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.

PFAS (sidenote: PFAS (per- and polyfluoroalkyl substances) Large group of chemicals, also referred to as ‘forever chemicals’, consisting of a more or less long or branched carbon chain and containing at least one fluorinated group. Their extreme persistence in the environment has been understood for a long time. However, other properties of these compounds that are displayed by certain subgroups of PFAS, are concerning: 

- potential for bioaccumulation in living organisms; 
- high mobility in water, soil and air;
- long-range transport potential; and
- (eco)toxicological effects that impact humans and the environment.


Sources: 
European Environment Agency: PFAS Pollution in European Waters
Gaillard L, Bernal K, Coumoul X et al. Forever pollutants and human contamination: State of art and challenges around per- and polyfluoroalkyl substances (PFASs).Cah Nut & Diet. 2024. Dec (59);6:349-361. ) , or “forever chemicals,” are widely found in everyday objects (fire-resistant materials in our furniture, non-stick pans, etc.), and today they’re turning up in the environment, in our food... and apparently in the bacteria of our gut microbiota. At least, that’s what a study ¹ has demonstrated for the first time in mice that were fed 42 PFAS commonly found in our diet. 

More or less bioaccumulating bacteria

Result: several of their gut bacteria massively bioaccumulate certain PFAS. Their surprising favorites: large-sized PFAS.

Among the 89 bacterial strains studied, 38 turned out to be formidable PFAS “vacuum cleaners,” particularly those belonging to the Bacteroidota family. Even at very low doses, PFAS are absorbed in just 3 minutes and accumulate within the bacteria at concentrations up to 50 times higher than in the bacteria’s surrounding environment.

No harm done!

As surprising as it may seem, despite their toxicity and their “soapy” effect (PFAS are known and used for their surfactant properties), PFAS appear to have little impact on the functioning of gut bacteria.

They accumulate inside these microorganisms in the form of compact clusters, which, according to the authors, may limit their toxicity. 
Even better, the bacteria seem to adapt: after about a hundred generations, the descendants of Bacteroides uniformis or E. coli grow faster than their predecessors, despite the continued presence of PFAS which they continue to trap efficiently.
Even though the bacteria survive well, some changes are nevertheless observed in their functioning in response to this stress, although, at this stage, it is not yet possible to assess the consequences for the microbiota or the host. 

PFAS eliminated through stool

But above all – and this is the study’s major discovery – the bacteria that trap PFAS facilitate their natural elimination. In mice transplanted with human gut microbiota, PFAS were found in greater amounts in their droppings than in mice without microbiota. And the greater the bioaccumulation potential of the bacteria in the digestive system, the more significant this elimination becomes.

The gut microbiota is a major regulator of responses to immune checkpoint inhibitors (sidenote: Immune checkpoint inhibitors (ICIs) Therapies that seek to remove the mechanisms that inhibit the immune system’s response to cancer cells. Targeted checkpoints include Programmed Death-1 (PD-1), Programmed Death-Ligand 1 (PDL-1), and cytotoxic T-lymphocyte associated protein 4 (CTLA-4). Lifting these brakes allows the immune system to recognize and attack cancer cells.
  ) in several cancers, including melanoma and non-small-cell lung cancer (NSCLC). However, the impact of dietary factors such as sweeteners remains poorly understood. For example, sucralose is a widely consumed sweetener known to alter the microbiota. Does it play a role? To answer this question, researchers studied the link between consumption of this sweetener and the effectiveness of anti-PD-1 treatments.

Diminished outlook among sweetener users

The analysis involved three patient cohorts: 91 patients with advanced melanoma, 41 with advanced NSCLC, and 25 with high-risk resectable melanoma, all treated with anti-PD-1 immunotherapy.

High sucralose consumption (> 0.16 mg/kg/day) is associated with poorer clinical outcomes:

• in advanced melanoma, median progression-free survival (PFS) decreases from 13 to 8 months
• in NSCLC, it falls from 18 to 7 months, with a lower treatment response rate (12% vs. 49%)
• in resectable melanoma, treatment response is lower, as is relapse-free survival (19 vs. 25 months).

Similar trends were observed with another sweetener, acesulfame, but not with aspartame or saccharin.

Underlying mechanisms involving T cells

Murine models have confirmed these findings and made it possible to explore the underlying mechanisms. Sucralose consumption leads to resistance to anti-PD-1 immunotherapy and significantly increased tumor growth, whereas sucrose (table sugar) consumption has no effect. The mechanisms appear to involve T cells: sucralose consumption has deleterious effects on several T cell processes (proliferation, cytotoxic function, metabolism). These effects do not appear to be limited to cancer alone, but instead may affect various diseases, from cancer to seasonal viral infections.
 

