Reed College

NSF Awards · FY 2026 · 2026-08

This research investigates how biological diversity is maintained between closely related species in a changing environment. The work focuses on two species of yellow monkeyflowers—ecologically diverse wildflowers common across North America—that frequently meet and interbreed to create hybrids. In a unique, multi-year study of natural populations in the Columbia River Gorge, this research will track how fluctuating environmental conditions, such as drought, influence whether these plant species interbreed or remain separate. By combining detailed field observations with advanced genetic analyses, the project will identify specific genes that help plants adapt to their surroundings and maintain species barriers. Understanding the genetic basis of reproductive barriers like flowering time is critically important for modern plant breeding and biotechnology. For example, knowledge from this work could lead to developing crops that are better synchronized with specific growing seasons or more resilient to climate-driven stressors like drought. Additionally, these projects will offer rich training experiences for undergraduate and graduate students who will be involved in all aspects of the research. The projects will also provide significant outreach opportunities, including public lectures, experimental demonstrations at the field sites, greenhouse tours, and engagement with high school students. The origin of species is usually shown as a simple splitting of one lineage into two, but hybridization is pervasive across the tree of life and can complicate the speciation process. This long-term study of naturally hybridizing yellow monkeyflower (Mimulus) species will reveal how interspecific gene flow affects the probability of adaptation and tempo of speciation. The evolutionary impact of hybridization depends critically on the rate of interspecific mating (pre-zygotic barriers) and the fitness of hybrids (post-zygotic barriers), and these factors, in turn, are often highly contingent upon the environment. The specific scientific objectives of this research are as follows: 1) Identify the environmental determinants of Mimulus ancestry structure in secondary contact zones across space and time. 2) Determine how reproductive barriers respond to environmental variation. 3) Identify the genetic basis of divergent ecological adaptation and assess how mapped barrier loci respond to fluctuating natural environments. 4) Discover the ecological context and genomic impact of hybridization across a broad geographic region. Completion of the aims in this proposal will provide an unprecedented view of the ecological variables, phenotypes, and genetic loci that determine the fate and evolutionary impact of hybridization. Additionally, this project includes several public outreach initiatives and provides unique cross-training opportunities for students at a Research 1 institution (University of Georgia) and a predominantly undergraduate institution (Reed College). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2026 · 2026-06

Manganese is an essential nutrient for bacteria. It helps bacteria defend against harmful molecules that are part of the human immune response. However, too much manganese is toxic. Unlike nutrients such as sugars or vitamins, bacteria cannot produce manganese. It must be imported from their environment. As a result, they must carefully control how much enters and leaves the cell. To maintain this balance, bacteria use specialized proteins that collaborate to reduce uptake when manganese levels are high and remove excess metal to prevent toxicity. This project will elucidate the molecular details of such collaboration. The work will use structural biology and biochemistry to study how bacterial proteins control manganese levels and influence bacterial virulence. Obtention of the detailed molecular structures of these bacterial proteins will aid the future design of more precise drugs that target harmful pathogens. This will allow the biotech industry to produce new treatments for serious infections to improve public health outcomes. The work will also improve STEM education at primarily undergraduate institutions. It will expand access of undergraduate students to advanced structural biology techniques. These activities will prepare them for jobs in the research and biotech workforces. This project advances NSF’s priorities in Biotechnology. This project aims to develop a comprehensive understanding of manganese homeostasis in bacteria by structurally and functionally characterizing the network of manganese influx and efflux proteins from Bacillus subtilis as well as the mechanism of regulation of their expression and function by the dual metallosensor protein, MntR and other metal ions such as zinc and iron, respectively. To achieve this goal, the work in the project will use a combination of structural biology techniques including single-particle cryogenic-electron microscopy (cryo-EM) and X-ray crystallography coupled with functional assays such as in vivo transcription assays, in vitro solution experiments (e.g. mass photometry) and metal ion transport assays on influx and efflux proteins reconstituted in proteoliposomes. By investigating the molecular mechanisms of manganese sensing, capture, and translocation at atomic resolution, this research will provide molecular insights into the larger family of such transporters (e.g. ATP binding cassette and Cation Diffusion Facilitator proteins) and transcription metalloregulators across bacterial species and their interplay with other metal homeostatic pathways. This research also has tremendous downstream potential for applied science, e.g. in the design of microbial biosensors engineered to track Mn pollution in soil as well as have immediate impact on the broader field of bioinorganic chemistry and metal homeostasis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY/ABSTRACT Non-muscle myosin II (NMII) contractility is critical to number cellular processes from development to disease. NMII is an ATP-dependent molecular motor that functions as a dimer composed of two heavy chains, which are made of an ATPase/motor domain that binds actin and a coiled-coil tail domain. It is also bound to two accessory proteins, the essential light chain which plays structural roles, and the regulatory light chain which is the target of phosphorylation, integrating the molecule into a myriad of signaling pathways. Phosphorylation of the regulatory light chain leads to a relief of an autoinhibition, opening up the molecule and making it competent to bind actin, however, by itself it is a poor motor protein. The second required step of activation is oligomerization into higher ordered, bi-polar filaments. This oligomerization is thought to be regulated by the tail domain where again, phosphorylation is hypothesized to be the main driver of this transition. While decades of research have revealed much about these biochemical and biophysical properties, we questioned whether there were other, yet-to-be revealed, mechanisms that may contribute to NMII’s regulation. The overarching goal of this proposal is to understand the mechanisms that regulate NMII contractility. In Project 1, we explore a potential novel NMII binding protein, Split Discs (Spdi). Spdi’s human homolog, SPECC11L has been implicated in a spectrum of cranial-facial pathologies, highly suggestive of abearent cranial neural crest cell migration. SPECC1L was initially characterized as actin-microtubule crosslinking proteins, however data from my lab suggests that its target is NMII and actin. It is our hypothesis that Spdi binds NMII to regulate its contractility. Through a series of biochemical characterization and cell biology experiments where we elucidate the mechanism by which Spdi associates with NMII, and employ an ex-vivo developmental model to understand how its regulation of contractility affects collective cell migration. In Project 2 we focus on the role of acetylation on the regulation of NMII filament assembly. While phosphorylation has long been thought of as the major driver of NMII dynamics and behavior, recent data from my lab suggests that acetylation may play an equally important role in this process. We will identify the enzymes involved in this acetylation-deacetylation cycle, and elucidate the role this post-translational modification has on force generation. The proposed research spans the molecular and biochemical, to cell biology and development, integrating high-resolution microscopy and capitalizing on Drosophila and the broad genetic tools they provide. Given the high degree of conservation and its universality to number of critical cellular processes the results we obtain here will have broad implications for how NMII is regulated across species and will bring new insights to how NMII is integrated in cellular signaling paradigms.

