What is inside the probiotic coconut-based yogurt?

The coconut-based yogurt is made from organic coconut meat and coconut water, fermented with 16 custom probiotic strains, including Lactobacillus acidophilus, Bifidobacterium breve, and Streptococcus thermophilus.

What health benefits does it claim to offer? Is it truly beneficial for health?

It is reported online that consuming this yogurt may improve digestion, reduce bloating, promote healthier skin, and strengthen the immune system. While probiotics can offer health benefits, scientific evidence specifically supporting this yogurt’s claim remains limited.

We know that coconut flesh is mainly composed of lipids and such yogurt provides very little protein. On top of that coconut oil is used as a cure for all sorts of ailments, such as fighting viruses and bacteria, supporting immunity, reducing cholesterol, supporting thyroid function, and even weight loss ^1-4.

Coconut oil contains medium-chain triglycerides (MCT) fatty acids, which are more easily digested and less absorbed compared to longer-chain fatty acids. However, of all the saturated fatty acids in coconut oil, MCTs constitute only half. Some MCTs, such as lauric acid and capric acid, have antifungal and antiviral properties ^1-3, but the purpose of consuming food is to provide components that strengthen the immune system, which then fights microbes ⁴.

How does it impact the gut microbiota?

This probiotic-enriched yogurt contains live bacteria that can potentially influence gut microbiota. However, the effectiveness of probiotics depends on various factors, including the specific strains used, their ability to survive stomach acid, and the individual’s existing gut microbiome composition.

Some studies suggest that mediumchain triglycerides (MCTs), found in coconut, may affect microbiome composition. However, research on probiotic coconut-based products is still in its early stages. Moreover, while coconut oil contains antimicrobial compounds like lauric acid (converted into monolaurin in the body), this does not necessarily translate into overall gut health benefits ^{1, 3}.

An interesting rat study investigating different dietary oils’ effects on gut microbiota found that coconut oil consumption led to reduced bacterial diversity, increased markers of metabolic endotoxemia, fatty liver disease, and higher LDL cholesterol levels ⁵. While animal studies provide insight, further clinical trials in humans are needed to determine this probiotic-enriched yogurt’s actual effects on gut health.

From your dietary perspective, are these new probiotic products worth considering?

Remember that food is primarily intended to provide us with nutrients, vitamins and minerals. Coconut dairy, like yogurt, does not have high nutritional density ^{1, 3}.

While this probiotic-rich yogurt presents an innovative approach to delivering beneficial bacteria, its high-fat content, low protein levels, and cost should be considered when recommending it as a dietary option ^{2, 6}. Traditional probiotic-rich foods, such as yogurt, kefir, and fermented vegetables, provide similar benefits with a more balanced nutritional profile. A varied and balanced diet, low in processed foods and rich in vegetables, fruits, whole grains, and legumes, supports microbiome diversity.

Transgender women: a specific neovaginal flora

Some transgender women correct the gender incongruity of feeling like a woman in the depth of their being despite the physical presence of male genitalia and being referred to as a man by undergoing “penile inversion vaginoplasty.” In other words, by surgically transforming their penis into a vagina. However successful the surgery, the skin of this newly constructed vagina will combine skin from the penis and a skin graft from the scrotum and/or other area (s) (stomach, groin, etc.). How does this affect health? Vaginal microbiota makes a crucial contribution to good vaginal health in cisgender women.

And American researchers have now turned their attention to the intimate flora of transgender women undergoing surgery: might the composition of neovaginal microbiota explain certain problems, including the frequently reported issue of vaginal discharge? It is a question worth asking, and one that has now been answered thanks to a study comparing the vaginal microbiota of transgender women undergoing vaginoplasty with that of cisgender women. The results? They have very different microbiota. The vaginal flora of cisgender women is not very diverse and is dominated largely by lactobacilli, which creates an acidic environment that repels pathogens. That of transgender women has less than 3% of these precious allies and is much more diverse. Diversity in the vagina is not a sign of good health; quite the opposite. It is observed in cisgender women suffering from bacterial vaginosis, which increases risk of sexually transmitted infections (including HIV/AIDS) and miscarriage.

How is this new microbial ecosystem created? Or more precisely, which bacteria make up the neovaginal microbiota of transgender women having undergone surgery? They result no doubt from the flora of the skin (penis, scrotum, etc.) used during surgery. However, oral-genital and genital-genital transmission also appears to be involved. In fact, the neovaginal flora of transgender women having undergone surgery has been shown to include bacterial species typical not only of the skin and digestive tract, but also of the mouth. Since sexual relations influence the likelihood of a bacterium called E. faecalis, there is also genital transfer.

