Biology subjects

Ellis, R.

Publications and source records attributed to Ellis, R..

7 recordsLinked to original sources

bioRxiv2026

In vivo gene disruption and homology-directed repair in muscles and muscle stem cells using CRISPR/Cas9

Programmable endonucleases such as CRISPR/Cas9 provide powerful tools to edit mammalian genomes by engaging cellular mechanisms of DNA double-strand break (DSB) repair. CRISPR-catalysed homology-directed repair (CRISPR-HDR), though generally less efficient than other modes of DNA repair, holds particular promise to enable precise sequence replacement by targeted insertion of a homologous DNA template1,2. While recent studies have reported appreciable levels of HDR in cardiomyocytes in vivo3, skeletal muscle myofibres have historically been considered refractory to HDR-mediated genome editing4. Furthermore, how repair outcomes differ across tissues after systemic delivery of CRISPR/Cas9 editors, whether precise HDR editing can be achieved in regenerative tissue stem cells, and how developmental timing influences accessibility to CRISPR-induced repair remain unclear. Here, we use an adeno-associated virus (AAV)-delivered in vivo GFP-to-BFP colour-switching reporter system (AAV-GFP-to-BFP) to examine in vivo CRISPR-HDR with cellular- and tissue-level resolution. We find that postnatal cardiac muscle, skeletal muscle, and muscle stem cells undergo templated HDR at different rates across discrete developmental stages in mice. While HDR-edited muscle stem cells and myofibres were readily detectable after in vivo editing in juvenile mice, editing in neonatal mice yielded more efficient HDR in cardiac tissue. Based on these results, we adapted the CRISPR-HDR approach to rescue the therapeutically relevant Dmd mutation in mdx mice, demonstrating recoding to the wild-type protein sequence in both skeletal and cardiac muscles. These results provide a framework for advancing donor-templated DNA repair in living postnatal animals, and reveal unexpected cellular, developmental, and disease-related constraints on precise, therapeutic in vivo gene correction.

cell biology↗

bioRxiv2026

In vivo base editing via single myotrophic adeno-associated viruses in dystrophic mouse muscle and satellite cells

Duchenne muscular dystrophy (DMD) is the most common, lethal X-linked neuromuscular disorder of childhood and is caused by mutations in the Dmd gene that disrupt dystrophin expression. Although adeno-associated virus-mediated gene therapies hold tremendous promise for DMD treatment, their clinical applications have been limited by dose-dependent vector and genome-level toxicities. Here, we developed and tested a single-vector adenine base editing strategy as a potentially safer genome editing approach to recode the pathogenic nonsense mutation into a benign missense mutation in mdx4cvDMD mouse model. Delivered using a muscle-tropic adeno-associated virus (MyoAAV) at a clinically-feasible dose (4E13 VG/kg), this strategy enabled detectable molecular recoding of the mdx4cv mutation in mice ranging in age from 3 days to 6 months. Yet, the overall efficiency and therapeutic impact of in vivo base editing with this system was highest in mice treated at the juvenile stage, with animals administered MyoAAV vectors at 3 weeks of age showing robust recovery of dystrophin expression and significant improvement in muscle contractile properties only one month later. Notably, introduction of adenine base editors either earlier in development, in neonatal mice, or later, in adulthood, yielded substantially lower editing efficiencies, particularly in muscle satellite cells whose editing is essential to ensure durable rescue of dystrophin expression in growing and regenerating muscle. Taken together, these results demonstrate the therapeutic potential of single-vector adenine base editing for DMD and underscore the importance of recipient age and disease stage in achieving optimal treatment outcomes for this and other genetic muscle disorders.

cell biology↗

bioRxiv2023

A Deep Learning Approach for Mental Health Quality Prediction Using Functional Network Connectivity and Assessment Data

