Intermittent Fasting Amplifies Gut–Endocrine Axis Responses to Senna alexandrina Supplementation in Obese Rats

ABSTRACT

Obesity induced by high‑fat, high‑sucrose diets (HFSD) remains a major global health challenge, disrupting lipid metabolism, glucose homeostasis, and gut microbial balance. These disturbances underscore the need for safe interventions capable of restoring metabolic regulation. Senna alexandrina (SA), traditionally used for weight reduction, has recently been shown to modulate the gut microbiota beyond its laxative effects. To enhance efficacy while minimizing adverse outcomes, this study investigated the effects of a low and safe dose of SA combined with intermittent fasting (IF), a strategy that reshapes nutrient availability and microbial dynamics. HFSD‑induced obese rats were treated for four weeks with SA leaf powder (300 mg/kg/day), IF, or both. Bioactive constituents of SA were characterized using LC‑HRMS, alongside systematic evaluation of physiological and metabolic parameters—including adiposity, morphometry, lipid profiles, insulin sensitivity markers, and gut‐endocrine axis indicators. SA supplementation showed improvements across all parameters, surpassing those achieved with IF alone. Importantly, the combined intervention (SA+IF) yielded complementary benefits, notably enhancing GLUT4 expression, short‑chain fatty acid (SCFA) production, peptide YY (PYY) secretion, and reducing the Firmicutes/Bacteroidetes ratio. These findings highlight the complementary roles of SA and IF in metabolic regulation, providing experimental evidence for a potential dietary approach to mitigate obesity‑related dysfunction.

A high‐fat and high‐sucrose diet (HFSD) induced obesity and metabolic dysfunction in rats. Senna alexandrina (SA) with intermittent fasting (IF) alleviates HFSD‑induced obesity in rats, improving lipid metabolism and insulin sensitivity, enhancing GLUT4, SCFA, and PYY levels, and lowering the Firmicutes/Bacteroidetes (F/B) ratio more effectively than either treatment alone.

1. Introduction

Obesity has emerged as a major global health burden, affecting 13% of the world's population in 2022, with prevalence steadily increasing in recent years [1]. It is a major contributor to metabolic disorders, including type 2 diabetes, dyslipidemia, cardiovascular disease (CVDs), and non‑alcoholic fatty liver disease [2]. The pathophysiology of obesity involves a chronic positive energy balance that drives excessive adiposity, dysregulated lipid metabolism, ectopic lipid deposition in non‑adipose tissues, and progressive insulin resistance [2–4]. Recent evidence further highlights the pivotal role of the gut–endocrine axis, with alterations in gut microbiota composition—particularly shifts in the Firmicutes/Bacteroidetes (F/B) ratio—closely linked to obesity [5, 6, 7]. This F/B shift is implicated in short‑chain fatty acid (SCFA) production, impaired endocrine signaling (e.g., GLP‑1 and PYY), increased energy harvest, adiposity, low‑grade systemic inflammation, and insulin resistance [8]. Furthermore, the resulting hormonal imbalance contributes to increased food intake, adiposity, and systemic inflammation, forming a feedback loop that worsens insulin resistance and metabolic dysfunction. Therefore, strategies targeting gut microbiota dysbiosis offer potential to re‐establish metabolic homeostasis in obesity.

Lifestyle modifications, including dietary regulation and regular exercise, are foundational approaches to obesity management. Nevertheless, these strategies are often constrained by long‐term adherence and weight regain [9]. On the other hand, pharmacological options are also limited: orlistat, though widely prescribed, is frequently discontinued due to gastrointestinal adverse events and other undesirable side effects [10]. Even promising new incretin‐based agents, such as GLP‐1 agonists, require ongoing dosing to sustain weight loss and may carry risks, including visual loss [11, 12].  Consequently, alternative approaches that not only address energy balance but also modulate gut microbiota have gained significant attention. In particular, antioxidants, polyphenolic pharmacotherapies, and bioactive‑rich botanical supplements are being explored for their potential to restore microbial homeostasis and endocrine signaling [13, 14].

Senna alexandrina (SA) is a medicinal plant widely distributed in tropical and subtropical regions and traditionally consumed as a herbal drink for its purgative and digestive stimulant [15]. Its potent laxative activity has been recognized by the World Health Organization (WHO) and is approved by the U.S. Food and Drug Administration (FDA) for use in bowel cleansing prior to medical procedures [16]. Beyond this established use, SA contains diverse bioactive metabolites—including anthraquinones, flavonoids, and naphthalenes—that contribute to emerging evidence of metabolic benefits [17, 18]. Several in vitro and in vivo studies suggest that SA may influence glucose and lipid metabolism, linking it to obesity, metabolic syndrome, and diabetes [19 ^, 20]. Nevertheless, its therapeutic application requires careful dose control, as recent reports have documented significant dose‑dependent toxicity, ranging from adverse histological alterations to severe poisoning [21, 22, 23]. Despite this recognized metabolic potential, studies examining the effects of SA on the gut endocrine axis remain limited, highlighting a significant research gap. This limitation underscores the need to develop strategies that enhance SA's metabolic effects without increasing its dose, such as combining its administration with fasting, to determine whether safe use can beneficially modulate the gut–endocrine axis and support metabolic health.

