Introduction

Folic acid, also known as vitamin B9 or pteroyl glutamate, is a water-soluble B-vitamin essential for nucleic acid biosynthesis, DNA methylation reactions, homocysteine regeneration of methionine, and other critical metabolic processes in the human body. Folic acid is rich in green vegetables, animal liver, egg yolk, and folic acid-fortified foods (Alam et al. 2020). Given the inability of humans to synthesize folic acid internally, folic acid must be taken in daily diet or supplemented with chemically synthesized folic acid. Both naturally sourced and chemically synthetically produced folic acid (non-reduced folic acid (FA)) are eventually converted into 5-methyltetrahydrofolate (MTHF), which serves as the primary form of folate in the serum (Liu et al. 2022). At present, many studies focus on the metabolism of commensal bacteria in the gut to produce folic acid. For example, specific strains of lactic acid bacteria (LAB) such as Lactococcus lactis, Streptococcus thermophilus, and Lactiplantibacillus plantarum have been found to possess a cluster of folate synthesis genes capable of producing MTHF in the presence of para-aminobenzoic acid (PABA) (Sybesma et al. 2003).

Recent research indicates a potential correlation between the folic acid deficiency and gut microbiota. Inflammatory bowel disease is characterized by intestinal microecological dysregulation in patients and is one of the disorders associated with folate insufficiency (Pan et al. 2017; Gevers et al. 2014; Morgan et al. 2012). Zhang et al. (2020) reported that fermented yogurt with Lactiplantibacillus plantarum GSLP-7 V can significantly ameliorate gut microbiota dysregulation caused by folic acid deficiency and restored serum folate and homocysteine levels to normal. Intriguingly, folate seems to enhance host fitness by modulating the gut microbiota. Mardinoglu et al. (2018) discovered that a carbohydrate-restricted diet increases folate cycling, leading to significant promotion of the growth of folate-producing bacteria such as Streptococcus and Lactococcus. This promotes mitochondrial β-oxidation, reduces oxidative stress, and improves hepatic fat metabolism. Existing research on the regulation of gut microbiota by folic acid primarily relies on mouse models with folic acid deficiency, and there is limited literature available on the development of in vitro folic acid deficiency models.

The most effective and direct approach to studying the impact of folic acid on the human gut microbiota is through clinical trials. However, the practicality of conducting such trials is significantly constrained by ethical, safety, and economic factors (Steinway et al. 2020). Consequently, it is crucial to develop a viable in vitro model that accurately replicates the ecological conditions of the human colon. Lei et al. (2012) demonstrated the influence of the Viande Levure (VL) growth medium on the microbial community structure of a chemostat system, which serves as a reliable in vitro gut modeling system with excellent reproducibility. Moro Cantu-Jungles et al. (2019) investigated specific variations in species or strain abundances using a modified fecal slurry fermentation model. Previous studies utilizing in vitro intestinal fermentation models have employed different mimicry media tailored to specific research objectives. Browne et al. (2016) demonstrated that YCFA (yeast extract, casein hydrolysate, fatty acids) medium can be customized to fulfill the growth requirements of most intestinal microorganisms, while Liu et al. (2019) developed a veal infusion starch broth (VIS) medium for human intestinal microorganisms by modifying the primary veal infusion broth (VI) medium. However, there is currently a gap in the available in vitro experimental models for studying folic acid deficiency in the human gut microbiota.

In this study, we optimized an in vitro fecal slurry fermentation model to construct a folic acid deficiency environment, building upon the previous work of Hang et al. (2022) and using a folic acid assay medium to simulate the intestinal milieu. We examined the effects of different forms of folate supplementation (MTHF and FA) on the regulation of the human gut microbiota. To assess changes in the abundance of specific intestinal microbiota and short-chain fatty acids (SCFAs) in response to folic acid supplementation, we employed the 16S rRNA technique and conducted a short-chain fatty acid assay. Additionally, Spearman correlation analysis was performed to investigate potential associations between these alterations and folic acid supplementation. The aim of this study was to provide insights for future research focusing on the folate-intestinal microbial pathway within the context of dietary intervention therapy.

