recently, a glycine-specific MysE was identified in Nostoc sp. UHCC 0926, although its catalytic activity has not yet been biochemically confirmed.
Traditional methods for the mass production of MAAs have primarily relied on extracting them from the algae . However, these methods are inefficient due to the low MAA content. Therefore, using heterologous hosts such as bacteria or yeasts for producing MAAs is viewed as a promising alternative. − In our previous work, we engineered yeast strains, and to produce a range of MAAs, such as shinorine, phorphyra-334, and M2G, by expressing mysDs with varying substrate specificity. , We demonstrated that the addition of xylose as a cosubstrate alongside glucose effectively enhances MAA production, especially in . This enhancement is attributed to the increased S7P pool, resulting from the utilization of xylose via the pentose phosphate pathway.
However, employing mysD led to the generation of byproducts due to the substrate promiscuity of MysD. In contrast, expressing mysE from A. variabilis (Av.mysE) in achieved the exclusive synthesis of shinorine, although the total MAA production levels were lower than those using mysD from N. punctiforme. Recently, Av.mysE was also successfully expressed in the bacterial host to produce shinorine. It is noteworthy that Av.mysE did not exhibit functional expression in , suggesting that a bacterial host or might be more suitable for expressing mysE.
In this study, we enhanced the activity or altered the substrate specificity of MysE to facilitate its use in MAA production. We found that phosphopantetheinyl transferase (PPTase), which is crucial for MysE functionality, affects the MysE activity in heterologous hosts. This influence is particularly notable in , where this enzyme is absent. To overcome the substrate specificity limitations of MysE, an enzyme engineering approach was employed, resulting in a mutant MysE capable of producing a rare MAA, MG-alanine. These results demonstrate the potential of engineered yeast strains for the enhanced biosynthesis of various MAAs for use as biobased sunscreen.
2. Materials and Methods
2.1. Strains and Culture Conditions
The strains utilized in this investigation are outlined in Table . strains derived from PO1f strain were cultured in YP medium (10 g/L yeast extract and 20 g/L bactopeptone) with 20 g/L glucose. strains were cultured in YP medium with 10 g/L glucose and 10 g/L xylose. Cells were cultured in 5 mL of medium within 50 mL Erlenmeyer flasks for the first inoculation. Precultured cells were then transferred to 10 mL of medium in 100 mL Erlenmeyer flasks to OD600 of 0.5. The cells were cultivated at 30 °C, with shaking at 170 rpm, for 120 h.
1. Strains Used in This Study.
| Strain | Genotype | Reference |
|---|---|---|
| JHYM0 | PO1f ku70Δ | This study |
| JHYM100 | JHYM0 C3:P UAS1B8‑TEF(136) -Av.mysA-T CYC1 -P UAS1B8‑TEF(136) -Av.mysB-T CYC1 -P UAS1B8‑TEF(136) -Av.mysC-T CYC1 -loxP | This study |
| JHYM110 | JHYM100 A1:P UAS1B8‑TEF(136) -Av.mysE-T CYC1 -loxP | This study |
| JHYM101 | JHYM100 B:P UAS1B8‑TEF(136) -Av.pptA-T CYC1 -loxP | This study |
| JHYM111 | JHYM110 B:P UAS1B8‑TEF(136) - Av.pptA-T CYC1 -loxP | This study |
| JHYM120 | JHYM100 A1:P UAS1B8‑TEF(136) -Np.mysD-T CYC1 -lox72 | This study |
| JHYM130 | JHYM100 A1: P UAS1B8‑TEF(136) -Nl.mysD-T CYC1 -lox72 | This study |
| JHYM111V223F | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE V223F-T CYC1 | This study |
| JHYM111S292G | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE S292G-T CYC1 | This study |
| JHYM111D324H | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE D324H-T CYC1 | This study |
| JHYM111D324G | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE D324G-T CYC1 | This study |
| JHYM111D324L | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE D324L-T CYC1 | This study |
| JHYM111D324W | JHYM101 axp1::P UAS1B8‑TEF(136) -Av.mysE D324W-T CYC1 | This study |
| JHYM211 | JHYM111 E3:P UAS1B8‑TEF(136) -Av.mysA-T CYC1 - P UAS1B8‑TEF(136) -Av.mysB-T CYC1 -P UAS1B8‑TEF(136) -Av.mysC-T CYC1 | This study |
| JHYM311 | JHYM211 F3:P UAS1B8‑TEF(136) -Av.mysA-T CYC1 - P UAS1B8‑TEF(136) -Av.mysB-T CYC1 -P UAS1B8‑TEF(136) -Av.mysC-T CYC1 | This study |
| JHYM411 | JHYM311 D1:P UAS1B8‑TEF(136) -Av.mysA-T CYC1 - P UAS1B8‑TEF(136) -Av.mysB-T CYC1 -P UAS1B8‑TEF(136) -Av.mysC-T CYC1 | This study |
| JHYM511 | JHYM411 axp1::P UAS1B8‑TEF(136) -Av.mysA-T CYC1 - P UAS1B8‑TEF(136) -Av.mysB-T CYC1 -P UAS1B8‑TEF(136) -Av.mysC-T CYC1 | This study |
| JHYM421 | JHYM411 axp1::P UAS1B8‑TEF(136) -Av.mysE-T CYC1 | This study |
| JHSM13 | CEN.PK2–1C HIS3::P TDH3 -XYL1-T CYC1 -P TEF1 -XYL2-T GPM1 -P TPI1 -XYL3-T TPI1 hxk2::P TDH3 -Av.MysA-T CYC1 tal1::loxP- P TDH3 -Av.MysA-T CYC1 Delta integration of P TDH3 -Np.mysA-T CYC1 and P TEF1 -Np.mysC-T GPM1 -P TDH3 -Np.mysB-T CYC1 | (Kim et al., 2023) |
| JHSM14 | JHSM13 H8:P TDH3 -Av.mysE-T CYC1 | This study |
| JHSM141 | JHSM14 H4:P TDH3 -Av.pptA-T CYC1 | This study |
| JHSM142 | JHSM14 H4:P TDH3 -Yl.PPT1-T CYC1 | This study |
| JHSM143 | JHSM14 H4:P TDH3 - Yl.PPT2-T CYC1 | This study |
2.2. Plasmid and Strains Construction
Plasmids and primers used in this study are listed in Tables S1 and S2. codon-optimized genes, including Ava3858 (mysA), Ava3857 (mysB), Ava3856 (mysC), Ava3855 (mysE), and Ava2597 (pptA) from A. variabilis, were synthesized and utilized. These genes were incorporated into plasmids through standard molecular cloning techniques, involving restriction enzymes and DNA ligases. The plasmids designed for genomic integration into harbored gene expression cassettes under the control of UAS1B8-TEF(136) promoter and CYC1 terminator, coupled with loxP (or lox71)-URA3-loxP (or lox66) markers flanked by 1-kb upstream and downstream regions of specific integration sites such as A1, B, C3, D1, E3, F3, or axp1 locus. Correct integration of the gene expression cassettes was verified by colony PCR using gene- and site-specific primers (Table S1).
