| Literature DB >> 33857251 |
Giorgia Mori1, Mark Morrison1, Antje Blumenthal1.
Abstract
Tuberculosis (TB) remains an infectious disease of global significance and a leading cause of death in low- and middle-income countries. Significant effort has been directed towards understanding Mycobacterium tuberculosis genomics, virulence, and pathophysiology within the framework of Koch postulates. More recently, the advent of "-omics" approaches has broadened our appreciation of how "commensal" microbes have coevolved with their host and have a central role in shaping health and susceptibility to disease. It is now clear that there is a diverse repertoire of interactions between the microbiota and host immune responses that can either sustain or disrupt homeostasis. In the context of the global efforts to combatting TB, such findings and knowledge have raised important questions: Does microbiome composition indicate or determine susceptibility or resistance to M. tuberculosis infection? Is the development of active disease or latent infection upon M. tuberculosis exposure influenced by the microbiome? Does microbiome composition influence TB therapy outcome and risk of reinfection with M. tuberculosis? Can the microbiome be actively managed to reduce risk of M. tuberculosis infection or recurrence of TB? Here, we explore these questions with a particular focus on microbiome-immune interactions that may affect TB susceptibility, manifestation and progression, the long-term implications of anti-TB therapy, as well as the potential of the host microbiome as target for clinical manipulation.Entities:
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Year: 2021 PMID: 33857251 PMCID: PMC8049499 DOI: 10.1371/journal.ppat.1009377
Source DB: PubMed Journal: PLoS Pathog ISSN: 1553-7366 Impact factor: 6.823
Summary of microbiome studies performed on animal models of TB and TB patients, investigating the impact of M. tuberculosis infection on the host microbiome.
| Impact of | ||||||
|---|---|---|---|---|---|---|
| Location | Specimen | Host and study design | Change in microbiota composition | Effects on the immune system | Sequencing technology and data analysis | Ref |
| Feces | Newly diagnosed TB patients (NTB,
| Decrease of | 16S rRNA gene amplicon (Illumina) sequencing; Greengenes databaseΔ; Quantitative Insights into Microbial Ecology (QIIME Version 1.7.0°) | [ | ||
| Feces | TB patients who did not receive antibiotics 1 month
prior to enrollment ( | Decrease of | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Greengenes databaseΔ; (QIIME v 1.9.1°) | [ | |
| Feces | TB patients ( | Increase of | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Greengenes databaseΔ; (QIIME v 1.8°) | [ | |
| Feces | TB patients ( | Presence of | n.d. | Shotgun metagenomic Illumina sequencing; Metaphlan2 (species abundance) | [ | |
| Feces | TB patients ( | A higher relative abundance of Bacteroidetes concurrent with low Firmicutes/Bacteroidetes ratio in active TB and LTBI | Positive association of Bacteroidetes and polymorphonuclear neutrophils in TB and LTBI patients; concurrent increase of pro-inflammatory cytokines (IL-6 and IL-1B) and low relative abundance of Bifidobacteriaceae in TB patients | 16S rRNA gene amplicon (Illumina) sequencing; Greengenes databaseΔ; QIIME° | [ | |
| Feces | Female Balb/c mice ( | Decrease of Clostridiales (Lachnospiraceae, Ruminococcaceae families) and Bacteroidales orders. | n.d. | 16S rRNA gene amplicon (454) pyrosequencing sequencing; Silva databaseΔ; QIIME° | [ | |
| Feces | Female C57BL/6 mice treated with a cocktail of
broad-spectrum antibiotics ceased 2 days before
| Decrease of Bacteroidetes and Firmicutes; increase of Betaproteobacteria | Decrease in MAIT cells and IL17A in the lungs and
increased susceptibility to | RT-qPCR was performed using phylum-specific primers | [ | |
| Feces | Female C57BL/6J-CD45a(Ly5a) mice
( | Decreased relative abundance of Clostridiales; increased Bacteroidales; although neither significant by 20 weeks | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; custom reference database built from the NCBI 16S rRNA gene sequence and taxonomy database (version May 2016Δ; QIIME v 1.9.1°) | [ | |
| Feces | Rhesus macaques ( | Families Lachnospiraceae, Ruminococcaceae, and
Clostridiaceae significantly increased in animals with severe
disease; members of the family Streptococcaceae,
Erysipelotrichaceae, and the Bacteroidales RF16 and
Clostridiales vadin B660 groups were decreased in the same
group. | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Silva databaseΔ; QIIME2/ DADA2°; Shotgun metagenomics with NextSeq 500 platform | [ | |
| BAL | Pulmonary TB patients (TB) ( | Decrease of | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; (QIIME v 1.8°) | [ | |
| BAL | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Silva databaseΔ; Mothur (v 1.35.1°) | [ | |||
| BAL | TB patients ( | Presence of the 4 important genus of lung
microbiota ( | Frequency of | Lung microbiota was detected through culture methods. | [ | |
| BAL | TB patients ( | n.d. | 16S rRNA gene amplicon (454) pyrosequencing; Ribosomal Database Project (RDP)Δ; Fast UniFrac° | [ | ||
| nasal, oropharynx, sputum samples | TB patients ( | Abundance of Thermi phylum and unclassified
sequences belonging to the Streptococcaceae family in TB
patients; decrease of the genus | n.d. | 16S rRNA gene and ITS amplicon (454) pyrosequencing; Greengenes databaseΔ; QIIME (v 1.6°) | [ | |
| OWs, BALs, bronchoscope control samples | Cynomolgus macaques ( | Increase of | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Greengenes databaseΔ; QIIME° | [ | |
*NTB, no more than 1 week anti-TB treatment; RTB, previously treated and declared as cured prior to recurrence.
