Subtracting the background by reducing cell-free DNA's confounding effects on Mycobacterium tuberculosis quantitation and the sputum microbiome.

Humans Mycobacterium tuberculosis / genetics Sputum / microbiology Microbiota / drug effects Cell-Free Nucleic Acids RNA, Ribosomal, 16S / genetics DNA, Bacterial / genetics Tuberculosis / microbiology Female Male Adult Middle Aged Azides / pharmacology Tuberculosis, Pulmonary / microbiology Propidium / analogs & derivatives
Mycobacterium tuberculosis DNaseI PEMAX Propidium monoazide Sputum microbiome Xpert MTB/RIF

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
27 Sep 2024
Historique:
received: 14 06 2024
accepted: 18 09 2024
medline: 28 9 2024
pubmed: 28 9 2024
entrez: 27 9 2024
Statut: epublish

Résumé

DNA characterisation in people with tuberculosis (TB) is critical for diagnostic and microbiome evaluations. However, extracellular DNA, more frequent in people on chemotherapy, confounds results. We evaluated whether nucleic acid dyes [propidium monoazide (PMA), PEMAX] and DNaseI could reduce this. PCR [16S Mycobacterium tuberculosis complex (Mtb) qPCR, Xpert MTB/RIF] was done on dilution series of untreated and treated (PMA, PEMAX, DNaseI) Mtb. Separately, 16S rRNA gene qPCR and sequencing were done on untreated and treated sputa before (Cohort A: 11 TB-negatives, 9 TB-positives; Cohort B: 19 TB-positives, PEMAX only) and 24-weeks after chemotherapy (Cohort B). PMA and PEMAX reduced PCR-detected Mtb DNA for dilution series and Cohort A sputum versus untreated controls, suggesting non-intact Mtb is present before treatment-start. PEMAX enabled sequencing-based Mycobacterium-detection in 7/12 (58%) TB-positive sputa where no such reads otherwise occurred. In Cohort A, PMA- and PEMAX-treated versus untreated sputa had decreased α- and increased β-diversities. In Cohort B, β-diversity differences between timepoints were only detected with PEMAX. DNaseI had negligible effects. PMA and PEMAX (but not DNaseI) reduced extracellular DNA in PCR and improved pathogen detection by sequencing. PEMAX additionally detected chemotherapy-associated taxonomic changes that would otherwise be missed. Dyes enhance microbiome evaluations especially during chemotherapy.

Identifiants

DOI: 10.1038/s41598-024-73497-3 PMID: 39333362
pubmed: 39333362
doi: 10.1038/s41598-024-73497-3
pii: 10.1038/s41598-024-73497-3
doi:

Substances chimiques

Cell-Free Nucleic Acids 0
RNA, Ribosomal, 16S 0
DNA, Bacterial 0
propidium monoazide 0
Azides 0
Propidium 36015-30-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

22350

Subventions

Organisme : NIH HHS
ID : K43TW012302
Pays : United States
Organisme : NIH HHS
ID : R01AI136894
Pays : United States
Organisme : National Research Foundation
ID : 98948
Organisme : European and Developing Countries Clinical Trials Partnership
ID : SF1041

Informations de copyright

© 2024. The Author(s).

