Biology subjects

Coleman, S.

Publications and source records attributed to Coleman, S..

16 recordsLinked to original sources

bioRxiv2026

Charting developmental trajectories of dynamic brain networks during emotional face processing

Emotional face processing is a critical component in the development of social cognition through childhood. The neural mechanisms supporting this development can be understood by tracking age-related changes in brain activity. Prior work in this area with MEG relies on static, bandlimited, or region-specific measures, which do not capture the dynamic, distributed nature of brain activity. Here we used Dynamic Network Modes (DyNeMo) to analyze MEG data from a large cohort of typically developing individuals (N=224, ages 5-40) during an emotional faces vigilance task. DyNeMo is a data-driven, generative modelling approach which captures functional networks as a set of whole-brain spatiospectral "modes" whose relative mixture (i.e., activation levels) can change dynamically in response to stimuli. We inferred six modes from the MEG data and characterized developmental trajectories in task-related activation and mode connectivity. Across modes we observed distinct developmental trajectories in both measures. With respect to mode activation, a visual mode and a frontotemporal mode (whose labels reflect their respective spatial profiles) increased nonlinearly with age; meanwhile, activation in temporal and sensorimotor modes decreased linearly with age. Meanwhile, connectivity broadly increased with age in all modes, but with different degrees of nonlinearity. These results suggest developmental dissociations between different modes (e.g., visual versus sensorimotor), as well as within individual modes (task-related mode activation versus connectivity). These results provide a comprehensive and complex picture of functional network development underlying emotional face processing. Significance StatementBrain networks supporting social cognition undergo profound changes from childhood through adolescence to adulthood. However, current understanding of how these networks develop has been limited by conventional analyses of brain imaging data, which typically provide a static picture of brain activity. Here we leveraged a cutting-edge, data-driven modeling approach (DyNeMo) to characterize age-related changes in distributed and dynamic networks supporting emotional face processing, in a large cohort of children and young adults (N=224). We inferred six functional networks whose activation levels changed rapidly in response to emotional faces. Network activation and connectivity exhibited profound and distinct non-linear changes with age, indicating that emotional face processing is supported by complex interactions among multiple dynamic networks, each with different maturational trajectories.

neuroscience↗

bioRxiv2025

Exploring the importance and preference of sugar feeding behaviour of malaria vectors in sugar plantations of southern Malawi

BackgroundReliable tools are needed to control opportunistic outdoor biting and resting malaria vectors that remain beyond the reach of indoor targeted interventions. The attractive targeted sugar baits (ATSBs) have demonstrated effectiveness in some settings but have shown limited impact in other areas, likely due to differences in mosquito species preferences and the presence of competing natural sugar sources. However, these factors remain poorly understood and understudied. We evaluated sugar-feeding behaviour of Anopheline mosquitoes in a sugarcane plantation area of Chikwawa, Malawi, to generate additional field data that could enhance the efficacy and design of sugar-based vector control tools tailored for malaria endemic regions such as Malawi. MethodsUsing three collection tools, CDC Light traps; Prokopack aspirator and the barrier screen, we collected 187 adult anophelines from the Illovo sugar plantations. Collected mosquitoes were subjected to cold anthrone tests in the laboratory to assess the presence of plant sugars in their gut. Additionally, 810 adult Anopheles gambiae s.l., reared in the insectary from wild caught larvae, were exposed in an olfactory-driven choice experiment to identify the most attractive available sugar source in the area. Sugar sources included guavas, melon, bananas, mango, marula and sugarcane. ResultsOver 40% (n=74) of the collected Anopheles mosquitoes-including An. gambiae s.l., An. funestus, An. coustani and An. tenebrous were found to have fed on natural sugar sources. For the sugar attractiveness tests for An. gambiae s.l., guava was found to be twice as attractive (IRR = 1.97, 95% CI: 1.49-2.62, p < 0.001) as sugarcane (our reference fruit), followed by banana (IRR= 1.68, 95% CI: 1.26-2.24, P < 0.001), then mango, and melon (IRR= 1.49, 95% CI: 1.11-2.01, P= 0.008) and (IRR=1.45, 95% CI: 1.08-1.96, P= 0.014) respectively. ConclusionSugar feeding is a key activity for Anopheles mosquitoes and presents a potential target for control efforts. In this setting with abundant sugarcane, guava was identified as the most attractive sugar source for An. gambiae s.l., followed by banana, mango, and melon, with sugarcane being the least attractive. Understanding local sugar source preferences can help tailor novel intervention strategies to specific environmental contexts.

