Biology subjects

Butler, C.

Publications and source records attributed to Butler, C..

13 recordsLinked to original sources

bioRxiv2026

A spatially-specific pattern of cortical thickness in frontal lobe predisposes to faster future amyloid accumulation in individuals with subjective cognitive decline

The risk of developing AD is conferred through numerous genetic and environmental factors. How these risks influence brain structure prior to the onset of AD pathology is not yet known. We hypothesise that there may be specific anatomic endophenotypes that predispose to AD years before the first signs of amyloid accumulation occur. Using clinical, genetic and brain MRI data from Fundacio ACE Healthy Brain Initiative (FACEHBI) --a longitudinal cohort of individuals with Subjective Cognitive Decline aged > 50 years--, we identified a spatially-specific, fine-grained pattern of cortical thickness in frontal lobe regions among amyloid-negative individuals at baseline that holds a significant relationship with the rate of amyloid accumulation during the next five years. This pattern may represent a structural fingerprint of increased susceptibility to the initiation of the AD cascade.

neuroscience↗

bioRxiv2025

Non-invasive in vivo acoustoelectric neuromodulation and its contribution to ultrasound stimulation

Non-invasive brain stimulation offers therapeutic potential without the risks of surgery, yet current electrical approaches lack spatial precision and depth due to the long wavelengths of electric fields. Here we demonstrate that the acoustoelectric interaction--the nonlinear coupling between applied acoustic and electric fields--can overcome these limitations to achieve spatially focused, non-invasive neuromodulation. Using in vitro and in vivo rodent electrophysiology, we show motor-evoked potentials that depend on both the amplitude and frequency of the acoustoelectric field, with artefactual controls excluding purely acoustic or electrical origins. We further identify an acoustoelectric contribution to conventional ultrasound stimulation, arising from the interaction between ultrasound-induced electrical signals and propagating acoustic waves. These findings establish acoustoelectric neuromodulation as a distinct mechanism of neural activation and a significant contributor to how ultrasound stimulation influences brain activity, opening new directions for precise, non-invasive neuromodulation and neurotherapeutic development.

neuroscience↗

bioRxiv2025

Rapid spread of knockdown resistance allele frequencies in a suburban population of Aedes albopictus

Aedes albopictus is a major vector of arboviral diseases and is often targeted by pyrethroid-based mosquito control in residential areas. While knockdown resistance (kdr) mutations are well documented in Ae. aegypti, their emergence in Ae. albopictus has been less studied, particularly in suburban environments where insecticide application is often uncoordinated. Understanding the temporal and spatial dynamics of resistance evolution in this context is critical for preserving the effectiveness of public health interventions. We conducted longitudinal sampling of Ae. albopictus populations in Wake County, North Carolina, from 2016 to 2024. Using a novel allele-specific PCR melt curve assay, we genotyped 2,273 mosquitoes at the F1534S locus in the voltage-gated sodium channel gene. Resistance allele frequencies were calculated annually and mapped across the county for three key years--2016, 2018, and 2023-- representing the pre-emergence, initial detection, and widespread phases of resistance development. Selection and dominance were estimated using the Wright-Fisher Approximate Bayesian Computation algorithm for locus F1534S. The F1534S resistance allele was first detected in 2018 at a central, affluent neighborhood. By 2023, the allele had spread throughout the sampling region, with the highest frequencies near the site of first detection. Resistance allele frequency peaked at 0.36 in 2023, accompanied by an increase in heterozygous and homozygous resistance genotypes. Temporally sampled sites showed consistent trends in rising resistance, with all temporally-sampled locations harboring resistance genotypes by 2022. The resistance allele was found to be under high selection pressure and partially recessive in this population. Our findings reveal rapid emergence and spatial expansion of the F1534S kdr allele in Ae. albopictus populations in a suburban setting. The pattern of spread suggests strong local selection pressure, likely driven by residential pyrethroid use. These results highlight the need for proactive resistance monitoring and integrated management strategies that address private-sector contributions to insecticide selection pressure.

evolutionary biology↗

bioRxiv2025

Deep-learning-based interpolation of longitudinal microbiome data powers biologically informative discovery

The human microbiome is a foundational and dynamic foundation for several health-related functions and disease processes. Advances in microbiome sequencing have enabled the characterization of microbial communities in several niches. Longitudinal microbiome studies further strive to discover clinically informative microbial community trajectories. However, these data are fraught with dropout events, high noise, and irregular sampling that limit and prevent the use of many available longitudinal analysis tools. To address these challenges, we introduce Bidirectional GRU-ODE-Bayes (BGOB), a deep learning framework developed for longitudinal microbiome interpolation. BGOB combines bidirectional information flow and ODE-based continuous modeling to jointly interpolate and smoothen trends across individual participants, providing uniform, denoised time intervals across patients. BGOB enables vastly improved performance in differential abundance testing and time-to-event analysis, and makes possible longitudinal analyses requiring uniformity, such as lead-lag detection and temporal clustering. After interpolation, previously low-powered datasets are able to broadly recapitulate known microbiology and elucidate interacting microbial communities. We highlight several associations between microbial taxa and disease, including novel species associated with Early Childhood Caries and disruption of key healthy gut microbiota in Inflammatory Bowel Disease. The BGOB package is publicly available at https://github.com/Rachel-Lyu/BGOB_n_test.