While SA exemplifies the promise of natural remedy approaches, intermittent fasting (IF) has also emerged as a promising dietary intervention for metabolic syndrome and obesity. Evidence from a recent meta‑analysis indicates that IF improves lipid profiles, enhances insulin sensitivity, and supports glycemic control [24]. Moreover, it has been shown to modulate the gut microbiota composition by promoting SCFA‐producing bacteria and increasing microbial diversity [25]. Given the dose‑dependent toxicity concerns associated with SA, combining it with IF offers a strategic means to amplify its metabolic benefits while maintaining safe dosing. Building on this rationale, the present study combined IF with a LC‐HRMS‐characterized preparation of S. alexandrina to evaluate their complementary effects on the gut microbiota composition and metabolic regulation.

2. Experimental Section

2.1. Sample Preparation and Extraction

Leaves of Senna alexandrina (SA) were collected from the Indonesian Center for Research and Development of Medicinal Plants and Traditional Medicine, taxonomically confirmed, and prepared accordingly. Dried SA leaves were ground into a fine powder and administered at a dosage of 300 mg/kg body weight for four weeks. This dosage was selected based on the findings of a previous toxicity study [21], ensuring its safety for in vivo experimentation. To standardize the SA composition used in this study, simplicia powder was extracted by maceration using 70% ethanol (v/v) for 72 h at room temperature in a tightly closed container with occasional stirring. The mixture was filtered through Whatman No. 1, concentrated in a rotary evaporator at 50 °C, and dried in an oven at 40 °C until a constant weight was obtained. The total phenolic (TPC) and flavonoid contents (TFC) were determined colorimetrically, as previously described [18]. Results were expressed as gallic acid equivalents (GAE) and quercetin equivalents (QE), respectively.

2.2. Phytochemical Analysis of S. alexandrina Using LC‐HRMS

Untargeted metabolite profiling was performed using a Vanquish UHPLC system coupled to a Q Exactive Orbitrap MS (Thermo Fisher Scientific). Separation was achieved on an Accucore Phenyl‐Hexyl column (100 × 2.1 mm, 2.6 µm) using a gradient of water and methanol (both containing 0.1% formic acid). Data were acquired in Full MS/dd‐MS² modes (m/z 66.7–1000) in both positive and negative polarities. Data processing, alignment, and compound identification were performed using Compound Discoverer 3.3 and ClassyFire [26]. The detailed instrument parameters and identification workflow are described in the Supplementary Material.

2.3. Animal Experiment

The study was conducted in accordance with the ARRIVE guidelines and approved by the Ethics Committee of Universitas Diponegoro (No. 083/EC‐H/KEPK/FK‐UNDIP/VII/2023). Thirty male Sprague Dawley rats (Rattus norvegicus; aged 8 weeks and weighing 170–200 g) were housed under standard conditions. Male rats were chosen because they are more sensitive to high‐fat, high‐sucrose diets (HFSD), thereby reducing variability in metabolic outcomes. Animals were acclimatized for one week, housed individually under controlled conditions (temperature 18–26 °C, humidity 55%–60%, 12‑h light/dark cycle), with free access to water and a standard diet (Japfa Comfed AD II; production code 153688). Obesity was induced using a high‐fat, high‐sucrose diet (HFSD) via oral gavage for 21 days. The obese rat model was validated by calculating the Lee index, which was > 300. The Lee index was calculated according to a previous study [27] using the following formula:

$$Leeindex=\sqrt[3]{\frac{bodyweight\left(g\right)}{naso-anallength\left(cm\right)}x1000}$$

Rats were randomized into six groups (n  =  5 per group). Five groups underwent obesity induction with a high‑fat, high‑sucrose diet (HFSD): an obese control group (OB, no treatment), an orlistat‑treated group (OB+ORL, 120 mg/kg BW/day), a Senna alexandrina‐treated group (OB+SA, 300 mg/kg/day), an intermittent fasting‐tretated group (OB+IF), and a combined treatment group (OB+SA+IF). An additional non‑obese normal control group (NC) was maintained on a standard diet without HFSD induction. Modified fasting was implemented on an alternate‑day schedule, consisting of two consecutive days per week. During fasting days, animals were restricted to a single meal providing approximately 20% of their daily caloric needs, followed by five days of ad libitum feeding with continuous water access, as described previously [28].

