Pathway-Guided Medium Engineering for Enhanced Prodiginine Production in Spartinivicinus ruber MCCC 1K03745^T

Abstract

Cycloheptylprodigiosin is a promising anticancer candidate that induces cancer cell death accompanied by severe Golgi stress. Although the soybean oil-based optimized MB2216 medium produced a total prodiginine titer approximately three times that of the basal MB2216 medium, the overall production level remained limited. In addition, a substantial fraction of the pigments partitioned into floating oil droplets, hindering efficient recovery by simple centrifugation. In this study, a novel medium was rationally formulated based on genomic insights derived from homology analysis of conserved biosynthetic genes involved in cycloheptylprodigiosin production in Spartinivicinus ruber MCCC 1K03745^T. Sequential optimization through single-factor experiments, full factorial designs, steepest ascent experiments and response surface methodology identified an optimal medium consisting of peptone (5 g/L), yeast extract (1 g/L), peanut meal (7.611 g/L), and L-Proline (0.695 g/L) prepared in seawater at pH 7.6. Under the optimized conditions, the total prodiginine titer reached 53.33 mg/L, which was 11.37 times that of the basal MB2216 medium and 3.29 times that of the soybean oil-based MB2216 medium. Moreover, the pigment-associated biomass could be efficiently recovered by centrifugation. This study provides a genomics-informed strategy for improving prodiginine production in S. ruber and facilitates downstream pigment recovery.

1. Introduction

Prodiginines are a class of red secondary metabolites produced by diverse microorganisms, including Serratia spp., actinomycetes and certain marine bacteria. These pigments have attracted considerable interest owing to their broad spectrum of biological activities, including anticancer, antifungal and antibacterial effects, while exhibiting relatively low cytotoxicity toward normal tissues [1]. In addition, prodiginines are not substrates of multidrug resistance proteins, which frequently contribute to chemotherapy failure [2,3,4]. Collectively, these properties highlight their potential as promising drug candidates.

Structurally, prodiginines share a conserved tripyrrole scaffold, with structural diversity primarily arising from modifications in the C-ring moiety. The biosynthesis of prodigiosin in Serratia marcescens has been extensively characterized and proceeds via a bifurcated pathway involving the independent formation of 2-methyl-3-n-amyl-pyrrole (MAP) and 4-methoxy-2,2′-bipyrrole-5-carbaldehyde (MBC), followed by enzymic condensation catalyzed by PigC. The MAP branch originates from 2-octenal and involves sequential reactions mediated by PigD, PigE and PigB. In contrast, the MBC branch begins with L-proline and proceeds through a series of enzymatic steps catalyzed by PigI, PigA, PigJ, PigH, PigM and PigF/PigN. A related yet distinct pathway has been described in Streptomyces coelicolor, in which the MBC module is conserved, whereas the monopyrrole moiety is synthesized from acetyl-CoA and malonyl-CoA to generate undecylprodigiosin [1]. These studies collectively illustrate the modular and evolutionarily conserved nature of prodiginine biosynthesis.

Cycloheptylprodigiosin represents a distinctive member of the prodiginine family and has been reported to induce cancer cell death accompanied by severe Golgi stress [5]. However, the underlying molecular mechanism remains unclear necessitating sufficient quantities of the compound for detailed mechanistic and in vivo pharmacological investigations. To date, the only known producer, Spartinivicinus ruber MCCC 1K03745^T, generates approximately 5 mg/L of total prodiginines (including cycloheptylprodigiosin and heptylprodigiosin at a ratio of 1:1.5) when cultured in basal Marine Broth 2216 (MB2216) medium [6]. Although supplementation with soybean oil increased the titer to 14.64 mg/L in our previous study, a substantial proportion of the pigments partitioned into the floating oil droplets, complicating downstream recovery [7]. Therefore, an improved strategy is required to enhance production while simplifying product isolation.

Genome analysis of S. ruber revealed conserved homologs of key prodiginine biosynthetic genes, suggesting that prodiginines in this strain are likely synthesized via a pathway analogous to the bifurcated MAP-MBC architecture described in other prodiginine-producing bacteria [6]. Based on this genomic inference, we hypothesized that precursor availability in the MAP-like and MBC branches may constitute a limiting factor for cycloheptylprodigiosin production. Accordingly, candidate substrates potentially associated with these two biosynthetic modules were rationally selected and systematically evaluated.

