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Biology subjects

Owen, J.

Publications and source records attributed to Owen, J..

9 recordsLinked to original sources

Shifting baselines increase the risk of misinterpreting biodiversity trends

Ecological studies quantifying the impact of land-use change on biodiversity may be sensitive to the choice of reference points - or baselines - particularly when sampling across human land-use gradients and other space-for-time comparisons. Much depends on whether the chosen baseline has already undergone shifts in species composition because of hunting, habitat loss and degradation. However, few studies have assessed the influence of shifting baselines on estimates of anthropogenic impacts. Using new survey data from five West African land-use gradients, we examine how habitat patch size and structure influences the estimated impact of land-use change on bird species richness and functional diversity. We show that smaller forests have already lost many forest-dependent birds, particularly those with large body size or specialised ecological niches, leading to reduced estimates of biodiversity loss after deforestation. The steepest biodiversity loss was found in mid-sized forests whereas relatively shallow declines were estimated for the most extensive forests - despite their richer taxonomic and functional diversity. In these larger forest blocks, accurate estimates of biodiversity loss may require longer transects extending beyond the biodiversity shadow caused by the more extensive spillover of forest species into the surrounding landscape, potentially linked to source-sink dynamics. These findings suggest that biodiversity assessments are highly sensitive to baseline selection and transect design, highlighting the risk of underestimating land-use impacts unless shifting baselines are carefully considered.

ecology↗

Discovery of small molecule antagonists of human Retinoblastoma Binding Protein 4 (RBBP4)

RBBP4 is a nuclear WD40 motif-containing protein widely implicated in various cancers and a putative drug target. It interacts with multiple proteins within diverse complexes such as nucleosome remodeling and deacetylase (NuRD) complex and polycomb repressive complex 2 (PRC2), as well as histone H3 and H4 through two distinct binding sites. B-cell lymphoma/leukemia 11A (BCL11A), friend of GATA-1 (FOG-1), plant homeodomain finger protein 6 (PHF6) and histone H3 bind to the top of the donut-shaped seven-bladed {beta}-propeller fold of RBBP4, while suppressor of zeste 12 (SUZ12), metastasis associated protein 1 (MTA1) and histone H4 bind to a pocket on the side of the WD40 repeats of this protein. Here, we report the discovery of the first small molecule antagonists of the RBBP4 top pocket, competing with interacting peptides from proteins such as BCL11A and histone H3. We also determined the first crystal structure of RBBP4 in complex with a small molecule (OICR17251), paving the path for structure-guided design and optimization towards more potent antagonists.

biochemistry↗

Superinfection Exclusion of Alphaherpesviruses Interferes with Virion Trafficking

Superinfection exclusion (SIE) is a phenomenon in which a primary viral infection interferes with secondary viral infections within that same cell. Although SIE has been observed across many viruses, it has remained relatively understudied. A recently characterized glycoprotein D (gD) -independent SIE of alphaherpesviruses presents a novel mechanism of co-infection restriction for Herpes Simplex Virus Type 1 (HSV-1) and Pseudorabies virus (PRV). In this study, we evaluated the role of multiplicity of infection (MOI), receptor expression, and trafficking of virions to gain greater insight into potential mechanisms of alphaherpesvirus SIE. We observed that high MOI secondary viral infections were able to overcome SIE in a manner that was independent of receptor availability. Utilizing recombinant viruses expressing fluorescent protein fusions, we assessed virion localization during SIE through live fluorescent microscopy of dual-labeled virions and localization of capsid assemblies. Analysis of these assemblies confirmed changes in the distribution of capsids during SIE. These results indicate that SIE during PRV infection inhibits viral entry or fusion while HSV-1 SIE inhibits infection through a post-entry mechanism. Although the timing and phenotype of SIE is similar between alphaherpesviruses, the related viruses implement different mechanisms to restrict coinfection. IMPORTANCEMost viruses utilize a form of superinfection exclusion to conserve resources and control population dynamics. gD-dependent superinfection exclusion in alphaherpesviruses is well-documented. However, the under-characterized gD-independent SIE provides new insight into how alphaherpesviruses limit sequential infection. The observations described here demonstrate that gD-independent SIE differs between PRV and HSV-1. Comparing these differences provide new insights into the underlying mechanisms of SIE implemented by two related viruses.

