Effect of fiber-modified kombucha tea on gut microbiota in healthy population: A randomized controlled trial (RCT)

Abstract

Background

The development of functional foods with health-promoting properties is a priority in addressing chronic diseases. Studying the effect of these foods on gut microbiota provides critical insights into the interplay between microorganisms, health, and disease.

Objective

This study aimed to evaluate the effects of fiber-enriched kombucha tea on biochemical parameters and gut microbiota composition in a healthy population.

Methods

A randomized, double-blind, parallel nutritional intervention trial was conducted with 60 participants (58 completed: 42 women and 16 men; mean ± SD age: 39.79 ± 14.58 years). Participants were randomized into two groups consuming either 250 mL/day of a control beverage (unfermented tea) or the fiber-enriched kombucha tea for six weeks. Lifestyle and biochemical data were collected, and gut microbiota composition and diversity were assessed using 16S rDNA sequencing.

Results

Significant biochemical and microbiota-related improvements were observed in the study group compared to the control. The treatment significantly affected triglyceride levels (p-value = 0.031). In particular, the study group exhibited a reduction in triglyceride levels very close to significance (baseline mean ± SEM: 69.59 ± 6.98 mg/dL; post-intervention: 62.80 ± 5.14 mg/dL; p = 0.053), while the control group did not experience a significant variation. Additionally, fiber-enriched kombucha consumption led to a notable increase in Bifidobacterium abundance, recognized for its intestinal health benefits and immunomodulatory effects. A reduction in Ruminococcus torques, linked to inflammatory bowel diseases, was also observed.

Conclusions

The studied fiber-enriched kombucha drink demonstrated potential health benefits, including triglyceride modulation and positive alterations in gut microbiota composition. These findings suggest its promise as a functional beverage for improving metabolic and gut health in healthy individuals. However, further randomized controlled trials are warranted to confirm these benefits. This trial was registered at clinicaltrials.gov as NCT06626997.

Graphical abstract

Highlights

• •Fiber-enriched kombucha intervention reduced serum triglyceride levels.
• •Increased Bifidobacterium and decreased Ruminococcus torques were observed.
• •Significant shifts in beta diversity promote gut microbiota modulation.
• •Findings support fiber-kombucha as a synbiotic with dual benefits for human health.

Abbreviations:

ALT

Alanine transaminase

AST

Aspartate transaminase

ASVs

Amplicon sequence variants

BMI

body mass index

Ce PRO

Celiac Disease Patient-Reported Outcome

DASS-21 scale

Depression, Anxiety and Stress Scale

EFSA

European Food Safety Authority

ENAC

Entidad Nacional de Acreditación (Spain)

FDA

Food and Drug Administration

GGT

gamma-glutamyl transferase

GOT

Glutamic Oxalacetic Transaminase

GPT

Glutamate-Pyruvate Transaminase

GRADE

Grading of Recommendations, Assessment, Development, and Evaluation

GRAS

Generally Recognized as Safe

GSRS

Gastrointestinal Symptom Rating Scale

HbA1c

Glycated haemoglobin

HDL

high density lipoprotein

HEI

healthy eating index

HOMA

Homeostasis Model Assessment

IBD

inflammatory bowel diseases

IFCC

International Federation of Clinical Chemistry

IPAQ

International Physical Activity Questionnaire

LDL

low density lipoprotein

LEITAT

Acondicionamiento Tarrasense (Spain)

METs

The Metabolic Equivalents of Task

OSQ

Oviedo Sleep Questionnaire

PCoA

Principal Coordinate Analysis

PRO

Patient Reported Outcome

RCT

Randomized Controlled Trial

SCOBY

Symbiotic Culture of Bacteria and Yeast

SD

standard deviation

SEM

standard error of the mean

SIBO

Small Intestinal Bacterial Overgrowth

T2MD

type II diabetes mellitus

1. Introduction

The human microbiota consists of a vast and diverse community of over 10¹⁴ microorganisms —including bacteria, fungi, viruses, and other microbes—which coexist symbiotically within the body, primarily in the gastrointestinal tract (Thursby and Juge, 2017). Alterations in gut microbiota balance (Hou et al., 2022), known as intestinal dysbiosis, have been linked to various gastrointestinal, metabolic, neurological, and inflammatory disorders (Durack and Lynch, 2019). Therefore, the gut microbiota plays an essential role in maintaining immunological and metabolic homeostasis, interacting with nutrient absorption, intestinal barrier and immune modulation (Fan and Pedersen, 2021; Jandhyala et al., 2015).

In response, next-generation synbiotics combine prebiotics with fermented foods (El Sheikha and Hu, 2020; El Sheikha A.F. 2022; Ray R.C. et al., 2014) to enhance gut microbiota benefits (Wastyk et al., 2021). In this context, kombucha tea, a fermented beverage produced with black, oolong, and/or green tea from Camellia sinensis, sucrose along with a biofilm containing the symbiotic culture of bacteria and yeast, known as SCOBY (Symbiotic Culture of Bacteria and Yeast) (Jakubczyk et al., 2020), has seen a significant rise in global popularity by the early 20th century for its perceived health benefits (Chong et al., 2023; Kapp and Sumner, 2019). Traditionally consumed in Asia, in recent years it has experienced a significant expansion in Europe (following Spain this trend), where market volume reached 500 million euros in 2023 and is expected to grow to 1.3 billion euros by 2030 (Virtue Market Research, 2024).

Despite its growing consumption, clinical evidence on its impact on human gut microbiota remains still limited, with only six registered clinical trials (https://clinicaltrials.gov). Two of them have not shown results yet (NCT04051294 (U.S. National Library of Medicine, 2023b), NCT06502509 (U.S. National Library of Medicine, 2024a)). One of the studies involved 42 healthy adults [NCT03873350 (U.S. National Library of Medicine, 2019)] found no significant changes in gut microbiota after kombucha consumption, though methodological challenges may have affected the outcomes (Bergström, 2018). Another study examined the effects of inulin-enriched, pasteurized kombucha on 40 patients with irritable bowel syndrome showed improvements in constipation symptoms by increasing stool frequency and consistency [NCT05164861 (Isakov et al., 2023; Pilipenko et al., 2022; U.S. National Library of Medicine, 2023a)]. Other studies demonstrated beneficial effects on glucose regulation in diabetic patients [NCT04107207 (Mendelson et al., 2023; U.S. National Library of Medicine, 2021),] and modest shifts on biochemical parameters and gut microbiome composition in healthy individuals [NCT06484504 (Ecklu-Mensah et al., 2024; U.S. National Library of Medicine, 2024b)].

Most evidence arises from animal models where kombucha has been shown to reduce body weight and improve lipid profiles, possibly through decreased lipid absorption and liver function enhancement (Aloulou et al., 2012; Costa et al., 2023; Z.-W. Yang et al., 2009). Even in nematode Caenorhabditis elegans system, research models have been proposed to evaluate the transcriptional mechanisms involved in lipid metabolism modulation (DuMez-Kornegay et al., 2024).

