Biology subjects

Carson, J.

Publications and source records attributed to Carson, J..

10 recordsLinked to original sources

bioRxiv2026

Mice in the Robbers Cave: Induction of intergroup conflict in mice using the competitive Tsunahiki task

Intergroup conflict is one of the most significant issues in human society. In the 1950s, Sherif et al. reported that intergroup conflict could be artificially induced in boys through intergroup competition with tug-of-war and ball games. Since this iconic study, researchers have developed various experimental methods to replicate intergroup competition and/or conflicts. However, although intergroup conflicts in wild animals are often reported, it has been difficult to establish a situation of intergroup conflict in laboratory rodents that is discriminable from aggressive behavior individually. In this study, we established a novel experimental paradigm for intergroup competition in mice in which the members of each group shared objectives and tasks. Adult male ICR/Jcl mice were housed in groups of six, divided into two teams of three and repeatedly performed a competitive Tsunahiki task (tsunahiki means tug-of-war in Japanese). The competitive Tsunahiki task was conducted in an open field divided into two experimental fields, with three ropes stuck to a wall separating the fields. The mice were required to pull two ropes out faster than their opponent team to win, and only the winners could proceed to the reward area separated by a guillotine door. We demonstrated that the experience of the competitive Tsunahiki task induced attack bites selectively toward members of the other team (out-group members). Our findings suggest that intergroup competition induces intergroup conflict in mice, providing a technical breakthrough in elucidating the detailed neuroscientific mechanisms underlying intergroup conflict.

animal behavior and cognition↗

bioRxiv2025

Diagnostics of dated phylogenies in microbial population genetics

Microbial population genetic studies often involve the use of a dated phylogeny to show how the genomes are related over a relevant timescale. Many tools have recently been developed to date the nodes of a standard phylogeny, but all make underlying assumptions that may not be realistic for a given dataset, making the results potentially unreliable. Model comparison is sometimes used to remedy this issue, whereby inference under several models is compared to establish which result can be trusted. Although such comparison is clearly useful to assess the relative merits of several inference attempts, here instead we focus on the problem of evaluating how good an inference is in absolute terms, without comparison. We consider several approaches for diagnosing potential issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis. These methods are well-established diagnostics tools in other areas of statistics, but here we show how they can be applied to the specific inference of dated phylogenies. We illustrate their use on many simulated datasets, with inference being performed either from the correct model to quantify the specificity or from an incorrect model to quantify the sensitivity of the diagnostics methods. We also applied the methods to three real-life datasets to showcase the range of issues that they can detect. We advocate the use of these diagnostics tools for all microbial population genetic studies that involve the reconstruction of a dated phylogeny.

evolutionary biology↗

bioRxiv2025

Impacts of disease surveillance frequency on understanding and controlling Rift Valley fever virus

Effective livestock disease surveillance faces numerous socio-economic and disease-specific challenges, particularly within resource-limited settings. Rift Valley fever (RVF), a zoonotic vector-borne disease which is of growing threat to human and veterinary health, exemplifies these challenges, consequently leading to irregular or infrequent surveillance. While mathematical models frequently utilise these surveillance data to understand disease dynamics and assess the effectiveness of disease control measures, the impact of surveillance frequency on these model-based assessments is not clear. To address this, we used a livestock RVF virus infection model, which incorporates spatial and age structures, livestock movement, and environmental factors. We then generated synthetic cross-sectional seroprevalence surveys with varying frequencies from outbreak scenarios inferred from empirical serological data from the Comoros archipelago. By refitting the model to these synthetic data, we found that lower surveillance frequency was associated with increased uncertainties in understanding disease biology, inferring past outbreak timing, predicting future outbreak size, and recommending optimal control measures. In particular, once serological surveillance was less frequent than annually, the ability to distinguish spatio-temporal patterns of disease transmission and forecast trends diminished. These findings emphasise the need for adequately frequent surveillance data to ensure robust model-based analyses which inform effective preparedness and control strategies for livestock diseases within resource-limited settings. Author summaryDisease surveillance underpins mathematical models that are used to understand the emergence, spread and persistence of disease, and assess and compare the impacts of disease control measures. However, regular surveillance is a particular challenge for livestock diseases in resource-limited settings, such as those affected by Rift Valley fever. Here, our work provides an illustrative example of how surveillance frequency impacts our ability to understand disease outbreaks and to decide which control measures are most effective at combatting disease, using outbreak scenarios for Rift Valley fever in the Comoros archipelago. By simulating from a mathematical model informed by different surveillance frequencies, we found that less frequent surveillance was associated with greater uncertainty in model predictions, and demonstrated that this may distort epidemiological understanding and future control recommendations of a disease. Our work has crucial implications for animal health decision-making, highlighting the importance of consistent and frequent surveillance to improve disease management and prioritise disease control measures.