microbiology↗

Cancer-associated hypersialylated MUC1 drives the differentiation of monocytes into macrophages with a pathogenic phenotype

The tumour microenvironment plays a crucial role in the growth and progression of cancer and the presence of tumour-associated macrophages (TAMs) is associated with poor prognosis. Recent studies show that TAMs show transcriptomic, phenotypic, functional and geographical diversity. Here we show that a sialylated tumour-associated glycoform of the mucin MUC1, MUC1-ST, through the engagement of Siglec-9 can specifically and independently induce the differentiation of monocytes into TAMs with a unique phenotype. These TAMs can recruit and maintain neutrophils, inhibit the function of T cells, degrade basement membrane allowing for invasion, are inefficient at phagocytosis, and can induce plasma clotting. This novel macrophage phenotype is enriched in the stroma at the edge of breast cancer nests and their presence is associated with poor prognosis in breast cancer patients.

cancer biology↗

Efficient rational modification of non-ribosomal peptides by adenylation domain substitution

Non-ribosomal peptide synthetase (NRPS) enzymes form modular assembly-lines, wherein each module typically governs the incorporation of a specific amino acid or related monomer into a short peptide product. Modules are comprised of one or more key domains, including adenylation (A) domains, which recognise and activate the monomer substrate; condensation (C) domains, which catalyse amide bond formation; and thiolation (T) domains, which shuttle reaction intermediates between catalytic domains.1 This arrangement offers prospects for rational peptide modification via substitution of substrate-specifying domains within an assembly line.2,3 For over 20 years, it has been considered that both A domains and C domains play key roles in selecting and "proof-reading" the substrate;4 a presumption that has greatly complicated rational NRPS redesign.2,5 Here we present evidence derived both from natural and directed evolution studies that C domains do not play a substrate-specifying role, and that novel non-ribosomal peptides can be generated by substitution of A domains alone. We identify permissive A domain recombination boundaries and show that these allow us to efficiently generate novel pyoverdine peptides at high yields. We further demonstrate the transferability of our approach in the PheATE-ProCAT model system originally used to infer C domain substrate specificity, generating novel dipeptide products at yields that should not be attainable according to existing dogma.

molecular biology↗

Spectral Graph Theory of Brain Oscillations

The relationship between the brains structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed-form solution for the structure-function problem, specified by the graph spectrum of the structural connectomes Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. The resulting parsimonious and analytical solution stands in contrast to complex numerical simulations of high dimensional coupled non-linear neural field models. This spectral graph model accurately predicts spatial and spectral features of neural oscillatory activity across the brain and was successful in simultaneously reproducing empirically observed spatial and spectral patterns of alpha-band (8-12 Hz) and beta-band (15-30Hz) activity estimated from source localized scalp magneto-encephalography (MEG). This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole-brain dynamics. Significance StatementThe relationship between the brains structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed-form solution for the structure-function problem, specified by the graph spectrum of the structural connectomes Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole-brain dynamics.

neuroscience↗

Radiation resistant cancer cells enhance the survival and resistance of sensitive cells in prostate spheroids

Intratumoural heterogeneity contributes to local tumour recurrence and variable responses to radiotherapy in prostate cancer. Despite the multiclonal nature of the disease, tumour control probability for conventional treatment plans is modelled on the assumption that tumour cells in the target region respond identically and independently. Here, using tumour cell subpopulations with different radiation sensitivities from prostate tumour cell lines, we show that radiation resistant cells enhance the survival and radiation resistance of radio-sensitive cells in spheroids but not in monolayer culture. Mathematical modelling indicates that these phenotypic changes result from both competitive and antagonistic cellular interactions in spheroids. Interactions mediated by oxygen constraints define the spatial localisation of the cell populations in spheroids and in xenografts, while those mediated by paracrine signals further modify the microenvironment. Our results show new mechanisms of radiotherapy resistance mediated by cellular interactions and by the microenvironment.

