Ph.D. - Molecular Biosciences and Bioengineering

Permanent URI for this collectionhttps://hdl.handle.net/10125/2110

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Revealing small non-coding RNA signatures in non-small cell lung cancer using machine learning
(University of Hawai'i at Manoa, 2025) Gao, Zitong; Deng, Youping YD; Molecular Biosciences and Bioengineering
Non-small cell lung cancer (NSCLC) is ranked as the second leading type of cancer among both genders in the United States. Despite a decline in death rates due to better smoking cessation and treatment improvement, NSCLC in non-smokers is still increasing. Early detection of cancer can significantly increase the overall survival of patients. Small non-coding RNA (sncRNA) such as tRNA derived fragments (tRDF) and piRNA have been identified in different types of tissue in next generation sequencing dataset. Increasing evidence has shown that both tRDF and piRNA expressed aberrantly in cancers, which is expected with novel biomarkers on the identification of cancer cases. Up till now, no comprehensive study has investigated these two types of sncRNA expression profile and their biological functions in NSCLC. With the development of different machine learning techniques, more methods can be applied in the classification of cancer and non-cancer cases based on the small RNA-seq data. In this work, this study utilized the multi-center small RNA-seq raw data from NSCLC combined machine learning methods with the aims of 1) identify promising signatures from tRDFs for NSCLC diagnosis, prognosis and its biological function; 2) identify promising signatures from piRNAs for NSCLC diagnosis and its potential in liquid biopsy. Besides the ML application for cancer detection, this study took advantage of the Transformer architecture to understand the contextual interaction between miRNA/piRNA and mRNA via target sites on specific genes, which is the last aim 3) prediction of miRNA/piRNA target gene and target site by integrative T5 model of miRNA/piRNA-mRNA binding and targeting experiment data. The study comprehensively analyzed multi-center data across thousands of NSCLC patient samples from tissue, plasma, and exosome datasets. For tRDFs, diagnostic and prognostic signatures were identified through expression profiles, which six diagnostic signatures achieved AUC values up to 0.90 in independent validations. For piRNAs, the study established and validated a novel piRNA-Based Tumor Probability Index (pi-TPI) by integrating plasma and exosomal piRNA signatures. The pi-TPI model incorporating five ribosome-derived piRNA signatures distinguished NSCLC patients from healthy individuals with AUCs exceeding 0.80, achieving 0.85 in plasma cohorts and 0.96 in non-cancer versus cancer subgroups. In parallel, a deep learning framework was developed named Contrastive miRNA-mRNA Sequence model (COMIMS), using transformer-based encoders and contrastive learning to predict sncRNA-mRNA interactions with high precision. The COMIMS framework achieved an AUC of 0.96 for 3’UTR and 0.99 for CDS miRNA-mRNA interaction prediction, confirming exceptional generalizability. When fine-tuned on piRNA-mRNA data from CLASH-seq experiments, COMIMS maintained high performance with AUC as 0.96 in predicting 5’UTR binding sites in lung cancer cell lines. The integrated study provides a comprehensive atlas of sncRNA-mRNA regulatory networks in NSCLC and introduces robust diagnostic and prognostic frameworks based on tRDFs, piRNAs, and miRNAs. The combination of experimental validation and deep learning-based prediction underscores the potential of sncRNA biomarkers for early, non-invasive detection and molecular stratification of lung cancer, paving the way toward precision diagnostics and therapeutic intervention.
Elucidating the effect of CO2-nanobubbles on the growth and carbon uptake of the indigenous Hawaiian macroalgae, Ulva
(University of Hawai'i at Manoa, 2025) Shitanaka, Ty K.; Khanal, Samir K.; Molecular Biosciences and Bioengineering
Macroalgae, also known as limu in Hawaiian, are ubiquitous and photosynthetic powerhouses with tremendous morphological and genetic diversity. Macroalgae grow quickly, have favorable characteristics for bioproducts (e.g. bioenergy, biomaterials), and can help drive a more sustainable blue economy. There are three main algal groups, the Chlorophyta (green algae), Rhodophyta (red algae), and Phaeophyta (brown algae), each of which are taxonomically classified based on their pigment composition, genetic lineage, and morphological features. One of the macroalgae in the Chlorophyta phylum, Ulva, is widespread globally and typically grows in shallow coastal waters attached to substrate. This genus exhibits extremely rapid growth rates with sufficient nutrients and light, causing green tides in stagnant waters. However, because of these very fast growth rates, Ulva has also been proposed as a promising macroalgal species to cultivate to capture carbon and create valuable bioproducts. Yet, without sufficient nutrients and carbon availability, they do not exhibit these high productivities. Nanobubbles (NB) are gas-filled bubbles within aqueous solutions, ranging from around 50 – 200 nm in diameter and exhibit unique physicochemical properties. Due to their miniscule size, they are able to stay within solutions for long periods of time, up to days to weeks. Moreover, they exhibit negative zeta potentials on the order of -20 – 30 mV, allowing for electrostatic repulsion effects and furthering their retention time in liquids. They can be generated with a multitude of methods, including pressure dissolution, electrolysis, membranes, among others, with varying gas species used depending on the application. It has been proposed previously that NB could be used for improving algal growth through the improved delivery and retention of CO2, thus boosting carbon availability within liquid mediums. However, the physicochemical properties (zeta potential, concentration, size, mass transfer, decay kinetics) and carbonate equilibria dynamics of CO2 delivered with NB technology have scarcely been characterized, as well as tested in whether carbon uptake is improved within algal cultivation. In addition, it is not known how CO2-NB affects the resulting macromolecular profile of Ulva, which could alter its resulting use cases. In this dissertation, we show that CO2 delivered with NB technology (NB) differ in physicochemical characteristics compared to CO2 delivered with a conventional diffuser (CON) based on the following results: 1) Gas-liquid mass transfer coefficients (kLa) with NB were improved by 4.87-fold and 2.58-fold in ultrapure water (UPW) and seawater (SW), respectively, while also extending dissolved CO2 retention times during the decay phase (0.10 h-1 in UPW and 0.14 h-1 in SW). Additionally, NB had nearly 2-fold higher bubble concentrations with less negative zeta potential than CON. 2) NB did not substantially modify carbonate equilibria compared to CON, with PHREEQC modeling showing overlapping carbonate speciation, mineral saturation trajectories, pH differences of <0.3 at peak CO2 input. This suggests that NB primarily improved CO2 gas-liquid mass transfer and CO2 retention times through physical mechanisms, rather than chemically driven processes. 3) When applied to algal cultivation, CO2 delivered via NB in mixed, shallow 145 L raceways supported reliable Ulva production, with fresh weight (FW) biomasses increasing from ~25 g per raceway on Day 1 to ~43 g FW by Day 10 (mean specific growth rates of 6 – 7% d-1). However, when compared to conventional CO2 bubbling at the same CO2 input rates, this biomass improvement was not statistically significant. Furthermore, in both the NB and CON CO2 supplied raceways, Ulva was able to rapidly assimilate daily nutrient additions, with dissolved inorganic nitrogen (DIN) and PO4 reaching concentrations of ≤ 0.05 mg N L-1 and ≤ 0.015 P L-1 (~98% and ~95% removal efficiencies for DIN and PO4, respectively). Dissolved inorganic and organic carbon tracking, coupled with the biomass measurements resulted in raceway scale carbon mass balances that showed ~15 – 17% of injected CO2 being retained overall, with 40 – 45% incorporated into Ulva biomass, 40 – 45% to dissolved organic carbon, and 12 – 14% to residual DIC. 4) Based on macromolecular analyses, NB did not substantially alter the composition of Ulva compared to CON, with around 39 – 47%, 16 – 17%, 4 – 7%, and 29 – 33% DW in carbohydrates, protein, lipids, and ash, respectively. We show this through conducting thorough mass transfer and decay analyses using a dissolved CO2 sensor, inorganic carbon measurements, nanoparticle tracking analysis, electrophoretic light scattering, and modeling in the USGS program PHREEQC. Furthermore, we also demonstrate a novel NB-integrated raceway that facilitates improved productivity of Ulva biomass while suggesting improvements to existing macromolecular protocols. To the extent of our knowledge, this is the first report that comprehensively examines the generation and decay of CO2 delivered with NB technology, benchmarked against a conventional diffuser in both ultrapure water and saltwater, while also utilizing it in production of Ulva biomass. Taken together, these studies provide valuable insights and knowledge into the fundamental physicochemical properties of CO2 delivered with NB technology and differentiates it from CO2 delivered through conventional diffusers, which will aid in many industrial sectors that require aqueous phase CO2, while showcasing a use-case proof-of-concept in the form of Ulva biomass production.
Myostatin regulates the expression of inflammatory cytokines and chemokines, invasion of rheumatoid arthritis synovial fibroblasts, and the CD4+ Th cells’ transmigration
(University of Hawai'i at Manoa, 2025) Lansakara Hitihamillage, Samudra; Kim, Yong soo; Molecular Biosciences and Bioengineering
Rheumatoid arthritis synovial fibroblast cells (RASFs), which are present in the rheumatoid synovium, play a pivotal role in the destructive process of RA. Myostatin (MSTN), a regulator of skeletal muscle mass, is highly expressed in the synovium of RA. However, its function in RASFs during the progression of RA remains poorly understood. We hypothesized that MSTN regulates the expression of inflammatory cytokines, chemokines, and matrix metalloproteinases (MMPs), RASF cell invasion, and immune cell transmigration. The immortalized MH7A cells (RASFs) and healthy synovial fibroblasts (HSFs) were treated with MSTN (0, 10, and 20 ng/mL) for 0, 24, and 48 h. Then, the secretion and expression of inflammatory cytokines (IL-8, IL-17, TNF-, IL-6, IL-23, IFN-, IFN-) and chemokines (CCL2, CCL20, CXCL13, CXCL1) were measured by ELISA, RT-qPCR, and western blots. Furthermore, RASFs and HSFs were treated with TNF-, IL-17, IFN-, IFN-, CCL2, and CXCL1 (0 and 20 ng/mL) for 24 h to examine their effects on MSTN. The impact of MSTN on the proliferation of Thy-1(CD90)+ RASFs and HSFs was analyzed by immunofluorescence. CD4+ Th cell transmigration under MSTN-treated RASF and HSF culture medium was measured using a transwell transmigration assay. MSTN-treated RASF and HSF cell invasion was also measured. The RASF phenotype differs from the HSFs, exhibiting high cell proliferation and elevated expression of cytokines and chemokines. MSTN treatment (20 ng/mL) significantly increased the secretion and expression of inflammatory cytokines and chemokines, with CXCL1 being the highest induction by MSTN in RASFs. IFN- and IL-17 significantly increased MSTN expression in RASFs. MSTN did not affect the proliferation of Thy-1(CD90)+ RASF and HSF cells. Current results demonstrate a cross-stimulation between MSTN and inflammatory cytokines and chemokines. MSTN significantly increased RASF cell invasion and CD4+ Th cell transmigration. Blocking CXCL1 and IL-17 significantly decreased the CD4+ Th cell transmigration, and the decrease in CD4+ Th cell transmigration by CXCL1 blocking was much more significant than that by IL-17, underscoring the critical role of CXCL1 signaling in immune cell infiltration. This study highlights the potential of MSTN as a therapeutic target for mitigating inflammation in RA.
Exploring Community-Specific Associations among Obesity, Meta-Inflammation, and the Gut Microbiome in the Context of Native Hawaiian and Other Pacific Islander Health Disparities on Oʻahu
(University of Hawai'i at Manoa, 2024) Wells, Riley Kauilani; Maunakea, Alika K.; Molecular Biosciences and Bioengineering
Native Hawaiians and other Pacific Islanders (NHPIs) face a higher prevalence of obesity-related diseases and are more likely to be classified as obese according to conventional body mass index (BMI) standards. However, BMI is differentially effective as an indicator of obesity-related health risk, and its generalized application may introduce biases in clinical or comparative research settings. Community-specific characterizations of obesity risk are needed to improve the accuracy and relevance of health disparities research for NHPIs. Community clinic events were held for study recruitment, health-related survey administration, clinical health measure collection, blood sample collection, and at-home stool collection kit distribution. Point-of-care glycosylated hemoglobin (A1c; %) tests were used to designate type 2 diabetes mellitus (T2DM) categories/risk status according to thresholds recommended by the American Diabetes Association. Blood pressure (BP) was also measured, and hypertension (HT) status was determined according to 2017 guidelines recommended by the American College of Cardiology. Community-specific definitions for metabolically healthy (MH; non- or pre-diabetic and non-hypertensive) and metabolically unhealthy (MU; diabetic and/or hypertensive) obesity were obtained for each racial-ethnic group in an NHPI-enriched cohort. To achieve this, receiver operating characteristic (ROC) areas under the curve (AUC) values were used to compare the predictive performance of various anthropometric indices for MU status. These included WC (waist circumference), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), WHT.5R (waist-to-height0.5 ratio), ABSI (A body shape index), BAI (body adiposity index), BRI (body roundness index), and WWI (weight-adjusted waist index). Ideal thresholds were then back-calculated for each anthropometric index to maximize accurate classifications for T2DM risk and HT. Youden’s J statistic was then calculated for each threshold to determine their predictive performance for MU status. Plasma concentrations of GLP-1, IFN-α, IFN-γ, IL-1β, IL-10, IL-12, IL-13, IL-18, IL-3, IL-6, IL-8 (CXCL8), Insulin, MCP-1 (CCL2), PYY, TNF-α, TNFRI, and VEGF-A (pg/ml) were measured using the 17-Plex Human ProcartaPlex Panel (ThermoFisher Scientific, Warrington, England). Linear discriminant analysis (LDA) was performed to determine the contribution of each biomarker to the separation between MH and MU risk status. Plasma concentrations between ethnic groups were compared using Kruskal and Wilcox rank-sum tests. Ethnic-specific associations between significant meta-inflammatory factors and MH/OB risk were then compared by logistic regression. Home stool sample self-collection kits were distributed to participants upon biometric data collection. Each kit included one sample tube containing RNAlater (5 ml; a sample preservative supplied by ThermoFisher Scientific, Waltham, MA). DNA (40 ng) isolated from each stool sample was subjected to polymerase chain reaction (PCR) amplification targeting 16S rDNA hypervariable regions V2-4-8 and V3-6,7-9 (Ion Torrent 16S Metagenomics Kit; ThermoFisher Scientific, Warrington, England). 16S rDNA libraries were prepared from 150 ng of pooled amplicons (Ion Plus Fragment Library Kit; ThermoFisher Scientific, Austin, TX, USA) and barcoded using Ion Xpress Barcode Adapters (Life Technologies, Carlsbad, CA, USA). DNA libraries were pooled (80 pmol from up to 60 libraries) and loaded onto Ion 530™ chips (Ion S5 Next-Generation Sequencing System) in preparation for sequencing. 16S Metagenomics Kit analysis was performed using Ion Reporter Software v5.18.4.0 (ThermoFisher Scientific). Chimeric sequences were automatically identified and removed. Reads were mapped to reference databases Greengenes v13.5 and MicroSEQ ID v3.0. Gut microbiome profiles were compiled using metagenome taxonomic data via the Curated MicroSEQ(R) 16S Reference Library v2013.1. Differential abundance analyses were performed using Analysis of Compositions of Microbiomes with Bias Correction; the ‘ANCOM-BC2’ in R. Anthropometric thresholds associated with MU risk were generally highest among Part/NHPIs compared to other groups. Part/NHPI-specific BMI thresholds resembled the conventional cutoff, ranging from 27.81 to 30.25 kg/m2, while those for Asian, White, and Mixed groups were relatively lower, ranging from 23.62 to 25.36 kg/m2. However, anthropometric indices were less effective as health risk predictors for NHPIs than for White (P=2.3E-5) and Mixed (P=0.030) groups. BRI emerged as the most consistent and effective predictor of T2DM and HT risk across the total cohort, suggesting that its use in clinical and research settings may better capture obesity-related health disparities in NHPI-inclusive communities than BMI. However, the effectiveness of anthropometric indices varies among diverse populations and is least effective for NHPIs compared to other racial-ethnic groups. The features that strongly contributed to the distinction between MH and MU risk categories were age, gender, BRI, IFN-α, IFN-γ, IL-10, IL-12, IL-13, IL-1β, IL-6, IL-8, and TNF-α. Among significant meta-inflammatory biomarkers, IFN-α, IL-10, IL-13, IL-1β, and TNF-α were the most important features in the distinction between MH and MU risk status for NHPIs. After adjusting for age and gender, IL-1β levels were significantly higher in NHPIs compared to the White group (P<0.01). GLP-1 levels were lower in the NHPI group than in the White or Mixed groups (P<0.001). PYY was also lower in NHPIs compared to Part NHPIs and the Mixed group (P<0.01). MCP-1 was lower in NHPIs compared to Asian and Mixed groups (P<0.001), and IL-3 was lower in NHPIs compared to White (P<0.001) and Mixed groups (P<0.01). At the genus level, NHPIs had the highest prevalence of Eggerthella, Blautia, Megamonas, Veillonella, Lachnoclostridium, Lactobacillus, Fusobacterium, Haemophilus, Klebsiella, and Mannheimia and the lowest prevalence of