Fractionation-guided profiling of silkworm pupae (Bombyx mori) peptides: molecular features governing stage-specific fermentative performance of Limosilactobacillus reuteri DSM 17938

Abstract

Silkworm pupa peptides (SPPs) are promising functional nitrogen sources, but their structure–activity relationships with probiotics remain unclear. We compared Alcalase- (SPP-A) and Flavourzyme-derived SPPs (SPP-F) for supporting limosilactobacillus reuteri DSM 17938. Both contained over 92% components below 3 kDa and enhanced growth, viability, and overall organic acid accumulation under nitrogen limitation, with SPP-A showing greater overall activity. Activity-guided fractionation revealed stage-dependent size effects. 1–3 kDa fractions promoted logarithmic phase growth, whereas the 3–5 kDa SPP-A fraction better sustained stationary stage viability and acid production. Gel filtration identified F2–1 (1–2 kDa) and A2–2 (2–3 kDa) as highly active, while ion-exchange chromatography identified FI-2 as the most consistently active charge-based fraction. LC–MS/MS showed that F2–1 was enriched in short, hydrophilic, acidic peptides containing recurrent lipoprotein-derived hydrophobic motifs. Thus, peptide molecular weight and charge jointly govern temporal nitrogen availability, supporting the use of SPP fractions as complementary functional nitrogen sources for L. reuteri fermentation.

Highlights

• •Silkworm pupae peptides acted as effective nitrogen sources for L. reuteri
• •Peptide molecular weight was linked to fermentation-stage-dependent activity
• •The 1–3 kDa fractions preferentially supported logarithmic phase growth
• •Peptide molecular weight and charge jointly control nitrogen availability for L. reuteri
• •F2–1 was enriched in short, hydrophilic and acidic peptides mainly from lipoproteins

1. Introduction

Probiotics are live microorganisms that confer health benefits when administered in adequate amounts. Among various probiotic microorganisms, lactobacilli are widely used in functional foods and nutritional products due to their roles in maintaining intestinal homeostasis, modulating host responses, and inhibiting pathogenic microorganisms (Latif et al., 2023). limosilactobacillus reuteri (L. reuteri) is a gastrointestinal commensal with strain-dependent tolerance to gastrointestinal stress and adhesion to intestinal epithelial cells. In addition, its metabolite reuterin possesses broad-spectrum antimicrobial activity, contributing to its potential applications in maintaining intestinal microbial balance and host health (Cleusix et al., 2007). Soybean proteins and peptides have been shown to enhance the growth and organic acid secretion of L. reuteri DSM 17938, supporting the potential of protein-derived nitrogen sources for improving its fermentation performance (Wang, Wang, et al., 2024).

The survival and functional performance of probiotic cultures depend strongly on nutrient availability (Chandrasekaran et al., 2024). Beyond carbohydrate-based prebiotics, protein hydrolysates are receiving attention as readily accessible nitrogen sources (Zhang et al., 2020). Recent studies have demonstrated selective peptide utilization by lactic acid bacteria. In Lactococcus lactis, peptide utilization preferences were associated with amino acid composition, including the presence of branched-chain and nonpolar residues (Canon et al., 2022). Similarly, peptide utilization by Lacticaseibacillus rhamnosus Lra05 varied with chain length, hydrophobicity, and terminal residues (Zhang et al., 2023). These findings suggest that peptide composition and structural characteristics may influence their utilization as nitrogen sources. Soybean protein-derived hydrolysates and peptides can enhance the growth or metabolic activity of selected starter and probiotic bacteria, including Streptococcus thermophilus, Lacticaseibacillus rhamnosus, L. reuteri, and Bifidobacterium species (Hongfei et al., 2013; Li et al., 2021; Sun et al., 2021; Zhang et al., 2022, Zhang et al., 2021). More recent studies have further demonstrated that specific soybean-derived peptide fractions can promote the growth and metabolism of L. rhamnosus, while quinoa protein hydrolysates can enhance the growth and overall organic acid accumulation of Lactiplantibacillus plantarum (Chen et al., 2024; Zhang et al., 2023). Together with the growth responses reported for protein hydrolysates, these findings suggest that the form and composition of supplied nitrogen may influence probiotic fermentation.

Silkworm pupae (Bombyx mori) represent an underutilized protein-rich resource with potential applications in the food industry (Zeng et al., 2021). Apart from direct consumption, silkworm pupae powder has been investigated as an alternative protein source in high-energy biscuits (Akande et al., 2020). Silkworm pupa protein hydrolysate have also been explored as a potential ingredient for protein-fortified and functional foods (Anootthato et al., 2019; Cermeño et al., 2022). Enzymatic hydrolysis can improve the solubility and selected functional properties of silkworm pupae proteins, supporting their potential use in protein-enriched food formulations (Anootthato et al., 2019). These hydrolysates usually contain peptides with diverse molecular weights, amino acid compositions and sequences. These structural differences may affect their utilization efficiency by probiotics and consequently influence bacterial growth and metabolic activity. Recent studies have combined activity-guided fractionation with LC–MS/MS to identify bioactive peptides from silkworm pupae protein hydrolysates; however, these investigations have primarily focused on antioxidant, myogenic, and other bioactivities, while few investigate their growth-promoting effects on probiotic microorganisms (Chukiatsiri et al., 2024; Huang et al., 2025; Kang et al., 2023). Accordingly, the relationships among peptide fraction characteristics, peptide profiles, and probiotic growth and metabolic responses remain poorly understood. Systematic activity-guided fractionation coupled with peptide profiling is therefore required to identify the peptide fractions associated with probiotic-promoting activity and to facilitate the development of silkworm pupae peptides as functional nitrogen sources.

Accordingly, L. reuteri DSM 17938 was selected as a model probiotic strain to investigate the effects of silkworm pupae peptides prepared using Alcalase and Flavourzyme. The influence of different enzymatic hydrolysates on bacterial growth, viable cell counts, total organic acid accumulation and cellular morphology was evaluated, together with characterization of peptide molecular-weight distribution and amino acid composition. Furthermore, active peptide fractions were separated and characterized using ultrafiltration, gel filtration chromatography, ion exchange chromatography and LC-MS/MS analysis. This study aimed to examine the associations between peptide characteristics and the growth responses of L. reuteri DSM 17938, providing a basis for the development of silkworm pupae-derived nitrogen sources for probiotic fermentation.

2. Materials and methods

2.1. Materials and reagents

L. reuteri DSM 17938 was provided by Hebei Fremont Biotechnology Co., Ltd. (Handan, China). Silkworm pupae were purchased from Hechi Jinheng Biotechnology Co., Ltd. (Guangxi, China). Alcalase (BR grade, 200 U/mg) and Flavourzyme (BR grade, 20 U/mg) were obtained from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China); enzyme activities were specified by the manufacturer. HPLC-grade acetonitrile was purchased from Fisher Scientific (USA), trifluoroacetic acid from Sigma-Aldrich (USA), and lactic and acetic acid standards from Shanghai Yuanye Bio-Technology Co., Ltd. The amino acid standard mixture was obtained from Sigma-Aldrich. MRS components were of microbiological grade, and all other reagents were of analytical grade unless otherwise stated.

