<p>With increasing global renewable energy demands, there is a need for new materials with improved performance, lower cost, and less toxicity. One such application is photovoltaics, where halide perovskites (HaPs) represent the fastest growing market of absorbers owing to their impressive optoelectronic properties and excellent tunability from composition engineering and structural manipulation. However, the practically infinite composition-structure space of HaPs when considering cation and/or anion site mixing, octahedral distortion and rotation, and other forms of polymorphism, raise considerable challenges when comprehensively exploring their stability and optoelectronic properties. First principles calculations are powerful tools that can investigate large numbers of compounds and structures in a high-throughput fashion. </p><p>In my thesis, I performed high-throughput density functional theory (DFT) computations to generate a HaP dataset within a wide chemical space covering ~500 unique chemical compositions in the (pseudo-)cubic phase, across a 14-dimensional ionic space. This work explored both pure and alloyed compositions, with the latter simulated using the special quasi-random structures approach. Many critical properties were computed using the semi-local GGA-PBE and hybrid non-local HSE06 functionals, including decomposition and mixing energies, electronic band gap, and spectroscopic limited maximum efficiency (SLME), which is a theoretical surrogate for the likely absorption efficiency of the compound when used in a single-junction solar cell. Property screening over this dataset yielded 32 stable perovskite candidates with attractive optoelectronic properties.</p><p>Polymorphism in HaPs is investigated by simulating larger supercell alloys with different ionic ordering, generating compounds with random octahedral distortions and rotations, and optimizing various compositions in non-cubic phases such as tetragonal and orthorhombic. Linear correlation analysis is performed to gain a critical understanding of how properties are influenced by specific cations and anions, their mixing fractions, the perovskite phase, ionic clustering, and amount of strain or distortion in the lattice. Finally, trends, design rules, and predictive insights achieved from the DFT datasets are applied over a much larger set of thousands of hypothetical compounds, resulting in identification of more promising materials and understanding of the most important A-B-X combinations that yield multiple desired objectives.</p><p>Furthermore, a similar DFT workflow is applied for designing transition metal electrocatalysts. DFT simulations are performed to model Hydrogen adsorption, OH adsorption, and the water splitting reaction on Ni3N/Ni and Co2N/Co hybrid structures, to explore their likelihood in being used for Hydrogen Evolution Reaction (HER). The results reveal the excellent catalytic performance of transition metal and transition metal nitride hybrid structures.</p><p><br></p>

Our ability to sense small molecules with high specificity, over a broad range of concentrations, is limited and difficult to accomplish in a way that is inexpensive and continuous. The most commercially successful biosensor is the enzyme-based blood glucose electrochemical biosensor, yet for nearly all other biomolecules, detection and monitoring require specialized equipment, trained personnel, and long lead times, and are not amenable to continuous monitoring. Industries in need of enzyme-based small-molecule biosensors, including medical diagnostics, industrial production, environmental monitoring, food safety analysis, and international security, would benefit greatly from the development of new devices capable of measuring biomolecules of interest. Environmental microbes have been gaining attention because of the vast array of biomolecules that they are capable of sensing and degrading. These microbes do so, in part, through redox enzymes with diverse substrate specificities that represent an immense resource for developing electrochemical biosensors. However, the development of new enzyme biosensors has largely been limited by the lack of a general high-throughput method to identify these redox enzymes, making discovery slow, laborious, and ad hoc. To address this need, a high-throughput functional screening approach has been developed to isolate microbial oxidase enzymes from complex metagenomic DNA libraries based solely on the enzyme-mediated degradation of any target analyte. The approach can be applied to DNA isolated from any complex microbial sample, including unidentified or unculturable bacteria. In this research, I first describe the development of a general assay to capture the activity of oxidase enzymes expressed in E. coli cells. I then demonstrate how the assay can be used to screen for the nicotine degrading oxidase NicA2 from a genomic DNA library generated from the microbe P. putida. Lastly, I describe the use of this screen to identify a new hydrocortisone-responsive oxidase from a pooled genomic DNA library of eight microbes, representing over 43 Mb of DNA sequence space. This hydrocortisone oxidase represents the first of many new enzymes that can be discovered leveraging our screening platform, which is poised to revolutionize the electrochemical biosensing field and substantially broaden the number of molecules these electrochemical biosensors can detect continuously and quantitatively. / 2023-02-17T00:00:00Z

Thesis advisor: Charles Hoffman / The second messenger cyclic 3’-5’ adenosine monophosphate (cAMP) signaling pathway plays an important physiological role in many organisms. Cyclic nucleotide phosphodiesterases (PDEs) regulate signal transduction by catalyzing the hydrolysis of cAMP and cGMP allowing for the downregulation of cyclic nucleotide levels. Human PDEs are encoded by 21 genes grouped into 11 families. The biological role of the most recently discovered PDE family (PDE11) remains poorly understood partly due to the lack of selective inhibitors. Mutations in the PDE11A gene have been linked to a wide range of diseases, such as Cushing Syndrome, which is a result of inactivating mutations expressed in adrenocortical tumors. Meanwhile, PDE11 levels are seen to increase in the ventral hippocampus as a function of aging, and is associated with a loss of social memory. Thus, the development of a selective PDE11 inhibitor could provide a potential therapeutic benefit to patients receiving long-term corticosteroid treatment by stimulating cortisol production by the adrenal gland, as well as to aging adults to maintain social memory. To address these needs, candidate PDE11 inhibitors related to a compound discovered by the Hoffman lab in a high throughput screen for PDE11 inhibitors are being synthesized by the Rotella laboratory. I have been evaluating these compounds using two fission yeast-based growth assays in complement with in vitro enzyme assays carried out by Dr. Jeremy Eberhard. Here I describe my role in the project, leading to the identification of a compound, SMQ2-57, which is a selective inhibitor of the PDE11 enzyme whose potency has been confirmed through both yeast-based assays and in vitro enzyme assays. In addition, I have taken both a forward and reverse genetic approach to identify PDE11A4 mutant alleles that confer resistance to inhibitor compounds as such knowledge could guide a rational drug design approach to produce more effective PDE11 inhibitors. Based on our results, SMQ2-57 could serve as a useful tool in understanding the biological role of PDE11. Meanwhile, data from my study of compound resistant mutant PDE11 alleles should allow for the characterization of the physical interaction between PDE11 and its inhibitors in an effort to guide a medicinal chemistry program to develop a more potent and drug-like PDE11 inhibitor. / Thesis (BS) — Boston College, 2023. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Scholar of the College. / Discipline: Biology.

