Microscopy pipeline to automatically identify SEPT7-S. flexneri interactions. Credit: (2024). DOI: 10.7554/eLife.97495.1

Researchers are using AI-powered microscopy to study the bacterium Shigella, offering fresh hope in the battle against antimicrobial resistance.

Serge Mostowy and Ana López Jiménez discuss using AI-powered microscopy to study Shigella, a estimated to have killed 148,000 people in 2019, at an unprecedented scale.

Their , published in the journal eLife, demonstrates how this cutting-edge technology is accelerating the potential discovery of new drug targets and treatments for antimicrobial resistant infections.

Credit: London School of Hygiene & Tropical Medicine

More information: Ana T. López-Jiménez et al, High-content high-resolution microscopy and deep learning assisted analysis reveals host and bacterial heterogeneity during Shigella infection, eLife (2024).

Journal information: eLife

Provided by London School of Hygiene & Tropical Medicine