Throughout the next 28‐day intervention, all groups were maintained on a standard non‑HFSD diet, and body weight was measured weekly. At the end of the intervention, rats were euthanized under deep anesthesia (intramuscular ketamine), followed by chloroform exposure and cervical dislocation. Approximately 2 mL of blood was collected from the retroorbital sinus for biochemical analyses, including lipid profiles, hormone levels, and glucose concentrations. The cecum was harvested for SCFA quantification and assessment of the gut microbiome. Liver and heart tissues were excised and weighed to determine wet weight. Figure 1A illustrates the design of the animal diet used in this study.

FIGURE 1.

Phytochemical identification of Senna alexandrina (SA).  (A) SA leaves were ground into a fine powder and used for the in vivo intervention as described. The extract was then prepared for phytochemical profiling. Quantitative analysis of the extract was performed to determine the extraction yield, total phenolic content (TPC), and total flavonoid content (TFC). (B) Metabolomic profiling of the SA extract revealed the distribution of the major chemical superclasses. The detailed identification of the corresponding compounds is provided in Table 1.

2.4. Biochemical Analysis

Serum samples were obtained by centrifugation at 3,000 rpm for 10 min. Lipid profile parameters (total cholesterol, triglycerides, HDL, and LDL) and glucose levels were measured using DiaSys kits (DiaSys Diagnostic Systems GmbH, Germany). Insulin, PYY, and GLUT4 (from skeletal muscle tissue) were quantified using FineTest ELISA kits (Wuhan Fine Biotech Co., Ltd., China) according to the manufacturer's protocol.

Short‐chain fatty acids (SCFAs) were analyzed from rat cecum samples using gas chromatography‐mass spectrometry (GC–MS) following an in‐house organic extraction protocol modified from a previous study [29]. Briefly, cecal contents were acidified with metaphosphoric acid solution, followed by the addition of NaCl. Samples were vortexed, mixed with methyl tert‑butyl ether (MTBE), and centrifuged to separate phases. The MTBE layer was collected and transferred into 2 mL vials for GC–MS injection. Standard solutions were prepared using a volatile fatty acid (VFA) mix (CRM46975, Supelco) at concentrations ranging from 0.1 to 2 mM and processed using the same extraction procedure without the addition of metaphosphoric acid. GC–MS analysis was performed using a DB‑FastFAME column (30 m × 250 µm × 0.25 µm) with helium as the carrier gas at a flow rate of 1 mL/min. The oven temperature program was set as follows: initial 50 °C for 1 min, ramped at 15 °C/min to 200 °C and held for 1 min, then ramped at 30 °C/min to 230 °C and held for 1 min, with a total run time of 14 min. The inlet was operated in split mode at 250 °C with a 1 µL injection volume and a split ratio of 1:10. Mass spectrometry was conducted under electron impact ionization (70 eV), with a transfer line temperature of 250 °C, source temperature of 230 °C, quadrupole temperature of 150 °C, and mass range scanned from m/z 20–200. Data acquisition was performed between 3.8 and 10.5 min of the chromatographic run. SCFA concentrations, including acetate, propionate, and butyrate, were calculated from calibration curves generated with the VFA standard mix, normalized to sample wet weight, and expressed as mean ± SD for each group. Statistical differences were assessed using one‑way ANOVA followed by Tukey's post hoc test, with p < 0.05 considered significant. Results were summarized in tables and bar graphs to highlight relative changes among groups.

2.5. Firmicutes/Bacteroidetes Ratio by qPCR

DNA was isolated from rat cecum samples using the FavorPrep Stool DNA Isolation Kit (Favorgen Biotech Corp., Taiwan). DNA quality and purity were assessed spectrophotometrically, and only samples with an A260/A280 ratio of 1.8‐2.0 were used for downstream analysis. Quantitative PCR (qPCR) was performed on a Bio‑Rad CFXT real‑time PCR system using 2× Universal SYBR Green Fast qPCR Mix (Abclonal Technology, China) in a two‑step cycling protocol according to the manufacturer's instructions. Each reaction contained 50 ng of template DNA and 0.2 µM of each primer in a total volume of 20 µL. Primers specific for Firmicutes (forward: CTG ATG GAG CAA CGC CGC GT; reverse: ACA CYT AGY ACT CAT CGT TT), Bacteroidetes (forward: CCG GAW TYA TTG GGT TTA AAG GG; reverse: GGT AAG GTT CCT CGC GTA), and universal bacterial 16S rRNA (forward: TCC TAC GGG AGG CAG CAG T; reverse: GGA CTA CCA GGG TAT CTA TCC TGT T) were used. Reaction specificity and quality were verified by melt curve analysis, with a single peak at the expected melting temperature (Tm) confirming primer specificity and the absence of non‑specific amplification. Relative quantification of Firmicutes and Bacteroidetes was calculated using the ΔΔCt method, normalized to universal bacterial 16S rRNA [30].

