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In the article mycobacterium tuberculosis (Mtb) has contributed to the rise of a health hazard, thus helping to the use of medicine that fights this bacterium. Genome sequencing is used to relate the increase of the bacteria withdrawn from cynomolgus macaques, which are mobile. The bacterium has grown over the period of the previous years due to mutations, and thus in treatment, the patients with tuberculosis are treated with a couple of drugs. In Mtb the patients are treated with one antibiotic isoniazid(INH) this is because this infection has a different form of mutation of the bacteria thus, different antibiotics cannot be used. To ensure complete treatment, the rate of variation has to be figured out to determine the percentage of resistance towards the drug. Whole genome sequencing(WGS) provides the mutation rate of Mtb when one has been infected. The hypothesis that Ford, et al, proposed was that Mtb has a similar number of mutations during the latency stages and active disease stages.
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To support this hypothesis, Ford and his colleagues conducted whole genome sequencing on an extracted pure genetic material from cynomolgus macaques. A procedure of WGS was applied on Mtb, Erdman, 33 isolates from 9 cynomolgus macaques that were part of the three possible results of the infection which included; active, latent, and proactive after dominated latency. In the results, the genome covered 93% in the 33 isolates, and the penetration was one hundred and seventeen times in the genomes. The INDELs were not recognized in the 33 genomes analyzed. The SNPs were seen through WGS in thirty-three Mtb Strains separated from 9 cynomolgus macaques during various stages of the infection. These SNPs were also inferred in Sanger sequencing. The average rate of mutation of the bacteria was also gathered. This can be estimated by getting the number of variations that have transpired in a genome over a value of organisms. In vivo, unlike vitro, which is faster, the mutation degree in an average of hours between 17-241 hours by use of polymorphism given by Whole Genome Sequencing.
The article concluded that the mutations occur at similar rates despite the level of the infection. The SNPs showed the rate of mutation in the bacterium during its life, and the number of mutations is assumed to be the right way of calculating the mutation rate in the cell. The results show the significance of drug opposition challenges and keen nursing of patients with such an infection. It was also concluded that the use of one type of antibiotic increases the risk of developing Mtb resistant strains. Moreover, after the administration of antibiotics, the drugs only kill the susceptible bacteria, leaving the mutated ones. The process reactivates the mutation process resulting in more severe infections. Mtb strain has in vivo mutation, which is consistent in terms of the number of mutations. Hence, based on epidemiologic studies, external factors like chemicals will have no influence on the mutation process. It was also concluded that there is a strong connection between Mtb resistant strain and HIV+ individuals due to suppressed immunity. Such patients are at high risk of having resistant strains of Mtb.
The data collection involved the generation of two read lengths of 2 by 75 base pairs were than snipped to ensure the purity of bases, later to go under filtration. To ensure all the base pairs were known, all the chromosomes containing unknown bases were discarded. Eight million reads were left after the process of filtering. The processing of the filtered reads was done with Edena v2.1.110, that permitted for the detection and insertion of nitrogenous bases in the chromosomes. The change in genetic makeup within the chromosome was then established. Counting the number of newly formed was done using statistical analysis of WGS data. The selection of scientific statistical data should be able to detect the changes in Mtb after sequencing the newly formed chromosome after mutations.
The comparison of the number of chromosomal mutations during the latent and active disease stages showed that Mtb is prone to mutations which creates the resistance to antibiotics. The Ford et al. hypothesis was evident after the end of the study which proved that Mtb has a similar number of mutations during the latency stages and active disease stages. Statistical analysis of WGS data helped the researchers to account for all the base pairs formed after the research. The research, therefore, explained the reason for Mycobacterium tuberculosis antibiotic resistance.
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