Effect of seven anti-tuberculosis treatment regimens on sputum microbiome: a retrospective analysis of the HIGHRIF study 2 and PanACEA MAMS-TB clinical trials.


Journal

The Lancet. Microbe
ISSN: 2666-5247
Titre abrégé: Lancet Microbe
Pays: England
ID NLM: 101769019

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 27 07 2022
revised: 18 05 2023
accepted: 14 06 2023
medline: 6 11 2023
pubmed: 14 10 2023
entrez: 13 10 2023
Statut: ppublish

Résumé

Respiratory tract microbiota has been described as the gatekeeper for respiratory health. We aimed to assess the impact of standard-of-care and experimental anti-tuberculosis treatment regimens on the respiratory microbiome and implications for treatment outcomes. In this retrospective study, we analysed the sputum microbiome of participants with tuberculosis treated with six experimental regimens versus standard-of-care who were part of the HIGHRIF study 2 (NCT00760149) and PanACEA MAMS-TB (NCT01785186) clinical trials across a 3-month treatment follow-up period. Samples were from participants in Mbeya, Kilimanjaro, Bagamoyo, and Dar es Salaam, Tanzania. Experimental regimens were composed of different combinations of rifampicin (R), isoniazid (H), pyrazinamide (Z), ethambutol (E), moxifloxacin (M), and a new drug, SQ109 (Q). Reverse transcription was used to create complementary DNA for each participant's total sputum RNA and the V3-V4 region of the 16S rRNA gene was sequenced using the Illumina metagenomic technique. Qiime was used to analyse the amplicon sequence variants and estimate alpha diversity. Descriptive statistics were applied to assess differences in alpha diversity pre-treatment and post-treatment initiation and the effect of each treatment regimen. Sequence data were obtained from 397 pre-treatment and post-treatment samples taken between Sept 26, 2008, and June 30, 2015, across seven treatment regimens. Pre-treatment microbiome (206 genera) was dominated by Firmicutes (2860 [44%] of 6500 amplicon sequence variants [ASVs]) at the phylum level and Streptococcus (2340 [36%] ASVs) at the genus level. Two regimens had a significant depressing effect on the microbiome after 2 weeks of treatment, HR HR European and Developing Countries Clinical Trials Partnership and German Ministry of Education and Research.

Sections du résumé

BACKGROUND BACKGROUND
Respiratory tract microbiota has been described as the gatekeeper for respiratory health. We aimed to assess the impact of standard-of-care and experimental anti-tuberculosis treatment regimens on the respiratory microbiome and implications for treatment outcomes.
METHODS METHODS
In this retrospective study, we analysed the sputum microbiome of participants with tuberculosis treated with six experimental regimens versus standard-of-care who were part of the HIGHRIF study 2 (NCT00760149) and PanACEA MAMS-TB (NCT01785186) clinical trials across a 3-month treatment follow-up period. Samples were from participants in Mbeya, Kilimanjaro, Bagamoyo, and Dar es Salaam, Tanzania. Experimental regimens were composed of different combinations of rifampicin (R), isoniazid (H), pyrazinamide (Z), ethambutol (E), moxifloxacin (M), and a new drug, SQ109 (Q). Reverse transcription was used to create complementary DNA for each participant's total sputum RNA and the V3-V4 region of the 16S rRNA gene was sequenced using the Illumina metagenomic technique. Qiime was used to analyse the amplicon sequence variants and estimate alpha diversity. Descriptive statistics were applied to assess differences in alpha diversity pre-treatment and post-treatment initiation and the effect of each treatment regimen.
FINDINGS RESULTS
Sequence data were obtained from 397 pre-treatment and post-treatment samples taken between Sept 26, 2008, and June 30, 2015, across seven treatment regimens. Pre-treatment microbiome (206 genera) was dominated by Firmicutes (2860 [44%] of 6500 amplicon sequence variants [ASVs]) at the phylum level and Streptococcus (2340 [36%] ASVs) at the genus level. Two regimens had a significant depressing effect on the microbiome after 2 weeks of treatment, HR
INTERPRETATION CONCLUSIONS
HR
FUNDING BACKGROUND
European and Developing Countries Clinical Trials Partnership and German Ministry of Education and Research.

