13 March 2019
In March of 1882, Robert Koch used tissue from infected guinea pigs to show that the lung disease tuberculosis (TB) is caused by the organism Mycobacterium tuberculosis. At that time, TB was a constant presence in the population, infecting between 70 to 90 percent of people in urban areas of Europe and North America. Nowadays, although the mortality due to TB has reduced in developed countries, it remains a huge health issue and March is recognised globally as TB Awareness Month. In fact, the disease is still the leading cause of infection-related death worldwide, with up to one-third of the human population having latent TB.
Mice are resistant to TB, so in nature, you would never find a mouse with TB infection. Sadly, this does not save them from a life of laboratory experimentation. To get around their natural immunity, researchers manipulate mouse genetics, deleting mouse genes, and sometimes adding human genes, in order to create a TB-susceptible mouse. Whilst these manipulations are designed to make it easier for researchers to infect mice with different human diseases, this approach doesn’t necessarily create accurate and predictive models of the human condition. There is also huge wastage in this approach. For example, for one study requiring 50 genetically defined animals, 84 female “breeder mice” are used to produce a total of 400 animals, of which 350 are simply discarded and killed, being surplus to requirements. This over-breeding to generate animals with the requisite, manipulated genetics is not isolated to TB research – it is a strategy used throughout medical research.
Female mice are more likely to be used in TB research, not due to any physiological or biological evidence that females are more relevant, but because experiments are long-term, often lasting months, and female animals are less likely to display aggression when they are housed together for long periods of time. The irony is that for most other experimental investigations, male animals are used. In fact, in people, TB shows a male bias that is not linked to social status or access to health care. So when it may actually be more relevant to use males, researchers use females. Indeed, male mice are more susceptible to experimental TB infection than females.
Guinea pigs featured in Koch’s research -they are naturally susceptible to TB. Guinea pigs develop the lung damage typical of human TB but do not show the human symptoms of infection such as persistent cough, high temperature and fatigue. Guinea pigs were subjected to infection with increasing numbers of Mycobacterium tuberculosis so that researchers could work out how many organisms caused disease. Even those animals given less than 5 organisms started to die after 14 weeks and many of the guinea pigs given a high dose (500-1000 organisms) only survived for 8 weeks. Guinea pigs bear little outward sign of TB infection and so these animals were likely to die slow and painful deaths. The relatively rapid deaths of the guinea pigs infected with high doses of mycobacteria bears no resemblance to the slow progression of TB in humans and therefore has questionable relevance as a model of the human disease.
Human disease is further complicated by co-morbidities which can worsen the prognosis or cause more serious health issues. Co-morbidities tend to be uniquely human and many co-morbidities impact on the health of people with TB. These include socioeconomic status, cigarette smoking, being anxious or depressed, or other significant health issues such as chronic lung disease or diabetes.
Given that so much TB-related animal research uses the wrong gender, dose, and species, what can be done? How about using computers instead? With computers, we can carry out epidemiological modelling. This can be used to track a contagious disease throughout a population and can help control or prevent the spread of disease. Computers have been instrumental in examining the structure of Mycobacterium tuberculosis, and identifying vulnerable areas within it. Computational models can therefore be used as preclinical tools for drug development, to discover possible new targets on the organism as regions of attack, to design new anti-TB drugs and to discover possible vaccine candidates. A computer simulation of a virtual population was recently used to see whether alterations in medication would still be effective. Other computer-based technologies have been developed to work out exactly which kind of Mycobacterium tuberculosis is responsible for an individual’s disease – this helps to determine which drugs would be most effective for them.
The computing power that lies, literally, at our fingertips shows such promise in designing and testing new medicines to defeat TB that surely this technological approach makes scientific, financial, moral and ethical sense?