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京都大学 / 新制・課程博士 / 博士(生命科学) / 甲第24052号 / 生博第478号 / 新制||生||63(附属図書館) / 京都大学大学院生命科学研究科高次生命科学専攻 / (主査)教授 朝長 啓造, 教授 野田 岳志, 教授 今吉 格 / 学位規則第4条第1項該当 / Doctor of Philosophy in Life Sciences / Kyoto University / DFAM

Thesis advisor: Tim van Opijnen / Thesis advisor: Michelle Meyer / Although bacteria are often studied as planktonic or free-living organisms, they frequently grow in complex surface-attached communities known as biofilms. Biofilms are communities of microorganisms attached to surfaces and embedded in a self-produced extracellular matrix. Biofilms are dynamic structures analogous to human settlements shaped by space and environment. These microbial communities fulfill critical roles in multiple infections in the human body. Streptococcuspneumoniae is a human pathogen that can cause biofilm-associated infections in various tissues and organs. This thesis offers a unique outlook for the study of S. pneumoniae biofilms by combining in vitro, genome-wide, and in vivo experiments to elucidate the complex population dynamics of S. pneumoniae biofilms. Existing methods to cultivate S. pneumoniae biofilms fail to fully capture the complexity of these communities, and most studies are limited to short periods of time. We developed a robust in vitro assay to grow S. pneumoniae biofilms. This assay can be maintained forever rather than days. We then use this robust assay to study their behavior in vivo and monitor disease outcomes. After establishing clear differences in biofilm and dispersal samples, we monitor population dynamics using genome-wide techniques (Tn-seq, RNA-seq and WGS) to provide some insights into this complex mode of growth. This work includes the first global identification of genetic requirements during biofilm establishment in two different S. pneumoniae strains using Tn-Seq. Coupled with our transcriptomic analysis, we found that genes involved in multiple pathways, such as capsule biosynthesis, nucleotide metabolism, and stress response, contributed to biofilm growth. Lastly, we studied the development of antibiotic resistance to three different types of antibiotics under S. pneumoniae biofilm conditions. We revealed common adaptive pathways to achieve biofilm growth and antibiotic resistance (antibiotic target genes), as well as novel routes of adaptation to develop resistance. Our findings add to the growing body of knowledge in the field of bacterial genetics and antimicrobial resistance, paving the way for future research and therapeutic advancement. / Thesis (PhD) — Boston College, 2023. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Malaria is vectored by the mosquito Anopheles gambiae (Ag) in Sub-Saharan Africa and infects approximately 500 million people annually. The increasing prevalence of pyrethroid-resistant mosquitoes has amplified the need for development of new, selective mosquitocides for use on insecticide-treated nets. We have developed several phenyl-substituted N-methylcarbamates producing a high degree of selectivity for Anopheles gambiae acetylcholinesterase (AgAChE) over human AChE. Molecular models suggest alternate conformations (flexibility) of W84 and W431 (Ag numbering) at the hydrophobic subpocket of the AgAChE active site and poor flexibility within human AChE, allowing for the high selectivity of our novel carbamates. Initial selectivity data was obtained through screening of these insecticides while using ethanol as a solvent. Re-screening of these carbamates in the presence of 0.1% DMSO (v/v) resulted in antagonism of inhibition for AgAChE, thus reducing the AgAChE-selectivity by at least 10-fold. However, the presence of 0.1% DMSO did not antagonize the inhibition of human, Drosophila melanogaster, or Musca domestica AChE. Non-selective carbamates also displayed no solvent-dependent antagonism of inhibition in any species studied, including AgAChE. Molecular models provide an explanation for antagonism of inhibition when DMSO is present. I, and collaborators, propose that W84 and W431 in AgAChE comprise an allosteric pocket that is stabilized by DMSO and is responsible for the solvent-dependent antagonism of inhibition observed with AgAChE. / Master of Science in Life Sciences

<p dir="ltr">Phospholipase C (PLC) enzymes are essential for normal cardiovascular function. These enzymes hydrolyze phosphatidylinositol 4,5-bisphosphate (PIP₂) at the inner leaflet of the plasma membrane, producing diacylglycerol (DAG) and inositol phosphates (IP₃). IP₃ increases intracellular Ca²⁺, a key secondary messenger in cardiovascular activity. Changes in PLC expression and activity, specifically PLCβ3, have been found to play a critical role in cardiac hypertrophy and contractility. Cardiac hypertrophy, especially left ventricular hypertrophy, is a primary cause of ischemic heart disease, the leading cause of mortality worldwide. Despite the importance of these enzymes, a selective inhibitor for studying their function in cells and animal models has not yet been discovered. To address this unmet need, a lentiviral system for expressing human PLCβ3 and its two major activators, the heterotrimeric G protein subunits Ga_q and Gβγ was developed. These constructs were then utilized to establish a high-throughput screening methodology with the aim of identifying a novel allosteric inhibitor of PLCβ3, and ultimately other PLCs.</p>