2.2. Preparation of defatted silkworm pupae powder

Defatted silkworm pupae powder was prepared as described by Zhou et al. (2016), with minor modifications. Dried pupae were finely ground, mixed with n-hexane at a solid-to-liquid ratio of 1:12 (w/v), and stirred at 45 °C for 5 h. Defatting was repeated once. The mixture was centrifuged at 8000 ×g for 10 min at 4 °C; the supernatant was discarded, and residual solvent was allowed to evaporate in a fume hood. The defatted powder was then passed through an 80-mesh sieve (180 μm) and stored in a cool, dry environment until use.

2.3. Preparation of silkworm pupae peptides

Silkworm pupae peptides were prepared according to Dai et al. (2023), with minor modifications. Defatted powder was suspended in distilled water at 20% (w/v). For Alcalase protease hydrolysis, the suspension was adjusted to pH 10.0, enzyme was added at 6% (w/w, relative to substrate), and hydrolysis proceeded at 45 °C for 3 h with continuous stirring. For Flavourzyme hydrolysis, the suspension was adjusted to pH 7.5 and incubated with the same enzyme-to-substrate ratio at 50 °C for 3 h. Enzymes were inactivated at 85 °C for 15 min. The hydrolysates were centrifuged, and the supernatants were freeze-dried and stored at −20 °C. Products generated with Alcalase protease and Flavourzyme were designated SPP-A and SPP-F, respectively.

2.4. Physicochemical characterization of silkworm pupae peptides

2.4.1. Determination of protein content

Protein content was determined by the Kjeldahl method in accordance with Chinese national standard GB 5009.5–2016.

2.4.2. Amino acid composition analysis

Amino acid composition was determined according to Chinese national standard GB 5009.124–2016. Samples were hydrolyzed with 6 mol/L hydrochloric acid at 110 ± 1 °C for 22 h under nitrogen. Following hydrolysis, the samples were processed according to the standard and analyzed using an amino acid analyzer with ion-exchange separation and post-column ninhydrin derivatization. Amino acids were quantified using external amino acid standards, and their contents were expressed as g/100 g of sample.

2.4.3. Molecular weight distribution analysis

Molecular-weight distribution was determined as described by Xun et al. (2025). SPP-A, SPP-F, and molecular-weight standards were dissolved in distilled water (1 mg/mL) and passed through a 0.22 μm membrane. Samples were analyzed using an HPLC–DAD system equipped with a TSKgel G2000SWXL column (300 mm × 7.8 mm, 5 μm). The mobile phase was acetonitrile/water/TFA (40:60:0.1, v/v/v), delivered at 0.5 mL/min; the injection volume was 10 μL, and detection was at 220 nm. A calibration curve relating retention time to the molecular weights of standards was used to estimate the relative molecular-weight distributions of the hydrolysates.

2.5. Evaluation of silkworm pupae peptides as nitrogen sources for L. reuteri DSM 17938

2.5.1. Preparation of fermentation media

Four media were prepared based on Zhang et al. (2022): complete MRS medium (MRS, positive control); MRS medium containing half of the standard nitrogen content (LN, nitrogen-limited control); and LN in which the removed nitrogen was replaced by an equivalent nitrogen amount supplied as SPP-A or SPP-F. Media were autoclaved at 121 °C for 15 min.

2.5.2. Growth performance and viable cell counts

L. reuteri DSM 17938 was activated twice in MRS medium before inoculation into the test media and incubation at 37 °C. OD₆₀₀ was measured every 2 h with a microplate reader. For viable counts, samples collected at 6, 10, 14, and 18 h were serially diluted in sterile 0.9% NaCl, plated on MRS agar, and incubated at 37 °C for 48 h. Counts were expressed as colony-forming units (CFU/mL). Experiments were performed in triplicate.

2.5.3. Organic acid analysis

Lactic and acetic acids were quantified by HPLC. Fermentation broth (2 mL) was centrifuged at 10,000 rpm for 10 min, and the supernatant was rapidly frozen in liquid nitrogen and stored at −80 °C. Separation was performed on an Aminex HPX-87H column (300 mm × 7.8 mm; Bio-Rad, Richmond, CA, USA) at 65 °C using 13 mmol/L sulfuric acid as the mobile phase (0.8 mL/min; 10 μL injection). Concentrations were calculated from peak areas using external calibration curves prepared with lactic and acetic acid standards.

2.5.4. Scanning electron microscopy observation

Cell morphology was examined by scanning electron microscopy (SEM). After fermentation, cells were collected, washed three times with phosphate-buffered saline, and fixed in 2.5% glutaraldehyde at 4 °C for 12 h. Samples were washed, dehydrated through graded ethanol (30%, 50%, 70%, 80%, 90%, and 100%), treated with tert-butanol, critical-point dried, sputter-coated with gold, and examined by SEM.

2.6. Bioactive peptide fractionation and purification

2.6.1. Ultrafiltration fractionation

SPP-A and SPP-F were dissolved separately in ultrapure water (20 mg/mL), passed through a 0.45 μm membrane, and fractionated sequentially using 5-, 3-, and 1-kDa molecular-weight-cutoff membranes. SPP-F yielded F1 (<1 kDa), F2 (1–3 kDa), and F3 (3–5 kDa); SPP-A yielded A1 (<1 kDa), A2 (1–3 kDa), and A3 (3–5 kDa). Fractions were freeze-dried, stored at −20 °C, and evaluated in the fermentation assay. Fractions with the strongest activity were advanced to further purification.

2.6.2. Sephadex G-50 gel filtration chromatography

Following the method described by (Ma et al., 2024), selected active fractions were separated on a Sephadex G-50 column (1.6 cm × 30 cm) equilibrated with ultrapure water. Peptide solutions (20 mg/mL) were passed through a 0.22 μm membrane, and 1 mL was loaded. Elution with ultrapure water was driven by a peristaltic pump at 50 r/min and monitored at 280 nm. Fractions were collected at 1-min intervals, freeze-dried, and evaluated for growth-promoting activity.

2.6.3. Ion exchange chromatography

SPP-A and SPP-F were separately fractionated using Q Sepharose Fast Flow anion-exchange chromatography, adapted from Kim et al. (2013). The selected fraction was dialyzed against 20 mmol/L Tris–HCl (pH 8.0) and loaded onto an equilibrated Q Sepharose column (1.6 cm × 20 cm). After washing with equilibration buffer, bound components were eluted with a 0–1 mol/L NaCl gradient in the same buffer at 1 mL/min and monitored at 214 nm. Target fractions were pooled, concentrated, dialyzed to remove salts, freeze-dried, and evaluated for activity and peptide composition.