Additionally, kombucha tea may also improve glycemic control and pancreatic function in type II diabetes mellitus (T2MD), with effects comparable to metformin, likely due to antioxidant compounds (Aloulou et al., 2012; Costa et al., 2023). However, it is important to note that most research has been conducted in animal models, primarily in mice. In these models, the effects of kombucha supplementation have been observed over a shorter period; for instance, some authors estimate that 9 days of supplementation in mice is equivalent to one year in humans (Moreira et al., 2022; Swanson et al., 2020).

Kombucha is recognized as a probiotic beverage, but some researchers suggest it may also function as a prebiotic. Prebiotics are dietary compounds that serve as a substrate for beneficial gut bacteria, enhancing microbial balance. Certain studies indicate that kombucha's supernatant promotes the in vitro growth of beneficial strains such as Bifidobacterium and Collinsella, highlighting its potential prebiotic effects (Vargas et al., 2021). Potential prebiotic components present in kombucha include phenolic compounds, which are not absorbed in the small intestine.

Beyond its probiotic potential, kombucha may also exhibit prebiotic properties, particularly when enriched with specific dietary fibers such as inulin (Reimer et al., 2020). Inulin, a naturally occurring polysaccharide from the fructan group, is extracted from plants like chicory root and Jerusalem artichoke. It is a water-soluble dietary fiber composed of a linear chain of fructose molecules and has been extensively studied for its ability to modulate gut microbiota, stimulate the growth of beneficial bacteria and improve bowel function (Shoaib et al., 2016). FIBRULINE™ is a type of dietary fiber extracted from chicory roots, also known as chicory root fiber or chicory inulin (Fibruline—cosucra, 2014). Among its advantages are its ability to improve digestion, increase fiber content in foods, and serve as a substitute for unhealthy sugars and fats.

Kombucha is considered a safe fermented beverage when properly prepared, stored, and consumed (Kitwetcharoen et al., 2023). According to the Food and Drug Administration (FDA) Food Code recommendations, a pH of 4.2 in kombucha is considered a critical limit and must be reached within seven days of production. From a microbiological standpoint, due to fermentation, acidic foods (pH 4–4.5 or lower) are generally safe, as pathogenic microorganisms cannot thrive in such environments (Coban, 2020; de Miranda et al., 2022; Kitwetcharoen et al., 2023; Nummer, 2013). Regulatory bodies such as the European Food Safety Authority (EFSA) and the U.S. FDA recognize inulin as a Generally Recognized as Safe (GRAS) ingredient, a designation given to chemicals or substances deemed suitable for regular consumption under the intended conditions of use. The average daily intake (10 g/day) in European and North American populations (Coussement, 1999). Moreover, an excessive consumption may cause gastrointestinal discomfort (Comité Científico de la Agencia Española de Seguridad Alimentaria y Nutrición AESAN, 2012).

Therefore, given the importance of maintaining a healthy gut microbiota for the prevention and treatment of multiple chronic diseases, this study aims to evaluate the effects of commercial kombucha (probiotic) tea enriched with inulin (prebiotic) on the gastrointestinal tract and nutritional status in a healthy population. The high prevalence of obesity, metabolic syndrome, diabetes, and chronic diseases in general highlights the need to study foods that may have beneficial effects in this regard. Due to the growing public interest in kombucha consumption and the lack of clinical studies on its effectiveness and safety, it is essential to conduct further research to provide more evidence on its health effects.

2. Methods

2.1. Subjects and study protocol

This was a double-blinded parallel randomized controlled clinical trial with a duration of 6 consecutive weeks. Participants were divided into two groups: the study group (consumers of fiber-enhanced kombucha tea) and the control group (consumers of a beverage of a similar nutritional composition but without fermentation or fiber enrichment). The aim was to evaluate the effects on microbiota and other nutritional markers (body composition, biochemical parameters, diet, lifestyle factors and gastrointestinal symptoms). The Fisterra tool was used to calculate the sufficient sample size according to the possible changes in the microbiota. This assumed a mean relative change (d) of 1.5 in the study group compared to placebo, and that the variance (S²) is 2.25. The randomization method was carried out using R Studio Statistical Software (Version, 2023.03.1) (www.r-project.org), which generated a randomized sequence of assignment according to the two treatment groups (balanced blocking and sequentially numbered containers). The random allocation sequence was generated by the biostatistician, ensuring allocation concealment.

Participants were recruited through the Platform for Clinical Trials in Nutrition and Health (GENYAL) at IMDEA Food Institute (Madrid, Spain) and assigned to their respective groups only after enrollment. Nutritionists were responsible for both enrollment and assignment to interventions. All the subjects were evaluated in one screening visit to confirm compliance with the inclusion/exclusion criteria. Subsequently, an initial visit and a final visit were conducted. Inclusion criteria for recruitment required participants to be males or females aged ≥18 years, with an adequate cultural level, understanding of the clinical study and provide written informed consent. Exclusion criteria included severe diseases (e.g. dementia, mental disorders, hepatic or renal disease, immunosuppressed illness, etc.), a body mass index (BMI) of ≥30 kg/m² or pharmacological treatment for weight loss, pregnant or breastfeeding women, immunological pathologies, gallstones, gastric ulcers or coagulation problems. Additionally, individuals with specific conditions that contraindicate inulin and probiotic intake, those undergoing antibiotic treatment, or those regularly consuming probiotic supplements were excluded. To ensure study integrity, participants were also required to adhere to controlled dietary guidelines regarding probiotic and prebiotic intake. Specifically, consumption of probiotic-rich foods was limited to one serving per day, while prebiotic-containing foods were restricted to a maximum of 7–8 servings per week.

2.2. Ethical aspects

The study was conducted in accordance with the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Research Ethics Committee of IMDEA Food (IMD: PI-060). Written informed consent was obtained from all subjects prior to the intervention.

2.3. Evaluated products and consumption guidelines

The fiber-enhanced kombucha tea and the control beverage were produced by Komvida Kombucha, S.L. (Fregenal de la Sierra, Badajoz, Spain). The fiber-enriched kombucha tea was prepared by dissolving chicory root inulin (Fibruline® Instant, Cosucra Group) into the kombucha beverage at the end of the fermentation process. The inulin used was in powdered form, with a particle size below 500 μm, allowing for easy homogenization and dissolution. The final concentration of inulin in the fiber-enriched kombucha was 39.33 g/L, which corresponds to approximately 9.83 g of inulin per 250 mL serving. This intake level is within the range considered safe and functionally relevant. In combination with the probiotic properties of kombucha, this may result in a symbiotic functional effect. The inulin (fructan) content in the samples was determined according to AOAC Official Method 997.08 (AOAC International, 2000). This involves enzymatic hydrolysis of fructans followed by quantification of released fructose and glucose. This validated method is widely used for analysing inulin levels in food products (Horwitz, 2002). In terms of functional characteristics, inulin is a well-known prebiotic fiber that can promote beneficial gut bacteria, improve digestion and intestinal transit, and slightly enhance the natural sweetness of kombucha, which is often perceived as bitter. These properties may influence both the sensory profile and physiological effects of the fiber-enriched kombucha (Fibruline® Instant Technical Sheet, Cosucra Group). The control beverage was produced through an infusion of sweetened tea, which was then packaged and pasteurized, ensuring a nutritional composition similar to the fiber-enriched fermented beverage. This control beverage was not subjected to fermentation treatment. This approach ensured that any differences in outcomes could be more confidently attributed to the bioactive compounds generated during fermentation, and not simply to tea consumption or inulin alone. Any microbiological content derived from the raw materials used (dried tea leaves and white sugar) was eliminated through pasteurization, guaranteeing its stability throughout the six-week study period. Nutritional composition and microbiological analysis of both the control and functional kombucha beverages are shown in Supplementary Table S1.