In the present study, we developed a genomics-informed medium optimization strategy integrating targeted precursor supplementation with statistical experimental design. This approach led to a novel medium formulation that significantly enhanced prodiginine production while enabling efficient recovery of pigment-associated biomass. Our findings demonstrate that genome-guided rational design can complement conventional empirical optimization for improving prodiginine biosynthesis in S. ruber.

2. Materials and Methods

2.1. Reagents

S. ruber was preserved in our lab, and it is also available from China Marine Culture Collection Center, accession No. MCCC 1K03745. Peptone (Cat No. P8450) was purchased from Solarbio (Beijing, China). Yeast extract (Cat No. LP0021B) was from Oxoid (Basingstoke, UK). Glycerol (Cat No. 10010618), D-(+)-glucose (Cat No. 63005518), sucrose (Cat No. 10021463), were from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). D-(+)-trehalose (Cat No. D110019-5g), glycine (Cat No. A110752-500g), L-proline (Cat No. P108709-500g), L-methionine (Cat No. M101130-500g), L-serine (Cat No. S103483-500g) were from Aladdin Scientific (Shanghai, China). Peanut meal (Cat No. Y039), cottonseed meal (Cat No. Y031), rapeseed meal (Cat No. Y040), and soybean meal (Cat No. Y030A) were from Hongrun Baoshun Technology (Beijing, China).

2.2. Bioinformatic Analysis

Amino acid sequences of PigD (Q5W251), PigB (Q5W253), PigE (Q5W250) from S. marcescens and RedP (O54151) from S. coelicolor were retrieved from the UniProt database (https://www.uniprot.org). Homologous sequences were identified by BLASTP searches against the annotated genome of S. ruber (https://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 26 February 2026) [8,9]. Sequence alignment was generated and visualized using the ESPript 3.2 online server (https://espript.ibcp.fr/ESPript/cgi-bin/ESPript.cgi, accessed on 26 February 2026) [10].

2.3. Fermentation Conditions

Fermentation was carried out as previously described in our earlier study [7], with minor modifications. The basal medium consisted of peptone (5 g/L) and yeast extract (1 g/L) prepared in natural seawater collected from Quanzhou Bay.

A single colony was picked and inoculated into 10 mL of MB2216 medium, followed by incubation at 35 °C and 140 rpm for 16 h to prepare the seed culture. For fermentation, the seed culture was inoculated at 1% (v/v) into 30 mL of sterile medium in Erlenmeyer flasks and incubated at 30 °C and 140 rpm for 30 h. Carbon sources were added prior to inoculation, whereas sterile amino acid stocks solutions were supplemented 12 h after inoculation, corresponding to the early stage of prodiginine production in S. ruber.

2.4. Sequential Design Strategy for Fermentation Optimization

A sequential experimental design strategy was employed, in which single-factor experiments, full factorial design, steepest ascent, and central composite design (CCD) were applied in a stepwise manner to ensure efficient and reliable optimization.

2.4.1. Single-Factor Experiments for Preliminary Range Determination

Single-factor experiments were conducted to evaluate the effects of individual medium components and provide rational ranges for subsequent full factorial design. In each experiment, one component was supplemented to the basal medium while all other conditions were kept constant. The tested components included carbon sources, slow-release nitrogen sources and amino acid precursors. Carbon sources and amino acid precursors were sterilized by filtration through 0.22 μm membrane filters.

2.4.2. Full Factorial Design and Steepest Ascent Experiments for Interaction Analysis and Region Exploration

A full factorial design (

Table 1. Factors and levels used in full factorial design.

Factors	Low Level (−1)	High Level (+1)
A-peanut meal (g/L)	1	3
B-glycerol (g/L)	0	5
C-L-proline (g/L)	0	0.5

and

Table 2. Full factorial design of prodiginine fermentation by Spartinivicinus ruber MCCC 1K03745^T.

