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At least 19 recordsLinked to original sources

PubMed2026

Mikania micrantha invasion restructures rhizosphere nitrogen cycling through enzyme activation, microbial recruitment, and allelopathic regulation.

BACKGROUND: Plant invasions profoundly influence terrestrial ecosystems by reshaping nutrient cycling processes. However, the mechanisms through which invasive plants such as Mikania micrantha modulate soil nitrogen (N) cycling and microbial communities remain insufficiently explored. Moreover, comparative studies with indigenous congener are scarce, limiting insights into whether such effects reflect species-specific strategies or genus-wide traits. This study investigates how M. micrantha modulates nitrogen metabolic pathways and rhizosphere microecology using combined metagenomic and metabolomic analyses. RESULTS: Integrated analyses revealed that M. micrantha established a distinctive "high total nitrogen-low mineral nitrogen" profile in the rhizosphere soil. Metagenomic profiling showed consistent enrichment of key ammonium assimilation enzymes, including glutamine synthetase and glutamate dehydrogenase, promoting enhanced incorporation of NH₄⁺ into organic nitrogen pools. In contrast, genes encoding nitrate reductase and nitrate transporters were significantly lower in relative abundance, limiting nitrate assimilation. Mikania micrantha also selectively enriched nitrogen-fixing microbes (notably rhizobia genera) and plant growth-promoting rhizobacteria (PGPR), thereby enhancing biological nitrogen fixation capacity. Metabolomic analysis further identified several allelopathic compounds in invaded soils at higher relative abundance, particularly epicatechin, which exhibited inhibitory effects on nitrifying bacteria. Compared with the congener Mikania cordata, which exerted weaker impacts on soil nitrogen cycling and microbial assembly, M. micrantha deployed a more comprehensive strategy integrating biochemical, microbial, and metabolic regulation. CONCLUSIONS: These findings demonstrate that under greenhouse-controlled conditions, M. micrantha reconfigures rhizosphere nitrogen cycling through a multi-dimensional strategy that couples biochemical regulation, microbial recruitment, and metabolite-mediated interference, thereby suggesting a potential mechanism that may contribute to its ecological advantage in natural settings. Video Abstract.

Rhizosphere↗

PubMed2025

Concurrent stimulation of diflufenican biodegradation and changes in the active microbiome in gravel revealed by Total RNA.

The use of slowly degraded pesticides poses a particular problem when these are applied to urban areas such as gravel paths. The urban gravel provides an environment very different from agricultural soils; i.e., it is both lower in carbon and microbial activity. We, therefore, endeavored to stimulate the degradation of the pesticide diflufenican added to urban gravel microcosms amended with dry alfalfa to increase microbial activity. In the present study, alfalfa addition significantly increased the formation of diflufenican's primary metabolite, 2-[3-(trifluoromethyl)phenoxy]nicotinic acid (AE-B), indicating stimulated biotransformation. The concurrent changes of the active microbial communities within the gravel were explored using shotgun metatranscriptomic sequencing of ribosomal RNA and messenger RNA. Although bacterial taxa remained dominant (87.0%-98.5% relative abundance), the alfalfa treatment led to a 4-5-fold increase in eukaryotic groups, including fungi and microbial grazers. Several microbial taxa potentially involved in the degradation of complex carbon compounds and aromatic pollutants-including Bacteroidetes, Verrucomicrobia, Sordariomycetes, Mortierellales, Tremellales, Sphingopyxis, and Phenylobacterium-increased in relative abundance following alfalfa amendment. Functional gene profiling revealed elevated expression of genes related to microbial activity and biomass production. Genes with potential roles in the breakdown of complex carbon structures (e.g., xylanases/chitin deacetylases) and in the transformation of aromatic compounds (e.g., ring-cleaving dioxygenases) were revealed. We conclude that complex carbon amendments can enhance the microbial activity, promoting the biotransformation of diflufenican in urban gravel environments. These findings provide new insights into the interactions between microbial community dynamics, gene expression profiles, and pesticide biotransformation in non-agricultural matrices.IMPORTANCEPesticides used on urban areas, e.g., gravel paths, are likely to have different effects and fates than when these are used on agricultural soils. Hence, studies into the degradation of pesticides applied to urban matrices are needed. We have previously shown that metabolites of the persistent pesticide diflufenican are even more persistent in urban soils, and it has also previously been shown that these metabolites leach from gravel surfaces. The reasons behind this are that the urban gravel provides an environment very different from agricultural soils; i.e., it is both lower in carbon and microbial activity. In the present study, we, therefore, endeavored to stimulate the degradation of the pesticide diflufenican added to urban gravel microcosms amended with dry alfalfa to increase microbial activity, concurrently studying the changes in the active microbiome by Total RNA-metatranscriptomics.

