Increasing antibiotic resistance (AR) poses dangers of treatment complications and even treatment failure to astronauts. An AR determinant is a gene of resistance carried by bacteria. This article considers the issue of the stability of AR determinants and the influence of manned spaceflight conditions on this characteristic. A phenomenological model has been developed that makes it possible to evaluate the integral value of the stability of determinants of AR in bacteria as a function of time. Based on experimental results obtained during implementation of the SALYUT 7 space program, the stability of determinants of AR in Escherichia coli strains isolated before and after a spaceflight in 16 astronauts was evaluated. In addition, an assessment was made of the integral value of the stability of determinants of AR in bacteria during in vitro experiments, both in spaceflight and terrestrial conditions, after preincubation in space. The calculation using the developed phenomenological model showed that the stability of AR determinants in E. coli bacteria isolated from astronauts before the spaceflight is 33% higher than after the flight. The in vitro experiment carried out on board the International Space Station showed the opposite situation-an increase in the stability of AR determinants by 33% in cultures that have been in space compared with terrestrial control. This indicates an additional influence on the stability of determinants and of the astronaut's immune system, as well as space conditions. The common result in these two types of studies is the experimental fact that the largest number of bacteria, in space conditions, had two determinants of AR. The importance of fighting bacteria with two determinants is that at least three different antibiotics are required to have an effect. This circumstance makes it possible to predict a possible strategy for the use of antibiotics in autonomous spaceflights.
Keywords: Antibiotic resistance; E. coli; International space station; SALYUT 7; Space conditions; Stability model.