Biology subjects

Adamson, C.

Publications and source records attributed to Adamson, C..

9 recordsLinked to original sources

bioRxiv2026

Coordinated GlcNAc transport couples nutrient acquisition to invasive growth and virulence in Candida albicans

Candida albicans is a prevalent gut commensal and opportunistic fungal pathogen whose transition from intestinal colonization to invasive infection is influenced by environmental cues. N-acetylglucosamine (GlcNAc), abundant in the gut from host and microbial sources, serves not only as a carbon source but also as a potent signal that promotes hyphal morphogenesis and virulence. However, how C. albicans coordinates GlcNAc uptake to regulate these pathogenic responses remains incompletely understood. Here, we identify Hgt1, a canonical glucose transporter, as an alternative GlcNAc transporter that cooperates with the GlcNAc-specific transporter Ngt1 to promote fungal morphogenesis and virulence. Simultaneous deletion of HGT1 and NGT1 markedly impairs GlcNAc-induced hyphal morphogenesis and virulence-associated gene expression. Mechanistically, Hgt1 facilitates the initial uptake of GlcNAc, promoting Ngt1 induction and subsequent robust hyphal growth, as evidenced by delayed Ngt1 expression and hyphal formation in cells lacking HGT1. These findings reveal a coordinated uptake mechanism involving two differentially regulated sugar transporters that enables C. albicans to respond efficiently to GlcNAc availability. Importantly, disruption of GlcNAc uptake reduces fungal dissemination to distal organs and associated host inflammatory responses in a mouse intestinal colonization model under GlcNAc-supplemented conditions. Together, our findings uncover a previously unrecognized mechanism by which C. albicans coordinates sugar transport to drive nutrient-induced pathogenicity, highlighting GlcNAc uptake as a potential target for limiting fungal virulence and systemic dissemination.

microbiology↗

bioRxiv2026

A natural glycolipid exposes the outer membrane interface as a tunable regulator of bacterial surface attachment.

Surface attachment initiates bacterial colonization and biofilm formation, yet remains difficult to target owing to redundant and species-specific mechanisms. Here we identify dalberoside, a natural glycolipid that inhibits adhesion by non-disruptive remodeling of the Gram-negative outer membrane interface. Dalberoside inhibited Pseudomonas aeruginosa and Acinetobacter baumannii attachment and biofilm formation without measurable bactericidal activity or membrane permeabilization. It reduced P. aeruginosa retention on epithelial cells, delayed P. aeruginosa cytotoxicity and rapidly detached surface-associated A. baumannii. High-resolution microscopy of a fluorescent analogue and in situ cryo-electron tomography support a model in which dalberoside associates with the bacterial outer membrane, remodeling its outer leaflet. Biophysical measurements further indicated altered local interfacial properties. Thus, dalberoside reveals the outer membrane interface as a chemically addressable regulator of bacterial surface attachment.

microbiology↗

bioRxiv2024

Gut microbiota-derived GlcNAc-MurNAc is a TLR4 agonist that protects the host gut

Gut microbiota-derived peptidoglycan fragments (PGNs) are key signaling molecules that regulate multiple aspects of the hosts health. Yet the exact structures of natural PGNs in hosts have not been fully elucidated. Herein, we developed an LC-HRMS/MS analytical platform for global quantification and profiling of natural PGN subtypes in host gut and sera, unexpectedly revealing the abundance of PGN-derived saccharide moieties that do not resemble canonical ligands of mammalian NOD1/2 receptors. Focusing on the disaccharide GlcNAc-MurNAc (GM), a natural gut PGN that does not activate NOD1/2 yet still exhibits robust immunostimulatory effects in host immune cells, we unambiguously established GM as a TLR4 agonist, adding to the growing knowledge of NOD-independent mechanisms of PGN sensing in hosts. Importantly, the administration of GM effectively mitigates colonic inflammation in the DSS-induced colitis model in mice via TLR4-dependent mechanisms, highlighting the in vivo significance of natural gut microbiota-derived PGNs in maintaining host intestinal homeostasis.

biochemistry↗

bioRxiv2021

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure. Furthermore, we provide open resources to support future advances towards adoption of brain charts as standards for quantitative benchmarking of typical or atypical brain MRI scans.

neuroscience↗

bioRxiv2019

Parcellation of the cortex using Surface-based Melbourne Children's Regional Infant Brain atlases (M-CRIB-S)

