Biology subjects

Perry, A.

Publications and source records attributed to Perry, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Intonation Units in spontaneous speech evoke a neural response

Spontaneous speech is produced in chunks called Intonation Units (IUs). IUs are defined by a set of prosodic cues and occur in all human languages. Linguistic theory suggests that IUs pace the flow of information and serve as a window onto the dynamic focus of attention in speech processing. IUs provide a promising and hitherto unexplored theoretical framework for studying the neural mechanisms of communication, thanks to their universality and their consistent temporal structure across different grammatical and socio-cultural conditions. In this article, we identify a neural response unique to the boundary defined by the IU. We measured the EEG of participants who listened to different speakers recounting an emotional life event. We analyzed the speech stimuli linguistically, and modeled the EEG response at word offset using a GLM approach. We find that the EEG response to IU-final words differs from the response to IU-nonfinal words when acoustic boundary strength is held constant. To the best of our knowledge, this is the first time this is demonstrated in spontaneous speech under naturalistic listening conditions, and under a theoretical framework that connects the prosodic chunking of speech, on the one hand, with the flow of information during communication, on the other. Finally, we relate our findings to the body of research on rhythmic brain mechanism in speech processing by comparing the topographical distributions of neural speech tracking in model-predicted and empirical EEG. This qualitative comparison suggests that IU-related neural activity contributes to the previously characterized delta-band neural speech tracking.

neuroscience↗

bioRxiv2022

Epigenetic reprogramming shapes the cellular landscape of schwannoma

Cell state evolution underlies tumor development and response to therapy1, but mechanisms specifying cancer cell states and intratumor heterogeneity are incompletely understood. Schwannomas are the most common tumors of the peripheral nervous system and are treated with surgery and ionizing radiation2-5. Schwannomas can oscillate in size for many years after radiotherapy6,7, suggesting treatment may reprogram schwannoma cells or the tumor microenvironment. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas. We find schwannomas are comprised of 2 molecular groups distinguished by reactivation of neural crest development pathways or misactivation of nerve injury mechanisms that specify cancer cell states and the architecture of the tumor immune microenvironment. Schwannoma molecular groups can arise independently, but ionizing radiation is sufficient for epigenetic reprogramming of neural crest to immune-enriched schwannoma by remodeling chromatin accessibility, gene expression, and metabolism to drive schwannoma cell state evolution and immune cell infiltration. To define functional genomic mechanisms underlying epigenetic reprograming of schwannomas, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of cancer evolution and establish a paradigm of epigenetic reprograming of cancer in response to radiotherapy.

cancer biology↗

bioRxiv2022

Characterisation of key genotypic and phenotypic traits of clinical cystic fibrosis Staphylococcus aureus isolates

IntroductionOne third of people with CF in the UK are co-infected by both Staphylococcus aureus and Pseudomonas aeruginosa. Chronic bacterial infection in CF contributes to the gradual destruction of lung tissue, and eventually respiratory failure in this group. Gap StatementThe contribution of S. aureus to cystic fibrosis (CF) lung decline in the presence or absence of P. aeruginosa is unclear. Defining the molecular and phenotypic characteristics of a range of S. aureus clinical isolates will help further understand its pathogenic capabilities. AimOur objective was to use molecular and phenotypic tools to characterise twenty-five clinical S. aureus isolates collected from mono- and coinfection with P. aeruginosa from people with CF at the Royal Victoria Infirmary, Newcastle upon Tyne. MethodologyGenomic DNA was extracted and sequenced. Multilocus sequence typing was used to construct phylogeny from the seven housekeeping genes. A pangenome was calculated using Roary. and cluster of Orthologous groups were assigned using eggNOG-mapper which were used to determine differences within core, accessory, and unique genomes. Characterisation of sequence type, clonal complex, agr and spa types was carried out using PubMLST, eBURST, AgrVATE and spaTyper, respectively. Antibiotic resistance was determined using Kirby Bauer disk diffusion tests. Phenotypic testing of haemolysis was carried out using ovine red blood cell agar plates and mucoid phenotypes visualised using Congo red agar. ResultsClinical strains clustered closely based on agr type, sequence type and clonal complex. COG analysis revealed statistically significant enrichment of COG families between core, accessory and unique pangenome groups. The unique genome was significantly enriched for replication, recombination and repair, and defence mechanisms. The presence of known virulence genes and toxins were high within this group, and unique genes were identified in 11 strains. Strains which were isolated from the same patient all surpassed average nucleotide identity thresholds, however, differed in phenotypic traits. Antimicrobial resistance to macrolides was significantly higher in the coinfection group. ConclusionThere is huge variation in genetic and phenotypic capabilities of S. aureus strains. Further studies on how these may differ in relation to other species in the CF lung may give insight into inter-species interactions. Data summaryThe assembled GenBank (gbk) files for all clinical isolates in this study have been deposited in ENA under the study accession PRJEB56184, accession numbers for each of the twenty-five clinical isolates have been provided in Table S1. The reference strains were collected from the NCBI BioSample database (www.ncbi.nlm.nih.gov/biosample): MRSA_252 (NC_002952.2), HO 5096 0412 (NC_017763.1), ST398 (NC_017333.1) and NCTC8325 (NC_007795.1).

