Introduction

For bloodstream infections, initiation of an adequate antibiotic therapy is time critical. Whole-genome sequencing of bacterial DNA from blood cultures could provide both rapid species identification and resistance prediction, thereby reducing mortality from bloodstream infections.

We have therefore established a method for purifying bacterial DNA from blood culture bottles, which can also remove the potent enzyme inhibitor SPS from the samples. The purified DNA allows sequencing using a Nanopore sequencer, enabling both species identification and resistance prediction.

Methods

In a first step, the human DNA was depleted via gel centrifugation and selective lysis. SPS was removed by organic extraction with benzyl alcohol. The bacterial DNA was purified from the aqueous phase using a spin-column-based kit.

The purified DNA was sequenced using a shotgun sequencing workflow on a Nanopore sequencer. The generated reads were analysed in EPI2ME using the wf-Metagenomics workflow, including both species identification and a search for resistance genes.

Results

The developed protocol enabled the purification of DNA from the blood culture bottles, while at the same time efficiently removing SPS. Via the addition of the host DNA depletion steps bacterial DNA could enriched from an average of 42.3% to 79.8% of the total DNA.

In 94/96 of the blood cultures examined, all species that were detected by culture were correctly identified using sequencing. In two of these, obligate anaerobes were detected in addition to the cultured species. In the remaining two bottles, not all cultured species could be found via sequencing.

For Enterobacterales and Staphylococci, the positive and negative predictive value of the resistance prediction varies between 75% and 100%, depending on the antibiotic.

Conclusion

A protocol was successfully established that can both selectively purify bacterial DNA from blood culture bottles and remove the enzyme inhibitor SPS. By nanopore sequencing of the purified DNA, both reliable species identification and relatively accurate resistance prediction for the most relevant pathogens of bloodstream infections could be achieved.