The use of computational models of memory has been effective in adaptive learning environments and in determining the memory capabilities of learners. However, these models have not been widely applied in clinical settings. Evaluation of memory loss still heavily relies on extensive neuropsychological testing performed by neurologists or psychiatrists, especially in the context of progressive neurodegenerative disorders. Current evaluation tools lack the necessary reliability, convenience, and repeatability to effectively capture key dynamics of memory decline, including the unique and changing nature of memory over time. The goal of this study was to predict and monitor memory decline in individuals diagnosed with Mild Cognitive Impairment (MCI) using a model-based adaptive fact learning system. Participants, aged 58 to 78 years, were divided into two groups based on their cognitive classification and completed weekly online learning assessments at home, tracking their individual speed of forgetting (SoF) across various study materials. The results showed that this method was effective in accurately diagnosing mild memory impairment, with a success rate of over 80% after a single 8-minute learning session. The study also demonstrated the model’s ability to distinguish MCI subtypes through computations of participants' SoF. These findings offer novel insights into the progressive nature of memory decline and could have implications for early detection and management of Alzheimer’s disease as well as other forms of dementia and cognitive impairment. Further development of this method could serve as an alternative or complement to established diagnostic procedures and be used in clinical settings.

The leading causes of hearing and balance disorders are damage and loss of inner ear hair cells. Noise overexposure and aging can damage the fragile synaptic transmission between presynaptic hair cells (HC) and postsynaptic afferent neurons (AN), leading to “hidden” hearing loss. Hidden hearing loss is a condition where one can show normal auditory sensitivity when tested but still have difficulty in situations such as hearing one person in loud environments. Mitochondria might play an essential role in this connection by regulating transmission and energy supply. Mitochondria are known to adapt their morphologies to meet cellular demands. Studying mitochondrial morphology may reveal solutions to hearing preservation and contribute to our overall knowledge of the auditory system and general biology. Our lab has previously found that presynaptic hair cells harbor unique mitochondrial networks localized at the presynaptic HC release sites (ribbons) regulated by activity. However, the synapse requires postsynaptic neurons to function correctly to maintain healthy auditory transmission, so we examined the postsynaptic ANs. Preliminary data of two postsynaptic ANs revealed mitochondrial networks that extend between different HCs, but substantial evidence was lacking. Using the zebrafish lateral line as a model system, I microinjected fluorescent probes that tag AN mitochondria, Ca2+ uptake, and track depolarization via Channelrhodopsin. I used serial block-face scanning electron microscopy (SBFSEM) to reconstruct zebrafish AN and their mitochondria. SBFSEM cuts thin layers of the fluorescently tagged structures and images each layer to generate high-resolution 3D images. Probes successfully tracked the different functional characteristics. We observed distinctive architecture in postsynaptic mitochondria, confirming our preliminary findings. Further research will assess changes in postsynaptic mitochondria and regulation by synaptic activity. Understanding the connection between mitochondrial architecture at the synapse and its functional mechanisms will contribute to our knowledge of proper synaptic transmission and the pursuit of healthy hearing preservation.

Research suggests that recruitment, the number of fish entering a population in a given year, is influenced by the environment. However, environmental drivers are not currently used to refine the recruitment estimates of most statistical models used in fisheries management (hereafter, population assessment models). This is increasingly relevant as fish populations experience long-term productivity shifts due to climate change. One major goal of the National Oceanic and Atmospheric Administration (NOAA) in recent years has been to incorporate environmental drivers into population assessment models. This is achieved by using time series data of environmental drivers to inform model estimates. One ongoing challenge is determining which environmental drivers have potential to improve model estimates. In this project, we aimed to determine how correlated an environmental driver time series must be to historical recruitment deviations to improve key model estimates – recruitment deviations and population depletion – in recent years for a range of species. We used R to simulate mock environmental driver time series with varying correlation levels to recruitment deviations by randomly sampling data from a normal distribution. We then compared errors in estimates between population assessment models fit with and without the simulated environmental data. Our results suggest that the more correlated an environmental driver is to historical recruitment deviations, the more accurate estimates of both recruitment deviations and population depletion become. However, our results also reveal that the correlation level necessary for environmentally-driven models to consistently produce more accurate estimates than the original model varies across species. These correlation thresholds are also generally higher than observed correlations between recruitment deviations and environmental drivers in actual fish populations. We suggest fisheries scientists run similar simulation experiments to determine which correlation levels have the potential to improve population assessment models for their target species.