While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we can gain new insights into the biology and behavioral aspects of brain health. Resting-state fMRI (rs-fMRI) can be used to identify biomarkers of these conditions and study patterns of abnormal connectivity. In this work, we estimate mental health quality for individual participants using static functional network connectivity (sFNC) data from rs-fMRI. The deep learning model uses the sFNC data as input to predict four categories of mental health quality and visualize the neural patterns indicative of each group. We used guided gradient class activation maps (guided Grad-CAM) to identify the most discriminative sFNC patterns. The effectiveness of this model was validated using the UK Biobank dataset, in which we showed that our approach outperformed four alternative models by 4-18% accuracy. The proposed models performance evaluation yielded a classification accuracy of 76%, 78%, 88%, and 98% for the excellent, good, fair, and poor mental health categories, with poor mental health accuracy being the highest. The findings show distinct sFNC patterns across each group. The patterns associated with excellent mental health consist of the cerebellar-subcortical regions, whereas the most prominent areas in the poor mental health category are in the sensorimotor and visual domains. Thus the combination of rs-fMRI and deep learning opens a promising path for developing a comprehensive framework to evaluate and measure mental health. Moreover, this approach had the potential to guide the development of personalized interventions and enable the monitoring of treatment response. Overall this highlights the crucial role of advanced imaging modalities and deep learning algorithms in advancing our understanding and management of mental health.

neuroscience↗

bioRxiv2022

Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

Mismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/{beta}Catenin, mitogen-activated protein kinase and TGF{beta} receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.

cancer biology↗

bioRxiv2021

Two subsets of human marginal zone B cells resolved by global analysis of lymphoid tissues and blood

B cells generate antibodies that are essential for immune protection. Major events driving B cell responses occur in lymphoid tissues, which guide antigen acquisition and support cellular interactions, yet complexities of B cell subsets in human lymphoid tissues are poorly understood. Here we perform undirected, global profiling of B cells in matched human lymphoid tissues from deceased transplant organ donors and tracked dissemination of B cell clones. In addition to identifying unanticipated features of tissue-based B cell differentiation, we resolve two clonally independent subsets of marginal zone B cells that differ in cell surface and transcriptomic profiles, tendency to disseminate, distribution bias within splenic marginal zone microenvironment and immunoglobulin repertoire diversity and hypermutation frequency. Each subset is represented in spleen, gut-associated lymphoid tissue, mesenteric lymph node, and also blood. Thus, we provide clarity and diffuse controversy surrounding human MZB - the elephant in the room of human B cell biology.

immunology↗

bioRxiv2020

Human marginal zone B cell development from early T2 progenitors

B cells emerge from the bone marrow as transitional (TS) B cells that differentiate through T1, T2 and T3 stages to become naive B cells. We have identified a bifurcation of human B cell maturation from the T1 stage forming IgMhi and IgMlo developmental trajectories. IgMhi T2 cells have higher expression of 4{beta}7 integrin and lower expression of IL4 receptor (IL4R) compared to the IgMlo branch and are selectively recruited into gut-associated lymphoid tissue. IgMhi T2 cells also share transcriptomic features with marginal zone B cells (MZB). Lineage progression from T1 cells to MZB via an IgMhi trajectory is identified by pseudotime analysis of scRNA-sequencing data. Reduced frequency of IgMhi gut homing T2 cells is observed in severe SLE and is associated with reduction of MZB and their putative IgMhi precursors. The collapse of the gut-associated MZB maturational axis in severe SLE affirms its existence and importance for maintaining health.

cell biology↗

bioRxiv2020

Regional transmission and reassortment of 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses in Bulgarian poultry 2017/18

Between 2017 and 2018, several farms across Bulgaria reported outbreaks of H5 HPAI viruses. In this study we use genomic and traditional epidemiological analyses to trace the origin and subsequent spread of these outbreaks within Bulgaria. Both methods indicate two separate incursions, one restricted to the North-Eastern region of Dobrich, and another largely restricted to Central and Eastern Bulgaria including places such as Plovdiv, Sliven and Stara Zagora, as well as one virus from the Western region of Vidin. Both outbreaks likely originate from different European 2.3.4.4b virus ancestors circulating in 2017. The viruses were likely introduced by wild birds or poultry trade links in 2017 and have continued to circulate, but due to lack of contemporaneous sampling and sequences from wild bird viruses in Bulgaria, the precise route and timing of introduction cannot be determined. Analysis of whole genomes indicates complete lack of reassortment in all segments but the MP, which presents as multiple smaller clusters associated with different European 2.3.4.4b viruses. Ancestral reconstruction of host states of the HA gene of viruses involved in the outbreaks suggests that transmission is driven by domestic ducks into galliform poultry. Thus, according to present evidence we suggest that surveillance of domestic ducks as epidemiologically relevant species for subclinical infection. Monitoring spread due to movement between farms within regions and links to poultry production systems in European countries can help to predict and prevent future outbreaks.

microbiology↗