Skip to main content
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About JCM
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
Journal of Clinical Microbiology
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About JCM
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
Bacteriology

Investigation of Preanalytical Variables Impacting Pathogen Cell-Free DNA in Blood and Urine

Kanagavel Murugesan, Catherine A. Hogan, Zaida Palmer, Byron Reeve, Grant Theron, Alfred Andama, Akos Somoskovi, Amy Steadman, Damian Madan, Jason Andrews, Julio Croda, Malaya K. Sahoo, Adithya Cattamanchi, Benjamin A. Pinsky, Niaz Banaei
Karen C. Carroll, Editor
Kanagavel Murugesan
aDepartment of Pathology, Stanford University School of Medicine, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kanagavel Murugesan
Catherine A. Hogan
aDepartment of Pathology, Stanford University School of Medicine, Stanford, California, USA
bClinical Microbiology Laboratory, Stanford Health Care, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zaida Palmer
cNRF/DST Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Byron Reeve
cNRF/DST Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Grant Theron
cNRF/DST Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alfred Andama
dCollege of Health Sciences, Makerere University, Kampala, Uganda
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Akos Somoskovi
eGlobal Health Technologies, Global Good Fund, Intellectual Ventures Laboratory, Bellevue, Washington, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amy Steadman
fIntellectual Ventures Laboratory, Bellevue, Washington, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Damian Madan
fIntellectual Ventures Laboratory, Bellevue, Washington, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jason Andrews
gDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Julio Croda
hFaculty of Health Sciences, Federal University of Grande Dourados, Dourados, Brazil
iOswaldo Cruz Foundation, Campo Grande, Brazil
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Julio Croda
Malaya K. Sahoo
aDepartment of Pathology, Stanford University School of Medicine, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Adithya Cattamanchi
jDepartment of Medicine, University of California, San Francisco, San Francisco, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Benjamin A. Pinsky
aDepartment of Pathology, Stanford University School of Medicine, Stanford, California, USA
bClinical Microbiology Laboratory, Stanford Health Care, Stanford, California, USA
gDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Benjamin A. Pinsky
Niaz Banaei
aDepartment of Pathology, Stanford University School of Medicine, Stanford, California, USA
bClinical Microbiology Laboratory, Stanford Health Care, Stanford, California, USA
gDivision of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karen C. Carroll
Johns Hopkins University School of Medicine
Roles: Editor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/JCM.00782-19
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

ABSTRACT

Pathogen cell-free DNA (pcfDNA) in blood and urine is an attractive biomarker; however, the impact of preanalytical factors is not well understood. Blood and urine samples from healthy donors spiked with cfDNA from Mycobacterium tuberculosis, Salmonella enterica, Aspergillus fumigatus, and Epstein-Barr virus (EBV) and samples from tuberculosis patients were used to evaluate the impact of blood collection tube, urine preservative, processing delay, processing method, freezing and thawing, and sample volume on pcfDNA. The PCR cycle threshold (CT) was used to measure amplifiable cfDNA. In spiked samples, the median CT values for M. tuberculosis, S. enterica, and EBV cfDNA were significantly lower in blood collected in K2EDTA tubes than those in Streck and PAXgene blood collection tubes, and they were was significantly lower in urine preserved with EDTA (EDTA-urine) than in urine preserved with Streck reagent (Streck-urine). Blood and urine samples from TB patients preserved with K2EDTA and Tris-EDTA, respectively, showed significantly lower median M. tuberculosis CT values than with the Streck blood collection tube and Streck urine preservative. Processing delay increased the median pathogen CT values for Streck and PAXgene but not K2EDTA blood samples and for urine preserved with Streck reagent but not EDTA. Double-spin compared with single-spin plasma separation increased the median pathogen CT regardless of blood collection tube. No differences were observed between whole urine and supernatant and between fresh and thawed plasma and urine after 24 weeks at –80°C. Larger plasma and urine volumes in contrived and patient samples showed a significantly lower median M. tuberculosis CT. These findings suggest that large-volume single-spin K2EDTA-plasma and EDTA-whole urine with up to a 24-h processing delay may optimize pcfDNA detection.

INTRODUCTION

Analysis of cell-free DNA (cfDNA) in the acellular fraction of plasma and urine, also known as “liquid biopsy,” has emerged in the past decade as a promising new modality for noninvasive testing for conditions such as prenatal genetic abnormalities (1) and cancer driver mutations (2, 3). In the field of infectious diseases, the detection of Epstein-Barr virus (EBV) cfDNA in plasma has been in clinical use for several decades as a screening and prognostic test for EBV-associated nasopharyngeal carcinoma (4, 5). EBV cfDNA in plasma has been shown to be superior to cellular EBV as a marker of EBV-related diseases, particularly, posttransplant lymphoproliferative disorder (6). Pathogen cfDNA has also been applied to diagnose invasive infectious diseases. A number of studies have reported on the performance of targeted cfDNA assays for the diagnosis of tuberculosis (TB) (7–12), invasive fungal infections (13–16), and invasive parasitic infections (17). More recently, metagenomic next-generation sequencing of plasma cfDNA was evaluated in patients with bloodstream infection, cardiac surgery-associated Mycobacterium chimaera infection, and invasive fungal infection (18–22). Despite the growing interest, it is unclear how the biology and immunopathogenesis of each pathogen impact the availability of its cfDNA as a diagnostic biomarker. Furthermore, although noninvasive diagnosis of infectious diseases using cfDNA is an attractive premise, particularly in resource-poor settings, further research is needed to optimize preanalytical and analytical variables to define best practices and maximize assay performance (23).

In the field of oncology and obstetrics, much progress has been made in investigating and optimizing preanalytical factors that negatively impact the analysis of tumor and fetal cfDNA, respectively. Rapid processing of blood within 6 h of collection and using the standard K2EDTA blood collection tube were shown to be essential for preventing the dilution of tumor cfDNA with genomic DNA (gDNA) due to postcollection lysis of white blood cells (WBCs) (24–26). Fetal cfDNA was shown to remain stable up to 24 h at room temperature after blood collection in a K2EDTA blood collection tube (27). The storage of blood in K2EDTA tubes at 4°C was insufficient to prevent the dilution of tumor cfDNA (25). To mitigate tumor and fetal cfDNA dilution, cfDNA blood collection tubes, such as Cell-Free DNA BCT (Streck, Omaha, NE), the PAXgene blood circulating cell-free DNA (ccfDNA) tube (Qiagen, Germantown, MD), and a CellSave preservative tube (CellSearch, Huntington Valley, PA), have been developed and commercialized to stabilize WBCs ex vivo and enable delayed blood processing at room temperature up to 7 days without compromising tumor cfDNA fraction (24–26, 28). Similarly, urine preservatives, such as the Streck Cell-Free DNA urine preserve, has been developed to preserve cfDNA. The separation of plasma from the cellular fraction using double-spin versus single-spin methods has been shown to reduce the dilution of tumor cfDNA (26). Studies have also positively correlated the yield of tumor cfDNA to plasma volume used for extraction (26). Whether these reagents and processing methods uniformly apply to pathogen cfDNA is unclear. Unlike tumor cfDNA assays, which are designed to detect mutant allele in an abundant background of wild-type allele, targeted pathogen nucleic acid amplification tests (NAATs) are designed to amplify a highly specific pathogen sequence with no competition from a “wild type allele.” Thus, rapid processing, double-spin plasma separation, and stabilization of WBCs using expensive reagents and complex methods may not be critical for pathogen cfDNA. However, other preanalytical factors, such as sample volume, may be equally vital to the sensitive detection of pathogen cfDNA.