microbiology↗

bioRxiv2022

Effects of social presence on behavioural, neural and physiological aspects of empathy for pain

In mediated interactions (e.g. video calls), less information is available about the other. To investigate how this affects our empathy for one another, we conducted an EEG study, in which thirty human participants observed one of 5 targets undergoing painful electric stimulation, once in a direct interaction and once in a live, video-mediated interaction. We found that observers were as accurate in judging others pain and showed as much affective empathy via video as in a direct encounter. While mu suppression, a common neural marker of empathy, was not sensitive to others pain, theta responses to others pain as well as skin conductance coupling between participants were reduced in the video-mediated condition. We conclude that physical proximity with its rich social cues is important for nuanced physiological resonance with the others experience. More studies are warranted to confirm these results and to understand their behavioural significance for remote social interactions.

neuroscience↗

bioRxiv2022

Phenotypic trait variation in a long-term, multisite common garden of Scots pine in Scotland

Multisite common garden experiments, exposing common pools of genetic diversity to a range of environments, allow quantification of plastic and genetic components of trait variation. For tree species, such studies must be long term as they typically only express mature traits after many years. As well as evaluating standing genetic diversity, these experiments provide an ongoing test of genetic variation against changing environmental conditions and form a vital resource for understanding how species respond to abiotic and biotic variation. Finally, quantitative assessments of phenotypic variation are essential to pair with rapidly accumulating genomic data to advance understanding of the genetic basis of trait variation, and its interaction with climatic change. We describe a multisite, population-progeny, common garden experiment of the economically and ecologically important tree species, Scots pine, collected from across its native range in Scotland and grown in three contrasting environments. Phenotypic traits, including height, stem diameter and budburst were measured over 14 growing seasons from nursery to field site. The datasets presented have a wide range of applications.

ecology↗

bioRxiv2022

Dynamic regulation of neural variability during working memory reflects dopamine, functional integration, and decision-making

The regulation of moment-to-moment neural variability may permit effective responses to changing cognitive demands. However, the mechanisms that support variability regulation are unknown. In the context of working memory, we leverage the largest available PET and fMRI dataset to jointly consider three lenses through which neural variability regulation could be understood: dopamine capacity, network-level functional integration, and flexible decision processes. We show that with greater working memory load, upregulation of variability was associated with elevated dopamine capacity and heightened functional integration, effects dominantly expressed in the striato-thalamic system rather than cortex. Strikingly, behavioral modeling revealed that working memory load evoked substantial decision biases during evidence accumulation, and those who jointly expressed a more optimal decision bias and higher dopamine capacity were most likely to upregulate striato-thalamic variability under load. We argue that the ability to align striato-thalamic variability to level of demand may be a hallmark of a well-functioning brain.