The beverages produced were transported and stored in cold storage for the entire conservation period (temperature: 3-4 °C). All participants were instructed on the proper method of conservation: keeping the bottles upright (cap facing up) in the fridge (4 °C temperature) and avoiding shaking before consumption. To maintain study masking, identical packaging was used for both beverages (study and control group). Blinded randomization was performed, so that neither the participants nor the investigators knew which group received the study or control product.

Participants consumed 1 bottle of 250 mL of either the study or control product daily (slightly shaken before opening), between main meals (preferably mid-morning or mid-afternoon), for a period of 6 weeks. Together with the consumption of the product, participants followed a healthy eating plan and physical activity recommendations. In addition, they were provided with guidelines on limiting the intake of certain foods (Supplementary Figure S1) to avoid interference with the study product. At the same time, the method of conservation was also reminded. Adherence to the intervention was monitored through a daily product consumption record, and compliance was considered sufficient when intake was ≥80 % of the total assigned product over the study period.

2.4. Assessments and measurements

For this study, three visits were conducted: a selection visit (V0), an initial visit (V1, Week 0), and a final visit (V2, Week 6). During the selection visit (V0), participants were assessed for eligibility based on inclusion and exclusion criteria. Written informed consent was obtained, randomization was performed, and participants received questionnaires and sample collection tubes for home use. At the initial visit (V1, Week 0), clinical and anthropometric assessments were performed, including medical history collection, anthropometric measurements, evaluation of vital signs, and verification of completed questionnaires. Blood and stool samples were also collected. The final visit (V2, Week 6) repeated all procedures conducted at V1, with the exception of the medical history assessment. This visit was used to evaluate changes over the 6-week intervention period.

2.5. Nutritional assessments and vital signs

Anthropometric and body composition variables were evaluated using standard validated techniques (Durnin and Fidanza, 1985; Norton, 1995). Height was measured with a Leicester stadiometer (Biological Medical Technology SL, Barcelona, Spain). Body weight, body mass index (BMI), fat mass, lean mass, visceral fat classification and basal metabolism were assessed using the body composition monitor BF511 (Omron Healthcare UK, LT, Kyoto, Japan). Waist and hip circumferences were determined using a Seca 201 non-elastic tape (Quirumed, Valencia, Spain).

Blood pressure and heart rate were recorded at all visits: initial (V1) and final (V2) using an automatic digital blood pressure monitor (Model M3) (OMRON HEALTHCARE UK, LT, Kyoto, Japan). Both measurements were taken with participants seated comfortably in a temperature-controlled setting.

Dietary intake was assessed using a validated 72-h food record for the Spanish population (Ortega Anta and Requejo Marcos, 2025). Participants received training to complete the questionnaire and dietary data (energy, macro and micronutrients intake) (Basiotis et al., 2002; Kennedy et al., 1995) were analyzed with the DIAL Software (Version 2.16, Alce Ingeniería) (Ortega et al., 2021).

2.6. Physiological habits and lifestyle assessment

Physical activity was evaluated using the International Physical Activity Questionnaire (IPAQ), validated for the Spanish population (Roman-Viñas et al., 2010). The Metabolic Equivalents of Task (METs) were calculated based on the activity duration, number of days in a week, and intensity of the physical activity done the week prior to the visit.

Psychological well-being variables (anxiety, stress and depression) were assessed with the DASS-21 scale (Depression, Anxiety and Stress Scale) (Antony et al., 1998). This categorization of the different dimensions was obtained by adding the scores of the responses obtained in the items corresponding to each of the factors. The response options available to answer this scale were: 0 (it has not happened to me); 1 (it has happened to me a little, or during part of the time); 2 (it has happened to me a lot, or during a good part of the time); and 3 (it has happened to me a lot, or most of the time).

Sleep patterns (particularly insomnia) were evaluated by the Oviedo Sleep Questionnaire (OSQ) (Bobes et al., 2000). This questionnaire consists of 15 items, 13 of which are categorized into 3 subscales: subjective sleep satisfaction (1 item), insomnia (9 items) and hypersomnia (3 items). Higher scores indicate greater insomnia severity.

Stool characteristics, in both healthy subjects and patients with gastrointestinal disorders, were assessed using the Bristol Stool Scale, a validated tool for classifying fecal patterns based on consistency, appearance, and morphology (Parés et al., 2009). Participants selected the most representative stool type over the past six weeks, with higher scores indicating softer stools.

Changes in gastrointestinal symptoms were measured using the Gastrointestinal Symptom Rating Scale (GSRS) (Svedlund et al., 1988), which includes 15 items grouped into 5 categories: reflux, abdominal pain, indigestion, diarrhea, and constipation. The volunteer indicated the intensity of discomfort among the options: none, negligible, slight, moderate, fairly strong, strong and very strong. It has a score based on a 7-degree Likert-type scale, where 1 represents the most positive option and 7 the most negative. Its validity and reliability in the general population is documented (Dimenäs et al., 1996).

The Patient Reported Outcome (PRO) questionnaire was evaluated at each visit (Leffler et al., 2015). For this purpose, volunteers had to indicate the perceived intensity of gastrointestinal symptoms (cramps, abdominal pain, abdominal bloating, constipation, diarrhea, flatulence, loose stools, vomiting, headaches and fatigue) on a scale from 0 (absence of the symptom) to 10 (the highest perception) over the past 6 weeks.

2.7. Biochemical markers

Blood tests were performed at baseline initial visit (V1) and final visit (V2). Blood samples were obtained by venous puncture in the early morning, with the subject having been in a fasting state (12 h). These samples were used to determine parameters related to glucose, lipid, and liver enzymes. The extractions and biochemical determinations were performed by an external clinical analysis laboratory, UNILABS (UNITED LABORATORIES MADRID, S.A), accredited in Spain by ENAC (Entidad Nacional de Acreditación), following the international UNE-ISO standards.

2.8. Fecal sample collection and microbial characterization

Collection and processing of these samples were performed according to the recommendations of the International Human Microbiome Consortium guidelines (Cardona et al., 2012; Costea et al., 2017; Santiago et al., 2014).

