Synthetic peptide tags have been key to improving the ease with which scientists can interface with proteins in living systems. This PhD. work centers on demonstrating how peptide tags can be used to build modular platforms to accelerate live cell imaging, isolation of genetically engineered cells, cryo-EM, and applied DNA origami. First, we employed a set of three peptide/binder tagging systems, we developed tag-assisted splitHalo (TA-splitHalo), a versatile, multiplexable endogenous tagging platform. We applied TA-splitHalo sytems to live-cell imaging and complex knock-in sorting of lamin A/C knock-ins. Second, we utilized a peptide tag knock-in approach that combines split- fluorescent proteins and affinity purification to perform cryogenic electron microscopy (cryo-EM) on native structures derived from genetically edited suspension cell lines. This workflow was prototyped on native human proteasome complexes, demonstrating the pulldown of biologically relevant variants. Third and independently from the knock-in platforms, we engineered a SpyTag/SpyCatcher strategy in bacteria to create purification pipelines for proteins with two different and desired functional domains, enabling new ways to self-assemble biological nanoarchitectures. This was done by tethering cytokines to a transcription activator-like effector (TALE) protein to create immunomodulatory DNA binding proteins that can functionalize DNA origami structures. Our work demonstrates that the short length and minimally invasive nature of peptide tags enable plug-and-play platforms that can be applied at high-throughput for a wide range of applications.

The critical size limit of electric polarization remains a open domain in nanoscale ferroelectric research; in particular, the fundamental limit of switchable electric dipoles has extensive implications for the scaling of energy-efficient nanoelectronics due to the intrinsic ability to control electric polarization with an applied voltage. As ferroelectric materials are made thinner however, polarization is typically suppressed, as size effects in ferroelectrics have been thoroughly investigated in the prototypical perovskite oxides. Furthermore, perovskites suffer from various chemical, thermal, electrical, and interfacial incompatibilities with silicon and modern semiconductor processes. Recently, fluorite-structure binary oxides have attracted considerable interest as they overcome many of the silicon compatibility issues afflicting its perovskite ferroelectric counterparts. To address the missing void in ferroelectric research regarding ultrathin stabilization and Si compatibility, the first part of this dissertation focuses on stabilizing ferroelectric order in ultrathin HfO₂-ZrO₂ fluorite-structure oxides, grown by atomic layer deposition, on silicon. Indeed, this research demonstrates the persistence of inversion symmetry breaking and spontaneous, switchable polarization down to a thickness of one nanometer in Zr:HfO₂ films and five angstroms in ZrO₂ films, equivalent to just two and one fluorite-structure unit cell thickness, respectively; the latter result marks the thinnest demonstration of ferroelectric polarization switching in any material system, remarkably in a conventionally paraelectric material. Reversible electric dipoles at the 2D limit offers exciting possibilities for low-power high-density memory exploiting electronic order on silicon, evidenced by proof-of-principle ferroelectric tunnel junctions implementing 10 Å Zr:HfO₂ and 5 Å ZrO₂ barriers which demonstrate distinct polarization-driven resistive states. Furthermore, the emergence of atomic-scale ferroelectricity and switchable electric dipoles in fluorite-structure oxides not only cements its technological promise for silicon electronics, but also highlights its distinct nature from a fundamental ferroic perspective. These results indicate the presence of ultrathin-enhanced polar distortion in fluorite oxide thin films on silicon, which oppose conventional perovskite ferroelectric trends; notably these ‘reverse' size effects are consistent with predictions of its atypical piezoelectric origins. Therefore, simple binary oxides can serve as a model material system to explore novel 2D ferroelectricity in which ‘reverse’ size effects can counter-intuitively stabilize polar symmetry in the ultrathin regime.