Ruminiclostridium, Barnesiella, Prevotella, Herbaspirillum, Desulfovibrio, and Akkermansia compared to other racial-ethnic groups. Gut bacterial taxa that were more prevalent in NHPIs than other groups have been previously linked to inflammation, T2DM, HT, or gastrointestinal complications. Those less prevalent in NHPIs than other groups were variably associated with beneficial metabolic effects. However, these associations were primarily observed in NHPI-exclusive study populations. In NHPIs, A1c levels were positively associated with unclassified members of Clostridiales, Flavonifractor, Megasphaera, and Turicibacter but negatively associated with Mannheimia and Megamonas. There were no significant associations between gut bacterial genera and A1c levels in the Asian, White, or Mixed groups. Racial-ethnic differences in obesity, meta-inflammation, and the gut microbiome may contribute to racial-ethnic differences in metabolic health risk. BRI was the most effective predictor for metabolic outcomes in an ethnically diverse population. Still, anthropometric indices may be less effective as health risk indicators for NHPIs than other groups. Meta-inflammation may differentially associate with metabolic outcomes between racial-ethnic groups, and the association may be stronger in NHPIs than in other groups. Gut bacterial associations with metabolic outcomes also differed by race-ethnicity. Further community-specific research is necessary to characterize these differences effectively.
DESIGN, APPLICATION, AND STABILITY OF SUPERCOOLED STATES IN FOOD PRESERVED USING ENGINEERED ELECTRIC AND MAGNETIC FIELDS
(University of Hawai'i at Manoa, 2024) Lee, Dongyoung; Jun, Soojin; Molecular Biosciences and Bioengineering
Supercooling is the process of cooling a liquid or food below its freezing point without the formation of ice crystals, which prevents cellular damage and preserves the texture, moisture content, and overall freshness. Lowering the temperature beyond conventional refrigeration it slows microbial growth and enzymatic reactions, leading to an extended shelf life. While it offers significant advantages over conventional preservation technologies such as refrigeration and freezing, achieving and maintaining the supercooled state poses challenges. The inherent thermodynamic instability of the supercooled state presents several practical challenges. Recent advancements suggest that using external AEF and OMF could achieve the supercooled states. The primary objectives were to design and fabricate AEF and OMF modules for food supercooling, to analyze the preservative effects on high-value seafood such as tuna, and to validate the supercooling stability under mechanical and thermal stresses.A core-based electromagnet was designed and optimized through numerical simulations using COMSOL Multiphysics to address challenges. The electromagnet was intended to generate a uniform OMF for supercooling applications, with numerical simulations to evaluate both its magnetic and thermal performance. Experimental validation showed strong agreement with the simulations the system can effectively achieve the desired magnetic field strength while managing heat generation, which is crucial for maintaining supercooled states in practical food preservation applications. Experimental validation showed a high correlation with simulation results, with only a 4.04% error in magnetic flux density and 3.4% in thermal behavior, demonstrating the effectiveness of the developed modeling approach in designing supercooling systems. Seafood is highly perishable, and spoilage begins immediately after harvesting due to the production of various metabolites. Freezing, a conventional long-term preservation method, often leads to quality degradation caused by ice crystallization. Supercooling has emerged as a promising technique to prevent ice formation and reduce quality degradation. Tuna fillets were supercooled at -3.5°C using optimized AEF and OMF. Quality factors, including drip loss, color, microbial load, texture, and total volatile basic nitrogen (TVB-N), were evaluated and compared with refrigerated, frozen-thawed, and supercooled samples during the storage period (10 days). Results indicated that supercooled tuna samples exhibited lower TVB-N values than those stored under refrigeration while maintaining aerobic plate counts that remained stable from 1 to 7 days. Supercooling also preserved the textural integrity of the fillets and significantly reduced drip loss compared to frozen-thawed samples. The stability of supercooled states in food was tested under external stresses, such as mechanical vibrations and temperature fluctuations, to simulate real-world cold chain conditions. Using OMF at specific working frequencies, the stability of supercooled agar gel samples was evaluated. OMF-treated samples demonstrated significantly higher resistance to ice nucleation compared to untreated controls, with a 95% probability of maintaining supercooling under orbital motions at 200 RPM, while untreated samples showed only a 10% success rate. However, vertical vibrations exceeding a peak force of 0.6 g triggered ice nucleation, indicating the need for further optimization to improve robustness against such disturbances. A scaled-up supercooling system (30 L volume capacity) was developed and tested for larger food samples, addressing the limitations of previous systems in handling small sample sizes. The prototype system, designed to maintain stable supercooling conditions for larger volumes of food, successfully extended the supercooled state of packaged tuna fillets.
Clinical implications of non-coding RNAs in cancer
(University of Hawai'i at Manoa, 2024) Wang, Junlong; Yu, Herbert; Molecular Biosciences and Bioengineering
AbstractNon-coding RNAs (ncRNAs), play critical roles in regulating cellular processes, but their involvement in cancer, particularly breast cancer, remains underexplored. This thesis is divided into three chapters. In the first chapter, we provide a comprehensive background on breast cancer, ncRNAs and the emerging significance of ncRNAs in breast cancer pathology. In Chapters two and three, we investigate the clinical implications of two specific ncRNAs—ZNF582-AS1, a lncRNA, and mt-tRF-Tyr-GTA-001, a mitochondrial tRNA-derived fragment (mt-tRF)—in breast cancer progression and patient outcomes. In chapter two, we analyzed The Cancer Genome Atlas (TCGA) dataset to identify lncRNAs associated with breast cancer survival. ZNF582-AS1 expression was found to be significantly lower in breast tumors compared to adjacent normal tissues. Patients with low ZNF582-AS1 expression were more likely to have high-grade or ER-negative tumors and had poorer disease-free survival (DFS) and overall survival (OS). A validation study using fresh tumor samples from 361 breast cancer patients confirmed these findings. Meta-analysis of multiple datasets supported that high ZNF582-AS1 expression was associated with lower risks of relapse and death, independent of tumor grade, disease stage, patient age, and hormone receptor status. Promoter methylation was identified as a possible mechanism suppressing ZNF582-AS1 expression. Bioinformatic analyses suggested that ZNF582-AS1 could inhibit tumor growth by downregulating the HER2-mediated signaling pathway. Moreover, online data indicated that HIF-1-related transcription factors may suppress ZNF582-AS1 expression, and the lncRNA might bind to hsa-miR-940, a known oncogenic miRNA in breast cancer. In chapter three, we focused on mitochondrial tRNA-derived fragments and their role in breast cancer. Analysis of TCGA small RNA-seq data revealed that mt-tRF-Tyr-GTA-001, a fragment derived from mitochondrial tRNA with tyrosine anticodon GTA, was significantly downregulated in breast tumors compared to normal tissues. Patients with low mt-tRF-Tyr-GTA-001 expression had a higher risk of death, independent of clinical variables. This association was validated in our independent cohort using qRT-PCR. The expression of mt-tRF-Tyr-GTA-001 was positively correlated with ribonucleases ANG and RNase 4, enzymes responsible for tRF generation. Functional analyses suggested that mt-tRF-Tyr-GTA-001 could suppress cell transformation, tumor growth, and invasion. In silico predictions identified potential binding targets involved in cell cycle regulation, including transcription factors E2Fs, CCNE1, and FOXM1. Additionally, mt-tRF-Tyr-GTA-001 was correlated with immune cell populations such as M0 macrophages and resting mast cells, highlighting its potential role in innate immunity. In conclusion, our study demonstrates that ncRNAs, particularly ZNF582-AS1 and mt-tRF-Tyr-GTA-001, may play pivotal roles in suppressing breast cancer progression. Understanding their molecular functions and regulatory mechanisms could provide novel insights into breast cancer prognosis and potential therapeutic strategies.