The characterization analysis of bacterial communities in fecal and kombucha samples was conducted by Acondicionamiento Tarrasense (LEITAT) in Barcelona (Spain). Genomic DNA from the samples was extracted using the ZymoBIOMICS DNA Miniprep Kit (Zymo Research, Irvine, Canada), following the manufacturer's protocol. All samples were homogenized and lysed for 30 min using a Vortex Genie. DNA quantification was performed using a Qubit 4 Fluorometer (Invitrogen). DNA library amplicons were generated from 16S rRNA, specifically targeting the V3-V4 regions (341F/R805). Sequencing was carried out using Illumina NovaSeq, following the guidelines provided by Illumina Inc. Data processing was performed using QIIME (Version 2 2022.11). Amplicon sequence variants (ASVs) were assigned using the DADA2 pipeline. Taxonomy was assigned at a 99 % similarity level using the q2-feature-classifier plugin with the SILVA 132 database (Version, 2019.10.0). Moreover, kombucha samples were processed similarly, with a prior centrifugation step at 10,000×g, and DNA was extracted from the pellet following the same protocol used for fecal samples. Sequencing was performed using Oxford Nanopore Technologies. Library preparation utilized the 16S Barcoding Kit 1–24 (SQK-16S024) following the manufacturer's protocol with slight modifications. The number of PCR cycles was increased from 25 to 40 to enhance assay sensitivity and increase sequence yield. A total of 20 barcoded libraries were pooled in equimolar concentrations and sequenced for 24 h using the FLO-MIN106 R10.4.1 flow cell on the MinION sequencer via the MinKNOW platform with super-accuracy basecalling.

2.9. Statistical analyses

Data were analyzed using R Studio Statistical Software (Version, 2023.03.1) (www.r-project.org). Numerical variables were summarized as mean ± standard error of the mean (SEM).

For within-group comparisons (baseline vs. final values), a paired t-test was used for normal variables, while the Wilcoxon signed-rank test was applied for non-normal variables. Normality was assessed visually using histograms and further tested with the Lilliefors test. Baseline comparisons between the two groups were conducted using unpaired t-test for normal variables and the Kruskal-Wallis test for non-normal variables.

To evaluate treatment effects over time, linear mixed-effects models were applied, considering the time × treatment interaction as a fixed factor and including the participant as a random effect to account for intra-subject correlation. Models were adjusted for sex, age, and BMI. A significant time × treatment interaction was interpreted as a statistically significant treatment effect over time. Additionally, pairwise comparisons were performed between visits within each treatment group and between treatment groups at each visit. Given the exploratory nature of the study, no correction for multiple testing was applied.

Moreover, microbiota statistical analyses and graphical visualizations were performed using R Studio. Ecological analyses of alpha and beta diversity were conducted with the vegan, phyloseq, and microeco packages. For alpha and beta diversity assessments, the Shannon and Bray-Curtis indices were used, respectively. Statistical analyses also included the most abundant differential genera. A multivariate analysis of statistical significance was performed using PERMANOVA (Adonis2) with 999 permutations (p < 0.05). Taxonomic distribution was represented at the phylum, family, and genus levels. Differential abundance analysis was conducted at the genus level. The Lefse function was used to transform relative abundance, and an ANOVA differential abundance analysis (p < 0.05) was performed to determine the significance of each bacterial genus within each group. In this case, results between Groups A (control) and B (study) were analyzed separately to compare each visit. Correlation analysis was performed using the relative abundance of the genus. All samples were processed together and by treatment groups.

3. Results

3.1. Study population and baseline characteristics

This study was conducted in the Autonomous Community of Madrid (Spain). A total of 58 participants completed the intervention and were analyzed: 29 in the control group (21 women and 8 men, with a mean age ± SD of 39.20 ± 15.93 years) and 29 in the study group (21 women and 8 men, with a mean age of 40.59 ± 13.04 years).

Initially, 246 individuals expressed interest in participating, and 70 subjects were ultimately deemed eligible and attended the selection visit. Following this visit, a total of 60 subjects were enrolled in the study (initial visit: V1). During the 6-week intervention, only one participant withdrew due to antibiotic consumption, and one subject was excluded from the analysis for consuming less than 75 % of the study product (Fig. 1).

Fig. 1.

CONSORT flowchart. Group A and B correspond to control group and study group, respectively.

All participants included in this study were of Caucasian ethnicity, with the majority being of Mediterranean European descent (91 %). The study population was predominantly single (59 %), with higher education (66 %), and employed (74 %).

At baseline, no significant differences were observed between the groups in any of the studied variables (anthropometric, dietary, physical activity, biochemical variables, or fecal microbiota analysis) except for walking, where the study group showed higher levels than the control group (control group mean ± SEM: 984 ± 202 METs vs. study group: 1430 ± 182 METs, p = 0.027). In this regard, the intervention groups were considered homogeneous at baseline (Table 1, p-value∗). The analyzed parameters show a healthy cohort with normal body weight and all biochemical levels remaining within established reference ranges.

Table 1.

Comparison of parameters (anthropometric, biochemical, dietary intake and lifestyle) before and after intervention of participants (mean ± SEM), according to control and functional groups.

