Introduction

Seaweeds are a significant part of the daily nutritional intake in many Southeast Asian countries and have gained popularity worldwide for their nutritional and functional properties1. In Australia, beach-cast brown seaweeds such as Durvillaea potatorum, Cystophora siliquosa Phyllospora comosa, Sargassum fallax and Ecklonia radiata, are abundant along the coastlines, particularly after storms. These seaweeds are rich in phenolic compounds including syringic acid, p-hydroxybenzoic acid, rutin, vanillic acid, chlorogenic acid, gallic acid, quercetin and hesperidin, as identified in earlier studies2,3. Apart from phenolics and flavonoids, brown seaweed is rich in phlorotannins, which are biosynthesized through the acetate–malonate (polyketide) pathway3. Phenolics in brown seaweed have demonstrated various health benefits, including antioxidant, anti-inflammatory and anti-mitotic activities4.

Despite their health potential, phenolic compounds have limited bioavailability due to their large molecular size, preventing absorption in the small intestine5. Low molecular weight phenolics such as phenolic acids and flavonoid monomers typically range from 150 to 500 Da, whereas high molecular weight compounds like phlorotannins and polymeric proanthocyanidins can exceed 1,000 Da6. According to a previous study, phlorotannins have a range of wider mass range (from 126 to 1 × 105 Da and higher)7. Instead of being absorbed in the small intestine, phenolics normally reach the colon, where gut microbiota metabolize them into bioactive metabolites8. For example, flavonoids such as hesperidin and naringin may be first converted to their aglycons and then further broken down to other phenolics. Seaweed also contains dietary fiber, which, along with phenolics may act as prebiotics, promoting beneficial gut bacteria such as Lactobacillus and Bifidobacterium9. Recent studies suggest that other microbial groups including Eubacterium, Roseburia, Bacteroides, certain Clostridia species, Faecalibacterium and Akkermansia muciniphila, may also contribute to phenolic metabolism and short-chain fatty acid (SCFAs) production10.

While the interaction between seaweed phenolics and gut microbiota is recognized, the modes of action influencing microbial composition and metabolic outputs remain unclear. Pigs (Sus domesticus) serve as a well-established model for human digestion due to their comparable gut microbiota composition and function11. This study aims to investigate the colonic fermentation of five Australian brown seaweeds, focusing on their impact on gut microbial composition, phenolic biotransformation, antioxidant potential and short-chain fatty acid production. The findings from this study provide detailed insights into how phenolic-rich Australian brown seaweeds influence gut microbiota composition, phenolic biotransformation and short-chain fatty acid production during colonic fermentation, thereby contributing to a better understanding of their potential role in promoting gut health.

Results and discussion

Total phenolic content of Australian brown seaweeds in the intestinal phase

In this study, estimation of total phenolic content, total flavonoid content and phlorotannin content in the intestinal phase was performed. Our findings in Fig. 1A illustrate the changes in phenolic content observed at different time points during colonic fermentation. This allows us to understand the variation in bioactivity and composition among different seaweeds. Among the seaweed species, D. potatorum exhibited (p < 0.05) significantly high phenolic content at 8 h (3.14 GAE mg/g), compared to other species and time points. This aligns with a previous study showing that phenolic content increases at 8 h12. However, the phenolic content at 2 h was similar across all species, ranging from 1.08 to 1.68 GAE mg/g, consistent with another study observing that the gut microbiome fermented the majority of hydrolysable tannins within 2 h13.

After gastric digestion, around 85% of flavonoids are not completely liberated or digested; colonic bacteria and enzymes are still needed for hydrolysis14. In the total flavonoid content assay shown in Fig. 1B, P. comosa showed high levels of flavonoids at 0 h (0.733 QE mg/g). The high flavonoid content at the beginning of colonic fermentation is likely due to the degradation of proanthocyanidins, which increases phenolic content15. D. potatorum exhibited significant (p < 0.05) flavonoid content at 2 h (0.063 QE mg/g), while P. comosa displayed elevated levels at both 4 h and 8 h (0.31 QE mg/g). At 18 h, D. potatorum again showed substantial flavonoid content (0.35 QE mg/g) and at 8 h, increased levels were observed in both D. potatorum (0.25 QE mg/g) and S. fallax (0.32 QE mg/g). C. siliquosa had the lowest presence of flavonoid compounds.

Phlorotannin content was measured using two methodologies as shown in Fig. 1C and D. The Folin Denis Assay captures a broader spectrum of phenolics and normally results in higher total phenolic content compared to the Prussian Blue Assay, which primarily detects high-molecular-weight phenolics. The difference in specificity explains the observed variations in total phenolic values across seaweed species. The Prussian blue assay detected low phlorotannin levels at 0 h across all species. However, E. radiata exhibited high phlorotannin content at all time frames, followed by S. fallax and C. siliquosa. The Folin-Denis methodology showed high phlorotannin levels at 12 h in D. potatorum (0.255 PGE mg/g), C. siliquosa (0.24 PGE mg/g) and S. fallax (0.20 PGE mg/g), followed by high levels at 18 h in S. fallax (0.223 PGE mg/g) and C. siliquosa (0.223 PGE mg/g). In this study, phenolic levels were initially low, followed by an increase during 2 to 18 h and then gradually declined at later time points. This pattern may reflect the early release of soluble phenolics, subsequent microbial biotransformation, release of bound phenolics and eventual degradation or utilization by the gut microbiota. The extent and timing of these changes are influenced by seaweed composition, microbial community dynamics and fermentation conditions.

