Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity

Genestet, Charlotte; Refrégier, Guislaine; Hodille, Elisabeth; Zein-Eddine, Rima; Meur, Adrien Le; Hak, Fiona; Barbry, A; Westeel, Emilie; Berland, Jean-Luc; Engelmann, Astrid; Verdier, Isabelle; Lina, Gérard; Ader, Florence; Dray, Stéphane; Jacob, Laurent; Massol, François; Venner, Samuel; Dumitrescu, Oana

doi:10.1016/j.ijid.2022.10.026

Cited by 7 publications

(4 citation statements)

References 38 publications

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“…The modified Bandim TBscore was used to evaluate the severity in patients with PTB at the time of diagnosis, before the initiation of anti-Tuberculosis treatment 21 , 22 . It considers five symptoms (cough, hemoptysis, dyspnea, chest pain, and night sweats) and seven clinical findings (anemia, pulse > 90 beats/min, positive finding at lung auscultation, temperature > 37 °C (axillary), body mass index (BMI) < 18 and < 16, hypoproteinemia, and bilateral lung involvement in CT or X-ray).…”

Section: Methodsmentioning

confidence: 99%

circRNA_SLC8A1 promotes the survival of mycobacterium tuberculosis in macrophages by upregulating expression of autophagy-related protein SQSTM1/p62 to activate the NF-κB pathway

Li,

Gao,

Zhang

et al. 2024

Sci Rep

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Macrophages act as the first immune defense line of the host against Mycobacterium tuberculosis (Mtb). A previous study showed that circRNA_SLC8A1 was significantly upregulated in Mtb-infected macrophages, but its regulatory mechanism in anti-tuberculosis infection is unclear. Therefore, this study aimed to investigate the role of circRNA_SLC8A1 in the anti-tuberculosis activity of macrophages. We showed that circRNA_SLC8A1 was upregulated in tuberculosis patients. Moreover, the binding sites of miR-20b-5p on circRNA_SLC8A1 and Sequestosome 1 (SQSTM1/p62) mRNA were predicted by StarBase and verified by the double luciferase reporter gene assay. Next, we found that miR-20b-5p expression was decreased, while SQSTM1 protein expression was increased in a time- and dose-dependent manner in the human macrophage U937 in response to Mtb infection. Furthermore, circRNA_SLC8A1 overexpression vector (circRNA_SLC8A1) or shRNA (sh-circRNA_SLC8A1) and/or miR-20b-5p mimic or inhibitor and/or SQSTM1 overexpression vector (SQSTM1) or small interfering RNA (si-SQSTM1) or its corresponding control were transfected into Mtb-infected macrophages. Results showed that overexpression of circRNA_SLC8A1 or miR-20b-5p inhibitor promoted the secretion of pro-inflammatory factors IL-1β, IL-6, and TNF-α, increased Nitric Oxide (NO) content and inducible nitric oxide synthase (iNOS) expression, inhibited Reactive oxygen species (ROS) production. Cleaved-caspase-3 protein expression, and cell apoptosis, and promoted Mtb survival. Silencing SQSTM1 inhibited secretion of pro-inflammatory factors and activation of the NF-κB pathway. Overexpression of miR‐20b‐5p blocked the promoting of circ‐SLC8A1 on SQSTM1 protein expression. In summary, circRNA_SLC8A1 sponged miR‐20b‐5p to upregulate SQSTM1/p62 expression and promoted Mtb survival in macrophages through the NF-κB signaling pathway.

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Section: Methodsmentioning

confidence: 99%

circRNA_SLC8A1 promotes the survival of mycobacterium tuberculosis in macrophages by upregulating expression of autophagy-related protein SQSTM1/p62 to activate the NF-κB pathway

Li,

Gao,

Zhang

et al. 2024

Sci Rep

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show abstract

“…With the increasing availability of bacterial WGS data, it is now possible to use GWAS to probe the relationship between pathogen genotypes and clinical disease phenotypes. GWAS has identified genetic determinants of MTB drug resistance ( Coll et al, 2018 ; Farhat et al, 2013 ), TB transmission ( Sobkowiak et al, 2020 ), virulence ( Genestet et al, 2022 ) and host preference ( Luo et al, 2022 ). In this study, GWAS was used to identify bacterial genetic variants associated with poor treatment outcomes in patients with drug-susceptible TB and assess their impact on outcomes.…”