Run	A- Peanut Meal	B- Glycerol	C- L-Proline	Prodiginine Concentration (mg/L)
1	+1	−1	−1	39.26
2	+1	−1	+1	46.53
3	−1	−1	+1	23.13
4	+1	+1	−1	41.41
5	−1	+1	−1	18.55
6	+1	+1	+1	45.03
7	−1	+1	+1	25.61
8	−1	−1	−1	18.80

) was employed to identify significant factors and their interactions affecting prodiginine production. Based on the results, a steepest ascent experiment (

Table 3. Factors and levels used in the steepest ascent experiment.

Step	Peanut Meal (g/L)	L-Proline (g/L)
1	3	0.500
2	4	0.567
3	5	0.633
4	6	0.700
5	7	0.767
6	8	0.833

) was performed to approach the region of maximum response prior to CCD based on response surface methodology.

2.4.3. Response Surface Methodology for Final Optimization

Based on the results of the steepest ascent experiment, the center point for the CCD was selected from the region showing the highest response, so that the response surface analysis could be conducted in the vicinity of the optimal region. The effects of medium components, including peanut meal and L-proline, were evaluated at the levels listed in

Table 4. Factors and levels used in the central composite design (CCD).

Level	Factors
	A-Peanut Meal (g/L)	B-L-Proline (g/L)
−1.41421	0.55	0.337
−1	2	0.433
0	5.5	0.667
+1	9	0.900
+1.41421	10.45	0.997

, and the experimental design (

Table 5. CCD matrix and corresponding prodiginine production in S. ruber.

Run	Factors		Prodiginine Concentration (mg/L)
	A-Peanut Meal	B-L-Proline
1	0	+1.41421	49.57
2	0	0	51.87
3	+1	−1	51.03
4	+1	+1	53.14
5	0	0	51.26
6	0	0	50.08
7	0	−1.41421	50.10
8	−1.41421	0	15.54
9	0	0	49.61
10	0	0	51.31
11	−1	−1	28.69
12	−1	+1	28.44
13	+1.41421	0	47.11

) and statistical analysis were performed using Design-Expert 13 software (Stat-Ease, Minneapolis, MN, USA).

2.5. Extraction and Quantification of Prodiginine

Prodiginines were extracted and quantified as previously described [7]. Briefly, cultures were centrifuged to collect cell pellets, which were extracted with acidified methanol assisted by sonication. After removal of cellular debris by centrifugation, the supernatants were adjusted to defined volume, and optical density was measured at 535 nm using an Infinite M200 Pro microplate reader (Tecan, Männedorf, Switzerland).

Prodiginine concentration was calculated according to the calibration equation [7]:

y = 0.0414x + 0.0446,

where x represents prodiginine concentration and y represents the corresponding OD_535nm value.

2.6. Statistical Analysis

All quantitative results are expressed as mean ± standard deviation (SD) from three independent experiments (n = 3). Statistical significance was evaluated by one-way analysis of variance (ANOVA) followed by the Holm–Sidak post hoc test. Differences were considered statistically significant at p < 0.05.

3. Results

3.1. Homology Analysis Reveals a Putative Prodiginine Biosynthetic Pattern in S. ruber

The biosynthesis of known prodiginines generally follows bifurcated pathways. While the synthesis of the bipyrrole intermediate MBC is conserved in both S. marcescens and S. coelicolor, the formation of the monopyrrole moiety differs substantially between these organisms, as none of the MAP-associated genes in S. marcescens is conserved in S. coelicolor. Homology analysis revealed that the PigD (UniProt Accession No. Q5W251) from S. marcescens, which catalyses the initial step of MAP biosynthesis, shares 51% sequence identity and 68% similarity with its homolog in S. ruber (Figure 1). Other MAP-associated enzymes in S. marcescens were likewise conserved in S. ruber (

Table A1. Homology analysis of key enzymes involved in MAP-like biosynthesis in S. marcescens and S. ruber.