EFFECTS OF HAEMATOCOCCUS PLUVIALIS ASTAXANTHIN ON HEAT-INDUCED OXIDATIVE STRESS AND CELLULAR SIGNAL TRANSDUCTION PATHWAYS IN POULTRY BROILERS
(University of Hawai'i at Manoa, 2024) Kuehu, Donna Lee W.; Deng, Youping; Molecular Biosciences and Bioengineering
ABSTRACTHaematococcus pluvialis is a species of green microalgae that belongs to the phylum Chlorophyta, class Chlorophyceae, and order Chlamydomonadales. In nature, H. pluvialis is generally found in freshwater ponds, lakes, shallow temporary standing water bodies, depressions in rocks and bird baths. H. pluvialis species of microalgae is able to exist in a wide range of environmental conditions of radiation, temperature, and salt concentrations because of its capacity to encyst. H. pluvialis exhibits two main morphological forms, a green vegetative motile form, and a red non-motile aplanospore form. Under favorable conditions, H. pluvialis exists as a biflagellate, green motile cell, and when exposed to stress conditions such as nutrient deprivation or high light intensity, it transitions into the non-motile aplanospore cyst giving the cells their distinctive red color and accumulation of large amounts of astaxanthin. Astaxanthin is derived from the keto-carotenoid family and has a unique molecular structure that includes a series of conjugated double bonds and polar functional groups. This structure enhances its strong antioxidant properties, as it is lipid-soluble and integrates into cellular membranes, playing a vital role in safeguarding cells from oxidative damage. Astaxanthin has diverse applications in the nutraceutical, cosmetic, food, and animal nutrition industries. Biomedical research investigating its effects on oxidative stress, inflammation and cell signaling pathways are studied for its mechanisms of action and potential health benefits. Astaxanthin is used as a feed additive in livestock and poultry to help reduce oxidative stress and improve overall animal health benefits and welfare. The demand for high-quality protein in commercial poultry production of broilers for meat makes astaxanthin an excellent feed additive. The primary objective of this dissertation was to investigate whether a H. pluvialis-derived astaxanthin-rich dietary feed additive as an exogenous source of antioxidants can mitigate heat-induced oxidative stress in poultry broilers. In this present study, we observed the effects in the ceca microbiome, hypothalamus, ileum small intestine, and thymus tissues of broilers by comparing the growth performance and gene expression of cellular signal transduction pathways among three groups: thermal neutral, heat stress and heat stress with astaxanthin. The thermal neutral temperature was 21–22◦C with 50% relative humidity, and the heat stress temperature was 32–35◦C with 42-50% relative humidity. The broilers were reared under thermal neutral conditions and provided a normal starter feed in the first 21 days, then in the last 21 days provided normal finisher feed, and separated further into the two temperature regimes, with the heat stress with astaxanthin group supplemented with 1.33mg/kg of astaxanthin additive. The results showed a significant negative impact of heat stress on growth performance indicators, and more severely the group without astaxanthin additive, but not statistically significant for the ceca microbiota diversity except for the amplicon sequence variants identified. The metagenomic analysis of the ceca microbiome in the terpenoid biosynthesis enzyme pathway resulted in isopentenyl-diphosphate delta-isomerase enzyme marginally significant in the production pathway of astaxanthin. Glutamate-cysteine ligase the rate limiting enzyme in glutathione biosynthesis was significantly higher in the astaxanthin group over the heat stress group, and the reactive oxygen species degradation pathway resulted in superoxide reductase and catalase peroxidase to be significantly higher in the astaxanthin over the heat stress group, while thioredoxin-disulfide reductase was found to be marginally higher in the heat stress group over the thermal neutral group. The hypothalamus experiments resulted in the upregulation of the astaxanthin treated group across the cell signal transduction pathways for thermoregulatory sensing of the TRP ion channels, NF-kB, NFE2L2, PPARa and cytoprotective capacity genes. The ileum small intestine experiments resulted in the astaxanthin treated group upregulated in the cytoprotective gene expression for HSF2, SOD2, GPX3, and TXN, as well as the upregulation of epithelial integrity genes LOX, CLDN1, and MUC2. Ileum histomorphology measurements showed further physiological changes in the villus and crypt which may be adaptive to preserving intestinal function and optimization of nutrient absorption. The thymus experiments resulted in the heat stress group showing significant upregulation in the signal transduction pathways indicating heat-induced oxidative stress and apoptosis, however, expression levels showed no significant differences between the thermal neutral and heat stress with antioxidant groups, suggesting that astaxanthin may mitigate inflammation and oxidative stress damage. In summary, the findings resulting from the studies described herein suggest that H. pluvialis astaxanthin may mitigate heat-induced oxidative stress in broilers, and that further research into dosing concentrations and additive mixtures may further compliment the protective mechanisms of action and potential health benefits.
FUNCTIONAL CHARACTERIZATION OF PROTEIN DISULFIDE ISOMERASE 9 IN ARABIDOPSIS THALIANA AND ITS ROLE IN THE UNFOLDED PROTEIN RESPONSE
(University of Hawai'i at Manoa, 2024) Carrillo, Rina Marie; Christopher, David; Molecular Biosciences and Bioengineering
The endoplasmic reticulum (ER) is responsible for synthesis, folding, and maturation of most secretory proteins in eukaryotes. Environmental stressors disrupt secretory protein folding and proteostasis in the ER leading to ER stress. The unfolded protein response (UPR) senses ER stress and restores proteostasis by increasing the expression of ER resident protein folding chaperones, such as the protein disulfide isomerases (PDIs) and BiP. In plants, the transmembrane ER stress sensor-kinase, IRE1, activates the UPR by unconventionally splicing the mRNA encoding the bZIP60 transcription factor, triggering UPR gene transcription. The induced PDIs catalyze disulfide-based polypeptide folding to restore the folding capacity in the ER. The Arabidopsis PDI-M subfamily member, PDI9, is highly induced in response to ER stress and the UPR, however the substrates with which PDI9 interact and the specific role that PDI9 has on the ER stress response is not well understood. To determine the modulatory role of PDI9 on the UPR, a bZIP60 reporter construct fused to GFP was generated to measure UPR activation. Interaction with the conserved ER stress sensor IRE1 was also tested. Through various protoplast transfection assays and quantitative microscopy analyses, it was revealed that PDI9 modulated the UPR and interacts with IRE1 in Arabidopsis. Genetic markers of UPR were highly upregulated in the pdi9 mutants relative to WT, suggesting PDI9 plays an important role in mitigating against overactive UPR and in maintaining proteostasis under stress. To identify other novel protein interactors of PDI9, a PDI9 stable transformant was generated and pull-down experiments were performed from ER-stress induced roots and cotyledons of Arabidopsis. It was discovered that PDI9 interacts with the UPR-mediator and ER-resident molecular chaperones, BiP1 and BiP2. The dynamin-related GTPases, DRP1 and DRP2, were also discovered as novel interactors of PDI9. In addition, homodimerization was detected between PDI9 through quantitative FRET analysis in protoplast cells. These findings indicate that PDI9 plays an important role in the UPR pathway through interaction with IRE1 to potentially attenuate the UPR in a manner analogous to mammalian models. Additional regulatory roles of PDI9 may also be taking place to modulate this UPR pathway through interaction with the UPR-responsive chaperone, BiP1 and BiP2, or by PDI9 homodimerization. We propose a model in which PDI9 modulates the UPR through two competing activities: secretory protein folding and via interaction with IRE1 to maintain proteostasis in plants. By uncovering novel biological roles of PDIs and regulatory players of the UPR in plants, these results contribute to the foundational understanding of how plants mitigate and adapt to environmental stressors such as heat and drought, to maintain their viability and growth.