Biodegradation, Environmental↗

PubMed2026

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea↗

PubMed2026

Do Multi-Omics Approaches Improve the Diagnosis of Microbial Overgrowth Syndromes?

PURPOSE OF REVIEW: This review investigates how advances in breath testing (BT), small bowel (SB) culture, metagenomics, metatranscriptomics, transcriptomics and proteomics are reshaping the definition and diagnosis of small intestinal bacterial overgrowth (SIBO). It also discusses whether SIBO should be redefined as part of a larger group of microbial overgrowth syndromes. RECENT FINDINGS: Recent studies identify distinct hydrogen-, methane-, and hydrogen sulfide-associated overgrowth phenotypes, termed SIBO, intestinal methanogen overgrowth (IMO), and intestinal sulfide overproduction (ISO). SB sampling shows that these conditions involve different microbial patterns and functional activity, symptoms, and host responses. Quantitative shotgun metagenomics provides greater taxonomic and functional resolution than culture, while metatranscriptomics reveals active microbial pathways. On top of that, host transcriptomics and proteomics contribute to the better understanding of the predominant microbial effects in host cellular mechanisms in each of the distinct small bowel overgrowth types. SIBO has been increasingly identified as a disorder of microbial ecology and function rather than bacterial quantity alone. Integrating BT with SB sampling and multi-omics approaches may improve classification, clarify symptom mechanisms, and support a more individualized treatment, although standardized methods and further clinical validation remain necessary.

Humans↗

PubMed2025

Metabolism and gene expression models for the microbiome reveal how diet and metabolic dysbiosis impact disease.

The gut microbiome plays a critical role in human health, spurring extensive research using multi-omic technologies. Although these tools offer valuable insights, they often fall short in capturing the complexity of microbial interactions that associate with disease onset, progression, and treatment. Thus, integration of multi-omics datasets with metabolic models is needed to predict associations between microbial activity and disease. Here, we automated the reconstruction of 495 metabolic and gene expression models (ME-models), overcoming the main limitation preventing the wide use of this approach. We integrated them with multi-omics data from patients with inflammatory bowel disease (IBD), identifying taxa associated with variations in amino acids, short-chain fatty acids, and pH in the gut of IBD patients. In general, this approach provides testable hypotheses of the metabolic activity of the gut microbiota, and the automated pipeline opens the opportunity to study microbial interactions in other biologically relevant settings using ME-models.

Humans↗

PubMed2025

Impact of RNA extraction on respiratory microbiome analysis using third-generation sequencing.

BACKGROUND: The respiratory microbiome, which comprises bacteria, fungi, and viruses, plays a crucial role in respiratory health and disease. However, its study is limited by the low microbial biomass in respiratory samples and the dominance of host RNA. Metatranscriptomics offers comprehensive insights into active microbial communities and their interactions with the host but requires optimized RNA extraction protocols for robust and unbiased analysis. This study evaluated two RNA extraction kits—one employing chemical lysis (CL) and another combining chemical and mechanical lysis (CML)—to determine their effectiveness for metatranscriptomic analysis of respiratory samples. RESULTS: The CML protocol significantly increased double-stranded DNA (dsDNA) library yields, leading to higher sequencing read counts for both sample types (p < 0.0001). The read length was unaffected by the lysis protocol for the BAL and NPS samples. Taxonomic profiling revealed that CML enhanced the detection of robust microorganisms, such as gram-positive bacteria and fungi, without compromising viral detection. CONCLUSIONS: The CML protocol demonstrated superior recovery of genetic material, particularly for fungi and gram-positive bacteria, making it better suited for comprehensive metatranscriptomic analyses. These findings underscore the need for tailored RNA extraction strategies on the basis of sample type and research objectives. Optimized metatranscriptomic protocols are pivotal for advancing our understanding of the respiratory microbiome and its role in health and disease.