Fig. 1
figure 1

Assessment of the phenolic content and phlorotannin of seaweed species following colonic fermentation. (A) Total phenolic content; (B) Total flavonoid content; (C) Prussian blue assay; (D) Folin-Denis Assay; Phloroglucinol equivalents (PGE), quercetin equivalents (QE) and gallic acid equivalents (GAE). **Statistically significant difference (p ≤ 0.05); ***Statistically very significant difference (p ≤ 0.01) within the species.

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Antioxidant content of Australian brown seaweeds in the intestinal phase

In this study, we have four antioxidant assays: DPPH, FRAP, ABTS and TAC, as shown in Fig. 2. Slight variations were observed in the results from different methods, which can be attributed to their different reaction mechanisms. The DPPH assay measures free radical scavenging capacity, primarily detecting hydrogen-donating antioxidants, such as phenolic acids and flavonoids16. On the other hand, the FRAP assay evaluates the electron-donating ability of antioxidants in reducing Fe³⁺ to Fe²⁺, favouring compounds with strong reducing power, such as phlorotannins17.

In the present study, S. fallax (1.156 TE mg/g) and C. siliquosa (0.953 TE mg/g) exhibited high DPPH activity at 18 h, while FRAP values were significantly high at 24 h in all species ranging between 0.07 and 0.12 TE mg/g. This discrepancy may be due to differences in the dominant antioxidant compounds at each time point, as certain flavonoids and phenolic acids preferentially act through radical scavenging mechanisms (DPPH), while others, like phlorotannins and tannins, contribute more effectively to reducing power (FRAP).

Similarly, the ABTS assay, which measures both hydrophilic and lipophilic antioxidants, showed high activity at 24 h in P. comosa, S. fallax and C. siliquosa, while TAC activity was consistently present across all phases in S. fallax but absent at 8 h in C. siliquosa. These differences may be explained by variations in the solubility and interaction of antioxidants with the assay reagents, as well as potential synergistic effects between different phenolic compounds present in each species18.

Fig. 2
figure 2

The evaluation of seaweed species’ antioxidant capacity during colonic fermentation. Trolox equivalents (TE.). Abbreviations of DPPH: 2,2′-Diphenyl-1-picrylhydrazyl; FRAP: Ferric Reducing Antioxidant Power; ABTS: 2,2′-azino-bis-3-ethyl benzothiazoline-6-sulfonic acid assay; TAC: total antioxidant content. TE, Trolox equivalents. **Statistically significant difference (p ≤ 0.05); ***Statistically very significant difference (p ≤ 0.01) within the species.

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Microbial profile was modulated by seaweed phenolics during in vitro colonic fermentation

To observe the effects of various seaweeds, including P. comosa, E. radiata, D. potatorum, S. fallax and C. siliquosa, on the microbiota composition during in vitro colonic fermentation, we analysed the bacterial configuration of each seaweed infused sample. This analysis was conducted by examining the 16S rRNA amplicons of the treatments incubated at various time points (0, 2, 4, 8, 12, 18, 24 and 48 h).

As shown in Fig. 3, alpha diversity indices, ACE and Chao1, were employed to assess the distribution of taxonomic group for richness and diversity, respectively, for each treatment19. For ACE, both the control and seaweed samples showed a high bacterial community richness at 0 h, which increased at 8 h and 12 h, followed by a substantial decrease from 18 h onwards. This pattern was similarly reflected in the Chao1 diversity index. Among the treatments, the sample treated with D. potatorum exhibited the highest bacterial community richness at 0 h, followed by P. comosa (8 h) and S. fallax (12 h).

To assess the variation in microbial community composition during seaweed colonic fermentation across different seaweed treatments, we performed a Bray-Curtis Beta diversity analysis at 24 h. Our findings revealed that E. radiata, P. comosa and D. potatorum shared similar bacterial communities. Likewise, S. fallax and C. siliquosa exhibited similar bacterial communities. As shown in Fig. 4, the differential abundance of bacteria is influenced by the addition of seaweed samples to the fermentation process. For instance, the relative abundance of Erysipelotrichales order was affected by the addition of D. potatorum. Similarly, Catenibacterium genus was more abundant in the E. radiata samples, has been suggested to play role in fiber breakdown20.

As illustrated in Fig. 5, the relative abundance of the most prevalent (< 1%) microbial genera within the bacterial community in each treatment was computed at the genus level in order to determine the changes in particular bacterial taxa during the 48 h in vitro colonic fermentation. P. comosa, E. radiata, D. potatorum, S. fallax and C. siliquosa each influenced the microbiota composition in distinct ways, affecting the relative abundances of different microbial genera at various fermentation time points during the in vitro colonic fermentation. Overall, due to the nature of ratification in the microbiota data analysis, some results might have been lost or not analysed in the larger dataset. Each sample had a different read depth and an equal depth length had to be selected, matching the depth of the lowest sample.

Fig. 3
figure 3

Changes in the fecal microbiota during various treatments. (A) Analysis of the faecal microbiota’s alpha diversity at various intervals during the in vitro colonic fermentation process (0 h, 2 h, 4 h, 8 h, 12 h, 18 h, 24 h and 48 h). Statistical significance between seaweed treatments and the control sample were analysed using the Kruskal-Wallis test. (B) Bray-Curtis dissimilarities at 24 h.

