Biology subjects

Wade, K.

Publications and source records attributed to Wade, K..

5 recordsLinked to original sources

bioRxiv2026

Population genomics reveals multi-scale mechanisms sustaining schistosomiasis re-emergence in a near-elimination setting

In China, sustained snail control, environmental management, and mass drug administration with praziquantel reduced schistosomiasis to near-elimination levels, yet re-emergence in Sichuan Province during the early 2000s exposed vulnerabilities in late-stage control. We conducted a novel investigation of Schistosoma japonicum re-emergence in Sichuan in order to identify the processes underlying re-emergence and to showcase how genomic data can be used in such investigations. We sequenced whole genomes from 270 miracidia collected from 53 human hosts across 17 villages in 2007 - the year after re-emergence was documented. Population genomic analyses revealed a broadly cohesive regional parasite population with weak geographic structuring. Genome-wide diversity was substantial, and demographic reconstructions revealed no recent decline in effective population size, demonstrating that parasite populations were not demographically fragmented at the onset of re-emergence, hinting at maintenance in reservoir populations. At finer spatial scales, several villages exhibited low diversity and elevated inbreeding, consistent with localized transmission maintained by small founding populations. Estimates of pairwise genetic relatedness revealed dense within-village sibling clusters alongside second- and third-degree relationships spanning villages, and rare first- and second-degree cross-village links. These findings are consistent with highly focal transmission with episodic parasite dispersal across villages, leading to a regional transmission network. Inferred minimum worm burden across hosts varied from 1 to 11 adult worm pairs, indicating heterogeneity in within-host parasite diversity, although uneven sampling limited inference. Together, these findings indicate that schistosomiasis re-emergence in this near-elimination setting was likely facilitated by a diverse parasite population maintained in reservoir populations, and that transmission, while predominantly local was occurring across a network of connected villages. This work illustrates how population genomics can reveal mechanisms driving re-emergence in late-stage elimination in complex, multi-host transmission systems. Author SummarySchistosomiasis is a parasitic disease that affects millions of people worldwide. Understanding the factors that contribute to persistence and transmission, even in the face of control programs, is central to reducing and ultimately eliminating the disease. In China, decades of intensive control efforts have dramatically reduced infections, yet the disease continued to persist in some regions. In this study, we analyzed the genomes of 270 parasite larvae collected from infected humans across 17 villages in Sichuan Province, China, shortly after schistosomiasis re-emerged in the region. By examining genetic relationships among parasites, we reconstructed patterns of transmission across villages and within individual infections. Our findings suggest that, despite major reductions in human infection prevalence, parasite populations sizes do not show signatures of recent population decline, indicating that non-human hosts may serve as key reservoirs promoting persistence. We also find that local transmission pathways, including clonal infections infecting multiple humans derived from a relatively small number of snail hosts, maintain parasite transmission pathways. Collectively, these findings suggest non-human hosts, intact local transmission pathways, and regional connectivity together enabled re-emergence, highlighting important challenges for elimination programs

genomics↗

bioRxiv2024

Synaptic alterations in pyramidal cells following genetic manipulation of neuronal excitability in monkey prefrontal cortex

In schizophrenia, layer 3 pyramidal neurons (L3PNs) in the dorsolateral prefrontal cortex (DLPFC) are thought to receive fewer excitatory synaptic inputs and to have lower expression levels of activity-dependent genes and of genes involved in mitochondrial energy production. In concert, these findings from previous studies suggest that DLPFC L3PNs are hypoactive in schizophrenia, disrupting the patterns of activity that are crucial for working memory, which is impaired in the illness. However, whether lower PN activity produces alterations in inhibitory and/or excitatory synaptic strength has not been tested in the primate DLPFC. Here, we decreased PN excitability in rhesus monkey DLPFC in vivo using adeno-associated viral vectors (AAVs) to produce Cre recombinase-mediated overexpression of Kir2.1 channels, a genetic silencing tool that efficiently decreases neuronal excitability. In acute slices prepared from DLPFC 7-12 weeks post-AAV microinjections, Kir2.1-overexpressing PNs had a significantly reduced excitability largely attributable to highly specific effects of the AAV-encoded Kir2.1 channels. Moreover, recordings of synaptic currents showed that Kir2.1-overexpressing DLPFC PNs had reduced strength of excitatory synapses whereas inhibitory synaptic inputs were not affected. The decrease in excitatory synaptic strength was not associated with changes in dendritic spine number, suggesting that excitatory synapse quantity was unaltered in Kir2.1-overexpressing DLPFC PNs. These findings suggest that, in schizophrenia, the excitatory synapses on hypoactive L3PNs are weaker and thus might represent a substrate for novel therapeutic interventions. Significance StatementIn schizophrenia, dorsolateral prefrontal cortex (DLPFC) pyramidal neurons (PNs) have both transcriptional and structural alterations that suggest they are hypoactive. PN hypoactivity is thought to produce synaptic alterations in schizophrenia, however the effects of lower neuronal activity on synaptic function in primate DLPFC have not been examined. Here, we used, for the first time in primate neocortex, adeno-associated viral vectors (AAVs) to reduce PN excitability with Kir2.1 channel overexpression and tested if this manipulation altered the strength of synaptic inputs onto the Kir2.1-overexpressing PNs. Recordings in DLPFC slices showed that Kir2.1 overexpression depressed excitatory (but not inhibitory), synaptic currents, suggesting that, in schizophrenia, the hypoactivity of PNs might be exacerbated by reduced strength of the excitatory synapses they receive.

