Alma Haydee Astorga Gaxiola, Luis Martin Sánchez Magaña, Liliana León López, Cuauhtémoc Reyes Moreno, Saraid Mora Rochín
The gut microbiota is a dynamic ecosystem shaped by dietary factors, lifestyle factors, environmental exposures, and host characteristics, with important implications for metabolism, immune regulation, intestinal barrier function, and host–microbiota interactions. This narrative review examines how dietary patterns, specific food components, physical activity, sleep and circadian rhythms, aging, and medication exposure modulate gut microbial composition and function, with particular emphasis on interindividual variability and personalized nutrition. A literature search was conducted in Scopus, ScienceDirect, PubMed, and Google Scholar for publications from 2000 to 2026, with emphasis on recent peer-reviewed evidence. Current evidence indicates that dietary patterns and individual food components can modify microbial community structure, metabolic pathways, and bioactive metabolite production, although responses vary substantially across individuals. Physical activity may modify microbial ecology, intestinal physiology, barrier function, and microbial metabolism, whereas sleep disruption and circadian misalignment may alter microbial rhythmicity and host metabolic regulation. Aging and antibiotic exposure are associated with context-dependent changes in microbial composition, function, resilience, and, with antibiotics, the gut resistome. Across these determinants, interindividual variability emerges as a central feature driven by host characteristics, habitual diet, lifestyle, medication history, baseline microbiota, and microbial functional capacity. Personalized nutrition therefore represents a promising but evolving framework in which microbiome data may be integrated with host and environmental characteristics to predict differential responses. Future research should prioritize longitudinal human studies, standardized methodologies, multi-omics integration, and prospective validation of microbiome-informed interventions to establish clinically meaningful benefits.
Vaginal bacterial communities are increasingly recognized as key determinants of fertility in cattle. This study explored bacterial communities in the cervico-vaginal mucus of healthy heifers, cows with cervicitis, repeat-breeding, and cows within the 35-day postpartum period using the microbiological culture method (n=35) and sequencing of the V3-V4 hypervariable regions of 16S rRNA gene (n=18), along with antimicrobial susceptibility testing. Micrococcus spp. and Enterobacter spp. were the top two bacteria isolated across the groups. Alarmingly, antimicrobial sensitivity tests revealed a high prevalence of multidrug resistance (71.7%) and elevated multiple antibiotic resistance indices in the isolated bacteria; none of the isolates were sensitive to all the tested bacteria. From 16S rRNA sequencing, a total of 1,047,482 sequences and 2,366 operational taxonomic units (OTUs) were generated. All groups shared 434 OTUs, and they did not differ in alpha diversity and beta diversity except for healthy heifers and cervicitis cattle. Bacillota, followed by Pseudomonadota, Fusobacteriota, Actinomycetota, Bacteroidota, and Mycoplasmatota dominated the vaginal microbiota across all groups. Genus-level comparisons revealed the following group-specific enriched taxa: Chryseobacterium with a linear discriminant analysis (LDA) score > 3 in cervicitis, Filifactor (LDA score > 2) in repeat breeding cow, and Histophilus (LDA score > 3.5) in healthy heifers. These findings offer important insights into the structure of bovine vaginal microbial communities while highlighting the urgent need to monitor antimicrobial resistance. This study lays the groundwork for defining the core vaginal microbiota and its potential implications for reproductive health and disease. To the best of our knowledge, this is the first study in Nepal to investigate cervico-vaginal microbiota and antimicrobial resistance patterns in cattle across different reproductive statuses using both culture-dependent methods and 16S rRNA gene sequencing.
