Resistant Traits in Digital Organisms Do Not Revert Preselection Status despite Extended Deselection: Implications to Microbial Antibiotics Resistance

Abstract

Antibiotics resistance is a serious biomedical issue as formally susceptible organisms gain resistance under its selective pressure. There have been contradictory results regarding the prevalence of resistance following withdrawal and disuse of the specific antibiotics. Here, we use experimental evolution in “digital organisms” to examine the rate of gain and loss of resistance under the assumption that there is no fitness cost for maintaining resistance. Our results show that selective pressure is likely to result in maximum resistance with respect to the selective pressure. During deselection as a result of disuse of the specific antibiotics, a large initial loss and prolonged stabilization of resistance are observed, but resistance is not lost to the stage of preselection. This suggests that a pool of partial persists organisms persist long after withdrawal of selective pressure at a relatively constant proportion. Hence, contradictory results regarding the prevalence of resistance following withdrawal and disuse of the specific antibiotics may be a statistical variation about constant proportion. Our results also show that subsequent reintroduction of the same selective pressure results in rapid regain of maximal resistance. Thus, our simulation results suggest that complete elimination of specific antibiotics resistance is unlikely after the disuse of antibiotics once a resistant pool of microorganisms has been established.

Novel Populations from Simulated Admixed Populations

“…Mersenne Twister has been shown by several studies to be suit-able for most Monte Carlo simulation studies [40][41][42]. The same random module was used in other tools; such as, DOSE [43,44]; where null hypotheses have been reported [45,46]. Although there has been reported cases where Mersenne Twister [42,[47][48][49] were found not to be suitable, this is unlikely the case as a recent study using Island [36] has also demonstrated instances of null hypothesis [37].…”

Untitled

“…Finding Reference Genes [39][40][41][42][43][44] CY Chia Evolution by Digital Organisms [54][55][56] CFG Castillo ZE Chay Figure 1 Timeline of projects.…”

“…This was published. 55 In the second instance, we repeated the original study 55 but considered fitness cost in the maintenance of resistance traits in the absence of selective pressure. However, the conclusions are consistent with that of no fitness cost, suggesting that fitness cost may have limited role to revert from resistance to susceptibility and other factors had to be considered in future studies.…”

The Bioinformaticist’s/Computational Biologist’s Laboratory

“…Computer simulations of virtual organisms (commonly known as "digital organisms" or "artificial life") had been used instead [11] and may provide some insights into human evolution [12]. Digital organism simulations had also been used to provide insights into areas that are ethically impossible to access, such as antibiotics resistance [13,14], as it is not ethical to willfully induce antibiotics resistance.…”

“…A significant number of my research work, which resulted in publications [12][13][14][17][18][19][20][21], started off as pet projects that I engage out of my salaried jobs; hence, received no funding, using no prior experimental data that I had generated and have to pay for article processing fees levied by journal if I cannot obtain a full waiver. Despite so, with a laptop, I am able to do something.…”