Références

Bouskra, D. et al. Lymphoid tissue genesis induced by commensals through NOD1 regulates intestinal homeostasis. Nature456 (7221), 507–510 (2008).
pubmed: 18987631 doi: 10.1038/nature07450
VanEvery, H. et al. Microbiome epidemiology and association studies in human health. Nat. Rev. Genet.24 (2), 109–124 (2023).
pubmed: 36198908 doi: 10.1038/s41576-022-00529-x
Wen, J. & He, J. Q. The causal impact of the gut microbiota on respiratory tuberculosis susceptibility. Infect. Dis. Ther.12 (11), 2535–2544 (2023).
pubmed: 37815754 pmcid: 10651823 doi: 10.1007/s40121-023-00880-4
Wipperman, M. F. et al. Gastrointestinal microbiota composition predicts peripheral inflammatory state during treatment of human tuberculosis. Nat. Commun.12 (1), 1141 (2021).
pubmed: 33602926 pmcid: 7892575 doi: 10.1038/s41467-021-21475-y
Musisi, E. et al. Effect of seven anti-tuberculosis treatment regimens on sputum microbiome: a retrospective analysis of the HIGHRIF study 2 and PanACEA MAMS-TB clinical trials. Lancet Microbe4 (11), e913–e922 (2023).
pubmed: 37832571 doi: 10.1016/S2666-5247(23)00191-X
Wipperman, M. F. et al. Antibiotic treatment for tuberculosis induces a profound dysbiosis of the microbiome that persists long after therapy is completed. Sci. Rep.7 (1), 10767 (2017).
pubmed: 28883399 pmcid: 5589918 doi: 10.1038/s41598-017-10346-6
Global tuberculosis report 2023. Geneva: World Health Organization (2023).
Theron, G. et al. Xpert MTB/RIF results in patients with previous tuberculosis: can we distinguish true from false positive results? Clin. Infect. Dis.62 (8), 995–1001 (2016).
pubmed: 26908793 pmcid: 4803105 doi: 10.1093/cid/civ1223
Mishra, H. et al. Xpert MTB/RIF Ultra and Xpert MTB/RIF for diagnosis of tuberculosis in an HIV-endemic setting with a high burden of previous tuberculosis: a two-cohort diagnostic accuracy study. Lancet Respir. Med.8 (4), 368–382 (2020).
pubmed: 32066534 doi: 10.1016/S2213-2600(19)30370-4
Theron, G. et al. False-positive Xpert MTB/RIF results in retested patients with previous tuberculosis: frequency, profile, and prospective clinical outcomes. J. Clin. Microbiol.56 (3) (2018).
Jacobs, R. et al. Identification of novel host biomarkers in plasma as candidates for the immunodiagnosis of tuberculosis disease and monitoring of tuberculosis treatment response. Oncotarget7 (36), 57581 (2016).
pubmed: 27557501 pmcid: 5295374 doi: 10.18632/oncotarget.11420
Goletti, D. et al. Can we predict tuberculosis cure? What tools are available? Eur. Respir. J.52 (5) (2018).
Namasivayam, S. et al. Longitudinal profiling reveals a persistent intestinal dysbiosis triggered by conventional anti-tuberculosis therapy. Microbiome5 (1), 1–17 (2017).
doi: 10.1186/s40168-017-0286-2
Burdet, C. et al. Impact of antibiotic gut exposure on the temporal changes in microbiome diversity. Antimicrob. Agents Chemother.63 (10) (2019).
Rogers, G. et al. The exclusion of dead bacterial cells is essential for accurate molecular analysis of clinical samples. Clin. Microbiol. Infect.16 (11), 1656–1658 (2010).
pubmed: 20148918 doi: 10.1111/j.1469-0691.2010.03189.x
Agustí, G. et al. Viability determination of Helicobacter pylori using propidium monoazide quantitative PCR. Helicobacter15 (5), 473–476 (2010).
pubmed: 21083754 doi: 10.1111/j.1523-5378.2010.00794.x
Rawsthorne, H., Dock, C. & Jaykus, L. PCR-based method using propidium monoazide to distinguish viable from nonviable Bacillus subtilis spores. Appl. Environ. Microbiol.75 (9), 2936–2939 (2009).
pubmed: 19270144 pmcid: 2681676 doi: 10.1128/AEM.02524-08
Vesper, S. et al. Quantifying fungal viability in air and water samples using quantitative PCR after treatment with propidium monoazide (PMA). J. Microbiol. Methods72 (2), 180–184 (2008).
