Search Results (2,495)

The gut microbiome plays a key role in immune regulation. Young children experience rapid microbiome development, yet data on its alteration during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remain limited. This study aimed to characterize gut microbiome changes and immune-related pathway alterations in young children with coronavirus disease 2019 (COVID-19). Eighteen children under 2 years old with confirmed SARS-CoV-2 infection and seven healthy controls were enrolled between December 2021 and June 2022. Stool samples were analyzed using 16S rRNA gene sequencing. In children with COVID-19, the gut microbiome exhibited an increase in Bacteroidota and Bacillota, whereas Actinomycetota and Pseudomonadota were reduced, with higher abundances of Bifidobacterium, Escherichia, and Streptococcus and lower abundances of Faecalibacterium, Clostridium, and Ruminococcus compared with healthy controls. Children with COVID-19 exhibited reduced alpha diversity, indicating microbial dysbiosis, and significant differences in beta diversity compared with healthy controls. Predictive functional analysis revealed downregulation of key immune-related pathways, such as interleukin-17, NOD-like receptor, and Toll-like signaling, which may impact mucosal immunity and viral clearance in children with COVID-19. SARS-CoV-2 infection in early childhood is associated with gut dysbiosis and the suppression of key immune pathways. These findings highlight the potential long-term impact of early-life microbial disruptions on immune development. Full article

Bacterial endophytes have emerged as critical components of plant microbiomes, offering multifaceted benefits ranging from growth promotion to stress resilience. This review synthesizes two decades of research, from 2004 to 2024, on bacterial endophyte identification and applications, highlighting advances in both traditional culture-based techniques and modern omics approaches. The review also focuses on interactions between these microorganisms and their host plants, emphasizing their roles in biocontrol, phytoremediation, and nanoparticle biosynthesis. While significant progress has been made in characterizing cultivable bacterial endophytes, challenges persist in accessing unculturable species and understanding strain-specific functional mechanisms. The integration of metagenomics, metatranscriptomics, and metabolomics has begun unraveling this hidden diversity, revealing novel metabolic pathways and plant–microbe communication systems. There have been limitations in endophyte isolation protocols and field applications, and therefore a need exists for standardized frameworks to bridge lab-based discoveries with agricultural practices. Cutting-edge multi-omics techniques, such as genomics, transcriptomics, metabolomics, proteomics, and phenomics, should be used more in future research to clarify the mechanistic underpinnings of plant–endophyte interactions to thoroughly profile the microbial communities and unlock their functional potential under diverse environmental conditions. Overall, bacterial endophytes present viable paths toward sustainable farming methods, supporting food security and crop resilience in the face of environmental difficulties by providing a transformative opportunity for next-generation agriculture, mitigating climate-related agricultural stressors, reducing dependence on synthetic agrochemicals, and enhancing crop productivity. Full article

Background/Objectives: Antimicrobial peptides (AMPs) have emerged as promising alternatives to conventional antibiotics in livestock, offering a sustainable strategy for controlling bacterial pathogens in food production systems. In addition to their direct antimicrobial effects, AMPs play a key role in modulating host-associated microbiomes, influencing both microbial composition and function. Advances in metagenomic sequencing and bioinformatic tools now enable comprehensive exploration of AMP diversity and activity within complex microbial ecosystems. Methods: In this study, we employed Illumina-based next-generation sequencing (NGS) to analyze intestinal contents from six gut sections of broiler chickens obtained from a Spanish slaughterhouse. Results: Through de novo assembly and bioinformatic annotation, we identified biosynthetic gene clusters (BGCs) encoding ribosomally synthesized and post-translationally modified peptides (RiPPs), other specialized bioactive secondary metabolites, antimicrobial resistance genes (ARGs), virulence factor genes (VFGs), and a diverse microbial community. Among all gut sections, the cecum exhibited the highest genetic richness, characterized by a high diversity of RiPP-like clusters and antimicrobial resistance determinants. Conclusions: These findings highlight the poultry gut, particularly the cecum, as a significant reservoir of antimicrobial peptides (AMPs) with potential implications in antibiotic-free poultry production and enhanced food safety. Full article

Apples and pears are among the most popular and frequently consumed fruits worldwide. The polyphenol and dietary fibre components of these fruits are known to influence the gut microbiota and the subsequent human health outcomes. This study investigated the effects of New Zealand grown apples and pears with differing polyphenol contents on the structure and function of the human gut microbiota. Five apple and two pear cultivars underwent in vitro human digestion and microbial fermentation. Samples taken at 0 and 18 h were analysed for changes in pH, microbial composition, and organic acid production. The change in pH after faecal fermentation was influenced by the type of fruit (apple or pear), with lower pH being observed in the apples. Significant apple or pear cultivar effects were observed for the gut microbiome and organic acid production. The apple cultivar ‘Golden Hornet’ produced the least butyrate and the greatest microbial alpha diversity, while the pear ‘PremP009’ showed greater butyrate production with increases in a butyrogenic species (Acidaminococcus intestini). Further studies are needed to investigate the effect of cultivar and type of fruit on nutrient absorption and microbial fermentation and the impact of these on human health. Full article

