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Opinion

Intermittent Fasting and Probiotics for Gut Microbiota Modulation in Type 2 Diabetes Mellitus: A Narrative Review

Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
*
Author to whom correspondence should be addressed.
Nutrients 2026, 18(1), 119; https://doi.org/10.3390/nu18010119 (registering DOI)
Submission received: 29 November 2025 / Revised: 27 December 2025 / Accepted: 28 December 2025 / Published: 30 December 2025
(This article belongs to the Special Issue Intermittent Fasting: Health Impacts and Therapeutic Potential)

Abstract

Background: Type 2 diabetes mellitus (T2DM) is a global epidemic in which gut microbiota dysbiosis contributes to impaired glucose homeostasis and chronic inflammation. Intermittent fasting (IF) and probiotic supplementation have independently demonstrated glycemic benefits in T2DM, largely through microbiota remodeling. This narrative review synthesizes evidence up to October 2025 to clarify the microbiota-dependent mechanisms of IF and probiotics, and to evaluate the biological plausibility and preliminary clinical data for their combined application in T2DM management. Methods: We conducted a comprehensive literature review of preclinical and clinical studies (PubMed, Embase, Web of Science, and Cochrane Library) examining IF regimens (primarily time-restricted feeding and 5:2 protocols) and multi-strain probiotics containing Lactobacillus and Bifidobacterium species in T2DM or relevant models. Mechanistic pathways, microbial compositional shifts, and metabolic outcomes were qualitatively synthesized, with emphasis on overlapping signaling (short-chain fatty acids, bile acids, GLP-1, and barrier function). Results: IF consistently increases Akkermansia muciniphila and, variably, Faecalibacterium prausnitzii abundance, restores microbial circadian rhythmicity, and enhances SCFA and secondary bile acid production. Multi-strain probiotics modestly reduce HbA1c (–0.3% to –0.6%) and fasting glucose, outperforming single-strain preparations. Both interventions converge on reduced endotoxaemia and improved intestinal integrity. Preclinical models indicate potential synergy, whereas the only direct human trial to date showed neutral results. Conclusions: IF and probiotics engage overlapping microbiota-mediated pathways, supporting their combined use as an adjunctive strategy in T2DM. Adequately powered randomized trials incorporating deep metagenomics, metabolomics, and hard clinical endpoints are now required to confirm additive or synergistic efficacy.

1. Introduction

Type 2 diabetes mellitus (T2DM) affects over 500 million adults worldwide and remains a leading cause of cardiovascular disease, kidney failure, and premature mortality [1]. Despite advances in pharmacotherapy, a substantial proportion of patients fail to achieve glycemic targets, underscoring the need for effective, sustainable, and widely accessible adjunctive strategies [2]. The gut microbiota has emerged as a critical regulator of host glucose homeostasis [3,4]. Patients with T2DM typically exhibit reduced microbial diversity, depletion of butyrate-producing taxa, and impaired barrier function, collectively contributing to metabolic endotoxemia and systemic inflammation [5,6]. Interventions that favorably remodel microbial composition or function therefore represent attractive therapeutic targets.
Intermittent fasting (IF)—encompassing time-restricted feeding (TRF), alternate-day fasting, and 5:2 regimens—improves insulin sensitivity, reduces body weight, and lowers HbA1c in individuals with T2DM, often independently of calorie reduction [7,8,9]. Beyond direct metabolic effects, IF profoundly alters gut microbial ecology within days to weeks. Clinical studies, including large recent randomized trials, demonstrate that 14–18 h daily fasting windows consistently increase the relative abundance of Akkermansia muciniphila and, with greater inter-individual variability, Faecalibacterium prausnitzii [10,11,12,13,14]. These shifts coincide with restored microbial circadian rhythmicity, enhanced short-chain fatty acid (SCFA) production, and improved intestinal barrier integrity—mechanisms that likely contribute to the observed glycemic benefits [15,16,17]. Probiotic supplementation offers a complementary microbiota-directed approach. Meta-analyses of randomized controlled trials up to 2025 indicate that multi-strain preparations containing Lactobacillus and Bifidobacterium species modestly reduce fasting glucose (−0.4 to −0.9 mmol/L) and HbA1c (−0.3% to −0.6%) in T2DM, whereas single-strain interventions frequently yield null results [18,19,20,21]. The superior efficacy of multi-strain formulations is attributed to ecological complementarity, cross-feeding, and broader immunomodulatory effects [22,23,24]. Although IF and probiotics independently engage overlapping pathways—SCFA signaling, GLP-1 secretion, bile acid metabolism, and reduction in low-grade inflammation—their potential interaction remains underexplored. Preclinical models suggest that fasting-induced expansion of Akkermansia may create a more permissive niche for exogenous beneficial strains, whereas probiotics could stabilize IF-induced microbial shifts during refeeding phases [25,26]. However, the only dedicated human trial combining IF with a Lactobacillus rhamnosus strain in prediabetes reported no additive benefit [17], highlighting the need for cautious interpretation.
This narrative review, based on a structured literature search of PubMed, Embase, and Scopus and manual reference screening, aims to: (1) summarize the effects of IF and probiotic interventions on gut microbiota composition and function in T2DM; (2) delineate the microbiota-dependent mechanisms underlying their metabolic benefits, with emphasis on Akkermansia muciniphila and Faecalibacterium prausnitzii; (3) critically evaluate the biological plausibility and preliminary evidence for combined approaches; and (4) identify priority areas for future research, including adequately powered trials incorporating multi-omics and hard clinical endpoints. By clarifying the microbiota as a convergent hub for timed eating and microbial therapeutics, we seek to inform the rational design of precision nutrition strategies for T2DM.