To integrate these plasmids into the PO1f strain, they were first linearized using NdeI or SmiI restriction enzymes, then transformed into the yeast cells, and selected in SC-Ura medium. For marker recovery, a pYL-Cre-LEU2 plasmid, incorporating the LEU2 marker and the Cre recombinase gene under the EXP1 promoter, was introduced into and selected on a SC-Leu medium. The cells were then cultured in YPD and selected for clones with LEU– and URA– phenotypes. Additionally, plasmids designed for genomic integration into contained gene expression cassettes controlled by P TDH3 -T CYC1 and P TEF -T GPM1 . These plasmids were linearized using NcoI or SmiI restriction enzymes and used for integration facilitated through the CRISPR/Cas9 system targeting the H4 or H8 locus.
2.3. Bioinformatic Analysis
We employed BLASTP to identify proteins with similar sequences. , When this method did not produce appropriate homologous sequences, we conducted an in-depth search of the UniProt database (accessed on February 12, 2024) to identify relevant candidates. To compare protein sequences, we performed multiple sequence alignment using Clustal Omega. Subsequently, to evaluate the similarity among proteins, we generated a phylogenetic tree using MEGA11 and adopted the maximum likelihood method as a statistical method for tree construction. Additionally, we employed the bootstrap method with 500 replications to ensure the robustness of the tree.
Furthermore, to construct Sequence Similarity Networks (SSN), we initially conducted BLASTP searches to identify 10,000 similar proteins. We then utilized EFI-EST for clustering, employing the e-value as the filter type with a filter value set to 130 for MysC. Moreover, we constrained the proteins to a minimum length of 300 and a maximum length of 700 amino acids for clustering purposes. The resulting SSN was visualized using Cytoscape, providing a comprehensive overview of protein relationships and similarities. Additionally, in our genome mining efforts, we employed EFI-GNT to explore potential gene clusters. Utilizing clusters generated from EFI-EST, we investigated genome neighborhoods to unveil the presence of the MAA biosynthetic gene cluster containing the mysBC genes.
2.4. Protein Structure Prediction
Protein structures were visualized using Chimera X, facilitating the exploration and analysis of configurations of proteins. When crystal structures were available, we referred to the RCSB PDB database (accessed on February 12, 2024) for structural insights. In cases where crystal structures were not available, we utilized the AlphaFold protein structure database (accessed on February 12, 2024) to access predicted protein structures. , To predict rotamers of mutants, we employed the Dunbrack backbone rotamer library integrated within Chimera X. The rotamer with the highest prevalence was selected for visualization.
2.5. Analytical Methods
Cell growth was monitored at 600 nm (OD600) using a Varian Cary 50 UV–vis spectrophotometer. To observe glucose consumption, 500 μL of culture supernatant was filtered through a 0.22 μm PVDF syringe filter and analyzed it using an UltiMate 3000 HPLC system equipped with an Aminex HPX-87H column (300 mm × 7.8 mm, 5 μm, Bio-Rad) and a refractive index (RI) detector. The mobile phase comprised water with 0.05% (v/v) H2SO4, and analysis was conducted at a flow rate of 0.6 mL/min, with the column temperature maintained at 60 °C.
MAAs both in the cell supernatants and pellets were detected as described previously. To detect MAAs in the medium, the cell supernatants were filtered through a 0.22 μm PVDF syringe filter. To extract MAAs from cells, 500 μL of cell broth was collected, centrifuged, resuspended in 500 μL of water, and mixed with 750 μL of chloroform. Following vortexing for 10 min to disrupt the cells, the upper water layer was obtained after centrifugation, filtered through a 0.22 μm PVDF syringe filter, and analyzed using an UltiMate 3000 HPLC system equipped with an Agilent Eclipse XDB-C18 column (5 μm, 4.6 × 250 mm) and a UV–vis detector set at 334 nm. Shimadzu HPLC system equipped with a photodiode array (PDA) detector (SPD-M40) was also used to obtain the absorption spectra of samples extracted from the cells. The PDA detector covered wavelengths from 190 to 800 nm, allowing for the simultaneous acquisition of absorbance data from the cell extracts. The mobile phase consisted of water and acetonitrile (95:5, v/v) with 0.1% (v/v) TFA, operating at a flow rate of 0.5 mL/min at 40 °C. Additionally, dry cell weight (DCW) was determined by drying 1 mL of a cell pellet in an oven at 60 °C, enabling the quantification of cellular biomass.
