Add like
Add dislike
Add to saved papers

Coinfections identified from metagenomic analysis of cervical lymph nodes from tularemia patients.

BACKGROUND: Underlying coinfections may complicate infectious disease states but commonly go unnoticed because an a priori clinical suspicion is usually required so they can be detected via targeted diagnostic tools. Shotgun metagenomics is a broad diagnostic tool that can be useful for identifying multiple microbes simultaneously especially if coupled with lymph node aspirates, a clinical matrix known to house disparate pathogens. The objective of this study was to analyze the utility of this unconventional diagnostic approach (shotgun metagenomics) using clinical samples from human tularemia cases as a test model. Tularemia, caused by the bacterium Francisella tularensis, is an emerging infectious disease in Turkey. This disease commonly manifests as swelling of the lymph nodes nearest to the entry of infection. Because swollen cervical nodes are observed from many different types of human infections we used these clinical sample types to analyze the utility of shotgun metagenomics.

METHODS: We conducted an unbiased molecular survey using shotgun metagenomics sequencing of DNA extracts from fine-needle aspirates of neck lymph nodes from eight tularemia patients who displayed protracted symptoms. The resulting metagenomics data were searched for microbial sequences (bacterial and viral).

RESULTS: F. tularensis sequences were detected in all samples. In addition, we detected DNA of other known pathogens in three patients. Both Hepatitis B virus (HBV) and Human Parvovirus B-19 were detected in one individual and Human Parvovirus B-19 alone was detected in two other individuals. Subsequent PCR coupled with Sanger sequencing verified the metagenomics results. The HBV status was independently confirmed via serological diagnostics, despite evading notice during the initial assessment.

CONCLUSION: Our data highlight that shotgun metagenomics of fine-needle lymph node aspirates is a promising clinical diagnostic strategy to identify coinfections. Given the feasibility of the diagnostic approach demonstrated here, further steps to promote integration of this type of diagnostic capability into mainstream clinical practice are warranted.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app