Biology subjects

Magill, D.

Publications and source records attributed to Magill, D..

3 recordsLinked to original sources

bioRxiv2024

Strengthening Phage Resistance of Streptococcus thermophilus by Leveraging Complementary Defense Systems

CRISPR-Cas and restriction-modification systems represent the core defense arsenal in Streptococcus thermophilus to block lytic phages, but their effectiveness is compromised by phages encoding anti-CRISPR proteins (ACRs) and other counter-defense strategies. Here, we explored the resistome of 263 S. thermophilus strains to uncover other anti-phage systems. The defense landscape of S. thermophilus was enriched by 21 accessory defense systems, 13 of which had not been previously investigated in this species. Experimental validation of 17 systems with 14 phages showed varying anti-phage levels, uncovering intra-genus specificities among the five viral genera infecting S. thermophilus. Interestingly, the resistance levels were even higher when some defense systems (Dodola and PD-Lambda-1) were expressed from a low-copy plasmid or when integrated into the chromosome. We also observed a synergistic effect when combining Gabija with CRISPR-Cas, underscoring the potential of these additional defense systems for developing more robust industrial S. thermophilus strains, particularly against ACR-encoding phages.

microbiology↗

bioRxiv2024

Decoding Protein Dynamics: ProFlex as a Linguistic Bridge in Normal Mode Analysis

Artificial intelligence has revolutionized structural bioinformatics, with AlphaFold being arguably the most impactful development to date. The structural atlases generated by these methods present significant opportunities for unraveling biological mysteries, but also pose challenges in leveraging such massive datasets effectively. In this work, we explore the dynamic landscape of hundreds of thousands of AlphaFold-predicted structures using normal mode analysis. The resulting data is used to define an alphabet summarizing relative protein flexibility, termed ProFlex. We believe that refining and further applying ProFlex-like approaches offers novel opportunities for understanding protein function and enhancing other methods.

bioinformatics↗

bioRxiv2023

Application of a Machine Learning Approach Towards the Targeted Identification of Phage Depolymerases

Biofilm production plays a clinically significant role in the pathogenicity of many bacteria, limiting our ability to apply antimicrobial agents and contributing in particular to the pathogenesis of chronic infections. Bacteriophage depolymerases, leveraged by these viruses to circumvent biofilm mediated resistance, represent a potentially powerful weapon in the fight against antibiotic resistant bacteria. Such enzymes are able to degrade the extracellular matrix that is integral to the formation of all biofilms and as such would allow complementary therapies or disinfection procedures to be successfully applied. In this manuscript, we describe the development and application of a machine learning based approach towards the identification of phage depolymerases. We demonstrate that on the basis of a relatively limited number of experimentally proven enzymes and using an amino acid derived feature vector that the development of a powerful model with an accuracy on the order of 90% is possible, showing the value of such approaches in the discovery of novel therapeutic agents.

bioinformatics↗