Microbiota↗

PubMed2025

Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data.

MOTIVATION: Taxonomic analysis of environmental microbial communities is now routinely performed thanks to advances in DNA sequencing. Determining the role of these communities in global biogeochemical cycles requires the identification of their metabolic functions, such as hydrogen oxidation, sulfur reduction, and carbon fixation. These functions can be directly inferred from metagenomics data, but in many environmental applications metabarcoding is still the method of choice. The reconstruction of metabolic functions from metabarcoding data and their integration into coarse-grained representations of biogeochemical cycles remains a difficult bioinformatics problem today. RESULTS: We developed a pipeline, called Tabigecy, which exploits taxonomic affiliations to predict metabolic functions constituting biogeochemical cycles. In a first step, Tabigecy uses the tool EsMeCaTa to predict consensus proteomes from input affiliations. To optimize this process, we generated a precomputed database containing information about 2404 taxa from UniProt. The consensus proteomes are searched using bigecyhmm, a newly developed Python package relying on Hidden Markov Models to identify key enzymes involved in metabolic function of biogeochemical cycles. The metabolic functions are then projected on coarse-grained representation of the cycles. We applied Tabigecy to two salt cavern datasets and validated its predictions with microbial activity and hydrochemistry measurements performed on the samples. The results highlight the utility of the approach to investigate the impact of microbial communities on biogeochemical processes. AVAILABILITY AND IMPLEMENTATION: The Tabigecy pipeline is available at https://github.com/ArnaudBelcour/tabigecy. The Python package bigecyhmm and the precomputed EsMeCaTa database are also separately available at https://github.com/ArnaudBelcour/bigecyhmm and https://doi.org/10.5281/zenodo.13354073, respectively.

Metagenomics↗

PubMed2025

Nutritional modulation of host physiology, behavior, and gut microbiome in the captive rodent Octodon degus.

Diet is a key determinant of health by affecting nutrient metabolism, energy balance, body weight regulation, and mental health. The gut-brain axis is a critical pathway through which dietary factors influence cognitive function and behavior via microbial metabolites. While this relationship has been extensively studied in traditional laboratory models, diet-microbiome-cognition interactions remain largely unexplored in Octodon degus, an emerging model for aging, neurodegeneration, and cognitive research. Here, we compared two widely used rodent diets-LabDiet and Champion-to evaluate their effects on digestive efficiency, behavior, and gut microbiome composition. We also examined the relationships between these variables using piecewise structural equation modeling (pSEM). Our results indicated that LabDiet-fed degus exhibited enhanced nutrient absorption, higher fecal acetic acid levels, and a higher abundance of Actinobacteria (particularly Bifidobacterium), likely driven by its vitamin C supplementation. These animals also showed improved working memory and social motivation, but they displayed increased anxiety-like behavior. In contrast, Champion-fed degus, which consumed a more fiber-diverse, plant-based diet, showed lower anxiety traits and significantly greater gut microbial richness, with higher abundance of Bacteroidota and Tenericutes. Innate behaviors, such as burrowing and nesting, remained unaffected by the diet. SEM analysis revealed that diet explained most of the variance in microbial activity and identified a positive association between acetic acid levels and cognitive performance. This emphasizes a strong relationship among diet, microbiome, and brain function. Overall, our results suggest that dietary composition is a key factor influencing experimental outcomes in degus, with important implications for physiology, cognition, and microbial ecology. Standardizing dietary inputs is essential to ensure reproducibility in behavioral and biomedical studies using this model. Additionally, our results reinforce the microbiome's role as a mediator of diet-driven brain function via SCFAs, underscoring degus as a powerful system for investigating diet-microbiome-neurobehavioral interactions relevant to aging and mental health.

Animals↗

PubMed2026

Reduced legacy precipitation decreases microbial community growth efficiency and alters soil organic carbon in a California grassland.

