Biology subjects

Weston, A. E.

Publications and source records attributed to Weston, A. E..

4 recordsLinked to original sources

bioRxiv2025

Dissecting PADI6 function defines oocyte cytoplasmic lattices as regulatory hubs for fundamental cellular processes

Oocyte cytoplasmic lattices are critical for early embryo development but their composition and function are not fully understood. Mutations in PADI6, an essential component of cytoplasmic lattices, lead to early embryonic developmental arrest and female infertility. To investigate PADI6 function in mRNA storage, global protein levels, and lattice composition during early mammalian development we used single cell transcriptomics and proteomics methods to study two mouse models. Padi6 null mutation resulted in inhibition of embryonic genome activation, defective maternal mRNA degradation, and disruption to protein storage on the cytoplasmic lattices. Distinct developmental phenotypes were observed with a hypomorphic Padi6 mutation. By developing a powerful single cell proteomic fractionation method, we define the cytoplasmic lattice enriched proteome in which we find essential components of another major oocyte-specific compartment, the endolysosomal vesicular assembly (ELVA), suggesting previously unknown interconnections between them. Our findings highlight a critical scaffolding function of PADI6 and implicate cytoplasmic lattices as regulatory hubs for key processes in the oocyte and early embryo, including translation, respiration and protein degradation.

developmental biology↗

bioRxiv2020

Geometric differences between nuclear envelopes of Wild-type and Chlamydia trachomatis-infected HeLa cells

In this work, the geometrical characteristics of two different types of cells observed with Electron Microscopy were analysed. The nuclear envelope of Wild-type HeLa cells and Chlamydia trachomatis-infected HeLa cells were automatically segmented and then modelled against a spheroid and converted to a two-dimensional surface. Geometric measurements from this surface and the volumetric nuclear envelope were extracted to compare the two types of cells. The measurements included the nuclear volume, the sphericity of the nucleus, its flatness or spikiness. In total 13 different cells were segmented: 7 Wild-type and 6 Chlamydia trachomatis-infected. The cells were statistically different in the following measurements. Wild-type HeLa cells have greater volumes than that of Chlamydia trachomatis-infected HeLa cells and they are more spherical as Jaccard index suggests. Standard deviation ({sigma}), and range of values for the nuclear envelope, which shows the distance of the highest peaks and deepest valleys from the spheroid, were also extracted from the modelling against a spheroid and these metrics were used to compare two different data sets in order to draw conclusions.

cell biology↗

bioRxiv2020

Semantic Segmentation of HeLa Cells: An Objective Comparison between one Traditional Algorithm and Three Deep-Learning Architectures

In this work, images of a HeLa cancer cell were semantically segmented with one traditional image-processing algorithm and three deep learning architectures: VGG16, ResNet18 and Inception-ResNet-v2. Three hundred slices, each 2000 x 2000 pixels, of a HeLa Cell were acquired with Serial Block Face Scanning Electron Microscopy. The deep learning architectures were pre-trained with ImageNet and then fine-tuned with transfer learning. The image-processing algorithm followed a pipeline of several traditional steps like edge detection, dilation and morphological operators. The algorithms were compared by measuring pixel-based segmentation accuracy and Jaccard index against a labelled ground truth. The results indicated a superior performance of the traditional algorithm (Accuracy = 99%, Jaccard = 93%) over the deep learning architectures: VGG16 (93%, 90%), ResNet18 (94%, 88%), Inception-ResNet-v2 (94%, 89%).

cancer biology↗

bioRxiv2018

Modelling the nuclear envelope of HeLa cells

This paper describes a framework for the automatic segmentation of the nuclear envelope of cancerous HeLa cells and the modelling of the volumetric shape against an ellipsoid. The framework is automatic and unsupervised and reported a Jaccard Similarity Index of 0.968 against a manual segmentation. The modelling of the surface provides a visual display of the variations, both smooth and rugged over the surface, and measurements can be extracted with the expectation that they can correlate with the biological characteristics of the cells.

cancer biology↗