Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Innate immune responsiveness predicts enhanced cellular immunity and symptomatic disease after controlled human influenza infection.

Nature medicine·2026
Same author

Educating for translation.

Nature biotechnology·2026
Same author

Influenza coinfection inhibits control of mycobacterial infection in a human challenge model.

Nature communications·2026
Same author

Early immune events during SARS-CoV-2 infection impact memory T and B cell responses.

Communications biology·2026
Same author

Empiric azithromycin alters the upper respiratory microbiome and resistome without anti-inflammatory benefit in COVID-19.

Nature microbiology·2026
Same author

Author Correction: Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors.

Communications medicine·2026

Related Experiment Video

Updated: Nov 7, 2025

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
09:13

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Published on: January 13, 2016

8.2K

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

Ephraim L Tsalik1,2,3,4,5,6,7,8,9,10,11,12,13, Ricardo Henao2,4,5, Jesse L Montgomery6

  • 1Durham Veterans Affairs Health Care System, Durham, NC.

Critical Care Medicine
|May 3, 2021
PubMed
Summary

A new host response test accurately distinguishes bacterial from viral infections in under 45 minutes. This rapid diagnostic tool shows improved performance over procalcitonin, aiding antibiotic stewardship.

More Related Videos

Author Spotlight: Advancing Rapid Detection of Respiratory Pathogens Using Microfluidic Chip
06:11

Author Spotlight: Advancing Rapid Detection of Respiratory Pathogens Using Microfluidic Chip

Published on: March 29, 2024

2.1K
Vaccinia Reporter Viruses for Quantifying Viral Function at All Stages of Gene Expression
10:48

Vaccinia Reporter Viruses for Quantifying Viral Function at All Stages of Gene Expression

Published on: May 15, 2014

11.7K

Related Experiment Videos

Last Updated: Nov 7, 2025

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
09:13

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Published on: January 13, 2016

8.2K
Author Spotlight: Advancing Rapid Detection of Respiratory Pathogens Using Microfluidic Chip
06:11

Author Spotlight: Advancing Rapid Detection of Respiratory Pathogens Using Microfluidic Chip

Published on: March 29, 2024

2.1K
Vaccinia Reporter Viruses for Quantifying Viral Function at All Stages of Gene Expression
10:48

Vaccinia Reporter Viruses for Quantifying Viral Function at All Stages of Gene Expression

Published on: May 15, 2014

11.7K

Area of Science:

  • Infectious disease diagnostics
  • Host response biomarkers
  • Molecular diagnostics

Background:

  • Host gene expression signatures can differentiate bacterial and viral infections.
  • Existing methods lack translation to clinical platforms for rapid diagnosis.
  • This study addresses the need for a validated clinical test for infection type.

Purpose of the Study:

  • To describe and validate a novel, first-in-class host response test for bacterial/viral infections.
  • To evaluate the performance of this test in an independent patient cohort.
  • To compare the test's efficacy against procalcitonin and clinical adjudication.

Main Methods:

  • Recruited 623 subjects with acute respiratory illness or suspected sepsis from 2006-2016.
  • Utilized a 45-transcript signature measured on the BioFire FilmArray System.
  • Reference standard was expert panel clinical adjudication, blinded to molecular results.

Main Results:

  • The host response test achieved an Area Under the Curve (AUC) of 0.85 for bacterial and 0.91 for viral infection in validation.
  • Demonstrated average weighted accuracy of 80.1% for bacterial and 86.8% for viral infections.
  • Significantly outperformed procalcitonin (68.7% accuracy) with p < 0.001.

Conclusions:

  • The BioFire-based host response test rapidly and accurately discriminates bacterial from viral infections.
  • This diagnostic capability surpasses procalcitonin performance.
  • The test supports more appropriate antibiotic use by clarifying infection etiology.