Rbiotics

Conventional antibiotics generally work against a broad spectrum of bacterial pathogens. This promotes the development of antibiotic resistance and damages our protective microbiota, which can have unwanted effects on our health. New antibiotics are therefore needed that can directly target individual pathogens, leaving beneficial bacteria unharmed. In a multidisciplinary approach, our team is researching antibiotics based on RNA-like molecules, so-called peptide nucleic acids (PNA), which can be used to specifically attack individual bacterial strains. These RNA antibiotics can be modified through simple chemical means to achieve effectiveness against emerging pathogens. In order to automate this process, we created a digital platform using high-throughput processes and machine learning, that enables researchers to specifically design drug molecules against a variety of dangerous pathogens.

Within the Rbiotics project, the consortium succeeded in advancing a completely new class of highly specific anti-infective agents based on antisense oligomers (ASOs)—synthetic, RNA-like molecules that bind precisely to essential bacterial mRNAs and block their translation. To achieve this, the team established a standardized experimental pipeline capable of systematically assessing ASO efficacy, cellular uptake, and potential off-target effects across diverse bacterial species. Using this platform, they identified essential genes in key gut commensals and pathogens—including E. coli, Salmonella enterica, and Clostridioides difficile—whose inhibition becomes bactericidal within minutes. A comprehensive comparison of seven distinct ASO chemotypes revealed that only peptide nucleic acids (PNA) and phosphorodiamidate morpholino oligomers (PMO) are efficiently taken up by bacteria and capable of inhibiting growth, establishing clear design rules for future RNA-based antimicrobials. These discoveries were complemented by the development of the openly accessible MASON web server, a global resource enabling researchers to rationally design ASO sequences—bridging academic innovation and clinical application.

In parallel, Rbiotics created a tightly integrated workflow combining molecular microbiology, RNA sequencing, and machine learning. Transcriptome responses to ASO treatment were used to dissect mechanisms of action and to computationally predict new or improved ASO candidates, forming a rapid iterative loop that substantially accelerated development. This approach was extended to members of the human gut microbiota, demonstrating the feasibility of patient-specific ASO therapies that selectively target pathogens while preserving the protective microbiome. The project achieved considerable international visibility through publications, new software tools, collaborative networks, and the establishment of the ASOBIOTICS conference, which brought together researchers from around the world working on antibacterial ASO technology. By uniting molecular precision, computational design, and open data principles, Rbiotics has laid the foundation for a paradigm shift in anti-infective therapy—toward programmable, RNA-based interventions that can counteract resistant pathogens and, in the future, complement or even replace traditional antibiotics.