Enzymes in S. marcescens (UniProt Accession No.)	Homologs in S. ruber (NCBI Reference Sequence Accession No.)	Sequence Identities	Sequence Positives	Query Coverage	E Value
PigD (Q5W251)	prodigiosin MAP biosynthesis protein PigD (WP_163833139.1)	51%	68%	90%	0.0
PigB (Q5W253)	NAD(P)/FAD-dependent oxidoreductase (WP_163833141.1)	42%	59%	79%	2e−140
PigE (Q5W250)	prodigiosin MAP biosynthesis aminotransferase PigE (WP_163833138.1)	59%	76%	100%	0.0

), with substantial query coverage and statistically significant E-values. In contrast, RedP (UniProt Accession No. O54151), which is essential for undecylprodigiosin biosynthesis in S. coelicolor, exhibited no significant homologs in S. ruber under the applied BLASTP criteria. Collectively, the conservation of MAP branch enzymes and the absence of RedP-like homologs suggest that cycloheptylprodigiosin and heptylprodigiosin biosynthesis in S. ruber more likely resembles the prodigiosin-type condensation of a MAP-like intermediate with MBC, although alternative catalytic strategies cannot be fully excluded. These findings suggest that the biosynthesis of prodiginines in S. ruber likely relies on metabolic precursors similar to those in S. marcescens. This information provided a rationale for considering key nutritional factors, such as carbon and nitrogen sources, in the subsequent fermentation optimization.

3.2. Effects of Single Factors on Prodiginine Production

In our previous study, soybean oil markedly enhanced prodiginines production in S. ruber. However, a substantial portion of the pigments partitioned into floating lipid droplets, which interfered with efficient recovery by centrifugation. Therefore, alternative carbon souces were evaluated for their effects on fermentation titer. As shown in Figure 2A, supplementation with glycerol increased the prodiginine titer to 1.56-fold compared with the basal MB2216 medium. Based on this result, glycerol was selected as the carbon source for subsequent optimization. Further investigation revealed that the optimal glycerol concentration ranged from 2.5 to 10 g/L, whereas higher dosages did not further enhance prodiginine production (Figure 2B).

Given that S. ruber may synthesize prodiginines via a pathway resembling that of S. marcescens, precursor-related subtrates were evaluated for their potential influence on production. Enals, such as 2-decenal and 2-octenal can be generated through the autoxidation of linoleic acid [11]. To maintain precursor availability while avoiding complications associated with oil-based media, oilseed meals—commonly used slow-releasing nitrogen sources containing minor residual oil—were tested instead. As shown in Figure 2C, supplementation of peanut meal, rapeseed meal and soybean meal substaintially increased prodiginine production. Among these, peanut meal at 5 g/L elevated the titer to 50.29 mg/L (Figure 2D) and was selected for further study.

In addition, several amino acids potentially involved in prodiginine biosynthesis were examined. As shown in Figure 2E, only L-proline significantly promoted prodiginine production. The maximal titer was observed at appoximately 1 g/L L-proline supplementation (Figure 2F).

Collectively, glycerol, peanut meal and L-proline were identified as key factors for subsequent statistical optimization.

3.3. Analysis of Main Effects and Interactions Using a Full Factorial Design

To evaluate the direct effects and potential interactions among glycerol, peanut meal and L-proline, a full factorial design was performed (Table 1 and Table 2). As shown in

Table 6. One-way analysis of variance (ANOVA) for the full factorial model.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	995.63 a	4	248.91	1666.39	<0.0001	significant
A-peanut meal	927.41	1	927.41	6208.82	<0.0001	significant
B-glycerol	1.03	1	1.03	6.88	0.0789
C-L-proline	62.09	1	62.09	415.66	0.0003	significant
ABC	5.11	1	5.11	34.20	0.0100	significant
Residual	0.4481	3	0.1494
Cor Total	996.08	7

^a R² = 0.9996; adjusted R² = 0.9990; predicted R² = 0.9968.

, factor A (peanut meal) and factor C (L-proline) significantly affect prodiginine production in S. ruber, and the three-factor interation term (ABC) was also statistically significant. Factor B (glycerol) exhibited a marginally significant effect, whereas the two-factor interactions (AB, AC and BC) were not significant. As illustrated in Figure 3, factor A and C exerted positive effects, while the ABC interaction showed a negative contribution.

