Case studies
Combining comparative analysis approaches with AMR detection opens the door to a wide range of analyses. One primary research area that used these tools is AMR epidemiology, which focuses on tracking the spread of antimicrobial-resistant strains and plasmids within a population.
In this step, we will present two case studies monitoring AMR strains that you may find interesting to explore:
Using comparative analysis to identify source MDR M. tuberculosis outbreak
Walker et al. used core genome analysis to identify 29 cases of M. tuberculosis across seven European countries, over a 14-month period, among immigrants from Northern Africa. In this analysis, any two cases were found to be within 2 SNPs or less of at least one other case in the cluster.
When undertaking a comparative analysis it is important to also include appropriate contextual sequences to provide insights into the population structure. The authors used a further 29 sequences which had a similar MIRU-VNTR profile (a mid-resolution typing tool used for this pathogen) as context, to demonstrate the possible diversity within the population. Using epidemiologic data, including travel history and date of disease onset, the authors determined that transmission probably occurred prior to arrival in Europe, possibly in Somalia or Djibouti.
Further analysis of the drug resistance mechanisms within this cluster revealed a background of capreomycin resistance, characterized by a common mutation (tlyA N236K) present in all sequences. The outbreak strains and all other sequences from Djibouti shared the same mutations conferring resistance to rifampicin, isoniazid, and ethambutol. However, only the outbreak strains exhibited additional resistance to pyrazinamide.
In cases like this, additional temporal analysis can be conducted. However, the nature of M. tuberculosis pathogenesis can complicate this, as the dates of symptom onset usually do not correspond to the dates of acquisition.
Genomic approaches for monitoring transmission of Vancomycin resistant E. faecium (VREfcm)
Higgs et al tested a range of core genome based approaches to develop a strategy for identification of transmission of VREfcm within a hospital setting. By using a step-wise approach that combines core genome multilocus sequence typing (cgMLST) and split k-mer analysis, Higgs et a demonstrated that whole genome comparative analysis can effectively identify the wards that are likely sources of transmission (Figure 1). This information can assist officials in implementing accurate containment measures to limit the spread of VREfcm.
Figure 1. Transmission network of VREfcm from a hospital setting. The various colouring and labelling schemes show how high-level strain typing (ST groupings) can be broken down into more granular genome-based transmission clusters using cgMLST and even further using k-mer based (SKA2) and SNP-based approaches. See Figure 5 from the original paper for a more detailed explanation: https://www.nature.com/articles/s41467-022-28156-4/figures/5
Do you know of any AMR epidemiology studies undertaken on your pathogen of choice? Share them below and briefly explain their main finding.
Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis
Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis
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