2.7. LC–MS/MS identification of peptides in active fractions

Active fractions were dissolved in 0.1% trifluoroacetic acid, desalted using ZipTip C18 tips, vacuum-dried, reconstituted in 0.1% formic acid, and centrifuged at 17,000 ×g for 20 min at 4 °C. Supernatants were used for LC–MS/MS analysis.

Peptides were separated by nano-LC on a C18 analytical column (75 μm × 150 mm; Acclaim PepMap RPLC C18, 2 μm, 100 Å) at 300 nL/min. Solvent A was 2% acetonitrile/0.1% formic acid, and solvent B was acetonitrile/0.1% formic acid. The gradient was 2% B at 0–2 min, 2–20% B at 2–44 min, 20–32% B at 44–50 min, 32–90% B at 50–52 min, and 90% B at 52–60 min.

A Q Exactive high-resolution mass spectrometer (Thermo Scientific, USA) was operated in positive-ion mode at a capillary temperature of 270 °C and spray voltage of 2.2 kV. Full scans were acquired over m/z 300–1650 at a resolution of 70,000. The 20 most intense precursor ions were selected for higher-energy collisional dissociation at a normalized collision energy of 27%.

Raw spectra were processed in PEAKS Studio and searched against the Bombyx mori UniProt protein database. Precursor and fragment mass tolerances were 10 ppm and 0.02 Da, respectively. Methionine oxidation and N-terminal acetylation were specified as variable modifications; no fixed modification was specified. Identifications were filtered to a false discovery rate below 1%.

2.8. Statistical analysis

Experiments were independently performed at least three times, and data are presented as means ± standard deviations. Statistical analyses were conducted using IBM SPSS Statistics 27.0, and figures were prepared using Origin 2019. Fermentation data were analyzed using linear mixed-effects models, with treatment, time as a categorical factor, and their interaction as fixed effects and fermentation culture as a random intercept to account for repeated sampling. Models were fitted using restricted maximum likelihood, and fixed effects were evaluated using F-tests. Comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. Molecular-weight distribution and amino acid composition data in Table 1 were analyzed using one-way ANOVA followed by Tukey's multiple-comparison test. Statistical significance was set at p < 0.05.

Table 1.

Molecular weight distribution of silkworm pupae protein hydrolysates and amino acid composition of defatted silkworm pupae powder and its hydrolysates. (A) Molecular weight distribution of SPP-F and SPP-A. (B) Amino acid composition of defatted silkworm pupae powder (SP), SPP-A, SPP-F.

Molecular weight (kDa)	>5	3–5	1–3	0.5–1	<0.5
SPP-A (%)	0.18 ± 0.01a	5.57 ± 0.15b	26.24 ± 0.28a	19.97 ± 0.19a	48.03 ± 0.09a
SPP-F (%)	0.18 ± 0.01a	7.10 ± 0.15a	25.81 ± 0.37a	19.64 ± 0.19a	47.27 ± 0.07b

Amino acid (g/100 g)	SP	SPP-A	SPP-F
Lys	6.20 ± 0.03b	6.37 ± 0.05a	6.21 ± 0.06b
Trp	1.16 ± 0.04a	1.12 ± 0.06a	1.14 ± 0.08a
Met	2.12 ± 0.05a	2.29 ± 0.09a	2.26 ± 0.08a
Cys	2.03 ± 0.07a	2.10 ± 0.07a	2.16 ± 0.06a
Asp	10.21 ± 0.04c	11.09 ± 0.06a	10.88 ± 0.10b
Thr	4.13 ± 0.01b	4.41 ± 0.05a	4.41 ± 0.10a
Ser	3.83 ± 0.12b	4.04 ± 0.05a	4.06 ± 0.03a
Glu	10.95 ± 0.08c	11.68 ± 0.04a	11.45 ± 0.06b
Gly	3.32 ± 0.07b	3.49 ± 0.06a	3.35 ± 0.03b
Ala	3.84 ± 0.02a	3.86 ± 0.04a	3.92 ± 0.06a
Val	6.52 ± 0.03a	6.60 ± 0.06a	6.65 ± 0.06a
Ile	4.82 ± 0.03b	4.92 ± 0.04a	4.87 ± 0.03ab
Leu	7.79 ± 0.10b	8.02 ± 0.06a	7.93 ± 0.05ab
Tyr	4.81 ± 0.06c	4.98 ± 0.06b	5.12 ± 0.07a
Phe	6.81 ± 0.02c	6.99 ± 0.04a	6.89 ± 0.04b
His	2.50 ± 0.03b	2.57 ± 0.05ab	2.60 ± 0.03a
Arg	5.17 ± 0.05b	5.37 ± 0.06a	5.36 ± 0.04a
Pro	3.01 ± 0.04b	3.20 ± 0.05a	3.23 ± 0.06a

Notes: Values are expressed as mean ± SD from three independent analytical replicates (n = 3). Different lowercase superscript letters within the same column in panel A or within the same row in panel B indicate significant differences among samples (p < 0.05). SPP-A, silkworm pupae protein hydrolysate prepared using Alcalase; SPP-F, silkworm pupae protein hydrolysate prepared using Flavourzyme.

3. Results and discussion

3.1. Enzymatic hydrolysis generated predominantly low-molecular-weight peptides

SPP-A and SPP-F showed closely similar molecular-weight profiles (Fig. 1). Components above 5 kDa accounted for only 0.18% of each hydrolysate, whereas more than 92% occurred below 3 kDa. The fraction under 500 Da was the largest, accounting for 48.03% of SPP-A and 47.27% of SPP-F. The 500–1000 Da fractions accounted for 19.97% and 19.64%, and the 1–3 kDa fractions for 26.24% and 25.81%, respectively (Table 1A). All amino acids detected in defatted silkworm pupae powder (SP) were retained after hydrolysis (Table 1B). Aspartic acid contents were 10.21 ± 0.04, 11.09 ± 0.06, and 10.88 ± 0.10 g/100 g in SP, SPP-A, and SPP-F, respectively; the corresponding glutamic acid contents were 10.95 ± 0.08, 11.68 ± 0.04, and 11.45 ± 0.06 g/100 g. For both amino acids, SPP-A had significantly higher contents than SPP-F, and both hydrolysates had significantly higher contents than SP (p < 0.05).

Fig. 1.

Molecular weight distribution profiles of SPP-F and SPP-A. (A) Molecular weight distribution profiles of SPP-F, (B) Molecular weight distribution profiles of SPP-A.