Considering integrate nanoscale ferroelectricity in HfO₂-ZrO₂-based thin films can be synthesized directly on silicon, the next prong of this dissertation focuses on the atomic-scale design of negative capacitance – a novel phenomena present in ferroelectric materials which can enable energy-efficient nanoscale transistors – in ultrathin (< 2 nm) HfO₂-ZrO₂ films. The negative capacitance effect from a ferroelectric layer has a unique experimental signature: it results in a net capacitance enhancement of a dielectric-ferroelectric heterostructure over that of the constituent dielectric layer, which violates the expected equivalent capacitance of two capacitors connected in series. With the scaling of lateral dimensions in advanced transistors, an increased gate capacitance is desirable both to retain the control of the gate electrode over the channel and to reduce the operating voltage, enabling high-current and low-power operation. This led to the adoption of high-κ dielectric HfO₂ in the gate stack in 2008, which remains as the material of choice to date. Unfortunately, stabilizing negative capacitance is not as simple as stabilizing ferroelectricity, and until now, it has yet to be reported in the technologically-relevant HfO₂-ZrO₂ system. The second half of this dissertation demonstrates evidence of negative capacitance via capacitance enhancement in ultrathin 2 nm HfO₂-ZrO₂ multilayers and 1 nm ZrO₂ single layers on SiO₂-buffered Si. This atomic-scale design of negative capacitance builds off the previous materials characterization of ultrathin ferroelectricity in Zr:HfO₂ and ZrO₂; in particular, the antiferroelectric- ferroelectric phase evolution in ZrO₂ as a function of thickness enables mixed-ferroic phase competition at the ultrathin regime, the microscopic origin of negative capacitance in this system. Beyond just the stabilization of negative capacitance, this research also delves into how negative capacitance gate oxide stacks demonstrate key device-level benefits once integrated into Si transistors, providing a new path towards advanced gate oxide stacks beyond the conventional HfO₂-based high-κ dielectrics.

Overall, through the model system of HfO₂-ZrO₂ system on Si, this dissertation establishes new physical thickness limits and effective oxide thickness limits for ferroelectricity and negative capacitance, respectively, and proposes microscopic mechanisms for the observed phenomena.

Dexterous control of upper arm movements is integral to activities of daily living. This important ability may be lost due to neurological injury or disease, yet brain-machine interfaces (BMIs) or neuroprosthetics may offer the ability to restore motor function by bypassing damaged neural circuitry. Though tremendous progress has been made in BMI performance and robustness, additional gains are needed to improve the clinical utility of BMI systems. Of particular importance is the need to scale BMI performance beyond the simple 2-D reaching paradigm typically studied and extend to the multi-degree-of-freedom (multi-DOF) case. We explored methods and design considerations for redundant multi-DOF BMIs and examine the neuroprosthetic control mechanisms engaged by subjects.

In this work, healthy non-human primate subjects controlled a variety of virtual and physical actuators using neural signals recorded from electrode arrays implanted in the motor cortex. We analyzed 2-D natural arm movements and developed a fast method to extract sparse components of hand kinematics during point-to-point reaching. We then analyzed neuroprosthetic control of a computer cursor in which neural decoding is performed using a Kalman filter (KF). We discovered several links between KF parameters and control performance of the overall BMI system, including the ability to manipulate the speed-accuracy tradeoff of neural cursors. Building from hypotheses of model based control in natural motor control, we examine BMI cursor control for evidence of model-based and feedforward control.

We then proceeded to develop an architecture for BMI control of a redundant actuator. Subjects learned BMI control of a redundant four-link virtual “arm” which was confined to move in a two-dimensional plane. When controlling this redundant arm, performance improved when subjects made use of the redundant control dimensions. Furthermore, redundant control signals were critical to escaping manipulator singularities, similar to how redundant control signals are used in robotic systems. These results suggest the utility of using neural signals in conjunction with standard robotic path planning methods to control endpoint-redundant aspects of a robotic prosthesis. Altogether, the work of this dissertation contributes progress toward BMI control of highly redundant prosthetic systems for clinical use.

