Biology subjects

Gaboriau, D. C. A.

Publications and source records attributed to Gaboriau, D. C. A..

6 recordsLinked to original sources

bioRxiv2022

Lung extracellular matrix modulates KRT5+ basal cell activity in pulmonary fibrosis

Aberrant expansion of KRT5+ basal cells in the distal lung accompanies progressive alveolar epithelial cell loss and tissue remodelling during fibrogenesis in idiopathic pulmonary fibrosis (IPF). The mechanisms determining activity of KRT5+ cells in IPF have not been delineated. Here, we reveal a potential mechanism by which KRT5+ cells migrate within the fibrotic lung, navigating regional differences in collagen topography. In vitro, KRT5+ cell migratory characteristics and expression of remodelling genes are modulated by extracellular matrix (ECM) composition and organisation. Mass spectrometry-based proteomics revealed compositional differences in ECM components secreted by primary human lung fibroblasts (HLF) from IPF patients compared to controls. Over-expression of ECM glycoprotein, Secreted Protein Acidic and Cysteine Rich (SPARC) in the IPF HLF matrix restricts KRT5+ cell migration in vitro. Together, our findings demonstrate how changes to the ECM in IPF directly influence KRT5+ cell behaviour and function contributing to remodelling events in the fibrotic niche.

cell biology↗

bioRxiv2021

Content-aware frame interpolation (CAFI): Deep Learning-based temporal super-resolution for fast bioimaging

The development of high-resolution microscopes has made it possible to investigate cellular processes in 4D (3D over time). However, observing fast cellular dynamics remains challenging as a consequence of photobleaching and phototoxicity. These issues become increasingly problematic with the depth of the volume acquired and the speed of the biological events of interest. Here, we report the implementation of two content-aware frame interpolation (CAFI) deep learning networks, Zooming SlowMo (ZS) and Depth-Aware Video Frame Interpolation (DAIN), based on combinations of recurrent neural networks, that are highly suited for accurately predicting images in between image pairs, therefore improving the temporal resolution of image series as a post-acquisition analysis step. We show that CAFI predictions are capable of understanding the motion context of biological structures to perform better than standard interpolation methods. We benchmark CAFIs performance on six different datasets, obtained from three different microscopy modalities (point-scanning confocal, spinning-disk confocal and confocal brightfield microscopy). We demonstrate its capabilities for single-particle tracking methods applied to the study of lysosome trafficking. CAFI therefore allows for reduced light exposure and phototoxicity on the sample and extends the possibility of long-term live-cell imaging. Both DAIN and ZS as well as the training and testing data are made available for use by the wider community via the ZeroCostDL4Mic platform.

cell biology↗

bioRxiv2021

4D live-cell imaging of microgametogenesis in the human malaria parasite Plasmodium falciparum

Formation of gametes in the malaria parasite occurs in the midgut of the mosquito and is critical to onward parasite transmission. Transformation of the male gametocyte into microgametes, called microgametogenesis, is an explosive cellular event and one of the fastest eukaryotic DNA replication events known. The transformation of one microgametocyte into eight flagellated microgametes requires reorganisation of the parasite cytoskeleton, replication of the 22.9 Mb genome, axoneme formation and host erythrocyte egress, all of which occur simultaneously in <20 minutes. Whilst high-resolution imaging has been a powerful tool for defining stages of microgametogenesis, it has largely been limited to fixed parasite samples, given the speed of the process and parasite photosensitivity. Here, we have developed a live-cell fluorescence imaging workflow that captures the explosive dynamics of microgametogenesis in full. Using the most virulent human malaria parasite, Plasmodium falciparum, our live-cell approach combines three-dimensional imaging through time (4D imaging) and covers early microgametocyte development through to microgamete release. Combining live-cell stains for DNA, tubulin and the host erythrocyte membrane, 4D imaging enables definition of the positioning of newly replicated and segregated DNA. It also shows the microtubular cytoskeleton, location of newly formed basal bodies and elongation of axonemes, as well as behaviour of the erythrocyte membrane, including its specific perforation prior to microgamete egress. 4D imaging was additionally undertaken in the presence of known transmission-blocking inhibitors and the untested proteasomal inhibitor bortezomib. Here, for the first time we find that bortezomib inhibition results in a clear block of DNA replication, full axoneme nucleation and elongation. These data not only define a framework for understanding microgametogenesis in general but also suggest that the process is critically dependent on proteasomal activity, helping to identify potentially novel targets for transmission-blocking antimalarial drug development.

microbiology↗

bioRxiv2020

Calm on the surface, dynamic on the inside. Molecular homeostasis in response to regulatory and metabolic perturbation of Anabaena sp. 7120 nitrogen metabolism

