16S rDNA droplet digital PCR for monitoring bacterial DNAemia in bloodstream infections

Autoři: Ingrid Ziegler aff001;  Sofia Lindström aff003;  Magdalena Källgren aff004;  Kristoffer Strålin aff002;  Paula Mölling aff002
Působiště autorů: Department of Infectious Diseases, Örebro University Hospital, Örebro, Sweden aff001;  School of Health and Medical Sciences, Örebro University, Örebro, Sweden aff002;  Department of Laboratory Medicine, Västerås Hospital, Västerås, Sweden aff003;  Department of Laboratory Medicine, Karlskoga Hospital, Karlskoga, Sweden aff004;  Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden aff005;  Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden aff006;  Department of Laboratory Medicine, Örebro University Hospital, Örebro, Sweden aff007
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224656


Repeated quantitative measurement of bacterial DNA on whole blood has been shown to be a promising method for monitoring bloodstream infection (BSI) with selected bacterial species. To enable broad use of this method, we developed a quantitative droplet digital PCR (ddPCR) method for 16S rDNA. It was validated with species-specific ddPCRs for Staphylococcus aureus (nuc), Streptococcus pneumoniae (lytA), and Escherichia coli (uidA) on spiked whole blood samples and on repeated whole blood samples (days 0, 1–2, 3–4, 6–8, and 13–15) from 83 patients with BSI with these pathogens. In these patients, 16S rDNA and species-specific DNA were detected in 60% and 61%, respectively, at least at one time-point. The highest positivity rates were seen in S. aureus BSI, where 92% of the patients were 16S rDNA-positive and 85% nuc-positive. Quantitative 16S rDNA and species-specific DNA showed strong correlations in spiked samples (r = 0.98; p < 0.0001) and clinical samples (r = 0.84; p < 0.0001). Positivity for 16S rDNA was rapidly cleared in patients with S. pneumoniae and E. coli BSI, but more slowly and sometimes persisted, in those with S. aureus BSI. The initial 16S rDNA load was higher in BSI patients with sepsis (Sepsis-3 definition) than without sepsis (median 2.38 vs. 0 lg10 copies/mL; p = 0.031) and in non-survivors than in survivors (median 2.83 vs. 0 lg10 copies/mL; p = 0.006). 16S rDNA ddPCR appears to be a promising method for bacterial DNA monitoring during BSI. The clinical value of such monitoring should be further studied.

Klíčová slova:

Bacterial pathogens – Blood – Bloodstream infections – Escherichia coli – Pneumococcus – Polymerase chain reaction – Sepsis – Staphylococcus aureus


1. Fleischmann C, Scherag A, Adhikari NK, Hartog CS, Tsaganos T, Schlattmann P, et al. Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations. Am J Respir Crit Care Med. 2016;193(3):259–72. doi: 10.1164/rccm.201504-0781OC 26414292

2. Lamy B, Dargere S, Arendrup MC, Parienti JJ, Tattevin P. How to Optimize the Use of Blood Cultures for the Diagnosis of Bloodstream Infections? A State-of-the Art. Front Microbiol. 2016;7:697. doi: 10.3389/fmicb.2016.00697 eCollection 2016. 27242721

3. Bloos F, Sachse S, Kortgen A, Pletz MW, Lehmann M, Straube E, et al. Evaluation of a polymerase chain reaction assay for pathogen detection in septic patients under routine condition: an observational study. PloS one. 2012;7(9):e46003. Epub 2012/10/03. doi: 10.1371/journal.pone.0046003 23029360; PubMed Central PMCID: PMC3459981.

4. Lehmann LE, Hunfeld KP, Emrich T, Haberhausen G, Wissing H, Hoeft A, et al. A multiplex real-time PCR assay for rapid detection and differentiation of 25 bacterial and fungal pathogens from whole blood samples. Med Microbiol Immunol. 2008;197(3):313–24. Epub 2007/11/17. doi: 10.1007/s00430-007-0063-0 18008085.

5. Wellinghausen N, Kochem AJ, Disque C, Muhl H, Gebert S, Winter J, et al. Diagnosis of bacteremia in whole-blood samples by use of a commercial universal 16S rRNA gene-based PCR and sequence analysis. Journal of clinical microbiology. 2009;47(9):2759–65. Epub 2009/07/03. doi: 10.1128/JCM.00567-09 19571030; PubMed Central PMCID: PMC2738079.

6. Jordana-Lluch E, Gimenez M, Quesada MD, Rivaya B, Marco C, Dominguez MJ, et al. Evaluation of the Broad-Range PCR/ESI-MS Technology in Blood Specimens for the Molecular Diagnosis of Bloodstream Infections. PLoS One. 2015;10(10):e0140865. doi: 10.1371/journal.pone.0140865 26474394

7. Ziegler I, Josefson P, Olcen P, Molling P, Stralin K. Quantitative data from the SeptiFast real-time PCR is associated with disease severity in patients with sepsis. BMC infectious diseases. 2014;14:155. Epub 2014/03/25. doi: 10.1186/1471-2334-14-155 24656148; PubMed Central PMCID: PMC3994454.

