Departamento de Doenças Infecciosas
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Browsing Departamento de Doenças Infecciosas by Subject "16S rRNA"
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- Identification of nontuberculous mycobacteria by partial gene sequence and public databasesPublication . Joâo, Inês; Cristovão, Paula; Antunes, Liliana; Nunes, Baltazar; Jordão, LuísaBackground: Nontuberculous mycobacteria (NTM) are a heterogeneous group of microorganisms with distinct clinical relevance. The treatment of NTM infections depends significantly upon the crucial identification of species at this level. The steady increase of mycobacteria species, the use of time-consuming techniques and the lack of standardized identification methods makes the achievement of this goal a demanding challenge. Additionally, inaccurate diagnosis can lead to therapeutic approaches consistent with Mycobacterium tuberculosis infection that are useless. In the present study, the performance of public databases in the accurate identification of NTM by sequence analysis of 16S rRNA and hsp65 genes were evaluated and compared. An algorithm is proposed to achieve an accurate classification of NTM in the geographic region of Portugal (Western Europe). Methods: Partial sequencing of 16S rRNA and hsp65 genes of 22 reference strains and 54 clinical isolates was performed. The resulting sequences were analysed by public web databases since their performance is evaluated statistically. The phenotypic characteristics of the isolates were also evaluated. Results: The use of commercial kits allowed the accurate identification of 57.4% of the clinical isolates. This result was improved either by the use of 16S rRNA (75.9%) and hsp65 (88.9%) genes analysis alone or combined (96.3%. Conclusions: Analysis of 16S rRNA gene alone is insufficient for the accurate identification of NTM. A stepwise algorithm combining 16S rRNA and hsp65 gene analysis by multiple public databases is proposed to identify NTM at the species’ level.
- Validação de um algoritmo para identificação de Mycobacterium spp. no diagnóstico laboratorialPublication . João, Inês; Jordão, Luisa; Hänscheid, ThomasThe last decade of the 20th century was marked by the appearance of the HIV pandemic. Together with this plague came not only the resurgence of tuberculosis but also the appearance of opportunistic infections due to nontuberculous mycobacteria (NTM) mainly by members of Mycobacterium avium complex (MAC). Later on these opportunistic infections were also often described in other groups of patients (e.g., organ transplanted and oncologic patients), which shared a compromised immune system. Concurrently, the number of NTM recognized as potential ethological agents of human diseases increased. Among these we highlight M. kansasii, M. abcessus, M. chelonae, M. malmoense and M. xenopi. Currently, NTM infections are an important health care problem, affecting both immunodepressed and immunocompetent individuals, with difficult diagnose and treatment since NTM are highly resistant to the available drugs. This fact lead us to a paradoxical situation in which microorganisms rated as level 1 and 2, based on biohazard classification, represent a threat similar to Mycobacterium tuberculosis multidrug resistant strains. The first step to overcome this problem is the implementation of fast and efficient diagnosis methods. This will enable the physician to diagnose and rapidly implement a therapeutical scheme in order to treat the patient and prevent the spread of the disease within the community. The present work intends to be a step forward to the achievement of this goal. In the present work 54 NTM strains from the INSA, Infection Diseases Department bacterial collection (years 2008-2009) were identified at least by two molecular biology methods following accepted guidelines. The results rendered by three different methods (PRA-hsp65, 16S rRNA and hsp65 sequention) were compared in order to analyze their performance in NTM identification. The main conclusion drawn from this work is that the correct identification of a NTM can only be achieved by the combination of at least two different methods. Usually is necessary to combine genotyping methods with the analysis of key phenotypic characteristics.