A Comparison of Blood Pathogen Detection Among Droplet Digital PCR, Metagenomic Next-Generation Sequencing, and Blood Culture in Critically Ill Patients With Suspected Bloodstream Infections.

Bangchuan Hu,Yue Tao,Yang Zheng,Ziqiang Shao,Xi Li,Run Zhang,Xuejing Yang,Jingquan Liu,Renhua Sun

doi:10.3389/fmicb.2021.641202

Abstract

Metagenomic next-generation sequencing (mNGS) and droplet digital PCR (ddPCR) have recently demonstrated a great potential for pathogen detection. However, few studies have been undertaken to compare these two nucleic acid detection methods for identifying pathogens in patients with bloodstream infections (BSIs). This prospective study was thus conducted to compare these two methods for diagnostic applications in a clinical setting for critically ill patients with suspected BSIs. Upon suspicion of BSIs, whole blood samples were simultaneously drawn for ddPCR covering 20 common isolated pathogens and four antimicrobial resistance (AMR) genes, mNGS, and blood culture. Then, a head-to-head comparison was performed between ddPCR and mNGS. A total of 60 episodes of suspected BSIs were investigated in 45 critically ill patients, and ddPCR was positive in 50 (83.3%), mNGS in 41 (68.3%, not including viruses), and blood culture in 10 (16.7%) episodes. Of the 10 positive blood cultures, nine were concordantly identified by both mNGS and ddPCR methods. The head-to-head comparison showed that ddPCR was more rapid (~4 h vs. ~2 days) and sensitive (88 vs. 53 detectable pathogens) than mNGS within the detection range of ddPCR, while mNGS detected a broader range of pathogens (126 vs. 88 detectable pathogens, including viruses) than ddPCR. In addition, a total of 17 AMR genes, including 14 blaKPC and 3 mecA genes, were exclusively identified by ddPCR. Based on their respective limitations and strengths, the ddPCR method is more useful for rapid detection of common isolated pathogens as well as AMR genes in critically ill patients with suspected BSI, whereas mNGS testing is more appropriate for the diagnosis of BSI where classic microbiological or molecular diagnostic approaches fail to identify causative pathogens.

Highlights

Blood culture coupled with antimicrobial susceptibility testing (AST) remains the gold standard for bloodstream infections (BSIs) diagnosis, as it is easy to perform and displays a good analytical performance
The present study compared the methods dedicated to early BSI detection, including droplet digital PCR (ddPCR), metagenomic next-generation sequencing (mNGS), and blood culture, in critically ill patients with suspected BSI
Our findings were in line with the results of several previous studies that investigated the difference in the ability to detect pathogens from whole blood using nucleic acidbased and culture-based methods (Long et al, 2016; Korber et al, 2017; Grumaz et al, 2019)

Summary

Introduction

Blood culture coupled with antimicrobial susceptibility testing (AST) remains the gold standard for BSI diagnosis, as it is easy to perform and displays a good analytical performance. Blood culture is limited by a long turnaround time, relatively low sensitivity (because of a low microbial inoculum or growth inhibition by prior use of antibiotics; Lamy et al, 2016; Pilecky et al, 2019), and low specificity (Liesenfeld et al, 2014; Opota et al, 2015). Metagenomic next-generation sequencing (mNGS) and droplet digital PCR (ddPCR) have shown great potential in pathogen detection for patients with suspected BSIs. mNGS is culture-free and can analyze the entire microbial community in a clinical sample (Miao et al, 2018; Blauwkamp et al, 2019). MNGS can help identify causative microorganisms for patients with suspected BSIs with high sensitivity and specificity (Gyarmati et al, 2016; Brenner et al, 2018; Goggin et al, 2019). MNGS can help identify causative microorganisms for patients with suspected BSIs with high sensitivity and specificity (Gyarmati et al, 2016; Brenner et al, 2018; Goggin et al, 2019). ddPCR, as an emerging versatile tool with high sensitivity and excellent accuracy and precision, has been increasingly used in multiple clinical scenarios including BSIs (Li et al, 2018; Abram et al, 2020; Wouters et al, 2020)

Methods

Results

Conclusion