Browsing by Author "Jalihal, Amogh P."

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    Efficient Synthesis of Mutants Using Genetic Crosses
    Pratapa, Aditya; Jalihal, Amogh P.; Ravi, S. S.; Murali, T. M. (2018-06-29)
    The genetic cross is a fundamental, flexible, and widely-used experimental technique to create new mutant strains from existing ones. Surprisingly, the problem of how to efficiently compute a sequence of crosses that can make a desired target mutant from a set of source mutants has received scarce attention. In this paper, we make three contributions to this question. First, we formulate several natural problems related to efficient synthesis of a target mutant from source mutants. Our formulations capture experimentally-useful notions of verifiability (e.g., the need to confirm that a mutant contains mutations in the desired genes) and permissibility (e.g., the requirement that no intermediate mutants in the synthesis be inviable). Second, we develop combinatorial techniques to solve these problems. We prove that checking the existence of a verifiable, permissible synthesis is NP-complete in general. We complement this result with three polynomial time or fixed-parameter tractable algorithms for optimal synthesis of a target mutant for special cases of the problem that arise in practice. Third, we apply these algorithms to simulated data and to synthetic data. We use results from simulations of a mathematical model of the cell cycle to replicate realistic experimental scenarios where a biologist may be interested in creating several mutants in order to verify model predictions. Our results show that the consideration of permissible mutants can affect the existence of a synthesis or the number of crosses in an optimal one. Our algorithms gracefully handle the restrictions that permissible mutants impose. Results on synthetic data show that our algorithms scale well with increases in the size of the input and the fixed parameters.
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    Modeling and analysis of the macronutrient signaling network in budding yeast
    Jalihal, Amogh P.; Kraikivski, Pavel; Murali, T. M.; Tyson, John J. (American Society for Cell Biology, 2021-11-01)
    Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic"of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.