GUT MICROBIOTA AS A THERAPEUTIC TARGET IN OBESITY AND TYPE 2 DIABETES MELLITUS

GUT MICROBIOTA AS A THERAPEUTIC TARGET IN OBESITY AND TYPE 2 DIABETES MELLITUS

Yash Prashar * and Preet Mohinder Singh

Department of Pharmacology, Chandigarh College of Pharmacy, Landran, Punjab, India.

ABSTRACT: Obesity and type 2 diabetes mellitus (T2DM) are increasing worldwide, and gut microbial features are repeatedly associated with adiposity, insulin resistance and low-grade inflammation. This structured narrative review evaluates whether those associations support therapeutic use. PubMed/MEDLINE, Google Scholar, Clinical Trials.gov and authoritative regulatory or guideline sources were searched for English-language literature published from January 2004 to 17 July 2026. Evidence was classified as experimental, observational, randomized clinical trial or systematic review/meta-analysis. Animal studies support mechanisms involving intestinal permeability, short-chain fatty acids, bile-acid signalling and host-microbial co-metabolism, but these findings cannot be assumed to produce clinical benefit. In humans, dietary fibre and selected prebiotic, probiotic or synbiotic products may produce small, heterogeneous improvements in glycaemia or adiposity. Preparation-specific trials of Akkermansia muciniphila are promising, particularly for pasteurized products, but live, pasteurized and protein-based preparations are not interchangeable and none is an approved treatment for obesity or T2DM. Fecal microbiota transplantation remains experimental for metabolic disease because engraftment is variable, metabolic outcomes are inconsistent and infection-transmission risk requires rigorous donor screening. Microbiota changes after bariatric surgery, metformin, acarbose or berberine may contribute to response but do not replace their established direct mechanisms. Microbiota-directed strategies should therefore be regarded as adjunctive or investigational, with future trials requiring strain or product identification, dose standardization, adequate power, longer follow-up and clinically meaningful endpoints.

Keywords: Gut microbiota, Obesity, Type 2 diabetes mellitus, Short-chain fatty acids, Akkermansia muciniphila, Clinical trials

INTRODUCTION: Obesity and T2DM now impose a major clinical and economic burden. In 2022, approximately 2.5 billion adults were overweight and 890 million were living with obesity; about 43% of adults were overweight and 16% had obesity ¹.

The International Diabetes Federation estimated that 589 million adults aged 20-79 years were living with diabetes in 2024 (11.1% of this age group), with a projected increase to 853 million by 2050; diabetes was associated with about 3.4 million deaths and more than US$1 trillion in health expenditure in 2024 ².

These conditions frequently coexist and increase cardiovascular, renal, hepatic and other complications, creating a need for effective prevention and treatment without overstating unproven alternatives. The human gut microbiota comprises bacteria, archaea, viruses and fungi whose collective gene content and metabolic functions interact with diet, medications and host physiology. Current estimates place bacterial and human cell numbers in the same order of magnitude, while metagenomic catalogues reveal a microbial gene repertoire much larger than the human genome ^{3, 4}. The Human Microbiome Project and later studies established roles in nutrient transformation, vitamin production, xenobiotic metabolism, colonization resistance and mucosal immune development ^{5, 6}.

Early mouse studies reported increased microbial energy-harvesting capacity with obesity, and small human studies popularized the Firmicutes-to-Bacteroidetes ratio ^{7, 8}. This ratio is not a consistent diagnostic marker across populations. Transferring microbiota from obesity-discordant twins to germ-free mice transmitted aspects of the donor phenotype, supporting biological plausibility under controlled experimental conditions ⁹. In humans, lower microbial gene richness has been associated with adiposity and inflammation, and metagenome-wide association studies have identified altered microbial functions in T2DM ^{10, 11, 12}. These human findings are primarily associative: diet, geography, medication, disease duration and bowel transit can influence both the microbiome and metabolic phenotype ¹³.

A central interpretive problem is therefore the gap between association, experimental causation and clinical utility. Animal models can isolate mechanisms but do not reproduce the heterogeneity, drug exposure or long-term outcomes of human obesity and T2DM. Observational studies may identify biomarkers but cannot establish that changing a taxon will change disease. Randomized trials provide more direct evidence, yet many microbiota interventions are small, short and based on surrogate endpoints. This review addresses that gap by integrating evidence according to study design; distinguishing live, pasteurized and protein-based microbial preparations; comparing major human trials by strain or product, dose and duration; and separating microbiota-mediated hypotheses from established drug or surgical mechanisms. Recent 2025-2026 clinical and regulatory evidence is incorporated to clarify what is ready for adjunctive use and what remains investigational.

MATERIALS AND METHODS:

Literature-Search Strategy: A structured narrative search was conducted in PubMed/MEDLINE, Google Scholar and ClinicalTrials.gov. WHO and International Diabetes Federation sources were used for disease-burden estimates; FDA, European Food Safety Authority and European Commission sources were used for safety and regulatory statements; and current clinical guidelines were used for the clinical perspective. The search period was 01 January 2004 to 17 July 2026, and the final search was performed on 17 July 2026. Seminal pre-2004 reports were not required for the questions addressed.

The core search string was: ("gut microbiota" or "gut microbiome" or "gastrointestinal microbiome") and (obesity or "type 2 diabetes" or "insulin resistance" or "metabolic syndrome") and (probiotic* or prebiotic* or synbiotic* or "dietary fibre" or "dietary fiber" or "short-chain fatty acid*" or "bile acid*" or "Akkermansia muciniphila" or "fecal microbiota transplantation" or "faecal microbiota transplantation" or metformin or acarbose or berberine or "bariatric surgery" or pharmacomicrobiomics or postbiotic* or "live biotherapeutic product*"). Focused combinations of the disease terms with each intervention or mechanism were also used. Searches were limited to English-language records.