Recent studies suggest that errors facilitate learning in certain conditions. Despite this, reinforcement paradigms dominate learning methods, subscribing to the narrative that errorless learning is the foundation of an ideal learning environment. If we continue to view learning from this restrictive perspective, we may fail to capture and apply the benefits of errors. Furthermore, although error learning is now a well-documented phenomenon, research on its underlying mechanisms is sparse. Two prominent theories have arisen out of this research; the elaborative hypothesis, in which meaningful connections are derived from errors, and the mediator hypothesis, in which errors act as secondary cues. To go beyond speculation, both must be examined empirically to successfully leverage error learning. Using a combined approach, data from computational models formulated to reflect different mechanisms of error learning were compared to behavioral data. In the behavioral task, participants (N = 61) learned word pairs in either a study or error trial before taking a final test. Supporting past error learning literature, errors before a study opportunity led to better performance on a final test. Differences in reaction times between conditions support the theory that errors increase learning through mediation by acting as a secondary cue rather than as a way to establish a deeper network between the cue and answer. Furthermore, comparing behavioral results to computational cognitive models provided insight into individual differences in mechanisms of error learning.

Memory loss is a debilitating symptom of neurodegenerative diseases. The exact process of memory decline or forgetting in the brain remains unclear. To address this issue, the development of technologies to preserve or improve memory is a continuous objective in translational medicine. This study aimed to uncover the brain networks involved in forgetting and investigate if reducing forgetting was possible through the use of transcranial alternating current stimulation (tACS; 60 Hz or sham) targeted to the dorsolateral prefrontal cortex (dlPFC). The dlPFC was considered a potential target for memory interventions as it had been linked to various aspects of memory function including working memory, executive control, encoding, and retrieval, as well as memory and attention functional connectivity networks. Participants took part in four visits, each consisting of three 8-minute memory tasks using an adaptive fact-learning software. The memory tasks assessed recognition memory (multiple choice), recall memory (fill-in-the-blank), and retrieval learning (response generation). The software used a neurocomputational model that adapted to each participant's performance. This cognitive model is based on established cognitive and biological principles and simulates memory encoding and passive forgetting. The model's α parameter, which represents the speed of forgetting and measures how quickly an individual's memories fade, was used as a dependent variable. Additionally, participants completed two resting state functional MRI (fMRI) scans to evaluate their brain's functional connectivity before and after stimulation. The study compared individual speeds of forgetting to individual patterns of functional connectivity to identify the neural networks most predictive of forgetting, and compared functional connectivity between participants who received tACS and those who received a sham stimulation. We hypothesize that tACS to the dlPFC will decrease forgetting rates and be associated with increases in functional connectivity. In conclusion, tACS has the potential to become a low-cost and non-invasive method to ameliorate memory impairments.

