After 15, 30, 45, 60, 75, and 90 days of treatment (Supplementary Table 1), OLZ treatment caused significant weight gain in rats compared to the normal control group (p < 0.001), emphasising the substantial impact of OLZ on BW. The weights of the animals in the low-dose (p < 0.05) and high-dose probiotic (p < 0.001) groups were significantly lower than those in the OLZ and N groups on days 15, 30, and 45, and in comparison, the weights of the test groups (V and VI) (p < 0.001) were significantly lower on days 60, 75, and 90 days. Both groups V and VI demonstrated significant weight control from 15 to 90 days of treatment compared to the OLZ group (p < 0.001) and both probiotic-only treated groups (Fig. 2).

Mean of comparison of BW between various experimental groups at baseline at the end of 90 days. μ: compared to (vs) N (p < 0.001); Å: vs O (p < 0.001); κ: vs PM (p < 0.001); λ: vs PH (p < 0.001); δ: vs groups PM, PH, TM, and TH (p < 0.001), γ: vs. N, O, TM, TH (p < 0.001)

After 15 days, OLZ treatment significantly increased the MAP of the rats compared to that in the N, PM, and PH groups (p < 0.001). After 30 days, the MAP was lower in the PM (p < 0.05), PH (p < 0.001), and TM (p < 0.05) groups than in the OLZ group. The OLZ group maintained significantly greater MAP than all the treatment groups (I, III, IV, V, and VI) from 45 to 90 days (p < 0.001), underscoring the persistent hypertensive effect of OLZ over time. MAP was significantly lower in groups V and VI than in the OLZ group after 15, 30 (p < 0.05), and 45–90 days (p < 0.001), highlighting the ability of probiotics to counteract OLZ-induced hypertension (supplementary data Table 2 and Fig. 3).

Mean of comparison of MAP between various experimental groups at baseline at the end of 90 days. μ: compared to (vs) N (p < 0.001); δ: vs groups PM, PH, TM, and TH (p < 0.001); Å: vs O (p < 0.001)

After 30 days of OLZ treatment, there was a significant increase in TC levels compared to those in the N (p < 0.05), PM (p < 0.05), PH (p < 0.05), and both TM and TH (p < 0.001) groups. After 45 days, the OLZ group continued to exhibit a significant increase in TC levels compared to those of the N (p < 0.05), TM (p < 0.05), PM, and PH (p < 0.001) groups. The pattern persisted at 60, 75, and 90 days, with the OLZ group showing significantly higher cholesterol levels than the normal control group and all other treatment groups (p < 0.001). The sustained cholesterol-lowering benefit of probiotic treatment, alone or in conjunction with OLZ (p < 0.001), was evident throughout the study (Table 1).

After 15 days of OLZ treatment, there was a significant increase in TG levels compared to those in the PM and TM groups (p < 0.05). After 30, 45, 60, 75, and 90 days of treatment, OLZ significantly increased the TG levels compared to those in all other groups (p < 0.001). Both probiotic-only treated groups consistently exhibited significant reductions in TG levels, indicating a sustained antihyperlipidemic effect. The TM and TH treatments effectively reduced TG levels, suggesting that probiotics are more effective at mitigating the hyperlipidemic effects of OLZ over an extended period.

After 30 days, OLZ treatment significantly decreased HDL-C levels compared to those in both the low- and high-dose probiotic groups (p < 0.05). Similarly, compared with those in the OLZ group, the HDL-C levels in the TM and TH groups were significantly greater (p < 0.001). After 45 days of treatment, the data showed that both the low- and high-dose probiotic groups experienced a significant increase in HDL-C levels compared to groups I, II, V, and VI, with p < 0.001. This trend of significant improvement continued for both probiotic-only treated groups at the end of 60, 75, and 90 days, consistently showing higher HDL-C levels compared to all other groups, with significance noted at p < 0.001 across all these time points.

Conversely, compared with OLZ alone, the combination of OLZ with either low-dose or high-dose probiotics increased HDL-C levels at 45 days (p < 0.001). This pattern of increase persisted at 60, 75, and 90 days, indicating a beneficial effect of probiotics when used in conjunction with OLZ, suggesting sustained improvements in HDL-C levels with probiotic cotreatment.

After the 90-day study, OLZ treatment significantly decreased the serum serotonin and serum dopamine levels in rats (p < 0.05) compared to those in the probiotics group (both low- and high-dose) when given alone and in combination with OLZ. Conversely, treatment with both low and high doses of probiotics alone or in combination with OLZ significantly increased serum serotonin and serum dopamine levels (p < 0.005) compared to those in the OLZ-only group, indicating the effectiveness of long-term use of probiotics in managing the OLZ-induced changes in serotonin and dopamine levels that impact MS (Figs. 4 and 5).