Nitrogen is a key macro-nutrient required for the metabolism and growth of biological systems. Although multiple nitrogen sources can serve this purpose, they are all converted into ammonium/ammonia as a first step of assimilation. It is thus reasonable to expect that molecular parts involved in the transport of ammonium/ammonia across biological membranes (i.e. catalysed by AMT transporters) connect with the regulation of both nitrogen and central carbon metabolism. In order to test this hypothesis, we applied both (1) genetic (i.e. {Delta}amt mutation) and (2) environmental treatments to a target biological system, the cyanobacterium Anabaena sp. PCC 7120. Cyanobacteria have a key role in the global nitrogen cycle and thus represent a useful model system. The aim was to both (1) perturb sensing and low-affinity uptake of ammonium/ammonia and (2) induce multiple inner N states, followed by targeted quantification of key proteins, metabolites and enzyme activities, with experiments intentionally designed over a longer time-scale than the available studies in literature. We observed that the absence of AMT transporters triggered a substantial response at a whole-system level, affecting enzyme activities and the quantity of both proteins and metabolites, spanning both N and C metabolism. Moreover, the absence of AMT transporters left a molecular fingerprint indicating N-deficiency even under N replete conditions (i.e. greater GS activity, lower 2-OG content and faster nitrogenase activation upon N deprivation). Contrasting with all of the above dynamic adaptations was the striking near-complete lack of any externally measurable phenotype (i.e. growth, photosynthesis, pigments, metabolites). We thus conclude that this species evolved a highly robust and adaptable molecular network to maintain homeostasis, resulting in substantial internal but minimal external perturbations. The analytical data highlights several internal adaptations, including increased N assimilation (i.e. greater GS activity) and nitrogenase activity (i.e. faster activation upon N deprivation) together with altered amino acids metabolism, as indicated by changes in Gln, Glu and 2-OG, indicating an altered C/N balance. The analyses provides evidence for an active role of AMT transporters in the regulatory/signalling network of N metabolism in this biological system, and the existence of a novel fourth IF7A-independent regulatory mechanism controlling GS activity.

systems biology↗

bioRxiv2019

A machine learning approach to define antimalarial drug action from heterogeneous cell-based screens

Drug resistance threatens the effective prevention and treatment of an ever-increasing range of human infections. This highlights an urgent need for new and improved drugs with novel mechanisms of action to avoid cross-resistance. Current cell-based drug screens are, however, restricted to binary live/dead readouts with no provision for mechanism of action prediction. Machine learning methods are increasingly being used to improve information extraction from imaging data. Such methods, however, work poorly with heterogeneous cellular phenotypes and generally require time-consuming human-led training. We have developed a semi-supervised machine learning approach, combining human- and machine-labelled training data from mixed human malaria parasite cultures. Designed for high-throughput and high-resolution screening, our semi-supervised approach is robust to natural parasite morphological heterogeneity and correctly orders parasite developmental stages. Our approach also reproducibly detects and clusters drug-induced morphological outliers by mechanism of action, demonstrating the potential power of machine learning for accelerating cell-based drug discovery. One Sentence SummaryA machine learning approach to classifying normal and aberrant cell morphology from plate-based imaging of mixed malaria parasite cultures, facilitating clustering of drugs by mechanism of action.

microbiology↗

bioRxiv2019

Chloroplasts navigate towards the pathogen interface to counteract infection by the Irish potato famine pathogen

Upon immune activation, chloroplasts switch off photosynthesis, produce anti-microbial compounds, and associate with the nucleus through tubular extensions called stromules. Although it is well-established that chloroplasts alter their position in response to light, little is known about the dynamics of chloroplasts movement in response to pathogen attack. Here, we report that chloroplasts accumulate at the pathogen interface during infection by the Irish potato famine pathogen Phytophthora infestans, associating with the specialized membrane that engulfs the pathogen haustorium. Chemical inhibition of actin polymerization reduces the accumulation of chloroplasts at the pathogen haustoria, suggesting this process is partially dependent on the actin cytoskeleton. However, chloroplast accumulation at haustoria does not necessarily rely on movement of the nucleus to this interface and is not affected by light conditions. Stromules are typically induced during infection, embracing haustoria and interconnecting chloroplasts, to form dynamic organelle clusters. We found that infection-triggered stromule formation relies on BRASSINOSTEROID INSENSITIVE 1-ASSOCIATED KINASE 1 (BAK1) mediated surface immune signaling, whereas chloroplast repositioning towards haustoria does not. Consistent with the defense-related induction of stromules, effector mediated suppression of BAK1 mediated immune signaling reduced stromule formation during infection. On the other hand, immune recognition of the same effector stimulated stromules, presumably via a different pathway. These findings implicate chloroplasts in a polarized response upon pathogen attack and point to more complex functions of these organelles in plant-pathogen interactions.

plant biology↗