8. Hackett SJ, Guiver M, Marsh J, Sills JA, Thomson AP, Kaczmarski EB, et al. Meningococcal bacterial DNA load at presentation correlates with disease severity. Arch Dis Child. 2002;86(1):44–6. Epub 2002/01/25. doi: 10.1136/adc.86.1.44 11806883; PubMed Central PMCID: PMC1719043.

9. Peters RP, de Boer RF, Schuurman T, Gierveld S, Kooistra-Smid M, van Agtmael MA, et al. Streptococcus pneumoniae DNA load in blood as a marker of infection in patients with community-acquired pneumonia. Journal of clinical microbiology. 2009;47(10):3308–12. Epub 2009/08/14. doi: 10.1128/JCM.01071-09 19675218; PubMed Central PMCID: PMC2756912.

10. Rello J, Lisboa T, Lujan M, Gallego M, Kee C, Kay I, et al. Severity of pneumococcal pneumonia associated with genomic bacterial load. Chest. 2009;136(3):832–40. Epub 2009/05/13. doi: 10.1378/chest.09-0258 19433527.

11. Øvstebø R, Brandtzaeg P, Brusletto B, Haug KBF, Lande K, Høiby EA, et al. Use of Robotized DNA Isolation and Real-Time PCR To Quantify and Identify Close Correlation between Levels of Neisseria meningitidis DNA and Lipopolysaccharides in Plasma and Cerebrospinal Fluid from Patients with Systemic Meningococcal Disease. J Clin Microbiol. 2004;42(7):2980–7. doi: 10.1128/JCM.42.7.2980-2987.2004 15243048

12. Ho YC, Chang SC, Lin SR, Wang WK. High levels of mecA DNA detected by a quantitative real-time PCR assay are associated with mortality in patients with methicillin-resistant Staphylococcus aureus bacteremia. Journal of clinical microbiology. 2009;47(5):1443–51. Epub 2009/03/13. doi: 10.1128/JCM.01197-08 19279177; PubMed Central PMCID: PMC2681853.

13. Chuang YC, Chang SC, Wang WK. Using the rate of bacterial clearance determined by real-time polymerase chain reaction as a timely surrogate marker to evaluate the appropriateness of antibiotic usage in critical patients with Acinetobacter baumannii bacteremia. Crit Care Med. 2012;40(8):2273–80. Epub 2012/07/20. doi: 10.1097/CCM.0b013e3182515190 22809902.

14. Chuang YC, Chang SC, Wang WK. High and increasing Oxa-51 DNA load predict mortality in Acinetobacter baumannii bacteremia: implication for pathogenesis and evaluation of therapy. PLoS One. 2010;5(11):e14133. doi: 10.1371/journal.pone.0014133 21152436

15. Van Zanten AR. Real-time polymerase chain reaction to evaluate antibiotic appropriateness: should we spread the news to multiply it? Crit Care Med. 2012;40(8):2492–3. doi: 10.1097/CCM.0b013e318258e7f3 22809917

16. Vetrovsky T, Baldrian P. The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses. PloS one. 2013;8(2):e57923. doi: 10.1371/journal.pone.0057923 Epub 2013 Feb 27. 23460914

17. Kembel SW, Wu M, Eisen JA, Green JL. Incorporating 16S gene copy number information improves estimates of microbial diversity and abundance. PLoS Comput Biol. 2012;8(10):e1002743. doi: 10.1371/journal.pcbi.1002743 Epub 2012 Oct 25. 23133348

18. Laupland KB, Church DL. Population-based epidemiology and microbiology of community-onset bloodstream infections. Clin Microbiol Rev. 2014;27(4):647–64. doi: 10.1128/CMR.00002-14 25278570

19. Sogaard M, Norgaard M, Dethlefsen C, Schonheyder HC. Temporal changes in the incidence and 30-day mortality associated with bacteremia in hospitalized patients from 1992 through 2006: a population-based cohort study. Clin Infect Dis. 2011;52(1):61–9. doi: 10.1093/cid/ciq069 21148521

20. Morley AA. Digital PCR: A brief history. Biomol Detect Quantif. 2014;1(1):1–2. doi: 10.1016/j.bdq.2014.06.001 eCollection Sep. 27920991

21. Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem. 2011;83(22):8604–10. doi: 10.1021/ac202028g Epub 2011 Oct 28. 22035192

22. Hindson CM, Chevillet JR, Briggs HA, Gallichotte EN, Ruf IK, Hindson BJ, et al. Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods. 2013;10(10):1003–5. doi: 10.1038/nmeth.2633 Epub 013 Sep 1. 23995387

23. Cajander S, Rasmussen G, Tina E, Magnuson A, Soderquist B, Kallman J, et al. Dynamics of monocytic HLA-DR expression differs between bacterial etiologies during the course of bloodstream infection. PLoS One. 2018;13(2):e0192883. doi: 10.1371/journal.pone.0192883 29466395

24. Droplet Digital PCR Applications Guide: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_6407.pdf. Bio-Rad Laboratories Inc.