ecology↗

bioRxiv2024

Structure-Based Design of Small-Molecule Inhibitors of Human Interleukin-6

Human Interleukin-6 (hIL-6) is a pro inflammatory cytokine that binds to its receptor, IL-6R followed by binding to gp130 and subsequent dimerization to form a hexamer signaling complex. A critical inflammation mediator, hIL-6 is associated with a diverse range of diseases and monoclonal antibodies are in clinical use that either target IL-6R or hIL-6 to inhibit signaling. Here, we perform high throughput structure-based computational screening using ensemble docking for small molecule antagonists for which the target conformations were taken from 600 ns long molecular dynamics simulations of the apo protein. Prior knowledge of the contact sites from binary complex studies and experimental work was incorporated into the docking studies. The top 20 scored ligands from the in silico studies after post analysis were subjected to in vitro functional assays. Among these compounds, the ligand with second-highest calculated binding affinity showed experimentally [~]84% inhibitory effect on IL6-induced STAT3 reporter activity at 10-5 molar concentration. This finding may pave the way for designing small molecule inhibitors of hIL-6 of therapeutic significance.

bioinformatics↗

bioRxiv2024

An Accessible 3D HepG2/C3A Liver Spheroid Model Supporting the Complete Intrahepatocytic Lifecycle of Plasmodium falciparum

Current liver-stage Plasmodium falciparum models are complex, expensive, and largely inaccessible, hindering research progress. Here, we show that a 3D liver spheroid model grown from immortalized HepG2/C3A cells supports the complete intrahepatocytic lifecycle of P. falciparum. Our results demonstrate sporozoite infection, development of exoerythrocytic forms, and breakthrough infection into erythrocytes. The 3D-grown spheroid hepatocytes are structurally and functionally polarised, displaying enhanced albumin and urea production and increased expression of key metabolic enzymes, mimicking in vivo conditions - relative to 2D cultures. This accessible, reproducible model lowers barriers to malaria research, promoting advancements in fundamental biology and translational research.

microbiology↗

bioRxiv2024

Experimental challenge of Chinook salmon with Tenacibaculum maritimum and Tenacibaculum dicentrarchi fulfils Kochs postulates

The bacterial skin disease tenacibaculosis, caused by Tenacibaculum species, can compromise numerous species of economically important marine fish, including salmonids. While tenacibaculosis is a known threat to Atlantic salmon (Salmo salar) aquaculture, the pathogenesis of Tenacibaculum maritimum and Tenacibaculum dicentrarchi on Chinook salmon (Oncorhynchus tshawytscha) has not yet been investigated. In this study, three molecular O-AGC types of T. maritimum (O-AGC Type 3-0, Type 2-1 and Type 3-2) and T. dicentrarchi isolated during a disease outbreak of farmed Chinook salmon in Aotearoa New Zealand were assessed for their ability to induce tenacibaculosis in salmon smolts under controlled conditions. Naive Chinook salmon were exposed to T. maritimum or T. dicentrarchi by immersion. Clinical signs of tenacibaculosis were apparent post-exposure and observed in 100% of all three molecular O-AGC types of T.-maritimum-challenged fish, with 100% morbidity in O-AGC Type 2-1 and Type 3-2 and 60% in O-AGC Type 3-0. Chinook salmon exposed to T. dicentrarchi showed characteristic clinical signs of disease in 51% of the challenged population, with 28% morbidity. Common gross pathological signs observed for both Tenacibaculum species were congruent with observations on farmed fish in the field, including scale loss, erythematous skin lesion, skin ulcers, fin necrosis, mouth erosion and gill ulceration. Exophthalmia was observed only in T. maritimum-challenged fish, while skin ulcers appeared grossly more severe with exposed musculature in T. dicentrarchi-challenged fish. Pure T. maritimum and T. dicentrarchi cultures were reisolated from the skin and gills of the challenged fish and their identity was confirmed by species-specific PCR and molecular O-AGC typing. Challenge experiments and associated field surveillance (for T. maritimum) did not show the presence of culturable T. maritimum cells in the anterior kidney. This provides compelling evidence that tenacibaculosis in farmed Chinook salmon is an external infectious disease, and that Tenacibaculum is a marine obligate organism that is unable to survive in fish body fluids and does not cause septicaemia. This has repercussions for approaches to experimental challenges with Tenacibaculum species, which must occur by immersion rather than intraperitoneal or intramuscular inoculation, to replicate the natural transmission pathway and to ensure a successful challenge model. This study fulfilled modernised Kochs postulates for the three molecular O-AGC types of T. maritimum and single strain of T. dicentrarchi as aetiological agents of tenacibaculosis in Chinook salmon that cause mortalities with considerable external abnormalities. Author summaryChinook salmon, Oncorhynchus tshawytscha, is the most significant species of Pacific salmon for its large size and nutritional content which makes it a premium choice for aquaculture. In Aotearoa|New Zealand, Chinook salmon is the only marine salmon species farmed. For a decade, the industry was impacted by an undiagnosed skin disease resulting in high mortalities. Disease susceptibility in Chinook salmon is scarcely studied and added to the challenge for a timely diagnosis. This novel research provides insight on disease susceptibility of Chinook salmon and confirms Tenacibaculum species identified in New Zealand pose a high threat to the aquaculture industry. This research has global implications and contributes valuable insights and approaches to disease management that can be applied in British Columbia and Canada where Chinook salmon populations are in decline.