Together, these results established that both enzyme treatments produced peptide-rich nitrogen sources dominated by components below 3 kDa, while providing descriptive compositional profiles for both hydrolysates. Although Alcalase and Flavourzyme generated broadly similar molecular-weight distributions, Alcalase acts primarily as an endopeptidase, whereas Flavourzyme combines endo- and exopeptidase activities; these catalytic differences can alter peptide termini and sequence patterns even when bulk size profiles are similar (Merz et al., 2015; Tacias-Pascacio et al., 2020). The differences in total amino acid composition are unlikely, by themselves, to explain the observed biological differences. Previous studies in lactic acid bacteria have shown that peptide utilization depends not only on peptide size but also on physicochemical and sequence-related characteristics, including charge and hydrophobicity, which can influence substrate recognition and uptake by peptide transport systems (Detmers et al., 1998; Juillard et al., 1998). Profiling of crude hydrolysates cannot resolve the respective growth-promoting contributions of heterogeneous peptide sub-fractions differing in molecular weight and physicochemical features. Accordingly, activity-guided fractionation approaches were adopted to further dissect how peptide size and charge modulate the fermentative performance of L. reuteri DSM 17938.

3.2. SPP-A and SPP-F improved growth performance and overall organic acid accumulation under nitrogen limitation

To evaluate the potential of silkworm pupae peptides as alternative nitrogen sources for L. reuteri DSM 17938, the effects of the SPP-A and the SPP-F supplementation on bacterial growth, viable cell counts, total organic acid accumulation, and cell morphology were investigated. Growth of L. reuteri DSM 17938 was compared in MRS, nitrogen-limited medium (LN), and LN supplemented with an equivalent nitrogen amount from SPP-A or SPP-F (Fig. 2). Growth patterns were similar during the first 10 h. Thereafter, OD₆₀₀ increased more rapidly in both peptide-supplemented groups than in MRS and LN groups (p < 0.05). The SPP-A group showed a higher growth level throughout fermentation compared with the SPP-F group.

Fig. 2.

Growth, metabolic profiles, and cellular morphology of limosilactobacillus reuteri DSM 17938 under different culture conditions. (A) Growth curves; (B) viable cell counts; (C) lactic acid content; (D) acetic acid content; (E) scanning electron microscopy (SEM) images after 10 h of cultivation; and (F) SEM images after 18 h of cultivation. Notes: MRS, de Man–Rogosa–Sharpe broth; LN, MRS broth containing half the original nitrogen source concentration. SPP-A and SPP-F denote LN supplemented with Alcalase- and Flavourzyme-generated silkworm pupae hydrolysates, respectively. Data in (A–D) are presented as means ± SD from three independent experiments (n = 3). Data in (B–D) were analyzed separately using linear mixed-effects models, with treatment, categorical time, and their interaction as fixed effects and individual fermentation culture as a random intercept to account for repeated sampling. The treatment × time interaction was significant for each outcome in (B–D) (p < 0.001). Pairwise comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. In (B–D), different lowercase letters indicate significant differences among treatments at the same time point, and different uppercase letters indicate significant differences among time points within the same treatment (p < 0.05).

Viable counts corroborated the growth curve results (Fig. 2B). The peptide groups did not show an early advantage at 6 h. After 10 h, the viable cell counts of both SPP-A and SPP-F groups increased significantly. However, the SPP-A group was 1.68-fold that of MRS and 1.78-fold that of LN (p < 0.05), and it remained the highest among the treatments at 14 h. Counts declined in all groups by 18 h, but both peptide-supplemented groups retained significantly greater viability than MRS and LN group. Lactic acid and acetic acid concentrations also rose during fermentation (Fig. 2C, D). No group difference was detected at 6 h, whereas both SPP-A and SPP-F produced more lactic acid than MRS and LN from 10 h to 18 h (p < 0.05). Acetic acid showed similar pattern, with greater accumulation in the peptide-supplemented groups during the log phase and stationary phase. The SPP-A group exhibited the highest accumulation of lactic acid and acetic acid after 14 h and 18 h. The onset of increased acid production therefore coincided with the divergence in viable counts. Because the peptide-supplemented cultures also had higher viable counts, the greater organic acid accumulation may partly reflect a larger bacterial population rather than increased cell-specific metabolic activity. The increases in growth and overall organic acid accumulation observed following SPP-A and SPP-F supplementation are consistent with previous findings that soybean proteins and peptides enhanced the growth and organic acid secretion of L. reuteri LR08 (Zhang et al., 2022). Related growth and metabolic responses have also been reported for Lacticaseibacillus rhamnosus and Bifidobacterium animalis supplied with soybean-derived nitrogen sources (Li et al., 2021; Zhang et al., 2021). Together, these studies support the potential of protein-derived nitrogen sources to improve probiotic fermentation, while indicating that their effects should be evaluated for individual strains and substrates.

Overall, both SPP-A and SPP-F effectively improved the growth performance, viable cell counts, and total organic acid accumulation of L. reuteri DSM 17938 under nitrogen-restricted conditions. Among them, SPP-A showed stronger effects compared with SPP-F. These findings indicate that silkworm pupae peptides, particularly SPP-A, have potential as functional nitrogen sources for supporting L. reuteri DSM 17938 fermentation, motivating activity-guided fractionation.

3.3. Molecular-size fractionation revealed growth-stage-dependent activity of L. reuteri DSM 17938

3.3.1. Activity of SPP-F ultrafiltration fractions

During the 4–12 h logarithmic phase, SPP-F, positive-control MRS, and fractions F1, F2 and F3 entered rapid growth at a similar time point, with no obvious differences in growth onset. F2 showed the strongest growth response, followed by F3 and F1, whereas the negative control LN showed substantially poor growth capacity. In the stationary phase after 12 h, SPP-F peaked at 14 h with the highest OD₆₀₀ and then declined rapidly. In contrast, the separated fractions maintained relatively stable OD₆₀₀ values in late stationary phase (Fig. 3A). At 10 h, the viable counts for the F2 group were approximately 1.19-fold those in MRS and was significantly higher than those in LN (p < 0.05; Fig. 3B). F2 maintained a relatively high count at 14 h and remained more effective than the other fractions at 18 h. Its bioactivity was even higher than that of original SPP-F. It indicates that the smallest molecular-weight fraction was not necessarily the most effective under our culture conditions. Previous studies have characterized soybean peptides associated with enhanced growth and metabolism of L. reuteri LR08 (Zhang et al., 2022), while specific RP-HPLC fractions of digested soybean peptides exhibited stronger growth- and metabolism-promoting effects on L. rhamnosus Lra05 than other fractions (Zhang et al., 2023). These findings support evaluating individual peptide fractions rather than predicting their activity solely from molecular-weight ranges. It should also be noted that the abundant below 0.5 kDa fraction, which accounts for more than 47% of both hydrolysates, may contain not only short low-molecular-weight peptides but also free amino acids. Accordingly, the growth-promoting bioactivity attributed to low-molecular-weight peptides in the present study could also partially originate from free amino acids and other small nitrogenous substrates readily available for L. reuteri utilization.