In mammals, hair cell loss or damage leads to permanent loss of auditory and vestibular function due to the inability of mammals to regenerate these cells. The primary function of hair cells is to respond to auditory and vestibular stimuli to facilitate perception of sound, head movement, and gravity. Hair cells are particularly sensitive to changes in their mitochondria, a membrane enclosed organelle that provides ATP in all eukaryotic cells. Disturbances or damages to the mitochondria can be caused by mitochondrial deafness genes, aminoglycoside-induced death, or senescence. Currently, there is very little known about the biology of hair cell mitochondria.The zebrafish neuromasts within the lateral line can serve as a functional model for cochlear hair cells because of its homology with the mammalian inner ear at genetic and structural levels. We use the zebrafish lateral line system in conjunction with the serial-block face scanning electron microscopy (SBFSEM) to produce three dimensional imaging of hair cell mitochondrial morphology. SBFSEM allows us to measure and quantify mitochondrial phenotypes. We have identified structural characteristics of mitochondrial networks adjacent to post-synaptic release sites that interact with afferent neurons and regulate synaptic transmission. The information gained from SBFSEM on hair cell mitochondrial morphologies will provide valuable insight on protective intracellular mechanisms that can prevent synaptopathy and protect against hearing loss. In our future work, we will quantify this mitochondrial networking morphology. These data will further inform functional experiments regarding the role of mitochondria at these synapses.

By 2050, the global human population is expected to reach 9.7 billion. Supporting this rapid growth will challenge global food systems, increasing the demand for healthier affordable foods such as poultry-sourced products (meat and eggs). Improving the accuracy of genotype-to-phenotype predictions for farmed animals could enable better breeding strategies and management practices that are crucial to meeting this goal. By characterizing regulatory genomic regions within various tissues, epigenetic factors which dictate specific cellular phenotypes can be pinpointed: improving phenotype prediction accuracy. To this end, we genetically sequenced (whole-genome bisulfite sequencing) samples of reproductive tissues (magnum, shell gland, isthmus, and ovary) from farmed groups of chickens (G. gallus). Through bioinformatics, we functionally annotated regulatory patterns of DNA methylation to identify tissue-specific epigenetic variation across the female chicken reproductive system. To tackle this, we utilized CGmapTools software to comparatively analyze tissues in a pairwise manner. In order to quantify each pairs’ differentially methylated regions (DMRs), all methylated regions were intersected and filtered through a statistical t-test. We found the pairwise comparison analysis between isthmus and ovary tissues to show the highest number of significant DMRs, being 51% hypermethylated in the isthmus. On the other hand, a comparative analysis between isthmus and shell gland tissues showed the lowest number of significant DMRs, being 54% hypermethylated in the isthmus. Upon annotating and conducting enrichment analyses on the DMRs, we learned that genes related to ECM-receptor interactions and focal adhesion were most prominent. Results of this research will aid the FAANG consortium (an international effort to improve farmed animal production) in improving genotype-to-phenotype predictions, hopefully enabling more sustainable genomic selection practices and genome-enabled management in the future of agriculture.

Implicit bias refers to unconscious attitudes and stereotypes in patient-provider communication that can lead to discrimination based on race, sexual orientation, gender, or other characteristics. This disproportionately impacts historically marginalized communities, including Black, Indigenous, and People of Color (BIPOC) and Lesbian, Gay, Bisexual, Transgender, Queer, and/or Questioning people (LGBTQ+). Although interventions have been developed to improve provider awareness of implicit bias, there has been little exploration of patient perspectives. With the help of my team, I conducted an analysis of 7 previously conducted co-design workshops with 32 BIPOC and LGBTQ+ people to understand patient perspectives on interventions to mitigate the impact of provider implicit bias in healthcare interactions. These workshops included group discussions about personal experiences with healthcare discrimination and a storyboarding activity to envision solutions for improving patient-provider interactions. Across workshops, participants created 13 storyboards that depict solutions in a primary care setting, several of which focus on improving patient-provider communication and promoting self-advocacy and empowerment. Through our collaborative qualitative analysis, my team and I identified two prominent themes from the workshops: communication tools and patient advocates. Participants shared experiences of feeling dismissed and unheard during healthcare visits, leading to storyboard proposals of communication tools, such as "smart boards" that allow patients to describe their symptoms in a nuanced manner. Another storyboard proposed a "panic button" that helps patients ask for help or request a different provider. Other storyboards focus on strategies to hold providers accountable, such as a "patient advocate" who approaches the provider about the patient's experience of discrimination and recommends a communication training intervention that raises awareness of bias. These findings can inform future research on interventions to address implicit bias in provider-patient communication. By prioritizing patient perspectives, we can create a healthcare system that is equitable and inclusive for all.

