skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Theoretical investigation of stochastic clearance of bacteria: first-passage analysis
Understanding mechanisms of bacterial eradication is critically important for overcoming failures of antibiotic treatments. Current studies suggest that the clearance of large bacterial populations proceeds deterministically, while for smaller populations, the stochastic effects become more relevant. Here, we develop a theoretical approach to investigate the bacterial population dynamics under the effect of antibiotic drugs using a method of first-passage processes. It allows us to explicitly evaluate the most important characteristics of bacterial clearance dynamics such as extinction probabilities and extinction times. The new meaning of minimal inhibitory concentrations for stochastic clearance of bacterial populations is also discussed. In addition,we investigate the effect of fluctuations in population growth rates on the dynamics of bacterial eradication. It is found that extinction probabilities and extinction times generally do not correlate with each other when random fluctuations in the growth rates are taking place. Unexpectedly, for a significant range of parameters, the extinction times increase due to these fluctuations, indicating a slowing in the bacterial clearance dynamics. It is argued that this might be one of the initial steps in the pathway for the development of antibiotic resistance. Furthermore, it is suggested that extinction times is a convenient measure of bacterial tolerance.  more » « less
Award ID(s):
1664218
PAR ID:
10094149
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Journal of the Royal Society interface
ISSN:
1742-5662
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The size of fruit bat colonies ranges from dozens to hundreds of thousands of individuals, depending on the species. While a deterministic modelling approach is appropriate for large colonies, the role of population fluctuations can be all-important for small colonies. From this perspective, we analyse the infection dynamics in small zoonotic niches due to filoviruses, e.g. Ebola. To this end, we perform stochastic numerical simulations and analytical calculations. The inherent stochasticity in ecological processes may play a significant role in driving small populations towards extinction. Here, we reveal that fluctuations can either lead to virus eradication or to sustain infection compared with the deterministic dynamics, depending on the size of the zoonotic niche. Altogether, our findings reveal non-trivial stochastic effects, which can shed light on the infection dynamics in small- and medium-sized bat colonies and help design preventive measures for zoonotic diseases. 
    more » « less
  2. Abstract PremiseUnderstanding how population dynamics vary in space and time is critical for understanding the basic life history and conservation needs of a species, especially for narrow endemic species whose populations are often in similar environments and therefore at increased risk of extinction under climate change. Here, we investigated the spatial and temporal variation in population dynamics ofRanunculus austro‐oreganus, a perennial buttercup endemic to fragmented prairie habitat in one county in southern Oregon. MethodsWe performed demographic surveys of three populations ofR. austro‐oreganusover 4 years (2015–2018). We used size‐structured population models and life table response experiments to investigate vital rates driving spatiotemporal variation in population growth. ResultsOverall,R. austro‐oreganushad positive or stable stochastic population growth rates, though individual vital rates and overall population growth varied substantially among sites and years. All populations had their greatest growth in the same year, suggesting potential synchrony associated with climate conditions. Differences in survival contributed most to spatial variation in population growth, while differences in reproduction contributed most to temporal variation in population growth. ConclusionsPopulations of this extremely narrow endemic appear stable, with positive growth during our study window. These results suggest that populations ofR. austro‐oreganusare able to persist if their habitat is not eliminated by land‐use change. Nonetheless, its narrow distribution and synchronous population dynamics suggest the need for continued monitoring, particularly with ongoing habitat loss and climate change. 
    more » « less
  3. Abstract Evolution is the main feature of all biological systems that allows populations to change their characteristics over successive generations. A powerful approach to understand evolutionary dynamics is to investigate fixation probabilities and fixation times of novel mutations on networks that mimic biological populations. It is now well established that the structure of such networks can have dramatic effects on evolutionary dynamics. In particular, there are population structures that might amplify the fixation probabilities while simultaneously delaying the fixation events. However, the microscopic origins of such complex evolutionary dynamics remain not well understood. We present here a theoretical investigation of the microscopic mechanisms of mutation fixation processes on inhomogeneous networks. It views evolutionary dynamics as a set of stochastic transitions between discrete states specified by different numbers of mutated cells. By specifically considering star networks, we obtain a comprehensive description of evolutionary dynamics. Our approach allows us to employ physics-inspired free-energy landscape arguments to explain the observed trends in fixation times and fixation probabilities, providing a better microscopic understanding of evolutionary dynamics in complex systems. 
    more » « less
  4. Understanding how populations respond to increasingly variable conditions is a major objective for natural resource managers forecasting extinction risk. The lesson from current modelling is clear: increasing environmental variability increases population abundance variability. We show that this paradigm fails to describe a broad class of empirically observed dynamics, namely endogenously driven population cycles. In contrast to the dominant paradigm, these populations can exhibit reduced long-run population variance under increasing environmental variability. We provide evidence for a mechanistic explanation of this phenomenon that relies on how stochasticity interacts with long transient dynamics present in the deterministic cycling model. This interaction stands in contrast to the often assumed additivity of stochastic and deterministic drivers of population fluctuations. We show evidence for the phenomenon in two cyclical populations: flour beetles and Canadian lynx. We quantify the impact of the phenomenon with new theory that partitions the effects of nonlinear dynamics and stochastic variation on dynamical systems. In both empirical examples, the partitioning shows that the interaction between deterministic and stochastic dynamics reduces the variance in population size. Our results highlight that previous predictions about extinction under environmental variability may prove inadequate to understand the effects of climate change in some populations. 
    more » « less
  5. The inoculum effect (IE) is an increase in the minimum inhibitory concentration (MIC) of an antibiotic as a function of the initial size of a microbial population. The IE has been observed in a wide range of bacteria, implying that antibiotic efficacy may depend on population density. Such density dependence could have dramatic effects on bacterial population dynamics and potential treatment strategies, but explicit measures of per capita growth as a function of density are generally not available. Instead, the IE measures MIC as a function of initial population size, and population density changes by many orders of magnitude on the timescale of the experiment. Therefore, the functional relationship between population density and antibiotic inhibition is generally not known, leaving many questions about the impact of the IE on different treatment strategies unanswered. To address these questions, here we directly measured real-time per capita growth of Enterococcus faecalis populations exposed to antibiotic at fixed population densities using multiplexed computer-automated culture devices. We show that density-dependent growth inhibition is pervasive for commonly used antibiotics, with some drugs showing increased inhibition and others decreased inhibition at high densities. For several drugs, the density dependence is mediated by changes in extracellular pH, a community-level phenomenon not previously linked with the IE. Using a simple mathematical model, we demonstrate how this density dependence can modulate population dynamics in constant drug environments. Then, we illustrate how time-dependent dosing strategies can mitigate the negative effects of density-dependence. Finally, we show that these density effects lead to bistable treatment outcomes for a wide range of antibiotic concentrations in a pharmacological model of antibiotic treatment. As a result, infections exceeding a critical density often survive otherwise effective treatments. 
    more » « less