Variables	Control Group (n = 29)			Study Group (n = 29)
	Baseline	After 6 Weeks	p-Value	Baseline	After 6 Weeks	p-Value	p-Value∗	p-Value∗∗
Anthropometric
Height (cm)	164.41 ± 1.69	n.a.	n.a.	166.28 ± 1.28	n.a.	n.a.	0.383	n.a.
Weight (kg)	64.02 ± 2.27	63.70 ± 2.22	0.294	64.75 ± 1.81	64.90 ± 1.80	0.368	0.804	0.539
BMI (kg/m2)	23.53 ± 0.54	23.40 ± 0.53	0.122	23.41 ± 0.57	23.50 ± 0.58	0.569	0.878	0.142
Fat mass (%)	28.41 ± 1.24	29.40 ± 1.26	0.046	28.57 ± 1.69	28.30 ± 1.70	0.457	0.941	0.063
Lean mass (%)	31.21 ± 0.85	30.70 ± 0.86	0.091	31.12 ± 1.09	31.30 ± 1.11	0.829	0.950	0.257
Visceral fat (classification)	6.07 ± 0.57	5.82 ± 0.55	1.000	5.72 ± 0.60	5.93 ± 0.61	0.120	0.343	0.428
Waist (cm)	74.33 ± 1.91	74.30 ± 1.84	0.576	73.79 ± 1.99	74.40 ± 1.95	0.169	0.843	0.572
Basal metabolism (kcal/day)	1407.21 ± 42.03	1388.00 ± 41.94	0.037	1412.86 ± 31.13	1413.00 ± 31.88	0.639	0.519	0.207
Systolic blood pressure (mmHg)	117.00 ± 2.33	116.00 ± 2.61	0.796	116.00 ± 3.28	115.00 ± 2.80	0.729	0.818	0.905
Diastolic blood pressure (mmHg)	72.20 ± 1.77	73.00 ± 1.78	0.498	71.00 ± 1.87	69.70 ± 1.55	0.260	0.661	0.19
Biochemical
Glycemia (mg/dL)	83.14 ± 1.30	83.40 ± 1.09	0.783	83.07 ± 1.43	83.50 ± 1.49	0.652	0.972	0.908
Insulinemia (μUI/mL)	5.78 ± 0.63	6.10 ± 0.73	0.724	4.90 ± 0.46	6.51 ± 0.93	0.027	0.314	0.465
HOMA	1.21 ± 0.14	1.26 ± 0.17	0.798	1.00 ± 0.09	1.36 ± 0.20	0.026	0.222	0.421
HbA1c (%)	5.44 ± 0.04	5.51 ± 0.05	0.328	5.45 ± 0.04	5.54 ± 0.05	0.092	0.568	0.645
HbA1c IFCC (mmol/mol)	35.95 ± 0.40	36.70 ± 0.50	0.230	36.09 ± 0.39	37.10 ± 0.52	0.049	0.568	0.645
Total Cholesterol (mg/dL)	178.34 ± 6.39	187.00 ± 6.35	0.005	176.48 ± 5.33	178.00 ± 4.95	0.703	0.824	0.051
HDL Cholesterol (mg/dL)	56.93 ± 2.99	63.30 ± 2.88	<0.001	61.28 ± 2.63	67.70 ± 2.69	<0.001	0.280	0.983
Triglycerides (mg/dL)	77.24 ± 8.62	82.70 ± 8.77	0.387	69.59 ± 6.98	62.80 ± 5.14	0.053	0.410	0.031
LDL Cholesterol (mg/dL)	105.97 ± 5.71	107.00 ± 5.69	0.684	101.29 ± 4.47	97.30 ± 4.56	0.126	0.522	0.175
GOT (UI/L)	27.60 ± 5.88	23.60 ± 1.93	0.547	23.90 ± 2.06	21.30 ± 0.77	0.608	0.441	0.842
GPT (UI/L)	27.00 ± 6.55	22.80 ± 2.66	0.374	22.60 ± 2.59	19.70 ± 1.51	0.989	0.450	0.852
Dietary intake
Calories (Kcal)	1750.00 ± 59.70	1790.00 ± 77.30	0.586	1780.00 ± 56.70	1870.00 ± 69.00	0.142	0.750	0.529
Proteins (% TEI)	18.00 ± 0.57	16.90 ± 0.43	0.024	18.30 ± 0.57	17.50 ± 0.65	0.393	0.735	0.684
Carbohydrates (%TEI)	44.00 ± 1.65	46.50 ± 1.47	0.080	41.70 ± 1.16	45.10 ± 1.43	0.022	0.264	0.629
simple sugars (g.)	69.00 ± 5.44	84.50 ± 4.13	0.007	61.40 ± 3.18	80.20 ± 3.91	<0.001	0.231	0.61
vegetable fiber (g.)	24.70 ± 2.43	23.00 ± 1.84	0.505	25.90 ± 2.85	35.70 ± 2.56	<0.001	0.926	<0.001
Lipids (% TEI)	36.00 ± 1.58	34.70 ± 1.29	0.402	38.20 ± 1.20	35.70 ± 1.03	0.697	0.269	0.591
HEI	64.80 ± 1.90	65.40 ± 1.85	0.817	60.90 ± 1.92	63.50 ± 1.82	0.251	0.158	0.538
Lifestyle
Walk (METs)	984 ± 202	970 ± 154	0.987	1430 ± 182	911 ± 132	0.002	0.027	0.015
Moderate activity (METs)	584 ± 97	679 ± 134	0.952	564 ± 98	603 ± 98	0.689	0.884	0.729
Intense activity (METs)	169 ± 52	122 ± 52	0.300	141 ± 41	154 ± 48	0.887	1.000	0.395
Total physical activity (METs)	1730 ± 248	1770 ± 244	0.830	2170 ± 196	1670 ± 137	0.019	0.065	0.027
DASS Total	7.10 ± 1.32	7.59 ± 1.32	0.680	6.38 ± 1.31	6.48 ± 1.48	0.680	0.767	0.789
COS-Total	25.10 ± 1.21	23.20 ± 0.71	0.048	25.59 ± 1.12	24.10 ± 1.32	0.268	0.771	0.805
BRISTOL Test	3.55 ± 0.17	3.83 ± 0.15	0.145	3.48 ± 0.15	3.38 ± 0.18	0.539	0.863	0.136
GSRS Total	25.60 ± 1.54	25.70 ± 1.11	0.665	27.10 ± 1.83	29.90 ± 1.45	0.065	0.538	0.208
CeD PRO Totala	15.83 ± 2.26	14.93 ± 1.91	0.760	16.55 ± 2.16	14.19 ± 2.26	0.264	0.818	0.200

p-value: comparison between baseline and final results across the same group (Paired t-test or Wilcoxon); p-value∗: comparison of baseline values between groups (ANOVA or Kruskal-Wallis); p-value∗∗: comparison differences by time between groups, adjusted for sex, age, and baseline BMI. In the analysis of the BMI variable, only age and sex were adjusted. SEM: standard error of the mean.

BMI: Body Mass Index; Ce PRO: Celiac Disease Patient-Reported Outcome; DASS: Depression, Anxiety and Stress Scale; GOT: Glutamic Oxalacetic Transaminase; GPT: Glutamate-Pyruvate Transaminase; GSRS: Gastrointestinal symptom rating scale (Supplementary Table S2); HbA1c: Glycated haemoglobin; HDL: high density lipoprotein; HEI: healthy eating index (DIAL software, version: 3.15.1.0); HOMA: Homeostasis Model Assessment. Wallace et al. (2004): HOMA-IR = (Basal Glucose (mg/dL)/18) x basal insulin (mUI/mL)/22.5; IFCC: International Federation of Clinical Chemistry; LDL: low density lipoprotein; METs: metabolic equivalent of task; n.a.: not available; OSQ: Oviedo Sleep Questionnaire; TEI: total energy intake.

^aIn the CeD PRO study, 10 items were included (Cramping, Abdominal pain, Abdominal bloating, Constipation, Diarrhea, Gas, Loose stools, Vomiting, Headaches, Tiredness) (Supplementary Figure S2 and S3).

3.2. Anthropometric and biochemical parameters, dietary intake and physical activity

As shown in Table 1 (p-value∗∗), no statistically significant differences were observed in body composition or vital signs between groups, considering the parameters obtained before and after the intervention.

From a biochemical perspective, a statistically significant difference in triglyceride levels (p = 0.031) was observed over time between the treatment groups (Fig. 2). Specifically, the study group exhibited a reduction in triglyceride levels close to statistical significance (mean ± SEM at baseline: 69.59 ± 6.98 mg/dL; final: 62.80 ± 5.14 mg/dL, p-value = 0.053), whereas the control group did not show a statistically significant variation (mean ± SEM at baseline: 77.24 ± 8.62 mg/dL; final: 82.70 ± 8.77 mg/dL, p-value = 0.387). Despite this significant difference, the values remained within the normal ranges throughout the study period, consistent with the trends observed for the other biochemical parameters.