3. Results

3.1. Phytochemical Profiling of SA by LC‐HRMS

Untargeted LC‐HRMS metabolomics analysis identified 514 metabolites in SA. Rigorous filtering based on mass accuracy, fragmentation matching, and literature validation for the senna genus and specific compounds yielded 389 high‐confidence annotated compounds (Supplementary Materials). Automated chemical classification revealed 15 major chemical classes, with a balanced distribution of bioactive superclasses: fatty acyl compounds (13.21%), organonitrogen compounds (12.78%), and phenylpropanoids and polyketides (14.80%) (Figure 1B). Flavonoids constituted the largest subclass of phenylpropanoids, representing 12.14% of all annotated compounds. Table 1 presents the profiles of the 33 selected compounds identified as major components, species markers, and pharmacologically active constituents. These include the well‐known sennosides B‐D, anthraquinone derivatives, and markers of the senna genus, as well as other anthracenes such as aloe‐emodin, rhein, and physcion. Senna is rich in flavonoids (TFC: 22.14 mg QE/g) and phenolic acids (TPC: 109.74 mg GAE/g) (Figure 1A), which are known for their antioxidant and metabolic‐regulating properties. The flavonoids identified by LC‐HRMS were quercetin, kaempferol, rutin, catechin, and resveratrol, as well as essential fatty acids such as linoleic acid. The presence of these bioactive constituents suggests that SA may have multitarget activity and serve as a reservoir of pharmacologically active compounds.

TABLE 1.

Profile of bioactive metabolites in Senna alexandrina extract determined by LC‐HRMS analysis.

No	Classification	Metabolite	Formula	Adducts	RT (min)	m/z	Peak area (a.u.)
Benzenoids (Major Laxative Compounds)
1	Anthracenes	Sennoside B	C42H38O20	[M+Na]+	5.84	885.18	24,144.07
2	Anthracenes	Sennoside D	C42H40O19	[M+NH4]+	5.93	848.22	69,242.71
3	Anthracenes	Sennidin C (Aglycone)	C30H20O9	[M+H]+	6.18	525.12	5,354,451.09
4	Anthracenes	Rhein	C15H8O6	[M+H]+	9.46	285.04	6,283,751.33
5	Anthracenes	Aloe‐emodin / Emodin	C15H10O5	[M+H]+	8.35	271.06	29,091,249.18
6	Anthracenes	Chrysophanol	C15H10O4	[M+H]+	7.39	255.07	2,617,303.25
7	Anthracenes	Physcion	C16H12O5	[M+H]+	7.04	285.08	17,878,270.8
8	Anthracenes	2‐Hydroxyemodin glucoside	C21H20O10	[M+H]+	5.63	433.11	36,741,024.17
Benzenoids (Naphtalene Derivatives/ Species Markers)
9	Benzenoids—Naphthalenes	Tinnevellin / Torachrysone glucoside	C20H24O9	[M+H]+	6.87	409.15	473,631,009.8
10	Benzenoids—Naphthalenes	6‐Hydroxymusizin	C14H16O4	[M+H]+	9.97	249.11	2,170,381.14
Flavonoids (Antioxidants)
11	Flavonoids	Kaempferol‐O‐hexoside‐pentoside (Major)	C27H30O15	[M+H]+	4.62	595.17	192,164,293.7
12	Flavonoids	Quercetin	C15H10O7	[M+H]+	7.49	303.05	84,852,384.96
13	Flavonoids	Kaempferol	C15H10O6	[M+H]+	8.40	287.06	144,797,778.3
14	Flavonoids	Isorhamnetin	C16H12O7	[M+H]+	5.58	317.07	53,261,437.13
15	Flavonoids	Rutin	C27H30O16	[M+H]+	5.80	611.17	368,796,582
16	Flavonoids	Hyperoside / Quercetin‐3‐glucoside	C21H20O12	[M+H]+	5.72	465.10	62,624,217.02
17	Flavonoids	Kaempferol‐3‐O‐glucoside	C21H20O11	[M+H]+	6.20	449.11	72,540,979.18
18	Flavonoids	Vitexin	C21H20O10	[M+H]+	5.63	433.11	36,883,078.44
19	Flavonoids	Orientin	C21H20O11	[M+H]+	5.17	449.11	3,966,605.54
20	Flavonoids	Catechin / Epicatechin	C15H14O6	[M+H]+	4.44	291.09	12,690,087.41
21	Flavonoids	Myricetin	C15H10O8	[M+H]+	4.78	319.05	24,264,984.3
22	Flavonoids	Apigetrin	C21H20O10	[M+H]+	6.43	433.11	9,320,153.78
23	Flavonoids	Biochanin A	C16H12O5	[M+H]+	7.14	285.08	11,148,876.8
24	Flavonoids	Daidzein	C15H10O4	[M+H]+	7.32	255.07	4,520,096.67
Phenolic Acids and Others
25	Cinnamic acids	Caffeic acid	C9H8O4	[M+H‐H2O]+	6.07	163.04	6,845,908.27
26	Cinnamic acids	Ferulic acid	C10H10O4	[M+H‐H2O]+	5.73	177.06	15,456,022.13
27	Cinnamic acids	p‐Coumaric acid	C9H8O3	[M+NH4]+	0.99	182.08	22,077,448.6
28	Cinnamic acids	Sinapic acid	C11H12O5	[M+H‐H2O]+	5.84	207.07	13,513,246.99
29	Phenols	Gentisic acid	C7H6O4	[M+H]+	1.60	155.03	5,122,941.41
30	Phenols	Salicylic acid	C7H6O3	[M+H]+	1.71	139.04	12,254,394.75
31	Other	cis‐Resveratrol	C14H12O3	[M+H]+	7.17	229.09	5,138,718.21
Fatty Acyls
32	Fatty Acyls	Linoleic acid	C18H32O2	[M+H]+	14.97	281.25	22,327,261.14
33	Fatty Acyls	Palmitic acid	C16H32O2	[M+H‐H2O]+	14.36	239.24	23,206,036.16