2. Mechanistic Pathways Linking Intermittent Fasting, Gut Microbiota, and Type 2 Diabetess

Intermittent fasting (IF) improves glycemic control and insulin sensitivity in individuals with T2DM through multiple microbiota-dependent mechanisms. These include altered substrate availability, reinforcement of microbial and host circadian rhythms, remodeling of bile acid metabolism, increased production of short-chain fatty acids (SCFAs), and enhanced intestinal barrier function.

2.1. Altered Substrate Availability and Microbial Selection

Prolonged daily fasting markedly reduces the delivery of dietary polysaccharides and proteins to the distal gut, creating a low-energy, mildly acidic, mucus-reliant niche. This environment suppresses fast-growing opportunists (e.g., Enterobacteriaceae) while favoring mucin-degrading specialists, particularly Akkermansia muciniphila, and certain Lactobacillus species [12,13,17]. In both rodent TRF models and human Ramadan cohorts, 14–18 h daily fasting consistently increases Akkermansia abundance (1.5–5-fold) and often enriches Faecalibacterium prausnitzii [12,13,27,28,29]. These compositional shifts persist for days to weeks after fasting cessation, indicating a degree of microbial “memory” [17,30].

2.2. Restoration of Microbial and Host Circadian Oscillations

Feeding-fasting cycles act as a potent zeitgeber for the gut microbiome. Ad libitum feeding or mistimed meals flatten diurnal microbial oscillations, whereas TRF restores rhythmic fluctuations in Akkermansia, Lactobacillus, and butyrate-producing taxa [17,31,32,33,34,35,36]. In humans, early time-restricted eating (eTRE) reinstates microbial rhythmicity within 2–4 weeks. It also increases α-diversity and elevates fecal butyrate. These changes correlate with improved insulin sensitivity and reduced systemic inflammation [7,37,38,39,40]. Alignment of feeding with the host molecular clock (CLOCK/BMAL1) appears essential, as genetic disruption of Bmal1 abolishes microbial cycling and exacerbates glucose intolerance [31].

2.3. Bile Acid Rhythmicity and Host Signaling

TRF restores diurnal oscillations in hepatic bile acid synthesis (Cyp7a1, Cyp8b1) and ileal bile acid pool size, amplifying peak-to-trough differences [41,42]. The resulting rhythmic exposure to conjugated primary bile acids favors taxa possessing bile salt hydrolase (BSH) activity, including Akkermansia and certain Bacteroides spp. Deconjugation and limited 7α-dehydroxylation alter the secondary-to-primary bile acid ratio, modulating intestinal FXR and TGR5 signaling. Although the net effect of FXR activation in T2DM remains context-dependent [43,44,45,46]. IF-induced bile acid remodeling consistently correlates with reduced hepatic glucose output and enhanced GLP-1 secretion in preclinical and small human studies [43,44,47]. These effects culminate in improved insulin signaling, as illustrated in Figure 1.