The inclusion criteria were human randomized trials, prospective or cross-sectional studies, systematic reviews or meta-analyses, and authoritative guidelines or regulatory documents relevant to obesity, T2DM, insulin resistance or metabolic syndrome. Animal and in-vitro studies were retained only when they provided mechanistic information that could not be inferred from human trials. The exclusion criteria were duplicate records, non-English reports, conference abstracts without sufficient methods or results, articles unrelated to metabolic outcomes, unverified secondary claims and animal-only studies without clear mechanistic relevance.

The broad PubMed query returned approximately 8,364 records before focused refinement. Titles and abstracts were screened for relevance, followed by full-text or complete abstract assessment of potentially eligible sources and backward citation checking of major trials and reviews. Because this was a structured narrative review rather than a systematic review or meta-analysis, a PRISMA flow and quantitative risk-of-bias synthesis were not undertaken. Seventy-five sources were retained in the final narrative, including experimental, observational, randomized, meta-analytic, guideline and regulatory evidence. The evidence type and principal limitations were recorded during synthesis. Ethical approval and consent were not required because no new human or animal data were collected.

RESULTS AND DISCUSSION;

Evidence Framework: From Mechanism to Therapeutic Outcome: Evidence is described in four categories. Experimental evidence includes in-vitro systems, germ-free or antibiotic-treated animals and microbial-transfer studies; it can support causality within a model but not clinical efficacy. Observational human evidence identifies associations and potential responders but remains vulnerable to confounding and reverse causation. Randomized clinical trials evaluate an intervention-product combination in a defined population; their results should not be generalized to different strains, doses or preparations. Systematic reviews and meta-analyses increase precision but inherit heterogeneity and product-mixing from the included trials. Accordingly, mechanistic plausibility is not presented here as proof of weight loss, HbA1c reduction or prevention of complications.

Barrier Dysfunction, Inflammation and Insulin Resistance: In mice, high-fat feeding and chronic low-dose lipopolysaccharide (LPS) exposure can increase intestinal permeability, inflammatory signalling, adiposity and insulin resistance ^{14, 15}. These experiments support a model in which microbial products activate Toll-like receptor and nuclear factor-kappa B pathways, with cytokine release and adipose-tissue immune-cell recruitment ¹⁶. However, LPS assays and permeability markers vary substantially in humans. Cross-sectional elevations cannot show whether barrier dysfunction caused metabolic disease or resulted from diet, adiposity or medication. The clinically relevant inference is therefore limited: weight loss and dietary quality may improve barrier-related biology, but no LPS-targeted microbiota product has established efficacy for obesity or T2DM.

Akkermansia muciniphila: Preparation-specific Evidence: Akkermansia muciniphila is a mucin-associated bacterium linked with mucus-layer and epithelial signalling. In diet-induced obese mice, live A. muciniphila improved barrier-related and metabolic measures ¹⁷. Pasteurization and the purified outer-membrane protein Amuc_1100 also improved several metabolic endpoints in mice, demonstrating that live colonization is not required in that model ¹⁸. Protein-based findings are preclinical and should not be represented as evidence for a marketed protein therapy.

The first randomized proof-of-concept human study enrolled 40 insulin-resistant adults with overweight or obesity; 32 completed three months of daily placebo, live A. muciniphila or pasteurized A. muciniphila at 1 × 10^10 cells. Pasteurized bacteria improved insulin sensitivity and selected anthropometric or biochemical outcomes compared with placebo, whereas the live preparation did not reproduce every endpoint. The study was exploratory, small and not designed for clinical events ¹⁹. A 2026 trial randomized 90 adults with overweight or obesity who first lost at least 8% of body weight during an eight-week low-energy diet and then received daily pasteurized A. muciniphila MucT or placebo for 24 weeks. Mean weight regain was lower with the pasteurized preparation (1.2 ± 0.7 versus 3.2 ± 0.4 kg), with no treatment-related serious adverse event; short follow-up, commercial involvement and the selected post-weight-loss population limit generalization ²⁰.

For live strain AKK-WST01, a 2025 randomized 12-week study in 58 drug-naive adults with overweight or obesity and T2DM reported no significant overall between-group metabolic benefit. Exploratory analyses suggested colonization and metabolic improvement among participants with low baseline abundance, but this subgroup result requires prospective confirmation ²¹. Thus, live and pasteurized products cannot be treated as equivalent, and response may depend on baseline ecology. EFSA concluded that a specified pasteurized preparation was safe under defined novel-food conditions, and the European Union authorized pasteurized A. muciniphila as a novel food ^{22, 23}. Novel-food authorization is not medicinal approval; no live, pasteurized or protein-based A. muciniphila product is approved as a treatment for obesity or T2DM.

Energy Harvest, Diet and Microbial Adaptability: Germ-free mouse work established that microbial colonization can regulate host fat storage, and microbial-transfer experiments demonstrate that donor communities can modify phenotype in controlled recipients ^{24, 9}. In humans, diet can alter microbiota composition within days, while longer dietary interventions may improve microbial gene richness together with metabolic markers ^{25, 26}. The direction of causality remains complex: reduced energy intake and weight loss can change both metabolism and microbiota, and the microbiota change may be a mediator, a marker or both. This supports dietary intervention as standard care with potential microbiome effects, not the use of stool composition as an independent treatment target.

Short-chain Fatty Acids: Beneficial Pathways and Context-Dependent Effects: Acetate, propionate and butyrate are produced during microbial fermentation, but they differ in tissue handling and signalling. Butyrate is an important colonocyte fuel and can support epithelial integrity; acetate enters peripheral metabolism; and propionate is substantially utilized by the liver. SCFAs also influence histone deacetylases and receptors such as FFAR2 and FFAR3 ^{27, 28}. In cellular and animal systems, SCFAs can stimulate GLP-1 and peptide YY and modulate immune function ²⁹. These mechanisms provide a rationale for fibre-rich diets but do not imply that a higher concentration of every SCFA is always beneficial. Context matters. In a mouse model, acetate participated in a microbiome-brain-beta-cell pathway that promoted hyperphagia and metabolic syndrome ³⁰. Propionate administration increased glucagon and fatty acid-binding protein 4 and impaired insulin action in experimental systems, with short-term findings also explored in humans ³¹. Conversely, controlled delivery of propionate to the colon has reduced weight gain in a separate human trial. Differences in route, dose, compartment, background diet, host phenotype and duration can explain apparently conflicting effects. Fecal SCFA concentrations also reflect production minus absorption and transit, so a high fecal value is not necessarily evidence of high systemic benefit. SCFA-based claims should therefore specify the molecule, delivery site, exposure and population ³². Other metabolites, including branched-chain amino acids and indole or trimethylamine-related compounds, further complicate a single-metabolite interpretation ³³.