Fig. 2.

Evolution of triglyceride levels (mg/dL) during the intervention.

The analysis of safety parameters, assessed by monitoring liver enzyme levels (GOT and GPT), showed no clinically relevant changes or differences in evolution between groups. Enzyme levels remained within the normal range throughout the study.

From a dietary perspective, no significant differences were observed over time between the treatment groups in total caloric intake or macronutrient distribution. However, a statistically significant difference was found in total fiber intake (p < 0.001), which was expected due to the fiber content added to the study product and accounted for in participants' dietary records. In our study, the macronutrient distributions (relative to the total caloric value) aligned with the expected dietary patterns for the Spanish population. Regarding the Healthy Eating Index (HEI), calculated using the DIAL dietary software (Alce Ingeniería), the average values ranged between 60 and 65 points, indicating a diet classified as acceptable to good (above 80 points signifies an excellent diet, 71–80 indicates a very good diet, 61–70 corresponds to a good diet, 51–60 represents an acceptable diet, and 0–50 reflects an inadequate diet). This study context is crucial and highlights the importance of considering baseline dietary habits when evaluating a nutritional intervention, as diet significantly influences gut microbiota composition.

However, a statistically significant difference was observed in total physical activity levels over time between the treatment groups, particularly in walking. As shown in Table 1, physical activity decreased in the study group, while no changes were observed in the control group (Total physical activity: p = 0.027; Walk: p = 0.015). This decrease could have influenced the unfavorable results obtained for the study product. Despite this, no relevant effects were detected when evaluating the treatments (control and study) over time. This reinforces the robustness of the findings, highlighting that the observed effect was not due to variations in physical activity but rather to the impact of the nutritional intervention.

3.3. Gastrointestinal symptoms and physiological rhythms

In terms of psychological profile (DASS questionnaire) and sleep quality (COS questionnaire), no statistically significant changes were detected as a result of the intervention.

Gastrointestinal symptoms and physiological rhythms were assessed using the following questionnaires: the Patient-Reported Symptom Questionnaire (CeD PRO. Supplementary Figure S2 and S3), the Gastrointestinal Symptom Rating Scale (GSRS. Supplementary Table S2), defecation frequency, and the Bristol Stool Chart (used to classify stool consistency and form). Among the symptoms evaluated, statistically significant differences were observed in gas (p = 0.003), as reported by both the CeD PRO and GSRS (p = 0.018). In both cases, the study group experienced a considerable increase in gas, whereas no notable differences were observed in the control group.

3.4. Microbiota composition and diversity

In total, the microbiota analysis identified 19 phyla, 102 families, and 311 genera. The results for the different products (control and study) were compared before and after the intervention. At the general composition level, the most dominant phylum was Firmicutes, followed by Bacteroidetes and Actinobacteria. Overall, the microbiota composition of volunteers was very similar between both groups, both at baseline and at the end of the intervention. However, in some participants, an increase (without significant differences) in the abundance of Actinobacteria was observed following the consumption of study group.

An alpha diversity analysis was conducted to assess species richness in fecal samples across groups (study and control) and time points (baseline and final). The results indicated a high species richness in both groups, as measured by the Shannon index. In the study group, species richness was slightly lower than in the control group. In both groups, community richness remained relatively stable throughout the intervention, with a slight but non-significant decrease. Beta diversity analysis was performed to examine variations in species diversity between treatments. In the Principal Coordinate Analysis (PCoA) plot (Fig. 3), using Bray-Curtis dissimilarity to represent beta diversity, the two-dimensional coordinates PCo1 and PCo2 explain the largest variation in species composition between samples. In our study, PCo1 accounts for the greatest percentage of variation, while PCo2 explains the second greatest. Both principal coordinates indicate a predominantly homogenous distribution in samples from both the initial (V1) (Fig. 3A) and final (V2) (Fig. 3B) time points, across volunteers in both the control (group A) and study groups (group B). In both cases, these two PCoA explained more than 50 % of the distribution over time.

Fig. 3.

Beta diversity distribution represented by a PCoA using Bray-Curtis. A: Beta diversity at baseline (V1) and B: Beta diversity at final time point (V2). The two boxes represent the two groups: Group A (control, green dots) and Group B (study, orange dots). The variance explained by each coordinate is indicated within the ellipses.

At the initial time point (V1), no significant differences were found between control group A and study group B (p = 0.196, R² = 0.0184). However, at the final time point (V2), significant differences were observed when comparing control and study group (p = 0.001, R² = 0.0304). This significant change in the gut microbiota after the intervention indicates that an alteration occurred in the microbiota of the volunteers between the two groups and that this change was not initially driven by the baseline microbiome composition.

At the genus level, the most significant differential genera for each group of volunteers were studied. Focusing on the control group (A), no significant changes were observed at the genus level when comparing the initial time point to the final time point after the intervention. However, in the case of the volunteers in the study group (B), significant differences were observed between the initial and final time points for several bacterial genera (Fig. 4). These included: Bifidobacterium, Ruminococcus, Marvinbryantia, and Negativabacillus.

Fig. 4.

Differential analysis of significant genera represented by a bar chart and divided by groups with standard deviations. A: Groups that showed no significant differences. B: Groups that showed significant differences.

Bifidobacterium is the most increased genus at the final time point (p = 0.001). On the other hand, there is a decrease in Ruminococcus torques (p = 0.01).

Considering the analysis of the microorganisms present in the kombucha, we observed that it was predominantly colonized by Liquorilactobacillus species (relative abundance: week 1, 99.30 %; week 3, 97.38 %; week 6, 99.31 %). The genus Zymomonas was also detected (week 1, 0.34 %; week 3, 2.14 %; week 6, 0.43 %). These two genera were the most representative in the kombucha samples analyzed. The genus Acetobacter, associated with acetic acid bacteria, was detected at a much lower relative abundance, averaging 0.10 % across the three time points.

4. Discussion

After the six-week intervention, and with 59 participants completing the study, the results showed that the evaluated symbiotic beverage (fiber-enriched kombucha) partially modified the lipid profile and gut microbiota at the genus level, although no changes were observed at the broader taxonomic levels. In this context, the obtained results indicate possible benefits from the consumption of fiber-enriched kombucha in a healthy population.

Among the key findings, a statistically significant reduction in triglyceride levels was observed in the study group compared to the control group, suggesting that fiber-enriched kombucha may have a favorable effect on lipid metabolism. These results align with previous research using animal models, which have demonstrated that kombucha positively influenced by reducing triglycerides (Costa et al., 2023). Similarly, another study in rodents observed that kombucha tea delayed the absorption of LDL cholesterol and triglycerides, while increasing HDL cholesterol levels (Aloulou et al., 2012). Furthermore, protection of liver tissue in diabetic mice was noted, attributed to a reduction in liver enzymes such as Aspartate transaminase (AST), Alanine transaminase (ALT) and gamma-glutamyl transferase (GGT).