microbiology↗

bioRxiv2024

LP-Micro Offers Interpretable Disease Outcome Prediction by Leveraging Microbial Biomarkers and Their Time-Varying Effects

Information generated from longitudinally-sampled microbial data has the potential to illuminate important aspects of development and progression for many human conditions and diseases. Identifying microbial biomarkers and their time-varying effects can not only advance our understanding of pathogenetic mechanisms, but also facilitate early diagnosis and guide optimal timing of interventions. However, longitudinal predictive modeling of highly noisy and dynamic microbial data (e.g., metagenomics) poses analytical challenges. To overcome these challenges, we introduce a robust and interpretable machine-learning-based longitudinal microbiome analysis framework, LP-Micro, that encompasses: (i) longitudinal microbial feature screening via a polynomial group lasso, (ii) disease outcome prediction implemented via machine learning methods (e.g., XGBoost, deep neural networks), and (iii) interpretable association testing between time points, microbial features, and disease outcomes via permutation feature importance. We demonstrate in simulations that LP-Micro can not only identify incident disease-related microbiome taxa but also offers improved prediction accuracy compared to existing approaches. Applications of LP-Micro in two longitudinal microbiome studies with clinical outcomes of childhood dental disease and weight loss following bariatric surgery yield consistently high prediction accuracy. The identified critical early predictive time points are informative and aligned with clinical expectations.

bioinformatics↗

bioRxiv2023

A Method for Sampling the Living Wood Microbiome

Efforts to characterize microbial life across diverse environments have progressed tremendously, yet the microbiome of Earths largest biomass reservoir--the wood of living trees--has been largely unexplored. Current understanding of the tree microbiome is largely confined to roots and leaves, with little attention given to the endophytic microbiome of wood, even though emergent studies have indicated this zone as a niche for unique taxa, of consequence for ecosystem health and global biogeochemical cycles. The lack of investigation derives partly from the physical recalcitrance of wood, which presents challenges during sampling, homogenization, and the extraction of nucleic acids. In response to these issues, we present an optimized method for processing wood for use in microbial analyses, from sampling through to downstream analyses. Using methane-cycling taxa as model endophytes, we assess losses in recovery during our method, and determine a limit-of-detection of approximately 500 cells per 100 mg of (dry) wood. For all six species evaluated--which represented several diverse taxa of hardwoods and softwoods--PCR inhibition proved minimal, and we expect this method to be applicable for a majority of tree species. The methods presented herein can facilitate future investigation into the wood microbiome and global microbial ecology of methane cycling.

ecology↗

bioRxiv2021

Global network structure and local transcriptomic vulnerability shape atrophy in sporadic and genetic behavioral variant frontotemporal dementia

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioral variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). We first identify distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbors, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicenter of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and anteromedial temporal areas. Finally, we find that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, effectively modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability.

neuroscience↗

bioRxiv2021

HolistiC: Leveraging Hi-C and Whole Genome Shotgun Sequencing for Double Minute Chromosome Discovery

Double minute chromosomes are acentric extrachromosomal DNA artifacts that are frequently observed in the cells of numerous cancers. They are highly amplified and contain oncogenes and drug resistance genes, making their presence a challenge for effective cancer treatment. Algorithmic discovery of double minutes (DM) can potentially improve bench-derived therapies for cancer treatment. A hindrance to this task is that DMs evolve, yielding circular chromatin that shares segments from progenitor double minutes. This creates double minutes with overlapping amplicon coordinates. Existing DM discovery algorithms use whole genome shotgun sequencing in isolation, which can potentially incorrectly classify DMs that share overlapping coordinates. In this study, we describe an algorithm called " HolistIC" that can predict double minutes in tumor genomes by integrating whole genome shotgun sequencing (WGS) and Hi-C sequencing data. The consolidation of these sources of information resolves ambiguity in double minute amplicon prediction that exists in DM prediction with WGS data used in isolation. We implemented and tested our algorithm on the tandem Hi-C and WGS datasets of three cancer datasets and a simulated dataset. Results on the cancer datasets demonstrated HolistICs ability to predict DMs from Hi-C and WGS data in tandem. The results on the simulated data showed the HolistIC can accurately distinguish double minutes that have overlapping amplicon coordinates, an advance over methods that predict extrachromosomal amplification using WGS data in isolation. AvailabilityOur software is available at http://www.github.com/mhayes20/HolistIC.