Factor B did not exhibit a statistically significant main effect (p = 0.0789) and explained less than 0.2% of the total variance. Although the ABC interaction reached statistical significance, its contribution was minor compared with the dominant effects of factors A and C. To simplify the model and improve optimization efficiency, factor B was fixed at its relatively favorable level.

The highest prodiginine titer was obtained when both factors A and C were at the +1 level. Under this condition, the yield at B = −1 (Run 2, Table 2) exceeded that at B = +1 (Run 6). Accordingly, the medium composition corresponding to Run 2 was selected as the starting point for the steepest ascent experiments, with factor B fixed at the −1 level.

3.4. Approaching the Optimal Region via Steepest Ascent

Starting from the composition corresponding to Run 2 (Table 2), a steepest ascent experiment was performed (Table 3) to approach the region of maximal response. As shown in Figure 4, the highest prodiginine production was observed between step 3 and step 4. The relatively small differences among steps suggest the presence of a plateau-like region near the optimum.

3.5. Optimization by Response Surface Methodology

The midpoint between step 3 and step 4 was selected as the center point. A central composite design (CCD) was subsequently employed for the final optimization (Table 4 and Table 5). In the initial model, the interaction term AB was not significant (p = 0.2159) and was therefore pooled into the residual error. ANOVA of the final quadratic model (

Table 7. ANOVA for response surface quadratic model.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	1725.13 a	4	431.28	518.40	<0.0001	significant
A-peanut meal	1051.11	1	1051.11	1263.44	<0.0001	significant
B-L-proline	0.1551	1	0.1551	0.1865	0.6773
A2	670.19	1	670.19	805.57	<0.0001	significant
B2	2.17	1	2.17	2.61	0.1446
Residual	6.66	8	0.8319
Lack of Fit	3.09	4	0.7734	0.8685	0.5527	not significant
Pure Error	3.56	4	0.8905
Cor Total	1731.79	12

^a R² = 0.9962; adjusted R² = 0.9942; predicted R² = 0.9900.

) demonstrated that factor A (peanut meal) and its quadratic term (A²) significantly affected prodiginine production. Factor B showed no significant linear effect, whereas its quadratic term (B²) was marginally significant. The final predictive model was:

y = 50.83 + 11.46A + 0.1393B − 9.82A² − 0.5590B².

The coefficients of determination (R², adjusted R² and predicted R²) were 0.9962, 0.9942 and 0.9900, respectively. The lack-of-fit test was not significant (p = 0.5527) indicating that the model adequately described the experimental data.

As shown in the three-dimensional response surface (Figure 5), a plateau-like region was observed around the maximal response, consistent with the steepest ascent results. According to the regression model, the optimal medium formulation consisted of: peptone (5 g/L), yeast extract (1 g/L), peanut meal (7.611 g/L), and L-Proline (0.695 g/L) in seawater at pH 7.6.

Verification experiments confirmed that under this optimal formulation (designated as optimized MB2216 V2 in Figure 6A), the prodiginine titer reached up to 53.33 mg/L, which was comparable to the predicted 54.18 mg/L. This represented 11.37-fold and 3.29-fold the titer obtained with the basal and soybean oil-based MB2216 (designated as optimized MB2216 V1), respectively.

To assess robustness, fermentation performance across different seawater batches was analyzed (Figure 6B). Although overall ANOVA indicated a significant difference among batches (p < 0.05), post hoc analysis revealed that significant differences were confined to the comparison between Batch 1 and Batch 2. No significant differences were observed between Batch 2 and Batch 3 or between Batch 1 and Batch 3, suggesting generally stable fermentation performance with limited batch-to-batch variability.

4. Discussion

Increasing attention has been directed toward prodiginines in recent decades due to their diverse biological activities, particularly their anticancer potential. Cancer remains one of the leading causes of mortality worldwide, with an estimated 18.5 million new cases and 10.4 million cancer deaths reported in 2023 [12]. Preclinical studies have demonstrated that prodiginines disrupt multiple cellular processes, including autophagy modulation [13,14], cytoplasmic acidification [15,16], induction of endoplasmic reticulum stress [17,18], and dysregulation of signaling pathways [16,19], ultimately leading to cell death.