The aim of this study was to use contrived and clinical samples to investigate the impact of preanalytical variables, such as type of blood collection tube or urine preservative, processing delay, processing method, freezing and thawing, and sample volume on pathogen cfDNA detection in plasma and urine.

MATERIALS AND METHODS

Ethics.This study was approved by the institutional review board at Stanford University. Approval for the collection of clinical samples was obtained from the institutional review board at the Federal University of Grande Dourados (UFGD) and the Comissão Nacional de Ética em Pesquisa in Brazil, the Stellenbosch University Faculty of Health Sciences Research Ethics Committee (N14/10/136) in South Africa, the Committee on Human Research at the University of California, San Francisco (UCSF), the Research Ethics Committee at the Makerere University School of Medicine Research, and the Uganda National Council for Science and Technology. All participants were >18 years of age and provided written informed consent.

Study design.Spiking experiments with pathogen cfDNA from Mycobacterium tuberculosis, Salmonella enterica, Aspergillus fumigatus, and Epstein-Barr virus (EBV) were performed with fresh blood and urine from healthy donors to evaluate the impact of (i) blood collection tube and urine preservative, (ii) processing delay, (iii) processing method, (iv) freezing and thawing, and (v) sample volume on pathogen cfDNA in plasma and urine. Blood and urine from pretreatment TB patients collected under a different protocol at each site were used to validate findings from spiking experiments. A schematic overview of the study design is shown in Fig. 1.

FIG 1
  • Open in new tab
  • Download powerpoint
FIG 1

Study design. Spiking experiments with pathogen cfDNA from M. tuberculosis (Mtb), S. enterica (Salmonella), A. fumigatus (Aspergillus), and Epstein-Barr virus (EBV) were performed with fresh blood and urine from healthy donors to evaluate the impact of blood collection tube and urine preservative (blue circle), processing delay (brown circle), processing method (purple circle), sample storage (orange circle), and sample volume (red circle) on pathogen cfDNA in plasma and urine. In addition to using contrived samples, blood collection tube and urine preservative (blue circle) and sample volume (red circle) were evaluated using blood and urine samples from TB patients.

Study participants.Ten healthy health care workers (5 females and 5 males between 23 and 46 years old of White, Asian, and Middle Eastern race) with no symptoms or signs of infection were recruited from the clinical laboratories at Stanford Health Care for blood and urine collection. Patients with confirmed pulmonary tuberculosis (TB) based on culture and/or the Xpert MTB/RIF assay (Cepheid, Sunnyvale, CA, USA) were recruited from UFGD hospital and mass screening studies in the Dourados prison in Brazil for blood collection, the Kiruddu Hospital and Kisenyi Healthcare Center level IV in Uganda for urine collection, and the Scottsdene and Wallacedene Community Health Centres in South Africa for blood collection.

Pathogen cfDNA preparation.Based on the fact that eukaryotic plasma cfDNA is ≈168 bp and that bacterial cfDNA in a septic patient was shown to be slightly shorter than 168 bp, we aimed to generate 200-bp cfDNA fragments for the spiking studies (29, 30). Genomic DNA from M. tuberculosis and S. enterica was extracted with a QIAamp DNA minikit (Qiagen), and A. fumigatus DNA was extracted with PrepMan Ultra sample preparation reagent (Applied Biosystems, Foster City, CA). DNA was digested with Fragmentase (New England BioLabs, Ipswich, MA), according to the manufacturer’s instructions. DNA fragments were separated on a 1.2% agarose gel using electrophoresis, and the region corresponding to 200 bp was cut and gel purified using the Wizard SV gel and PCR clean-up system (Promega, Madison, WI). A plasma sample from an infected patient containing naturally occurring EBV cfDNA at 2,000 IU/ml was used directly. DNA extracts and the plasma sample were serially diluted 1:10 in water, 3 μl of each dilution was spiked into 1 ml of donor plasma and urine, and the entire volume was extracted with the Maxwell RSC ccfDNA plasma kit (Promega) on the Maxwell RSC system. Real-time PCR was performed using the primers and probes shown in Table S1 in the supplemental material. PCRs consisted of 0.5 μM each primer and 0.2 μM each probe, 5 μl of 2× FastStart TaqMan Probe mastermix (Roche Applied Science, Indianapolis, IN), and 3 μl of DNA extract. The total volume was 10 μl per reaction. The reactions were run on a magnetic induction cycler (Bioline, Taunton, MA), with the following cycling parameters: 95°C for 10 min and 45 cycles of 95°C for 15 s, 60°C for 30 s, and 72°C for 30 s. Detection was performed in the green, yellow, orange, and red channels at 72°C. The threshold was set at 0.2 for all channels. The dilution that produced a cycle threshold (CT) between 25 and 30 was chosen for spiking experiments. Aliquots were stored at –20°C and thawed only one time for spiking studies.

cfDNA spiking.Within 10 min of blood and urine collection, samples were spiked with pathogen cfDNA at 3 μl per ml of blood and urine and gently mixed.

Blood collection tube and urine preservative.For spiking experiments, venipuncture blood was collected in three sets of K2EDTA (Becton, Dickinson, Franklin Lakes, NJ), Streck Cell-Free DNA BCT (Omaha, NE), and PAXgene blood ccfDNA (PreAnalytiX GmbH, Hombrechtikon, Switzerland) blood collection tubes. TB patients in South Africa were drawn concurrently in K2EDTA and Streck tubes and processed immediately. Plasma was frozen at –80°C and shipped to Stanford University for testing.

For an investigation of urine preservative in spiking experiments, urine collected in a collection cup was immediately transferred to four sets of conical tubes for each preservative and raw urine specimen. Urine specimens were treated with preservative to obtain a final concentration of 25 mM EDTA using 0.5 M EDTA (pH 7.6) stock (Sigma-Aldrich), 10 mM Tris-EDTA using 0.5 M Tris-HCl (pH 8.5), and 0.5 M EDTA (pH 7.6) stock, and a 1:20 dilution of Streck Cell-Free DNA urine preserve. Urine from TB patients in Uganda was preserved in 10 mM Tris-HCl–10 mM EDTA (pH 8.5) and Streck Cell-Free DNA urine preserve, frozen at –80°C, and shipped to Stanford University for testing.

Processing delay.One set of blood collection tubes and urine specimens was immediately processed. The second and third sets were processed after room temperature incubation periods of 6 and 24 h, respectively. All remaining procedures were identical for the three sets.