Multiple myeloma (MM) is an incurable malignancy of the B-cell lineage, characterized by neoplastic, monoclonal expansion of plasma cells in the bone marrow. Remarkable progress has been made in the treatment of MM with the anti-CD38 monoclonal antibodies such as Daratumumab and Isatuximab, which can kill MM cells through the induction of complement-dependent cytotoxicity (CDC). The CDC efficacy of Daratumumab and Isatuximab is however limited by membrane complement inhibitors, including CD46 and CD59, which are upregulated in MM cells. We recently developed a small recombinant protein (Ad35K++) capable of blocking CD46 and sensitizing tumor cells to anti-CD20 mAb triggered CDC (e.g Rituximab and Ofatumumab). Here we tested Ad35K++ in combination with Daratumumab and Isatuximab. We show that Ad35K++ increases the CDC efficacy of Daratumumab and Isatuximab on Burkitt’s lymphoma and MM cell lines (MOLP8 and SUDHL-8). Ad35K++ salvaged the efficacy of Daratumumab and Isatuximab at subtherapeutic (“low”) doses in MM lines. Daratumumab and Isatuximab treatment of MM lines (without Ad35K++) resulted in the upregulation of CD46/survival of CD46 high MM cells which escaped a second round of Daratumumab and Isatuximab treatment. Escape was reduced by combining Daratumumab and Isatuximab with Ad35K++. We also tested a small recombinant protein that targets CD59 (rIYD4) in combination with Daratumumab and Isatuximab on MM cells. rIYD4 also increased CDC killing of MM cells by Daratumumab and Isatuximab. The combination of Ad35K++ and rILYD4 additively enhanced the CDC effect of Daratumumab and Isatuximab. Studies with patient MM cells will be reported. Overall, our data demonstrate that Ad35K++ and rILYD4 are efficient co-therapeutics of Daratumumab and Isatuximab and could be used to improve the treatment of multiple myeloma.

CCR5 is a co-receptor required for HIV to infect the body. Several AIDS patients were completely cured after receiving hematopoietic stem cell (HSC) transplants from donors with a mutation in their CCR5 gene making it functionally inactive. However, HSC transplantation is a very risky and expensive procedure, making it inaccessible for most AIDS patients in developing countries. Our aim was to develop a technology that introduces CCR5 gene mutations in the HSCs of AIDS patients in vivo by a single intravenous injection of a gene transfer vector. The vector delivers a genome editing enzyme (base editor) targeted to the CCR5 gene. CCR5-gene edited HSCs will give rise to CCR5-negative HIV target cells, thereby blocking HIV infection and providing life-long protection. We tested three strategies to functionally inactivate CCR5 expression: i) creating a premature stop codon, ii) eliminating the ATG start codon and iii) mutating splice acceptor sites to skip exons. We employed an advanced adenine base editor version (ABE8e) and an early version of cytidine base editor (CBE) delivered with helper-dependent adenovirus vectors (HDAd5/35++) that efficiently infect HSCs in vivo. The base editors are directed to specific target sites by single guide RNAs (sgRNAs). We screened a small library of sgRNAs and identified two species (sgSTOP2 and sgR5-1) that mediated the highest on-target editing rates and CCR5 down-regulation. HDAdAd5/35++ vectors were produced using these sequences. In a test cell line infected with these vectors, 50% of CCR5 alleles were edited. This blocked HIV infection in 40% and 95% of HDAd-ABE8e-sgSTOP2- and HDAd-CBE-sgR5-1-infected cells, respectively. We concluded that the HDAd-CBE-sgR5-1 vector is more efficient in blocking HIV infection and will further improve this vector and test it in primary human lymphocytes and HSCs in the context of HIV infection. This approach has the potential to provide a technically simple HIV/AIDS therapy.

