Metagenomic sequencing has provided scientists with the ability to investigate microbial populations, termed microbiomes, in environmental and clinical settings. Current approaches to metagenomic research involve the use of next-generation sequencing (NGS) to generate short, precise reads for characterization of microbial compositions. While highly accurate, short reads possess several limitations that restrict their application in metagenomic research. Third generation, long-read sequencing technologies may offer several advantages for metagenomic research. Here, we used simulated datasets, as well as experimental data from murine fecal samples, to compare the relative performance of short and long reads for metagenomic research, and their impact on assessing microbial composition. Long-read data demonstrated increased precision for identification of microbiome constituents and assessing abundance without sacrificing sensitivity. Hierarchical clustering of microbiome similarity from paired short- and long-read datasets obtained from murine fecal samples revealed clustering was driven by read type as opposed to sample type, underscoring the importance of sequence type. These findings led us to use long-read sequencing for elucidating the effects of propionic acid (PPA) on the murine gut microbiome. PPA has been shown to induce physiological changes like those observed in autism spectrum disorder (ASD). Individuals with ASD may suffer from gastrointestinal comorbidities, suggesting an association with the gut microbiome. Murine offspring fed a PPA-rich diet were assessed for microbiota perturbations. Our results demonstrated that a PPA-rich diet alters the gut microbiome of progeny mice, selecting for several bacterial species that have previously been found in greater abundance among people iv with ASD. In our study, changes to microbial abundance were also associated with significant variation in bacterial metabolic pathways related to steroid hormone biosynthesis, amino sugar, and nucleotide sugar metabolism. Taken together, our findings provide empirical evidence supporting the use of long-read sequencing in metagenomic research by elucidating links between PPA exposure and gut microbiome composition.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1431 |
| Date | 01 January 2024 |
| Creators | Greenman, Noah |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
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