Towards an automated fast microbiology and next-generation sequencing pathogen discovery approach in microbiology laboratory: the new frontiers of diagnostics and surveillance

Over the past two decades, laboratory workflows in disciplines such as clinical chemistry and hematology have undergone extensive automation, whereas microbiology diagnostics has largely relied on manual processes. During the COVID-19 pandemic, microbiology laboratories played a central role in diagnostic testing, patient management, and infection control, highlighting the need for standardized, reproducible methods and reduced turnaround time (TAT). This context accelerated the adoption of total laboratory automation and innovative technologies to support rapid and accurate microbiological diagnosis. Rapid identification of pathogens and antimicrobial susceptibility testing are crucial for targeted therapy, particularly in bloodstream infections, which account for approximately 20% of global deaths and are frequently caused by antimicrobial-resistant bacteria. The FRIDA project evaluated Radian® (Copan Italia), an automated rapid antimicrobial susceptibility testing system based on disc diffusion. Compared with standard workflows, Radian® reduced TAT by approximately 13 hours in 181 positive blood cultures, enabling earlier transition from empirical to targeted antibiotic therapy in line with Rapid Microbiology principles. Automation was also applied to molecular surveillance, as demonstrated by the AURISafe project focused on Candida auris, an emerging pathogen prioritized by the Word Health Organization. Following the first Italian outbreak in 2019 and Italy’s classification as a high-risk country, AURISafe implemented automated yeast culture, DNA extraction, and PCR setup, allowing the rapid processing of 1,616 surveillance swabs and timely identification of colonized patients to support infection control measures. Finally, the HighGENES project addressed the growing relevance of non-tuberculous mycobacteria, whose detection has increased to 30–50% of total Mycobacterium isolates. An NGS-based Pathogen Discovery approach enabled the identification of 20 previously undefined isolates as Mycobacterium saskatchewanense and highlighted the rpoB gene as a useful discriminatory marker. Overall, these projects aimed to standardize innovative diagnostic workflows to improve patient outcomes, enhance surveillance, and strengthen healthcare responses to emerging infectious threats.