To date, at least 33 prodiginine analogs have been identified [20], although most investigations have been focused on prodigiosin, cycloprodigiosin and undecylprodigiosin. In our previous work, we characterized the anticancer mechanism for cycloheptylprodigiosin in non-small-cell lung cancer models. Notably, cycloheptylprodigiosin induced cell death via a mechanism distinct from canonical pathways such as apoptosis, autophagic cell death, necroptosis, pyroptosis, and ferroptopsis [5]. These properties highlight its potential not only as a pharmacological candidate but also as a valuable probe for studying noncanonical cell death mechanism. However, the low fermentation titer of S. ruber cultured in basal MB2216 medium limited further mechanistic and translational investigations, thereby necessitating medium optimization.

Carbon and nitrogen sources are primary determinants of fermentation yield. Previous studies have reported that sucrose [21], starch [22,23] and vegetable oils [7,24] can enhance prodiginine production. However, the relative effectiveness of these substrates varies among strains and experimental conditions. In our prior study, soybean oil promoted prodiginine production more effectively than sucrose or glycerol at 5 g/L. Nevertheless, a substantial fraction of pigments partitioned into the floating lipid droplets, complicating downstream recovery. Therefore, alternative carbon sources were evaluated in the present study. Glycerol modestly enhanced prodiginine production, whereas trehalose had no significant effect. In contrast, galactose reduced the fermentation titer. Collectively, these results suggest that glycerol represents a more suitable carbon source when vegetable oils are excluded, balancing production performance and process feasibility.

Organic nitrogen sources generally outperform inorganic counterparts in supporting prodiginine biosynthesis. For example, glycine increased prodigiosin production in S. marcescens compared with ammonium sulfate [21], and peptone was also superior to various ammonium salts [22,25]. Oilseed meals, widely used as slow-release nitrogen sources, have also been reported to enhance prodiginine fermentation [23]. In this study, peanut meal markedly increased the titer to approximately 50.29 mg/L at 5 g/L supplementation. This effect may be partially attributed to the residual lipids present in peanut meals, which could serve as precursors for enal formation and thereby facilitate the biosynthesis of the MAP-like monopyrrole branch. However, the precise metabolic contribution warrants further investigation.

Amino acids have been reported to influence prodiginine production through both precursor supplementation and metabolic regulation [26,27,28,29]. L-proline serves as a direct substrate in MBC biosynthesis and consistently promoted production in multiple strains [26,28]. In contrast, certain amino acids enhance production without direct incorporation into the molecule, suggesting regulatory effects [30,31]. In the present study, L-proline significantly increased prodiginine titer, whereas L-serine showed no stimulatory effect. Glycine and L-methionine exhibited inhibitory effects under our experimental conditions. These findings indicate that amino acid supplementation influences prodiginine biosynthesis in a strain-specific manner and may involve both precursor availability and broader metabolic regulation.

Inorganic salts have been reported to modulate prodigiosin biosynthesis, although their impact is generally less pronounced than that of carbon and nitrogen sources [7,21,22]. Our previous experiments indicated that Fe³⁺ had no effect and Mg²⁺ was less impactful than nitrogen sources; hence, these variables were not further examined in this study [7]. While KH₂PO₄ increased prodiginine production in our system (Figure A1), its addition to the seawater-based medium resulted in substantial precipitation, likely due to interactions with divalent metal cations such as Mg²⁺ and Ca²⁺ under near-neutral pH conditions. These changes in medium appearance suggested that nutrient availability in the culture system may have been altered. Therefore, KH₂PO₄ was also excluded from subsequent optimization to ensure medium stability and robustness.

Statistical optimization further clarified the relative contributions of the selected factors. In the full factorial design, peanut meal and L-proline significantly influenced prodiginine production, whereas glycerol exerted a minor effect. However, in the response surface model, only peanut meal remained statistically significant. This shift suggests that the contribution of L-proline became less pronounced as production approached the optimal region. Two possible explanations may account for this observation. First, lipid-derived precursors from peanut meal may enhance MAP-like branch flux to a level that exceeds the condensation capacity of PigC, thereby limiting further increases through MBC precursor supplementation. Alternatively, peanut meal may simultaneously stimulate both MAP-like and MBC branches by increasing acetyl-CoA availability via β-oxidation, thus elevating malonyl-CoA pools. In this scenario, prodiginine biosynthesis may become constrained by feedback regulation at higher titers [32]. Future studies involving PigC overexpression or in situ absorption strategies using resin supplementation may provide mechanistic insight into these alternative explanations [32,33].

