Clinical metagenomics bioinformatics pipeline for the identification of hospital-acquired pneumonia pathogens antibiotic resistance genes from bronchoalveolar lavage samples

Tournoud, Maud; Ruppé, Étienne; Perrin, Guillaume; Schicklin, Stéphane; Guigon, Ghislaine; Mahé, Pierre; Lazarevic, Vladimir; Hauser, Sébastien; Mirande, Caroline; Levrat, Albrice; Louis, Karen; Gervasi, Gaspard; Schrenzel, Jacques

doi:10.1101/2020.02.26.966309

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…For the identification of pathogens, sequence reads were analyzed using the metagenomics pipeline described by Jaillard et al ( 30 ) and Tournoud et al [awaiting peer review ( 31 )]. The detection of antibiotic resistance genes was not assessed in this study.…”

Section: Methodsmentioning

confidence: 99%

A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

Hauser,

Lazarevic,

Tournoud

et al. 2023

Microbiol Spectr

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The management of ventilator-associated and hospital-acquired pneumonia requires rapid and accurate quantitative detection of the infecting pathogen(s). To achieve this, we propose a metagenomics next-generation sequencing (mNGS) assay that includes the use of an internal sample processing control (SPC) for the quantitative detection of 20 relevant bacterial species of interest (SOI) from bronchoalveolar lavage (BAL) samples. To avoid very major errors in the identification of respiratory pathogens due to “false-negative” cases, each sample was spiked with Bacillus subtilis , at a precisely defined concentration, using rehydrated BioBall. This SPC ensured the detection and quantification of the pathogen(s) at defined minimum concentrations. In the presented mNGS workflow, absolute quantification of Staphylococcus aureus was as accurate as quantitative PCR. We defined a metagenomics threshold at 5.3 × 10 3 genome equivalent unit per milliliter of the sample for each SOI, to distinguish colonization from higher amounts of pathogens that may be associated with infection. Complete mNGS process and metrics were assessed on 40 clinical samples, showing >99.9% sensitivity compared to microbial culture. However, 19 out of the 29 (66%) SOI detections above the metagenomics threshold were not associated with bacterial growth above classical culture-based clinical thresholds. Taxonomic classification of 7 (37%) of the “false-positive” detections was confirmed by finding specific 16S/MetaPhlAn2 markers, the 12 other “false-positive” detections did not yield enough reads to check their taxonomic classification. Our SPC design and analytical workflow allowed efficient detection and absolute quantification of pathogens from BAL samples, even when the bacterial DNA quantity was largely below the manufacturer’s recommendations for NGS. The frequent “false-positive” detections suggested the presence of nonculturable cells within the tested BAL samples. Furthermore, mNGS detected mixed infections, including bacterial species not reported by routine cultures. IMPORTANCE The management of ventilator-associated pneumonia and hospital-acquired pneumonia requires rapid and accurate quantitative detection of the infecting pathogen. To this end, we propose a metagenomic sequencing assay that includes the use of an internal sample processing control for the quantitative detection of 20 relevant bacterial species from bronchoalveolar lavage samples.

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Section: Methodsmentioning

confidence: 99%

A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

Hauser,

Lazarevic,

Tournoud

et al. 2023

Microbiol Spectr

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“…For identi cation of pathogens, sequence reads were analyzed using the metagenomics pipeline described by Tournoud et al [29,30]. The detection of antibiotic resistance genes (ARG) was not assessed in this study.…”

Section: Bioinformatics Pipelinementioning

confidence: 99%

A Metagenomics Method for the Quantitative Detection of Pathogens Causing Ventilator-Associated Pneumonia