BACKGROUND: Changes in global patterns can leave a lasting legacy in semiarid grasslands by reshaping microbial growth dynamics and carbon cycling during the first wet-up in the autumn-a period known for intense microbial activity and significant carbon emissions. To study the lasting impacts of decreased winter rain, we implemented two precipitation regimes (100% vs. 50% mean annual precipitation) in California Mediterranean-climate grassland field plots. After the dry season, soils were rewetted in the laboratory with H218O and sampled at 0 h, 3 h, 24 h, 48 h, 72 h, and 168 h post rewet. We quantified CO2 efflux, measured microbial growth and mortality via quantitative 18O stable isotope probing and 16S rRNA gene amplicon sequencing, and characterized the soil organic carbon chemical composition, metagenomes, and metatranscriptomes. RESULTS: We found that reduced winter precipitation imposed a strong legacy effect on microbial turnover; despite maintaining similar respiration rates, microbial growth declined by ~1 order of magnitude, yielding decreased community growth efficiency (CGE = new biomass growth/respiration), and microbial mortality declined by ~2 orders of magnitude. Soil organic carbon also shifted from lipid-like, amino-sugar-like, and protein-like compounds (indicative of microbial necromass) to more oxidized lignin-like and tannin-like compounds (indicative of decomposing plant-derived compounds). Meta-omics revealed distinct metabolic strategies linked to CGE. At high-CGE, microbes appeared to consume more energetically favorable N-rich necromass (released via high microbial turnover); this allowed for increased amino acids and peptidoglycan biosynthesis and greater aromatic compound degradation, fueling further energy production and growth efficiency. At low CGE, communities had elevated carbohydrate metabolism and lipid turnover, consistent with increased investment in plant detritus degradation and membrane repair and maintenance rather than growth. CONCLUSIONS: Together, our findings demonstrate that reduced winter rainfall decreases microbial turnover following rewetting without a concurrent reduction in CO2 emissions. This shift results in persistently lower CGE, which has the potential to increase soil carbon loss as CO2. If such conditions are maintained over multiple years, these changes could reshape soil organic carbon stocks and alter the balance of grassland ecosystems under future climate scenarios. While our data suggest that sustained reductions in CGE may drive SOC decline, the magnitude and persistence of these effects depend on long-term environmental dynamics and warrant further investigation. Video Abstract.

Soil Microbiology↗

PubMed2026

Human DNA levels in feces reflect gut inflammation and associate with presence of gut species in IBD patients across the age spectrum.

BACKGROUND: Feces represent a complex biological matrix that provides valuable information about intestinal physiology and gut microbial activity. Comprehensive fecal DNA sequencing is mostly utilized as a non-invasive way to profile the gut microbiome, and both clinical practice and research on inflammatory bowel diseases (IBD) would greatly benefit from accurate and non-invasive methods to monitor gut inflammation in IBD patients. In IBD, excessive immune cell recruitment and epithelial cell shedding in the gut increase the amount of human DNA in feces, making fecal DNA profiling a desirable approach to monitor gut inflammation dynamics. METHODS: We used a combination of sequencing techniques to comprehensively characterize the fecal DNA diversity in a newly established cohort of pediatric IBD patients and controls (Pediatric cohort, N = 134 children, Israel). We performed methylation-based human cell-specific profiling together with shotgun metagenomics to characterize the human and the microbial DNA content in feces, respectively. Moreover, we included a large complementary external cohort including adult IBD patients and controls (Adult cohort, N = 689 adults, the Netherlands), not only to compare microbial patterns across the age spectrum, but also to extend our findings from the methylation-based profiling to the more broadly-available quantification of human DNA in metagenomic sequencing. RESULTS: We found that neutrophil DNA dominates fecal human DNA content in IBD patients, and our measurements were highly correlated with fecal calprotectin levels. Combining neutrophil and other cell type DNA fractions in one metric was able to distinguish between remissive and active cases of IBD. Human reads percentage by metagenomics was well correlated with disease severity and species richness, which had distinct trends in CD and UC over time. We used a combination of species richness, human DNA percentage, and microbiome composition data to predict IBD and distinguish CD from UC in both adult and pediatric IBD cohorts. CONCLUSIONS: The comprehensive characterization of human and microbiome fecal DNA is a useful approach to track immune response level and investigate the interaction that the immune system has with gut microbiome richness and composition over time, enriching opportunities for better disease monitoring and thus better treatment of IBD patients. Video Abstract.

