generating-controlled-dynamic-chemical-landscapes-to-study-microbial

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

We demonstrate a method for the generation of controlled, dynamic chemical pulses&#8213;where localized chemoattractant becomes suddenly available at the ...

Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering

Many chemotactic bacteria inhabit environments in which chemicals appear as localized pulses and evolve by processes such as diffusion and mixing. We show that, in such environments, physical limits on the accuracy of temporal gradient sensing govern when and where bacteria can accurately measure the cues they use to navigate. Chemical pulses are surrounded by a predictable dynamic region, outside which bacterial cells cannot resolve gradients above noise. The outer boundary of this region initially expands in proportion to the square root of time before rapidly contracting. Our analysis also reveals how chemokinesis-the increase in swimming speed many bacteria exhibit when absolute chemical concentration exceeds a threshold-may serve to enhance chemotactic accuracy and sensitivity when the chemical landscape is dynamic. More generally, our framework provides a rigorous method for partitioning bacteria into populations that are 'near' and 'far' from chemical hotspots in complex, rapidly evolving environments such as those that dominate aquatic ecosystems. 

Physical limits on bacterial navigation in dynamic environments.

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species.

Marine phytoplankton inhabit a dynamic environment where turbulence, together with nutrient and light availability, shapes species fitness, succession and selection. Many species of phytoplankton are motile and undertake diel vertical migrations to gain access to nutrient-rich deeper layers at night and well-lit surface waters during the day. Disruption of this migratory strategy by turbulence is considered to be an important cause of the succession between motile and non-motile species when conditions turn turbulent. However, this classical view neglects the possibility that motile species may actively respond to turbulent cues to avoid layers of strong turbulence. Here we report that phytoplankton, including raphidophytes and dinoflagellates, can actively diversify their migratory strategy in response to hydrodynamic cues characteristic of overturning by Kolmogorov-scale eddies. Upon experiencing repeated overturning with timescales and statistics representative of ocean turbulence, an upward-swimming population rapidly (5-60 min) splits into two subpopulations, one swimming upward and one swimming downward. Quantitative morphological analysis of the harmful-algal-bloom-forming raphidophyte Heterosigma akashiwo together with a model of cell mechanics revealed that this behaviour was accompanied by a modulation of the cells' fore-aft asymmetry. The minute magnitude of the required modulation, sufficient to invert the preferential swimming direction of the cells, highlights the advanced level of control that phytoplankton can exert on their migratory behaviour. Together with observations of enhanced cellular stress after overturning and the typically deleterious effects of strong turbulence on motile phytoplankton, these results point to an active adaptation of H. akashiwo to increase the chance of evading turbulent layers by diversifying the direction of migration within the population, in a manner suggestive of evolutionary bet-hedging. This migratory behaviour relaxes the boundaries between the fluid dynamic niches of motile and non-motile phytoplankton, and highlights that rapid responses to hydrodynamic cues are important survival strategies for phytoplankton in the ocean.

Phytoplankton can actively diversify their migration strategy in response to turbulent cues.

Many microorganisms have evolved chemotactic strategies to exploit the microscale heterogeneity that frequently characterizes microbial habitats. Chemotaxis has been primarily studied as an average characteristic of a population, with little regard for variability among individuals. Here, we adopt a classic tool from animal ecology - the T-maze - and implement it at the microscale by using microfluidics to expose bacteria to a sequence of decisions, each consisting of migration up or down a chemical gradient. Single-cell observations of clonal Escherichia coli in the maze, coupled with a mathematical model, reveal that strong heterogeneity in the chemotactic sensitivity coefficient exists even within clonal populations of bacteria. A comparison of different potential sources of heterogeneity reveals that heterogeneity in the T-maze originates primarily from the chemotactic sensitivity coefficient, arising from a distribution of pathway gains. This heterogeneity may have a functional role, for example in the context of migratory bet-hedging strategies.

Bacterial chemotaxis in a microfluidic T-maze reveals strong phenotypic heterogeneity in chemotactic sensitivity.

Chemotaxis allows microorganisms to exploit gradients in chemical stimuli to find nutrient resources and hosts or escape noxious substances. Thus, the life of individual microbes in their natural environments is a continual sequence of decisions based on the perceived chemical gradients. However, it has remained unclear to what extent the chemotaxis properties vary among cells of one species, and whether there is a spectrum of different 'decision makers' within populations of bacteria. In our recent study (Salek, Carrara , Nature Communications 10 (1), 1877), we combine microfluidic experiments with mathematical modeling to demonstrate that even in clonal populations, bacteria are individuals with different abilities to climb chemical gradients.

Francesco Carrara

Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior