Biology subjects

Waters, N. R.

Publications and source records attributed to Waters, N. R..

4 recordsLinked to original sources

bioRxiv2025

Correlating High-dimensional longitudinal microbial features with time-varying outcomes with FLORAL

Correlating time-dependent patient characteristics and matched microbiome samples can identify biomarkers in longitudinal microbiome studies. Existing approaches typically repeat a pre-specified modeling approach for all taxonomic features, followed by a multiple testing adjustment step for false discovery rate (FDR) control. In this work, we develop an alternative strategy of using log-ratio penalized generalized estimating equations, which directly models the longitudinal patient characteristic of interest as the outcome variable and treats microbial features as high-dimensional compositional covariates. A cross validation procedure is developed for variable selection and model selection among different working correlation structures. In extensive simulations, the proposed method achieved superior sensitivity over the state-of-the-art methods with robustly controlled FDR. In the analyses of correlating longitudinal dietary intake, bloodstream infection status, and microbial features from matched samples of cancer patients, the proposed method effectively identified gut health indicators and clinically relevant microbial markers, showing robust utilities in real-world applications. The method is implemented under the open-source R package FLORAL, which is available at (https://vdblab.github.io/FLORAL/).

bioinformatics↗

bioRxiv2024

Sugar-rich foods exacerbate antibiotic-induced microbiome injury

Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury. One Sentence SummaryAnalyses of hematopoietic cell transplant patients and of mice uncover links between foods and microbiome disruption.

microbiology↗

bioRxiv2021

Mining underutilized whole-genome sequencing projects to improve 16S rRNA databases

Current approaches to interpreting 16S rDNA amplicon data are hampered by several factors. Among these are database inaccuracy or incompleteness, sequencing error, and biased DNA/RNA extraction. Existing 16S rRNA databases source the majority of sequences from deposited amplicon sequences, draft genomes, and complete genomes. Most of the draft genomes available are assembled from short reads. However, repeated ribosomal regions are notoriously difficult to assemble well from short reads, and as a consequence the short-read-assembled 16S rDNA region may be an amalgamation of different loci within the genome. This complicates high-resolution community analysis, as a draft genomes 16S rDNA sequence may be a chimera of multiple loci; in such cases, the draft-derived sequences in a database may not represent a 16S rRNA sequence as it occurs in biology. We present Focus16, a pipeline for improving 16S rRNA databases by mining NCBIs Sequence Read Archive for whole-genome sequencing runs that could be reassembled to yield additional 16S rRNA sequences. Using riboSeed (a genome assembly tool for correcting rDNA misassembly), Focus16 provides a way to augment 16S rRNA databases with high-quality re-assembled sequences. In this study, we augmented the widely-used SILVA 16S rRNA database with the novel sequences disclosed by Focus16 and re-processed amplicon sequences from several benchmarking datasets with DADA2. Using this augmented SILVA database increased the number of amplicon sequence variants that could be assigned taxonomic annotations. Further, fine-scale classification was improved by revealing ambiguities. We observed, for example, that amplicon sequence variants (ASVs) may be assigned to a specific genus where Focus16-correction would indicate that the ASV is represented in two or more genera. Thus, we demonstrate that improvements can be made to taxonomic classification by incorporating these carefully re-assembled 16S rRNA sequences, and we invite the community to expand our work to augment existing 16S rRNA reference databases such as SILVA, GreenGenes, and RDP.

bioinformatics↗

bioRxiv2017

riboSeed: leveraging prokaryotic genomic architecture to assemble across ribosomal regions

The vast majority of bacterial genome sequencing has been performed using Illumina short reads. Because of the inherent difficulty of resolving repeated regions with short reads alone, only {approx}10% of sequencing projects have resulted in a closed genome. The most common repeated regions are those coding for ribosomal operons (rDNAs), which occur in a bacterial genome between 1 and 15 times, and are typically used as sequence markers to classify and identify bacteria. Here, we exploit conservation in the genomic context in which rDNAs occur across taxa to improve assembly of these regions relative to de novo sequencing by using the conserved nature of rDNAs across taxa and the uniqueness of their flanking regions within a genome. We describe a method to construct targeted pseudocontigs generated by iteratively assembling reads that map to a reference genomes rDNAs. These pseudocontigs are then used to more accurately assemble the newly-sequenced chromosome. We show that this method, implemented as riboSeed, correctly bridges across adjacent contigs in bacterial genome assembly and, when used in conjunction with other genome polishing tools, can assist in closure of a genome.

bioinformatics↗