Introduction
Bloodstream infection (BSI) represents a major cause of death worldwide,
contributing to increased healthcare costs, length of hospital stay, and
in-hospital morbidity (McNamara, et al., 2018). Timely and accurate
pathogen identification is critical to guide antimicrobial treatment for
patients in the early stage of BSI. Blood culture remains the gold
standard for identifying the pathogens in BSI (Blevins and Bronze,
2010). However, it is limited by the low sensitivity and the long
turnaround time (Riedel and Carroll, 2016, Tabak, et al., 2018). In
septic patients within the first 6 h of documented hypotension, every
1-h delay in appropriate antibiotic therapy leads to an average increase
of mortality rate by 7.6% (Kumar, et al., 2006). For hospitalized
patients with bacterial infections, inappropriate initial antimicrobial
treatment almost doubles the risk of 30-day mortality (Fraser, et al.,
2006). Thus, it is necessary to develop a rapid and accurate method to
identify the causal pathogens in BSI.
Recently, the culture-independent, real-time PCR-based or
microarray-based methods, such as SeptiFast (Roche, Switzerland),
Magicplex (Seegene, Korea), and TaqMan array card assay (Academy of
Military Medical Science, China), have shown promising performance in
rapidly identifying the pathogens and
initiating early targeted antibiotic therapy in BSI. However, the low
sensitivities ranging from 29% to 79.4% may limit the clinical
application of these methods (Warhurst, et al., 2015, Buehler, et al.,
2016, Riedel and Carroll, 2016, Zhang, et al., 2018, Zboromyrska, et
al., 2019). Droplet digital polymerase chain reaction (ddPCR) is a novel
molecular method to detect and quantify nucleic acids. In ddPCR, the
template is partitioned into thousands of nanoliter-sized droplets and
amplified. After amplification, the numbers of positive and negative
reactions are counted, and the copy number of the template is calculated
using Poisson statistics (Huggett, et al., 2015, Kuypers and Jerome,
2017). As an emerging versatile tool with high sensitivity, accuracy,
and precision, ddPCR has been increasingly applied in multiple clinical
scenarios, including oncology (Gevensleben, et al., 2013, Taly, et al.,
2013, Jennings, et al., 2014, Postel, et al., 2018, Galimberti, et al.,
2019), non-invasive prenatal testing (Barrett, et al., 2012, Tan, et
al., 2019), and infectious diseases (Kelley, et al., 2013, Pholwat, et
al., 2013, Sedlak, et al., 2014, Sedlak, et al., 2014, Whale, et al.,
2016, Wouters, et al., 2019).
Acinetobacter baumannii and Klebsiella pneumoniae are two
major Gram-negative bacteria involved in BSI, with high capabilities to
develop antibiotic resistance. BSIs due to multidrug-resistant A.
baumannii and K. pneumoniae significantly contribute to the
mortality in the intensive care unit (ICU), with a mortality rate over
50% (Balkhair, et al., 2019, Brink, 2019). In this study, we developed
and validated a ddPCR-based method to detect A.baumannii andK. pneumonia in blood samples of patients with suspected BSI. Our
results provide ddPCR as a promising method to accurately and rapidly
diagnose BSIs caused by A. baumannii and K. pneumoniae.