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Taifi, A.

Publications and source records attributed to Taifi, A..

2 recordsLinked to original sources

Longitudinal Long-Read Microbiome Profiling in a Canine Model Reveals How Age, Diet, and Birth Mode Shape Gut Community Dynamics

The gut microbiome undergoes dynamic age-related changes, shaped by diet and maternal factors. Here, we present a species-level, long-read 16S rRNA survey of the developing gut microbiome in a translational canine model, profiling 89 purebred Hungarian Pumis across early-life and reproductive stages. We collected 456 fecal samples longitudinally: 60 puppies followed from birth to 81 weeks, their mothers sampled during pregnancy and lactation, and adult controls from six kennels. We recorded detailed dietary metadata and reproductive status throughout the study. Age was the strongest determinant of alpha diversity, with a rapid increase during weaning and stabilization by six months of age. Beta diversity analyses revealed structured compositional transitions from early developmental phases to adulthood, including a shift toward more uniform, adult-like communities. Within-kennel variation was modest, consistent with shared environmental exposures. Mixed-effects models showed robust associations between specific taxa and age, diet, and kennel, while SparCC-inferred co-occurrence networks indicated increasing ecological complexity with age. We also demonstrated that the delivery mode - vaginal versus cesarean - impacted early-life microbiome composition: Lactobacillus spp. was significantly more abundant in cesarean-born puppies than in vaginally delivered littermates during the 8-10-week window. We also observed reproducible maternal microbiome shifts during pregnancy and lactation, with potential implications for vertical microbial transfer. Taken together, our results show that domestic dogs follow a reproducible, age-structured trajectory of microbial maturation that parallels human development, including delivery-mode effects and diet-responsive taxa. IMPORTANCEMicrobiome research is among the fastest-moving areas in biomedicine, driven by major global efforts to understand how microbial communities shape human health and disease. Dogs provide an ideal translational model because their gut microbiota more closely resembles that of humans than that of other studied animals; moreover, breeds show high within-breed genetic homogeneity, diets can be tightly regulated, and longitudinal sampling across the lifespan is feasible. Mapping shifts driven by diet and maternal factors - from early-life events through later life, including senior stages - is essential to leverage microbial plasticity for prevention, with implications for inflammation, metabolic disease, and neurodegeneration. Here, we advance this goal by providing a longitudinal, high-resolution dataset and demonstrating that full-length 16S rRNA sequencing is a powerful tool for resolving fine-scale patterns of gut colonization and maturation.

microbiology↗

Comprehensive Metagenomic Profiling of Diverse Microbiomes

The canine gut microbiome serves as a key model for veterinary and human health research, but inconsistent findings arise due to methodological variations. This study presents a three-part dataset to clarify how DNA extraction, primer selection, and sequencing platforms influence microbial profiling. First, we performed ultra-deep sequencing of a single dog fecal sample using five DNA isolation kits, multiple library protocols, and four sequencing platforms (Illumina MiSeq/NovaSeq, ONT MinION, PacBio Sequel IIe), enabling direct comparisons of 16S rRNA and shotgun sequencing techniques. Second, we analyzed 40 fecal samples from eight co-housed dogs using Zymo High-Molecular-Weight (ZHMW) and Zymo MagBead (ZMB) extraction kits to assess longitudinal extraction-kit effects. Third, we evaluated three 16S primer systems (standard ONT, PacBio, and modified ONT with degenerate bases) using synthetic mock communities and human/canine fecal samples to quantify primer biases. By integrating synthetic and biological replicates, this dataset provides a standardized resource for benchmarking bioinformatics pipelines and improving cross-study comparability. The study generated 75.31GB of new sequencing data: 43.451GB from ZHMW-ZMB comparisons, 22.611GB for primer evaluations, and 9.191GB from the single-sample analysis. Combined with 31.51GB of prior data, the total dataset exceeds 1061GB, including all analytical outputs. These resources enhance methodological transparency and accuracy in canine gut microbiome research across diverse laboratory workflows.

microbiology↗