ecology↗

bioRxiv2025

A modular, Galaxy-based immunopeptidogenomic (iPepGen) analysis pipeline for discovery, verification, and prioritization of candidate cancer neoantigen peptides

Characterizing tumor-specific neoantigen peptides, derived from genomic or transcriptomic aberrations and presented to the immune system, is critical for immuno-oncology studies. To this end, the modular iPepGen immunopeptidogenomics pipeline provides these functions: (1) Neoantigen prediction and protein database generation from genomic or transcriptomic sequencing data; (2) Peptide identification (3) Verification from immunopeptidomic mass spectral data; (4) Neoantigen classification and visualization; (5) Candidate prioritization for further study. Easy access via a publicly available, scalable cloud-based gateway coupled with online, interactive training materials streamlines the adoption by cancer researchers who require immunopeptidogenomic analysis tools but lack advanced computational expertise and resources.

bioinformatics↗

bioRxiv2025

Nemo-like kinase disrupts nuclear import and drives TDP43 mislocalization in ALS

Cytoplasmic TDP43 mislocalization and aggregation are pathological hallmarks of amyotrophic lateral sclerosis (ALS). However, the initial cellular insults that lead to TDP43 mislocalization remain unclear. In this study, we demonstrate that Nemo-like kinase (NLK)--a proline-directed serine/threonine kinase--promotes the mislocalization of TDP43 and other RNA-binding proteins by disrupting nuclear import. NLK levels are selectively elevated in neurons exhibiting TDP43 mislocalization in ALS patient tissues, while genetic reduction of NLK reduces toxicity in human neuron models of ALS. Our findings suggest that NLK is a promising therapeutic target for neurodegenerative diseases.

neuroscience↗

bioRxiv2024

Entomological investigations into yellow fever outbreak in northern Ghana

BackgroundRecently, arboviruses have been of concern as pathogens for emerging and re-emerging infectious diseases. In Ghana, yellow fever outbreak occurred in Savannah Region in the year 2021. A team from different institutions, organisations, and stakeholders of health with varying vital expertise was assembled to respond to this national emergency to assess, contain and/or control the rapid spread of the disease. This paper presents findings from the entomological investigations conducted during the yellow fever outbreak. MethodsImmature stages of Aedes mosquitoes were collected from breeding containers in and around houses, and adult mosquitoes sampled using BG-Sentinel traps, human landing catches and Prokopack collections. After morphological identification of these mosquitoes, they were screened for Chikungunya, Dengue Fever, Yellow Fever, and Zika viruses using real time reverse-transcription polymerase chain reaction. ResultsIn all, 12,264 breeding containers were examined. A total of 3,885 larvae and 1,186 pupae were obtained from 173 containers. Out of 1,001 houses surveyed, 130 were positive for larvae and/or pupae. The breeding receptacles included plastic (6,529), metallic (6,024), clay jar (753), tire (565), and well (34). The WHO thresholds for arboviruses larval indices were used to assess risk. A total of 1571 adults identified [Aedes aegypti aegypti (35), Aedes aegypti formosus (619), and Culex (917)] were collected with adult mosquito sampling methods or emerged from immature mosquitoes stages. None of the arboviruses were detected using qPCR. ConclusionVectors had no yellow fever infections. There was a high risk of arbovirus transmission in the study areas although mosquito vectors were not positive for arboviruses. Aedes aegypti formosus was the dominant Aedes species. They might be drivers for yellow fever transmission during outbreak. Generally, arboviral transmission was high in all study districts. Although yellow fever virus was not detected, Aedes aegypti populations and transmission risk in study districts was high. Author summaryIn 2021, Savannah Region of Ghana experienced yellow fever outbreak. This spread quickly to adjoining regions. The disease is transmitted by some female mosquitoes infected with yellow fever virus. These same mosquitoes can transmit other viral infections resulting in disease outcomes such as chikungunya, dengue, and zika. A team of experts from stakeholders of health were mobilised to control and/or contain the spread of the disease to other parts of Ghana. The team carried out several activities and assessments to stop the spread of yellow fever. Notably is the investigation to determine different types of mosquitoes involved in transmitting the disease. We collected some mosquitoes and processed them for vital information that could prevent future outbreaks of the aforementioned diseases. There is no surveillance system in Ghana to pick up early warnings regarding potential viral disease outbreaks. Therefore, there is scanty information on these type of mosquitoes and viruses found in different places. We used standard procedures to assess the risk of these mosquitoes in causing future disease outbreaks. Our findings suggested a high risk of future outbreaks for any of the viral diseases tested. We therefore recommended the implementation of a mosquito surveillance system to prevent future outbreaks.