Material and methods

Material

LeucovOrin (biofolic acid, purity > 99%) and 5-methyltetrahydrofolate (reduced folic acid, purity > 99%) were purchased from MedChemExpress (MCE), NJ, USA. Folic acid standard (non-reduced folic acid, purity > 98%) and tetrahydrofolic acid (non-reduced folic acid, purity > 65%) were purchased from Yuanye Bio-Technology (Shanghai, China). Folic acid assay medium was purchased from Land Bridge Technology Co., LTD. (Beijing, China). Resazurin sodium salt, PBS solution, and sulfuric acid (guaranteed reagent) were purchased from Chemical Reagent Co. (Shanghai, China). Anhydrous ethyl ether (analytical reagent) was purchased from Fuyu Fine Chemical Co., LTD. (Tianjin, China). Cyclohexanone (analytical reagent) was purchased from Sinopharm Chemical Reagent Co., LTD. (Shanghai, China). Short-chain fatty acid standards (purity > 90%) were purchased from Dr. Ehrenstorfer GmbH Co. (Augsburg, Germany).

Sampling collection

Fecal samples were obtained from a cohort of 8 healthy human volunteers residing in Hangzhou, China, with their ages ranging from 22 to 35. These individuals were in good overall health and had not received any medications or antibiotics within the past 3 months. Prior to participation, all donors provided informed written consent, and the study received approval from the Ethics Committee of Zhejiang Gongshang University (Zhejiang, China).

VIS medium and folic acid assay medium

The inoculation culture was carried out using the in vitro intestinal simulation model of Rycroft et al. (2001) and Lei et al. (2012) and was optimized based on this. The VIS medium formulation was as follows: starch (8 g/L), tryptone (3.0 g/L), peptone (3.0 g/L), NaCl (4.5 g/L), bile salt no. 3 (0.4 g/L), L-cysteine hydrochloride (0.8 g/L), hemin (0.05 g/L), KCl (2.5 g/L), MgCl2·6H2O (0.45 g/L), CaCl2·6H2O (0.2 g/L), yeast extract (4.5 g/L), KH2PO4 (0.4 g/L), 1 mL Tween 80, and 2 mL trace element (3 g/L MgSO4·7H2O, 0.1 g/L CaCl2·2H2O, 0.32 g/L MnCl2·4H2O, 0.1 g/L FeSO4·7H2O, 0.18 g/L CoSO4·7H2O, 0.18 g/L ZnSO4·7H2O, 0.01 g/L CuSO4·5H2O, and 0.092 g/L NiCl2·6H2O) solution, autoclaved at 121 °C for 5 min. The above reagents were purchased from Changqing Agrochemical Co., Ltd. (Jiangsu, China). Incorporating a resazurin solution into the folic acid assay medium, achieving a final concentration of 0.1%, and boiling induced a color change (red to yellow). The medium was aliquoted into cilium bottles (5 mL per bottle), ensuring an oxygen-free environment with immediate nitrogen introduction. After capping, bottles underwent high-pressure sterilization at 121 °C for 5 min, followed by cooling and preservation for future use.

Cultivation of samples

Fresh fecal samples were collected immediately after defecation from the 8 volunteers. Of fecal samples, 0.2 g was homogenized in 2 mL 0.1 M PBS to create a fecal suspension. A total of 8 such samples were prepared per volunteer and randomly divided into lFA, mFA, hFA, lMTHF, mMTHF, hMTHF, control (Ctrl), and K cases. Of prepared fecal suspension, 0.5 mL was inoculated into 5 mL of VIS medium for each case, except for the K case. Subsequently, lFA, mFA, and hFA cases were exposed to 100 μL of FA at concentrations of 1, 10, and 100 mg/mL, respectively. Similarly, lMTHF, mMTHF, and hMTHF cases were exposed to 100 μL of MTHF at concentrations of 1, 10, and 100 mg/mL, respectively. The Ctrl case received a supplementation of 100 μL of 0.1 M PBS. The K case involves adding 0.5 mL prepared fecal samples to 5 mL 0.1 M PBS, followed by addition of 100 μL 0.1 M PBS. In sum, each case of treatment presented in total 8 individual biological repeats due to the 8 different volunteers.

Similarly, each volunteer’s 0.2 g fecal samples were homogenized in 2 mL 0.1 M PBS. A total of 4 such samples were prepared for each volunteer and randomly divided into FA, MTHF, Ctrl, and Ori cases. Of prepared fecal suspension, 0.5 mL was inoculated into 5 mL of folic acid assay medium for each case, except for the Ori case. Following this, the FA case and the MTHF case were supplemented with 100 μL of FA or MTHF, respectively, at a concentration of 1 mg/mL. The Ctrl case was supplemented with 100 μL of 0.1 M PBS. In the Ori case, the procedure entailed the addition of 0.5 mL of prepared fecal samples to 5 mL of 0.1 M PBS, followed by an additional 100 μL of 0.1 M PBS. Also here, each case of treatment presented thus in total 8 individual biological repeats due to the 8 different volunteers.