neuroscience↗

bioRxiv2022

HexSE: Simulating evolution in overlapping reading frames

MotivationGene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may provide a mechanism to increase the information content of compact genomes. The presence of overlapping reading frames (OvRFs) can skew estimates of selection based on the rates of non-synonymous and synonymous substitutions, since a substitution that is synonymous in one reading frame may be non-synonymous in another, and vice versa. ResultsTo understand the impact of OvRFs on molecular evolution, we implemented a versatile simulation model of nucleotide sequence evolution along a phylogeny with any distribution of open reading frames in linear or circular genomes. We use a custom data structure to track the substitution rates at every nucleotide site, which is determined by the stationary nucleotide frequencies, transition bias, and the distribution of selection biases (dN/dS) in the respective reading frames. Availability and implementationOur simulation model is implemented in the Python scripting language. All source code is released under the GNU General Public License (GPL) version 3, and is available at https://github.com/PoonLab/HexSE.

bioinformatics↗

bioRxiv2021

CoVizu: Rapid analysis and visualization of the global diversity of SARS-CoV-2 genomes

Phylogenetics has played a pivotal role in the genomic epidemiology of SARS-CoV-2, such as tracking the emergence and global spread of variants, and scientific communication. However, the rapid accumulation of genomic data from around the world -- with over two million genomes currently available in the GISAID database -- is testing the limits of standard phylogenetic methods. Here, we describe a new approach to rapidly analyze and visualize large numbers of SARS-CoV-2 genomes. Using Python, genomes are filtered for problematic sites, incomplete coverage, and excessive divergence from a strict molecular clock. All differences from the reference genome, including indels, are extracted using minimap2, and compactly stored as a set of features for each genome. For each Pango lineage (https://cov-lineages.org), we collapse genomes with identical features into variants, generate 100 bootstrap samples of the feature set union to generate weights, and compute the symmetric differences between the weighted feature sets for every pair of variants. The resulting distance matrices are used to generate neigihbor-joining trees in RapidNJ and converted into a majority-rule consensus tree for the lineage. Branches with support values below 50% or mean lengths below 0.5 differences are collapsed, and tip labels on affected branches are mapped to internal nodes as directly-sampled ancestral variants. Currently, we process about million genomes in approximately nine hours on 34 cores. The resulting trees are visualized using the JavaScript framework D3.js as beadplots, in which variants are represented by horizontal line segments, annotated with beads representing samples by collection date. Variants are linked by vertical edges to represent branches in the consensus tree. These visualizations are published at https://filogeneti.ca/CoVizu. All source code was released under an MIT license at https://github.com/PoonLab/covizu.

bioinformatics↗

bioRxiv2017

Investigating the role of insulin in increased adiposity: Bi-directional Mendelian randomization study

Insulin may serve as a key causal agent which regulates fat accumulation in the body. Here we assessed the causal relationship between fasting insulin and adiposity using publicly-available results from two large-scale genome-wide association studies for body mass index and fasting insulin levels in a two-sample, bidirectional Mendelian Randomized approach. This approach is only valid on the condition that the two instruments are independent of one another. In analysis excluding overlapping loci, there was an increase of 0.20 (0.17, 0.23) log pmol/L fasting insulin per SD increase in BMI (P= 2.80 x 10-36), while there was a null effect of fasting insulin on BMI, with a 0.01 (-0.39, 0.38) SD decrease in BMI per log pmol/L increase in fasting insulin (P= 0.98). Furthermore, a high degree of heterogeneity in the causal estimates was obtained from the insulin-related variants, which may be attributed to varying mechanisms of action of the insulin-associated variants. Results were largely consistent when an Egger regression technique and weighted median and mode estimators were applied. Findings suggest that the positive correlation between adiposity and fasting insulin levels are at least in part explained by the causal effect of adiposity on increasing insulin, rather than vice versa.

epidemiology↗