Nongenetic individuality, changeability, and inheritance in bacterial behavior.

Isogenic populations often display remarkable levels of phenotypic diversity even in constant, homogeneous environments. Such diversity results from differences between individuals ("nongenetic individuality") as well as changes during individuals' lifetimes ("changeability"). Yet, studies that capture and quantify both sources of diversity are scarce. Here we measure the swimming behavior of hundreds of Escherichia coli bacteria continuously over two generations and use a model-independent method for quantifying behavior to show that the behavioral space of E. coli is low-dimensional, with variations occurring mainly along two independent and interpretable behavioral traits. By statistically decomposing the diversity in these two traits, we find that individuality is the main source of diversity, while changeability makes a smaller but significant contribution. Finally, we show that even though traits of closely related individuals can be remarkably different, they exhibit positive correlations across generations that imply nongenetic inheritance. The model-independent experimental and theoretical framework developed here paves the way for more general studies of microbial behavioral diversity.

Homeorhesis and ecological succession quantified in synthetic microbial ecosystems.

The dynamics of ecological change following a major perturbation, known as succession, are influenced by random processes. Direct quantitation of the degree of contingency in succession requires chronological study of replicate ecosystems. We previously found that population dynamics in carefully controlled, replicated synthetic microbial ecosystems were strongly deterministic over several months. Here, we present simplified, two-species microbial ecosystems consisting of algae and ciliates, imaged in toto at single-cell resolution with fluorescence microscopy over a period of 1 to 2 weeks. To directly study succession in these ecosystems, we deliberately varied the initial cell abundances over replicates and quantified the ensuing dynamics. The distribution of abundance trajectories rapidly converged to a nearly deterministic path, with small fluctuations, despite variations in initial conditions, environmental perturbations, and intrinsic noise, indicative of homeorhesis. Homeorhesis was also observed for certain phenotypic variables, such as partitioning of the ciliates into distinct size classes and clumping of the algae. Although the mechanism of homeorhesis observed in these synthetic ecosystems remains to be elucidated, it is clear that it must emerge from the ways each species controls its own internal states, with respect to a diverse set of environmental conditions and ecological interactions.

Bioluminescence dynamics in single germinating bacterial spores reveal metabolic heterogeneity.

Spore-forming bacteria modulate their metabolic rate by over five orders of magnitude as they transition between dormant spores and vegetative cells and thus represent an extreme case of phenotypic variation. During environmental changes in nutrient availability, clonal populations of spore-forming bacteria exhibit individual differences in cell fate, the timing of phenotypic transitions and gene expression. One potential source of this variability is metabolic heterogeneity, but this has not yet been measured, as existing single-cell methods are not easily applicable to spores due to their small size and strong autofluorescence. Here, we use the bacterial bioluminescence system and a highly sensitive microscope to measure metabolic dynamics in thousands of B. subtilis spores as they germinate. We observe and quantitate large variations in the bioluminescence dynamics across individual spores that can be decomposed into contributions from variability in germination timing, the amount of endogenously produced luminescence substrate and the intracellular reducing power. This work shows that quantitative measurement of spore metabolism is possible and thus it opens avenues for future study of the thermodynamic nature of dormant states.

Quantitation of cellular dynamics in growing Arabidopsis roots with light sheet microscopy.

To understand dynamic developmental processes, living tissues have to be imaged frequently and for extended periods of time. Root development is extensively studied at cellular resolution to understand basic mechanisms underlying pattern formation and maintenance in plants. Unfortunately, ensuring continuous specimen access, while preserving physiological conditions and preventing photo-damage, poses major barriers to measurements of cellular dynamics in growing organs such as plant roots. We present a system that integrates optical sectioning through light sheet fluorescence microscopy with hydroponic culture that enables us to image, at cellular resolution, a vertically growing Arabidopsis root every few minutes and for several consecutive days. We describe novel automated routines to track the root tip as it grows, to track cellular nuclei and to identify cell divisions. We demonstrate the system's capabilities by collecting data on divisions and nuclear dynamics.

Microbial population dynamics by digital in-line holographic microscopy.

Measurements of population dynamics are ubiquitous in experiments with microorganisms. Studies with microbes elucidating adaptation, selection, and competition rely on measurements of changing populations in time. Despite this importance, quantitative methods for measuring population dynamics microscopically, with high time resolution, across many replicates remain limited. Here we present a new noninvasive method to precisely measure microbial spatiotemporal population dynamics based on digital in-line holographic (DIH) microscopy. Our inexpensive, replicate DIH microscopes imaged hundreds of swimming algae in three dimensions within a volume of several microliters on a time scale of minutes over periods of weeks.