Biology subjects

Garry, D. J.

Publications and source records attributed to Garry, D. J..

4 recordsLinked to original sources

bioRxiv2025

Treatment of STEC infection via CRISPR-Cas targeted cleavage of the Shiga toxin gene in animal models

Escherichia coli is a ubiquitous gut commensal but also an opportunistic pathogen responsible for severe intestinal and extra-intestinal infections. Shiga toxin-producing E. coli (STEC) pose a significant public health threat, particularly in children, where infections can lead to bloody diarrhea and progress to hemolytic uremic syndrome (HUS), a life-threatening condition with long-term complications. Antibiotics are contraindicated in STEC infections due to their potential to induce prophages carrying Shiga toxin (stx) genes, triggering toxin production. Here, we present a CRISPR-based antimicrobial strategy that selectively targets and eliminates O157 STEC clinical isolates while preventing toxin release. We designed a Cas12 nuclease to cleave >99% of all stx variants found in O157 strains, leading to bacterial killing and suppression of toxin production. To enable targeted delivery, we engineered a bacteriophage-derived capsid to specifically transfer a non-replicative DNA payload to E. coli O157, preventing its dissemination. In a mouse STEC colonization model, our therapeutic candidate, EB003, reduced bacterial burden by a factor of 3x103. In an infant rabbit disease model, EB003 mitigated clinical symptoms, abrogated stx-mediated toxicity, and accelerated epithelial repair at therapeutically relevant doses. These findings demonstrate the potential of CRISPR-based antimicrobials for treating STEC infections and support further clinical development of EB003 as a precision therapeutic against antibiotic-refractory bacterial pathogens.

synthetic biology↗

bioRxiv2023

Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences

The breakthrough high-throughput measurement of the cis-regulatory activity of millions of randomly generated promoters provides an unprecedented opportunity to systematically decode the cis-regulatory logic that determines the expression values. We developed an end-to-end transformer encoder architecture named Proformer to predict the expression values from DNA sequences. Proformer used a Macaron-like Transformer encoder architecture, where two half-step feed forward (FFN) layers were placed at the beginning and the end of each encoder block, and a separable 1D convolution layer was inserted after the first FFN layer and in front of the multi-head attention layer. The sliding k-mers from one-hot encoded sequences were mapped onto a continuous embedding, combined with the learned positional embedding and strand embedding (forward strand vs. reverse complemented strand) as the sequence input. Moreover, Proformer introduced multiple expression heads with mask filling to prevent the transformer models from collapsing when training on relatively small amount of data. We empirically determined that this design had significantly better performance than the conventional design such as using the global pooling layer as the output layer for the regression task. These analyses support the notion that Proformer provides a novel method of learning and enhances our understanding of how cis-regulatory sequences determine the expression values.

bioinformatics↗

bioRxiv2019

A novel algorithm for the collective integration of single cell RNA-seq during embryogenesis

Single cell RNA-seq (scRNA-seq) over specified time periods has been widely used to dissect the cell populations during mammalian embryogenesis. Integrating such scRNA-seq data from different developmental stages and from different laboratories is critical to comprehensively define and understand the molecular dynamics and systematically reconstruct the lineage trajectories. Here, we describe a novel algorithm to integrate heterogenous temporal scRNA-seq datasets and to preserve the global developmental trajectories. We applied this algorithm and approach to integrate 3,387 single cells from seven heterogenous temporal scRNA-seq datasets, and reconstructed the cell atlas of early mouse cardiovascular development from E6.5 to E9.5. Using this integrated atlas, we identified an Etv2 downstream target, Ebf1, as an important transcription factor for mouse endothelial development.

bioinformatics↗

bioRxiv2018

Hedgehog signaling controls progenitor differentiation timing during heart development

Heterochrony, defined as differences in the timing of developmental processes, impacts organ development, homeostasis, and regeneration. The molecular basis of heterochrony in mammalian tissues is poorly understood. We report that Hedgehog signaling activates a heterochronic pathway that controls differentiation timing in multiple lineages. A differentiation trajectory from second heart field cardiac progenitors to first heart field cardiomyocytes was identified by single-cell transcriptional profiling in mouse embryos. A survey of developmental signaling pathways revealed specific enrichment for Hedgehog signaling targets in cardiac progenitors. Removal of Hh signaling caused loss of progenitor and precocious cardiomyocyte differentiation gene expression in the second heart field in vivo. Introduction of active Hh signaling to mESC-derived progenitors, modelled by transient expression of the Hh-dependent transcription factor GLI1, delayed differentiation in cardiac and neural lineages in vitro. A shared GLI1-dependent network in both cardiac and neural progenitors was enriched with FOX family transcription factors. FOXF1, a GLI1 target, was sufficient to delay onset of the cardiomyocyte differentiation program in progenitors, by epigenetic repression of cardiomyocyte-specific enhancers. Removal of active Hh signaling or Foxf1 expression from second heart field progenitors caused precocious cardiac differentiation in vivo, establishing a mechanism for resultant Congenital Heart Disease. Together, these studies suggest that Hedgehog signaling directly activates a gene regulatory network that functions as a heterochronic switch to control differentiation timing across developmental lineages.

developmental biology↗