Biology subjects

Alexander, B.

Publications and source records attributed to Alexander, B..

9 recordsLinked to original sources

bioRxiv2023

SMAD4: A Critical Regulator of Cardiac Neural Crest Cell Fate and Vascular Smooth Muscle Differentiation

BackgroundThe pharyngeal arch arteries (PAAs) are precursor vessels which remodel into the aortic arch arteries (AAAs) during embryonic cardiovascular development. Cardiac neural crest cells (NCs) populate the PAAs and differentiate into vascular smooth muscle cells (vSMCs), which is critical for successful PAA-to-AAA remodeling. SMAD4, the central mediator of canonical TGF{beta} signaling, has been implicated in NC-to-vSMC differentiation; however, its distinct roles in vSMC differentiation and NC survival are unclear. ResultsHere, we investigated the role of SMAD4 in cardiac NC differentiation to vSMCs using lineage-specific inducible mouse strains in an attempt to avoid early embryonic lethality and NC cell death. We found that with global SMAD4 loss, its role in smooth muscle differentiation could be uncoupled from its role in the survival of the cardiac NC in vivo. Moreover, we found that SMAD4 may regulate the induction of fibronectin, a known mediator of NC-to-vSMC differentiation. Finally, we found that SMAD4 is required in NCs cell-autonomously for NC-to-vSMC differentiation and for NC contribution to and persistence in the pharyngeal arch mesenchyme. ConclusionsOverall, this study demonstrates the critical role of SMAD4 in the survival of cardiac NCs, their differentiation to vSMCs, and their contribution to the developing pharyngeal arches.

developmental biology↗

bioRxiv2021

Benchmarking Geometric Deep Learning for Cortical Segmentation and Neurodevelopmental Phenotype Prediction

The emerging field of geometric deep learning extends the application of convolutional neural networks to irregular domains such as graphs, meshes and surfaces. Several recent studies have explored the potential for using these techniques to analyse and segment the cortical surface. However, there has been no comprehensive comparison of these approaches to one another, nor to existing Euclidean methods, to date. This paper benchmarks a collection of geometric and traditional deep learning models on phenotype prediction and segmentation of sphericalised neonatal cortical surface data, from the publicly available Developing Human Connectome Project (dHCP). Tasks include prediction of postmenstrual age at scan, gestational age at birth and segmentation of the cortical surface into anatomical regions defined by the M-CRIB-S atlas. Performance was assessed not only in terms of model precision, but also in terms of network dependence on image registration, and model interpretation via occlusion. Networks were trained both on sphericalised and anatomical cortical meshes. Findings suggest that the utility of geometric deep learning over traditional deep learning is highly task-specific, which has implications for the design of future deep learning models on the cortical surface. The code, and instructions for data access, are available from https://github.com/Abdulah-Fawaz/Benchmarking-Surface-DL.

neuroscience↗

bioRxiv2021

Deep learning redesign of PETase for practical PET degrading applications

Plastic waste poses an ecological challenge1. While current plastic waste management largely relies on unsustainable, energy-intensive, or even hazardous physicochemical and mechanical processes, enzymatic degradation offers a green and sustainable route for plastic waste recycling2. Poly(ethylene terephthalate) (PET) has been extensively used in packaging and for the manufacture of fabrics and single-used containers, accounting for 12% of global solid waste3. The practical application of PET hydrolases has been hampered by their lack of robustness and the requirement for high processing temperatures. Here, we use a structure-based, deep learning algorithm to engineer an extremely robust and highly active PET hydrolase. Our best resulting mutant (FAST-PETase: Functional, Active, Stable, and Tolerant PETase) exhibits superior PET-hydrolytic activity relative to both wild-type and engineered alternatives, (including a leaf-branch compost cutinase and its mutant4) and possesses enhanced thermostability and pH tolerance. We demonstrate that whole, untreated, post-consumer PET from 51 different plastic products can all be completely degraded by FAST-PETase within one week, and in as little as 24 hours at 50 {degrees}C. Finally, we demonstrate two paths for closed-loop PET recycling and valorization. First, we re-synthesize virgin PET from the monomers recovered after enzymatic depolymerization. Second, we enable in situ microbially-enabled valorization using a Pseudomonas strain together with FAST-PETase to degrade PET and utilize the evolved monomers as a carbon source for growth and polyhydroxyalkanoate production. Collectively, our results demonstrate the substantial improvements enabled by deep learning and a viable route for enzymatic plastic recycling at the industrial scale.

bioengineering↗

bioRxiv2020

Curvature of the retroviral capsid assembly is modulated by a molecular switch

During the maturation step, the capsid proteins (CAs) of a retrovirus assemble into polymorphic capsids, whose acute curvature is largely determined by insertion of 12 pentamers into the hexameric lattice. Despite years of intensive research, it remains elusive how the CA switches its conformation between the quasi-equivalent pentameric and hexameric assemblies to generate the acute curvature in the capsid. Here we report the high-resolution structural model of the RSV CA T=1 capsid. By comparing with our prior model of the RSV CA tubular assembly consisting entirely of hexameric lattices, we identify that a dozen of residues are the key to dictate the incorporation of acute curvatures in the capsid assembly. They undergo large torsion angle changes, which result a 34{degrees} rotation of the C-terminal domain relative to its N-terminal domain around the flexible interdomain linker, without substantial changes of either the conformation of individual domains or the assembly contact interfaces. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/424437v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@40cf38org.highwire.dtl.DTLVardef@e490beorg.highwire.dtl.DTLVardef@1dae0c5org.highwire.dtl.DTLVardef@dac850_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2020

New mechanism of fibronectin fibril assembly revealed by live imaging and super-resolution microscopy.

