Orientation Patch Count (OPC) is a method of research used by biologists and paleontologists to analyze the complexity of an animal’s feeding surface while inferring their diets; diet and tooth complexity have evolved in concert with one another, which is why this method has been used on reptilian and mammalian (denticular) species. However, it has not been extensively tested on edentulous (toothless) clades. Therefore, my research examines the OPC of an edentulous species - specifically the endangered Madagascar big-headed turtle (Erymnochelys madagascariensis) using  three CT-scanned specimens. Three primary programs were used in order to analyze the quantitative morphometricsof the species: Slicer for processing and editing CT scans from the University of Washington’s Friday Harbor Lab, MeshLab for editing 3D models, and RStudio for data analysis. This research contributes to a broader study on turtle species led by paleontologist Brenlee Shipps, who will apply these findings to extinct beaked clades, specifically dicynodonts.

We are developing a RNA scaffold-based CRISPR activation and inhibition system to controllably tune gene expression in  primary immune cells, which will allow us to manipulate and increase production and function of immune cells, vastly increasing their efficacy in fighting diseases such as cancer. Here we target Bcl11b, a key T cell transcription factor necessary for progenitor cell commitment to the T cell lineage. CRISPR activation and CRISPR interference (CRISPRai) enable activation or repression of targeted genes. Due to the large size of dCas9 activator and reperessor fusions, it is not possible to express the necessary machinery in primary mouse T cells. Thus, we are developing a CRISPRai system where the gRNA (guide RNA) contains an additional RNA hairpin to recruit RNA binding protein-effectors, enabling activation and repression in the same cell. To optimize the efficiency of CRISPRi in T cells, we are 1) cloning and testing a repressor domain for its ability to drive gene silencing and 2) testing alternative RNA base pairs (BP) and hairpin pairs. We are testing these optimizations in a T cell progenitor cell line which has turned on Bcl11b with a downstream YFP (fluorescent) reporter. Here, YFP expression, which we measure using flow cytometry, is directly correlated to Bcl11b expression levels. We hypothesize that an alternative validated RNA hairpin BP in conjunction with a novel compact transcriptional effector will result in decreased levels of YFP expression compared to the existing system.

Previous studies suggest that tooth morphology (shape, size, and other features of teeth) strongly correlates with an organism’s dietary patterns, and analyzing dentition is common practice in the field of Biology. Orientation patch count rotated (OPCr), a technique used in establishing dentition-diet correlations, has recently been demonstrated as applicable to turtle triturating surfaces to understand their dietary adaptations. The aim of this study is to add to an ongoing project characterizing the relationship between diet and the cutting/grinding surface in the jaw (triturating surface) in edentulous (toothless) organisms using techniques used in traditional dental topographic analysis. Turtles are a diverse group of edentulous organisms with beaks of keratin to process their food — making them ideal for this study. Specimens of the omnivorous Forest-Hinge Back Tortoise (Kinixys erosa) were micro-computed tomographically (CT) scanned. We reconstructed the CT scans into photogrammetric 3D models using Slicer software. Then, we isolated the triturating surface using MeshLab software. Finally, we read the triturating surface into the R package molaR — resulting in OPCr values that estimate the complexity of their specimen’s triturating surface. Ideally, the OPCr values showcase extreme high triturating surface complexity, as previous research suggests tortoises (Testudinidae) have highly complex triturating surfaces compared with other clades of turtles. Our research hopes to contribute to a new technique for analyzing extinct beaked or edentulous taxa.

Diet is one of the most significant contributors to an organism’s morphology, as without morphological features to acquire food the organism will cease to live. Previous studies have quantified these morphological features in toothed taxa using Rotated Orientation Patch Count (OPCr) but not in edentulous taxa. Previously, we obtained OPCr from several turtle species using photogrammetry, created 3D models with Slicer, edited them down to just the triturating surface in MeshLab, and ran statistical analysis in R. Specifically, I worked on the unique, endangered turtle species Carettochelys insculpta (n=6) using CT scans obtained from MorphoSource to add to our photogrammetry data. However, the OPCr values obtained from these meshes discarded more surface area and were significantly lower than the meshes made from photogrammetry. To increase the surface area counted in the OPCr and potentially get results more comparable to the photogrammetry meshes we experimented with decreasing the percentage of patches discarded during analysis in R from 1% to 0.1% and tried smoothing the meshes in Slicer using a factors of 0.3, 0.5, and 0.7. A simple T-test was used to determine significant differences. To increase the number of available specimens and compare turtle species with different diets – durophagous and omnivorous respectively – Malaclemys terrapin specimens (n=5) were used in addition to the Carettochelys insculpta specimens. We expect to find increased surface area and higher OPCr values when increasing the percentage of patches discarded from 1% to 0.1%. We also expect that smoothing will increase the amount of surface area counted at both 1% and 0.1%. As a result of this study, we hope to create a better method for processing CT scans for morphological analysis of the triturating surfaces of turtles, and to develop a methodology for determining diet in any edentulous organism.

