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Biology subjects

Donnelly, K.

Publications and source records attributed to Donnelly, K..

7 recordsLinked to original sources

Programmable Lipid Nanoparticle Targeting via Corona Engineering

Lipid nanoparticles (LNPs) are a versatile platform for in vivo delivery of biomolecules, yet systemically administered LNPs predominantly accumulate in the liver, limiting extrahepatic applications. This tropism arises from LNP adsorption of serum proteins, particularly apolipoprotein E (ApoE), which binds to LDL receptors (LDLR) on hepatocytes. Here, we overcome this tropism with two compatible strategies. First, we engineer dead ApoE mutants (dApoE) with five receptor-binding domain substitutions that selectively disrupt the ApoE-LDLR interaction but retain lipid binding. In cultured cells, pre-coating with these dApoE markedly inhibited LDLR-mediated uptake. Second, we pretreat cells with hyperactive PCSK9 (haPCSK9) to internalize surface LDLR, similarly reducing the LDLR-mediate uptake of LNPs. In vivo, both strategies substantially reduced liver LNP transduction without inducing redistribution to other major organs. To retarget LNP to new cell types we combined antibody conjugation with dApoE or haPCSK9, effectively engineering tropism to T cells, brain and lung tissues in vivo with substantially reduced hepatic background. In pilot studies, this strategy enabled specific delivery of reporter mRNAs to additional tissues, including megakaryocytes, hematopoietic progenitor cells, and cardiac tissue, and in aged T cells, to deliver miRNA cargos that produced a sustained reduction in DNA damage markers following a single systemic dose. dApoE coated CD5-targeted LNPs generated CAR+ T cells that retained cytotoxicity against CD19+ targets, while simultaneously reducing hepatocyte transduction by 90%. These findings establish a modular framework that integrates dApoE and haPCSK9-mediated detargeting with antibody-based retargeting, allowing for improvements in LNP specificity and broadening the therapeutic scope of LNPs.

bioengineering↗

Lymph-node transcriptomics define prognostic immune states in mucosal melanoma and reveal IBA1 as a practical biomarker for improved prognosis

Mucosal melanoma (MM) is a rare and aggressive cancer in humans with poor prognosis and limited response to immunotherapy or targeted therapy. Progress has been hindered by the lack of immune-competent, translational models. Dogs develop oral mucosal melanoma (OMM), a biologically equivalent disease, making them a valuable companion animal model that shares the human environment and immune context. In this study, we present the first transcriptomic analysis of regional lymph nodes in dogs with OMM, revealing that lymph nodes stratify into two distinct subgroups, independent of histopathological metastatic status at time of surgery, and which can be succinctly captured with a 35-gene signature. Notably, this stratification correlates with survival outcomes, providing unique early prognostic insights at the time of diagnosis. Furthermore, we explore the immune landscape of these subgroups and identify IBA1+ monocyte/macrophage infiltration as a key distinguishing biomarker. Using immunohistochemistry (IHC) and digital pathology, we demonstrate that higher IBA1 expression is associated with the transcriptomic subgroups associated with improved survival. These findings highlight IBA1 as a potential biomarker for risk stratification, offering a clinically relevant tool for refining prognosis and guiding treatment decisions in canine OMM. HighlightsO_LITranscriptomic profiling of canine OMM lymph nodes identifies two prognostic subgroups, independent of histopathological metastatic status. C_LIO_LILymph node transcriptomic stratification correlates with survival, providing prognostic insights beyond conventional histopathology at the time of diagnosis. C_LIO_LIIBA1+ monocyte/macrophage infiltration is associated with improved survival, and shows strong diagnostic potential via immunohistochemistry, supporting its use as a clinically feasible stratification tool. C_LI

