Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global epidemic that affects approximately 25% of the adult population and is strongly associated with metabolic disorders such as obesity, insulin resistance, and type 2 diabetes (Kuang et al., 2023). In recent years, the interaction mechanism between gut microbiota and host metabolism through the gut-liver axis has gradually become the focus of research. Dysbiosis of the gut microbiosis can affect hepatic metabolic homeostasis through a variety of pathways, including bile acid metabolism reprogramming, abnormal production of short-chain fatty acids, and endotoxin-mediated inflammatory responses (Abenavoli et al., 2021). For example, gut microbiota-modified bile acids have been found to be inversely correlated with liver fat content (Kuang et al., 2023), while a reduction in the microbiota-derived tryptophan metabolite indole-3-acetic acid may exacerbate liver lipid deposition (Aron-Wisnewsky et al., 2020b). Animal experiments have further confirmed that dietary fiber can significantly improve inflammation and fibrosis in nonalcoholic steatohepatitis (NASH) by modulating microbiota metabolites such as 3-succinylcholic acid (Wei et al., 2023).

Notably, disruption of intestinal barrier function leads to translocation of microbial-associated molecular patterns to the liver, activating the Toll-like receptor pathway and inducing insulin resistance and hepatocyte damage (Scorletti et al., 2020). Clinical studies have revealed characteristic changes in the gut microbiota of patients with MASLD, including changes in the abundance of Ruminococcaceae and Bifidobacterium, which correlate with disease severity and fibrosis progression (Aron-Wisnewsky et al., 2020a). However, there is still heterogeneity in existing studies, such as the effects of age, gender, and dietary patterns on microbiota-host interactions in different populations that have not been fully elucidated (Aron-Wisnewsky et al., 2020a).

In terms of intervention strategies, precision therapy targeting intestinal microbiota has shown broad prospects. Clinical randomized controlled trials have shown that synbiotics (probiotics combined with prebiotics) can regulate microbiota composition but fail to significantly reduce liver fat content (Ye et al., 2024), while resistant starch has shown unique advantages in improving hepatic steatosis by enriching butyrate-producing bacteria and reducing branched-chain amino acid levels (Ni et al., 2023). In addition, specific probiotic strains such as Bifidobacterium pseudolongum inhibit liver cancer-related signaling pathways by secreting acetate, providing a new idea for the prevention of MASLD-related liver cancer (Leung et al., 2022). However, the role of fungal and virome in MASLD remains to be further explored, for example, the association between Candida and systemic immune responses suggests that fungal-host interactions may influence disease progression (Zheng et al., 2025).

This review systematically reviews the key molecular mechanisms of the interaction between MASLD and intestinal microbiota, evaluates the clinical translation potential of existing intervention strategies, and explores the application prospects of microbiome-targeted therapy in personalized medicine, aiming to provide a theoretical basis for the development of new diagnosis and treatment protocols based on the regulation of the gut-liver axis.

There is a complex bidirectional regulatory network between the pathogenesis of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and the intestinal microbiota, which interact with liver metabolic homeostasis through intestinal barrier function, microbial metabolites, immune inflammatory pathways, and bile acid metabolism. We will systematically elucidate the core mechanism of intestinal microbiota regulating MASLD through the “gut-liver axis,” and discuss its molecular basis and clinical significance based on the latest research progress.

The interaction mechanism between Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and gut microbiota provides an important direction for the development of novel intervention strategies. Based on the central role of intestinal microbiota in the pathological process of MASLD (such as bile acid metabolism disorder, endotoxemia, short-chain fatty acid imbalance, etc.), the current intervention methods for intestinal microbiota mainly include microbial targeted therapy, dietary modification, metabolic surgery, and drug target development. The mechanisms, clinical evidence, and limitations of these strategies are systematically described below (Table 1).

The current intervention strategies face challenges such as individualized treatment needs, optimization of combination therapies, and long-term safety assessment. Precise typing based on microbiota characteristics (e.g., intestinal type classification) may improve efficacy (Spencer et al., 2011), while the synergistic effect of probiotics in combination with FXR agonists or dietary interventions needs to be further validated (Lambert et al., 2015). In addition, the risk of resistance and the immune impact of antibiotics or FMT need to be critically evaluated (Aron-Wisnewsky et al., 2020b). In the future, it is necessary to analyze the microbiota-host interaction network by combining multi-omics technology, and verify the feasibility of personalized protocols through large-scale clinical trials.

Significant progress has been made in the study of the interaction mechanism between metabolism-related fatty liver disease (MASLD) and intestinal microbiota, but it still needs to be explored in many aspects in the future.

Refinement of mechanism research: At present, the molecular mechanism of intestinal microbiota affecting liver lipid metabolism and inflammation through bile acid metabolism, short-chain fatty acids, endogenous ethanol and other pathways still needs to be further analyzed. For example, the mechanism by which microbiota-modified bile acids improve lipid deposition by activating hepatocyte CYP7B1 and PPARα signaling pathways (Kuang et al., 2023), and pathway in which specific microbiota (e.g., Odoribacteraceae) regulates the hepatic immune microenvironment through metabolites, need to be validated in more clinical cohorts (Miyamoto et al., 2024). In addition, the mechanism of how metabolites in the microbiota-gut-liver axis, such as acetic acid, promote hepatic lipid synthesis through ACSS2 still needs to be further explored (Zhao et al., 2020).