Previous studies have shown that the diet of an organism can provide valuable insight into a variety of characteristics including habitat, behavior, and ecological role. Analyzing dentition is one method used to determine an organism’s diet, but this becomes complicated for edentulous taxa. In this study, we investigated the dietary ecology of Caretta caretta, or the loggerhead sea turtle, through the 3D morphometrics of several CT-scanned skull specimens. We are particularly interested in studying a notable feature on the occlusal surface: the accessory triturating ridge. This structure functions as a way to process food and thus provides important insight into what kinds of nutritional sources Caretta caretta may be drawing from. To analyze and interpret the morphology of the ridge, we took a series of computed tomography (CT) scans and processed them into 3D models using Slicer. We then isolated the occlusal surface in MeshLab and used R to assess variations in morphology. This results in a rotated orientation patch count (OPCr), which we can use to analyze the complexity of the occlusal surface. This acts as a topographic map, with a higher OPCr value likely indicating an omnivorous or herbivorous diet, and a lower OPCr value predicting a carnivorous diet. Because Caretta caretta are known to be omnivorous, we expect to see a higher OPCr value, suggesting that their occlusal surface is more complex than that of other turtles. Analysis of this species contributes to our project's overarching goal of applying morphological analyses to edentulous species and can offer insights into conservation efforts for this ecologically vulnerable turtle.

Per-Arnt-Sim (PAS) domains are ubiquitous protein modules that enable cells to detect and respond to environmental signals. For instance, circadian rhythm regulators leverage PAS domains to sense stimuli and initiate protein-protein interactions critical for maintaining biological oscillations. Structurally, the sensory region of PAS domains detects environmental cues—such as fluctuations in phosphorylation levels—while the effector domain converts these signals into cellular responses, including altered gene expression or protein interactions. Inspired by this natural framework, our project aims to design de novo sensory domains that selectively recognize tyrosine phosphorylation, a key post-translational modification in cellular signaling, through association/dissociation between bound and unbound states regulated by the phosphorylation/dephosphorylation cycles. During the design phase, we prioritized synthetic peptide targets for initial proof of principle and systematically deployed computational pipelines: (1) Rosetta introduced phosphotyrosine modifications into pre-designed protein-peptide heterodimer scaffolds; (2) iterative LigandMPNN with Rosetta FastRelax optimized binding interfaces to accommodate the phosphotyrosine modifications; (3) RFdiffusion Partial Diffusion enhanced the structural diversity around promising designs with the aim of improving affinity and specificity; and (4) Chai-1 and AlphaFold enabled in silico folding and structure-based filtering of final candidates. High-confidence designs will be expressed and purified from E. coli, and then undergo in vivo characterization via size exclusion chromatography (SEC) binding assays and enzyme-linked immunosorbent arrays (ELISA) to quantify their binding affinity, specificity, and the function of phosphorylation-dependent switching. Validated scaffolds will then be integrated with pre-designed effector domains to assemble fully de novo PAS domains. This modular platform establishes a foundation for designing phosphorylation-sensitive biosensors. Future adaptation to natural phosphorylation sites could yield programmable tools for interrogating signaling networks, advancing synthetic biology, and enabling precise manipulation of cellular communication pathways.

In nature, Per-Arnt-Sim (PAS) domains comprise a sensor that undergoes conformational changes upon signal recognition which either activates or deactivates an effector domain. Natural PAS domains detect environmental cues, such as oxygen, light, and small ligands; however, they do not sense phosphorylation, a key post-translational modification. Here, we present a designed de novo phosphorylation-inducible heterodimer that serves as a sensor domain. This system toggles between association and dissociation states in response to phosphorylation and dephosphorylation events. To engineer reversible association and dissociation, we designed phosphorylated peptides and their corresponding binders. Starting from a library of previously designed peptide-binder complexes, mutations were introduced into the peptide sidechains, replacing selected residues with phosphorylated tyrosine, serine, or threonine. Next, we ran iterative cycles of LigandMPNN-FastRelax to generate binder sequence candidates. Finally, we used AlphaFold2 and Chai1 to predict the folded structures of our input sequences and selected those that were predicted with high confidence. For experimental validation, the designed proteins will be overexpressed in Escherichia coli and purified using affinity and size exclusion chromatography. Phosphorylation-dependent binding specificity and affinity will be assessed through enzyme-linked immunosorbent assays (ELISA), surface plasmon resonance (SPR), and fluorescence polarization (FP). Subsequently, we will fuse these sensor domain designs to a collection of previously designed hinge proteins—which can bind/release an effector protein—to produce de novo PAS domains, thereby linking the sensing event to downstream functional responses. This adaptable system offers broad applications in biomaterials and synthetic biology, including the development of responsive scaffolds for biosensors and synthetic protein motors with controlled conformational cycles. 

The triturating surface of a beaked animal is the part of the beak that contacts food. Previous work has been conducted on determining a value for the complexity of beaked turtles’ triturating surface by creating a 3D mesh of it. We analyzed these meshes using  the R package molaR which then determined an OPCr (orientation patch count rotated) number that could be compared to the known diet of the turtle. My role in this study is  to examine the effect that manipulation of thresholding the skull has on the OPCr output using five different skulls from the species Malaclemys terrapin, which are known to be durophagous. Thresholding is conducted in the first half of mesh construction, when the CT scan is run through Slicer. At this step, we input both a higher and lower threshold value, as well as a standard value. A higher threshold value will lead to higher density material being excluded from the data set. The skull that is constructed in Slicer is then put into MeshLab to be further trimmed into only the triturating surface, and then it is run through molaR. We suspect that a higher threshold value will lead to a higher OPCr value than a lower thresholding value would. The implication of these results will determine what effect thresholding has on the scan, and estimate what value will be most optimal for preserving the integrity of the scan.