Harmonized genome wide typing of tubercle bacilli using a web-based Gene-by-Gene nomenclature system
An international research team led by the Research Center Borstel, developed a new method to label tubercle bacilli, the causative agents of tuberculosis with unique identifiers created from whole genome sequence data. The results of the study, published recently in The Lancet journal EBioMedicine, allow for high resolution pathogen surveillance based on easy-to-read genomic signatures, and thus to identify and combat outbreaks earlier.
Tuberculosis (TB) is caused by bacteria from the Mycobacterium tuberculosis complex (Mtbc), and is still one of the deadliest human infectious diseases. Treatment is long and difficult, and patients are often left with serious health problems even if the disease can be cured. TB not only affects individual health, it is also major poverty risk of TB case family members especially for vulnerable communities. In recent years, multidrug (MDR) and extensively drug resistant (XDR) strains, impervious to the most important drugs, have emerged on a global scale. As there is no environmental reservoir known for Mtbc bacteria, controlling human-to-human transmission is key for successful local and global TB control, and for achieving the targets of the “End TB strategy” proposed by the World Health Organization
To analyze and detect transmission, the ability to uniquely label and recognize a strain of a bacterial pathogen from its genome, i.e. genotyping, has become essential. Pathogen genotypes are key for public health officials to recognize transmissions occurring in a local setting, such as an acute outbreak of TB in a city or region. In addition, transmission of strains can be traced across borders, which is especially important for the particularly threatening MDR/XDR strains. Based on high resolution transmission analysis data, effective measures to reduce transmission can be developed.
In the current study, a collaborative team of experts from a bioinformatics company, public-health institution, a research institute and universities in Germany and the United Kingdom led by Stefan Niemann from the Research Center Borstel and the German Center for Infection Research developed an approach that reliably translates the genome sequence of TB pathogens into a set of 2891 (allele) numbers. This creates a unique identifier for any Mtbc strain. By comparing the respective sets of numbers, the relatedness of two or more pathogen strains can be measured, allowing for the detection of likely recent transmission chains or ongoing outbreaks.
The authors of the study extended their previous work and demonstrated that the refined approach is able to reliably classify strains from all pathogen types causing TB in humans. Using a huge dataset from the United Kingdom for calibration, they defined the maximum number of allele differences, i.e. distinct numbers in the unique identifier, for a direct connection by transmission between the tuberculosis pathogens from two patients. Furthermore, they combined the method with a web-based nomenclature server that harmonizes tracing of clinical Mtbc strains needed for prospective local and global surveillance.
“Several studies have shown the incredible usefulness of whole genome data for a detailed understanding of the transmission dynamics of tuberculosis. However, a standardized way to classify all tubercle pathogens for easy communication between laboratories and/or public health officials on the local, national, and international level was missing.” said Prof Stefan Niemann, senior author of the study.
In light of declining costs to generate whole genome data, and the currently ongoing adoption of the technology by laboratories around the world, genotyping using genome sequencing may become the standard for the analysis of bacterial pathogens such as those causing tuberculosis.
“One of the main advantages of the suggested approach is its simplicity. The precise identifier of a potentially dangerous multiple resistant strain identified in one country can even be distributed by a simple email.” said Dr Thomas Kohl, first author of the publication.
The team of Prof Stefan Niemann is currently working together with partners and public health institutions in Europe and worldwide to assess the full usefulness of the approach in active infectious disease surveillance and to set up best practices for its implementation. These efforts are also supported by the Thematic Translational Unit Tuberculosis of the German Center for Infection Research (DZIF).