In a recent study, where C. elegans was exclusively fed kombucha tea microbes, improvements in lipid profiles were not due to reduced nutrient absorption, but rather to transcriptional changes related to lipid metabolism, such as an increase in liposomal lipase (DuMez-Kornegay et al., 2024). Thus, the transcriptomic study of enzymes associated with lipid metabolism could be a promising avenue for future human studies. The obtained results in this study, where triglyceride levels decreased despite normal baseline levels, align with in vivo studies. It is also worth noting that the dietary profile was not significantly modified during the treatment, except for an increase in fiber intake in the study group, likely due to the inulin-enriched treatment (a soluble fiber from chicory root). Therefore, the increased fiber intake could also contribute to the reduction of blood lipid levels, as supported by the literature (Zhang et al., 2024).

A systematic review on soluble fiber supplementation in individuals with T2DM highlighted its favorable impact on lipid profiles, particularly on triglyceride levels (Gupta et al., 2025). However, another systematic review and meta-analysis indicated that, while soluble fiber may reduce triglyceride levels, the evidence level, according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach, is insufficient to consider it as effective for this purpose (Talukdar et al., 2024).

Regarding the main modifications observed in the gut microbiota following the nutritional intervention, a significant change in beta diversity between groups was noted after the intervention, as well as significant differences between the initial and final time points for Bifidobacterium and Ruminococcus in the study group. A significant difference in beta diversity between the study and control group at final visit showed an impact on altering the gut microbiota composition. This finding supports the potential efficacy of study product as a beneficial probiotic agent. Compared to a previous study (Ecklu-Mensah et al., 2024), which observed only modest changes in microbial composition, these results suggest that fiber-enriched kombucha tea may exert stronger effects on gut microbiota diversity. The observed differences may be due to variations in probiotic strain composition, intervention duration, or participant-specific microbiome baselines.

Unlike the study by Ecklu-Mensah et al. (2024), our product was enriched with soluble fiber, which could explain these results. However, individual studies are needed to identify the specific component involved in the effect.

In addition, the obtained results indicated that the consumption of study product led to significant changes in certain bacterial genera. Notably, there was a significant increase in Bifidobacterium, known for its benefits to intestinal health and its ability to modulate immune responses. Additionally, a decrease in the abundance of Ruminococcus torques, a genus associated with inflammatory bowel diseases, was observed. These changes suggest a positive impact of study product on gut microbiota composition.

The Bifidobacterium genus is one of the main indicators of a healthy gut microbiome, playing a key role in intestinal homeostasis and health. Bifidobacteria are among the most abundant bacteria in the gut microbiota of healthy, breastfed infants. They rapidly colonize the infant gut within the first weeks after birth, a process largely driven by the bifidogenic activity of specific oligosaccharides derived from human milk (Turroni et al., 2019). This colonization follows a mother-to-child vertical transmission route, a mechanism observed in both humans (Avershina et al., 2016) and other mammals (Ferrario et al., 2015). Therefore, Bifidobacterium is one of the dominant genera in early life and is closely linked to breastfeeding. However, as individuals reach adulthood, the prevalence of these bacteria declines (Kato et al., 2017).

Different strains of Bifidobacterium play a key role in maintaining and protecting health and may serve as important biomarkers for certain diseases (Arboleya et al., 2016). They provide various health benefits, including antimicrobial and immunomodulatory effects, increasing immunoglobulin levels and either inducing or reducing pro-inflammatory and anti-inflammatory cytokines, respectively. Some strains inhibit the growth or adhesion of pathogenic bacteria, including antibiotic-resistant bacteria, and their antibacterial activity may be enhanced when combined with certain antibiotics (Lim and Shin, 2020).

Moreover, studies have also shown changes in the gut microbiota following the consumption of inulin. Therefore, these changes could also be influenced by this compound. Thus, the most consistent change observed in human studies after the consumption of inulin was an increase in the Bifidobacterium genus, according to a systematic review (Bastard et al., 2020).

In contrast, Ruminococcus torques is associated with mucin degradation, directly affecting intestinal structures and glycans. This degradation process has been linked to inflammatory bowel diseases (IBD) (Schaus et al., 2024; J. Yang et al., 2024). Overexpression of Ruminococcus torques has been observed in chronic infections, potentially influencing the host's ability to combat parasites (Tran et al., 2023). Previous studies have described its role in altering the microbial proteome and have linked it to pro-inflammatory diets (Zheng et al., 2020).

These findings reinforce the potential probiotic benefits of fiber-enriched kombucha tea, as it promotes an increase in beneficial Bifidobacterium while reducing the abundance of Ruminococcus torques, a genus associated with intestinal inflammation. These results are in line with previous in vivo studies that suggest kombucha supplementation can induce shifts in gut microbiome diversity, increasing the Firmicutes/Bacteroidetes ratio and promoting the growth of Akkermansia muciniphila, a bacterium associated with gut barrier integrity and glucose metabolism (Xu et al., 2020). Compared to another kombucha intervention study conducted in the US (Ecklu-Mensah et al., 2024), which also reported significant changes in other specific bacterial genera (with Bifidobacterium also showing a significant effect), this suggests that different probiotic or fermented interventions (with or without soluble fiber) may exert distinct effects on gut microbiota composition. On the other hand, while the overall composition of the microbiota remained stable across volunteers, individual variations in Actinobacteria response were observed. In some participants, an increase in the abundance of Actinobacteria phyla was detected after consuming the study product. This change could suggest potential benefits for intestinal homeostasis, due to the anti-inflammatory and antimicrobial effects of certain strains within this phylum (Lim and Shin, 2020; Binda et al., 2018). Previous studies have associated this increase with improved metabolic health, including better glucose metabolism and reduced inflammation (Crudele et al., 2023). Their presence is also linked to enhanced production of antimicrobial peptides and reinforcement of the intestinal barrier (O'Callaghan and van Sinderen, 2016). Furthermore, in the present study, species richness remained relatively stable during the intervention, with no significant changes observed in both groups (control and study). Although a slight decrease over time was observed, this reduction was not statistically significant. This suggests that probiotic products, in this case study product, do not drastically alter species richness.

In parallel, the microbial composition of kombucha revealed that it was mainly colonized by Liquorilactobacillus, a Gram-positive, anaerobic lactic acid bacterium frequently found in fermented foods. This genus is known for contributing to both the organoleptic properties and its potential health benefits. Additionally, Zymomonas, a genus recognized for its unique metabolic pathway and ethanol tolerance (Fabricio et al., 2022), was also identified. It has been previously reported in kombucha (Marsh et al., 2014) and other fermented beverages such as kefir (Hsieh et al., 2012; Marsh et al., 2013). These bacteria can produce ethanol, sorbitol, or gluconic acid depending on the available carbon source. Interestingly, no overlap was found between the genera identified in kombucha and those detected in fecal samples. This was expected given the general stability of the human gut microbiota, which typically resists colonization by exogenous microbial strains. However, this does not preclude that the changes observed in fecal microbiota composition were indirectly modulated by the microbial community in the fiber-enriched fermented beverage. We suggest further exploration of possible associations between these kombucha-associated genera and the increased abundance of Bifidobacterium and Ruminococcus observed in fecal samples.

