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

Abstract

BackgroundUnderlying 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.MethodsWe 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).ResultsF. 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.ConclusionOur 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.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3218-2) contains supplementary material, which is available to authorized users.

Non-SARS-CoV-2 genome sequences identified in clinical samples from COVID-19 infected patients: Evidence for co-infections

“…The importance of detecting co-infections is becoming more recognized (Griffiths et al, 2011;Li & Zhou, 2013), but it remains challenging to get such information. The source of clinical samples and the sequencing technology can be inferior in co-infection detection (Birdsell et al, 2018).…”

“…Therefore, exploring new diagnostic approaches is essential to advance understanding of co-infection contribution to disease manifestations and treatment responses (Birdsell et al, 2018).…”

Peer Review #1 of "Non-SARS-CoV-2 genome sequences identified in clinical samples from COVID-19 infected patients: Evidence for co-infections (v0.1)"

“…Therefore, exploring new diagnostic approaches is essential to advance understanding of coinfection contribution to disease manifestations and treatment responses (Birdsell et al 2018a).…”

Peer Review #2 of "Non-SARS-CoV-2 genome sequences identified in clinical samples from COVID-19 infected patients: Evidence for co-infections (v0.2)"

“…The importance of detecting co-infections is becoming more recognized (Griffiths et al 2011;Li & Zhou 2013), but it remains challenging to get such information. The source of clinical samples and the sequencing technology can be inferior in co-infection detection (Birdsell et al 2018b).…”