As information processing machines approach the nanoscale level, DNA has emerged as a powerful tool in molecular engineering systems. The specificity and programmability of its hybridization interactions offer flexible and fine-tuned control over reacting species. Among the DNA computing techniques used today, strand displacement circuits are highly popular, with potential applications ranging from disease diagnostics to DNA-based artificial neural networks. The fundamental mechanism of these circuits is the hybridization of a single-stranded DNA input strand to a double-stranded complex which triggers the release of a prehybridized output strand. When released, this output can be detected and used to characterize circuit behavior. The output strands of strand displacement circuits are typically read out using fluorescence spectroscopy. However, due to spectral overlap of traditional reporters (e.g. FAM, TAMRA, Cy5), the number of outputs that can be detected in parallel is severely limited. To address this, we present the use of nanopore sensing technology as an alternative readout device that enables highly scalable, real-time detection and quantification of DNA strand displacement circuits. We demonstrate dynamic sensing of an operating circuit within the flow cell of a commercially-available high-throughput nanopore sensor array (Oxford Nanopore Technologies’ MinION device) and show that strand capture frequency can be correlated to concentration, allowing for direct quantification of desired circuit elements. To investigate this reporter strategy’s multiplexing potential, we present a collection of ten orthogonal circuit output sequences (barcodes) that can be classified at the single-molecule level from raw nanopore signal data using machine learning, with the potential to scale to larger barcode sets. We conclude that nanopore-based detection of strand displacement circuits holds key advantages over fluorescence-based methods for real-time, multiplexed circuit readout on an inexpensive, portable sensor device.

Honeybees, Apis mellifera, demonstrate an ability to perform visual learning to such an extraordinary extent that it is not typically associated with smaller brains. Those learning abilities may be linked to their degree of sociality as they aggregate into colonies and synergistically work together on tasks. The Social Brain Hypothesis suggests that an organism's level of intelligence is correlated to how social their environment is. Some bees like the leaf cutter bee, Megachile rotundata, are solitary bees who do not live in a hive but instead reside in individual nests. The purpose of this research is to explore the visual learning capability of leaf cutter bees and compare them to the learning capability of the well documented honeybee. The methods used for this study include placing a tethered bee on a free rotating ball that is placed in front of a screen. Two colors are projected onto the screen and the bee controls the movement of the shapes. A positive and negative reinforcement are assigned to each shape. By analyzing how many times the bee picked each color, how fast it responded to the shapes, and how far from a distance it walked to fixate on that color, we can make an informed statement about the solitary bee’s ability to visually learn. We anticipate one of three outcomes, the leaf cutter bee will either have a greater learning rate, less learning rate, or equal learning rate to that of the honeybee. These results will help supplement more data for the Social Brain Hypothesis and allow a deeper understanding of how sociality is related to cognition. This study also has major relevance to pollination practices as leaf cutter bees are used in agriculture, therefore understanding the neural basis of cognition can open the door for new reforms in crop pollination.

It’s known that plant-pollinator relationships are central to the proper functioning of agricultural and ecological systems. Of the many navigation pathways pollinators use, floral scent signaling for insects is the most complex yet also the most at-risk from atmospheric human activity. Oenothera pallida, a primrose, interacts with the pollinators Hyles lineata, a hawk moth, and Megachile rotundata, a leaf-cutter bee, via this scent pathway. Because of their reactivity with floral scent, human-released ozone and NO₂ are the main perpetrators of scent degradation. To understand this relationship being damaged, I exposed the moth and bee species to a normal Oenothera scent versus a degraded one, recording the antennal response as well as the behavioral, expecting a poorer response to the degraded scent. Moth antennae act as the site of odor reception, bearing sensory hairs that detect odors, allowing the moths to navigate to scent sources. I conducted electroantennographic experiments (EAG) to record the electric signal from the insect antennae in response to each scent blend, with the degraded scent representing the impact of NO_x interactions. Following the EAG, I conducted Proboscis Extension Reflex (PER) experiments with Megachile to show the relationship between insect behavior and antennal physiology when in the presence of the scent blends. I expect that the EAG experiments show that the antennae respond worse to NOx degraded scents in comparison to the normal, unaltered scent blend. Likewise, Megachile has a worse PER when exposed to the degraded scent, linking the chemical biology of the scent interaction to the feeding and pollination behavior. This work has broader implications regarding the importance of plant-pollinator relationships, especially when considering environmental and agricultural health as well as the issue of food security in our changing climate.

Almost all of our tangible understanding of the world is mediated by the skin, a highly innervated sensory organ. However, many injuries to the skin result in the severance of somatosensory axons, causing temporary or permanent loss of feeling. To reestablish innervation, epidermal and neuronal cells launch wound healing responses. Neuronal cells undergo a transition to a more juvenile state to promote new axon growth for reinnervation. Surrounding keratinocytes and immune cells migrate to the affected area to clear cellular debris and promote axon regeneration. Although we know these cellular processes occur, it is unclear how changes in gene expression direct these responses. My project aims to transcriptomically characterize healing responses using zebrafish (Danio rerio) as a model organism. Zebrafish are widely used in regeneration studies and have a fully sequenced genome available for reference. Unlike in human skin where complete regeneration is not observed, zebrafish have almost perfect regenerative abilities. To address our question, we plucked fish scales to induce a rapid regenerative response of both somatosensory neurons and skin. We then collected and purified RNA from somatosensory neurons and skin at zero, one, and three days post pluck for sequencing to characterize gene expression over time. With high-throughput RNA sequencing, we can uncover expression patterns and ontologies of differentially expressed genes in neurons and skin after injury. Thus far, we have found that several previously characterized regeneration associated genes (RAGs) are transiently upregulated in neurons following injury. Transcription factors involved in somatosensory development show a drop in gene expression following injury and are upregulated as the regenerating axon develops. We hope that by understanding skin reinnervation in successfully regenerating organisms, we can develop strategies to improve tissue recovery in humans through manipulation of conserved mechanisms.

Skin is an organ system with a diverse cell ecosystem that plays important barrier and sensory functions, which are critical to organism survival. Because of its superficial location, the skin, and its composite cells, are easily damaged and need to be repaired to maintain homeostasis. Zebrafish are an excellent model to study skin repair because they regenerate tissue efficiently and share conserved skin architecture with other vertebrates. I am addressing two related questions that examine how the sensory axons that innervate the skin and resident skin cells interact during development and tissue repair. First, how do skin-resident immune cells called Langerhans cells contribute to skin repair? Previous work in the lab found that Langerhans cells phagocytose degenerating cutaneous sensory axons, leading me to hypothesize that Langerhans cells play a broad, and previously unappreciated role, in skin repair. As a first step, I have been examining the effects of genetic mutations on Langerhans cell development. I have compiled a data set from several mutants proposed to regulate Langerhans cell development using image analysis of transgenic zebrafish. Second, how do peripheral nerves in the skin influence tissue regeneration? To answer this, I have created week-long time-lapses of skin regeneration in mutants lacking peripheral neurons compared with wild type sibling fish. To induce regeneration, I removed a concentrated patch of scales, a type of skin appendage, on the lateral side centered above the pelvic fin. I then visualize and quantify scale regeneration using a fluorescent imaging of a stain that labels scales. By comparing the genetic groups, I hope to determine whether nerves influence the rate and amount of regrown scales. Together these projects will provide insights into how interactions between the complex cell types of the skin regulate tissue repair, which we hope will ultimately have implications for wound repair in humans.