Browsing by Author "Chen, Zhuo"

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    Modeling of gene regulatory networks controlling cell-fate decisions in Bacillus subtilis
    (2022-04-21) Chen, Zhuo; Igoshin, Oleg A.
    To adapt to various environments, bacterial cells can activate distinct gene-expression programs and differentiate into mutually exclusive cell types. This process is called cell-fate decision. Bacillus subtilis is a well-studied model system for investigating bacterial cell-fate decisions. In Bacillus subtilis, a master regulator, Spo0A, controls several cell-differentiation pathways. Spo0A is activated by phosphorylation via a phosphorelay – a cascade of phosphotransfer reactions commencing with autophosphorylation of histidine kinases KinA, KinB, KinC, KinD, and KinE. Upon moderate starvation, phosphorylated Spo0A (Spo0A~P) activates biofilm formation by indirectly inducing matrix production in a subpopulation of cells via a SinI-SinR-SlrR regulatory network. When the nutrient is further depleted, Spo0A~P activates sporulation by directly and indirectly regulating sporulation gene expression. In this work, using mathematical modeling, we provide system-level understandings of the mechanisms controlling cell-fate decisions in Bacillus subtilis. It is unclear how different kinases regulate distinct cell fates via the same master regulator. To understand the roles of different kinases in the regulation of cell-fate decisions in B. subtilis, we built a mathematical model of the phosphorelay network. With this model, we revealed that KinC, one of the sensor kinases that activate Spo0A, has distinct effects on Spo0A at different growth stages: under fast growth, KinC acts as a phosphate source and activates Spo0A; whereas under slow growth, KinC becomes a phosphate sink and contributes to decreasing Spo0A activity. Moreover, we showed that considering the single-cell level heterogeneity is essential to understand the role of KinC in the regulation of cell-fate decisions. Next, to understand the single-cell heterogeneity of different cell fates, we built a model of the SinI-SinR-SlrR regulatory network. With this model we showed that the fluctuations in the cellular growth rate and the intrinsic noise in the SinI-SinR-SlrR regulatory network can explain the single-cell heterogeneity of biofilm matrix production; moreover, we showed that the cellular growth rate affects matrix production in a feed-forward manner. Our model successfully predicts the dynamics of biofilm matrix production under genetic perturbations and explains why matrix production and sporulation are mutually exclusive on single-cell level.
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    Three Essays on Firms' Management and Exploitation of Corporate Venture Capital Investments
    (2020-04-22) Chen, Zhuo; Zhang, Yan
    Researchers in strategic management are increasingly interested in the role of corporate venture capital (CVC) investments in learning about external technologies and improving internal innovation. In this three-essay dissertation, I examine how firms manage and exploit CVC investments to facilitate the learning process. In Essay 1, I examine information externality of CVC investments. I propose that firms may attend to other firms’ CVC investments and take strategic actions by inferring investing firms’ strategic intent from their investments. In the context of acquisitions as the strategic action, I find that acquirers are more likely to acquire ventures in technology domains with a higher intensity of other firms’ CVC investments and this relationship is stronger if the domain has high technological proximity to the acquirer. I also find that technological proximity between an acquirer and a CVC increases the likelihood that the acquirer will acquire ventures that have received investments from the CVC. In Essay 2, I examine firms’ use of CVC investments to facilitate identification of acquisition targets in distant technological domains. I suggest that while firms are less likely to acquire ventures in more distant technological domains, such negative relationship is weaker if the potential target has high technological proximity to the firm’s CVC portfolio. I further advocate that firms are more proficient in using information and knowledge gained through CVC investing to facilitate acquisition of distant targets when they have more prior acquisition experience. In Essay 3, I examine CVC portfolio configuration. I propose that firms configure their CVC portfolios along two dimensions – technological distance between the firm and its CVC portfolio and heterogeneity of the CVC portfolio. I find that firms will choose a subsequent investee such that the heterogeneity of the updated CVC portfolio (after adding the new investee) is negatively related to the technological distance between the firm and its current CVC portfolio. I also find that firms’ learning from its CVC portfolio is positively related to heterogeneity of the CVC portfolio, but such relationship is weakened if the technological distance between the investing firm and its CVC portfolio is high.