Processing method.For single-spin plasma separation, blood collection tubes were centrifuged at 500 × g for 10 min at room temperature, and the plasma was transferred to a new tube. For double-spin plasma separation, 1.5 ml of plasma was additionally centrifuged at 16,000 × g for 10 min at room temperature, and the supernatant was transferred to a new tube. For urine processing, whole urine was centrifuged at 500 × g for 10 min, and the supernatant was transferred to a new tube.

Fresh versus thawed.Plasma obtained through single-spin plasma separation and whole urine from the spiking experiments were stored at –80°C for 1 and/or 24 weeks. Samples were thawed at room temperature and extracted for comparison to fresh samples.

Sample volume.Blood collected in K2EDTA tubes and EDTA-urine from five healthy donors were spiked with M. tuberculosis cfDNA at the highest detectable dilution (see “Pathogen cfDNA preparation,” above) and at a 10-fold higher concentration. Blood was processed using single-spin centrifugation. One and 4 ml of fresh EDTA-plasma and whole urine were extracted using the Maxwell RSC system. The Maxwell RSC ccfDNA plasma kit and a custom Maxwell RSC large-volume ccfDNA kit available commercially were used to extract 1 and 4 ml, respectively. Sample volume was also investigated in TB patients using EDTA-plasma from patients in Brazil and Tris-EDTA-urine from patients in Uganda. After thawing samples, blood samples were extracted with QIAamp circulating nucleic acid kit (Qiagen), and urine samples were extracted with the Maxwell RSC system.

cfDNA measurement.Except for assessments of sample volume, 1 ml each of plasma and urine were extracted at each time point using the Maxwell RSC ccfDNA plasma kit. The real-time PCR conditions described above were used to determine CT values for M. tuberculosis, S. enterica, A. fumigatus, and EBV in spiking experiments and M. tuberculosis in clinical samples. Each PCR was performed in singlicate. The median CT values, a measure of amplifiable cfDNA, were compared between different conditions. Except for fresh versus thawed experiments, all cfDNA extracts from the same individual’s plasma and urine were tested in the same PCR run.

Statistical analysis.A nonparametric test, the Wilcoxon signed-rank test of medians, was used to compare differences between paired results. The EDTA group was used as the comparator for all analyses. All statistical tests were computed for a two-sided type I error rate of 5%. Statistical analyses were performed using the Prism software (GraphPad, San Diego, CA).

RESULTS

Blood collection tube and urine preservative.A comparison of the standard K2EDTA tube to two cfDNA blood collection tubes spiked with pathogen cfDNA and processed identically for plasma separation and extraction showed a significantly lower median CT value with K2EDTA tubes for M. tuberculosis and S. enterica than with Streck and PAXgene tubes (Fig. 2A and B and Table S2). The median A. fumigatus CT was significantly lower for K2EDTA tubes than with Streck tubes but only after 6- and 24-h processing delays (Fig. 2C). The median A. fumigatus CT was significantly lower for PAXgene tubes than for K2EDTA tubes except for the 24-h processing delay with double-spin plasma separation (Fig. 2C). The median EBV CT was lower for K2EDTA tubes than for Streck and PAXgene tubes, but the difference was significant only after 6- and 24-h processing delays for single- and/or double-spin plasma separation (Fig. 2D).

FIG 2
  • Open in new tab
  • Download powerpoint
FIG 2

Comparison of blood collection tubes for recovery of pathogen cfDNA in plasma using contrived samples. (A to D) Blood was collected from 10 healthy donors in a K2EDTA (EDTA) tube, Streck Cell-Free DNA BCT, and a PAXgene blood ccfDNA tube and spiked with short fragments of DNA from M. tuberculosis (A), S. enterica (B), A. fumigatus (C), and EBV (D). Blood collection tubes were processed after 0-, 6-, and 24-h delays at room temperature, and plasma was obtained using one-spin (1spin) and double-spin (2spin) separation. PCR was performed on cfDNA extracts. Bars show median CT, and whiskers show the CT range. For each condition (processing time and plasma separation method), Streck and PAXgene tubes were compared to EDTA tubes. *, P < 0.05; **, P < 0.01.

A comparison of three urine preservatives using urine specimens from healthy donors spiked with pathogen cfDNA showed significantly lower median pathogen CT values for 25 mM EDTA than with Streck urine preservative for all four pathogens at all time points for whole urine (unspun) and/or urine supernatant (one spin), with the exception of EBV, which was significantly lower only after 6- and 24-h processing delays (Fig. 3 and Table S3). In many instances, 25 mM EDTA yielded a lower median CT than did 10 mM Tris-EDTA, but this difference reached statistical significance only after 6- and/or 24-h processing delays for whole urine and/or urine supernatant (Fig. 3). Unpreserved (neat) urine consistently yielded a significantly higher median CT than did 25 mM EDTA for all four pathogens at all time points, with the exception of A. fumigatus, which was significant only after 6- and 24-h processing delays (Fig. 3 and Table S3).

FIG 3
  • Open in new tab
  • Download powerpoint
FIG 3

Comparison of urine preservatives for recovery of pathogen cfDNA using contrived samples. (A to D) Urine was collected from 10 healthy donors and preserved with 25 mM EDTA, 10 mM Tris-EDTA, or Streck Cell-Free DNA urine preserve, or left unpreserved (neat urine) and spiked with short fragments of DNA from M. tuberculosis (A), S. enterica (B), A. fumigatus (C), and EBV (D). Urine samples were processed after 0-, 6-, and 24-h delays at room temperature. Whole urine (unspun) and urine supernatant (1spin) were included. PCR was performed on cfDNA extracts. Bars show median CT, and whiskers show the CT range. In the absence of amplification for S. enterica in neat urine, a CT of 45 was assigned. For each condition (processing time and urine processing method), Tris-EDTA, Streck, and neat were compared to EDTA. *, P < 0.05; **, P < 0.01.

In patients with pulmonary TB and detectable M. tuberculosis cfDNA in plasma, blood samples concurrently collected in K2EDTA and Streck tubes and processed immediately showed significantly lower median M. tuberculosis CT values with K2EDTA-plasma than with Streck-plasma (P = 0.021) (Fig. 4A and Table S4). In patients with pulmonary TB and detectable M. tuberculosis cfDNA in urine, urine samples concurrently preserved with 10 mM Tris-EDTA and Streck urine preserve showed significantly lower median M. tuberculosis CT with 10 mM Tris-EDTA than with Streck urine preservative (P = 0.035) (Fig. 4B and Table S4).

FIG 4
  • Open in new tab
  • Download powerpoint
FIG 4

Comparison of blood collection tubes and urine preservatives for detection of M. tuberculosis cfDNA in plasma and urine from patients with tuberculosis. (A and B) IS6110 PCR CT values are plotted for plasma samples collected concurrently in K2EDTA and Streck Cell-Free DNA BCT (n = 7) (A), and urine samples concurrently preserved in Tris-EDTA and Streck Cell-Free DNA urine preserve (n = 20) (B). Results are shown for patients with detectable M. tuberculosis cfDNA with both collection tubes and preservatives.