Fig. 3.

Effects of SPP-F and its ultrafiltration fractions on the growth curves (A), viable cell counts (B), lactic acid content (C), and acetic acid content (D) of limosilactobacillus reuteri DSM 17938. Notes: MRS, de Man–Rogosa–Sharpe broth; LN, MRS broth containing half the original nitrogen source concentration. SPP-F denotes LN supplemented with the Flavourzyme-generated silkworm pupae hydrolysate. F1, F2, and F3 denote LN supplemented with the <1, 1–3, and 3–5 kDa fractions, respectively, obtained from SPP-F by ultrafiltration. Data in (A–D) are presented as means ± SD from three independent experiments (n = 3). Data in (B–D) were analyzed separately using linear mixed-effects models, with treatment, categorical time, and their interaction as fixed effects and individual fermentation culture as a random intercept to account for repeated sampling. The treatment × time interaction was significant for each outcome in (B–D) (p < 0.001). Pairwise comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. In (B–D), different lowercase letters indicate significant differences among treatments at the same time point, and different uppercase letters indicate significant differences among time points within the same treatment (p < 0.05).

The effects of different SPP-F fractions on overall organic acid accumulation were further evaluated (Fig. 3C and D). Among all tested fractions, F2 resulted in the highest lactic acid concentration during the logarithmic growth phase and the highest acetic acid concentration during the stationary phase. F3 also showed an increased lactic acid concentration after 14 h of cultivation. Higher lactic and acetic acid concentrations in the F2 group corresponded to its higher viable cell counts, reflecting greater total acid accumulation in this culture. Collectively, the 1–3 kDa fraction (F2) derived from SPP-F exhibited the strongest growth response and overall acid accumulation on L. reuteri DSM 17938 and was therefore selected for further purification to identify more active peptide fractions.

3.3.2. Activity of SPP-A ultrafiltration fractions

In a similar way to SPP-F, SPP-A was also separated into A1 (<1 kDa), A2 (1–3 kDa), and A3 (3–5 kDa). As shown in Fig. 4A, all SPP-A-derived fractions exhibited different degrees of growth-promoting effects. During the log stage (6–10 h), the A1, A2 and A3 fraction showed higher growth rate than MRS and SPP-A. However, when growth enters the stationary phase, the A3 fraction exhibited the highest growth level. A1 and A2 group showed lower growth than MRS. Viable counts showed a similar phase-specific pattern (Fig. 4B). A2 produced the highest count at 10 h. At 14 h, A3 group reached the highest viable count, approximately 1.10-fold that in MRS (p < 0.05). At 18 h, A3 and SPP-A remained at approximately 1.12- and 1.05-fold the MRS count, respectively.

Fig. 4.

Effects of SPP-A and its ultrafiltration fractions on the growth (A), viable cell counts (B), lactic acid content (C), and acetic acid content (D) of limosilactobacillus reuteri DSM 17938. Notes: MRS, de Man–Rogosa–Sharpe broth; LN, MRS broth containing half the original nitrogen source concentration. SPP-A denotes LN supplemented with the Alcalase-generated silkworm pupae hydrolysate. A1, A2, and A3 denote LN supplemented with the <1, 1–3, and 3–5 kDa fractions, respectively, obtained from SPP-A by ultrafiltration. Data in (A–D) are presented as means ± SD from three independent experiments (n = 3). Data in (B–D) were analyzed separately using linear mixed-effects models, with treatment, categorical time, and their interaction as fixed effects and individual fermentation culture as a random intercept to account for repeated sampling. The treatment × time interaction was significant for each outcome in (B–D) (p < 0.001). Pairwise comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. In (B–D), different lowercase letters indicate significant differences among treatments at the same time point, and different uppercase letters indicate significant differences among time points within the same treatment (p < 0.05).

The effects of different SPP-A fractions on total organic acid accumulation were further analyzed (Fig. 4C and D). At 10 h, the A2 fraction yielded 8.70 g/L lactic acid and 2.98 g/L acetic acid, compared with 8.00 and 2.67 g/L in MRS. At 14 h and 18 h, A3 produced 4.07 and 3.89 g/L acetic acid, respectively, which were significantly higher than those of other treatments. Thus, A2 was associated with the early response, whereas A3 better sustained later viability and overall acid accumulation. Considering the comprehensive effects on bacterial growth and fermentation performance, the A2 and A3 fractions were selected for further purification and activity evaluation.

3.3.3. Gel filtration localized activity within the 1–3 kDa range

To further enrich the active peptide components, the selected fractions F2 (SPP-F, 1–3 kDa), A2 (SPP-A, 1–3 kDa), and A3 (SPP-A, 3–5 kDa) were further separated by Sephadex G-50 gel filtration chromatography (Fig. 5A, B, C). Based on the elution profiles, six subfractions were obtained, including F2–1 (1–2 kDa), F2–2 (2–3 kDa) from F2; A2–1 (1–2 kDa), A2–2 (2–3 kDa) from A2; A3–1 (3–4 kDa), and A3–2 (4–5 kDa) from A3. The effects of these fractions on the growth performance and viable cell counts of L. reuteri DSM 17938 were subsequently evaluated.

Fig. 5.

Gel filtration chromatographic profiles of silkworm pupae peptide fractions and effects of the resulting subfractions on the growth of limosilactobacillus reuteri DSM 17938. (A) Chromatographic profile of the SPP-A 1–3 kDa fraction; (B) chromatographic profile of the SPP-A 3–5 kDa fraction; (C) chromatographic profile of the SPP-F 1–3 kDa fraction; (D) growth curves; and (E) viable cell counts. Notes: MRS, de Man–Rogosa–Sharpe broth; LN, MRS broth containing half the original nitrogen source concentration. F2–1 and F2–2 denote LN supplemented with the 1–2 and 2–3 kDa subfractions, respectively, obtained from SPP-F by gel filtration chromatography. A2–1 and A2–2 denote LN supplemented with the 1–2 and 2–3 kDa subfractions, respectively, obtained from SPP-A. A3–1 and A3–2 denote LN supplemented with the 3–4 and 4–5 kDa subfractions, respectively, obtained from SPP-A. Data in (D) and (E) are presented as means ± SD from three independent experiments (n = 3). Data in (E) were analyzed separately using linear mixed-effects models, with treatment, categorical time, and their interaction as fixed effects and individual fermentation culture as a random intercept to account for repeated sampling. The treatment × time interaction was significant for each outcome in (E) (p < 0.001). Pairwise comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. In (E), different lowercase letters indicate significant differences among treatments at the same time point, and different uppercase letters indicate significant differences among time points within the same treatment (p < 0.05).

