Ask a german researcher and he may answer “yes, it is”, expecially if the german researcher you question is Stefan Niemann from the Molecular Mycobacteriology Department of the Forschungszentrum Borstel Institute in Sülfeld, Germany. Niemann’s team primary aim was to find a SNP-based distinction able to classify different Mycobacterium tuberculosis strains.  They considered 86 different strains of M. tuberculosis isolated from a TB outbreak in the german lander of Hamburg and Schleswig-Holstein in a period between 1997 and 2010, in wich more than 2000 people were affected by tubercolosis. They compared the classical genotyping, a standard test in matter of different strains classification,  with a whole genomic sequencing- based approach. This new test was found to provide more accurate informations on clustering and longitudinal spread of the patogen than the classical genotiping standard test. It is important to say that the whole genome sequencing revealed many falsely cludered by classical gentyping.

The whole genome sequencing let the authors estimate that the genetic material of M. tuberculosis evolved at a 0.4 mutations rate per genome per year, suggesting that the bacterium grows in infected people with a doubling time of 22 hours and 400 generations per year.

This article is a good proof of the potential of bioinformatics and new sequencing approaches. These methods provide more accurate information, can be applied in several fields of biological research and their cost is progressively decreasing. We can say that there is a good probability that these methods can become the new standards surpassing the classical genomics methods.

The authors of the article seem to believe this too: “Our study demonstrates that whole genome sequencing-based typing provides epidemiologically relevant resolution of large, longitudinal (Mycobacterium tuberculosis) outbreaks much more efficiently than classical genotyping. (…) We envision that (whole genome sequencing) progressive effective implementation will be accelerated by the continuously decreasing sequencing costs, broader distribution of so-called bench top genome sequencers, and upcoming bioinformatics developments to facilitate quick and relevant interpretation of the resulting data in public health and medical contexts.”



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