Biology subjects

Coffey, A.

Publications and source records attributed to Coffey, A..

3 recordsLinked to original sources

bioRxiv2026

Eggerthella lenta evades bacteriophage through reversible megabase-scale inversions of capsular polysaccharide gene clusters

Bacteriophages are a promising tool for microbiome editing, yet their development has been constrained by limited insights into bacteriophage-host interactions within their shared mammalian body habitat. We isolated a lytic phage {Phi}KL11 that efficiently targets a disease-associated member of the human gut microbiota, Eggerthella lenta, during in vitro growth. However, {Phi}KL11 selects for a pre-existing and reversible bacteriophage-resistant sub-population in mice. Long-read sequencing revealed a massive genomic inversion event, representing >50% of the E. lenta genome, enriched in response to bacteriophage infection. Transcriptomics linked this inversion to the altered expression of three capsular polysaccharide synthesis (CPS) gene clusters and transmission electron microscopy confirmed differential capsule production. Finally, we show that {Phi}KL11 has a broad host range attributable to CPS and other strain-variable genes. These findings suggest a previously unrecognized strategy for phage evasion in the gut, involving megabase-scale genomic inversions and reversible capsule variation driving phage resistance.

microbiology↗

bioRxiv2025

Zinc Finger Repressors mediate widespread PRNP lowering in the nonhuman primate brain and profoundly extend survival in prion disease mice

Prion disease is a rapidly progressing and invariably fatal neurodegenerative disorder with no approved treatment. The disease is caused by the self-templated misfolding of the prion protein (PrP) into toxic species, ultimately leading to neurodegeneration and death. We evaluated a novel epigenetic regulation approach using Zinc Finger Repressors (ZFRs) to ablate PrP expression at the transcriptional level. When delivered using adeno-associated virus (AAV), ZFRs potently and specifically reduced prion mRNA expression by >95% in vitro and to near undetectable levels within single neurons in vivo. In wildtype mice, ZFRs stably lowered neuronal PrP expression throughout the central nervous system for at least 17 months. In mice inoculated with misfolded PrP, AAV-ZFRs given at either early or late disease stages profoundly extended lifespan, significantly reduced PrP in the brain, and improved an array of molecular, histological, biomarker, and behavioral readouts. Finally, we delivered a ZFR targeting the human prion gene (PRNP) to cynomolgus monkeys using a novel blood-brain-barrier penetrant AAV capsid. Extensive bulk and single-cell assessments revealed widespread ZFR expression and PRNP repression in all 35 brain regions assessed, providing the first demonstration of epigenetic regulation across the nonhuman primate neuraxis following a single intravenous (IV) dose. These results highlight the potential of a one-time IV administered ZFR treatment for prion disease and other neurological disorders.

neuroscience↗

bioRxiv2019

Non-Parametric Rank Statistics for Spectral Power and Coherence

Despite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/cross-spectra have shown promise for robust estimation of spectral power and coherence estimates. However, the statistical inference based on these non-parametric estimates remain to be formulated and tested. In this report a set of methods based on non-parametric rank statistics for 1-sample and 2-sample testing of spectral power and coherence is provided. The proposed methods were demonstrated and tested using simulated neural signals in different conditions. The results show that non-parametric methods provide robustness against artefactual components. Moreover, they provide new possibilities for robust 1-sample and 2-sample testing of the complex coherency function, including both the magnitude and phase, where existing methods fall short of functionality. The utility of the methods were further demonstrated by examples on experimental neural data. The proposed approach provides a new framework for non-parametric spectral analysis of digital signals. These methods are especially suited to neuroscience and neural engineering applications, given the attractive properties such as minimal assumption on distributions, statistical robustness, and the diverse testing scenarios afforded.

bioinformatics↗