On the other hand, while the proliferation of protective lactobacilli in cisgender women can be explained by hormones, the hormonal status of transgender women (comparable to that of cisgender women due to treatment) seemed to make no difference. Further studies on larger numbers of transgender women will be needed to better understand their neovaginal health.

^{Winston McPherson G, Goldstein Z, Salipante SJ, et al. The Vaginal Microbiome of Transgender and Gender Nonbinary Individuals. Transgend Health 2024; 9: 205-11.}

Gut microbiota regulates insomnia-like behaviors via gut-brain axis

While sleep is known to be in bidirectional connection with the gut microbiota, the underlying mechanisms have been largely unknown. However, it seems that gut-derived metabolites can affect some behaviors in the host, such as anxiety-like behavior. Additionally, some clinical studies have reported alterations in the gut microbiota in individuals with chronic insomnia.

Wang et al. sought to clarify how the gut microbiota could shape sleep behavior. For this purpose, they studied sleepwake behavior in specific pathogen-free (SPF) and germ-free (GF) mice. GF mice are free of all microorganisms, including those that are typically found
in the gut, while SPF mice are free of a specific list of pathogens by routine testing The recording of 24-h ambulatory electroencephalogram (EEG)-electromyogram (EMG) showed that GF mice had decreased time of wakefulness and REM sleep compared to SPF mice. To identify specific metabolites that are involved in gut microbiota-mediated sleep-related behavioral changes, the authors studied feces and hypothalamus tissue samples using targeted metabolomics. It was found that gut microbiota-derived short chain fatty acid, butyrate was the most significant modulator of sleep behavior. Further, oral administration of tributyrin, a precursor of butyrate administration led to a significant 39.50% reduction of wakefulness and 77.99% increase in REM sleep. The underlying mechanism seems to be that tributyrin inhibits lateral hypothalamus orexin neuron activity.

By studying humans, the authors also observed a decrease in 39 butyrate producers in insomnia patients compared with controls. Ultimately, the authors also showed that GF mice that received microbiota from insomnia patients exhibited sleep disturbances, which were recovered by butyrate supplementation. To conclude, the study highlights the potential of butyrate as a therapeutic agent to mitigate sleep disorders.

^{Wang Z, Wang Z, Lu T, et al. Gut microbiota regulate insomnia-like behaviors via gut-brain metabolic axis. Mol Psychiatry 2025; 30: 2597-611.}

Campylobacter jejuni-derived cytolethal distending toxin promotes colorectal cancer metastasis

Several pro-tumorigenic bacteria, such as genotoxic Escherichia coli (E. coli), and enterotoxigenic Bacteroides fragilis (B. fragilis), have been associated with the promotion of cancer metastasis. In addition, cytolethal distending toxin (CDT)-producing Campylobacter have been found to be enriched in tumor tissues compared to normal adjacent tissues. However, the connection between genotoxin-producing bacteria and cancer metastasis is poorly understood. The authors of this study obtained primary colorectal cancer (CRC) tissues from 34 chemotherapy-naive patients (TNM stage I and IIA) with distant metastasis within 3 years (metastasis group) and 37 patients who remained metastasis-free (non-metastasis group) during 3 years’ follow-up. They found a significant enrichment of Campylobacter in the metastasis group, and that the patients with intratumor Campylobacter had significantly poorer prognosis. They also confirmed their findings using a validation cohort and a publicly available database. CDT is the major virulence factor responsible for Campylobacter-mediated pathogenesis, and in the host cells it induces DNA damage and cell-cycle arrest. The metastasis group expressed more bioactive CDT subunit cdtB and Campylobacter invasion antigen B (ciaB), a virulence factor specific to C. jejuni. In vitro, C. jejuni significantly increased cell migration and invasion ability of various CRC cell lines. In one mice model, administration of C. jejuni increased migration and invasion ability as compared with controls, and in another it significantly increased liver metastasis. Altogether, these findings prove that intestinal C. jejuni promotes CRC metastasis. Interestingly, the pro-metastasis ability was attenuated in the absence of CdtB. Mechanistically, it seems that CDT activated JAK-STAT signaling pathway leading to expression of MMP genes and tumor metastasis.