Most of the knowledge available on the composition and functionality of microbial communities in different ecosystems comes from short-read sequencing methods. It implies limitations regarding taxonomic resolution, variant detection, and genome assembly contiguity. Long-read sequencing technologies can overcome these limitations, transforming the analysis of microbial community composition and functionality. It is essential to understand the characteristics of each sequencing technology to select the most suitable one for each microbiome study. This review aims to show how long-read sequencing methods have revolutionized microbiome analysis in ecosystems and to provide a practical tool for selecting sequencing methods. To this end, the evolution of sequencing technologies, their advantages and disadvantages for microbiome studies, and the new dimensions enabled by long-read sequencing technologies, such as virome and epigenetic analysis, are described. Moreover, desirable characteristics for microbiome sequencing technologies are proposed, including a visual comparison of available sequencing platforms. Finally, amplicon and metagenomics approaches and the sequencing depth are discussed when using long-read sequencing technologies in microbiome studies. In conclusion, although no single sequencing method currently possesses all the ideal features for microbiome analysis in ecosystems, long-read sequencing technologies represent an advancement in key aspects, including longer read lengths, higher accuracy, shorter runtimes, higher output, more affordable costs, and greater portability. Therefore, more research using long-read sequencing is recommended to strengthen its application in microbiome analysis. Full article

Consumers are increasingly concerned about the flavor quality of poultry meat, yet the relationship between inosine monophosphate (IMP), intramuscular fat (IMF), and the gut microbiota remains largely unclear. This study aimed to characterize the cecal microbiota associated with IMP/IMF deposition in Daheng broilers selectively bred for high-IMP/IMF levels (High group) and low levels (Control group). A two-stage microbiome analysis strategy was applied. Initially, 16S rRNA gene sequencing was conducted to assess microbial diversity and composition. Significant differences were observed between groups in alpha diversity indices (Chao1 and Faith_PD) and beta diversity (p < 0.05). LEfSe analysis identified 55 differentially abundant taxa (LDA > 3, p < 0.05), primarily within the Phylum bacteroidota. To achieve species-level and functional insights, whole-metagenome shotgun sequencing was performed. Taxonomic profiling of 62,443 microbial species revealed significant beta diversity differences (p < 0.05), with 120 dominant species differentially enriched (LDA > 3, p < 0.05), including 77 species in the High group such as Merdivivens faecigallinarum. Enriched functional genes were mainly involved in methane metabolism, starch and sucrose metabolism, and the nucleoside phosphate metabolic process. A total of 882 metagenome-assembled genomes (MAGs) were reconstructed and integrated with 19,628 publicly available chicken MAGs, resulting in 2609 non-redundant genomes, including 52 novel ones. These findings suggest that cecal microbial composition and function are associated with IMP/IMF levels in broilers, providing candidate bacterial species and functional pathways for further validation through gavage-based intervention and multi-omics analysis. Full article

Obesity is a growing global health challenge, closely linked to chronic low-grade inflammation. This persistent, low-intensity immune response contributes to the development of metabolic, cardiovascular, and cancer-related diseases. A key player in this process is the gut microbiota. Dysbiosis, an imbalance in gut bacterial composition, disrupts metabolic function, weakens the intestinal barrier, and promotes the production of pro-inflammatory cytokines. In people with obesity, gut microbial diversity is reduced, and the ratio of beneficial to harmful bacteria shifts, affecting lipid metabolism and immune balance. Short-chain fatty acids, produced by gut bacteria, help maintain gut integrity and reduce inflammation. Butyrate, a major SCFA, also improves insulin sensitivity and may support obesity treatment. Diet plays a central role in shaping the gut microbiome. Western diets tend to promote dysbiosis and inflammation, while Mediterranean-style diets encourage the growth of beneficial bacteria. Targeted modulation of the microbiota through diet, probiotics, or medication emerges as a promising strategy for preventing and managing obesity. Full article