All cases underwent anaerobic cultivation for 24 h at 37 °C in an anaerobic workstation (SPX-150B-Z, Boxun Industrial Co., Ltd., Shanghai, China). All samples were taken out and immediately frozen and stored at − 80 °C for the subsequent analysis of 16S rRNA sequencing and SCFA content.

Determination of SCFAs

Gas chromatographic-mass spectrometric (GC–MS) analysis was employed to investigate the effect of folic acid availability on SCFAs in an in vitro simulation. The fermentation broth (2 mL) was centrifuged at 12,000 rpm for 5 min in sterile centrifuge tubes, and the supernatant was stored at − 20 °C for subsequent SCFA analysis. The SCFA content in the samples was determined using GC–MS with a previously published method, with slight modifications (Valdés-Varela et al. 2016; Zhou et al. 2018). The specific procedure was as follows: 500 μL of a sample was added to 2 mL of aqueous phosphoric acid (1:3), vortexed, and homogenized for 2 min. Then, each 1 mL of ether was added for two extractions. The two extracts were combined and evaporated to a final volume of 1 mL. The analysis was performed using a gas chromatography-single quadrupole mass spectrometry system (ISQ™ LT GC–MS, Thermo Scientific, Shanghai, China) with electron ionization (EI) source. The quantification of SCFA compounds was based on peak areas using a TG WAX capillary column (30 mm × 0.25 mm × 0.25 μm) from Thermo Scientific (Shanghai, China), employing the external standard method. The temperature program for SCFA determination was as follows: the initial column temperature was set at 100 °C, then ramped up to 150 °C at a rate of 5 °C/min, followed by a further ramp-up to 240 °C at a rate of 30 °C/min. The column flow rate was maintained at 1.0 mL/min. Mass spectrometry analysis was performed using an EI source with a bombardment voltage of 70 eV, single-particle scan mode, an ion source temperature of 200 °C, and a connecting line temperature of 250 °C. Each sample was tested for three times.

16S rRNA gene amplification and high-throughput sequencing analysis

Bacterial genomic DNA was extracted from fermented fecal samples using the QIAamp DNA Stool Mini Kit (QIAGEN, Hilden, Germany), and DNA integrity was confirmed by 1% agarose gel electrophoresis (Fu et al. 2019). Bacterial DNA was extracted and preserved on dry ice and immediately sent to Biomarker Technologies (Hangzhou, China) for high-throughput sequencing and microbial community diversity analysis. The platform (Illumina, San Diego, CA, USA) was used for double-end sequencing of the sequenced samples. All raw sequences of samples (inputs) were filtered, denoised, merged, and non-chimeric using the DADA2 plug-in in QIIME2 software to define operational taxonomic units (OTUs) (Langille et al. 2013; Callahan et al. 2016; Bolyen et al. 2019). Based on the absolute abundance and annotation of OTUs, each sample was analyzed for species composition, OTU differences between cases, alpha diversity, and beta diversity. All raw reads were deposited into the NCBI GEO database (GSE227224).

Statistical analysis

GraphPad Prism 9.0 was used for analysis (GraphPad Software, Inc., San Diego, CA, USA). Experimental data were expressed as mean ± standard deviation (SD). Differences between cases were analyzed by one-way analysis of variance (ANOVA) and Tukey’s multi-range test and considered significant when p < 0.05. Sequences were clustered using USEARCH (version 10.0) with 97% similarity (default), and we used 0.005% of the sequenced sequence number to filter OTUs (Edgar 2010). The DADA2 method in QIIME2 (version 2020.6) was used to denoise the quality-controlled data, and 0.005% of the sequence number was used as the threshold for filtering amplicon sequence variants (ASVs) (Langille et al. 2013; Callahan et al. 2016; Bolyen et al. 2019).

Results

Microbial composition analysis of folic acid in VIS medium fermentation

To assess the effects of folic acid on the microbiota in a VIS medium-based in vitro gut model, we performed 16S rRNA sequencing by processing samples from each volunteer in each case individually. Figure 1 illustrates the species composition at the phylum and genus levels for the two produced forms of folic acid, FA and MTHF, across different concentration gradients (low, moderate, high). Among these, the predominant phyla observed were Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes, with slight variations in their relative abundance. Notably, the hFA case demonstrated a significant difference (p < 0.05) compared to the other experimental cases, exhibiting an increased proportion of 27.8% within the Bacteroidetes phylum as the concentration of folic acid increased. In the MTHF case, the proportion of the Firmicutes phylum decreased from 27.5 to 23.9%, while in the FA case, it gradually increased from 29 to 30%. Moreover, the Actinobacteria phylum exhibited an increasing proportion from 24.8 to 27.2% in the FA case with increasing concentration of FA, whereas in the MTHF case, it climbed from 24.7 to 26.7%. At the genus level, no significant differences in colony composition were observed between the FA, MTHF, Ctrl, and K cases. The top five genera, ranked by percentage, were Bifidobacterium, Bacteroides, Megamonas, Prevotella, and Escherichia. Notably, the hFA case exhibited a lower percentage (16.7%) in the genus Bacteroides compared to the other cases, while its proportion in the genus Faecalibacterium was notably higher (4%) compared to the other cases. The hFA case also displayed a significantly lower abundance of the genus Prevotella (7.4%) compared to the other cases.