3. Results and Discussion
3.1. Activating the MysE Activity in by Introducing Phosphopantetheinyl Transferase
To produce various MAAs, we first generated the MG-producing strain JHYM100 by integrating mysA, mysB, and mysC genes from A. variabilis (Av) under the control of the UAS1B8-TEF(136) promoter. Next, Av.mysE or mysD was obtained from N. punctiforme (Np) and N. linckia (Nl), each with different substrate specificities, was integrated into the JHYM100 strain, generating JHYM110, 120, and 130, respectively. Np.MysD and Nl.MysD have been demonstrated to exhibit specificity for serine and threonine, respectively. The strains were grown in YPD medium to detect the production of MAAs. In agreement with the previous study, JHYM110 expressing Av.mysE led to the exclusive production of shinorine (Figure A). On the other hand, JHYM120 and 130 primarily produced shinorine and porphyra-334, respectively, but they also generated additional byproducts, reflecting the substrate promiscuity of MysD enzymes (Figure A). These results demonstrate the effectiveness of the NRPS enzyme MysE in producing specific MAA species.
2.
Differences in substrate specificities and reaction mechanisms of MysE and MysD. (A) strains JHYM110, JHYM120, and JHYM130, expressing Av.mysA, mysB, and mysC and the indicated mysD or mysE genes, were grown in YPD media. The HPLC spectra of cell extracts are shown along with the standards for shinorine and porphyra-334. (B) Comparisons between the multimodular structures of typical NRPSs and the single-module MysE. A crucial post-translational modification involves the attachment of a phosphopantetheinyl group to the T domain by PPTase. (C) Proposed reaction processes of MysE and MysD. A, adenylation domain; T, thiolation domain; C, condensation domain; TE, thioesterase domain; PPTase, phosphopantetheinyl transferase.
NRPSs are large multimodular enzymes that synthesize a variety of bioactive peptides, including antibiotics. Each module typically contains condensation (C), adenylation (A), thiolation (T), and thioesterase (TE) domains (Figure B). The C domain forms peptide bonds between substrates, the A domain activates specific amino acids for chain incorporation, while the T domain (or peptidyl carrier proteins) acts as a linker between modules, transferring activated amino acids. This function is critically dependent on phosphopantetheinylation within the T domain, facilitated by phosphopantetheinyl transferase (PPTase). The TE domains, situated at the end of the NRPS line, release the finished peptide product.
The MysE protein deviates from typical NRPS structures comprising only the A, T, and TE domains, forming a single-module NRPS structure (Figure B). MysEs with the C domain are also found in some cyanobacteria. , This enzyme activates serine through adenylation and catalyzes its incorporation into the precursor molecule MG, leading to shinorine synthesis (Figure C). Conversely, MysD first activates MG through phosphorylation before attaching an amino acid (Figure C).
The JHYM110 strain, which expresses Av.mysE along with Av.mysABC genes, produced 234.4 mg/L shinorine in YPD medium containing 20 g/L glucose (Figure A). However, when the Av.mysE gene was expressed in an MG-producing strain JHSM13, the resulting strain JHSM14 produced only 1.3 mg/L of shinorine in YP medium with 10 g/L glucose and 10 g/L xylose, suggesting very inefficient function of MysE (Figure B). The JHSM13 strain has demonstrated high efficiency in MAA production when expressing mysD genes, achieving over 500 mg/L of shinorine under identical culture conditions. HPLC chromatograms revealed a clear accumulation of MG in JHSM14, indicating that MG production is not a limiting step in MAA biosynthesis in this strain (Figure S1). We hypothesized that the inactivity of MysE could be in part attributed to inadequate post-translational modifications (PTMs), particularly the phosphopantetheinylation within the T domain, which is crucial for the NRPS function.
3.
Improvement of shinorine production by expressing PPTase. (A) Enhancement of shinorine production by expressing Av.pptA in . The cells were grown in YPD media for 120 h. (B) Enhancement of shinorine production by expressing Sfp type PPTase genes in . The cells were grown in YP medium with 10 g/L glucose and 10 g/L xylose for 120 h. (C) The phylogenetic tree of PPTases. (D) Effects of biosynthetic gene copy numbers in shinorine production in . The numbers represent the integrated gene copy numbers for each of the specified gene(s). Error bars indicate standard deviations from three independent experiments.
To explore this hypothesis, we searched for a PPTase present in A. variabilis that could catalyze the phosphopantetheinylation of MysE. Bacterial PPTases are classified into two categories based on their substrate specificity and roles: AcpS-type PPTase and Sfp-type PPTase. AcpS, first identified in , activates fatty acid acyl carrier proteins, which is essential for fatty acid biosynthesis. On the other hand, Sfp, first identified in , has a broader substrate specificity, activating carrier proteins involved in NRPS, polyketide biosynthesis, lysine biosynthesis, and other pathways. Since is not a natural producer of polyketides or nonribosomal peptides, it lacks an inherent Sfp-type PPTase. Therefore, we searched the A. variabilis genome for homologs of the Sfp protein from B. subtilis and identified a gene, Ava2597 (accession number: Q3M9X4), which we named pptA. Coexpression of Av.pptA with Av.mysE in (JHSM141) resulted in a 22.2-fold increase in shinorine production compared to expressing Av.mysE alone (JHSM14), confirming the effectiveness of Av.pptA as a gene encoding a PPTase that activates MysE (Figure B and S1). Nevertheless, the level of shinorine production reached only about 28.8 mg/L, which is significantly lower than that achieved by expressing mysD from Lyngbya sp. PCC8106 in JHSM13 (>500 mg/L). This suggests that factors beyond PPTase may also contribute to the low activity of MysE in .