neuroscience↗

bioRxiv2021

CaveCrawler: An interactive analysis suite for cavefish bioinformatics

The growing use of genomics data in diverse animal models provides the basis for identifying genomic and transcriptional differences across species and contexts. Databases containing genomic and functional data have played critical roles in the development of numerous genetic models but are lacking for most emerging models of evolution. There is a rapidly expanding use of genomic, transcriptional, and functional genetic approaches to study diverse traits of the Mexican tetra, Astyanax mexicanus. This species exists as two morphs, eyed surface populations and at least 30 blind cave populations, providing a system to study convergent evolution. We have generated a web-based analysis suite that integrates datasets from different studies to identify how gene transcription and genetic markers of selection differ between populations and across experimental contexts. Results can be processed with other analysis platforms including Gene Ontology (GO) to enable biological inference from cross-study patterns and identify future avenues of research. Furthermore, the framework that we have built A. mexicanus can readily applied to other emerging model systems.

bioinformatics↗

bioRxiv2021

Escaping the Fate of Sisyphus: Assessing Resistome Hybridization Baits for Antimicrobial Resistance Gene Capture

Finding, characterizing, and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive, and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19,933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3,565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement. Originality-Significance StatementThis work is applicable to a wide range of research. It helps to define conditions under which hybridization capture is useful regarding not only antimicrobial resistance specifically, but also more generally how to assess the ongoing utility of existing bait sets - giving objective criteria for when and by what strategies baits should be updated. We also provide a method for quantifying and comparing antimicrobial resistance genes (ARGs) similar to what is used for RNAseq experiments. This approach improves comparison of ARGs across environments. Thus, the work provides an improved foundation for ARG future studies, while cutting across traditional areas of microbiology and extending beyond.

microbiology↗

bioRxiv2021

Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research

Scots pine (Pinus sylvestris) is the most widespread coniferous tree in the boreal forests of Eurasia and has major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies and genomic selection. We present a new 50K SNP genotyping array for Scots pine research, breeding programs, and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array, and identified 47 712 high-quality SNPs for the final array (called PiSy50k). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns, and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from breeding populations from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.92%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the amount of Mendelian error was negligible. In addition, array genotypes successfully discriminate Scots pine populations from different geographic origins. The PiSy50k array will be a valuable tool for future genetic studies and forestry applications. Significance statementScots pine is an evolutionary, economically and ecologically impressive coniferous species but its gigantic genome has limited studying e.g. the genetic basis of its functional trait variation. We have developed a genotyping array that facilitates Scots pine genetic research and linking its trait variation to genetic polymorphisms and gene expression levels across the genome.

genomics↗

bioRxiv2021

Larvae and adults exhibit contrasting patterns of immune gene expression and infection resistance in wild flour beetle populations

In nature, hosts face shifting patterns of parasite exposure and life history trade-offs as they develop from birth to old age. As a result, the net fitness benefit of immunological investment can change dramatically from one life stage to the next. Previous work has revealed a puzzling diversity of relative immune investment patterns among juvenile and adult stages, and it is not clear whether lessons learned from one particular population or species can be generalized to wild populations, after accounting for local adaptation and other variance-generating processes. In this study, we quantify larval and adult immune gene expression and resistance to bacterial infection in two flour beetle species (Tribolium castaneum and T. confusum) from two lab-adapted and five wild-derived populations. Our results provide a clear signal of higher infection-induced immunological investment and resistance in adults relative to larvae, despite variation among species in immune gene regulation. Better characterization of stage-specific investment in infection resistance in natural populations can inform our understanding of life history evolution and improve predictions of disease dynamics in the wild.

evolutionary biology↗

bioRxiv2021

Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies

Candida albicans, an opportunistic fungal pathogen, is a significant cause of human infections, particularly in immunocompromised individuals. Phenotypic plasticity between two morphological phenotypes, yeast and hyphae, is a key mechanism by which C. albicans can thrive in many microenvironments and cause disease in the host. Understanding the decision points and key driver genes controlling this important transition, and how these genes respond to different environmental signals is critical to understanding how C. albicans causes infections in the host. Here we build and analyze a Boolean dynamical model of the C. albicans yeast to hyphal transition, integrating multiple environmental factors and regulatory mechanisms. We validate the model by a systematic comparison to prior experiments, which led to agreement in 18 out of 22 cases. The discrepancies motivate alternative hypotheses that are testable by follow-up experiments. Analysis of this model revealed two time-constrained windows of opportunity that must be met for the complete transition from the yeast to hyphal phenotype, as well as control strategies that can robustly prevent this transition. We experimentally validate two of these control predictions in C. albicans strains lacking the transcription factor UME6 and the histone deacetylase HDA1, respectively. This model will serve as a strong base from which to develop a systems biology understanding of C. albicans morphogenesis.