Abstract: Manipulating Skeletal Muscle Acetylation to Enhance Healthspan and Lifespan

Human aging is marked by a progressive loss of skeletal muscle mass and cognitive function—two primary determinants of healthspan and lifespan. Even though there are many studies characterizing this association, the mechanisms underlying this relationship remain unclear. In contrast to aging, endurance exercise has been shown to improve skeletal muscle mass and function and slow age-related cognitive decline 1,2. Further, animals bred for low levels of physical activity show impaired muscle and neurocognitive function 3. The main adaptations seen with endurance exercise training are heightened fat oxidation, and increased mitochondrial mass and activity downstream of a transcriptional co-factor called the peroxisome-proliferator activates receptor 1α (PGC-1α), which is regulated by acetylation 4,5. Roberts et al (2017) demonstrated that the use of a ketogenic diet (KD), increased protein acetylation and activated PGC-1α in muscle concomitant with improved markers of skeletal muscle strength, mitochondrial mass and activity, endurance, neurocognitive function, and extended lifespan 13.6% in mice 6. Along with enhanced healthspan and lifespan, mice on a KD demonstrated improved muscle mitochondrial biogenesis, muscle mass, and oxidative fiber cross-sectional area; all things associated with endurance exercise training 7. However, the molecular mechanisms underlying the benefits seen with increases in either exercise or a KD on skeletal muscle and neurocognitive function remains largely unexplored. Our global hypothesis for this body of work was that increasing protein acetylation plays a central role in improving skeletal muscle mass and function, mitochondrial biogenesis, and neurocognitive function. In the present work, we identify novel mechanisms that underlie the ability of skeletal muscle to increase muscle mass and function, and describe the role of skeletal muscle mitochondria in augmenting cognitive performance in response to manipulation of acetylation either through natural compounds, pharmaceuticals, or a KD. Our approach to understand how acetylation both with and without a KD enhances healthspan, and lifespan was 4-fold: 1) Determine the effect of a cocktail of natural products, selected to inhibit the NAD-dependent deacetylase Sirtuin 1 (SIRT1) in rats following ablation of the gastrocnemius and soleus muscles (Functional Overload—FO), on the resulting increase in plantaris muscle fiber cross sectional area, 2) Establish how the class II histone deacetylase (HDAC) inhibitor, scriptaid, affects skeletal muscle and neurocognitive function, and 3) Determine whether a 2-month KD alters skeletal muscle function, mitochondrial mass, and cognitive behavior in middle-aged female mice, Muscle mass and strength are important aspects of human health. Low levels of muscle mass and strength are directly correlated with lifespan. In Chapter 2, we optimized a cocktail of naturally occurring compounds (epicatechin, epicatechin-gallate, and celestrol) that were believed to inhibit sirtuin 1. This work shows that optimal inhibition of SIRT1 increases global protein acetylation (Figure 2.3C), and the increase in fiber cross sectional area (fCSA) in response to FO 61.5% more than vehicle dosed counterparts (Figure 2.2H). One proposed limit to skeletal muscle hypertrophy in both mice and man is the capacity for protein synthesis (i.e., ribosome mass)8–10. In response to an optimal dose of the SIRT1 inhibitor cocktail, ribosomal RNA (which comprises ~80% of the total RNA) relative to muscle mass decreased in the optimal group (Figure 2.4B). This was supported by lower markers of ribosome biogenesis (ITS1 and 5’ETS RNA levels) indicating that the benefit of the cocktail is not the result of increased translational machinery (Figure 2.4C&D). One possible explanation for the apparent increase in hypertrophy could be an increase in translational efficiency secondary to acetylation of ribosomes 11. In support of this, immunoprecipitation of ribosomal subunits showed greater associated acetylated lysine levels in the optimal group when compared to control animals (Figure 2.6A-C). Though a long term KD has been shown to help maintain oxidative fCSA and improve muscle and cognitive metrics, there is still uncertainty surrounding the mechanism underlying the changes caused by a KD 6,7. To address this gap in knowledge, in Chapter 3 we employed an isocaloric (11.2 kcal/day) KD in 23-month-old mice (Table 3.2) together with concomitant injection of either the class II HDAC inhibitor scriptaid (SCRIPT) or a vehicle (VEH) control. Our findings demonstrated that a