Genetic Determinants Leading to Increased Resistance to Antituberculosis

The Purpose of the Paper

The scientific article is meant to identify the genetic determinants that lead to increased resistance to antituberculosis drugs. A genome-wide association study (GWAS) was performed using the 6,465 mycobacterium tuberculosis isolates gotten from 30 countries. A phylogenetics-based test was performed for independent mutations after the GWAS under the mixed-regression framework to understand the independent mutations (Coll et al., 2018, p 307). The research incorporated insertions and deletions to enhance the detection of mutations.

The results proved that novel mutations cause resistance to pyrazinamide, cycloserine, capreomycin, ethionamide, and para-aminosalicylic acid. The results also showed the odds ratio for mutations in candidate genes which reflect the level of resistance. Besides, the article identified new epistatic relationships between the genes under investigation and drug resistance. The results also suggested that efflux pumps contribute to drug- resistance (Coll et al., 2018, p. 307). The article provides insights into the design of new diagnostic tests that can be used for research on antituberculosis drug resistance and the compensatory epistatic mechanisms.

Its relevance to other literature

The article proves the alarming prevalence in resistance of Mycobacterium tuberculosis to multiple antituberculosis drugs. Tuberculosis has become incurable because it has been a challenge to develop effective treatment when the resistance to the wide range of available drugs has increased (Coll et al., 2018, p. 308). Due to this, the treatment of patients who have experienced drug-resistant during the treatment of tuberculosis has increased. The treatment outcomes are poor and, therefore, the need to conduct this research.

The article provides insights on the drug’s high toxicity levels and poor toleration, whereby the effects become severe and sometimes irreversible. Other literature has shown the inadequate treatment of tuberculosis, which has increased the risk of antituberculosis drug resistance, threatening transmissions. Information on the mutations that cause antituberculosis drug resistance would help manufacture effective antituberculosis drugs (Coll et al., 2018, p 308). Also, from the information in the article, scientists would be able to design high-level sensitivity tests.

Methods Used to Answer the Research Questions

Whole-Genome Sequencing

The research utilized a whole-genome sequencing analysis of 6,465 clinical isolates for mycobacterium tuberculosis. It gives insights into the genetic determinants that cause antituberculosis drug resistance.

GSWA Approach

The study used a GSWA approach to understand nucleotide variation and the genome loci that cause drug resistance by using Mtb9-11 and bacteria 12, 13.

Sample Size

The sample size was from more than 30 countries representing the four major Mycobacterium tuberculosis lineages (Coll et al., 2018, p. 313). The tested sample size ranged from more than 6,000 for the first-line drugs, including rifampicin and isoniazid, to 248 for cycloserine and 255 for para-aminosalicylic acid (Coll et al., 2018, p. 313).

Investigation Using First Line and Second Line Drugs

The study did investigations on 14 drugs that had phenotypic data on drug susceptibility tests. However, the data was not available for every isolate for the 14 drugs. The research limited the use of second-line drugs due to their widespread resistance. The isolates that are susceptible to first-line drugs do not require routine testing to sensitivity.

Interpretation of the Figures

Figure 1

Shows geographical distributions of the mycobacterium tuberculosis isolates that were used in the study. The study involved large samples identifying the infrequent genetic effects and reducing misclassification and any errors during phenotypic drug susceptibility testing (Coll et al., 2018, p. 308). The figure also shows that resistance is prevalent in many countries. If the resistance is not addressed, more countries will likely be affected in the future, making it hard to deal with resistance to the drugs.

Figure 2

Shows the whole-genome phylogeny of the Mtb isolates used in the study, which helps identify the specific loci involved with the resistance (Coll et al., 2018, p. 308).

Summary of Findings 


The inclusion of samples reduced the possibility for bias which occurs to the lack of standardization for the methodologies employed for the phenotypic testing methodologies of Mtb. The research also ensured the completeness of the susceptibility test data, making it possible to utilize the homoplasy-based methods and the GWAS across the 14 drugs used (Coll et al., 2018, p. 314).


However, the study had a limitation in the sampling method since there was no control or systematic approach during the collection of isolates due to the sample size and geographic locations; it was difficult to distribute the resistant isolates across the collection sites evenly.


Despite this, the research is reliable, and the methods are precise and explained well. The study covered the major Mtb lineages, making it possible to understand the differences in the mechanisms and prevalence of mutations causing Mtb drug resistance (Coll et al., 2018, p. 314). The conclusion is appropriate, and it gives insights on what to be looked out for when developing more accurate molecular diagnostics for the drug resistance to tuberculosis.


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