Bile-acid Signalling through FXR and TGR5: Gut microbes modify the bile-acid pool by deconjugation and conversion of primary to secondary bile acids. These molecules signal through farnesoid X receptor (FXR) and Takeda G-protein-coupled receptor 5 (TGR5), affecting hepatic glucose and lipid pathways, intestinal hormones and energy expenditure ³⁴. Much mechanistic evidence derives from mice; for example, microbiota-dependent reduction of tauro-beta-muricholic acid alters intestinal FXR signalling, but this bile acid is prominent in mice and the result cannot be directly transferred to humans ³⁵. TGR5 activation can increase energy expenditure or GLP-1 in experimental models, while FXR effects vary by tissue, bile-acid species and disease stage ^{36, 37}. The appropriate clinical conclusion is that bile-acid signalling may mediate part of the response to diet, surgery or drugs, not that universal FXR activation, inhibition or TGR5 stimulation will improve every patient.

TABLE 1: MAJOR MECHANISMS LINKING GUT MICROBIOTA WITH OBESITY AND T2DM, EVIDENCE LEVEL AND THERAPEUTIC INTERPRETATION

FXR, farnesoid X receptor; LPS, lipopolysaccharide; SCFA, short-chain fatty acid; T2DM, type 2 diabetes mellitus; TGR5, Takeda G-protein-coupled receptor 5.

Prebiotics, Dietary Fibre and Food-Pattern Interventions: Prebiotics are substrates selectively utilized by host microorganisms that confer a health benefit, whereas not every dietary fibre fulfils this definition ³⁸. Inulin-type fructans, galacto-oligosaccharides and resistant starch differ in fermentability, dose-response and tolerability. Fibre can support microbial functions and SCFA production, but effects depend on the food matrix, background diet, bowel transit and baseline microbiota ^{39, 40}. Whole grains, pulses, vegetables, fruits, nuts and seeds also provide nutrients and can improve cardiometabolic health through mechanisms that do not require microbial mediation.

Human trials illustrate this variability. In an exploratory study of women with obesity, inulin-type fructans modified Bifidobacterium and selected metabolic measures, but the study was small and outcome-specific ⁴¹. In 60 adults with overweight, 10 g/day inulin-propionate ester for 24 weeks reduced weight gain and abdominal adiposity compared with inulin control, but this engineered delivery system should not be generalized to all fibre products ⁴². Across randomized trials, prebiotic effects on glucose and lipid outcomes are generally modest and heterogeneous ⁴³. A gradual increase in food-based fibre is usually practical; bloating, pain, diarrhoea or constipation can limit adherence, and patients with complex gastrointestinal disease may need individualized advice.

Probiotics, Synbiotics and Postbiotics: A probiotic is a live microorganism that confers a health benefit when administered in an adequate amount. The effect is tied to the identified strain or defined strain combination, dose, delivery matrix and endpoint; it cannot be assigned to an entire genus or species ⁴⁴. Product labels should state genus, species and strain, viable count through the end of shelf life, storage conditions, serving size and safety information. Expert criteria also require strain-level characterization, evidence of safety and at least one positive human trial for the claimed benefit ⁴⁵. Synbiotics combine live microorganisms and a selectively utilized substrate, with either complementary or synergistic logic ⁴⁶. Postbiotics are preparations of inanimate microorganisms and/or their components that confer a health benefit; purified microbial proteins alone are not automatically postbiotics ⁴⁷.

Meta-analyses suggest statistically significant but clinically limited average effects in T2DM. Earlier analyses found small changes in glucose, adiposity and lipid markers with substantial differences among products ^{48, 49}. A 2026 meta-analysis of 48 randomized trials reported mean reductions of approximately 7 mg/dL in fasting glucose, 0.34 percentage point in HbA1c and 0.91 in HOMA-IR, but heterogeneity, varying strain combinations and short durations weaken product-level conclusions ⁵⁰. These average effects are smaller than those expected from established glucose- or weight-lowering therapies and should not justify replacing indicated medication.

Specific trials should be interpreted only for the tested formulation. A six-month multi-strain product in T2DM improved selected insulin-resistance and inflammatory measures, but the combination does not validate other mixtures ⁵¹. A six-week trial of 300 g/day yogurt containing Lactobacillus acidophilus La-5 and Bifidobacterium animalis subsp. lactis Bb-12 (at least 10^6 colony-forming units/g of each) in 60 adults with T2DM reported improved fasting glucose and antioxidant markers; its duration and surrogate endpoints limit conclusions ⁵². Product quality is a clinical issue: loss of viability from heat or poor storage, contamination, inaccurate counts and substitution of strains can invalidate efficacy evidence. Common adverse effects are gas and altered stool pattern. Rare bloodstream infection is a concern in severely immunocompromised, critically ill or central-line patients, so selection and monitoring matter.

Fecal Microbiota Transplantation:

Experimental for Metabolic Disease: FMT transfers a complex donor community and associated metabolites. In 18 men with metabolic syndrome, a single lean-donor intestinal infusion improved insulin sensitivity at six weeks compared with autologous transfer ⁵³. A later study found that improvement at six weeks was not durable at 18 weeks and depended partly on baseline recipient microbiota ⁵⁴. In the FMT-TRIM pilot trial, 24 adults with obesity received weekly oral lean-donor or placebo capsules for six weeks; engraftment occurred, but body weight and major metabolic outcomes did not significantly improve ⁵⁵. Another capsule trial demonstrated microbial changes without convincing weight loss ⁵⁶. In a 70-participant phase 2 trial, a single oral FMT combined with daily low-fermentable fibre improved HOMA2-IR at six weeks, whereas FMT alone did not establish a consistent metabolic effect ⁵⁷. These small trials show biological activity but inconsistent efficacy and uncertain durability.