zoology↗

bioRxiv2024

Single-cell DNA methylation analysis tool Amethyst reveals distinct noncanonical methylation patterns in human glial cells

Single-cell sequencing technologies have revolutionized biomedical research by enabling deconvolution of cell type-specific properties in highly heterogeneous tissue. While robust tools have been developed to handle bioinformatic challenges posed by single-cell RNA and ATAC data, options for emergent modalities such as methylation are much more limited, impeding the utility of results. Here we present Amethyst, a comprehensive R package for atlas-scale single-cell methylation sequencing data analysis. Amethyst begins with base-level methylation calls and expedites batch integration, doublet detection, dimensionality reduction, clustering, cell type annotation, differentially methylated region calling, and interpretation of results, facilitating rapid data interaction in a local environment. We introduce the workflow using published single-cell methylation human peripheral blood mononuclear cell (PBMC) and human cortex data. We further leverage Amethyst on an atlas-scale brain dataset to describe a noncanonical methylation pattern in human astrocytes and oligodendrocytes, challenging the notion that this form of methylation is principally relevant to neurons in the brain. Tools such as Amethyst will increase accessibility to single-cell methylation data analysis, catalyzing research progress across diverse contexts.

neuroscience↗

bioRxiv2024

Molecular characterisation of Streptococcus pyogenes (StrepA) non-invasive isolates during the 2022-23 UK upsurge

