Evidence map›Paper›PMID 40067770›Full record

ArticleClinical chemistry2025

Enrichment of Microbial DNA in Plasma to Improve Pathogen Detection in Sepsis: A Pilot Study.

Eddie G Dominguez, Bradon R McDonald, Haikun Zhang, Michelle D Stephens, Elise C Dietmann, Megan Nedden, Nicole Byington, Sydney Thompson, Mary Junak, Caitlin S Pepperell and 1 more

Abstract read
In one paragraph

Article in Clinical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Eddie G DominguezDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.ORCID 0000-0002-6810-8670
Bradon R McDonaldDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Haikun ZhangDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Michelle D StephensDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Elise C DietmannDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Megan NeddenDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Nicole ByingtonDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Sydney ThompsonDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Mary JunakDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Caitlin S PepperellDepartment of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.
Mehreen T KisatDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States.

Funding

Drifting to victory: resolving the paradox of M.tuberculosis evolutionR01AI113287 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI Caitlin S Pepperell · 2015 to 2026
$6.5M
Improving diagnosis of post-traumatic sepsis using plasma microbial DNA sequencingK08GM148858 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Mehreen T Kisat · 2023 to 2026
$762k
NIAID NIH HHS R01 AI113287NIGMS NIH HHS K08 GM148858NIH HHS K08GM148858NIH/NIAID R01-AI113287the American Association for Surgery of Trauma Research and Education Fund Trauma Critical Care Scholarship
6 · The paper itself

Abstract

backgroundDiagnosis of sepsis and timely identification of pathogens in critically ill patients remains challenging. Plasma metagenomic sequencing to detect microbial cell-free DNA (mDNA) has shown promise, but low abundance of mDNA in plasma limits sensitivity and necessitates high sequencing depth. mDNA is shorter and more fragmented than human cell-free DNA. Here, we evaluated whether combining single-stranded DNA (ssDNA) sequencing library preparation and size selection can enrich mDNA and improve pathogen detection.

methodsWe prospectively enrolled 48 trauma patients and collected daily blood samples during the first 10 days of intensive care unit (ICU) admission. For patients with culture-proven infections, we extracted plasma DNA, prepared double-stranded DNA (dsDNA) and ssDNA sequencing libraries, and applied size selection to exclude fragments >110 bp. Following sequencing, we performed taxonomic classification, and evaluated differences in mDNA fractions and in sensitivity for pathogen detection (compared to background noise).

resultsWe analyzed 46 plasma samples from 5 patients who developed culture-proven infections, including 17 samples coincident with positive microbial cultures. Size-selected ssDNA libraries showed the total mDNA fraction 204-fold higher on average than conventional dsDNA libraries (P < 0.0001). However, for pathogen-specific DNA (at the genus level), the highest sensitivity was observed in size-selected dsDNA (82%), compared to dsDNA (41%), ssDNA (71%), and size-selected ssDNA (35%) library preparations.

conclusionsOur results demonstrate that combining ssDNA library preparation together with fragment size selection improves mDNA yield, potentially reducing sequencing requirements. However, at the genus level, this combination also increases background noise, which limits sensitivity for pathogen detection.

Indexed as

Cell-Free Nucleic AcidsDNA, BacterialSepsisAgedDNA, Single-StrandedFemaleHumansMaleMiddle AgedPilot ProjectsProspective StudiesCell-Free Nucleic AcidsDNA, BacterialDNA, Single-Stranded

Identifiers

PMID40067770
PMCPMC12702648

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.