Update in tuberculosis and nontuberculous mycobacterial infections 2013

Screening, epidemic trends and drug sensitivity analysis of nontuberculous mycobacteria in a local area of China

OBJECTIVE

To analyze the isolation rate, prevalence trends, species distribution, and drug sensitivity of non-tuberculous mycobacteria (NTM) in Anhui Province, providing a reference for diagnosis and treatment strategies.

METHODS

Specimens from suspected mycobacterial infection patients at Anhui Chest Hospital (including outpatients and inpatients) from January 2021 to December 2023 were cultured. Identified NTM strains were analyzed for species distribution and drug sensitivity.

RESULTS

Of 10,519 mycobacteria strains cultured, 1,589 were NTM (15.11%). The top four species were Mycobacterium intracellulare (75.36%), Mycobacterium abscessus (11.78%), Mycobacterium kansasii (7.09%), and Mycobacterium avium (2.85%). NTM strains showed high sensitivity to amikacin and clarithromycin (≥90%) and significant sensitivity to rifabutin, moxifloxacin, and rifampicin (89.03%-79.61%). They exhibited high resistance to imipenem/cilastatin, sulfamethoxazole, minocycline, and doxycycline (≥95%).

CONCLUSION

NTM isolation rates in Anhui have remained stable, with the predominant species being M. intracellulare, M. kansasii, M. abscessus, and M. avium. NTM strains are highly sensitive to amikacin, clarithromycin, rifabutin, moxifloxacin, and rifampicin. These findings can guide diagnosis, treatment strategies, and drug selection for NTM disease in Anhui Province.

Comparative genome analysis reveals high-level drug resistance markers in a clinical isolate of Mycobacterium fortuitum subsp. fortuitum MF GZ001

Introduction

Infections caused by non-tuberculosis mycobacteria are significantly worsening across the globe. M. fortuitum complex is a rapidly growing pathogenic species that is of clinical relevance to both humans and animals. This pathogen has the potential to create adverse effects on human healthcare.

Methods

The MF GZ001 clinical strain was collected from the sputum of a 45-year-old male patient with a pulmonary infection. The morphological studies, comparative genomic analysis, and drug resistance profiles along with variants detection were performed in this study. In addition, comparative analysis of virulence genes led us to understand the pathogenicity of this organism.

Results

Bacterial growth kinetics and morphology confirmed that MF GZ001 is a rapidly growing species with a rough morphotype. The MF GZ001 contains 6413573 bp genome size with 66.18 % high G+C content. MF GZ001 possesses a larger genome than other related mycobacteria and included 6156 protein-coding genes. Molecular phylogenetic tree, collinearity, and comparative genomic analysis suggested that MF GZ001 is a novel member of the M. fortuitum complex. We carried out the drug resistance profile analysis and found single nucleotide polymorphism (SNP) mutations in key drug resistance genes such as rpoB, katG, AAC(2')-Ib, gyrA, gyrB, embB, pncA, blaF, thyA, embC, embR, and iniA. In addition, the MF GZ001strain contains mutations in iniA, iniC, pncA, and ribD which conferred resistance to isoniazid, ethambutol, pyrazinamide, and para-aminosalicylic acid respectively, which are not frequently observed in rapidly growing mycobacteria. A wide variety of predicted putative potential virulence genes were found in MF GZ001, most of which are shared with well-recognized mycobacterial species with high pathogenic profiles such as M. tuberculosis and M. abscessus.

Discussion

Our identified novel features of a pathogenic member of the M. fortuitum complex will provide the foundation for further investigation of mycobacterial pathogenicity and effective treatment.

Clinical Characteristics and Antimicrobial Susceptibility of Mycobacterium intracellulare and Mycobacterium abscessus Pulmonary Diseases: A Retrospective Study

The incidence of nontuberculous mycobacteria (NTM) diseases is increasing every year. The present study was performed to investigate the clinical characteristics, CT findings, and drug susceptibility test (DST) results of patients diagnosed with M. intracellulare or M. abscessus nontuberculous mycobacterial pulmonary disease (NTMPD). This retrospective study included patients diagnosed with NTMPD due to M. intracellulare or M. abscessus for the first time at Anhui Chest Hospital between 01/2019 and 12/2021. The patients were grouped as M. intracellulare-NTMPD group or M. abscessus-NTMPD group. Clinical features, imaging data and DST data, were collected. Patients with M. intracellulare infection had a higher rate of acid-fast smears (66.1% vs. 45.2%, P=0.032) and a higher rate of cavitation based on pulmonary imaging (49.6% vs. 19.4%, P=0.002) than patients with M. abscessus infection, but both groups had negative TB-RNA and GeneXpert results, with no other characteristics significant differences. The results of DST showed that M. intracellulare had high susceptibility rate to moxifloxacin (95.9%), amikacin (90.1%), clarithromycin (91.7%), and rifabutin (90.1%). M. abscessus had the highest susceptibility rate to amikacin (71.0%) and clarithromycin (71.0%). The clinical features of M. intracellulare pneumopathy and M. abscessus pneumopathy are highly similar. It may be easily misdiagnosed, and therefore, early strain identification is necessary. M. intracellulare has a high susceptibility rate to moxifloxacin, amikacin, clarithromycin, and rifabutin, while M. abscessus has the highest susceptibility rate to amikacin and clarithromycin. This study provides an important clinical basis for improving the management of NTMPD.