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Fig. 4
figure 4

The taxonomic cladogram produced by linear discriminant analysis (LDA) effect size (LEfSe) identifies significantly discriminant (Kruskal–Wallis sum rank test α < 0.05; LDA score > 2.00) taxa linked to various treatments. The identified bacterial taxa that were differentially abundant in a certain treatment group are shown by the distinct color shading.

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Fig. 5
figure 5

Variations in the fecal microbiota’s relative abundances at the genus level during colonic fermentation for each treatments (average of n = 3). The most prevalent microbial genera (> 1%) among all seaweed groupings are plotted according to their relative abundances for each fermentation time point (0 h, 2 h, 4 h, 8 h, 12 h, 18 h, 24 h and 48 h).

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Characterization and identification of LC-ESI-QTOF-MS/MS

LCMS/MS is commonly used for identifying and characterizing phenolic compounds found in marine seaweed. The qualitative analysis of these phenolic compounds was conducted using LC-ESI-QTOF-MS/MS in positive and negative ionization modes. Compounds with mass error < 5 or > -5 ppm and Personal Compound Databases and Libraries (PCDL) library score > 80 selected for MS/MS identification and characterization. In total, 32 phenolic compounds were identified and shown in Table 1, categorized into phenolic acids (including 5 hydroxybenzoic acids and 10 hydroxycinnamic acids), flavonoids (including 3 flavanols, 4 flavones, 1 flavonones, 2 flavonols, 1 anthocyanin and 2 isoflavonoids) and 4 lignans.

Gallic acid (compound 2, [M-H]−, m/z 169.0152) and 2-hydroxybenzoic acid (compound 5, [M – H]−, m/z 137.0234) were identified, with characteristic product ions observed at m/z 125 and m/z 93 due to the loss of CO221,22. Gallic acid was detected in seaweed species P. comosa, E. radiata and S. fallax at 2 h. suggesting early microbial hydrolysis, likely mediated by Lactobacillus spp. and Bifidobacterium spp., which are known to cleave tannins and flavonoid glycosides into bioavailable benzoic acid derivatives23.

2-Hydroxybenzoic acid was found in S. fallax and E. radiata at 4 h and 0 h respectively, followed by E. radiata, D. potatorum and C. siliquosa at 2 h, confirming the presence of total phenolic compounds in the in vitro assays. In this study, Bacillus spp. and Enterococcus spp. were theorised as playing a role in the hydroxylation of 2-hydroxybenzoic acid to form 2,3-dihydroxybenzoic acid compound which are found in the latter part of colonic fermentation24and may have possibly influence this conversion.

Caffeic acid (Compound 8, [M – H]−, m/z 179.0357) was confirmed by the product ions at m/z 143 and m/z 133 due to the loss of 2H2O and HCOOH25. The compound had been detected in C. siliquosa at 8 h. Caffeic acid, primarily esterified with quinic acid to generate chlorogenic acid26has been previously observed to inhibit the growth of both common pathogenic and commensal strains such as Staphylococcus aureus27. Moreover, Compound 10 ([M – H]−, m/z 147.0446) was tentatively recognized as cinnamic acid with product ions at m/z 103 due to the loss of CO2 (44Da). Furthermore, the microbes involved in the conversion of cinnamic acid to p-coumaric acid is believed to be Lactobacillus spp., and Escherichia coli, which has been observed among the microbial specimens in the present study28 and may have possibly facilitated this conversion.

Naringin 4’-O-glucoside (Compound 23, m/z 741.2286, [M-H]−) was tentatively identified, with product ions at m/z 271 confirming the compound due to the loss of [M–H–rha-glu]−29. Naringin has been recorded to directly modulate the intestinal microbiota and its metabolic activity, significantly lowering the presence of bacteria linked to gastrointestinal diseases. It has also been demonstrated to decrease inflammation-related protein expression, reduce colonic damage induced by dextran sulfate sodium and enhance colonic barrier function30. The compound was found in 48 h of P. comosa and 4 h of E. radiata in this study. In line with our findings, the compound has been previously detected in Ecklonia stolonifera31. Additionally, phenolic compounds like naringin 4’-O-glucoside, detected at 48 h in P. comosa, have been previously linked to gut barrier enhancement and reduced inflammation30.

The tentative identification of quercetin 3-O-xylosyl-glucuronide (Compound 24, [M+H]+, m/z 611.1232) was confirmed by product ions at m/z 303, due to the loss of glucuronide. The MS2 spectrum showed fragment ions at m/z 285 [M + H–glucuronide–H2O] and m/z 239 [M + H–glucuronide–2H2O–CO]32. Similarly, quercetin 3-O-xylosyl-rutinoside (compound 25 [M – H]+, m/z 743.2006) was identified based on the observed product ions at m/z 479 (loss of two pentoses) and m/z 317 (loss of a hexose)33. Our study observed a reduction in the relative abundance of Streptococcus sp. in the rarified dataset during fermentation, which may be possibly linked to the antimicrobial properties of seaweed phenolics. Previous research has demonstrated that quercetin derivatives can suppress pathogenic and opportunistic bacteria in the gut34. The presence of these compounds at 12 h in D. potatorum and at 4 h in C. siliquosa indicates that they might have potentially contributed to the inhibition of Streptococcus sp. at these time points. This aligns with prior findings that phenolic compounds from natural sources may play a significant role in modulating microbial communities by selectively inhibiting harmful bacteria while promoting beneficial ones: however, more detailed and targeted research is needed to verify the findings.