Current clinical guidance supports fecal microbiota-based therapies for selected recurrent Clostridioides difficile infection scenarios, not for obesity or T2DM ⁵⁸. FDA-approved fecal microbiota products are indicated to prevent recurrent C. difficile infection after antibacterial treatment; their approval does not extend to metabolic disease ⁵⁹. Investigational FMT requires robust donor history and laboratory screening for enteric pathogens, multidrug-resistant organisms and relevant viruses; standardized collection and processing; traceability; informed consent; and adverse-event follow-up. Serious infection transmission, including fatal events involving resistant organisms, has been reported ⁶⁰. Long-term transfer of unrecognized phenotypes and unpredictable engraftment remain concerns. FMT for obesity or T2DM should therefore occur only in an appropriately approved clinical trial, not routine practice.

Bariatric Surgery and the Microbiome: Bariatric or metabolic surgery can produce substantial and durable weight loss and improve T2DM through reduced intake, altered anatomy, nutrient sensing, bile-acid and incretin changes and weight-dependent and weight-independent mechanisms. Human studies show substantial microbiome change after surgery, but microbial composition can remain abnormal and is influenced by diet, anatomy and medication ⁶¹.

Transfer of microbiota from gastric-bypass-treated mice reduced adiposity in recipient mice, supporting a contributory mechanism in that model ⁶². Long-term human cohort data associate postsurgical microbiome changes with fat-mass regulation but do not prove independent mediation ⁶³. Clinical eligibility should follow obesity and diabetes guidelines, not a stool profile ⁶⁴. It is not currently possible to reproduce the established benefits of surgery by a probiotic or FMT.

Metformin, Acarbose and Berberine: Direct Actions versus Microbial Mediation: Metformin lowers glucose through established hepatic and intestinal actions and can also alter the gut environment. In treatment-naive T2DM, randomized and mechanistic human work showed microbiome changes and supported a partial contribution to therapeutic effects ⁶⁵. Cross-sectional studies must account for metformin because its microbial signature can be mistaken for a disease signature ⁶⁶. Associations with increased A. muciniphila or SCFA-producing taxa and changes in bile acids or incretin-related pathways are plausible mediators, not proof that the microbiome is the primary mechanism ^{67, 68}. Gastrointestinal adverse effects may also involve gut exposure and microbial interactions.

Acarbose directly and reversibly inhibits intestinal alpha-glucosidases and delays carbohydrate absorption. More carbohydrate therefore reaches the colon, secondarily changing fermentation, microbial composition and bile-acid profiles.

Human stratification data suggest that baseline microbiota may modify response, but glycaemic benefit should not be attributed solely to microbial change ⁶⁹. Berberine has direct molecular and intestinal effects as well as microbiota-related hypotheses. Rat studies show microbial remodeling during prevention of diet-induced obesity and insulin resistance but cannot establish human efficacy ⁷⁰. In the 409-participant PREMOTE trial, berberine alone or with probiotics lowered HbA1c more than placebo or probiotics alone over 12 weeks; the design, antibiotic run-in and gastrointestinal adverse effects limit attribution of benefit to microbiota mediation ⁷¹.

Pharmacomicrobiomic biomarkers are promising for predicting response, but none of these drugs should be selected or withheld on the basis of a commercial stool test.

TABLE 2: MICROBIOTA-TARGETED INTERVENTIONS: PRODUCT SPECIFICITY, POTENTIAL BENEFIT, LIMITATIONS AND SAFETY

FMT, fecal microbiota transplantation; HbA1c, glycated haemoglobin; HOMA-IR, homeostatic model assessment of insulin resistance; RCT, randomized controlled trial; T2DM, type 2 diabetes mellitus.

Biomarkers and Analytical Limitations: Candidate features include gene richness, butyrate-producing taxa, A. muciniphila abundance, microbial pathways, bile-acid profiles and circulating or fecal metabolites.

None has a validated universal clinical cutoff for diagnosing obesity, T2DM or treatment response. Technical variation arises from stool collection, storage, DNA extraction, sequencing platform, bioinformatic pipeline and compositional statistics. Biological variation arises from diet, geography, age, bowel transit, antibiotics and other medication. Repeated association does not make an individual taxon a causal biomarker.

Commercial microbiome reports should therefore not be used to prescribe probiotics, stop medication or determine eligibility for surgery or FMT. Multi-omic markers may be valuable in prospectively validated trials ^{72, 73}.

TABLE 3: CANDIDATE MICROBIOTA-RELATED BIOMARKERS AND THEIR PRESENT CLINICAL STATUS

FXR, farnesoid X receptor; LPS, lipopolysaccharide; SCFA, short-chain fatty acid; T2DM, type 2 diabetes mellitus; TGR5, Takeda G-protein-coupled receptor 5.

TABLE 4: COMPARATIVE SUMMARY OF MAJOR HUMAN CLINICAL STUDIES OF MICROBIOTA-DIRECTED METABOLIC INTERVENTIONS

CFU, colony-forming units; FMT, fecal microbiota transplantation; GI, gastrointestinal; HbA1c, glycated haemoglobin; HOMA2-IR, updated homeostatic model assessment of insulin resistance; T2DM, type 2 diabetes mellitus. Where a complete cell dose was not available in the accessible report, the wording is deliberately limited to the published regimen.