3.2. Identifying Native PPTases in
In contrast to , the JHYM110 strain, which expresses mysE, produced 234.4 mg/L of shinorine even without the expression of Av.pptA. This implies that harbors intrinsic PPTase activity, enabling the activation of MysE. Introducing Av.pptA into the JHYM110 strain (creating JHYM111) led to an approximately 1.23-fold increase in shinorine production, further supporting the role of Av.PptA in enhancing MysE activity (Figure A). To identify the native PPTase that activates MysE in , we explored the UniProt database, identifying two genes, YALI1B21042g (accession number: A0A1H6PSB4) and YALI1E11510g (accession number: A0A1H6PYL5), which we named PPT1 and PPT2, respectively. Both Ppt1 and Ppt2 contain the conserved motif [W/F]xxKE[A/S], a hallmark feature of PPTases. Analysis of the phylogenetic tree shows that Av.PptA and Yl.Ppt2 are more closely related to Sfp of , while Yl.Ppt1 is closer to AcpS of (Figure C).
To verify the functionality of PPT1 and PPT2, we tried to delete these genes in . However, gene deletion was unsuccessful, suggesting that these genes may be essential. Subsequently, we introduced PPT1 or PPT2 into JHSM13 strain, along with Av.mysE, generating strains JHSM142 and JHSM143, respectively. While the expression of PPT1 did not significantly alter shinorine production compared to the control strain JHSM14, which lacks PPTase expression, the introduction of PPT2 led to a 2.53-fold increase in shinorine synthesis (Figure B). However, this increase was less than that observed with the Av.pptA expression. These results suggest that Ppt2 may serve as the native PPTase for MysE in , which aligns with its phylogenetic relationship to Sfp-type PPTases. Although the role of PPTases in NRPS activation is broadly recognized, our results reveal a specific PPTase–MysE pairing that enhances shinorine production, offering a valuable approach to metabolic engineering.
3.3. Multicopy Integration of MG Biosynthetic Genes into to Enhance Shinorine Production
Given its significantly higher shinorine production compared with , all subsequent genetic manipulations were performed in . To further increase shinorine production via providing more MG supply, we serially integrated the Av.mysABC genes into strain JHYM111 at different chromosomal loci, generating strains harboring Av.mysABC genes ranging from two to five copies (JHYM211 to 511). In YPD media with 20 g/L glucose, shinorine production increased with up to four copies of Av.mysABC (JHYM411), reaching 609.7 mg/L, but no further enhancement was observed beyond this number (Figure D). Integrating an additional copy of Av.mysE into JHYM411, resulting in JHYM421, did not lead to a further increase in the level of shinorine production. These genetic modifications had a minimal impact on cell growth (Figure D). When glucose level was increased to 40 g/L, JHYM511 showed slightly higher shinorine production level than JHYM411, reaching to 788 mg/L (Figure S2).
In our previous study, the highest shinorine production in batch culture reached 516.3 mg/L. This was achieved using a highly engineered strain, JHSM132, which expressed mysD from Lyngbia sp., incorporated multiple integrations of pathway genes, and carried deletions of HXK2 and TAL1, along with the introduction of a xylose utilization pathway. The strain was cultured in medium containing 10 g/L each of glucose and xylose to reach this production level (Kim et al., 2023). However, unlike our previous research on MAA production in and , ,,, the strains used in this study lacked genes for xylose-utilizing genes. Consequently, we solely used glucose as the carbon source yet still achieved higher production level with greater selectivity. These results indicate that is suitable as a yeast host for MAA production, highlighting its robust intrinsic pentose phosphate pathway that efficiently supplies S7P without the need for introduced xylose metabolism.
3.4. Genome Mining to Explore the Diversity in the Specificity of MysEs
The broad specificity of MysD across different species enables the production of a variety of MAAs, including shinorine, porphyra-334, and M2G. In contrast, experimentally validated MysE exhibits a more restricted specificity toward serine. , A recent analysis of MysE enzymes across 293 cyanobacterial genomes identified variants predicted to exhibit specificity for glycine and proline as well, although experimental validation is still required. To extend genome mining of MysE beyond cyanobacteria, we used the EFI-enzyme similarity tool to identify ten thousand enzymes similar to Av.MysC and constructed a sequence similarity network (SSN). , We aimed to explore the genomic neighborhoods of clusters in the SSN using the EFI-genome neighborhood tool to identify the cluster containing MysC. We identified a cluster where all nodes were associated with genes encoding mysA, mysB, or both, leading to the identification of 462 MAA biosynthetic gene clusters (Figure S3). Further analysis of the MAA biosynthetic gene clusters revealed a total of 28 clusters containing a putative mysE. Within these gene clusters, 25 NRPS sequences were identified, excluding identical sequences (Table S3). In NRPS, amino acids are activated via adenylation, with substrate specificity determined by the catalyzing A domain. Predictions made using the NRPSsp tool revealed that among the NRPS sequences, 15 A domains were specific to serine, 9 to proline, and one to glycine. Additionally, applying Stachelhaus codesa technique for predicting substrate specificity of A domains in NRPSs - to these 25 NRPS sequences confirmed that their specificities matched those predicted by NRPSsp (Table S4). Despite the extended genome mining efforts, we were unable to identify any MysE enzymes with predicted specificity beyond serine, glycine, and proline, yielding results consistent with previous analyses of cyanobacterial genomes.