The key objective of the LC-ESI-QTOF-MS/MS analysis was to identify native and microbial-derived phenolic compounds throughout colonic fermentation to understand their transformation and potential bioactivity. The results revealed that large native phenolics such as gallic acid and caffeic acid appeared early (0 to 2 h), while microbial metabolites such as 2,3-dihydroxybenzoic acid, quercetin derivatives and naringin 4′-O-glucoside, emerged during mid to late fermentation (12 to 48 h), indicating microbial biotransformation. Notably, each seaweed species exhibited distinct phenolic profiles and transformation timelines, with P. comosa showing naringin 4′-O-glucoside at 48 h and C. siliquosa presenting caffeic acid at 8 h. Beyond phenolic shifts, key findings included the identification of anti-inflammatory and antimicrobial metabolites, which may explain the observed variations in the microbiota . This analysis confirms the enhanced bioavailability and functional potential of seaweed phenolics following microbial fermentation.

Table 1 Compounds found in different time intervals of colonic fermentation.
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Short chain fatty acids (SCFAs)

Substrate availability, the composition of the microbiota and duration of intestinal transit primarily influence the types and quantities of SCFAs produced in healthy individuals. The current research detected various SCFAs, including butyric acid, propionic acid, acetic acid, isovaleric acid, isobutyric acid and valeric acid, as displayed in Fig. 6. Acetate is produced from pyruvate either directly from acetyl-CoA or via the reductive acetyl-CoA (Wood–Ljungdahl) pathway35. Acetic acid levels were significantly high at 12 h in P. comosa but were not detected at 8 h in E. radiata, P. comosa and D. potatorum. This compound was present at 48 h and also detected at 0 h in E. radiata, P. comosa, D. potatorum and S. fallax. Acetate can be produced by enteric bacteria such as Akkermansia muciniphila, Prevotella spp., Bifidobacterium spp., Bacteroides spp., Ruminococcus spp., Lactobacillus spp. and Streptococcus spp. through the Wood-Ljungdahl and acetyl-CoA pathways36.

Propionate is produced through the succinate pathway and can also be produced from lactate via the acrylate pathway, using simple sugars (pentoses and hexoses) as substrates, or via the propanediol pathway using deoxyhexoses (fucose and rhamnose)35. For propionic fermentation, glucose and lactate are the main substrates. The pathway varies depending on the bacteria, potentially forming succinate or acrylate37. Propionic acid levels were high at 2 h in E. radiata followed by at 12 h in P. comosa. Its presence was negligible at 2 h in all other species but was prominently present in all species at 18 h. Propionate is believed can be produced by Coprococcus catus, Megasphaera elsdenii, Dialister spp., Bacteroides spp., Veillonella spp., Phascolarctobacterium succinatutens, Ruminococcus obeum, Roseburia inulinivorans and Salmonella spp. via the succinate, acrylate and propanediol pathways38. The presence of Phascolarctobacterium spp., Dialister spp., Megasphaera spp., Roseburia spp., Ruminococcus spp. and Coprococcus spp., was detected in our microbiome study.

Butyrate is formed through the reduction of acetoacetyl CoA to butyryl CoA, which is then converted to butyrate by transbutyrylase and butyrate kinase. Alternatively, butyryl CoA may yield butyrate via butyryl-CoA transferase-acetate Co-A35. Butyrate-producing bacteria include Fusobacterium nucleatum, some Clostridium species and Butyrivibrio fibrisolvens. The end products are butyric acid, a small amount of acetic acid, CO2 and H2, with some species also producing lactic acid and/or ethanol37. Butyrate can be synthesised by Clostridium leptum, Eubacterium rectale, Roseburia spp., Faecalibacterium prausnitzii, Coprococcus eutactus, Anaerostipes caccae, Eubacterium hallii and Coprococcus catus39. Research indicates that 70% of the energy used by intestinal epithelial cells is derived from butyric acid produced by Ruminococcus and Faecalibacterium40. Butyric acid was significantly high at 12 h in P. comosa and detected at 0 h in E. radiata, P. comosa and D. potatorum. Well-known butyrate-producing bacteria, such as Eubacterium spp. and Roseburia spp. are abundant in the microbiome during butyric acid production41. The presence of Clostridium spp., Roseburia spp., Eubacterium hallii, Coprococcus spp. and Faecalibacterium spp., were detected in the microbiome study.

