Nucleic Acid Extraction and Enrichment

Recent advances in RNA sample preparation techniques for the detection of SARS-CoV-2 in saliva and gargle

Molecular detection of SARS-CoV-2 in gargle and saliva complements the standard analysis of nasopharyngeal swabs (NPS) specimens. Although gargle and saliva specimens can be readily obtained non-invasively, appropriate collection and processing of gargle and saliva specimens are critical to the accuracy and sensitivity of the overall analytical method. This review highlights challenges and recent advances in the treatment of gargle and saliva samples for subsequent analysis using reverse transcription polymerase chain reaction (RT-PCR) and isothermal amplification techniques. Important considerations include appropriate collection of gargle and saliva samples, on-site inactivation of viruses in the sample, preservation of viral RNA, extraction and concentration of viral RNA, removal of substances that inhibit nucleic acid amplification reactions, and the compatibility of sample treatment protocols with the subsequent nucleic acid amplification and detection techniques. The principles and approaches discussed in this review are applicable to molecular detection of other microbial pathogens.

Mini Review: Clinical Routine Microbiology in the Era of Automation and Digital Health

Clinical microbiology laboratories are the first line to combat and handle infectious diseases and antibiotic resistance, including newly emerging ones. Although most clinical laboratories still rely on conventional methods, a cascade of technological changes, driven by digital imaging and high-throughput sequencing, will revolutionize the management of clinical diagnostics for direct detection of bacteria and swift antimicrobial susceptibility testing. Importantly, such technological advancements occur in the golden age of machine learning where computers are no longer acting passively in data mining, but once trained, can also help physicians in making decisions for diagnostics and optimal treatment administration. The further potential of physically integrating new technologies in an automation chain, combined to machine-learning-based software for data analyses, is seducing and would indeed lead to a faster management in infectious diseases. However, if, from one side, technological advancement would achieve a better performance than conventional methods, on the other side, this evolution challenges clinicians in terms of data interpretation and impacts the entire hospital personnel organization and management. In this mini review, we discuss such technological achievements offering practical examples of their operability but also their limitations and potential issues that their implementation could rise in clinical microbiology laboratories.