At the end of 2022 into early 2023 the UK Health Security Agency reported unusually high levels of scarlet fever and invasive disease caused by Streptococcus pyogenes (StrepA or group A Streptococcus). During this time, we collected and genome sequenced 341 non-invasive throat and skin S. pyogenes isolates identified during routine clinical diagnostic testing in Sheffield, a large UK city. We compared the data with that obtained from a similar collection of 165 isolates from 2016-17. Numbers of throat-associated isolates collected peaked in early December 2022, reflecting the national scarlet fever upsurge, while skin infections peaked later in December. The most common emm-types in 2022-23 were emm1 (28.7%), emm12 (24.9%), and emm22 (7.7%) in throat; and emm1 (22%), emm12 (10%), emm76 (18%), and emm49 (7%) in skin. Whilst all emm1 isolates were the M1UK lineage, comparison with 2016-17 revealed diverse lineages in other emm-types, including emm12, and emergent lineages within other types including a new acapsular emm75 lineage, demonstrating that the upsurge was not completely driven by a single genotype. Analysis of the capsule locus predicted only 51% of throat isolates would produce capsule compared to 78% of skin isolates. 90% of throat isolates were also predicted to have high NADase and Streptolysin O (SLO) expression, based on the promoter sequence, compared to only 56% of skin isolates. Our study has highlighted the value in analysis of non-invasive isolates to characterise tissue tropisms, as well as changing strain diversity and emerging genomic features which may have implications for spillover into invasive disease and future S. pyogenes upsurges. Data summaryAll new genome sequence data is available on the NCBI short read archive under the bioproject PRJNA1062601 and individual accession numbers are listed in Supplementary Table 1 and Table 2. Impact statementThe human bacterial pathogen Streptococcus pyogenes, also known as group A Streptococcus or StrepA, caused a dramatic and sudden upsurge in scarlet fever in the UK at the end of 2022 into early 2023. We present molecular characterisation of this upsurge, through genome sequence analysis of throat, skin and other types of non-severe infection isolates collected by the microbiology diagnostic lab at the Northern General Hospital in Sheffield, England. We found that, whilst two strain types were the predominant cause of infections during the upsurge, other types had emerged or changed when compared to a similar collection from 2016-17. We also identified differences between throat-associated isolates and skin-associated isolates and highlighted important bacterial factors that might influence infection types. Isolates from non-severe throat/skin types of infections are rarely saved and therefore our knowledge of them is limited. However, here we demonstrate that study of such isolates may be key to understanding upsurges of more severe infections.

microbiology↗

bioRxiv2024

A Novel, Robust, and Portable Platform for Magnetoencephalography using Optically Pumped Magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped-magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of OPM-MEG systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG remains in its infancy with limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range (arguably the biggest limitation of existing instrumentation). We show that this system produces equivalent measures when compared to an established instrument; specifically, when measuring task-induced beta-band, gamma-band and evoked neuro-electrical responses, source localisations from the two systems were highly comparable and temporal correlation was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG - the clinical standard). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG technology and offers an attractive platform for next generation functional medical imaging.

neuroscience↗

bioRxiv2023

Genomic insights into southern white rhinoceros ( Ceratotherium simum simum ) reproduction: revealing granulosa cell gene expression

In vivo-collected granulosa cells (GC) from the southern white rhinoceros (SWR) provide a non-invasive assessment of the developmental status of oocytes prior to in vitro culture, which could aid in the development of assisted reproductive technologies (ART). Our study aimed to investigate gene expression in SWR granulosa cells, collected in vivo and gain preliminary insight into the transcriptional activity occurring within the cells during various stages of oocyte development. It was hypothesized there would be similarities between the SWR GC transcriptome and cattle and humans, two species for which well-annotated genomes are available and ART are commonly used. GC were collected from SWR following ovum pickup (OPU) and pooled from all aspirated follicles. Total RNA was isolated, libraries prepared, and sequencing performed using an Illumina NextSeq 500. Reads were aligned and annotated to CerSimCot1.0. Databases for cattle and human were acquired for comparison. This study identified 37,407 transcripts present in GC of SWR. It was determined that cattle and human transcriptomes are valuable resources with a homology of 45% with the SWR. In conclusion, these data provide preliminary, novel insights into the transcriptional activity of GC in the SWR that can be used to enhance ART in this species.

genomics↗

bioRxiv2022

A semi-supervised Bayesian mixture modelling approach for joint batch correction and classification