Comparison of serum serotonin levels at baseline and at the end of 90 days of treatment in various treatment groups. *Compared to (vs) O (p < 0.05); β: vs groups (PM, PH, TM and TH) (p < 0.05); #: vs N (p < 0.05)

Comparison of serum dopamine levels at baseline and at the end of 90 days of treatment in various treatment groups. *Compared to (vs) O (p < 0.05); β: vs PM, PH, TM and TH groups (p < 0.05); #: vs N (p < 0.05)

H&E-stained cross-sections of the colon were observed under a light microscope at 40× magnification. The structure of the mucosal and submucosal regions was considered for qualitative assessment. The N, PM, PH, and TH groups exhibited normal colon epithelium with intact surface epithelium and intestinal crypts (shown with yellow arrow) with abundant goblet cells (black arrow). The submucosa looked normal, with loose connective tissue and blood vessels (Fig. 6).

H&E-stained rat intestine under ×40 magnification showing changes (arrows) in the normal control (N) (a), probiotic low dose (PM) (c), probiotic high dose (PH) (d), OLZ + probiotic low dose (TM) (e), OLZ (O) (b), and OLZ + probiotic high dose (TH) (f) groups at the end of 90 days

The colonic mucosa looked highly abnormal in the O (Fig. 6b) and TM (Fig. 6e) groups. There were several indications of superficial mucosal necrosis. Intestinal crypts appeared damaged and reduced in number in some places (white arrow). At many places, massive inflammatory cell infiltration into the lamina propria, submucosa, and surrounding smooth muscle fibres of the muscularis mucosa was observed (red arrows) (Fig. 6b, e). Other histopathological features of ischaemic colitis, such as intestinal crypt injury, crypt dropout, lamina propria hyalinization, and vascular congestion, were also observed in some regions.

Photomicrographs of H&E-stained liver tissue as observed under a light microscope (40× magnification). Two major components of liver structure, the hepatocellular architecture and biliary system, were considered for qualitative assessment. Notably, the hepatic architecture of the N, PM, and PH groups was normal (the black arrow indicates normal hepatocytes). Group O, TM, and TH showed features of fatty liver (the yellow arrows indicates fatty liver cells) (Fig. 7).

H&E-stained rat hepatic tissue under ×40 magnification showing changes in the normal control (N) (a), OLZ (O) (b), probiotic low-dose (PM) (c), probiotic high-dose (PH) (d), OLZ + probiotic low-dose (TM) (e), and OLZ + probiotic high-dose (TH) (f groups at the end of 90 days of treatment; CV is the central vein of the liver, the black arrow indicates normal hepatocytes, and the yellow arrow indicates fatty liver cells

The normal control group (Fig. 7a) exhibited a normal liver structure with hexagonal hepatic lobules, a central vein, and a typical arrangement of hepatic cords radiating from the central vein. Portal triads were also normal in their location and pattern. Group O (Fig. 7b) exhibited abnormal hepatic architecture. Large areas of steatosis (fatty liver) and inflammatory cell collection indicate pathology leading to MS. The PM and PH groups (Fig. 7c, d) mostly exhibited a normal hepatocyte structure and architecture without fatty liver or inflammatory cells. The TM group (Fig. 7e) showed predominantly normal hepatic architecture; some areas of tissue demonstrated features of fatty liver. The TH group (Fig. 7f) mostly exhibited normal hepatocyte structure and architecture. However, some areas showed features of mild fatty cells in the liver.

Taxonomic analysis was performed using a bar plot (type III) of the relative abundance (RA) (%) of phyla and genera in the GM between various groups after 16S rRNA metagenomic analysis of the rat fecal samples. RA bar plots of the phylum comparisons of the treatment groups are given below:

As shown in Fig. 8A, the taxonomic analysis bar plot (type III) indicated that the RA (%) of the GM of the top nine phyla varied between group I and group II after 16S rRNA metagenomic analysis of the rat fecal samples. Among these phyla, the Firmicutes group (60%) was predominant in group II, followed by the Saccharibacteria (TM7) (23%), Bacteroidetes (10%), Actinobacteria (5%), other bacteria (1%), and Proteobacteria (1%) groups. In group I, the predominant phyla were the Bacteroidetes (46%), Firmicutes (45%), TM7 (8%), other bacteria (1%), and Proteobacteria (1%) (Fig. 8C).