Cautious Clinical Perspective: Current evidence does not support a prescriptive microbiome-treatment algorithm. Clinical management should follow established guidelines: nutritionally adequate dietary intervention, physical activity, sleep and behavioural support; evidence-based glucose- and weight-lowering medicines selected for glycaemic, cardiovascular, kidney and weight goals; and metabolic surgery for eligible patients ^{64, 74}. A diverse, fibre-rich dietary pattern may be recommended for its overall health value and can influence microbial function. A named probiotic or synbiotic may be considered only as an adjunct when its exact formulation has relevant human evidence, quality documentation and acceptable safety. Expected benefits should be described as small and uncertain. Clinicians should review gastrointestinal disease, immune status, central venous access, recent antibiotics and concurrent medicines before recommending a live microbial supplement. Product identity, viable count at end of shelf life, storage, batch quality, adverse effects and stop criteria should be documented. Weight, waist circumference, HbA1c, glucose, lipids, medication use and patient-reported tolerability are more clinically meaningful than a change in relative abundance. FMT, engineered organisms and unapproved live biotherapeutic products should remain within regulated research. No routine stool sequencing panel currently determines which diet, probiotic, drug or surgical procedure a patient should receive.

Safety, Regulation and Implementation Limits: The safety profile depends on the intervention. Food-based fibre commonly causes dose-related bloating and stool changes. Live probiotics require accurate identification and manufacturing controls; sporadic invasive infections are most relevant in vulnerable hosts. Postbiotics and pasteurized preparations avoid replication but still require product-specific toxicology and efficacy data. Novel-food authorization addresses defined conditions of food use and does not establish treatment efficacy. FMT carries the broadest biological exposure and requires donor screening, traceability and infection surveillance ^{45, 22, 60}. Antibiotic exposure, proton-pump inhibitors, metformin and other drugs can alter microbiota and confound both research and clinical interpretation. Probiotics do not necessarily restore an individual's pre-antibiotic community and, in one controlled study, delayed mucosal reconstitution compared with spontaneous recovery ⁷⁵.

Long-term ecological effects, horizontal gene transfer, antimicrobial resistance and durability require monitoring for next-generation products. Regulatory terminology should be precise: food or supplement, novel food, live biotherapeutic product, biologic and approved medicine are not interchangeable categories.

Emerging and Investigational Directions: Artificial-intelligence models that integrate diet, metagenomics, metabolomics and clinical data may help generate response predictions, but they require external validation, transparent performance reporting and protection against demographic or geographic bias. Engineered microbes, defined consortia and metabolite-delivery systems may improve product control, yet containment, gene stability and long-term safety remain unresolved. Postbiotics may offer greater storage stability than live products, although benefits must be demonstrated for each preparation. Personalized microbiota therapy based on baseline abundance, functional genes or metabolite profiles is biologically plausible and supported by exploratory responder analyses, but it remains investigational. Future trials should preregister strain or product identity, genome-level characterization, dose, viability or inactivation method, storage, diet and medication control, colonization or exposure, adverse events and clinically meaningful outcomes. Longer studies should compare any microbiota adjunct with contemporary standard care and determine whether effects persist after treatment.

CONCLUSION: Gut microbial functions are biologically connected with intestinal barrier integrity, inflammation, SCFAs, bile acids, appetite signals and drug exposure. The strongest human evidence supports a cautious conclusion: food-based fibre and certain defined prebiotic, probiotic or synbiotic products can be useful adjuncts, but average improvements in weight or glycaemia are generally small and heterogeneous. Preparation-specific trials of pasteurized A. muciniphila are encouraging, whereas live-strain results are not uniformly positive and protein-based evidence remains preclinical. FMT produces engraftment but has inconsistent and often transient metabolic effects, carries infection-transmission risk and is experimental for obesity and T2DM. Microbiota changes after metabolic surgery, metformin, acarbose and berberine may contribute to response but do not independently explain their established clinical effects. Standard lifestyle, pharmacological and surgical care should remain primary. Progress will require adequately powered, longer randomized trials with defined strain or product, dose, manufacturing quality, safety surveillance, hard metabolic endpoints and prospective validation of responder biomarkers.

ACKNOWLEDGEMENT: The authors are thankful to the management and the Director/Principal of Chandigarh College of Pharmacy, Landran, and Doaba College of Pharmacy, Kharar, for academic support.

Author Contributions: Y Prashar: Conceptualization, methodology, literature search, data curation, writing-original draft, writing-review and editing, and supervision. PM Singh: Literature search, data curation, validation, and editing.

Declaration of AI Use: No Generative AI or AI-assisted technologies were used in the preparation of this manuscript.

Funding: No external funding was received for this review article.

CONFLICT OF INTEREST: The authors declare no conflict of interest.

REFERENCES:

1. World Health Organization: Obesity and overweight. WHO, Geneva, updated 08 December 2025. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed 17 July 2026).
2. Genitsaridi I, Salpea P, Salim A, Sajjadi SF, Tomic D and James S: IDF Diabetes Atlas 2025: global estimates of diabetes prevalence in adults for 2024 and projections for 2050. The Lancet Diabetes & Endocrinology 2026; 14(2): 149-156. doi: 10.1016/S2213-8587(25)00299-2.
3. Sender R, Fuchs S and Milo R: Revised estimates for the number of human and bacteria cells in the body. PLoS Biology 2016; 14(8): e1002533. doi: 10.1371/journal.pbio.1002533.
4. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS and Manichanh C: A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010; 464(7285): 59-65. doi: 10.1038/nature08821.
5. The Human Microbiome Project Consortium: Structure, function and diversity of the healthy human microbiome. Nature 2012; 486(7402): 207-214. doi: 10.1038/nature11234.
6. Thursby E and Juge N: Introduction to the human gut microbiota. Biochemical Journal 2017; 474(11): 1823-1836. doi: 10.1042/BCJ20160510.
7. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER and Gordon JI: An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006; 444(7122): 1027-1031. doi: 10.1038/nature05414.
8. Ley RE, Turnbaugh PJ, Klein S and Gordon JI: Microbial ecology: human gut microbes associated with obesity. Nature 2006; 444(7122): 1022-1023. doi: 10.1038/4441022a.
9. Ridaura VK, Faith JJ, Rey FE, Cheng J, Duncan AE and Kau AL: Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 2013; 341(6150): 1241214. doi: 10.1126/science.1241214.
10. Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F and Falony G: Richness of human gut microbiome correlates with metabolic markers. Nature 2013; 500(7464): 541-546. doi: 10.1038/nature12506.
11. Qin J, Li Y, Cai Z, Li S, Zhu J and Zhang F: A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 2012; 490(7418): 55-60. doi: 10.1038/nature11450.
12. Karlsson FH, Tremaroli V, Nookaew I, Bergstrom G, Behre CJ and Fagerberg B: Gut metagenome in European women with normal, impaired and diabetic glucose control. Nature 2013; 498(7452): 99-103. doi: 10.1038/nature12198.
13. Gurung M, Li Z, You H, Rodrigues R, Jump DB, Morgun A and Shulzhenko N: Role of gut microbiota in type 2 diabetes pathophysiology. E Bio Medicine 2020; 51: 102590. doi: 10.1016/j.ebiom.2019.11.051.
14. Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C and Bastelica D: Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 2007; 56(7): 1761-1772. doi: 10.2337/db06-1491.
15. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM and Delzenne NM: Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 2008; 57(6): 1470-1481. doi: 10.2337/db07-1403.
16. Tilg H and Moschen AR: Microbiota and diabetes: an evolving relationship. Gut 2014; 63(9): 1513-1521. doi: 10.1136/gutjnl-2014-306928.
17. Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C and Bindels LB: Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proceedings of the National Academy of Sciences of the United States of America 2013; 110(22): 9066-9071. doi: 10.1073/pnas.1219451110.
18. Plovier H, Everard A, Druart C, Depommier C, Van Hul M and Geurts L: A purified membrane protein from Akkermansia muciniphila or pasteurized bacterium improves metabolism in obese and diabetic mice. Nature Medicine 2017; 23(1): 107-113. doi: 10.1038/nm.4236.
19. Depommier C, Everard A, Druart C, Plovier H, Van Hul M and Vieira-Silva S: Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study. Nature Medicine 2019; 25(7): 1096-1103. doi: 10.1038/s41591-019-0495-2.
20. Mount S, Canfora EE, Jocken JW, Umanets A, Hul G and Coenjaerds M: Pasteurized Akkermansia muciniphila MucT for weight loss maintenance in people with overweight and obesity: a controlled randomized trial. Nature Medicine 2026; 32(6): 2107-2116. doi: 10.1038/s41591-026-04394-7.
21. Zhang Y, Liu R, Chen Y, Cao Z, Liu C and Bao R: Akkermansia muciniphila supplementation in patients with overweight/obese type 2 diabetes: efficacy depends on its baseline levels in the gut. Cell Metabolism 2025; 37(3): 592-605.e6. doi: 10.1016/j.cmet.2024.12.010.
22. EFSA Panel on Nutrition, Novel Foods and Food Allergens: Safety of pasteurised Akkermansia muciniphila as a novel food pursuant to Regulation (EU) 2015/2283. EFSA Journal 2021; 19(9): 6780. doi: 10.2903/j.efsa.2021.6780.
23. European Commission: Commission Implementing Regulation (EU) 2022/168 of 08 February 2022 authorising the placing on the market of pasteurised Akkermansia muciniphila as a novel food. Official Journal of the European Union 2022; L 28: 5-8.
24. Backhed F, Ding H, Wang T, Hooper LV, Koh GY and Nagy A: The gut microbiota as an environmental factor that regulates fat storage. Proceedings of the National Academy of Sciences of the United States of America 2004; 101(44): 15718-15723. doi: 10.1073/pnas.0407076101.
25. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE and Wolfe BE: Diet rapidly and reproducibly alters the human gut microbiome. Nature 2014; 505(7484): 559-563. doi: 10.1038/nature12820.
26. Cotillard A, Kennedy SP, Kong LC, Prifti E, Pons N and Le Chatelier E: Dietary intervention impact on gut microbial gene richness. Nature 2013; 500(7464): 585-588. doi: 10.1038/nature12480.
27. Koh A, De Vadder F, Kovatcheva-Datchary P and Backhed F: From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 2016; 165(6): 1332-1345. doi: 10.1016/j.cell.2016.05.041.
28. den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud DJ and Bakker BM: The role of short-chain fatty acids in the interplay between diet, gut microbiota and host energy metabolism. Journal of Lipid Research 2013; 54(9): 2325-2340. doi: 10.1194/jlr.R036012.