one-month KD intervention increases mitochondrial mass (Figure 3.2D) and improved grip strength (Figure 3.1G) in skeletal muscle preferentially while not affecting fCSA (Figure 3.4A&B). As an explanation for the significant improvement on grip strength in the KD fed animals, we are the first to report that an acute KD increases dystrophin protein levels (Figure 3.4F). These data indicate that KD muscle is better able to laterally transmit force and prevent contraction induced muscle damage than their CD fed counterparts. To understand to what degree a short-term KD started late in life influences cognitive behavior the Y-Maze, Novel Object Recognition, and Open Field assays were conducted (Figure 3.1H, 3.1J&K). We report no changes between the CD and KD fed animals. These findings indicate that an acute KD first effects skeletal muscle biochemistry and functionality prior to that of neurocognitive function. Interestingly, all of the biochemical and functional benefits seen with an acute KD were blunted when paired with SCRIPT treatment. This blunting of adaptation coincides with KD SCRIPT animals’ inability to produce adequate ketones in the fasted state. This finding implies that ketone production may be a crucial component of maintaining skeletal muscle adaptation and functionality in aged female mice. Even though positive effects of a KD had been demonstrated in old and diseased male mice, whether the diet could benefit females was uncertain. To test the hypothesis that female mice would thrive on a KD, in Chapter 4 middle-aged female mice were put on a two-month isocaloric KD (Table 4.1) and upon collection, skeletal muscle and liver mitochondrial mass and biogenesis, cognitive function, and serum were analyzed. Our results show that a two-month KD is sufficient to improve mitochondrial mass (Figure 4.4A) and PGC-1 protein level in the total and nuclear muscle fractions (Figure 4.4C&E) of skeletal muscle. PGC-1α being responsible for the expression of kynurenine aminotransferases (KAT) in muscle 12, enzymes that convert a potential neurotoxin kynurenine (KYN) into kynurenic acid (KYNA) that cannot enter the brain, therefore we measured KAT protein levels in muscle after a 2-month KD. Two KAT proteins, KAT1 and KAT4 increased in the GTN muscle (Figure 4G&I). The increase in muscle KAT proteins was associated with a significant decrease in circulating KYN and strong trend for KYNA to increase (Figure 4F&G). The increase in KAT protein and decrease in circulating KYN were associated with improvements in Barnes maze and rearing assays, indicating greater spatial learning and memory capacity along with decreased anxiousness (Figure 4J&K). We are the first to propose a mechanism that connects muscle metabolism to brain function in response to a dietary intervention. Within this dissertation, I discuss mechanisms whereby altering acetylation in skeletal muscle improves translational efficiency resulting in greater load-induced skeletal muscle hypertrophy; however, acetylation is not sufficient to induce mitochondrial biogenesis or improve cognitive function.

Purpose of review

Recent findings

Summary

Performance visualization is an emerging field that adapts to the growing ecosystem of High-Performance Computing (HPC). With the continued growth in scale and complexity of HPC systems, code developers face the challenge of optimizing performance, requiring a detailed understanding of runtime behaviors of the system and the ability to identify and address performance bottlenecks. To meet this challenge, various tools have been developed to capture performance behaviors and conduct performance analysis, but the complexity and scale of the resulting data have made visualization systems essential for revealing and understanding key patterns that expose performance bottlenecks. The dissertation presents novel visual analytic methods that address the four key data challenges associated with performance analysis: Attribution, Scalability, Correlation, and Velocity. My contributions are driven by domain experts’ requirements to facilitate scalable interactive analysis of large-scale performance profiles and traces. Specifically, the dissertation addresses the challenges of analyzing and correlating collected performance data across three key domains of supercomputing — Hardware, Application, and Communication (HAC). Overall, the dissertation addresses the challenges of analyzing and correlating collected performance data in HAC domains, leading to a set of tools that are expected to greatly enhance HPC experts’ ability to understand and optimize the performance of demanding applications through interactive and scalable visual analytics.