NICOTIANAMINE BIOSYNTHESIS IN PLANTS
(University of Hawai'i at Manoa, 2024) Carrillo, James Thomas; Borthakur, Dulal; Molecular Biosciences and Bioengineering
Plants rely upon a small chemical ligand, nicotianamine (NA), to chelate metallic ions during transport throughout tissues and across cell membranes. The production of this essential compound is achieved by three enzymes: S-adenosylmethionine (SAM) synthetase, NA synthase and 5’-methylthioadenosine (MTA) nucleosidase. The characterization of each of these enzymes from any plant species is lacking or absent, therefore the coding sequence for these genes were isolated from local hardwood species and characterized in vitro. The cDNA encoding for SAM-synthetase, NA synthase and MTA nucleosidase was isolated from giant leucaena (Leucaena leucocephala subsp. glabrata) root tissue mRNA. Transcriptome data and/or 5’-RLM-RACE were used to obtain the full transcript sequence. The complete coding sequences were cloned into a T7-expression vector and expressed in Escherichia coli. The giant leucaena SAM-synthetase displayed optimal enzyme activity at pH 10.0, 55 oC, and 200 mM KCl. In addition to thermophilic activity, giant leucaena SAM-synthetase remains highly active in solutions containing up to 4 M KCl and accepts Na+ to some extent as a substitute for K+, a known required cofactor for SAM-synthetases. The enzyme followed Michaelis–Menten kinetics (Km = 1.82 mM, Kcat = 1.17 s-1, Vmax 243.9 µM. min-1) and was not inhibited by spermidine, spermine or nicotianamine. Plant SAM-synthetases have not been characterized previously and the activity of the giant leucaena SAM-synthetase differed greatly from that of nonplant SAM-synthetases. Therefore, a second plant SAM-synthetase from Acacia koa was investigated. The activity of the Acacia koa SAM-synthetase resembles that from the giant leucaena (Km = 1.44 mM, Kcat = 1.29 s-1, Vmax 170 µM. min-1) and exhibited similar alkali-thermophilic properties. Four single-point mutation variants of the Acacia koa SAM-synthetase were produced, each with varying degrees of reduced reaction rate, greater sensitivity to product inhibition and loss of thermophilic properties. Although an enhanced mutant was not produced, the addition of organic solvent was shown to have a beneficial effect on enzyme activity. Feedback inhibition was reduced in SAM-synthetase enzyme assays containing 25% acetonitrile, methanol or dimethylformamide and total SAM production improved by 30-65%. Transcriptome sequence data and 5’-RLM-RACE methods identified the complete NA synthase coding sequence, which was cloned for heterologous expression and in vitro assays. Soluble expression was highly repressed, however heat-shocking and high-NaCl media improved recombinant enzyme production approximately 6-fold. Feedback inhibition by MTA is known to severely limit the in vitro activity of SAM dependent enzymes, however this work demonstrates comparable effects produced by substrate inhibition. Producing enantiomerically pure substrate in situ, using a recombinant SAM-synthetase, enabled 5-fold faster NA synthase activity (Vmax = 1.25 µM. h-1) and 2-fold net nicotianamine production than when commercially purified substrate, a racemate, is provided. Sequence and structural analyses suggest residues involved in azetidine ring formation, and other aspects of the mechanism are explored. The complete coding sequence of a MTA nucleosidase was obtained from the giant leucaena transcriptome and cloned into pet39b, thereby expressing a fusion protein secreted into the E. coli periplasm. The crude periplasmic extract was tested for MTA-nucleosidase activity and when combined with SAM-synthetase and NA-synthase, further improved the reaction rate 22-fold (Vmax = 27.5 µM. h-1) and net NA production 3-fold. In vitro NA production is optimal in solutions containing all three enzymes (SAM-synthetase, NA-synthase, and MTA-nucleosidase), however the reaction becomes fully inhibited upon producing 58.5 µM NA. In addition to the in vitro characterization of recombinant enzymes, the in plantae transcription of NA synthase, SAM synthetase and 17 other genes was quantified in giant leucaena seedlings. In response to high-iron fertilization, real-time PCR performed on root and foliar tissue showed overall upregulation of most genes. Notable genes affected include glutathione synthase (20-fold increase in leaf), ferric chelate reductase (15-fold increase in root), mimosinase (20-fold increase in leaf) and nicotianamine synthase (30-fold increase in root). In response to iron fertilization, mimosine metabolism was shown to be increased by metal induced stress; that is oxidative stress and not iron itself. Furthermore, the gene expression profile of leaf tissue indicated that plants with high mimosinase activity were less affected by iron and experienced less oxidative stress. Therefore, mimosine metabolism may broadly affect iron-regulated processes and enable the hyperaccumulation of iron or other metals.
Developing Robust Machine Learning Models to Predict NSCLC Immune Checkpoint Therapy Outcomes
(University of Hawai'i at Manoa, 2024) Chen, Shaoqiu; Deng, Youping; Molecular Biosciences and Bioengineering
Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, despite recent advancements in treatment options. Immune checkpoint inhibitors (ICIs) have shown promise in improving patient outcomes, but their efficacy varies widely among individuals. Predicting patient responses to ICIs is crucial for optimizing treatment strategies and improving overall survival. However, current predictive biomarkers, such as PD-L1 expression and tumor mutational burden (TMB), have limitations in terms of accuracy and invasiveness.This dissertation aims to advance the field of personalized medicine in non-small cell lung cancer (NSCLC) treatment by developing innovative strategies for predicting patient responses to immune checkpoint inhibitors (ICIs). Through a series of interconnected studies, we leverage the potential of transcriptomics, machine learning, and non-invasive biomarkers to create more accurate and precise predictive models. Our research begins with the development of a robust 11-gene signature derived from the largest dataset of pre-treatment tumor tissue samples compiled for this purpose. This signature demonstrates strong predictive performance, distinguishing responders from non-responders with an AUC of 0.85 in discovery datasets and 0.84 in validation datasets. We then apply advanced machine learning techniques and address class imbalance issues to further enhance the performance and reliability of our predictive models, showing their superiority over established biomarkers. Recognizing the limitations of invasive tissue-based approaches, we develop a novel 11-gene signature derived from peripheral blood mononuclear cells (PBMCs) and buffy coat samples. This non-invasive biomarker proves effective in predicting ICI responses, with AUCs of 0.87 and 0.84 in PBMC and buffy coat cohorts, respectively. By offering a less invasive approach to monitoring treatment efficacy, this signature has the potential to improve NSCLC management, particularly for the people of Hawaii who face challenges in accessing specialized care. The findings of this dissertation contribute to the growing body of tools for tailoring immunotherapy to individual patient needs and optimizing healthcare resource allocation. As we continue to validate and refine these predictive biomarkers and machine learning models, we move closer to a future where precision medicine becomes the standard of care for NSCLC treatment, offering improved outcomes for patients in Hawaii and beyond. This dissertation represents a significant step forward in the quest for personalized medicine, laying the foundation for a new era of targeted, effective, and patient-centric care in the face of a major health challenge.