Processing delay.Compared to immediate processing (i.e., 0-h delay) of blood collection tubes for plasma separation, a delay of 6 and/or 24 h at room temperature increased the median pathogen CT values of all four pathogens spiked in Streck and PAXgene tubes after single- and/or double-spin plasma separation, although the difference was only consistently significant for M. tuberculosis and S. enterica (Fig. 5 and Table S5). Processing delays of 6 and 24 h with single-spin plasma separation did not significantly change the median CT values of any of the four spiked pathogens in a K2EDTA tube (Fig. 5 and Table S5).

FIG 5
  • Open in new tab
  • Download powerpoint
FIG 5

Impact of processing delay on recovery of pathogen cfDNA in plasma using contrived samples. (A to D) Blood was collected from 10 healthy donors in a K2EDTA tube, Streck Cell-Free DNA BCT, and PAXgene blood ccfDNA tube and spiked with short fragments of DNA from M. tuberculosis (A), S. enterica (B), A. fumigatus (C), and EBV (D). Blood collection tubes were processed after 0-, 6-, and 24-h delays at room temperature, and plasma was obtained using one-spin (1spin) and double-spin (2spin) separation. PCR was performed on cfDNA extracts. The bars show the median CT, and whiskers show the CT range. For each condition (blood collection tube and plasma separation method), 6- and 24-h processing delays were compared to 0 h. *, P < 0.05; **, P < 0.01.

For urine samples, processing delays of 6 and 24 h did not increase the median CT values of any of the four pathogens in urine preserved with 25 mM EDTA and 10 mM Tris-EDTA (Fig. 6 and Table S6). Preservation of urine with Streck preservative resulted in a significant increase in median CT values of M. tuberculosis, S. enterica, and EBV after 6- and/or 24-h delays in unspun urine and/or urine supernatant (1 spin). With unpreserved (neat) urine, the median CT increased significantly for M. tuberculosis, A. fumigatus, and EBV, which was statistically significant after a 24-h delay in whole urine and/or supernatant. In neat urine spiked with S. enterica, most samples had undetectable PCR amplification at all time points.

FIG 6
  • Open in new tab
  • Download powerpoint
FIG 6

Impact of processing delay on recovery of pathogen cfDNA in urine using contrived samples. (A to D) Urine was collected from 10 healthy donors and preserved with 25 mM EDTA, 10 mM Tris-EDTA, Streck Cell-Free DNA urine preserve, or left unpreserved (neat urine) and spiked with short fragments of DNA from M. tuberculosis (A), S. enterica (B), A. fumigatus (C), and EBV (D). Urine samples were processed after 0-, 6-, and 24-h delays at room temperature. Whole urine (unspun) and urine supernatant (1spin) were evaluated. PCR was performed on cfDNA extracts. The bars show median CT values, and whiskers show the CT range. In the absence of amplification for S. enterica in neat urine, a CT of 45 was assigned. For each condition (urine preservative and urine processing method) 6- and 24-h processing delays were compared to 0 h. *, P < 0.05; **, P < 0.01.

Processing method.A comparison of single-spin and double-spin plasma separation methods showed lower median CT values of all four pathogens with single-spin separation than with double-spin separation, except for A. fumigatus in K2EDTA and Streck tubes after a 0-h processing delay (Fig. 7 and Table S7). The difference was statistically significant for M. tuberculosis, S. enterica, and EBV at all three time points (0-, 6-, and 24-h processing delays) and with all three blood collection tubes, with the exception of EBV, which was only significant with K2EDTA and PAXgene tubes. For A. fumigatus, the difference was statistically significant only after 0- and 24-h processing delays with the PAXgene tube.

FIG 7
  • Open in new tab
  • Download powerpoint
FIG 7

Comparison of single-spin to double-spin plasma separation for recovery of pathogen cfDNA using contrived samples. (A to D) Blood was collected from 10 healthy donors in a K2EDTA tube, Streck Cell-Free DNA BCT, and PAXgene Blood ccfDNA tube and spiked with short fragments of DNA from M. tuberculosis (A), S. enterica (B), A. fumigatus (C), and EBV (D). Blood collection tubes were processed after 0-, 6-, and 24-h delays at room temperature, and plasma was obtained using one-spin (1spin) and double-spin (2spin) separation. PCR was performed on cfDNA extracts. Bars show median CT values, and whiskers show the CT range. For each condition (blood collection tube and processing delay), double spin was compared to one spin. *, P < 0.05; **, P < 0.01.

A comparison of whole urine (unspun) to urine supernatant (one spin) showed no consistent difference in median CT values of all four pathogens at all three time points (0-, 6-, and 24-h processing delays) and with all three urine preservatives (Fig. S1 and Table S8).

Fresh versus thawed.A comparison of fresh and thawed plasma after 1 and 24 weeks of storage at –80°C showed no significant difference in median CT values of all four pathogens after immediate processing with all three blood collection tubes, with the exception of S. enterica in a PAXgene tube (Fig. S2 and Table S9).

A comparison of fresh and thawed urine after 24 weeks of storage at –80°C showed no difference in median CT values of all four pathogens after immediate processing with all three urine preservatives (Fig. S3 and Table S10).

Sample volume.A comparison of small and large volumes of plasma and urine for the detection of M. tuberculosis cfDNA using contrived samples (1 ml versus 4 ml) and clinical samples from newly diagnosed TB patients (plasma, 0.5 ml versus 3.0 ml; urine, 1 ml versus 4 ml) showed a significantly lower median CT with larger volumes for both plasma and urine (Fig. 8 and Table S11). In a fraction of contrived and clinical samples, amplification was only detected with the larger sample volume (Fig. 8).

FIG 8
  • Open in new tab
  • Download powerpoint
FIG 8

Comparison of small- and large-volume plasma and urine for detection of M. tuberculosis cfDNA using contrived samples and tuberculosis patient samples. (A and C) Spiked plasma (A) and urine (C) samples from five healthy donors (unique symbols). Blood samples were collected in a K2EDTA tube, and urine samples were preserved with 25 mM EDTA. Blood and urine samples were spiked with short fragments of DNA from M. tuberculosis at the highest detectable dilution (open symbols) and at 10-fold higher concentration (filled symbols). (B and D) K2EDTA plasma (n = 12) (B) and Tris-EDTA urine (n = 10) (D) samples from tuberculosis patients with detectable cfDNA. IS6110 PCR was performed on cfDNA extracts, and CT values were plotted. Unpaired symbols indicate that a positive result was only observed with a larger volume.

DISCUSSION

The detection of pathogen cfDNA in plasma and urine potentially affords an attractive novel noninvasive approach to diagnosing invasive infections. However, little is known about the impact of preanalytical factors, such as type of blood collection tube or urine preservative, processing delay, processing method, sample volume, and freezing and thawing, on the detection of pathogen cfDNA (23). We showed that most of the preanalytical factors deemed important for fetal and tumor cfDNA (24–26, 28) do not seem to apply to pathogen cfDNA. These results increase the potential for low-cost pathogen cfDNA assays to be developed for infectious disease diagnostics.