Humans↗

PubMed2026

Gut microbial diversity at baseline conditions the clinical, microbiome, and metabolic response to paraprobiotic Lactiplantibacillus plantarum LRCC5282 in overweight adults.

The gut microbiota is increasingly recognized as a target for obesity management; however, whether baseline gut microbial diversity conditions responsiveness to microbiota-targeted interventions remains unclear. We aimed to investigate whether baseline gut microbial diversity is associated with responsiveness to a paraprobiotic derived from Lactiplantibacillus plantarum LRCC5282 (LP5282-P) in overweight adults. In a 12-week, randomized, double-blind, placebo-controlled, multicenter trial of 120 overweight adults, LP5282-P produced no significant between-group differences in any clinical outcome across the overall per-protocol population. However, in the low-diversity subgroup, LP5282-P was associated with significant reductions in body weight, body mass index, and circulating leptin levels. These clinical changes were accompanied by compositional shifts in the gut microbiota, including higher relative abundances of Christensenellaceae, Faecalibacterium, and Alistipes. Fecal metabolite profiles showed elevated acetate and butyrate concentrations and altered bile acid composition. Within the low-diversity subgroup, changes in the relative abundances of Akkermansia and Eubacterium were inversely correlated with changes in body weight, body fat mass, and leptin levels. In contrast, the high-diversity subgroup exhibited no consistent response across the outcome domains examined. Overall, baseline gut microbial diversity was associated with differential responsiveness to LP5282-P, supporting its potential use as a stratification variable in future microbiota-targeted intervention trials. Further studies integrating direct measures of microbial activity and host response are warranted to elucidate the biological pathways underlying this diversity-dependent responsiveness. Trial registration: Clinical Research Information Service (CRIS), KCT0008119.

Humans↗

PubMed2026

Proteomic profiling of bone for the estimation of post-mortem interval and post-mortem submersion interval: a systematic review.

Accurate estimation of the Post-Mortem Interval (PMI) and Post-Mortem Submersion Interval (PMSI) remains a persistent challenge in forensic science, especially when traditional morphological and entomological methods fail due to advanced decomposition or in aquatic environments. Proteomic profiling of bone tissues has recently emerged as a promising approach, leveraging the predictable degradation patterns of bone proteins to estimate time since death more reliably. This systematic review, conducted in accordance with PRISMA guidelines, analyzed 24 peer-reviewed studies focusing on the application of proteomic techniques to bone tissue for PMI and PMSI estimation. The included studies were evaluated based on sample type, analytical techniques used, identified biomarkers, environmental conditions assessed, and the overall reliability and reproducibility of the findings. The review found that specific bone proteins, particularly collagen, osteocalcin, fetuin-A, etc. exhibited consistent degradation patterns that correlated strongly with elapsed post-mortem time. Cortical bone was identified as a more stable and informative matrix compared to trabecular bone. Mass spectrometry, especially LC-MS/MS, emerged as the predominant analytical technique due to its high sensitivity and accuracy in detecting low-abundance proteins over extended PMIs and PMSIs. However, protein degradation rates were significantly influenced by environmental variables such as temperature, humidity, soil pH, and microbial activity. This review also emphasizes the transformative role of bone proteomics in advancing forensic science while identifying key gaps that must be addressed to achieve global standardization and practical implementation in diverse forensic contexts. The integration of proteomics with other emerging technologies, such as machine learning algorithms and computational modeling, may further enhance the precision of PMI and PMSI estimation in future applications.

Postmortem Changes↗

PubMed2026

Detoxification-driven recovery of nitrogen removal under high linear alkylbenzene sulfonate stress by immobilized Pseudomonas sp. LM2.