The gut microbiota, necessary and sufficient

The effect of sucralose depends entirely on the gut microbiota: fecal microbiota transplants (FMT) from mice that consume sucralose are sufficient to reduce the effectiveness of immunotherapy in naive mice. Conversely, an FMT from mice that respond to treatment restores the effectiveness of immunotherapy in mice that consume sucralose.

PFAS¹, also known as “forever chemicals,” have invaded our daily lives: fire-retardant foams in our sofas, waterproof clothing, non-stick pans, and more. Yet interactions between certain PFAS accumulating in the environment and bacteria have already been documented: some strains of Pseudomonas, isolated from sites contaminated with PFAS, bioaccumulate a sulfur-containing PFAS, while certain lactobacilli ‘bio-bind’ with another PFAS. How does the gut microbiota, the key interface between dietary exposure to these substances and our body, come into play? This question is explored in studies released in Nature Microbiology in 2025.
 

Strong and rapid bioaccumulation

By testing 89 microbial strains, researchers found that PFAS bioaccumulation capacity varies greatly from one bacterium to another: 38 strains, including bacteria belonging to the Bacteroidota phylum, showed particularly high bioaccumulation ability, even at low PFAS concentrations. The process proved to be very fast (just a few minutes), irreversible (no release) and highly efficient: the intracellular PFAS concentration in bacteria is about 50 times higher than that of the medium, reaching the millimolar range. The longer the PFAS molecule, the more strongly it is bioaccumulated by the bacterium.

Little impact on bacterial function

Surprisingly, bioaccumulated PFAS have little effect on bacterial life: their physicochemical properties cause them to aggregate into dense intracellular clusters, limiting their cellular toxicity and effects. Bacteria even appear to adapt over generations: the 100th generation of B. uniformis and E. coli ΔtolC grows faster than their ancestors in the presence of PFAS while maintaining their bioaccumulation capacities.

Although it does not compromise bacterial viability, bioaccumulation nonetheless induces certain changes, particularly in the most accumulative strains: alterations are observed in membrane proteins (particularly efflux pumps responsible for excreting toxins) and in the secretion of amino acids involved in the gut–brain axis or stress response.

PFAS excreted in stool

Finally, the presence of bioaccumulating bacteria in the intestine increases the elimination of PFAS: the stool of mice carrying human microbiota is significantly richer in PFAS than that of mice without microbiota. And PFAS excretion is all the more effective when intestinal flora bacteria are strong bioaccumulators. For now, however, the authors are not drawing any conclusions about possible health benefits.

Every parent knows the cascade of events: a simple cough and runny nose can quickly progress into a full-blown ear infection, or worse, bronchiolitis. We’ve long blamed the virus, but a critical new study in Nature Communications ¹ reveals that the virus is often just the opening act. The real drama unfolds within your baby’s ENT microbiota (sidenote: ENT Microbiota This refers to the specific community of microorganisms (bacteria, fungi, viruses) that reside in the interconnected regions of the ear, nose, and throat. This ecosystem is distinct from the gut microbiota and plays a crucial, direct role in local immunity and respiratory health. ) , the complex community of bacteria in the nose and throat that serves as the frontline of the immune system. This research provides a new framework for understanding respiratory health during the crucial first year of life.

The viral trigger for bacterial colonization

Researchers followed 300 infants from birth, meticulously tracking their health and analyzing over 2,400 nasal samples. The data reveals a clear mechanism: a viral infection, whether from a common Rhinovirus or Respiratory Syncytial Virus (RSV), profoundly alters the landscape of the respiratory system.

The presence of a virus was shown to increase the odds of infant bacterial colonization (sidenote: Bacterial Colonization This is the persistent presence and growth of bacteria on a host surface, such as the nasal passages, without causing clinical signs of disease. It is a necessary prerequisite for infection but is distinct from it, representing an asymptomatic carrier state. ) with Haemophilus influenzae by 44% and Streptococcus pneumoniae by a striking 83%.

For infants already carrying S. pneumoniae, a viral infection amplified its density (sidenote: Colonization Density This is a quantitative measure of the bacterial load, or the number of a specific bacterium present in a sample, rather than a simple presence/absence result. High colonization density can increase the risk of a pathogen transitioning from a harmless colonizer to an active infection. ) nearly four-fold, creating a high-risk environment for invasive disease.

Here is the most significant insight from the study. The virus doesn’t just help harmful bacteria; it actively sabotages the beneficial microbes that keep them in check.

The analysis identified specific protective species, like Corynebacterium, that normally prevent pathogens from gaining a foothold. The data showed that a viral infection leads to a direct loss of these beneficial bacteria. It is this depletion that opens the door for pathogens to colonize.

In a counterintuitive twist, the same viral infections were associated with a 55% lower odds of acquiring Staphylococcus aureus, revealing just how specific and complex these microbial interactions are.