Carneiro Sofia, Pinto Miguel, Rodrigues Joana, Gomes João Paulo, Macedo Rita
National Reference Laboratory for Mycobacteria, Department of Infectious Diseases, National Institute of Health, Lisbon, Portugal; Department of Life Sciences, NOVA School of Science and Technology, NOVA University Lisbon, Caparica, Portugal.
Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health, Lisbon, Portugal.
Infect Genet Evol. 2024 Nov;125:105682. doi: 10.1016/j.meegid.2024.105682. Epub 2024 Oct 20.
Opportunist infections caused by nontuberculous mycobacteria (NTM) have emerged as a significant public health problem. Among these, species of the Mycobacterium avium complex (MAC) are the main responsible for the increase in the number of human disease cases. In order to address the current needs in the detection and surveillance of MAC disease cases, we evaluated different species classification methodologies (BLASTn-based marker-gene approach, Kraken v2, rMLST and MLST databases) and their congruence with a core-SNP phylogenetic approach, based on whole genome sequencing (WGS) data. For this purpose, we used a collection of 142 MAC isolates from Portuguese patients diagnosed between 2014 and 2022. The marker-gene approach (based on the rpoB, hsp65 and groEL genes), showed the best results, allowing the identification of the 142 MAC isolates to the species/subspecies level (M. avium subsp. hominissuis, M. intracellulare, M. intracellulare subsp. chimaera, M. intracellulare subsp. yongonense, M. marseillence and M. colombiense). Additionally, we performed drug susceptibility testing that confirmed clarithromycin efficacy as a first-line treatment for MAC disease, as 93 % of the Portuguese isolates were susceptible. Using a core-SNP approach we also performed an in-depth phylogenetic analysis within each identified species group, and despite the high genetic diversity within the MAC species, we were able to clearly distinguish all the species/subspecies and identify genetic clusters with epidemiological potential. We highlight not only the need for the standardization of an appropriate genotyping approach for species identification and management of MAC disease, but also a more robust large-scale WGS data analysis, in a One Health perspective, in order to identify potential routes of transmission.
非结核分枝杆菌(NTM)引起的机会性感染已成为一个重大的公共卫生问题。其中,鸟分枝杆菌复合群(MAC)的菌种是导致人类疾病病例数增加的主要原因。为了满足当前对MAC疾病病例检测和监测的需求,我们评估了不同的菌种分类方法(基于BLASTn的标记基因方法、Kraken v2、rMLST和MLST数据库)及其与基于全基因组测序(WGS)数据的核心SNP系统发育方法的一致性。为此,我们使用了一组来自2014年至2022年期间被诊断出的葡萄牙患者的142株MAC分离株。标记基因方法(基于rpoB、hsp65和groEL基因)显示出最佳结果,能够将142株MAC分离株鉴定到种/亚种水平(鸟分枝杆菌亚种人型、胞内分枝杆菌、胞内分枝杆菌亚种嵌合体、胞内分枝杆菌亚种永贡、马赛分枝杆菌和哥伦比亚分枝杆菌)。此外,我们进行了药敏试验,证实克拉霉素作为MAC疾病的一线治疗药物有效,因为93%的葡萄牙分离株对其敏感。使用核心SNP方法,我们还在每个鉴定出的物种组内进行了深入的系统发育分析,尽管MAC物种内存在高度的遗传多样性,但我们能够清楚地区分所有的种/亚种,并识别具有流行病学潜力的基因簇。我们强调不仅需要标准化一种适用于MAC疾病菌种鉴定和管理的基因分型方法,还需要从“同一健康”的角度进行更强大的大规模WGS数据分析,以识别潜在的传播途径。