Biology subjects

Elmore, Z.

Publications and source records attributed to Elmore, Z..

3 recordsLinked to original sources

bioRxiv2023

Predicting Protein-encoding Gene Content in Escherichia coli Genomes

In this study, we built machine learning classifiers for predicting the presence or absence of the variable genes occurring in 10-90% of all publicly available high-quality Escherichia coli genomes. The BV-BRC genus-specific protein families were used to define orthologs across the set of genomes, and a single binary classifier was built for predicting the presence or absence of each family in each genome. Each model was built using the nucleotide k-mers from a set of 100 conserved genes as features. The resulting set of 3,259 XGBoost classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across MLSTs, and that the trend can be recapitulated through sampling with a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins", were easily predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions, including transposition- (F1 = 0.895 [0.882-0.907, 95% CI]), phage- (F1 = 0.872 [0.868-0.876, 95% CI]), and plasmid-related (F1 = 0.824 [0.814-0.834, 95% CI]) functions had slightly lower F1 scores, but were still accurate. Finally, we applied the models to a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources and observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. ImportanceHaving the ability to predict the protein-encoding gene content of a genome is important for a variety of bioinformatic tasks, including assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance (AMR) and other virulence genes. In this study, we built a series of binary classifiers for predicting the presence or absence of variable genes occurring in 10-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer.

bioinformatics↗

bioRxiv2021

The membrane associated accessory protein is an adeno-associated viral egress factor

Adeno-associated viruses (AAV) rely on helper viruses to transition from latency to lytic infection. Some recombinant AAV serotypes are secreted in a pre-lytic manner as extracellular vesicle (EV)-associated particles, although mechanisms underlying such are unknown. Here, we discover that the membrane-associated accessory protein (MAAP), expressed from a (+1) frameshifted open reading frame (ORF) in the AAV capsid (cap) gene, is a novel viral egress factor. MAAP contains a highly conserved, cationic amphipathic domain critical for AAV secretion. Wild type or recombinant AAV with a mutated MAAP start site (MAAP{Delta}) show markedly attenuated secretion and correspondingly, increased intracellular retention. Trans-complementation with recombinant MAAP restored extracellular secretion of multiple AAV/MAAP{Delta} serotypes. MAAP is sorted into recycling Rab11+ vesicles and strongly associates with EV markers upon fractionation. In addition to characterizing a novel viral egress factor, these studies highlight a prospective engineering platform to modulate secretion of AAV vectors or other EV-associated cargo.

molecular biology↗

bioRxiv2020

Rescuing AAV gene transfer from antibody neutralization with an IgG-degrading enzyme

Pre-existing humoral immunity to recombinant adeno-associated viral (AAV) vectors restricts the treatable patient population and efficacy of human gene therapies. Approaches to clear neutralizing antibodies (NAbs), such as plasmapheresis and immunosuppression are either ineffective or cause undesirable side effects. Here, we describe a clinically relevant strategy to rapidly and transiently degrade NAbs prior to AAV administration using an IgG degrading enzyme (IdeZ). We demonstrate that recombinant IdeZ efficiently cleaves IgG in dog, monkey and human antisera. Prophylactically administered IdeZ cleaves circulating, human IgG in mice and prevents AAV neutralization in vivo. In macaques, a single intravenous dose of IdeZ rescues AAV transduction by transiently reversing seropositivity. Importantly, IdeZ efficiently cleaves NAbs and rescues AAV transduction in mice passively immunized with individual human donor sera representing a diverse population. Our antibody clearance approach presents a new paradigm for expanding the prospective patient cohort and improving efficacy of AAV gene therapy.

immunology↗