Abbreviations: RT, retention time; m/z, mass‐to‐charge ratio.

3.2. Body Weight and Relative Organ Weights

To evaluate the anti‐obesity potential of SA powder, IF, and their combined intervention (SA+IF), changes in body weight and morphometric indices in experimental rats were systematically monitored over 28 days. The obese group (OB) exhibited markedly rapid body weight gain compared to the normal control group (NC) following obesity induction using a high‐fat‐high‐sucrose diet (HFSD) (Figure 2A). Intervention with SA or IF as monotherapy or in combination (SA+IF) attenuated weight gain relative to the untreated OB. A comparable reduction in weight gain was also observed in obese rats treated with orlistat (OB+ORL), a reference anti‑obesity drug that inhibits lipid absorption.

FIGURE 2.

Therapeutic effects on body morphometry and organ indices. (A) Weekly body weight trajectory over a 9‐week experimental period. (B) Comparative analysis of the Lee Index before and after the intervention. (C) Relative liver weight and (D) relative heart weight normalized to body weight (g/100 g). (E) Representative images of rats from each experimental group. Data are presented as mean ± SD (n = 5 biological replicates). In panel B, the statistical significance between pre‐ and post‐intervention is indicated by ** for p < 0.01 and **** for p < 0.001. In panels C and D, different superscript letters (a–d) denote significant differences between groups at p < 0.05 (one‑way ANOVA followed by Tukey's post hoc test). NC, normal control; OB, obese control; ORL, orlistat; SA, Senna alexandrina powder; IF, intermittent fasting.

The decrease in body weight was also confirmed using the Lee Index, a measure of adiposity (Figure 2B). As anticipated, the untreated OB group maintained an elevated Lee Index during the intervention period, despite the HFSD being replaced with a standard diet. In contrast, all treatment groups (ORL, SA, IF, and SA+IF) showed a marked decrease in adiposity markers relative to their respective pre‐intervention values (p < 0.001), indicating a return to a lean metabolic state. Macroscopic assessment also confirmed these findings, as the treated rats were exhibited less obesity than the OB animals (Figure 2E).

To extend these findings, we assessed obesity‐related organ hypertrophy. Relative liver and heart weights were markedly elevated in obese rats compared to those in the NC group (p < 0.05), indicating hepatomegaly and cardiac hypertrophy (Figure 2C, D). The weights of these organs in the obese treated groups were significantly lower than those in the untreated OB, suggesting that the interventions alleviated obesity‐associated stress in the visceral organs. Importantly, co‐administration of SA and IF (OB+SA+IF) resulted in a greater reduction in hepatic weight than either treatment alone.

3.3. Attenuation of Atherogenic Dyslipidemia and Mitigation of Cardiovascular Risk Indices

A HFSD induced dyslipidemia in the OB group, characterized by markedly elevated total cholesterol (TC), triglyceride (TG), and low‐density lipoprotein (LDL) levels compared to the normal control (NC) (p < 0.05). At the same time, high‐density lipoprotein (HDL) levels were significantly lower (Figure 3A‐D). SA and IF interventions significantly improved lipid imbalances. In particular, SA administration showed greater therapeutic potential than IF and demonstrated a therapeutic efficacy that marginally exceeded that of standard ORL treatment. Surprisingly, the combined administration (SA did not confer additional benefits, as the lipid profile was restored only to levels comparable to those observed in the respective monotherapy groups.

FIGURE 3.