Using blood and urine samples spiked with cfDNA from four different pathogens representative of bacteria, fungi, and DNA viruses, we showed the standard K2EDTA blood collection tube, which is inexpensive and widely available, yields an amount of detectable pathogen cfDNA higher than or equivalent to that of Streck and PAXgene tubes, except for A. fumigatus cfDNA in PAXgene tubes. Importantly, the addition of preservative to urine was critical to preventing the degradation of pathogen cfDNA, and preservation with 25 mM EDTA was superior to Streck urine preservative. We were also able to confirm the superiority of K2EDTA and 25 mM EDTA over Streck tubes using plasma and urine, respectively, from patients with active TB. Similar to tumor cfDNA in plasma (25), we showed that pathogen cfDNA in blood collected in K2EDTA and urine preserved with 25 mM EDTA is stable for at least 24 h at room temperature. Unlike tumor cfDNA, for which double-spin plasma separation helps prevent tumor cfDNA dilution after delayed processing (26), a single low-speed centrifugation was sufficient to maximize the yield of spiked pathogen cfDNA up to 24 h after sample collection. With urine samples, we showed that separation of cellular fraction from whole urine with a centrifugation step had no impact on the yield of pathogen cfDNA up to 24 h after urine collection. In agreement with tumor cfDNA, extraction of a higher volume of plasma and urine yielded a higher abundance of M. tuberculosis cfDNA in contrived samples and samples collected from TB patients. Last, freezing and thawing of plasma and urine samples after storage at –80°C up to 24 weeks did not have any impact on the abundance of pathogen cfDNA in spiked samples.

Our findings bear implications for the application of pathogen cfDNA in the clinical laboratory for the diagnosis of invasive infections, particularly in resource-limited settings. The findings that the K2EDTA blood collection tube combined with single-spin low-speed plasma separation and 24-h processing delay yields the maximum amount of amplifiable cfDNA for 3 out of 4 pathogens we evaluated implies that optimized preanalytical steps can be feasibly and inexpensively implemented in the routine microbiology laboratory workflow, both in resource-rich and resource-limited settings. Unlike Streck and PAXgene cfDNA blood collection tubes, which cost about $10 each, K2EDTA tubes cost less than $0.50. Similarly, the findings that 25 mM EDTA preserves pathogen cfDNA in whole urine without the need to remove cellular debris with centrifugation and up to a 24-h processing delay implies that optimized preanalytical steps can be inexpensively operationalized for pathogen cfDNA testing in urine.

Although the findings of this study are promising, a better understanding of the underlying biochemical basis of preanalytical factors impacting cfDNA recovery may lead to further optimization and improvement of cfDNA testing. The finding that the K2EDTA blood collection tube was superior to the Streck and PAXgene tubes for the recovery of cfDNA from M. tuberculosis, S. enterica, and EBV after delayed processing may be explained by EDTA (1.8 mg/ml) in K2EDTA, which protects pathogen cfDNA from endogenous DNase activity in blood (31). Whether increasing the EDTA concentration by as much as 10-fold, as suggested by Barra and colleagues to fully inhibit endogenous DNase activity (31), can further increase the yield of pathogen cfDNA remains to be shown. Another interesting finding was that more A. fumigatus cfDNA was recovered from PAXgene tubes than from K2EDTA tubes. Whether this can be reproduced in patients with invasive fungal disease and the molecular basis of this result have important implications for the sensitivity of cfDNA assays used to diagnose invasive fungal disease (13, 15). We also observed a higher pathogen cfDNA yield after single-spin plasma separation than with double-spin separation. The molecular basis underlying this finding is unclear, but understanding it may facilitate designing a novel tube with higher cfDNA yield. Last, the difference in urine cfDNA stability between pathogens is intriguing. While M. tuberculosis and S. enterica cfDNA were rapidly degraded in unpreserved urine, A. fumigatus and EBV cfDNA was less prone to degradation. Whether this is due to differences in DNA packaging between prokaryotic and eukaryotic organisms remains to be determined.

This study has several limitations. First, although the variables investigated using TB patient samples in this study correlated very well with findings from contrived samples, not all findings from contrived samples could be confirmed. As such, further studies are needed to validate our findings with clinical samples. Second, although many of the findings with spiked samples were statistically significant, there was an overlap between groups in most cases. Thus, the clinical significance of our findings needs to be further investigated in clinical studies. Third, we did not include a serum collection tube to compare serum to plasma for the recovery of pathogen cfDNA. This was because serum has been shown to have 15-fold higher endogenous nuclease activity and a smaller fraction and quantity of tumor and fetal cfDNA, respectively, than with plasma (25, 31). Importantly, the sensitivity of Aspergillus PCR was shown to be higher in plasma than in serum (94.7% versus 68.4%, respectively) (13). We also did not investigate heparin as the anticoagulant for plasma because older studies had shown that it inhibits PCR (32–34). Fourth, we did not investigate processing delays beyond 24 h. However, 24 h is a sufficient time period to collect and transport samples to the laboratory for processing in most institutions. Last, we did not compare extraction methods for pathogen cfDNA. This was the topic of investigation of a recent study that evaluated commercial methods available for the extraction of plasma cfDNA (35). A key finding from this study was that commercial methods are biased toward longer cfDNA. Further studies are needed to investigate and optimize the extraction of pathogen cfDNA from plasma and urine.

In summary, we evaluated preanalytical factors impacting the recovery of pathogen cfDNA from blood and urine and found that large-volume single-spin K2EDTA-plasma and EDTA-whole urine with up to a 24-h processing delay represent good choices for pathogen cfDNA. Future studies can focus on measuring the performance of pathogen cfDNA assays using optimized preanalytical factors described here. It is likely that more efficient pathogen cfDNA extraction methods and sensitive cfDNA NAATs, ideally, sample-to-answer tests, are needed to complement the preanalytical optimization steps described in this study in order to move noninvasive diagnosis of invasive infections into routine practice.

ACKNOWLEDGMENTS

We thank Stanford Global Health and the Stanford ChEM-H institute for sponsoring this study. C.A.H. is supported by fellowship funding from the Canadian Institutes for Health Research (CIHR). A.A. is supported by the Pulmonary Complications of AIDS Research Training (PART) program. We also acknowledge Bill and Melinda Gates for sponsoring a portion of this work through the Intellectual Ventures Global Good Fund. G.T. acknowledges funding from South African Medical Research Council (SAMRC flagship project MRC-RFA-IFSP-01-2013) and the European and Developing Countries Clinical Trials Partnership (EDCTP).

FOOTNOTES

    • Received 24 May 2019.
    • Returned for modification 25 June 2019.
    • Accepted 3 September 2019.
    • Accepted manuscript posted online 11 September 2019.
  • Supplemental material for this article may be found at https://doi.org/10.1128/JCM.00782-19.