systems biology↗

bioRxiv2020

Identifying and testing marker-trait associations for growth and phenology in three pine species

In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.

plant biology↗

bioRxiv2020

A subset of pediatric thalamic gliomas share a distinct DNA methylation profile, H3K27me3 loss and frequent alteration of EGFR

BackgroundMalignant astrocytic gliomas in children show a remarkable biological and clinical diversity. Small in-frame insertions or missense mutations in the EGFR gene have recently been identified in a distinct subset of pediatric bithalamic gliomas with a unique DNA methylation pattern. MethodsHere, we investigated an epigenetically homogeneous cohort of malignant gliomas (n=58) distinct from other subtypes and enriched for pediatric cases and thalamic location, in order to elucidate the overlap with this recently identified subtype of pediatric bithalamic gliomas. ResultsEGFR gene amplification was detected in 16/58 (27%) tumors, and missense mutations or small in-frame insertions in EGFR were found in 20/30 tumors with available sequencing data (67%; five of them co-occurring with EGFR amplification). Additionally, eight of the 30 tumors (27%) harbored an H3.1 or H3.3 K27M mutation (six of them with a concomitant EGFR alteration). All tumors tested showed loss of H3K27me3 staining, with evidence of EZHIP overexpression in the H3 wildtype cases. Although some tumors indeed showed a bithalamic growth pattern, a significant proportion of tumors occurred in the unilateral thalamus or in other (predominantly midline) locations. ConclusionsOur findings present a distinct molecular class of pediatric malignant gliomas largely overlapping with the recently reported bithalamic gliomas characterized by EGFR alteration, but additionally showing a broader spectrum of EGFR alterations and tumor localization. Global H3K27me3 loss in this group appears to be mediated by either H3 K27 mutation or EZHIP overexpression. EGFR inhibition may represent a potential therapeutic strategy in these highly aggressive gliomas. Key pointsO_LIThis study confirms a distinct new subset of pediatric diffuse midline glioma with H3K27me3 loss, with or without H3 K27 mutation C_LIO_LIThe poor outcome of these tumors is in line with the broader family of pediatric diffuse midline gliomas with H3 K27 mutation or EZHIP overexpression C_LIO_LIFrequent EGFR alterations in these tumors may represent a therapeutic target in this subset C_LI Importance of the StudyMalignant astrocytic gliomas in children show a remarkable biological and clinical diversity. Here, we highlight a distinct molecular class of pediatric malignant gliomas characterized by EGFR alteration and global H3K27me3 loss that appears to be mediated by either H3 K27 mutation or EZHIP overexpression. EGFR inhibition may represent a potential therapeutic strategy in these highly aggressive gliomas.

cancer biology↗

bioRxiv2019

3D-Cardiomics: A spatial transcriptional atlas of the mammalian heart

Understanding spatial gene expression and regulation is key to uncovering developmental and physiological processes, during homeostasis and disease. Numerous techniques exist to gain gene expression and regulation information, but very few utilise intuitive true-to-life three-dimensional representations to analyze and visualize results. Here we combined spatial transcriptomics with 3D modelling to represent and interrogate, transcriptome-wide, three-dimensional gene expression and location in the mouse adult heart. Our study has unveiled specific subsets of genes that display complex spatial expression in organ sub-compartments. Also, we created a web-based user interface for spatial transcriptome analysis and visualization. The application may be accessed from http://3d-cardiomics.erc.monash.edu/.

systems biology↗

bioRxiv2019

Natural variation in the contribution of microbial density to inducible immune dynamics