Modulatory effects on serum lipid profiles and atherogenic risk indices. (A‐D) Serum concentrations of total cholesterol (TC), triglycerides (TG), LDL, and HDL. (E) atherogenic index of plasma (AIP), calculated as log₁₀ (TG/HDL). (F) Castelli's risk index I (TC/HDL) and (G) Castelli'srisk index II (LDL/HDL) serve as predictive markers of cardiovascular risk. Data are presented as mean ± SD (n = 5 biological replicates). Different superscript letters (a–e) indicate statistically significant differences between groups at p < 0.05 (one‐way ANOVA followed by Tukey's test). Group abbreviations are defined as previously stated.

Alongside lipid biomarkers, the atherogenic index of plasma (AIP) and Castelli's risk index (CRI) were calculated for their qualitative effects on lipoprotein profiles implicated in CVDs. While the OB group showed marked elevations in both markers, SA intervention was significantly more effective than IF in mitigating these elevations (Figure 3E‐G). Collectively, the administration of SA and IF not only lowers lipid mass but also actively shifted the lipoprotein profile toward a nonatherogenic state, thereby mitigating the estimated risk of coronary events; however, this represents a partial recovery, as the indices do not fully return to baseline levels in healthy controls (NC).

3.4. Improvement of Systemic Glucose Homeostasis and Insulin Sensitivity

To better understand the mechanisms driving metabolic recovery in adiposity and lipid metabolism, we assessed the roles of glycemic control and insulin resistance. Compared with the NC group, obese rats (OB group) exhibited markedly higher fasting blood glucose levels, lower insulin levels, and reduced GLUT4 expression (Figure 4A–C). Coupled with elevated HOMA‐IR and reduced HOMA‐β indices (Figure 4D,E), the data clearly demonstrate obesity‐induced insulin resistance. SA and IF interventions improved this condition, although SA was more effective than IF monotherapy in markedly correcting glycemic disturbances. Its efficacy in reducing insulin resistance was comparable to that of the standard ORL treatment. Importantly, the combination of SA and IF demonstrated superior efficacy in upregulating GLUT4 expression, achieving values significantly higher than those observed in the other intervention groups, indicating a significant additive effect. Collectively, these findings indicate that SA and IF interventions improve glycemic control and enhance insulin sensitivity and secretion, thereby reducing the risk of progressive metabolic failure.

FIGURE 4.

Improvement of glycemic control via GLUT4 modulation. (A) Fasting blood glucose levels after the intervention period. (B) Serum insulin concentration. (C) GLUT4 protein expression level. (D) Assessment of insulin sensitivity using HOMA‐IR and (E) HOMA‐β levels. Data are presented as mean ± SD (n = 5 biological replicates). Different superscript letters (a–f) indicate statistically significant differences between groups at p < 0.05 (one‐way ANOVA followed by Tukey's test). Group abbreviations are defined as previously stated.

3.5. Shifting the Gut‐Endocrine Axis

To examine the potential link between gut dysbiosis and metabolic dysfunction, we assessed the Firmicutes‐to‐Bacteroidetes (F/B) ratio and evaluated the related metabolic byproducts. The OB group exhibited a significantly higher F/B ratio and a lower caecum weight than the normal group (NC), indicating severe dysbiosis (Figure 5A‐B). Following the interventions, the F/B ratio was significantly lower in both the SA and IF groups than in the OB group. Notably, co‐administration of SA and IF demonstrated the strongest efficacy, lowering the F/B ratio to levels statistically indistinguishable from those in the healthy NC group, while also enhancing SCFA production more effectively than either intervention alone (Figure 5D‐F). Circulating PYY levels showed modest improvement in the SA+IF group compared with either monotherapy, although recovery remained below that of the normal control group (Figure 5C).

FIGURE 5.

Gut microbiota modulation enhances SCFA–mediated secretion of peptide YY (PYY). (A) Relative cecum weight. (B) Firmicutes‐to‐Bacteroidetes ratio (F/B). (C) Circulating peptide YY (PYY) concentrations. (D–F) Short‐chain fatty acids (SCFAs): acetic acid (D), propionic acid (E), and butyric acid (F). Data are presented as mean ± SD (n = 5 biological replicates). Different superscript letters (a–e) indicate statistically significant differences between groups at p < 0.05 (one‐way ANOVA followed by Tukey's test). Group abbreviations are defined as previously stated.

Spearman's rank correlation analysis was conducted to assess the relationship between microbial metabolites and hormonal responses. Figure 6 demonstrates a strong positive correlation between increased SCFA concentrations and PYY secretion (P < 0.001). In contrast, a significant negative correlation was observed between these markers and the dysbiosis F/B ratio. These findings indicate that the therapeutic effects of the combination strategy are mechanistically linked to gut microbiota remodelling, which, in turn, promotes SCFA‐mediated signalling.

FIGURE 6.

