Biology subjects

Johnston, R. L.

Publications and source records attributed to Johnston, R. L..

5 recordsLinked to original sources

bioRxiv2026

Computational drug repurposing identifies N-acetylglucosamine as a potential therapeutic compound for CLN3 Batten disease

Batten disease, also known as neuronal ceroid lipofuscinoses, is one of the most common causes of childhood dementia. It is characterized by the accumulation of lipofuscin in lysosomes, leading to loss of brain cell function, onset of dementia-like symptoms, vision loss and seizures and has extremely limited treatment options. Here, we performed computational drug repurposing analysis to identify existing compounds that may target Batten disease risk genes. A total of 81 candidate compounds were identified, 6 of which were selected based on clinical tractability for downstream testing in Batten disease (CLN3) iPSC-derived models. After confirming disease phenotype and drug candidate safety, CLN3 brain cell cultures treated with and without drug candidates underwent bulk RNA-seq to identify drug responses. One of the candidate drugs N-acetylglucosamine (GlcNAc) significantly upregulated Batten disease risk gene CLN5 expression and several other lysosomal markers within CLN3 brain cells, and modulated several pathways implicated in lysosomal storage disorders. Importantly, GlcNAc significantly reduced lipofuscin burden in both CLN3 iPSC-derived neurons and astrocytes, supporting its investigation as an additional therapy for Batten disease.

neuroscience↗

bioRxiv2024

Sequential transcriptional programs underpin activation of quiescent hippocampal stem cells.

Postnatal neural stem cells are primarily quiescent, which is a cellular state that exists as a continuum from deep to shallow quiescence. The molecular changes that occur along this continuum are beginning to be understood but the transcription factor network governing these changes has not been defined. We show that these transitions are regulated by sequential transcription factor programs. Single-cell transcriptomic analyses of mice with loss- or gain-of-function of the essential activation factor Ascl1, reveal that Ascl1 promotes the activation of hippocampal neural stem cells by driving these cells out of deep quiescence, despite its low protein expression. Subsequently, during the transition from deep to shallow quiescence, Ascl1 induces the expression of Mycn, which drives progression through shallow states of quiescence towards an active state. Together, these results define the required sequence of transcription factors during hippocampal neural stem cell activation.

neuroscience↗

bioRxiv2023

Increased tau expression in the APOE4 blood-brain barrier model is associated with reduced anti-tau therapeutic antibody delivery in vitro.

Tau protein is a critical driver of neurodegeneration and an important drug target in Alzheimers disease (AD). Tau-specific immunotherapy has emerged as a promising treatment strategy for AD, however the therapeutic efficacy of anti-tau antibodies may be limited by their insufficient delivery across the blood-brain barrier (BBB). The apolipoprotein E4 allele (APOE4) is the strongest genetic risk factor for sporadic AD and is known to influence tau-mediated neurodegeneration. Interestingly, both tau and APOE4 have been implicated in the cerebrovascular pathology observed in AD. Yet, the crosstalk between APOE4 and tau at the level of the BBB and its consequences for anti-tau immunotherapeutics delivery, remain poorly understood. Here, we utilised APOE3- and APOE4-carrying human iPSC-derived induced brain endothelial-like cells (iBECs) as a sporadic AD BBB model, determined the levels of endogenous tau in iBECs, and explored the transport of two novel monoclonal anti-tau antibodies, RNF5 and RN2N, across the in vitro barrier. Our results demonstrate that MAPT gene transcription, tau protein levels and tau phosphorylation are increased in iBECs in an APOE4-related manner and are associated with reduced iBEC monolayer integrity and increased permeability to biologically inert fluorescent tracers. Additionally, elevated levels of intracellular tau in APOE4 cells were accompanied by the reduced passive permeability of therapeutic anti-tau antibodies through the APOE4 iBEC monolayer, which could be improved by the application of focused ultrasound and microbubble drug-delivery technology. Together, our study illustrates a new role for APOE4 and tau in human iBECs with potential implications for BBB dysfunction and anti-tau therapeutic antibody delivery.

cell biology↗

bioRxiv2022

Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology

Trust and transparency are critical for deploying deep learning (DL) models into the clinic. DL application poses generalisation obstacles since training/development datasets often have different data distributions to clinical/production datasets that can lead to incorrect predictions with underestimated uncertainty. To investigate this pitfall, we benchmarked one pointwise and three approximate Bayesian DL models used to predict cancer of unknown primary with three independent RNA-seq datasets covering 10,968 samples across 57 primary cancer types. Our results highlight simple and scalable Bayesian DL significantly improves the generalisation of uncertainty estimation (e.g., p-value = 0.0013 for calibration). Moreover, we demonstrate Bayesian DL substantially improves accuracy under data distributional shifts when utilising uncertainty thresholding by designing a prototypical metric that evaluates the expected (accuracy) loss when deploying models from development to production, which we call the Area between Development and Production curve (ADP). In summary, Bayesian DL is a hopeful avenue of research for generalising uncertainty, which improves performance, transparency, and therefore safety of DL models for deployment in real-world.

bioinformatics↗

bioRxiv2022

A sporadic Alzheimer's blood-brain barrier model for developing ultrasound-mediated delivery of Aducanumab and anti-Tau antibodies.

RationaleThe blood-brain barrier (BBB) is a major impediment to therapeutic intracranial drug delivery for the treatment of neurodegenerative diseases, including Alzheimers disease (AD). Focused ultrasound applied together with microbubbles (FUS+MB) is a novel technique to transiently open the BBB and increase drug delivery. Evidence suggests that FUS+MB is safe, however the effects of FUS+MB on human BBB cells, especially in the context of AD, remain sparsely investigated. MethodsHere we generated BBB cells (induced brain endothelial cells (iBECs) and astrocytes (iAstrocytes)) from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). We then developed a human sporadic AD BBB cell platform to investigate the effects of FUS+MB on BBB cells and screen for the delivery of two potentially therapeutic AD antibodies. ResultsWe utilized this robust and reproducible human BBB model to demonstrate increased delivery of therapeutic AD antibodies across the BBB following FUS+MB treatment, including an analogue of Aducanumab (AduhelmTM; anti-amyloid-{beta}) and a novel anti-Tau antibody RNF5. Our results also demonstrate the safety of FUS+MB indicated by minimal changes in the cell transcriptome as well as little or no changes in cell viability and inflammatory responses within the first 24 h post FUS+MB. Finally, we report a more physiologically relevant hydrogel-based 2.5D BBB model as a key development for FUS+MB-mediated drug delivery screening, with potentially higher translational utility. ConclusionOur results demonstrate an important translatable patient BBB cell model for identifying FUS+MB-deliverable drugs and screening for cell- and patient-specific effects of FUS+MB, accelerating the use of FUS+MB as a therapeutic modality in AD. One Sentence SummaryFocused ultrasound increases the in vitro delivery of therapeutic antibodies Aducanumab and anti-Tau in a sporadic Alzheimers disease patient-derived blood-brain barrier cell model.

neuroscience↗