Combining comparative genomic analysis with machine learning reveals some promising diagnostic markers to identify five common pathogenic non-tuberculous mycobacteria

Non-tuberculous mycobacteria (NTM) can cause various respiratory diseases and even death in severe cases, and its incidence has increased rapidly worldwide. To date, it's difficult to use routine diagnostic methods and strain identification to precisely diagnose various types of NTM infections. We combined systematic comparative genomics with machine learning to select new diagnostic markers for precisely identifying five common pathogenic NTMs (Mycobacterium kansasii, Mycobacterium avium, Mycobacterium intracellular, Mycobacterium chelonae, Mycobacterium abscessus). A panel including six genes and two SNPs (nikA, benM, codA, pfkA2, mpr, yjcH, rrl C2638T, rrl A1173G) was selected to simultaneously identify the five NTMs with high accuracy (> 90%). Notably, the panel only containing the six genes also showed a good classification effect (accuracy > 90%). Additionally, the two panels could precisely differentiate the five NTMs from M. tuberculosis (accuracy > 99%). We also revealed some new marker genes/SNPs/combinations to accurately discriminate any one of the five NTMs separately, which provided the possibility to diagnose one certain NTM infection precisely. Our research not only reveals novel promising diagnostic markers to promote the development of precision diagnosis in NTM infectious, but also provides an insight into precisely identifying various genetically close pathogens through comparative genomics and machine learning.

Burden of non-tuberculous mycobacterial pulmonary disease in Germany

The objective of this study was to estimate the burden of disease in incident patients with non-tuberculous mycobacterial pulmonary disease (NTM-PD).

A sample of 7 073 357 anonymised persons covered by German public statutory health insurances was used to identify patients with NTM-PD. In total, 125 patients with newly diagnosed NTM-PD in 2010 and 2011 were matched with 1250 control patients by age, sex and Charlson Comorbidity Index, and followed for 39 months.

The incidence rate for NTM-PD was 2.6 per 100 000 insured persons (95% CI 2.2–3.1). The mortality rate for patients with NTM-PD and the control group in the observational period was 22.4% and 6%, respectively (p<0.001). Mean direct expenditure per NTM-PD patient was €39 559.60 (95% CI 26 916.49–52 202.71), nearly 4-fold (3.95, 95% CI 3.73–4.19) that for a matched control (€10 006.71, 95% CI 8907.24–11 106.17). Hospitalisations were three times higher in the NTM-PD group and accounted for 63% of the total costs. Attributable annual direct costs and indirect work-loss costs in NTM-PD patients were €9093.20 and €1221.05 per control patient, respectively. Only 74% of NTM-PD patients received antibiotics and nearly 12% were prescribed macrolide monotherapy.

Although NTM-PD is considered rare, the attributable mortality and financial burden in Germany are high. Efforts to heighten awareness of appropriate therapy are urgently needed.

Platelet-lymphocyte ratios: a potential marker for pulmonary tuberculosis diagnosis in COPD patients

BACKGROUND

In recent decades, morbidity and mortality have been found to be significantly increased in patients with chronic obstructive pulmonary disease (COPD) complicated with pulmonary tuberculosis (PTB). Platelet-lymphocyte ratio (PLR) is an indicator for inflammatory diseases. This study aims to investigate whether PLR could act as a potential marker for patients with COPD complicated with PTB.

METHODS

In this retrospective study, laboratory characteristics of 87 COPD patients complicated with PTB (determined by Mycobacterium tuberculosis positive culture from sputum or bronchial lavage fluid) and 83 COPD patients (as the control group, determined by M. tuberculosis culture negativity from sputum or bronchial lavage fluid) were investigated. Data obtained on the day of admission were analyzed.

RESULTS

PLR >216.82 was identified as the optimal cutoff value for discriminating COPD patients with PTB (sensitivity 92.4%, specificity 84.5%, positive-predictive value 91.6%, negative-predictive value 86.2%, and area under the curve [AUC] was 0.87) from patients with COPD alone. The AUC of PLR was significantly greater than that of neutrophil-lymphocyte count ratio (AUC, 0.74; 95% confidence interval, 0.67-0.81; P<0.01).

CONCLUSION

PLR could be developed as a valuable maker for identifying tuberculosis infection in COPD patients.