Spearman correlation heatmap illustrating associations between PYY, SCFAs, and gut microbiota composition. The correlation analysis evaluates the relationships among PYY hormone levels, short‐chain fatty acid (acetic acid, propionic acid, butyric acid) profiles, and gut microbiota composition (F/B ratio, Firmicutes, Bacteroidetes). Values inside the boxes represent the correlation coefficient (r). The color scale indicates the strength and direction of the correlation: lighter colors represent a strong positive correlation, and darker colors represent a negative correlation. Asterisks denote statistical significance levels: **p < 0.01 and ***p < 0.001. ns, non‐significant.

4. Discussion

This study highlights the distinct yet complementary roles of Senna alexandrina (SA) leaf powder supplementation and alternate‐day IF in the management of diet‐induced obesity in a rat model. SA exerted broader and more potent effects on adiposity, lipid regulation, and glycemic stability, whereas IF primarily influenced systemic metabolic reprogramming via microbial composition and endocrine signaling. Interestingly, the combined intervention demonstrated additive benefits in gut endocrine signaling and metabolic regulation, highlighting its therapeutic potential.

The pronounced lipid‐lowering effects of SA observed in this study can be attributed to its diverse phytochemical composition, as confirmed by LC‐HRMS profiling. The analysis identified 389 annotated compounds, including flavonoids and anthraquinones, consistent with earlier reports using HPLC‐MS/MS [19] and LC‐ESI‐MS [17] analyses. Key metabolites such as sennosides, apigetrin, isorhamnetin, and kaempferol have been reported to regulate obesity‐related traits. Supporting evidence from previous studies shows that upon ingestion, sennosides are hydrolyzed by colonic β‐glucosidases to produce sennidin derivatives, including the biologically active Sennidin C [31]. This compound has been shown to accelerate intestinal transit, reduce fat absorption, and ultimately limit fat deposition [32]. In addition to sennosides, other phytochemicals in SA also contribute to metabolic regulation. Apigetrin suppresses adipogenesis by downregulating PPARγ and CCAAT/enhancer‐binding protein alpha (C/EBPα) [33], whereas flavonoids such as isorhamnetin and kaempferol enhance lipoprotein lipase activity, promoting triglyceride hydrolysis [31]. Collectively, these findings explain the significant reduction in triglyceride and cholesterol levels observed in SA‐treated rats, positioning SA as a potent modulator of lipid metabolism.

In parallel with SA‐derived phytochemical modulation, our study also demonstrated that alternate‑day IF improved body weight, the Lee index, and fat deposition in both cardiac and hepatic tissues. These outcomes reflect systemic metabolic adaptation, whereby energy utilization shifts from glucose to fatty acid oxidation, enhancing adipose tissue lipolysis and restoring glucose homeostasis [34, 35]. According to previous research, IF suppresses lipogenic gene expression (SREBP1c) and activates AMPK, which inhibits ACC and FAS activity, thereby reducing hepatic triglyceride synthesis [36]. Such mechanisms likely underlie the metabolic improvements observed in the fasting groups.

In the combined intervention group, circulating lipid outcomes did not differ significantly from those observed with SA monotherapy, indicating that IF did not provide additional lipid‑lowering benefits. Regulation of lipid metabolism in this group was likely mediated through distinct mechanisms: IF via systemic metabolic reprogramming and SA mainly through direct enzymatic and absorptive modulation. Notably, despite these complementary pathways, the combination did not yield further reductions in lipid parameters beyond those achieved with SA alone. We hypothesize that this reflects a physiological “ceiling effect,” whereby SA exerts a near‑maximal inhibitory action on intestinal lipid absorption, leaving little space for IF to further lower circulating lipids. It is important to note that this interpretation remains hypothetical and requires confirmation in future studies.

Beyond modulation of lipid profiles, our study demonstrated that both SA and IF improved glycemic control and insulin sensitivity. Obese rats exhibited lower circulating insulin levels despite persistent hyperglycemia, reflecting chronic β‑cell dysfunction. With intervention, HOMA‐β scores improved, and GLUT4 expression increased, indicating partial restoration of β‐cell capacity and enhanced peripheral glucose uptake. Supporting evidence from previous studies shows that IF activates AMPK signaling [37], facilitating GLUT4 translocation in the skeletal muscle and improving glucose uptake [38]. Likewise, phytochemicals in SA, including sennosides and apigenin (the unglycosylated form of apigetrin), have been reported to stimulate GLP‑1 secretion and reduce ectopic fat deposition, thereby reinforcing insulin sensitivity and endocrine balance [39 ^, 40]. Interestingly, the additive effect of SA and IF was most evident in GLUT4 expression. This selective effect may reflect the convergence of complementary mechanisms: IF enhances systemic insulin sensitivity through AMPK activation and metabolic reprogramming, while SA phytochemicals such as apigenin reinforce glucose transport by modulating endocrine pathways. The overlap of these pathways likely amplifies GLUT4 translocation in skeletal muscle, explaining why the combined intervention yielded significantly higher GLUT4 levels compared to either monotherapy.

