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Ruben, Mars A

0000-0002-3917-9517

Mayo Clinic

Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.

Citations 2

Robust taxonomic classification in gut and vaginal microbiomes demonstrated through benchmarking with age-specific synthetic communities

No container title available | July 7, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.07.06.736764

Abstract Accurate taxonomic profiling of human microbiomes is essential for advancing research and understanding the complex role microbial communities play in human health. When using shotgun metagenomics, the sequencing data is analyzed through metagenomic pipelines, which incorporate various open-source tools and classify microbes based on matched paired-end DNA reads. However, differences in sequencing and computational approaches can produce substantially different microbiome profiles from the same sample, making validation critical. One approach for validation is benchmarking with realistic mock communities, but this remains relatively rare. Additionally, existing benchmarks often overlook microbiome variability across life stages and body sites, limiting their clinical and research utility. Here, we developed age- and body site-stratified synthetic metagenomes, enabling context-aware benchmarking of microbiome pipelines. Using novelty-based sampling to prioritize microbial diversity and minimize redundancy among selected samples, we selected 300 representative, real biological samples spanning six categories: adult, child, toddler, and infant (>6 months and <6 months) gut samples, as well as adult vaginal samples. We validated three pipelines, Tiny Health’s proprietary Metagenomic Classifier v2 (THMCv2), MetaPhlAn4, and Kraken2+Bracken, using precision, recall, F1 score, and area under the precision-recall curve (AUPR) across age groups and sample types. THMCv2 demonstrated higher recall and F1 scores, detecting more taxa across sample types and ages, while MetaPhlAn4 achieved the highest precision. THMCv2 also achieved the highest area under the precision-recall curve, reflecting peak performance across both abundant and rare species. When analyses were weighted by abundance, THMCv2 and MetaPhlAn4 each characterized the mock community nearly perfectly. Errors for THMCv2 were largely restricted to very low-abundance taxa (<0.001%), whereas MetaPhlAn4 occasionally produced false positives for higher-abundance taxa. Species-level analyses of clinically relevant microbes confirmed these patterns, with THMCv2 demonstrating higher sensitivity, MetaPhlAn4 higher specificity, and Kraken2 lower overall performance. These results demonstrate clear precision-recall trade-offs in metagenomic profiling. This benchmarking framework provides a reproducible approach for evaluating pipeline performance across diverse microbiome contexts and life stages.
Metagenomic Insights into Microbial Signatures in Thrombi from Acute Ischemic Stroke Patients Undergoing Endovascular Treatment

Brain Sciences | February 6, 2025 | Volume: 15 | Issue: 2 | Pages: 157

10.3390/brainsci15020157 | PMID 40002490

Background: Variability in recanalization success during endovascular treatment for acute ischemic stroke (AIS) has led to increased interests in thrombus composition and associated cellular materials. While evidence suggests that bacteria may influence thrombus characteristics, limited data exist on microbiological profiles of thrombi in stroke patients. Objectives: Characterization of bacterial communities present in thrombi of AIS patients undergoing mechanical thrombectomy, providing insights into microbial contributions to stroke pathogenesis and treatment outcomes. Methods: Thrombi were collected from 20 AIS patients. After extracting metagenome, 16S rDNA sequencing was performed. Bioinformatic analysis included taxonomy and diversity assessments. The presence of bacterial DNA and viable bacteria in thrombi was validated using polymerase chain reaction (PCR) and bacterial culturing followed by matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) analysis, respectively. Results: 16S rDNA was amplified in 19/20 thrombi (95%). Analysis identified a diverse microbial community, with Corynebacterium spp. as the most prevalent genus, followed by Staphylococcus spp., Bifidobacterium spp., Methylobacterium spp., and Anaerococcus spp. Alpha diversity analyses (Shannon index: 4.0–6.0 and Simpson index: 0.8–1.0) revealed moderate to high microbial diversity across samples; beta diversity demonstrated distinct clustering, indicating inter-patient variability in microbial profiles. PCR confirmed the presence of DNA specific to dominant bacterial taxa identified through sequencing. Culturing showed the presence of Staphylococcus epidermidis and Enterococcus faecalis in some clots as identified through MALDI analysis. Conclusions: This study shows bacterial communities present in AIS patients’ thrombi, suggesting a potential link between microbial signatures and thrombus characteristics.