As shown in Fig. 5D, supplementation with different Sephadex G-50 fractions improved the growth of L. reuteri DSM 17938 compared with the LN group, although differences were observed among fractions. During the log phase, F2–1, F2–2, and A2–2 fractions exhibited higher growth-promoting effects, with OD600 values exceeding those of the LN group and approaching or even slightly exceeding the MRS group. In contrast, the growth-promoting effects of A3–1 and A3–2 were relatively weaker. While the growth enters stationary phase, F2–1 and A2–2 continue to exhibit high activity.

The viable cell counts results showed a little different trend (Fig. 5E). During the early fermentation stage (6 h), no significant differences were observed among the different treatments. However, at 14 h, the F2–1 group showed the highest viable cell count, reaching approximately 1.06-fold that of the MRS group. At 18 h, although viable cell counts decreased in all groups, F2–1, A2–2, and A3–2 maintained relatively higher cell viability, reaching approximately 1.06-, 1.02-, and 1.08-fold of the MRS group, respectively. Comparable effects have been reported for casein-derived fractions below 3 kDa, which enhanced the growth and lactic acid production of yoghurt cultures containing Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus (Zhang et al., 2011). However, Xiong et al. (2024) identified the 2–5 kDa fraction of wheat protein hydrolysates as an important nutrient source for promoting Lactobacillus acidophilus growth. These findings suggest that the molecular-weight range associated with growth-promoting activity may vary with the protein source and bacterial strain.

Overall, Sephadex G-50 fractionation further enriched fractions associated with growth-promoting activity from the ultrafiltration fractions. Among the purified fractions, F2–1 (1–2 kDa) and A2–2 (2–3 kDa) showed the strongest effects on supporting the growth and survival of L. reuteri DSM 17938. Therefore, these fractions were selected for subsequent LC-MS/MS analysis to profile the peptides present in the active fractions and to investigate their potential relationship with the observed bioactivity.

3.4. Charge-based separation identified FI-2 as the most consistently active fraction

To investigate whether silkworm pupae peptides fraction at different dimensions exerts differential effects on the growth and metabolism of L. reuteri, ion-exchange chromatography was performed to obtain peptide fractions according to their charge properties. SPP-A and SPP-F were subjected to ion-exchange fractionation, resulting in three fractions from SPP-F (FI-1–FI-3) and four fractions from SPP-A (AI-1–AI-4) (Fig. 6A and B). The effects of individual fractions on the growth performance and viable cell counts of L. reuteri DSM 17938 were subsequently evaluated.

Fig. 6.

Ion-exchange chromatographic profiles of silkworm pupae hydrolysates and effects of the resulting fractions on the growth of limosilactobacillus reuteri DSM 17938. (A) Chromatographic profile of SPP-F; (B) chromatographic profile of SPP-A; (C) growth curves; and (D) viable cell counts. Notes: MRS, de Man Rogosa Sharpe broth; LN, MRS broth containing half the original nitrogen source concentration. AI-1–AI-4 denote LN supplemented with the corresponding peak fractions (peaks 1–4) obtained from SPP-A by ion-exchange chromatography; FI-1–FI-3 denote LN supplemented with the corresponding peak fractions (peaks 1–3) obtained from SPP-F. Data in (C) and (D) are presented as means ± SD from three independent experiments (n = 3). Data in (D) were analyzed separately using linear mixed-effects models, with treatment, categorical time, and their interaction as fixed effects and individual fermentation culture as a random intercept to account for repeated sampling. The treatment × time interaction was significant for each outcome in (D) (p < 0.001). Pairwise comparisons among treatments at each time point and among time points within each treatment were performed using estimated marginal means with Bonferroni adjustment. In (D), different lowercase letters indicate significant differences among treatments at the same time point, and different uppercase letters indicate significant differences among time points within the same treatment (p < 0.05).

During log phase, FI-2 and FI-3 exhibited higher growth-promoting effect than other fraction groups and MRS. When entering stationary phase, FI-3 gradually slow down the growth rate, however, FI-2 group still maintain higher growth level. FI-1 and AI-3 groups also surpass MRS groups during stationary phase (Fig. 6C). The differences among ion-exchange fractions were further confirmed by viable cell count analysis (Fig. 6D). At 10 h, viable counts in AI-3 and FI-2 were approximately 1.10- and 1.14-fold that in MRS, respectively (p < 0.05; Fig. 6D). At 14 h, FI-2 group exhibited the highest viable cell count among all treatments, approximately 1.10-fold higher than that of the MRS group. At the end of cultivation (18 h), although viable cell counts decreased in all groups, FI-2 and AI-3 fractions still maintained relatively higher cell numbers compared with other ion-exchange fractions. The different activities of the ion-exchange fractions suggest that charge-associated differences in fraction composition may contribute to the growth response of L. reuteri DSM 17938.

Among all tested fractions, FI-2 exhibited the strongest and most consistent effect on supporting the growth and survival of L. reuteri DSM 17938, followed by AI-3 and FI-1. FI-2 maintained the clearest advantage across sampling times, supporting the view that molecular size alone does not determine performance (Detmers et al., 2000). Therefore, the FI-2 fraction was selected for subsequent LC-MS/MS analysis to identify the peptide sequences associated with the observed bioactivity.

3.5. Peptide profiles of the active fractions

3.5.1. FI-2 contained a small set of predominantly acidic, hydrophilic peptides

Following ion-exchange chromatographic fractionation, the peptide composition of fraction FI-2 was characterized by mass spectrometry. LC–MS/MS initially identified 3013 peptide sequences in FI-2. Applying thresholds of −10lgP ≥ 20 and peak area ≥ 1 × 107 retained 16 high-confidence peptides (Table 2A). Their molecular masses ranged from 676.34 to 3620.89 Da and their lengths from 6 to 32 residues. The ten most abundant peptides averaged 16.7 residues in length, indicating that FI-2 comprised both short oligopeptides and relatively long peptides rather than being selectively enriched according to molecular size. The most abundant peptide, YPYEPTPKESEPF (13 residues, 3.00%), contained several polar or charged residues, particularly Glu and Lys, interspersed with aromatic Tyr and Phe and nonpolar Pro residues. This peptide was classified as hydrophilic and had a predicted pI of 4.02. The second most abundant peptide, SVVVADYDSAVEKSKHLYEEKKSEVITNVVNK (32 residues, 2.94%), contained a Val-rich N-terminal region and several Asp, Glu and Lys residues elsewhere in its sequence. It was classified as hydrophilic, with a predicted pI of 5.56. Several other abundant peptides, including SVVVADYDSAVEKSKH (16 residues, 1.91%) and SVVVADYDSAVEKSKHLYEEKKS (23 residues, 1.71%), overlapped with this 32-residue sequence. These overlapping sequences may have arisen from successive cleavage of related precursor proteins. In contrast, the short peptides GDFPDIL (7 residues, 2.06%) and GLPDIY (6 residues, 1.40%), as well as GHDGEVAGLPDIF (13 residues, 1.23%), were classified as hydrophobic and shared a PDIL/GLPDI-related sequence motif enriched in Leu, Ile, Phe and Pro. Overall, seven of the ten most abundant peptides and 12 of the 15 unique peptides were hydrophilic. The most abundant peptides were particularly enriched in Val (13.8%), Glu (12.6%), Lys and Ser (10.8% each), and Asp (9.6%), representing both nonpolar and polar or charged residues. Moreover, most peptides had acidic-to-near-neutral isoelectric points. Eight exhibited pI values below 5.0 and six had pI values between 5.0 and 7.5, whereas only one peptide showed a basic pI of 9.44. This charge distribution is consistent with the charge-selective nature of ion-exchange chromatography, although the precise retention behavior would additionally depend on the exchanger type and the pH and ionic strength of the mobile phase. Collectively, most of the peptides identified in FI-2 were hydrophilic, with a small number of short hydrophobic peptides, and their pI ranged from acidic to near-neutral. The recurrent overlapping motifs indicated that a limited number of precursor proteins, particularly lipoprotein-related proteins, contributed multiple peptide products through stepwise proteolytic cleavage.