AO_SCPLOWBSTRACTC_SCPLOWSystematic differences between batches of samples present significant challenges when analysing biological data. Such batch effects are well-studied and are liable to occur in any setting where multiple batches are assayed. Many existing methods for accounting for these have focused on high-dimensional data such as RNA-seq and have assumptions that reflect this. Here we focus on batch-correction in low-dimensional classification problems. We propose a semi-supervised Bayesian generative classifier based on mixture models that jointly predicts class labels and models batch effects. Our model allows observations to be probabilistically assigned to classes in a way that incorporates uncertainty arising from batch effects. By simultaneously inferring the classification and the batch-correction our method is more robust to dependence between batch and class than pre-processing steps such as ComBat. We explore two choices for the within-class densities: the multivariate normal and the multivariate t. A simulation study demonstrates that our method performs well compared to popular off-the-shelf machine learning methods and is also quick; performing 15,000 iterations on a dataset of 750 samples with 2 measurements each in 11.7 seconds for the MVN mixture model and 14.7 seconds for the MVT mixture model. We further validate our model on gene expression data where cell type (class) is known and simulate batch effects. We apply our model to two datasets generated using the enzyme-linked immunosorbent assay (ELISA), a spectrophotometric assay often used to screen for antibodies. The examples we consider were collected in 2020 and measure seropositivity for SARS-CoV-2. We use our model to estimate seroprevalence in the populations studied. We implement the models in C++ using a Metropolis-within-Gibbs algorithm, available in the R package batchmix. Scripts to recreate our analysis are at https://github.com/stcolema/BatchClassifierPaper.

bioinformatics↗

bioRxiv2021

Bacteriophage self-counting in the presence of viral replication

When host cells are in low abundance, temperate bacteriophages opt for dormant (lysogenic) infection. Phage lambda implements this strategy by increasing the frequency of lysogeny at higher multiplicity of infection (MOI). However, it remains unclear how the phage reliably counts infecting viral genomes even as their intracellular number increases due to replication. By combining theoretical modeling with single-cell measurements of viral copy number and gene expression, we find that, instead of hindering lambdas decision, replication facilitates it. In a nonreplicating mutant, viral gene expression simply scales with MOI rather than diverging into lytic (virulent) and lysogenic trajectories. A similar pattern is followed during early infection by wildtype phage. However, later in the infection, the modulation of viral replication by the decision genes amplifies the initially modest gene expression differences into divergent trajectories. Replication thus ensures the optimal decision--lysis upon single-phage infection, lysogeny at higher MOI.

systems biology↗

bioRxiv2020

Multi-Omic Analysis Reveals Cannabidiol Disruption of Cholesterol Homeostasis in Human Cell Lines

The non-psychoactive cannabinoid, cannabidiol (CBD), is FDA-approved for treatment of two drug-resistant epileptic disorders, and is seeing increased use among the general public, yet the mechanisms that underlie its therapeutic effects and side-effect profiles remain unclear. Here, we report a systems-level analysis of CBD action in human cell lines using temporal multi-omic profiling. FRET-based biosensor screening revealed that CBD treatment resulted in a sharp rise in cytosolic calcium, and activation of AMPK and ERK kinases in human keratinocyte and neuroblastoma cell lines. CBD treatment led to alterations in the abundance of metabolites, mRNA transcripts, and proteins consistent with activation of cholesterol biosynthesis, transport and storage. We found that CBD rapidly incorporated into cellular membranes and altered cholesterol chemical activity, suggesting direct perturbation of cholesterol-dependent membrane properties. CBD treatment induced apoptosis in a dose-dependent manner in multiple human cell lines, which was rescued by inhibition of cholesterol synthesis, and potentiated by compounds that disrupt cholesterol trafficking and storage. Our data point to a pharmacological interaction of CBD with cholesterol homeostasis pathways, with potential implications in its therapeutic use.

systems biology↗

bioRxiv2019

Genomic and epidemiological evidence of a dominant Panton-Valentine leucocidin-positive Methicillin Resistant Staphylococcus aureus lineage in Sri Lanka with spread to the United Kingdom and Australia