F. B. R. P. Kumara, D. K. Hettiarachchi, N. D. A. D. Wijegunawardana
Cutaneous leishmaniasis is a growing public health threat in Sri Lanka, transmitted primarily by phlebotomine sand flies. While biological control using Wolbachia has proven effective against other vector-borne diseases, its potential application in phlebotomine sand flies remains largely unexplored. Therefore, investigating the natural prevalence of these endosymbionts in Sri Lankan sand fly populations is well justified. To address this knowledge gap and evaluate the feasibility of symbiont-mediated control, we conducted a six-month entomological survey across four endemic sampling areas in the North Central Province. Captured sand flies were morphologically identified at genus level, and 90 females belonging to the genera Phlebotomus and Sergentomyia were screened for Wolbachia using wsp -targeted polymerase chain reaction (PCR). To provide complementary evidence and characterize the broader sand fly-associated bacterial community, high-throughput 16S rRNA gene amplicon sequencing was performed on a pooled sample of 25 females. Wolbachia was not detected in any of the individually screened specimens (0/90; observed prevalence, 0.0%; approximate rule-of-three upper 95% prevalence limit, 3.3%) or in the pooled 16S dataset. Sequencing generated 220,698 non-chimeric reads, and Serratia was the most abundant identifiable genus, accounting for 41.71% of bacterial reads. These findings indicate an absence of detectable Wolbachia under the methods applied, rather than its definitive absence from the wider regional sand fly population. The study provides baseline evidence relevant to evaluating the feasibility and limitations of symbiont-mediated strategies for leishmaniasis vector control in Sri Lanka.
Global health challenges associated with neurodegenerative disorders are increasing, prompting growing interest in the gut-brain axis (GBA) as a key contributor to disease pathogenesis. The GBA represents a bidirectional communication network linking the gut microbiota, immune signalling pathways, metabolic processes, and the central nervous system (CNS). This review highlights the role of the GBA in the onset and progression of Alzheimer’s disease (AD) and Parkinson’s disease (PD), focusing on comparative disease mechanisms involving microbial dysbiosis, neuroinflammation, and metabolic dysfunction. Particular emphasis is placed on alterations in short-chain fatty acids (SCFAs), lipopolysaccharide (LPS), microbial amyloids, and inflammatory mediators including tumour necrosis factor alpha (TNF-α), interleukin 1 beta (IL-1β), interleukin 6 (IL-6), toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-κB), and NLR family pyrin domain containing 3 (NLRP3) inflammasome, which contribute to protein misfolding, blood-brain barrier disruption, and the accumulation of amyloid-β, hyperphosphorylated Tau, and α-synuclein. Furthermore, the review discusses recent advances in artificial intelligence (AI) and machine learning (ML) for integrating microbiome, clinical, neuroimaging, and multi-omics datasets to improve disease prediction, biomarker discovery, and patient stratification. AI approaches, including random forest, support vector machine, convolutional neural networks, and XGBoost, together with microbiome analysis platforms such as QIIME 2 and multi-omics integration tools including mixOmics and MOFA+, are highlighted for their potential in precision neurology. Collectively, integrating GBA biology with AI-driven analytics provides promising opportunities for early diagnosis, personalised therapeutic strategies, and precision medicine to address the growing burden of neurodegenerative disorders.
Fadwa Khalfallah, Nicolas Legay, Sebastien Bonthoux, Amélie A. M. Cantarel, Jean-Christophe Clement, Arnaud Foulquier, Catherine Joulian, Xavier Le Roux, Agnès Richaume, Marie-Paule Norini, Jennifer Harris
Urbanization alters soil conditions and may strongly affect microbial communities, yet the functional consequences of these changes remain poorly understood. We investigated how urban land use and management intensity shape microbial diversity, functional traits, and interaction patterns in urban soils. We sampled 135 soils across eight land-use types in Blois (France), each assigned a management intensity level from 1 (low) to 4 (high). Bacterial and fungal communities were characterized using Illumina sequencing, fungal guilds were identified using FungalTraits, bacterial taxa were classified by life strategies, enzymatic activities were measured, and co-occurrence networks were constructed. Land-use type and management intensity strongly influenced microbial composition, diversity, and functioning. Highly managed sites (Gardens, Sports fields) showed lower fungal 18S rRNA gene abundance, higher bacterial 16S rRNA gene copy numbers, reduced diversity, and lower nitrogen-related enzyme activities compared to less managed sites (Unused areas). These sites also exhibited more oligotroph-dominated and interconnected communities. Co-occurrence networks were less connected than those reported in semi-natural ecosystems, indicating more fragmented microbial associations in urban soils. Our findings reveal that management intensity acts as a strong ecological filter shaping microbial functional traits and interaction patterns in urban soils. The reduced connectivity and functional shifts observed in intensively managed sites highlight the need to integrate microbial indicators into urban green-space planning and management.