Table 2.

Identification and characterization of selected peptides from FI-2 and F2–1. (A) Selected peptides identified in FI-2, (B) the 20 most abundant peptides identified in F2–1. (A) Selected peptides identified in FI-2. (B) The 20 most abundant peptides identified in F2–1.

Peptide	Mass (Da)	Length	Abundance (%)	Source protein description	Isoelectric point (pI)	Hydrophobicity
YPYEPTPKESEPF	1582.72	13	3.00	30 kDa lipoprotein	4.02	Hydrophilic
SVVVADYDSAVEKSKHLYEEKKSEVITNVVNK	3606.88	32	2.94	DNA ligase	5.56	Hydrophilic
GDFPDIL	775.38	7	2.06	Hemocyanin C-terminal domain-containing protein	2.96	Hydrophobic
SVVVADYDSAVEKSKH	1732.86	16	1.91	Low molecular mass lipoprotein	5.31	Hydrophilic
SVVVADYDSAVEKSKHLYEEKKS	2610.32	23	1.71	Hemocyanin C-terminal domain-containing protein	5.50	Hydrophilic
SIVVADYDSAVEKSKHLYEEKKSEVITNVVNK	3620.89	32	1.42	Low molecular mass lipoprotein 4	5.56	Hydrophilic
GLPDIY	676.34	6	1.40	Low molecular mass lipoprotein	3.13	Hydrophobic
ADSDVPNDILEEQ	1443.64	13	1.31	Vitellogenin	2.79	Hydrophilic
YPYEPTPKESEP	1435.65	12	1.26	30 kDa protein	4.02	Hydrophilic
GHDGEVAGLPDIF	1325.63	13	1.23	Low molecular mass lipoprotein	3.73	Hydrophobic
SAVEKSKHLYEEKKSEVITNVVNK	2758.49	24	1.18	Low molecular mass lipoprotein	9.44	Hydrophilic
SIVVADYDSAVEKSKH	1746.88	16	1.09	Low molecular mass lipoprotein	5.31	Hydrophilic
SIVVADYDSAVEKSKHLYEEKKS	2624.33	23	0.90	Low molecular mass lipoprotein	5.50	Hydrophilic
DEDMAANEDREA	1380.51	12	0.83	Low molecular mass lipoprotein	3.41	Hydrophilic
SVVVADYDSAVEKSKHLYEEKKSEVITN	3166.60	28	0.82	30 kDa protein	4.88	Hydrophilic
SIVVADYDSAVEKSKH	1746.88	16	1.09	Low molecular mass lipoprotein	5.31	Hydrophilic

Peptide	Mass (Da)	Length	Abundance (%)	Source protein description	Isoelectric point (pI)	Hydrophobi-city
LPRGTEGGFP	1029.52	10	2.49	Surface layer protein	6.94	Hydrophilic
NEPLETGYWPK	1332.64	11	1.85	Lipoprotein	4.33	Hydrophilic
LPDIFSW	876.44	7	1.77	Lipoprotein	3.13	Hydrophobic
IPHYTPDKAQL	1281.67	11	1.72	Lipoprotein	7.72	Hydrophilic
LPRGTEGGFPFQ	1304.65	12	1.69	Surface layer protein	6.94	Hydrophilic
GLPDIYSW	949.45	8	1.43	Lipoprotein	3.13	Hydrophilic
YPYEPTPKESEPFKS	1797.85	15	1.4	Lipoprotein	4.62	Hydrophilic
LPKGTYDGFP	1093.54	10	1.27	Lipoprotein	6.65	Hydrophilic
AGLPDIF	731.39	7	1.17	Lipoprotein	3.13	Hydrophobic
LPPFNS	673.34	6	1.14	Lipoprotein	5.97	Hydrophilic
SILTGDYDSAVRQS	1510.73	14	1.11	Lipoprotein	3.91	Hydrophilic
FPYI	538.28	4	1.07	Lipoprotein	5.92	Hydrophobic
GLPDIFS	747.38	7	0.88	Lipoprotein	3.13	Hydrophobic
LPRGTEGGFPF	1176.59	11	0.87	Surface layer protein	6.94	Hydrophilic
YPTIP	589.31	5	0.86	Lipoprotein	5.92	Hydrophilic
GDFPDILA	846.41	8	0.78	Lipoprotein	2.96	Hydrophobic
AGLPDIFSW	1004.5	9	0.75	Lipoprotein	3.13	Hydrophobic
WNEPLETGYWPK	1518.71	12	0.73	Lipoprotein	4.33	Hydrophilic
IPDIF	603.33	5	0.67	Lipoprotein	3.13	Hydrophobic
VPVPQPYP	895.48	8	0.63	Lipoprotein	5.92	Hydrophilic

3.5.2. F2–1 was enriched in short, hydrophilic, and acidic peptides

The peptide composition of the most active gel filtration fraction F2–1 was further characterized by LC-MS/MS analysis. A total of 4494 peptide sequences were initially identified, of which 116 met the identification-confidence (−10lgP ≥ 20) and peak-area (≥ 1 × 107) thresholds. The identified peptides ranged from 375.22 to 1881.94 Da, with 57.8% between 800 and 1400 Da, which was consistent with the molecular weight range obtained by Sephadex G-50 fractionation. Peptides containing 3–5, 6–9, 10–13, and 14–18 residues accounted for 21%, 33%, 32%, and 14%, respectively. Among the 116 high-confidence peptides, 77 (66.4%) were hydrophilic and 39 (33.6%) were hydrophobic. Approximately 60% had predicted pI values below 6.0, consistent with frequent Asp and Glu residues.

