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1.
Nat Prod Res ; : 1-15, 2024 Jun 04.
Article in English | MEDLINE | ID: mdl-38832530

ABSTRACT

Despite the many advances in drug research, natural products are still being explored as a promising source for discovering new bioactive compounds to treat global diseases such as tuberculosis. However, there is a lack of studies and information about coastal natural products, which thrive in the transitional environment between two different ecosystems and produce unique secondary metabolites. Mangroves, estuaries, and mudflats make up areas for coastal species and have shown promising results in antituberculosis research, some of them are present in hotspot areas. This review focuses on research conducted in coastal environments and explores the reasons why these natural products tend to outperform non-coastal ones against the causative agent of tuberculosis, Mycobacterium tuberculosis.

2.
Microbiol Spectr ; 12(6): e0350623, 2024 Jun 04.
Article in English | MEDLINE | ID: mdl-38651877

ABSTRACT

Tuberculosis (TB) and infectious diseases caused by non-tuberculous mycobacteria (NTM) are global concerns. The development of a rapid and accurate diagnostic method, capable of detecting and identifying different mycobacteria species, is crucial. We propose a molecular approach, the BiDz-TB/NTM, based on the use of binary deoxyribozyme (BiDz) sensors for the detection of Mycobacterium tuberculosis (Mtb) and NTM of clinical interest. A panel of DNA samples was used to evaluate Mtb-BiDz, Mycobacterium abscessus/Mycobacterium chelonae-BiDz, Mycobacterium avium-BiDz, Mycobacterium intracellulare/Mycobacterium chimaera-BiDz, and Mycobacterium kansasii-BiDz sensors in terms of specificity, sensitivity, accuracy, and limit of detection. The BiDz sensors were designed to hybridize specifically with the genetic signatures of the target species. To obtain the BiDz sensor targets, amplification of a fragment containing the hypervariable region 2 of the 16S rRNA was performed, under asymmetric PCR conditions using the reverse primer designed based on linear-after-the-exponential principles. The BiDz-TB/NTM was able to correctly identify 99.6% of the samples, with 100% sensitivity and 0.99 accuracy. The individual values of specificity, sensitivity, and accuracy, obtained for each BiDz sensor, satisfied the recommendations for new diagnostic methods, with sensitivity of 100%, specificity and accuracy ranging from 98% to 100% and from 0.98 to 1.0, respectively. The limit of detection of BiDz sensors ranged from 12 genome copies (Mtb-BiDz) to 2,110 genome copies (Mkan-BiDz). The BiDz-TB/NTM platform would be able to generate results rapidly, allowing the implementation of the appropriate therapeutic regimen and, consequently, the reduction of morbidity and mortality of patients.IMPORTANCEThis article describes the development and evaluation of a new molecular platform for accurate, sensitive, and specific detection and identification of Mycobacterium tuberculosis and other mycobacteria of clinical importance. Based on BiDz sensor technology, this assay prototype is amenable to implementation at the point of care. Our data demonstrate the feasibility of combining the species specificity of BiDz sensors with the sensitivity afforded by asymmetric PCR amplification of target sequences. Preclinical validation of this assay on a large panel of clinical samples supports the further development of this diagnostic tool for the molecular detection of pathogenic mycobacteria.


Subject(s)
Mycobacterium Infections, Nontuberculous , Mycobacterium tuberculosis , Nontuberculous Mycobacteria , Polymerase Chain Reaction , Humans , Mycobacterium tuberculosis/genetics , Mycobacterium tuberculosis/isolation & purification , Polymerase Chain Reaction/methods , Mycobacterium Infections, Nontuberculous/diagnosis , Mycobacterium Infections, Nontuberculous/microbiology , Nontuberculous Mycobacteria/genetics , Nontuberculous Mycobacteria/isolation & purification , Nontuberculous Mycobacteria/classification , Sensitivity and Specificity , RNA, Ribosomal, 16S/genetics , Tuberculosis/diagnosis , Tuberculosis/microbiology , DNA, Bacterial/genetics , Biosensing Techniques/methods
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