Evidence map›Paper›PMID 36103272›Full record

ArticleClinical chemistry2022

Identifying Clinically Relevant Bacteria Directly from Culture and Clinical Samples with a Handheld Mass Spectrometry Probe.

Sydney C Povilaitis, Ashish Chakraborty, Lindsey M Kirkpatrick, Rachel D Downey, Sarmistha B Hauger, Livia S Eberlin

Abstract read
In one paragraph

Article in Clinical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Recipient plasma metabolomics as a predictor of heart transplant severe primary graft dysfunction.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026
    Article
  4. Article
  5. Review
  6. "Touch&Play" Wood Typification by the MasSpec Pen.Journal of mass spectrometry : JMS · 2025
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sydney C PovilaitisDepartment of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA.
Ashish ChakrabortyDepartment of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA.
Lindsey M KirkpatrickDepartment of Pediatrics, Division of Pediatric Infectious Diseases, J.W. Riley Hospital for Children, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Rachel D DowneyDepartment of Pediatric Infectious Diseases, Dell Children's Medical Group, Austin, TX 78723, USA.ORCID 0000-0002-3506-4034
Sarmistha B HaugerDepartment of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.
Livia S EberlinDepartment of Surgery, Baylor College of Medicine, Houston, TX 77030, USA.ORCID 0000-0002-3885-3215

Funding

Advanced Development of the MasSpec Pen for Cancer Diagnosis and Surgical Margin EvaluationR33CA229068 · NCI · UNIVERSITY OF TEXAS AT AUSTIN · PI SCHIAVINATO EBERLIN, LIVIA · 2019 to 2021
$1.3M
Development of the MasSpec Pen Technology for Rapid and Accurate Identification of Pediatric InfectionsR21HD106614 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI SCHIAVINATO EBERLIN, LIVIA · 2021 to 2022
$454k
NCI NIH HHS R33 CA229068NICHD NIH HHS R21 HD106614
6 · The paper itself

Abstract

backgroundRapid identification of bacteria is critical to prevent antimicrobial resistance and ensure positive patient outcomes. We have developed the MasSpec Pen, a handheld mass spectrometry-based device that enables rapid analysis of biological samples. Here, we evaluated the MasSpec Pen for identification of bacteria from culture and clinical samples.

methodsA total of 247 molecular profiles were obtained from 43 well-characterized strains of 8 bacteria species that are clinically relevant to osteoarticular infections, including Staphylococcus aureus, Group A and B Streptococcus, and Kingella kingae, using the MasSpec Pen coupled to a high-resolution mass spectrometer. The molecular profiles were used to generate statistical classifiers based on metabolites that were predictive of Gram stain category, genus, and species. Then, we directly analyzed samples from 4 patients, including surgical specimens and clinical isolates, and used the classifiers to predict the etiologic agent.

resultsHigh accuracies were achieved for all levels of classification with a mean accuracy of 93.3% considering training and validation sets. Several biomolecules were detected at varied abundances between classes, many of which were selected as predictive features in the classifiers including glycerophospholipids and quorum-sensing molecules. The classifiers also enabled correct identification of Gram stain type and genus of the etiologic agent from 3 surgical specimens and all classification levels for clinical specimen isolates.

conclusionsThe MasSpec Pen enables identification of several bacteria at different taxonomic levels in seconds from cultured samples and has potential for culture-independent identification of bacteria directly from clinical samples based on the detection of metabolic species.

Indexed as

BacteriaStaphylococcus aureusHumansMass Spectrometrybacteria identificationinfectious diseaseMasSpec Penmass spectrometry

Identifiers

PMID36103272
PMCPMC11610516

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.