In F2–1, the 20 most abundant peptide sequences are listed in Table 2B, and the remaining identified peptides are provided in Table S1. Sequence analysis of the 116 peptides identified in fraction F2–1 revealed a pronounced enrichment of several structurally related high-abundance peptides. The 10 and 20 most abundant peptides accounted for 31.0% and 47.3% of the total peptide abundance, respectively. The top 20 peptides contained 4–15 amino acid residues, with a mean length of 9.0 residues, while peptide abundance showed essentially no association with peptide length (Spearman's ρ = −0.025). Of the 20 most abundant peptides, 13 were classified as hydrophilic and seven as hydrophobic; many contained both polar and nonpolar residues. Nonpolar or aromatic residues, including Pro, Leu, Ile, Phe, Tyr, and Trp, represented approximately 56.1% of the residues, whereas polar or ionizable residues accounted for 33.3%, with Gly comprising the remaining 10.6%. Pro was the most abundant residue (18.9%), followed by Gly (10.6%), Phe and Leu (8.3% each), Asp and Ile (6.7% each), and Tyr (6.1%). The frequent interspersion of acidic or polar residues, particularly Asp, Glu, Ser, and Thr, among Pro-, Leu-, Ile-, and aromatic-rich regions explains why many peptides were classified as hydrophilic despite containing substantial hydrophobic domains. Consistently, 11 of the top 20 peptides had pI values below 5.0, with a mean pI of 4.89. F2–1 contained predominantly hydrophilic peptides with a broad distribution of chain lengths. Previous studies have reported that peptide utilization varies with both hydrophobicity and chain length. For example, L. rhamnosus Lra05 preferentially utilized hydrophobic soybean peptides containing three to five residues and hydrophilic peptides containing more than five residues (Zhang et al., 2023). Cui et al. (2022) also reported a high affinity of bifidobacteria for hydrophilic peptides containing growth-promoting amino acids, with strain-dependent differences in the lengths of transportable peptides. Sequence ordering was non-random. Leu frequently occurred at the N-terminus, particularly as an LP motif, whereas Pro, Ser, Phe, and Trp were common C-terminal residues. Recurrent motifs included LP, PD, DI, FP, and IF, and several overlapping peptide families were identified, including LPRGTEGGFP/LPRGTEGGFPF/LPRGTEGGFPFQ,NEPLETGYWPK/WNEPLETGYWPK/EPLETGYWPK, and LPDIFSW/AGLPDIFSW/GLPDIFS/IPDIF. These nested sequences suggest stepwise N- or C-terminal trimming of common precursor proteins and the preferential retention of relatively stable peptide cores. The abundance of Pro may promote turn formation, disrupt extended secondary structures, and increase resistance to further proteolysis (Yaron et al., 1993). Notably, 17 of the top 20 peptides originated from lipoproteins and the remaining three from surface-layer proteins, indicating that these proteins were the principal precursors of the dominant peptides in F2–1. Similar hydrophobic motifs have been reported in food-derived peptides, where such residues influence structural properties and intermolecular interactions (López-Pérez et al., 2017). The repeated occurrence of LPDIF-related and LPRGTEGGFP-derived fragments from different precursor proteins suggests preferential cleavage of these regions during enzymatic hydrolysis. Their frequent generation may be linked to greater accessibility of these protein regions to proteolytic attack (Ji et al., 2021).

While fraction F2–1 displayed growth-promoting bioactivity, it comprises a complex pool of peptides with varied sequences and physicochemical characteristics. LC-MS/MS enabled identification of candidate structural features associated with this active fraction. Nevertheless, peptide profiling and relative abundance information alone are insufficient to pinpoint which individual sequences are responsible for the observed effect. Assessing these peptide candidates via individual synthesis, functional assays, and measurement of their uptake by L. reuteri DSM 17938 falls outside the scope of the current work. Thus, the functional roles of discrete peptides and the proposed structure-utilization relationship require further experimental validation in future investigations.

4. Conclusions

This study systematically demonstrates that silkworm pupa-derived peptides (SPPs) can serve as effective functional nitrogen sources for limosilactobacillus reuteri DSM 17938. Both Alcalase (SPP-A) and Flavourzyme (SPP-F) hydrolysates were dominated by low-molecular-weight components (<3 kDa, >92.00%). SPP-A had significantly higher aspartic acid, glutamic acid, lysine, and phenylalanine contents than SPP-F. SPP-A also showed a stronger growth response under these conditions.

Activity-guided fractionation uncovered a previously unrecognized stage-dependent size effect. 1–3 kDa peptides accelerated exponential-phase proliferation, whereas the 3–5 kDa SPP-A fraction better sustained late-stage viability and acid accumulation. This temporal complementarity suggests that tailored peptide blends could optimize fermentation performance across the entire cultivation cycle. Further purification by gel filtration and ion-exchange chromatography identified F2–1 (1–2 kDa), A2–2 (2–3 kDa), and FI-2 as highly active fractions. LC-MS/MS profiling revealed that F2–1 is enriched in short (3–18 residues), predominantly hydrophilic and acidic peptides derived from lipoproteins, with recurrent hydrophobic motifs that may facilitate bacterial uptake and utilization. However, individual peptides were neither synthesized nor independently tested. Their growth-promoting activities and uptake by L. reuteri DSM 17938 therefore remain to be verified in future investigation.

Collectively, these findings establish that the probiotic response to SPPs is not merely a function of total nitrogen content but is critically modulated by peptide size distribution and charge characteristics. This work provides a rational framework for designing silkworm pupa-derived peptide ingredients with targeted growth-promoting functions, while offering a sustainable strategy to valorise an underutilized protein resource in functional food and fermentation applications. Future studies should focus on validating the activity of individual synthetic peptides, elucidating transport mechanisms, and scaling up the fractionation process for industrial feasibility.

CRediT authorship contribution statement

Yuan Liu: Writing – review & editing, Writing – original draft, Validation, Supervision, Investigation, Data curation. Xiaohan Zhang: Visualization, Investigation. Siyu Chen: Visualization, Investigation. Tongtong Chen: Visualization, Investigation. Xinqi Liu: Visualization, Validation, Investigation. Chi Zhang: Writing – review & editing, Writing – original draft, Visualization, Project administration, Investigation, Conceptualization.

Funding

This work was supported by the Guangxi Key Research and Development Program (AB25069475), the National Key Research and Development Program of China (2021YFD2100402), and the Cultivation Project of Double First-Class Disciplines of Food Science and Engineering, Beijing Technology & Business University (BTBUYXTD202207).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary material

Complete List of Peptides Identified and Characterized with High Confidence in Active Fraction F2-1

Data availability

Data will be made available on request.