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Biology subjects

Pignotti, S.

Publications and source records attributed to Pignotti, S..

2 recordsLinked to original sources

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↗

Efficient and Robust Search of Microbial Genomes via Phylogenetic Compression

Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections has made it effectively impossible to search these data using tools such as BLAST and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. We show that, when applied to modern diverse collections approaching millions of genomes, lossless phylogenetic compression improves the compression ratios of assemblies, de Bruijn graphs, and k-mer indexes by one to two orders of magnitude. Additionally, we develop a pipeline for a BLAST-like search over these phylogeny-compressed reference data, and demonstrate it can align genes, plasmids, or entire sequencing experiments against all sequenced bacteria until 2019 on ordinary desktop computers within a few hours. Phylogenetic compression has broad applications in computational biology and may provide a fundamental design principle for future genomics infrastructure.

bioinformatics↗