Linear alkylbenzene sulfonate (LAS) is a widely used anionic surfactant that can inhibit microbial activity and destabilize biological wastewater treatment systems under high loading conditions. In this study, a sequencing batch reactor (SBR) was exposed to increasing LAS concentrations (0-100 mg/L) to define the collapse trajectory of activated sludge and evaluate recovery following bioaugmentation with immobilized Pseudomonas sp. LM2. The system remained stable at 20 mg/L LAS, deteriorated after prolonged exposure to 50 mg/L, and developed severe sludge disintegration with near-complete nitrification failure at 100 mg/L. In the LM reactor, LAS removal increased from 25.4% to 53.1% after bioaugmentation, together with improved nitrogen-removal performance. Blank carriers did not restore reactor performance. Genome annotation showed that LM2 encoded genes associated with LAS degradation and denitrification but lacked nitrification genes. Thus, the observed nitrification recovery was likely indirect and associated with lower LAS stress and recovery of indigenous nitrifiers. Quantitative PCR and amplicon analyses showed enrichment of Nitrospira and Thauera and a shift toward more deterministic community assembly after bioaugmentation. The carrier-only control showed taxonomic recovery but persistent functional inhibition under high residual LAS exposure. Overall, the results indicate that immobilized bioaugmentation can support partial recovery of nitrogen removal under severe LAS stress.

Bioaugmentation↗

PubMed2026

Multiomic insights into fungal polylactic acid degradation: Metabolic adaptation and hydrolytic mechanisms of Sporobolomyces pararoseus.

Polylactic acid (PLA), a biodegradable polyester from renewable resources, is a sustainable alternative to petrochemical plastics. However, its environmental degradation is inefficient naturally, requiring specific microbial activities. While bacterial PLA-degrading mechanisms are well documented, fungal degrading systems-particularly their molecular mechanisms-are underexplored.We isolated Sporobolomyces pararoseus ZRQ01 from the gut microbiota of PLA-fed mealworms. This fungal strain noticeably degraded PLA in PLA-containing medium supplemented with 2% glucose. Biodegradation assays revealed 22.8% loss of the PLA film weight after 35 days of incubation, and scanning electron microscopy confirmed extensive surface erosion and pore formation. Integrated transcriptomic and proteomic analyses, together with the reference genome of S. pararoseus ZRQ01, revealed that S. pararoseus ZRQ01 upregulates hydrolytic enzymes at both transcript and protein levels to cleave PLA into lactic acid. After lactic acid is transferred into S. pararoseus ZRQ01 cells by monocarboxylate transporters with increased abundance, it is assimilated by pathways of pyruvate metabolism and the TCA cycle with increased protein abundance. Intriguingly, upregulation of genes in autophagy-related and MAPK signaling pathways underscores an adaptive stress response potentially supporting cellular homeostasis and degradation-related gene expression. Our results highlight S. pararoseus ZRQ01's metabolic potential for bioremediation and offer insights into fungal bioplastic degradation pathways.

Polyesters↗

PubMed2026

Integrating multi-omics technologies to decipher microbiome functions.

Multi-omics approaches have revolutionized our understanding of microbial communities by enabling simultaneous interrogation of genomic, transcriptomic, proteomic, and metabolomic data. The systematic integration and analysis of these deep datasets help decipher the functional roles of microbiomes, providing critical insights into microbial activities, interactions, and dynamics across diverse environments. Biological complexity makes multi-omics analysis of a single, isolated organism demanding but highly informative, yet this complexity increases further when samples comprise hundreds to thousands of individual species. As microbiome research continues to expand into clinical, environmental, and engineered systems, standardized workflows, benchmarked datasets, and community-driven initiatives are essential to ensure reproducibility, standardization and interpretability. Establishing and disseminating best practices for experimental design, data processing, and integrative analyses will be critical for maximizing comparability and scientific rigor across studies. This perspective highlights recent advances in multi-omics microbiome research, outlines key obstacles in data integration and metadata harmonization, and proposes a collaborative roadmap for scalable, FAIR-compliant multi-omics investigations and potentially disruptive Artificial Intelligence (AI) advances comparable to those of AlphaFold in the field of microbiome science.

Multiomics↗

PubMed2026

Lpb. plantarum inhalation powders for the reduction of lung inflammation and S. aureus growth control in non-CF bronchiectasis.