^{He Z, Yu J, Gong J, et al. Campylobacter jejuniderived cytolethal distending toxin promotes colorectal cancer metastasis. Cell Host Microbe 2024; 32: 2080-91.}

Quiescent Crohn’s disease, sulfidogenic microbes and sulfur metabolic pathways: the functional consequences

In the quiescent inflammatory bowel disease, there is no active inflammation. However, the patients report persistent symptoms, especially with Crohn’s disease (CD). The microbiome is shown to be altered in quiescent CD patients with persistent symptoms (qCD + S). Specifically, the patients with qCD + S have been shown to have more sulfidogenic microbes and microbial gene pathways of sulfur metabolism. Nevertheless, the functional significance of these changes has remained unknown. In this multicenter observational study,
metagenomic shotgun sequencing and metabolomics profiling of the qCD + S patients’ feces were performed. Additionally, patient with active Crohn’s Disease (aCD), with quiescent Crohn’s disease without persistent GI symptoms (qCD-S) and with diarrhea predominant irritable bowel syndrome (IBS-D) were included and compared with qCD + S.

The authors report that fecal metabolites within cysteine/methionine, bile acid, and fatty acid pathways were among the most differentially abundant in qCD + S patients relative to other groups. The differences persisted even when inflammation, i.e., calprotectin levels were lower. Glycine, serine, and threonine; glutathione; and cysteine and methionine were the most enriched pathways in
qCD + S, and these are important sulfur metabolic pathways in the human gut. In addition to metabolites, many bacterial sulfur metabolic genes were dysregulated in qCD + S. By integrating the metagenomic and metabolomic datasets, the authors further found that taurine and hypotaurine; nicotinate and nicotinamide; cysteine and methionine; and glycine, serine, and threonine were the top metabolic pathways associated with the enriched microbes in qCD + S. AS elevated H2S concentrations inhibit mitochondrial
functions of the host, the results suggest links between microbial-derived metabolites and host mitochondrial function in patients with qCD + S. Altogether, the results of this study suggest that strategies to decrease sulfidogenic microbes and associated sulfur metabolic pathways could represent a novel strategy to improve quality of life in quiescent Crohn’s disease with persistent symptoms.

^{Golob J, Rao K, Berinstein JA, et al. Why Symptoms Linger in Quiescent Crohn’s Disease: Investigating the Impact of Sulfidogenic Microbes and Sulfur Metabolic Pathways. Inflamm Bowel Dis 2025; 31: 763-76.}

Mechanisms

Microbiota includes a wide variety of bacteria, viruses, fungi, and other microorganisms which have been found to be crucial for immunologic, hormonal, and metabolic homeostasis of their host. We often referred to it as a “hidden organ”.

When this ecosystem is disrupted (dysbiosis), it can contribute to a wide range of diseases - from gastrointestinal diseases to systemic metabolic and neurological disorders ¹.

At birth, the newborn’s gut is sterile, but it is rapidly colonized by microorganisms from the environment, including Enterobacteria, Enterococci, Lactobacilli, and Bifidobacteria. The gut microbiota undergoes dynamic and gradual changes from infancy to adulthood, shaped by various internal and external factors. These microbial shifts are critical for establishing a stable and resilient microbiome that supports health across the lifespan. In healthy adults, the gut microbiota is estimated to include over 1,000 species of bacteria. Importantly, this microbial community can influence drug pharmacodynamics by either directly metabolizing drugs or modifying the host’s metabolic and immune responses.

Orally administered drugs travel through the gastrointestinal (GI) tract, with their absorption and metabolism influenced at each stage. Drugs that are not completely absorbed in the upper GI tract may reach the colon. In turn, the gut microbiome actively participates in the chemical transformation of these drugs, affecting their pharmacokinetics, bioactivity, and potential toxicity.

Several mechanisms are involved by which drugs affect gut microbiota, including:

1 / direct effects (antibiotics can kill some species of microbiota, including both harmful and beneficial species, leading to imbalances
in gut microbiota);

2 / altered gut motility (particular drugs can slow down gut motility, which can lead to overgrowth of harmful bacteria);

3 / modulation of immune function (several drugs can interact with gut immunity which in turn can affect gut microbiota);

4 / changes in pH in the intestine (the pH balance plays a significant role in the gastrointestinal tract which affects the growth and survival of different types of species of gut microbiota. Some drugs can change the pH value of the gut, which affects the proliferation of different microbes, thereby affecting the overall composition of gut microbiota);

5 / interference with microbial metabolism (several drugs can interfere with microbial metabolism, which may have an effect on gut microbiota);

6 / dietary changes (certain drugs can change the dietary environment in the gut. This may influence gut microbiota by changing the availability of nutrients and other compounds that gut microbiota use to grow and survive) ^2-4.