bioinformatics↗

bioRxiv2020

CaMKII activation triggers persistent formation and segregation of postsynaptic liquid phase

Transient information input to brain leads to persistent changes in synaptic circuit, thereby forming memory engrams. Synapse undergoes coordinated functional and structural changes during this process but how such changes are achieved by its component molecules still largely remain enigmatic. We found that activated CaMKII, the central player of synaptic plasticity, undergoes liquid-liquid phase separation (LLPS) with NMDAR subunit GluN2B. Due to CaMKII autophosphorylation, the condensate stably persists even after Ca2+ is removed. The selective binding of activated CaMKII with GluN2B co-segregates AMPAR/neuroligin (NLGN) into a phase-in-phase assembly. Because postsynaptic NLGN clusters presynaptic neurexin and other active zone proteins thereby increasing the release probability of synaptic vesicles, this ensures efficient synaptic transmission. In this way, Ca2+-induced and persistent formation of LLPS by CaMKII serves as molecular basis of memory by functioning as an activity-dependent crosslinker for postsynaptic proteins and segregating trans-synaptic nanocolumns.

neuroscience↗

bioRxiv2019

Data-driven algorithm for the diagnosis of behavioral variant frontotemporal dementia

INTRODUCTIONBrain structural imaging is paramount for the diagnosis of behavioral variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. METHODSA total of 515 subjects from two different bvFTD databases (training and validation cohorts) were included to perform voxel-wise deformation-based morphometry analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from morphometric differences in isolation and together with bedside cognitive scores. RESULTSAverage ten-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In a separate validation cohort of genetically confirmed bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added cognitive scores. DISCUSSIONThe random forest classifier developed can accurately predict bvFTD at the individual subject level.

neuroscience↗

bioRxiv2019

Analysis of brain atrophy and local gene expression implicates astrocytes in Frontotemporal dementia

Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of FTD, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work we combined gene expression data for 16,772 genes from the Allen Institute for Brain Science atlas with brain maps of gray matter atrophy in symptomatic C9orf72, GRN and MAPT mutation carriers obtained from the Genetic FTD Initiative study. No significant association was seen between (C9orf2, GRN and MAPT expression and the atrophy patterns in the respective genetic groups. Between 1,000 and 5,000 genes showed a negative or positive correlation with the atrophy pattern within each individual genetic group, with the most significantly associated genes being TREM2, SSBP3 and GPR158 (negative association in C9orf72, GRN and MAPT respectively) and RELN, MXRA8 and LPA (positive association in C9orf72, GRN and MAPT respectively). An overrepresentation analysis identified a negative correlation with genes involved in mitochondrial function, and a positive correlation with genes involved in vascular and glial cell function in each of the genetic groups. After adjusting for spatial autocorrelation, a set of 423 and 700 genes showed significant positive and negative correlation, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in FTD than previously assumed, and in the case of the positively-associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood-brain barrier respectively. Abbreviated summaryAltmann et al. investigated the concordance between spatial cortical gene expression in healthy subjects and atrophy patterns in genetic frontotemporal dementia. They found that elevated gene expression of endothelial cell and astrocyte-related genes in regions with atrophy, suggesting a role of these cell types in the aetiology of frontotemporal dementia.

neuroscience↗

bioRxiv2019

Specific nanoscale synaptic reshuffling and control of short-term plasticity following NMDAR- and P2XR-dependent Long-Term Depression

Long-Term Potentiation (LTP) and Long-Term Depression (LTD) of excitatory synaptic transmission are considered as cellular basis of learning and memory. These two forms of synaptic plasticity have been mainly attributed to global changes in the number of synaptic AMPA-type glutamate receptor (AMPAR) through a regulation of the diffusion/trapping balance at the PSD, exocytosis and endocytosis. While the precise molecular mechanisms at the base of LTP have been intensively investigated, the ones involved in LTD remains elusive. Here we combined super-resolution imaging technique, electrophysiology and modeling to describe the various modifications of AMPAR nanoscale organization and their effect on synaptic transmission in response to two different LTD protocols, based on the activation of either NMDA receptors or P2X receptors. While both type of LTD are associated with a decrease in synaptic AMPAR clustering, only NMDAR-dependent LTD is associated with a reorganization of PSD-95 at the nanoscale. This change increases the pool of diffusive AMPAR improving synaptic short-term facilitation through a post-synaptic mechanism. These results demonstrate that specific dynamic reorganization of synapses at the nanoscale during specific LTD paradigm allows to improve the responsiveness of depressed synapses.