INTRODUCTION: The reduced diversity of the lung microbiome in respiratory conditions, including bronchiectasis, promotes bacterial infection and inflammation, contributing to worsening clinical outcomes. Traditional treatments often fail to address both infection and inflammation. Because of their potential dual-action, lactic acid bacteria (LAB) directly administered to the lungs could represent an innovative therapeutic approach for these diseases. RESEARCH DESIGN AND METHODS: Two powders for inhalation containing Lpb. plantarum, lactose, l-leucine with and without raffinose, a prebiotic, were produced by spray drying and in vitro tested. The focus was on investigating their potential in vitro anti-inflammatory and anti-microbial activities against S. aureus. RESULTS: The powders showed a fine particle fraction (<5 µm) of >40% and allowed the maintenance of anti -inflammatory activity in vitro for both treatment and prevention. Moreover, both powders led to a significant reduction in S. aureus growth. The stability study of the powders in capsules at different storage conditions showed the preservation of the LAB up to 90 days in refrigerated conditions (4°C/-20°C). CONCLUSIONS: This proof-of-concept study shows that inhalable spray-dried live LABs retain biological activity and are suitable for pulmonary delivery, supporting their potential as a microbiota-modulating therapy, which, however, requires further preclinical validation.

Inhalation↗

PubMed2026

Interconnected influences of diet, gut microbiome, and metabolome on cognition across three metabolomics platforms.

Cognitive impairment is increasing with global aging, yet mechanisms linking diet, the gut microbiome, and metabolism to cognitive function remain unclear. To investigate a diet-microbiome-metabolome axis associated with cognition, we integrated fecal metagenomics, diet, and multi-platform plasma metabolomics in 505 older adults from four ADRCs. Several microbes broadly associated with circulating metabolites were also linked to multiple measures of cognitive performance. These taxa exhibited coordinated metabolic signatures, with cognition-positive microbes associated with antioxidant, lipid, and microbial-host co-metabolites, and microbes negatively associated with cognition were linked to inflammatory and aromatic amino acid-derived metabolites. Dietary patterns, particularly the Healthy Eating Index Greens and Beans component, were associated with microbial composition and metabolomic structure. Mediation analyses supported a diet-microbe-metabolite-cognition pathway, while metabolites remained associated with cognition after accounting for microbial features. These findings highlight the metabolome as a central integrator of diet, microbial activity, and cognitive function.

Journal Article↗

PubMed2026

Transcriptomic Association Between Poliovirus Receptor (PVR/CD155) and Claudin Signaling Pathways in Colorectal Cancer.

BACKGROUND/AIM: Enterotoxigenic Bacteroides fragilis promotes colorectal carcinogenesis through toxin-mediated cleavage of E-cadherin, a process facilitated by membrane-associated Claudin-4 (CLDN4). Separately, the poliovirus receptor (PVR/CD155) modulates tumor epithelial and immune dynamics. This study explored potential transcriptomic interactions and co-expression frameworks between PVR and claudin signaling pathways in colorectal cancer. MATERIALS AND METHODS: Transcriptomic and proteomic data from the The Cancer Genome Atlas-colon adenocarcinoma cohort (TCGA-COAD) were evaluated. An exploratory E-cadherin Cleavage Index was modeled to capture transcript-protein discordance. To control for tissue composition heterogeneity without mathematical circularity, a de-circularized, non-parametric partial rank residual model adjusted for independent CLDN4 expression was deployed within the stable microsatellite-stable (MSS) sub-cohort (N=473). RESULTS: Multivariable survival models showed no independent associations between overall survival and continuous PVR (p=0.79) or CLDN3 (p=0.56) expression. Robust linear modeling revealed no significant baseline interaction between PVR and CLDN4 regarding the exploratory Cleavage Index (p=0.82). However, de-circularized partial correlation analysis revealed a highly stable, positive co-expression between PVR and CLDN3 (rho=0.2459, p=3.23×10-7). Both epithelial markers retained modest inverse correlations with the infiltrating lymphocytic axis (TIGIT and CD96). CONCLUSION: Baseline PVR expression is coordinated with CLDN3 tissue programs independent of general epithelial cellularity but does not interact with the CLDN4 axis or impact overall survival in an unexposed cohort. Because TCGA lacks virome or active microbial exposure tracking, these findings serve as baseline benchmarks for future context-dependent mechanistic studies.

Bacteroides fragilis toxin↗