Fig. 1
figure 1

Bacterial community composition in the VIS medium model after different types of folic acid supplementation. A Composition of phylum levels after fermentation at three concentrations of different types of folic acid supplementation. Each bar represents the relative abundance of OTUs of each phylum in the gut microbiota. B Composition of genus levels after supplemental fermentation at three concentrations with different types of folic acid. Each bar indicates the relative abundance of OTUs for each genus in the gut microbiota

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Effect of various doses of folic acid on SCFA content

Acetic acid, propionic acid, butyric acid, and other SCFAs, which are the primary fermentation products of anaerobic bacteria in the intestine, exhibit beneficial effects on the human body (Mortensen and Clausen 1996). Figure 2 illustrates the gradual accumulation of SCFAs with increasing fermentation time after 24 h of anaerobic fermentation with FA or MTHF. No significant difference was observed in the total acid content between the FA and MTHF cases, as well as compared to the Ctrl case (Fig. 2A) (p > 0.01). Notably, a significant difference in acetic acid levels (Fig. 2B) (p < 0.01) was observed between reduced folate (lMTHF) and non-reduced folate (hFA). However, no significant variations were observed in the concentrations of propionic acid and isobutyric acid.

Fig. 2
figure 2

Lack of observed effect of folic acid supplementation on SCFA production in the VIS medium model. A Total acid. B Acetic acid. C Propionic acid. D Isobutyric acid. Fermentation time is 24 h. The horizontal coordinates are the different concentrations of the two types of folic acid experimental cases. E HPLC identification of folate in VIS medium. *p < 0.05 with one star

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HPLC analysis to determine the amount of folic acid in VIS medium

We concentrated the VIS medium by a factor of 10 and performed HPLC analysis to further confirm the presence of folic acid in the VIS medium. The chromatogram (Fig. 2E) clearly showed the presence of folic acid in the VIS medium, with an estimated level of 69.42 ng/mL. Based on these findings, it can be inferred that the folic acid content in the medium is sufficient to maintain adequate intestinal folate homeostasis, thereby preventing the occurrence of nutritional deficiencies. However, the potential impact of folic acid supplementation on the gut microbiome might be masked by the existing folic acid levels within the in vitro simulation system. Therefore, it is necessary to create a folic acid-deficient environment in order to compare the influence of different forms of folic acid on the intestinal microecology.

Analysis of the effect of folic acid supplementation on microbial composition in the environment of folic acid deficiency

Analysis of microbial diversity

To create a folic acid-deficient environment, we made modifications to the in vitro gut mimicry by substituting the gut mimicking medium (VIS) with a folic acid assay medium. This adjustment aimed to eliminate background interference from folic acid and enhance the suitability of the medium for our research. The effects of various folic acids (FA, MTHF) on intestinal bacteria were assessed by 16S rRNA sequencing. Our analysis revealed 488 operational taxonomic units (OTUs) shared among the three cases, along with 2326 unique OTUs in the FA case and 1631 unique OTUs in the MTHF case, both significantly differing from the Ctrl case (Fig. 3A). Figure 3B presents the indicators of alpha diversity. In the in vitro intestinal simulations, we employed the ACE index, Chao1 index, Shannon index, and Observed Features to evaluate the diversity and abundance of bacterial populations. Consistent findings across the various indices of alpha diversity (Fig. 3B) indicate that the FA case exhibited the highest community abundance, while the MTHF and Ctrl cases displayed relatively lower abundance, with the Ori case showing the lowest abundance.