Gut microbiome-drug interactions are shaped not only by microbial activity but also by host genetics, environmental exposures, and their interplay, posing a complex challenge for personalized therapy. Genome-wide association studies (GWAS) have identified human genetic variants, especially in genes related to immunity, metabolism, and digestion (e.g., C-type lectins and lactase) that influence gut microbiota composition.

The examples of irinotecan and cytochrome p450

Irinotecan, an anti-cancer medication, is reactivated in the gut by microbial enzymes causing severe diarrhea - a major side effect of the chemotherapy. Certain gut bacteria, particularly β-glucuronidase-producing species such as Escherichia coli, Clostridium and Bacteroides, produce enzymes that convert SN-38G back into its active form SN-38 in the intestine. This reactivation is toxic to intestinal
epithelial cells, causing mucosal injury, inflammation, and severe delayed-onset diarrhea ³.

The gut microbiome can profoundly influence the host’s drug-metabolizing enzymes, an emerging factor in personalized medicine. Cytochrome P450 enzymes, particularly CYP3A4, are modulated by gut-derived compounds. Short-chain fatty acids (SCFAs) can modulate enzyme gene expression through epigenetic mechanisms. Meanwhile, secondary bile acids interact with nuclear receptors like FXR, CAR, and PXR, altering drug metabolism ³.

Strategies for reducing the collateral damage of drugs on the microbiome ⁵

To protect the gut microbiome, one key strategy is to avoid drugs known to disrupt microbial balance whenever possible. Minimizing direct interaction between drugs and gut microbes can reduce negative effects. In contrast, restorative approaches aim to repair microbial communities after disruption. These include dietary interventions, probiotics, live biotherapeutic products, and fecal microbiota transplantation. Dietary interventions act as microbiota- targeted therapies. Dietary fibers, for instance, foster the growth of SCFA-producing bacteria, which are essential for immune function, epithelial development, and maintaining an anaerobic gut environment ⁵. Probiotics such as Saccharomyces boulardii CNCM I-745, Lactobacillus reuteri and Bifidobacterium spp. support colonization resistance, immune modulation, and gut barrier integrity. Postbiotics, composed of inactivated microbes or their components, also offer health benefits without requiring live organisms. Meanwhile, live biotherapeutic products represent a new category of medical interventions using live microbes specifically designed to treat or prevent disease, distinct from traditional supplements ³.

Restoring the microbial community involves more than simply recolonizing bacteria. It requires reestablishing a balanced ecosystem that supports immune, metabolic, and barrier functions. Strategies to protect the microbiome during drug therapy fall into two main categories: preventive approaches that minimize drug-induced disruption, and restorative approaches that aim to rebuild microbial diversity and function after damage has occurred ⁵.

Selecting the right strategy requires a precision-based approach, tailored to the drug, disease context, and patient. Success depends on a deep understanding of the ecological and biochemical principles that govern microbiota drug interactions. Ongoing research is essential to guide effective recovery and protection of the gut microbiome during and after drug therapy.

The dysbiotic gut in functional abdominal pain disorders in children

Functional abdominal pain disorders (FAPDs), also referred to as functional gastrointestinal disorders (FGIDs), represent the one of the main etiologies of chronic abdominal pain in the pediatric population that involve interplay among regulatory factors in the enteric and central nervous systems ¹. The ongoing classification system, ROME IV, distinguishes several pain-predominant FGIDs based on their recognizable patterns of symptoms, such as functional dyspepsia (FD), irritable bowel syndrome (IBS), abdominal migraine, and FAP-not otherwise specified (FAP-NOS) ². During the past two decades numerous studies researched possible causes and underlying mechanisms of appearance, but the clear pathophysiology is yet to be revealed, despite pediatric neurogastroenterology findings in terms of intestinal motility, signaling molecules, changes in microbiota or epigenetic mechanisms ³. Gut microbiota modifications, known as a dysbiotic gut, may play a role in functional abdominal pain disorders through gut immunity and integrity alteration ^{4, 5}. Several studies have reported a lower level of microbial diversity in patients with functional abdominal pain disorders ^{6, 7} and species such as Lactobacilli and Bifidobacteria are heavily altered ⁸. Thus, a growing body of clinical data have been gathered around using probiotics in functional disorders’ management, although study data are lacking on children ⁹.

Research insights

The analysis of microbiota in 18 patients with FGIDs provided data about intestinal dysbiosis at the moment of the diagnosis and its changes over a period of three months of treatment with specific strains of probiotics and prebiotics (figure 1).

Individuals. Age 4-14 years and diagnosed with functional abdominal pain disorders (functional dyspepsia and irritable bowel syndrome) according to ROME IV criteria.