Section: Discussionmentioning

confidence: 99%

The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome

Chen

Jiang

Mijiti

et al. 2023

eLife

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Drug resistance is a known risk factor for poor tuberculosis (TB) treatment outcomes, but the contribution of other bacterial factors to poor outcomes in drug susceptible TB is less well understood. Here, we generate a population-based dataset of drug-susceptible Mycobacterium tuberculosis (MTB) isolates from China to identify factors associated with poor treatment outcomes. We analyzed whole-genome sequencing (WGS) data of MTB strains from 3196 patients, including 3105 patients with good and 91 patients with poor treatment outcomes, and linked genomes to patient epidemiological data. A genome-wide association study (GWAS) was performed to identify bacterial genomic variants associated with poor outcomes. Risk factors identified by logistic regression analysis were used in clinical models to predict treatment outcomes. GWAS identified fourteen MTB fixed mutations associated with poor treatment outcomes, but only 24.2% (22/91) of strains from patients with poor outcomes carried at least one of these mutations. Isolates from patients with poor outcomes showed a higher ratio of reactive oxygen species (ROS)-associated mutations compared to isolates from patients with good outcomes (26.3% vs 22.9%, t test, P=0.027). Patient age, sex, and duration of diagnostic delay were also independently associated with poor outcomes. Bacterial factors alone had poor power to predict poor outcomes with an AUC of 0.58. The AUC with host factors alone was 0.70, but increased significantly to 0.74 (DeLong's test, P = 0.01) when bacterial factors were also included. In conclusion, although we identified MTB genomic mutations that are significantly associated with poor treatment outcomes in drug-susceptible TB cases, their effects appear to be limited.

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“…With the increasing availability of bacterial WGS data has made it possible to use GWAS to study the relationship between pathogen genotypes with clinical disease phenotypes. In MTB, GWAS has identified genetic determinants of drug resistance (Coll et al, 2018; Farhat et al, 2013), TB transmission (Sobkowiak et al, 2020), host preference (Luo et al, 2022) and virulence (Genestet et al, 2022). In this study, GWAS analysis was used to identify bacterial genetic variants associated with poor outcomes in drug-susceptible TB patients, and assess their impact.…”

Section: Discussionmentioning

confidence: 99%

The mutational signatures of poor treatment outcomes on the drug-susceptibleMycobacterium tuberculosisgenome

Chen

Jing

Mijiti

et al. 2022

Preprint

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Drug resistance is a known risk factor for poor tuberculosis (TB) treatment outcomes, but the contribution of other bacterial factors to poor outcomes in drug susceptible TB is less understood. Here, we generate a population-based dataset of drug-susceptibleMycobacterium tuberculosis(MTB) isolates from China to identify factors associated with poor treatment outcomes. We sequenced the whole genome of 3496 MTB strains and linked genomes to patient epidemiological data. A genome-wide association study (GWAS) was performed to identify bacterial genomic variants associated with poor outcomes. Risk factors identified by logistic regression analysis were used in clinical models to predict treatment outcomes and their associations were assessed with structural equation models (SEM). GWAS identified fourteen MTB variants (24.2% vs 7.5%, P<0.001) and ade novoreactive oxygen species (ROS) mutational signature (26.3%±18.2% vs 22.9%±13.8%, P=0.027) that were more frequent in patients with poor treatment outcomes. Patient age, sex, and duration of diagnostic delay were also independently associated with poor outcomes. The best clinical prediction model, with an AUC of 0.74, incorporates both host and bacterial risk factors, and host factors are more important. Together, our results reveal that although host factors are the most important determinants for poor treatment outcomes, the genomic characteristics of the infecting MTB strain may also contribute significantly to poor treatment outcomes. Fourteen genetic variants were statistically associated with poor TB treatment outcomes, but the optimal model for predicting treatment outcomes includes both patient characteristics and bacterial genomic determinants.

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Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity

Cited by 7 publications

References 38 publications

circRNA_SLC8A1 promotes the survival of mycobacterium tuberculosis in macrophages by upregulating expression of autophagy-related protein SQSTM1/p62 to activate the NF-κB pathway

circRNA_SLC8A1 promotes the survival of mycobacterium tuberculosis in macrophages by upregulating expression of autophagy-related protein SQSTM1/p62 to activate the NF-κB pathway

The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome

The mutational signatures of poor treatment outcomes on the drug-susceptibleMycobacterium tuberculosisgenome

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