Non-tuberculous mycobacterial pulmonary disease (NTM-PD): Epidemiology, diagnosis and multidisciplinary management

Biochip-Based Identification of Mycobacterial Species in Russia

Infections caused by nontuberculous mycobacteria (NTM) are rising globally throughout the world. The number of species isolated from clinical samples is steadily growing, which demands the implementation of a robust diagnostic method with wide specificity. This study was carried out in in 2022-2024 in three clinical antituberculosis centers in the biggest cities of Russia: Moscow, Saint Petersburg, and Novosibirsk. We developed the DNA hybridization assay 'Myco-biochip' that allows the identification of 79 mycobacterial species and analyzed 3119 samples from 2221 patients. Sixty-eight mycobacterial species were identified in clinics, including the three novel species phylogenetically related to M. duvalii, M. lentiflavum, and M. talmoniae. The identification of a close relative of M. talmoniae adds to the existence of separate clade between M. terrae, M. triviale complexes and other slow-growing Mycobacteria, which supports the thesis against the splitting of Mycobacteria into five separate genera. Adding to the list of potentially pathogenic species, we identified M. adipatum and M. terramassiliense, which were previously described as natural habitats. The diversity of acid-fast bacilli identified in TB-suspected persons was not limited to the Mycobacteria genus and also includes species from genera Nocardia, Gordonia, Corynebacterium, Tsukamurella, and Rhodococcus of the order Mycobacteriales. The revealed bacterial diversity in patients with suspected NTM-diseases requires the implementation of relevant species identification assays as the first step in the laboratory diagnostic pipeline.

Intrapulmonary pharmacokinetics of SPR719 following oral administration of SPR720 to healthy volunteers

SPR720 is a phosphate ester prodrug that is converted rapidly in vivo to SPR719, the active moiety, which exhibits potent in vitro activity against clinically relevant mycobacterial species including Mycobacterium avium complex (MAC) and Mycobacterium abscessus. SPR720 is in clinical development for the treatment of nontuberculous mycobacterial pulmonary disease (NTM-PD) due to MAC. This study evaluated the safety and the intrapulmonary pharmacokinetics of SPR719 in healthy volunteers. A total of 30 subjects received oral SPR720 1,000 mg once daily for 7 days followed by bronchoscopy and bronchoalveolar lavage, with blood samples collected for plasma pharmacokinetic assessments. Mean SPR719 area under the concentration-time curve from time 0 to 24 hours (AUC0-24) and maximum concentration (Cmax) for plasma, epithelial lining fluid (ELF), and alveolar macrophages (AM) were 52,418 ng·h/mL and 4,315 ng/mL, 59,880 ng·h/mL and 5,429 ng/mL, and 128,105 ng·h/mL and 13,033 ng/mL, respectively. The ratios of ELF to total plasma concentrations of SPR719 based on AUC0-24 and Cmax were 1.14 and 1.26, and the ratios of AM to total plasma concentrations of SPR719 based on AUC0-24 and Cmax were 2.44 and 3.02, respectively. When corrected for protein binding, the ratios of ELF to unbound plasma concentrations of SPR719 for AUC0-24 and Cmax were 19.87 and 21.88, and the ratios of AM to unbound plasma concentrations of SPR719 for AUC0-24 and Cmax were 42.50 and 52.53, respectively. No unexpected safety findings were observed. Results from this study of the intrapulmonary disposition of SPR719 support further investigation of SPR720 as a potential oral agent for the treatment of patients with NTM-PD.This study is registered with Clinicaltrials.gov as NCT05955586.

Enhancing the antimycobacterial efficacy of pyridine-4-carbohydrazide: linkage to additional antimicrobial agents via oxocarboxylic acids

This study evaluates the antimycobacterial potential of novel "mutual" bioactive amides, combining pyridine-4-carbohydrazide (isoniazid, INH) with various antimicrobial agents (sulphonamides, 4-aminosalicylic acid, thiosemicarbazide, diphenyl (thio)ethers) via oxocarboxylic acids. The aim was to enhance activity against both drug-susceptible and multidrug-resistant (MDR) Mycobacterium tuberculosis and non-tuberculous strains, while overcoming drug resistance through dual-action mechanisms. Many derivatives exhibited potent antimycobacterial activity, with minimum inhibitory concentrations (MICs) as low as ≤0.25 μM, outperforming INH, especially diphenyl (thio)ethers and biphenyl analogues. Additionally, the compounds were effective against M. kansasii (MICs ≤1 μM) and inhibited MDR strains at higher concentrations (≥8 μM). The cytotoxicity assay indicated a favourable safety profile, with no significant haemolysis at 125 μM, and some compounds were even protective. Selectivity for mycobacteria was confirmed by low inhibition of Gram-positive bacteria and inactivity against Gram-negative bacteria or fungi, highlighting the potential for further development as antimycobacterial agents.

Drinking Water Microbiota, Entero-Mammary Pathways, and Breast Cancer: Focus on Nontuberculous Mycobacteria

The prospect of drinking water serving as a conduit for gut bacteria, artificially selected by disinfection strategies and a lack of monitoring at the point of use, is concerning. Certain opportunistic pathogens, notably some nontuberculous mycobacteria (NTM), often exceed coliform bacteria levels in drinking water, posing safety risks. NTM and other microbiota resist chlorination and thrive in plumbing systems. When inhaled, opportunistic NTM can infect the lungs of immunocompromised or chronically ill patients and the elderly, primarily postmenopausal women. When ingested with drinking water, NTM often survive stomach acidity, reach the intestines, and migrate to other organs using immune cells as vehicles, potentially colonizing tumor tissue, including in breast cancer. The link between the microbiome and cancer is not new, yet the recognition of intratumoral microbiomes is a recent development. Breast cancer risk rises with age, and NTM infections have emerged as a concern among breast cancer patients. In addition to studies hinting at a potential association between chronic NTM infections and lung cancer, NTM have also been detected in breast tumors at levels higher than normal adjacent tissue. Evaluating the risks of continued ingestion of contaminated drinking water is paramount, especially given the ability of various bacteria to migrate from the gut to breast tissue via entero-mammary pathways. This underscores a pressing need to revise water safety monitoring guidelines and delve into hormonal factors, including addressing the disproportionate impact of NTM infections and breast cancer on women and examining the potential health risks posed by the cryptic and unchecked microbiota from drinking water.

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Rapid and accurate identification and differentiation of Mycobacterium tuberculosis and non-tuberculous mycobacteria using PCR kits available in a high-burden setting

Infections caused by mycobacteria, including Mycobacterium tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), are a major public health issue worldwide. An accurate diagnosis of mycobacterial species is a challenge for surveillance and treatment, particularly in high-burden settings usually associated with low- and middle-income countries. In this study, we analyzed the clinical performance of two commercial PCR kits designed for the identification and differentiation of MTBC and NTM, available in a high-burden setting such as Ecuador. A total of 109 mycobacteria isolates were included in the study, 59 of which were previously characterized as M. tuberculosis and the other 59 as NTM. Both kits displayed great clinical performance for the identification of M. tuberculosis, with 100% sensitivity. On the other hand, for NTM, one of the kits displayed a good clinical performance with a sensitivity of 94.9% (CI 95%: 89-100%), while the second kit had a reduced sensitivity of 77.1% (CI 95%: 65-89%). In conclusion, one of the kits is a fast and reliable tool for the identification and discrimination of MTBC and NTM from clinical isolates.