Gradient_BG

Discovering Drug Resistance Using DNA Sequencing

Written by Psomagen
0 min

What is Drug Resistance?

The World Health Organization (WHO) defines drug resistance (also called antimicrobial resistance) as the change that occurs in microorganisms that renders medications ineffective. There are other types of drug resistance, such as cancer cell resistance to chemotherapeutic agents. This discussion, however, will focus on antimicrobial drug resistance. As antimicrobial drugs become less effective, it is more difficult to combat infections that were previously manageable. Developing means to rapidly and accurately detect and identify resistant microbial strains is vital to managing and overcoming drug-resistance challenges.

What are Current Common Approaches to Drug Resistance Testing?

There are a number of widely used and conventional approaches to drug-resistance testing. One method is bacterial isolation, culture, and drug exposure. PCR-based testing is another approach used to detect the presence of resistant bacterial strains. Polymerase Chain Reaction (PCR) based testing works by amplifying genes already known to be associated with drug resistance in a given bacterial species. In 2008, the WHO endorsed molecular line probe assay (LPA) technology which is a method used to rapidly detect multidrug-resistant tuberculosis. This test is performed by obtaining DNA from M. tuberculosis isolates or clinical specimen. PCR is used to amplify specific drug-resistance gene regions; however, the PCR products are immobilized on a strip, and detection is achieved via a colorimetric reaction.

 

DNA Sequencing Technology and Drug Resistance Testing (DRT)

Whole Genome Sequencing for DRT VS. Other Common Methods: What are the Advantages of WGS?

The conventional approaches to DRT demonstrate limitations in regards to the most effective means to track and identify drug-resistant organisms. In the case of the bacterial culture/drug exposure approach, the effort to determine all drugs to which an isolated microbe is susceptible would be laborious, costly, and time-consuming (it can take weeks or even months). Also, a higher chance of misdiagnosis is possible when an infection is caused by a mix of isolates or unrelated bacterial strains.

The benefit of PCR-based technologies is the ability to rapidly amplify specific gene sequences known to be associated with drug resistance in a given bacterial species. However, some information regarding which sequence to detect is necessary. Similarly, line probe assays also provide rapid detection, but previous knowledge of sequence data is still necessary.

With the WGS approach, previously unknown sequence information can be obtained. This is a significant advantage to other common drug resistant testing approaches. The improved power and resolution, lower cost, and speed of high-throughput WGS have greatly impacted and benefited epidemiological efforts, such as identifying and tracking drug-resistant organisms.

How has WGS furthered DRT Already?

Many drug resistance determinants have been successfully identified for numerous pathogenic bacteria (such as ampC in E. coli and mecC in S. aureus) using WGS technologies. Blood cultures of a male patient with cardiomyopathy and soft tissue necrosis revealed an infection by a β-lactamase producing E. coli. Whole genome sequencing performed on bacterial isolates uncovered several resistance genes such as AmpC2.

The possibility of a meticillin-resistant S. aureus (MRSA) outbreak in a special care baby ward in Europe was investigated using whole genome sequencing of isolates from the patients and community members. The sequencing data revealed MRSA carriage and transmission within the ward and in the community. It also showed that an infected staff member was linked to persistence of the outbreak (3).

The Case for Tuberculosis

The existence of multi-, extensively, and total drug-resistant tuberculosis strains poses significant challenges to treatment and increases the threat to public health. Whole genome sequencing approaches can have a high impact on the public health threat from tuberculosis since this technology can allow the complete characterization of drug resistance. However, the immensity and complexity of the data obtained poses challenges that must be overcome to translate to clinical applications.

New tools are essential in order to process and interpret the ever-increasing DNA sequence data. Coll, et al. (4) have developed a tool called the TB-Profiler to bolster drug-resistance testing efforts. They compared in silico whole-genome analysis to conventional DRT testing for 11 anti-TB drugs. The online TB Profiler tool inputs raw sequence data (from a library of over 1000 mutations), identifies drug resistance and lineage-specific mutations, and outputs the corresponding data. This analytical approach provides a means to predict resistance to the 11 anti-TB drugs tested. Given the need for early diagnosis of tuberculosis, and subsequent effective and minimally or non-toxic treatment, having the full drug-resistance profile of strains would greatly improve treatment success.

 

How Has DNA Sequencing Been Used for Infectious Disease Management?

The power of WGS has been harnessed to study the emergence of drug resistance in the clinical realm. Not only can the application of sequencing technology identify current drug-resistant pathogens, but it can also provide clues as to the potential for a pathogen to become resistant. This is possible via the identification of genes that are precursors to resistance genes (called proto-resistance genes) (5)

Whole genome sequencing technologies have been used to identify resistance determinants, and this information exists in databases such as the Antibiotic Resistance Genes Database. Whole genome sequencing data can bolster the design of new and more accurate diagnostic assays/test kits that can be used in the field or clinical laboratory. A number of tests continue to be developed that are based on accumulated genomic information for drug-resistant bacteria, such as the mecC-based test proposed by Paterson et al to detect resistant S. aureus. (6) The utility and power of WGS as an approach to detect and combat drug resistance would be strengthened with easy-to-implement bioinformatics tools to efficiently manage and interpret the ever-increasing sequence databases. So that the information can be used with confidence at the clinical and epidemiological level, protocols and methods for validation are paramount. Armed with the antibiotic-resistance profiles of pathogens, it would be possible to greatly facilitate the development of new effective antibiotics and the design of personalized therapies. Linking WGS data from humans to that of microorganisms can further achieve increased recovery from infectious diseases and reduction of morbidity in a population. This is important in examining the host-pathogen relationship and the factors that are associated with human susceptibility to drug-resistant microorganisms.

 

 

 

References

  1. WHO policy statement: molecular line probe assays for rapid screening of patients at risk of multidrug-resistant tuberculosis. http://www.who.int/tb/laboratory/line_probe_assays/en/
  1. Buchanan R, Stoesser N, Crook D, Bowler IC. Multidrug-resistant Escherichia coli soft tissue infection investigated with bacterial whole genome sequencing. BMJ case reports. 2014;2014.
  1. Harris SR, Cartwright EJ, Torok ME, Holden MT, Brown NM, Ogilvy-Stuart AL, et al. Whole-genome sequencing for analysis of an outbreak of methicillin-resistant Staphylococcus aureus: a descriptive study. The Lancet Infectious Diseases. 2013;13(2):130-6.
  1. Coll F, McNerney R, Preston MD, Guerra-Assuncao JA, Warry A, Hill-Cawthorne G, et al. Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome medicine. 2015;7(1):51.
  1. Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nature Reviews Genetics. 2013;14(4):243-8.
  1. Paterson GK, Harrison EM, Holmes MA. The emergence of mecC methicillin-resistant Staphylococcus aureus. Trends in microbiology. 2014;22(1):42-7.