ObjectiveTo undertake the first detailed genomic analysis of methicillin-resistant Staphylococcus aureus (MRSA) isolated in Sri Lanka.\n\nMethodsA prospective observational study was performed on 94 MRSA isolates collected over a four month period from the Anuradhapura Teaching Hospital, Sri Lanka. Screening for mecA, mecC and the Panton-Valentine leucocidin (PVL)-associated lukS-PV/lukF-PV genes and molecular characterisation by spa typing was undertaken. Whole genome sequencing (WGS) and phylogenetic analysis was performed on selected multilocus sequence type (MLST) clonal complex 5 (CC5) isolates from Sri Lanka, England, Australia and Argentina.\n\nResultsAll 94 MRSA harboured the mecA gene. Nineteen spa types associated with nine MLST clonal complexes were identified. Most isolates were from skin and soft tissue infections (76.9%), with the remainder causing more invasive disease. Sixty two (65.9%) of isolates were PVL positive with the majority (56 isolates; 90.3%) belonging to a dominant CC5 lineage. This lineage, PVL-positive ST5-MRSA-IVc, was associated with community and hospital-onset infections. Based on WGS, representative PVL-positive ST5-MRSA-IVc isolates from Sri Lanka, England and Australia formed a single phylogenetic clade, suggesting wide geographical circulation.\n\nConclusionsWe present the most detailed genomic analysis of MRSA isolated in Sri Lanka to date. The analysis identified a PVL-positive ST5-MRSA-IVc that dominates MRSA clinical infections in Sri Lanka. Furthermore, transmission of the strain has occurred in the United Kingdom and Australia.

microbiology↗

bioRxiv2018

Geographical Distributions and Spatial Equilibrium in Historical Epidemics of the United States

This research examines the geographical distributions of several historical epidemics in the United States and investigates whether they reached a geographical equilibrium, however briefly. An equilibrium distribution over a geographical area, as the end state of a diffusion or spatial contagion process, has definitive mathematical properties. These permit qualitative and quantitative tests that may confirm an equilibrium and identify its characteristics. The analysis uses United States state-level data for several common infectious diseases of the 1950s, and results show geographical equilibrium distributions for several epidemics. These are not predicted by the most commonly used epidemiological models but are consistent with observed geographical disparities in disease prevalence that continued over a number of years in spite of recurrent epidemic cycles and long-term trends.

epidemiology↗

bioRxiv2017

The relationship between varicella (chickenpox) and scarlet fever in contemporary Hong Kong

Scarlet fever epidemics have reemerged in China, the UK, and Hong Kong. This research tests whether scarlet fever epidemics in Hong Kong are linked to varicella epidemics. Varicella infection is a known risk for invasive Group A Streptococcal infections, and historical research shows a connection between varicella and scarlet fever. This analysis examines the relationship between these two disease in Hong Kong from 2011 to 2015 and compares varicella rates before and after the reintroduction of scarlet fever. Analysis shows that scarlet fever and varicella have synchronous annual epidemic cycles, and a mathematical model of the relationship between scarlet fever and varicella is estimated. Varicella rates were unchanged by the return of scarlet fever, but annual varicella cycles may have influenced the size and timing of scarlet fever outbreaks. Vaccination policies for varicella may need to be adjusted to limit scarlet fever epidemics.

epidemiology↗

bioRxiv2017

The Association between Tuberculosis and Diphtheria

This research investigates the now-forgotten relationship between diphtheria and tuberculosis. Historical medical reports from the 19th century are reviewed followed by a statistical regression analysis of the relationship between the two diseases in the early 20th century. Historical medical records show a consistent association between diphtheria and tuberculosis that can increase the likelihood and severity of either disease in a co-infection. The statistical analysis uses historical weekly public health data on reported cases in five American cities over a period of several years, finding a modest but statistically significant relationship between the two diseases. No current medical theory explains the association between diphtheria and tuberculosis. Alternative explanations are explored with a focus on how the diseases assimilate iron. In a co-infection, the effectiveness of tuberculosis at assimilating extracellular iron can lead to increased production of diphtheria toxin, worsening that disease, which may in turn exacerbate tuberculosis. Iron-dependent repressor genes connect both diseases.

epidemiology↗