The relationships of gene mutations between ESX and drug resistance in the patients with extra-pulmonary tuberculosis in local regions of Southwest China
Jiwen Fan , Haoming Feng , Dazhi Yang , Haiyang Zhao , Tao Shi , Tongxin Li
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引用次数: 0
Abstract
Background
Drug resistant extrapulmonary tuberculosis (DR-EPTB) is a major threat to human health. The mycobacterial ESAT-6 secretion (ESX) system is main virulence protein export system of Mycobacterium tuberculosis (MTB). This study aimed to determine the relationships between ESX and drug resistance (DR) in patients with DR-EPTB in local regions of Southwest China.
Methods and design
Patients were retrospectively studied from January 2020 to December 2021. All the isolates were cultured, drug susceptibility was detected, and gene mutations were detected using whole-genome sequencing (WGS). The correlations between the mutant genes of the ESX system and DR pattern, patient demographics, and DR mutant gene sites were analyzed.
Results
A total of 111 patients with DR-EPTB were enrolled including 40 females and 71 males. In the five ESX systems there were 1664 gene mutation sites and ESX-3 accounted for 32.6 %. The most common mutant gene site in all the ESX systems was eccC2. There was a significant difference in the number of mutant gene sites between ESX-1 and DR (P < 0.01). There were significant correlations between the numbers of mutant gene sites in the different ESX systems and gender (P < 0.05), age group (P < 0.05), residence (P < 0.01), type of treatment (P < 0.01), lineage (P < 0.01) and cluster (P < 0.01).
Conclusion
In patients with DR-EPTB, ESX-3 was the system that included the most mutant gene sites and the eccC2 gene had the highest frequency. The gender, age group, residence, type of treatment, lineage and cluster were risk factors for gene mutations in the ESX system. The mutant gene sites of ESX-1 were correlated with those of DR and the mutations in espA and espK may be the main factors.
期刊介绍:
(aka Journal of Molecular Epidemiology and Evolutionary Genetics of Infectious Diseases -- MEEGID)
Infectious diseases constitute one of the main challenges to medical science in the coming century. The impressive development of molecular megatechnologies and of bioinformatics have greatly increased our knowledge of the evolution, transmission and pathogenicity of infectious diseases. Research has shown that host susceptibility to many infectious diseases has a genetic basis. Furthermore, much is now known on the molecular epidemiology, evolution and virulence of pathogenic agents, as well as their resistance to drugs, vaccines, and antibiotics. Equally, research on the genetics of disease vectors has greatly improved our understanding of their systematics, has increased our capacity to identify target populations for control or intervention, and has provided detailed information on the mechanisms of insecticide resistance.
However, the genetics and evolutionary biology of hosts, pathogens and vectors have tended to develop as three separate fields of research. This artificial compartmentalisation is of concern due to our growing appreciation of the strong co-evolutionary interactions among hosts, pathogens and vectors.
Infection, Genetics and Evolution and its companion congress [MEEGID](http://www.meegidconference.com/) (for Molecular Epidemiology and Evolutionary Genetics of Infectious Diseases) are the main forum acting for the cross-fertilization between evolutionary science and biomedical research on infectious diseases.
Infection, Genetics and Evolution is the only journal that welcomes articles dealing with the genetics and evolutionary biology of hosts, pathogens and vectors, and coevolution processes among them in relation to infection and disease manifestation. All infectious models enter the scope of the journal, including pathogens of humans, animals and plants, either parasites, fungi, bacteria, viruses or prions. The journal welcomes articles dealing with genetics, population genetics, genomics, postgenomics, gene expression, evolutionary biology, population dynamics, mathematical modeling and bioinformatics. We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services .