From Genes to Pastures: Unraveling Ancestry, Admixture, and Environmental Adaptations of Beef Cattle in Hawai‘i
(University of Hawai'i at Manoa, 2024) Adhikari, Mandeep; He, Yanghua YH; Molecular Biosciences and Bioengineering
Cattle ranching in Hawai‘i, shaped by its unique climate and geography, is of historical and contemporary significance. Yet comprehensive genomic studies of Hawaiian cattle remain scarce. This is the first dedicated genomic study of Hawaiian cattle, which decoded the genetic background, breed composition, and genetic variants governing cattle production and climate adaptation.In this study, we collected blood samples from 351 cattle heads spanning 11 ranches across four Hawaiian islands and genotyped them with Neogen GGP 100K SNP chips. Genetic admixture and divergence events in the Hawaiian cattle population were analyzed to decode cattle ancestry and deduce the evolution of cattle breeds on Hawaiian lands historically. These data were further used for two association studies, including the Genome-Wide Association Study (GWAS) and the Genome-Environment Association Study (GEA). In addition, we collected tissue samples from the digestive tract of pasture-finished cattle at the Mealani Research Station, belonging to the University of Hawai‘i at Mānoa. We performed a transcriptomics study to understand the roles of diet and the influence of production systems in health and immune defense mechanisms against biotic and abiotic stress. This study identified the dominance of Angus beef cattle in Hawai‘i. However, the present-day Hawaiian Angus was drifting away from their original lineage. Admixture and interactions among genetics, environments, and selection pressures may have significantly played roles in developing new breed entities in this isolated geography with diverse climates. We identified an admixture of one to ten percent of indicine lineage from the Brahman breed in continental Angus, which developed into a tropical Hawaiian Angus, as novel findings of this study. GWAS and GEA studies identified genetic variants and candidate genes, including RGS20, ZMAT3, RUVBL1, EEFEC, and SEC61A1, associated with production and adaptation in tropical pasture-based conditions. A comparative transcriptomics study of cattle subjected to grain-fed versus pasture-fed diets revealed diet-induced gastrointestinal dysfunctions. Cattle fed a more hygienic diet and raised in open pasture-based production showed promoted gut health and defense against stress. This was evidenced by upregulations of Mitogen-Activated Protein Kinases (MAPKs) and downregulations of proinflammatory cytokines. This study opens a door for future genomic studies in the Hawaiian beef cattle population, exploring their unique traits and quality, particularly in comparative studies with cohorts from Hawaiian Angus adapted to tropical environments, can be valuable genetic resources for crossbreeding as a strategy for combating observed consequences of climate change.
IMMUNOPHENOTYPE OF SOLID TUMORS AND TUMOR METABOLIC REPROGRAMMING
(University of Hawai'i at Manoa, 2024) zitello, emory david; Bingham, Jon-Paul; Molecular Biosciences and Bioengineering
ABSTRACTWith the technological advances in biotechnology that have been made high-throughput measurement of nucleic acids feasible and affordable, the tumor microenvironment (TME) has been intensively studied. Advances in therapy have made pharmacologic treatment of cancer more effective than ever before. However, in consideration of the expense of the new class of monoclonal immunotherapeutic antibodies, their occasionally serious side effect profile, and a somewhat limited spectrum of activity among patient cohorts, there has come a great demand to understand the factors which make individual cases of cancer differ. Many approaches to address the issue of individual patient response to immunomodulatory antibodies have been devised. Both traditional, bench-based approaches and more modern, bioinformatical solutions have yielded important insights into the problem. Unfortunately, many difficult and important questions have remained unexplained. In particular, a general theory that is capable of explaining the broadest similarity of observed clinical responses to therapy with monoclonal immunotherapeutic agents across dissimilar patient cohorts that identifies a clear relationship to cellular and molecular features has been elusive. Understanding the most important concepts involved in tumor immunology requires drawing together some intermediate and detailed knowledge from several subdisciplines in biology and clinical medicine. In the studies presented here, elements of bioinformatic data analysis, details of immunological function, and knowledge of cellular and molecular processes relevant to cancer are reviewed in terms of published literature as an introduction. In a second segment, these topics of perceived relevance to studies of cancer are then highlighted with presentations of new findings based upon a novel bioinformatic approach. A summary is presented in Chapter 3 containing a brief discussion of how these findings impact the field with reference to current knowledge and practice, while a series of Appendices further substantiate the importance of these findings with brief details of a variety of related results.
Revealing Effective Antiviral Targets: Unraveling the Mechanisms Behind the Recruitment of West Nile Virus Components to the Replication Complexes
(University of Hawai'i at Manoa, 2020) Tseng, Alanna; Kaufusi, Pakieli; Molecular Biosciences and Bioengineering
West Nile virus (WNV) is a global mosquito-borne pathogen that poses a major threat to public health. WNV preferentially infects neuronal cells in the central nervous system and can cause encephalitis, meningitis or paralysis, which can lead to long-term neurocognitive impairment. Infection of WNV is characterized by the reorganization of the rough endoplasmic reticulum (RER) membranes to create unique intracellular compartments known as replication organelles (RO). These RO comprise the viral non-structural (NS) proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) for robust virus replication. The RO consists of vesicle packets (VP) and convoluted membranes (CM) compartments, which serve as the putative sites for RNA synthesis and proteolytic processing, respectively. Out of all of the NS proteins, only the two largest NS proteins, NS3 and NS5, have clearly defined functions and contain all of the enzymatic roles required for viral RNA replication. NS3 consists of protease and RNA helicase domains while NS5 harbors the methyltransferase and RNA-dependent RNA polymerase domains. Given that NS3 and NS5 are soluble proteins that must associate with the RO to promote efficient virus replication, how NS3 and NS5 are recruited from the cytoplasm and retained at the ER-derived RO compartments remains unclear. Previous studies have shown that other NS proteins may contribute to the functional activation of NS3 and NS5, but the mechanistic details of these interactions at the RO are unknown. Furthermore, how the RO structures are initially formed has not yet been elucidated. In this dissertation, we characterized the viral NS protein(s) that (1) promote the ER association and RO compartment localization of NS3 and NS5 and (2) induce RO formation in human embryonic kidney cells (HEK293T). Using high-resolution confocal microscopy (HRCM) and biochemical assays, we demonstrate that soluble NS3 appeared to be peripherally recruited to the ER and was proteolytically active when NS2B was provided in trans. Therefore, we reveal the potential dual role for NS2B in not only serving as the cofactor for NS3 enzymatic activity, but also in recruiting NS3 to the ER membrane for RO association. In addition, we observed that NS5 did not localize to the ER in the presence of other viral NS proteins using HRCM. However, NS1 or NS3 appeared to partially influence the membrane association of NS5 in our sucrose gradient centrifugation assay. For NS5 to completely associate with the ER, we therefore propose that other events of the viral life cycle, such as the enwrapment of NS5 by the RO compartments, are important for NS5 retention in the ER. Furthermore, the partial association of NS5 with NS1 led us to examine whether NS1 initiates the VP structures, where NS5 exerts its enzymatic functions. Using transmission electron microscopy (TEM) of transfected HEK293T cells, we clearly demonstrate that expression of NS1 alone remodeled the ER membrane to form vesicles that were reminiscent of those formed during WNV infection. To the extent of our knowledge, this is the first report showing that WNV NS1, in the absence of other viral NS proteins, initiates VP formation. Taken together, these studies provide valuable insight on the physical and enzymatic link between NS1, NS3, and NS5 in VP localization and biogenesis, which will aid in the identification of novel targets for antiviral drug therapy.