Intervention. Six bacterial strains (Lactobacillus rhamnosus R0011, Lactobacillus casei R0215, Bifidobacterium lactis BI-04, Lactobacillus acidophilus La-14, Bifidobacterium longum BB536, Lactobacillus plantarum R1012) and 210 mg of fructo-oligosaccharides-inulin. One capsule was administered orally, daily, for 12 weeks, and the medication was provided by the healthcare practitioners.

Clinical outcome. The patients were scored for severity of abdominal discomfort, dyspepsia, flatulence, and epigastric pain on a ten-point ordinate (numerical rating) scale.

Fecal samples were collected from participants before and after treatment using a special laboratory kit with two sterile containers, which were then brought to the laboratory in conditions depending on the time spent from collection to laboratory delivery: if the interval was less than 24 hours, both containers were stored and transported in cooled conditions at 4 °C; if the period between stool elimination and laboratory delivery was more than 24 hours, one container was stored in a frozen condition at – 80 °C until analysis, and the other one was cooled at 4 °C. Stool samples were analyzed using the test Colonic dysbiosis-basic profile (SBY 1) performed by Synlab-Germany. Microbiota composition was expressed as number of colony forming units (CFU) for various aerobic/anaerobic bacterial and fungal species. The analysis provided data on fecal pH, IgA in μg/mL (normal ranges 510–2,040 μg/mL), lactoferine μg/ mL (normal ranges < 7.2), calprotectin in mg/kg (normal ranges < 50.0 negative, 50–99 intermediary, > 100 positive).

In the fecal microbial analysis, there was an increasing proportion of bacterial genera associated with health benefits (e.g., Bifidobacterium and Lactobacillus), for both IBS-C and IBS-D (IBS-C: 31.1 ± 16.7% vs. 47.7 ± 13.5%, p = 0.01; IBS-D: 35.8 ± 16.2% vs. 44.1 ± 15.1%, p = 0.01). On the other hand, genera of harmful bacteria, including Escherichia, Clostridium, and Klebsiella were proven to decrease after treatment (21.3 ± 16.9% vs. 16.3 ± 9.6%, p = 0.02).

No particularities were found in children with FD. At baseline, before any symbiotic intervention, Bifidobacterium profiles were significantly different between IBS-C and IBS-D (87.14 ± 23.19 vs. 71.37 ± 12.24; p = 0.02), with lower counts in IBS-D. The symbiotic administration had a significant effect on bacterial profiles from baseline to the end of treatment in both IBS-C and IBS-D groups (Table 1).

Practical consequences

The clinical symptoms in study population were more diminished after treatment, with statistical significance, suggesting that influencing gut dysbiosis might also reduce patients’ burden and improve clinical scores.

Overall, 14 (78%) patients reported treatment success (defined as no pain). The proportion of patients with adequate symptom relief was higher in the IBS-D than in the IBS-C group; however, the difference was not statistically significant (74.4% vs. 61.9%, p = 0.230). In both IBS-C and IBS-D groups, scores on the Bristol scale improved significantly after intervention (baseline vs. after treatment; 2.8 ± 0.6 vs. 3.9 ± 0.9, p = 0.03, 6.1 ± 0.9 vs. 4.1 ± 1.0, P = 0.01, respectively). Abdominal distension and flatulence were significantly improved in both IBS-C and IBS-D groups (IBS-C: 6.5 ± 2.8 vs. 3.7 ± 1.8, p = 0.01; IBS-D: 5.9 ± 2.2 vs. 2.9 ± 1.8, p = 0.01).

What do we already know about this subject

Childhood malnutrition is a major public health problem and one of the leading causes of death before the age of five. Moderate acute malnutrition (MAM) is associated with delayed neurocognitive development, but the link remains poorly understood. It is also associated with dysbiosis of the gut microbiota (GM), whose establishment is slowed and marked by enrichment in Bifidobacterium and Escherichia species. These disturbances in the gut microbiota could have an impact on cerebral development via the gut-brain axis, due to defective nutrient absorption or accumulation of toxic metabolites. This inter-organ communication could be mediated indirectly by plasma lipids, as lipids are the essential constituent of the brain and are modulated by MI metabolites  such as bile acids.

What are the main insights from this study?

The study was carried out in the Mirpur region of Bangladesh, and compared 159 children with MAM with 75 well-nourished controls at 12 months of age. MAM was defined by a weight/height ratio between -2 and -3 z-scores. The MAM group was significantly associated with social-demographic factors (toilet, mode of delivery and water treatment - kettle).