NSF Awards · FY 2026 · 2026-05

The Summer School on Homotopy Colimits will be held at the University of Regina, Canada on June 22-26, 2026. It is aimed at graduate students and early career researchers to learn about homotopy (co)limits, a fundamental tool in homotopy theory. Having a workshop focused on this unifying technical tool will foster connections between different research groups in homotopy theory and adjacent areas. The summer school will consist of five mini-courses, which will be taught by experts in the field (Alejandro Adem, Anna Marie Bohmann, Brenda Johnson, Chris Kapulkin, and Inna Zakharevich). Homotopy limits and colimits are constructions that are broadly used in all areas of homotopy theory. This summer school will expose participants to the tools for working with homotopy (co)limits, specifically in the context of model categories and infinity categories. Additionally, the mini-courses will also provide participants with perspectives on how homotopy (co)limits are used in various branches of algebraic topology, in particular, equivariant homotopy theory, calculus of functors, and classifying spaces of groups. More information is available on the website: https://sites.google.com/view/reginahomotopy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

An award is made to Reed College to enable the development of computational tools that model complex tissue structures in the vertebrate eye. By combining advances in live imaging microscopy and computational image analysis, the project will generate graph-based models that capture patterns of cell organization in the developing zebrafish retina. The project will also create reproducible protocols for applying these tools to publicly-available imaging datasets, expanding access to scientists with limited imaging and compute resources. Broader impacts include new undergraduate educational opportunities in computational image analysis and a faculty mentoring network at predominantly undergraduate institutions (PUIs) to build capacity for undergraduate teaching and research at resource-limited institutions. The three-year peer mentoring network will foster professional development and resource sharing among PUI faculty, strengthening the nation’s STEM workforce through expanded access to undergraduate computational biology training. The project advances fundamental methods for analyzing complex tissues by integrating graph theory with high-resolution microscopy. While graphs have long been used in systems biology, their full potential has not been leveraged for modeling multi-cell patterns in tissue imaging. Further, neuronal tissues such as the eye complicate traditional modeling approaches due to elongated cell shapes. To address a need for models that reflect the spatial complexity of tissue, this project develops graph-based frameworks to analyze cell organization in the zebrafish retina. These frameworks extend graph algorithms to capture local patterns of cell types and model multi-cell interactions, offering more interpretable representations of tissue organization. Graph-based methods offer computationally efficient alternatives to deep learning approaches and have the potential to generalize to other sensory systems. This project will bridge developmental biology and computer science, offering new perspectives on tissue organization and growth across multiple scales. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

This project aims to improve the practice of verifying probabilistic programs. Probabilistic programs are a way of capturing randomized behavior using the same kinds of structures we use for regular programming. This kind of randomness is a key component of many machine learning algorithms, so probabilistic programs are an important tool for building safer, more robust machine learning systems. However, techniques for verifying that probabilistic programs behave safely are under-studied compared to traditional deterministic programs. This project's novelties are improved tools for verification of probabilistic programs, allowing more properties to be verified for a larger set of programs. This project's impacts are improved safety and reliability for systems which include probabilistic programs and ultimately for systems with machine learning components. The project will support student learning by providing the undergraduate students working in the project with high-demand skills such as software verification. Concretely, this project builds on the framework of abstract interpretation, an existing methodology for verifying traditional programs. While there has been some work in extending abstract interpretation to probabilistic programs, that work has various drawbacks making it infeasible for analyzing complex programs. This project will develop novel abstract domains for verifying programs with complex, continuous probability distributions modeled by traditional programming constructs. Such problems arise naturally in (for example) continuous control settings. The project aims to equip these domains with the order-theoretic operators required to handle programs with unbounded loops. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.