Fig. 3
figure 3

Bacterial community diversity and structure at OTU level of gut microbiota after different types of folic acid supplementation in the simulation of folic acid deficiency. A Petal Venn diagram of all samples. B Alpha diversity index of bacteria including (a) ACE, (b) Chao1, (c) Shannon, and (d) Observed Feature. C PCoA of all bacterial samples, based on unweighted Unifrac distances of the four experimental cases (p = 0.001, R2 = 0.999). The top and bottom of the box represent the 75th and 25th percentile, respectively. The top and bottom whiskers extend to data no more than 1.5 times the interquartile range from the upper and lower edges of the box, respectively

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Principal coordinate analysis (PCoA) was employed to assess the overall composition of the in vitro intestinal mimicking microbial community at the OTU level. Axis 1 and axis 2 accounted for 10.87% and 6.37% of the observed variation, respectively. As depicted in Fig. 3C, the fitted circle exhibited a shift from the negative half-axis of axis 1 to the positive half-axis, progressing from the Ctrl case to the FA case and then to the MTHF case. The sampling points of the Ctrl case consistently clustered around (0, 0), indicating minimal differences within this case. Following fermentation with FA and MTHF supplementation, notable increases in sample dissimilarities were observed, potentially reflecting the influence of individual variations in intestinal types.

Analysis of microbial community composition

To examine the variations in microbial composition among different forms of folic acid, we analyzed the gut microbiota at the phylum and genus levels. Firmicutes, Bacteroidetes, and Proteobacteria were the dominant phyla, comprising the majority of the total population. Following fermentation, the proportion of Firmicutes phylum decreased slightly in the FA case (56.7%) compared to the Ctrl case (60.41%), while it increased more noticeably in the MTHF case (64.9%). In the Bacteroidetes phylum, the relative abundance of FA (29.7%) and MTHF (27.9%) decreased compared to the Ctrl case (34.3%) after fermentation with folic acid supplementation. The highest relative abundance in the Proteobacteria phylum was observed in the FA case at 10.4% (Fig. 4A (a)).

Fig. 4
figure 4

Bacterial community composition in the simulation of folic acid deficiency after different types of folic acid supplementation. A Composition of phylum levels after fermentation at three concentrations of different types of folic acid supplementation. Each bar represents the relative abundance of OTUs of each (a) phylum and (b) genus in the gut microbiota. B Relative abundances of selected bacteria (a) Lactobacillus, (b) Bifidobacterium, (c) Bacteroides, and (d) Pediococcus folic acid supplementation at the genus level

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Figure 4A (b) showed the top 30 genera in terms of relative abundance, with Lactobacillus, Bacteroides, Escherichia-Shigella, Faecalibacterium, and Klebsiella being the five most prevalent genera. The results revealed a slight increase in the abundance of Lactobacillus in the FA case (22.75%), which further increased to 30.76% in the MTHF case (Fig. 4B (a)). Bacteroides genera were downregulated in both experimental cases (FA, MTHF) compared to the Ctrl case, accounting for 17% and 18%, respectively (Fig. 4B (c)). The relative abundance of Bifidobacterium differed significantly (p < 0.05) among the MTHF case (1.06%) compared with Ctrl case (0.24%) (Fig. 4B (b)). Figure 4B (d) demonstrated the relative abundance of Pediococcus, which was 0.06% in the Ctrl case and increased to 0.81% after FA supplementation.

Species significant difference analysis

Linear discriminant analysis effect size (LEfSe) analysis was performed to identify significant differences in the abundance of taxonomic units among the four cases (Fig. 5). The taxonomic levels of the significantly enriched bacterial cases are indicated by the corresponding nodes on the right side in Fig. 5A, B. When comparing the relative abundance of bacteria in the FA, MTHF, Ctrl, and Ori cases, LEfSe analysis was conducted (LDA threshold of 5.0). In the FA case, g_Enterobacter, f_Streptococcaceae, g_Streptococcus, g_Pediococcus, f_Sh765B_AG_111, and g_Veillonella showed statistically significant differences, while in the MTHF case, c_Bacilli, o_Lactobacillales, f_Lactocillaceae, g_Lactobacillus, g_Catenibacterium, and g_Dorea exhibited significant differences. The Ori case differences, from high to low, were observed in c_Bacilli, o_Lactobacillales, f_Lactocillaceae, g_Lactobacillus, g_Catenibacterium, and g_Dorea. In the Ctrl case, only g_Elizabethkingia showed a difference compared to the other cases.