Clostridium species, particularly those involved in amino acid fermentation, have been associated with gut dysbiosis. These bacteria can metabolize amino acids into odorous compounds such as isovaleric acid, isobutyric acid and hexanoic acid, as well as amines, hydrogen sulfide and methyl mercaptan37. Excessive accumulation of isobutyric and isovaleric acid may indicate fermentation and digestion inefficiencies, potentially due to unabsorbed proteins or amino acids reaching the intestines. This could also be a marker of pathogenic microbiota overgrowth in the small intestine42. In this study, isobutyric acid levels were notably high at 18 h in S. fallax and significantly increased at 12 h across all species. The compound was also detected at 48 h. Similarly, isovaleric acid showed a peak at 12 h in P. comosa but was absent at 4 h in all species and detected at 0 h only in D. potatorum. Valeric acid levels were significantly elevated at 24 h across all species and also increased at 12 h in P. comosa. Interestingly, the observed reduction in the relative abundance of Clostridium species over time may possibly be linked to the presence of caffeic acid in C. siliquosa at 8 h, which has been reported to inhibit pathogenic bacteria, including Clostridium sp43. The antimicrobial effects of caffeic acid, along with other seaweed phenolics, may have contributed to suppressing the relative abundance of Clostridium in the rarified data set while modulating gut microbial composition.

These microbial shifts may be linked to the production of SCFAs, which play a crucial role in intestinal health by regulating immune function and providing energy to colonocytes35. The high levels of acetic acid, butyric acid, isovaleric acid, and total SCFAs observed at 12 h in P. comosa  likely correspond to an increase in beneficial bacteria known for fermenting dietary fiber and polyphenols into SCFAs39. In addition to SCFA production, the microbial shifts observed in this study are associated with antioxidant activity. The rise in antioxidant activity, as indicated by the DPPH and FRAP assays at 18–24 h in S. fallax and C. siliquosa, aligns with an increase in Bacteroides, known to metabolize polyphenols into highly bioavailable antioxidant metabolites9. Furthermore, naringin 4’-O-glucoside, detected at 48 h in P. comosa, has been linked to gut barrier enhancement and reduced inflammation30further supporting the idea that microbial fermentation may enhance the bioavailability of phenolic antioxidants. These findings could suggest that seaweed-derived polyphenols not only promote the growth of SCFA-producing bacteria but may also enhance antioxidant activity through microbial biotransformation. The ability of seaweed phenolics to influence gut microbiota composition highlights their possible potential as functional food ingredients for promoting gut health. Although, future studies are needed to validate and explore the specific metabolic pathways involved in these microbial transformations and assess their in vivo implications.

Fig. 6
figure 6

The production of different seaweed digesta by SCFAs (A) the amount of acetic acid; (B) the amount of propionic acid; (C) the amount of iso-butyric acid; (D) the amount of butyric acid; (E) the amount of isovaleric acid; (F) the amount of valeric acid; (G) the total short chain fatty acids.

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Conclusion

This study demonstrates that Australian brown seaweeds are rich in phenolic compounds that undergo significant microbial transformation during colonic fermentation, resulting in enhanced antioxidant activity, modulation of gut microbiota, and increased short-chain fatty acid (SCFA) production. Among the species in this study, both Phyllospora comosa and Durvillaea potatorum exhibited the most promising outcomes. P. comosa had high initial flavonoid content, peak SCFA production at 12 h, and the presence of bioactive microbial metabolites such as naringin 4′-O-glucoside. These effects are likely attributed to its distinct phenolic composition and higher fermentability. On the other hand, D. potatorum exhibited the highest total phenolic content at 8 h and significantly elevated phlorotannin levels, particularly at 12 and 48 h. It also supported the highest bacterial community richness at 0 h. These outcomes highlight D. potatorum’s potential as a rich source of phenolics and a possible modulator of microbial diversity early in fermentation. The use of pig fecal inoculum provided a physiologically relevant model for simulating human colonic fermentation, allowing for the assessment of microbial shifts and metabolite generation. Notably, the richness and diversity of the gut microbiome was influenced by the addition of seaweeds, suggesting a possible correlation between microbial modulation and seaweed-derived phenolics, although more detailed analysis is required to confirm this theory. It is important to acknowledge that the seaweed samples used were whole extracts, not purified phenolics, and thus matrix components such as polysaccharides and proteins may have contributed to the observed bioactivities. While this represents real-world dietary conditions, further studies using fractionated extracts are warranted to determine the contributions of individual phenolics. Overall, this research theorises the potential of P. comosa and other Australian seaweeds as candidates for developing functional foods or nutraceuticals. Future research is essential and should focus on in vivo validation of these findings to confirm the health benefits of seaweed-derived phenolics in human models. Additionally, investigating the specific mechanisms of microbial metabolism and host-microbe interactions will provide deeper insights into how these bioactive compounds may contribute to gut health. Exploring the formulation and stability of seaweed-derived functional foods will be essential for their successful integration into the food industry.

Materials and methods

Sample collection and preparation

P. comosa, E. radiata, D. potatorum, S. fallax, and C. siliquosa seaweeds were located at Queenscliff Harbour (38°15’54.0"S 144°40’10.3"E), Victoria, Australia, and were collected in February 2024 (summer). The seaweed samples were randomly collected and identified at the Deakin Marine Institute in Queenscliff, Victoria, Australia. Freshly collected samples were initially rinsed with tap water and then doused three times with Milli-Q water to remove any sand and other residues. The seaweed was then manually cut into 1–3 cm pieces using a stainless-steel food-grade knife, freeze-dried for 72 h, and a coarse powder was achieved with grinding. The dried samples were stored at 4 °C until further use44.