3. Microbiota-Mediated Mechanisms Underlying the Metabolic Benefits of Intermittent Fasting

Intermittent fasting (IF) improves glycemic control in T2DM primarily through microbiota-dependent pathways. These include enhanced short-chain fatty acid (SCFA) signaling, restored gut barrier integrity, increased GLP-1 secretion, and improved peripheral insulin sensitivity [15,16,17,48,49,50,51]. However, while human trials consistently show microbial compositional shifts and metabolic improvements, most mechanistic details are derived from preclinical models (rodent TRF studies, germ-free mouse colonization, and in vitro assays), with human evidence largely limited to correlative associations from fecal metagenomics, plasma metabolites, and indirect biomarkers [9,14,47]. Tissue-level (e.g., intestinal L-cells, liver, muscle) validation in humans remains scarce.
The two most consistently modulated taxa in human IF studies are Akkermansia muciniphila and Faecalibacterium prausnitzii. Meta-analyses of trials up to 2025 confirm that 14–18 h daily fasting windows typically increase A. muciniphila abundance (effect size 0.6–1.2 log2 fold) and, less uniformly, F. prausnitzii [9,14,47]. Preclinical evidence proposes overlapping and distinctive contributions from these taxa, primarily through the following pathways (summarized in Figure 2).

3.1. Overlapping Mechanisms

In rodent models and human fecal analyses, SCFAs from both taxa are proposed to activate FFAR2/3 on L-cells. This stimulates GLP-1 and PYY secretion (acetate/propionate from A. muciniphila; butyrate-dominant from F. prausnitzii). These metabolites may also engage AMPK and PI3K–Akt signaling in peripheral tissues (liver, muscle, adipose). This suppresses gluconeogenesis (via PEPCK/G6Pase downregulation) and enhances glucose uptake via GLUT4 translocation [48,49,50,51]. Both taxa additionally appear to reinforce intestinal barrier function by upregulating tight-junction proteins (ZO-1, occludin) and mucin production, potentially reducing LPS translocation and metabolic endotoxemia—a correlation observed in small human IF cohorts [10,12,14,26,52,53].

3.2. Distinctive Contributions

Akkermansia muciniphila and Faecalibacterium prausnitzii are two taxa most consistently associated with IF-related metabolic effects, although mechanistic support in humans remains limited. For A. muciniphila, preclinical studies suggest that its outer-membrane protein Amuc_1100 (TLR2-dependent) and the secreted protein P9 (via the ICAM-2/PLC/Ca2+/CREB axis) may induce GLP-1 secretion largely independently of SCFAs, improving glucose homeostasis in obese and diabetic mouse models [36,47,54,55]. Human data are limited to associations between fecal Akkermansia levels and plasma GLP-1/insulin sensitivity [47,56].
F. prausnitzii is primarily implicated through anti-inflammatory mechanisms. In vitro and rodent studies demonstrate secretion of the microbial anti-inflammatory molecule (MAM), inhibition of NF-κB signaling, and induction of antigen-specific CD4+CD8αα+ regulatory T cells producing IL-10 and TGF-β, collectively reducing systemic inflammation [36,57,58,59]. Human IF trials report reduced circulating inflammatory markers correlating with F. prausnitzii enrichment, but causality is unproven [14,47].
In contrast, responses of Bacteroides spp. (including the B. fragilis group) to IF appear heterogeneous across studies [18,29,60]. While preclinical data suggest potential immunoregulatory effects via polysaccharide A–induced IL-10–producing Tregs through TLR2 signaling [61,62], other evidence indicates strain- and context-dependent adverse metabolic effects, including FXR dysregulation, impaired metformin efficacy, and hepatic steatosis [46]. Human metabolic implications therefore remain uncertain and warrant caution.
Collectively, these microbiota-associated mechanisms—supported predominantly by preclinical evidence—are hypothesized to converge on improved peripheral insulin sensitivity and reduced hepatic glucose output, as schematically summarized in Figure 2. Confirmation of causal relevance in humans will require longitudinal intervention studies integrating strain-resolved multi-omics and tissue-level validation.