  • Copyright © 2019 Murugesan et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

REFERENCES

  1. 1.↵
    1. Bianchi DW,
    2. Parker RL,
    3. Wentworth J,
    4. Madankumar R,
    5. Saffer C,
    6. Das AF,
    7. Craig JA,
    8. Chudova DI,
    9. Devers PL,
    10. Jones KW,
    11. Oliver K,
    12. Rava RP,
    13. Sehnert AJ, CARE Study Group
    . 2014. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med 370:799–808. doi:10.1056/NEJMoa1311037.
    OpenUrlCrossRefPubMedWeb of Science
  2. 2.↵
    1. Crowley E,
    2. Di Nicolantonio F,
    3. Loupakis F,
    4. Bardelli A
    . 2013. Liquid biopsy: monitoring cancer-genetics in the blood. Nat Rev Clin Oncol 10:472–484. doi:10.1038/nrclinonc.2013.110.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Wan JCM,
    2. Massie C,
    3. Garcia-Corbacho J,
    4. Mouliere F,
    5. Brenton JD,
    6. Caldas C,
    7. Pacey S,
    8. Baird R,
    9. Rosenfeld N
    . 2017. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer 17:223–238. doi:10.1038/nrc.2017.7.
    OpenUrlCrossRef
  4. 4.↵
    1. Lin JC,
    2. Wang WY,
    3. Chen KY,
    4. Wei YH,
    5. Liang WM,
    6. Jan JS,
    7. Jiang RS
    . 2004. Quantification of plasma Epstein-Barr virus DNA in patients with advanced nasopharyngeal carcinoma. N Engl J Med 350:2461–2470. doi:10.1056/NEJMoa032260.
    OpenUrlCrossRefPubMedWeb of Science
  5. 5.↵
    1. Lo YM,
    2. Chan LY,
    3. Chan AT,
    4. Leung SF,
    5. Lo KW,
    6. Zhang J,
    7. Lee JC,
    8. Hjelm NM,
    9. Johnson PJ,
    10. Huang DP
    . 1999. Quantitative and temporal correlation between circulating cell-free Epstein-Barr virus DNA and tumor recurrence in nasopharyngeal carcinoma. Cancer Res 59:5452–5455.
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    1. Kanakry JA,
    2. Hegde AM,
    3. Durand CM,
    4. Massie AB,
    5. Greer AE,
    6. Ambinder RF,
    7. Valsamakis A
    . 2016. The clinical significance of EBV DNA in the plasma and peripheral blood mononuclear cells of patients with or without EBV diseases. Blood 127:2007–2017. doi:10.1182/blood-2015-09-672030.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Ushio R,
    2. Yamamoto M,
    3. Nakashima K,
    4. Watanabe H,
    5. Nagai K,
    6. Shibata Y,
    7. Tashiro K,
    8. Tsukahara T,
    9. Nagakura H,
    10. Horita N,
    11. Sato T,
    12. Shinkai M,
    13. Kudo M,
    14. Ueda A,
    15. Kaneko T
    . 2016. Digital PCR assay detection of circulating Mycobacterium tuberculosis DNA in pulmonary tuberculosis patient plasma. Tuberculosis (Edinb) 99:47–53. doi:10.1016/j.tube.2016.04.004.
    OpenUrlCrossRefPubMed
  8. 8.↵
    1. Click ES,
    2. Murithi W,
    3. Ouma GS,
    4. McCarthy K,
    5. Willby M,
    6. Musau S,
    7. Alexander H,
    8. Pevzner E,
    9. Posey J,
    10. Cain KP
    . 2018. Detection of apparent cell-free M. tuberculosis DNA from plasma. Sci Rep 8:645. doi:10.1038/s41598-017-17683-6.
    OpenUrlCrossRef
  9. 9.↵
    1. Patel K,
    2. Nagel M,
    3. Wesolowski M,
    4. Dees S,
    5. Rivera-Milla E,
    6. Geldmacher C,
    7. Dheda K,
    8. Hoelscher M,
    9. Labugger I
    . 2018. Evaluation of a urine-based rapid molecular diagnostic test with potential to be used at point-of-care for pulmonary tuberculosis: Cape Town cohort. J Mol Diagn 20:215–224. doi:10.1016/j.jmoldx.2017.11.005.
    OpenUrlCrossRef
  10. 10.↵
    1. Labugger I,
    2. Heyckendorf J,
    3. Dees S,
    4. Haussinger E,
    5. Herzmann C,
    6. Kohl TA,
    7. Richter E,
    8. Rivera-Milla E,
    9. Lange C
    . 2017. Detection of transrenal DNA for the diagnosis of pulmonary tuberculosis and treatment monitoring. Infection 45:269–276. doi:10.1007/s15010-016-0955-2.
    OpenUrlCrossRef
  11. 11.↵
    1. Fortún J,
    2. Martín-Dávila P,
    3. Gómez-Mampaso E,
    4. González-García A,
    5. Barbolla I,
    6. Gómez-García I,
    7. Wikman P,
    8. Ortíz J,
    9. Navas E,
    10. Cuartero C,
    11. Gijón D,
    12. Moreno S
    . 2014. Extra-pulmonary tuberculosis: differential aspects and role of 16S-rRNA in urine. Int J Tuberc Lung Dis 18:478–485. doi:10.5588/ijtld.13.0555.
    OpenUrlCrossRefPubMed
  12. 12.↵
    1. Cannas A,
    2. Goletti D,
    3. Girardi E,
    4. Chiacchio T,
    5. Calvo L,
    6. Cuzzi G,
    7. Piacentini M,
    8. Melkonyan H,
    9. Umansky SR,
    10. Lauria FN,
    11. Ippolito G,
    12. Tomei LD
    . 2008. Mycobacterium tuberculosis DNA detection in soluble fraction of urine from pulmonary tuberculosis patients. Int J Tuberc Lung Dis 12:146–151.
    OpenUrlPubMedWeb of Science
  13. 13.↵
    1. White PL,
    2. Barnes RA,
    3. Springer J,
    4. Klingspor L,
    5. Cuenca-Estrella M,
    6. Morton CO,
    7. Lagrou K,
    8. Bretagne S,
    9. Melchers WJ,
    10. Mengoli C,
    11. Donnelly JP,
    12. Heinz WJ,
    13. Loeffler J, EAPCRI
    . 2015. Clinical performance of Aspergillus PCR for testing serum and plasma: a study by the European Aspergillus PCR initiative. J Clin Microbiol 53:2832–2837. doi:10.1128/JCM.00905-15.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. Wang D,
    2. Hu Y,
    3. Li T,
    4. Rong HM,
    5. Tong ZH
    . 2017. Diagnosis of Pneumocystis jirovecii pneumonia with serum cell-free DNA in non-HIV-infected immunocompromised patients. Oncotarget 8:71946–71953. doi:10.18632/oncotarget.18037.
    OpenUrlCrossRef
  15. 15.↵
    1. Millon L,
    2. Herbrecht R,
    3. Grenouillet F,
    4. Morio F,
    5. Alanio A,
    6. Letscher-Bru V,
    7. Cassaing S,
    8. Chouaki T,
    9. Kauffmann-Lacroix C,
    10. Poirier P,
    11. Toubas D,
    12. Augereau O,
    13. Rocchi S,
    14. Garcia-Hermoso D,
    15. Bretagne S,
    16. Dupont H,
    17. Marolleau JP,
    18. Totet A,
    19. Damiani C,
    20. Berceanu A,
    21. Larosa F,
    22. Bonhomme J,
    23. Chabrot C,
    24. Bouteille B,
    25. Boutoille D,
    26. Gastinne T,
    27. Peterlin P,
    28. Gari Toussaint M,
    29. Poisson D,
    30. Briet D,
    31. Buret J,
    32. Legrand M,
    33. Denis B,
    34. Raffoux E,
    35. Bergeron A,
    36. Veinstein A,
    37. Godet C,
    38. N'guyen Y,
    39. Diallo S,
    40. Sabou M,
    41. Denis J,
    42. Ledoux MP,
    43. Recher C,
    44. Ruiz J,
    45. Desoubeaux G,
    46. Bailly E,
    47. Chachaty E,
    48. Dromer F,
    49. Lortholary O,
    50. Sitbon K, et al
    . 2016. Early diagnosis and monitoring of mucormycosis by detection of circulating DNA in serum: retrospective analysis of 44 cases collected through the French Surveillance Network of Invasive Fungal Infections (RESSIF). Clin Microbiol Infect 22:810.e1–810.e8. doi:10.1016/j.cmi.2015.12.006.
    OpenUrlCrossRef
  16. 16.↵
    1. Aguado JM,
    2. Vazquez L,
    3. Fernandez-Ruiz M,
    4. Villaescusa T,
    5. Ruiz-Camps I,
    6. Barba P,
    7. Silva JT,
    8. Batlle M,
    9. Solano C,
    10. Gallardo D,
    11. Heras I,
    12. Polo M,
    13. Varela R,
    14. Vallejo C,
    15. Olave T,
    16. Lopez-Jimenez J,
    17. Rovira M,
    18. Parody R,
    19. Cuenca-Estrella M,
    20. Zarzuela MP,
    21. Candel Gonzalez FJ,
    22. Amador PM,
    23. Mediavilla JD,
    24. Camps IR,
    25. Barba P,
    26. Castillo N,
    27. Martin MT,
    28. Soriano JA,
    29. Fernando IH,
    30. Castilla-Llorente C,
    31. Cesteros R,
    32. Rodriguez Mondejar MR,
    33. Vazquez L,
    34. Villaescusa T,
    35. Caballero D,
    36. Garcia JE,
    37. Garcia IG,
    38. de la Mano Gonzalez S,
    39. Fernandez Garcia-Hierro JM,
    40. Solano C,
    41. Tormo M,
    42. Navarro D,
    43. Angel Molla M,
    44. Vallejo C,
    45. Gonzalez AJ,
    46. Gonzalez S,
