npj Biofilms and Microbiomes最新文献

Implant-associated infections caused by biofilm-forming bacteria, such as Staphylococcus aureus, remain a major clinical challenge due to their high tolerance to conventional antibiotic therapies. We report a dual-targeted therapeutic strategy that combines a tri-enzymatic cocktail designed to degrade key components of the biofilm matrix (TEC; comprising a DNA/RNA endonuclease, an endo-1,4-β-D-glucanase, and a β-N-acetylhexosaminidase), with vancomycin, both delivered via a thermosensitive poloxamer 407 hydrogel, for localized treatment of S. aureus biofilms. The formulation was evaluated both in vitro, on titanium-adherent biofilms, and in vivo, using a model of tissue cages containing titanium beads implanted in the back of guinea pigs. Animals additionally received intraperitoneal administration of vancomycin alone or combined with rifampicin. In vitro, this formulation enabled sequential drug release, with TEC delivered within the first 24 h and vancomycin for up to 96 h, and achieved >5 Log₁₀ reductions in CFU counts after two applications at 48 h interval. In vivo, biofilm-associated bacterial counts reached the detection limit (100 CFU; >5 Log₁₀ decrease from the initial inoculum) in 75% of implants 1 day post-treatment and remained undetectable in 37.5% of them 5 days post-treatment, with no emergence of resistance. Treatment efficacy was reduced if TEC or vancomycin were omitted in the hydrogel or if rifampicin was not included in the intraperitoneal treatment. Vancomycin in the hydrogel also prevented the emergence of rifampicin resistance. These findings underscore the therapeutic potential of a dual-targeted approach, combining biofilm disruption with local sustained antibiotic release, to improve the management of implant-associated infections.

Microbial communities play a central role in viticulture, influencing wine characteristics (a concept termed microbial terroir). Yet, the individual factors shaping these microbiomes remain poorly understood. We conducted a multi-year, large-scale survey of Swiss vineyards (95 sites, 680 samples), longitudinally sampling 12 sites (within 2.46 km and identical cultivar and rootstock) over three years. Using 16S rRNA gene and internal transcribed spacer (ITS) amplicon sequencing, untargeted metabolomics (GC-MS, LC-MS/MS), environmental monitoring, and sensory data, we disentangled environmental factors associated with community assembly and fermentation dynamics. Topography and climate collectively structured microbiomes but affected soil- and plant-associated communities differently. Berry-associated fungi showed the strongest site-specific signature, enabling machine-learning predictions of microclimatic variation. Climatic factors and berry chemistry selectively favor fermentative yeasts, which are each linked to distinct metabolite and aroma profiles. Plant stress metabolites were further associated with microbial and metabolite composition. Our integrative approach thereby fundamentally advances our understanding of microbial biogeography and terroir in viticulture.

Anxiety and sensory hyperresponsiveness are common in children with autism spectrum disorder (ASD), but effective treatments are lacking. Targeting the microbiota-gut-brain axis is a promising strategy. This open-label pilot study evaluated SCM06, a novel synbiotic designed to target anxiety and sensory hyperresponsiveness, in 30 children with ASD (mean age 8.2 years, 22 males). We assessed symptom improvement, compliance, and safety, and collected stool samples for metagenomics and metabolomic analysis over 12 weeks. SCM06 was safe and well-tolerated, and significant improvements were observed in anxiety, sensory hyperresponsiveness, and abdominal pain. Following SCM06 treatment, increase in Bifidobacterium pseudocatenulatum was associated with improved functional abdominal pain (p = 0.0011, p_{_adj} = 0.054), while the abundances of valeric acid and butyric acid increased (p_{_adj} = 0.004 and p_{_adj} = 0.072). Key microbial species, Coprococcus comes and Veillonella dispar, were candidate mediators of symptom improvements. Further randomised controlled trials are warranted to confirm its clinical efficacy.

Sub-Clinical Necrotic Enteritis (SCNE), caused by toxin-producing Clostridium perfringens, is a major challenge in poultry production. SCNE has traditionally been managed with in-feed antibiotics; however, increasing concerns about the spread of antimicrobial resistance call for antibiotic-free strategies for its control. We recently described an NE control strategy leveraging Limosilactobacillus reuteri probiotic strains genetically engineered to deliver nanobodies against alpha toxin and NetB from C. perfringens in the poultry gut. Here, in a controlled study under SCNE conditions, we found that the engineered strains significantly improved feed conversion ratios and weight gain of broilers, outperforming treatment with either a prophylactic antibiotic or the wild-type probiotic strains. To investigate the systemic factors contributing to these performance differences, we analyzed histomorphometrics of the small intestine, microbial metatranscriptomics of jejunal contents, and gene expression from the jejunum and liver tissues. Our results confirmed the in situ expression of the nanobodies and provided evidence that nanobody delivery mitigates SCNE-associated inflammation in the jejunum and toxin-induced damage in the liver, leading to a more quiescent immune state, lower oxidative stress, and improved growth performance. Our findings demonstrate the potential of probiotic-vectored nanobody delivery as an effective strategy for targeting gut antigens across a range of diseases.