pubmed: 18160156 doi: 10.1016/j.mimet.2007.11.017
Agustí, G., Fittipaldi, M. & Codony, F. False-positive viability PCR results: an association with microtubes. Curr. Microbiol.74 (3), 377–380 (2017).
pubmed: 28175959 doi: 10.1007/s00284-016-1189-3
Wagner, A. O. et al. Removal of free extracellular DNA from environmental samples by ethidium monoazide and propidium monoazide. Appl. Environ. Microbiol.74 (8), 2537–2539 (2008).
pubmed: 18296534 pmcid: 2293149 doi: 10.1128/AEM.02288-07
Vondrakova, L. et al. Impact of various killing methods on EMA/PMA-qPCR efficacy. Food Control85, 23–28 (2018).
doi: 10.1016/j.foodcont.2017.09.013
Kragh, M. L., Thykier, M. & Hansen, L. T. A long-amplicon quantitative PCR assay with propidium monoazide to enumerate viable Listeria monocytogenes after heat and desiccation treatments. Food Microbiol.86, 103310 (2020).
pubmed: 31703859 doi: 10.1016/j.fm.2019.103310
Cuthbertson, L. et al. Implications of multiple freeze-thawing on respiratory samples for culture-independent analyses. J. Cyst. Fibros.14 (4), 464–467 (2015).
pubmed: 25459563 doi: 10.1016/j.jcf.2014.10.004
Nocker, A. et al. Use of propidium monoazide for live/dead distinction in microbial ecology. Appl. Environ. Microbiol.73 (16), 5111–5117 (2007).
pubmed: 17586667 pmcid: 1951001 doi: 10.1128/AEM.02987-06
Nocker, A., Cheung, C. Y. & Camper, A. K. Comparison of propidium monoazide with ethidium monoazide for differentiation of live vs. dead bacteria by selective removal of DNA from dead cells. J. Microbiol. Methods67 (2), 310–320 (2006).
pubmed: 16753236 doi: 10.1016/j.mimet.2006.04.015
Hortelano, I. et al. Optimization of pre-treatments with Propidium Monoazide and PEMAX™ before real-time quantitative PCR for detection and quantification of viable Helicobacter pylori cells. J. Microbiol. Methods185, 106223 (2021).
pubmed: 33872638 doi: 10.1016/j.mimet.2021.106223
Kayigire, X. A. et al. Propidium monoazide and Xpert MTB/RIF to quantify Mycobacterium tuberculosis cells. Tuberculosis101, 79–84 (2016).
pubmed: 27865403 doi: 10.1016/j.tube.2016.08.006
Nikolayevskyy, V. et al. Utility of propidium monoazide viability assay as a biomarker for a tuberculosis disease. Tuberculosis95 (2), 179–185 (2015).
pubmed: 25534168 doi: 10.1016/j.tube.2014.11.005
Kim, Y. J. et al. Evaluation of propidium monoazide real-time PCR for early detection of viable Mycobacterium tuberculosis in clinical respiratory specimens. Ann. Lab. Med.34 (3), 203 (2014).
pubmed: 24790907 pmcid: 3999318 doi: 10.3343/alm.2014.34.3.203
de Assunção, T. M. et al. Real time PCR quantification of viable Mycobacterium tuberculosis from sputum samples treated with propidium monoazide. Tuberculosis94 (4), 421–427 (2014).
pubmed: 24863654 doi: 10.1016/j.tube.2014.04.008
Miotto, P. et al. Early tuberculosis treatment monitoring by Xpert
pubmed: 22547737 doi: 10.1183/09031936.00124711
Lu, J. et al. Direct detection from clinical sputum samples to differentiate live and dead Mycobacterium tuberculosis. J. Clin. Lab. Anal.33 (3), e22716 (2019).
pubmed: 30461054 doi: 10.1002/jcla.22716
Esmail, A. et al. An all-oral 6-month regimen for multidrug-resistant tuberculosis: a multicenter, randomized controlled clinical trial (the NExT study). Am. J. Respir. Crit Care Med.205 (10), 1214–1227 (2022).
pubmed: 35175905 doi: 10.1164/rccm.202107-1779OC
Invitrogen. PureLink™ Microbiome DNA Purification Kit. Pub. No. MAN0014267 Rev. A.0.
Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci.108 (Supplement 1), 4516–4522 (2011).
pubmed: 20534432 doi: 10.1073/pnas.1000080107
GenIUL PEMAX 25 Reagent Monodose (TBC-Biomarker kit) INSTRUCTIONS in Doc Code 450000075-00 (2015).
