Tuberculosis has shaped human society since the Stone Age

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Mycobacterium tuberculosis bacterium, which causes the disease. Image: NIAB (Flickr)

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The researchers Clara Prats, Martí Català and Pere-Joan Cardona, co-authors of the study

Researchers from the Germans Trias i Pujol Research Institute (IGTP), the Comparative Medicine and Bioimaging Centre (CMCiB-IGTP), CIBERES and the UPC have discovered, by means of a mathematical model that combines biological, anthropological and historical data, that not only have humans continued to survive despite tuberculosis infections, but tuberculosis has probably played a key role in shaping human society as we know it. The article has been published in the journal Scientific Reports.

Feb 24, 2020

Tuberculosis (TB), caused by the microbe Mycobacterium tuberculosis complex (MtbC), has been infecting humans since the Old Stone Age, or Paleolithic period, when small groups of people lived as hunter-gatherers. Around 43,000 years ago, during the Neolithic period, people started to stay in settlements and create farms, and about this same time the most virulent modern form of tuberculosis developed. TB is a devastating disease, it has killed about an estimated one billion people—the current population of the American continent—in the last 200 years and raises interesting questions. Why did it not kill off the small population of early humans? How have both TB and its hosts survived? And why do women seem to be more resistant to the disease than men?

To answer these questions a team led by Pere-Joan Cardona of the Experimental Tuberculosis Unit (UTE) at the Germans Trias i Pujol Research Institute (IGTP) has carried out complex detective work using a mathematical model to combine biological, anthropological and historical data. The result is staggering: not only have humans continued to survive despite TB infections, but TB has probably played a key part in shaping human society as we know it.

The study is a collaboration between the IGTP, the Comparative Medicine and Bioimaging Centre (CMCiB-IGTP), the Respiratory Diseases Networking Biomedical Research Centre (CIBERES) and the Universitat Politècnica de Catalunya · BarcelonaTech (UPC). The paper has been published in the journal Scientific Reports.

“It is a long story of the battle between people and bacteria”, explains Martí Català, a student on the UPC’s doctoral programme in Computational and Applied Physics and the modeller of the team. “When the disease appeared in the Paleolithic, population growth fell from 1% to only 0.003%. Small groups that got infected probably died out. Our model shows that at that time, when infant mortality was 50%, women needed to have two surviving children (meaning four births) just to maintain the population. When the modern strains of Mycobacterium tuberculosis appeared, the disease became more deadly and this rose so that women needed to have three surviving children, or six births, just to continue the species”.

Why people transitioned from hunter-gathering to a settled farming life at a time when the habitable parts of the world were limited to the land between the Indian subcontinent and Australia due to widespread glaciation has never been properly understood. So far, there had been no obvious reason for this change.

“Our data suggest that the only way for our species to survive the ravages of TB was to increase fertility and the best way to do so was probably to start farming and increase food production”, explains the professor Clara Prats, a researcher from the Computational Biology and Complex Systems Group (BIOCOM-SC) linked to the UPC’s Department of Physics and the coordinator of the in silico modelling programme at the CMCiB-IGTP that has developed the model. “Data suggest that the death of entire groups could only be halted by an unprecedented increase in population (a multiplication of 20 times in 100 years). A resistance to the disease for people who had been infected by earlier bacterial strains but survived also developed around this time. Ironically, moving from the fresh air, exercise and open country to towns with smoky buildings and poor sanitation made people less healthy than they had been and more susceptible to infection”, adds Prats, who is also a professor at the Barcelona School of Agriculture (ESAB).

“Our model also shows that female resistance was a key part in this ongoing battle”
, says Cardona. “It means that we must rethink the factors involved in population growth in the Paleolithic, which will be essential to understand how both MtbC and humans have survived. We also need to learn more about why females are more resistant to TB, as it not only sheds light on the evolution of our species, but is also vital to today’s ongoing fight to stop TB from causing debilitating disease and death as it is still doing today”.

Data and modelling to paint a picture of our story
This study was conducted at the CMCiB-IGTP in conjunction with the UPC using a mathematical model. The team designed a compartmental mathematical model (TBOREX: TB, origin and sex) based on five differential equations to describe the dynamics of MtbC infection in the population. It allows researchers to model a standard scenario of a human group with one infected person and then add and modify several factors to see how they affect population dynamics over time. This research model was used to study how the ancient and modern strains of TB interacted, what factors are needed to sustain TB epidemics and how female resistance has been essential for the co-evolution of MtbC and humans.

Cardona stresses the importance of these new research techniques. “This is an important part of the work of the CMCiB, using so-called in silico or computational techniques to leverage existing data from experiments to make new discoveries. In this case, we have new information about our past, but also about how we can better defend ourselves against one of the major threats to humankind in the modern age”. The study is part of a project supported by ”la Caixa” Foundation that promotes new experimental methods to reduce or remove the need for animal experiments (LCF/PR/GN16/10290002). “In this case we have built a new in silico model for studying infectious disease”, adds Cardona.