MAM was associated with decreased bacterial alpha diversity (Shannon), increased prevalence and abundance of Rothia mucilaginosa and Streptococcus salivarius (figure 1), and an increased Bacteroidetes/Firmicutes ratio. Functional analyses of the MI showed no differences.

The electroencephalogram (EEG) showed a significant decrease in beta (12-30 Hz) and gamma (30-45 Hz) frequencies in the temporal and frontal regions of children with MAM. Significant decreases in expressive communication, fine and gross motor scores, and vocalization were also observed.

After adjusting for mode of delivery, gender and duration of exclusive breastfeeding, MAM was associated with changes in plasma lipidome, with relative abundance increased by 128 (16%) compounds and decreased by 189 (24%) (figure 2).

Integration of multimodal data showed that the best predictors of MAM at 12 months were: 1) plasma lipids (AUROC = 0.95 0.05); 2) brain and behavioral measures (Wolke score, EEG, Bayley score) (AUROC = 0.73±0.05, 0.71±0.10, 0.68±0.07 respectively) ; 3) the taxonomic, functional and predicted metabolite profile of the fecal microbiome (AUROC = 0.56±0.07, 0.53±0.07, 0.52±0.06). Note the high proportion of data related to the fecal microbiome for predicting MAM in multimodal analysis, despite the poor performance of the fecal microbiome (figure 3).

Multimodal network analysis predicted that a cluster of B. fragilis, pyruvate fermentation pathways, plasma ceramides, EEG and expressive communication was strongly correlated with good nutritional status at 12 months. Finally, the strongest effect as an interspecies interaction was observed between R. mucilaginosa and S.salivarius, whose combined presence amplified the prediction of MAM at 12 months.

What are the consequences in practice?

This study shows the importance of GM in the nutritional status of infants. The presence of commensal gram-positive and facultative anaerobic oral bacteria such as R. mucilaginosa and S. salivarius may be responsible for deregulation of bile acids. This could lead to lipid changes that are important for brain development.

In addition, it is important to highlight the benefit of B. fragilis in relation to fermentation pathways on nutritional status at 12 months.

What do we already know about this subject?

Gut microbiome-based therapeutics (including probiotics, live biotherapeutic products, prebiotics/synbiotics and faecal transplantation) aim to restore a healthy microbiota, but with varying degrees of success depending on the population. To optimise these approaches, a consensual definition of a “healthy” microbiome would be needed - a challenging task due to the high degree of interindividual variability.
However, meta-analyses reveal taxa that are consistently depleted or enriched across multiple diseases, suggesting that microbes can be positioned along a spectrum of association with host health ^{2, 3}. High-ranking species on this scale would have the greatest potential: i) as direct therapeutic agents or targets for enrichment;ii) as markers of clinical efficacy. The authors therefore propose creating a priority index integrating three criteria: positive association with health, contribution to microbiota stability and strong community “interaction”. This index, which can be applied to large public datasets, would serve as a rational tool for selecting and evaluating future microbial therapeutic strategies.

What are the main insights from this study?

Using a discovery cohort comprising 39,926 gut microbiomes from 127 cohorts (including cross-sectional and longitudinal data, spanning 42 countries and 28 different diseases), the authors generated a ranking of 201 prevalent (core) gut microbiota taxa (those detected in ≥ 5% of samples in ≥ 50% of the studied cohorts), the HACK index (Health-Associated Core Keystone Index), each being assigned a score based on three quantifiable properties: i) prevalence/community association in non-diseased subjects; ii) temporal stability; and iii) negative association with disease.

The HACK index was calculated as the product of two scores: i) the mean of the association scores of a taxon for all the three properties; and ii) a reward score assessing the similarity (or how evenly distributed) these three scores were with respect to each other. Analysis of the highest- ranked taxa based on this order revealed 17 taxa having a HACK index of ≥ 75% (figure 1). These taxa all had individual scores of ≥ 70% for the three properties. These included Faecalibacterium prausnitzii, a well-recognised marker of microbiome health [4], followed by Bacteroides uniformis. The list also features several species from the genera Roseburia, Alistipes, and Eubacterium, as well as Coprococcus catus.

The authors then demonstrated the reproducibility of both the individual scores and the overall HACK index by recalculating the association scores within each cohort separately, using different sequencing methods (Shotgun or 16S) and across different type of populations (industrialised urban versus other), followed by an additional validation dataset composed of 14 additional cohorts totalling 5,498 microbiomes.

Beyond their stronger association with health and microbiota stability, some taxa with a high HACK index were also associated with favourable responses to various microbiota-related interventions, such as the Mediterranean diet or anti- cancer immunotherapy.