Segal, L. N. et al. Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype. Nat. Microbiol.1 (5), 1–11 (2016).
doi: 10.1038/nmicrobiol.2016.31
Segal, L. N. et al. Anaerobic Bacterial Fermentation Products Increase Tuberculosis Risk in Antiretroviral-Drug-Treated HIV Patients (Cell Host & Microbe, 2017).
Tsay, J. C. J. et al. Airway Microbiota is associated with upregulation of the PI3K pathway in lung cancer. Am. J. Respir. Crit Care Med.198 (9), 1188–1198 (2018).
pubmed: 29864375 pmcid: 6221574 doi: 10.1164/rccm.201710-2118OC
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol.37 (8), 852–857 (2019).
pubmed: 31341288 pmcid: 7015180 doi: 10.1038/s41587-019-0209-9
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods13 (7), 581–583 (2016).
pubmed: 27214047 pmcid: 4927377 doi: 10.1038/nmeth.3869
McDonald, D. et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J.6 (3), 610–618 (2012).
pubmed: 22134646 doi: 10.1038/ismej.2011.139
Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J.6 (8), 1621–1624 (2012).
pubmed: 22402401 pmcid: 3400413 doi: 10.1038/ismej.2012.8
Davis, N. M. et al. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome6, 1–14 (2018).
doi: 10.1186/s40168-018-0605-2
Oksanen, J. et al. The vegan package. Community Ecol. Pack.10, 631–637 (2007).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of Fold change and dispersion for RNA-seq data with DESeq2. Genome Biol.15 (12), 550 (2014).
pubmed: 25516281 pmcid: 4302049 doi: 10.1186/s13059-014-0550-8
Elizaquível, P., Aznar, R. & Sánchez, G. Recent developments in the use of viability dyes and quantitative PCR in the food microbiology field. J. Appl. Microbiol.116 (1), 1–13 (2014).
pubmed: 24119073 doi: 10.1111/jam.12365
Kim, Y. J. et al. Evaluation of propidium monoazide real-time PCR for early detection of viable Mycobacterium tuberculosis in clinical respiratory specimens. Ann. Lab. Med.34 (3), 203–209 (2014).
pubmed: 24790907 pmcid: 3999318 doi: 10.3343/alm.2014.34.3.203
Sulaiman, I. et al. Evaluation of the airway microbiome in nontuberculous mycobacteria disease. Eur. Respir. J.52(4) (2018).
Naidoo, C. C. et al. Anaerobe-enriched gut microbiota predicts pro-inflammatory responses in pulmonary tuberculosis. EBioMedicine67, 103374 (2021).
pubmed: 33975252 pmcid: 8122180 doi: 10.1016/j.ebiom.2021.103374
Ticlla, M. R. et al. The sputum microbiome in pulmonary tuberculosis and its association with disease manifestations: a cross-sectional study. Front. Microbiol.12, 633396 (2021).
pubmed: 34489876 pmcid: 8417804 doi: 10.3389/fmicb.2021.633396
Kateete, D. P. et al. Sputum microbiota profiles of treatment-naïve TB patients in Uganda before and during first-line therapy. Sci. Rep.11 (1), 24486 (2021).
pubmed: 34966183 pmcid: 8716532 doi: 10.1038/s41598-021-04271-y
Pezzulo, A. A. et al. Abundant DNase I-sensitive bacterial DNA in healthy porcine lungs and its implications for the lung microbiome. Appl. Environ. Microbiol.79 (19), 5936–5941 (2013).
pubmed: 23872563 pmcid: 3811377 doi: 10.1128/AEM.01752-13
Nocker, A., Sossa, K. E. & Camper, A. K. Molecular monitoring of disinfection efficacy using propidium monoazide in combination with quantitative PCR. J. Microbiol. Methods70 (2), 252–260 (2007).
pubmed: 17544161 doi: 10.1016/j.mimet.2007.04.014
Codony, F., Agustí, G. & Allué-Guardia, A. Cell membrane integrity and distinguishing between metabolically active and inactive cells as a means of improving viability PCR. Mol. Cell Probes29 (3), 190–192 (2015).
pubmed: 25797787 doi: 10.1016/j.mcp.2015.03.003
de Goffau, M. C. et al. Recognizing the reagent microbiome. Nat. Microbiol.3 (8), 851–853 (2018).
pubmed: 30046175 doi: 10.1038/s41564-018-0202-y