    47. Gonzalez AP,
    48. Palomo P,
    49. Porras RP,
    50. Batlle M, et al
    . 2015. Serum galactomannan versus a combination of galactomannan and polymerase chain reaction-based Aspergillus DNA detection for early therapy of invasive aspergillosis in high-risk hematological patients: a randomized controlled trial. Clin Infect Dis 60:405–414. doi:10.1093/cid/ciu833.
    OpenUrlCrossRefPubMed
  17. 17.↵
    1. Weerakoon KG,
    2. McManus DP
    . 2016. Cell-free DNA as a diagnostic tool for human parasitic infections. Trends Parasitol 32:378–391. doi:10.1016/j.pt.2016.01.006.
    OpenUrlCrossRef
  18. 18.↵
    1. Blauwkamp TA,
    2. Thair S,
    3. Rosen MJ,
    4. Blair L,
    5. Lindner MS,
    6. Vilfan ID,
    7. Kawli T,
    8. Christians FC,
    9. Venkatasubrahmanyam S,
    10. Wall GD,
    11. Cheung A,
    12. Rogers ZN,
    13. Meshulam-Simon G,
    14. Huijse L,
    15. Balakrishnan S,
    16. Quinn JV,
    17. Hollemon D,
    18. Hong DK,
    19. Vaughn ML,
    20. Kertesz M,
    21. Bercovici S,
    22. Wilber JC,
    23. Yang S
    . 2019. Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease. Nat Microbiol 4:663–674. doi:10.1038/s41564-018-0349-6.
    OpenUrlCrossRef
  19. 19.↵
    1. Hong DK,
    2. Blauwkamp TA,
    3. Kertesz M,
    4. Bercovici S,
    5. Truong C,
    6. Banaei N
    . 2018. Liquid biopsy for infectious diseases: sequencing of cell-free plasma to detect pathogen DNA in patients with invasive fungal disease. Diagn Microbiol Infect Dis 92:210–213. doi:10.1016/j.diagmicrobio.2018.06.009.
    OpenUrlCrossRef
  20. 20.↵
    1. Farnaes L,
    2. Wilke J,
    3. Ryan Loker K,
    4. Bradley JS,
    5. Cannavino CR,
    6. Hong DK,
    7. Pong A,
    8. Foley J,
    9. Coufal NG
    . 2019. Community-acquired pneumonia in children: cell-free plasma sequencing for diagnosis and management. Diagn Microbiol Infect Dis 94:188–191. doi:10.1016/j.diagmicrobio.2018.12.016.
    OpenUrlCrossRef
  21. 21.↵
    1. Nomura J,
    2. Rieg G,
    3. Bluestone G,
    4. Tsai T,
    5. Lai A,
    6. Terashita D,
    7. Bercovici S,
    8. Hong DK,
    9. Lee BP
    . 2019. Rapid detection of invasive Mycobacterium chimaera disease via a novel plasma-based next-generation sequencing test. BMC Infect Dis 19:371. doi:10.1186/s12879-019-4001-8.
    OpenUrlCrossRef
  22. 22.↵
    1. Armstrong AE,
    2. Rossoff J,
    3. Hollemon D,
    4. Hong DK,
    5. Muller WJ,
    6. Chaudhury S
    . 2019. Cell-free DNA next-generation sequencing successfully detects infectious pathogens in pediatric oncology and hematopoietic stem cell transplant patients at risk for invasive fungal disease. Pediatr Blood Cancer 66:e27734. doi:10.1002/pbc.27734.
    OpenUrlCrossRef
  23. 23.↵
    1. Fernández-Carballo BL,
    2. Broger T,
    3. Wyss R,
    4. Banaei N,
    5. Denkinger CM
    . 2019. Toward the development of a circulating free DNA-based in vitro diagnostic test for infectious diseases: a review of evidence for tuberculosis. J Clin Microbiol 57:e01234-18. doi:10.1128/JCM.01234-18.
    OpenUrlAbstract/FREE Full Text
  24. 24.↵
    1. Kang Q,
    2. Henry NL,
    3. Paoletti C,
    4. Jiang H,
    5. Vats P,
    6. Chinnaiyan AM,
    7. Hayes DF,
    8. Merajver SD,
    9. Rae JM,
    10. Tewari M
    . 2016. Comparative analysis of circulating tumor DNA stability in K3EDTA, Streck, and CellSave blood collection tubes. Clin Biochem 49:1354–1360. doi:10.1016/j.clinbiochem.2016.03.012.
    OpenUrlCrossRef
  25. 25.↵
    1. Parpart-Li S,
    2. Bartlett B,
    3. Popoli M,
    4. Adleff V,
    5. Tucker L,
    6. Steinberg R,
    7. Georgiadis A,
    8. Phallen J,
    9. Brahmer J,
    10. Azad N,
    11. Browner I,
    12. Laheru D,
    13. Velculescu VE,
    14. Sausen M,
    15. Diaz LA, Jr.
    2017. The effect of preservative and temperature on the analysis of circulating tumor DNA. Clin Cancer Res 23:2471–2477. doi:10.1158/1078-0432.CCR-16-1691.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. Sherwood JL,
    2. Corcoran C,
    3. Brown H,
    4. Sharpe AD,
    5. Musilova M,
    6. Kohlmann A
    . 2016. Optimised pre-analytical methods improve KRAS mutation detection in circulating tumour DNA (ctDNA) from patients with non-small cell lung cancer (NSCLC). PLoS One 11:e0150197. doi:10.1371/journal.pone.0150197.
    OpenUrlCrossRef
  27. 27.↵
    1. Angert RM,
    2. LeShane ES,
    3. Lo YM,
    4. Chan LY,
    5. Delli-Bovi LC,
    6. Bianchi DW
    . 2003. Fetal cell-free plasma DNA concentrations in maternal blood are stable 24 hours after collection: analysis of first- and third-trimester samples. Clin Chem 49:195–198. doi:10.1373/49.1.195.
    OpenUrlFREE Full Text
  28. 28.↵
    1. Toro PV,
    2. Erlanger B,
    3. Beaver JA,
    4. Cochran RL,
    5. VanDenBerg DA,
    6. Yakim E,
    7. Cravero K,
    8. Chu D,
    9. Zabransky DJ,
    10. Wong HY,
    11. Croessmann S,
    12. Parsons H,
    13. Hurley PJ,
    14. Lauring J,
    15. Park BH
    . 2015. Comparison of cell stabilizing blood collection tubes for circulating plasma tumor DNA. Clin Biochem 48:993–998. doi:10.1016/j.clinbiochem.2015.07.097.
    OpenUrlCrossRef
  29. 29.↵
    1. Kisat MT
    . 2016. Circulating mitochondrial and bacterial DNA as biomarkers of sepsis. MSc thesis. University of Arizona, Tucson, AZ. https://repository.arizona.edu/bitstream/handle/10150/621839/azu_etd_14986_sip1_m.pdf?sequence=1&isAllowed=y.
  30. 30.↵
    1. Fan HC,
    2. Blumenfeld YJ,
    3. Chitkara U,
    4. Hudgins L,
    5. Quake SR
    . 2008. Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A 105:16266–16271. doi:10.1073/pnas.0808319105.
    OpenUrlAbstract/FREE Full Text
  31. 31.↵
    1. Barra GB,
    2. Santa Rita TH,
    3. de Almeida Vasques J,
    4. Chianca CF,
    5. Nery LF,
    6. Santana Soares Costa S
    . 2015. EDTA-mediated inhibition of DNases protects circulating cell-free DNA from ex vivo degradation in blood samples. Clin Biochem 48:976–981. doi:10.1016/j.clinbiochem.2015.02.014.
    OpenUrlCrossRefPubMed
  32. 32.↵
    1. Beutler E,
    2. Gelbart T,
    3. Kuhl W
    . 1990. Interference of heparin with the polymerase chain reaction. Biotechniques 9:166.
    OpenUrlPubMedWeb of Science
  33. 33.↵
    1. Jung R,
    2. Lubcke C,
    3. Wagener C,
    4. Neumaier M
    . 1997. Reversal of RT-PCR inhibition observed in heparinized clinical specimens. Biotechniques 23:24. doi:10.2144/97231bm03.
    OpenUrlCrossRefPubMedWeb of Science
  34. 34.↵
    1. Färnert A,
    2. Arez AP,
    3. Correia AT,
    4. Björkman A,
    5. Snounou G,
    6. do Rosário V
    . 1999. Sampling and storage of blood and the detection of malaria parasites by polymerase chain reaction. Trans R Soc Trop Med Hyg 93:50–53. doi:10.1016/s0035-9203(99)90177-3.
    OpenUrlCrossRefPubMedWeb of Science
  35. 35.↵
    1. Cook L,
    2. Starr K,
    3. Boonyaratanakornkit J,
    4. Hayden R,
    5. Sam SS,
    6. Caliendo AM
    . 2018. Does size matter? Comparison of extraction yields for different-sized DNA fragments by seven different routine and four new circulating cell-free extraction methods. J Clin Microbiol 56:e01061-18. doi:10.1128/JCM.01061-18.
    OpenUrlAbstract/FREE Full Text
View Abstract
PreviousNext
Back to top
Download PDF
Citation Tools
Investigation of Preanalytical Variables Impacting Pathogen Cell-Free DNA in Blood and Urine
Kanagavel Murugesan, Catherine A. Hogan, Zaida Palmer, Byron Reeve, Grant Theron, Alfred Andama, Akos Somoskovi, Amy Steadman, Damian Madan, Jason Andrews, Julio Croda, Malaya K. Sahoo, Adithya Cattamanchi, Benjamin A. Pinsky, Niaz Banaei
Journal of Clinical Microbiology Oct 2019, 57 (11) e00782-19; DOI: 10.1128/JCM.00782-19