cancer biology↗

Sensory Over-Responsivity: Parent Report, Direct Assessment Measures, and Neural Architecture

BackgroundSensory processing differences are common across neurodevelopmental disorders. Thus, reliable measures are needed to understand biologic underpinnings of these differences. This study aims to define a scoring methodology specific to tactile (TOR) and auditory (AOR) over-responsivity. Second, using MRI Diffusion Tensor Imaging, we seek to determine whether children with AOR show measurable differences in their white matter integrity.\n\nMethodsThis study includes children with AOR and TOR from a mixed neurodevelopmental disorders cohort including autism and sensory processing dysfunction (n= 176) as well as neurotypical children (n= 128). We established cut-off scores for over-responsivity using the parent report: Short Sensory Profile (SSP), and the direct assessment: Sensory Processing-Three Dimensions:Assessment (SP-3D:A). Group comparisons, based on AOR phenotype, were then conducted comparing the white matter fractional anisotropy in 23 regions of interest.\n\nResultsUsing the direct assessment, 31% of the children with neurodevelopmental disorders had AOR and 27% had TOR. The Inter-test-agreement between SSP and SP-3D:A for AOR was 65% and TOR was 50%. Children with AOR had three white matter tracts showing decreased fractional anisotropy relative to children without AOR.\n\nConclusionsThis study identified cut scores for AOR and TOR using the SSP parent report and SP-3D:A observation. A combination of questionnaire and direct observation measures should be used in clinical and research settings. The SSP parent report and SP-3D:A direct observation ratings overlapped moderately for sensory related behaviors. Based on these initial structural neuroimaging results, we suggest a putative neural network may contribute to AOR.

neuroscience↗

Functional rerouting via the structural connectome is associated with better recovery after mild TBI

Traumatic brain injury damages white matter pathways that connect brain regions, disrupting transmission of electrochemical signals and causing cognitive and emotional dysfunction. Connectome-level mechanisms for how the brain compensates for injury have not been fully characterized. Here, we collected serial MRI-based structural and functional connectome metrics and neuropsychological scores in 26 mild traumatic brain injury subjects (29.4{+/-}8.0 years, 20 male) at 1 and 6 months post-injury. We quantified the relationship between functional and structural connectomes using network diffusion model propagation time, a measure that can be interpreted as how much of the structural connectome is being utilized for the spread of functional activation, as captured via the functional connectome. Overall cognition showed significant improvement from 1 to 6 months (t25=-2.15, p=0.04). None of the structural or functional global connectome metrics were significantly different between 1 and 6 months, or when compared to 34 age- and gender-matched controls (28.6{+/-}8.8 years, 25 male). We predicted longitudinal changes in overall cognition from changes in global connectome measures using a partial least squares regression model (cross-validated R2 = 0.27). We observe that increased network diffusion model propagation time, increased structural connectome segregation and increased functional connectome integration were related to better cognitive recovery. We interpret these findings as suggesting two connectome-based post-injury recovery mechanisms: one of neuroplasticity that increases functional connectome integration and one of remote white matter degeneration that increases structural connectome segregation. We hypothesize that our inherently multi-modal measure of network diffusion model propagation time captures the interplay between these two mechanisms.\n\nAbbreviationsmild traumatic brain injury (mTBI), structural connectome (SC), functional connectome (FC), network diffusion (ND), functional MRI (fMRI), diffusion MRI (dMRI), principal component analysis (PCA), partial least squares regression (PLSR), confidence interval (CI), Attention Network Test (ANT), California Verbal Learning Test II (CVLT-II), Coma Recovery Scale - Revised (CRS-R)

neuroscience↗