EPIGENOMIC AND EPITRANSCRIPTOMIC LANDSCAPE: ANALYSIS, PERFORMANCE ASSESSMENT, AND INTEGRATIVE MULTI-OMICS PROFILING IN HUMAN COLORECTAL CANCER
(University of Hawai'i at Manoa, 2023) Gong, Ting; Deng, Youping; Molecular Biosciences and Bioengineering
The interplay between genetic and epigenetic factors is crucial in the onset and progression of colorectal cancer (CRC), a disease characterized by its complexity and high morbidity and mortality rates globally. This dissertation is focused on unraveling the roles of epigenomic and epitranscriptomic modifications in CRC, with the aim of identifying significant biomarkers and characterizing their functional implications through advanced bioinformatics and machine learning techniques.The first part established a foundation by examining DNA methylation, a crucial epigenetic mechanism. It delved into whole-genome bisulfite sequencing (WGBS), presenting a detailed comparison of methodologies and tools for analyzing DNA methylation patterns. This set the stage for understanding aberrant methylation in CRC, highlighting its significance in disease pathology, and offering insights into the complexities of epigenomic profiling. Building upon this, the second part expanded the scope to include a broader range of epigenetic methods. It presented a multi-platform assessment, utilizing several human cell lines to evaluate the reproducibility and efficiency of different genome-wide methylome sequencing protocols. This comprehensive characterization not only benchmarked current methods but also linked DNA methylation patterns to the wider epigenomic alterations observed in CRC. Subsequently, the final part evaluated m6A MeRIP-Seq data analysis pipelines, focusing on their sensitivity and specificity in detecting and quantifying m6A modifications, ensuring that the results can reliably inform about the presence and potential role of m6A modifications in CRC. Utilizing the selected m6A MeRIP-Seq pipelines in conjunction with RNA sequencing data, the analyses provide a comprehensive epitranscriptomic characterization of CRC. This involved identifying novel m6A modification patterns that are functionally relevant to CRC's development and progression. Furthermore, the research delved into the interaction between epitranscriptomic alterations and their subsequent impact on gene expression, signaling pathways, and the tumor microenvironment, thereby providing a holistic view of the molecular dynamics at play in CRC. This multifaceted approach endeavors to bridge the gap between epigenomic and epitranscriptomic research, offering a thorough understanding of their implications in CRC. The insights gained from this study aim to contribute to the field of cancer genomics, potentially leading to the development of new diagnostic and therapeutic strategies.
REDUCING THE BURDEN OF CANCER WITH ARTIFICIAL INTELLIGENCE: IMAGE-BASED MODELS FOR BREAST CANCER DETECTION, ADVANCED STAGE RISK, AND CROSS-MODALITY VISUALIZATION
(University of Hawai'i at Manoa, 2023) Leong, Lambert T.; Shepherd, John A.; Molecular Biosciences and Bioengineering
Medical imaging provides a non-invasive method for obtaining valuable information used to detect cancer and assess cancer risk. Constant improvements to imaging technologies have resulted in more available information as well as new types of information that can be tied to biomarkers of cancer. Our central hypothesis is that only a portion of the imaging information related to breast cancer risk and detection is currently being utilized due to the limitations of deriving and testing preconceived imaging biomarkers of simple constructs. The objective of this dissertation is to develop artificial intelligence (AI) and machine learning (ML) models to fully interrogate medical images for additional information related to cancer detection and risk. In this work, we also develop methods to address limited labeled training data, which is a common problem in ML. Our specific aims and outcomes are as follows: 1) Identify compositional imaging biomarkers related to breast cancer detection; 2) Investigate imaging features associated with risk of advanced-stage breast cancer; 3) Implement pretraining methods to improve modeling with limited labeled medical images for body composition. Novel contributions to the field resulting from each aim are as follows: 1) Malignant lesions were confirmed to have unique compositional signatures which can be used to improve detection specificity; 2) Mammographic images were found to contain advance stage cancer risk information beyond just breast density; 3) Self-supervised pretraining with domain-specific data helped us overcome limitations stemming from the size of our labeled dataset. Both a more quantitatively accurate image generation model and a more accurate dual-energy X-ray absorptiometry image analysis model resulted from this study aim.
Elucidating The Role Of Peptidyl tRNA Hydrolase 2 In The Heart
(University of Hawaii at Manoa, 2023) Montoya-Uribe, Vanessa Maria; Matter, Michelle L.; Molecular Biosciences and Bioengineering
Peripartum cardiomyopathy (PPCM) is a form of maternal heart failure that presents with left ventricular dysfunction and may lead to heart failure and death. PPCM occurs during the last month of pregnancy or within five months after delivery in previously healthy women. PPCM is a condition of unknown etiology. Previous hypotheses have pointed at hemodynamical stresses as the underlying cause of PPCM. More recently, a genetic predisposition approach has gained more interest in explaining the pathophysiology of PPCM. Peptidyl tRNA hydrolase 2 (PTRH2) has been identified as a key regulator in skeletal muscle development and myogenic differentiation. PTRH2 has also been shown to transmit mechanosensory signals by interaction with an integrin-FAK complex to induce survival in attached cells. Additionally, biallelic mutations in Ptrh2 gene cause an infantile multisystem neurologic-endocrine-pancreatic disease (IMNEPD) in humans. We found that left ventricular expression of PTRH2 increases upon pregnancy in non-transgenic (Ptrh2-flox/flox, Ptrh2-NT) mice. We developed a heart specific knockout of PTRH2 (Ptrh2-CKO) and found that all pregnant female mice develop a pregnancy-induced phenotype like that of PPCM patients. Here, we report a novel hypothesis of mechano-transduction for the pathogenesis of PPCM in which PTRH2 is the key player. We hypothesize that PTRH2 may be protecting the heart by acting as a cardiac mechano-sensor in response to pregnancy-induced pressure overload. Additionally, we performed histological, echocardiographic, gene and protein expression analyses to characterize the PPCM phenotype in the female Ptrh2-CKO mice hearts compared to pregnant Ptrh2-NT controls as well as proteomics analyses and yeast-two hybrid screening to identify interacting partners of PTRH2. Co-immunofluorescence staining, proximity ligation, co-immunoprecipitation and pull-down assays were carried out to confirm direct interactions. Human samples from PPCM and dilated cardiomyopathy (DCM) patients were also analyzed by whole exome sequencing (WES) for potential Ptrh2 gene mutations. Our results showed that Ptrh2-CKO mice exhibit left ventricular enlargement and hypertrophy that transitions into dilated cardiomyopathy Post-Partum. These cardiac mechanical stresses ultimately lead to heart failure as confirmed by histology, echoes, and gene expression analyses. Yeast-two hybrid screening and proteomic analyses identified cardiac beta-myosin heavy chain (β-MHC) and myosin regulatory light chain (MYL2), cardiac regulators of contractility, as potential interacting partners for PTRH2. Further, β-MHC and PTRH2 were found to form a complex in solution and co-localize at the Z-disc, a dynamic sarcomere structure that regulates signal transduction across the myofibrils during contraction. Loss of Ptrh2 also disrupted sarcomere arrangement and Ptrh2-CKO mice exhibited decreased contractility function leading to heart failure. Human WES revealed a potential homozygous deletion of Ptrh2 that may be contributing to the PPCM phenotype in patients. Altogether, these findings suggest PTRH2 as a potential modulator of pregnancy-induced cardiac stress and as an essential mechano-transducer in the heart via cardiac β-MHC.