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print

Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this Journal of Clinical Microbiology article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Investigation of Preanalytical Variables Impacting Pathogen Cell-Free DNA in Blood and Urine
(Your Name) has forwarded a page to you from Journal of Clinical Microbiology
(Your Name) thought you would be interested in this article in Journal of Clinical Microbiology.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Investigation of Preanalytical Variables Impacting Pathogen Cell-Free DNA in Blood and Urine
Kanagavel Murugesan, Catherine A. Hogan, Zaida Palmer, Byron Reeve, Grant Theron, Alfred Andama, Akos Somoskovi, Amy Steadman, Damian Madan, Jason Andrews, Julio Croda, Malaya K. Sahoo, Adithya Cattamanchi, Benjamin A. Pinsky, Niaz Banaei
Journal of Clinical Microbiology Oct 2019, 57 (11) e00782-19; DOI: 10.1128/JCM.00782-19
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

cell-free DNA
liquid biopsy
PCR
preanalytical

Related Articles

Cited By...

About

  • About JCM
  • Editor in Chief
  • Board of Editors
  • Editor Conflicts of Interest
  • For Reviewers
  • For the Media
  • For Librarians
  • For Advertisers
  • Alerts
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Article Types
  • Resources for Clinical Microbiologists
  • Ethics
  • Contact Us

Follow #JClinMicro

@ASMicrobiology

       

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

 

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

Print ISSN: 0095-1137; Online ISSN: 1098-660X