neuroscience↗

bioRxiv2017

Trends in Escherichia coli bloodstream infection, urinary tract infections and antibiotic susceptibilities in Oxfordshire, 1998-2016: an observational study

BackgroundThe incidence of Escherichia coli bloodstream infections (EC-BSIs), particularly those caused by antibiotic-resistant strains, is increasing in the UK and internationally. This is a major public health concern but the evidence base to guide interventions is limited.\n\nMethodsIncidence of EC-BSIs and E. coli urinary tract infections (EC-UTIs) in one UK region (Oxfordshire) were estimated from anonymised linked microbiological and hospital electronic health records, and modelled using negative binomial regression based on microbiological, clinical and healthcare exposure risk factors. Infection severity, 30-day allcause mortality, and community and hospital co-amoxiclav use were also investigated.\n\nFindingsFrom 1998-2016, 5706 EC-BSIs occurred in 5215 patients, and 228376 EC-UTIs in 137075 patients. 1365(24%) EC-BSIs were nosocomial (onset >48h post-admission), 1863(33%) were community (>365 days post-discharge), 1346(24%) were quasi-community (31-365 days post-discharge), and 1132(20%) were quasi-nosocomial ([≤]30 days postdischarge). 1413(20%) EC-BSIs and 36270(13%) EC-UTIs were co-amoxiclav-resistant (41% and 30%, respectively, in 2016). Increases in EC-BSIs were driven by increases in community (10%/year (95% CI:7%-13%)) and quasi-community (8%/year (95% CI:7%-10%)) cases. Changes in EC-BSI-associated 30-day mortality were at most modest (p>0{middle dot}03), and mortality was substantial (14-25% across groups). By contrast, co-amoxiclav-resistant EC-BSIs increased in all groups (by 11%-19%/year, significantly faster than susceptible EC-BSIs, pheterogeneity<0{middle dot}001), as did co-amoxiclav-resistant EC-UTIs (by 13%-29%/year, pheterogeneity*0{middle dot}001). Co-amoxiclav use in primary-care facilities was associated with subsequent co-amoxiclav-resistant EC-UTIs (p=0{middle dot}03) and all EC-UTIs (p=0{middle dot}002).\n\nInterpretationCurrent increases in EC-BSIs in Oxfordshire are primarily community-associated, with high rates of co-amoxiclav resistance, nevertheless not impacting mortality. Interventions should target primary-care facilities with high co-amoxiclav usage.\n\nFundingNational Institute for Health Research.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for publications from inception up until October 26, 2017, with the terms \"Escherichia coli\", \"E. coli\", \"bacteraemia\", \"bloodstream infection\", restricting the search to English language articles, and also reviewed references from retrieved articles. Escherichia coli (E. coli) is the most common cause of bloodstream infection, and the incidence of E. coli bloodstream infection, and particularly antibiotic-resistant infections, is increasing in the UK and internationally. Although the UK government aims to reduce healthcare-associated E. coli bloodstream infection, there is only limited evidence to inform appropriate interventions.\n\nAdded value of this studyWe investigated potential drivers for these increases in incidence by exploiting available linked electronic health records over 19 years for ~5200 patients with E. coli bloodstream infection and ~140000 with E. coli urinary tract infection, together with community antimicrobial prescribing data for the most recent six years. Our study identified several findings with significant implications for health policy and patient care: O_LIIncreases in the incidence of E. coli bloodstream infections were driven mainly by non-hospital-associated cases; however, neither patients with previous urinary tract infections nor having previously had urine specimens sent from catheters appeared to be driving the increases\nC_LIO_LICo-amoxiclav-resistant bloodstream infections rose significantly faster than co-amoxiclav-susceptible bloodstream infections, with the greatest number of co-amoxiclav-resistant bloodstream infections in 2016 being in patients discharged more than a month previously (i.e. community-associated)\nC_LIO_LIHigher co-amoxiclav use in primary care was associated with higher rates of both co-amoxiclav-resistant E. coli urinary tract infections and E. coli urinary tract infections overall, supporting drives to reduce broad-spectrum and inappropriate antibiotic use in primary care\nC_LIO_LIDespite substantial increases in co-amoxiclav-resistant bloodstream infections there was no evidence that mortality was increasing in these cases; this does not support moving to broader empiric antibiotic prescribing in hospitals (i.e. carbapenems, piperacillin-tazobactam)\nC_LI\n\nImplications of all available adviceThis suggests that government strategies to effectively reduce E. coli bloodstream infections should target community settings, as well as healthcare-associated settings. The absence of an increased mortality signal suggests that co-amoxiclav resistant E. coli infections are either being successfully treated by dual empiric therapy in severe cases (e.g. with concomitant gentamicin), can be \"rescued\" once isolate susceptibilities become available, or currently deployed phenotypic susceptibility testing breakpoints do not adequately correlate with clinical outcome.

epidemiology↗