cancer biology↗

Programmable RNA writing with trans-splicing

RNA editing offers the opportunity to introduce either stable or transient modifications to nucleic acid sequence without permanent off-target effects, but installation of arbitrary edits into the transcriptome is currently infeasible. Here, we describe Programmable RNA Editing & Cleavage for Insertion, Substitution, and Erasure (PRECISE), a versatile RNA editing method for writing RNA of arbitrary length and sequence into existing pre-mRNAs via 5' or 3' trans-splicing. In trans-splicing, an exogenous template is introduced to compete with the endogenous pre-mRNA, allowing for replacement of upstream or downstream exon sequence. Using Cas7-11 cleavage of pre-mRNAs to bias towards editing outcomes, we boost the efficiency of RNA trans-splicing by 10-100 fold, achieving editing rates between 5-50% and 85% on endogenous and reporter transcripts, respectively, while maintaining high-fidelity. We demonstrate PRECISE editing across 11 distinct endogenous transcripts of widely varying expression levels, showcasing more than 50 types of edits, including all 12 possible transversions and transitions, insertions ranging from 1 to 1,863 nucleotides, and deletions. We show high efficiency replacement of exon 4 of MECP2, addressing most mutations that drive the Rett Syndrome; editing of SHANK3 transcripts, a gene involved in Autism; and replacement of exon 1 of HTT, removing the hallmark repeat expansions of Huntington's disease. Whole transcriptome sequencing reveals the high precision of PRECISE editing and lack of off-target trans-splicing activity. Furthermore, we combine payload engineering and ribozymes for protein-free, high-efficiency trans-splicing, with demonstrated efficiency in editing HTT exon 1 via AAV delivery. We show that the high activity of PRECISE editing enables editing in non-dividing neurons and patient-derived Huntingtons disease fibroblasts. PRECISE editing markedly broadens the scope of genetic editing, is straightforward to deliver over existing gene editing tools like prime editing, lacks permanent off-targets, and can enable any type of genetic edit large or small, including edits not otherwise possible with existing RNA base editors, widening the spectrum of addressable diseases.

molecular biology↗

Genetic variation at 11q23.1 confers colorectal cancer risk by dysregulation of colonic tuft cell transcriptional activator POU2AF2

Common genetic variation at 11q23.1 is associated with colorectal cancer (CRC) risk, and exerts local (cis) expression quantitative trait locus (cis-eQTL) effects on POU2AF2, COLCA1 and POU2AF3 genes. However, complex linkage disequilibrium and correlated expression at the 11q23.1 locus has thus far hindered elucidation of the mechanisms by which genetic variants impart CRC risk. Here, we establish that rs3087967 is the likely causal eQTL at this locus, co-localising with expression of POU2AF2 and CRC risk. Furthermore, we show trans-eQTL effects on 21 distant target genes, which are highly enriched for Tuft cell markers. Analysis of available scRNAseq, ChIPseq and scATACseq data implicates POU2AF2 as the primary controller of the tuft cell specific trans-genes through POU2F3-correlated genetic regulation. Immunofluorescence demonstrates that the rs3087967 risk genotype (T) is associated with lower tuft cell abundance in human colonic epithelium. CRISPR-mediated deletion of the 11q23.1 risk locus in the mouse germline exacerbated the ApcMin/+ mouse phenotype upon abrogation of Pou2af2 expression specifically. Taken together, we implicate a key protective role of tuft cells in the large bowel and the importance of mis-regulation of POU2AF2 as the prime tuft cell transcriptional activator at this locus.

genetics↗

Exploring the association between Body Mass Index, Sex and Gene Expression in human colorectal epithelium