In the context of gastrointestinal symptoms, one notable effect observed during the intervention was the increased gastrointestinal discomfort reported in the study group, particularly the rise in gas production. This outcome is commonly associated with the intake of prebiotic fibers and fermented foods, which often triggers a period of gastrointestinal adaptation characterized by increased flatulence or bloating due to enhanced microbial fermentation in the colon. This adaptation process is actually indicative of microbiota changes. However, this effect should be interpreted with caution, as it may also indicate successful microbial fermentation and beneficial modulation of the gut microbiota (Mutuyemungu et al., 2023), particularly given the increase in Bifidobacterium and other fiber-fermenting genera observed in the study group.

Our findings align with previous research suggesting that dietary fibers such as inulin play a key role in modulating gastrointestinal symptoms (Mysonhimer and Holscher, 2022) and improving the functional properties of fermented beverages (Reimer et al., 2020; Shoaib et al., 2016). In particular, studies have shown that inulin supplementation can lead to gastrointestinal effects such as increased gas and bloating, especially during the early phases of consumption due to enhanced microbial fermentation in the colon. This may partly explain the gastrointestinal discomfort observed in our study and suggests that the addition of inulin may amplify these effects compared to regular kombucha alone. To date, only two human studies have explored the impact of fiber-enriched kombucha, both conducted by the same research group (Isakov et al., 2023; Pilipenko et al., 2022). These studies demonstrated improvements in constipation-related symptoms in individuals with irritable bowel syndrome, thereby supporting the therapeutic potential of fiber-enriched fermented beverages. However, they did not assess microbiota composition or biochemical markers, which limits the scope for comparison. Our study addresses this gap by evaluating both gastrointestinal outcomes and microbiota changes in healthy individuals, offering a broader view of kombucha's effects when enriched with functional fibers. Moreover, our results support previous in vivo findings on the synergistic impact of prebiotic and probiotic combinations on gut microbiota and metabolic health (Costa et al., 2023; Moreira et al., 2022).

However, this study still presents several limitations that should be considered when interpreting the results. One limitation of both our study and prior works is the inability to isolate the individual contributions of kombucha and fiber. Therefore, a three-arm study design including a control beverage, non-enriched kombucha, and fiber-enriched kombucha would provide greater clarity on the specific effects of each component. This should be considered in future research to better understand the effects of the bioactive compounds and to optimize the formulation of functional fermented beverages. Additionally, given that this is a nutritional study conducted over time, the relatively small size and homogenous origin of the participants limit the generalizability of the findings to broader and more diverse populations. While the six-week intervention period was adequate to observe initial microbiota responses, extending the duration in future studies may help to identify longer-term changes in gut microbiota composition. In order to overcome these limitations, further studies with longer follow-up periods, larger and more diverse populations are needed to validate and expand upon these findings.

Despite these limitations, our study offers several notable strengths. Importantly, this study focuses on healthy individuals, providing novel clinical data that complement prior research predominantly performed in animal models or diseased populations. To the best of our knowledge, this is the first study to provide multidisciplinary clinical evidence on microbiota changes in response to fiber-enriched kombucha in healthy individuals. By evaluating both microbial and symptom-level outcomes, this study advances the field by offering updated insights into the prebiotic potential of functional fermented beverages. Furthermore, the observed changes in microbiota composition may have broader implications for health.

Given the growing interest in gut microbiota modulation for the prevention and management of chronic diseases, further research is essential to evaluate the combined effects of probiotic kombucha and prebiotic inulin on gut health. To date, no human clinical trials have specifically examined this combination. Therefore, our study provides valuable insights into how targeted probiotic interventions can beneficially modulate the gut microbiota, emphasizing the importance of considering individual dietary contexts and the specific characteristics of probiotic products.

5. Conclusions

The present study provides preliminary evidence that short-term consumption of a fiber-enriched kombucha beverage may exert beneficial effects on lipid metabolism and gut microbiota composition in healthy adults. Notably, the intervention was associated with a reduction in serum triglyceride levels and significant shifts in gut microbiota profiles, including an increase in the relative abundance of Bifidobacterium and a decrease in Ruminococcus torques. These microbial changes, along with the observed modulation in beta diversity, support the synbiotic potential of the study product. While the results suggest that kombucha may modestly influence the gut microbiome and certain health markers, further research is necessary to fully understand its long-term effects, optimal consumption patterns, and mechanisms of action.

Given the promising nature of these findings, future research should aim to explore the potential of fiber-enriched kombucha as a dietary intervention across broader populations and clinical contexts. Overall, this synbiotic beverage demonstrates strong potential as a functional food with a dual impact on gut health and metabolic regulation.

CRediT authorship contribution statement

Beatriz Arce-López: wrote the paper, had primary responsability for final content and review and edit the reviewed manuscript. Guadalupe X. Bazan: conducted research. Susana Molina: conducted research. Maria Carmen Crespo: conducted research. María García-Beccaria: analyzed data. Silvia Cruz-Gil: conducted research. Cristina M. Fernández-Díaz: conductedd research. Ana Ramírez de Molina: designed research. Ricardo Ramos-Ruiz: designed research. Maria Isabel Espinosa-Salinas: designed research, had primary responsability for final content and review and edit the reviewed manuscript. All authors read and approved the final manuscript.

Informed consent statement

Informed consent was obtained from all subjects involved in the study.

Institutional review board statement

In accordance with the Ethical Principles outlined in the Declaration of Helsinki, all procedures involving human subjects in this study were conducted with utmost consideration for their welfare, rights and confidentiality. Volunteers were recruited by the Platform for Clinical Trials in Nutrition and Health (GENYAL) at IMDEA Food Institute (Madrid, Spain) with ethical approval from the Research Ethics Committee (IMD: PI-060).

Data availability

Data described in the manuscript is contained within the article or supplementary material.

Author disclosures

The authors declare no conflict of interest.

Funding

This study is promoted by the project grant IDI-20220532: “Functional improvement of fiber-enriched kombucha, validated using omics technologies” (R&D&I projects of the CDTI, an agency dependent on the Spanish Ministry of Science and Innovation). This work was supported by Komvida Kombucha, S.L. (Fregenal de la Sierra, Badajoz, Spain).

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: GENYAL Platform, IMDEA Food reports financial support was provided by Komvida Kombucha, S.L. (Fregenal de la Sierra, Badajoz, Spain). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Handling editor: Dr. Yeonhwa Park

Appendix A. Supplementary data

The following is/are the supplementary data to this article.

Data availability

Data will be made available on request.