#No healthy individuals recruited as controls, positive M. tuberculosis (Mtb) detection determined by a combination of sputum smear, culture, RT-PCR, and GeneXpert.
ΔTaxonomic assignment.
°Operational Taxonomic Units (OTUs) analysis.
BAL, bronchoalveolar lavage; LTBI, latent tuberculosis infection; n.d., not determined; NTB, newly diagnosed TB patients; OW, oral wash; RTB, recurrent TB patients; RT-qPCR, quantitative reverse transcription PCR; TB, tuberculosis.
Fig 1Alterations in microbiome composition (A = gut; B = respiratory tract) in individuals with active TB compared to controls. Significantly over- and underrepresented bacteria in the gut (A) and lungs (B) of TB patients (circle), mice (rhombus), or macaques (triangle) models of TB. Taxonomic details are shown, and over- or underrepresentation of the taxonomic level reported by each study is indicated by a red or blue shape, respectively.
Summary of microbiome studies performed on animal models of TB and TB patients, investigating the impact of anti-TB treatment on the host microbiome.
| Effects of anti-TB treatment on the host microbiome composition | |||||||
|---|---|---|---|---|---|---|---|
| Location | Specimen | Host | Treatment | Change in microbiota composition | Effects on the immune system | Sequencing technology and data analyisis | Ref |
| Feces | LTBI ( | INH, RIF, EMB, and PZA | Decrease of | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; Ribosomal Database Project (RDP) Δ; Mothur v.1.36.1° | [ | |
| Feces | LTBI ( | INH, RIF, EMB, and PZA | Enrichment of
| n.d. | 16S rRNA gene amplicon (Illumina) sequencing; NCBI refseq_rna database with custom scriptsΔ; QIIME°/ Shotgun metagenomic Illumina sequencing; Metaphlan2 (microbial species abundances) and HUMAnN2 (functional pathways) | [ | |
| Feces | MDR-TB treatment group ( | MDR-TB treatment | Bacteroidetes, Cyanobacteria, and Patescibacteria are biomarkers for the recovered group: decrease of Actinobacteria and Firmicutes; increase of Bacteroidetes in recovered group. | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; RDP classifier (v 2.2)Δ; Mothur° | [ | |
| Feces | 6–10 weeks old C57BL/6 mice ( | RIF or INH + PYZ | Expansion of | Expression levels of MHCII and production of TNFα
and IL-1β significantly reduced after | 16S rRNA gene amplicon (Illumina) sequencing; Microbiome Analyst web application (community diversity profiling and statistical analysis) | [ | |
| Feces | 4–8-week-old C57BL/6J-CD45a(Ly5a) female mice
( | INH, RIF, and PZA + INH and RIF | Decrease of genera | n.d. | 16S rRNA gene amplicon (Illumina) sequencing; custom reference database built from the NCBI 16S rRNA gene sequence and taxonomy database (version May 2016)Δ; QIIME (v 1.9.1°) | [ | |
| Sputum samples and throat swab samples | New TB group (N-TB, | mix of DS-TB and MDR-TB treatments | n.d. | 16S rRNA gene amplicon (454) pyrosequencing; Greengenes databaseΔ; QIIME (v 1.5.0°) | [ | ||
ΔTaxonomic assignment.
°Operational Taxonomic Units (OTUs) analysis.
DS-TB, drug-susceptible TB; LTBI, latent tuberculosis infection; MDR-TB, multidrug-resistant TB; n.d., not determined; TB, tuberculosis.
Fig 2Alterations in microbiome composition (A = gut; B = respiratory tract) of patients upon TB antibiotics treatment. Significantly over- and underrepresented bacteria in the gut (A) and lungs (B) of TB patients (circle), mice (rhombus), or macaques (triangle) models of TB undergoing therapy for drug-sensitive or multidrug-resistant TB. Taxonomic details are shown, and over- or underrepresentation of the taxonomic level reported by each study is indicated by a red or blue shape, respectively.
Fig 3Proposed microbiome-immune interactions in M. tuberculosis infection.
Microbiota of the upper and lower respiratory tract may define epithelial barrier integrity, M cell frequency, antimicrobial defense, composition, and functionality of innate and adaptive immune mechanisms. Through the gut-lung axis, the microbiota of the intestinal tract influences barrier and immune functions in the periphery and at sites of M. tuberculosis infection. Fig 3 was created with BioRender.