At the gut level, our study found that both SA and IF interventions lowered the Firmicutes‐to‐Bacteroidetes (F/B) ratio in obese rats, an indicator often associated with improved microbial balance. These changes were accompanied by increased SCFA concentrations, particularly butyrate, and enhanced PYY secretion, suggesting the responsiveness of gut‐derived signaling to single interventions. To date, very limited studies have directly examined the impact of SA on gut microbiota composition, making these findings an important early indication of Senna's potential influence on microbial ecology. In support of this, previous reports have shown that diverse bacterial guilds, including Bacteroidetes, Clostridium, and Eubacterium, metabolize sennoside A into its active metabolite, rhein anthrone, via nitroreductase enzymes such as NrfA [41]. Such selective microbial transformation may contribute to the reduced Firmicutes/Bacteroidetes ratio and increased SCFA concentrations observed in senna‑treated obese rats in this study. Furthermore, Senna's flavonol apigenin has been reported to enhance butyrate production, support gut barrier integrity, and reinforce GLP‑1 signaling [42], which is consistent with the PYY increases observed in our SA groups. IF, on the other hand, has also been reported to reshape microbial communities by reducing carbohydrate availability, thereby limiting the expansion of Firmicutes while favoring Bacteroidetes due to their metabolic flexibility [43]. Moreover, fasting–feeding cycles entrain microbial diurnal oscillations, selectively suppressing Firmicutes and promoting Bacteroidetes [44]. These structural shifts alter SCFA dynamics, increasing propionate levels and modifying butyrate pathways, thereby contributing to changes in gut endocrine signaling, including PYY secretion [43].

In contrast to hepatic lipid metabolism, the gut‐endocrine axis in our study remained highly responsive to combined modulation. Pairing IF with SA supplementation resulted in additive improvements in SCFA concentrations and PYY secretion, surpassing the effects of either intervention alone. This amplification likely reflects the convergence of IF‐driven‐ microbial shifts with Senna's gut‐protective‐ actions, whereby fasting alters substrate availability and microbial oscillations. At the same time, bioactive compounds in SA reinforce barrier integrity and incretin signaling. Together, these complementary mechanisms account for the enhanced gut‐endocrine outcomes observed with this combined intervention.

Nevertheless, this study has several limitations. First, relying on the F/B ratio as a proxy for microbial shifts, without comprehensive metagenomic profiling, limits insights into the broader microbiome. Future studies should incorporate functional analyses, including SCFA synthase pathways, bile acid pool characterization, and incretin hormone profiling (GLP‑1, GIP), as well as the SCFA receptor FFAR2/3, to provide mechanistic precision. Second, due to its high anthraquinone content and potent laxative properties, SA must be positioned as a strictly dosed adjunctive therapy rather than a routine “functional food.” Carefully designed human pilot studies with rigorous safety monitoring are essential for this purpose. Finally, computational modeling of SA metabolite pharmacokinetics could clarify the balance between systemic and gut‑localized actions, offering mechanistic insights and guidance for clinical translation. Such integrative approaches will be crucial for establishing IF‐ and SA‐based interventions as scientifically robust and clinically viable strategies for managing metabolic health.

5. Concluding Remark

In conclusion, SA supplementation and alternate‑day IF each conferred significant benefits in mitigating diet‑induced obesity in rats. Both interventions improved metabolic health by modulating circulating lipids, stabilizing glycemic control, and supporting microbial balance. Importantly, the convergence of IF‑driven ecological shifts with Senna's gut‑active phytochemicals yielded additive effects on the Firmicutes‑to‑Bacteroidetes ratio, SCFA production, and PYY secretion, suggesting involvement of gut–endocrine signaling. Collectively, these findings highlight the potential therapeutic relevance of integrating phytochemical supplementation with lifestyle strategies, while emphasizing the need for mechanistic precision and rigorous safety evaluation in future translational studies.

Author Contribution

FF and LB: conceptualization; FF: methodology; SAB, RJK, RCDH, MIF, GC, and FF: data acquisition; ISW: formal analysis; FF, ISW, LB, and RMDA: writing – original draft preparation; FF: writing – review and editing; FF: funding acquisition. All authors have read and agreed to the published version of this manuscript.

Funding

This research was funded by the Grant for Research, Development, and Application (RPP), Faculty of Medicine, Diponegoro University (Grant Decree No. 22/UN7.F4/PP/III/2024).

Conflicts of Interest

The authors declare no conflicts of interest.

Ethics Statement

This study was conducted in accordance with the ARRIVE guidelines. Ethical approval for this study was obtained from the Health Research Ethics Committee (KEPK) of the Faculty of Medicine, Universitas Diponegoro, Semarang, Indonesia (Approval No. 083/EC‐H/KEPK/FK‐UNDIP/VII/2023).

Supporting information

Supporting File: mnfr70531‐sup‐0001‐SuppMat.docx.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.