IntroductionColorectal cancer (CRC) is the second most common cause of cancer death globally. Genome-wide association studies have established that cancer risk mediated through common genetic variants can be linked to variation in gene expression. Since obesity and male sex impart substantially elevated CRC risk, we studied transcriptional profiles of normal colorectal mucosa using RNA sequencing to better understand the relationship of these risk factors with gene expression levels. MethodsNormal colorectal mucosa was sampled from 365 participants (208 males, 157 females) either during surgery (n=103) or through endoscopic biopsy (n=262) from cancer patients and patients with other unrelated conditions. In total, 238 samples were used for our discovery dataset and 380 samples were obtained for the validation of our findings. The transcription analysis was done using paired-end total RNA sequencing. Data processing and gene filtering followed the Genotype-Tissue Expression (GTEx) Project pipeline v8. Differential Expression Analysis (DEA) was performed on normalised counts to evaluate effects of sex and body mass index on the total gene expression, as well as possible confounding effects of cancer presence on the gene expression in normal colorectal tissue. ResultsFollowing filtering, there were 15,465 genes available for analysis. DEA identified two genes that were significantly associated with sex and five associated with body mass index. However, whilst these nominal signals are of interest, none of the genes associated with sex remained significant in a replication dataset. Due to the missing BMI information, replication of DEA by BMI was not possible. ConclusionWe found no systematic differences in gene expression in normal colorectal epithelium between males and females, nor did we find a strong association between gene expression and BMI. Although sample size may limit our analysis, the results suggest no or limited confounding effects of BMI and sex on gene expression in normal colorectal mucosa samples.

genomics↗

Transcriptional dynamics of colorectal cancer risk associated variation at 11q23.1 are correlated with tuft cell abundance and marker expression in silico

Colorectal cancer (CRC) is characterised by heritable risk that is not well understood. Heritable, genetic variation at 11q23.1 is associated with increased colorectal cancer (CRC) risk, demonstrating eQTL effects on 3 cis- and 23 trans-eQTL targets. We sought to determine the relationship between 11q23.1 cis- and trans-eQTL target expression and test for potential cell-specificity. scRNAseq from 32,361 healthy colonic epithelial cells was aggregated and subject to weighted gene co-expression network analysis (WGCNA). One module (blue) included 19 trans-eQTL targets and was correlated with C11orf53 expression only. Following unsupervised clustering of single cells, the expression of 19 trans-eQTL targets was greatest and most variable in cluster number 11, which transcriptionally resembled tuft cells. 14 trans-eQTL targets were found to demarcate this cluster, 11 of which were corroborated in a second dataset. Intra-cluster WGCNA and module preservation analysis then identified twelve 11q23.1 trans-eQTL targets to comprise a network that was specific to cluster 11. Finally, linear modelling and differential abundance testing showed 11q23.1 trans-eQTL target expression was predictive of cluster 11 abundance. Our findings suggest 11q23.1 trans-eQTL targets comprise a C11orf53-related network that is likely tuft cell-specific and reduced expression of these genes correlates with reduced tuft cell abundance in silico.

bioinformatics↗

Short-term diet intervention alters the small non-coding RNA (sncRNA) landscape of human sperm

Offspring health outcomes are often linked with epigenetic alterations triggered by maternal nutrition and intrauterine environment. Strong experimental data also link paternal preconception nutrition with pathophysiology in the offspring, but the mechanism(s) routing the effects of paternal exposures remain elusive. Animal experimental models have highlighted small non-coding RNAs (sncRNAs) as potential regulators of paternal effects, though less is known about the existence of similar mechanisms in human sperm. Here, we first characterised the baseline sncRNA landscape of human sperm, and then studied the effects of a 6-week diet intervention on their expression profile. Baseline profiling identified 5tRFs, miRNAs and piRNAs to be the most abundant sncRNA subtypes, primarily expressed from regulatory elements like UTRs, CpG-rich regions and promoters. Expression of a subset of these sncRNAs varied with age, BMI and sperm quality of the donor. Diet intervention enriched in vitamin D and omega-3 fatty acids showed a marked increase of these nutrients in circulation and altered the sperm sncRNA expression. These included 3 tRFs, 15 miRNAs and 112 piRNAs, with gene targets involved in fatty acid metabolism, vitamin D response (LXR/RXR activation, TGF-beta and Wnt signaling), and transposable elements. These findings provide evidence that human sperms are sensitive to alterations in exposures such as diet, and sncRNAs capture the epigenetic imprint of this change. Hence changes to paternal nutrition during preconception may improve sperm quality and offspring health outcomes. To benefit future research, we developed iDad_DB, an open access database of baseline and diet-altered sncRNA in human male germline.

bioinformatics↗