Fig. 5
figure 5

Effects of folic acid supplementation on the composition of microbiota in an in vitro simulated gut model. A LEfSe revealed the microbiomes with significantly different abundances in Ctrl (green), FA (red), MTHF (blue), and Ori (purple) cases. LEfSe clearly distinguished bacterial taxa in the gut microbiota of folic acid from cases Ctrl, FA, MTHF, and Ori. B Statistical Spearman correlation analysis between gut microbiota

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To investigate the interrelationships within the gut microbiota, Spearman correlation network analysis was employed (Fig. 5B), using a correlation coefficient threshold of 0.4. We found that within the Firmicutes phylum, Faecalibacterium, Lachnoclostridium, Roseburia, Eubacterium_eligens_group, UCG_002, Subdoligranulum, Ruminococcus, Fusicatenibacter, Dialister, Megamonas, Eubacterium_coprostanoligenes_group, Catenibacterium, and bacteria of the genus Ruminococcus_gnavus_group exhibited significant symbiotic relationships with each other. The genera Lactobacillus and Pediococcus within the Firmicutes phylum were negatively correlated, while the genus Bifidobacterium within the Actinobacteria phylum showed a negative correlation with the genus Bacteroides. The genera Bacteroides, Aliatipes, Parabacteroides, and Alloprevotella of the Bacteroidetes phylum might be inhibited by Lactobacillus and Pediococcus. Taking these findings into consideration, it is evident that FA supplementation promoted the growth of the Pediococcus phylum and gradually restored the disrupted structure of the gut microbiota by inhibiting the growth of most of the Firmicutes and Bacteroidetes phyla.

Effect of folic acid treatment on the content of SCFAs in fecal slurry cultures

Figure 6A presents the relative amounts of acetic, propionic, butyric, isobutyric, valeric, isovaleric, hexanoic, and total acids in different cases. Acetic, propionic, and butyric acids constitute 90% to 95% of SCFAs in the human colon. The overall content of SCFAs exhibited significant changes (p < 0.05) with the addition of FA and MTHF. Following folic acid supplementation, the acetic acid content decreased by 23.9 μg/mL (p < 0.0001) and 13.4 μg/mL (p < 0.01), respectively, compared to the Ctrl case. Furthermore, propionic acid, butyric acid, isobutyric acid, isovaleric acid, and capric acid concentrations showed an upward trend after treatment with the two forms of folic acid. Notably, there was a significant difference in the amount of isovaleric acid between the MTHF case and the Ctrl case (p < 0.05).

Fig. 6
figure 6

Effects of folic acid supplementation on SCFA production in an in vitro simulated gut model. A Concentration of SCFAs produced by fermentation of folic acid in vitro: (a) total acid; (b) acetic acid; (c) propionic acid; (d) n-butyric acid; (e) isobutyric acid; (f) n-valeric acid; (g) isovaleric acid; and (h) caproic acid; fermentation time was 24 h. Horizontal coordinates are different concentrations of the two types of folic acid experimental cases. B Heatmap of correlation between gut microbiota and SCFAs. **p < 0.01 and ***p < 0.001

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Correlation analysis of intestinal microorganisms and SCFAs

According to the taxonomic level, correlations between genera and SCFAs were analyzed and evaluated. Figure 6B illustrates the significant differences in correlation coefficients between the majority of SCFA concentrations and species composition. The results revealed positive associations between acetic acid and the genera Lachnospiraaceae ND3004, Roseburia, and Lachnospira. Propionic acid exhibited positive correlations with 15 genera; the genus Oscillospira UCG 005 showed the strongest connection (p < 0.01). Lachnospiraceae UCG 010 demonstrated a strong negative correlation, while Ralstonia and Nocardioides displayed positive correlations with butyric acid levels. Isobutyric acid content showed positive correlations with genus Serratia and Nocardioides, while Bacteroides and Lachnospiraceae UCG 010 exhibited negative correlations. Megamonas and Bamesiella showed a negative association with valeric acid, whereas Phocea and Desulfovibrio with valeric acid levels displayed positive correlations. Among the Firmicutes phylum, several bacteria, including Lachnospiraceae UCG 010, Lachnospira, and Roseburia, exhibited a strong negative correlation with isovaleric acid levels. Ralstonia, Serratia, and Parasutterella spp. of the Proteobacteria phylum showed significant positive associations with hexanoic acid concentration. However, Megamonas and Sutterella displayed a negative correlation with hexanoic acid in terms of their colony abundance levels. Finally, seven genera (Parasutterella, Olsenella, Alcanivorax, Eubacterium ruminantium, Bifidobacterium, Incertae Sedis, and Coprococcus) made significant contributions to the total SCFA concentration. Additionally, Romboutsia, Subdoligranulum, UCG 005, Odoribacter, Coprobacter, Ralstonia, Lahnospiraceae ND3004, and Lactococcus were significantly correlated with the total acid level (p < 0.05).

Discussion

The metabolism of folic acid in vivo has been widely explored, with a primary focus on organs such as the blood and liver (Chen et al. 2019; Li et al. 2022). However, recent literature suggests a potential link between folic acid and the modulation of gut microbiota in the colon (Sun et al. 2022). In line with this research, the present study sought to investigate the impact of folic acid on human intestinal microbiota via the establishment of an in vitro model simulating folic acid deficiency. To evaluate the effects of different forms of folic acid (FA and MTHF), we compared their respective abilities to regulate the human gut microbiota.