 Cancer metastasis, the spread of tumor cells to different parts of the body, significantly increases patient mortality. An early step in the metastasis process is invasion into surrounding tissues. One way that tumor invasion is studied is through tumor organoids. Tumor organoids mimic tumors in vitro through 3D cell culture. While it is generally held that invasion continues to increase monotonically over time, I recently discovered that invasion of tumor organoids has a temporal pattern, where invasion spikes up, then decreases after a certain time. This finding suggests more complex regulation of invasion dynamics than thought previously. The goal of this project is to investigate the temporal dynamics of cell-matrix associated RNAs and proteins during breast tumor organoid invasion. I can perform a qPCR time course of particular genes related to invasion to measure the levels of RNA at specific time points. In addition, I can check for protein levels using a novel method developed in the Cheung lab. This method utilizes bio-orthogonal click-chemistry to perform rapid, selective pairing of intracellular proteins with azidohomoalanine, a clickable methionine analog. Click-chemistry allows us to pick up proteins that cells are either secreted or on the surface of the cells. To define a cancer-specific invasion signature of tumor invasion, I compare RNA and protein dynamics in breast tumor organoids with normal mammary organoids (FVB) migrating in 3D collagen gels. I hypothesize that there will be specific genes associated with increased and decreased invasion levels. In future work we will target those genes by either suppressing those genes that increase with invasion or increasing the expression of invasion suppressors. We expect this work to reveal new regulators of the metastatic process.

Prostate cancer is the second most prevalent cancer among men in the United States. Characteristic biochemical markers include abundant Androgen Receptor (AR) and Prostate Specific Antigen (PSA), a downstream marker for AR activity. A rare neuroendocrine prostate cancer (NEPC), however, is characterized by low AR and PSA activity and high Synaptophysin (SYP; NEPC marker) expression. AR pathway inhibitors (ARPIs), the first-line treatment for prostate cancer, have minimal therapeutic effects on NEPC. This suggests that suppressed AR activity inhibits ARPI effect, and restoring AR could induce sensitivity to ARPIs, such as Enzalutamide. This study investigates the impact of overexpressing a tRNA, Arg-TCT-1-1, in NEPC. tRNA-sequencing of NEPC cell lines identified reduced expression of the Arg-TCT-1-1 tRNA isodecoder (Arg-TCT). Stable cell lines were generated for adenocarcinoma (AD) and neuroendocrine (NE) phenotypes, with overexpression of Arg-TCT or mutant TCT (mut-TCT). Reverse Transcriptase Quantitative Polymerase Chain Reaction confirmed Arg-TCT and mut-TCT overexpression. Cell lysate was immunoblotted for AR, PSA, and SYP; cell growth assays were then performed with Enzalutamide in DMSO to assess cell proliferation and sensitivity. Enzalutamide inhibited AR activity in LNCaP (1uM) and C4-2B AD (20 uM). Immunoblot suggests that Arg-TCT-1-1 overexpression rescues AR activity in NE cells, while mut-TCT does not affect AR activity. Cell growth assays reveal Arg-TCT-1-1 upregulation induces increased cell proliferation and enzalutamide sensitivity in NE cells. These novel findings demonstrate that upregulated tRNA promotes ARPI sensitivity in NEPC cells. Further research on how Arg-TCT-1-1 regulates AR activity and its transferability to other cancers is needed. These results suggest a promising therapeutic vulnerability if confirmed in murine models.

