Combining deep learning and droplet microfluidics for rapid and label-free antimicrobial susceptibility testing of colistin.

Efficient tools for rapid antibiotic susceptibility testing (AST) are crucial for appropriate use of antibiotics, especially colistin, which is now often considered a last resort therapy with extremely drug resistant Gram-negative bacteria. Here, we developed a rapid, easy and miniaturized colistin susceptibility assay based on microfluidics, which allows for culture and high-throughput analysis of bacterial samples. Specifically, a simple microfluidic platform that can easily be operated was designed to encapsulate bacteria in nanoliter droplets and perform a fast and automated bacterial growth detection in 2 h, using standardized samples. Direct bright-field imaging of compartmentalized samples proved to be a faster and more accurate detection method as compared to fluorescence-based analysis. A deep learning powered approach was implemented for the sensitive detection of the growth of several strains in droplets. The DropDeepL AST method (Droplet and Deep learning-based method for AST) developed here allowed the determination of the colistin susceptibility profiles of 21 fast-growing Enterobacterales (E. coli and K. pneumoniae), including clinical isolates with different resistance mechanisms, showing 100 % categorical agreement with the reference broth microdilution (BMD) method performed simultaneously. Direct AST of bacteria in urine samples on chip also provided accurate results in 2 h, without the need of complex sample preparation procedures. This method can easily be implemented in clinical microbiology laboratories, and has the potential to be adapted to a variety of antibiotics, especially for last-line antibiotics to optimize treatment of patients infected with multi-drug resistant strains.

Latest trends in bioimaging and building a proactive network of early-career young scientists around bioimaging in Europe.

Biological research is in constant need of new methodological developments to assess organization and functions at various scales ranging from whole organisms to interactions between proteins. One of the main ways to evidence and quantify biological phenomena is imaging. Fluorescence microscopy and label-free microscopy are in particular highly active fields of research due to their compatibility with living samples as well as their versatility. The Imabio Young Scientists Network (YSN) is a group of young scientists (PhD students, postdocs and engineers) who are excited about bioimaging and aim to create a proactive network of researchers with the same interest. YSN is endorsed by the bioimaging network GDR Imabio in France, where the initiative was started in 2019. Since then, we aim to organize the Imabio YSN conference every year to expand the network to other European countries, establish new collaborations and ignite new scientific ideas. From 6-8 July 2022, the YSN including researchers from the domains of life sciences, chemistry, physics and computational sciences met at the Third Imabio YSN Conference 2022 in Lyon to discuss the latest bioimaging technologies and biological discoveries. In this Meeting Review, we describe the essence of the scientific debates, highlight remarkable talks, and focus on the Career Development session, which is unique to the YSN conference, providing a career perspective to young scientists and help to answer all their questions at this career stage. This conference was a truly interdisciplinary reunion of scientists who are eager to push the frontiers of bioimaging in order to understand the complexity of biological systems.