By analysing genome-level functional annotations from 32,005 genomes representing 122 of the 201 taxa, the authors identified 150 functional features (tags or fragments) specifically enriched and conserved in the genomes of taxa having high HACK indices. These represent a wide range of functions: production of butyrate/propionate with anti-inflammatory properties, synthesis of numerous vitamins, biosynthesis of neuroactive amino acids like tryptophan, and their beneficial anti-inflammatory derivatives such as indoles, or chondroitin sulphates. These are functionalities which warrant exploration to understand underlying mechanisms.

What are the consequences in practice?

The HACK indices were calculated from a global cohort of 45,000 gut microbiomes spanning the six major continents, making this one of the most comprehensive studies to date. These indices represent a step forward in the rational prioritisation of gut microbial species as potential candidates for microbiome based therapeutics. In addition, functionalities associated with high HACK indices may help identify pathways and metabolic capabilities linked to the general health and stability of the microbiome.

The vaginal microbiota (or vaginal flora) is in some ways the exception that proves the rule: it thrives when not diverse and is largely dominated by lactobacilli. When these bacteria predominate, they repel pathogenic microbes and with them the risk of vaginal infections such as bacterial vaginosis and vulvovaginal candidiasis.

But how can we make sure these beneficial vaginal lactobacilli predominate? Does our diet play a role? A study ¹ on 113 Italian students appears to confirm the impact of good and bad eating habits.

Bad habits to avoid

An increase in animal protein intake (mainly from red meat (sidenote: Red meat All mammalian muscle meat such as beef, veal, pork, lamb, mutton, horse, and goat, including that contained in processed foods and in most beefburgers. It does not include poultry or wild game, or offal. However, the definition may vary from country to country: in France, for example, “red meat” refers to beef, lamb, and horse meat, but not to pork or veal, which are considered white meats.

Sources: WHO WHO/IARC CIV (French meat information center) ) and processed meat (sidenote: Processed meat Meat that has been transformed through salting, curing, fermentation, smoking, or other processes to enhance flavor or improve preservation.
Most processed meats contain pork or beef, but processed meats may also contain other red meats, poultry, offal, or meat by-products such as blood.
Examples of processed meat include hot dogs (frankfurters), ham, sausages, corned beef, and biltong or beef jerky as well as canned meat and meat-based preparations and sauces.

Source: WHO
  ) ) goes hand in hand with a vaginal flora imbalance. According to the authors, this kind of diet could increase inflammatory markers or produce toxic compounds that raise vaginal pH, thereby promoting the growth of pathogenic bacteria. 

Alcohol consumption also appears to promote vaginal dysbiosis and boost pathogens such as Gardnerella and Atopobium, confirming the results of a French study which found that heavy drinking adversely affects the intimate flora of young women.

What explains this? Does alcohol have a direct effect on our bacteria, “intoxicating” our beneficial lactobacilli? Or does it alter our immune system, opening the door to the proliferation of unwanted bacteria? 

A few good habits to cultivate

The good news is that some dietary habits are beneficial to the vaginal flora.

• For example, an increased intake of alpha-linolenic acid, an anti-inflammatory omega-3 (sidenote: Omega-3 A family of essential fatty acids that includes alpha-linolenic acid (ALA), which is both essential in itself (our body cannot produce it, so it must be obtained from food) and a precursor to other omega-3s.
  From ALA, our body can synthesize other omega-3 fatty acids, such as the well-known EPA and DHA.
  However, the body’s rate of conversion of ALA to DHA is too low to meet our DHA requirements. Since DHA is also considered essential, it must also be obtained from food.
  
  Source: ANSES
    ) found in certain plant-based foods (nuts, rapeseed oil, walnut oil, linseed oil, etc.), appears to reduce the risk of vaginal flora dominated by L. iners (a lactobacillus less protective than others) and promote the beneficial L. crispatus. 
• Plant proteins (from legumes such as lentils, beans, etc.), fiber, and starch appear to keep the pathogen Gardnerella at bay. The authors believe that these nutrients boost the production of vaginal glycogen, the favorite food of lactobacilli, thus promoting their development. 

The gut microbiota acts as a metabolic organ, supporting digestion, immunity, and homeostasis ¹. Its interaction with drugs, however, is bidirectional: medications can disrupt microbial balance, while microbes can alter drug activity. This makes the microbiome a significant yet often overlooked factor in adverse drug reaction (ADR) risk ^{2, 3}. Gut microbial enzymes can transform drugs into more toxic forms, increasing tissue exposure and harmful effects. Growing evidence highlights microbial variability as a key driver of individual differences in drug response and ADRs ^{2, 4}. Integrating pharmacomicrobiomics into risk assessment alongside genetics and clinical data could help predict susceptibility to drug-related harm and guide personalized prevention strategies.

