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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Thesis
  • Peer Reviewed
UC San Diego Electronic Theses and Dissertations (2023)

In this dissertation, we present a comprehensive study on two sets of phenomenological models examining bacterial population dynamics, focusing on chemotaxis-driven expansion and microbial interactions in non-steady-state environments. Our first model provides a quantitative understanding of how chemotaxis and cell growth lead to the rapid expansion of bacterial populations. We establish analytical relations that describe the dependence of expansion speed and density profile on molecular, cellular, and environmental parameters. We demonstrate that expansion speeds can significantly increase when the environmental availability of chemicals is high relative to the cellular limits of chemical sensing. Our results offer a mathematical framework for investigating the roles of taxis in diverse ecological contexts across broad parameter regimes.The second set of models explores microbial interactions in non-steady-state environments, as ecological dynamics often feature large self-generated environmental changes driving microbes through distinct physiological states. We introduce a phenomenological model to investigate the dynamic coexistence of microbes in cyclic environments. By considering growth according to a global ecological coordinate, specifically total community biomass, our model bypasses specific interactions leading to different physiological states. Our analysis provides rigorous, quantitative criteria for the dynamic coexistence of many species in terms of differential species' dominance ("growth niche") along the ecological coordinates. Our research shifts the focus of ecosystem dynamics from bottom-up studies based on inter-species interaction to top-down studies based on accessible macroscopic observables such as growth rates and total biomass. This approach allows for a quantitative examination of community-wide characteristics. In summary, this dissertation presents a detailed analytical investigation of bacterial population dynamics, shedding light on the underlying processes of chemotaxis-driven expansion and microbial interactions in changing environments. The mathematical frameworks and insights provided have broad applicability to diverse ecological contexts and open up new avenues for understanding complex spatiotemporal dynamic processes in microbial ecosystems.

    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2021)
    Bacterial cells navigate their environment by directing their movement along chemical gradients. This process, known as chemotaxis, can promote the rapid expansion of bacterial populations into previously unoccupied territories. However, despite numerous experimental and theoretical studies on this classical topic, chemotaxis-driven population expansion is not understood in quantitative terms. Building on recent experimental progress, we here present a detailed analytical study that provides a quantitative understanding of how chemotaxis and cell growth lead to rapid and stable expansion of bacterial populations. We provide analytical relations that accurately describe the dependence of the expansion speed and density profile of the expanding population on important molecular, cellular, and environmental parameters. In particular, expansion speeds can be boosted by orders of magnitude when the environmental availability of chemicals relative to the cellular limits of chemical sensing is high. Analytical understanding of such complex spatiotemporal dynamic processes is rare. Our analytical results and the methods employed to attain them provide a mathematical framework for investigations of the roles of taxis in diverse ecological contexts across broad parameter regimes.
      Cover page: A traveling-wave solution for bacterial chemotaxis with growth
      • Article
      • Peer Reviewed
      UC San Diego Previously Published Works (2023)
      Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics-that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higherconcentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of nonresponding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated stimulation, which we also validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping heterogeneous gene expression.
        Cover page: Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells.
        • Article
        • Peer Reviewed
        UC San Diego Previously Published Works (2023)
        Metabolic cross-feeding plays vital roles in promoting ecological diversity. While some microbes depend on exchanges of essential nutrients for growth, the forces driving the extensive cross-feeding needed to support the coexistence of free-living microbes are poorly understood. Here we characterize bacterial physiology under self-acidification and establish that extensive excretion of key metabolites following growth arrest provides a collaborative, inter-species mechanism of stress resistance. This collaboration occurs not only between species isolated from the same community, but also between unrelated species with complementary (glycolytic vs. gluconeogenic) modes of metabolism. Cultures of such communities progress through distinct phases of growth-dilution cycles, comprising of exponential growth, acidification-triggered growth arrest, collaborative deacidification, and growth recovery, with each phase involving different combinations of physiological states of individual species. Our findings challenge the steady-state view of ecosystems commonly portrayed in ecological models, offering an alternative dynamical view based on growth advantages of complementary species in different phases.
          Cover page: Stress-induced metabolic exchanges between complementary bacterial types underly a dynamic mechanism of inter-species stress resistance
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