4. Probiotic-Mediated Modulation of Gut Microbiota in T2DM

Meta-analyses of RCTs up to 2025 consistently demonstrate that multi-strain probiotics containing Lactobacillus and Bifidobacterium species modestly but significantly improve glycemic control in T2DM, reducing HbA1c by 0.3–0.6% and fasting glucose by 0.4–0.9 mmol/L when administered for ≥8 weeks [19,20,63]. These effect sizes are comparable to or exceed those of some oral glucose-lowering agents, with excellent tolerability. By contrast, single-strain interventions—particularly Lactobacillus monotherapy—frequently yield null or clinically negligible results [19,21,64].
Network meta-analyses confirm superior efficacy of multi-strain over single-strain formulations, attributable to ecological complementarity, cross-feeding (e.g., BifidobacteriumFaecalibacterium butyrate production), and broader immunomodulatory coverage [20,65,66]. Subgroup analyses indicate that interventions containing ≥3 strains and total doses ≥109 CFU/day are most effective [20,63].

4.1. Core Microbiota-Dependent Mechanisms

Multi-strain Lactobacillus–Bifidobacterium probiotics engage largely overlapping microbiota-mediated pathways with intermittent fasting (as detailed in Section 3), including enhanced SCFA production and FFAR2/3 signaling, reinforcement of intestinal barrier integrity, suppression of proinflammatory pathways, and restoration of peripheral insulin signaling [50,67,68,69,70]. Notably, certain aspects may be more pronounced or complementary with probiotics: Cross-feeding synergies: Bifidobacterium strains efficiently produce acetate, which promotes butyrate synthesis by indigenous producers such as Faecalibacterium prausnitzii [65,66]. Strain-specific immunomodulation: Selected Lactobacillus strains potently inhibit NF-κB activation and upregulate tight-junction proteins [68,70,71]. These complementary effects likely underlie the greater efficacy of multi-strain preparations compared to single strains.

4.2. Translational Limitations

Although multi-strain probiotics containing Lactobacillus and Bifidobacterium species have demonstrated modest but reproducible improvements in glycemic control in T2DM across multiple meta-analyses [19,20,63], several important limitations and sources of heterogeneity constrain their current clinical application and interpretation of efficacy. Mechanistic understanding remains predominantly derived from preclinical models and indirect circulating biomarkers. Human data providing tissue-level or causal validation of proposed pathways are sparse [68,69]. Strain-specific effects, optimal combinations, dosing thresholds, and long-term safety profiles beyond 12 months are incompletely characterized [19,20]. Furthermore, substantial inter-individual and inter-study variability in response exists. This variability is driven by differences in baseline microbiota composition, host genetics, concurrent medications (particularly metformin), dietary patterns, and degree of metabolic dysregulation. As a result, outcomes are heterogeneous, reducing the reliability of pooled estimates and limiting generalizability [3,5,12,20,70].

5. Intermittent Fasting Combined with Probiotics

5.1. Preclinical Evidence Suggesting Potential Interactions

Preclinical studies provide preliminary evidence suggesting potential interactions between intermittent fasting (IF) and multi-strain probiotics in experimental models of T2DM. In high-fat diet/STZ-induced diabetic mice, alternate-day fasting combined with a multi-strain Lactobacillus–Bifidobacterium cocktail resulted in greater reductions in fasting glucose, HOMA-IR, and hepatic steatosis than either intervention alone [7]. These effects were accompanied by enrichment of Akkermansia and Faecalibacterium species and increased fecal butyrate levels [7,26,48]. However, these findings are derived exclusively from animal models and cannot be directly extrapolated to human clinical efficacy.
Mechanistically, IF may favor the expansion of mucin-degrading and butyrate-producing taxa, potentially altering microbial ecology during re-feeding periods [14,23,27,34]. In theory, such shifts could influence the metabolic activity of exogenous Lactobacillus and Bifidobacterium strains, while probiotics may help stabilize fasting-induced microbial changes and modulate SCFA signaling and intestinal barrier function in metabolic disease models [50,51,65]. Importantly, these proposed interactions remain mechanistic and require validation in well-designed human studies.

5.2. Clinical Evidence Suggesting Potential Interactions

Clinical evidence evaluating the combined effects of IF and probiotic supplementation in T2DM remains sparse and inconclusive. To date, only one dedicated human randomized controlled trial (RCT) has explicitly examined this interaction. The PROFAST trial (2020) [17] evaluated a 5:2 IF regimen combined with a single-strain probiotic (Lacticaseibacillus rhamnosus HN001) versus IF plus placebo in 34 adults with prediabetes. Both groups achieved similar reductions in HbA1c (−0.4%) and body weight, with no additional glycemic benefit attributable to probiotic supplementation [17]. Interpretation of these findings is limited by the small sample size, the use of a single probiotic strain with limited evidence of efficacy in T2DM, and the inclusion of individuals with prediabetes rather than established T2DM.
A 2024 pilot RCT in medication-naïve T2DM patients (n = 46) investigated 16:8 time-restricted feeding combined with a multi-strain probiotic formulation. Although the combined intervention produced a numerically greater reduction in HbA1c compared with IF alone (−0.9% vs. −0.6%), this difference did not reach statistical significance (p = 0.07) [72]. The study was underpowered for primary glycemic endpoints due to its small sample size and the absence of stratification by baseline gut microbiota composition, which may have introduced additional variability. While secondary outcomes showed greater increases in circulating butyrate and GLP-1 levels, these findings should be interpreted as exploratory rather than indicative of clinical superiority.
Current evidence does not support clear clinical benefits of combined IF–probiotic interventions. Probiotic meta-analyses show only modest glycemic effects, and studies are heterogeneous in formulation and design [19,20,63], Well-powered RCTs are needed. These should use multi-strain or next-generation probiotics, consider baseline microbiota for stratification, and include hard endpoints such as cardiovascular outcomes or medication reduction, before additive or synergistic effects can be confirmed.
Table 1 summarizes representative preclinical and clinical studies of intermittent fasting and probiotic interventions relevant to T2DM. Several studies were conducted in non-T2DM populations or animal models and are included to illustrate mechanistic plausibility rather than direct clinical efficacy; large, long-term trials of combined interventions in T2DM remain lacking.

6. Discussion

IF and multi-strain probiotics independently remodel the gut microbiota in T2DM. The most consistent changes include enrichment of Akkermansia muciniphila and, to a lesser extent, Faecalibacterium prausnitzii, along with alterations in SCFA signaling, intestinal barrier function, and inflammatory tone (Section 2, Section 3 and Section 4). In human studies, these microbial shifts are generally associated with modest improvements in glycemic control. Reported HbA1c reductions range from ~0.3–0.6% for probiotic interventions and vary for IF depending on regimen, duration, and population [7,9,14,19,20,63,73,74,75]. Despite this mechanistic convergence, evidence supporting additive or synergistic clinical effects of combined IF–probiotic interventions remains limited, with only preclinical models and small pilot studies suggesting potential complementarity [7,17,72]. Table 1 provides a concise overview of representative studies and underscores the scarcity of direct human evidence for combination therapy.
Collectively, current evidence suggests several relatively consistent patterns. First, A. muciniphila shows the most reproducible increase across human IF trials, coinciding with restoration of microbial rhythmicity and changes in SCFA and bile acid metabolism [10,11,12,13,14,30,33,47,75]. Second, multi-strain probiotic formulations (typically ≥3 strains at doses ≥ 109 CFU/day) appear more effective than single-strain preparations, plausibly through ecological complementarity, cross-feeding, and broader immunomodulatory effects [20,63,65,66]. Finally, while these observations provide a coherent mechanistic rationale for combined approaches, human evidence remains preliminary and insufficient to establish clinical superiority.

6.1. Limitations

Studies vary widely in design, populations, fasting protocols, and probiotic formulations, complicating synthesis and comparison [14]. Most mechanistic insights come from animal or reductionist models. Human data are mostly associative, based on correlations between fecal microbiota and circulating metabolic or inflammatory markers. Direct tissue-level or causal validation, such as FMT or strain-targeted interventions, is limited [68,69]. Key limitations therefore include the predominance of associative evidence, the scarcity of long-term trials (with most interventions lasting ≤12 weeks and limited data beyond 6 months), the lack of hard clinical endpoints (such as cardiovascular events, diabetes complications, or mortality), and the near absence of adherence and cost-effectiveness data—issues that are particularly relevant for lifestyle-based interventions such as IF.

6.2. Real-World Feasibility

Translation of IF–probiotic strategies into routine clinical practice faces several practical challenges. Adherence to IF may be limited by cultural and social eating patterns, lifestyle constraints (e.g., shift work, family meals), and concerns regarding hypoglycemia in medicated patients with T2DM, with dropout rates in some trials reported in the range of 20–40% [7,9,40]. Probiotic implementation is further constrained by issues of shelf stability and viability (particularly in hot or humid climates), relatively high costs for multi-strain products, variability in strain composition across commercial formulations, and uncertain engraftment in markedly dysbiotic gut ecosystems [22,66]. These considerations highlight the need for pragmatic, real-world studies that extend beyond short-term efficacy.

6.3. Future Directions

Future research should address the following major gaps through targeted, high-quality studies:
  • Limited human evidence for combined interventions: Only one small RCT has tested IF with probiotics, showing no additive benefit [17]. Large-scale, adequately powered RCTs are needed to evaluate optimized IF regimens combined with evidence-based multi-strain probiotics.
  • Short-term focus and lack of hard endpoints: Most trials are ≤12 weeks and report surrogate markers. Longer-duration studies incorporating hard clinical outcomes (e.g., cardiovascular events, diabetes complications, remission rates) are essential.
  • Insufficient causal mechanistic data: Current human findings are largely correlative. Trials should integrate strain-resolved metagenomics, metabolomics, and—where ethical and feasible—tissue-level assessments to establish causality.
  • Real-world translation gaps: Adherence, safety, and cost-effectiveness remain underexplored in diverse populations. Pragmatic trials in clinically representative cohorts are required to assess long-term feasibility.
These priorities will determine whether combined IF–probiotic approaches offer meaningful adjunctive benefits beyond contemporary standards of care.
In conclusion, while intermittent fasting and probiotic supplementation represent promising, microbiota-targeted adjunctive strategies for T2DM, combined approaches should currently be regarded as experimental. Rigorous, long-term evaluation against established standards of care is required before routine clinical recommendations can be justified.

Author Contributions

Conceptualization, Z.Z. and D.P.; methodology, Z.Z.; software, Z.Z.; validation, Z.Z. and D.P.; formal analysis, Z.Z.; investigation, Z.Z.; resources, D.P.; data curation, Z.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, D.P.; visualization, Z.Z.; supervision, D.P., S.W. and G.S.; project administration, D.P., S.W. and G.S.; funding acquisition, D.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (82204030) and the Fellowship of China Postdoctoral Science Foundation (2025M770748, 2024T170134).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The funding unit had no role in the whole study including study design, collection of data, analysis of results and composition of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AMPAMP-activated protein kinase
BMAL1Brain and muscle Arnt-like 1
BSHBile salt hydrolase
CREBcAMP response element-binding protein
Cyp7a1Cholesterol 7α-hydroxylase
eTREEarly time-restricted eating
FFAR2/3Free fatty acid receptor 2/3
FXRFarnesoid X receptor
G6PaseGlucose-6-phosphatase
GLP-1Glucagon-like peptide-1
GLUT4Glucose transporter type 4
HbA1cGlycated hemoglobin A1c
HGPHepatic glucose production
ICAM-2Intercellular adhesion molecule 2
IFIntermittent fasting
IL-10Interleukin-10
LPSLipopolysaccharide
MAMMicrobial anti-inflammatory molecule
NF-κBNuclear factor kappa B
PEPCKPhosphoenolpyruvate carboxykinase
PI3KPhosphatidylinositol 3-kinase
PLCPhospholipase C
PYYPeptide YY
RCTRandomized controlled trial
SCFAShort-chain fatty acid
T2DMType 2 diabetes mellitus
TGF-βTransforming growth factor beta
TGR5Takeda G protein-coupled receptor 5
TLR2Toll-like receptor 2
TRFTime-restricted feeding
ZO-1Zonula occludens-1

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Figure 1. Intermittent fasting remodels gut microbiota composition in type 2 diabetes by reducing substrate availability, restoring microbial circadian rhythmicity, and amplifying bile acid oscillations, thereby selectively enriching Akkermansia muciniphila and other beneficial taxa to improve insulin sensitivity and glycemic control.
Figure 1. Intermittent fasting remodels gut microbiota composition in type 2 diabetes by reducing substrate availability, restoring microbial circadian rhythmicity, and amplifying bile acid oscillations, thereby selectively enriching Akkermansia muciniphila and other beneficial taxa to improve insulin sensitivity and glycemic control.
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Figure 2. Overlapping and distinctive microbiota-mediated mechanisms by which intermittent fasting may improve glycemic control in type 2 diabetes mellitus (primarily supported by preclinical evidence). (a) SCFA-independent signaling pathways of Akkermansia muciniphila: outer-membrane protein Amuc_1100 activates TLR2, while secreted protein P9 engages the ICAM-2/PLC/Ca2+/CREB axis; both promote GLP-1 secretion and peripheral insulin sensitivity via PI3K–Akt. (b) Anti-inflammatory actions of Faecalibacterium prausnitzii: microbial anti-inflammatory molecule (MAM) inhibits NF-κB, and metabolites induce IL-10/TGF-β-producing CD4+CD8αα+ regulatory T cells, reducing endotoxemia and inflammation. Black arrows represent activation or promotion, while red lines denote inhibition. Solid and dashed lines indicate direct and indirect regulation, respectively. The upward and downward arrows indicate an increase and a decrease in levels, respectively.
Figure 2. Overlapping and distinctive microbiota-mediated mechanisms by which intermittent fasting may improve glycemic control in type 2 diabetes mellitus (primarily supported by preclinical evidence). (a) SCFA-independent signaling pathways of Akkermansia muciniphila: outer-membrane protein Amuc_1100 activates TLR2, while secreted protein P9 engages the ICAM-2/PLC/Ca2+/CREB axis; both promote GLP-1 secretion and peripheral insulin sensitivity via PI3K–Akt. (b) Anti-inflammatory actions of Faecalibacterium prausnitzii: microbial anti-inflammatory molecule (MAM) inhibits NF-κB, and metabolites induce IL-10/TGF-β-producing CD4+CD8αα+ regulatory T cells, reducing endotoxemia and inflammation. Black arrows represent activation or promotion, while red lines denote inhibition. Solid and dashed lines indicate direct and indirect regulation, respectively. The upward and downward arrows indicate an increase and a decrease in levels, respectively.
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Table 1. Summary of evidence on intermittent fasting and probiotic interventions affecting glucose metabolism and related metabolic outcomes.
Table 1. Summary of evidence on intermittent fasting and probiotic interventions affecting glucose metabolism and related metabolic outcomes.
ReferenceTypeInterventionPopulation/ModelSample SizeKey Microbiota ChangesMetabolic Outcomes
Liu et al. (2024) [7]PreclinicalIF + SLBZS (prebiotic-like)STZ-HFD diabetic miceN = 63 (9/group)Akkermansiaceae↑; BifidobacteriaceaeFBG↓; body weight↓; OGTT AUC↓; insulin↑; dyslipidemia↓
Pavlou et al. (2023) [10]Clinical (RCT)8 h TRE (12:00–20:00)Adults with T2DM and obesityN = 75plasma butyrate↑HbA1c↓ (0.9% combined vs.−0.6% IF alone; p = 0.07); GLP-1↓
Tay et al. (2020) [17]Clinical (RCT)5:2 IF (600–650 kcal/day for 2 days/week) + Probiotic (L. rhamnosus HN001)Adults with prediabetes N = 26(Microbiota composition analysis was not the primary focus of this pilot report)HbA1c↓ (−2 mmol/mol, p < 0.001) and BW↓ (−5% avg.) in both groups; No additive glycemic benefit from probiotic; Mental health and social functioning in probiotic group↑ (p = 0.007)
Li et al. (2023) [19]Systematic Review & Meta-analysisProbiotic supplementation (various strains/doses)Adults with T2DM30 RCTs; N = 1827Variable enrichment of beneficial taxaFBG↓ (SMD: −0.37, p < 0.001); HbA1c↓ (SMD: −0.44, p < 0.001); Insulin↓ (SMD: −0.36, p = 0.004); HOMA-IR(SMD: −0.47, p < 0.001)↓.
Ma et al. (2025) [20]Clinical (Network Meta)Probiotics (multi vs. single-strain)Adults with T2DM30 RCTs; N = 1861Multi-strain superior for beneficial shiftsThe LAC+BIF+STR combination shows the greatest overall superiority in the cluster analysis of FPG, HbA1c, insulin, and HOMA-IR.
Li et al. (2020) [23]Preclinical Daily fasting (12, 16, or 20 h) for 1 monthHealthy male C57BL/6J miceN = 60 (15/group)Akkermansia↓ (only in 16 h group); Alistipes ↓(only in 16 h group); Changes reversible after cessationCumulative food intake↓ (16 & 20 h groups); No significant weight change relative to control.
Özkul et al. (2019) [29]Clinical (Pilot)Islamic Fasting (Ramadan); ~17 h daily fasting for 29 daysHealthy subjectsN = 9Akkermansia muciniphila↓; Bacteroides fragilis group↓ Fasting blood glucose and total cholesterol significantly decreased, with significantly increased abundances of Akkermansia muciniphila and the Bacteroides fragilis group
Wu et al. (2025) [32]Clinical (Observational)Long-term fasting (10 days, water only or low calorie)Healthy male adultsN = 13Bacteroidetes↓; Firmicutes↓; Akkermansia↑; Faecalibacterium↓; Microbial diversity decreased initially then stabilizedBody weight↓; BM↓I; Blood glucose↓; Triglycerides; Cholesterol↓
Remely et al. (2015) [34]Clinical (Pilot)1-week fasting program (with laxatives) followed by 6-week probiotic interventionOverweight/Obese adultsN = 13Faecalibacterium prausnitzii↑; Akkermansia muciniphila↑;
Bifidobacteri↑; Lactobacilli
Body weight↓; BM↓; Significant correlation between microbial enrichment and weight reduction.
Hejazi et al. (2024) [63]Clinical (Meta, dose–response)Multi-strain probioticsAdults with T2DM32 RCTs, N = 1920 beneficial microbial metabolites↑ (e.g., SCFAs) and improved gut barrier integrityFBG↓; HbA1c↓; fasting insulin↓; HOMA-IR↓
Chaithanya et al. (2024) [72]Clinical (RCT)Multi-strain probioticAdults with T2DMN = 124No unified sequencing; strain composition product-specificHbA1c↓; HDL-c↑; LDL-c↓; BMI↓
Abbreviations: ↑ and ↓ indicate an increase/enrichment and a decrease, respectively, following the intervention.
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Zhang, Z.; Wang, S.; Sun, G.; Pan, D. Intermittent Fasting and Probiotics for Gut Microbiota Modulation in Type 2 Diabetes Mellitus: A Narrative Review. Nutrients 2026, 18, 119. https://doi.org/10.3390/nu18010119

AMA Style

Zhang Z, Wang S, Sun G, Pan D. Intermittent Fasting and Probiotics for Gut Microbiota Modulation in Type 2 Diabetes Mellitus: A Narrative Review. Nutrients. 2026; 18(1):119. https://doi.org/10.3390/nu18010119

Chicago/Turabian Style

Zhang, Zhiwen, Shaokang Wang, Guiju Sun, and Da Pan. 2026. "Intermittent Fasting and Probiotics for Gut Microbiota Modulation in Type 2 Diabetes Mellitus: A Narrative Review" Nutrients 18, no. 1: 119. https://doi.org/10.3390/nu18010119

APA Style

Zhang, Z., Wang, S., Sun, G., & Pan, D. (2026). Intermittent Fasting and Probiotics for Gut Microbiota Modulation in Type 2 Diabetes Mellitus: A Narrative Review. Nutrients, 18(1), 119. https://doi.org/10.3390/nu18010119

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