Biology subjects

Dick, D. W.

Publications and source records attributed to Dick, D. W..

3 recordsLinked to original sources

bioRxiv2024

Mucociliary Clearance is Impaired in Small Airways of Cystic Fibrosis Pigs

RationaleCystic fibrosis is a genetic disorder characterized by recurrent airway infections, inflammation, and progressive decline in lung function. Autopsy and spirometry data suggest that cystic fibrosis may start in the small airways which, due to the fractal nature of the airways, account for most of the airway tree surface area. However, they are not easily accessible for testing. ObjectivesHere, we tested the hypothesis that mucociliary clearance is abnormal in the small airways of newborn cystic fibrosis pigs. MethodsCurrent mucociliary clearance assays are limited therefore we developed a dynamic positron emission tomography scan assay with high spatial and temporal resolution. Each study was accompanied by a high-resolution computed tomography scan that helped identify the thin outer region of the lung that contained small airways. Measurements and Main ResultsClearance of aerosolized [68Ga]macro aggregated albumin from distal airways occurred within minutes after delivery and followed a two-phase process. In cystic fibrosis pigs, both early and late clearance rates were slower. Stimulation of the cystic fibrosis airways with the purinergic agonist UTP further impaired late clearance. Only 1 cystic fibrosis pig treated with UTP out of 6 cleared more than 20% of the delivered dose. ConclusionsThese data indicate that mucociliary transport in the small airways is fast and can easily be missed if the acquisition is not fast enough. The data also indicate that mucociliary transport is impaired in small airways of cystic fibrosis pigs. This defect is exacerbated by stimulation of mucus secretions with purinergic agonists.

physiology↗

bioRxiv2021

Revisiting the recombinant history of HIV-1 group M with dynamic network community detection

A new abundance of full-length HIV-1 genome sequences provides an opportunity to revisit the standard model of HIV-1/M diversity that clusters genomes into largely non-recombinant subtypes, which is not consistent with recent evidence of deep recombinant histories for SIV and other HIV-1 groups. Here we develop an unsupervised non-parametric clustering approach, which does not rely on predefined non-recombinant genomes, by adapting a community detection method developed for dynamic social network analysis. We show that this method (DSBM) attains a significantly lower mean error rate in detecting recombinant breakpoints in simulated data (quasibinomial GLM, P < 8 x 10-8), compared to other reference-free recombination detection programs (GARD, RDP4 and RDP5). Applied to a representative sample of n = 525 actual HIV-1 genomes, we determined k = 25 as the optimal number of DSBM clusters, and used change point detection to estimate that at least 95% of these genomes are recombinant. Further, we identified both known and novel recombination hotspots in the HIV-1 genome, and evidence of inter-subtype recombination in HIV-1 subtype reference genomes. We propose that clusters generated by DSBM can provide an informative new framework for HIV-1 classification.

evolutionary biology↗

bioRxiv2018

Evidence for a Recombinant Origin of HIV-1 group M from Genomic Variation

Reconstructing the early dynamics of the HIV-1 pandemic can provide crucial insights into the socioeconomic drivers of emerging infectious diseases in human populations, including the roles of urbanization and transportation networks. Current evidence indicates that the global pandemic comprising almost entirely of HIV-1/M originated around the 1920s in central Africa. However, these estimates are based on molecular clock estimates that are assumed to apply uniformly across the virus genome. There is growing evidence that recombination has played a significant role in the early history of the HIV-1 pandemic, such that different regions of the HIV-1 genome have different evolutionary histories. In this study, we have conducted a dated-tip analysis of all near full-length HIV-1/M genome sequences that were published in the GenBank database. We used a sliding window approach similar to the bootscanning method for detecting breakpoints in intersubtype recombinant sequences. We found evidence of substantial variation in estimated root dates among windows, with an estimated mean time to the most recent common ancestor (tMRCA) of 1922. Estimates were significantly autocorrelated, which was more consistent with an early recombination event than with stochastic error variation in phylogenetic reconstruction and dating analyses. A piecewise regression analysis supported the existence of at least one recombination breakpoint in the HIV-1/M genome with interval-specific means around 1929 and 1913, respectively. This analysis demonstrates that a sliding window approach can accommodate early recombination events outside the established nomenclature of HIV-1/M subtypes, although it is difficult to incorporate the earliest available samples due to their limited genome coverage.

evolutionary biology↗