In this study, folic acid inoculation cultures were conducted using the widely used in vitro intestinal mimicking medium (VIS). At the genus level, no differences in colony composition were observed between the FA, MTHF, Ctrl, and K cases. The top five genera, in terms of percentage, were Bifidobacterium, Bacteroides, Megamonas, Prevotella, and Escherichia. The addition of high doses of FA resulted in a decrease in the proportion of Bacteroides decreased, accompanied by an increase in the proportion of Faecalibacterium. Phylogenetic analysis conducted by Lopez-Siles et al. (2017) demonstrated variations in the abundance of Faecalibacterium between healthy individuals and those with digestive disorders, suggesting its potential as a valuable biomarker for distinguishing between Crohn’s disease and ulcerative colitis. Additionally, Faecalibacterium is known as the most significant butyrate-producing bacterium in the human colon, and its metabolism generates microbial anti-inflammatory molecules (MAMs) that regulate the healing of intestinal barrier damage through the modulation of tight junction protein (such as zona occluden-1) (Xu et al. 2020). However, high doses of FA supplementation significantly inhibited the Prevotella genus. Iljazovic et al. (2021) reported that Prevotella species have been associated with the etiology of rheumatoid arthritis and periodontal disease. Therefore, further research is needed to investigate whether high FA concentrations can influence the abundance of Prevotella spp. in the colon and potentially reduce the incidence of rheumatoid arthritis.

Based on the obtained results, the supplementation of folic acid was found to have negligible effects on the microbial composition of the VIS medium. These findings are in contrast to previous studies investigating the influence of folic acid, which have reported significant alterations in microbial composition. Jiao et al. (2020) reported that folic acid supplementation decreased the relative abundance of the Actinomycetes phylum and increased the relative abundance of the Anaplasma phylum. At the genus level, they observed varying increases in the genera Lactobacillus, Odoribacter, Alistipes, and Roseburia. Folic acid deficiency and supplementation have been shown to affect host physiology, particularly in relation to changes in the intestinal microbial population, including genera such as Clostridiales, Faecalibacterium, Akkermansia, Alistipes, and Odoribacter (Gurwara et al. 2019; Steinert et al. 2020; Mjaaseth et al. 2021). Furthermore, previous investigations have established a strong connection between alterations in SCFAs and the composition of gut microorganisms (Peng et al. 2013). Various enteric bacteria utilize different pathways, such as the acetyl-CoA or the Wood-Ljungdahl pathway, to convert pyruvate into acetic acid (Hetzel et al. 2003). The propionate production pathways include the succinate cycle, the acrylate pathway, and the propylene glycol pathway (Scott et al. 2006). Butyrate is formed by combining two acetyl-CoA molecules, which are subsequently reduced to butyryl-CoA via the phosphotransferase and butyrate kinase pathway or the acetate CoA transferase process (Duncan et al. 2002; Louis et al. 2014). The hFA case showed higher levels of acetic acid, and Bifidobacterium had the highest relative abundance among the microbial diversity analysis, accounting 25.3% of the bacteria in the hFA case. This finding aligns with a previous study reported by Wang et al. (2017) who suggests a positive association between the relative abundance of Bifidobacteria and the acetic acid concentration when administering Bifidobacteria as a supplement to alleviate constipation in mice. However, the standard in vitro mimicking medium (VIS) was deemed inappropriate for our study, as evidenced by the lack of significant and valid gut microbiota and SCFA data.

The presence of high background levels of the target substance within a system can potentially undermine the functional evaluation of the target substance, thus rendering the subsequent addition of folic acid unable to affect the gut microbiota. Therefore, it is crucial to determine the folic acid content in the VIS medium. HPLC–MS examination revealed a detection of 69.42 ng/mL of folic acid in the VIS medium (Fig. 2E). In order to eliminate the interference caused by background folic acid, Lactobacillus emerged as the new dominant genus after folic acid supplementation (MTHF, FA) when using the folic acid assay medium to create a folic acid-deficient growth environment. This finding is consistent with a previous study by Wang et al. (2021) who reported similar results in the gut microbiota of weaned piglets.