The glycine-specific MysE, located on a plasmid in Nostoc sp. UHCC, is hypothesized to attach glycine to MG, producing M2G, as an intermediate in the biosynthesis of Aplysiapalythine E, an MAA produced by this strain. Conversely, based on the proposed reaction mechanisms of MysE, the proline-specific MysE is unlikely to attach proline at the C1 position of MG. Proline lacks a hydrogen atom on its side chain, which prevents the ring formation required for imine formation, making the reaction improbable (Figure S4). In fact, only serine, threonine, glycine, alanine, valine, and glutamate have been reported to bind to MG, with no cases of proline conjugation identified to date. , In contrast to serine-specific mysE, proline-specific mysEs are clustered with other MAA biosynthetic genes, such as mysI, mysF, and even mysD (Figure S5), suggesting that proline conjugation might be involved in the formation of more complex MAA structures.
3.5. Synthesizing a MG-Alanine, a Rare MAA Derivative, by Engineering the A Domain in MysE
Given that most natural MysEs were predicted to have specificity for serine or glycine at the C1 position of MG, we explored the possibility of engineering MysE to modify its substrate specificity by altering the structure of the binding pocket in its A domain. To test this, we attempted to change the substrate specificity in the A domain from serine to threonine. We compared the A domain structure of the serine-specific Av.MysE with that of a threonine-specific NRPS to identify the potential residues for point mutations. As no crystal structure of Av.MysE was available, we utilized its predicted model structure from the AlphaFold Protein Structure Database (ID: AF-Q3M6C6–F1) for reference. For the threonine-specific A domain, we utilized the crystal structure of the Thr1 protein from Streptomyces sp. (PDB ID: 5N9X), which is the only available crystal structure with threonine binding. Using Chimera X, we superimposed the structures of each protein and analyzed their binding pocket structures, identifying three potential mutation candidates: V223F, S292G, and D324H (Figure A). These residues are located near the γ-carbon of the threonine substrate in the Thr1 crystal structure and are also threonine-specific signature residues included in the Stachelhaus code (Table S5).
4.
Biosynthesis of rare MAA, MG-alanine by engineering the A domain of MysE (A) The overlapping structures of ligand-binding sites in NRPSs. The blue structure represents the binding pocket in Av.MysE, while the pink structure represents the binding pocket in the Thr1 protein (PDB ID: 5N9X), which is specific to threonine. The gray molecule depicts a threonine molecule bound to the Thr1 protein. The three mutant candidates, V223F, S292G, and D324H, associated with substrate specificity changes, are indicated. (B) The HPLC spectra of MAAs produced in JHYM111 strain expressing the wild type Av.mysE and JHYM111V223F, JHYM111S292G, and JHYM111D324H strains expressing mutants Av.mysE. (C) The LC-MS data of MAAs (peak 1 and 2, as shown in Figure 4B) produced in JHYM111D324H.
The mysE mutants were introduced into the JHYM101 strain containing Av.mysABC and Av.pptA genes. When the produced MAAs were monitored using HPLC, the V223F mutant showed a loss of activity (Figure B). On the other hand, the S292G mutant exhibited peaks at the same positions as the wild type, indicating little change in substrate specificity. Notably, the D324H mutant displayed a new major peak (peak 2) distinct from those of shinorine and porphyra-334, along with a small amount of shinorine (peak 1) (Figure B). This new peak was also observed as a minor product in the strain expressing the S292G mutant. To elucidate the identity of this compound, LC-MS analysis was conducted, revealing an m/z of 317.1. Given that the molecular weight of MG-alanine, where alanine is attached at the C1 position of MG, is 316.31, the observed m/z value suggests that the D324H mutant may exhibit specificity for alanine within the MysE structure (Figure C). To identify the maximum absorption wavelength of this compound, we analyzed the cell extract from the strain expressing the mysE D324H mutant using HPLC-PDA (Figure S6A). The absorption wavelength spectra of shinorine (Figure S6B) and MG-alanine (Figure S6C) revealed that MG-alanine shares the same absorption wavelength at 330 nm as shinorine. MG-alanine was detected as a minor byproduct alongside shinorine and porphyra-334 when the biosynthetic gene cluster from , which includes the serine-specific mysD gene, was expressed in SUKA22. Nonetheless, an alanine-specific MysD has not yet been discovered yet.
These results were unexpected, as the Stachelhaus code of Av.MysED324H showed a limited similarity to that of the alanine-specific A domain (Table S5). To understand how the D324H mutation leads to specificity for alanine, we examined the predicted structure of the binding pocket. In the wild type, the D324 residue forms a hydrogen bond with the hydroxyl group of the substrate serine, stabilizing its position within the pocket (Figure A). The altered specificity might arise from the D324H residue’s inability to form a hydrogen bond with the hydroxyl group of serine, or the larger histidine side chain could constrict the binding pocket, making it more suitable for the smaller alanine (Figure A). To investigate this, D324 in MysE was substituted with hydrophobic residues of different sizes, including glycine, leucine, and tryptophan. The mutant mysE genes were then introduced into the JHYM101 strain to evaluate the activity of the modified MysE enzymes.
5.
The modeled structures of binding pockets in wild-type MysE and various D324 mutants. (A) The modeled structure of binding site in wild type and D324 mutant MysE proteins. In wild type MysE, the original substrate, serine, forms a hydrogen bond with the D324 residue. The green surface represents residues capable of forming hydrogen bonds with serine. In the modeled structure of the binding site in MysE mutants, the red surfaces indicate residues that are unable to form hydrogen bonds with serine. (B) Production levels of shinorine and MG-Ala in JHYM111D324H, JHYM111D324G, JHYM111D324L, JHYM111D324W strains expressing the indicated Av.mysE mutants. Error bars indication standard deviations from three independent experiments.
