Browsing by Author "Pai, Anand"

Now showing 1 - 3 of 3
  • Thumbnail Image
    ItemOpen Access
    A noisy linear map underlies oscillations in cell size and gene expression in bacteria.
    (Nature, 2015-07-16) Tanouchi, Yu; Pai, Anand; Park, Heungwon; Huang, Shuqiang; Stamatov, Rumen; Buchler, Nicolas E; You, Lingchong
    During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.
  • Thumbnail Image
    ItemOpen Access
    Bacterial Communication and Cooperation: From Understanding to Applications
    (2013) Pai, Anand

    Bacteria communicate, coordinate, and cooperate as a population and this `social' behavior is key to their proliferation. Quorum sensing (QS) is the cell-cell communication mechanism by which bacteria sense their population density and modulate their target gene expression accordingly. While QS is ubiquitous among bacteria, there is tremendous diversity in terms of the sensory elements used and the biochemical and transport properties of signaling molecules. Further, the targets of QS include a wide range of cooperative actions, such as the secretion of enzymes for nutrient foraging, virulence toxins, and biofilm-forming compounds. Here I investigate what role QS and cooperation play, as universal social characteristics, in promoting bacterial proliferation.

    Engineered biological circuits offer the potential to test our understanding of natural systems under well-defined contexts, by focusing on the key characteristics and components of interest. In my doctoral work, I have taken advantage of this methodology to study bacterial social behavior. Combining mathematical modeling with quantitative experiments using gene circuits, my research has (1) elucidated the `core' components of cell-cell communication across bacteria, (2) explained how communication and cooperation advantage bacterial growth, and (3) opened up the important application of this research in generating novel antibacterial therapies.

  • Thumbnail Image
    ItemOpen Access
    Programming stress-induced altruistic death in engineered bacteria.
    (Mol Syst Biol, 2012) Tanouchi, Yu; Pai, Anand; Buchler, Nicolas E; You, Lingchong
    Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment.