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Characterization of metabolism in human gut Coriobacteriia using a newly developed genetic toolkit
No full textThe human gastrointestinal tract is colonized by trillions of microorganisms that greatly impact health and disease. Among these organisms are Coriobacteriia, a class of prevalent human gut Actinobacteria implicated in drug and dietary phytochemical metabolism and associated with multiple human diseases. Gaining a mechanistic understanding of Coriobacteriia metabolic activities and their regulation could better inform efforts to modulate gut microbial activities to improve human health. However, the whole Coriobacteriia taxon, including Eggerthella lenta, is currently genetically intractable. This thesis describes our efforts to develop a comprehensive genetic toolkit for Coriobacteriia and our application of these tools to characterize biochemical activities of human gut Coriobacteriia and their genetic regulation.
Chapter 2 describes our efforts to develop a genetic toolkit for Coriobacteriia. We construct shuttle vectors and develop methods to transform E. lenta, Gordonibacter urolithinfaciens, and other Coriobacteriia. With these tools, we characterize endogenous E. lenta constitutive and inducible promoters using a reporter system and construct inducible expression systems, enabling tunable gene regulation. We also achieve genome editing by harnessing an endogenous type I-C CRISPR-Cas system. We further create a transposon mutagenesis library for E. lenta and G. urolithinfaciens by engineering a native transposable element. By greatly expanding our ability to study and engineer gut Coriobacteriia, these tools will reveal mechanistic details of host-microbe interactions and provide a roadmap for genetic manipulation of other understudied human gut bacteria.
Chapter 3 details our work characterizing Coriobacteriia enzymes involved in polyphenol metabolism. Polyphenols are an important group of phytochemicals known for their antioxidant and anti-inflammatory properties. These dietary compounds are greatly impacted by gut bacterial metabolism, which changes their bioactivity and bioavailability. A prominent reaction in polyphenol metabolism is the removal of para-hydroxyl groups from catechols by molybdenum-dependent catechol dehydroxylases encoded in Coriobacteriia. However, the substrates of most putative catechol dehydroxylases remain unidentified due to the challenges of obtaining these enzymes from standard heterologous expression systems. To solve this problem, we establish G. urolithinfaciens as a versatile bacterial host to express active catechol dehydroxylases. The heterologous expression system allows us to streamline the catechol dehydroxylase discovery process and rapidly deorphanize twelve previously uncharacterized gut bacterial catechol dehydroxylases that selectively dehydroxylate intermediates in the gut bacterial metabolism of plant-derived catechins and lignans. Unexpectedly, we discover multiple instances of distinct catechol dehydroxylases that selectively metabolize individual substrate enantiomers, setting the stage for future efforts to elucidate the mechanisms and evolution of these enantiocomplementary dehydroxylases. Altogether, these findings greatly increase our knowledge of these metalloenzymes and provide a more comprehensive understanding of phytochemical metabolism relevant to human health.
Chapter 4 illustrates our work to elucidate the function and mechanism of a unique class of transmembrane transcriptional regulators in Coriobacteriia. Aiming to address the molecular details underlying the regulation of catechol dehydroxylase expression, we identify a previously unappreciated family of transcriptional regulators comprised of a 12-transmebrane helix domain and a LuxR-type DNA-binding domain, which are referred to here as 12-TM LuxR. Bioinformatic analyses show their high diversification and wide distribution in Coriobacteriia. We confirm that 12-TM LuxRs sense specific compounds and upregulate cognate metabolic enzymes. We further combine genetic and biochemical approaches to characterize the mechanism underlying 12-TM LuxR regulation. We show that 12-TM LuxRs are one-component systems that directly bind to their inducers. The 12-TM domains structurally resemble major facilitator superfamily (MFS) transporters, and we show these domains determine inducer specificity. Lastly, we show that inducer binding likely promotes 12-TM LuxR dimerization/oligomerization, which activates the regulator. Our findings suggest that Coriobacteriia evolved MFS-like domains for metabolic regulation, representing a new mechanism for bacterial nutrient sensing and signal transduction.Chemistry and Chemical Biolog
Interferometry of Integer and Fractional Quantum Hall Edge States in Graphene
No full textIn this thesis, we develop Fabry-Pérot quantum Hall interferometers in graphene and measure anyon braiding in the fractional quantum Hall effect. Our results demonstrate the potential of van der Waals materials for constructing quantum coherent electronic devices with advanced functionalities in order to unveil a wealth of physics that is otherwise inaccessible via transport measurements. We begin by first demonstrating clear Aharonov-Bohm resistance oscillations in integer quantum Hall states, overcoming a major technical challenge of “Coulomb dominated” oscillations, which plagued decades of experiments in traditional semiconductor-based platforms. Next, we develop an improved, density-tunable interferometer and measure tunable Coulomb coupling between copropagating integer edge states, revealing the physics behind anomalous interference phase jumps and Aharonov-Bohm oscillation frequency doubling in the integer quantum Hall effect. Similar observations in other semiconductor platforms had been unexplained for a decade. The combined theoretical developments and precise tuning knobs added by our work enable further experiments probing correlations in strongly coupled one-dimensional chiral edge channels. Finally, we observe robust Aharonov-Bohm oscillations in two distinct fractional quantum Hall states, filling fractions ν=1/3 and ν=4/3, and discover 3-state telegraph noise consistent with localized anyon number fluctuations, which we put to use to directly measure the 2π/3 abelian anyon braiding phase in both states. This final work enables further experiments to demonstrate control of the localized anyon number and eventually measure the braiding properties of non-abelian anyons in even-denominator fractional quantum Hall states. Many open questions, such as whether non-abelian order describes these states, how robust topological order really is, which excitations belong to which fractional states in real devices, and whether we can build a technology leveraging the exotic physics of the fractional quantum Hall effect will soon be directly addressable.Engineering and Applied Sciences - Applied Physic
Patriots for Profits: An Investigation into the Crimes and Mismanagement of American Manufacturing Corporations during the First World War Era
No full textAmerica’s military-industrial complex suffered from widespread profiteering that severely hindered its efficiency and performance during the nation’s involvement in World War I. Of all American industries that suffered the most from corruption and theft, aircraft production suffered the most. This thesis explores the extent of the damage caused by profiteering by individuals and companies on the American aeronautic industry along with case studies exploring the effect of profiteering on lumber and copper production. This research argues that profiteering led to the widespread inefficiencies, reduced quality, and shortages experienced by the American military-industrial complex in the First World War. With over one billion dollars spent on building a modern air service between 1917 and 1918, unadjusted for inflation, the Americans failed to produce more than one type of operational combat plane and never produced a pursuit plane. The Aircraft Production Board and War Department only issued contracts for the mass production of a single airplane motor, the Liberty Motor, which proved too large and powerful to be used in any small pursuit fighter planes forcing them to be utilized in the large and unpopular DH-4 type. The favoritism of the Liberty Motor along with certain manufacturing companies had its origin not in ignorance exclusively, but in corrupt profiteering
Advancing Molecular and Functional Understanding of Cells with Artificial Intelligence
No full textRapid advancements in biotechnology are transforming our ability to measure biological systems across multiple modalities and scales. On the molecular level, spatially resolved single-cell transcriptomics enables comprehensive profiling of gene expression while preserving the spatial architecture of tissues. On the functional level, flexible brain-machine interfaces permit stable, long-term recordings of single-neuron activity throughout behavioral learning and disease progression. These innovations have increasingly shifted the life sciences toward a data-centric paradigm. However, traditional computational modeling approaches remain limited in their capacity to extract meaningful biological insights from heterogeneous, high-dimensional data, especially for decoding complex cell states and functions across space and time. To address this critical gap, this dissertation introduces a suite of computational methods that integrate artificial intelligence and machine learning (AI/ML) with cutting-edge biotechnologies. These methods are designed to interpret large-scale, multimodal biological data and feed insights back into experimental design for iterative discovery.
Chapter 2 presents ClusterMap, a spatially informed, unsupervised clustering framework for single-cell and tissue segmentation directly from in situ transcriptomic data. Building on this, Chapter 3 builds a comprehensive spatial atlas of the mouse central nervous system by integrating single-cell gene expression and spatial data at subcellular resolution. To generalize spatial analysis across datasets and technologies, Chapter 4 introduces FuseMap, a universal deep-learning framework that harmonizes multiple brain atlases into a common coordinate framework, enabling gene imputation, tissue region annotation, and cross-dataset integration. Expanding beyond transcriptomics, Chapter 5 introduces AutoSort, a real-time multimodal spike sorting algorithm for stable long-term neural recordings, and UnitedNet, a multi-task learning model that jointly performs cell-type identification, cross-modal prediction, and feature relevance discovery across diverse single-cell modalities.
In summary, this dissertation presents novel AI-powered frameworks that bridge molecular and functional modalities at the single-cell level. These approaches not only enhance our ability to decode the complex architecture and dynamics of biological systems but also provide a foundation for future integrative studies in development, disease, and therapeutic response.Engineering and Applied Sciences - Engineering Science
High-resolution dissection of cis-regulatory elements
No full textGene expression is a highly regulated process that governs almost all aspects of life. Precise gene regulation guarantees that every cell selectively expresses a subset of all genes to perform specialized cellular functions. Therefore, dysregulated gene expression often leads to disease and is implicated in aging. A key step of eukaryotic gene regulation is transcriptional regulation, where protein factors such as transcription factors (TFs) and nucleosomes bind to cis-regulatory elements (CREs) in the genome to determine the transcription of target genes. Our understanding of gene regulation therefore heavily depends on our ability to observe the action of regulatory proteins on genomic DNA, and scientists have worked for decades building ever better technologies to measure protein-DNA interactions at regulatory elements. This dissertation presents technological advances that allows measurement of protein-DNA interaction at cis-regulatory elements with significantly improved cellular (cell-type/state- resolved), genomic (single base-pair), and molecular (single molecule) resolution.