microbiology↗

bioRxiv2023

Inference of infectious disease transmission using multiple genomes per host

In recent times, pathogen genome sequencing has become increasingly used to investigate infectious disease outbreaks. When genomic data is sampled densely enough amongst infected individuals, it can help resolve who infected whom. However, transmission analysis cannot rely solely on a phylogeny of the genomes but must account for the within-host evolution of the pathogen, which blurs the relationship between phylogenetic and transmission trees. When only a single genome is sampled for each host, the uncertainty about who infected whom can be quite high. Consequently, transmission analysis based on multiple genomes of the same pathogen per host has a clear potential for delivering more precise results, even though it is more laborious to achieve. Here we present a new methodology that can use any number of genomes sampled from a set of individuals to reconstruct their transmission network. We use simulated data to show that our method becomes more accurate as more genomes per host are provided, and that it can infer key infectious disease parameters such as the size of the transmission bottleneck, within-host growth rate, basic reproduction number and sampling fraction. We demonstrate the usefulness of our method in applications to real datasets from an outbreak of Pseudomonas aeruginosa amongst cystic fibrosis patients and a nosocomial outbreak of Klebsiella pneumoniae.

microbiology↗

bioRxiv2022

The bounded coalescent model: conditioning a genealogy on a minimum root date

The coalescent model represents how individuals sampled from a population may have originated from a last common ancestor. The bounded coalescent model is obtained by conditioning the coalescent model such that the last common ancestor must have existed after a certain date. This conditioned model arises in a variety of applications, such as speciation, horizontal gene transfer or transmission analysis, and yet the bounded coalescent model has not been previously analysed in detail. Here we describe a new algorithm to simulate from this model directly, without resorting to rejection sampling. We show that this direct simulation algorithm is more computationally efficient than the rejection sampling approach. We also show how to calculate the probability of the last common ancestor occurring after a given date, which is required to compute the probability of realisations under the bounded coalescent model. Our results are applicable in both the isochronous (when all samples have the same date) and heterochronous (where samples can have different dates) settings. We explore the effect of setting a bound on the date of the last common ancestor, and show that it affects a number of properties of the resulting phylogenies. All our methods are implemented in a new R package called BoundedCoalescent which is freely available online.

evolutionary biology↗

bioRxiv2021

LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a broad-spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease and drug treatment. These atlases are provided as independent and integrated queriable datasets, with an emphasis on dynamic visualization, figure generation and reference-based classification of user-provided datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, data portals and datasets from LungMAP and external research efforts.

systems biology↗

bioRxiv2021

Integration of whole genome sequencing and transcriptomics reveals a complex picture of insecticide resistance in the major malaria vector Anopheles coluzzii

Insecticide resistance is a major threat to gains in malaria control, which have been stalling and potentially reversing since 2015. Studies into the causal mechanisms of insecticide resistance are painting an increasingly complicated picture, underlining the need to design and implement targeted studies on this phenotype. In this study, we compare three populations of the major malaria vector An. coluzzii: a susceptible and two resistant colonies with the same genetic background. The original colonised resistant population rapidly lost resistance over a 6-month period, a subset of this population was reselected with pyrethroids a third population of this colony that did not lose resistance was also available. The original resistant, susceptible and re-selected colonies were subject to RNAseq and whole genome sequencing, which identified a number of changes across the transcriptome and genome linked with resistance. Firstly, an increase in the expression of genes within the oxidative phosphorylation pathway were seen in both resistant populations compared to the susceptible control; this translated phenotypically through an increased respiratory rate, indicating that elevated metabolism is linked directly with resistance. Genome sequencing highlighted several blocks clearly associated with resistance, including the 2Rb inversion. Finally, changes in the microbiome profile were seen, indicating that the microbial composition may play a role in the resistance phenotype. Taken together, this study reveals a highly complicated phenotype in which multiple transcriptomic, genomic and microbiome changes combine to result in insecticide resistance.

genomics↗