# Contrasting biotic and abiotic drivers of adaptive evolution in a host-pathogen conflict > **NIH NIH F32** · STANFORD UNIVERSITY · 2021 · $65,994 ## Abstract Project Summary/Abstract To be successful, organisms must adapt to both abiotic (e.g. environmental pressures) as well as biotic (e.g. parasites) selection pressures. Although both of these pressures can drive evolutionary innovation, theory predicts that antagonistic relationships may drive recurrent episodes of adaptation. Dissecting these selective pressures has implications for understanding treatment of both human infectious disease and cancers, where both pathogens and clonally dividing malignant cells are adapting to both host immunity (biotic) and environmental (abiotic) therapeutics. Additionally, the human microbiota is a complex and dynamic community containing competing microbes in the context of both host immunity and gut environment. These complex co- evolution scenarios are challenging to study and disentangling the respective contributions of various selective pressures and fitness tradeoffs can be confounding. I propose to use RNA viruses of yeast as a model system to study the evolutionary consequences of both abiotic and biotic selective pressures of genome evolution in the presence of genetic conflict. RNA viruses of yeasts encode a “Killer” toxin-antitoxin addiction system, which protects virus-bearing Killer cells but kills virus-lacking sensitive cells. As a result, these RNA viruses can be maintained in host populations despite imposing a metabolic cost to their host. In my research proposal, I will study adaptation in the face of both abiotic (toxin) and biotic (virus) selective pressures. Killer itself requires multiple viral genomes for toxin production as well as host cellular components. With sensitive cells in the environment, this system is a four-party genetic conflict, with competing fitness tradeoffs. In spite of this complexity, budding yeast is one of the best-supported model eukaryote systems with many genetic and molecular tools. This makes this model system supremely experimentally tractable, even while maintaining the biological complexity of a naturally occurring system. I will identify beneficial mutations that arise in populations of competing killer and sensitive cells (Aim 1), in sensitive cells that evolve resistance to toxins in the absence of virus (Aim 2), and determine which genomes adapt to regain competitive fitness in a molecular arms race (Aim 3). Together, these aims will uncover how intricate biotic systems co-evolve and constrain one another and reveal the evolutionary dynamics imposed by antagonistic coevolution, versus abiotic adaptation. Understanding how genomes evolve, and specifically how genetic conflict (antagonistic co-evolution) drives adaptation, is fundamental for understanding and treating many processes that shape and drive disease. By exploring host-parasite coevolution from first principles, we can develop a foundation towards understanding the impact of these processes on human health and disease. This proposed work will benefit many fields by experimentally addressing fu... ## Key facts - **NIH application ID:** 10230445 - **Project number:** 1F32AI160906-01 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** Michelle Hays - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $65,994 - **Award type:** 1 - **Project period:** 2021-04-01 → 2023-09-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10230445 ## Citation > US National Institutes of Health, RePORTER application 10230445, Contrasting biotic and abiotic drivers of adaptive evolution in a host-pathogen conflict (1F32AI160906-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10230445. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*