Chemicals and reagents

The analytical grade standards and chemicals used in this study were obtained from Sigma-Aldrich Chemicals (Castle Hill, NSW, Australia). These included yeast extract, calcium chloride, peptone, pectin, L-cysteine, sodium chloride, soluble starch, magnesium sulfate heptahydrate, sodium bicarbonate, mucin, guar, potassium dihydrogen phosphate, ammonium carbonate, sodium hydroxide, casein, magnesium chloride, hydrochloric acid, dipotassium phosphate, pepsin, tryptone, Tween®-80, potassium chloride, and bile salts. The pancreatin and α-amylase enzymes used for in vitro digestion were sourced from US Biological (Assay Matrix Pty Ltd., Australia).

In vitro gastrointestinal digestion

The dried seaweed samples (in triplicates) are subjected to in vitro digestion using the harmonized INFOGEST 2.0 methodology, as detailed by Brodkorb, et al.45. During the oral phase, stimulated oral fluid (SOF) and salivary α-amylase (75 U/mL) dissolved in SOF were mixed in a 1:1 (v/v) ratio using 2.5 mL of the sample, which contained 0.5 g of dried seaweed. The mixture was then incubated for two min at 37 °C while being continuously shaken. Stimulated gastric fluid (SGF) (1:1, v/v) and 2000 U/mL porcine pepsin dissolved in SGF were added to each sample during the gastric phase. The mixture was then brought to pH 3.0 with HCl and incubated for two hours at 37 °C. The previous reaction mixture was neutralized to pH 7.0, 1:1, stimulated intestinal fluid (SIF), 100 U/mg trypsin dissolved in SIF, and 10 mM bile salts was composed of the intestinal phase. The mixture was incubated for two hours at 37 °C.

Colonic fermentation

The fecal mixture was prepared by pooling freshly collected pig feces collected in an anaerobic chamber from Diamond Valley Pork (VIC, Australia). Fecal samples were collected from a sounder of white pigs in both sexes, housed at Diamond Valley Pork’s facility in Laverton North, VIC, Australia, after 14 days of standard diet (Ethics Approval ID: 10395) . The fecal media consisted of a mixture of feces and 0.1 M sterilized phosphate buffer (pH 7.0) (1:40, w/v), homogenised in a stomacher mixer (MiniMix® Lab Blender, Thomas Scientific, NJ United States), and filtered through a muslin cloth. The sample, basal media and fecal media were combined (1:10:10, w/v/v) in seven sets of tubes, in triplicate, flushed with N2 gas. The tubes were anaerobically incubated according to their incubation time (0, 2, 4, 8, 16, 24, and 48 h), oscillating 120 rpm. After incubation samples were snap-frozen at -196 °C and frozen at -20 °C for analysis. The selected time points (0, 2, 4, 8, 12, 18, 24 and 48 h) were based on typical colonic transit times and microbial fermentation stages. The early phases (0–8 h) capture the breakdown of easily fermentable compounds and initial SCFA production. The mid-phase (12–24 h) represents peak microbial fermentation, where SCFA levels are highest. The 48-hour time point was included to observe the final stages of fermentation when microbial activity slows down as nutrients are depleted. These time points ensure that key metabolic changes during fermentation are captured.

Phenolic content determination

Determination of total phenolic content (TPC)

The total phenolic content (TPC) was measured by the Folin-Ciocalteu method, as outlined by Mussatto, et al.46. A volume of 25 µL of Folin–Ciocalteu reagent (diluted 1:3 with water), 25 µL of sample extract and 200 µL of distilled water were added to a 96-well microplate (Costar, Corning, NY, USA). The plate was incubated in the dark at room temperature (~ 25 °C) for 5 min. Following this, 25 µL of 10% (w/w) sodium carbonate solution was added and the mixture was incubated for 60 min at 25 °C. The absorbance was then measured at 765 nm using a spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). A standard calibration curve was generated using gallic acid concentrations ranging from 0 to 200 µg/mL, and the total phenolic content (TPC) was expressed as milligrams of gallic acid equivalents per gram of dry sample weight (mg GAE/g d.w.).

Determination of total flavonoid compounds (TFC)

Total flavonoid content (TFC) was determined using a modified aluminum chloride method, as described by Ali, et al.47. A total of 80 µL of sample extract was added to a 96-well microplate, followed by 80 µL of aluminum chloride solution and 120 µL of 50 g/L sodium acetate. The plate was incubated in the dark for 2.5 h. Absorbance was recorded at 440 nm. A quercetin calibration curve ranging from 0 to 50 µg/mL was used to quantify the total flavonoid content (TFC), which was expressed as milligrams of quercetin equivalents per gram of dry sample weight (mg QE/g d.w).

Prussian blue assay (PBA)

To determine the total phlorotannin content, the method of later modified by Margraf, et al.48 was modified and used. A 50 µL aliquot of the diluted sample was mixed with 50 µL of ferric ammonium sulfate solution (0.1 M FeNH₄(SO₄)₂ in 0.1 M HCl) and kept in the dark for 2 min. Then, 50 µL of potassium ferricyanide solution (0.008 M K₃Fe(CN)₆) was added to the mixture. The reaction was incubated in the dark for 15 min, and absorbance was measured at 725 nm. A standard curve prepared using phloroglucinol (0–3.125 µg/mL) was used to quantify total phlorotannin content, expressed as milligrams of phloroglucinol equivalents per gram of dry weight (mg PGE/g d.w).