BackgroundLongitudinal studies of cortical morphology are best facilitated by parcellation schemes that are compatible across all life stages. Until recently, neonatal atlases derived strictly from neonatal data, rather than warping brain labels from an adult atlas, did not exist. The Melbourne Childrens Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases now provide voxel-based parcellations of the cerebral cortex within T2-weighted neonatal images. These atlases are compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes commonly used for older children and adults. However, there is still a need for a surface-based approach for parcellating neonatal images using these atlases. AimsWe aimed to introduce surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), along with a pipeline for automated parcellation with FreeSurfer tools. We also aimed to evaluate the automated parcellation accuracy of our M-CRIB-S atlases using cross-validation with manually labelled data; and to evaluate accuracy of the proposed automated parcellation pipeline for the M-CRIB-S labels against the publicly available surface-based University of North Carolina (UNC) 4D neonatal atlas, which has labels derived from the DK adult atlas. MethodsUsing datasets of 10 M-CRIB or M-CRIB 2.0 manually labelled ground truth images and 48 unlabelled T2-weighted magnetic resonance images (MRI) of healthy neonates, cortical surfaces were extracted using the Deformable module within MIRTK. Cortical regions from the labelled images were encoded into a spherical template space using FreeSurfer tools wherein M-CRIB-S(DK) and M-CRIB-S(DKT) atlases were constructed. Automatic parcellation of the labelled and unlabelled (L+U) images (n=58) using the M-CRIB-S(DK) and M-CRIB-S(DKT) atlases were computed with Bayesian labelling using FreeSurfer tools. Accuracy was assessed by comparison with manually labelled ground truth data (n=10) using Dice coefficients and within a Leave-One-Out (LOO) cross-validation framework. Agreement of the UNC atlas parcellations with manual M-CRIB labelling was also evaluated using Dice coefficients. ResultsWhen comparing automated parcellations from the M-CRIB-S atlases to manual labels, disagreements were mostly closely confined to region boundaries, suggesting high overlap overall. Quantitatively, average regional Dice coefficients were 0.88 (L+U) and 0.83 (LOO) for the M-CRIB 2.0 labels and 0.87 (L+U), 0.80 (LOO) for the M-CRIB labels, and 0.67 for the UNC atlas. ConclusionsThe M-CRIB-S atlases and automatic pipeline described in this paper allow infant cortical surfaces to be accurately parcellated according to the DK or DKT parcellation schemes. This will help facilitate surface-based investigations of brain function at the neonatal time point, and potentially longitudinally across the lifespan. The use of M-CRIB-S outperformed a technique that relies on an adult-derived atlas. The atlases, averaged white, inflated, pial and spherical surfaces, along with customised scripts for segmentation, cortical surface extraction and parcellation, are available for public download.

neuroscience↗

bioRxiv2018

Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders

The neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and bootstrapped permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p=0.01, n=5000 permutations; 10 surface area features, p=0.006, n=5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.

neuroscience↗

bioRxiv2018

Desikan-Killiany-Tourville Atlas Compatible Version of M-CRIB Neonatal Parcellated Whole Brain Atlas: The M-CRIB 2.0

Our recently published M-CRIB atlas comprises 100 neonatal brain regions including 68 compatible with the widely-used Desikan-Killiany adult cortical atlas. A successor to the Desikan-Killiany atlas is the Desikan-Killiany-Tourville atlas, in which some regions with unclear boundaries were removed, and many existing boundaries were revised to conform to clearer landmarks in sulcal fundi. Our first aim here was to modify cortical M-CRIB regions to comply with the Desikan-Killiany-Tourville protocol, in order to offer: a) compatibility with this adult cortical atlas, b) greater labelling accuracy due to clearer landmarks, and c) optimisation of cortical regions for integration with surface-based infant parcellation pipelines. Secondly, we aimed to update subcortical regions in order to offer greater compatibility with subcortical segmentations produced in FreeSurfer. Data utilized were the T2-weighted MRI scans in our M-CRIB atlas, for ten healthy neonates (postmenstrual age at MRI 40-43 weeks, 4 female), and corresponding parcellated images. Edits were performed on the parcellated images in volume space using ITK-SNAP. Cortical updates included deletion of frontal and temporal poles and Banks STS, and modification of boundaries of many other regions. Changes to subcortical regions included the addition of ventral diencephalon, and deletion of subcortical matter labels. A detailed updated parcellation protocol was produced. The resulting whole-brain M-CRIB 2.0 atlas comprises 94 regions altogether. This atlas provides comparability with adult Desikan-Killiany-Tourville-labelled cortical data and FreeSurfer-labelled subcortical data, and is more readily adaptable for incorporation into surface-based neonatal parcellation pipelines. As such, it offers the ability to help facilitate a broad range of investigations into brain structure and function both at the neonatal time point and developmentally across the lifespan.

neuroscience↗

bioRxiv2018

Marker-based watershed transform method for fully automatic mandibular segmentation from low-dose CBCT images

Introduction Introduction Methods and materials Results Discussion Conclusions Funding References Three-dimensional mandibular models are useful for planning maxillofacial surgery and orthodontic treatment.1,2 In studies of growth, mandibular models are important for assessing morphological changes over time.3,4 Such models are typically obtained from conventional computed tomography (CT), using high radiation dose to capture fine detail of the bony structure. Cone beam computed tomography (CBCT) shows promise for oral and craniofacial imaging applications due to lower radiation dose, lower cost and shorter acquisition time compared to CT. However, CBCT images have lower contrast and higher levels of ...

bioinformatics↗

bioRxiv2017

Modelling Neuroanatomical Variation Due To Age And Sex During Childhood And Adolescence

Brain development is a dynamic process that follows a choreographed trajectory during childhood and adolescence with tissue-specific alterations that reflect complex and ongoing biological processes. Accurate identification and modelling of these anatomical processes in vivo with MRI may provide clinically useful imaging markers of individual variability in development. In this study, we build a model of age- and sex-related anatomical variation using multimodal imaging measures and manifold learning.\n\nUsing publicly-available data from two large, independent developmental cohorts (n=768 and 862), we apply a multimodal machine learning approach combining measures of tissue volume, cortical area and cortical thickness into a low-dimensional data representation.\n\nWe find that neuroanatomical variation due to age and sex can be captured by two orthogonal patterns of brain development and we use this model to predict age with a mean error of 1.6-2 years and sex with an accuracy of 80-84%.\n\nWe present a framework for modelling anatomical development during childhood using low-dimensional data representations. This model accurately predicts age and sex based on image-derived markers of cerebral morphology and generalises well to independent populations.

neuroscience↗