Auteurs

Charissa C Naidoo (CC)

DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.
African Microbiome Institute, Division of Molecular Biology & Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

Rouxjeane Venter (R)

DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.

Francesc Codony (F)

Municipal Laboratory - Aigües de Mataró, Mataró, Spain.

Gemma Agustí (G)

Reactivos para Diagnóstico, Setmenat, Spain.

Natasha Kitchin (N)

Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

Selisha Naidoo (S)

Institute of Infectious Disease and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.

Hilary Monaco (H)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Hridesh Mishra (H)

DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.
Public Health Research Institute, New Jersey Medical School, Newark, New Jersey, USA.

Yonghua Li (Y)

Division of Pulmonary, Critical Care, and Sleep Medicine, New York University School of Medicine, New York, USA.

Jose C Clemente (JC)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Robin M Warren (RM)

DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.

Leopoldo N Segal (LN)

Division of Pulmonary, Critical Care, and Sleep Medicine, New York University School of Medicine, New York, USA.

Grant Theron (G)

DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa. gtheron@sun.ac.za.
African Microbiome Institute, Division of Molecular Biology & Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. gtheron@sun.ac.za.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Effectiveness of Virtual Yoga for Chronic Low Back Pain: A Randomized Clinical Trial.

Hallie Tankha, Devyn Gaskins, Amanda Shallcross et al.
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Subtracting the background by reducing...
questionsmedicales.fr › Bactéries › Bactéries à Gram positif › Bâtonnets à Gram positif › Bâtonnets asporogènes à Gram positif › Bâtonnets asporogènes réguliers à Gram positif › Mycobacteriaceae › Mycobacterium › Mycobacterium tuberculosis › Subtracting the background by reducing...
questionsmedicales.fr › Liquides et sécrétions biologiques › Sécrétions corporelles › Expectoration › Subtracting the background by reducing...
questionsmedicales.fr › Environnement et santé publique › Environnement › Écosystème › Biodiversité › Biote › Microbiote › Subtracting the background by reducing...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › Acides nucléiques acellulaires › Subtracting the background by reducing...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ARN › ARN ribosomique › ARN ribosomique 16S › Subtracting the background by reducing...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ADN › ADN bactérien › Subtracting the background by reducing...
questionsmedicales.fr › Infection › Infections bactériennes et mycoses › Infections bactériennes › Infections bactériennes à Gram positif › Infections à Actinomycetales › Infections à Mycobacterium › Tuberculose › Subtracting the background by reducing...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Subtracting the background by reducing...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Adulte d'âge moyen › Subtracting the background by reducing...
questionsmedicales.fr › Composés chimiques organiques › Azotures › Subtracting the background by reducing...
questionsmedicales.fr › Maladies de l'appareil respiratoire › Infections de l'appareil respiratoire › Tuberculose pulmonaire › Subtracting the background by reducing...
questionsmedicales.fr › Composés hétérocycliques › Composés hétérocycliques à cycles fusionnés › Composés hétérocycliques 3 noyaux › Phénanthridines › Propidium › Subtracting the background by reducing...