29. Tolhurst G, Heffron H, Lam YS, Parker HE, Habib AM and Diakogiannaki E: Short-chain fatty acids stimulate glucagon-like peptide-1 secretion via the G-protein-coupled receptor FFAR2. Diabetes 2012; 61(2): 364-371. doi: 10.2337/db11-1019.
30. Perry RJ, Peng L, Barry NA, Cline GW, Zhang D and Cardone RL: Acetate mediates a microbiome-brain-beta-cell axis to promote metabolic syndrome. Nature 2016; 534(7606): 213-217. doi: 10.1038/nature18309.
31. Tirosh A, Calay ES, Tuncman G, Claiborn KC, Inouye KE and Eguchi K: The short-chain fatty acid propionate increases glucagon and FABP4 production, impairing insulin action in mice and humans. Science Translational Medicine 2019; 11(489): eaav0120. doi: 10.1126/scitranslmed.aav0120.
32. Canfora EE, Meex RCR, Venema K and Blaak EE: Gut microbial metabolites in obesity, non-alcoholic fatty liver disease and type 2 diabetes. Nature Reviews Endocrinology 2019; 15(5): 261-273. doi: 10.1038/s41574-019-0155-4.
33. Pedersen HK, Gudmundsdottir V, Nielsen HB, Hyotylainen T, Nielsen T and Jensen BAH: Human gut microbes impact host serum metabolome and insulin sensitivity. Nature 2016; 535(7612): 376-381. doi: 10.1038/nature18646.
34. Wahlstrom A, Sayin SI, Marschall HU and Backhed F: Intestinal crosstalk between bile acids and microbiota and its impact on host metabolism. Cell Metabolism 2016; 24(1): 41-50. doi: 10.1016/j.cmet.2016.05.005.
35. Sayin SI, Wahlstrom A, Felin J, Jantti S, Marschall HU and Bamberg K: Gut microbiota regulates bile acid metabolism by reducing the levels of tauro-beta-muricholic acid, a naturally occurring FXR antagonist. Cell Metabolism 2013; 17(2): 225-235. doi: 10.1016/j.cmet.2013.01.003.
36. Watanabe M, Houten SM, Mataki C, Christoffolete MA, Kim BW and Sato H: Bile acids induce energy expenditure by promoting intracellular thyroid hormone activation. Nature 2006; 439(7075): 484-489. doi: 10.1038/nature04330.
37. Li T and Chiang JYL: Bile acid signaling in metabolic disease and drug therapy. Pharmacological Reviews 2014; 66(4): 948-983. doi: 10.1124/pr.113.008201.
38. Gibson GR, Hutkins R, Sanders ME, Prescott SL, Reimer RA and Salminen SJ: The International Scientific Association for Probiotics and Prebiotics consensus statement on the definition and scope of prebiotics. Nature Reviews Gastroenterology & Hepatology 2017; 14(8): 491-502. doi: 10.1038/nrgastro.2017.75.
39. Makki K, Deehan EC, Walter J and Backhed F: The impact of dietary fiber on gut microbiota in host health and disease. Cell Host & Microbe 2018; 23(6): 705-715. doi: 10.1016/j.chom.2018.05.012.
40. Sonnenburg JL and Backhed F: Diet-microbiota interactions as moderators of human metabolism. Nature 2016; 535(7610): 56-64. doi: 10.1038/nature18846.
41. Dewulf EM, Cani PD, Claus SP, Fuentes S, Puylaert PGB, Neyrinck AM: Insight into the prebiotic concept: lessons from an exploratory, double-blind intervention study with inulin-type fructans in obese women. Gut 2013; 62(8): 1112-1121. doi: 10.1136/gutjnl-2012-303304.
42. Chambers ES, Viardot A, Psichas A, Morrison DJ, Murphy KG and Zac-Varghese SEK: Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults. Gut 2015; 64(11): 1744-1754. doi: 10.1136/gutjnl-2014-307913.
43. Kellow NJ, Coughlan MT and Reid CM: Metabolic benefits of dietary prebiotics in human subjects: a systematic review of randomised controlled trials. British Journal of Nutrition 2014; 111(7): 1147-1161. doi: 10.1017/S0007114513003607.
44. Hill C, Guarner F, Reid G, Gibson GR, Merenstein DJ and Pot B: The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nature Reviews Gastroenterology & Hepatology 2014; 11(8): 506-514. doi: 10.1038/nrgastro.2014.66.
45. Binda S, Hill C, Johansen E, Obis D, Pot B and Sanders ME: Criteria to qualify microorganisms as probiotic in foods and dietary supplements. Frontiers in Microbiology 2020; 11: 1662. doi: 10.3389/fmicb.2020.01662.
46. Swanson KS, Gibson GR, Hutkins R, Reimer RA, Reid G and Verbeke K: The International Scientific Association for Probiotics and Prebiotics consensus statement on the definition and scope of synbiotics. Nature Reviews Gastroenterology & Hepatology 2020; 17(11): 687-701. doi: 10.1038/s41575-020-0344-2.
47. Salminen S, Collado MC, Endo A, Hill C, Lebeer S and Quigley EMM: The International Scientific Association of Probiotics and Prebiotics consensus statement on the definition and scope of postbiotics. Nature Reviews Gastroenterology & Hepatology 2021; 18(9): 649-667. doi: 10.1038/s41575-021-00440-6.
48. Koutnikova H, Genser B, Monteiro-Sepulveda M, Faurie JM, Rizkalla S and Schrezenmeir J: Impact of bacterial probiotics on obesity, diabetes and non-alcoholic fatty liver disease-related variables: a systematic review and meta-analysis of randomised controlled trials. BMJ Open 2019; 9(3): e017995. doi: 10.1136/bmjopen-2017-017995.
49. Wang Z, Feng Y, Yang N, Jiang T, Xu H and Lei H: Fermented foods and probiotic supplements for type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. Public Health 2022; 210: 149-159. doi: 10.1016/j.puhe.2022.06.012.
50. Setayesh A, Karimi M, Karimi MA, Pirzad S, Heydari M and Asbaghi O: Effects of probiotic and synbiotic supplementation on glycemic indices in adult individuals with prediabetes and type 2 diabetes mellitus: a GRADE-assessed systematic review and dose-response meta-analysis of RCTs. Probiotics and Antimicrobial Proteins 2026; 18(2): 3181-3204. doi: 10.1007/s12602-025-10644-w.
51. Sabico S, Al-Mashharawi A, Al-Daghri NM, Wani K, Amer OE and Hussain DS: Effects of a 6-month multi-strain probiotic supplementation on cardiometabolic status of patients with type 2 diabetes: a randomized double-blind placebo-controlled trial. Clinical Nutrition 2019; 38(4): 1561-1569. doi: 10.1016/j.clnu.2018.08.009.
52. Ejtahed HS, Mohtadi-Nia J, Homayouni-Rad A, Niafar M, Asghari-Jafarabadi M and Mofid V: Probiotic yogurt improves antioxidant status in type 2 diabetic patients. Nutrition 2012; 28(5): 539-543. doi: 10.1016/j.nut.2011.08.013.