The D324G and D324L mutations maintained their specificity for alanine, whereas the enzyme activity was lost with the D324W mutation (Figure B). The preservation of alanine specificity with the smaller glycine substitution at position D324 implies that alterations in the size of the binding pocket might not be the main driver behind changes in substrate specificity (Figure A). Substituting D324 with leucine, which is similar in size to histidine (Figure A), resulted in reduced activity toward both alanine and serine (Figure B). Since standard molecules of MG-Ala are not available, its exact concentration could not be determined. However, based on the ratio of shinorine to MG-Ala production levels, estimated from the peak area of MG-Ala, the D324L mutation improved alanine selectivity over serine by approximately twofold compared to D324H and D324G. This suggests that the primary mechanism behind the change in substrate specificity might be the disruption of the hydrogen bonding with serine. Conversely, substituting D324 with the larger tryptophan is expected to considerably reduce the size of the binding pocket, impeding effective amino acid binding and leading to a loss of enzyme activity (Figure A,B). A more detailed structural analysis may be required to fully understand the catalytic mechanisms involved in the substrate selection.
Although our initial goal was to design a threonine-specific MysE, we unexpectedly developed an alanine-specific MysE. However, this outcome highlights the potential for engineering a MysE to produce novel or rare MAAs that are difficult to obtain from natural sources. Future studies focusing on the characterization of MG-alanine, particularly regarding its stability and biological activities, will be essential in evaluating its potential alongside well-established MAAs such as shinorine and porphyra-334. Additionally, the integration of various MAA biosynthetic genes with enzyme engineering presents promising opportunities for developing safer sunscreen alternatives.
Supplementary Material
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (2021R1A2C2003595) and a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (HP23C0089).
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jafc.5c03130.
Primers used in this study (Table S1); Plasmids used in this study (Table S2); The putative MysEs found by genome mining using MysC homologues (Table S3); Stachelhaus codes of MysEs predicted to have different specificities (Table S4); Stachelhaus codes of the D324H mutant (Table S5); HPLC spectra of strains expressing Av.mysE (Figure S1); Shinorine production in YPD media containing 4% glucose (Figure S2); Sequence similarity network (SSN) of MysC homologues (Figure S3); Proposed reaction process of MysE (Figure S4); MAA biosynthetic gene clusters-containing MysE (Figure S5); HPLC-PDA analysis of MAAs produced in JHYM111D324H strain (Figure S6) (PDF)
D.Y.L.: Investigation, Conceptualization, Data analysis, Writing-original draft; H.B.J.: Investigation; S.J.K.: Investigation; S.W.K.: Investigation; E.Y. P: Investigation; D.W.Y.: Supervision; J.-S.H.: Conceptualization, Funding acquisition, Supervision, Writing-original draft.
The authors declare no competing financial interest.
References
- Llewellyn C. A., Airs R. L.. Distribution and Abundance of MAAs in 33 Species of Microalgae across 13 Classes. Mar. Drugs. 2010;8(4):1273–1291. doi: 10.3390/md8041273. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Weiss E. L., Cape M. R., Pan B. J., Vernet M., James C. C., Smyth T. J., Ha S.-Y., Iriarte J. L., Mitchell B. G.. The Distribution of Mycosporine-like Amino Acids in Phytoplankton across a Southern Ocean Transect. Front Mar. Sci. 2022;9:1022957. doi: 10.3389/fmars.2022.1022957. [DOI] [Google Scholar]
- Rosic N. N., Dove S.. Mycosporine-Like Amino Acids from Coral Dinoflagellates. Appl. Environ. Microbiol. 2011;77(24):8478–8486. doi: 10.1128/AEM.05870-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Garcia-Pichel F., Castenholz R. W.. Occurrence of UV-Absorbing, Mycosporine-Like Compounds among Cyanobacterial Isolates and an Estimate of Their Screening Capacity. Appl. Environ. Microbiol. 1993;59(1):163–169. doi: 10.1128/aem.59.1.163-169.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Balskus E. P., Walsh C. T.. The Genetic and Molecular Basis for Sunscreen Biosynthesis in Cyanobacteria. Science. 2010;329(5999):1653–1656. doi: 10.1126/science.1193637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen M., Jiang Y., Ding Y.. Recent Progress in Unraveling the Biosynthesis of Natural Sunscreens Mycosporine-like Amino Acids. J. Ind. Microbiol. Biotechnol. 2023;50:kuad038. doi: 10.1093/jimb/kuad038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen M., Rubin G. M., Jiang G., Raad Z., Ding Y.. Biosynthesis and Heterologous Production of Mycosporine-Like Amino Acid Palythines. J. Org. Chem. 2021;86(16):11160–11168. doi: 10.1021/acs.joc.1c00368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Arsın S., Delbaje E., Jokela J., Wahlsten M., Farrar Z. M., Permi P., Fewer D.. A Plastic Biosynthetic Pathway for the Production of Structurally Distinct Microbial Sunscreens. ACS Chem. Biol. 2023;18(9):1959–1967. doi: 10.1021/acschembio.3c00112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Waditee-Sirisattha R., Kageyama H., Sopun W., Tanaka Y., Takabe T.. Identification and Upregulation of Biosynthetic Genes Required for Accumulation of Mycosporine-2-Glycine under Salt Stress Conditions in the Halotolerant Cyanobacterium Aphanothece Halophytica. Appl. Environ. Microbiol. 