Immune responses evolve to balance the benefits of microbial killing against the costs of autoimmunity and energetic resource use. Models that explore the evolution of optimal immune responses generally include a term for constitutive immunity, or the level of immunological investment prior to microbial exposure, and for inducible immunity, or investment in immune function after microbial challenge. However, studies rarely consider the functional form of inducible immune responses with respect to microbial density, despite the theoretical dependence of immune system evolution on microbe-versus immune-mediated damage to the host. In this study, we analyze antimicrobial peptide (AMP) gene expression from seven wild-caught flour beetle populations (Tribolium spp.) during acute infection with the virulent bacteria Bacillus thuringiensis (Bt) and Photorhabdus luminescens (P.lum) to demonstrate that inducible immune responses mediated by the humoral IMD pathway exhibit natural variation in both microbe density-dependent and independent temporal dynamics. Beetle populations that exhibited greater AMP expression sensitivity to Bt density were also more likely to die from infection, while populations that exhibited higher microbe density-independent AMP expression were more likely to survive P. luminescens infection. Reduction in pathway signaling efficiency through RNAi-mediated knockdown of the imd gene reduced the magnitude of both microbe-independent and dependent responses and reduced host resistance to Bt growth, but had no net effect on host survival. This study provides a framework for understanding natural variation in the flexibility of investment in inducible immune responses and should inform theory on the contribution of non-equilibrium host-microbe dynamics to immune system evolution.

evolutionary biology↗

bioRxiv2019

Left prefrontal connectivity links subthalamic stimulation with depressive symptoms in Parkinson’s disease

ObjectiveSubthalamic nucleus deep brain stimulation (STN-DBS) in Parkinsons Disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non-motor DBS effects is not well characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN-DBS which have been reported to improve, worsen or remain unchanged. MethodsDepressive symptoms before and after STN-DBS surgery were documented in 116 PD patients from three DBS centers (Berlin, Queensland, Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTA) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross-validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as test-set for which depressive symptom change was predicted. ResultsStructural connectivity was linked to depressive symptom change under STN-DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training-set map predicted changes in depressive symptoms in the independent test-set. Worsening of depressive symptoms was associated with left prefrontal connectivity. InterpretationFibers linking the STN electrode with left prefrontal areas predicted worsening of depressive symptoms. Our results suggest that for the left STN-DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms.

neuroscience↗

bioRxiv2019

GNI-A1 mediates trade-off between grain number and grain weight in tetraploid wheat

Grain yield is a highly polygenic trait determined by the number of grains per unit area, as well as by grain weight. In wheat, grain number and grain weight are usually negatively correlated. Yet, the genetic basis underlying trade-off between the two is mostly unknown. Here, we fine-mapped a grain weight QTL using wild emmer introgressions in a durum wheat background, and showed that grain weight is associated with the GNI-A1 gene, a regulator of floret fertility. In-depth characterization of grain number and grain weight indicated that suppression of distal florets by the wild emmer GNI-A1 allele increase weight of proximal grains in basal and central spikelets due to alteration in assimilate distribution. Re-sequencing of GNI-A1 in tetraploid wheat demonstrated the rich allelic repertoire of the wild emmer gene pool, including a rare allele which was present in two gene copies and contained a non-synonymous mutation in the C-terminus of the protein. Using an F2 population generated from a cross between wild emmer accessions Zavitan, which carries the rare allele, and TTD140, we demonstrated that this unique polymorphism is associated with grain weight, independent of grain number. Moreover, we showed, for the first time, that GNI-A1 proteins are transcriptional activators and that selection in domesticated wheat targeted compromised activity of the protein. Our finding expand the knowledge of the genetic basis underlying trade-off between key yield components and may contribute to breeding efforts for enhanced grain yield.

plant biology↗

bioRxiv2018

Differentiation of Alzheimer’s disease based on local and global parameters in personalized Virtual Brain models

Alzheimers disease (AD) is marked by cognitive dysfunction emerging from neuropathological processes impacting brain function. AD affects brain dynamics at the local level, such as changes in the balance of inhibitory and excitatory neuronal populations, as well as long-range changes to the global network. Individual differences in these changes as they relate to behaviour are poorly understood. Here, we use a multi-scale neurophysiological model, \"The Virtual Brain (TVB)\", based on empirical multi-modal neuroimaging data, to study how local and global dynamics correlate with individual differences in cognition. In particular, we modeled individual resting-state functional activity of 124 individuals across the behavioral spectrum from healthy aging, to amnesic Mild Cognitive Impairment (MCI), to AD. The model parameters required to accurately simulate empirical functional brain imaging data correlated significantly with cognition, and exceeded the predictive capacity of empirical connectomes.

neuroscience↗