Biology subjects

Mars, R. A. T.

Publications and source records attributed to Mars, R. A. T..

4 recordsLinked to original sources

bioRxiv2026

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

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.

microbiology↗

bioRxiv2021

Shared and disease-specific host gene-microbiome interactions across human diseases

While the gut microbiome and host gene regulation separately contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here, we developed a machine learning-based framework to jointly analyze host transcriptomic and microbiome profiles from 416 colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease, and irritable bowel syndrome. We identified potential interactions between gut microbes and host genes that are disease-specific, as well as interactions that are shared across the three diseases, involving host genes and gut microbes previously implicated in gastrointestinal inflammation, gut barrier protection, energy metabolism, and tumorigenesis. In addition, we found that mucosal gut microbes that have been associated with all three diseases, such as Streptococcus, interact with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes.

genomics↗

bioRxiv2021

Niche partitioning facilitates coexistence of closely related gut bacteria

Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro. However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.

microbiology↗

bioRxiv2017

Disentangling metabolic functions of bacteria in the honey bee gut

It is presently unclear how much individual community members contribute to the overall metabolic output of a gut microbiota. To address this question, we used the honey bee, which harbors a relatively simple and remarkably conserved gut microbiota with striking parallels to the mammalian system and importance for bee health. Using untargeted metabolomics, we profiled metabolic changes in gnotobiotic bees that were colonized with the complete microbiota reconstituted from cultured strains. We then determined the contribution of individual community members in mono-colonized bees, and recapitulated our findings using in vitro cultures. Our results show that the honey bee gut microbiota utilizes a wide range of pollen-derived substrates including flavonoids and outer pollen wall components, suggesting a key role for degradation of recalcitrant secondary plant metabolites and pollen digestion. In turn, multiple species were responsible for the accumulation of organic acids and polyphenol degradation products, and a specific gut symbiont, Bifidobacterium asteroides, stimulated the production of host hormones known to impact bee development. While we found evidence for cross-feeding interactions, [~]80% of the identified metabolic changes were also observed in mono-colonized bees with Lactobacilli being responsible for the largest share of the metabolic output. These results suggest that bacteria in the honey bee gut colonize largely independent metabolic niches, which may be a general characteristic of gut microbiomes. Our study reveals diverse metabolic functions of gut bacteria that are likely to contribute to bee health, and provide fundamental insights into how metabolic functions are partitioned within gut communities.\n\nAuthor summaryHoney bees are important pollinators that harbor a simple gut microbiota with striking parallels to the mammalian system. This makes them relevant models to study gut microbiota functions and its impact on host health. We applied untargeted metabolomics to characterize metabolic changes induced by the gut microbiota, and to characterize contributions of the major community members. We find that the gut microbiota digests recalcitrant substrates derived from the bees pollen-diet. Most metabolic changes could be explained by the activity of individual community members suggesting substrate specificity and independent metabolic niches. Our study provides novel insights into the functional understanding of the bee gut microbiota and provides a framework for applying untargeted metabolomics to disentangle metabolic functions of gut bacteria.

microbiology↗