Fn1 fibrils have long been viewed as continuous fibers composed of extended, periodically aligned Fn1 molecules. However, our live imaging and single-molecule localization microscopy (SMLM) are inconsistent with this traditional view and show that Fn1 fibrils are composed of roughly spherical nanodomains containing 6-11 Fn1 dimers. As they move toward the cell center, Fn1 nanodomains become organized into linear arrays, wherein nanodomains are spaced at the average periodicity of 105{+/-}17 nm. Periodical Fn1 nanodomain arrays are bona fide fibrils: they are resistant to deoxycholate treatment and retain nanodomain periodicity in the absence of cells. The nanodomain periodicity in fibrils remained constant when probed with antibodies recognizing distinct Fn1 epitopes or combinations of antibodies recognizing epitopes spanning the length of Fn1. FUD, a bacterial peptide that binds Fn1 N-terminus and disrupts Fn1 fibrillogenesis does not disrupt the formation of Fn1 nanodomains, instead, it blocks the organization of Fn1 nanodomains into periodical arrays. These studies establish a new paradigm of Fn1 fibrillogenesis.

cell biology↗

bioRxiv2019

White Matter Extension of the Melbourne Children’s Regional Infant Brain Atlas: M-CRIB-WM

BackgroundUnderstanding typically developing infant brain structure is crucial in investigating neurological disorders of early childhood. Brain atlases providing standardised identification of neonatal brain regions are key in such investigations. Our previously developed Melbourne Childrens Regional Infant Brain (M-CRIB) and M-CRIB 2.0 neonatal brain atlases provide standardised parcellation of 100 and 94 brain regions respectively, including cortical, subcortical, and cerebellar regions. The aim of this study was to extend the M-CRIB atlas coverage to include 54 white matter regions.\n\nMethodsParticipants were ten healthy term-born neonates who comprised the sample for the M-CRIB and M-CRIB 2.0 atlases. WM regions were manually segmented on T2 images and co-registered diffusion tensor imaging-based, direction-encoded colour maps. Our labelled regions are based on those in the JHU-neonate-SS atlas, but differ in the following ways: 1) we included five corpus callosum subdivisions instead of a left / right division; 2) we included a left / right division for the middle cerebellar peduncle; and 3) we excluded the three brainstem divisions. All segmentations were reviewed and approved by a paediatric radiologist and a neurosurgery research fellow for anatomical accuracy.\n\nResultsThe resulting neonatal WM atlas comprises 54 WM regions: 24 paired regions, and six unpaired regions comprising five corpus callosum subdivisions and one pontine crossing tract. Detailed protocols for manual WM parcellations are provided, and the M-CRIB-WM atlas is presented together with the existing M-CRIB and M-CRIB 2.0 cortical, subcortical and cerebellar parcellations in ten individual neonatal MRI datasets.\n\nConclusionThe updated M-CRIB atlas including the WM parcellations will be made publicly available. The atlas will be a valuable tool that will help facilitate neuroimaging research into neonatal WM development in both healthy and diseased states.

neuroscience↗

bioRxiv2019

Blood cells of adult Drosophila do not expand, but control survival after bacterial infection by induction of Drosocin around their reservoir at the respiratory epithelia

Drosophila melanogaster has been an excellent model for innate immunity, but the role and regulation of adult blood cells and organismal immunity have remained incompletely understood. Here we address these questions in a comprehensive investigation of the blood cell system in adult Drosophila. As a central finding, we reveal the largest reservoir of blood cells (hemocytes) at the respiratory epithelia (tracheal air sacs) and fat body of the thorax and head. We show that most hemocytes of adult Drosophila are phagocytic macrophages (plasmatocytes), derived by more than 60% from the embryonic lineage that parallels vertebrate tissue macrophages. Surprisingly, in contrast to hemocytes at the larval stage, we find no capacity of the adult blood cell system to expand. Instead, we demonstrate its central role in relaying an innate immune response to tissues surrounding the blood cell reservoir: Hemocytes, through Imd signaling and the Jak/Stat pathway ligand Upd3, act as sentinels of bacterial infection that induce expression of the antimicrobial peptide gene Drosocin in the respiratory epithelia and colocalizing domains of the fat body. We demonstrate that endogenous Drosocin expression in these tissues promotes animal survival after bacterial infection. Our work identifies the first molecular step in a new relay of organismal immunity, establishing adult Drosophila as model to dissect mechanisms of inter-organ immunity.

immunology↗

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

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↗