Genetically encoded fluorescent indicators (GEFI) change fluorescence level under microscope following a conformational change when bound to a target molecule, and can be used to visualize spatiotemporally specific biological processes involving a targeted molecule. Various imaging analysis tools exist to analyze the non-temporal fluorescent cell data, however there was no industry standard for the pipeline used to analyze molecular dynamics when imaged with GEFI in time-series experiments. This project aimed to develop a computational pipeline that analyzed the fluorescent readout of single cells in spatiotemporal experiments that utilized GEFI. The pipeline included both segmentation of cells, utilizing Cellpose, an existing deep learning-based generalizable and highly efficient segmentation program, and tracking of single cells across all frames. I personally contributed to the design, implementation, and testing of the tracking component of the pipeline. The tracking algorithm was designed using unsupervised machine learning, specifically k-means clustering with convolutional neural network feature extraction techniques. The pipeline was implemented using Python and made available and open source, accessible through Google Colaboratory for a more user friendly version, as well as Github for more thorough documentation and generalizability. Ultimately, this project aimed to minimize bias to result in more accurate and efficient high-throughput investigation of molecular dynamics when using fluorescent probes for dynamic cell imaging. Preliminary results demonstrated the effectiveness of the pipeline in tracking cells across various time points and provided a foundation for future optimizations and applications.

Treatment of individuals with HIV using antiretroviral therapy (ART) is highly effective, but effective clinical management depends on maintaining therapeutic drug concentrations. Antiretroviral (ARV) drug concentrations in patients with HIV can vary due to differences in drug metabolism, medication adherence, or interactions between multiple drugs. These individuals may have subtherapeutic or supratherapeutic drug concentrations, putting them at risk of treatment failure, acquisition of drug resistance, and risk of hospitalization or death. Current measurement of ARV concentration is done through liquid chromatography tandem mass spectrometry, which requires expensive equipment and requires a labor-intensive protocol. This restricts accessibility to specialized laboratories, making it difficult for persons with HIV to have routine measurements of ARV drug concentrations. The goal of the project is to develop an assay that is simple to perform and uses standard equipment to increase access to routine clinic-based drug level monitoring to improve HIV care. We designed an assay using a 2-step process of DNA strand transfer and quantitative polymerase chain reaction (qPCR) to quantify integrase strand transfer inhibitors (INSTIs). We tested for dolutegravir (DTG) and cabotegravir (CAB) in both buffer and plasma -- the latter to simulate patient blood samples. We were able to demonstrate that the assay could quantify clinically relevant drug concentrations of DTG and CAB. By developing an assay that can be readily integrated into most clinical laboratories, we will contribute to increasing access to routine HIV drug level monitoring to improve clinical HIV care and maintaining viral suppression in persons with HIV.

Injuries to the spinal cord are among the most debilitating injuries to the human body. The task of repairing this dense network of nerve cells and fibers has been seen as insurmountable. However, new techniques emerging from the field of regenerative medicine have illustrated the possibility of encouraging the body to repair these injuries on its own. In the Wills Lab, we study the model organism Xenopus tropicalis, or the Western clawed frog, which has the incredible ability to regenerate its spinal cord and associated tissue following amputation. My project focuses on how Xenopus uses the classic developmental morphogen Sonic Hedgehog (Shh) to recapitulate the dorsal-ventral patterning of the spinal cord during regeneration. Previous research in a closely related organism showed that a switch to non-canonical mode of Shh signaling, not involving the Gli family of transcription factors, was important during regeneration. In order to investigate this further, I used chemical inhibitors of the canonical Shh signaling pathway to confirm this pathway’s limited importance in terms of gross regeneration. Next I used in-situ hybridization to visualize the expression of Shh and its associated genes along a regenerative time-course. It is anticipated that inhibition of the canonical pathway will decrease these expression levels and confirm the selectivity of our inhibitors. An understanding of the role of key biological signals like Shh will be integral in the development of regenerative therapies for spinal cord injury.