The Bioinformatics Exploration of Stevia rebaudiana
(University of Hawaii at Manoa, 2023) Doherty, James; Panee, Jun; Molecular Biosciences and Bioengineering
Stevia rebaudiana (stevia) is a short-day perennial Asteraceae that is native to Brazil and Paraguay and is renowned for its sweet taste. In the undertaking of this project, a large Next Generation Sequencing (NGS) dataset was generated from twenty-three genetically unique stevia plants. Stevia leaf samples were collected three times over eleven months in 2019. The leaf samples were used to generate RNA-seq data and resulted in a cDNA library of over one billion Illumina small reads. The dissertation work commenced with constructing the best possible transcriptome from S. rebaudiana leaf tissue. This effort resulted in a high-quality, non-redundant (to 95% similarity) catalog of S. rebaudiana genes replete with names and functional annotations and a BUSCO score of 96%. The high BUSCO score indicates that the final catalog of stevia RNAs is complete and representative. The resultant index of RNAs contains 66,022 complete RNA sequences that can be sorted by putative function, length, or expression level and contains ~23% more RNAs than the publicly available transcriptome published in 2021. The catalog of 66,022 RNA sequences also includes 9,275 novel RNAs that were missed in the previous construction of the stevia genome. During an early stage of the de novo transcriptome, the presence of a Picornavirus, Bundaberg Bee Virus 4 (BBV4), was detected in some of the samples. This represents the first identification of BBV4 in Hawaii and the second in the world. This unexpected finding expanded my interest from stevia genetics to the virome of the stevia plants grown in Hawaii. The genome of BBV4 was extensively characterized, and the results have been accepted for publication in the European Journal of Biotechnology. Further effort was exerted to catalog the virome in the transcriptome, and the results provided fascinating insights into the viral landscape of stevia plants grown in Hawaii. Initially, the virome catalog was exclusive to Riboviria, as the data was generated from RNA-seq. However, the discovery of viral RNA from a DNA virus was identified in the dataset, and after that, the project's scope expanded to include DNA viruses. The revised direction resulted in a comprehensive catalog of over 40 viruses, 70 species of bacteriophages, and at least one mega-virus. In summary, this project constructed the most complete transcriptome of S. rebaudiana to date, and cataloged 66,022 full stevia RNA sequences, of which, including 9,275 novel stevia RNAs that were identified for the first time. Furthermore, this project documented the first virome in the leaves of S. rebaudiana grown in Hawaii and comprehensively characterized the genome of one of the Picornaviruses, BBV4. This project employed many bioinformatics tools across multiple platforms to examine and analyze the dataset and obtained a rich body of genetic information of stevia plants and the virome associated with the plants. The ever-changing nature of bioinformatics necessitates ongoing engagement with new tools, resources, and methods, and this project exemplifies that sentiment.
The Genetics and Epigenetics of Maize Centromeres
(University of Hawaii at Manoa, 2022) Laspisa, Daniel Joseph; Presting, Gernot; Molecular Biosciences and Bioengineering
Centromeres are chromosomal structures defined epigenetically by the histone cenH3. These structures are required for the faithful segregation of chromosomes during cell division, and survival of all eukaryotic organisms. The sequences of the centromere are highly repetitive, primarily containing tandem repeats and transposable elements. Remarkably, the repeats and proteins involved in centromere function evolve rapidly though the function of centromeres is highly conserved, a phenomenon referred to as the “centromere paradox”. This has been interpreted to be due to evolutionary pressure on both molecules based on their interaction (centromere drive). Recent investigations into domesticated maize have shown that artificial selection and genetic bottlenecks during domestication heavily influenced the evolution of domesticated centromeres, rather than the interplay of centromeric repeats and proteins as hypothesized by meiotic drive. Disruption of the ancestral centromere has the potential to cause the formation of a neocentromere in the pericentromere or chromosome arm. In Zea mays, loss of the centromeric tandem repeat centC has the potential to destabilize centromeres. When the centC is lost cenH3 can either spread into the chromatin flanking centC, or jump to a new locus entirely. Our investigations have determined that the jump from CEN5M to CEN5L or CEN5R was the result of transcribed genes flanking CEN5M which restricted the spread of cenH3 into flanking regions following loss of centC. The pericentromeres provide relatively ideal locations for neocentromere formation due to low transcription. The newly formed neocentromeres were stabilized through the loss of a H2A.Z loci that were shown to destabilize cenH3, via deletions and suppression by cenH3. Regions of limited recombination surrounding centromeres were defined by structural variation and selection in CEN2 and it was observed that a tight linkage between a domestication locus to a centromeric haplotype region can reduce the observed centromeric diversity likely due to linkage drag. Following the formation of neocentromeres they were rapidly colonized by CR2 retrotransposons which expanded in a burst event during domestication. There was extensive recombination among these elements, but a preferred recombination was not responsible for their expansion. It is possible that expansion of the CR2 subfamily was the result of horizontal transfer of a foreign CR2 element, or the result of epigenetic changes in the ancestral centromere following neocentromere formation. Regardless of the trigger for expansion, the CR2 insertions served to further stabilize the neocentromeres by increasing the repeat content and pushing sensitive DNA such as genes and regulatory regions out of the neocentromeres. Overall, these investigations suggest the story of domesticated maize centromere evolution was one of stability. The process of domestication destabilized the centromeres, and the centromeres have since been evolving to reacquire stability in a new genomic context.
Data Science For Molecular Genetics And Communication In The Natural Sciences
(University of Hawaii at Manoa, 2022) Bartlett, Bjarne; Kantar, Michael B.; Molecular Biosciences and Bioengineering
“By 2025, it’s estimated that 463 exabytes of data will be created each day globally – that’s the equivalent of 212,765,957 DVDs per day!” -World Economic Forum Data science refers to the study of increasingly large and complex datasets. Data that are too large for standard tools (e.g., Excel, Google Sheets) to analyze are often referred to as “big data.” While big data exists across many areas and is thought to be the path to answering many questions, there is still no consensus on the fundamental principles and skills needed to interact with big data. Further, skills to study big data are not universally taught systematically at the college level–the resulting gap in skills leaves students unable to analyze the same big data that are touted as the way to answer complex questions. This dissertation proposes a plan to close the big data knowledge gap by incorporating data science principles from diverse disciplines into a biology curriculum. Specifically, essential information was distilled from three independent study systems in cancer diagnostics, plant genomics, and academic publishing. Each study system contributed a different perspective on skills and knowledge from analyzing big data. From these systems, I identified three critical areas that are central to using big data effectively. From these diverse perspectives, I developed a model to assist instructors in constructing curricula that will work in many different biological contexts. I piloted the use of these principles in a summer course. I found that by incorporating instruction developed across knowledge areas, meaningful data science instruction can occur in any curriculum at any student level.
The Utilization Of Natural Products For Agricultural Benefits
(University of Hawaii at Manoa, 2022) Ooka, Joey Kan; Owens, Daniel; Molecular Biosciences and Bioengineering
The invasive species Psidium cattleianum, termed strawberry guava, poses a major problem for the State of Hawaii. It outcompetes native plants, with the dominance of strawberry guava potentially due to allelopathy, which is the biochemical inhibition of one plant by another. To isolate potential allelochemicals, water extracts from both varieties of strawberry guava (red and yellow), were tested and found to reduce dicot and monocot growth. The yellow variety of strawberry guava produced an Inhibition constant of 50% lethality (IC50) of 10.74mg/mL for lettuce and 12.2 mg/mL for green onion, while the red variety produced a IC50 of 9.57mg/mL for lettuce and 6.54 mg/mL for green onion. In soil trials, it has been found that Psidium cattleianum leaf chemicals reduced the germination rate of the monocot (Echinochloa sp.) more relative to the dicot (Amaranthus retroflexus). High performance liquid chromatography bioassay mediation fractionation and tandem mass spectroscopy found that the phenolic acid, gallic acid, is a constituent for Psidium cattleianum’s allelopathy. Additionally, in-silica molecular docking was conducted with the enzymatic molecular target site, hydroxyphenylpyruvate dioxygenase, to create a predictive model. The trends showed that, based upon 2-acyl-cyclohexane-1,3-diones with simple aliphatic side chains, the perfect R1 tail length is an undecyl 11-C. Too short a tail did not fully utilize the binding pocket, while too long of a tail did not fit within the binding pocket properly, showcased by having a more positive binding energy and a less efficient IC50 value. This class, along with cyclohexane-1,3-diones with phenyl side chains or phenylene side chains also followed another trend, where the addition of an R2 methyl group again made a more positive binding energy and a less efficient IC50 value, possibly due to sterics. This showed proof of concept that it is possible to correlate binding energy and measured IC50 values to create this predictive model that can be adapted to other molecular target sites and ligands. In addition, while only strawberry guava was investigated within the course of this work, there remains multiple suspected allelopathic species than can be further analyzed following strawberry guava’s path as a blueprint for future studies.

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