First, we describe PRINT and seq2PRINT, which are computational methods for tracking transcription factor and nucleosome binding within cis-regulatory regions using single-cell ATAC-seq (scATAC-seq) data. PRINT detects footprints of DNA-binding proteins across spatial scales by accurately modeling enzymatic sequence bias and signal dispersion using machine learning. Using pseudo-bulked scATAC-seq, PRINT achieves cell-type- and cell-state-resolved TF and nucleosome footprint landscapes in systems with complex cell type composition and across hundreds of thousands of CREs genome-wide. Building upon PRINT, we describe seq2PRINT, which is a deep-learning model that uses local DNA sequence as the sole input to predict footprint patterns in the same locus. By extracting sequence features learned during training, seq2PRINT can accurately predict TF binding events with single base-pair resolution.
Aided by low-rank approximation (LoRA), we can scale up seq2PRINT to hundreds of samples or cell-type/states. With PRINT and seq2PRINT, we reveal complex dynamics of TF and nucleosome binding within CREs in human hematopoiesis with unprecedented cell state and genomic resolution. We show that many CREs display distinct combinations of TF binding across cell types undetectable in traditional accessibility-based analyses. We further use PRINT and seq2PRINT to characterize murine hematopoietic stem cell (HSC) aging and show widespread reorganization of CREs and identify age-associate TF cooperations.
Second, we describe TDAC-seq, which is a technology that achieves single-molecule long-read profiling of chromatin accessibility and protein footprints using a double-strand DNA deaminase DddA11. We show that DddA11 can introduce C-to-T mutations in DNA regions that are accessible and unprotected from proteins, allowing accessibility and footprint measurements with nanopore sequencing. We show that TDAC-seq allows simultaneous read out of chromatin organization and genetic perturbations such as deletions introduced by CRISPR Cas9 or A-to-G mutations introduced by an adenine base editor (ABE). This allowed high throughput pooled CRISPR screen or ABE screen where the effect of each deletion/editing outcome on local chromatin organization can be individually assessed.
In summary, the body of work presented in this dissertation resolved several long-standing technological challenges in measuring chromatin-level biological processes in gene-regulation. The technologies described enable cell-type/state-resolved single base-pair tracking of regulatory factor binding, as well as single-molecule long-read measurement of chromatin organization, providing powerful new tools for gene regulation studies.Biological and Biomedical Science
OSEP, SSIPs and the Future of Special Education: Practitioner Leadership in an Evolving Federal Landscape
No full textThe Office of Special Education Programs (OSEP) is a division of the United States Department of Education (Ed). OSEP’s mission is to lead the nation’s efforts to improve outcomes for infants, toddlers, children and young adults with disabilities, birth through twenty-one years old. However, a decade ago OSEP recognized a need to place a greater emphasis on student outcome results as compared to procedural compliance. In 2014, the State Systemic Improvement Plan (SSIP), a comprehensive multi-year plan, was developed as part of OSEP’s Results Driven Accountability (RDA) initiative to improve early intervention and educational services, including special education and related services for children with disabilities.
The SSIP was intended to be a key lever that allowed states to formally focus on system-wide improvement strategies. While each year states have submitted these plans as a part of their annual performance report, because of competing and shifting priorities, OSEP has placed varying levels of focus on supporting implementation of the SSIP, and ongoing staffing capacity issues have negatively impacted OSEP’s ability to assess the fidelity of SSIP implementation.
As a resident, I worked in the Office of the Director (OD) in OSEP examining SSIPs from all sixty states and territories. Additionally, my role involved creating a SSIP advisory group to address critical questions about the effectiveness, sustainability, and scalability of these plans, diving deeply into the data to understand both the successes achieved and the ongoing challenges. With a decade of SSIP data and years of implementation by states, this work offered a rare chance to provide insights into how large-scale educational reforms evolve over time, adapt to emerging needs, and drive lasting change in special education.
This Capstone chronicles my efforts to support OSEP’s desire to examine national SSIP impact as it works toward its mission. My analysis offers recommendations for OSEP to 1) add to the already existing OSEP infrastructure to routinely examine the SSIP and build MSIP State Lead capacity to support states, 2) work collaboratively through effective teaming as a necessary and consistent framework to engage in data improvement cycles to inform decision making and, 3) utilize psychologically safe containers to build and strengthen relationships within shifting political environments to maintain focus on the progress leaders are trying to achieve.Educatio