Bar plot-III (A, B) indicating that the relative abundance (RA) (%) of the GM of the top nine phyla (A) and ten genera (B) varied between group I (N) and group II (O) after 90 days of treatment; C, D are pie charts of the RA (%) of the top 8 phyla (C) and the top 10 genera (D) of group I and group II after 90 days of treatment (E)MDA plot of genera (group I vs. group II), (F) MDA plot of phyla (group I vs. group II

Taxonomic analysis indicated that the RA (%) of the 43 genera in the GM varied between groups I and II. Figure 8B–D shows the 10 most abundant genera and the genera of the other organisms in both groups. Among these genera, Ruminococcaceae (34%) was the predominant genus in group II, followed by TM7_genus_incertae_sedis (23%), others (11%), Clostridiales and Firmicutes (7% each), Porphyromonadaceae and Ruminococcus (4% each), Lachnospiraceae (3%), Bifidobacterium (2%), Collinsella (2%), and Blautia (2%). In the normal control group, Ruminococcaceae (22%) was the most prevalent genus, followed by other bacteria (17%), Porphyromonadaceae (11%), Bacteroides (9%), Prevotella and TM7_genus_incertae_sedis (8% each), Firmicutes (6%), Bacteriodales, Ruminococcus, Bacteroidetes and Clostridiales (5% each).

The MDA plot of genera (group I vs. group II) (Fig. 8E) illustrates that Blautia, Bifidobacterium, Barnesialla, Bacteroidetes, Bacteroides, Bacteroidales, Anaerovorax, Anaeroplasma, Anaerofustis, Anaerobiospirillum, Allobaculum, Alistipes, and Actinomyces are important genera for differentiating/classifying these two groups. Lower Blautia, Bifidobacterium, Anaerovorax, Anaerobiospirillum, Allobaculum, and Actinomyces abundances are characteristic of group I, whereas higher Barnesiales, Bacteroidetes, Bacteroides, Bacteroidales, Anaeroplasma, Anaerofustis, and Alistipes abundances are characteristic of group II. Both groups of organisms can be identified using the levels of these genera.

The MDA plot of phyla (group I vs. group II) (Fig. 8F) illustrates that TM7, Tenericutes, Proteobacteria, Firmicutes, Elusimicrobia, Bacteroidetes, and Actinobacteria are important phyla for differentiating/classifying these two groups. Lower TM7, Proteobacteria, Firmicutes, and Actinobacteria abundances and higher Tenericutes, Elusimicrobia, and Bacteroidetes abundances are characteristic of group I. The exact opposite is true for group II. Using the levels of these phyla, both groups of organisms can be identified. A higher MDA value indicates the importance of that taxa in predicting or differentiating the groups. The genera/phyla obtained in the MDA plots are essential for classifying the respective groups.

The genus comparison bar plots, MDA plots, and pie charts of the remaining group comparisons are provided in the supplementary files.

The RA (%) of the GM of the top nine phyla varied between groups I and III after 16S rRNA metagenomic analysis of the rat faecal samples (Fig. 9). Among these phyla, Bacteroidetes (46%) was predominant in group I, followed by the Firmicutes group (44%), TM7 (8%), other bacteria (1%), and Proteobacteria (1%). In group III, the predominant phyla were the Bacteroidetes (47%), Firmicutes (39%), TM7 (10%), Actinobacteria (2%), and other bacteria (1%).

Bar plots of the RAs (%) of the GM phyla of group I (N) and group III (PM) after 90 days of treatment

The RAs (%) of the GM of the top nine phyla varied between groups I and IV after 16S rRNA metagenomic analysis of the rat faecal samples, as depicted in Fig. 10. Among these phyla, Bacteroidetes (46%) was the most abundant in group I, followed by Firmicutes (44%), TM7 (8%), other bacteria (1%), and Proteobacteria (1%). In group IV, the most prevalent phylum was Firmicutes (47%), followed by Bacteroidetes (32%), TM7 (18%), Actinobacteria (2%), other bacteria (1%), and Proteobacteria (1%).

Bar plots of the RA (%) of the GM of groups I (N) and IV (PH) phyla after 90 days of treatment

Figure 11 depicts the bar plot of the RA (%) of the GM of phyla that varied between groups II and V after 16S rRNA metagenomic analysis of the rat faecal samples. After supplementation with a low dose of probiotics along with OLZ, the abundance of Firmicutes decreased (43% compared with 60% in group II), with a substantial 33% increase in the abundance of Bacteroidetes in group V (43% compared with group V vs. 10% compared with group II). There was also an increase in the abundance of Actinobacteria (11% compared with group V vs. 5%—group II) and a decrease in the abundance of Actinobacteria in TM7 (< 1%—group V vs. 23%—group II) compared with those in the OLZ group.