53. Vrieze A, Van Nood E, Holleman F, Salojarvi J, Kootte RS and Bartelsman JF: Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology 2012; 143(4): 913-916.e7. doi: 10.1053/j.gastro.2012.06.031.
54. Kootte RS, Levin E, Salojarvi J, Smits LP, Hartstra AV and Udayappan SD: Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metabolism 2017; 26(4): 611-619.e6. doi: 10.1016/j.cmet.2017.09.008.
55. Yu EW, Gao L, Stastka P, Cheney MC, Mahabamunuge J and Soto MT: Fecal microbiota transplantation for the improvement of metabolism in obesity: the FMT-TRIM double-blind placebo-controlled pilot trial. PLoS Medicine 2020; 17(3): e1003051. doi: 10.1371/journal.pmed.1003051.
56. Allegretti JR, Kassam Z, Mullish BH, Chiang A, Carrellas M and Hurtado J: Effects of fecal microbiota transplantation with oral capsules in obese patients. Clinical Gastroenterology and Hepatology 2020; 18(4): 855-863.e2. doi: 10.1016/j.cgh.2019.07.006.
57. Mocanu V, Zhang Z, Deehan EC, Kao DH, Hotte N and Karmali S: Fecal microbial transplantation and fiber supplementation in patients with severe obesity and metabolic syndrome: a randomized double-blind placebo-controlled phase 2 trial. Nature Medicine 2021; 27(7): 1272-1279. doi: 10.1038/s41591-021-01399-2.
58. Peery AF, Kelly CR, Kao D, Vaughn BP, Lebwohl B and Singh S: AGA clinical practice guideline on fecal microbiota-based therapies for select gastrointestinal diseases. Gastroenterology 2024; 166(3): 409-434. doi: 10.1053/j.gastro.2024.01.008.
59. United States Food and Drug Administration: Fecal microbiota products. FDA, Silver Spring. Available from: https://www.fda.gov/vaccines-blood-biologics/fecal-microbiota-products (accessed 17 July 2026).
60. United States Food and Drug Administration: Safety alert regarding use of fecal microbiota for transplantation and risk of serious adverse reactions due to transmission of multi-drug resistant organisms. FDA, Silver Spring, 13 June 2019. Available from: https://www.fda.gov/vaccines-blood-biologics/safety-availability-biologics (accessed 17 July 2026).
61. Aron-Wisnewsky J, Prifti E, Belda E, Ichou F, Kayser BD and Dao MC: Major microbiota dysbiosis in severe obesity: fate after bariatric surgery. Gut 2019; 68(1): 70-82. doi: 10.1136/gutjnl-2017-314860.
62. Liou AP, Paziuk M, Luevano JM Jr, Machineni S, Turnbaugh PJ and Kaplan LM: Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity. Science Translational Medicine 2013; 5(178): 178ra41. doi: 10.1126/scitranslmed.3005687.
63. Tremaroli V, Karlsson F, Werling M, Stahlman M, Kovatcheva-Datchary P and Olbers T: Roux-en-Y gastric bypass and vertical banded gastroplasty induce long-term changes on the human gut microbiome contributing to fat mass regulation. Cell Metabolism 2015; 22(2): 228-238. doi: 10.1016/j.cmet.2015.07.009.
64. American Diabetes Association Professional Practice Committee: Obesity and weight management for the prevention and treatment of type 2 diabetes: Standards of Care in Diabetes-2026. Diabetes Care 2026; 49(1): 166-182. doi: 10.2337/dc26-S008.
65. Wu H, Esteve E, Tremaroli V, Khan MT, Caesar R and Manneras-Holm L: Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nature Medicine 2017; 23(7): 850-858. doi: 10.1038/nm.4345.
66. Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E and Sunagawa S: Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature 2015; 528(7581): 262-266. doi: 10.1038/nature15766.
67. de la Cuesta-Zuluaga J, Mueller NT, Corrales-Agudelo V, Velasquez-Mejia EP, Carmona JA and Abad JM: Metformin is associated with higher relative abundance of mucin-degrading Akkermansia muciniphila and several short-chain fatty acid-producing microbiota in the gut. Diabetes Care 2017; 40(1): 54-62. doi: 10.2337/dc16-1324.
68. Napolitano A, Miller S, Nicholls AW, Baker D, Van Horn S and Thomas E: Novel gut-based pharmacology of metformin in patients with type 2 diabetes mellitus. PLoS One 2014; 9(7): e100778. doi: 10.1371/journal.pone.0100778.
69. Gu Y, Wang X, Li J, Zhang Y, Zhong H and Liu R: Analyses of gut microbiota and plasma bile acids enable stratification of patients for antidiabetic treatment. Nature Communications 2017; 8(1): 1785. doi: 10.1038/s41467-017-02238-y.
70. Zhang X, Zhao Y, Zhang M, Pang X, Xu J and Kang C: Structural changes of gut microbiota during berberine-mediated prevention of obesity and insulin resistance in high-fat diet-fed rats. PLoS One 2012; 7(8): e42529. doi: 10.1371/journal.pone.0042529.
71. Zhang Y, Gu Y, Ren H, Wang S, Zhong H and Zhao X: Gut microbiome-related effects of berberine and probiotics on type 2 diabetes: the PREMOTE study. Nature Communications 2020; 11(1): 5015. doi: 10.1038/s41467-020-18414-8.
72. Tilg H, Zmora N, Adolph TE and Elinav E: The intestinal microbiota fuelling metabolic inflammation. Nature Reviews Immunology 2020; 20(1): 40-54. doi: 10.1038/s41577-019-0198-4.
73. Wu J, Yang K, Fan H, Wei M and Xiong Q: Targeting the gut microbiota and its metabolites for type 2 diabetes mellitus. Frontiers in Endocrinology 2023; 14: 1114424. doi: 10.3389/fendo.2023.1114424.
74. Celletti F, Buse JB, Meara JG, Osewe PL and colleagues: World Health Organization guideline on glucagon-like peptide-1 therapies for adults living with obesity. JAMA 2026; 335(5): 434-438. doi: 10.1001/jama.2025.24288.
75. Suez J, Zmora N, Zilberman-Schapira G, Mor U, Dori-Bachash M and Bashiardes S: Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous fecal microbiome transplantation. Cell 2018; 174(6): 1406-1423.e16. doi: 10.1016/j.cell.2018.08.047.
    

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    Prashar Y and Singh PM: Gut microbiota as a therapeutic target in obesity and type 2 diabetes mellitus. Int J Pharm Sci & Res 2026; 17(11): 3340-52. doi: 10.13040/IJPSR.0975-8232.17(11).3340-52.

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