Development of individualized intervention strategies: Individual differences in gut microbiota significantly affect the disease phenotype and treatment response of MASLD. For example, changes in the abundance of Gammaproteobacteria and Erysipelotrichi in the gut of different individuals under a choline-deficient diet are directly related to the degree of hepatic fat accumulation (Spencer et al., 2011), suggesting that individualized diets or probiotic/prebiotic regimens based on microbiota characteristics will be needed in the future. Integrated analysis of multi-omics technologies (e.g., metagenomics, metabolomics) will facilitate precise typing and targeted interventions (Aron-Wisnewsky et al., 2020b).

Application of new microbial control technologies: The clinical efficacy of existing intervention methods (such as probiotics and synbiotic preparations) is controversial (Scorletti et al., 2020), and more efficient microbiota editing tools need to be explored in the future. For example, phage-targeted clearance of pro-inflammatory flora [e.g., Lactobacillaceae is associated with endogenous ethanol production (Meijnikman et al., 2022)] or delivery of specific metabolites by engineered bacteria may be new directions. In addition, the potential of fecal microbiota transplantation (FMT) in MASLD needs to be validated urgently (Mehal, 2013).

Integrative studies of cross-organ interaction networks: The association of MASLD with chronic kidney disease (CKD) suggests that microbiota metabolites may affect multi-organ function through systemic inflammation or oxidative stress (Byrne and Targher, 2020). In the future, it is necessary to combine single-cell sequencing and spatial transcriptome technology to elucidate how the microbiota regulates systemic metabolic disorders through the gut-liver-kidney axis (Musso et al., 2016).

The limitations of this review article are mainly reflected in the following aspects: first, the existing research on the interaction between MASLD and gut microbiota has significant technical problems and design biases, for example, when analyzing the diversity of gut microbiota, the reliability of the conclusions may be affected due to the limitations of technical methods (such as sequencing depth or sample processing bias), which limit our understanding of the precise role of gut microbiota in MASLD pathology (Gil-Gómez et al., 2021); Second, the important evidence supporting the role of gut microbiota in the development of MASLD mainly comes from animal experimental studies, while data based on human clinical studies are relatively scarce, and this dependence leads to uncertainties in translational applications, such as insufficient effectiveness in validating mechanisms such as bile acid metabolism or TLR4/NF-κB inflammatory pathways in human patients (Bakhshimoghaddam and Alizadeh, 2021); In addition, although intervention strategies (such as probiotics, prebiotics, or fecal microbiota transplantation) have shown potential efficacy, the existing literature shows that their clinical application still needs to optimize key parameters such as bacterial strain selection, treatment time, and dose determination, and the current lack of standardized protocols limits the replicability of large-scale clinical practice (Bakhshimoghaddam and Alizadeh, 2021). In terms of quantitatively assessing the association between gut microbiota and MASLD, there is a lack of systematic bibliometric analysis or multi-omics integration methods, which may ignore hot trends and knowledge gaps, and hinder the development of future precision interventions (Li et al., 2022). Finally, geographic factors (e.g., diet or lifestyle) and virome/fungal influences are not discussed in depth, and these limitations reflect the shortcomings of current research and highlight the need to strengthen human clinical trials, improve technical frameworks, and promote interdisciplinary integration.

The interaction mechanism between metabolism-related fatty liver disease and intestinal microbiota is complex and multi-layered, involving the direct regulation of hepatocyte lipid metabolism, immune cell function and intestinal barrier integrity by microbial biota metabolites. Available evidence suggests that imbalances in bile acid metabolism, endogenous ethanol production (Meijnikman et al., 2022), and abnormal short-chain fatty acid signaling (Zhao et al., 2020) are central components of microbiota-driven MASLD progression. In terms of intervention strategies, probiotics/prebiotics can regulate the structure of microbiota and improve hepatic steatosis (Marchesi et al., 2016), but the long-term efficacy is affected by individual microbiota heterogeneity and intervention timing (Scorletti et al., 2020); Targeting specific metabolic pathways, such as FXR agonists or PPARα activators (Kuang et al., 2023), may be more specific.

However, there are still limitations in current research: most of the mechanistic evidence comes from animal models, and clinical translation needs to overcome species differences; Randomized controlled trials of microbiota interventions were small and endpoints were inconsistent (Lambert et al., 2015); The interaction between microbiota and host genetics and diet has not been fully elucidated (Spencer et al., 2011). In the future, it is necessary to build a microbiota-host interaction network through multi-omics integration, organoid models, and artificial intelligence prediction, and promote the clinical practice of personalized intervention programs. Finally, an integrated management strategy targeting gut microbiota is expected to open up a new path for the prevention and treatment of MASLD (Aron-Wisnewsky et al., 2020b).