Drug-induced microbiota disruption: antibiotics and beyond

Antibiotics are well known to disrupt the gut microbiota by reducing diversity, altering composition, and promoting resistant strains (table 1) ^{5, 6}. Van Zyl et al. found that antibiotics especially quinolones and β-lactams consistently disrupt microbial communities across body sites, with combination regimens causing prolonged dysbiosis and increased pathogenic burden ⁵. Similarly, Maier et al. showed that different antibiotic classes have distinct effects on gut bacteria, with macrolides and tetracyclines causing sustained losses in anaerobes, and drugs like amoxicillin and ceftriaxone shifting populations toward Proteobacteria. Despite individual variability, a common trend emerged: depletion of obligate anaerobes (e.g., Firmicutes) and enrichment of facultative and potentially pathogenic microorganisms ⁶.

Beyond antibiotics, many non-antibiotic drugs including PPIs, metformin, NSAIDs, antipsychotics, and statins also alter the gut microbiota (figure 1, table 2) ^{7, 8}. Drugs influence the gut microbiota through various mechanisms direct antimicrobial action, altered pH, bile acid modulation, intestinal motility changes, and mucus secretion ⁹.

Gut microbiota modifies drugs metabolism

The gut microbiota can biotransform therapeutic drugs, altering their activity, efficacy, and toxicity (figure 2, table 3) ^12-14. Zimmermann et al. mapped microbial metabolism by screening 271 oral drugs against 76 gut bacterial strains, finding that 176 were metabolized by at least one strain. Notably, Bacteroides dorei and B. uniformis metabolized nearly 100 drugs. Over 40 microbial enzymes were identified,
mediating a wide range of reactions including reduction, hydrolysis, decarboxylation, dealkylation, and demethylation ¹².

Javdan et al. developed a personalized platform (MDM-Screen) to assess microbial drug metabolism using ex vivo microbiota from individual donors. Screening 575 drugs, they found that 13% were metabolized by gut microbes, including many previously unrecognized interactions. These transformations such as hydrolysis, reduction, and deacetylation can activate, inactivate, or increase drug toxicity. The study also revealed significant inter-individual variability and identified key microbial genes (e.g., uridine phosphorylase, β-glucuronidase) linked to specific metabolic pathways ¹⁵.

The efficacy of some drugs may depend more on the microbiota composition than on the host genetics.

Clinical consequences: toward personalized medicine

Microbiota-drug interactions have major clinical implications, as individual differences in gut microbiota may explain variability in drug response and side effects. Importantly, it is not just microbiota composition but also its functional stability that influences treatment outcomes.

These insights underscore the need to integrate both human and microbial genomics into pharmacological assessments. In drug development, simulating microbiota–drug interactions in silico has become key. Dodd and Cane proposed a detailed framework combining in vitro systems (e.g., strain libraries, stool-derived communities), genetic tools (gain/loss-offunction assays), and metagenomics to identify microbial genes involved in drug metabolism. Gnotobiotic mouse models further help disentangle microbial from host effects on pharmacokinetics.

As this field advances, microbiota-informed prescribing is emerging as a way to tailor treatments and reduce adverse effects. In the future, pharmacomicrobiomics could guide drug choices and dosages based on microbial biomarkers, enabling truly personalized medicine ¹⁷.

Personalizing treatment could one day require a microbiota fingerprint.

Preserving and restoring the microbiota: a therapeutic frontier

Protecting the gut microbiota during drug therapy is a promising strategy to reduce ADRs and preserve efficacy. While probiotics and prebiotics show some benefit against drug-induced dysbiosis, their effectiveness varies. Targeted probiotics tailored to specific drug effects, and fecal microbiota transplantation (FMT), particularly for recurrent C. difficile infection, offer more reliable options.

Precision tools such as microbial enzyme inhibitors (e.g., β-glucuronidase blockers for irinotecan toxicity), bioengineered probiotics,
microbiota-sparing drug designs, and diet-based interventions are under investigation. Clinical trials are exploring synbiotics customized to drug regimens to improve outcomes with minimal microbiota disruption. Postbiotics like butyrate are also being evaluated for anti-inflammatory and gut barrier-supporting effects.

Integrating microbiota-targeted strategies into pharmacology will require advanced tools multi-omics, machine learning, and systems microbiome modeling to predict and manage microbiota–drug interactions effectively.

Manipulating the gut microbiota may enhance treatment success and reduce complications.