Transforming clinical microbiology with bacterial genome sequencing

Abstract

Whole-genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for addressing many microbiological questions. Here, we review the current status of clinical microbiology and how it has already begun to be transformed by using next-generation sequencing. We focus on three essential tasks: identifying the species of an isolate, testing its properties, such as resistance to antibiotics and virulence, and monitoring the emergence and spread of bacterial pathogens. We predict that the application of next-generation sequencing will soon be sufficiently fast, accurate and cheap to be used in routine clinical microbiology practice, where it could replace many complex current techniques with a single, more efficient workflow.

MLST revisited: the gene-by-gene approach to bacterial genomics

“…WGS studies of bacteria are currently in a golden age, with many resources and much interest being dedicated to the area as a whole and especially to WGS applications for clinical problems [36][37][38]63 . However, when this initial excitement has passed, it will be …”

“…This, in turn, depends on the particular question being addressed, as some questions require more discrimination among specimens than others. To use the clinical setting as an example: very high resolution is necessary for the detection of outbreaks and the investigation of within-patient variation 43 ; lower resolution is required to determine the membership of a particular clonal complex or lineage 61 ; and even lower resolution is sufficient for determining the species causing an infection 37,62,63 . The gene-bygene approach is inherently hierarchical and scalable, as fewer genes can be used for lowerresolution typing, whereas higher levels of resolution can be attained by increasing the number of genes included in the analysis.…”

Making the genomic leap in HCT: application of second-generation sequencing to clinical advances in hematopoietic cell transplantation

“…47 Finally, early detection and therapy of microbial infections are crucial determinants of HCT outcomes as 430% of HCT recipients develop an episode of bacteremia in the first weeks following transplant and 15% of all mortalities following unrelated allogeneic HCT are infection related. 5 Rapid and accurate detection, identification and drug-susceptibility phenotyping methods for isolated clinical pathogen(s) using WGS and CAS of non-human DNA or RNA 48,49 using genomic or ribosomal multi-locus sequence typing (MLST/rMLST) already exist. In one approach, for example, a Abbreviations: ALL, acute lymphoblastic leukemia; EFS, event-free survival; GC, glucocorticoids; GI, gastrointestinal; HCT, hematopoietic stem cell transplant; MRD, minimal residual disease; TRM, transplant-related mortality.…”

“…These TGS platforms do not require amplification or culturing, and affords single DNA molecule sequencing of samples directly acquired from body fluids or sample sites. 49,52 In addition, SGS can be coupled with PGx to improve antimicrobial selection and dosing by detecting high-resistance strains that require strain-specific therapy and reducing the frequency of severe ADRs to anti-microbial agents. SGS has already transformed clinical practices in the care of highly virulent infections such as HIV.…”

Microbial bioinformatics 2020

“…Microbial genomics and metagenomics are hurtling full‐steam ahead into the clinical arena and into efforts to map the global landscape of microbial biodiversity (Pallen et al ., 2010; Didelot et al ., 2012; Robinson et al ., 2013; Kyrpides et al ., 2014; Brown et al ., 2015; Luheshi et al ., 2015; Spang et al ., 2015). In both settings, it is clear that microbial taxonomy, with its polyphasic approach that requires laboratory culture and phenotypic investigation, is already broken and simply will not cope with an era in which most microorganisms are going to be identified and characterized through the analysis of macromolecular sequences (Chun and Rainey, 2014; Ramasamy et al ., 2014; Thompson et al ., 2015; Baltrus, 2016).…”