Following fermentation with MTHF and non-reducing folic acid supplementation in folic acid assay medium, folic acid modulated the human gut microbiota by increasing the abundance of Lactobacillus, Pediococcus, and Bifidobacterium, while decreasing the abundance of Bacteroides. Bifidobacterium and Lactobacillus can utilize folic acid supplementation to positively regulate the gut microbiota (Degnan et al. 2014). This may be attributed to the fact that Lactobacillus and Bifidobacterium, as prototrophs capable of folic acid synthesis, can synthesize folic acid through the pterin branches and PABA branches (Rossi et al. 2011). However, since folic acid biosynthesis is an energetically demanding process, protoplasmic nutritional organisms “prefer” uptake from the growth environment (Ciobârcă et al. 2020). Thus, folate may function as a feedback regulator. The increase in microbial utilization after FA supplementation promoted growth and community diversity, particularly the significant increase in the proportion of the Pediococcus genus. Previous studies have indicated that certain Pediococcus species are folic acid-dependent, and their growth can be used as an indicator of folic acid uptake and utilization (Zittoun 1993). The lower relative abundance of the Ctrl case compared to the Ori case provides evidence for the successful construction of the folic acid deficiency model. Moreover, various Pediococcus species have demonstrated anti-inflammatory, anti-cancer, anti-aging, detoxifying, and hypolipidemic properties in studies (Higashikawa et al. 2016; Zhao et al. 2012; Masuda et al. 2010; Ilavenil et al. 2016). The increased abundance of these specific strains suggests that the gut microbiota can be regulated by folic acid, effectively restoring the disrupted structure of the gut microbiota.

Combined with the aforementioned 16S rRNA findings, it is evident that FA supplementation promotes the growth of the Pediococcus genus and gradually regulates the disrupted structure of the gut microbiota by inhibiting the growth of most Firmicutes and Bacteroidetes phyla. In contrast to FA supplementation, MTHF appears to stimulate the proliferation of Firmicutes in fecal samples. However, the supplementation of MTHF exerts an inhibitory effect on pathogenic bacteria while promoting the growth LAB, potentially through the production of organic acids and bacteriocins (Zhou et al. 2021). Concurrently, MTHF supplementation creates a conducive growth environment for specific genera such as Rumincoccus, Fusicatenibacter, Prevotella, and Dialister, suggesting a regulatory role of folic acid on gut microbiota composition (Mager et al. 2020; Hezaveh et al. 2022). Notably, folic acid supplementation, particularly through MTHF, fosters favorable conditions for the proliferation of beneficial bacteria. Overall, FA supplementation promotes the growth of the Firmicutes phylum, represented by Pediococcus and Enterobacter, while MTHF supplementation promotes the growth of the Firmicutes phylum, represented by Lactobacillus and Dorea. These findings underscore the capacity of both FA and MTHF to directly or indirectly shape the intestinal environment and impact the gut microbiota composition upon introduction into the gastrointestinal tract. It was observed that the introduction of folic acid supplementation resulted in the stimulation of Firmicutes phylum growth, specifically characterized by Pediococcus representation, which seems to be a unique and unexplored observation. However, further research is needed to explore the differences in the correlation between FA, MTHF, and changes in the gut microbiota.

The results of our SCFA study demonstrate that the addition of folic acid to fecal samples stimulates the production of propionic, butyric, and isovaleric acids, while inhibiting the production of acetic acid. The decrease in acetic acid content may be associated with the relative abundance of Prevotella, as Prevotella is known to be a major producer of acetic acid (Cheng et al. 2022). This finding is consistent with the notion that folate supplementation can alter the microbial composition. The trend in the effects of different types of folic acid on SCFAs is also consistent. MTHF supplementation, compared to FA, stimulates the production of propionic and isovaleric acids. Previous research has shown that propionate can be produced by Faecalibacteria, Eubacterium, Roseburia, Megasphaera, Ruminococcus, and Roseburia (Reichardt et al. 2014; Louis and Flint 2017), which is in line with 16S rRNA findings indicating changes in the gut microbiota following folic acid treatment in vitro. Isovaleric acid, a branched-chain SCFA, has received less attention, but some studies have found associations between fecal isobutyric acid levels and mesolipid parameters (Granado-Serrano et al. 2019).

In conclusion, the results of our in vitro fecal slurry fermentation study demonstrate that both non-reducing folic acid and MTHF have a significant impact on the gut microbiota and SCFA production. The changes in SCFA levels observed after folic acid supplementation align with those observed after MTHF supplementation, with a decrease in acetate production and an increase in isovaleric acid production. Furthermore, it appears that the two forms of folic acid exert distinct effects on different microbial populations, with non-reducing folic acid inducing more changes in Pediococcus, while MTHF has a greater influence on Lactobacillus. These findings provide new insights into the effects of vitamin B9 (folic acid) on the gut microbiota and have important implications for future research on the bioavailability of micronutrients and their impact on the gut microbiota.