Hauser¹,

Lazarević²,

Tournoud³

et al. 2021

Preprint

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Background The management of ventilator-associated and hospital-acquired pneumonia requires rapid and accurate quantitative detection of the infecting pathogen(s). To do it, we propose a metagenomics next-generation sequencing (mNGS) assay that includes an internal sample processing control (SPC) for the quantitative detection of 20 relevant bacterial species of interest (SOI) from bronchoalveolar lavage (BAL) samples. Results To avoid very major errors in identification of respiratory pathogens due to “false negative” cases, each sample was spiked with Bacillus subtilis, at a precisely defined concentration, using rehydrated BioBall®. This SPC ensured detection and quantification of the pathogen(s) at defined minimum concentrations. In the presented mNGS workflow, absolute quantification of Staphylococcus aureus was as accurate as quantitative PCR. We defined a metagenomics threshold at 5.3E+3 genome equivalent unit per milliliter of the sample for each SOI, to distinguish colonization from higher amounts of pathogens that may be associated with infection. Complete mNGS process and metrics were assessed on 40 clinical samples, showing 100 % sensitivity compared to microbial culture. However, 19 out of the 29 (66 %) SOI detections above the metagenomics threshold were not associated with bacterial growth above classical culture-based clinical thresholds. Taxonomic classification of 7 (37 %) of these “false positive” detections were confirmed by finding specific 16S/MetaPhlAn2 markers, the 12 other (63 %) “false positive” detections did not yield enough reads to check their taxonomic classification. Conclusions Our SPC design and analytical workflow allowed efficient detection and absolute quantification of pathogens from BAL samples, even when the bacterial DNA quantity was largely below manufacturer’s recommendations for NGS. The frequent "false positive" detection suggested the presence of non culturable cells within the tested BAL samples. Finally, mNGS detected mixed infections including bacterial species that were not reported by routine cultures.

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Metagenomics for the microbiological diagnosis of hospital-acquired pneumonia and ventilator-associated pneumonia (HAP/VAP) in intensive care unit (ICU): a proof-of-concept study

Heitz,

Levrat,

Lazarevic

et al. 2023

Respir Res

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Background Hospital-acquired and ventilator-associated-pneumonia (HAP/VAP) are one of the most prevalent health-care associated infections in the intensive care unit (ICU). Culture-independent methods were therefore developed to provide faster route to diagnosis and treatment. Among these, metagenomic next-generation sequencing (mNGS) has shown considerable promise. Methods This proof-of-concept study describes the technical feasibility and evaluates the clinical validity of the mNGS for the detection and characterization of the etiologic agents causing hospital-acquired and ventilator-associated pneumonia. We performed a prospective study of all patients with HAP/VAP hospitalized in our intensive care unit for whom a bronchoalveolar lavage (BAL) was performed between July 2017 and November 2018. We compared BAL fluid culture and mNGS results of these patients. Results A total of 32 BAL fluids were fully analyzed. Of these, 22 (69%) were positive by culture and all pathogens identified were also reported by mNGS. Among the culture-positive BAL samples, additional bacterial species were revealed by mNGS for 12 patients, raising the issue of their pathogenic role (colonization versus coinfection). Among BALF with culture-negative test, 5 were positive in mNGS test. Conclusions This study revealed concordant results for pneumonia panel pathogens between mNGS and culture-positive tests and identified additional pathogens potentially implicated in pneumonia without etiologic diagnosis by culture. mNGS has emerged as a promising methodology for infectious disease diagnoses to support conventional methods. Prospective studies with real-time mNGS are warranted to examine the impact on antimicrobial decision-making and clinical outcome.

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Clinical metagenomics bioinformatics pipeline for the identification of hospital-acquired pneumonia pathogens antibiotic resistance genes from bronchoalveolar lavage samples

Cited by 3 publications

References 49 publications

A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

A Metagenomics Method for the Quantitative Detection of Pathogens Causing Ventilator-Associated Pneumonia

Metagenomics for the microbiological diagnosis of hospital-acquired pneumonia and ventilator-associated pneumonia (HAP/VAP) in intensive care unit (ICU): a proof-of-concept study

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