Folin-Denis assay (FDA)

Phlorotannin content was observed using the Folin-Denis assay as followed by Stern, et al.49. The Folin-Denis reagent was prepared by dissolving 25 g of sodium tungstate (Na₂WO₄·2 H₂O) and 5 g of dodecamolybdophosphoric acid (12MoO₃·H₃PO₄·H₂O) in 175 mL of distilled water. To this, 12.5 mL of phosphoric acid was added, and the solution was refluxed for 2 h before being made up to a final volume of 250 mL. For the assay, 5 µL of the sample was combined with 20 µL of Folin-Denis reagent, 40 µL of saturated sodium carbonate solution, and 125 µL of distilled water. The mixture was incubated in the dark for 2 h, and absorbance was measured at 725 nm. A phloroglucinol standard curve (0–100 µg/mL) was used to determine the total phlorotannin content, expressed as milligrams of phloroglucinol equivalents per gram of dry weight (mg PGE/g d.w).

Antioxidant potential estimation

2,2′-Diphenyl-1-picrylhydrazyl (DPPH) assay

The DPPH method was used to estimate the antioxidant potential of the seaweed samples in all phases of the study by the method of Nebesny and Budryn50. The DPPH radical solution was prepared by dissolving 4 mg of DPPH in 100 mL of analytical-grade methanol. For the assay, 40 µL of the sample extract and 260 µL of the DPPH solution were added to a 96-well microplate. The plate was shaken vigorously and incubated in the dark at 25 °C for 30 min. Absorbance was recorded at 517 nm. A Trolox calibration curve (0–200 µg/mL) was used to quantify the DPPH radical scavenging activity, expressed as milligrams of Trolox equivalents per gram of dry weight (mg TE/g d.w).

Ferric reducing antioxidant power (FRAP) assay

This assay was used to estimate the antioxidant potential in seaweeds, following the protocol of Benzie and Strain17 with minor modifications. The FRAP reagent was prepared by mixing 20 mM Fe(III) solution, 10 mM TPTZ solution, and 300 mM sodium acetate buffer in a 1:1:10 ratio. For the assay, 20 µL of the sample extract was combined with 280 µL of the freshly prepared FRAP reagent in a 96-well microplate. The mixture was incubated at 37 °C for 10 min, and the absorbance was measured at 593 nm. A Trolox standard curve ranging from 0 to 100 µg/mL was used to calculate the antioxidant capacity, which was expressed as milligrams of Trolox equivalents per gram of dry weight (mg TE/g d.w).

2,2′-Azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assay

The free radical scavenging activity of marine seaweed samples was measured using the ABTS radical cation decolorization test, based on an existing procedure Re, et al.18with minor modification. The ABTS⁺ working solution was prepared by mixing 88 µL of 140 mM potassium persulfate with 5 mL of 7 mM ABTS solution, followed by incubation in the dark for 16 h to generate the radical cation. For the assay, 10 µL of the sample extract was added to 290 µL of the ABTS⁺ solution in a 96-well microplate. The mixture was incubated at 25 °C for 6 min, and absorbance was measured at 734 nm. Antioxidant activity was calculated using a Trolox standard curve (0–500 µg/mL) and expressed as milligrams of Trolox equivalents per gram of dry weight (mg TE/g d.w).

Total antioxidant capacity (TAC)

The total antioxidant capacity (TAC) was assessed using the phosphomolybdate method described by Prieto, et al.51. The phosphomolybdate reagent was prepared by mixing 0.028 M sodium phosphate, 0.6 M sulfuric acid, and 0.004 M ammonium molybdate. For the assay, 40 µL of the sample extract was combined with 260 µL of the reagent in a 96-well microplate. The reaction mixture was incubated at 90 °C for 90 min, then cooled to room temperature. Absorbance was measured at 695 nm. Total antioxidant capacity was quantified using a Trolox calibration curve (0–200 µg/mL) and expressed as milligrams of Trolox equivalents per gram of dry sample weight (mg TE/g d.w).

Identification of phenolic compounds by LC-ESI-QTOF-MS/MS analysis

The methodology for characterization and identification by Liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (LC-ESI-QTOF-MS/MS) for seaweeds, as published by Ebrahimi, et al.52. Prior to analysis, the extracts were filtered through a 0.45 μm syringe filter (Thermo Fisher Scientific Inc., Waltham, MA, USA). Chromatographic separation was carried out using a Synergi Hydro-RP 80 Å LC column (250 mm × 4.6 mm, 4 μm; Phenomenex, Torrance, CA, USA) maintained at 25 °C, with the sample held at 10 °C. A 10 µL injection volume was introduced into a binary solvent system comprising mobile phase A (99.9% Milli-Q water with 0.1% formic acid) and mobile phase B (99.9% acetonitrile with 0.1% formic acid), delivered at a flow rate of 0.8 mL/min. The gradient program began with 2% B for the first 4 min, increased to 5% B between 4 and 10 min, then gradually rose to 45% B from 10 to 50 min. From 50 to 52 min, the gradient reached 98% B, held for 2 min, and was then brought back to 2% B between 54 and 56 min.

