Biology subjects

Wilton, R.

Publications and source records attributed to Wilton, R..

6 recordsLinked to original sources

bioRxiv2026

A network perspective on the role of c-di-GMP-associated protein complexes in biofilm formation.

1.The secondary messenger cyclic di-GMP is a ubiquitous bacterial signal that regulates the switch from a free-swimming to a sessile biofilm-forming lifestyle. Many biofilm-forming Pseudomonas species possess numerous c-di-GMP-binding proteins (CDGs) which regulate gene expression, protein activity, and protein complexes. However, the mechanisms by which numerous CDG effectors form a coherent signaling network to coordinate lifestyle changes remain poorly understood. We addressed this knowledge gap by focusing on ten CDG proteins involved in biofilm development in P. fluorescens SBW25. We used an integrated approach combining a protein interaction network from genome-wide yeast two-hybrid (Y2H) screens with large-scale biofilm and motility phenotype analyses via CRISPR interference (CRISPRi). Our network associated c-di-GMP signaling with processes such as signal transduction, solute transport, secretion, virulence, transcriptional regulation, DNA repair, and cell division. We discovered unknown functions of two CDG proteins in DNA repair and cell division, supporting the significance of our network. Notably, the phosphodiesterase DipA interacts with numerous CDG proteins through GGDEF domains. Phenotypic analyses revealed that CDG partners were highly correlated or strongly anticorrelated with DipA. These findings suggest that DipA is a central hub for CDG interactions that integrates opposing modules. These findings support the hub-based model of c-di-GMP signaling, which is crucial for localized control and rapid adaptation to environmental changes.

microbiology↗

bioRxiv2022

BiocMAP: A Bioconductor-friendly, GPU-Accelerated Pipeline for Bisulfite-Sequencing Data

BackgroundBisulfite sequencing is a powerful tool for profiling genomic methylation, an epigenetic modification critical in the understanding of cancer, psychiatric disorders, and many other conditions. Raw data generated by whole genome bisulfite sequencing (WGBS) requires several computational steps before it is ready for statistical analysis, and particular care is required to process data in a timely and memory-efficient manner. Alignment to a reference genome is one of the most computationally demanding steps in a WGBS workflow, taking several hours or even days with commonly used WGBS-specific alignment software. This naturally motivates the creation of computational workflows that can utilize GPU-based alignment software to greatly speed up the bottleneck step. In addition, WGBS produces raw data that is large and often unwieldy; a lack of memory-efficient representation of data by existing pipelines renders WGBS impractical or impossible to many researchers. ResultsWe present BiocMAP, a Bioconductor-friendly Methylation Analysis Pipeline consisting of two modules, to address the above concerns. The first module performs computationally-intensive read alignment using Arioc, a GPU-accelerated short-read aligner. The extraction module extracts and merges DNA methylation proportions - the fractions of methylated cytosines across all cells in a sample at a given genomic site. Since GPUs are not always available on the same computing environments where traditional CPU-based analyses are convenient, BiocMAP is split into two modules, with just the alignment module requiring an available GPU. Bioconductor-based output objects in R utilize an on-disk data representation to drastically reduce required main memory and make WGBS projects computationally feasible to more researchers. ConclusionsBiocMAP is implemented using Nextflow and available at http://research.libd.org/BiocMAP/. To enable reproducible analysis across a variety of typical computing environments, BiocMAP can be containerized with Docker or Singularity, and executed locally or with the SLURM or SGE scheduling engines. By providing Bioconductor objects, BiocMAPs output can be integrated with powerful analytical open source software for analyzing methylation data.

bioinformatics↗

bioRxiv2020

Widespread methylation quantitative trait loci and their role in schizophrenia risk

DNA methylation (DNAm) regulates gene expression and may represent gene-environment interactions. Using whole genome bisulfite sequencing, we surveyed DNAm in a large sample (n=344) of human brain tissues. We identify widespread genetic influence on local methylation levels throughout the genome, with 76% of SNPs and 38% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting putative functional regions that explain much of the heritability associated with risk loci. Furthermore, some CpH sites associated with genetic variation. We have established a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain. One-sentence summaryMost genetic variants associated with DNA methylation levels, and implicated schizophrenia GWAS variants in the human brain.

genomics↗

bioRxiv2019

Characterizing the dynamic and functional DNA methylation landscape in the developing human cortex

DNA methylation (DNAm) is a key epigenetic regulator of gene expression across development. The developing prenatal brain is a highly dynamic tissue, but our understanding of key drivers of epigenetic variability across development is limited. We therefore assessed genomic methylation at over 39 million sites in the prenatal cortex using whole genome bisulfite sequencing and found loci and regions in which methylation levels are dynamic across development. We saw that DNAm at these loci was associated with nearby gene expression and enriched for enhancer chromatin states in prenatal brain tissue. Additionally, these loci were enriched for genes associated with psychiatric disorders and genes involved with neurogenesis. We also found autosomal differences in DNAm between the sexes during prenatal development, though these have less clear functional consequences. We lastly confirmed that the dynamic methylation at this critical period is specifically CpG methylation, with very low levels of CpH methylation. Our findings provide detailed insight into prenatal brain development as well as clues to the pathogenesis of psychiatric traits seen later in life.

neuroscience↗

bioRxiv2018

RMI-chip: a microfluidics setup for functional imaging of microbial interactions with tree roots

Coupling microfludics with microscopy has emerged as a powerful approach to study at cellular resolution the dynamics in plant physiology and root-microbe interactions. Most devices have been designed to study the model plant Arabidopsis thaliana at higher throughput than conventional methods. However, there is a need for microfluidic devices which enable in vivo studies of root development and root-microbe interactions in woody plants. Here, we developed the RMI-chip, a simple microfluidic setup in which Populus tremuloides (aspen tree) seedlings can grow for over a month, allowing continuous microscopic observation of interactions between live roots and rhizobacteria. We find that the colonization of growing aspen roots by Pseudomonas fluorescens in the RMI-chip involves dynamic biofilm formation and dispersal, in keeping with previous observations in a different experimental set-up. Also, we find that whole-cell biosensors based on the rhizobacterium Bacillus subtilis can be used to monitor compositional changes in the rhizosphere but that the application of these biosensors is limited by their efficiency at colonizing aspen roots and persisting. These results indicate that functional imaging of dynamic root-bacteria interactions in the RMI-chip requires careful matching between the host plant and the bacterial root colonizer.

physiology↗

bioRxiv2017

GPU-accelerated alignment of bisulfite-treated short-read sequences

The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a large genome involves a significant computational burden beyond that required to align non-bisulfite-treated reads. In the analysis of BS-seq data, this can present an important performance bottleneck that can potentially be addressed by appropriate software-engineering and algorithmic improvements. One strategy is to integrate this additional programming logic into the read-alignment implementation in a way that the software becomes amenable to optimizations that lead to both higher speed and greater sensitivity than can be achieved without this integration.\n\nWe have evaluated this approach using Arioc, a short-read aligner that uses GPU (general-purpose graphics processing unit) hardware to accelerate computationally-expensive programming logic. We integrated the BS-seq computational logic into both GPU and CPU code throughout the Arioc implementation. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments reported by the most widely used BS-seq read aligners. With simulated reads, Arioc's accuracy is equal to or better than the other read aligners we evaluated. With human sequencing reads, Arioc's throughput is at least 10 times faster than existing BS-seq aligners across a wide range of sensitivity settings.\n\nThe Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.

bioinformatics↗