Emotional obstacles affecting those living with chronic Inflammatory Bowel Disease (IBD) are a pain point that often lacks support. Emotional obstacles include feelings of depression, anxiety, body image issues, experiencing isolation, or feeling unheard, which can impact one’s quality of life. Support systems, or individuals who provide emotional or physical support, can help people manage the effects of these obstacles to support illness self-management. Research on IBD and emotional support demonstrate that many people do not know how to best support their loved ones with IBD. Poor understanding of patients’ needs often results in ineffective support that is not perceived by IBD patients as beneficial; support system members are perceived as being overly worried, being hyper-fixated on physical IBD symptoms, or trying to distract the patient from emotional pain. These strategies carry the risk of IBD patients suppressing their emotional obstacles, withdrawing from their support system, and struggling on their own. I want to improve social support systems for IBD patients. As a first step, I administered online surveys asking people with IBD what emotional obstacles they face, and how these burdens affect their daily life. To date, respondents (n = 57) reported experiencing body image issues (57%), anxiety (68%), feeling hindered from their potential (51%), depression (66%), and social isolation (61%). Respondents stated that their emotional obstacles inhibit their IBD self-management (73%), ability to follow medical advice (38%), and ability to follow their medication regime (40%). These findings characterize common emotional obstacles and key impacts on self-management, a principal factor in disease remission. As we continue to survey people with IBD, we are conducting follow-up interviews to understand their experience and support needs in greater depth to inform improvements to social support systems.

Unlike mammals, western clawed frog (Xenopus tropicalis) tadpoles are able to completely regenerate their spinal cord after tail amputation. This complete spinal cord regeneration is due to the ability of their neural progenitor cells (NPCs) to differentiate into neurons successfully. Our research focuses on two transcription factors—Meis1 and Pbx3– that are upregulated by regenerating neurons and are necessary for successful regeneration. We aim to elucidate how these two proteins are working together to guide successful spinal cord regeneration in X. tropicalis tadpoles. I am specifically investigating Meis1 and Pbx3 splice variant expression during neural regeneration. Previous work in mice found that different known splice variants of Pbx3 have different expression patterns. While X. tropicalis has two predicted splice variants each of Meis1 and Pbx3, nothing is known about their individual expression or function. I sought to fill in this gap by looking at Meis1 and Pbx3 splice variant expression in different tissues and over regenerative time. Based on previous research in mice, I hypothesize that both splice variants of Meis1 and Pbx3 have different gene expression patterns in different cell types over regenerative time. I aimed to investigate this hypothesis by doing two experiments. My first experiment was to study the expression of each splice variant over regenerative time by performing qPCRs in order to look at the presence of splice variant mRNA in uninjured, 24, and 72 hours post-amputation. For my second experiment, I made in situ hybridization probes specific for each splice variant to identify their tissue-specific expression patterns. Based on previous literature, we expect to see differential amounts of expression from each splie variants as spatial expression centralized on the spinal cord. Understanding the transcriptional network that is behind the regenerative mechanism of X. tropicalis can help us develop therapeutic tools to address spinal cord injury in humans. 

Nature uses only four nucleobases to store genetic information in DNA. However, additional synthetic bases which use Watson-Crick pairing have been developed and are known as non-standard bases (NSBs). NSBs P, Z, B and S incorporated alongside standard bases A, G, C and T compose DNA strands using a new genetic alphabet. Nanopores offer the potential capability for direct single-molecule sequencing of DNA containing non-standard bases (NSBs). Using a voltage gradient, DNA strands were directed through a nanopore, the biological membrane protein MspA, while we measured the ion current through the pore over time. In studying the effect of NSBs on the ion current through the pore, we observe current measurements corresponding to the Z base have a different noise profile compared to other bases. We hypothesize this noise may be associated with pH-dependent protonation of the base. To test this hypothesis, we conducted experiments with identical sequences in buffers of pH 8 and pH 7, as Z is known to have a pKa of 7.8. I analyzed the noise from the ion current signals to look for signs of protonation. I found increased current noise values associated with the Z NSB in pH 7 compared to pH 8, while the canonical A base had no change in noise values from pH 7 and pH 8, supporting the hypothesis that the increased current noise is due to protonation of the Z base. In addition to indicating potential sensing abilities of nanopores for probing protonation kinetics of DNA, this research contributes to a better understanding of the fundamental mechanisms that control the currents in nanopore sequencing of DNA.