25. Kramski M, Gaeguta AJ, Lichtfuss GF, Rajasuriar R, Crowe SM, French MA, et al. Novel sensitive real-time PCR for quantification of bacterial 16S rRNA genes in plasma of HIV-infected patients as a marker for microbial translocation. J Clin Microbiol. 2011;49(10):3691–3. doi: 10.1128/JCM.01018-11 Epub 2011 Aug 3. 21813723

26. Berglund C, Molling P, Sjoberg L, Soderquist B. Predominance of staphylococcal cassette chromosome mec (SCCmec) type IV among methicillin-resistant Staphylococcus aureus (MRSA) in a Swedish county and presence of unknown SCCmec types with Panton-Valentine leukocidin genes. Clinical microbiology and infection: the official publication of the European Society of Clinical Microbiology and Infectious Diseases. 2005;11(6):447–56. Epub 2005/05/11. doi: 10.1111/j.1469-0691.2005.01150.x 15882194.

27. Bogestam K, Vondracek M, Karlsson M, Fang H, Giske CG. Introduction of a hydrolysis probe PCR assay for high-throughput screening of methicillin-resistant Staphylococcus aureus with the ability to include or exclude detection of Staphylococcus argenteus. PLoS One. 2018;13(2):e0192782. doi: 10.1371/journal.pone.0192782 29425233

28. Sheppard CL, Harrison TG, Morris R, Hogan A, George RC. Autolysin-targeted LightCycler assay including internal process control for detection of Streptococcus pneumoniae DNA in clinical samples. J Med Microbiol. 2004;53(Pt 3):189–95. doi: 10.1099/jmm.0.05460-0 14970243

29. Yoshitomi KJ, Jinneman KC, Weagant SD. Optimization of a 3'-minor groove binder-DNA probe targeting the uidA gene for rapid identification of Escherichia coli O157:H7 using real-time PCR. Molecular and cellular probes. 2003;17(6):275–80. Epub 2003/11/07. 14602477.

30. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. Epub 1987/01/01. doi: 10.1016/0021-9681(87)90171-8 3558716.

31. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801–10. doi: 10.1001/jama.2016.0287 26903338

32. Ziegler I, Cajander S, Rasmussen G, Ennefors T, Molling P, Stralin K. High nuc DNA load in whole blood is associated with sepsis, mortality and immune dysregulation in Staphylococcus aureus bacteraemia. Infect Dis (Lond). 2019;51(3):216–26. doi: 10.1080/23744235.2018.1562205 Epub 2019 Jan 24. 30676833

33. Strain MC, Lada SM, Luong T, Rought SE, Gianella S, Terry VH, et al. Highly precise measurement of HIV DNA by droplet digital PCR. PloS one. 2013;8(4):e55943. doi: 10.1371/journal.pone.0055943 Epub 2013 Apr 3. 23573183

34. Sze MA, Abbasi M, Hogg JC, Sin DD. A comparison between droplet digital and quantitative PCR in the analysis of bacterial 16S load in lung tissue samples from control and COPD GOLD 2. PLoS One. 2014;9(10):e110351. doi: 10.1371/journal.pone.0110351 25329701

35. Lewin SR, Vesanen M, Kostrikis L, Hurley A, Duran M, Zhang L, et al. Use of real-time PCR and molecular beacons to detect virus replication in human immunodeficiency virus type 1-infected individuals on prolonged effective antiretroviral therapy. J Virol. 1999;73(7):6099–103. 10364365

36. Opota O, Jaton K, Greub G. Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood. Clinical microbiology and infection: the official publication of the European Society of Clinical Microbiology and Infectious Diseases. 2015;21(4):323–31. Epub 2015/02/18. doi: 10.1016/j.cmi.2015.02.005 25686695.

37. Khatib R, Riederer K, Saeed S, Johnson LB, Fakih MG, Sharma M, et al. Time to positivity in Staphylococcus aureus bacteremia: possible correlation with the source and outcome of infection. Clin Infect Dis. 2005;41(5):594–8. Epub 2005/08/05. doi: 10.1086/432472 16080079.

38. Thwaites GE, Edgeworth JD, Gkrania-Klotsas E, Kirby A, Tilley R, Torok ME, et al. Clinical management of Staphylococcus aureus bacteraemia. Lancet Infect Dis. 2011;11(3):208–22. doi: 10.1016/S1473-3099(10)70285-1 21371655

39. Werner AS, Cobbs CG, Kaye D, Hook EW. Studies on the bacteremia of bacterial endocarditis. JAMA. 1967;202(3):199–203. 4860941

40. Wain J, Diep TS, Ho VA, Walsh AM, Nguyen TT, Parry CM, et al. Quantitation of bacteria in blood of typhoid fever patients and relationship between counts and clinical features, transmissibility, and antibiotic resistance. J Clin Microbiol. 1998;36(6):1683–7. 9620400

41. Bacconi A, Richmond GS, Baroldi MA, Laffler TG, Blyn LB, Carolan HE, et al. Improved sensitivity for molecular detection of bacterial and Candida infections in blood. J Clin Microbiol. 2014;52(9):3164–74. doi: 10.1128/JCM.00801-14 Epub 2014 Jun 20. 24951806

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