Biology subjects

Silk, M.

Publications and source records attributed to Silk, M..

9 recordsLinked to original sources

bioRxiv2025

Fragmented social networks promote complex behavioural contagions over infectious disease spread

Group living and social interactions among animals provide key benefits, such as the exchange of beneficial social information and novel behaviours, but also pose the risk of spreading costly infectious diseases, presenting a social trade-off. While both information and infections spread across social networks, they typically have distinct mechanisms of transmission. Here, we model social information and behaviour spread as a complex contagion governed by a conformist learning rule, while pathogen transmission follows a simple contagion mechanism. Building on theoretical foundations, our study applies computational models to examine how subgroup structure (modularity) influences the spread of these contagions across diverse animal social structures sourced from the Animal Social Network Repository (ASNR). Our findings reveal that high modularity and subgroup structure slow simple contagion spread, whereas complex contagions are less impeded by this fragmentation. Consequently, our results suggest that social networks divided into small groups or subgroups can help balance the competing pressures of acquiring social information and avoiding infectious disease in real-world networks.

ecology↗

bioRxiv2024

Polymorphic tandem repeats shape single-cell gene expression across the immune landscape

Tandem repeats (TRs) - highly polymorphic, repetitive sequences across the human genome - are important regulators of gene expression but remain underexplored due to challenges in accurate genotyping and analysis1. Here, we generate new whole genome and single-cell RNA sequencing from >5.4 million blood-derived cells across 1,925 individuals in two cohorts [Cuomo et al., accompanying manuscript], and perform meta-analysis to characterize the impact of variation in >1.7 million TR loci on immune cell type-specific gene expression. We identify >69,000 single-cell expression TR loci (sc-eTRs), 30.7% of which are specific to one of 28 immune cell types, and reveal dynamic regulatory effects using cell-state inference. Matched single-cell ATAC sequencing profiles from >3.4 million nuclei in 922 individuals [Xue et al., accompanying manuscript]. uncover chromatin accessibility QTLs for nearly one-third of expression-associated TRs, supporting coordinated effects on cis-regulatory architecture. Fine-mapping implicates 1,490 TRs as candidate causal drivers of gene expression in 6.1% of tested genes, and colocalization analyses highlight >200 genes in which TRs likely mediate genetic associations with immune and hematological traits. Together, these results provide a genome-wide, multiomic view of TR-mediated regulation in the human immune system, establishing TRs as key contributors to cell type-specific regulatory variation and complex trait architecture.

genomics↗

bioRxiv2024

Density-dependent network structuring within and across wild animal systems

High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems.

ecology↗

bioRxiv2024

Spatial-temporal dynamics of contact among free-ranging domestic dogs Canis familiaris in rural Africa

1. Transmission of infection is affected by the spatial-temporal dynamics of host contacts. Domestic dogs Canis familiaris share pathogens with humans and wildlife, and managing dog-mediated diseases is a priority for public health and conservation interests. 2. We combined proximity sensors and GPS tracking to analyse spatial-temporal variation in contact among free-ranging dogs in six villages in rural Chad, during both the wet and dry seasons. We investigated dyadic interactions between dogs from different villages, the same village but different households and the same household. We assessed variation in (i) the probability of individuals having had contact, (ii) the hourly frequency of contact and (iii) contact durations. 3. Our results highlight clear seasonal and hourly patterns in contact behaviour. Contacts between dogs from different villages were rare, short in duration, primarily between male-female dyads and predominantly occurred within villages and during the dry season. Contact between dogs in the same village peaked at dawn and dusk. Sex differences were most pronounced in the wet season, where males from different households had the highest hourly contact probabilities, followed by male-female dyads. For all dogs, contact durations were longer in the dry season, but showed little hourly variation. 4. Contact patterns were not equal in space, and the probability of individuals having had contact was less than 5% when dwellings were more than 500m apart. Spatially, the probability of contact was lowest outside the village, but this increased in the dry season and peaked in the morning hours. Contact durations were notably longer outside the village, where they increased in duration for between-household dyads in the dry season. 5. At a coarse temporal scale, variation in dog contacts within and among households, and rarely between villages, may underpin seasonal variation in the incidence of dog-mediated diseases. Variation at finer temporal (hourly) and spatial scales (around households, within and outside villages) highlights the importance of routine behaviours and space use in determining patterns of contact between dogs. Practitioners should consider behavioural heterogeneities, such as those reported here, when using strategic models to support disease management decisions.

animal behavior and cognition↗

bioRxiv2024

Both environmental conditions and intra- and interspecific interactions influence the movements of a marine predator

Animal movements are typically influenced by multiple environmental factors simultaneously and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply Exponential Random Graph Models (ERGMs) to analyse movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social or other types of covariates on their movements. We found that intra- and interspecific factors often had stronger effects on movements than environmental variables. ERGMs proved to be a potentially useful tool for studying animal movement network data especially in the context of spatial attribute heterogeneity.

ecology↗

bioRxiv2022

The spectral underpinnings of pathogen spread on animal networks

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

ecology↗

bioRxiv2021

Insights from spatial measures of intolerance to identify pathogenic variants in developmental and epileptic encephalopathies

Developmental and epileptic encephalopathies (DEEs) are a group of epilepsies with early onset and severe symptoms that sometimes lead to death. While a number of genes have been successfully implicated, it remains challenging to identify causative mutations within these genes from the background variation present in all individuals due to disease heterogeneity. Our ability to detect likely pathogenic variants has continued to improve as in silico predictors of deleteriousness have advanced. We investigate their use in prioritising likely pathogenic variants in epileptic encephalopathy patient whole exome sequences and show that the inclusion of structure-based predictors of intolerance improve upon previous attempts to demonstrate enrichment within epilepsy genes.

neuroscience↗

bioRxiv2020

COVID-3D: An online resource to explore the structural distribution of genetic variation in SARS-CoV-2 and its implication on therapeutic development

The emergence of the COVID-19 pandemic has spurred a global rush to uncover basic biological mechanisms, to inform effective vaccine and drug development. Despite viral novelty, global sequencing efforts have already identified genomic variation across isolates. To enable easy exploration and spatial visualization of the potential implications of SARS-CoV-2 mutations on infection, host immunity and drug development we have developed COVID-3D (http://biosig.unimelb.edu.au/covid3d/).

bioinformatics↗

bioRxiv2019

Missense mutations in the MLKL brace region lead to lethal neonatal inflammation in mice and are present in high frequency in humans.

We have isolated a mouse strain with a single missense mutation in the gene encoding MLKL, the essential effector of necroptotic cell death. The resulting substitution lies within the two-helix brace and confers constitutive, RIPK3 independent, killing activity to MLKL. Mice homozygous for MlklD139V develop lethal inflammation within days of birth, implicating the salivary glands and pericardium as hotspots for necroptosis and inflammatory infiltration. The normal development of MlklD139V homozygotes until birth, and the absence of any overt phenotype in heterozygotes provides important in vivo precedent for the capacity of cells to clear activated MLKL. These observations offer an important insight into the potential disease-modulating roles of three common human MLKL polymorphisms that encode amino acid substitutions within or adjacent to the brace region. Compound heterozygosity of these variants is found at up to 12-fold the expected frequency in patients that suffer from a pediatric autoinflammatory disease, CRMO.

cell biology↗