Identifiants

pubmed: 37832571
pii: S2666-5247(23)00191-X
doi: 10.1016/S2666-5247(23)00191-X
pii:
doi:

Substances chimiques

Antitubercular Agents 0
Moxifloxacin U188XYD42P
RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e913-e922

Investigateurs

Emmanuel Musisi (E)
Bariki Mtafya (B)
Nyanda E Ntinginya (NE)
Norbert Heinrich (N)
Gibson S Kibiki (GS)
Michael Hoelscher (M)
Martin Boeree (M)
Stephen Gillespie (S)
Wilber Sabiiti (W)
Derek Sloan (D)
Larissa Hoffmann (L)
Ivan Noreña (I)
Wandini Lutchmun (W)
Julia Dreisbach (J)
Petra Gross Demel (PG)
Andrea Kelly (A)
Lindsey Te Brake (LT)
Elin Svensson (E)
Rob Aarnoutse (R)
Isobella Honeyborne (I)
Leticia Muraro Wildner (LM)
Robert Hunt (R)
Timothy D McHugh (TD)
Andrew J Nunn (AJ)
Patrick P J Phillips (PPJ)
Xue Gong (X)
Rodney Dawson (R)
Kim Narunsky (K)
Andreas Diacon (A)
Veronique de Jager (V)
Sven Friedrich (S)
Ian Sanne (I)
Mohammed Rassool (M)
Chacha Mangu (C)
Christina Manyama (C)
Issa Sabi (I)
Lilian T Minja (LT)
Francis Mhimbira (F)
Benno Mbeya (B)
Mohamed Sasamalo (M)
Klaus Reither (K)
Levan Jugheli (L)
Noel Sam (N)
Hadija Semvua (H)
Stellah Mpagama (S)
Alphonce Liyoyo (A)
Blandina T Mmbaga (BT)
Bayode Romeo Adegbite (BR)
Ayola Akim Adegnika (AA)
Martin Peter Grobusch (MP)
Martin P Grobusch (MP)
Bayode Romeo Adegbite (BR)
Bruce Kirenga (B)
Willy Ssengooba (W)
Moses Joloba (M)
Celso Khosa (C)
Isabel Massango (I)
Khalide Azam (K)
Ilesh Jani (I)
Mariott Nliwasa (M)
Hussein Hassan Twabi (HH)
Madalo Mukoka (M)
Chisomo L Msefula (CL)

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests WS and SHG provide pro bono advice for a company that is developing tuberculosis molecular bacterial load assay for clinical use. All other authors declare no competing interests.

Auteurs

Emmanuel Musisi (E)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK.

Adam Wyness (A)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK; Scottish Association of Marine Science, Oban, UK.

Sahar Eldirdiri (S)

Department of Microbiology, Kettering General Hospital, Kettering, UK.

Evelin Dombay (E)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK.

Bariki Mtafya (B)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK; National Institute for Medical Research, Mbeya Medical Research Centre, Mbeya, Tanzania.

Nyanda E Ntinginya (NE)

National Institute for Medical Research, Mbeya Medical Research Centre, Mbeya, Tanzania.

Norbert Heinrich (N)

Division of Infectious Diseases and Tropical Medicine, University Hospital, University of Munich (LMU), Munich, Germany.

Gibson S Kibiki (GS)

Kilimanjaro Clinical Research Institute, Moshi, Tanzania; Africa Research Excellence Fund (AREF), London, UK.

Michael Hoelscher (M)

Division of Infectious Diseases and Tropical Medicine, University Hospital, University of Munich (LMU), Munich, Germany; Fraunhofer ITMP, Immunology, Infection and Pandemic Research, Munich, Germany.

Martin Boeree (M)

Department of Lung Diseases, Radboud University Medical Centre, Nijmegen, Netherlands.

Rob Aarnoutse (R)

Department of Pharmacy, Radboud University Medical Centre, Nijmegen, Netherlands.

Stephen H Gillespie (SH)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK.

Wilber Sabiiti (W)

Division of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK. Electronic address: ws31@st-andrews.ac.uk.

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Classifications MeSH