From an industrial perspective, an optimal medium must balance productivity, cost, and downstream processability. The optimized MB2216 V2 developed in this study costs CNY 3.14 per liter (Chinese yuan, RMB), substantially lower than optimized MB2216 V1 (CNY 5.04 per liter) and commercial MB2216 (CNY 68.82 per liter) (

Table A2. Medium cost per liter of optimized MB2216 V1.

Component	Amount (/L)	Grade	Supplier	Unit Price (CNY/g or mL)	Quotation Date	Cost (CNY/L)
Peptone	11 g	-	Solarbio	0.400	March 2026	4.40
Yeast extract	1 g	-	Oxoid	0.350	March 2026	0.35
Soybean oil	5 mL	Food	Yihai Kerry	0.018	March 2026	0.09
MgCl2·6H2O	3 g	Analytical	Sinopharm	0.068	March 2026	0.20
total						5.04

and

Table A3. Medium cost per liter of optimized MB2216 V2.

Component	Amount (/L)	Grade	Supplier	Unit Price (CNY/g or mL)	Quotation Date	Cost (CNY/L)
Peptone	5 g	-	Solarbio	0.400	March 2026	2.00
Yeast extract	1 g	-	Oxoid	0.350	March 2026	0.35
Peanut meal	7.611 g	Fermentation	Hongrun Baoshun	0.080	March 2026	0.61
L-Proline	0.695 g	Analytical	Aladdin	0.260	March 2026	0.18
total						3.14

). Importantly, optimized MB2216 V2 supported a prodiginine titer of 53.33 mg/L, representing 11.37 and 3.29 times the titer obtained with the basal MB2216 and optimized MB2216 V1, respectively. Unlike oil-based formulations, optimized MB2216 V2 yielded a homogeneous suspension without floating pigment-containing droplets, thereby simplifying downstream recovery (Figure A2). Collectively, these findings demonstrate that optimized MB2216 V2 provides a cost-effective and operationally robust platform for prodiginine production in S. ruber.

To directly compare the newly designed medium with our previously optimized formulation, this study focused solely on medium composition while keeping other fermentation parameters, including temperature, shaking speed, and duration, consistent with prior work [7]. Further optimization of temperature, aeration, or extended fermentation may improve prodiginine yield. Nevertheless, S. ruber still produced substantially less prodiginine than S. marcescens, consistent with generally low yields reported for marine bacteria such as Hahella chejuensis KCTC 2396 (0.028 g/L) and Zooshikella rubidus S1-1 (0.048 g/L) [34,35]. Further integrative analyses combining metabolomics and proteomics would not only help validated the molecular mechanisms underlying the enhanced prodiginine production achieved in this study, but also provide insights into the inherently low production levels observed in marine bacteria. Importantly, the genome-guided strategy applied here, leveraging predicted bifurcated prodiginine pathways, could inform medium optimization in other prodiginine-producing strains, although its broader applicability remains to be validated. While industrial-scale production of prodiginine is extremely limited, its potential in biomedical applications and as a natural dye suggests a growing market.

5. Conclusions

In this study, homology analysis suggested that the putative biosynthetic pathway of prodiginines in S. ruber likely resembles that of prodigiosin in S. marcescens. Based on this inference, a rational medium design strategy was implemented to enhance prodiginine production through single-factor experiments, full factorial design, steepest ascent experiments and central composite design under response surface methodology. The optimized medium consisted of peptone (5 g/L), yeast extract (1 g/L), peanut meal (7.611 g/L), and L-Proline (0.695 g/L) in seawater at pH 7.6. Under these conditions, the fermentation titer reached 53.33 mg/L, representing 11.37 and 3.29 times the titer obtained with the basal MB2216 and optimized MB2216 V1, respectively. These findings establish a cost-effective and operationally feasible medium formulation for prodiginine production in S. ruber and provide a foundation for further process optimization and potential scale-up applications.