Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples
Background: Currently, diagnosis of bacterial infections is based on culture, possibly followed by the amplification and sequencing (Sanger method) of the 16S rDNA - encoding gene when cultures are negative. Clinical metagenomics (CMg), i.e. the sequencing of a sample’s entire nucleic acids, may all...
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Elsevier
2025-03-01
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| Series: | International Journal of Medical Microbiology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1438422125000062 |
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| author | Camille d’Humières Skerdi Haviari Marie Petitjean Laurène Deconinck Signara Gueye Nathan Peiffer-Smadja Lynda Chalal Naima Beldjoudi Geoffrey Rossi Yann Nguyen Charles Burdet Ségolène Perrineau Diane Le Pluart Roza Rahli Michael Thy Piotr Szychowiak Xavier Lescure Véronique Leflon-Guibout Victoire de Lastours Etienne Ruppé |
| author_facet | Camille d’Humières Skerdi Haviari Marie Petitjean Laurène Deconinck Signara Gueye Nathan Peiffer-Smadja Lynda Chalal Naima Beldjoudi Geoffrey Rossi Yann Nguyen Charles Burdet Ségolène Perrineau Diane Le Pluart Roza Rahli Michael Thy Piotr Szychowiak Xavier Lescure Véronique Leflon-Guibout Victoire de Lastours Etienne Ruppé |
| author_sort | Camille d’Humières |
| collection | DOAJ |
| description | Background: Currently, diagnosis of bacterial infections is based on culture, possibly followed by the amplification and sequencing (Sanger method) of the 16S rDNA - encoding gene when cultures are negative. Clinical metagenomics (CMg), i.e. the sequencing of a sample’s entire nucleic acids, may allow for the identification of bacteria not detected by conventional methods. Here, we tested the performance of CMg compared to 16S rDNA sequencing (Sanger) in 50 patients with suspected bacterial infection but negative cultures. Methods: This is a prospective cohort study. Fifty patients (73 samples) with negative culture and a 16S rDNA sequencing demand (Sanger) were recruited from two sites. On the same samples, CMg (Illumina NextSeq) was also performed and compared to 16S rDNA Sanger sequencing. Bacteria were identified using MetaPhlAn4. Results: Among the 73 samples, 20 (27 %, 17 patients) had a clinically relevant 16S rDNA Sanger sequencing result (used for patient management) while 11 (15 %, 9 patients) were considered contaminants. At the patient level, the sensitivity of CMg was 70 % (12/17) compared to 16S rDNA. In samples negative for 16S rDNA Sanger sequencing (n = 53), CMg identified clinically-relevant bacteria in 10 samples (19 %, 10 patients) with 14 additional bacteria. Conclusions: CMg was not 100 % sensitive when compared to 16S, supporting that it may not be a suitable replacement. However, CMg did find additional bacteria in samples negative for 16S rDNA Sanger. CMg could therefore be positioned as a complementary to 16S rDNA Sanger sequencing. |
| format | Article |
| id | doaj-art-0f3dff558e634d17805da54e090129f1 |
| institution | Kabale University |
| issn | 1438-4221 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Medical Microbiology |
| spelling | doaj-art-0f3dff558e634d17805da54e090129f12025-02-12T05:30:45ZengElsevierInternational Journal of Medical Microbiology1438-42212025-03-01318151650Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samplesCamille d’Humières0Skerdi Haviari1Marie Petitjean2Laurène Deconinck3Signara Gueye4Nathan Peiffer-Smadja5Lynda Chalal6Naima Beldjoudi7Geoffrey Rossi8Yann Nguyen9Charles Burdet10Ségolène Perrineau11Diane Le Pluart12Roza Rahli13Michael Thy14Piotr Szychowiak15Xavier Lescure16Véronique Leflon-Guibout17Victoire de Lastours18Etienne Ruppé19AP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Bactériologie, Paris F-75018, France; Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; AP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Bactériologie, Paris F-75018, France; Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Bactériologie, Paris F-75018, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; AP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; AP-HP, Hôpital Bichat-Claude Bernard, Département Epidémiologie Biostatistiques et Recherche Clinique, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceAP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceAP-HP, Hôpital Beaujon, Service de Médecine Interne, Clichy F-92110, FranceAP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; AP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris F-75018, FranceAP-HP, Hôpital Beaujon, Laboratoire de Microbiologie, Clichy F-92110, FranceUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; AP-HP, Hôpital Beaujon, Service de Médecine Interne, Clichy F-92110, FranceAP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Bactériologie, Paris F-75018, France; Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris F-75018, France; Corresponding author at: Laboratoire de Bactériologie, Hôpital Bichat-Claude Bernard, 46 rue Henri Huchard, Paris 75018, France.Background: Currently, diagnosis of bacterial infections is based on culture, possibly followed by the amplification and sequencing (Sanger method) of the 16S rDNA - encoding gene when cultures are negative. Clinical metagenomics (CMg), i.e. the sequencing of a sample’s entire nucleic acids, may allow for the identification of bacteria not detected by conventional methods. Here, we tested the performance of CMg compared to 16S rDNA sequencing (Sanger) in 50 patients with suspected bacterial infection but negative cultures. Methods: This is a prospective cohort study. Fifty patients (73 samples) with negative culture and a 16S rDNA sequencing demand (Sanger) were recruited from two sites. On the same samples, CMg (Illumina NextSeq) was also performed and compared to 16S rDNA Sanger sequencing. Bacteria were identified using MetaPhlAn4. Results: Among the 73 samples, 20 (27 %, 17 patients) had a clinically relevant 16S rDNA Sanger sequencing result (used for patient management) while 11 (15 %, 9 patients) were considered contaminants. At the patient level, the sensitivity of CMg was 70 % (12/17) compared to 16S rDNA. In samples negative for 16S rDNA Sanger sequencing (n = 53), CMg identified clinically-relevant bacteria in 10 samples (19 %, 10 patients) with 14 additional bacteria. Conclusions: CMg was not 100 % sensitive when compared to 16S, supporting that it may not be a suitable replacement. However, CMg did find additional bacteria in samples negative for 16S rDNA Sanger. CMg could therefore be positioned as a complementary to 16S rDNA Sanger sequencing.http://www.sciencedirect.com/science/article/pii/S1438422125000062Clinical metagenomics16SDiagnosisBacterial infections |
| spellingShingle | Camille d’Humières Skerdi Haviari Marie Petitjean Laurène Deconinck Signara Gueye Nathan Peiffer-Smadja Lynda Chalal Naima Beldjoudi Geoffrey Rossi Yann Nguyen Charles Burdet Ségolène Perrineau Diane Le Pluart Roza Rahli Michael Thy Piotr Szychowiak Xavier Lescure Véronique Leflon-Guibout Victoire de Lastours Etienne Ruppé Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples International Journal of Medical Microbiology Clinical metagenomics 16S Diagnosis Bacterial infections |
| title | Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples |
| title_full | Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples |
| title_fullStr | Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples |
| title_full_unstemmed | Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples |
| title_short | Comparison of clinical metagenomics with 16S rDNA Sanger sequencing for the bacteriological diagnosis of culture-negative samples |
| title_sort | comparison of clinical metagenomics with 16s rdna sanger sequencing for the bacteriological diagnosis of culture negative samples |
| topic | Clinical metagenomics 16S Diagnosis Bacterial infections |
| url | http://www.sciencedirect.com/science/article/pii/S1438422125000062 |
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