Rapid whole-genome sequencing for detection and characterization of microorganisms directly from clinical samples

Abstract

Whole-genome sequencing (WGS) is becoming available as a routine tool for clinical microbiology. If applied directly on clinical samples, this could further reduce diagnostic times and thereby improve control and treatment. A major bottleneck is the availability of fast and reliable bioinformatic tools. This study was conducted to evaluate the applicability of WGS directly on clinical samples and to develop easy-to-use bioinformatic tools for the analysis of sequencing data. Thirty-five random urine samples from patients with suspected urinary tract infections were examined using conventional microbiology, WGS of isolated bacteria, and direct sequencing on pellets from the urine samples. A rapid method for analyzing the sequence data was developed. Bacteria were cultivated from 19 samples but in pure cultures from only 17 samples. WGS improved the identification of the cultivated bacteria, and almost complete agreement was observed between phenotypic and predicted antimicrobial susceptibilities. Complete agreement was observed between species identification, multilocus sequence typing, and phylogenetic relationships for Escherichia coli and Enterococcus faecalis isolates when the results of WGS of cultured isolates and urine samples were directly compared. Sequencing directly from the urine enabled bacterial identification in polymicrobial samples. Additional putative pathogenic strains were observed in some culture-negative samples. WGS directly on clinical samples can provide clinically relevant information and drastically reduce diagnostic times. This may prove very useful, but the need for data analysis is still a hurdle to clinical implementation. To overcome this problem, a publicly available bioinformatic tool was developed in this study.

FIG 1

Phylogenetic relationships among Escherichia coli (A) and Enterococcus faecalis (B) strains identified using whole-genome sequencing of purified single isolates (labeled with sample numbers followed by “_i”) and direct sequencing of urine samples (labeled with sample numbers followed by “_d”). SNP trees were constructed using an online application (21). Data were obtained from single isolates and directly from samples clustered together, and it was also possible to place data in a phylogenetic context when it was not possible to culture single isolates. Branch length in the snpTree output indicates number of substitutions per site.

FIG 2

Schematic representation of the workflow anticipated after adoption of whole-genome sequencing used either on cultured isolates or directly on the clinical samples, with an expected time scale.