2014;80(5):1763–1769. doi: 10.1128/AEM.03729-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jin H., Kim S., Lee D., Ledesma-Amaro R., Hahn J.-S.. Efficient Production of Mycosporine-like Amino Acids, Natural Sunscreens, in Yarrowia Lipolytica. Biotechnol. Biofuels Bioprod. 2023;16(1):162. doi: 10.1186/s13068-023-02415-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Micallef M. L., D’Agostino P. M., Sharma D., Viswanathan R., Moffitt M. C.. Genome Mining for Natural Product Biosynthetic Gene Clusters in the Subsection V Cyanobacteria. BMC Genomics. 2015;16(1):669. doi: 10.1186/s12864-015-1855-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Becker K., Hartmann A., Ganzera M., Fuchs D., Gostner J. M.. Immunomodulatory Effects of the Mycosporine-Like Amino Acids Shinorine and Porphyra-334. Mar. Drugs. 2016;14(6):119. doi: 10.3390/md14060119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Park S.-H., Lee K., Jang J. W., Hahn J.-S.. Metabolic Engineering of Saccharomyces Cerevisiae for Production of Shinorine, a Sunscreen Material, from Xylose. ACS Synth. Biol. 2019;8(2):346–357. doi: 10.1021/acssynbio.8b00388. [DOI] [PubMed] [Google Scholar]
- Tsuge Y., Kawaguchi H., Yamamoto S., Nishigami Y., Sota M., Ogino C., Kondo A.. Metabolic Engineering of Corynebacterium Glutamicum for Production of Sunscreen Shinorine. Biosci., Biotechnol., Biochem. 2018;82(7):1252–1259. doi: 10.1080/09168451.2018.1452602. [DOI] [PubMed] [Google Scholar]
- Jin C., Kim S., Moon S., Jin H., Hahn J.-S.. Efficient Production of Shinorine, a Natural Sunscreen Material, from Glucose and Xylose by Deleting HXK2 Encoding Hexokinase in Saccharomyces Cerevisiae. FEMS Yeast Res. 2021;21(7):foab053. doi: 10.1093/femsyr/foab053. [DOI] [PubMed] [Google Scholar]
- Kim S.-R., Cha M., Kim T., Song S., Kang H. J., Jung Y., Cho J.-Y., Moh S. H., Kim S.-J.. Sustainable Production of Shinorine from Lignocellulosic Biomass by Metabolically Engineered Saccharomyces Cerevisiae. J. Agric. Food Chem. 2022;70(50):15848–15858. doi: 10.1021/acs.jafc.2c07218. [DOI] [PubMed] [Google Scholar]
- Yunus I. S., Hudson G. A., Chen Y., Gin J. W., Kim J., Baidoo E. E. K., Petzold C. J., Adams P. D., Simmons B. A., Mukhopadhyay A., Keasling J. D., Lee T. S.. Systematic Engineering for Production of Anti-Aging Sunscreen Compound in Pseudomonas Putida. Metab. Eng. 2024;84:69–82. doi: 10.1016/j.ymben.2024.06.001. [DOI] [PubMed] [Google Scholar]
- Kim S., Park B. G., Jin H., Lee D., Teoh J. Y., Kim Y. J., Lee S., Kim S. J., Moh S. H., Yoo D., Choi W., Hahn J. S.. Efficient Production of Natural Sunscreens Shinorine, Porphyra-334, and Mycosporine-2-Glycine in Saccharomyces Cerevisiae. Metab. Eng. 2023;78:137–147. doi: 10.1016/j.ymben.2023.05.009. [DOI] [PubMed] [Google Scholar]
- Holkenbrink C., Dam M. I., Kildegaard K. R., Beder J., Dahlin J., Doménech Belda D., Borodina I.. EasyCloneYALI: CRISPR/Cas9-Based Synthetic Toolbox for Engineering of the Yeast Yarrowia Lipolytica. Biotechnol. J. 2018;13(9):1700543. doi: 10.1002/biot.201700543. [DOI] [PubMed] [Google Scholar]
- Baek S., Utomo J. C., Lee J. Y., Dalal K., Yoon Y. J., Ro D. K.. The Yeast Platform Engineered for Synthetic GRNA-Landing Pads Enables Multiple Gene Integrations by a Single GRNA/Cas9 System. Metab. Eng. 2021;64:111–121. doi: 10.1016/j.ymben.2021.01.011. [DOI] [PubMed] [Google Scholar]
- Altschul S. F., Gish W., Miller W., Myers E. W., Lipman D. J.. Basic Local Alignment Search Tool. J. Mol. Biol. 1990;215(3):403–410. doi: 10.1016/S0022-2836(05)80360-2. [DOI] [PubMed] [Google Scholar]
- Altschul S. F., Madden T. L., Schäffer A. A., Zhang J., Zhang Z., Miller W., Lipman D. J.. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res. 1997;25(17):3389–3402. doi: 10.1093/nar/25.17.3389. [DOI] [PMC free article] [PubMed] [Google Scholar]
- The UniProt Consortium. UniProt: The Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2023, 51(D1), D523–D531. 10.1093/nar/gkac1052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sievers F., Wilm A., Dineen D., Gibson T. J., Karplus K., Li W., Lopez R., McWilliam H., Remmert M., Söding J., Thompson J. D., Higgins D. G. F.. Scalable Generation of High-quality Protein Multiple Sequence Alignments Using Clustal Omega. Mol. Syst. Biol. 2011;7(1):539. doi: 10.1038/msb.2011.75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zallot R., Oberg N., Gerlt J. A.. The EFI Web Resource for Genomic Enzymology Tools: Leveraging Protein, Genome, and Metagenome Databases to Discover Novel Enzymes and Metabolic Pathways. Biochemistry. 2019;58(41):4169–4182. doi: 10.1021/acs.biochem.9b00735. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Shannon P., Markiel A., Ozier O., Baliga N. S., Wang J. T., Ramage D., Amin N., Schwikowski B., Ideker T.. Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Res. 2003;13(11):2498–2504. doi: 10.1101/gr.1239303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Oberg N., Zallot R., Gerlt J. A.. EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools. J. Mol. Biol. 2023;435(14):168018. doi: 10.1016/j.jmb.2023.168018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Meng E. C., Goddard T. D., Pettersen E. F., Couch G. S., Pearson Z. J., Morris J. H., Ferrin T. E.. UCSF ChimeraX: Tools for Structure Building and Analysis. Protein Sci. 2023;32(11):e4792. doi: 10.1002/pro.4792. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Berman H. M., Westbrook J., Feng Z., Gilliland G., Bhat T. N., Weissig H., Shindyalov I. N., Bourne P. E.. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235–242. doi: 10.1093/nar/28.1.235. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jumper J., Evans R., Pritzel A., Green T., Figurnov M., Ronneberger O., Tunyasuvunakool K., Bates R., Žídek A., Potapenko A., Bridgland A., Meyer C., Kohl S. A. A., Ballard A. J., Cowie A., Romera-Paredes B., Nikolov S., Jain R., Adler J., Back T., Petersen S., Reiman D., Clancy E., Zielinski M., Steinegger M., Pacholska M., Berghammer T., Bodenstein S., Silver D., Vinyals O., Senior A. W., Kavukcuoglu K., Kohli P., Hassabis D.. Highly Accurate Protein Structure Prediction with AlphaFold. Nature. 2021;596(7873):583–589. doi: 10.1038/s41586-021-03819-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Varadi M., Anyango S., Deshpande M., Nair S., Natassia C., Yordanova G., Yuan D., Stroe O., Wood G., Laydon A., Žídek A., Green T., Tunyasuvunakool K., Petersen S., Jumper J., Clancy E., Green R., Vora A., Lutfi M., Figurnov M., Cowie A., Hobbs N., Kohli P., Kleywegt G., Birney E., Hassabis D., Velankar S.. AlphaFold Protein Structure Database: Massively Expanding the Structural Coverage of Protein-Sequence Space with High-Accuracy Models. Nucleic Acids Res. 2022;50(D1):D439–D444. doi: 10.1093/nar/gkab1061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dunbrack R. L., Karplus M.. Backbone-Dependent Rotamer Library for Proteins Application to Side-Chain Prediction. J. Mol. Biol. 1993;230(2):543–574. doi: 10.1006/jmbi.1993.1170. [DOI] [PubMed] [Google Scholar]
- Walsh C. T.. Insights into the Chemical Logic and Enzymatic Machinery of NRPS Assembly Lines. Nat. Prod. Rep. 2016;33(2):127–135. doi: 10.1039/C5NP00035A. [DOI] [PubMed] [Google Scholar]
- Lambalot R. H., Gehring A. M., Flugel R. S., Zuber P., LaCelle M., Marahiel M. A., Reid R., Khosla C., Walsh C. T.. A New Enzyme Superfamily - the Phosphopantetheinyl Transferases. Chem. Biol. 1996;3(11):923–936. doi: 10.1016/S1074-5521(96)90181-7. [DOI] [PubMed] [Google Scholar]
- Beld J., Sonnenschein E. C., Vickery C. R., Noel J. P., Burkart M. D.. The Phosphopantetheinyl Transferases: Catalysis of a Post-Translational Modification Crucial for Life. Nat. Prod. Rep. 2014;31(1):61–108. doi: 10.1039/C3NP70054B. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tippelt A., Nett M.. Saccharomyces Cerevisiae as Host for the Recombinant Production of Polyketides and Nonribosomal Peptides. Microb. Cell Fact. 2021;20(1):161. doi: 10.1186/s12934-021-01650-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Prieto C., García-Estrada C., Lorenzana D., Martín J. F.. NRPSsp: Non-Ribosomal Peptide Synthase Substrate Predictor. Bioinformatics. 2012;28(3):426–427. doi: 10.1093/bioinformatics/btr659. [DOI] [PubMed] [Google Scholar]
- Stachelhaus T., Mootz H. D., Marahiel M. A.. The Specificity-Conferring Code of Adenylation Domains in Nonribosomal Peptide Synthetases. Chem. Biol. 1999;6(8):493–505. doi: 10.1016/S1074-5521(99)80082-9. [DOI] [PubMed] [Google Scholar]
- Shukla V., Kumari R., Patel D. K., Upreti D. K.. Characterization of the Diversity of Mycosporine-like Amino Acids in Lichens from High Altitude Region of Himalaya. Amino Acids. 2016;48(1):129–136. doi: 10.1007/s00726-015-2069-z. [DOI] [PubMed] [Google Scholar]
- Sahu N., Mishra S., Kesheri M., Kanchan S., Sinha R. P.. Identification of Cyanobacteria-Based Natural Inhibitors Against SARS-CoV-2 Druggable Target ACE2 Using Molecular Docking Study, ADME and Toxicity Analysis. Indian J. Clin. Biochem. 2023;38(3):361–373. doi: 10.1007/s12291-022-01056-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Scaglione A., Fullone M. R., Montemiglio L. C., Parisi G., Zamparelli C., Vallone B., Savino C., Grgurina I.. Structure of the Adenylation Domain Thr1 Involved in the Biosynthesis of 4-Chlorothreonine in Streptomyces Sp. OH-5093-Protein Flexibility and Molecular Bases of Substrate Specificity. FEBS J. 2017;284(18):2981–2999. doi: 10.1111/febs.14163. [DOI] [PubMed] [Google Scholar]
- Miyamoto K. T., Komatsu M., Ikeda H.. Discovery of Gene Cluster for Mycosporine-like Amino Acid Biosynthesis from Actinomycetales Microorganisms and Production of a Novel Mycosporine-like Amino Acid by Heterologous Expression. Appl. Environ. Microbiol. 2014;80(16):5028–5036. doi: 10.1128/AEM.00727-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
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