Plants have evolved intricate defense strategies to combat herbivorous insect attacks, including the production of toxic secondary metabolites and the attraction of natural enemies. While bacterial-mediated direct toxicity in plant defenses has been demonstrated, the ecological mechanisms by which plants utilize bacteria to indirectly modulate the behavior of natural enemies remain insufficiently explored. In this study, we observed a significant enrichment of Staphylococcus in the tissues of zucchini Cucurbita pepo following infestation by the cotton-melon aphid Aphis gossypii. These bacteria traced from the damaged plant stems and leaves were subsequently found both in aphids and in their secreted honeydew. Among the four dominant bacterial strains isolated from the honeydew, Staphylococcus sp. markedly promoted oviposition preference in mated female ladybird beetles Propylea japonica. Further investigation identified a volatile organic compound, 4-Isopropylbenzyl alcohol, released by Staphylococcus sp. that stimulated strong antennal responses and attracted P. japonica to lay eggs. Collectively, our findings demonstrate that zucchini plants can employ indirect defense against A. gossypii through the enrichment of specific bacteria, revealing a novel ecological role for bacteria in plant defense and expanding our understanding of complex plant-microbe-insect-natural enemy interactions.

The gut microbiome is increasingly implicated in colorectal cancer (CRC), yet the functional signatures associated with disease progression remain poorly resolved across populations. We performed an assembly-based metagenomic analysis of more than 500 samples from three geographically distinct cohorts to characterize resistome and virulome patterns associated with CRC. Using a cross-validated modeling framework based on Partial Least Squares (PLS) regression, we identified two reproducible latent functional gradients that structured variation in antimicrobial-resistance and virulence-factor profiles. One gradient was enriched for adhesion, efflux, and biofilm-associated functions, while the second reflected immunomodulatory and barrier-related pathways. These components were statistically robust, directionally stable across cohorts, and consistent with functional themes frequently reported in CRC microbiome studies. To summarize variation along these gradients, we derived an exploratory Dual-Axis Index (DAI) based on the two stable PLS components. Although its discriminative performance was moderate, the DAI provided an interpretable low-dimensional representation of how resistome-virulome patterns differed across healthy, adenoma, and carcinoma states. These results suggest that functional gene profiles in CRC are organized along reproducible statistical axes, and highlight functional modules, such as adhesion-, iron-associated, and immune-interaction pathways that may complement taxonomic or metabolic biomarkers in future multimodal approaches. Our work provides a reproducible, assembly-based framework for examining the functional organization of CRC-associated microbiomes across diverse populations.

The oral-gut axis is a key pathway through which oral microbiota modulate systemic immunity. Oral bacteria and their derivatives, including microbial-associated molecular patterns and extracellular vesicles, can translocate to the gut, evade mucosal defenses, interact with local immune cells, and disrupt epithelial integrity. This review highlights mechanisms of gut colonization, immune modulation via pattern recognition receptors, and contributions to distal organ inflammation, providing a framework for understanding microbiota-driven systemic diseases.

We propose the term testobolome, analogous to the estrobolome, to describe gut bacteria that metabolize testosterone. Testosterone undergoes microbial transformations similar to estrogens, potentially influencing host hormone homeostasis and health. This review defines the testobolome, identifies its known members, and explores mechanisms that are shared or distinct from the estrobolome. We outline a framework for future research into microbiome-mediated steroid metabolism, including its role in aging and hormone-driven diseases.

Implant-associated infections (IAIs) arise from immune dysregulation and the resilience of bacterial biofilms, which create a permissive niche for persistent infection. Biofilms further suppress host immunity and impair repair. Advances in nanoengineered surfaces and multifunctional antimicrobial coatings, together with gas-releasing and stimulus-responsive nanoplatforms, offer effective non-antibiotic strategies to inhibit colonization, disrupt biofilms, and modulate local immunity. This review summarizes emerging immune-informed approaches for treating IAIs.

Large-scale, decentralized microbiome sampling surveys and citizen science initiatives often require periods of storage at ambient temperature, potentially altering sample composition during collection and transport. We developed a generalizable framework to quantify and model these biases using sourdough as a tractable fermentation system, with samples subjected to controlled storage conditions (4 °C, 17 °C, 30 °C, regularly sampled up to 28 days). Machine-learning models paired with multi-omics profiling-including microbiome, targeted and untargeted metabolome profiling, and cultivation-revealed temperature-dependent shifts in bacterial community structure and metabolic profiles, while fungal communities remained stable. Storage induced ecological restructuring, marked by reduced network modularity and increased centrality of dominant taxa at higher temperatures. Notably, storage duration and temperature were strongly encoded in the multi-omics data, with temperature exerting a more pronounced influence than time. 24 of the top 25 predictors of storage condition were metabolites, underscoring functional layers as both sensitive to and informative of environmental exposure. These findings demonstrate that even short-term ambient storage (<2 days) can substantially reshape microbiome, metabolome, and biochemical profiles, posing risks to data comparability in decentralized studies and emphasizing the need to recognize and address such biases. Critically, the high predictability of storage history offers a path toward bias detection and correction- particularly when standardized collection protocols are infeasible, as is common in decentralized sampling contexts. Our approach enables robust quantification and modeling of such storage effects across multi-omics datasets, unlocking more accurate interpretation of large-scale microbiome surveys.