Mass spectrometric detection was performed using both positive and negative electrospray ionization modes. Nitrogen gas served as both the nebulizer and drying gas at 15 psi, with a flow rate of 3.5 L/min and a source temperature of 300 °C. The instrument was operated with a capillary voltage of 3.5 kV and a nozzle voltage of 500 V. Mass spectra were acquired over a range of 50–1300 amu. MS/MS data were collected in automatic mode using collision energies of 10, 15, and 30 eV to induce fragmentation. Compound identification was performed using Mass Hunter Workstation software (version B.03.01, Agilent) with the Personal Compound Database and Library (PCDL). Only compounds with a mass error within ± 5 ppm and a PCDL match score above 80 were considered for confirmation of m/z values and MS/MS identification.

Short-chain fatty acid analysis

SCFAs analysis was observed following the procedure described by Yit Tao Loo11. One gram of the colonic fermentation sample was mixed with 5 mL of distilled water and acidified to pH 2.0 using 5 mol/L hydrochloric acid. The mixture was centrifuged at 10,000 rpm for 10 min at 10 °C. To the supernatant, 4 mL of an acid mixture containing 1% orthophosphoric acid and 1% formic acid was added. Short-chain fatty acid (SCFA) analysis was performed using a gas chromatograph (7890B Agilent, Santa Clara, USA) equipped with a flame ionization detector (GC-FID), an autosampler (Gilson GX-271, Gilson Inc., Middleton, WI, USA), and an autoinjector. Separation was carried out using an SGE BP21 capillary column (12 m × 0.53 mm ID, 0.5 μm film thickness) with a 2 × 0.53 mm ID guard column (SGE RGK2, SGE International, Ringwood, VIC, Australia). The injection volume was 1 µL. Helium was used as the carrier gas at a total flow rate of 14.4 mL/min, while nitrogen, hydrogen, and air were supplied at flow rates of 20, 30, and 300 mL/min, respectively. The oven temperature program was set as follows: initial temperature of 100 °C for 30 s, ramped to 180 °C at 6 °C/min and held for 1 min, followed by a final increase to 200 °C at 20 °C/min and held for 10 min. The injection port and detector temperatures were maintained at 200 °C and 240 °C, respectively. Calibration curves were generated for acetic, propionic, butyric, isobutyric, and valeric acids. SCFA concentrations were quantified and expressed in mmol/L.

16s rRNA extraction and sequencing

Triplicates of each seaweed treatment group across the seven different time points of in vitro colonic fermentation were received by the Australian Genome Research Facility Ltd (AGRF, Adelaide, Australia) for extraction and microbial diversity profiling. The bacterial DNA was extracted using a DNeasy PowerSoil Pro Kit (Qiagen Inc., US) following the manufacturers protocol in AGRF facilities. A bead-beating step for mechanical breakdown of bacteria was employed. Library preparation was carried out using the forward primer 27 F (AGAGTTTGATCMTGGCTCAG) and the reverse primer 519R (GWATTACCGCGGCKGCTG)53to PCR-amplify the V1–V3 region of the 16 S rRNA gene. The resulting amplicons were first screened for sufficient quantity (0.20 ng/µL), normalized, pooled, and sequencing was carried out using the Illumina MiSeq platform, employing Illumina’s Nextera XT Indexes and Paired End sequencing chemistry to generate 300 bp paired-end reads. A set of only basal and fecal matter with water were used as the control treatment to compare the effects of seaweed addition to the microbiome.

Data analysis

Using IBM® SPSS statistics software 27 (SPSS Inc., Chicago, IL, USA), one-way analysis of variance (ANOVA) and Tukey’s honestly significant difference (HSD) test were used to examine data and differences in in vitro phenolic, antioxidant potential, and SCFAs concentrations from various seaweed samples. Quantitative Insights into Microbial Ecology 2 (QIIME 2 2023.5) was used for microbiome bioinformatics54. Sequence data were first demultiplexed and subjected to quality filtering through the Divisive Amplicon Denoising Algorithm 2 (DADA2)55 with the trimming parameters optimised by FIGARO parameters (ZymoBIOMICS ). Truncating forward and reverse reads at 278 bp and 272 bp respectively, followed by trimming the 5’ end of the forward and reverse reads by 20 bp and 18 bp, respectively to remove primer sequences56. Taxonomy was assigned using the 99% identity SILVA (release 138.1) V1–V3 classifier57. Sample reads were processed to remove potential contamination sequences using the negative control samples containing phosphate buffer of the fecal media, employing the R package “Decontam” (version 1.22)58 with a threshold of 0.5,. Alpha and beta diversity analyses were performed using the R package “Phyloseq” (version 1.46)59 on a rarified dataset at 8795 depth (seed = 1997) in RStudio (version 4.3.2)60. ACE (Abundance-based Coverage Estimator) index and Chao161 was calculated as alpha diversity indexes. A pairwise Wilcoxon rank-sum test was used to calculate the statistically significant differences in the alpha-diversity of seaweed treatments and control using Benjamini-Hochberg adjustment method to control the false discovery rate62. To assess beta-diversity, Bray-Curtis dissimilarity was computed and represented through principal coordinates analysis (PCoA) at 24 h of fermentation, calculated and graphed in Rstudio63. Linear discriminant analysis (LDA) effect size (LefSe) analysis64 using “microbiome Marker” package (version 1.8.0)65 with default parameters and pre-sample normalization of the sum of the values to 1e + 06. Furthermore, the relative abundance plot was generated using Rstudio with the “ggplot2” package (version 3.4.4)66 for genera with > %1 relative abundance across the dataset.