Biology subjects

Durham, T.

Publications and source records attributed to Durham, T..

5 recordsLinked to original sources

bioRxiv2026

Hydrogen sulfide dynamically upregulates copper uptake and localization

The reactivity of copper, an essential micronutrient that undergoes facile cycling between Cu1+ and Cu2+ redox states, is carefully controlled within the confines of protein binding sites, and by sequestration in storage vesicles, or harnessed to kill pathogens by active pumping of Cu1+ into phagosomes. We have discovered that hydrogen sulfide, a signaling metabolite generated in copious quantities at the host-microbiome interface, upregulates Cu accumulation in diffusely dispersed puncta across the cell, as visualized by X-ray fluorescence microscopy. The Cu is predominantly in the Cu2+ state with oxygen/nitrogen ligands. Cu import occurs via the non- canonical ZNT1 transporter, while export, following sulfide withdrawal, is ATP7A-dependent. Cu accumulates at the apices of colon crypts in a mouse model of elevated sulfide exposure due to SQOR deficiency in the intestinal epithelium, establishing in vivo relevance. Our study reveals that sulfide is a dynamic regulator of the Cu pool, stimulating Cu2+ influx into highly concentrated puncta.

cell biology↗

bioRxiv2025

Himito: a Graph-based Toolkit for Mitochondrial Genome Analysis using Long Reads

Understanding the genetic and epigenetic regulation of mitochondrial DNA (mtDNA) is essential for elucidating mechanisms of aging and disease. Long-read sequencing can span the entire mitochondrial genome and directly capture base-modification signals, yet analytical tools for such data remain limited. We developed Himito, a graph-based toolkit for analyzing mitochondrial genome using long reads. Himito filters reads originating from nuclear mitochondrial insertions (NUMTs), constructs a sequence graph to represent mtDNA diversity, assembles primary haplotypes, calls variants, and analyzes 5-methylcytosine (5mC) modifications within a unified framework. Benchmarking on high-quality reference datasets shows Himito achieves superior performance in assembly and variant calling compared with existing tools. Applied to the All of Us (AoU) v8 dataset, Himito identified pathogenic mtDNA variants, revealed population-scale haplogroup diversity, and uncovered age-related genetic and epigenetic patterns. These results demonstrate that long-read sequencing, combined with graph-based analysis, enables integrated characterization of mitochondrial genomic and epigenomic variation. Himito is available at https://github.com/broadinstitute/Himito.

bioinformatics↗

bioRxiv2022

Scene-selective brain regions respond to embedded objects of a scene

Objects are fundamental to scene understanding. Scenes are defined by embedded objects and how we interact with them. Paradoxically, scene processing in the brain is typically discussed in contrast to object processing. Using the BOLD5000 dataset (Chang et al., 2019), we examined whether objects within a scene predicted the neural representation of scenes, as measured by fMRI in humans. Stimuli included 1,179 unique scenes across 18 semantic categories. Object composition of scenes were compared across scene exemplars in different semantic categories, and separately, in exemplars of the same category. Neural representations in scene- and object-preferring brain regions were significantly related to which objects were in a scene, with the effect at times stronger in the scene-preferring regions. The object model accounted for more variance when comparing scenes within the same semantic category to scenes from different categories. Thus, the functional role of scene-preferring regions should include the processing of objects. This suggests visual processing regions may be better characterized with respect to which processes are engaged when interacting with the stimulus category, such as processing groups of objects in scenes, or processing a single object in our foreground, rather than the stimulus category itself.

neuroscience↗

bioRxiv2018

Towards inferring causal gene regulatory networks from single cell expression measurements

Single-cell transcriptome sequencing now routinely samples thousands of cells, potentially providing enough data to reconstruct causal gene regulatory networks from observational data. Here, we present Scribe, a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe employs Restricted Directed Information to determine causality by estimating the strength of information transferred from a potential regulator to its downstream target. We apply Scribe and other leading approaches for causal network reconstruction to several types of single-cell measurements and show that there is a dramatic drop in performance for \"pseudotime\" ordered single-cell data compared to true time series data. We demonstrate that performing causal inference requires temporal coupling between measurements. We show that methods such as \"RNA velocity\" restore some degree of coupling through an analysis of chromaffin cell fate commitment. These analyses therefore highlight an important shortcoming in experimental and computational methods for analyzing gene regulation at single-cell resolution and point the way towards overcoming it.

genomics↗

bioRxiv2018

Functional Characterization of Enhancer Evolution in the Primate Lineage

BackgroundEnhancers play an important role in morphological evolution and speciation by controlling the spatiotemporal expression of genes. Due to technological limitations, previous efforts to understand the evolution of enhancers in primates have typically studied many enhancers at low resolution, or single enhancers at high resolution. Although comparative genomic studies reveal large-scale turnover of enhancers, a specific understanding of the molecular steps by which mammalian or primate enhancers evolve remains elusive.\n\nResultsWe identified candidate hominoid-specific liver enhancers from H3K27ac ChIP-seq data. After locating orthologs in 11 primates spanning [~]40 million years, we synthesized all orthologs as well as computational reconstructions of 9 ancestral sequences for 348 \"active tiles\" of 233 putative enhancers. We concurrently tested all sequences (20 per tile) for regulatory activity with STARR-seq in HepG2 cells, with the goal of characterizing the evolutionary-functional trajectories of each enhancer. We observe groups of enhancer tiles with coherent trajectories, most of which can be explained by one or two mutational events per tile. We quantify the correlation between the number of mutations along a branch and the magnitude of change in functional activity. Finally, we identify 57 mutations that correlate with functional changes; these are enriched for cytosine deamination events within CpGs, compared to background events.\n\nConclusionsWe characterized the evolutionary-functional trajectories of hundreds of liver enhancers throughout the primate phylogeny. We observe subsets of regulatory sequences that appear to have gained or lost activity at various positions in the primate phylogeny. We use these data to quantify the relationship between sequence and functional divergence, and to identify CpG deamination as a potentially important force in driving changes in enhancer activity during primate evolution.

genomics↗