Bar plots of the RA (%) of the GM of the group II (O) and group V (TM) phyla after 90 days of treatment

The RA (%) of the GM of the top seven phyla varied between groups II and VI after 16S rRNA metagenomic analysis of the rat faecal samples, as depicted in Fig. 12. There was a noteworthy 14% increase in Bacteroidetes and a minor 1% increase in the Proteobacteria phylum in group VI, whereas 10% Firmicutes and 4% Actinobacteria were reduced compared to those in group II.

Bar plots of the RA (%) of the GM of the group II (O) and group VI (TH) phyla after 90 days of treatment

Figure 13 shows that the RA (%) of the GM of the top seven phyla varied between groups V and VI after 16S rRNA metagenomic analysis of the rat faecal samples. There was a 23% and 7% increase in the RA of TM7 and Firmicutes, respectively, in group VI compared to group V. Bacteroidetes and Actinobacteria were increased by 19% and 10%, respectively, in the low-dose group compared to the high-dose group, highlighting the dose-dependent advantage of probiotics in inducing the phyla that are beneficial for preventing the symptoms of MS.

Bar plots of the RA (%) of the GM of group V (TM) and group VI (TH) at the phylum level after 90 days of treatment

Figure 14 shows the RA (%) of the GM across the top phyla, highlighting differences between groups II and III following 16S rRNA metagenomic analysis of the rat fecal samples. Notably, there was a 37% increase in the RA of the beneficial Bacteroidetes phylum in the group administered a low dose of probiotics compared to that in the OLZ group. This finding underscores the potential of probiotics for promoting MGBA homeostasis. Conversely, the OLZ group exhibited 21% and 13% increases in the Firmicutes and TM7 phyla, respectively. These changes highlight the association of OLZ with dysbiosis and the disruption of intestinal integrity, potentially leading to MS.

Bar plots of the RA (%) of the GM of group II (O) and group III (PM) at the phylum level after 90 days of treatment

The bar plot (Fig. 15) shows the RA (%) across the top phyla, highlighting differences between the GM of groups II and IV following 16S rRNA metagenomic analysis of rat fecal samples. Notably, there was a 22% increase in the RA of the beneficial Bacteroidetes phylum in the group administered a high dose of probiotics compared to that in the OLZ group. This finding underscores the potential of probiotics in promoting MGBA equilibrium. In contrast, the OLZ group exhibited 13%, 6%, and 3% increases in the Firmicutes, TM7, and Actinobacteria phyla, respectively. These changes highlight the association of OLZ with dysbiosis and the loss of gut barrier integrity, potentially leading to MS.

Bar plots of the RA (%) of the GM of groups II (O) and IV (PH) at the phylum level after 90 days of treatment

Alpha diversity was employed to assess both the richness and diversity of bacteria within a specific group. The species richness measured with the Chao1 index exhibited a significant difference between the groups (p < 0.05) (Figs. 16 and 17).

Comparison of alpha diversity among microbiome of different genera using Chao1 (p < 0.05, Kruskal–Wallis test)

Comparison of alpha diversity among microbiome of different phylum using Chao1 (p < 0.05, Kruskal–Wallis test)

Almost all the groups demonstrated reduced alpha diversity, as evidenced by both Simpson (p < 0.001) and Shannon (p < 0.001) indices (Figs. 18, 19, 20, 21).

Comparison of alpha diversity among microbiome of different genera using Shannon index (p < 0.05, Kruskal–Wallis test)

Comparison of alpha diversity among microbiome of different phylum using Shannon index (p < 0.05, Kruskal–Wallis test)

Comparison of alpha diversity among microbiome of different genera using Simpson index (p < 0.05, Kruskal–Wallis test)

Comparison of alpha diversity among microbiome of different phylum using Simpson index (p < 0.05, Kruskal–Wallis test)

The beta diversity analysis was carried out to understand how the microbial communities clustered among the six groups. Diversity profiles in samples were clustered and notably distinct from each group by the Principal Coordinate Analysis (Figs. 22 and 23). The compositional variations among the groups were found to be statistically significant (p < 0.01) based on the PERMANOVA test (Fig. 24).

Principal coordinate analysis (PCoA) highlighting beta diversity of distinct bacterial communities of genera clustering among the groups (p < 0.01, PERMANOVA)

Principal coordinate analysis (PCoA) highlighting beta diversity of distinct bacterial communities of phylum clustering among the groups (p < 0.01, PERMANOVA)

A The MDA plot of important genera as biomarkers among different groups. B The MDA plot of important phylum as biomarkers among different groups