Fermentation plays a pivotal role in shaping the flavor and overall quality of Pu-erh tea, a microbially fermented dark tea. Here, we monitored physicochemical properties, chemical constituents, and microbial succession at 15 fermentation time points. Amplicon sequencing identified Staphylococcus, Bacillus, Kocuria, Aspergillus, Blastobotrys, Thermomyces, and Rasamsonia as dominant genera, with prokaryotic communities showing greater richness and diversity than eukaryotic ones. Beta diversity and clustering analyses revealed stable microbial structures during late fermentation stages. Non-targeted metabolomics detected 347 metabolites, including 56 significantly differential compounds enriched in caffeine metabolism and unsaturated fatty acid biosynthesis. Fermentation phases exhibited distinct metabolic patterns, with volatile aroma compounds (2-acetyl-1-pyrroline, 2,5-dimethylpyrazine) and health-beneficial fatty acids (linoleic acid, arachidonic acid) accumulating in later stages. OPLS-DA and KEGG PATHWAY analyses confirmed significant shifts in metabolite profiles relevant to flavor and biofunctionality. RDA revealed strong correlations between microbial taxa, environmental parameters, and representative metabolites. To functionally verify microbial contributions, 17 bacterial and 10 fungal strains were isolated. Six representative strains, mainly Bacillus and Aspergillus, exhibited high enzymatic activity on macromolecules, confirming their roles in polysaccharide and protein degradation. This integrative multi-omics investigation provides mechanistic insights into Pu-erh tea fermentation and offers a scientific basis for microbial community optimization in tea processing. Full article

Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research. Full article

Linear models are not always able to sufficiently capture the structure of a dataset. Sometimes, combining predictors in a non-parametric method, such as deep neural networks (DNNs), would yield a more flexible modeling of the response variables in the predictions. Furthermore, the standard statistical classification or regression approaches are inefficient when dealing with more complexity, such as a high-dimensional problem, which usually suffers from multicollinearity. For confronting these cases, penalized non-parametric methods are very useful. This paper proposes two heuristic approaches and implements new shrinkage penalized cost functions in the DNN, based on the elastic-net penalty function concept. In other words, some new methods via the development of shirnkaged penalized DNN, such as ${\mathrm{DNN}}_{\mathrm{elastic-net}}$ and ${\mathrm{DNN}}_{\mathrm{ridge}\&\mathrm{bridge}}$, are established, which are strong rivals for ${\mathrm{DNN}}_{\mathrm{Lasso}}$ and ${\mathrm{DNN}}_{\mathrm{ridge}}$. If there is any dataset grouping information in each layer of the DNN, it may be transferred using the derived penalized function of elastic-net; other penalized DNNs cannot provide this functionality. Regarding the outcomes in the tables, in the developed DNN, not only are there slight increases in the classification results, but there are also nullifying processes of some nodes in addition to a shrinkage property simultaneously in the structure of each layer. A simulated dataset was generated with the binary response variables, and the classic and heuristic shrinkage penalized DNN models were generated and tested. For comparison purposes, the DNN models were also compared to the classification tree using GUIDE and applied to a real microbiome dataset. Full article

The composition of the gut and/or tumor microbiome has been intricately involved in the onset of carcinogenesis, tumor progression, therapy response, and patient outcomes in diverse solid cancers. The microbiome type, composition, and their metabolome have been functionally implicated in the multifarious cellular processes, transformation, proliferation, tumor immune evasion, cellular migration, etc. Despite such compelling evidence on the role of microbiome interactions in cancer, the realization of their role in neuroblastoma (NB), the deadly extracranial tumor in infants is few and fragmentary. This review comprehends the composition, diversity, and significance of microbiota in human health. Further, this review discusses the microbiota composition, their mode of action, and their signaling flow through and cellular processes in diverse cancers including NB. Precisely, this study for the first time has realized the functional relevance and clinical significance of the gut and tumor microbiome for NB. Interestingly, large cohort clinical and preclinical in vivo models of NB realized the following: gut microbiota predicts the risk for NB; postnatal (and or not maternal transmission) microbiome rearrangements; gut microbial effect on NB pathogenesis; tumor-altering gut microbial composition; microbial composition predicts treatment outcomes in NB; prebiotic remedies for stabilizing NB-associated microbial rearrangements; microbial composition in tumor-infiltrating microbiota predicts NB outcomes. Full article

In this study, the distribution patterns of the nitrifying and denitrifying microbiome in a large-scale biofilter (587.24 m³) in a cold freshwater recirculating aquaculture system (RAS) was investigated. Previous studies have revealed that the water quality, nitrification, and denitrification rates in the front (BFF), middle (BFM), and back (BFB) of this biofilter are different. The results showed the highest diversity of the denitrifying microbiome in the BFB, followed by BFF and BFM, whereas nitrifying microbiome diversity remained consistent across different positions. Two genera, Nitrosomonas and Nitrosospira, dominated the nitrifying microbiome, while Pseudomonas, Thauera, Cupriavidus, Dechloromonas, Azoarcus, and Paracoccus comprised the top six denitrifying genera. Principal coordinate analysis indicated a distinct spatial distribution pattern of the denitrifying microbiome but not the nitrifying microbiome. The genera Pseudomonas and Dechloromonas were the biomarkers of the BFF and BFB, respectively. Redundancy analysis showed that nitrite, nitrate, dissolved oxygen, and soluble reactive phosphorus influenced the functional microbiome distribution pattern. Network correlation analysis identified one nitrifying hub (Nitrosospira) in the BFF, five denitrifying hubs (Aromatoleum, Dechloromonas, Paracoccus, Ruegeria, and Thauera) in the BFM, and three denitrifying hubs (Azoarcus, Magnetospirillum, and Thauera) in the BFB. Exclusively negative correlations were found between hubs and its adjacent nodes in the BFF and BFB. This study demonstrates that habitat can shape the distribution patterns of the nitrifying and denitrifying microbiome in the biofilter of the RAS, with the BFF exhibiting greater benefits for the nitrification process. Full article

Low-dose carrot rhamnogalacturonan-I (cRG-I) has shown consistent modulatory effects on the gut microbiota and immune function in humans. In this study we investigated its effects on the microbial composition and metabolite production of the gut microbiota of small (5–10 kg), medium-sized (10–27 kg), and large (27–45 kg) dogs, using inulin and xanthan as comparators. Fecal samples from six dogs of each size group were evaluated. Overall microbiome composition, assessed using metagenomic sequencing, was shown to be driven mostly by dog size and not treatment. There was a clear segregation in the metabolic profile of the gut microbiota of small dogs versus medium-sized and large dogs. The fermentation of cRG-I specifically increased the levels of acetate/propionate-producing Phocaeicola vulgatus. cRG-I and inulin were fermented by all donors, while xanthan fermentation was donor-dependent. cRG-I and inulin increased acetate and propionate levels. The responses of the gut microbiota of different sized dogs to cRG-I were generally consistent across donors, and interindividual differences were reduced. This, together with the significant increase in P. vulgatus during fermentation in both this study and an earlier human ex vivo study, suggests that this abundant and prevalent commensal species has a core capacity to selectively utilize cRG-I. Full article

Male infertility is a multifactorial condition often associated with disruptions in sperm metabolism and mitochondrial function, yet traditional semen analysis provides limited insight into these molecular mechanisms. Understanding sperm bioenergetics and metabolic dysfunctions is crucial for improving the diagnosis and treatment of conditions such as asthenozoospermia and azoospermia. This systematic review synthesizes recent literature, focusing on advanced tools and techniques—including omics technologies, advanced imaging, spectroscopy, and functional assays—that enable comprehensive molecular assessment of sperm metabolism and development. The reviewed studies highlight the effectiveness of metabolomics, proteomics, and transcriptomics in identifying metabolic biomarkers linked to male infertility. Non-invasive imaging modalities such as Raman and magnetic resonance spectroscopy offer real-time metabolic profiling, while the seminal microbiome is increasingly recognized for its role in modulating sperm metabolic health. Despite these advances, challenges remain in clinical validation and implementation of these techniques in routine infertility diagnostics. Integrating molecular metabolic assessments with conventional semen analysis promises enhanced diagnostic precision and personalized therapeutic approaches, ultimately improving reproductive outcomes. Continued research is needed to standardize biomarkers and validate clinical utility. Furthermore, these metabolic tools hold significant potential to elucidate the underlying causes of previously misunderstood and unexplained infertility cases, offering new avenues for diagnosis and treatment. Full article

The rhizosphere microbiome plays an important role in carbon- and nitrogen-cycling in soil and in the stress response of plants. It also affects the function of the ammonium transporter (AmtB) that senses nitrogen levels inside and outside the cells of the associative nitrogen-fixing bacterium GXGL-4A. However, the potential mechanism of the interaction between the AmtB deletion mutant of GXGL-4A (∆amtB) and microorganisms in the rhizosphere of plants under low-nitrogen stress is still unclear. As revealed by transcriptome analyses, mutation of the amtB gene in GXGL-4A resulted in a significant up-regulation of many functional genes associated with nitrogen fixation and transportation at transcription level. The application of ∆amtB changed the nitrogen level in the rhizosphere of cucumber seedlings and reshaped the microbial community structure in the rhizosphere, enriching the relative abundance of Actinobacteriota and Gemmatimonadota. Based on bacterial functional prediction analyses, the metabolic capacities of rhizobacteria were improved after inoculation of cucumber seedlings with the original strain GXGL-4A or the ∆amtB mutant, resulting in the enhancement of amino acids, lipids, and carbohydrates in the cucumber rhizosphere, which promoted the growth of cucumber plants under a low-nitrogen stress condition. The results contribute to understanding the biological function of gene amtB, revealing the regulatory role of the strain GXGL-4A on cucumber rhizosphere nitrogen metabolism and laying a theoretical foundation for the development of efficient nitrogen-fixing bacterial agents for sustainable agricultural production. Full article